I
903R82100
United States
Environmental Protection
Agency
Washington, D.C. 20460
September 1982
Chesapeake Bay Program
Technical Studies: A Synthesis
al Protects* A|8W»
.ation Resourca
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FOREWORD
In recent years the well-being of Chesapeake
Bay and its tributaries has been stressed by
activities of the region's growing population.
Concern for this national resource prompted
Congress in 1976 to direct the U.S. Environ-
mental Protection Agency (EPA) to conduct an
intensive five-year study of the Bay's resources
and water quality, and develop related management
strategies. To address concerns of Congress, this
study, known as the Chesapeake Bay Program (CBP),
focused research on three principal problems in
the Bay—the presence of toxic substances, nutrient
enrichment, and the disappearance of valuable
submerged aquatic vegetation. In addition to
evaluating the severity of these problems and what
they may indicate about the Bay's water quality,
the CBP was directed to review current mechanisms
of pollution control and suggest management
strategies.
This document is the second of the Program's
four final reports. It is intended to share the
results and significance of the Chesapeake Bay
Program's technical studies with managers,
decision-makers, and citizens. The report
integrates* or synthesizes„ results of the
many technical studies that have addressed
Congress* concerns. This integration by key
scientists in the three problem areas centered
around a set of specific questions relevant to
managers and decision-makers of the Bay region,
and were developed by Program staff, and
State and Federal environmental managers. In
attempting to answer these questions with the
best scientific information, the authors of
the papers were not confined only to infor-
mation derived from the projects. They drew
on the research literature, personal communi-
cations, and their own rich knowledge of the
Bay's ecology, as well as their extensive
interaction with peer scientists. The
conclusions of each paper, although based
primarily on results from CBP research
projects, reflect a mixture of scientific
results and the best judgment of scientists
responding to management questions.
The authors and contributors hope that
this report will further knowledge of changes
taking place in the Bay, so that together, we
can manage Chesapeake Bay effectively.
Tudor T. Davies
Director
Chesapeake Bay Program
Thomas B. DeMoss
Deputy Director
Chesapeake Bay Program
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PA {MV--0-1".?. .lai Prelection Agency
k.,v.i Hi inclination Resource
Center (3PM52)
SUMMARY 8nChe:tr'UlS!re8L«> '
F^'-d^hia, PA 1910? / -.:
As part of the five year study plan for the EPA Chesapeake Bay Program
(CBP) , EPA staff, officials from Maryland and Virginia, and citizens
identified 10 areas as foremost water quality problems of the Bay, and
agreed upon three as most critical for intensive investigation: Nutrient
Enrichment, Toxic Substances, and the Decline of Submerged Aquatic
Vegetation. The EPA then initiated research to study intensively these
three problem areas. The following summary describes the findings from
research projects funded by the Chesapeake Bay Program in those three
technical areas. Two other CBP reports, "Characterization of Chesapeake
Bay" and "Management Strategies for Chesapeake Bay" assess Bay-wide
conditions and suggest management strategies.
NUTRIENT ENRICHMENT
Nutrients, both phosphorous (P) and nitrogen (N), are crucial to Bay
life. Nutrient enrichment occurs when excessive additions of nitrogen and
phosphorous compounds enter the water. Enrichment can lead to undesirable
consequences such as phytoplankton blooms, depletion of oxygen, and changes
in kinds of fish present. When an estuary, such as Chesapeake Bay, becomes
nutrient-enriched, algae can thrive and accumulate in the water column.
Their presence decreases light transparency, and, when they degrade, they
use up dissolved oxygen that other plants and animals need.
Nutrient enrichment in Chesapeake Bay is evaluated by measuring a
number of related factors including nutrient concentration and oxygen
levels in the water, amounts of chlorophyll a, (a green pigment found in
most algae), and transparency of the water (Secchi depth). Historical
records of these measurements were gathered and analyzed during the Bay
Program to look at trends in nutrients over the past 20 years. During this
time, nutrient concentrations have increased, causing enrichment in some
areas. Figure 1 shows areas of the Bay that are enriched. These include:
most of the western tributaries such as the Patuxent, Potomac, and James;
the northern and central main Bay; and some Eastern shore tributaries
including the Chester and Choptank. These areas show high levels of
nutrients and chlorophyll £, and reduced light transparency. The lower
Bay, however, has remained relatively unaffected. An analysis that relates
these trends to the health of fisheries in the Bay will be presented in the
CBP report entitled "Characterization of Chesapeake Bay."
Sources of Nutrients
Phosphorus (P) and nitrogen (N) enter the Bay from several major sources or
pathways: atmosphere, rivers, point sources, and sediments. The estimated
percentage that each of the sources contributes to the Bay during a year is
shown in Table 1.
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7T*'00'
76'10
Chesapeake -Bay
Region
NAUTICAL MILES
Q 5 10 15 20 28
STATUTE MILES
77-00-
Moderately Enriched
Heavily Enriched
76-30-
75- JO
75-00-
Figure I, Map showing portions of Chesapeake Bay that are moderately
or heavily enriched according to the criteria of Heinle et al. (1980)
ii
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TABLE 1. PERCENTAGE OF ANNUAL NUTRIENT LOADINGS FROM VARIOUS SOURCES(D
Constituent
Total nitrogen
Total phosphorus
Atmospheric
Sources
13
5
Riverine
Sources
56
35
Point
Sources
22
35
Sediment
Sources
9
25
(1'Definition of Terms
Atmosphere: aerial input that directly lands on fluvial or tidal waters.
Riverine: mass loadings of nutrients to Bay from above the head of tide.
Point sources: nutient loads from industry and municipalites below the
head of tide.
Sediment sources: nutrient releases or loads from the bottom sediment
of Chesapeake Bay.
Riverine Sources—
Riverine sources are a major contributor of N and P to the Bay;
approximately 56 percent of the total nitrogen loading comes from these
sources. This loading ranges from 39 percent in summer to 64 percent in
spring when river flows are highest. Riverine source loads for P are about
35 percent of the total annual input and range from 12 percent in summer to
57 percent in spring.
Of all the river sources, the Susquehanna River is the major
contributor of P and N, as shown in Table 2. The Susquehanna River has by
far the largest drainage area and annual flow discharge among the river
sources. This at least partly accounts for the relatively higher
contribution of N and P from the Susquehanna. This river carries about 70
percent of the total nitrogen and 56 percent of the total phosphorus
delivered to the Bay each year from riverine sources. Most of these loads
enter during the winter and spring.
The Susquehanna produces only about 40 percent of annual sediment load,
because the particulate matter is trapped in reservoirs located on the
lower 60 miles of the main stem of the river. Only a large flow, above
400,000 cubic feet per second (cfs), will transport sediment through the
reservoir and deliver them to the Bay. Such flows occur only one percent
of the time.
TABLE 2. ESTIMATED PERCENTAGE OF TOTAL ANNUAL RIVERINE NUTRIENT
AND SEDIMENT LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Constituent
Total nitrogen
Total phosphorus
Sediment
Susquehanna
70
56
40
Potomac
19
22
33
James
6
16
16
Other Tributaries
5
6
11
111
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Major land uses in the Chesapeake Bay basin and their estimated
contribution to riverine nutrient loads are shown in Table 3.
TABLE 3. MAJOR LAND-USES ABOVE THE FALL LINE AND THEIR ESTIMATED
CONTRIBUTION TO RIVERINE NUTRIENT LOADS
Land Use Percent In Basin Percent of Riverine Nutrient Loads
Cropland
Pasture
Forest
Urban
15-20
8-12
60-65
3- 5
TN
45-70
4-13
9-30
2-12
TP
60-85
3- 8
4- 8
4-12
Riverine loadings can vary considerably among land uses. The highest
riverine loading rates come from cropland, and lowest from forest sites.
Agricultural land appears to produce the largest fraction of the riverine
loads by at least a factor of three for both nitrogen and phosphorus, due
to the high unit-area loadings and large percentages of land used for
agriculture in this area. The CBP's Bay-wide watershed model has estimated
the relative contributions of nutrients from all nonpoint sources. These
results will be presented in the CBP report "Management Strategies for
Chesapeake Bay."
Point Sources—
Most of the remaining nutrients in the Bay are contributed from point
sources, such as sewage treatment plants and industries lying below the
head of tide (see Table 1). These point sources account for about 22
percent of total nitrogen load and some 35 percent of total phosphorus
input. The percentage of nutrient load from point sources ranges from 15
in spring to 29 in fall, while phosphorus percentages range from 59 percent
in fall to 21 percent in summer.
Other sources include the atmosphere and bottom sediments. Atmospheric
contribution constitutes about 13 percent of the total nitrogen and five
percent of the annual phosphorus input, while bottom sediments make up
about 10 percent of the annual nitrogen and 25 percent of the annual
phosphorous load.
Seasonal Nature of Nutrient Loads
The largest portion of the annual nitrogen load enters the Bay during
the winter and spring, while the highest portion of the annual phosphorus
load enters during the spring and summer. These nutrient inputs support
increases in algal standing crop. Since the relative abundance of nitrogen
and phosphorus changes from spring to summer, so the potential limiting
nutrient for the algal standing crop may change.
The limiting nutrient changes during the year in Chesapeake Bay as a
result of three prominent events. The first is the substantial nitrate
input with a spring runoff from the Susquehanna River. The second event
IV
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occurs during mid-summer when very low oxygen concentrations in deeper Bay
water permit release of phosphate from Bay sediments and accumulation of
both phosphate and ammonium in the deep water. The third event is the fall
nitrite maximum observed in both mid-Bay and in the lower Potomac River
estuary. Thus, peak nitrogen availability occurs in spring, while peak
phosphorus availability occurs in summer.
Consequently, phosphorus concentration is generally higher in deep
water during summer. Addition of phosphorus during the other seasons could
cause the standing crop of phytoplankton to increase, if nitrogen is
available. Thus, phosphorous appears to be the biomass limiting, or
regulating, nutrient for spring, fall, and winter. Nitrogen, however, is
at its lowest levels and could be limiting in summer; additions at this
time may cause phytoplankton to grow if phosphorous is available from the
deep water due to recycling processes. An awareness of the response of
phytoplankton to available nutrients is important when considering effects
on Bay resources and how to control input. Because phytoplankton form the
base of the Bay's food web, increases in their populations will create more
food for other Bay inhabitants, to a point. Beyond this point (we feel
that Figure 1 indicates what areas of the Bay are at this point) growth of
phytoplankton can be detrimental to the Bay's water quality and its
resources.
Management Implications
Management strategies to address the problem areas must take into
account the seasonal patterns of nitrogen and phosphorous we have described
and the degree to which each contributing source may be controlled, its
relative costs to achieve this control, and trade-offs between point and
nonpoint sources. The possible management strategies will be shown in the
GBP report "Management Strategies for Chesapeake Bay".
TOXIC SUBSTANCES
Toxic substances constitute the second of three critical areas studied
under the CBP. The research focused on determining the status of both
metals and organic compounds in Chesapeake Bay, including their
concentration in the water column, bed sediments, suspended sediments, and
in some bivalves. Sources of metals and organic compounds were also
investigated. A limited amount of research was performed on assessing the
toxicity of point source effluents and Bay sediments.
Toxic substances are usually defined as chemicals or chemical compounds
that can harm living plants and animals, including humans, or impair
physical or chemical processes. The two general classes of toxic
substances studied were inorganic and organic compounds. Inorganic
materials are metals such as arsenic (As), cadmium (Cd), chromium (Cr),
copper (Cu) , and zinc (Zn). Many of the organic compounds are products of
human activities and include pesticides, phthalate esters, polynuclear
aromatic hydrocarbons (PNA's), and other chlorinated hydrocarbon compounds
(PCBs, etc.).
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Current Status
The highest concentrations of metals in Bay sediment occur in Baltimore
Harbor and the Elizabeth River. In the main Bay, the highest metals
concentrations in sediment occur in the northern Bay and particularly near
the western shore where cadmium, cobalt, copper, manganese, nickel, lead,
and zinc are enriched (elevated relative to natural levels) two to eight
times above natural levels from the Susquehanna Flats to Baltimore Harbor
region. At least half of the metal loads for chromium, cadmium, copper,
and lead orginate from human sources.
Metals tend to partition with fine particulate matter such as detritus
and silt. Consequently, highest concentrations of metals in suspended
material (ug of metal per gram suspended material) occur in near-surface
water in the central Bay where organic matter tends to be high. Cadmium,
lead., copper, and zinc display the highest concentrations. Because this
enriched zone is an area of high organic activity where organisms respire,
reproduce, and grow, metals are available for uptake by phytoplankton and
marine organisms. Once in the plankton, the metals can be passed through
the food chain.
Like metals, organic compounds tend to cling to fine material that is
suspended in the water. When this material settles, organic compounds will
accumulate on the Bay floor. Concentrations of organic compounds in bottom
sediments are highest in the northern Bay. They exhibit similar trends to
metal enrichment, with highest concentrations occurring in the vicinity of
Baltimore Harbor. Concentrations tend to increase up the Bay from the
Potomac River mouth toward the Patapsco River. North of the Patapsco
River, elevated concentrations are found to exist to the Susquehanna River
mouth. It appears that many of these organic compounds may have entered
from the Susquahanna River. In the southern Bay, the highest
concentrations of organic compounds are found where the river estuaries
enter the main Bay.
The sediments of the Patapsco River estuary show the highest
concentrations of organic compounds. Highest levels occur near source
locations. These sediments appear to be largely trapped within Baltimore
Harbor.
Oysters collected from around the Bay and oyster-tissue extracts were
examined for organic compound concentrations. These bivalves did
accumulate some toxic compounds. There were 42 compounds detected whose
individual concentrations exceeded 50 parts per billion. The mouth of the
James River had 29 percent, and Baltimore Harbor 24 percent of these 42
compounds.
Sources
Riverine sources above the fall line, point sources below fall line,
and atmospheric sources, contribute most of the metals to Chesapeake Bay as
shown in Table 4. Of the three major rivers in which metal concentrations
were measured (Susquahanna, Potomac, and James), the Susquahanna
contributes the greatest amount of metals. These river loads include
municipal, nonpoint, and industrial sources above the fall lines. The
annual loadings of various metals of the three rivers are compared in Table
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5. The concentration levels of metals in the three rivers are similar,
however, the Susquehanna has greater loadings because of its higher flow.
The Susquehanna River is also very significant to quality of water in the
Bay proper, because the loads it delivers enter the Bay directly and are
not trapped in the sub-estuaries like those from the James and Potomac.
Industrial and municipal input below the fall line are a major
contributor of metals to the Bay (Table 4). For example, industrial loads
account for 66 percent of total cadmium load. Municipal POTWs account for
19 percent of total chromium load. The distribution of these loadings for
POTWs and industries below the fall line (Pennsylvania counties, thus, not
included) by counties is shown in Table 6. The inputs of Cd, Cr, Cu, Fe,
and Zn in Baltimore County and Baltimore City far exceed those from other
counties. Substantial inputs from POTWs are also noted for Cr, Fe, and Zn
in Richmond City; for Cr, Fe, and Zn from Norfolk City; and for Cr, Fe, and
Zn at Hopewell City. The industrial load exceeds POTW loadings by two
times. Loadings from urban runoff and atmospheric sources are also
significant for several metals as shown in Table 4.
Results from the CBP show that sources of organic compounds to the Bay
are human-related. In particular, organic compounds in northern-Bay
sediments are probably from the Susquehanna River, and possibly some from
the Patapsco. Concentrations of organic compounds in the Bay should be
highest in areas of sedimentation near industrial regions and high
population areas. The CBP is further investigating sources of toxic
substances and will present the results in CBP report "Management
Strategies for Chesapeake Bay".
TABLE 4. LOADINGS OF METALS FROM THE MAJOR SOURCES AND PATHWAYS TO
CHESAPEAKE BAY (VALUES IN METRIC TONS/YEAR)
Source Cr Cd Pb Cu Zn Fe
1
Industry 200 (19) 178 (66) 155 (22) 190 (22) 167 ( 6) 2,006 ( 1)
Municipal
Wastewater 200 (19) 6(2) 68 (10) 99 (12) 284 (10) 625 ( 1)
Atmospheric 3(1) 34 ( 5) 28 ( 3) 825 (29) 87 ( 1)
Urban Runoff 10 ( 1) 7(2) 111 (16) 9(1) 63 ( 2) 977 ( 1)
Rivers 551 (53) 75 (28) 307 (43) 517 (59) 1444 (50) 199,682 (77)
Shore Erosion 83 ( 8) 1(1) 28 ( 4) 29 (3) 96 ( 3) 57,200 (22)
^Values in parenthesis represent percent of total loading
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In certain areas, present levels of toxic substances could threaten the
health of organisms. Bioassay tests on bottom sediments from the Bay show
that sediments from the Patapsco and Elizabeth Rivers and northern Bay are
potentially more toxic than elsewhere. This toxicity is probably produced
by a combination of high metal content and large loads of organic
compounds. These tests on bottom sediments found concentrations that cause
mortality. The highest mortalities occurred on samples from the upper
reach of the Patapsco and Elizabeth Rivers, and the northern Bay. Tests
performed on effluent from industrial plants around the Bay area revealed
that up to half of effluents sampled killed test fish and invertebrates.
The significance of these results and their relationship to Bay resources
will be discussed in GBP report "Characterization of Chesapeake Bay".
TABLE 5. ESTIMATED AVERAGE ANNUAL LOADINGS FOR VARIOUS METALS FROM THE
MAJOR TRIBUTARIES OF THE CHESAPEAKE BAY FOR 1979-1980 PERIOD*
(VALUES IN METRIC TONS/YEAR) (FROM LANG AND GRASON 1980)
Parameter Susquehanna
@ Conowingo Dam
Potomac
@ Chain Bridge
James
@ Cartersville, Va.
Totals
Al-T
As-T
Cd-T
Co-T
Cr-T
Cu-T
Fe-D
Fe-S
Mn-T
Ni-T
Pb-T
Zn-T
161,618
82
65
59
383
390
1,844
192,422
14,469
229
174
837
69
71
87
40
70
75
57
65
77
57
57
58
37,626
13
4
39
105
86
839
76,227
1,933
109
102
322
16
12
5
27
19
17
26
26
10
27
33
22
33,884
20
6
48
63
41
567
27,783
2,327
64
31
285
15
17
8
33
11
8
17
9
13
16
10
20
233,128
115
75
146
551
517
3,250
296,432
18,729
402
307
1,444
*Values listed represent the mean of 1979 and 1980 calender year loadings.
(Note: Percentages above are approximate numbers)
D - Dissolved
S - Suspended
T - Total
Management Implications
Managing toxic substances requires a priority, or ranking, framework
that evaluates toxic material for its greatest potential to affect human
and environmental health. As with nutrients, areas where environmental
quality is severely degraded should be established, based on all available
environmental quality data (sediment, biota, and water) and should be top
Vlll
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priority for cleanup. The priority areas will be examined in the CBP
report "Characterization of Chesapeake Bay".
SUBMERGED AQUATIC VEGETATION
Pattern of Decline
Submerged aquatic vegetation (SAV) has, in the past, been very abundant
throughout Chesapeake Bay. Our current evidence indicates a pattern of SAV
decline that includes all species in all sections of the Bay. A marked
decline has occurred throughout the estuary since the mid-1960's. Present
abundance of Bay grasses is at its lowest level in recorded history.
Historical analysis of sediments on Bay-grass seeds and pollen
indicates a continuous presence of Bay grasses from the 17th century. In
the last 50 years, there have been several distinct periods and patterns
where Bay grasses have undergone major changes. An outbreak of eelgrass
wasting disease occurred in 1930 "s and reduced SAV populations, as did a
watermilfoil outbreak in the late 1950"s and early 1960's. However, a far
more dramatic and Bay-wide decrease in SAV populations occurred in the
1960's and 1970's where, unlike the eelgrass and milfoil events, all.
species in almost all areas of the Bay were affected. The change is not
attributable to disease.
Because there has not been a significant change in SAV distribution
along the east coast of the United States comparable to the Chesapeake Bay
decline, it is most likely that water quality problems affecting the
distribution of grasses in Bay are regional and specific to the Bay, its
tributaries, and their drainage basin. Recent international studies have
found that SAV declines in other countries are highly correlated with
changing water-quality conditions, such as decreasing water clarity
resulting from increased eutrophication, as sewage, agricultural runoff,
and suspended sediment inputs increase. CBP work suggests that sediment
composition and light availability are the most important factors
controlling the distribution of SAV within regions of the Bay. In
addition, SAV decline parallels historical increases in nutrients and
chlorophyll £ concentrations in the upper Bay and major tributaries that
occurred first in freshwater parts and have now moved "down-river".
Value
The severity of the decline is heightened by the importance of SAV to
the vitality of the Bay. The Bay grasses are vitally important to the Bay
because of their value as large primary producers, food sources for
waterfowl, habitat and nursery areas for many commercially important fish,
controls for shoreline erosion, and mechanisms to buffer negative effects
of excessive nutrients.
Numerous studies have shown that the primary productivity of SAV
communities is among the highest recorded for any aquatic systems.
However, trends in SAV biomass production follows those of its distribution
and abundance. The average biomass estimates for SAV in the Bay are low
relative to other communities. For example, we have estimated that some 40
percent of primary production in Bay was attributable to SAV in 1963 while
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only six percent is attributable to SAV in 1975. These trends along with
other results are indicative of stressed plants, particularly in the upper
Bay.
SAV provides food and habitat for many species of birds and animals.
The most definitive linkage is between SAV and waterfowl. Some types of
SAV are excellent food for waterfowl. In recent years, the most important
waterfowl wintering areas have also been the most abundantly vegetated
areas. Waterfowl have adapted to the SAV decline primarily by wintering
elsewhere in the Atlantic Flyway.
SAV beds in Chesapeake Bay support larger populations of most animals
than nearby unvegetated bottoms, and provide significant protection from
predators. Fish abundance in SAV communities in the upper Bay are among
the highest ever recorded, indicating that SAV are sources of food either
directly, or indirectly, to important Bay species. Few
commercially-important finfish use SAV beds as significant nursery
habitats. However, lower Bay beds do serve as a primary blue crab nursery,
supporting a very large number of juvenile blue crabs throughout the year.
Work in the upper Chesapeake Bay has shown that SAV is important in
stablizing suspended sediments. As turbid water enters SAV beds on rising
tides, sediments are effectively removed, and light transparency
increases. Sediment resuspension is reduced in proportion to SAV biomass.
SAV also reduces nutrient levels in the water. Our studies show that,
at moderate loading rates, nutrient concentrations are consistently lower
in SAV communities than in unvegetated sites. Ammonium concentrations
were one to 10 times lower, nitrate two to 10 times lower, and
orthophosphate generally two to four times lower in the SAV community than
in deeper, offshore waters. When loading rates and nutrient concentrations
reached high levels, SAV was no longer effective in reducing nutrient
levels.
Cause of the Decline
During the Bay program, investigators looked at light reduction as a
major cause of SAV decline. Overall, factors governing light energy
availability to submerged aquatic vegetation are the principal control for
growth and survival. Bay grasses are currently living in a marginal light
environment, and water quality problems, such as increases in nutrients and
chlorophyll £ concentrations in major tributaries and the main stem of the
Chesapeake Bay over the past several decades, are seriously affecting the
distribution and abundance of grasses in the Bay region. Epiphyte
communities, those organisms that directly attach to submerged aquatic
plant blades, can also limit light availability.
Another important factor contributing to the stress of SAV in the Bay
is the input of herbicides to the ecosystem. Our laboratory and field
experiments indicate that herbicides are not generally available to SAV in
toxic levels, and their presence alone probably did not cause the SAV
decline. However, herbicide-induced impacts could, in concert with the
other major stresses (such as those from light limitation), create
intolerable conditions for SAV existence.
In summary, the SAV decline parallels a general increase in nutrients,
chlorophyll £ concentrations, and turbidity in the upper Bay and major
tributaries. This decline first ocurred in freshwater portions, and has
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moved down-river. The upper-Bay, western-shore, and lower-Bay communities
have been the most severely impacted. Light, restricted by organic and
inorganic suspended particles from runoff and nutrient loads, and by
changes in physical-chemical regimes (salinity and temperature), is the
principal factor controlling Bay-grass growth and survival. Bay grasses
are now living in a marginal light environment and will be adversely
stressed if water quality in the Bay declines further. Management programs
that minimize sediment and nutrient loads will have to be improved and
expanded if SAV is to flourish again throughout the Bay.
The "Characterization" report will address relationships between SAV,
other natural resources, and water quality trends; the "Management
Strategies" report will suggest ways to protect and/or enhance these
resources.
xii
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CONTENTS
Parts Page
I. How We Studied The Bay 1
Introduction 2
Studying the Bay 4
Management Questions and Answers 6
II. Nutrient Enrichment 36
Introduction 37
Chapter 1. Nutrient Enrichment of Chesapeake Bay: An
Historical Perspective 45
Chapter 2. Nutrient Processes in Chesapeake Bay 103
Chapter 3. Nutrient and Sediment Loads to the
Tidal Chesapeake Bay System 147
Summary and Conclusions 259
Appendix 262
III. Toxic Substances in Chesapeake Bay 263
Section 1. Introduction 272
Section 2. Findings from Studies on Metals 277
Section 3. Findings from Studies on Organic Compounds . . 310
Section 4. Patterns of Toxic Metal Enrichment 321
Section 5. Findings on Sediments and Biota 328
Section 6. Toxic Substances and Biota 338
Section 7. Conclusions and Interpretations 342
Section 8. Research Needs 346
Appendices 359
IV. Submerged Aquatic Vegetation 376
Introduction 377
Chapter 1. Distribution and Abundance of Submerged
Aquatic Vegetation in Chesapeake Bay 381
Chapter 2. Ecological Role and Value of Submerged
Macrophyte Communities 428
Chapter 3. Herbicides in Chesapeake Bay and their
Effects on Submerged Aquatic Vegetation 503
Chapter 4. Light and Submerged Macrophyte Communities
in Chesapeake Bay 568
Appendix 631
Summary and Conclusions 633
Credits
Editors
Production
Artwork
Cover
Elizabeth Giles Macalaster
Debra Allender Barker
Mary Kasper
Dorothy Szepesi
Janet L. Malarkey
Laurie Harmon
Virginia Institute of Marine Science
Bill Allen
Gail Mackiernan
xiii
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PART I
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• HOW WE STUDIED THE BAY: ASKING AND ANSWERING THE QUESTIONS
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PART I
HOW WE STUDIED THE BAY: ASKING AND ANSWERING THE QUESTIONS
INTRODUCTION
At a singular gathering in October 1977, EPA staff, officials from
Maryland and Virginia, and citizens developed a five-year study plan for
the Chesapeake Bay Program (CBP). As part of the plan, they identified the
ten foremost water quality problems of the Bay, and methods needed to
research those areas. These ten problems were:
o wetlands alteration
o shoreline erosion
o water quality effects of boating and shipping
o hydrologic modification
o fisheries modification
o shellfish bed closures
o accumulation of toxic substances
o dredging and dredged material disposal
o nutrient enrichment
o submerged aquatic vegetation
By early the following winter, three critical areas were chosen from
the ten for intensive investigation — Nutrient Enrichment, Toxic
Substances, and the decline of Submerged Aquatic Vegetation (SAV).
In all three areas, we wanted to improve our understanding of major
changes taking place in the Bay. Increasing development within the Bay
area has enriched major tributaries and parts of the main Bay with
nutrients, resulting in loss of dissolved oxygen and large algae blooms.
In the nutrients area, CBP has assessed the relationship between nutrients
and water quality, and the potential for future enrichment. Until
inception of the Program, much of the basic information needed to assess
the presence of toxic material in the Bay and its effects on Bay
communities was not available, or poorly known. To build an information
base upon which future measures and effects can be compared, the CBP
estimated the distribution and abundance of toxic substances throughout the
Bay. The past ten years have also revealed sharp declines in the diversity
and density of SAV. The CBP looked at the role and value of SAV in the Bay
ecosystem and at some of the most probable causes of its decline.
With the completion of most of the technical studies in the summer of
1981, the CBP began to analyze and integrate results. Early in the program
the staff, State managers, citizens, and researchers posed a series of
questions pertinent to managing the Bay. These questions appear at the end
of this part of the report. Using the Management Questions as a guideline,
scientists in each of the three problem areas jointly wrote research papers
that integrate results across the specific problem areas. To best answer
the questions for managers, decision-makers, and citizens, the authors
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integrated into their papers not only data from specific projects, but
information from other research and world literature. The papers were
drafted prior to September 1981 and include data up to that point, except
where noted. (Some later data have been incorporated into the GBP's
characterization process as they were available.) Drafts of the synthesis
papers were carefully reviewed by scientists outside of the Bay area as
well as by CBP staff and State participants in the Program. The major
State agencies involved in contributing to, and reviewing the synthesis
papers include: The Virginia State Water Control Board; the Maryland
Department of Health and Mental Hygiene; the Maryland Department of Natural
Resources; and the Pennsylvania Department of Environmental Resources.
These papers not only respond to many of the Management Questions, but
also support the rest of the phases of GBP's program - water quality and
resources characterization, environmental quality classification, and
management strategies. The papers, for example, provide a sound technical
foundation for the CBP's characterization process, presented in the third
final report. In this analysis, many important parameters used to assess
water quality in parts of the Bay were identified from information in the
synthesis papers. Furthermore, the last final report on management
strategies builds on the management questions and answers in the synthesis
papers to present the best options for managing Chesapeake Bay.
In overview, this report represents the most technically comprehensive
product of the Program. A list of all of the products and their
relationship to the synthesis papers includes:
o 40 final reports on individual research projects, with summaries
of each report.
o Description of the Program's computer model of the Chesapeake Bay
system.
o Chesapeake Bay: Introduction to an Ecosystem—explains important
ecological relationships and serves as a reference for the
synthesis report, the characterization report, and the CBP
management alternatives.
o Chesapeake Bay Program Technical Studies: A Synthesis—summarizes
and explains the technical knowledge gained from the research
projects funded by this program in the areas of nutrient
enrichment, toxic substances, and submerged aquatic vegetation.
It provides an understanding of the processes which affect the
quality of Chesapeake Bay.
o Characterization of Chesapeake Bay — Assesses trends in water
quality and living resources over time, and examines relationships
between the two.
o Chesapeake Bay Program Management Study — Identifies control
alternatives for agriculture, sewage treatment plants, industry,
urban runoff, and construction; estimates costs and effectiveness
of different approaches to remedy "hot spots."
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STUDYING THE BAY
The integrity of Chesapeake Bay begins far from the actual estuary.
The Bay itself lies within the Atlantic Coastal Plain but draws water from
a drainage basin of 64,000 square miles that includes five states and parts
of the Piedmont and Allegheny Plateaus. The diverse rock types found in
the plateaus affect the chemical make-up of the many tributaries running to
the Bay. At the estuary, this chemically-varied riverine water meets and
mixes with oceanic water to form a variety of physical and chemical
environments. Since organisms living in water are suited to different
ranges of temperature and chemical mixtures, how the mixture changes
naturally, or unnaturally, influences the ability of the Bay to maintain a
wide variety of life.
More than 2000 species of plants and animals inhabit the Bay. These
plants and animals live in communities, such as in marshes or on the
bottom, and depend on each other for food and shelter. Communities respond
naturally to changes in the environment through changes in diversity and
abundance. Some variations result from seasonal changes, others from
long-term fluctuations; still others are caused by human influences.
Assigning the cause of this biological variation to natural or human
influences is one of the most difficult problems encountered in ecology.
To better understand the major processes governing the Bay and its
inhabitants, and how they may be affected by continued input of pollutants,
CBP devised Bay-wide research plans focusing on three study areas—nutrient
enrichment, toxic chemicals, and submerged aquatic vegetation. State and
CBP staff, together with EPA personnel, wrote plans of action and asked any
interested scientists to respond with suggestions and proposals for doing
research. These proposals were reviewed and modified, with selected ones
chosen for funding during the spring and summer of 1978. The program spent
nearly $17 million on 40 research projects, grants, cooperative agreements,
and contracts. This approach to funding the Program's studies allowed a
broad research community to take part in the investigations.
Scientists and institutes often cooperated in collecting and analyzing
their data. They shared research vessels, used commmon sampling sites, and
similar time periods. One of the largest cooperative efforts occurred
during a Bay-wide, water quality survey. During this series of cruises
aboard several research vessels, scientists from a dozen private research
institutions, and State and Federal agencies collected information on
nutrients, other important water quality factors, and hydrodynamics of the
Bay and its tributaries.
To ensure that the diverse data collected and analyzed during the five
years of investigation were credible, properly maintained, and analyzed
accurately, CBP undertook a quality assurance program. In this program a
computer and research staff made sure the data from research projects and
historical sources were reliable. The staff also prepared the data for
computer storage and analysis by devising a set of standardized names for
variables and units. Statistical analyses were documented in directories
and reviewed by CBP technical staff. In addition, inferences derived from
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the analyses were reviewed by both technical and computer staff to assure
statistical validity and technical accuracy.
The synthesis papers are divided into three parts. The first presents
a synthesis of information on nutrient enrichment — what the enrichment
problem is, what chemical, physical, and biological processes interact to
sustain the problem, and what the major sources of nutrients to the Bay
are. The second part covers the CBP toxic substances program. This
section discusses our knowledge of toxic chemicals, sources, distribution,
and concentration of metals and organic compounds in the water and
sediment, and how geochemical and biological processes of the Bay can
affect the character and distribution of toxic substances. The third part
explains the results of CBP's SAV investigations in light of what factors
caused its decline. The sections in this part discuss the distribution and
abundance of SAV now and in the past, the value of SAV to the Bay
ecosystem, the possibility of herbicides as a major factor in its decline,
and light as the link between SAV and its decline.
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• THE MANAGEMENT QUESTIONS AND ANSWERS
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MANAGEMENT QUESTIONS AND ANSWERS - NUTRIENT ENRICHMENT
1. The Nutrient Enrichment Problem
1.1. Where and how severe are nutrient enrichment problems in the Bay?
The upper Bay, upper Potomac, and upper James are nutrient enriched and
are the sites of current and potential problems. The mid-Bay, other
Western Shore tributaries and Susquehanna are less enriched, but could
become nutrient enrichment problems.
1.2. What are the consequences of nutrient enrichment?
The consequences of nutrient enrichment are enhanced plant production
and higher levels of organic matter in the water column. This organic
matter may accumulate in deep water, where its degradation results in
oxygen depletion. Mobile estuarine organisms leave the low oxygen water;
stationary organisms succumb. However, it is possible that planktivorous
organisms, like menhaden, could benefit from increased production of
plankton.
Nutrient enrichment may also alter the species composition of
phytoplankton, potentially causing changes in fisheries.
1.2.a. What factors are required by phytoplankton for
growth?
Phytoplankton require light, nutrients, appropriate temperature,
appropriate salinity, and innumberable other factors. Of the criteria
listed above, only the nutrients, specifically nitrogen and phosphorus, are
controllable by people. Any element can be limiting: phytoplankton cannot
grow in inadequate light or in areas having inappropriate salinity.
1.3. what are the advantages and disadvantages of the commonly used
criteria for evaluating a water quality problem related to
nutrient enrichment?
Chlorophyll a_ levels are useful because they give a direct indication
of phytoplankton density, which is one of the important consequences of
nutrient enrichment. There is also a fairly good historical record for
chlorophyll a_. However, laboratory techniques have changed over the years,
particularly in the mid-19701s, and there may be a problem in comparing
current data with historical data. Another disadvantage is that it is
possible to have high chlorophyll a_ levels in non-enriched situations,
because of circulation and behavioral responses of phytoplankton. For this
reason, chlorophyll a_ measurements should be repeated over time to
corroborate their validity.
Secchi depth is a commonly used criterion because its determination is
inexpensive, and it is reliably measured from person to person. It also
has a long historical record. On the other hand, it is not sensitive to
small changes in photic zone, which can reflect large changes in
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turbidity. It cannot distinguish between inorganic and organic sources of
turbidity.
Measurement of inorganic nutrient concentrations is fairly simple, and
methods have been reasonably uniform historically. However, while high
inorganic nutrient levels indicate a problem, low levels give no indication
of enrichment because nutrients can be tied up in organic forms.
Measurement of total nutrient levels would make it possible to assess the
total enrichment of the system, but is difficult to carry out and does not
have good historical record.
Dissolved oxygen levels are tremendously useful to managers because
oxygen depletion is the major consequence of enrichment. However,
dissolved oxygen should be expressed as oxygen deficit (a term related to
saturation level) and should account for season. The disadvantage is that
short-term events, like wind, can affect dissolved oxygen levels.
Algal species shifts are a good indicator of nutrient enrichment in
fresh waters, where blue-green algal blooms are known to occur under
enriched conditions. However, in estuarine systems the "normal" algal
flora is not well defined, so changes due to nutrient enrichment cannot at
present be documented.
1.4. What techniques can be used to evaluate or predict nutrient
enrichment problems?
Nutrient enrichment indices are desirable to managers because they give
an assessment of enrichment stated in very simple terms. Their
disadvantages are that they may not provide an adequate reflection of
complex ecological conditions; they are not generally applicable from
system to system, and they are subjective.
Computer-based mathematical models can quantify multiple combinations
of processes and conditions that are beyond the capacity of human
comprehension. They are valuable planning tools because they can project
the response of an estuarine system to specific conditions. On the other
hand, they are not generally applicable because specific pollutants and
systems require specific models. Calibration and verification may be
difficult because of gaps in data. Finally, people are inclined to expect
models to provide final answers, perhaps not scruitinizing the modelling
process or results sufficiently.
1.5. What are the historical trends in nucrient enrichment?
In some areas of the Chesapeake Bay system, chlorophyll a
concentrations have increased from a pre-settlement level of less than 30
ug/liter to over 60 ug/1 during the summer. These areas include the upper
Bay, upper Potomac, and upper James and, for this reason such areas are
considered to be heavily enriched. This question will be evaluated further
by the Chesapeake Bay Program Characterization Report.
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1.6 What are the greatest needs for further research?
The primary need in Chesapeake Bay research is long-term coordination.
Many gaps need to be filled in basic research, and this can only be
accomplished if areas needing further research are identified and a
concerted, coordinated, long-term effort made to fill the gaps.
Nutrients research would be furthered by the development of better
models for the estuarine system.
Finally, better understanding of processes like hydrodynamics, species
composition, algal productivity, assimilative capacity, and effects on
fisheries is needed.
2. Nutrient Processes
2.1 What nutrients are available, at what times, in the Chesapeake Bay
system?
The availability of nutrients in Chesapeake Bay follows an annual cycle
which has three prominent events. First, the spring freshet brings a
substantial amount of nitrate into the Bay. Second, deoxygenation of deep
water in summer results in phosphate release from the sediments and
accumulation of both phosphate and ammonium in the deoxygenated region.
Third, reoxygenation of deep waters in fall corresponds with the loss of
phosphate from the water column and the oxidation of ammonium to nitrite
and nitrate.
2.2 What is nutrient limitation? How does it regulate algal
production?
Healthy algae require carbon, nitrogen and phosphorus in certain
ratios. Algal production is regulated by the nutrient in least abundance
relative to the algal requirement (assuming that other factors like light
and salinity are adequate). The nutrient regulating algal production is
referred to as the limiting nutrient; addition of the limiting nutrient
stimulates algal production. (Taft pp 12-29)
2.3 When and where are phosphorus and nitrogen limiting?
The potential for phosphorus limitation in the tidal fresh regions of
the Bay exists throughout the year. This is because blue-green algae,
major constituents of fresh-water systems, are not limited by nitrogen due
to their ability to fix this nutrient from the atmosphere. (P limitation
is expressed as a potential because light may actually limit growth.)
Phosphorus is limiting in the Bay stem during spring, because this is the
major period of nitrogen influx from the tributaries, while phosphorus is
still largely bound to the sediments because of oxygenated conditions. (in
the maximum turbidity zone light may in fact be limiting, so the potential
for phosphorus limitation may not be expressed.)
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Nitrogen is limiting over most of the main Bay in summer (with the
exception of the maximum turbidity zone, where the potential for nitrogen
limitation exists but growth may actually be limited by light). During the
summer phosphorus is provided from the sediments because of anoxic
conditions, while there is no major influx of nitrogen.
2.4 How does light regulate phytoplankton production? When and where
is light limiting?
Light may limit algal production when turbidity is high due to sediment
accumulation in the water column. This happens particularly in spring in
the upper Bay when sediment influx is extensive. It may happen in maximum
turbidity zones year-round.
Chesapeake Bay Program research indicates that physical processes may
lift phytoplankton from dark subsurface layers into the surface waters,
overcoming the potential for light limitation for these algae. Light
limitation will also not be important where adequate mixing brings
phytoplankton to the surface regularly.
2.5 How does nutrient enrichment affect algal production?
Whether nutrient enrichment increases algal production depends on
whether the nutrient is limiting, whether luxuriant uptake occurs, and
whether the nutrient is in its "preferred" form.
Where a nutrient is limiting, its addition will increase algal
production. Addition of a non-limiting nutrient may also ultimately
increase biomass because of luxuriant uptake, in which phytoplankton take
up a nutrient but do not immediately utilize it. Internal stores of the
nutrient are created, which can be drawn from later if there is a shift in
the limiting nutrient.
Addition of nitrate or nitrite will not stimulate phytoplankton growth
in the presence of a threshold level of ammonium. Phytoplankton
preferentially take up ammonium and will not utilize added nitrate in the
presence of ammonium. The phenomenon was confirmed as a result of Bay
Program research, and is particularly significant in the spring when the
large inputs of nitrate appear to pass through into the lower areas of the
Bay, unutilized because of the presence of ammonium.
2.6 How does nutrient enrichment affect species composition, diversity
and trophic relationships of phytoplankton?
Shifts to blue-green algal dominance in the tidal fresh regions have
been a well-documented response to nutrient enrichment. Such compositional
shifts have not been shown in the higher salinity areas of the estuary.
Where blooms clearly do occur in response to nutrient enrichment, they
result in a decline in diversity and stability of the phytoplankton
community. Thus rapid growth can be followed by rapid declines, leading to
unaesthetic conditions, de-oxygenation, and other consequences.
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Nutrient enrichment probably affects trophic relationships, because
blue-green algae are inedible for most plankton feeders. When blue-green
algal blooms occur and little other phytoplankton is available in the
rivers, plankton feeders must find some other food source (switch-feeding)
or decline.
2.7 How might higher trophic levels be affected by the changes
described in 2.6?
When species shifts occur, the dominant organism may not provide
complete nutrition to grazers, which may shift the grazing population.
Planktivorous species may be favored by increased phytoplankton production
and species shifts; trends in menhaden populations may show this.
2.8 What are the major water column nutrient cycling processes?
Important processes contributing to water column nutrient dynamics are
hydrodynamics, grazing, decomposition, and bacterial transformations of
inorganic nutrients.
Grazing by predators (plankton feeders, etc.) and decomposition by
bacteria and fungi are the regeneration mechanisms. Nutrient regeneration
is important because phytoplankton can use primarily inorganic nutrients.
Regeneration can be a major source of nutrients to phytoplankton during
certain periods.
Grazing of phytoplankton by predators yields production of feces by the
grazers, as well as release of materials from the phytoplankton cells.
This facilitates bacterial degradation of phytoplankton organic material.
Bacteria and fungi decompose dead organic matter, converting complex
organic molecules into simple inorganic molecules like nitrate, ammonia,
phosphate, nitrite. They also transform inorganic nutrients in
nitrification and denitrification. New data from CBP research indicates
that nitrification is important in the fall, resulting in a nitrite maximum
then. Nitrogen fixation may be important in the tidal fresh portions but
is insignificant in the rest of the Bay.
Hydrodynamic processes like circulation, wind, and tides transport and
dilute nutrients. Increased stratification in summer results in nutrients
being held below the pycnocline. Important vertical exchange processes are
dilution and tidal or wind mixing. These processes, combined with chemical
and biological events, tend to retain nutrients in two-layered estuaries
like the Bay.
2.9 What are the major sediment nutrient cycling processes, and how do
these contribute to nutrient enrichment?
The important sediment nutrient processes are flux from the sediments
into the water column and vice versa, nutrient cycling, and binding of
phosphorus by iron and manganese oxides.
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If In fall, stratification is reduced, and the water is reaerated.
Nutrients are biologically and chemically transformed as a result of the
•| newly available oxygen.
In winter, the water is well oxygenated. Low temperatures and light
levels reduce system productivity; nutrients may be present in measurable
• quantities.
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Phosphorus flux rates depend on oxidation state: under anaerobic
conditions phosphorus is released from the sediments. This is an important
process in deeper Bay waters in mid-summer, which may then be anoxic.
During the rest of the year waters are oxic, and iron and manganese
compounds retain phosphorus in the sediments.
Ammonia flux rates vary with interstitial water concentration. In
mid-summer, ammonia is not readily oxidized and accumulates in bottom
waters.
CBP research indicates that water column nutrient recycling yields 5 to
10 times as much available nutrient as sediment processes.
2.10 What factors affect levels of dissolved oxygen in Bay waters and
sediments?
Oxygen is produced by photosynthesis. It is also added by re-aeration,
resulting from diffusion of oxygen from air into upper waters. Its rate
depends on wind, temperature, and the oxygen gradient in the water.
Oxygen is utilized by respiration, especially in summer. Respiration
is carried out by phytoplankton, microbes, and animals. Oxygen is also
utilized by microbes as they oxidize reduced chemical species like
ammonia. These processes result in BOD (biochemical oxygen demand) and SOD
(sediment oxygen demand).
In summer, respiration rates are high because of elevated temperatures
and high production. Respiration of detritus in bottom waters depletes
oxygen there, and stratification prevents re-aeration. In some areas of
the Bay this summer anoxia is probably natural, but it is aggravated by
nutrient enrichment.
2.11 Which processes dominate seasonally?
In spring, the major event is the nitrate influx and the effect of
freshwater on stratification.
In summer, bottom waters are depleted of oxygen by respiration;
replenishment is prevented by stratification. Phosphorus is released by
the sediments, and ammonia accumulates.
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3. Nutrient and Sediment Loads 1'
3.1 What is the atmospheric contribution to nutrient input?
The atmospheric nutrient contribution that directly enters tidal waters
is at least 40 million pounds of nitrogen and 1.6 million pounds of
phosphorous each year [Table VIII.1(a)]. This load constitutes about 13
percent of the annual nitrogen, and five percent of the annual phosphorous
input budgets [Table VIII.l(b)]. Seasonally, atmospheric sources may make
up as much as 20 percent of the seasonal total nitrogen (winter) input and
five percent of the seasonal total phosphorous (summer) input and as little
as seven percent of the total nitrogen load and three percent of the total
phosphorous load in the winter and spring [Tables VIII.2(b) to VIII.5(b)].
3.2. What percentage of the nutrients is from point sources?
On an annual basis, about 20 to 25 percent of the total nitrogen load
entering tidal waters comes from point sources basin-wide [Table
VIII.Kb)]. This percentage range would hold even if all of the point
sources load discharged above the fall line were transported directly to
the tidal system (a very conservative assumption since losses undoubtedly
occur in transport, especially during the summer). The proportions are
relatively invariant throughout the year, reaching the lower end of the
range in the spring and the upper end in the summer and fall.
To make a reasonable estimate of the percentage of the phosphorous load
deriving from point sources, some manipulations of the riverine loading
models developed in Chapter III were performed. Low flow values were
chosen for each of the major tributaries2, and the total phosphorous load
expected to occur at these flows was computed. This total flow (sum of all
three tributaries) was about 9660 cubic feet per second. Note from Table
IV.12(a) that the total point source flow entering above the fall line is
about 688 cfs. The total phosphorus load computed to be carried to the
tidal system at a stream discharge of 9660 cfsd is about 1950 Ibs./day or
about 0.7 million pounds per year. If the extremely conservative
assumption is made that all of this load derives from point source
discharges and is summed with the 10.8 million pounds of point source
phosphorous discharged per year below the fall line, the total point source
contribution of phosphorous is computed to be about 40 percent of the total
annual phosphorous input budget of around 11 million pounds per day.
Seasonally, the point source contribution of phosphorous makes up as much
as 65 percent of the fall total phosphorus input budget and as little as 25
percent of the summer total phosphorous input budget.
^•Answers to all questions in the following section are based on Chapter 3
of Part II in "Chesapeake Bay Program Technical Studies: A Synthesis."
^The "daily discharge that is greater than or equal to the flows that occur
10 percent of the time" was computed for each major tributary. They are:
Susquehanna, 6640 cfsd; Potomac, 1690 cfsd; James, 1330 cfsd.
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3.3. What percentage of nutrients is from nonpoint sources and how do
they vary over time?
To discuss nonpoint sources within the structure of this paper, we
define three categories of diffuse sources. They are:
i) Atmospheric contributions
ii) Land runoff/base flow contributions
iii) Bottom contributions
Categories i) and ii) are covered separately elsewhere in this section
of the Management Questions. To answer this Management Question, we define
nonpoint sources as the sum of land runoff and base flow (groundwater
discharge) carried by fluvial processes to the tidal Bay system.
Contributions from the coastal plain are not considered.
On an annual basis, the mean total nonpoint source nitrogen loading is
about 50 to 55 percent of the total input budget, or about 160 to 177
million pounds of nitrogen per year [Tables VIII.l(a) and VIII.l(b)],
making this the single largest external source of nitrogen loading to the
Bay. Seasonally, the variation in the nonpoint source nitrogen loading is
quite dramatic, ranging from about 23-25 million pounds in the summer (36 -
39 percent of the total source load) to around 69 - 71 million pounds in
the spring (63 - 66 percent of the total spring nitrogen load). The
dominant species of nonpoint source nitrogen at the fall line is always
nitrite-nitrate, making up consistently between 62 and 64 percent of the
total nitrogen from this source.
On an average annual basis, the nonpoint source loading of phosphorous
is about 30 to 34 percent of the total phosphorous input budget, ranging
from around 9 to 10 million pounds per year. As much as 65 to 70 percent
of this load on an annual basis is in the suspended phase, meaning most of
the phosphorous being carried to the Bay is associated with particulate
matter and therefore, not immediately available for phytoplankton
utilization. Seasonally, the nonpoint phosphorous contribution probably
varies from about 1.2 to 1.4 million pounds (only about 10-11 percent of
the summer total phosphorous budget) in the summer to about 4 million
pounds in the spring or 55 percent of the total spring input budget of
phosphorous from all sources. The very low percentage of the load coming
from fluvial sources in the summer is due mainly to the dominant effect of
bottom sources of phosphorous released in that season.
3.4. What are the pollutant runoff rates for particular land uses?
The information upon which this answer is based may be found in the EPA
Chesapeake Bay Program Information Series Nutrient Summary 3: "Assessment
of Nonpoint Source Discharge to Chesapeake Bay" (unpublished). The data
presented in that report are the results of a preliminary analysis of the
data from the Chesapeake Bay Program Intensive Watershed Studies (IWS).
The analysis performed on the data used the volume-weighted mean
concentrations of storm event runoff, computed for the CBP studies
(Hartigan, 1981) along with some typical expected average annual runoff
volumes for various land use/soil texture combinations, to generate
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generalized annual pollutant loadings for various classes of land use.
These data are presented in Table VIII.6. Although the analysis, in its
preliminary state, necessarily produced overlapping ranges of runoff
loading rates among land uses, the data in Table VIII.6 allow us to assign
order of magnitude rankings for the land uses studied by areal loading
rate. The generalized rankings are shown in Table VIII.7.
In all cases, the highest unit area loading rates were generally
exhibited by cropland sites and the lowest by forest sites.
(N.B. The rankings shown in Table VIII.7 are a very broad generalization'.)
TABLE VIII.7 CONCENTRATION, MG/L (TOP LINE), AND LOADING RATES, LBS/AC/YR
(BOTTOM LINE), FOR TOTAL SUSPENDED SOLIDS, TOTAL PHOSPHORUS,
ORTHOPHOSPHATE, TOTAL NITROGEN, AND NITRITE-NITRATE FROM
VARIOUS USES OF LAND(D(2)
Land Use
Cropland(3)
Pasture
Forest
Residential
SED
46.5-3202.8
10.54-2460.83
145.20-669.70
16.45-303.50
9.40-71.5
0.53-48.60
38.00-634.4
47.40-2395.1
TP
0.21-12.49
0.05-9.78
0.38-1.12
0.04-0.51
0.06-0.23
0.00-0.16
0.10-1.66
0.13-5.22
OP
0.01-2.77
0.01-2.20
0.06-0.14
0.01-0.06
0.00-0.04
0.00-0.03
0.02-0.17
0.03-0.54
TN
1.3-22.2
0.75-17.59
2.20-6.20
1.25-2.81
0.40-1.10
0.02-1.00
0.70-2.8
0.87-8.82
N023
0.02-16.20
0.02-12.90
0.30-1.71
0.03-0.78
0.01-0.48
0.00-0.33
0.26-0.90
0.32-2.84
^'Volume-weighted concentration data from preliminary analysis by NVPDC,
concentration in milligrams per liter. Personal Communication:
"Volume-Weighted Mean Concentrations of Storm Event Runoff from EPA/CBP
Test Watersheds," J.P. Hartigan, Regional Resources Division, Norther
Virginia Planning District Commission, Falls Church, VA, October 13, 1981.
'^'Loading rate computed by CBP staff, in Ibs./ac./year.
'3)cropland includes primarily conventional and minimum till with some no-
till land practices.
TABLE VIII.8 GENERALIZED RANKING OF LAND USES BY UNIT AREA RUNOFF LOADING
RATE (1 = HIGHEST RATE, 4 = LOWEST RATE)
Land Use TN N023 TP OP SED
Cropland
Residential
Pasture
Forest
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
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For instance, one of the cropland sites in the southern portion of the
western shore produced less nitrite-nitrate per acre than one of the forest
sites on the upper Eastern Shore. Although this example may be anomalous,
it illustrates that there is overlap in the data and that the rankings
shown are general in nature and by no means apply to all sites on all soil
types. They are intended to give indications of which land uses, in
general, have the highest loading rates and which uses have the lowest
rates, relative to one another.
Within the class of developed land use types such as residential and
commercial uses, it has been shown (Smullen, Hartigan, and Grizzard, 1978;
Smullen 1979, NVPDC 1979) that there is a direct relationship between
intensity of land use, often measured as the imperviousness of a site, and
the unit area loading rate yield of nutrients. A ranking of the urban uses
by loading rate is shown in Table VIII.8.
TABLE VIII.9 RANKING OF URBAN LAND USES BY UNIT AREA LOADING RATfil FOR
NUTRIENTS (HIGHEST LOADING RATE = 1, LOWEST LOADING RATE = 7)
Land Use Ranking
Central Business District 1
Shopping Center 2
High-Rise Residential 3
Multiple Family Housing 4
High Density Single Family Housing 5
Medium Density Single Family Housing 6
Low Density Single Family Housing 7
In general, urban uses exhibit higher unit area loading rates of nutrients
than forest or pasture uses and lower rates than cropland uses. Exceptions to
this "rule of thumb" are that pasture typically will yield slightly higher
rates than the very low-density residential uses and that well-managed,
low-tillage cropland uses on pervious soils can yield lower rates than some of
the more intensive urban uses.
3.5. What percentages of nonpoint source nutrient loadings can be
attributed to particular land uses?
To answer this question with any level of precision, we first must accept
two basic assumptions to facilitate the estimate, and they are: (1) that the
land uses are homogeneously distributed above the fall line; and (2) that
baseflow loadings (groundwater contributions) of nutrients may be considered a
constant background load, and the nonpoint load is measured as surface runoff
(Smullen, Hartigan, and Grizzard 1977)
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and interflowl nutrient loadings. The homogeniety of land use assumption is
considered reasonable because most of the urban population resides on the
coastal plain (below the fall line) and, with the exception of the mountainous
areas, the agricultural and forest lands in the basin are fairly evenly
distributed. This assumption is necessary because the closer a source is to
the Bay, the more effect its loading will have on the water quality of the
system. Thus, it is important that no large mass of a particular land use
type above the fall line be closer than any other type or there would be a
skew of the loadings at the fall line reflecting that skew in the land use
distribution. The second assumption is necessary because we do not
intuitively understand the functional relationship between land use and the
quality of groundwater discharge on basins the size of the Potomac, James, and
Susquehanna.2 We do know isolated facts — such as, the more fertilizer
applied, the greater the opportunity for increasing groundwater nitrate levels
and the resulting baseflow nitrate loadings in the stream. For the purpose of
this analysis, it is enough to accept that for land uses that do not involve a
lot of impervious cover, the baseflow loadings will move reasonably well with
the runoff loadings. That is to say, that land uses exhibiting higher
nutrient runoff loadings will produce groundwater discharge loadings equal to
or greater than those from uses exhibiting lower runoff nutrient loadings.
The land uses above the fall line of the Chesapeake basin are about:
60-65 percent forested, 15-20 percent cropland, 8-12 percent pasture, 3-5
percent urban/suburban, and 2-14 percent other. These are rough estimates
made from existing land use maps and will adequately serve the purpose of this
"order-of-magnitude" analysis. Land use/nutrient loading rate relationships
developed locally within the Chesapeake basin (Smullen, Hartigan, and Grizzard
1978, Smullen 1979, NVPDC 1979) used for this analysis are shown below:
Land Use
Percent in Basin
Estimated
Loading Rate (Ibs./ac./yr.)
Cropland
Pasture
Forest
Urban/ Suburban
15-20
8-12
60-65
3-5
TN
8-18
2-6
.5-2
4-10
TP
1.5-5
.3-. 5
.05-.!
1-2
^Interflow is the lateral movement of water through soils to streams at
shallow soil depths during and directly after storm events. It is of short
duration and, for our purposes, can be considered to be part of the runoff
hydrograph.
^This is a good example of why assessments such as this are best made with
mathematic models. They facilitate the orderly sorting out of base flow,
runoff, and interflow and allow the analyst to handle groundwater
contributions by inspection of observed flow data.
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The unit area loading rates shown above were weighted by
the fractions of the land areas in each use and the following ranges of
loading fractions were obtained;1
Land Use
Cropland
Pasture
Forest
Urban
Percent of Nonpoint Source Load
TN TP
45-70
4-13
9-30
2-12
60-85
3-8
4-8
4-12
In summary, agricultural cropland appears to produce the largest
fraction of the nonpoint source load from above the fall lines by at least
a factor of two for both nitrogen and phosphorous. This is partly due to a
high unit area loading rate for cropland and mostly due to the large
percentage of the land area in this use. Forest loadings of nitrogen are
the next highest percentage and this is entirely due to the large fraction
of the watershed still being in forest land. Urban/suburban and pasture
lands above the fall line produce approximately equal loads.
By inspection, the percentages shown above would change very little if
the Coastal Plain areas were included. Although the three major
metropolitan areas (Washington, B.C., Richmond, Virginia, and Baltimore,
Maryland) would increase the total amount of urban land area, this increase
would probably be offset by the large rural land areas of the eastern and
western shore portion of the Coastal Plain. At any rate, even if the
proportion of urban area doubled, cropland would still be the largest
nonpoint source nutrient load by an approximate factor of three.
3.6. What are the nutrient loadings from the fall line?
The nutrient loadings from the fall line are shown in Tables III.10 and
again in Tables VIII.2 through VIII.5 in Chapter 3 of Part II in this
report. The values for total nitrogen and total phosphorus are shown again
below in millions of pounds.
Annual
Winter
Spring
Summer
Fall
The
TN
TP
percentage of
178.1
10.3
the annual
51.4
2.97
above fall
72.2
4.29
line load
25.1
1.42
produced in
27.9
0.47
each season are
shown below:
best and worst case assumptions were used along with some common sense
judgment. For example, the lower range of cropland loading was produced by
assuming the lowest loading rate/percent land use combination for cropland
and the middle value of the ranges for all other uses.
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Winter Spring Summer Fall
TN 28.9 40.5 14.1 15.7
TP 28.8 41.7 13.8 4.6
From the data presented, it can be seen that the largest fraction of the
fluvial nutrient load (40 percent of both nitrogen and phosphorus) is
discharged to the tidal system during the spring. Observation of the data in
Table III.10 shows that a large fraction of these spring loads are in forms of
nutrients that are readily available for aquatic plant uptakel, with 68
percent of the nitrogen as ammonia or nitrite-nitrate and 34 percent of the
phosphorus as orthophosphorous. This is important since the spring is the
critical start-up period for the phytoplankton growing season, the aquatic
plant growth that will dominate, in part, the dissolved oxygen and chlorophyll
conditions in the Bay through the summer and into the early fall. As noted
elsewhere in this chapter, the predominant upstream source of the riverine
transported spring nutrient load is probably runoff and groundwater discharge
from agricultural lands. The next most important source of nitrogen (but
probably lower by almost an order of magnitude) in spring river discharge from
above the fall line is probably runoff and groundwater discharge from the
melting of the snow-pack in the physiographic provinces upstream of the
Piedmont (see Figure III.2).
The summer is the period during which the plankton growth in the Bay
reaches the annual maximum (see Chapter 2 of this part). The fluvial
transported nutrients play a lesser role during this period providing only
about 39 percent of the readily available nitrogen forms of plant nutrients
and only about 5 percent of the readily available phosphorus. Plankton
communities flourish during this period primarily by recycling nutrients
already in the water column (put there in part by the spring fluvial process)
as noted in Chapter VII (Table VII.5); and secondarily by the supply of
nitrogen from atmospheric, point and bottom sources and by the supply of
phosphorus from point and bottom sources.
3.7. What do the bottom sediments contribute to nutrient inputs?
On an annual basis, bottom sediments contribute 32 million pounds of
nitrogen and seven million pounds of phosphorus [Table VIII.l(a)]. This makes
up about 10 and 25 percent of the annual nitrogen and phosphorous budgets,
respectively [Table VIII.Kb)]. However, the nitrogen contributed from the
bottom source is predominately ammonia and makes up about 45 percent of the
total annual Bay-wide contribution of this nitrogen species, which is most
preferred by aquatic plants. More than 50 percent of the externally supplied
water column ammonia produced during the spring and summer comes from the
benthos.
The sediments have their most dramatic effect on the nutrient input budget
as a source of phosphorous in the summer. As discussed in Section V, most of
phosphorous migrating up through the sediments via the pore waters probably is
fixed chemically by iron in the overlying oxygen-rich waters and held in a
fluff layer as a small particle, or floe. This process occurs during most of
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the year (late fall, winter, spring). However, when the oxygen in the lower
layers of the Bay waters is depleted for periods during the summer, most of
the phosphorus incorporated or stored during the rest of the year probably is
released over a very short period of time. The result is that as much as 62
percent of the phosphorous input to the Bay in the summer could come from this
source. Other than recycling, the bottom source is probably the single
largest factor in the supply of phosphorous for summer primary productivity.
3.8. What are the flux rates of nutrients from the bottom sediments and
how do they vary seasonally?
The bottom flux rates for nitrogen range from as low as 0.5 pounds of N
per square foot per day in portions of the upper Bay in the spring to as high
as 5 pounds of N per square foot per day in portions of the upper Bay in the
spring and summer. The annual seasonal Bay-wide average flux rates for
nitrogen are shown below:
Nitrogen Benthic Flux of Nitrogen
(Thousands of Pounds Percent of
per day) Annual Average
Winter
Spring
Summer
Fall
Annual Average
88.1
75.3
98.4
91.2
88.3
100
85
111
103
As can be seen above, the summer period exhibits the highest flux rate of
nitrogen from the sediments, and the spring the lowest. The nitrogen is
moving out of the sediments fastest when the standing crop of phytoplankton is
largest, and being produced in a form readily available for plant uptake.
As discussed previously, the seasonal variation of phosphorous flux from
the sediment to the water column is severe, with about 85 percent of the total
annual input being released rapidly sometime from late May to mid-June, with
most of the other 15 percent released from that time through late summer.
The maximum Bay-wide phosphorous release rate might be as high as one-half
million pounds a day during the period of the rapid onset of bottom-water
anoxia. This rate probably levels off to about 16,000 pounds per day by late
summer and down to near zero by sometime in late fall.
3.9. Given the estimated loadings of nutrients for each of the sources,
which will be the most important in terms of their effects on the Bay
system?
This is a difficult question to answer, because there are so many
potential effects on the Bay system that could result from variations in
nutrient loadings. Some effects are understood well; some not so well, and
some are unknown. However, to provide an answer to this question, we will
consider the potential effects on Bay-wide primary production which might
result from variations in the amounts of nutrients entering from various
sources.
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On an annual basis (Table VII.2), probably only about 20 to 30 percent of
primary production in the Bay proper is supported by nitrogen and phosphorous
entering the water column from external sources. We will assume that nutrient
recycling rates by phytoplankton would vary only moderately in response to
changes in external nutrient supply. Given this assumption, it can be seen
from the data in Table VII.2 that even as much as a 50 percent reduction in
both point and nonpoint source annual nutrient loadings may result in only a
10 percent reduction in Bay-wide primary production. Seasonally, this effect
could decrease to a 5 percent reduction in summer production in response to a
50 percent reduction of summer point/nonpoint nutrient loading. If these
loading reductions were sustained, production would probably decrease futher
as the nutrient reservoir in the sediments depleted over time. These
estimated decreases of primary production in the short-term approach the
detection limit of our ability to assess such reductions.
The important point in this discussion is that changes in lower Bay water
quality (essentially meaning the great majority of the Bay that lies below the
mouth of the Patuxent) in response to changes in nutrient inputs would
probably take place slowly over decades. However, the upper portions of the
Bay and the tidal tributaries would be much more responsive to change in
nutrient loads than the main Bay. The nutrient loads that the main liay
receives must travel through these smaller, heavily impacted areas oE the
system.
The nutrient inputs are diluted as they move towards the lower Bay as a
function of ever increasing volume. In addition, the surface area available
for contributing nutrients from the sediments is much greater in the main Bay
than in the upper portions of the system, resulting in much larger bottom
releases of nutrients. These factors and others create a situation in the
main Bay that tends to buffer or dampen water quality response to changes in
anthropogenic nutrient loadings. It is, therefore, reasonable to expect the
water quality of the upper areas (tidal fresh areas) of the system to respond
more quickly to load reductions than the areas of the lower main Bay.,
The apparent improvement in the water quality of the upper Potomac in
response to decreased nutrient loadings over the last decade would seem to
support this concept. Even though some unknown amount of that improvement
probably results from differing climatic conditions over the last ten years,
some degree of the improvement is most likely due to the decreases in the
external nutrient supply from POTW's. We would not expect to see immediate
changes in lower Bay water quality due to that reduction of loading and, in
fact, have not. Such a change could only be seen over a much longer period of
time and to a lesser (diluted) extent. This situation would seem to support
the concept that if we manage the local ("near field") problems, the main Bay
("far field") will, in time, respond in kind. An aggressive policy of water
quality improvement in currently adversely impacted areas should insure the
maintenance of a nondegradation condition in the main Bay.
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MANAGEMENT QUESTIONS AND ANSWERS - TOXIC SUBSTANCES
1. Is there a toxic chemical problem in the Chesapeake Bay?
There are trends of general concern and specific problem areas.
There is concern that grass, shad, and bass have declined in the last
three decades and that oyster reproduction has diminished. In the James
River, chlorine is strongly suspected of causing massive fish kills and Kepone
has resulted in closure of the estuary to fishing for years. At the same
time, there is an increase in the number of potentially toxic chemicals
synthesized, produced, and used in the region. Analysis of a sediment core
from the northern Bay, for example, reveals an upward increase in metal
content of Cu and Zn with time. Enrichment factors range from 3 to 20.
Although it is recognized that toxicants accumulate in certain biota many
thousandfold more than ambient concentrations, the link between cause and
effect still eludes scientists. Toxic chemicals, however, are strongly
suspected of being partly responsible for the decline of essential biotic
components. The fact that many compounds are carcinogenic to mammals is cause
for concern.
Major problem areas are Baltimore Harbor - Patapsco River - and Norfolk
Harbor - Elizabeth River - which are sources of industrial/municipal discharge
and shipping activity. Because of their limited circulation, these areas are
natural "sinks" for toxics adsorbed on fine sediment. Concentrations of
metals, for example, are 2 to 50 times greater than in mid-Chesapeake Bay.
Zones of metals enrichment in Baltimore Harbor are associated with disrupted
bottom communities. Bioassays of fish, invertebrates and bacteria indicate
effluents have moderate to high toxicity. The greatest number of organic
compounds detected per oyster and the highest concentrations were recorded off
the James River and Baltimore Harbor.
1.1 What toxic chemicals are present and what is the concentration of
them in the estuary?
Two classes of chemicals pose a threat to the Bay; 1) inorganic compounds,
mainly trace metals like As, Cd, Cr, Cu, Hg, Sn and Zn; 2) organic compounds
including pesticides, phthalate esters, polynuclear aromatic hydrocarbons
(PAHs), polychlorinated hiphenyls (PCBs) and many other chlorinated
hydrocarbon compounds. Many of these chemicals are produced naturally or
synthetically. Approximately 300 organic compounds were found in the Bay's
sediment, the majority of these compounds were PAHs.
The trace metals are found in several phases; 1) dissolved, and 2) solids,
either sorbed to suspended sediment or bed sediment. Although concentrations
may reach high values in biota, the bed sediments contain the greater mass and
thus constitute the main toxic reservoir. Because sediments have a longer
residence time in the Bay than water, bottom filter feeders like oysters are
more exposed to contaminated sediment than water.
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SUMMARY OF MEAN METAL CONCENTRATIONS IN BOTTOM SEDIMENT,
SUSPENDED MATTER, AND DISSOLVED PHASES IN THE BAY
Metal
As
Cd
Co
Cr
Cu
Fe
Hg
Mn
Mo
Ni
Pb
Sc
Sn
Th
U
Zn
Bottom 1
Sediment
ug/g
3.9
0.4
12.8
28.9
21.6
24,250.0
0.1
848.0
26.1
29.4
0.7
157.0
Suspended 2
Sediment
ug/g
13.0
14.16
—
127.96
3.11%
3.89
2.88
95.80
160.30
17.97
0.75
Dissolved-^
Water Column
ug/1
0.05
0.07
0.17
0.66
3.12
13.88
3.26
1.21
0.11
0.86
0.93
1.19
1 - Means from combined Nichols and Helz (1981) data.
2 - From Nichols (1981)
3 - From Kingston (1981)
Summary of mean concentrations of various PAH organic compounds in Bay
sediments listed on EPA's priority pollutant list.
Compound Mean Concentration (ppm)
Phenanthrene 575
Pyrene 758
Floranthene 962
Benz (a) anthracene 310
Chrysene 448
Benzo (a) pyrene 440
Benzo (ghi) perylene 271
1.2 What are toxic chemicals associated with?
Most toxic materials tend to partition with sediment. Organic
compounds and metals tend to partition to suspended material and then are
deposited on the bottom as the suspended sediment is deposited. Because of
polarity, some organics may be dissolved in the water column and exist
below the detection limit of present day instrumentation.
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1.3 Do toxic substances entering the system accumulate?
Most toxic chemicals of all classes entering the system accumulate in
the sediment; others degrade, and some accumulate in the biota or are
flushed out of the system. The degradation process occurs under changing
physical/chemical conditions. Suspended sediment is particularly important
in the accumulation of toxic materials, because metals are adsorbed, found
and precipitated on suspended material. In this form they can be picked up
by filter-feeding organisms or metabolized by plankton and reach high
concentrations.
Fluid mud, dense suspensions of sediment, lies in fluid masses near the
bottom of the Bay. It serves both as a reservoir for potentially toxic
metals and as a medium for chemical transfer between the mud and overlying
water.
Analysis of selected sediment cores demonstrate that Cu, Zn, Pb and Co
increase dramatically near the sediment-water interface indicating that
sediments are an important reservoir of metals and that the origin of these
metals is man's activity.
1.4 Is the Bay regionally contaminated with trace metals?
Metal content of bed sediments from the main northern Bay is enriched 4
to 6 times in Mn, Pb and Zn compared to average shale. Sediment cores show
an upward increase of more than two times. The distribution of enrichment
factors in the main Bay is controlled by sediment type and deposition
processes rather than nearness to sources of contamination.
Enrichment of suspended material in near-surface water of the central
Bay in Cd, Cu, Ni, Pb, and Zn is related to high organic content.
Enrichment exceeds natural concentrations of metals in oceanic plankton 9
to 19 times.
1.5 Is the Bay regionally contaminated with organic compounds?
Although concentrations are variable, some areas of the Bay have
extremely high concentrations of toxic organic compounds. Approximate
maximum concentrations of various organic compounds measured in Bay
sediments are:
Compound Max. Concentration (ppm)
Phenanthrene 100
Pyrene 150
Floranthene 200
Benz (a) anthracene 70
Chrysene 90
Benzo (a) pyrene 90
Benzo (ghi) perylene 70
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With the magnitude of these concentrations, regional contamination is
very obvious and at alarming levels in some areas.
1.6 Do levels of toxic chemicals found in the environment present a
risk to the ecosystem?
Certain compounds including PAH's, PCB's, phthalate esters, DDT, As,
Cd, Cr, Pb, Hg, Zn, may represent a risk to the ecosystem. However, to
evaluate the risk associated with these chemicals is a complex problem.
Each specific compound has a different effect on various species.
Likewise, each species has a different reaction to specific compounds!. To
make the problem more complex, the synergistic effects and the stress which
toxic material places on organisms are nearly impossible to quantify. For
the most part, the observed dissolved metals concentrations do not exceed
risk levels. For organic compounds, we have very little information on
concentrations in the water column from which to make an evaluation.
Bioassays performed on specific sediment samples can indicate relative
toxicity of the sediment. These tests indicate that the sediments in the
Bay and several tributaries are generally more toxic than a west coast
estuary. Also, an assessment of biological indices of the bottom biota in
the Baltimore Harbor indicate that there are stressed and impacted
conditions existing there.
2.0 What is the distribution of toxic chemicals in the Bay?
In suspended material, metal content per gram of As, Cd, Cu, Pb, Hg,
Ni, Sn and Zn are maximal in near-surface water of the central Bay. These
concentrations most likely are bioaccumulated by plankton. On the other
hand, per liter of water, metal concentrations are highest in the northern
Bay where suspended sediment concentrations are high - a zone called the
turbidity maximum.
In bed sediment, metal content of Cr, Mn, Fe, Co, and Ni is highest in
fine sediment of the northern Bay. Concentrations of most metals are
maximal in the zone from the Susquehanna mouth to the Patapsco mouth where
fine sediment is entrapped. Concentrations of Cr, Pb, and Zn are maximal
in Baltimore Harbor and concentrations are not elevated in the main Bay off
Baltimore. Concentrations of metals are relatively low throughout the
southern Bay. Organic compounds are highest in fine, bed sediment from the
Bay between the Susquehanna River and the Patapsco River. They generally
decrease further seaward to the Potomac River; but in the southern Bay,
locally high concentrations are found in sediment from estuary entrances.
The distribution of both metal and organic compounds is associated with
the distribution of fine sediment and moderate to fast sedimentation.
2.1 What parts of the Bay are most susceptible to contamination?
The greatest enrichment may be expected in zones where: 1) the source
supply is high and entrapment is good; 2) fine sediment accumulates; and 3)
where rates of sedimentation are moderate to fast. Contamination of near
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source areas is common to tributaries near treatment plants and industrial
facilities. Contamination that follows the fine sediment and fast rates of
sedimentation is common to the main Bay, the zone of deep water in the
central Bay. Sediment water content and fluid mud thicknesses are greatest
in this region. This zone holds atmospheric contaminates as well as
water-borne contaminates settled from overlying water or dispersed a great
distance from their source.
Identifying locations of accumulation shows the distribution of fine
grain sediments to which toxic chemical attach. Locations in the Bay
accumulate sediments at variable rates from negative values because of
erosion, to several m/century. In the upper Bay, fine grain sediment
accumulates N to S generally down the Bay, especially between Baltimore and
mouth of the Chester River. These accumulations are small, amounting to .5
to 3 m/century.
In the lower Bay, accumulation is again N to S in three main regions.
The average rate is 0.5 m/century. The first region is in the deep channel
down the stem of the Bay and where the channel flairs, just above the
Rappahannock River. As much as 1.5 to 2 m/century accumulates at this
location and sediment here is mostly silt/clay. The second region is just
north of the York River; locally rates are as great as 2.5 m/century on the
eastern flank of the Cape Charles deep opposite Old Plantation Flats.
Sediment here is very fine sand. That same latitude, 37°20: shows
similar accumulation on the western side of the channel.
2.2 What role do the biota play in the transport of toxic substances
from the sediment to the water column?
Generally, benthic animals living in or on bottom sediments can
reintroduce chemicals from the sediments to the water column. In addition,
fish migrating to other parts of the Bay or Atlantic Ocean can transport
chemicals with them. The main activities of benthic animals that can
transport chemicals are:
o mixing - causing newly arrived surface material to be quickly
buried or resurfacing older material.
o ventilation - increasing the exchange between interstitial water
and the water column.
o increasing sediment stability - decreasing the probability that
buried material will be resurfaced.
o decreasing sediment stability - increasing the probability that
buried material will be resurfaced.
o causing rapid sedimentation - through pellitization of fine
suspended particles.
o causing erosion - by making sediment more easily transported.
o bioaccumulation
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2.3 What other processes (physical or chemical) exist which can cause
remobilization of toxic chemicals into the water column?
Materials in the bottom sediment may be reintroduced to the surface
environment and water column by two groups of processes.
Physical disturbance of the sediment can reintroduce toxic substances
by storms, biologic activity (bioturbation), dredging and other engineering
projects, propeller wash, harvesting of bottom organisms by dredging (e.g.,
clams, oysters).
Important chemical processes leading to remobilization might include
diffusion driven by concentration differences, and life processes of
benthic organisms such as irrigation of burrows and benthic feeding.
Physical disturbances are episodic occurrences whereas diffusion is a
continuously operating process. Exhumation and resuspension of sediment by
physical processes can re-expose material that had previously been buried
and out of direct contact with the surface environment. Interstitial
water, the water trapped in the voids between sediment particles as the
sediment accumulates in the subaqueuous environment, is the vehicle through
which chemical constituents in the sediment are continuously remobilized
and transported within the sediment and across the sediment-water interface.
3. What are the sources and loadings of the pollutants of concern?
3.1 What is the direct contribution of toxic material from point
sources?
Metric tons per year
Cr Cd Pb Cu Zn
Municipal Wastewater 200 6 68 99 284
Industrial Discharge 199 178 155 190 167
3.2 What is the direct contribution from nonpoint sources?
Metric tons per year
Cr Cd Pb Cu Zn
Shore Erosion 83 1 28 29 96
Atmosphere 189 99 582 95 ?
3.3 What are the loadings from the major tributaries?
Metric tons per year
Cr Cd Pb Cu Zn
Urban Runoff 1
Rivers 100 4 180 220 1500
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3.5 Are there other sources of toxic substances?
The massive reservoir of materials contained in the bottom sediments of
estuaries have largely been ignored as a potential source of nutrients and
trace elements until recent years. On the basis of interstitial water
chemistry investigations, it is apparent that there is a very substantial
contribution of these substances from the sediment to the water column. By
far, the largest source of Pb is the atmosphere, and the largest source of
Cd is industrial effluents.
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MANAGEMENT QUESTIONS AND ANSWERS - SUBMERGED AQUATIC VEGETATION
1. Is there a problem in Chesapeake Bay related to SAV?
Yes, because SAV is declining, and because it has an important
ecological role and economic value.
1.1. Are the current distribution and abundance of SAV unusually low ?
Yes, probably lower than every recorded in the Bay's history.
1.1.1. What is the current distribution and abundance of SAV in
Chesapeake Bay?
About 16,000 hectares, or 5 percent of the portion of the Bay less than
two meters deep is vegetated by SAV. (Sediment type and exposure to winds
and currents make much of this shallow area unsuitable for SAV.) Most SAV
is concentrated in four regions of the Bay: (1) the middle stretch of
Maryland's Eastern Shore, including the Chester River, Eastern Bay, and the
Choptank River, (2) the shoals between Smith and Tangier Islands, (3)
behind sand bars along Virginia's Eastern Shore, (4) around the mouth of
the York River from Mobjack Bay to Back River.
1.1.2. Have the distribution and abundance of SAV recently
declined?
Yes, dramatic declines have occurred since the 1960's. In limited
sampling between 1967 and 1969 along Maryland's Eastern shore from near the
head of the Bay to Pocomoke Sound, most areas had 70 to 100 percent of
their sampling stations vegetated by SAV. Only one area had less than a
third of its stations vegetated. An annual summer survey by the U.S. Fish
and Wildlife Service and Maryland's Department of Natural Resources shows
that only 28.5 percent of their sampling stations in Maryland was vegetated
in 1971, and only 10.5 percent was vegetated in 1973. Smaller fluctuations
have occurred since 1973, and the percentage of vegetated stations now
stands at an all-time low of eight. Archival aerial photography of six
locations in the lower Bay reveals that five of them experienced declines
since 1960s ranging from 45 to more than 99 percent.
1.1.3. Have all areas and species experienced declines at the
same time and to the same degree? Have the declines
been gradual, or sudden events occurring between periods
of relative stability?
All areas and species have been aftected, but not to the same degree,
nor at precisely the same time. The areas mentioned in 1.1 as currently
having most of the SAV have been the least affected. The head of the Bay,
Maryland's lower Eastern Shore from Taylors Island to Pocomoke Sound, and
the major Western Shore Rivers have been the most affected. Overall,
during the last 15 years, declines have been a combination of sudden drops
superimposed on an uneven but continuing downward trend. The Potomac and
Patuxent Rivers experienced large declines between 1965 and 1970. In 1907,
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the Potomac had dense beds of SAV along both shores, but by 1970, only
scattered pockets of vegetation remained. Large declines along Maryland's
Eastern Shore occurred between 1969 and 1971. Further big declines
occurred in the upper Bay in 1972, the year of tropical storm Agnes. In
the Susquehanna Flats during the early 1960's, European milfoil displaced
native species to a great extent. When milfoil declined in the mid-1960's,
the native species recovered about two-thirds of their former abundance
before decreasing slightly in the late 1960's. In 1972, there was a
dramatic decrease in SAV abundance. Virginia's Eastern Shore had major
declines between 1972 and 1974.
1.1.4. Have deeper areas been affected more than shallower
areas, thus implicating turbidity as a cause of decline?
There is not enough evidence to say conclusively that deeper areas have
been affected more than shallower areas, but limited evidence from archival
photography suggests that this may be the case, at least in some areas.
1.1.5. Does the biostratigraphic record indicate that a decline
as severe as the one of the last decade ever occurred
before, or that cyclic changes have occurred?
No, limited evidence from the Susquehanna Flats reveals a continuous
seed record until the top of the core. The seedless layer at the top
corresponds to the time since tropical storm Agnes. There is no evidence
of cycles in SAV abundance.
1.1.6. Has the recent decline of SAV in Chesapeake Bay been
paralleled by declines in estuarine and marine
ecosystems in other parts of the world, especially along
the Atlantic coast of North America?
Declines that have occurred around the world have been near population
centers. Localized declines, especially in Florida, have occurred along
the Atlantic coast of North America, but generally the extensive declines
in Chesapeake Bay stand in marked contrast to trends along the rest of the
Atlantic coast.
1.2. Does SAV have a significant ecological role and economic
value?
Yes.
1.2.1. Is SAV a direct or indirect source of food for
animals, including economically important species?
Before 1960, SAV constituted more than half the food of at least six
species of waterfowl (canvasbacks, ring-necked ducks, redheads, American
wigeon, gadwalls, and whistling swans). Canvasbacks were an especially
important species, attracting many hunters to Chesapeake Bay. With the
decline in SAV, whistling swans and canvasbacks have switched to other
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foods, while redheads and wigeon have found other wintering areas. SAV
also contributes to the detritus-based food web.
1.2.2. Does SAV provide habitat, especially for economically
important species?
SAV beds currently support two to five times more finfish and
invertebrates than nearby bare areas. SAV beds in Virginia are important
nurseries for blue crabs. In Chesapeake Bay, in contrast to other regions,
there is insufficient evidence to support tne idea that SAV beds are
nurseries for commercially important finfish; however, there is good
evidence that numerous fish of ecological, but not economic importance
occur in SAV beds.
1.2.3. Does SAV play an important role in nutrient dynamics?
SAV may act as a nutrient buffer, potentially taking up large
quantities of nutrients during the spring growth period. In comparison to
algae, SAV releases nutrients more slowly, and exerts a lower oxygen demand
during decomposition after autumn die-back. CBP research has demonstrated
the ability of SAV to rapidly take up nutrients from the water column, as
well as from sediments.
1.2.4. Does SAV play an important role in sediment dynamics?
SAV roots and rhizomes can stabilize sediments, and SAV shoots can slow
water currents and dissipate waves, thus allowing suspended material to
settle to the bottom. CBP research at sites in Eastern Bay and the
Choptank River has documented that suspended sediments are removed from
water moving into SAV beds.
2. If there is a problem regarding SAV, what caused it?
Different combinations of factors were probably important in different
localities.
2.1. Have herbicides been a factor in the decline of SAV?
They have probably not been the major Bay-wide factor. Extensive
research on atrazine and linuron indicate that these pesticides may have
been a contributing cause of decline of SAV already stressed by other
factors, but this would be true only for SAV beds near sites of herbicide
application, and in years when precipitation occurred soon after
application.
2.1.1. What effects do herbicides have on SAV, and at what
concentrations are these effects produced?
Atrazine and linuron concentrations of 50-100 ppb consistently cause
significant reductions in photosynthesis in several species of SAV. Five
to 10 ppb sometimes produce harmful effects. One ppm can kill SAV.
Sublethal effects can last several days after exposure times of one to a
few hours. Generally, full recovery occurs after exposures of less than
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100-500 ppb. Experiments have not been done on toxicity of degradation
products to SAV, but for agricultural weeds, degradation products of
atrazine are far less toxic than the parent compound.
2.1.2. How do herbicides enter SAV?
They are taken up from the water column through the leaves. Root
uptake can also occur, but is probably much less important because
herbicide availability in the sediment is low.
2.1.3. To what amounts of herbicides is SAV exposed, and for
how long?
Observed high concentrations of atrazine were 4 ppb in the mainstem of
the Bay, 7 ppb in the primary tributaries, 20 ppb in secondary bays and
coves, and 100 ppb in drainage creeks adjacent to agricultural fields.
Exposure concentrations declined from these highs to about 20 ppb in a few
hours in drainage creeks, to about 7 ppb in a few days in secondary bays
and coves, to about 4 ppb in a few weeks in the primary tributaries, and to
near zero ppb in a few weeks in the mainstem of the Bay.
2.1.4. What physical and chemical processes are involved in the
transfer of herbicides from agricultural fields to SAV?
What degradation rates and sorption constants do
herbicides have?
Atrazine applied to agricultural fields can adsorb to sediment
particles and colloidal material, or dissolve in water. Sorption
coefficients for colloids are about 10 times higher than those for
sediments, and sorption to sediments is about 10 times greater than
solubility in water. However, over 90 percent of the atrazine in estuaries
is in the unfilterable component of the water column. Herbicides are
transported to the estuary mainly by runoff, although transport by
subsurface drainage is also possible. Half lives of atrazine due to
degradation are a few days to a few weeks in estuarine water, a month or
more in estuarine sediments, and up to a year in agricultural soils.
2.2. Has the decline of SAV been caused by inadequate light reaching
SAV leaves?
Inadequate light may be the most important proximate cause of SAV
decline.
2.2.1. How does SAV respond to different amounts of
photosynthetically active radiation (PAR)?
As the amount of PAR increases, net photosynthesis increases to a
maximum. At this point net photosynthesis is light saturated. Above this
point, SAV may become inhibited by too much lihgt. Below the saturation
point, there is a compensation point at which gross photosynthesis equals
respiration, and net photosynthesis is zero. Community compensation points
are on the order of 200-300 microeinsteins per square meter per second.
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These rates can vary considerably depending on periphyton density and other
factors. Compensation points for individual species are on the order of 30
to 50 microeinsteins per square meter per second. Maximum rates of net
daytime photosynthesis are on the order of 1.1 to 1.3 mg C g~J-hr~l.
Upper Bay species are generally not light saturated (i.e., they are light
limited), and that their photosynthetic efficiency does not change
seasonally. In the lower Bay, Zostera marina is light limited during both
its spring and fall growing seasons, and appears to undergo acclimitization.
2.2.2. How do light and herbicides act together to affect SAV
photosynthesis?
Although other research indicates that herbicides have a diminished
relative effect at lower light levels, GBP research does not convincingly
support such a conclusion.
2.2.3. What is the quantity and spectral distribution of light
at different depths in SAV beds, bare areas, and areas
that recently have lost their vegetation, and how do
they vary seasonally?
Light penetration is greatest in the green and least in the blue region
of the spectrum. Studies in a limited region of the lower Bay indicated no
significant difference between spectral distributions in bare and vegetated
areas. The attenuation coeffiecient for PAR ranged from 0.5 m~l to 1.6
m~l, and increased significantly from April to July at most sites. No
clear pattern of difference occurred between vegetated and nearby bare
areas in the lower Bay. In the upper Bay, attenuation was usually less in
SAV beds than in bare areas.
2.2.4. What are the sources of turbidity, and what is their
relative importance?
Suspended sediments and phytoplankton are the major contributors to
turbidity. Their relative importance varies seasonally and between
localities.
2.3. Has the decline in SAV been caused by changes in nutrient levels
in the Bay?
Nutrient enrichment, through its stimulation of phytoplankton and
periphyton, is a factor controlling SAV, and may have contributed to its
decline.
2.3.1. To what levels of nitrogen is SAV exposed, and how do
they vary seasonally?
Nitrate concentrations in the water column range from near zero to 100
micromolar. Nitrite concentrations range from near zero to 2 micromolar.
Ammonium concentrations range from near zero to 20 micromolar. Nitrate
concentrations are highest in spring and decline to a low in summer. In
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the upper Bay, interstitial concentrations of ammonium ion in the rooting
zone (down to 15 to 20 cm) are about 80 micromolar.
2.3.2. How do nitrogen levels indirectly affect SAV?
Nutrient enrichment can stimulate the growth of phytoplankton, which
can contribute to attenuation of light in the water column. Phytoplankton
can also stimulate the growth of filter feeding animals that live attached
to SAV leaves. These filter feeders can form a crust that blocks light and
depresses photosynthesis. Nutrient enrichment can also stimulate epiphytic
algae, which can block light. Epiphytic algae may also be controlled by
animals that graze on the surface of SAV leaves. One such grazer that is
found in Virginia, the snail Diastoma, has been shown under experimental
conditions to dramatically decrease the density of periphyton on Zostera.
The western shore population of Diastoma may have been virtually eliminated
by the low salinities resulting from flooding at the time of tropical storm
Agnes in 1972. The loss of Diastoma may be an important cause of SAV
decline in certain localities along Virginia's western shore.
2.4. In summary, what are the most likely principal causes of SAV
decline during the last 20 years?
SAV can be stressed by many factors whose relative importance can vary
spatially, seasonally, and yearly. Some of these stresses include light
attenuation in the water column caused by suspended sediment and
phytoplankton, light attenuation by periphyton, herbicides, unusually high
salinities, physical damage by storms, eating by whistling swans, uprooting
by cownose rays, and biotic interactions that are not fully understood.
Underlying factors may control one or more of these stresses. For
instance, nutrient enrichment can stimulate both phytoplankton and
periphyton. These multiple stresses, and the complex time-space patterns
they can exhibit, must be considered against the background of the history
of SAV distribution and abundance in the Bay. Historically, Chesapeake Bay
probably had much more SAV than now. In 1907, extensive beds of SAV
occurred along the length of the Potomac River estuary. It is reasonable
to expect that the same was true of other parts of the Bay. Precipitous
declines have occurred throughout most of the Bay since 1969, but not all
species or areas have been equally affected. Disease cannot, by itself,
explain the declines because it probably would not affect all species
equally. The pattern of decline does not support the idea that point
sources of pollution are the single cause of decline. The biostratigraphic
record does not support the concept of entrained cycles in SAV populations,
and tropical storm Agnes, although probably an important factor, is not the
single cause of decline, again because the pattern of decline is not
consistent with such an hypothesis. Interestingly, there is a positive
correlation between SAV decline and potential diffuse loading (the ratio of
the drainage area of a river to the river's volume). These facts suggest
that a Bay-wide decline can be demonstrated. In particular, herbicides,
although potential stresses, are not the sole cause of decline. Nutrient
enrichment, and its effects of light attenuation, may be the most important
contributing causes.
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2.5. What are the minimum requirements for SAV growth?
Because factors may interact in a complex way, the minimum requirement
for one factor depends on current levels of other factors. The following
levels represent very rough approximations that cannot be well
substantiated by current information. Light: above 200-300 uE m~^s-l
measured in the water column of SAV beds. Herbicides: below 5 ppb
measured in water column.
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I PART II
NUTRIENT ENRICHMENT
•Christopher F. D'Elia
Jay Taft
James T. Smullen
• Joseph Macknis
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• Technical Coordinator
Willa Nehlsen
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TNTRODUCTION
The nutrients portion of this synthesis report presents the integrated
findings of the Nutrients Program of the Chesapeake Bay Program (CBP) .
More than 10 individual research projects (listed in Appendix A), funded
under the CBP, contributed to the three chapters of this part. Additional
literature, other data bases, and many individuals also contributed
valuable information for completing the synthesis of our knowledge of
nutrient enrichment in Chesapeake Bay.
The CBP studied nutrients, because the natural process of nutrient
enrichment, or eutrophication, is being hastened by anthropogenic (or
human-related) contributions of primarily nitrogen and phosphorus
compounds. Though needed by Bay organisms to grow, excesses of these
nutrients can deteriorate the water quality.
Inorganic nitrogen and phosphorus compounds, such as nitrite, nitrate,
ammonia, and phosphate, are referred to as "nutrients" because they are
required by plants for growth. In an estuary like the Chesapeake Bay,
nutrients support the growth of phytoplankton, submerged aquatic
vegetation, and emergent marsh grasses. This plant material, in turn,
supports the rest of the many organisms in the Bay.
When nutrients are introduced into an estuary in excessive amounts
(nutrient enrichment) detrimental effects may result. Growth of
phytoplankton may be stimulated, causing dense and unesthetic blooms. Or,
a few species may dominate, resulting in declines of other types and loss
of species diversity. Although phytoplankton blooms produce photosynthetic
oxygen as they develop, as they die, respiration may exceed
photosynthesis. Oxygen will be depleted from the water as a result. In
addition, grazers and decomposers deplete oxygen by respiration as they
process the phytoplankton. Consequently, oxygen depletion from the water
is a common corollary to nutrient enrichment. The severity of these
effects depends on season, rainfall, circulation, and the availability of
phytoplankton seed stock.
The relationship between nutrient enrichment, phytoplankton growth, and
oxygen depletion is fairly direct and well-documented. Less accepted are
indirect relationships between nutrient enrichment and higher trophic
levels, particularly commercial fisheries. Yet, in Chesapeake Bay,
declines of important fisheries like striped bass, American shad, blue crab
and oyster have been observed; it would be of great interest to know
whether these declines have resulted from anthropogenic nutrient inputs.
Although satisfying conceptual models can be developed in which nutrient
enrichment, algal species composition, and competitive/predative fisheries
interactions are related, data for calibration and verification are
scarce. There appears to be a relationship between nutrient enrichment and
another resource, submerged aquatic grasses. The value of Bay grasses and
the relationship between their decline and nutrient enrichment will be
discussed in Part IV on Submerged Aquatic Vegetation.
The Chesapeake Bay Program has assessed the nutrients problem in the
Bay from three perspectives: analysis of historical trends, assessment of
sources, and understanding of processes. With three separate but related
approaches, the Program can determine the extent and nature of the
nutrients problem and what should be done to alleviate it.
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Analysis of historical trends in nutrient enrichment is presented in
the first chapter of this part. Such an evaluation can help assess whether
a problem exists because it can establish an historical baseline against
which to compare present levels. Ideally, it is desirable to have a
"pristine" baseline, nutrient levels existing before human settlement.
However, it is obviously not possible to obtain such data. One must settle
for the earliest period for which good data exists, and anecdotal data for
earlier periods.
For Chesapeake Bay, the earliest large data base is that developed by
CBI in 1949-51. This provides us a baseline for analysis of trends in the
past 30 years. Within the Chesapeake Bay Program, these trends have been
analyzed by Heinle et al. and will be discussed in the first chapter.
In assessing historical trends for a large system like Chesapeake Bay,
it is important that a regional approach be taken. For example, trends in
the Potomac River are quite different from those of the upper Bay,, It is
also important that nutrient levels be assessed on a seasonal basis,
because nutrient processes are highly dependent on season (discussed more
fully in the Processes section). Finally, fresh-water inflow must: be
accounted for, as this can greatly affect runoff rates and dilution (to be
discussed under Sources).
Besides establishing a baseline, developing historical trends in
nutrient enrichment provides a source of comparison with trends in
resources like fisheries, submerged aquatic vegetation, etc. If declines
in resources can be correlated with increases in nutrients, it is possible
to begin investigating the causal relationships, if such exist, behind the
correlations. Comparisons of historical trends are being investigated in
the Bay Program's Characterization process.
The movements and transformations of nutrients in an estuary, called
nutrient processes, are directly related to their potential negative
effects. Understanding these processes is critical to developing
appropriate nutrient controls. Nutrient processes vary in space and time
(specific examples are discussed in the Processes section), and control
strategies must account for regional and seasonal factors. Major nutrient
processes include phytoplankton nutrient uptake, nutrient cycling, and
circulation and are discussed in the second chapter of this part.
The primary negative effect of nutrient enrichment is overgrowth of
phytoplankton. Whether phytoplankton growth occurs as a result of nutrient
addition, and the extent of this growth, depend on whether the
phytoplankton take up the nutrient and are able to grow. A number of
factors affect phytoplankton uptake and growth. For example, all other
growth requirements of the phytoplankton must be satisfied, such as
temperature and light. In general, addition of a nutrient will stimulate
growth only if that nutrient is limiting. Furthermore, some nutrients are
"preferred" by phytoplankton over others and will be taken up first.
Uptake of nutrients by phytoplankton does not always result in growth.
Under some conditions "luxury uptake" occurs, in which nutrient is taken up
and stored within the cell. As a result, nutrient depletion from the water
column may be observed without concomitant increase in phytoplankton
biomass.
Finally, ambient nutrient levels do not always correlate with high
phytoplankton biomass (as determined by chlorophyll
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water column. For this reason, measurement of ambient nutrient levels may
not provide a good indication of eutrophication.
Nutrient cycling is the general term for the many biological,
geological, and chemical processes by which nutrients change form. In the
Chesapeake Bay, the most important of these are grazing and decomposition,
nitrification and denitrification, and phosphate binding in the sediments.
Grazing of phytoplankton by predators is important because it prevents
accumulation of phytoplankton biomass and may increase productivity of
higher trophic levels. Thus, it can prevent the negative effects of
nutrient enrichment. Because of grazing, high nutrient levels may not lead
to high levels of chlorophyll a.. Whether grazing occurs depends in part on
the availability of grazers and on the palatability of the phytoplankton
(e.g., blue-green algae are generally inedible). Decomposition of dead
phytoplankton, animals and other organic matter by bacteria and fungi
converts nutrients from their organic to inorganic forms, making them again
available for phytoplankton and other plant uptake. It is an important
part of the eutrophication process, because the respiration required
depletes oxygen from the water column.
Nitrification and denitrification are bacterial transformations of
inorganic nitrogen forms. Nitrification is the conversion of ammonia to
nitrite and thence to nitrate. These conversions require the presence of
oxygen; thus, under conditions of oxygen depletion, ammonia and/or nitrite
may accumulate. Denitrification, the conversion of nitrate to nitrite and
thence to nitrogen gas, occurs under anerobic conditions and may be an
important mechanism for ridding the system of excess nitrogen.
The availability of phosphate in the water column depends in part on
processes in the sediments. Under aerobic conditions, phosphate complexes
with iron and manganese and precipitates to the sediments. Under anerobic
conditions, however, phosphate is released from the sediments into the
water column. Clearly, the cycling of nitrogen and phosphorus compounds is
dependent on oxygenation, particularly of bottom waters and sediments. As
a result, nutrient activities will be very different in the winter, when
water is well oxygenated, than in the summer when oxygen depletion of
bottom waters occurs.
Circulation is a critical component of nutrient processes. It
determines the spatial distribution of nutrients, as well as that of the
phytoplankton that would utilize them. It also affects the availability of
oxygen to the bottom waters, through the processes of stratification,
mixing, and turnover. Circulation is discussed in Processes.
In addition to understanding processes, assessing nutrient sources is
critical to developing effective controls. Sources of nutrients to
Chesapeake Bay include municipal sewage effluents and industrial nutrient
effluents (point sources), as well as agricultural, urban and other land
runoff (nonpoint sources), and atmospheric sources (precipitation). The
third chapter of this part addresses these sources.
Assessment of nutrient sources is generally accomplished by a
combination of monitoring and modeling. Point sources are routinely
monitored; modeling is used when projections of future point source loads
are made, or when the number of point source effluents is too great for
frequent routine monitoring, and expected loads must be calcuated.
Nonpoint source nutrient loads are much more difficult to quantify. An
estimate can be made by monitoring nutrient levels in the major tributaries
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entering the Bay (e.g., Susquehanna, Potomac, James Rivers). However, this
gives no indication of nutrient loads from specific land uses within the
watershed. That must be determined by monitoring nutrient levels in small
tributaries draining single land use types, and extrapolating to the entire
Bay watershed. Such nonpoint source modeling is an important technique in
understanding which land uses are the greatest sources of nutrients, and
where controls would be most effective.
The following chapters were prepared by CBP project investigators and
staff to describe findings of the Nutrients Program and their
implications. Nutrient Problems (author: Christopher D'Elia) discusses
historical trends in nutrient enrichment and its effects. In Nutrient
Processes, Jay Taft discusses the major nutrient processes and how these
events affect the outcome and management of nutrient enrichment. Finally,
James Smullen and Joe Macknis discuss the relative importance of nutrient
sources. A final chapter relates these findings to implications for
managing nutrient contributions to the Bay.
The chapters are organized around a set of management questions:
1. Is there a problem with nutrient levels in Chesapeake Bay?
2. What are the important processes interacting to create the problem?
3. What are the sources, loadings, and losses of the pollutants of
concern?
A more detailed list of the questions can be found at the end of the
Nutrients part.
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aerobic:
albedo:
allocthonous:
anaerobic:
autocthonous:
autotrophic:
bioassay:
biomass:
Technical Glossary
Environmental condition characterized by presence of
oxygen.
Relation between amount of light sent back from a dark or
unpolished surface and the amount falling on it, measuring
its power of reflection.
Material coming from outside; not produced internally.
Environmental condition lacking oxygen.
Originating in location where found, e.g., Bay
phytoplankton vs. river plankton washed into the Bay.
(Of plant) building up its food from simple chemical
substances, not using or not dependent on ready-made plant
substances, living or dead.
The measuring of power of substances by their effects on
organisms, e.g., toxic power of a heavy metal or organic
pesticide.
The total mass or amount of living organisms in a
particular area or volume.
biostratigraphy: Method used by geologists to analyze layers and fossil
remains.
brackish:
chironomids:
coprophagy:
Somewhat salty, as the waters of some marshes near the sea
or waters near the head of the Bay.
Midges, a class of mosquito-like insects; typically refers
to their larvae found in fresh to brackish Bay sediments.
The act of taking excrement as food.
electronic planimeter: Instrument for measuring the areas of plane curved
forms.
epiphytes: Plant fixed to another plant but not dependent on it for
food, using the host plant primarily as a substrate.
etiolation: Condition of a plant which is feeble and without normal
green color through not getting enough light.
euphotic zone: The upper zone of a sea or lake into which sufficient light
can penetrate for active photosynthesis to take place.
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eutrophication: Natural or artificial addition of nutrients to bodies of
water that results in increased plant bioraass and
typically low levels of dissolved oxygen during advanced
stages.
Fickian diffusion: Diffusion of a substance through a unit area at a rate
dependent upon concentration differences over a defined
distance.
Gelbstoff: "Yellow substance" found dissolved in seawater, believed
derived from decomposition products of plants, especially
carbohydrates, in the presence of araino acids to form
humic materials.
ground truth surveys: Technique to verify photographic interpretations.
Hill reaction:
isopod:
littoral zone:
meristic:
oligochaetes:
phytoplankton:
plastoquinone:
polychaetes:
Part of photosynthesis involving light reactions within
the chloroplast; fundamentally, splitting of a water
molecule resulting in the evolution of oxygen through
action of light on plant chloroplast. First stage in
photosynthesis named after discoverer.
Crustacean without a hard cover, having a body commonly
flat and made up of six or more divisions with legs used
for walking, and eyes with fixed or no stems. Typically
small in length (5 - 20 mm), living on and in sediments.
That part of the edge of the sea between high- and low-
water mark or a little further out, as the living place of
certain sorts of animals and plants.
Involving variation in number or geometrical relation of
body parts, e.g., a variation in flower petals.
Animal without a clearly marked head and with only a small
number of chaetae on every body division, hermaphrodite,
and living in earth or inland water, for example, the
earthworm.
Plants, most of which are very small, living in the water
of seas, rivers, etc., chiefly near the top, and moving
freely with it but having little or no power of swimming.
Lipoidal compound localized in subcellular organelles and
functioning as coenzymes in electron transport.
Animals having a great number of stiff hairs, a
well-marked head with special outgrowths. Sea animals in
which the sexes are seaparate and the uniting of sex cells
takes place outside the body.
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post-veliger larvae: Characteristic ciliated larvae whose free-
swimming existence has changed to one of settlement to the
bottom and attachment to a firm surface.
regression analysis: Mathematical method of fitting an equation to data,
usually expressed as the change in a y - variable
(dependent) relative to unit change in an x - variable
(independent).
spectral attenuation coefficient: A number multiplier that expresses the
diminuation of part of the light spectrum as the light
energy passes through water.
spectrophotometer: An instrument used for measuring the intensities of
light of different wave-lengths in a spectrum.
substrate: That substance on which an enzyme has the power of acting.
topographic quadrangles: A section of a topographic map seven and a half
by seven and a half minutes, at a 1:24,000 scale.
2-4D: 2,4, dichlorophenoxyacetic acid: synthetic compound used
as a weed killer in agriculture.
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TECHNICAL SYMBOLS
BOD
C
CFSD
chl a
COD
d
DIP
DN
DP
h
Ks
L
m
ug
ug atom
MGD
ug/L
um
N
NH4
N02
N03
N02>3
02
P
P04
POTWs
ppm
ppt
OP
Q
RQ
sec
SED
TKN
TN
TP
Vmax
— biological oxygen demand
— carbon
— cubic feet per second daily
— chlorophyll £
— carbon oxygen demand
- day
— dissolved inorganic phosphate
— dissolved nitrate
— dissolved phosphorus
— hour
— half saturation value
— liter
— meter
—.microgram
— microgram atom
— million gallons per day
— micrograms per liter
— micrometer
— nitrogen
— ammonium
— total ammonia nitrogen
— nitrite
— nitrate
— total nitrite plus total nitrate nitrogen
— oxygen
— phosphorus
— phosphate
— publicly owned treatment works
— parts per million
— parts per thousand
— orthophosphorous
— mean daily discharge
— respiratory quotient
— second
— suspended sediment
— total Kjeldahl nitrogen
— total nitrogen
— total phosphorus
— maximum uptake velocity
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CHAPTER 1
NUTRIENT ENRICHMENT OF CHESAPEAKE BAY:
AN HISTORICAL PERSPECTIVE
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| Christopher F. D'Elia
University of Maryland
Center for Environmental and Estuarine Studies
I Chesapeake Biological Laboratory
• Solomons, Maryland 20688
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CONTENTS
Figures 47
Tables 49
Sections
1. Introduction 50
Overview of Nutrient Enrichment 5Q
Sources of Nutrients 5^
2. Consequences of Nutrient Enrichment 52
Fate of Added Nutrients 52
Responses to Increased Loadings 55
Nutrient Enrichment and Algal Growth 53
3. Evaluating Nutrient Encrichment Problems
Indicators of Nutrient Enrichment ....... 60
Primary Indicators 60
Nutrient Concentrations . 60
Oxygen Concentrations 60
Secchi Depths 60
Chlorophyll £ Concentrations 61
Algal Species Shifts 61
Techniques for Evaluating Nutrient Enrichment 61
Water Quality Indices 62
Water Quality Models 62
Other Techniques 65
4. Historical Trends in Nutrient Enrichment 66
Trend Evaluation (by W. Boicourt) 66
Trends by Region 67
Upper Bay and Western Shore Tributaries 67
Middle Chesapeake Bay 87
Lower Bay gg
Eastern Shore Tributaries 90
5. Summary and Conclusions 94
Literature Cited,
98
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FIGURES
Number
1 Scheme of possible effects of enrichment in a stratified
water column .53
2 Simple one compartment box model of an estuary 54
3 Binary dendogram showing possible responses of the water
column to increased nutrient loadings 56
4 Regions of Chesapeake Bay ......... .68
* 5 Ranges of concentrations of orthophosphate-P observed during
studies of the upper Chesapeake Bay 70
* 6 Ranges of concentrations of nitrate plus nitrite-N observed
during studies of the upper Chesapeake Bay 71
* 7 Concentrations of orthophosphate-P in surface waters of the
Patuxent River upstream and downstream of Benedict Bridge versus
time of year 72
* 8 Concentrations of nitrate in surface waters of the Patuxent
River upstream and downstream of Benedict Bridge versus time
of year 75
* 9 Secchi depth during July in the Patuxent estuary versus salinity . . 77
*10 Weekly maximum and minimum concentrations of dissolved oxygen
at Benedict Bridge in the Patuxent estuary during 1964 and
1977 79
11 Bottom dissolved oxygen concentration in the lower Patuxent
River during July and August 1978 to 1980 versus a stratifi-
cation parameter (AS — surface to bottom salinity difference) . . 80
*12 Concentrations of dissolved oxygen in bottom waters of the
Patuxent River estuary during July, 1936 to 1940 and July,
1977 to 1979 82
*13 Concentrations of orthophosphate-P (by month) in the lower
James River, Virginia 84
*14 Concentrations of nitrate-N (by month) in the lower James River,
Virginia 85
*15 Concentrations of chlorophyll a (by month) in the lower James
River, Virginia 86
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FIGURES (Continued)
Number
*16 Monthly mean concentrations of orthophosphate-P ("soluble
reactive phosphorus") in the surface 10m at mid-Chesapeake
Bay versus time gg
*17 Concentrations of chlorophyll a at 0 to 10m and 0 to 30m depth
versus time gg
*18 Daytime concentrations of dissolved oxygen (D.O.) in surface
waters at mid-Bay during two selected time intervals 91
19 Nitrogen:Phosphorus ratios (dissolved inorganic nutrients
only) in surface and bottom waters of the Choptank River,
1980 92
*20 Map showing portions of Chesapeake Bay that are moderately
or heavily enriched according to the criteria of Heinle et
al. (1980) 95
*21 Map showing portions of Chesapeake Bay where natural
regimes of dissolved oxygen appear to have changed 96
Figures marked with an asterisk (*) are originals presented in the report
by Heinle et al. (1980).
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TABLES
Number Page
1 Classification Scheme for Nutrient Enrichment in
Estuaries by Neilson (1981) 63
I 2 Neilson1s (1981) Chart Showing Impacts of Nutrient Enrichment
on Water Uses 64
• 3 Examples of Natural Cycles Affecting Chesapeake Bay's
Ecosystem 57
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• 49
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SECTION 1
INTRODUCTION
The following paper deals with historical changes in the nutrient
enrichment of Chesapeake Bay and its tributaries. In the present context,
"historical changes" refer to those changes that have occurred primarily in
the last several decades during which we have data. "Nutrient enrichment"
refers to the addition of nitrogen and phosphorus compounds to bodies of
water, and in excess can lead to phytoplankton blooms, loss of oxygen, and
changes in fisheries species composition. Each section of the report
contains an important topic relative to nutrient enrichment and discussions
of the following Chesapeake Bay Program (CBP) management questions:
o Where and how severe are nutrient enrichment problems in the Bay?
o What are the consequences of nutrient enrichment?
o What are the commonly used criteria for evaluating a water quality
problem related to nutrient enrichment, and what are their
advantages and disadvantages?
o What techniques can be used to evaluate or predict nutrient
enrichment problems?
o What are the historical trends in nutrient enrichment?
o What addditional research needs to be done?
This paper draws heavily on a previous report to the EPA/CBP by Heinle,
D'Elia, Taft, Wilson, Cole-Jones, Caplins, and Cronin (1980). That report,
entitled "Historical Review of Water Quality and Climatic Data from
Chesapeake Bay with Emphasis on Effects of Enrichment," should be consulted
by readers interested in greater detail about historical changes in water
quality as they relate to anthropogenic and natural causes.
OVERVIEW OF NUTRIENT ENRICHMENT IN CHESAPEAKE BAY
There is little doubt that there are nutrient enrichment problems in
Chesapeake Bay and its tributaries; however, there is doubt as to how
extensive the problems are, and how rapidly environmental degradation is
occurring. Human population growth in the Chesapeake Bay area has resulted
in increased nutrient loadings from point (sewage) and non-point (runoff)
sources. These increased loadings have had their greatest effects in the
tributaries nearest the centers of demographic development, such as the
tidal freshwater portions of the Potomac River near Washington, DC, where
point source loadings from municipal sewage treatment plants had noticeable
effects early in this century (Gumming 1916, Gumming et al. 191.6).
Although earliest concerns focused on problems of human health and
sanitation, it was nonetheless recognized that the input of untreated
sewage to the Potomac caused oxygen depletion in receiving waters.
Blue-green algal blooms were observed in the upper Potomac estuary as early
as 1916 (Gumming et al. 1916). By the mid-19601s sewage inputs in the
tidal freshwater portion of the Potomac sufficiently enriched the water
with nutrients, and blue-green algae became a serious problem (Jaworski et
al. 1971b).
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Other tributaries of the Chesapeake also show signs of nutrient
enrichment. The upper Bay near Baltimore, MD, and the upper James near
Richmond, VA, are quite enriched. Also enriched, but to a lesser extent,
are the York, Rappahannock, Patuxent, and Susquehanna Rivers. Of these
moderately enriched tributaries, the greatest data base exists for the
Patuxent River and estuary. This excellent data base extends back to the
mid-1930's and is one of the older and more complete data bases for any
estuary in the world. For that reason, and because the estuary seems to be
undergoing continuing change (dissolved inorganic nutrient levels are
rising, and transparency and deep water dissolved oxygen concentrations are
decreasing), much of the following data analysis and discussion deals with
the Patuxent River. Furthermore, changes occurring in the Patuxent River
could also occur in the main Bay and other tributaries if enrichment in
these areas increases. The Patuxent River can be seen as an analog of the
main Bay and of other western shore tributaries (Klein, unpublished).
Background information on nutrient enrichment and its relationship to
algal growth is provided below to help underscore why the problem of
nutrient enrichment is complex and difficult to assess in light of data
gaps in the historical record. This report avoids the use of the term
"eutrophication" because its meaning can be ambiguous and unclear.
SOURCES OF NUTRIENTS
Nutrient inputs to estuaries come from "point" sources, such as sewage
treatment plant effluents, and "nonpoint" or "diffuse" sources such as
runoff from the land. Increases in loadings from both point and non-point
sources have occurred in the Chesapeake Bay region. As population
increased and urbanization occurred, particularly in the last two decades,
sewage treatment plants were constructed. Nutrients that would otherwise
have been applied over the land or contained in home septic systems were
combined and discharged at points along the rivers. Sewage treatment plant
construction was accelerated after the grant program established in the
1972 Federal Water Pollution Control Act (PL92-500) was adopted. As a
result of the move toward centralized treatment, large increases in total
amounts of nitrogen (N) and phosphorus (P) from human wastes discharged to
the Chesapeake Bay system have occurred. Brush (1974) summarized the
sewage discharges to the Bay in 1973, and EPA/GBP recently completed a
revised inventory. Details of the CBP inventory of sewage discharges are
found in the last chapter of this part.
In contrast to point sources that are solely attributable to human
activities, diffuse sources may be natural, or result from human
activities. Native, undisturbed ecosystems, such as forests, are natural
nonpoint sources. Agricultural or urban runoff accounts for much of the
anthropogenic diffuse loadings. The importance of nonpoint sources depends
on season. For example, in the spring, loadings from nonpoint sources are
by far the dominant source of nitrogen to the Bay system (Smullen et al.
1982). The CBP Modeling Study (Hartigan, unpublished) relates land use to
nonpoint source loads. Sources of nutrients and historical changes in
loadings are discussed in depth by Heinle et al. (1980) and in the last
chapter of this part.
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SECTION 2
CONSEQUENCES OF NUTRIENT ENRICHMENT
The task of enumerating the most important consequences of enrichment
in estuarine systems is yet incomplete, because the consequences of
nutrient enrichment of freshwater environments are much better understood
than for brackish or saline ones. The theme of a recent symposium (Neilson
and Cronin 1981) was the enrichment of estuaries with nutrients. Many of
the papers in the symposium deal directly with Chesapeake Bay. For
example, Webb (1981) formulated a conceptual model of an estuary's response
to nutrient enrichment in his review paper. His conclusions state that
small additions of nutrients increase overall production, with increased
biomass showing up at any trophic level. Large increases produce changes
in species composition at all trophic levels. Interested readers should
consult Webb's review for further details.
The consequences of enrichment in estuaries are more difficult to
assess than those in fresh waters, .because estuaries are generally subject
to more complex hydrodynamic processes. Also, the effects of salt on
biological and chemical processes have no analogues in fresh waters.
However, there appear to be certain consequences that are at least
qualitatively similar for all water bodies that are nutrient enriched.
Figure 1 presents a scheme of probable consequences. As shown, one
consequence is that plant productivity is enhanced by higher concentrations
of nutrients in the water. Levels of organic matter contained in the water
column in turn often increase, although enhancement in the rates of other
processes may counterbalance the increase to some extent. Organic matter
produced in the water column may accumulate in deep water where its
degradation results in an oxygen deficit that is not balanced by
atmospheric input. The Chesapeake Bay is characteristically two-layered;
there is a natural, seasonal isolation of deep water from potential
atmospheric oxygen inputs. Oxygen consumed during the oxidation of extra
organic matter produced by enrichment may not be replaced in the: lower,
isolated layer, resulting in an oxygen imbalance uncharacteristic to the
natural system. Most estuarine organisms of direct interest to
humans—fish and shellfish, for example, require oxygen; they will either
swim away from uncharacteristically low oxygen water or will perish.
FATE OF ADDED NUTRIENTS
An aquatic system can respond to nutrient enrichment in a variety of
ways. If one views such a system as a compartment or a series of
compartments, as mathematical modelers often do, one can more easily
conceive of the ways in which responses might occur. Figure 2 shows a
simple compartmental representation of an estuarine system: a single
compartment with a series of exchanges or fluxes across the compartment
boundaries. The simplest approach to understanding the nutrient mass
balance of such a system, is to measure the amount of a given nutrient
within the compartment and estimate the fluxes and exchanges of that
nutrient between the compartment and the outside. The amount of nutrient
contained in the box after a given time interval is a function of the
amount, or "standing stock," of nutrient in the box at the beginning of the
interval, less the amount lost over the interval, plus the amount gained
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INCREASED
• NUTRIENT INPUTS
I INCREASED
NUTRIENTS
| IN WATER COLUMN
I ^
INCREASED
• ALGAL GROWTH
1 IN WATER COLUMN
•
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| DECREASED CLARITY AND
1 INCREASED PARTI CULATE ORGANIC
LEVELS IN WATER COLUMN
I SETTLING OF PARTICULATE ORGANIC
MATERIAL TO DEEP WATER
1
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• DECAY OF PARTICULATE ORGANIC
MATERIAL AND DECREASE IN
• OXYGEN LEVELS
1 IN DEEP WATER
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Figure 1. Scheme of possible effects of enrichment in a stratified
water column.
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co
tu
CO
CO
o
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i£
<3
N
CO
UJ
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o
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O H
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in
01
to
UJ
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CO?
< CO
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(-1
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over the interval. Clearly this "black box" approach to understanding an
estuary has a number of deficiencies. For example, it tells us nothing
about the internal partitioning of specific nutrients of interest, or about
the biological response in the estuary to a change in a nutrient input or
loss. We know only whether the total amount of nutrient in the compartment
changes.
Understanding internal nutrient partitioning is essential if we are to
increase the complexity of our model to account for internal responses of
an estuarine system to changes in loadings or losses. Only in the last few
years was any attempt made to assess sediment-nutrient exchanges in the
Chesapeake. It is now known that they are of appreciable importance. For
example, during the summer, the sediments are the greatest source of
phosphorus in most of the Bay system (Smullen et al. 1982). Until
recently, very little emphasis was placed on collecting any information
other than on internal compartmental nutrient concentrations. The focus on
point-in-time measurements leaves the historical record grossly deficient
in process-oriented measurements of fluxes, exchanges, and trans-
formations. Although it is possible to infer from differences among
point-in-time measurements that changes occurred in the compartment, it is
difficult to attribute those changes to a specific cause, unless exchanges
that were not measured are assumed to remain constant during the interval
between measurements.
Chesapeake Bay bears little resemblance to the simple one- compartment
system represented in Figure 2. An estuary by definition is a place where
sea water and fresh water mix to produce a range of intermediate
salinities. Provisions must be made in a model to account for this
characteristic, and to understand how Chesapeake Bay might respond to
continued increases in nutrient loadings. Model complexity increases
greatly when one attempts to include provisions for time-varying phenomena
such as intra- and interannual changes in loadings, losses, and
hydrodynamics. Modelers dealing with the Bay and other estuarine systems
have been struggling to determine what level of complexity is necessary to
include in their models (e.g., Harleman 1977; O'Connor 1981).
SYSTEM RESPONSES TO INCREASED LOADS
What are the possible responses of the Chesapeake Bay system to
increased nutrient loads? Figure 3 presents a chart showing the possible
response of the water column to increased levels of nutrients. For
simplicity, we can assume that the single compartment conceptual model
given in Figure 2 represents the water column to which additional loadings
are applied. Figure 3a expands the single compartment into
subcompartments, reflecting partitioning at four levels. The partitioning
scheme is given to show the major pools into which added nutrients must go,
or pass through. Increased loading would manifest itself at level "i" as
higher levels of nutrients in the water column, as enhanced rates of
nutrient loss from the system, or as a combination of both. It is possible
for the internal nutrient content of any compartment to remain constant
over a period of years in the face of increased nutrient loadings, if
increases in net losses from the compartments keep pace with increases in
net inputs. There is no assurance that increased loadings will necessarily
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0)
JJ
(0
o
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to co
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60 M
C 4J
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be manifested in increases of the contents of any particular compartment.
Although the scheme developed in Figure 3 is constructed as a binary
dendrogram, an "either....or" situation is not necessarily implied, as
added nutrients may result in either of the binary choices or in some
intermediate of the two.
The historical record for Chesapeake Bay lacks information on a number
of the pools shown in Figure 3, and on the specific transformation
processes and rates affecting them. However, quite good catch records have
been kept by local authorities on harvestable fish species, providing some
information on partitioning of fisheries between commercially desirable and
undesirable species (level iv). From these records, Heinle et al. (1980)
present evidence that the partitioning to commercially less desirable and
undesirable species has increased in recent years. Unfortunately, little
is known, even now, about food chains leading to the production of
desirable species. Factors such as climate can play an important role
regulating the abundance of estuarine fish stocks.
To explain the changes in fisheries partitioning between desirable and
undesirable species, it is necessary to examine the previous hierarchical
level (level iii), the partitioning of added nutrients between biotic (here
signifying "living") and abiotic particulate material. The historical
record is poor on both the absolute quantities and the partitioning ratios
of nutrients in particulate material. Fortunately, however, the historical
record does include a considerable amount of information on transparency of
the water as determined by Secchi disk. Transparency is affected by the
amount of particulate matter in the water. This particulate matter is
composed of inorganic material (clays, silts, etc.), non-living organic
detrital material, and living material. There is convincing evidence that
in certain places on the Bay, such as near the mouth of the Patuxent River,
transparency as measured by Secchi disk has declined in the last 40 years.
This suggests that the amount of organic material and, by inference,
organically bound N and P in the water column, have increased. Turbidity
derived from inorganic material may have increased also.
Increased biotic particulate material results from increased nutrient
levels in the water column partitioned between the dissolved and
particulate forms. Because there is no way to measure how much N and P are
contained in living material relative to detrital material, it is of
interest to examine the partitioning of nitrogen and phosphorus compounds
(level ii). The total phosphorus in the water column is composed of
dissolved inorganic phosphorus, dissolved organic phosphorus, and
particulate phosphorus. Of these, the historical record contains
substantial information on dissolved inorganic phosphorus only. Total
nitrogen is composed of dissolved inorganic nitrogen (nitrate plus nitrite
plus ammonium), dissolved organic nitrogen, and particulate nitrogen.
Analytical techniques for the identification of all forms of nitrogen
existed in the 1930's but were unreliable, especially for ammonium. Heinle
et al. (1980) found no data on levels of particulate or dissolved organic
nitrogen anywhere in the Bay prior to the 1950's. This represents an
enormous gap in the data record for these forms of nitrogen. For this
reason we have very little understanding of what the historical
partitioning of dissolved versus particulate nutrients in the Bay was, and
how this may have changed in response to increased loads.
Increased loading will manifest itself as higher levels of nutrients in
the water column, as enhanced rates of nutrient loss from the system, or as
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a Combination of both. Increased nutrient loadings to the water column of
the Bay, not accompanied by increased nutrient losses to the atmosphere and
sediments, will result in increased nutrient levels in the water column.
It appears that, on an annual basis, sediments do not absorb more nutrients
than they release (Smullen et al. 1982). We can assume that additional
loadings will not result in equivalent additional losses, and that
nutrients entering the water column will remain there and be manifested as
a corresponding increase in dissolved nutrients, particulate nutrients, or
some other compartment shown in Figure 3.
Although quantity and partitioning data can yield information about
historical changes in the distributions and standing stocks of nutrients in
the system, they yield little knowledge about the internal dynamics of the
system that cause the changes. The next section addresses the internal
dynamics briefly; for more information refer to the following chapter by
Taft.
NUTRIENT ENRICHMENT AND ALGAL GROWTH
The addition of nutrients to an aquatic system frequently enhances
algal "specific growth rates" (increase in biomass per unit biomass).
"Nutrient sufficiency" occurs when algal specific growth rate is not
stimulated by further nutrient addition; "nutrient limitation" occurs when
algal specific growth rate is restricted by the availability of nutrients.
"Algal productivity," that is, the rate at which new organic material is
being produced per m^ by plants, is a function of both specific growth
rate and biomass. Systems can exhibit very high specific growth rates, and
the algae can be nutrient-sufficient, although the productivity per unit
area is low (systems can exhibit very high rates of productivity without
producing nuisance levels of algal biomass). Implicit in this is that the
biomass or standing stock of algae, although growing at a very fast rate,
is low, resulting in a low level of production. In other words, what
material is present is growing fast, but there is not very much of it
present to grow. The converse is also true. A rather high level of
production (that is, increase in algal biomass) occurs when large
quantities of slow-growing algae are present. The situation is reminiscent
of a bank account earning interest. The interest rate is analgous to the
growth rate, and the principal is the biomass. The increase in principal
per time is the analogue of productivity—the highest rate of increase in
principal will occur when the interest rate and the principal are both high.
An important distinction to make is that between "net" and "gross"
productivity. Gross primary productivity is the total rate of organic
production by photosynthesis, irrespective of accompanying consumption of
organic material by respiration. Net primary productivity is the rate of
accumulation of organic material in excess of its consumption by
respiration. In the bank account analogy, the principal in the account
will only grow at its fastest rate when no withdrawals are made, and there
are no bank charges. When the withdrawal rate or bank charges equal the
interest rate, principal does not grow. Unlike bank accounts in which we
want the highest possible increase in principal with time, in aquatic
systems there comes a point at which the accumulation of organic matter
becomes dangerously high. Nuisance levels of organic matter build
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up only when the rate of production of organic matter exceeds its rate of
consumption. Standing stocks of algae can be held at continuously low
levels and still exhibit high productivity if what is produced is consumed
as quickly as it is produced.
Systems where nutrient enrichment problems are greatest are usually
those in which the levels of production are greatest and out of balance
with consumption. Implicit in this is that high levels of biomass
accumulate, and what is produced is not removed quickly. Large
accumulations of biomass—organic matter representing high biochemical
oxygen demand (BOD)—are often responsible for oxygen depletion from the
water column and other negative effects we associate with over-
enrichment by nutrients.
Systems that exhibit high rates of productivity, but in which little
organic material or biomass accumulate, also exhibit high rates of nutrient
recycling or throughput. In such systems, N and P atoms resident in the
systems may "turn over," or pass through organisms in a matter of hours.
There are very few "new" atoms of. N and P entering the system from
outside. On the other hand, systems that quickly accumulate organic
material or biomass, exhibit low rates of turnover and generally high rates
of nutrient addition, without correspondingly high rates of removal. In
its pristine state, Chesapeake Bay probably fell more into the category of
a high productivity system in which standing stocks of organic material or
biomass did not accumulate as much as they do now. Decreases in
transparency as represented by Secchi depth probably signify the
accumulation of organic matter, and it is this organic matter that can
decay and use up oxygen to create a problem.
The important point to note from the above discussion is that increased
loadings may result in greater rates of algal production or nutrient uptake
without increasing standing stock of either; that is, the algae or
additional nutrients are removed from the system as fast as they are
produced or added. A truly adequate historical assessment of nutrient
enrichment effects should assess both standing stocks and process-oriented,
flux rate measurements. Unfortunately, in the present case, the historical
record is heavily weighted toward measurements of individual parameters of
standing stock, and it will not be possible to adequately consider the
changing dynamics of the system. Therefore, enrichment- related changes in
the system not observably affecting standing stocks will not be discernible.
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SECTION 3
EVALUATING NUTRIENT ENRICHMENT PROBLEMS
INDICATORS OF NUTRIENT ENRICHMENT
The traditional approach to assessing enrichment in an estuary relies
on both primary and secondary indicators of nutrient enrichment. "Primary
indicators" of nutrient enrichment are typically the first indicators used
in assessing enrichment. They are not necessarily the best indicators, but
are the ones for which this historical record is most complete. "Secondary
indicators" are those that have potential value in assessing enrichment,
but are secondarily used. Some of the major primary indictors are nutrient
concentration, Q£ concentration, Secchi depth, chlorophyll a, and algal
species shift. Secondary indicators include Measurements of dynamic
processes such as primary productivity and nutrient flux rates, and other
nutrient concentrations, pH, bacteria, BOD, and COD. These indicators will
not be discussed in this section.
Pr imary Indiea tors
Nutrient Concentrations—
Virtually any water quality assessment program will include
determination of nutrient concentrations in the system of interest. The
most commonly measured nutrient forms are nitrate, nitrite, ammonium, and
phosphate. They are of analytical interest, because they are the
"fertilizer" nutrients most often responsible for the growth of aquatic
plants. They also indicate the amount of N and P in the water column
readily available to support algal growth.
Oxygen Concentrations—
Most water quality assessment programs also provide for dissolved
oxygen determinations. Oxygen is probably the most crucial water quality
parameter. Low oxygen tensions occur as the result of the oxidation of
organic material without adequate physical means of oxygen resupply (that
is, reaeration). Because commercially important species require oxygen, we
are concerned with the effect of the accumulation of organic matter
released from sewage outfalls, or produced by algae in response to nutrient
enrichment on oxygen concentration. Fortunately, for analysis of trends,
the historical record for oxygen concentrations in Chesapeake and its
tributaries is good, particularly for the Patuxent River.
Secchi Depth—
The Secchi disk has been used for decades to measure the transparency
of water bodies and to make inferences about levels of organic material and
algae present in the water. Secchi depth (the depth to which the disk can
be lowered and still be visible) is greatest in water of the greatest
transparency. Secchi depth tends to be reliably determined from operator
to operator, and the historical data record is quite good, although Secchi
depth does not differentiate between turbidity from algae and other
materials present such as suspended sediments, detritus, and other
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particulates. Also, Secchi measurements are rather imprecise in extremely
turbid systems.
Chlorophyll £ Concentrations—
Chlorophyll a_ is a reliable indicator of algal biomass and can give a
general indication of the standing stock of phytoplankton present in the
water column. The measurement of chlorophyll did not come into wide
practice until the early 1960's, and since then, methods for measurement
have evolved considerably. Measurement of chlorophyll levels over the next
several decades will probably be more widely used in documenting changes
than it has been over the last several decades.
Algal Species Sh'ifts—
Many water quality studies have also involved collecting phytoplankton
samples for identification. In fresh waters, under highly enriched
conditions, the species composition often changes toward a dominance by
blue-green algae. Such shifts have been observed in the upper Potomac
River near Washington, DC, but are not generally observed in the saline
waters of the Bay. It is not widely appreciated that marine and estuarine
nutrient enrichment does not involve a shift in species composition toward
blue-greens. Therefore, blue-green algae are not considered good indictors
of nutrient pollution in saline systems.
A great difficulty encountered when attempting to examine the
historical data record for shifts in phytoplankton-species composition, is
the evolution of sampling and counting methods for phytoplankton. In the
1950's oceanographers began to appreciate that 35 to 50 um mesh (or
greater) nets traditionally used to sample for phytoplankton in the ocean,
were not catching the smaller-diameter algae responsible for the bulk of
photosynthesis. Phytoplankton sampling on Chesapeake has been no
exception. Early workers used nets and, therefore, their results do not
include counts on important, smaller species. McCarthy et al. (1974)
verified that the smaller phytoplankton on Chesapeake do indeed account for
most of the primary productivity. Thus, comparison of phytoplanktonic-
species composition with time must be done carefully.
TECHNIQUES FOR EVALUATING ENRICHMENT OF ESTUARIES
Evidence in Chesapeake Bay historical data base indicates that changes
have occurred in nutrient concentrations, oxygen levels, and Secchi depths
in parts of the Bay. These changes seem to have resulted from increased
nutrient loadings in the last twenty years. One must understand that
"historical" here refers to relatively recent history, that is, the last
several decades for which we have data. Anthropogenic changes in the
system may have occurred prior to collecting and recording of detailed
data. Other kinds of ecological evidence, particularly on rates of
production, consumption of organic matter, nutrient exchanges, and other
factors, would also be useful in assessing enrichment effects. Such data,
however, are obtained by relatively modern techniques and are difficult to
compare because of inconsistent methodologies. This section contains a
discussion of techniques developed previously for evaluating enrichment in
fresh waters; these techniques evaluate the state of enrichment and predict
changes in water quality in response to nutrient loadings.
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Water Quality Indices
Managers, when faced with the responsibility of evaluating and
improving the "water quality" of an estuary, often turn to water quality
indices to assess the current water quality. What is an index? Thomas
(1972) describes an index as a "composite value for an environmental
component for which we have more than one indicator." Ott (1978) defines
an index as any "mathematical approach which aggregates data on two or more
water quality variables to produce a single number." Pikul et al. (1972)
consider an index "a mathematical combination of two or more parameters
which has utility in an interpretive sense." McErlean and Reed (1981) have
reviewed the use and application of indices to estuaries, and have
concluded that lack of success of transferring counterpart freshwater
indices to estuaries is attributable to three reasons: (a) the lack of an
exact and widely accepted definition of estuarine "eutrophication"; (b) a
basic lack of knowledge of nutrient limitation and cycling in estuaries;
and (c) possible fundamental differences between estuaries and other water
bodies which invalidate transfer attempts. Other scientists have been
critical of indices because they oversimplify complex ecological
properties; they are biased in their formulation; and they do not clearly
associate cause and effect between nutrient enrichment and response of
plants and ecosystem level changes.
Two projects supported by the EPA/CBP were conducted to review the
applicability of existing indices and to develop new water quality indices
for the Bay. McErlean and Reed (1979) proposed the use of five indices in
estuaries. Four were selected from the available literature, and one was
developed by the authors. The four previously developed indices were the
National Sanitation Foundation Index (NSFI) by Brown et al. (1970), the
Minimum Operator (MO) or Water Pollution Index (Ott 1978), the Principal
Nutrient Index (PNl) by Olinger et al. (1975), and the Beta Function Index
(BFl) developed by the State of Illinois. McErlean and Reed's index is
entitled "Estuarine Index of Enrichment" or EIE. The second project was
that of Neilson (1981), who developed a use-oriented rather than a general
index of enrichment. Table 1, as an example, presents the simple indicator
criteria that constitute Neilson1s index. Table 2 shows the use-related
interpretations of indicator values that he has employed.
The use of indices in summarizing data from monitoring programs may
serve to identify areas that are changing, or are in need of closer study.
Indices may be of great value in the indentification of danger zones where
close scrutiny by scientists and managers is required.
Water Quality Models
Another approach to dealing with environmental problems associated with
excessive nutrient enrichment is to formulate and develop models that are
mathematical constructs attempting to represent numerically some key
features (for example, chlorophyll, oxygen concentration, nutrient
concentration) of ecological systems affected by nutrient enrichment.
EPA/CBP is making extensive use of such models.
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TABLE 1. CLASSIFICATION SCHEME FOR NUTRIENT ENRICHMENT IN ESTUARIES
(FROM NEILSON 1981)
Level of Nutrient
Enrichment
0
1
2
3
4
5
6
7
8
9
10
Total Nitrogen
mg/1
0.003
0.010
0.032
0.100
0.320
1.000
3.200
10.000
32.000
100.000
320.000
Total Phosphorus
mg/1
0.0004
0.001
0.004
0.014
0.044
0.140
0.440
0.400
4.400
13.800
44.000
Numerical water quality models have proved to be successful in
representing the operation of some sewage treatment plants and in
representing rivers, streams, and lakes in which hydrodynamic factors are
relatively simple and easy to simulate mathematically. Such models have
typically been "steady-state," that is, those in which boundary conditions
and inputs remain constant through a given model run, in contrast to
time-varying or "real-time" models where such parameters are not held
constant. In estuarine systems, the complexities of the non-steady-state
hydrodynamics greatly complicate nutrient cycles and distributions, oxygen
exchanges, and the growth and distribution of organisms (Harleman 1977,
D'Elia et al. 1981). Mathematical modeling of estuaries is considerably
more challenging. Below, some of the strengths and weaknesses of water
quality models as tools of the scientist and manager are briefly reviewed.
Since estuaries are complex time-varying systems in the hydrodynamic
sense, models may be constructed for different pollutants yet contain
similar hydrodynamic representation. However, factors not related to
hydrodynamics but that affect pollutant chemical specification and
transformation, will probably be pollutant-specific and, thus, require
different modeling formulation. Virtually any water-quality, numerical
model must be designed with the system and pollutants of interest in mind.
As in the case of water quality indices, data gaps can be problematical
with numerical water quality models. Standard procedure in developing such
models involves calibration and verification. Once a numerical model is
formulated it is "fine tuned" with a set of environmental data, so that an
appropriate set of inputs will reproduce a set of data actually collected
in the environment. At that point, it is calibrated. The model is next
verified by seeing if it can reproduce another set of "real" data collected
under different conditions. Data collected must be appropriate to provide
for rigorous calibration and verification. Time and space intervals used
in obtaining data for these processes must reflect the scales that the
model is designed to resolve, and the model, in turn, should be designed to
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reflect time and space scales of importance in nature.
Mathematical models often intimidate non-mathematicians who, therefore,
often find it difficult to evaluate the utility of models as management
tools. However, models' ability to predict or project water quality
conditions is not their only role in aiding managers. Clearly,
mathematical models are of special benefit in developing conceptual
formulations of nutrient enrichment responses and in identifying where
additional research and data collection are needed (cf. O'Connor et al.
1981).
Other Techniques
Other methods for evaluating the current state of nutrient enrichment
that have been less intensively utilized in the GBP. Two are presently
being incorporated in ongoing and incomplete studies of the Bay.
Considerable effort has been paid, in particular, to developing an
assessment methodology for determining available forms of phosphorus in
fresh waters. Relatively simple, statistical models have been developed to
relate phosphorus loading, hydraulic residence times, and algal biomass in
a number of lakes. Leaders in this area of endeavor have included
Vollenweider .(1976), Schindler (1977), and Lee et al. (1978). Such an
approach would be difficult to accomplish for Chesapeake Bay, because both
phosphorus and nitrogen seem to play roles as limiting nutrients at
different seasons and in different places, and because loading levels are
not adequately quantified. However, Lee and Jones (1981) have developed a
preliminary statistical model applicable to Chesapeake Bay.
Bay area scientists have also devoted some attention to the use of
salinity-dilution diagrams for nutrients. This method may help identify
localities of abundance and depletion of nutrients (Boynton and Kemp,
unpublished; Taft, unpublished; D'Elia, unpublished; Webb, unpublished).
The idea behind this approach is simple: when nutrients are supplied
primarily in freshwater inputs and diluted down-estuary by saline waters
low in nutrients, the concentration of a given nutrient in the water column
will be in proportion to the salinity, unless there are sinks or sources of
nutrients along the way. The statistical modeling of nutrient-loading
responses, and the diagraming of salinity-dilution relationships will
probably receive much greater attention in future evaluation of nutrient
enrichment of Chesapeake and its tributaries.
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SECTION 4
HISTORICAL TRENDS IN NUTRIENT ENRICHMENT
The review of historical trends in nutrient enrichment of Chesapeake
Bay (Heinle et al. 1980) concluded that nutrient enrichment problems were
greatest in the low salinity areas (less than 8 to 12 ppt), where summer
chlorophyll £ concentrations often reach or exceed 60 ug L~l. Such areas
are those where the tributaries pass through the more populous areas; prior
to population growth, chlorophyll levels in those areas may have rarely
exceeded 20 ug chlorophyll £ L~l. Climatic and other natural factors
strongly affect ecological expression of nutrient enrichment. This is now
of concern, particularly in the main stem of the Bay where relatively
unenriched seawater dilutes the nutrient content of the enriched river
water.
TREND EVALUATION
Separating human-induced changes from natural cycles is often the crux
in both scientific assessment of the state of the Bay and management
decisions in preserving (or improving) Bay environmental quality. The
obvious importance and weight of these determinations lead scientists and
managers to examine the ability to determine accurately a trend or change
in the presence of noise or large variation. Without resorting to the
formation of signal theory the problem is: can we be assured that a trend
or change we observe over time is not simply part of a natural cycle of
change, whose period is considerably longer than our viewing time? One
solution to this uncertainty is to observe the Bay over a time much longer
than the longest period of expected variablility. The difficulty here,
however, is that natural cycles of climate and runoff can vary over periods
greater than 10 years (Table 3). If time-series analysts were strict and
required many cycles for accurate determination, then they would demand
records of observations that were longer than all but a few available from
the Chesapeake Bay system. Table 3 lists some of the cycles that are
expected to affect the Bay's ecosystem. The shorter-period cycles (with
variation on the order of one year or less) can serve as guides for the
design of observational programs that ensure that the record length will
encompass the variability. The longer-period cycles offer a test of a
record's ability to separate trend from cycle.
One rule of thumb for time-series analysis is that a record should
comprise on the order of 10 cycles for proper resolution. If, for
instance, the Bay ecosystem responded to the six-year cycle in rainfall,
then a 60-year time series would be desirable. Few natural systems have
been observed with even simple measures for such a long time.
The situation is not hopeless, however, for scientists and managers who
are forced to assess trends or changes on the basis of time-series with
much shorter lengths. This assessment can often be made with acceptable
certainty if additional information, such as cause and effect, is
considered. For comparatively simple relationships, such as the effect of
runoff on estuarine salinity, the separation between trend and cycle can be
achieved despite shorter record length. A numerical model predicting
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TABLE 3. EXAMPLES OF NATURAL CYCLES AFFECTING CHESAPEAKE
BAY'S ECOSYSTEM
Cycle Period Type of Cycle
• 12 to 42 hours
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Semidiurnal tide
24 hours Diurnal light cycle, sea breeze, etc.
4 to 8 days Passage of low-pressure systems
14 days Spring-neap tidal range progression
1 month Monthly tidal variation
1 year Seasonal climatic cycle
6 years Climatic (rainfall, runoff)
11 to 12 years Climatic (rainfall, runoff)
20 years Climatic (sunspot activity cycle,
rainfall, runoff)
salinities from runoff data would provide the necessary additional
information here. For relationships that are derivative and not direct, or
that depend on multiple causes having cycles of differing periods,
separations between trends and cycles are difficult, even if long records
are available. Time-series analysis techniques can help refine the
statements on variability, but they cannot provide information that is not
on the record itself. In spite of these warnings and difficulties, the
history of an indicator of Bay environmetal quality is the necessary
starting place for an assessment of change.
TRENDS BY REGION
For purposes of contrast and comparison in the ensuing discussion, the
Bay is divided into four geographical regions (Figure 4). These regions
are: (1) the upper Bay and western shore tributaries, characterized by the
highest fluvial inputs; (2) the middle Chesapeake Bay; (3) the eastern
shore tributaries, characterized by low fluvial and sewage but high
agricultural nonpoint source inputs; and (4) the southern Chesapeake Bay.
The geographical regions reflect, in a general sense, the segmentation
approach to the Bay adopted by the EPA/CBP. For example, the main Bay and
western shore tributaries can be considered to be analagous (Klein,
unpublished). However, the EPA/CBP segmentation scheme is more detailed,
allowing for close examination of individual portions of the Bay and for
modeling purposes. The EPA/CBP segmentation approach, therefore, provides
for more resolution than is necessary for purposes of this paper. Readers
who wish to learn in greater detail about historical changes in specific
localities should consult Heinle et al. (1980).
Upper Bay and Western Shore Tributaries
This region has been most severely affected by anthropogenic, nutrient
enrichment. The enrichment problem is greatest in the summer when
water-residence times, light availability, and temperatures are also
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Chesapeake Bay
Region
Figure 4. Regions of Chesapeake Bay.
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greatest. Historical evidence for enrichment-related effects is most
substantial in this region, with long-term trends clearly distinguishable
from short-term variations. The seasonality of the nutrient cycle is very
evident and quite complex. Nutrient inputs through the tributaries are
greatest during the high-flow period of the year, typically in March
through May. These inputs are characterized by high N:P ratios; that is, N
is in excess of P relative to the ratio normally required by phytoplankton
(about 16 atoms of N per atom of P). The amount of N from fluvial sources,
during this period, is high relative to the amount of N coming into the
system from point sources—sewage treatment plants. High flow, nonpoint
source fluvial inputs are also highly oxidized. In other words, nitrate is
the primary form in which the N is found. There is some evidence,
especially for the nitrate input at high flow from the Susquehanna, the
largest volume tributary to the Bay, that much of this nitrate passes
through the Bay unassimilated, because of short residence times of this
nitrate relative to the seasonally slow uptake rates of the plankton for
nitrate (Taft 1982). A similar condition may exist in other tributaries,
and it is important to scale the importance of this N in annual input
budgets that have, as their goal, the development of input ratios for
steady-state mathematical models.
In the summer, when river flows decrease, point-source inputs to the
tributaries become the predominant input-source of new N and P to the
system. The N:P ratio of point-source inputs is much lower; however,
regeneration of N and P under oxic conditions from the stored reserves in
the sediments (in effect, a nonpoint source to the water column) may
counterbalance this to some extent. Chlorophyll levels in the water column
increase in response to greater hydraulic detention times and higher algal
growth rates. Oxygen concentrations in the water column are high in the
daytime when algal photosynthesis is high and are low at night when
planktonic respiration is not counterbalanced by photosynthetic oxygen
production that cannot occur without light. Fortunately, dissolved oxygen
levels in upstream waters rarely get critically low, because the water
column is typically shallow and unstratified and can easily mix and
reaerate.
Upper Bay—
Early data from the upper Bay exhibited a pattern of maximum dissolved
inorganic phosphate (DIP) concentrations in the spring and fall with
minimal concentrations in the winter, and especially in the summer; more
recent data suggest that relatively uniform concentrations exist all year
(Figure 5). For example, in 1949-1951 and 1964-1966, values in June, July,
and August did not exceed 0.645 ug atoms L~l. In contrast, values in
1969-1971 for those months exceeded 1 ug atom L~l. The upper Bay differs
from the western shore tributaries that apparently can reach much higher
levels of DIP. Nonetheless, the upper Bay appears to show some increase in
annual DIP abundance.
The concentration of nitrate plus nitrite-N, the only parameter for
which we have reliable data back to the early 1950's, does not appear to
have changed in the upper Bay (Figure 6). For example, in March, the
period of greatest influx, values in 1964 to 1966 ranged from 20 to over
100 ug atoms L"1. From 1969 to 1971, March values ranged from 28 to 83
ug atoms L~l. The seasonal pattern is typical for most of the Bay, with
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the nitrate maximum occurring during the high-flow period, and the nitrate
minimum during the low-flow period. The upper Bay is so dominated by the
flow of the Chesapeake's most important tributary, the Susquehanna River,
that it is not surprising that nitrate availability in the water column
strongly reflects nitrate input to the upper Bay by that river. Additional
information about the dominance of the Susquehanna is presented by Smullen
et al. (1982).
The effect of enrichment on chlorophyll levels in the upper Bay is
unclear. Evidence for increased concentrations of chlorophyll in the upper
Bay is inconclusive based on the Heinle et al. (1980) historical data base,
whereas the data presented by Salas and Thomann (1978) appear to indicate
conclusively that an increase in chlorophyll occurred. Although
concentrations of chlorophyll in the early CBI data never exceeded 10 ug
L~l, no measurements of chlorophyll £ were made during August and
September, the months in which annual chlorophyll maxima are often
achieved. Productivity may have increased in response to nutrient
enrichment without an accompanying increase in plant biomass, providing
that the turnover of plant material increased accordingly.
As in the Patuxent River where the issue of what nutrient, if any,
limits productivity is complex, the issue of what limits phytoplankton
production in the upper Bay is also complex. Salas and Thomann (1978) and
Jaworski (1981) concluded that P limitation predominates, but Clark et al.
1973 concluded that N limits phytoplankton growth. Without a complete
understanding of dissolved inorganic nitrogen inputs (other N forms such as
ammonium must be taken into account also) and without knowing the seasonal
breakdown on N:P input ratios, the question of whether N or P limits
productivity is very difficult to assess (Taft 1982).
Patuxent River—
The Patuxent River has an excellent historical record, and it appears
that it provides an analog of the main Bay and western shore tributaries.
(However, correlations evaluating the relationship are being made in the
CBP's characterization analysis). The Patuxent has been increasingly
enriched in recent years; detrimental effects of this enrichment could be
expected to occur in analogous segments of the Bay system if they were
equally enriched.
The Patuxent River shows a somewhat different pattern in DIP abundance than
does the upper Bay. Figure 7 shows the rather striking historical changes
that have occurred in DIP concentrations in surface waters there, probably
in response to increased point source loadings. Maximum concentrations of
DIP have clearly increased upstream of the Benedict Bridge, where
salinities are typically less than nine ppt. Downstream of the bridge,
where salinities range from about eight to 18 ppt, surface DIP
concentrations are significantly lower than those observed upstream (note
scale change between panels in Figure 7), presumably as a result of the
dilution of phosphate-rich fresh water by less enriched saline water.
There appears to have been an increase in DIP levels since the 1930 "s in
this region of the river also. This increase is most pronounced in the
summer. Such a summer phosphate maximum is characteristic of Chesapeake
Bay and other estuaries (Taft and Taylor 1967a, 1967b); it may result from
surfacing of water rich in phosphate, produced by enhanced rates of benthic
regeneration at higher summer temperatures, and by increased phosphate
73
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solubility at lower oxygen concentrations below the halocline. Because we
do not know the effect of enrichment on total phosphorus levels, we cannot
rule out a change in partitioning of water-column-total P resulting in
higher DIP levels.
On the basis of the 1968-to-present data set, phosphorus limitation
seems unlikely anywhere on the Patuxent River throughout most of the season
when severe oxygen deficits occur (late spring through fall). Light
limitation seems more probable (O'Connor et al. 1981). Phosphorus
limitation may have been present prior to the late 1960's, when P loadings
from sewage treatment plants were considerably lower, but this is riot
unquestionable.
The concentrations of nitrate plus nitrite-N in the Patuxent exhibit
the same seasonal cycle of abundance that has been reported for the upper
Bay; moreover, there appears to have been an increase in nitrate content of
the water since the late 1930's (Figure 8). Most of the increase appears
to have occurred later than 1965, coinciding with Che beginning of
extensive development of the Patuxent River basin. The source of this
nitrate is probably nonpoint; most sewage treatment: plants are not
discharging fully oxidized effluents—most inorganic N is usually in the
ammonium, not nitrate form. As for DIP, less nitrate is found in the water
south of Benedict Bridge, reflecting the dilution of nutrient-rich fresh
water by less enriched saline water.
The historical record does not include adequate data on ammonium. This
is unfortunate, because ammonium is taken up preferentially by
phytoplankton relative to most other N forms. We know from previous work
(Boynton et al. 1980) and work in progress at CBL, that the regeneration of
ammonium by the Patuxent riverbed occurs at some of the highest rates ever
recorded anywhere. This regenerated ammonium can drive internal recycling
processes in the absence of added nutrients (Nixon 1981). We know also
that this ammonium accumulates below the halocline and diffuses across that
boundary often at rates lower than those at which it is removed from the
water column above. Boynton (personal communication) does not consider the
sediment nitrogen reserves to be adequate for more than a few weeks' supply
of regenerated ammonium, and there appears to be rapid settlement and
mineralization of nitrogen on the benthos. Rapid recycling of nitrogen
occurs between the water column and the riverbed. A productive system
could be maintained for some time in the absence of added nutrients; the
effects of nutrient controls might not be immediately apparent.
Although the analytical procedure for determination of nitrite has
remained essentially the same over the last 50 years, relatively little
attention has been paid to its measurement. This is because it rarely
achieves significant concentrations in the water column. A number of
investigators have observed periodic accumulations of nitrite in Chesapeake
Bay waters (McCarthy et al. 1977; Webb and D'Elia 1980; Academy of Natural
Sciences of Philadelphia, unpublished). This nitrite accumulation occurs
in the late summer and early fall and is probably a consequence of ammonium
oxidation (nitrification, step one). In a synoptic sampling program
conducted in the fall of 1981, Taft et al. (unpublished) observed elevated
nitrite concentrations throughout the Bay. In the Patuxent River, levels
exceeded 15 uM nitrite-N. It is unknown whether this phenomenon occurred
historically, but Webb (1981) suggests that the magnitude of the nitrite
accumulation is a function of the degree of nutrient enrichment of the Bay
74
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during the summer, and he recommends continued monitoring of the nitrite
maximum.
There is strong evidence that nutrient enrichment stimulated increased
phytoplankton production and an accumulation of plant biomass in the lower
Patuxent River. This conclusion is based mainly on Secchi-depth data
rather than chlorophyll-concentration data, because the historical data
base for chlorophyll on the Patuxent is less complete (but suggests the
same trends). Figure 9 shows Secchi data from July, 1937 to July, 1978,
normalized against surface salinity (to account for variations in river
flow). The inability of the Secchi disk to resolve differences in
transparency when transparency is low, means that little can be said about
historical changes at surface salinities below about eight ppt. Such low
salinity regimes are also subject to high levels of because of turbidity
because of inorganic sediment. However, at the greater transparencies
found at higher salinities, the resolving power of the Secchi disk is good,
and inorganic sediment loads, particularly at lower flow times of the year
such as July, are less appreciable.
Transparencies of the water in the lower estuary during 1963 were
similar to those observed during 1936 to 1940 (Figure 9). Heinle et al.
(1980) felt that the decreased Secchi depths in the lower estuary during
the summer in recent years reflect increased standing stocks of alga.e and
probably also of organic detritus; an alternate explanation is that small
particle sediment levels have increased. Increases in algal standing
stocks imply that algal production has increased to a rate greater than
that of its consumption, and that a concomitant increase in BOD has also
occurred. This is of concern because, in the lower Patuxent estuary, which
is often stratified in the summer, oxygen concentrations are quite low in
the earliest data, and they may be driven lower by the settling of organic
matter with high BOD produced in surface waters. Still unresolved is how
great a role is played by nutrient rich-oxygen poor deep water advected
into the river from the Bay. Clearly, inputs from the Bay are important;
likewise, nutrient inputs to the lower river from upstream sources may
stimulate organic production in the lower river and increase BOD. This
increased BOD may further depress deep-water oxygen concentrations. Oxygen
concentration and factors that affect it in the lower Patuxent are
discussed in greater detail below.
One of the more common effects of excessive enrichment is increased
variation in diurnal and nocturnal dissolved oxygen concentration in the
water column, in response to greater levels of community metabolism. This
represents a particularly serious problem when nighttime consumption of
oxygen by respiration becomes great enough to lower oxygen tension to a
point where it jeopardizes the viability of aerobic organisms in the
community. Under such conditions, we observe the nuisance conditions most
often associated with excessive nutrient enrichment or as many refer to it
"eutrophication." There is evidence that day/night deflections in oxygen
concentration in the upper Patuxent are increasing, although the problem,
at least at Benedict where the measurements have been made, has yet to
reach crisis proportions. Cory (1974) and Cory and Nauman (1970) noted
evidence for such changes in the Patuxent at Benedict during the period
from 1963 through 1969. They observed greater extremes in concentration of
dissolved oxygen and a reduced ratio of production in respiration during
that period, suggesting that increased levels of heterotrophy are
76
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60
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occurring. In a later unpublished study from which Cory made his data
available to Heinle et al. (1980), it appears that continued changes have
occurred between 1969 and 1977. Figure 10 shows weekly maximum and minimum
concentrations of dissolved oxygen during May through August near the
surface at Benedict Bridge. Minimum concentrations observed (about 2 mg
02 L~*) are fortunately, transient, but are nonetheless approaching
dangerously low values. The increased range of values in 1977 over that of
1964 is clearly evident in Figure 10.
The greatest ecological concern in the Patuxent River does not rest in
oxygen concentrations nor in aesthetic deterioration by enhanced turbidity
in upstream waters but, instead, in the oxygen concentration in the deep
waters of the lower estuary. In a stratified body of water such as the
Patuxent estuary, increased productivity in the surface waters can cause
decreased oxygen concentrations in deeper waters as organic matter settles
in the water column and decomposes. Sustained oxygen depletion (perhaps by
this mechanism) is known to occur naturally in the central part of the Bay
(Newcombe and Home 1938, Taft et al. 1980). On the basis of present
information, the extent of this low-oxygen water is increasing with time.
Nash (1947) observed that the differences between surface and bottom
concentrations of dissolved oxygen were greater at times of greater
stratification, and he postulated that the degree of stratification was an
important determinant of bottom-dissolved-oxygen concentration. D'Elia and
Farrell (unpublished manuscript) have plotted bottom-dissolved-oxygen
content of lower Patuxent waters, versus an index of stratification;,
surface to bottom salinity difference, over a period of three summers
(Figure 11). They have verified Nash's observations that stratification
strength is a critical consideration. Bottom-oxygen levels decrease with
increasing stratification, because mixing with aerated upper waters is
prevented. Similar results have been observed for the mainstem of
Chesapeake Bay (Taft et al. 1980) and for the lower York River (Webb and
D'Elia 1980). This greatly complicates the interpretation of nutrient
enrichment effects, and it is not surprising that bottom-dissolved-oxygen
content in the historical data base shows a wide variation within a given
year (Figure 12).
The long-term decrease in mean oxygen content of deep waters in the
lower Patuxent is one of the more striking examples of an enrichment-
related phenomenon in the mesohaline regions of Chesapeake Bay. Figure 12
shows that recent, bottom-dissolved-oxygen content in the lower Patuxent is
considerably lower on the average than it was in earlier years. The
highest concentrations observed in the deep water south of Benedict do not
exceed about six mg L~l in the recent data, whereas in the 1936 to 1940
data, deep water oxygen concentration maxima were twice that, reeiching
supersaturation at 12 mg L"1. Heinle et al. (1980) noted that the
Winkler oxygen method has remained essentially the same for decades and,
after checking and verifying the accuracy of the notes and calculations of
the original analyst, concluded that the early data were reliable.
Concentrations of dissolved oxygen in bottom waters between Benedict
and Broomes Island appear to be affected by in situ respiration and
decomposition of organic matter produced within the Patuxent estuary and by
intrusion of Bay waters naturally low in dissolved oxygen. The relative
roles of these two causes of oxygen depletion are not certain. Low
concentrations of dissolved oxygen are often observed downstream of Broomes
78
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Island. On occasions when concentrations are low upstream of Broomes
Island, they are not so low downstream near the mouth of St. Leonard's
Creek (Figure 12). This suggests that the Bay is not the sole source of
the very low dissolved oxygen water.
Potomac River—
The Potomac River has been studied with varying degrees of intensity
since 1913, yet the early data set for the Potomac is not so extensive as
it is for the Patuxent, where CBL scientists were conducting some of the
first intensive basic research on the nutrient distribution and dynamics of
an estuary. Wolman (1971) reviewed the history of the effects of a growing
population on continuing efforts toward improvement of water quality in the
Potomac. Jaworski et al. (1972) also discuss the changes that have
occurred there. The USGS is presently conducting comprehensive studies on
the water column and sediments of the river, expecting to produce detailed
reports on their studies in the next year. There is an excellent
environmental atlas of the Potomac River (Lippson et al. 1979) that should
also be consulted for further details.
Because the most serious problems in the Potomac occur near the head of
tide near Washington, DC, most scientific and monitoring efforts have dealt
with that region of the river. Yet even now, with concern growing about
the higher salinity regions farther south in the river, most debate and
study of water quality still center on upriver regions. Gumming et al.
(1916) apparently measured nutrient and dissolved oxygen concentrations in
the lower estuary during 1913, but Heinle et al. (1980) could not locate
the data. Although CBI did conduct some sampling in 1949 to 1951 (Hires et
al. 1963, Stroup and Wood 1966), the first intensive studies of water
quality that encompassed the length of the estuary were those of CBI during
1965 to 1966 (Carpenter et al. 1969). What data do exist for the Potomac
estuary suggest that slightly higher concentrations of phosphorus and
considerably higher concentrations of chlorophyll a_ occur during the summer
in the lower Potomac. By the time of the CBI studies, quite elevated
chlorophyll a. concentrations of 80 to 100 ug L~l were common in the
portion of the estuary up to 20 miles or more downstream from Washington,
DC. Dissolved oxygen levels frequently reached low concentrations and
there were substantial blooms of blue-green algae (Jaworski et al. 1971b,
1972). Since that time, plans were made to limit both the N and P levels
in the effluent from the largest single point source to the Bay, the Blue
Plains Sewage Treatment Plant. However, N controls were never instituted.
A battle still rages over the effectiveness of the single nutrient advanced
wastewater treatment strategy in force; there have been hearings held in
front of administrative law judges in the past year.
The floating mats of blue-green algae that were prominent during the
1960's were not observed in the more recent studies, and this has prompted
EPA officials to regard the present Blue Plains effluent limitations as
effective. Proponents of the opposite point of view argue, instead, that
flow regimes and hydraulic detention times, characteristic during the
periods of the worst problems with blue-greens, have not occurred in recent
years. Irrespective of the outcome of the controversy, it is apparent that
some nutrient control strategy will be necessary to prevent future problems.
An interesting contrast occurs between the Potomac, where extensive
blue-green algal blooms are seen, and other tributaries to the Bay, where
81
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they are not. Blue-greens are rarely dominant in the water columns of
saline environments of any tributary, including the Potomac; in the
freshwater parts of the Potomac, N:P input ratios and characteristic
hydraulic features probably account for the blue-green blooms.
James River—
Heinle et al. (1980) were unable to locate substantial early data for
the James River. The first useful data on the James River were obtained by
CBI in 1950, followed by a more complete study by Brehmer and Haltiwanger
(1966), who sampled farther upstream than previous workers. By the time
they began their study, the upper James appeared to have already been
affected by enrichment. Summer chlorophyll concentrations of 50 to 80 ug
L~l were common at their upriver stations in the tidal-freshwater portion
of the estuary, and 20 to 50 ug L~l were observed at their midriver
stations. Prior to enrichment, annual chlorophyll maxima in the low
salinity regions of all of the western tributaries probably rarely exceeded
30 to 40 ug chlorophyll £ L~l.
DIP concentrations upriver show no seasonal or longitudinal patterns in
the data of Brehmer and Haltiwanger (1966); typical values are less than
1.0 ug-atom L~l. Downriver, a slight summer-concentration maximum is
apparent as is characteristic for the Chesapeake estuary (Taft and Taylor
1976a, 1976b) (Figure 13). Data collected in the 1970's (Adams et al.
1975) show markedly higher concentrations of DIP through most of the year
than in the earlier data (Figure 13). There have also been significant
increases in nitrate and nitrite in the lower James estuary (Figure 14).
Earlier data evidenced the spring seasonal maximum characteristic in Bay
tributaries; in the latter study nitrate levels were high year-round.
In spite of the high ambient levels of both N and P in the lower James,
concentrations of chlorophyll _a have apparently not increased (Figure 15).
The explanation for this apparent lack of response to enrichment is
uncertain, but may simply relate to an increased turnover rate, but not to
standing stock of plant material or to inadequate data availability.
York and Rappahannock Rivers—
In recent years, the York and Rappahannock have also exhibited
increased levels of chlorophyll and nutrients; changes are comparable to
those observed in other tributaries, so they will not be reviewed in detail
here. There are some interesting hydrographic aspects of the York, James,
and Rappahannock Rivers that have bearing on the water quality of those
estuaries. Haas (1977) noticed that there was a striking correlation on
those rivers between the occurrence of high spring tides and
destratification of the water column. Since then, in more detailed studies
of this predictable occurrence, it has been learned that the water quality
characteristics are affected greatly by this cycle (Webb and D'Elia 1980;
D'Elia et al. 1981). As for the Patuxent River, the bottom-dissolved-
oxygen concentration of the York (and presumably the James and
Rappahannock) River is generally highest under conditions of
destratification. Thus, the water quality of the river, as reflected in
oxygen content of the bottom water, can alternate rapidly between
acceptable and low values. Nutrients are also affected. Short-term
phenomena like this greatly complicate the evaluation of enrichment in an
estuary and cause considerable range in the values of water quality
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parameters measured. Such phenomena also seem to indicate that the
steady-state assumption often used in water quality models may be a risky,
one, if realistic model results are to be obtained.
Middle Chesapeake Bay
The mid-Bay is showing evidence of nutrient enrichment, but it is not
as severely affected as are the western shore tributaries and the upper
Bay, probably because of the sheer volume of this region and because of the
ameliorating affects of dilution by low-nutrient sea water. A fair amount
of early work at CBL was conducted in the mid-Bay off the mouth of the
Patuxent River (Newcombe 1940, Newcombe and Brust 1940, Newcombe and Lang
1939); there is a reasonably extensive set of older data for this area.
DIP was comparable at all depths from 1936 to 1951, with values ranging
from undetectable to 1.3 ug atom L~l (Figure 16). By 1964 to 1966,
maximum values increased to two ug atom L~l and, by the mid 1970's,
values of 2.5 ug atoms L~l were observed (Figure 16). Chlorophyll £ data
show some increases in the mid-Bay between 1951 and 1964 to 1966. Peak
values in the euphotic zone (upper 10 m) are less than 25 ug L~l (Figure
17). The highest values were observed in the deep water, usually in winter
or spring.
The data for nitrogen are less complete than for phosphorus. As in the
tributaries, nitrate tends to be the dominant inorganic form in the winter
and spring and is associated with high runoff. Salinity-dilution diagrams
of the main stem of the Bay prepared by Taft (1982) indicate that this
nitrate is conservatively diluted by seawater. This suggests that most of
this nitrogen is passing through the mid-Bay unassimilated. Ammonium is
more abundant in the summer and fall, but the lack of old historical data
for ammonium leaves no basis for comparison. As in the tributaries, there
is a late-summer, early-fall nitrite maximum in the mid-Bay (McCarthy et
al. 1977, Taft et al., unpublished); this nitrite is probably derived from
the oxidation of ammonium by nitrifying organisms (McCarthy, unpublished).
Phosphorus probably limits biomass in the spring when inorganic
nitrogen is abundant (Taft et al. 1975; Taft and Taylor 1976a, 1976b).
However, there are too few data to establish clearly a limiting nutrient in
other seasons. Flemer and Biggs (1971) have noted that "the suspended
particulate organic material in [that region] is suffering a relative loss
of nitrogen with respect to carbon," and it may be that there is temporal
variation in the limiting nutrient.
The range of dissolved oxygen values for surface waters is comparable
in the earliest and latest data sets available (Figure 18). Oxygen
concentrations in the deep water, however, seem to be depressed for longer
periods in the summer and over wider regions of the mid-Bay. There is some
concern that low-oxygen, high-nutrient water masses advected from the deep
mid-Bay into the lower tributaries such as the Patuxent exacerbate present
enrichment problems there.
87
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Lower Bay
Data for the lower Bay are available from CBI cruises of 1949 to 1951,
1961, and 1969 to 1971. Other data Heinle et al. (1980) used in comparison
came from Smith et al. (1977), from Patten et al. (1963), and from
Fleischer et al. (1977). Sufficient data exist to show that the lower Bay
has remained relatively unaffected by nutrient enrichment upestuary.
Because little change is evident, the data will not be reproduced here but
instead will highlight the major features characteristic of the nutrient
regime in the lower Bay.
DIP concentrations, throughout the lower Bay, were low historically and
continue to be so. The summer maximum of phosphate reaches or exceeds
slightly 1.0 ug atom L~l, but is generally half that or less in other
seasons. Nitrogen is not well represented in the historical data base so
historical changes cannot be assessed. Recent data showed that nitrate
availability in the lower Bay is similar to its availability in the central
Bay—high-flow nitrate maxima are observed, and most of this nitrate
probably passes out the Bay mouth unassimilated. Maxima in the spring may
approach, or even rarely exceed, 25 ug atom L~l. McCarthy et al. (1977)
provide a detailed summary, by season, of nitrogen dynamics and the
plankton of the lower Bay. Spring maxima in chlorophyll levels occur that
exceed 20 ug L~l; however, for the rest of the year, concentrations are
generally below 13 ug L~l, and are characteristic of a relatively
unenriched system.
Eastern Shore Tributaries
The flows associated with eastern shore tributaries are trivial with
respect to those of the western shore. Historical data suggest that
moderate effects of enrichment can be observed in eastern shore
tributaries. The earliest data were again obtained by CBI in the late
1940's. Early data show chlorophyll levels of less than six ug L~l in
the Chester, Choptank, and Miles Rivers, and low DIP levels as well (<0.6
ug atom L~l). More recent observations show chlorophyll levels exceeding
25 ug atom L~l.
Recent studies on SAV conducted for the EPA show that nitrogen is
likely to be severely limiting on the Choptank River during the summer.
Figure 19 presents results reported by Twilley et al. (1981) on dissolved
inorganic nitrogenrdissolved inorganic phosphorus (DIN:DIP) ratios in the
water column from April through September of 1980. There is a progression,
from a condition in which DIN is far more abundant than DIP in April, to a
condition in which the opposite is true in September. When N:P is less
than 15, nitrogen limitation may occur; Figure 19 shows nitrogen becoming
potentially limiting in July. DIN:DIP ratios shown for September are below
2.0 and are among the lowest values reported for the Chesapeake.
Most of the nutrients responsible for the observed enrichment, of
eastern shore tributaries undoubtedly derive from nonpoint source inputs
associated with agricultural runoff. With the cost of fertilizers going
up, more judicious and parsimonious application may occur, reducing
loadings. Increased awareness of minimum tillage practices and wiser land
use may also reduce nonpoint source inputs somewhat. Future nutrient
enrichment problems will result more from population increases and
associated point source loadings than from increases in diffuse sources.
90
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Figure 19. Nitrogen:Phosphorus ratios (dissolved inorganic nutrients only)
in surface and bottom waters of the Choptank River, 1980.
92
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The hypothesis has been advanced that the disappearance of submerged
aquatic vegetation (SAV), once abundant in the shallow waters of the
Eastern Shore and its tributaries, is because of turbidity related reduced
light levels to a point below which SAV can survive. The historical data
base on chlorophyll levels for eastern shore tributaries is consistent with
this hypothesis. Since nutrient loadings to this area of the Bay are
primarily from nonpoint sources, the prospect of controlling enrichment and
associated plant biomass induced turbidities seems poor.
93
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SECTION 5
SUMMARY AND CONCLUSIONS
Chesapeake Bay and its tributaries have undergone increased nutrient
input over the last several decades. The most severe effects of this input
that can be discerned with reasonable assurance have occurred in the.
tributaries. Particularly affected are the low-salinity regions near large
urban centers and sewage treatment facility effluents. Figure 20, taken
from the Heinle et al. (1980) report, gives approximate locations of: the
moderately and heavily enriched areas in the Bay and its tributaries. The
criteria used in developing this figure are as follows: In the low
salinity areas (less than 8 to 12 ppt), pre-enrichment concentrations of
chlorophyll £ were believed, by those authors, to be less than 30 ug L~l;
hence values between 30 and 60 ug L~l during the summer months were taken
to indicate moderate enrichment. Concentrations over 60 ug L~l were
taken to indicate high enrichment. In the high salinity areas (greater
than 8 to 12 ppt), where historical data suggest that concentrations of
chlorophyll rarely exceeded 20 ug L~l during the summer, concentrations
of 20 to 40 ug L~l were considered to represent moderate enrichment;
values exceeding that, great enrichment. Although Heinle et al. (1980)
recognized that chlorophyll levels per se were not necessarily bad, the
relatively great change in chlorophyll concentrations, over apparent
pristine levels, was considered a harbinger of enrichment problems. This
is especially true when the chlorophyll levels, now encountered, represent
the presence of an amount of organic material that when oxidized could
account for depletion of oxygen from the water column in summer months.
Heinle et al. (1980) emphasize that it is excessive oxygen depletion that
most laymen and professionals regard to be the most severe result of
jver-enrichment of natural waters. Oxygen depletion problems in the Bay
are discussed further below, but first some of the important regional
concerns represented in Figure 20 will be summarized.
A good and well-known example of a severely affected location is the
Potomac River near Washington, DC. Although other localities on the Bay
and its tributaries are not yet considered to exhibit such serious symptoms
of over-enrichment, effects of increased nutrient loadings have been
noticed. For example, the upper Patuxent River in Maryland, for which an
excellent historical data record exists, has shown signs of decreased
transparency and increased nutrient concentrations and standing stocks of
algae. The upper James River in Virginia can be considered similarly
enriched.
There is concern in the lower Patuxent River that increased production
of organic matter, as a result of increased nutrient loadings, may
ultimately lead to lower dissolved oxygen concentrations, particularly in
deep water, through the decay of organic matter. But because the nutrient
dynamics and trophic structure of this estuary are riot adequately
understood it is difficult to predict or project through modeling exactly
how the estuary will respond to increased loadings. The GBP's
characterization analysis will discuss these responses further.
The other lightly shaded areas shown in Figure 20, like the lower
Patuxent, are the middle salinity zones that are considered areas of prime
concern. Figure 21 shows portions of Chesapeake Bay where Heinle et: al.
94
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Chesapeake Bay
Region
I
Moderately Enriched I
Heavily Enriched
75! 30'
75TOO'
Figure 20. Map showing portions of Chesapeake Bay that are moderately
or heavily enriched according to the criteria of Heinle et al. (1980)
95
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_ Chesapeake - Bay
Region
SCALE
NAUTICAL MILES
Changes in Dissolved
Oxygen
Figure 21. Map showing portions of Chesapeake Bay where natural regimes
of dissolved oxygen appear to have changed.
96
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felt that worrisome alterations in oxygen regime of the deep water in
particular have apparently occurred in response to enrichment. Yet to be
learned is whether the most important causes of oxygen depletion in these
areas are enhanced productivities in local surface waters, periods of high
freshwater flow and resultant poor vertical mixing and reaeration, or
import and decay of organic material produced upstream. The interaction of
these factors is not completely understood, and the historical data base is
not comprehensive enough to allow us to analyze it adequately. However,
apparent changes in oxygen regime in the mid-Bay must be viewed as
tentative, but probable.
Because too little is presently known to manage the trophic structure
of the Bay to result in increased fisheries yields from additional nutrient
input, sensible efforts to control inputs should continue. The indication
that nitrogen is often limiting in the lower and middle reaches of the Bay
suggests that affordable advanced technologies for N enrichment control
should be sought and given due consideration for implementation. However,
other considerations are important; for instance, it will make little sense
to implement nutrient-removal processes that will ultimately prove too
costly to operate or too complex to manage properly. Workable management
programs for the future will certainly involve better land use practices
and control of nonpoint-source N inputs, particularly in the summer months
when hydraulic residence times are longest. Unconventional or unpopular
sewage treatment processes such as land application may prove important in
controlling enrichment.
Continued scientific evaluation of the trophic structure and of the
nutrient dynamics of the Bay will prove important if we are to assess
adequately future changes and the efficiency of control strategies.
Routine monitoring programs should be adopted and supplemented by more
basic research into effects of enrichment on algal productivity, species
composition, and the natural assimilative capacity of the environment for
nutrients. An inventory of point source inputs should be established and
kept up-to-date. These and other data are useful to environmental
scientists. The partitioning of the carbon, fixed by algal photosynthesis
among species at higher trophic levels, remains a poorly understood but
critical area for research. Dose-response studies, such as those sponsored
by the EPA in Narragansett Bay, Rhode Island, may prove extremely helpful
in this regard. Scientists, modelers, and managers should work closely to
develop models of hydrodynamics and of dose responses to nutrient
addition. This information will help identify gaps in understanding the
Bay's ecology and in locating problem areas.
97
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Haas, L. W. 1977. The Effect of the Spring-Neap Tidal Cycle on the
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Gumming, H. S., W. C. Purdy, and H. P. Ritter. 1916. Investigation of
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Vollenweider, R. A. 1976. Advances in Defining Critical Loading Levels
for Phosphorus in Eutrophication. Mem. 1st. Ital. Idrobiol. 33:53-83.
Webb, K. L. 1981. Conceptual Models and Processes of Nutrient Cycling in
Estuaries. In: Estuaries and Nutrients. B.J. Neilson and L.E.
Cronin, eds. Humana Press. Clifton, NJ. pp. 25-46.
Webb, K. L., and C. F. D'Elia. 1980. Nutrient and Oxygen Redistribution
During a Spring-Neap Tidal Cycle in a Temperate Estuary. Science.
207:983-985.
Wetzel, R., and R. Van Tine. Light and Submerged Macrophyte Communities in
Chesapeake Bay. This volume.
Wolman, M. G. 1971. The Nation's Rivers. Science. 174:905-918.
102
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CHAPTER 2
Nutrient Processes in Chesapeake Bay
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• Jay Taft
The Johns Hopkins University
•Chesapeake Bay Institute
4800 Atwell Road
Shady Side, Maryland 20867
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103
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CONTENTS
Page
Figures 105
Tables 106
Sections
1. Introduction -^QJ
2. Nutrient Availability and Phytoplankton Physiology -Q2
Patterns of Availability -^2
Bay 112
Tributaries -^5
Factors Affecting Phytoplankton Growth and Productivity -,24
Background: The Requirements of PhytoplanKton. . . -124
Response of Phytoplankton to Nutrients , „_
Response of Phytoplankton to Physical Processes . .
Kinetic Measurements of Nutrient Uptake
Summary of These Factors. -, ~o
3. Nutrient Cycling -to/
Introduction -,04
Water Column Processes ^05
Respiration -toe
Grazing . 137
Bacterial Activity . ion
Sediment Processes .
Nutrient Flux
Sorption-Desorption -i .-i
Geochemical Reactions -i AI
Marshes and Bay Grasses •
3. Dissolved Oxygen in the Estuary
Oxygen Sources . -,/o
Oxygen Utilization ,,-,
4. Summary and Conclusions • -•/,-
Literature Cited • 147
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FIGURES
Number Page
1 Map of Chesapeake Bay showing sampled stations 108
2 Binary dendogram showing possible response of the water column
to increased nutrient loadings 109
3 (a) Schematic diagram of the basic nutrient cycle in aquatic
systems, (b) inorganic nitrogen cycle transformations mediated
primarily by bacteria, and (c) interaction of orthophosphate
with iron oxyhydroxides
4 Conservative dilution of nutrient from the Susquehanna River
with low nitrate seawater 113
5 Nutrient distributions in the main portion of Chesapeake Bay. . 114
6 Distribution of ammonium along a transect at (a) 38°34'N,
(b) 38023'N, and (c) 38°18'N 116
7 Salinity in the Potomac River 119
8 Dissolved oxygen in the Potomac River 120
9 Chlorophyll a_ in the Potomac River 121
10 Nutrients in surface water of the Potomac River 122
11 Suspended sediment in the Potomac River 123
12 Nitrogen and phosphorus content in Chesapeake Bay 127
13 Flux of particulate organic carbon through Chesapeake Bay . . . 130
14 Phosphate uptake kinetics for a natural phytoplankton
population 131
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TABLES
Number Page
1 Half-Saturation Values and Maximum Uptake Velocities for
Nutrients in Chesapeake Bay .................. 132
2 August Respiration and Regeneration Rates for Total Plankton,
Plankton Passing through Mesh, and Plankton Passing through
Filters ............................ 136
3 February Respiration and Regeneration Rates for Total
Plankton Samples ..... .................. 136
4 Phytoplankton Grazers and Percent Daily Phytoplankton
Production Used ........................
5 Ammonium and Phosphate Flux from Chesapeake Bay Sediments . . . 140
106
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SECTION 1
INTRODUCTION
A principal characteristic of Chesapeake Bay (Figure 1) is that, like
other partially mixed estuaries, its two-layer circulation pattern enhances
the retention of nutrients. Although the flushing time for water in
Chesapeake Bay is about one year (based on the basin volume and annual
river flow), nutrients are not flushed out to sea in direct proportion.
Instead, soluble nitrogen and phosphorus are incorporated into particles,
such as phytoplankton, which sink from the seaward-flowing, surface water
into the landward-flowing, deep water. In this way, nutrients entering
from the tributaries are carried part way down the estuary, sink toward the
bottom, and are carried back upstream. This accumulation phenomenon is the
mechanism for desirable, high production on the one hand, and undesirable,
over-enrichment on the other.
This chapter deals with the shaded portion of the binary diagram in
Figure 2. In this portion, dissolved nutrients become particulate (biotic
component). (Abiotic particulate nutrients, such as phosphate flocculants,
are not discussed in this chapter.) The dissolved, and biotic particulate
nutrient compartments are expanded in Figure 3a to show the different
categories of dissolved and particulate constituents that will be discussed
in the following sections. The soluble forms of inorganic nitrogen and
urea are illustrated in Figure 3b. The transformations among these
constituents are generally mediated by bacteria, but all four forms may be
taken up and utilized by phytoplankton in Chesapeake Bay (McCarthy et al.
1977). Inorganic phosphorus, on the other hand (Figure 3c), is present
primarily as orthophosphate, which may interact with adsorbing minerals
such as iron oxyhydroxides under certain chemical conditions (Taft and
Taylor 1976a).
This chapter has three purposes. First, it is intended to acquaint the
non-scientist with fundamental concepts of the major estuarine processes
related to water quality. Second, it illustrates the concepts with data
from Chesapeake Bay or its tributaries. Finally, it relates the processes
to management concerns with the hope that decision-makers will gain insight
into the relations between water quality, the controlling estuarine
dynamics, and potential management options.
The uptake of nitrogen and phosphorus by phytoplankton is a major
pathway in the nutrient retention scheme in Chesapeake Bay. For this
reason, Section 2 will discuss pertinent details of phytoplankton
physiology, including patterns of nutrients available to phytoplankton and
factors affecting their growth and productivity.
Another major pathway, also discussed in Section 2, is phytoplankton
consumption by zooplankton. Zooplankton recycle some of the nutrients in
the phytoplankton back into the water, assimilate some into body tissue,
and release the remainder as particulate material which sinks to the
bottom. This material, comprising detritus, is colonized and further
degraded by bacteria, forming a third pathway that returns nutrients to
deep water flowing back upstream. Nutrient recycling from the organic
forms to the soluble inorganic forms requires oxygen utilization. Section
3 discusses oxygen sources and plankton respiration rates in relation to
nutrient retention and recycling.
107
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Figure 1. Map of Chesapeake Bay showing western shore tributaries
and stations routinely sampled for biological and chemical
data.
108
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Since the readership of this paper may vary from citizen to scientist,
the format will try to accommodate a range of technical expertise. The
indented sections explain, in less technical terms, important concepts the
reader should understand. The concepts are illustrated as much as possible
with data from the Chesapeake Bay estuarine system.
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SECTION 2
NUTRIENT AVAILABILITY AND PHYTOPLANKTON PHYSIOLOGY
PATTERNS OF NUTRIENT AVAILABILITY
Open Bay
The annual nutrient cycle in Chesapeake Bay is marked by three
prominent events. The first is the substantial nitrate input with winter
and spring runoff from the Susquehanna River (Carpenter et al. 1969). The
source of nitrate in the runoff is partly ground water and partly
atmospheric. Rain and snow contain nitrate concentrations of up to
one-third to one-half those in the runoff (Smullen 1982). Dilution in the
upper Bay (Figure 4 and Figure 5) followed by phytoplankton uptake in the
mid- and lower Bay depletes this nitrate from about 40 to 100 ug atom L~l
to less than one ug atom L~* by midsummer. Figure 4 shows how nitrate is
depleted toward the Bay mouth; Figure 5 shows its seasonal presence. The
bottom diagram shows nitrate present in May, but undetectable in August
(not shown in Figure). In contrast to the heavy input of nitrate,
orthoposphate is undetectable throughout spring (top diagrams).
The second important event occurs during midsummer when very low oxygen
concentrations in deeper Bay water permit release of phosphate and
accumulation of both phosphate and ammonium there ('raft and Taylor 1976a,
1976b). Some of these nutrients are transported by diffusion and advection
to the upper layers where they are incorporated into phytoplankton. The
annual maximum for total phosphorus in the surface layer of the Bay usually
occurs in summer, because phosphorus availability is greatest then.
However, not all of the deep water phosphorus reaches the upper layer. New
information suggests that some phosphorus may be precipitated by iron-rich
minerals at the boundary between the upper and lower water layers (Figure
3c). This natural control of phosphorus at the boundary may, at times,
prevent all of the nutrient from being available to the many non-motile
phytoplankton. Strong swimmers such as the dinoflagellates, however, may
migrate down to the nutrient-rich layer at night and up into the sunlight
during the day. As a result, their growth is not limited by phosphorus
availability.
The third event is the fall nitrite maximum observed in both mid-Bay
(McCarthy et al. 1977) and in the lower Potomac River estuary (Taft,
unpublished data). At present, ammonium oxidation appears to be the most
probable mechanism to explain these observations (Figure 3b). An
experiment was conducted as part of the Chesapeake Bay Program to measure
the rates of this important process; results are discussed in Section 3.
Although several studies have examined the longitudinal (vertical)
nutrient distributions in the Bay, none have explored the lateral
distributions. Since lateral integration of parameters is a common feature
in one and two dimensional models, it is necessary to show that lateral
changes are small compared to longitudinal, or vertical changes. When such
lateral measurements were made during April, 1977 they revealed an
interesting picture. A layer of ammonium was observed at mid-depth (Figure
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6), extending over much of the northern half of the Bay. This feature was
not observed during subsequent summer and winter cruises. At present, the
best explanation is that ammonium-enriched deep water is displaced westward
and upward by sea water, flowing in along the bottom on the eastern shore.
This view is particularly well supported by Figure 6a in which the maximum
value of nine ug atom NH^-N L~^ is found on the bottom along the
eastern shore sill (station #834A), but is at mid-depth in the eastern
channel (station 834C) where it has been displaced upward. Thus, this
action pushes nutrient-rich water upward to the photic zone where it is
available to phytoplankton.
Tributaries
The Potomac River was selected as a representative tributary because of
the extensive data on nutrient processes available. The analogue between
the Potomac and Bay is further described in the forthcoming
"Characterization of Chesapeake Bay" report. The patterns of nutrient
availability in the Potomac River have been studied extensively for the
last 20 years. This interest was stimulated by the necessity to discharge
sewerage from Washington, DC into the river near the head of tide.
Carpenter et al. (1969), Jaworski et al. (1972), McElroy et al. (1978), and
others have examined nutrient dynamics and budgets. Najarian and Harleman
(1977) and Najarian and Taft (1981) have modeled nitrogen dynamics using
data from the Potomac. Much of the following discussion is true not only
for the Potomac, but for the main Bay.
The Potomac River is somewhat similar to the main Bay with respect to
the availability of nutrients. The lower Potomac displays the same summer
release of phosphorus and the fall nitrite maximum (Taft, unpublished data)
as described for the main Bay. There is not the same extensive spring
nitrate influx, however. The sewage effluent from the Blue Plains
Treatment Plant is a major source of nutrients to the Potomac; its effect
on the availability of nutrients in the Potomac is discussed in the
following paragraph.
Data are presented here for June 1977 to orient the reader; this is not
intended as a comprehensive treatment. Figure 7, Figure 8, and Figure 9
show longitudinal distributions of salinity, dissolved oxygen, and
chlorophyll £ in the Potomac River. Figure 10 depicts surface nutrient
concentrations. Ammonium entering the river from the Blue Plains Sewage
Treatment Plant is diluted as it moves downstream but is also oxidized to
nitrite and then to nitrate. The nitrite peaks at mile 80, and the nitrate
peaks slightly farther downstream from there. Thus, nitrogen from Blue
Plains is detectable in one form or another for 30 miles from the
discharge. Phosphate, likewise, was detectable from mile 90 down to mile
60. However, unlike the nitrogen forms, phosphate increased again in the
turbidity maximum region of the river, possibly because of release from the
sediments (Boynton et al. 1980). The location of the turbidity maximum, a
region where sediment and associated phosphate is continually resuspended,
is shown in Figure 11, between river miles 55 and 65.
115
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FACTORS AFFECTING PHYTOPLANKTON GROWTH AND PRODUCTIVITY
Background: The Requirements of Phytoplankton
Phytoplankton photosynthesis, or primary productivity, requires
adequate light and nutrients. These nutrients stimulate phytoplankton
growth which, in turn, supports the remarkable productivity characteristics
of Chesapeake Bay. Phytoplankton growth occurs as a result of
photosynthesis, the process by which phytoplankton use light to produce
energy-rich molecules that are used, in light or dark, to convert carbon
dioxide to carbohydrates and oxygen.
Concept: Nutrient Limitation
The nutrition of higher trophic-level organisms in Chesapeake Bay
ultimately depends on the phytoplankton and, to a lesser extent, on the
macrophytes. The availability of nutrients, in turn, regulates! plant
standing crop, or biomass. The notion that standing crop could be
regulated by a single factor was expressed in 1840 by Justis Liebig,
who stated that "growth of a plant is dependent on the amount of
foodstuff which is presented to it in minimum quanity" (quote from Odum
1971).
In other words, a plant needs a certain amount of nitrogen and a
certain amount of phosphorus to grow at the maximum rate. If nitrogen
is scarce, but phosphorus is abundant, growth is nitrogen-limited. If
the reverse is true, the plant is phosphorus-limited. For maximum
growth, both elements in their correct proportions are needed.
Nutrient regulation of phytoplankton standing crop in Chesapeake Bay is
established by the natural annual cycles in nutrient inputs from the
rivers, direct land runoff, and the sediments. Minimum phosphorus
availability occurs during spring and fall in the main portion of the
estuary. Thus, natural cycles cause the limiting nutrient to change
over the year.
Although photosynthesis requires nutrients, it appears that the
specific rate of primary productivity of the biomass is not directly
influenced by nutrient concentrations, because high productivity often
coincides with low inorganic phosphorus and nitrogen concentrations in the
euphotic zone. The rate may be influenced more by intracellular nutrient
pool size and nutrient supply rates from external sources (tributaries,
sediments, recycling) than by extracellular concentration.
Although biomass is nutrient-regulated in the sense of Liebig's
statement, the specific rate of primary productivity of the biomass is not
controlled by the nutrient concentrations found in the water. Instead,
primary productivity is directly regulated by intracellular nutrient pools,
and, of course, light. The rate of internal nutrient replacement is
controlled primarily by the rate of nutrient supply to the environment, the
recycling rate. Even under conditions of nutrient limitation of
phytoplankton biomass, recycling supports a healthy, productive ecosystem.
Nutrients recycled in the water column may be considered as
"regenerated." Those recycled in the sediments and those entering from the
land may be considered as "new," since they are being added to the water
column. Comparison of nutrient flux estimates with productivity indicates
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that "new" nutrients could significantly support phytoplankton productivity
north of 39°N latitude (Chesapeake Bay Bridge) because of their greater
relative availability. "New" nutrients are less available and, thus, have
diminished importance to the south, where recycling seems to be the
dominant process providing nutrients for phytoplankton primary
productivity. "New" nutrients provided primarily by benthic biological and
chemical activity may have the dominant role in supporting phytoplankton
biomass increases in Chesapeake Bay as a whole.
In summary, the potential for phosphorus limitation in the tidal fresh
regions of Bay tributaries exists throughout the year. This is because
blue-green algae, common in fresh water, can utilize nitrogen gas, so that
nitrogen cannot become the limiting nutrient. The term "potential" is
used, because light may also limit biomass in high turbidity regions.
Phosphorus is limiting to biomass in the main portion of the Bay during
spring and fall. Nitrogen is limiting in summer. In winter, light or
phosphorus may be the limiting factor depending on inflow and cloud cover.
Concept: Regulation of photosynthesis by light
In the presence of adequate nutrients, photosynthesis is controlled
by both light quantity and quality. The net rate of photosynthesis is
not constant, even during daylight hours. Different organisms seem to
maximize photosynthetic efficiency during different times of the day.
This means that results of experiments designed to determine the
photosynthetic rate are influenced by light quantity, by light quality
as effected by scattering and absorption in the water, and by time of
day.
How Phytoplankton Respond to Nutrients
Occasionally, the production of phytoplankton biomass sufficiently
exceeds its loss through sinking, grazing, and flushing to permit algal
biomass accumulation in the main portion of the estuary (Loftus et al.
1972). But most of the year, phytoplankton standing crop falls in the
range of five to 30 ug chl £ L~l, with the higher numbers in the upper
layer during cold weather. Phytoplankton nutrition, as indicated by
particulate C:N:P atom ratios, reflects seasonal changes in nutrient
dynamics.
Concept: Particulate Nutrient Ratios
Well nourished phytoplankton contain optimum amounts of the
nutrient elements, carbon, nitrogen, and phosphorus. Field and
laboratory experiments indicate that the ratio of atoms of these
elements under optimum conditions, is approximately 106 atoms carbon to
16 atoms nitrogen to one atom phosphorus. This specific configuration
is called the Redfield ratio after the oceanographer who first
suggested it as a characteristic of well-nourished phytoplankton cells
(Redfield et al. 1963). Departures from the Redfield ratio provide
information about depleted intracellular nutrient stores.
Particulate samples collected on 12 Chesapeake Bay Institute (CBI)
cruises in the main Bay during 1972 to 1976 give particulate N:P atom
ratios in spring usually between 30:1 and 45:1, suggesting phosphorus
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deficiency with respect to phytoplankton nitrogen. Some of these data are
depicted in Figure 12. The rate of organic phosphorus utilization by
phytoplankton, a response to inorganic phosphorus deficiency, also peaks in
spring, supporting this interpretation (Taft et al. 1977). In summer most
N:P ratios drop below 30, and organic phosphorus degradation is reduced.
The atom ratio of ammonium nitrogen to phosphate-phosphorus in the deep
water is about four to one (Taft and Taylor 1976b), and the soluble
nitrogenous nutrients in the euphotic zone are insufficient to allow the
biomass of the phytoplankton present to double (McCarthy et al. 1975).
This evidence suggests that the biomass of phytoplankton is controlled by
nitrogen in summer — a shift from the spring situation of biomass control
by phosphorus.
In a nutrient-limited system, phytoplankton biomass is controlled by
the concentration of nutrients (assuming grazing, flushing, and sinking do
not occur). Phytoplankton productivity, however, appears to be fairly
independent of nutrient concentration. Thus, although the rate at which an
individual phytoplankter is productive is relatively independent of
nutrient concentration, increase in population biomass does depend
primarily on nutrient concentration.
A relationship between phytoplankton productivity and nutrient
concentration in the Bay is fairly difficult to demonstrate for several
reasons. First, the highest production rates coincide with very low
extracellular concentrations of one or more nutrients. In contrast to
Fournier's (1966) results for the lower York River, adding nutrients
singly, or in combination usually failed to stimulate primary productivity
in experimental incubations with natural Chesapeake Bay phytoplankton
assemblages (Taylor and McCarthy 1972). Second, phytoplankton exhibit
preferences for certain forms of nutrients over others.
Concept: Nutrient Preferences
It is energetically advantageous for a cell to take up reduced
nitrogen in the ammonium form, because it can be incorporated into
amino acids and proteins directly. At ammonium concentrations below a
threshold value, usually 1.0 to 1.5 ug-at L~l, oxidized nitrogen as
nitrite and nitrate are taken up as well (McCarthy et al. 1975, 1977).
The cell must expend more energy to reduce these ions to ammonium, but
the expenditure is justified. Similarly, phytoplankton incorporate
orthophosphate alone until concentrations fall below threshold. Then
cells degrade simple organic phosphates to supplement cellular
phosphorus nutrition. Convincing evidence indicates that, because of
phytoplankton preferences, much of the nitrate entering in spring from
the Susquehanna River passes through the upper Bay, because ammonium
concentrations are above threshold, to be utilized in the lower Bay
where ammonium concentrations are below threshold. The abundance of
nitrogen allows orthophosphate concentrations to drop below threshold,
and degradation of simple organic phosphates to be stimulated.
Ammonium is selected preferentially over nitrate. Although the
orthophosphate ion is generally the phosphorus source preferred by
phytoplankton, some species will grow equally well in culture with an
organic mono-ester as the phosphorus source (Kuenzler 1965; Taft,
unpublished data). However, like orthophosphate, mono-ester concentrations
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usually approach detectability limits; no transition concentration (as
exists for preferred nitrogen species) is obvious for preferred phosphorus
species.
Third, if nutrient concentrations do exert a regulating influence on
carbon fixation, it most likely occurs intracellularly near the enzyme
systems affecting final nutrient utilization. As one nutrient molecule is
removed by enzyme activity from the substrate pool, it could be replaced
from the dilute extracellular medium to retain necessary high
concentrations near the enzyme. This hypothesized sequence leads to the
notion that coupling between carbon incorporation rates and nutrient
incorporation rates should be very close; this does occur under conditions
of high productivity (growth rate) and low nutrient concentrations in
chemostats.
When growth rates are low, carbon fixation and nutrient uptake may
become uncoupled. Eppley and Renger (1974) observed (for the diatom
Thalassiosira pseudonana) increased maximum uptake velocities for nitrate
and ammonium as growth rate decreased. Orthophosphate uptake by P
deficient phytoplankton is frequently much more rapid than short-term
growth in culture (Ketchum 1939) or photosynthetic rate in Chesapeake Bay
(Taft et al. 1975). The potential for one phytoplankter to incorporate
nutrients rapidly at low external concentration leads to the conclusion
that nutrient uptake should never be concentration-limited (Kuenzler and
Ketchum 1962). Inability to demonstrate continuous, close-coupling between
carbon fixation and nutrient uptake, and elimination of the phosphate and
ammonium uptake steps as productivity regulating factors, also complicates
direct demonstration of nutrient regulation of phytoplankton primary
productivity.
These observations lead us to conclude that neither ambient nutrient
concentrations, nor increased uptake potential resulting solely from
elevated nutrient concentrations, have Bay-wide significance in regulating
open water phytoplankton productivity. Therefore, static measurements of
nutrient concentrations and other water quality parameters do not convey
enough information about the dynamic events taking place. Optimal water
quality management requires information about processes and their rates.
How Phytoplankton Respond to Physical Processes
Concept: Phytoplankton are Distributed Unevenly in Space and Time
The term "phytoplankton" implies a plant cell that has limited
mobility; it is transported more by water movement than by swimming.
The most advantageous use of swimming by phytoplankton is exhibited by
the dinoflagellates that can travel vertically,. In the two-layered
estuary, they have the capability to move from the seaward-flowing
surface layer to the landward flowing deep layer and, thus, sta.y in the
estuary. They can also migrate from nutrient-poor, surface water to
nutrient sources in the deep water or sediments. Weaker swimming
organisms and those, such as diatoms, which don't swim at all, depend
on buoyancy and water movement to keep them in a suitable environment.
The interaction of phytoplankton buoyancy or swimming with water
motion produces a spatially patchy distribution of organisms. The
upward motion of cells against downward-flowing water can result in the
accumulation of organisms near the surface of a so-called frontal
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region. Growth of surface organisms can be stimulated by the upward
motion of nutrient-rich deep water to the surface, so that biomass
increases in one area relative to nearby regions where such motion does
not exist.
Spatial distribution is also influenced by salinity of the water.
Some species can adapt to a wide range of salinities and may be found
throughout the estuary. But many riverine and marine forms have very
narrow salt tolerances so their occurrence is limited.
The temporal distribution of phytoplankton species depends
primarily on water temperature; some are considered summer species, and
others are winter species. If both temperature and salinity regimes
are acceptable, the organisms survive long enough to be transported by
circulation.
The use of phytoplankton distributions as indicators of water movement
has been demonstrated as a useful technique in Chesapeake Bay. Moreover,
the significance of coupling between phytoplankton ecology and physical
processes in the estuary has been clearly established for one
dinoflagellate species (Tyler and Seliger 1978). This research
reemphasizes the necessity of examining estuarine processes in detail to
understand the system. Further, research indicates that the tributaries
are very important sources of phytoplankton that may achieve local
numerical dominance, and in some cases, biomass dominance in the main
portion of Chesapeake Bay. Thus, the ecology of these organisms is closely
coupled to physical processes in the estuarine system.
Movement of phytoplankton through the estuary can be roughly estimated
using a box model with particulate organic carbon (POC) representing the
phytoplankton. Figure 13 shows the flux estimates for (a) February, (b)
May and (c) August 1975, and (d) February 1976. Units are 1C)5 Ug atom C
sec~l. Net POC flux was greater during the two winter periods. Vertical
transport of phytoplankton was dominated by upward movement over much of
the Bay. This upward movement was due to minimum stabilization of the
water column, which created high potential for mixing both salt ions and
particles upward from the deep layer. The source and sink terms, shown in
small boxes, represent nonconservative gains and losses of POC such as
growth, grazing, sinking, and disruption. The net values of these
processes were also higher over most of the Bay during winter than during
spring or summer. This information can help locate areas and times of high
activity that would, subsequently, increase phytoplankton biomass.
Kinetic Measurements of Nutrient Uptake by Phytoplankton
Environmental biologists began making kinetic measurements of nutrient
uptake by phytoplankton to obtain physiological information and predict
changes in species composition from changes in nutrient concentrations.
Nutrient uptake by phytoplankton proceeds at rates that are concentration-
dependent. Uptake rate increases with increasing concentration up to some
maximum rate, beyond which it is constant regardless of concentration
(Figure 14). The relation between substrate concentration and uptake rate
is usually expressed mathematically as a rectangular hyperbola. Two
characteristic parameters of this form are the half saturation value (Ks)
and the maximum uptake velocity (Vmax). Rs is the substrate
129
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0
Figure 14. Phosphate uptake kinetics for a natural phytoplankton
population containing primarily one dinoflagellate species.
131
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concentration at which uptake velocity reaches one-half the maximum rate.
In this way, nutrient uptake is treated as an analog of enzyme kinetics,
reflecting the participation of enzymes and carrier molecules in the uptake
process.
Concept: Kinetic Parameters are not Constant
The kinetic parameters Ks and Vmax are coefficients used in
mathematical models. However, they should not be considered
"constants" because they are subject to variation, even within species,
depending on environmental conditions, the organisms' recent history,
and the types of organisms present in a natural population. Kinetic
parameters determined with pure cultures can be employed in models of
natural systems if the modeler recognizes that a factor of ten range in
the values is not unusual. Table 1 shows the range of Ks and Vmax
values observed in Chesapeake Bay and Potomac River. These ranges
indicate differences in phytoplankton physiology. As the table shows,
nitrogen values can vary by a factor of two or more.
TABLE 1. HALF-SATURATION VALUES (Kg) AND MAXIMUM UPTAKE VELOCITIES
(vmax) F°R NUTRIENTS IN THE CHESAPEAKE BAY ESTUARINE SYSTEM
Nutrient Ks Vmax
ug atom-L ug atom chl a
Chesapeake Bay
Phosphate 0.09 to .172
Ammonium 1 to 2
Nitrate 2 to 4
0.004 to 0.160
Potomac River
Phosphate 0.2 to 0.4 0.0005 to 0.0015
Ammonium 1.5 to 1.7 0.003 to 0.017
Nitrate 1.2 0.005 to 0.039
Ks and Vmax are often considered constants for a particular
phytoplankton species for mathematical modeling purposes and for comparing
one species with another. Ks is an indicator of the affinity between the
nutrient and the cell's uptake system; the smaller Ks, the greater the
affinity. It has been a popular concept that a species with a lower Ks
can dominate when nutrient concentrations are low because of greater
affinity for the nutrient; a species with higher Ks can dominate only
when nutrients are high. As a generality, this concept is acceptable.
However, Ks is not a true constant. Modifications in the uptake system
or the membrane to which it is bound on the cell alter Ks. Such
modifications may be related to the relative amounts of saturated and
unsaturated lipids in the cell membrane, to the cell's immediate history,
and to the intracellular nutrient supply. Similarly, Vmax is not a true
constant. It may be changed by membrane alterations or changes in the
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number of uptake sites per cell. Since these kinetic parameters are not
constant, predictions of species shifts with changes in nutrient
concentrations have had limited success. At best, shifts between green and
blue-green algae in fresh waters can be described based on nutrient loading
ranges. Resolution beyond this remains to be developed.
It is possible, however, to describe a hypothetical relationship
between nutrients and commercial species based upon results from culture
experiments with a variety of organisms. From these experiments, it is
known that not all phytoplankton species have equal nutritional value for
the planktivores that graze them. High diversity of phytoplankton species,
in a natural population favors a balanced diet for the grazers.
Modifications of the nutrient regime, which cause species shifts and reduce
population diversity, may increase the potential for deficiencies in the
grazer diet. Thus, the yield of filter-feeding commercial species, such as
oysters and menhaden, could be influenced indirectly by nutrient inputs to
the system.
Summary
In summary, the best Bay management requires an understanding of the
major processes affecting growth and reproduction of phytoplankton because
the ecology of phytoplankton is closely coupled to physical processes of
the estuary. These influences include the effect of light, nutrients, and
physical and chemical processes on phytoplankton, and how quickly
phytoplankton assimilates nutrients.
In the presence of adequate nutrients, photosynthesis is regulated by
light. Specifically, the quality and quantity of light affect the rate of
photosynthesis in phytoplankton. However, in a nutrient-limited system,
such as the Bay, the presence of P or N in the smallest amount regulates
phytoplankton standing crop. Phosphorus is limiting in the main Bay in
spring and fall, with N limiting during summer. In winter, light or P can
be the limiting factor. The availability of these nutrients is controlled
by the recycling rate, or the rate of nutrient supply to the environment.
"New" nutrients, or those recycled in the sediments and entering by land,
provide the major source to phytoplankton and probably are the causes of
increases in biomass of Chesapeake Bay as a whole.
The uneven distribution of phytoplankton in the Bay results from their
responses to physical and chemical processes. Mobility of some
phytoplankton species enables them to overcome circulation patterns. They
can move vertically between layers of the Bay and migrate to nutrient-rich
areas. Circulation of the Bay brings, to certain areas, upward-moving,
rich waters; in these areas, growth of surface phytoplankton is
stimulated. Salinity limits the distribution of some phytoplankton, but
others dependent on water temperature will only persist at certain times of
the year.
Measuring the rate of nutrient uptake by phytoplankton can indicate
species shifts in phytoplankton and consequences on organisms higher in the
food chain. A certain species of phytoplankton with a slow uptake rate
will produce less biomass in a given time than a phytoplankton with a
faster uptake rate. The latter species would dominate, perhaps causing a
bloom. Diversity in phytoplankton favors a balanced diet for grazers,
which may ultimately influence the yield of filter-feeding Bay resources
such as oysters and menhaden.
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SECTION 3
NUTRIENT CYCLING
INTRODUCTION
The flow rate of nutrient molecules through remineralizing processes to
the inorganic forms may be an important factor regulating productivity.
These recycling processes include (1) grazing of the phytoplankton standing
crop by macro- and micro-zooplankton, followed by nutrient release through
excretion or heterotrophic bacterial activity; (2) activity of free-living
aquatic bacterial heterotrophs; (3) nutrient release from the sediments by
both biological and chemical processes; and (4) nutrient transport by
physical processes into contact with phytoplankton able to assimilate the
nutrient.
The basic elements in a living system are carbon, oxygen, hydrogen,
nitrogen, and phosphorus. Carbon, oxygen, and hydrogen are readily
available to plants in the biologically usable compounds, oxygen gas,
carbon dioxide, bicarbonate ion, and water. Nitrogen and phosphorus,
however, are not so abundant in a useable form. The cycling of these
nutrients in surface waters from the dissolved inorganic form to the living
form and back to the dissolved inorganic form, is the mechanism by which
the photosynthetic conversion of the more abundant elements into
metabolically useful compounds is maximized in the aquatic environment.
About 90 percent of the primary productivity in Chesapeake Bay is
accomplished by planktonic algae that pass through a 35 um mesh (McCarthy
et al. 1974). These organisms are the principal food of zooplankton in the
Bay, which become food for higher organisms. Studies of the larger
zooplankton in Chesapeake Bay reveal that 50 to 70 percent of the animals
caught on 103 um mesh are copepods of the genus Acartia (Rupp 1969).
Acartia tonsa is also abundant in the Patuxent River estuary (Heinle
1966). Copepods of the genus Eurytemora are seasonally abundant and are of
the same size as Acartia.
Previous studies reveal that grazing macro-zooplankton (adult copepods)
consumed only about 10 percent of the daily phytoplankton productivity in
Chesapeake Bay (Storms 1974). Therefore, the role of micro-zooplankton in
grazing phytoplankton and in returning nutrients to the water was
examined. It now appears that the most significant role of the
micro-zooplankton is to respond, through rapid growth, to graze blooms of
phytoplankton that occur periodically in the Bay (Heinbokel, unpublished
data). Data are now becoming available on protozoa and metazoa, that are
smaller than the common copepods. As a group, the zooplankton inhabiting
the estuary south of the Bay Bridge play a major role in regenerating
nitrogen and phosphorus to meet the requirements of the phytoplankton on
which they feed.
Concept: Nutrient Cycling
Nitrogen and phosphorus are converted from the inorganic, to
living, organic forms and back again on varying time scales in the
Chesapeake Bay estuary. For simplicity of illustration, here, the time
scales are divided into short-term (minutes to weeks) and long-term
(months to years). It is also convenient to conceptualize that short-
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term cycling occurs primarily in the water and the surface sediments
and long-term cycling takes place primarily in the deep sediments (more
than two cm below the surface).
WATER COLUMN PROCESSES
Respiration
Respiration rate is measured as the rate of oxygen consumption of a
water sample incubated in a darkened container. It is possible, by
measuring the plankton respiration rate accurately and precisely, to
estimate C, N, and P regeneration in the water column, using a suitable
respiratory quotient and particulate C:N:P ratio.
Results presented here are from two experiments at natural plankton
densities performed by Dr. Eric Hartwig with a sensitive photoelectric
oxygen titrator. A suitable respiratory quotient (RQ) must be used to
convert oxygen consumption to the amount of organic carbon degraded. The
respiratory quotient is the ratio of carbon dioxide produced to oxygen
consumed by an organism. Commonly determined RQ values range from 0.27 in
an intertidal sand flat to 1.6 for Chlorella using nitrate as the nitrogen
source (Teal and Kanwisher 1961, Pamatmat 1968). For the purposes of this
report, an RQ of 0.85 will be assumed, with the realization that deviation
in RQ of +_0.20 encompasses most RQ measurements found in the literature and
yields a +25 percent variability, which is within acceptable limits. The
incorporation of C:N:P atom ratios, into the calculation, yields estimates
of inorganic nitrogen phosphorus regeneration rates. The atomic ratio of
Redfield et al. (1963) (106 C to 16 N to 1 P) will be used.
The winter respiration rates given in Table 2 and Table 3 were 63
percent of the summer rates (August). The water temperature difference
between February and August was approximately 25oc (77°F). If the
respiration rate of the organisms present doubled for each 10°c (50°F)
temperature change (Q10 = 2), the February rates would only be 20 percent
of the August rates, other factors being equal. This implies that the
thermal regime of Chesapeake Bay exerts a selection pressure on microbial
communities so that bacterial species change during the year as the
temperature changes. Temperature changes of the magnitude existing in
Chesapeake Bay were found by Sieburth (1967) to cause shifts in the thermal
types of microbes present in Narragansett Bay, Rhode Island. Thermal
selection of bacterial species, adapted to either warm or cold
temperatures, may be a factor permitting maximum utilization of organic
substrates throughout the year.
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TABLE 2. AUGUST RESPIRATION AND REGENERATION RATES FOR TOTAL PLANKTON (TP),
PLANKTON PASSING THROUGH 35 urn MESH (*35 urn) AND PLANKTON PASSING
THROUGH 3 urn FILTERS «3 urn)
Station
904N
853F
834G
818P
744
7070
Potomac
Estuary
Estimated Estimated
Respiration rate N regeneration rate P regeneration rate
ug atom 02 ug atom N Ug atom P L"1
Sample L~l h"1 L^tT^-xlO"1 h'^-xlO'2
Surface TP
7m TP
Surface TP
<3um
6m TP
Surface TP
Surface TP
Surface TP
<35 urn
< 3 urn
Surface TP
10 m TP
Surface TP
< 3 urn
4.9
5.2
3.4
2.7
7.1
4.6
3.6
4.6
4.1
2.3
2.4
2.1
2.5
1.2
6.3
6.7
4.4
3.5
9.1
5.9
4.6
5.9
5.3
3.0
3.1
2.7
3.2
1.5
3.9
4.2
2.7
2.2
5.7
3.7
2.9
3.7
3.3
1.8
1.9
1.7
2.0
0.96
TABLE 3. FEBRUARY RESPIRATION AND REGENERATION RATES FOR TOTAL PLANKTON
SAMPLES
Estimated Estimated
Respiration rate N regeneration
Station
904N
834G
804C
744
7070
Calvert
Cliffs
Nuclear
Depth
2m
2m
lira
2m
9m
4m
20m
2m
10m
1m
10m
Intake
Discharge
ug atom 02
L-lh-lxlO-3
2.1
2.5
0.85
3.3
1.3
2.3
1.4
1.7
1.3
3.5
2.8
1.3
2.2
ug atom N
L-J-h-lxlO-1
2.7
3.2
1.1
4.2
1.7
3.0
1.8
2.2
1.7
4.5
3.6
1.7
2.8
rate P regeneration rate
ug atom P L~l
h-lxlO-2
1.7
2.0
0.68
2.7
1.0
1.9
1.1
1.4
1.0
2.8
2.3
1.0
1.8
Power Plant
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An important aspect of the water-column-nutrient-regeneration rate
concerns its coupling with the nutrient supply required for primary
productivity. Estimates of upper Bay productivity values for August [4 ug
atom C(L-h)-i] and February [0.6 ug atom C(L'h)"1] (Taylor,
personal communication), with a C:N:P assimilation ratio of 106:16:1, yield
a requirement for 0.6 ug atom N (L-h)~l and 0.04 ug atom P (L-h)~l
in August and a requirement for 0.09 ug atom N (L-h)~l and 0.005 ug
atom P (L-h)-l in February. Table 2 and Table 3 show estimates of
regenerated N and P, based on respiration measurements (Taft et al. 1980).
These data indicate that respiration could regenerate most of the nutrient
requirement for the upper Bay (stations 904N, 853G, 818P, 804C) in August,
and an excess of nutrients in February. As a result, addition of further
nutrients in August would increase biomass, but addition of nutrients in
February would result in nutrient accumulation in the water column.
Grazing
Grazing is the process by which herbivores, such as copepods, consume
primary producers (phytoplankton). The grazers in Chesapeake Bay span the
range from small ciliates, to rotifers and copepods, all the way up to
crustacean and fish larvae, and adult planktivorous fish such as menhaden.
The ecological role of these grazers is to transfer the organic material
and energy fixed by the phytoplankton through the food web. The grazers
themselves are consumed by higher predators such as the carnivorous fishes,
waterfowl, and humans. Grazing keeps estuaries in balance by restricting
phytoplankton populations.
However, not all of the primary production is assimilated into
animals. Some nutrients are released back into the water, directly by
excretion, or indirectly, by bacterial degradation of dead cells or animal
fecal material. In this way, the grazers help keep the estuary productive
by grazing the phytoplankton standing crop and supplying nutrients for
continued phytoplankton growth (Table 4). Thus, nutrients entering the
estuary are distributed throughout the food web and may be cycled through
the planktonic ecosystem several times each year. One of the major goals
of biological studies in Chesapeake Bay is to quantify recycling rates,
including the contributions from grazers.
TABLE 4. THE MAJOR PHYTOPLANKTON GRAZERS AND PERCENTAGE OF DAILY
PHYTOPLANKTON PRODUCTION USED
Animal percent daily phytoplankton production used
Copepods up to 15
Microzooplankton 15
Other 70
larval stages of small biota
planktivorous fish
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Copepods—
Copepods are small crustaceans inhabiting the estuary. Common species
are Acartia, Eurytemora, Temora, and Centropages. Copepods have, a somewhat
complex life cycle. Like most crustaceans, they exhibit several life
stages from nauplius to copepodite to adult. All of these stages graze
phytoplankton. The grazing may be accomplished by encounter feeding,
active hunting of single cells, and filter feeding. The adults have
specialized feeding appendages that sweep through the water, directing the
phytoplankton cells to the mouth. Some copepods seem to graze selectively
upon particular size cells, especially if one size range contains a large
fraction of the standing crop.
The copepods found in Chesapeake Bay, particularly the adults, have
been fairly well studied. The adults usually number from one to ten per
liter in the main portion of the estuary. They graze one to 15 percent of
the daily phytoplankton production. Less is known about grazing by early
life stages but, by analogy to studies of oceanic copepods, it is accepted
that naupliar stages may graze three to five times the adult rate per unit
of body weight.
Nutrient cycling rates by copepods can be estimated by assuming 30
percent assimilation efficiency, 60 percent incorporation into fecal
material, and 10 percent direct excretion. If copepods grazed 10 percent
of the daily phytoplankton production, three percent of the daily
production would be assimilated into copepod tissue (30 percent of 10
percent), six percent would be released as particulate fecal material, and
one percent would be directly excreted. Nutrients would be similarly
distributed, with about one percent of the phytoplankton nitrogen and
phosphorus returned directly to the water, and about one-half of the six
percent fecal nutrients returned by bacterial activity.
It is clear, by comparing phytoplankton growth with copepod recycling
of nutrients, that copepods are a small component of the nutrient cycling
system. The phytoplankton grow and divide about: once every one or two days
in spring, summer, and fall, but the phytoplankton standing crop does not
double each day, indicating that the loss due to grazing approximately
equals the phytoplankton growth rate. Since copepods are only eating one
percent to 15 percent of the daily production, other organisms must consume
the remaining 85 to 99 percent.
Micro-Zooplankton—
The micro-zooplankton are those grazers whose size approaches that of
the phytoplankton cells. The ciliates and small rotifers may be included
in this group. In addition to size similarity, the ciliates have growth
rates and generation times similar to phytoplankton, whereas rotifers and
copepods have long generation times compared to the phytoplankton.
Less is known about micro-zooplankton abundance distribution in
Chesapeake Bay. Recent studies at CBI reveal that ciliates consume about
15 percent of the daily production Bay-wide. Therefore, their contribution
to grazing pressure and the recycling of nutrients is probably only
slightly greater than that of the copepods. Experiments conducted as part
of the Chesapeake Bay Program (CBP) indicate that nitrogen is recycled by
micro-zooplankton at the rate of about 0.05 ug atom NH4~N L-lh-1.
This represents about 10 percent of the phytoplankton requirement for
nitrogen.
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Bacterial Activity
Bacteria are heterotrophic organisms that are probably numerically
dominant in the estuary. Bacterial abundance is thought to be one to ten
million cells per milliliter of water. A major role of these organisms is
to metabolize organic material during which some inorganic carbon,
nitrogen, and phosphorus are recycled. These metabolic processes consume
oxygen and, at times, may be the dominant oxygen-consuming process.
Important groups of bacteria involved in nutrient cycling are
Nitrosomonas and Nitrobacter. The genus Nitrosomonas oxidizes ammonium to
nitrite.NTtrobacter then further oxidizes nitrite to nitrate. These
reactions probably occur in oxygenated sediments year round, but are most
conspicuous during the late summer and fall in Chesapeake Bay when ammonium-
rich deep water is re-oxygenated. The ammonium is rapidly oxidized to
nitrite that reaches relatively high concentrations throughout the Bay.
The second oxidation step to nitrate has been observed less frequently than
the first.
An experiment was conducted under the CBP to specifically examine this
phenomenon. Ammonium was oxidized at the rate of 0.05 ug atom NH^-N
L~l h~l by planktonic bacteria. During the process, about one percent
of the NH^-N was converted to gaseous N20.
A considerable amount of research has been done on a few kinds of
bacteria in Chesapeake Bay, such as the shellfish pathogens, but little has
been done quantitating the role of bacteria in nutrient recycling during
the winter, fall, and spring. The bacterial contribution to recycling has
usually been estimated from oxygen consumption, or obtained by difference
calculation rather than measured directly. At best, there are
fractionation studies wherein water samples are passed through various size
filters, and the oxygen consumption of each fraction is measured. The
results of three such experiments are shown in Table 2 for samples passing
through a 3 um filter (labeled
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Nutrient Flux
The flux of nutrients out of the sediments is largely dependent on two
processes. One is degradation directly on the sediment surface. The other
is diffusion of nutrients out of the sediments, based upon the
concentration gradient in the interstitial water. Direct release to the
water can be estimated from the sediment-oxygen demand, as is done for
water-column- regeneration estimates.
Diffusion of nutrients out of the sediment can be calculated from the
concentration gradient and the physical characteristics of the sediment.
These calculated values are minimum values for nutrient flux out of the
sediments. Several other factors, difficult to quantify, have roles in
moving nutrients out of the sediment. One of these factors is stirring of
the sediments by benthic animals. Another is the lateral diffusion of
nutrients into animal burrows, followed by turbulent diffusion or advection
up the burrow to the sediment-water interface. A third possible factor is
hydrostatic pumping of water as a surface wave passes. Theoretically,
large hydrostatic pressure under a wave crest could pump water out of the
sediment under an adjacent wave trough, where hydrostatic pressure is less.
Another way to determine nutrient flux from sediments is by pilacing a
chamber on the bottom to isolate a portion of the sediment-water
interface. Flux rate is then determined from nutrient concentration
changes in the water contained by the chamber. Since this method may also
introduce some artifacts, we consider flux rates obtained in this way to be
maximum potential values.
During the course of the CBP, nutrient flux from the sediments was
studied by both the diffusion and chamber method. Table 5 summarizes the
results. For ammonium, the diffusion value is usually about one-fourth to
one-half of the measured chamber value. This is because processes at the
sediment surface (bioturbation and other biological processes) increase the
flux of nutrients over that permitted by diffusion alone. The actual
ammonium flux from undisturbed sediments lies between these two values and
is probably closer to the higher one. At present, this is the best
estimate that can be made from this data.
TABLE 5. AMMONIUM AND PHOSPHATE FLUX FROM CHESAPEAKE BAY SEDIMENTS
EXPRESSED AS ug atom m
-2 h-
POSITIVE IS OUT OF THE SEDIMENT
Location
Ammonium
Diffusion Chamber
* TDP
** DIP (Boynton)
Phosphate
-"Diffusion Chamber**
Worton Creek
Hart-Miller Island
Sharp's Island
Kenwood Beach
Todds Cove
Gwynn's Island
Pocomoke Sound
50
52
171
184
37
68
93
177
102
455
670
410
262
430
1.1
0.9
16.3
15.3
3.8
5.1
9.6
-4.2
2.3
0
40
16
10
-3.2
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In contrast, the phosphate flux values from diffusion calculations and
chamber measurements are more similar than the ammonium values, but
negative values are sometimes observed. This reflects the uptake of
phosphate by sediments, a process which partly results from sorption by
sediment particles.
The magnitude of the sediment flux of ammonium and phosphate can be
illustrated by comparing the amount of nutrient being added with the total
amount already in the water. Consider, for ammonium in the water column 1
m~2 «h~l, the ammonium concentration in the water would increase by
100 ug atom-h"! ,„ o , i
_ = 10 ug atom • m~-> • hi
10 m3
or 0.01 ug atom L~l h~l each day. The water would gain
0.24 ug atom L~l • d~l. If the total nitrogen concentration is 25 ug
atom L~l, the benthic flux increases the nitrogen content of the water by
about one percent per day. (Sedimentation removes nitrogen from the water
so a cycle is maintained.) This calculation can be used to evaluate the
nitrogen concentration in water from the flux measurements in Table 5.
Sorption - Desorption Reactions
Whereas ammonium leaves the sediments continually during the annual
cycle, phosphate release takes place primarily in the summer. This results
from the interaction of phosphate with iron at the sediment-water
interface. In the presence of oxygen, iron is present on the sediment
surface as solid iron oxyhydroxides. The phosphate diffusing upward in the
interstitial water is apparently adsorbed onto these solids that block
phosphate flux into the overlying water.
When the overlying water becomes anoxic in the deeper parts of the
estuary during summer, a two-step release process occurs. First, the iron
oxyhydroxides are reduced and dissolved, releasing both iron and phosphate
into the water in a pronounced pulse. Second, with the block removed,
phosphate in the interstitial water diffuses freely into the overlying
water, but more slowly than the initial release. When the deep water is
reoxygenated in late summer, the phosphate concentration declines rapidly.
We hypothesize that sorption reactions involving newly-formed iron
oxyhydroxides are responsible for a significant fraction of this phosphorus
removal.
The residence time of nitrogen and phosphate in the sediments cannot be
measured directly. From the relatively high interestitial water
concentrations, we estimate a rather long residence time for some fraction
of the nutrients. As much as one-third of the nitrogen could be
permanently buried in the sediments. For the remaining 70 percent of the
nitrogen and for much of the phosphorus, the residence time may be rather
short, on the order of months to a few years. Additional research is
required to further test ideas about processes influencing the residence
time, and about the size (depth) of the considered sediment reservoir.
Geochemical Reactions
Phosphate participates in geochemical processes in the sediments. A
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detailed evaluation is beyond the scope of this discussion. The reader is
referred to Bricker and Troup (1975) and Bray et al. (1973) for information
on the equilibrium chemistry of phosphate minerals in sediments.
Marshes and Bay Grasses
The marshes and Bay grasses along the shorelines of the Bay and its
tributaries serve as both sources and sinks for nutrients. At present,
there is not complete agreement as to whether marshes are net sources or
net sinks of nutrients. During the growing season, marsh plants assimilate
nutrients from the water. Nitrogen fixation by some species may be
significant when the water is nitrogen deficient. In winter, organic
material may be periodically flushed out of the marshes to the adjacent
open waters. Similarly, submerged aquatic vegetation (SAV) absorb
nutrients during the growing season and contribute organic material to the
system during the winter.
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SECTION 4
DISSOLVED OXYGEN IN THE ESTUARY
OXYGEN SOURCES
Dissolved oxygen is of primary interest to water quality managers,
because it directly affects the well-being of aquatic life. Sources of
oxygen include diffusion from the surface, photosynthesis, and reduction of
oxidized chemical species. Oxygen is lost from the water through
respiration and oxidation of reduced chemical species.
Oxygen gas enters the water by two major mechanisms; diffusion and
bubble entrainment at the air-water interface transfer oxygen to the
water. The rate of transfer depends on temperature, sea state, wind
velocity, and oxygen concentration in the water. Surface turbulence and
low temperature enhance both the exchange and the solubility of oxygen in
estuarine water. Salinity also exerts an influence, but it is small
compared to the other parameters.
Photosynthesis is the second mechanism by which gaseous oxygen enters
the system. Oxygen is a product of photosynthesis and is evolved during
daylight by the phytoplankton. This is an important mechanism for aeration
during summer when warm temperatures and calm weather minimize oxygen
solubility and transfer from the atmosphere. However, the same organisms
that produce oxygen during the day consume it at night. This results in a
daily fluctuation in oxygen concentration, with the minimum value just
before sunrise. Therefore, in regions of the estuary where oxygen
concentrations are critical, measurements should be made at sunrise for
comparison with the desired level of oxygen concentration.
A third oxygen input is the oxygen combined in sulfate and nitrate.
Major groups of heterotrophic bacteria fulfill their oxygen requirements by
reducing sulfate to sulfide. If gaseous oxygen is not mixed with the
sulfide to permit its reoxidation to sulfate, the sulfide accumulates.
Sediment interstitial water is characteristically sulfide rich as is the
Bay deep water during the summer. Some bacteria reduce nitrate to ammonium
and utilize the oxygen liberated. Although nitrate reduction preceeds
sulfate reduction, it is not so significant as sulfate reduction because of
the large sulfate concentration in sea water. However, this process does
result in the sediments consuming nitrate from the overlying water, when
nitrate concentrations are moderate to high.
OXYGEN UTILIZATION
Oxygen added to the water by processes just described is consumed by
both biological and chemical reactions. The sites for these reactions may
be susupended in the water, or contained in or on the sediments.
Respiration as a means of regenerating nutrients was discussed in Section
3. Now consider respiration as process by itself.
Respiration is the biological reaction coupling oxygen to reduced
substances, usually carbon, to release energy for other intracellular
processes. Respiration removes oxygen from the water. The amount of
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respiration occurring in a body of water is usually not critical to water
quality if the oxygen is replaced from the atmosphere as quickly as it is
consumed. However, at times, oxygen replenishment lags utilization, so
that undesirable conditions of low-oxygen concentration are reached. Since
reaeration depends on climate and meterology (factors out of man's
control) , people have tried to control the addition of oxygen-consuming
organic material and stimulants (nutrients) for the formation of organic
material to natural waters. Attaining desirable oxygen levels year-round
has been a major criterion for wastewater treatment in the United States.
Respiration occurs both in the water and in the sediments. In the main
portion of Chesapeake Bay, water-column respiration in the spring removes
oxygen faster than it is replenished, so that oxygen concentration declines
to zero by May or June. Although oxygen depletion can be accounted for
entirely by water-column respiration, the sediment demand is substantial.
Its importance is probably expressed more in shallow areas where the amount
of oxygen contained in the overlying water column is less, because the
amount of water is less. In well mixed shallows, high sediment respiration
can be sustained without undesirable oxygen depletion because reaeration
keeps pace with utilization.
IMPLICATIONS
The net result of these interacting processes is dissolved oxygen
depletion during summer in Bay waters deeper than about 10 m. Taft et al.
(1980) suggest that a major proportion of organic matter driving oxygen
depletion comes from primary production of the previous year. The
remainder could be delivered with the spring freshet of the Susquehanna
River. Since the oxygen decline has started as early as February when
temperatures are still low, it seems unlikely that winter/spring production
in the Bay itself contributes a significant organic load to the oxygen
d emand.
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SECTION 5
SUMMARY AND CONCLUSIONS
Either nitrogen or phosphorus flux into phytoplankton cells can be
limiting, according to season and to position in the estuary. The absolute
values for nutrient concentrations in the water and for phytoplankton
biomass, are the results of several processes tending to add or subtract
from the standing crop. High concentrations of nutrients or cells do not
necessarily indicate high turnover rates. If anything, the reverse tends
to be true.
Nutrients in Chesapeake Bay participate in complex cycles, involving
both biological and chemical interactions. Nitrogen and phosphorus have
different annual cycles in the open Bay, resulting in nitrogen limiting
biomass in summer, and phosphorus limiting it for most of the remainder of
the year. The peak in nitrogen availability occurs in spring, because of
large nitrate inputs from the tributaries in addition to ambient recycling
in water and sediments. The peak in phosphorus availability occurs in
summer and is linked with oxygen depletion in water deeper than ten
meters. Oxidized iron compounds may play a key role in removing some
phosphorus from the water, thus acting as a natural control mechanism where
iron is abundant.
Phytoplankton, the major nutrient consumers in the system, have
preferences for ammonium nitrogen and phosphate phosphorus. From modeling
and from experiments in the Bay, it appears that much of the nitrate
entering the upper Bay in spring passes through to the lower Bay, because
the phytoplankton are consuming ammonium in preference to the nitrate.
Analogs may exist in tributary estuaries.
The high productivity of Chesapeake Bay is sustained by rapid recycling
of nutrients in the water column and in the sediments. It appears that the
total plankton biomass in the system may be limited by nitrogen or
phosphorus at different times, but that the rate of phytoplankton growth is
not nutrient-limited because of rapid recycling.
The sediments are critical in nutrient processes, as both a source and
sink for different compounds. Progress is being made in quantifying the
rates of nutrient flux into and out of the sediments, but this area
requires additional research.
Environmental decision-makers should grasp the important
characteristics of the estuary discussed herein. In evaluating
alternatives for controlling inputs to the system, managers should consider
the amount of nutrient to be added to the system compared to what is
already there. They should also consider its form. For example, nitrogen
added in spring to the upper Bay as nitrate will probably not adversely
affect the upper Bay. Phosphate added to the system at any time could
increase phytoplankton standing crop, if the controlling influence of iron
compounds is exceeded.
Since this estuary, by nature, accumulates nutrients, most nutrients
and organic carbon added to the system will remain in it. Thus, once
degraded, the lower Bay whole would probably take a fairly long time to
recover. However, non-degradation is realistic and achievable.
Nevertheless, since the estuary tends to trap nutrients, common sense
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suggests that increases in the total amount of nutrients should be kept to
a minimum. If scientists can provide accurate information on process rates
and outputs from the system, it may be possible for managers to regulate
inputs to the level of the outputs. The key is quantifying the outputs to
the ocean, sediments, and commercial catches, something which so far has
proven to be difficult. Chapter 3 of this part of the GBP Synthesis
Resport discusses those outputs further. Understanding processes may help
humans overcome the estuary's tendency to accumulate nutrients, by finding
positive ways to utilize them within the coastal system.
Management agencies supporting research should consider studying
processes along with the traditional monitoring of nutrient
concentrations. Both kinds of information are important in assessing the
progress of chosen management strategies.
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LITERATURE CITED
Bray, J.T., O.P. Bricker, and B.N. Troup. 1973. Phosphate in
Intersititial Waters of Anoxic Sediments: Oxidation Effects During
Sampling Procedure. Science. 180:1362-1364.
Boynton. 1980.
Bricker, O.P., and B.N. Troup. 1975. Sediment-Water Exchange in
Chesapeake Bay. In: Estuarine Research L.E. Groin, ed, Academic
Press, New York pp. 3-27.
Carpenter, J.H., D.W. Pritchard, and R.C. Whaley. 1969. Observation of
Eutrophication and Nutrient Cycles in Some Coastal Plain Estuaries.
Acad. Sci., Washington, DC.
Eppley, R.W., and E.H. Renger. 1974. Nitrogen Assimilation of an Oceanic
Diatom in Nitrogen-Limited Continuous Culture. J. Phycology. 10: 15-23.
Fournier, Robert 0. 1966. Some Implications of Nutrient Enrichment on
Different Temporal Stages of a Phytoplankton Community. Ches. Sci. 7:
11-19.
Heinle, D.R. 1966. Production of a Calanoid Copepod, Acrtia Tonsa, in the
Patuxent River Estuary. Ches. Sci. 7: 59-74.
Jaworski, N.A., D.W. Lear, and 0. Villa. 1972. Nutrient Management in the
Potomac Estuary. In: Nutrients and Eutrophication: The Limiting
Nutrient Controversy. G.E. Likins, ed. Special Symposium, Volume 1.
pp. 246-273.
Ketchum, B.H. 1939. The Development and Restoration of Deficiencies in
the Phosphorus and Nitrogen Composition of Unicellular Plants. J.
Comp. Cell Physiol. 13:373-381.
Kuenzler, E.J. 1965. Glucose-6-Phosphate Utilization by Marine Alga. J.
Phycology. 1: 156-164.
Kuenzler, E.J., and B.H. Ketchum 1962. Rate of Phosphorus Uptake by
Paeodactylum Tricornutum. Biol. Bull. 123: 134-145.
Loftus, et al. 1972.
McCarthy, J.J., W.R. Taylor, and M.E. Loftus. 1974. Significance of
Nanoplankton in the Chesapeake Bay Estuary and Problems Associated with
the Measurement of Nanoplankton Productivity. Mar. Biol. 24: 7-16.
McCarthy, J.J., W.R. Taylor, and J.L. Taft. 1975. The Dynamics of
Nitrogen and Phosphorus Cycling in the Open Water of the Chesapeake
Bay. In: Marine Chemistry in the Coastal Environment. T.M. Church,
ed. ACS Symposium Series, No. 18, American Chemical Society, pp.
664-681.
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McCarthy, J.J., W.R. Taylor, and J.L. Taft. 1977. Nitrogenous Nutrition
of the Plankton in the Chesapeake Bay. I. Nutrient Availability and
Phytoplankton Preferences. Limnol. Oceaogr. 22: 996-1011.
McElroy, M.B., J.W. Elkins, S.C. Wofsy, E.E. Kolb, A.P. Duran, and W,,A.
Kaplan. 1978. Production and Release of N20 from the Potomac
Estuary. Limnol. Oceanogr. 23: 1168-1182.
Najarian, T.O., and D.R.F. Harleman. 1977. Real Time Simulation of
Nitrogen Cycle in an Estuary. J. Env. Eng. Div. ASCE. 103: 523-538.
Odum, E.P. 1971. Fundamentals of Ecology. 3rd Edition, Saunders,
Philadelphia. 574 pp.
Pamatmat, M.M. 1968. Ecology and Metabolism of a Benthal Community on an
Intertidial Sandflat. Int. Rev. Gesamten. Hydrobiol. 53: 211-298.
Redfield, A.C., B.H. Ketchum, and F.A. Richards. 1963. The Influence of
Organisms on the Composition of Sea-Water. In: The Sea. M.N. Hill,
ed. Vol. 2, Interscience, NY. pp. 26-77.
Rupp, N.M. 1969. Seasonal and Spatial Distribution of Acartia Tonsa. and
A. Clausi in Chesapeake Bay. Master's Essay, Johns Hopkins
University. 45 pp.
Siebarth. 1967.
Storms, S.E. 1974. Selective Feeding, Ingestion and Assimilation Rates,
and Distribution of The Copepod Arcartia in Chesapeake Bay. Ph.D.
Thesis. Johns Hopkins University 162 pp.
Taft et al. 1975.
Taft, J.L., M.E. Loftus, and W.R. Taylor. 1977. Phosphate Uptake from
Phosphomonoesters by Phytoplankton in the Chesapeake Bay. Limnol.
Oceanogr. 22: 1012-1021.
Taft, J.L., and W.R. Taylor. 1976a. Phosphorus Distribution in the
Chesapeake Bay. Ches. Sci. 17: 67-73.
Taft, J.L., and W.R. Taylor. 1976b. Phosphorus Dynamics in Some Coastal
Plain Estuaries. In: Estuarine Processes. M. Wiley ed., Academic
Press, NY. pp. 79-89.
Taylor, W.R., and J.J. McCarthy. 1972. Studies of Nutrient Requirements
of Chesapeake Bay Phytoplankton Using Enrichment Techniques. Progress
Report to U.S. AEC. Document No. COO-3279-03.
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Teal, J.M., and J. Kanwisher. 1961. Gas Exchanges in a Georgia Salt
• Marsh. Limnol. Oceanogr. 6: 388-399.
Tyler, M.A., and H.H. Seliger. 1978. Annual Subsurface Transport of a Red
•Tide Dinoflagellate to its Bloom Area: Water Circulation Patterns and
Organism Distributions in the Chesapeake Bay. Limnol. Oceanogr. 23:
227-246.
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CHAPTER 3
NUTRIENT AND SEDIMENT LOADS
TO THE TIDAL CHESAPEAKE BAY SYSTEM
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fl James T. Smullenl
Jay L. Taft2
• Joseph Macknis^
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II Chesapeake Bay Program, U.S. EPA, Annapolis, Maryland
7 . .
^ Chesapeake Bay Institute, the Johns Hopkins University, Shady Side,
Maryland
• 3 GEOMET Technologies, Inc., Annapolis, Maryland
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CONTENTS
Figures 149
Tables 150
Sections
I. Introduction 154
II. Atmospheric Sources of Nutrients 158
III. Riverine-Transported Sources of Nutrients and Sediments . . . 164
IV. Point Source Loadings of Nutrients 182
V. Bottom Fluxes of Nutrients 209
VI. Nutrient Fluxes at the Mouth of Chesapeake Bay 215
VII. Primary Productivity in Chesapeake Bay 220
VIII Summary and Conclusions: The Management Questions Answered . . 229
References 246
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FIGURES
Number
I.I Box model of nutrient and sediment input sources to the
Chesapeake Bay system 155
1.2 Binary dendogram showing possible responses of the water column to
increased nutrient loadings 156
II. i Rainfall sampling study area locations 160
III.l Physiographic provinces of Chesapeake Bay showing area drained by
the three fall line gauges 165
IV.1 River systems discharging to Chesapeake Bay with USGS fall
line 183
V.I Conceptual diagram of estuarine sediment column 210
VI.1 Net flows at the mouth of Chesapeake Bay in July 1980 as
viewed from the ocean looking into the Bay 216
VII.1 Map of Chesapeake Bay showing regions in which primary
productivity measurements have oeen averaged 221
VIII.1 Annual (a) nitrogen and (b) phosphorus budgets for
Chesapeake Bay 235
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TABLES
Number
II. 1 Seasonal and Annual Volume-Weighted Mean Nutrient Concentrations
Observed in Bay Area Rainfall 161
II.2 Bay-Wide Mean Monthly and Seasonal Precipitation, in Inches,
Computed from Monthly Averages at NOAA Stations 162
II.3 Seasonal and Annual Nutrient Loads from Precipitation to the
Tidal Chesapeake Bay System Ib2
III.l Annual and Seasonal Mean Daily Discharges and Drainage Areas of
the Major Basins Monitored: Susquehanna, Potomac, and James
Rivers 167
III.2 Regression Model Results for the Susquehanna River at
Conowingo, MD 169
III.3 Regression Model Results for the Potomac River at Chain
Bridge, Washington, DC 170
III.4 Regression Model Results for the James River, at
Cartersville, VA 171
III.5(a) Estimated Annual Mean Daily Nutrient and Sediment Loads
to the Chesapeake Bay System from Sources Transported by
Rivers 173
III.5(b) Estimated Percentage of Annual Nutrient and Sediment
Loads from Chesapeake Bay Tributaries 173
III.6(a) Estimated Winter Mean Daily Nutrient and Sediment Loads to
the Chesapeake Bay System from Sources Transported by
Rivers 174
III.6(b) Estimated Percentage of Winter Nutrient and Sediment
Loads from Chesapeake Bay Tributaries 174
III.7(a) Estimated Spring Mean Daily Nutrient and Sediment Loads to
the Chesapeake Bay System from Sources Transported by
Rivers 175
III.7(b) Estimated Percentage of Spring Nutrient and Sediment
Loads from Chesapeake Bay Tributaries 175
III.8(a) Estimated Summer Mean Daily Nutrient and Sediment Loads to
the Chesapeake Bay System from Sources Transported by
Rivers 176
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Number Page
III.8(b) Estimated Percentage of Summer Nutrient and Sediment
Loads from Chesapeake Bay Tributaries 176
III.9(a) Estimated Fall Mean Daily Nutrient and Sediment Loads to the
Chesapeake Bay System from Sources Transported by Rivers .... 177
III.9(b) Estimated Percentage of Fall Nutrient and Sediment
Loads from Chesapeake Bay Tributaries 177
III.10 Seasonal and Annual Nutrient and Sediment Loads Transported
by Rivers to the Tidal Chesapeake Bay System 180
IV. 1 Water Quality Variables and Variable Code 184
IV.2 USGS hydrologic Units Below the Functionally Defined Fall Line of
the Chesapeake Bay Drainage Basin 184
IV.3 Range of POTW Constituent Concentrations Based on Level of
Treatment 187
IV.4 Estimate of Distribution of POTW Nitrogen and Phosphorus into
Various Fractions According to Selected Treatment Process .... 187
IV.5 Estimates of Nutrient Loads from Municipal Point Sources .... 188
IV.6 Estimates of Nutrient Loads from Municipal Point Sources .... 189
IV. 7 SIC code and Economic Activity 192
IV.8(a) SIC Code and Assigned Concentration of Water Quality Constituents 193
IV.8(b) SIC Code and Source of Constituent Concentration 194
IV.9 SIC Code, Assigned Flow, and Source of Value 196
IV.10 Assigned Industrial Facilities, Nutrient Loadings from Observed
Data 197
IV.ll(a) Estimates of Nutrient Loads from Industrial Point Sources from
Above the Functionally Defined Fall Line 198
IV.ll(b) Estimates of Nutrient Loads from Industrial Point Sources
from Below the Functionally Defined Fall Line 199
IV.ll(c) Estimates of Nutrient Loads from Industrial Point Sources
from Above and Below the Functionally Defined Fall Line 200
IV.12(a) Estimates of Nutrient Loads from Municipal and Industrial
Point Sources from Above the Functionally Defined Fall Line . . . 202
151
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Number Page
IV.12(b) Estimates of Nutrient Loads from Municipal and Industrial
Point Sources from Below the Functionally Defined Fall Line . . . 204
IV.12(c) Estimates of Nutrient Loads from Municipal and Industrial
Point Sources Totaled Above and Below the Functionally
Defined Fall Line 206
IV.13 Total Estimated Average Seasonal and Annual Nutrient Loadings
from Point Sources to the Tidal Portions of the Chesapeake Bay
System 208
V.I Potential Nitrogen and Phosphorus Unit Area Diffusion from
Sediment Pore Waters 211
V.2 Potential Nitrogen and Phosphorus Mass Diffusion from Sediment
Pore Waters 212
V.3 Nutrient Release from the Sediments Measured Under Domes .... 214
V.4 Nutrient Release in Each Segment Calculated from Dome Studies . . 214
VI.1 Nutrient Fluxes Across the Mouth of Chesapeake Bay in July 1980 . 218
VI.2 Fluxes of Particulate Material at the Bay Mouth Calculated with a
Box Model 218
VII.1 Primary Productivity Measurements and Factors Used to Calculate
Annual Average Productivity for Chesapeake Bay ....... 223
VII.2 Relation Between Annual Plankton Productivity and Annual Nutrient
Inputs 224
VII.3 Seasonal Primary Productivity in Chesapeake Bay 225
VII.4 Relation Between Winter Phytoplankton Productivity and Nutrient
Inputs 225
VII.5 Relation Between Spring Phytoplankton Productivity and Nutrient
inputs 226
VII.6 Relation Between Summer Phytoplankton Productivity and Nutrient
Inputs 227
VII.7 Relation Between Fall Phytoplankton Productivity and Nutrient
Inputs 228
VIII.l(a) Average Annual Nutrient and Fluvial Sediment Input to the Water
Column of the Tidal Chesapeake Bay System 229
VIII. l(b) Percentages of Annual Nutrient Loadings from Various Sources . . 230
152
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Table Page
VIII.2(a) Average Winter Nutrient and Fluvial Sediment Input to the Water
Column of the Tidal Chesapeake Bay System 230
VIII.2(b) Percentages of Winter Nutrient Loadings from Various Sources . . 230
VIII.3(a) Average Spring Nutrient and Fluvial Sediment Input to the Water
Column of the Tidal Chesapeake Bay System 231
VIII.3(b) Percentages of Spring Nutrient Loadings from Various Sources . . 231
VIII.4(a) Average Summer Nutrient and Fluvial Sediment Input to the
Water Column of the Tidal Chesapeake Bay System 231
VIII.4(b) Percentages of Summer Nutrient Loadings from Various Sources . . 232
VIII.5(a) Average Fall Nutrient and Fluvial Sediment Input to the Water
Column of the Tidal Chesapeake Bay System 232
VIII.5(b) Percentages of Fall Nutrient Loadings from Various Sources . . . 232
VIII.6 Seasonal Distribution of Nutrient Loadings 233
VIII.7 Concentration and Loading Rates for Total Suspended Solids, Total
Phosphorus, Orthophosphate, Total Nitrogen, and Nitrite-Nitrate from
Various uses of Land 239
VIII.8 Generalized Ranking of Land Uses 239
VIII.9 Ranking of Urban Land Uses 240
A-l Water Quality Variables Included in Regression Analysis 251
A-2 Regression Models Chosen for the Susquehanna River at
Conowingo, MD 253
A-3 Regression Models Chosen for the Potomac River at Chain
Bridge, Washington, DC 255
A-4 Regression Models Chosen for the James River at
Cartersville, VA 257
153
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SECTION 1
INTRODUCTION
An important area of concentration of the Management Questions within the
CBP Nutrients Program is the excessive fertilization (over-enrichment) of the
Bay system. Nutrient over-enrichment can cause excessive algal blooms and
oxygen depletion. Although this fertilization process, called eutrophication,
occurs naturally (i.e., runoff from the land and atmospheric deposition
processes have always carried plant nutrients to receiving waters), the
cultural activities of man accelerate it. When coupled with the complicating
problem of increased sedimentation rates due to cultural activities, the
result can be the shortening of the life of the estuary and a decrease in the
value of the system and its resources. This two-pronged problem of nutrient
over-enrichment and increased sediment yield has come to be known as "cultural
eutrophication." The aquatic plant nutrients considered in this paper are the
various forms (species) of nitrogen and phosphorous.
To understand and manage potential cultural eutrophication problems in the
Bay system, we need to answer a number of questions concerning sources of
nitrogen, phosphorus, and sediment to the Bay and its tidal
tributaries. This paper seeks to synthesize available research findings on
these sources by answering the following Management Questions:
1. What is the atmospheric contribution to nutrient input?
2. What percentage of the nutrients is from point sources?
3. What percentage of the nutrients is from nonpoint sources? How do they
vary over time?
4. What are the pollutant runoff rates for particular land uses?
5 What percentage of nonpoint sources can be attributed to particular land
uses?
6. What are the nutrient loadings from the Fall Line?
7. What do the bottom sediments contribute to nutrient inputs?
8. What are the flux rates of nutrients from the bottom sediments, and how do
they vary seasonally?
9. Given the estimated loadings of nutrients for each of the sources, which
will be the most important in terms of their effects on the Bay system.
To answer the management questions, we synthesized available information
to understand the components of a nutrient budget. In this paper, the
approach taken for determining the nutrient budget centers on a simplified
consideration of the Bay as a container, or box, into which flow
nutrient-laden waters from various sources (see Figure I.I). This box model
approach allows the reader to visualize nutrient sources simultaneously as a
simple schematic diagram or picture. We considered five external sources
expressed both as annual and seasonal loadings. These sources are shown in
Figure 1.2 and include:
- Atmospheric Sources, defined for the purposes of this paper as nitrogen
and phosphorus falling onto tidal Chesapeake Bay system waters in
precipitation and nitrogen lost to the atmosphere as nitrous oxide and
gained through nitrogen fixation. No estimate is made of denitrification
losses.
154
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- Riverine-Transported Sources, defined as nitrogen, phosphorous, and
sediment, which derive from above the head of tide or the Fall Linel.
This source includes loadings from surface land runoff, atmospheric
loadings falling upon upland waters, groundwater contributing as baseflow,
municipal sewage treatment plant discharges from above the Fall Line and
industrial waste discharges from above the Fall Line as measured at the
Fall Line water quality monitoring stations. No estimate is made of land
runoff or groundwater loadings deriving from below the Fall Line.
- Point Sources to Tidal Waters, defined as nutrient loadings from
publicly owned sewage treatment works discharges and industrial waste
discharges that enter the tidal waters of the Bay system directly. For
the purposes of this paper (see definition of "functional" fall line in
Section IV) all such discharges are defined to be those that enter
downstream of the head of tide of the Susquehanna, Potomac and James
rivers;
- Bottom Sources, defined as fluxes of nitrogen and phosphorous between
the bottom sediments of the Bay and the water column. Because of the lack
of wide spread tributary benthic flux data, fluxes are computed only for
the Bay proper;
- Ocean Sources, defined as the net flux of nutrients between the Bay and
the Atlantic Ocean.
In addition to these five sources, the internal or re-cycled nutrients as
a source will also be discussed. The only sediment source considered is
riverine, included as described above under Riverine Transported Sources. No
estimates were made of potential sediment loads entering the system from the
ocean or shore erosion, nor of the contribution because of phytoplankton
production of skeletal material. The net sedimentation of nutrients was
determined by difference. A schematic diagram of the box model is shown in
Figure I.I, and the nutrient budgets appear in Section VIII. Nonpoint source
nutrient contributions below the fall line have not been included in this
paper because the data were not available at the time of writing. Estimates
from below the fall line are being currently made through a computerized model
and will be available in the near future. The eventual inclusion of these
data in the nutrient budget will tend to reduce the percentages of nutrient
loads shown here.
In summary, the authors of this paper have assembled available information
concerning the most important nutrient sources and attempted to answer the
pertinent management questions. Each of the sources is discussed in separate
sections, with a comparison of these sources made in Section VIII.
Conclusions and answers to the management questions are also found in the last
section.
l-Wolman (1968) describes a broad area trending from Southeast to
Northeast which defines the head of tide (and the head of navigation)
as the contact between the hard crystalline basement rocks and the
unconsolidated sediments of the Coastal Plain. This demarcation he calls
the Fall Line or Fall Zone.
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SECTION II
ATMOSPHERIC SOURCES OF NUTRIENTS
Precipitation and dust/dirt dryfall are the major mechanisms that
return to the earth's surface gaseous and particulate materials that are
injected into the atmosphere from natural and man-induced sources. To
determine the relative importance of the atmospheric source to the overall
nutrient input budget, we estimated the mass of nitrogen and phosphorous
carried into the Bay by rainfall. No estimate of the dryfall portion of
the atmospheric source has been made because of the paucity of available
data and the uncertainty of existing dryfall sampling techniques^.
Although about 10 percent of annual areal precipitation is made up of
forms other than rainfall (i.e., snow or ice), data on concentrations of
nutrients in these forms are lacking. Therefore, for the purpose of this
paper, the concentrations computed for rainfall will be assigned to the
total precipitation budget.
NUTRIENT CONCENTRATIONS IN PRECIPITATION
Rainfall quality data were chosen from studies conducted within the
Chesapeake Bay drainage basin. We chose this method to ensure that the
data reflect the natural and man-induced surface sources peculiar to the
region. The size of the available data base made the regional restriction
feasible. The data included interim reports, draft final reports,
completion reports or personal communications of six major regional
nonpoint pollution and rainfall quality studies (Northern Virginia Planning
District Commission [NVPDC] and Virginia Polytechnic Institute and State
University [VPI&SU] 1977, Bostater2 1981, Wade & Wong 1981, Correll et
al. 1978, Ward and Eckhardt 1979, Lietman3 1981, VPI & SU 1981, Weand^
1981). The general locations of these study areas are shown in Figure II.1.
The assembled data base consists of bulk precipitation samples from as
many as 125 storm events collected at up to 18 sampling locations for all
seasons from 1976 through 1981. In most cases, a raingage within, or near
the sample collection areas, recorded precipitation volumes. For most
storm events, composited samples were analyzed for ammonia nitrogen,
nitrite + nitrate nitrogen, total Kjeldahl nitrogen, orthophosphorus and
•'•The authors note that although some dryfall deposition data collected
within Chesapeake Bay sub-basins are available (Correll et al. 1978,
Virginia Polytechnic Institute & State University 1978), too little was
available to make reliable Bay-wide estimates.
^Personal Communication: "Patuxent River Park Rainfall Quality Data," C.
Bostater, Department of Natural Resources, State of Maryland, 1981.
^Personal Communication: "Pequea Creek Watershed Rainfall Quality Data,"
P. Lietman, Harrisburg Sub-district, U.S. Geological Survey, Harrisburg,
PA, October, 1981.
^Personal Communication: "Occoquan Watershed Rainfall Quality Data," B.
Weand, Occoquan Watershed Monitoring Laboratory, Manassas, VA, November,
1981.
158
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total phosphorus were assembled (total nitrogen was computed as the sum of
total Kjeldahl nitrogen plus nitrite + nitrate nitrogen). Concentrations
were recorded as milligrams per liter (mg/L) or converted to mg/L from data
expressed as molar concentration. All concentrations are expressed as
elemental nitrogen (N) or phosphorous (P).
Many investigators have shown that constituent concentrations in
rainfall are strongly related to precipitation amounts (Stensland 1980).
For example, given similar antecedent rainfall conditions, a smaller
rainfall event would probably have higher nutrient concentrations than a
larger rainfall event occurring in the same geographical area. This is due
primarily to the tendency for rainfall pollutant loadings to exhibit
"first-washout" or "first-flush" effects (NVPDC and VPI & SU 1978; Gambell
and Fisher; Uttormark, Chapin, and Green 1974). The first-flush effect is
characterized by concentrations of rainfall constituents reaching a maximum
value early in a storm event and declining rapidly thereafter. To
compensate for this effect it is common to report rainfall constituents as
volume-weighted average concentrations^ rather than as arithmetic average
concentrations (Stensland 1980). For this reason, all concentrations
reported in this chapter have been computed as volume-weighted averages.
For this analysis, we used the volume weighted mean of the nutrient
concentrations for data collected in each geographic area (shown in Figure
II.1), for each season. An equal-weight average of the means of data
collected at each of the geographic locations by season was computed. We
took this approach to reduce the potential for those studies with the most
data to skew the means in favor of one particular geographic area. The
results of these computations are reported in Table II.1.
Lang and Grason (1980) reported mean monthly precipitation totals
(based upon NOAA records, 1941-1970) at three sites within the Chesapeake
Bay Basin, including Richmond, VA, College Park, MD, and Harrisburg, PA.
An average of the mean monthly totals over the three stations was computed
to represent a Bay-wide average mean monthly precipitation and is reported
in Table II.2. Also shown in this Table are the computed seasonal totals
and the annual average of 39.6 inches of precipitation. It can be seen
from the data in Table II.2 that, on the average, the Bay receives 21.6,
25.3, 24.8, and 23.3 percent of its annual precipitation in winter, spring,
summer and fall respectively. These percentages were used as the weighting
factors to compute volume-weighted annual nutrient concentrations (from the
seasonal concentrations), shown on the last row of Table II.1.
1
= concentration
= volume
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PEQUEA CREEK
APPALACHIAN PLATEAU
'/APPALACHIAN
BRIDGE a VALLEY.
OCCOQUAN
RESERVOIR
\COASTAL
1 PLAIN
RHODE
RIVER
KILMARNOCK
MAPLE VIEW
(Near Exmore)
GLOUCESTER PT.
-NORFOLK
Figure II.1. Locations of rainfall sampling,
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TABLE II. 1. SEASONAL AND ANNUAL VOLUME-WEIGHTED MEAN NUTRIENT
CONCENTRATIONS OBSERVED IN BAY AREA RAINFALL (REPORTED AS
rag/L OF ELEMENTAL MATERIAL)
NH3-N N02+N03-N
WINTER
A
SPRING
A
SUMMER
A,
FALL
A,
ANNUAL
(1)
X
SD
,B
X
SD
,B
X
SD
B
X
SD
B
mg/L
0.376
0.169
4, 39
0.537
0.204
3, 98
0.250
0.141
3, 22
0.256
0.232
3, 22
0.351
mg/L
0.540
0.271
6, 50
0.731
0.304
5, 125
0.621
0.525
5, 40
0.360
0.193
4, 33
0.571
TKN
mg/L
0.586
0.545
5, 33
1.783
0.852
4, 96
0.988
0.426
4, 35
0.642
0.662
4, 33
1.022
TN Ortho P Total P
(N02+N03+TKN)
mg/L
1.126
___
2.514
1.609
__ — —
1.002
__—
1.593
mg/L
0.016
0.013
4, 37
0.015
0.009
3, 91
0.014
0.015
5, 21
0.021
0.013
3, 16
0.016
mg/L
0.038
0.030
6, 51
0.080
0.092
5, 122
0.079
0.098
5, 41
0.050
0.036
4, 31
0.064
1 Legend - X = Equal Weight Mean (mg/L)
SD = Standard Deviation
A = $ studies from which data were taken for computation
B = # station storms sampled (n)
Nutrient Loads in Precipitation
Seasonal and annual nutrient loadings were estimated based on
precipitation falling upon the water areas of Chesapeake Bay and its tidal
tributaries. Nutrient loadings, from precipitation falling upon the water
and land surfaces of the Bay watershed above the head of tide of the
Susquehanna, Potomac, and James Rivers, are accounted for in the fluvial
loadings computed in Chapter III of this paper. The mean annual and
seasonal precipitation values shown in Table II.2 were used to compute
expected annual and seasonal volumes of precipitation input to the 4412.1
square mile Chesapeake Bay tidal system. These volumes were applied to the
concentrations in Table II.1 to produce the seasonal and annual nutrient
loading estimates that are shown in Table II.3.
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TABLE II.2. BAY-WIDE MEAN MONTHLY AND SEASONAL PRECIPITATION, IN INCHES,
COMPUTED FROM MONTHLY AVERAGES OF NOAA STATIONS1
Month
Mean
Monthly
Total (in.
) Season
Mean
Seasonal
Total (in.)
Seasonal %
of Annual
Total
December
January
February
March
April
May
June
July
August
September
October
November
3.18
2.72
,65
,14
2.95
3.69
3.79
3.61
4.42
3.
2.
21
79
3.21
Winter
Spring
Summer
Fall
8.55
10.04
11.82
9.21
21.6
25.3
29.8
23.3
Average Annual Total = 39.62 in.
•"•Monthly totals shown are the average of the mean monthly totals at each of
three NOAA stations (Richmond, VA, College Park, MD, Harrisburg, PA) based on
precipitation records 1941-1970 as reported by Lang and Grason, 1980.
TABLE II.3.
SEASONAL AND ANNUAL NUTRIENT LOADS FROM PRECIPITATION TO THE
TIDAL CHESAPEAKE BAY SYSTEM (MILLIONS OF POUNDS)
Winter
Spring
Summer
Fall
Precipi-
tation
Volume
(inches)
8.55
10.04
11.82
9.21
Ammonia-
N
2.06
3.45
1.89
1.51
Nitrite +
Nitrate-N
2.95
4.70
4.70
2.12
Total
Kjeldahl
N
3.21
11.46
7.47
3.78
Total Total
Nitrogen-N Ortho- Phosphorus
Phosphorus P
P
6.16 0.088 0.208
16.15 0.096 0.514
12.17 0.106 0.598
5.91 0.124 0.295
Annual
39.62
8.91
14.47
25.92
40.39
0.399
1.64
The compilations in the Tables indicate that both concentrations and
areal loading rates in rainfall are significant in comparison to other sources
(Section VIII). Nitrogen and phosphorus concentrations shown are similar to
those found in other studies conducted in the northeastern United States
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(Ward and Eckhart 1977, Stensland 1980). The seasonal and annual rainfall
concentrations of total nitrogen exceeded the volume-weighted mean
concentrations observed in runoff from forested sites studied under the
Chesapeake Bay Programs's Intensive Watershed Studies Project1. (See Table
VIII.6 for these concentrations.) Orthophosphorus concentrations in
precipitation are of the same order of magnitude, but generally less than
those observed in forested land runoff. Concentrations of most constituents
are typically much less than those in runoff from other land uses.
Comparisons between atmospheric and other sources are made in Section
VIII. For example, it can be seen in Tables VIII.3(b) and VIII.4(b) that
precipitation is a major contributor of TKN in spring and summer. This could
be particularly important in summer, when nitrogen limits phytoplankton
biomass in much of the Bay (Chapter 2 of this part).
OTHER ATMOSPHERIC NUTRIENT INTERACTIONS
Other nutrient processes involving gains of nitrogen from the atmosphere
and losses of nitrogen to the atmosphere were considered. The nitrogen input
to the Bay by nitrogen fixation is not well known, but it should be small
compared to other inputs since nitrogen fixation rates in the water are
vanishingly small. We estimate 25,000 pounds per year net input from
marshes. The nitrogen loss to the atmosphere as N20 and NH3 gas is also
probably small. Few measurements have been made from which we estimate an
annual loss of 40,000 pounds per year from the estuary. We hope, future
research will refine these estimates. Losses due to denitrification were not
estimated, but were considered to be small relative to the sources (i.e.,
precipitation, riverine, etc.).
•'•Personal Communication: "Volume-Weighted Mean Concentrations of Storm
Event Runoff from EPA/CBP Test Watersheds," John P. Hartigan, Northern
Virginia Planning District Commission, Falls Church, VA, October 13 1981.
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SECTION III
RIVERINE-TRANSPORTED SOURCES OF NUTRIENTS AND SEDIMENT
A major objective of the EPA Chesapeake Bay Program was to assess the
loadings of nutrients, sediment and other water quality constituents from the
watersheds of the Bay to the tidal system. The approach taken included
developing an intensive data base of the nutrient and sediment loadings
entering the Bay from fluvial sources over a period of several years, and then
developing a methodology to extrapolate that data to produce reliable
estimates of the expected long-term loadings from the upstream sources. In
this chapter, we estimate seasonal and annual total mass flux of nutrients to
the tidal waters of the Bay system from above the head of tide, or the fall
line. The section is subdivided into three sub-sections. The first describes
a fairly rigorous development of loadings from the three major tributaries
(Susquehanna, Potomac, and James Rivers) based on data collected as part of
the EPA Chesapeake Bay Program. The second section contains estimates of
minor tributary (Patuxent, Rappahannock, Mattaponi, Pamunkey, and Chickahominy
Rivers) loadings based, in part, upon a field study performed by Guide and
Villa in 1969 through 1970. In the third section, the total annual and
seasonal fluvial-loading estimates are presented.
NUTRIENT INPUTS FROM THE MAJOR TRIBUTARIES
To determine the nutrient contributions from the major watersheds of the
Chesapeake Bay drainage area, the Bay Program established a fall line
monitoring project. This project, performed by the U.S. Geological Survey,
monitored water quality of three major tributaries of the Bay. The sites
monitored were: Susquehanna River at Conowingo, MD; Potomac River at Chain
Bridge, Washington, DC; James River at Cartersville, VA. Together, the three
rivers drain about 70 percent of the approximately 64,000 square mile
Chesapeake Bay drainage basin and account for about 80-85 percent of the long-
term average discharge Bay-wide (Wolman 1968) (see Figure III.l). Previous
work by Guide and Villa (1972) indicated that these three tributaries were the
primary riverine sources of nutrient loads to the tidal Chesapeake Bay
system. They found that these tributaries contributed as much as 94 percent
of the total phosphorus load and 95 percent of the total nitrogen load
emanating from the eight major Bay tributaries. •*•
The USGS began the sampling program in January of 1979 and continued
through April of 1981, a period of 28 months. Base flow water quality was
monitored every two weeks at the Conowingo station on the Susquehanna, and
once a month on the Potomac and James. Samples were also taken at high flows
on all stations to better understand the mechanisms affecting water quality
during these critical periods of high-mass transport. Samples were analyzed
for major ions, suspended sediment, selected nutrient species, and trace
metals.
•"•These are Susquehanna, Patuxent, Potomac, Rappahannock, Pamunkey,
Mattaponi, James, and Chickahominy Rivers.
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Figure III.l.
Physiographic provinces of Chesapeake Bay basin.
Shaded areas drain into the fall line areas in the
Susquehanna, Potomac, and James Rivers.
165
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An interim basic data report by Lang and Grason (1980) describes the
first year of this project, and a draft final report (Lang 1982) will soon be
completed.
Description of the Major Tributary Drainage Areas
Susquehanna: The Susquehanna River Basin has a drainage area of about
27,510 square miles of which 27,100 are above the fall line monitoring
station. The basin is about 250 miles long and about 170 miles wide. The
drainage lies within four physiographic provinces: the Appalachian, the Ridge
and Valley, the Piedmont, and the Blue Ridge. . The land-use is
predominately forest and agriculture with no major urban areas.
Potomac: The Potomac River Basin has a drainage area of about 14,670
square miles of which 11,560 lie above the monitoring station. The basin is
made up of eight major sub-basins with the main stem approximately 280 miles
in length. The drainage lies within five physiographic provinces: the
Applachian, the Ridge and Valley, the Piedmont, the Blue Ridge, and the Coastal
Plain (Figure III.2). The Coastal Plain portion of the basin does not lie
within the monitored area. The land use is predominately agriculture and
forest with the Washington, DC area draining below the monitoring gage site.
James: The James River Basin has a drainage area of about 10,000 square
miles of which 6,257 drain to the sampling station. The basin is about 400
miles in length and drains four physiographic provinces: the Ridge, and
Valley, the Piedmont, the Blue Ridge, and the Coastal Plain (Figure III.2).
None of the Coastal Plain portion of the watershed lies within the monitored
drainage. The basin is mostly agricultural and forested with the Richmond
metropolitan area draining below the monitoring point.
The mean annual and seasonal discharges for each basin are presented in
Table III.l. These data were computed based upon records retrieved from the
USGS stream discharge stored on the EPA STORET system. Water year 1981 data
were retrieved as provisional data, subject to revisions.
^•Although the monitoring period reported by Lang (1982) covers only 28
months, other collection efforts at the three sites resulted in data
being available for this analysis, beginning in October 1978 and running
through as late as November of 1981. Some of these data were collected as
part of the ongoing EPA/USGS National Stream-Quality Accounting Network
(NASQUAN).
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TABLE III.l. ANNUAL AND SEASONAL^1) MEAN DAILY DISCHARGES AND DRAINAGE
AREAS OF THE MAJOR BASINS MONITORED: SUSQUEHANNA, POTOMAC,
AND JAMES RIVERS
BASIN
DRAINAGE AREA
(Square miles)
MEAN DAILY DISCHARGED PERIOD OF
(Cubic Feet Per Second-Per Day) RECORD
(CFSD) Beginning year-
Ending year
(Number of
years/number of
days)
Susquehanna River
(aConowingo, MD 27,100
(01578310)
Potomac River 11,560
near Washington, DC
(01646500)
James River
@Cartersville, VA 6,257
(02035000)
Annual
Winter
Spring
Summer
Fall
Annual
Winter
Spring
Summer
Fall
Annual
Winter
Spring
Summer
Fall
43,286.8
50,109.6
68,011.5
25,193.3
29,317.5
10,953.9
13,286.9
18,466.8
6,147.2
5,883.3
6,879.1
8,811.7
10,209.3
4,248.2
4,271.7
Oct. 1967-Sept.l981
(14 yrs/5072 days)
(1,264 days)
(1,288 days)
(1,277 days)
(1,243 days)
March 1930-Sept . 1981
(51 yrs. 718,842 days)
(4,603 days)
(4,784 days)
(4,784 days)
(4,671 days)
Oct. 1924-Sept. 1981
(57 yrs. /20,505 days)
(5,060 days)
(5,156 days)
(5,155 days)
(5,134 days)
(1) Winter = December, January, February
Spring = March, April, May
Summer = June, July, August
Fall = September, October, November
Statistical comparisons between the Conowingo Station data and Harrisburg
Station data indicate that the 1967 through 1981 periods are
representative of the long term stream flow characteristics.
(2) Discharges shown were computed from records retrieved through the
USEPA-STORET data bank as transferred from the USGS-WATSTORE system.
Water Year 1981 records used are provisional and subject to revision.
adjustments (i.e., for diversions) have been made to the discharges.
Computations were made using the Statistical Analysis System Procedure
MEANS (SAS Institute 1979).
No
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Computation of Riverine-Transported Nutrient and Sediment Loads
To predict the statistically significant, expected value of the daily
nutrient loading from each of the major tributaries, we extrapolated the
nutrient data collected during the fall line monitoring project through a
series of linear and log-linear regression models. These models reslate
nutrient concentration, or nutrient loading rate, with mean daily discharge
for each of the monitored tributaries. In all cases, models were developed
using bivariate least squares regression techniques.
The independent, or predictor variable (X, in equation 1II-2) , is the
mean daily discharge of the flow-monitoring station adjacent to the water
quality monitoring site. We eliminated from consideration other potential
independent variables such as instantaneous flow, specific conductance, or
sediment concentration (Lang and Grason 1980, Lang 1982) in either
univariate or multivariate models, because there is no available long-term
record of occurrences of these water qualilty constituents.
The models tested in this analysis were either linear, or linearized
through transformations of the variables. This infers a direct
relationship between the frequency-duration distribution of the independent
variable (mean daily discharge) and that of the response variable (e.g.,
daily nutrient loads). It is implied that the response variable has the
identical (but perhaps transformed) frequency-duration distribution of the
predictor variable. Only a parameter with a long-term period of record
sufficient to develop a reliable frequency-duration relationship should be
utilized as a predictor variable. This limitation restricted the model
formulation process to use of mean daily discharge (Q) as the independent
variable in all models.
The period of record and the number of years of daily discharge data
available at each site are shown in Table III.l. For further detail on the
model development methodology, see Appendix A. This appendix contains the
equations used to normalize storm events. Development of concentration and
loading rate models using regression analysis is also explained.
Regression Analysis Results
As mentioned above, the development of the regression equation and the
model selection methodology can be found in Appendix A. The models chosen,
along with the appropriate regression statistics, are shown in Table III.2,
II1.3, and II1.4 for the Susquehanna, Potomac, and James stations
respectively. For example, the variance-stabilizing transformations were
selected for the Susquehanna River for the variables TN, DN, N023, TKN, and
DP (Table III.2) . These models either had r2 values below 0.65 for NH34,
TP,OP, and SED (Table III.3), or the examination of scatter plots did not
support the use of a variance stabilizing transformation and, therefore,
loading rate models were selected for these variables.
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TABLE III.2.
REGRESSION MODELS CHOSEN FOR THE SUSQUEHANNA RIVER AT
CONOWINGO, MD (1578310)
Water Regressed
Model Quality Intercept
Chosen Constituent (BQ)
ln(C/Q) vs ln(l/Q)
ln(C/Q) vs ln(l/Q)
ln(C/Q) vs ln(l/Q)
ln(LR) vs ln(Q)
ln(C/Q) vs ln(l/Q)
ln(LR) vs ln(Q)
ln(C/Q) vs ln(l/Q)
ln(LR) vs ln(Q)
ln(LR) vs ln(Q)
TN
DN
N023
NH34
TK.N
TP
DP
OP
SED
-0.318
0.0762
-0.600
-2.48
-1.732
-5.74
-4.42
-3.40
-1.19
Regressed
Slope
(B!)
0.937
0.982
0.948
1.15
0.921
1.42
0.972
1.11
1.56
Pr (I* Coefficient Degrees of
value of Freedom
t Determination
(slope) i
0.0001
0.0001
0.0001
0.000l(2)
0.0001
0.000l(2)
0.0001
0.000l(2)
0.0001(2)
(r2)
0.92
0.93
0.87
0.71
0.81
0.89
0.78
0.73
0.66
86
66
86
86
87
87
85
66
93
'•I'Students "t" test for Ho: slope = 0. The probability value shown
answers the question "If the parameter is really equal to zero, what is
the probability of getting a larger value of it?" A very small value for
this probability indicates that the slope is not likely to equal zero
and, therefore, that flow (or the indicated transformed flow) contributes
significantly to the model (SAS 1979, Procedure: General Linear Models).
(2)
NjB: The relationship implied by this model may be biased and,
therefore, may limit the usefulness of the student's
text).
"t" test (see
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TABLE III.3.
REGRESSION MODELS CHOSEN FOR THE POTOMAC RIVER AT CHAIN BRIDGE,
WASHINGTON, DC (1646580)
Water Regressed
Model Quality Intercept
Chosen Constituent (%)
ln(C/Q)vs.ln(l/Q)
ln(C/Q)vs.ln(l/Q)
ln(C/Q)vsln(l/Q)
ln(LR)vs.ln(Q)
ln(C/Q)vs.ln(l/Q)
ln(LR)vs.ln(Q)
ln(C/Q)vs.ln(l/Q)
ln(LR)vs.ln(Q)
ln(LR)vs.ln(Q)
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
-0.942
-1.49
-1.22
-3.53
-2.53
-3.87
-4.67
-2.58
-4.76
Regressed
Slope
(BL)
0.857
0.827
0.881
1.23
0.807
1.33
0.885
1.08
2.06
Pr (1) Coefficient Degrees of
value of Freedom
t Determination
(slope) i
0.0001
0.0001
0.0001
0.000l(2)
0.0001
0.0001^2)
0.0001
0.000l(2)
0.000l(2)
(r2)
0.86
0.84
0.80
0.71
0.72
0.85
0.72
0.70
0.88
64
63
64
61
80
79
77
47
60
d'
Students "t" test for HO: slope = 0. The probability value shown
answers the question "If the parameter is really equal to zero, what is
the probability of getting a larger value of it?" A very small value
for this probability indicates that the slope is not likely to equal
zero and, therefore, that flow (or the indicated transformed flow)
contributes significantly to the model (SAS 1979, Procedure: General
Linear Models).
relationship implied by this model may be biased and,
therefore, may limit the usefulness of the student's
text) .
"t" test (see
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TABLE III.4.
REGRESSION MODELS CHOSEN FOR THE JAMES RIVER AT CARTERSVILLE,
VA (2035000)
Model
Chosen
Water Regressed
Quality Intercept
Constituent (B0)
Regressed
Slope
(Bi)
Pr (I' Coefficient Degrees of
value of Freedom
t Determination
(slope)
ln(C/Q)
ln(C/Q)
ln(C/Q)
ln(C/Q)
ln(LR)
ln(C/Q)
ln(C/Q)
ln(C/Q)
ln(LR)
vs. ln( 1/Q)
vs.ln(l/Q)
vs. ln( 1/Q)
vs.ln( 1/Q)
vs.ln(Q)
vs.ln( 1/Q)
vs.ln(l/Q)
vs .ln(l/Q)
vs.ln(Q)
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
-2
-1
-2
-4
-1
-3
1
0.
-5
.11
.09
.20
.09
.72
.18
.07
0494
.06
0
0
0
0
1
0
1
1
2
.802
.957
.902
.909
.28
.885
.45
.35
.12
0
0
0
0
0
0
0
0
0
.0001
.0001
.0001
.0001
.0001(2)
.0001
.0001
.0001
.0001(2)
(r2)
0
0
0
0
0
0
0
0
0
.82
.89
.76
.65
.86
.67
.91
.82
.90
54
38
56
49
55
56
56
46
71
(2)
Students "t" test for HQ: slope = 0. The probability value shown
answers the question "If the parameter is really equal to zero, what is
the probability of getting a larger value of it?" A very small value for
this probability indicates that the slope is not likely to equal zero
and, therefore, that flow (or the indicated transformed flow) contributes
significantly to the model (SAS 1979, Procedure: General Linear Models).
NB_: The relationship implied by this model may be biased and,
therefore, may limit the usefulness of the student's "t" test (see
text).
Computation of Nutrient and Sediment Loads from the Major Tributaries
Each of the regression equations shown in Tables III.2, III.3, and III.4
were encoded in a Statistical Analysis System (SAS Institute 1979) program.
This program computed a daily load for each day in the period of record of the
flow data (Table III.l), multiplied the individual daily load by the relative
frequency of the day's flow (relative frequency = I/ number of days in period
of record), and summed the product over the period of record. In this way,
the program computed the area under the loading-frequency curve of one-day
duration, which is equivalent to the expected value of daily loading. This
technique ensured proper computation of expected values whether the model
being used was linear or non-linear. Computations were performed for annual
and seasonal discharge-frequency distributions of the three major tributaries
for the parameters shown in Table A-l. The results of these computations for
annual, winter, spring, summer, and fall seasons are presented in Tables
III.5(a), III.6(a), III.7(a), III.8(a), and III.9(a) respectively. Percentage
breakdowns for each source are listed for annual, winter, spring, summer, and
fall seasons in Tables III.5(b) , III.6(b), III.7(b), III.8(b), and 111.9(b)
respectively.
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Not computed here are flow/load ratios which would show that although the
Susquehanna River has the largest flows, the ratios of material to flow, and
material to drainage area, are no greater than in the other tributaries. In
fact, these ratios are less than those in several of the other Bay tributaries.
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TABLE III.5(a). ESTIMATED ANNUAL MEAN DAILY NUTRIENT AND SEDIMENT LOADS TO THE
CHESAPEAKE BAY SYSTEM FROM SOURCES TRANSPORTED BY RIVERS
(ALL VALUES x 103 LBS/DAY UNLESS OTHERWISE INDICATED)
Constituent Susquehanna
Total Fluvial
Load to the
Potomac James Other Tribs. Bay System
TN
DN
N023
NH34
TKN
TP
DP
OP
SED 7,
Discharge 43,
342.84
307.81
228.70
19.41
99.70
15.65
3.84
4.93
263.44
286.8cfsd
95.27
74.38
56.75
3.18
32.14
6.26
1.73
1.83
5,986.22
10,953.9cfsd
29.11
18.65
10.31
1.46
17.49
4.54
1.80
1.58
2,979.81
6,879.1cfsd
20.39(D
14.49(2)
9.15
0.74
11.24
1.69
0.57(3)
0.54(4)
1,925.5(5)
3,525cfsd(6)
468.61
415.33
304.91
24.79
160.57
28.14
7.94
8.88
18,155.00
64,644. 8cfsd
^ 'Computed as
'2 )fTc(- imaj-pH K
the sum of
v r r*m n M t~ i no
N02j3 + TKN
f"H£> mf^^n n f
DN-TN r-at-inc
fni- fho Pnt-nm;
if a nH Ta m^ c
(3)
(4)
(5)
(6)
and applying to the estimated TN loading rate for the 'Other Tribs.' The
Susquehanna was excluded from this calculation because it is a regulated
(i.e. reservoirs) system; mean DN:TN = 0.711, sd. = 0.10
Same method as in footnote 2 above; mean DP:TP = 0.336, sd. = 0.08.
Same method as in footnote 2 above; mean OP:TP = 0.320, sd. = 0.004.
Computed by applying the mean unit area sediment load from the Potomac and
James (497.0 Ibs/mi^/day) to the total drainage area of the minor
tributaries (3874 mi^), as measured at the USGS gauges used by Guide and
Villa (1972). The standard deviation of mean areal loading rate = 29.4.
Approximate annual mean daily flow for the Rappahannack, Mattaponi,
Paumunkey, Patuxent, and Chickahominy Rivers from various USGS Water
Resources Data Publications. The drainage area above the collected gauges
is about 3874 square miles.
TABLE III.5(b) .
ESTIMATED PERCENTAGE OF TOTAL ANNUAL NUTRIENT AND SEDIMENT
LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Const ituent
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
Discharge
Susquehanna
73.2
74.1
75.0
78.3
62.1
55.6
48.4
55.5
40.0
67.0
Potomac
20.3
17.9
18.6
12.8
20.0
22.2
21.8
20.6
33.0
16.9
James
6.2
4.5
3.4
5.9
10.9
16.1
22.7
17.8
16.4
10.6
Other Tribs.
4.4
3.5
3.0
3.0
7.0
6.0
7.2
6.1
10.6
5.5
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TABLE III.6(a).
ESTIMATED WINTER MEAN DAILY NUTRIENT AND SEDIMENT LOADS TO THE
CHESAPEAKE BAY SYSTEM FROM SOURCES TRANSPORTED BY RIVERS
(ALL VALUES x 103 LBS/DAY UNLESS OTHERWISE INDICATED)
Constituent Susquehanna
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
397.20
356.44
264.94
22.47
115.51
17.83
4.44
5.72
8,121.18
Potomac
95.27
90.58
69.09
3.87
39.14
59
11
23
6,295.99
James
29.11
24.00
13.34
1.89
22.93
5.89
2.13
1.91
3,616.87
Other Tribs.
Total Fluvial
Load to the
Bay System
20.09(1)
14.18(2)
10.74
0.87
9.35
1.65
0.53(3)
0.51(4)
2,174.65(5)
571.29
485.2
358.11
29.10
186.93
32.96
9.21
10.37
20,208.69
Discharge 50,109.6cfsd 13,286.9cfsd 8,811.7cfsd
(1'Computed as the sum of N0£ 3 + TKN.
(^Estimated using methodology shown in TABLE III.9(a), footnote (2). Winter
mean DN-.TN = 0.706, SD = 0.11.
(^Estimated as in TABLE III.9(a), footnote (3). Potomac and James Winter
mean DP:TP = 0.320, SD = .02.
(^Estimated as in TABLE 111.9(a) , footnote (4). Potomac and James Winter
mean OP:TP = 0.304, SD = .02.
(^Estimated as in TABLE III.9(a), footnote (5). Potomac and James Winter
mean areal sediment loading rate = 561.34 Ibs/mi2/day), SD = 23.6.
TABLE III.6(b) .
ESTIMATED PERCENTAGE OF WINTER NUTRIENT AND SEDIMENT LOADS
LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Constituent Susquehanna
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
69.5
73.5
74.0
77.2
61.8
54.1
48.2
55.2
Potomac
40.2
20.3
18.7
19.3
13.3
20.9
23.0
22.9
21.5
31.2
James
6.6
4.9
3.7
6.5
12.3
17.9
23.1
18.4
17.9
Other Tribs,
3.5
2.9
.0
.0
.0
3.
3.
5,
5.0
5.7
4.9
10.8
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ESTIMATED SPRING MEAN DAILY NUTRIENT AND SEDIMENT LOADS TO THE
CHESAPEAKE BAY SYSTEM FROM SOURCES TRANSPORTED BY RIVERS
(ALL VALUES x 103 LBS/DAY UNLESS OTHERWISE INDICATED)
Total Fluvial
Constituent Susquehanna
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
546.10
485.60
363.46
31.42
159.32
26.08
6.07
7.93
12,110.89
Potomac
166.84
131.18
98.80
5.69
56.94
11.39
3.01
3.16
,556.71
James
44.50
27.89
15.55
2.20
26.94
6.87
2.36
2.15
4,232.68
Other Tribs.
27.58(D
19.50(2)
14.78
1.22
12.8
2.33
0.7lO)
0.69(4)
3,247.76(5)
Load to the
Bay System
785.02
664.17
492.59
40.53
256.00
46.67
12.15
13.93
31,148.04
Discharge 68,011.Scfsd 18,466.8cfsd 10,209.3cfsd
(^Computed as the sum of N02 3 + TKN.
^2'Estimated using methodology shown in TABLE III.9(a), footnote (2). Spring
mean DN:TN = 0.707, SD = 0.11.
(^Estimated as in TABLE III.9(a), footnote (3).
mean DP:TP = 0.304, SD = .06.
(^Estimated as in TABLE III.9(a), footnote (4).
mean OP:TP = 0.295, SD = .03.
^'Estimated as in TABLE III.9(a), footnote (5). Potomac and James Spring
mean areal sediment loading rate = 838.09 Ibs/mi2/day), SD = 228.6.
Potomac and James Spring
Potomac and James Spring
TABLE III.7(b). ESTIMATED PERCENTAGE OF SPRING NUTRIENT AND SEDIMENT
LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Const ituent
TN
DN
N023
NH34
TKN
TP
DP
op
SED
Susquehanna
69.6
73.1
73.8
77.5
62.2
55.9
50.0
56.9
38.9
Potomac
21.3
19.8
20.1
14.0
22.2
24.4
24.8
22.7
37.1
James
5.7
4.2
3.2
5.4
10.5
14.7
19.4
15.4
13.6
Other Tribs.
3.5
2.9
3.0
3.0
5.0
5.0
5.8
4.9
10.4
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TABLE III.8(a).
ESTIMATED SUMMER MEAN DAILY NUTRIENT AND SEDIMENT LOADS TO THE
CHESAPEAKE BAY SYSTEM FROM SOURCES TRANSPORTED BY RIVERS
(ALL VALUES x 103 LBS/DAY UNLESS OTHERWISE INDICATED)
Constituent Susquehanna
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
195.66
178.06
130.92
10.87
56.66
8.92
2.21
2.78
4,398.53
Potomac
49.07
37.66
29.64
1.56
16.10
2.92
0.91
0.98
2,531.19
James
16.83
11.32
6.14
0.87
9.94
2.69
1.38
16
Other Tribs.
5.16
0.41
6.22
0.93
0.38(3)
0.36(4)
Total Fluvial
Load to the
Bay System
272.94
235.23
171.86
13.71
88.92
15.46
4.88
.28
2,318.98 1,142.02(5) 10,390.72
Discharge 25,193.3cfsd 6,147.2cfsd 4,248.2cfsd
'Computed as the sum of N0£ 3 + TKN.
^'Estimated using methodology shown in TABLE III.9(a) , footnote (2). Elummer
mean DN:TN = 0.720, SD = 0.07.
(-^Estimated as in TABLE III.9(a), footnote (3). Potomac and James Summer
mean DP:TP = 0.412, SD = 0.142.
(^)Estimated as in TABLE III.9(a), footnote (4). Potomac and James Summer
mean OP:TP = 0.383, SD = 0.07.
(-"'Estimated as in TABLE III.9(a) , footnote (5). Potomac and James Summer
mean areal sediment loading rate = 294.79 Ibs/mi^/day), SD = 107.24
TABLE III.8(b). ESTIMATED PERCENTAGE OF SUMMER NUTRIENT AND SEDIMENT
LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Constituent Susquehanna
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
71.7
75.7
76.2
79.3
63.7
57.7
45.3
52.7
42.3
Potomac
18.0
16.0
17
11
18
18
18.6
18.6
24.4
James Other Tribs.
6.2 4.2
4.81 3.5
3.6 3.0
6.4 3.0
11.2 7.0
17.4 6.0
28.3 7.9
22.0 6.8
22.3 11.0
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TABLE III.9(a).
ESTIMATED FALL MEAN DAILY NUTRIENT AND SEDIMENT LOADS TO THE
CHESAPEAKE BAY SYSTEM FROM SOURCES TRANSPORTED BY RIVERS
(ALL VALUES x 103 LBS/DAY UNLESS OTHERWISE INDICATED)
Constituent
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
Discharge
Susquehanna
228.17
207.42
152.66
12.62
66.06
9.56
2.58
3.42
4,311.54
29,317.5cfsd
Potomac
48.85
37.86
29.29
1.60
16.29
3.11
0.89
0.96
3,514.34
5,883cfsd
James
17.23
11.44
6.23
0.88
10.22
2.74
1.34
1.13
1,757.22
4,271.7cfsd
Other Tribs.
12.79^1)
9.02(2)
5.82
0.47
6.97
0.98
0.38(3)
0.36(4)
1,132.85
Total Fluvial
Load to the
Bay System
307.04
265.92
194.00
15.57
99.54
16.39
5.19
5.87
10,715.95
d'Computed as the sum of N02 3 + TKN.
(^Estimated using methodology shown in TABLE III.9(a), footnote (2). Fall
mean DN:TN = 0.719, SD = 0.08.
(^Estimated as in TABLE III.9(a), footnote (3). Potomac and James Fall
mean DP:TP = 0.388, SD = 0.14.
(^Estimated as in TABLE III.9(a) , footnote (4). Potomac and James Fall
mean OP:TP = 0.361, SD = 0.07.
(^Estimated as in TABLE III.9(a) , footnote (5). Potomac and James Fall
mean areal sediment bed = 292.43 Ibs/mi2/day), SD = 16.38
TABLE III.9(b). ESTIMATED PERCENTAGE OF FALL NUTRIENT AND SEDIMENT
LOADS FROM CHESAPEAKE BAY TRIBUTARIES
Constituent
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
Susquehanna
74.3
78.0
78.7
81.1
66.4
58.3
49.7
58.3
40.2
Potomac
15.9
14.2
15.1
10.3
16.4
19.0
17.2
16.4
32.8
James
5.6
4.3
3.2
5.7
10.3
16.7
25.8
19.3
16.4
Other Tribs.
4.2
3.5
3.0
3.0
7.0
6.0
7.3
6.1
10.6
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NUTRIENT INPUTS FROM SELECTED MINOR TRIBUTARIES
Guide and Villa (1972) reported seasonal and annual nutrient loadings
from five of the next largest tributaries (after the Susquehanna, Potomac,
and James) of the western shore of Chesapeake Bay. These basins are the
Patuxent, Rappahannock, Mattaponi, Paumunkey, and Chickahominy Rivers, that
together, drain parts of the Blue Ridge, Piedmont, and Coastal
physiographic provinces (Figure III.2). Loading estimates by Guide and
Villa were made for the areas of the tributaries that drain above USGS
discharge monitoring stations. The land-area contributing to these
estimates totaled 3,874 square miles, or about 6.1 percent of the total Bay
drainage basin, with an accummulated mean daily discharge of about 3,535
cfsd.
Guide and Villa observed, for the period June, 1969, through August,
1970, that these five basins generally contributed about five percent or
less of the nutrient loading of various nitrogen and phosphorus species.
They found that for the entire period of observation those minor
tributaries contributed six percent, seven percent, three percent, and
three percent of TP, TKN, N02)3, and HN3j4 loads respectively [see
Table III.5(b)]. Similarly, they found that for the winter and spring
months, these basins contributed five percent, five percent, three percent,
and three percent of TP, TKN, N0£ 3, and NH3 4 loads respectively,, All
loading estimates in that study were performed using log-linear models of
loading rate versus mean daily discharge developed with bivariate least
squares techniques. These methods were very similar to those used in the
previous section of this chapter and described in Appendix A.
Estimates of nutrient loadings were developed from the minor western
shore tributaries by utilizing the percentages reported by Guide and Villa
(1972) in conjunction with the estimate made in the previous section of the
loadings from the three major tributaries. For example, the annual mean
daily TP load from the three major tributaries is estimated in Table
III.5(a) to be 2.64 x 10^ pounds. If it is assumed, after Guide and
Villa (1972), that 6 percent of the total phosphorus load comes from the
minor tributaries, then the 2.64 x 10^ pounds of phosphorus should be
about 94 percent of the total load. The total TP load, therefore, should
be about 2.81 x 10^ pounds per day, and by difference, the load from the
minor tributaries about 1.69 x 10^ pounds per day.
The annual and seasonal expected daily nutrient loadings from the minor
tributaries have been computed in the manner described above and are
presented in the fifth column of Tables III.5(a), III.6(a), III.7(a),
III.8(a), and III.9(a) . The estimates shown in these tables for the minor-
basin DN, DP, and OP loadings were made, based upon the mean of the DN:TN,
DP:TP, and OP:TP ratios of the Potomac and James^. The estimates for the
minor tributaries' sediment loads were made by computing the mean areal
(per unit area) sediment loads on the Potomac and James ^ and applying
Susquehanna loading ratios and areal sediment yield rates were not
used because that river system is regulated by the reservoirs in the
downstream main stem. Lang (1982) notes that the Susquehanna reservoirs
cause sediment deposition and transformation among nutrient species.
These transformations would not normally occur in free flowing streams
like the minor tributaries under consideration.
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them to the 3874 square mile drainage area of the five small tributaries. The
calculations used for both these methods are shown in the footnotes of each
table.
COMPUTATION OF TOTAL NUTRIENT AND SEDIMENT LOADS FROM RIVERINE TRANSPORTED
SOURCES
The loading rates for each of the major tributaries and the estimates of
those from the minor tributaries are included in the 'a' parts of Tables III.5
through III.9. These sources are summed to form the sixth column of those
tables for the annual and for each of the four seasonal loading rates. The
percentage that each of these sources contributes to the total load has been
computed and is included as the 'b1 parts of Tables III.5 through III.9.
Inspection of the loading percentages shown in Table III.5(b) reveals that
the Susquehanna probably carries about 70 percent of the total nitrogen and 56
percent of the total phosphorus delivered to the Bay each year from
riverine-borne sources. Most of these loadings are carried during the winter
and spring seasons [Table III.6(a) and III.7(a)]. The predominent form of
fluvial-transported nitrogen entering the system is nitrate + nitrite, with
this effect most pronounced in the spring [Table III.7(a)]. Phosphorus enters
the system from riverine-transported sources primarily in the suspended phase.
The Susquehanna produces a much smaller fraction of the total
riverine-borne phosphorus load than that of nitrogen, contributing about 50
percent in the winter and 58 percent of the total load in the summer. The
same trend occurs when considering the sediment loads to the Bay, with the
Susquehanna producing only about 40 percent in any season — usually less than
that transported by the Potomac and" James taken together. The small fraction
of both the phosphorus and sediment loads produced by the Susquehanna relative
to its drainage area and flow, no doubt, is due to the trapping of particulate
matter in the reservoirs located on the lower sixty miles of the main stem of
the river. For example, in an average spring season, the Potomac and James
taken together contribute daily about 840 pounds of suspended sediment per
square mile of drainage while the Susquehanna would produce only about 447
pounds per square mile, or roughly about half as much^.
The data included in Tables III.5(a) through III.9(a) were used to
generate total expected seasonal and annual riverine-borne mass loadings of
nutrients and sediments to the Bay system. The results of these computations
are found in Table III.10.
Fluvial transported loadings are compared with other nutrient sources in
Chapter VIII. For example, in Table VIII.3(b) shows that riverine transported
sources provide the largest proportion of all nutrients entering the Bay
system in spring, with the exception of orthophosphate.
In summary, stream-transported loading estimates have been computed for
the Chesapeake Bay system. These estimates are well within order of magnitude
accuracy and are suitable for comparison with the estimated loads from other
sources discussed in this paper.
•"-Lang (1982) notes that the Susquehanna system probably begins to scour
(deliver to the Bay) the sediment stored in the reservoirs at flows above
400,000 cfs. Flows that large occur only less than one percent of the time,
however. Most of the time the reservoirs act as an efficient sediment
trap.
179
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TABLE III.10.
SEASONAL AND ANNUAL NUTRIENT AND SEDIMENT LOADS TRANSPORTED BY
RIVERS TO THE TIDAL CHESAPEAKE BAY SYSTEM,
(MILLIONS OF POUNDS UNLESS OTHERWISE NOTED)
Constituent
TN
DN
N023
NH34
TKN
TP
DP
OP
SED
Winter
51.4
43.7
32.2
2.62
16.8
2.97
0.829
0.933
1.83x109
Spring
72.2
61.1
45.3
3.73
23.6
4.29
1.12
1.28
2.87x109
Summer
25.1
21.6
15.8
1.26
8.18
1.42
0.449
0.486
1.07xl09
Fall
27.9
24.2
17.7
1.42
9.06
1.49
0.472
0.534
9.75xl08
Annu a 1
178.1
151.7
111.47
9.06
58.6
10.3
2.907
3.24
6.63xl()9
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The Tables (A-2, A-3, and A-4), presented in Appendix A, show that poor
fits (r2<'o.50) were found in almost all cases, for the concentration-
versus-discharge models. In most cases visual inspection of scatter
diagrams allows a case to be made for heterosodasticity and, for this
reason, the variance-stabilizing transformation was favored in selecting
appropriate models.! Only when correlation coefficients were
significantly below 0.65, or 't1 tests (H0:B^ = 0) indicated that B]_,
the slope, was not significantly different from zero at the 95 percent
confidence level, was a loading rate model chosen.
^During the course of examination of the concentrations, predicted by each of
the models over the range of flow observed in the period of record, it was
determined that the arithmetic form of the variance-stabilizing transformation
(C/Q versus 1/Q) yielded unrealistically high values for discharges, in excess
of those observed during the period of the monitoring program. The log-log
transformation of this model [ln(C/Q) versus ln(l/Q)] proved to be much better
behaved in predicting concentrations for these higher flows. The curves pro-
duced with this transformation 'flatten out1 very quickly, as flows approach
those at the upper limit of the discharge data, observed during the field pro-
gram. Therefore, only the log transformed versions of the variance-stabilizing
transformation were considered for cases exhibiting heterosodasticity.
181
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SECTION IV
POINT SOURCE LOADINGS OF NUTRIENTS
Water quality managers and researchers typically divide sources of
water pollution into two broad categories: point and nonpoint. Although
the distinction between them is not always clear, point sources are
generally described as those discharging to a water body from a discrete
pipe or ditch. Examples of point sources are municipal sewage treatment
plant discharges, industrial discharges, and combined sewer overflows.
Nonpoint sources arise from multiple causes and can be dramatically
affected by rainfall and storms. Examples of nonpoint sources are runoff
from urban and suburban storm sewers, agricultural activities, forestry
activities, and atmospheric deposition.
The objective of this Section is to estimate the load of nutrients
discharged to the Bay system from point sources. Table IV.1 lists the
nutrients analyzed for estimating loads. Municipal and industrial point
source loadings are estimated separately. Estimations are made above and
below the head of tide, or fall line, for the river systems (major/minor)
discharging to Chesapeake Bay. Loadings below the fall line represent
point source loads to the tidal Bay system in excess of what was computed
in riverine loads of Section 3.
The river basins that make up the Bay's 64,000 square mile drainage
area are delineated by EPA in its STORE! data system and are illustrated in
Figure IV.1. (STORET is a computerized data base maintained by EPA for the
storage and retrieval of parametric data, relating to the quality of the
waterways of the United States.) The "fall line"1 is delineated by USGS
hydrologic units (USGS, office of Water Data Coordination in consultation
with the U.S. Water Resource Council) and is also illustrated in Figure
IV.1. Section III discussed point sources of nutrients discharging above
the fall line, reflected in the fluvial loads computed at the fall line
monitoring stations of the Bay's three major tributaries. Therefore, for
this section, it was important to know which point sources discharge above
the line and which discharge below, so that a double counting could be
avoided. For this analysis, loads generated above the fall line are
included in the fall line monitoring data, but those generated below the
fall line are
•'•The "fall line" defined for the purpose of this Section is not the true
geologic Fall Line as defined in Section I. The functional definition of
the fall line used in this paper is the line of demarcation below the
drainage of the three major tributaries' monitoring stations (Susquehanna
at Conowingo, MD; Potomac at Chain Bridge, DC; James at Cartersville, VA)
described in Chapter III. All point sources discharging downstream of this
line are considered not to have been accounted for in the loads computed in
the previous Chapter. This definition assumes that all the point source
loadings from the Rappahannock and York Rivers (Pamunkey and Mattaponi) are
discharged below the monitoring stations employed by Guide and Villa
(1972), or that they have begun discharging since 1971 and were not
incorporated in the loads monitored during that study. In any event, the
potential for a double counting error is small as can be seen from the data
in Tables IV.12(a) and IV.12(b).
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SUSQUEHANNA
RIVER BASIN
LEGEND
BASIN BOUNDARY
FALL LINE
UPPER
CHESAPEAKE
BAYaDELMARVA
POTOMAC1^ V
RIVER BASIN
RAPPAHANNOCK^
'ORK RIVER
BASIN
'"•*
I JAMES RIVER
BASIN
Figure IV.1.
River systems discharging to Chesapeake Bay.
line indicates the USGS fall line.
183
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considered to discharge directly to the tidal waters of the Bay. Table
IV.1 identifies the USGS hydrologic units included below the fall line of
each major drainage basin. Hydrologic units, defined by the U.S.
Geological Survey, in cooperation with the U.S. Water Resources Council,
delineate the hydrographic boundaries of major river basins in the United
States. They provide a standard geographical framework for detailed,
water-related planning and serve as an aid to organizing and disseminating
data. Once point source loadings above and below the fall line for each
drainage basin are calculated, they can be compared to nonpoint source
loadings, and the relative contribution of each determined.
TABLE IV.1. WATER QUALITY VARIABLES
Water Quality Variable Variable Code
Total Nitrogen (as N) TN
Total Kjeldahl Nitrogen (as N) TKN
Total Nitrite plus Total Nitrate N02 + N03
Nitrogen (as N) or N023
Total Ammonia Nitrogen (as N) NH34
Organic Nitrogen ORGN
Total Phosphorus (as P) TP
Total Orthophosphorous (as P) OP
TABLE IV.2. USGS HYDROLOGIC UNITS BELOW THE FUNCTIONALLY-DEFINED FALL LINE
OF THE CHESAPEAKE BAY DRAINAGE BASIN
Drainage Basin USGS hydrologic units included
below fall line
Susquehanna
0212
Upper Chesapeake 02 - 06 - 00 - 02
Bay & Delmarva 02 - 06 - 00 - 03
0213 02 - 06 - 00 - 04
02 - 06 - 00 - 05
02 - 06 - 00 - 06
02 - 06 - 00 - 07
02 - 06 - 00 - 08
02 - 06 - 00 - 09
02 - 08 - 01 - 09
(continued)
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TABLE IV.2. (continued)
Potomac 02 - 07 - 00 - 10
0214 02 - 07 - 00 - 11
Rappahannock/York 02 - 08 - 01 - 02
0215 02 - 08 - 01 - 03
02 - 08 - 01 - 04
02 - 08 - 01 - 05
02 - 08 - 01 - 06
02 - 08 - 01 - 07
James 02 - 08 - 02 - 05
0216 02 - 08 - 02 - 06
02 - 08 - 02 - 07
02 - 08 - 02 - 08
02 - 08 - 01 - 08
Estimation of Nutrient Loads from Municipal Point Sources
The basic strategy for estimating nutrient loads from municipal point
sources or publicly owned treatment works (POTWs), called for merging
computerized data bases and accessing state and facility effluent
monitoring data. The data bases merged included the EPA 1980 Needs Survey
(Needs) and the Industrial Facilities Dischargers (IFD) file. The 1980
Needs Survey is performed in compliance with the provisions of Sections 205
(a) and 516 (b)(2) of the Clean Water Act Amendments of 1977, PL 95-217.
The Survey collects technical and administrative data on new and existing
POTWs, which then serve as a basis for Congressional allotment of
construction grant funds among the states. The Needs data base provided an
inventory of existing and projected flows, and of levels of treatment for
POTWs. The IFD file is a comprehensive data base on municipal and
industrial dischargers assembled by the Monitoring and Data Support
Division of EPA. It was used to verify the Needs file and furnished
valuable locational information.
Although the merging of these data bases generated an inventory of
POTWs and provided a substantial amount of information concerning their
flow, level of treatment, and location, it did not provide information
concerning the concentration of nutrients in effluents. To obtain this
information, we began a systematic analysis of the CBP-generated data
base. This analysis determined the percentage of total flow contributed by
POTWs in different flow (size) categories. It indicated that there are 580
POTWs located within the Chesapeake Bay drainage basin having a combined
flow of 1350 million gallons/day (MGD). Further analysis revealed that 96
percent of this flow is contributed by the 197 POTWs larger than 0.5 MGD,
and 78 percent of the flow by the 47 POTWs larger than 5.0 MGD. Based on
this analysis and existing data needs, we requested necessary information
from the Maryland Department of Health and Mental Hygiene, Office of
Environmental Programs (OEP), the Virginia State Water
Control Board (VSWCB), and the Pennsylvania Department of Environmental
Resources (DER).
185
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Each State staff was requested to provide 1980 data on operational
flow, total nitrogen (TN), total phosphorus (TP), five-day biological
oxygen demand (BOD5) , and total suspended solids (SED) concentration for
the POTWs larger than 5.0 MGD within their political boundaries. In
addition, the tasks were intended to determine the status of certain
dischargers that were in question. State expertise in these areas was
invaluable. In the meantime, estimates of the concentration of these
pollutants in wastewater after different levels of treatment were made
(Earth 1981)1 ancj inciuded in the CBP data base. They are presented in
Table IV.3. This table shows that for BOD, a lot of difference exists
between primary and secondary treatment. However, to obtain decreases in N
and P, tertiary treatment must probably be used. Later, program
requirements dictated that the TN and TP estimates be broken down into
various species. This information (Barth 1981)1 is presented in Table
IV.4. Again, not until AWT is used, will any significant decreases in N
and P occur.
The response from States staffs was very good, and we updated the CBP
data base with the provided information. In addition, we contacted several
POTW operators and requested actual data or estimates of nutrient
concentrations in their effluent. This information was also added to the
CBP data base and is presented in Table IV.5.
Using the updated CBP data base and our functional definition of the
fall line, we calculated nutrient loads from POTWs above and below the fall
line. This information is presented in Table IV.6 and is currently
undergoing final review by the states' staffs. This table shows that the
largest loadings above the fall line are discharged within the Susquehanna
drainage basin and, with the exception of TN (Potomac 57,489 Ibs/day vs.
James 43,770 Ibs/day), the largest loadings below the fall line are
discharged within the James drainage basin. The smallest loadings above
the fall line are discharged within the Upper Chesapeake Bay - Uelmarva
drainage basin and below the fall line within the Rappahanock - York
drainage basin. The large loadings from the Susquehanna indicate that its
basin is largely located above the fall line, but the small loadings from
the Upper Chesapeake Bay - Delmarva indicate it is mostly located below the
fall line. The small load from the Rappahannock/York is due to lack of
development. It is interesting to note that although the Potomac drainage
basin receives the greatest total volume of treated wastewater (589 MGD),
its total TP load (9,583 loads/day) is less than that from the Susquehanna
(16,052 Ibs/day) and James (11,920 Ibs/day). This results from the large
volume of wastewater undergoing phosphorus removal at the Blue Plains POTW.
Personal Communication: "Fractions of Nitrogen and Phosphorous in
Effluents," and others, E.F. Barth, Biological Treatment Section,
Municipal Environmental Research Laboratory, U.S. Environmental
Protection Agency, Cincinnati, OH, 1981.
186
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TABLE IV.3. RANGE OF POTW CONSTITUENTS CONCENTRATIONS BASED ON LEVEL OF
TREATMENT (MG/L) (SOURCE: BARTH 1981)
Treatment Level
None (Raw Discharge)
Primary^
Advanced Primary^
Secondary^
Advanced Secondary
(Nitrification)
Tertiary
(Nitrogen removal
and P removal)
210
130
60
20
10
5
BOD5
- 300
- 140
- 65
- 30
- 20
- 10
SED
230
100
40
20
10
5
- 300
- 130
- 52
- 30
- 20
- 10
TN
15 -
13.5 -
12 -
12 -
10 -
3 -
30
- 28
25
25
20
10
TP
9 -
9 -
8 -
7 —
i -
0.1 -
11.5
10
9
9
2
2
^-Preliminary treatment (bar screen and grit removal) and primary
sedimentation.
^Primary treatment with post aeration.
^Activated sludge, rotating biological contactors, or low-rate trickling
filters.
TABLE IV.4. ESTIMATE OF DISTRIBUTION OF POTW NITROGEN AND PHOSPHORUS INTO
VARIOUS FRACTIONS ACCORDING TO SELECTED TREATMENT PROCESS
(MG/L) (SOURCE: BARTH 1981) THE TN AND TP VALUES IN THIS TABLE
REPRESENT THE AVERAGE OF THE RANGE OF TN AND TP CONCENTRATIONS
FROM TABLE IV.3
Nitrogen
Treatment
None
Org-N
9
TKN
22.5
NH34
13.5
Fractions
N023
0
TN
22.5
Phosphorus Fractions
Insol +
Poly
6.75
OP
3.5
TP
10.25
(Raw discharge)
Primary
Advance
Primary
Secondary
AST
AWT
7.0
6.5
3.0
2.0
1.5
20.75
18.5
16.5
3.0
2.5
13.75
12
13.5
1.0
1.0
0
0
2.0
12
4.0
20.75
18.5
18.5
15
6.5
5.25
4.25
1.2
0.5
—
4.25
4.25
6.8
1.0
1.05
9.5
8.5
8.0
1.5
1.05
187
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188
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TABLE IV.6. ESTIMATES OF NUTRIENT LOADS FROM MUNICIPAL POINT SOURCES
ABOVE AND BELOW THE FUNCTIONALLY-DEFINED FALL LINE
(ALL VALUES IN LBS/DAY EXCEPT FLOW IN MGD)
Drainage
Basin
Susquehanna
(0212)
Upper
Chesapeake
Bay and
Delmarva
(0213)
Potomac
(0214)
Rappahannock/
York
(0215)
Water Quality
Parameter
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BODS
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Above
105899
16018
11504
48098
33502
14596
24353
9149
329
64
7
4
41
16
25
8
7
.3
29972
2883
2555
13089
8616
3760
6049
3014
87
355
55
42
310
112
198
69
43
2.4
Below
134
34
29
85
71
14
58
13
.6
54824
8224
5781
26406
12916
9482
10404
4303
164
50277
6700
5251
57489
26764
30298
23445
9263
502
2675
576
458
1542
1196
346
922
274
10.4
Total
106033
16052
11533
48183
33573
14610
24411
9162
330
54888
8231
5785
26447
12932
9507
10412
4310
164.3
80249
9583
7806
70578
35380
34058
29494
12277
589
3030
631
500
1852
1308
544
991
317
12.8
(continued)
189
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TABLE IV.6. (continued)
James
(0216)
BODS
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
7349
1574
1218
3730
3280
450
2567
713
24
74688
10346
7237
43770
39303
7216
32991
6277
231
82037
11920
8455
47500
42583
7666
35558
6990
255
Estimation of Nutrient Loads from Industrial Point Sources
Types of industrial activity with the potential to discharge the
nutrients TP, TN, TKN, and NH3 ^ were identified through discussion with
State and EPA officials. The Standard Industrial Classification (SIC)
system, which classifies industries by their economic activity, was used to
assign codes to these discharges. For example, industries engaged in the
preparation of fresh or frozen packaged fish and seafoods were assigned SIC
code 2092, the code corresponding to that particular economic activity.
For industries engaged in petroleum refining, the SIC code assigned was
2911, the code denoting petroleum refinering as the primary economic
activity. Table IV.7 lists the industrial economic activities considered
to be nutrient generators and their corresponding SIC codes. The advantage
of SIC codes is the speedy identification of all dischargers engaged in a
particular economic activity.
The EPA/GBP computerized data base was accessed to retrieve the
industries within the selected SIC - defined categories and located within
the Chesapeake Bay drainage basin. This EPA data base includes: the
Management Information Control System (MICS) - EPA Region Ill's
(Philadelphia) computerized system containing basic information on all
NPDES permitees; the Virginia NPDES permit file - the Virginia computerized
system containing NPDES permit conditions, facility information, and
discharge monitoring report (DMR) data; the National Enforcement
Investigations Center (NEIC) system - an EPA data base generated by EPA's
effort to define Major/Minor dischargers on a uniform national basis; and
the already discussed IFD file.
Concentrations of nutrients expected to be found in the effluent from
dischargers within a selected SIC category were obtained from EPA's
Effluent Guideline Division (EGD) and the literature. Maryland 1979 NPDES
permit compliance monitoring data and Virginia DMR's were also reviewed for
observed nutrient data. Table IV.8(a) presents the nutrient
concentrations estimated for the various SIC categories when observed data
were absent. Table IV.8(b) identifies the source of the estimated
concentrations.
Most flow data from the dischargers of interest were based on state
DMR's or from NPDES permits. In some cases, flow data were not available
from the sources and so were estimated from a particular industrial
190
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activity. Loads generated in this manner, however, constitute only a small
percentage of the total loading from industrial sources and are identified
as "estimated1 load (17 percent of TP and seven percent of TN). Table IV.9
presents assigned flows and the information source. Table IV.9 also
identifies the data base providing observed/permitted flows.
Anomalies in the nutrient loadings computed with this approach were
corrected by review of assigned concentrations and flows. In many cases,
this resulted in close examination of an individual discharger and the
assignment of more accurate nutrient loadings based on observed data.
Table IV.10 lists these dischargers and their assigned nutrient loads. In
addition, State officials familiar with dischargers within their
jurisdiction have reviewed the loadings assigned to specific dischargers
for reasonableness and completeness. The industrial point source loadings
calculated in this manner for each drainage basin above and below the fall
line are presented in Tables IV.ll(a), (b) , and (c). These tables reveal
several trends. Table IV.ll(b) indicates that the largest TP and TN
contributions from industrial point sources occur within the James drainage
basin. Most of the TP load is contributed by several large meat rendering,
poultry processing, and food processing plants. The large TN load is
attributable to these same dischargers, and to the presence of petroleum
refineries and a fertilizer manufacturer in the basin. For comparative
purposes, the largest industrial load of TP (1906 Ibs/day in the James)
constitutes only 15.5 percent of the total industrial and municipal TP load
below the fall line in the James. From this we can conclude that
industrial point sources are relatively minor contributors of nutrients.
191
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TABLE IV.7. SIC CODE AND ECONOMIC ACTIVITY
SIC Code Economic Activity
2011 Meat Packing & Rendering
2016 Poultry Processing
2023 Condensed and Evaporated Milk
2024 Ice Cream and Frozen Desserts
2026 Fluid Milk
2033 Canned Fruits, Preserves and Jams
2035 Pickled Fruits and Vegetables
2037 Frozen Foods
2038 Frozen Specialties
2077 Animal and Marine Fats and Oils
2091 Canned and Cured Fish and Seafoods
2092 Fresh or Frozen Packaged Fish and Seafoods
2812 Industrial Inorganic Chemicals - Alkalines and Chlorine
2813 Industrial Inorganic Chemicals - Industrial Gases
2816 Industrial Inorganic Chemicals - Inorganic Pigments
2819 Industrial Inorganic Chemicals - Not Elsewhere Classified
2821 Plastics Materials, Synthetic Resins, & Elastomers
2822 Synthetic Rubber
2823 Synthetic Organic Fibers
2824 Industrial Organic Chemicals - Cyclic Crude & Pigments
2833 Medicinal Chemicals & Botanical Products
2869 Industrial Organic Chemicals - Not Elsewhere Classified
2873 Manuf. of Nitrogenic Fertilizers
2874 Manuf. of Phosphatic Fertilizers
2879 Pesticides & Agricultural products
2891 Adhesives & Sealants
2892 Explosives Manufacture
2893 Printing Ink
2911 Petroleum Refineries
3111 Leather Tanning and Finishing
3312 Blast Furnaces, Steel Works
3321 Gray Iron Foundries
3322 Malleable Iron Foundries
3411 Metal Can Manufacture
3471 Electroplating
3612 Power Distribution & Specialty Transformers
3621 Electrical Industry Apparatus
3644 Electric Lighting & Equipment
3674 Semiconductors & Related Devices
3679 Electronic Components
3662 Radio Detection Equipment & Apparatus
3731 Ship Building & Repair
3861 Photographic Equipment & Supplies
6515 Mobile Home Site Operators
7011 Hotels, Motels, and. Tourist Courts
7215 Coin-Operated Laundries and Dry Cleaning
8211 Elementary and Secondary Schools
8221 Colleges and Universities
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TABLE IV.8(a). SIC CODE AND ESTIMATED CONCENTRATIONS OF WATER QUALITY
CONSTITUENTS (mg/L)
SIC
Code
2011
2016
2023
2024
2026
2033
2037
2038
2077
2091
2092
2812
2813
2816
2819
2821
2822
2823
2824
2865
2869
2873
2874
2879
2891
2892
2893
2911
3111
3312
3321
3322
3411
3471
3612
3621
3644
3674
3679
3662
3731
3861
6515
7011
7215
8211
8221
SED
67
90.36
157
157
157
302
302
302
520
520
18.5
18.5
18.5
18.5
30.1
30.1
30.1
30.1
30.1
30.1
31
18.5
30.1
27.16
27.16
27.16
27.16
25
25
25
25
25
25
25
25
25
25
40
40
43
40
40
BOD5
68
130.9
338
338
338
503
503
503
18.8
942.6
942.6
22.7
22.7
22.7
22.7
22.7
22.7
22.7
27.5
27.5
27.5
27.5
7.25
7.25
7.25
7.25
7.25
7.25
7.25
7.25
7.25
7.25
40
40
43
40
40
TP TN NH3
20
7.67 43.61 21.2
10.8
10.8
10.8
190.8
190.8
190.8
7.1
12.02 6.8
12.02 6.8
.183
.183
.183
.183
15
15
19.2
15
15
11.3
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
9 20
9 20
9
9 20
9 20
TKN
8.6
42.9
61.2
61.2
61.2
18
18
18
8.5
94.1
94.1
3.61
3.61
3.61
3.61
11.3
11.3
11.3
11.3
11.3
11.3
.85
3.63
8.33
8.3
8.3
8.3
1.15
1.15
1.15
1.15
1.15
1.15
1.15
1.15
1.15
1.15
193
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TABLE IV.8(b). SIC CODE AND SOURCE OF ESTIMATED CONSTITUENT CONCENTRATIONS
SIC Source of value
Code
2011 RFF Pollution Matrix Lookup Routine
2016 Average of data collected in 1979 MD. Compliance monitoring (3
plants)
2023 RFF Pollution Matrix Lookup Routine
2024 RFF Pollution Matrix Lookup Routine
2026 RFF Pollution Matrix Lookup Routine
2033 RFF Pollution Matrix Lookup Routine
2037 RFF Pollution Matrix Lookup Routine
2038 RFF Pollution Matrix Lookup Routine
2077 RFF Pollution Matrix Lookup Routine
2091 "Waste Treatment & Disposal From Seafood Processing Plants"
EPA-600/2-77-157, August 1977
2092 "Waste Treatment & Disposal From Seafood Processing Plants"
EPA-600/2-77-157, August 1977
2812 RFF Pollution Matrix Lookup Routine
2813 RFF Pollution Matrix Lookup Routine
2816 RFF Pollution Matrix Lookup Routine
2819 RFF Pollution Matrix Lookup Routine
2821 RFF Pollution Matrix Lookup Routine
2822 RFF Pollution Matrix Lookup Routine
2823 RFF Pollution Matrix Lookup Routine
2824 RFF Pollution Matrix Lookup Routine
2865 RFF Pollution Matrix Lookup Routine
2869 RFF Pollution Matrix Lookup Routine
2873 EPA Effluent Guidline Division
2874 EPA Effluent Guidline Division
2879 RFF Pollution Matrix Lookup Routine
2891 RFF Pollution Matrix Lookup Routine
2893 RFF Pollution Matrix Lookup Routine
2911 RFF Pollution Matrix Lookup Routine
3111 RFF & Maryland NDPES permit compliance data
3312 RFF & Maryland NDPES permit compliance data
3321 RFF & Maryland NDPES permit compliance data
3322 RFF & Maryland NDPES permit compliance data
3411 RFF Pollution Matrix Lookup Routine
3471 RFF Pollution Matrix Lookup Routine
3612 RFF Pollution Matrix Lookup Routine
3621 RFF Pollution Matrix Lookup Routine
3644 RFF Pollution Matrix Lookup Routine
3674 RFF Pollution Matrix Lookup Routine
3679 RFF Pollution Matrix Lookup Routine
3662 RFF Pollution Matrix Lookup Routine
3731 RFF Pollution Matrix Lookup Routine
(continued)
194
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TABLE IV.8(b). (continued)
3861 RFF Pollution Matrix Lookup Routine
6515 Earth - EPA, MERL, Cincinnati
7011 Earth - EPA, MERL, Cincinnati
7215 RFF Pollution Matrix Lookup Routine
8211 Earth - EPA, MERL, Cincinnati
8221 Earth - EPA, MERL, Cincinnati
195
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TABLE IV.9. SIC CODE, ASSIGNED FLOW, AND SOURCE OF VALUE (MGD)
SIC Code
2011
2016
2023
2024
2026
2033
2035
2037
2038
2077
2091
2092
2812
2813
2816
2819
2821
2822
2823
2824
2865
2869
2873
2874
2879
2891
2892
2893
2911
3111
3312
3321
3322
3411
3471
3612
3621
3644
3674
3679
3662
3731
3861
6515
7011
7215
8211
8221
Assigned
Flow
.09
.34
.001
.001
.001
.001
.05
.001
.001
.001
.001
.001
.05
.05
.05
.01
.1
.015
.039
Source
Average of Maryland NPDES "fact sheet data"
Average of Mayland 1979 NPDES compliance
monitoring data
Author's Best judgement
Author1 s Best judgement
Author's Best judgement
Author's Best judgement
Author's Best judgement
Author's Best judgement
Author's Best judgement
Author's Best judgement
State official recommendation
State official recommendation
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
Author's Best judgement
Author's Best judgement
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
IFD NEIC data bases
Author's Best judgement
Author's Best judgement
Author's Best judgement
Average of MD "fact sheet" data
Average of MD "fact sheet" data
196
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TABLE IV.10. ASSIGNED INDUSTRIAL FACILITIES NUTRIENT LOADINGS FROM OBSERVED
DATA1 (LBS./DAY) IN THE ABSENCE OF THESE KINDS OF DATA, LOADS
WERE CALCULATED FROM CONCENTRATIONS SHOWN IN TABLE IV.8(a)
Basin
0214
0214
0214
0214
0214
0214
0216
0214
0214
0213
0213
0216
0213
0214
0214
0214
0215
State NPDES Facility Name
(permit #)
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
MD
MD
VA
MD
VA
VA
VA
VA
1856
248
1651
1899
1902
1961
4782
2160
2178
2313
27871
3387
4031
2402
29416
1201
299
5291
311
2208
2267
4669
3115
Thiokol Fibers Div
Radford Army Ammunition plant
Burlington Ind. Inc.
Clarksville
Crompton-Shenandoan Company
Rocco Farms Foods Edinburg
Rockingham Poultry Market
Co . Inc .
TP
1
36
.76
.4
Wright Chemical Corp. Waver ly
Dupont Waynesboro
Merck Co. Inc. Stonewall PI.
Wampler Food Hinton
Virginia Chemicals Inc.
Holly Farms Glen Allen
General Electric Waynesboro
710
1
244
57
5
0
Bethlehem Steel 1660
Sparrows Point
FMC Corp. Organic Chem Div
Allied Chem. Corp
Hopewell
WR Grace Davidson Chem. Div.
Avtex Fibers Inc .
Virginia Oak Tannery
Dupont Spruance
Chesapeake Corporation
400
403
.0
.2
.0
.0
.4
.26
.0
.0
.0
NH34 TKN
6
129
10
0
36
12
0
92
1744
3
90
1488
1637
2203
15
.4 7.92
.8
.10 157.6
.10
.0
.0 25.0
.66
.4 347.0
.0
.6
.0
.0 3365.0
.0
.0
472.0
.0
94.0
631.0
SIC
2297
2892
2269
2016
2016
2016
2891
2821
2835
2016
2819
2016
3471
3312
2869
2869
2819
282
3111
2821
2621
1 305b reports, DMRs, and facility representatives
197
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TABLE IV.ll(a), ESTIMATES OF NUTRIENT LOADS FROM INDUSTRIAL POINT
SOURCES FROM ABOVE THE FUNCTIONALLY-DEFINED FALL LINE
(mg/L)
Drainage
Basin
Susquehanna
(0212)
Water Quality
Parameter
BODS
TP
TN
NH34
TKN
Above the fall line*
Estimated Measured Tota I
799
183
386
5718
214
2334
540
2318
6517
397
2720
540
2320
Upper
Chesapeake
Bay and Delmarva
(0213)
BOD5
TP
TN
NH34
TKN
0
0
0
0
Potomac
(0214)
BODS
TP
TN
NH34
TKN
132
24
42
.5
2589
95
5194
1917
3870
2721
119
5236
1917
3871
Rappahannock/
York
(0215)
BOD5
TP
TN
NH34
TKN
.29
.01
.05
.05
.29
.01
.05
.05
James
(0216)
BODS
TP
TN
NH34
TKN
36
1
34
2
7.4
.01
7.4
71
3
7.4
7.4
''Estimated' and 'measured' refer to how flow values for individual
dischargers or types of dischargers were determined. Estimated flows are
unmeasured flows and are based on averages of similar dischargers or best
judgement. Measured flows are recorded flows from NPDES 'fact sheet1 files
or assessed data bases. Estimated and measured flows were then multiplied
by expected concentrations of nutrients in wastewater to calculate loads.
These loads, in turn, were designated as estimated or measured.
198
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TABLE IV.ll(b). ESTIMATES OF NUTRIENT LOADS FROM INDUSTRIAL POINT
SOURCES FROM BELOW THE FUNCTIONALLY-DEFINED FALL LINE
(mg/L)
Drainage Water Quality
Basin
Susquehanna
(0212)
Upper
Chesapeake
Bay and Delmarva
(0213)
Potomac
(0214)
Rappahannock/
York
(0215)
James
0216)
Parameter
BOD5
TP
TN
NH34
TKN
BOD5
TP
TN
NH34
TKN
BOD5
TP
TN
NH34
TKN
BODS
TP
TN
NH34
TKN
BOD5
TP
TN
NH34
TKN
Below the fall line
Estimated
609
133
294
5
1192
301
296
7
45
477
68
153
1
16
1115
71
248
90
245
91
16
10
0
10
Measured
9760
488
6561
3815
6557
507
747
1513
203
1993
1422
24
575
255
445
17880
1890
3755
2295
4159
Total
609
133
294
5
9271
789
6857
3822
6602
984
815
1666
204
2009
2537
95
823
345
690
17971
1906
3765
2295
4169
199
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TABLE IV.ll(c). ESTIMATES OF NUTRIENT LOADS FROM INDUSTRIAL POINT SOURCES
FROM ABOVE AND BELOW THE FUNCTIONALLY-DEFINED FALL LINE
(LBS/DAY)
Drainage Water Quality
Basin
Susquehanna
(0212)
Upper
Chesapeake
Bay and Delmarva
(0213)
Potomac
(0214)
Ra ppahannock/
York
(0215)
James
0216)
Parameter
BOD5
TP
TN
NH34
TKN
BOD5
TP
TN
NH34
TKN
BODS
TP
TN
NH34
TKN
BOD5
TP
TN
NH34
TKN
BODS
TP
TN
NH34
TKN
Above and
Estimated
1409
316
680
7
1192
301
296
7
45
609
92
195
1
17
1115
71
248
90
245
126
17
10
0
10
Below the fall
Measured
5718
214
2334
540
2318
9760
448
6561
3815
6557
3096
842
6707
2120
5863
1422
24
575
255
445
17914
1892
3762
2295
4166
line
Total
7127
530
3014
540
2325
11952
749
6857
3822
6602
3705
934
6902
2121
5880
2537
95
823
345
690
18040
1909
3772
2295
4176
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Estimated Total Point Source Nutrient Loading
The total estimated municipal point source loading data (Table IV.6) and
the total estimated industrial point source loading data [Tables IV.ll(a),
(b) , and (c)] have been summed to generate a table of estimated total nutrient
loadings from all point sources to the Bay system [Tables IV.12(a), (b), and
(c)]. The data presented in Table IV.12 are broken out to delineate loadings
from above and below the functional fall line.
Tables IV.12(a), (b), and (c) indicate the relative magnitude of pollutant
loadings from municipal and industrial point sources. By changing these loads
to percentages, it can be seen from Table IV.12 that, above the fall line, the
industrial contribution of total TP ranges from two percent in the James to
four percent in the Potomac. For total TN, the industrial contribution ranges
from two percent in the James to 28.5 percent in the Potomac. Calculations on
data in Table IV.12(b) indicate that the industrial contribution of TP below
the fall line ranges from 8.7 percent in the Upper Chesapeake Bay Delmarva
drainage basin to 79.6 percent in the Susquehanna. However, it should be
pointed out that very little of the Susquehanna is below the fall line. More
representative of industrial point source nutrient contributions below the
fall line is the Potomac with industrial point sources contributing 10.8
percent of the total TP to its drainage basin and 14 percent to the
Rappahannock/York drainage basin. Without the Susquehanna, the industrial
contribution to the TN load, below the fall line, ranges from 2.8 percent in
the Potomac to 34.7 percent in the Rappahannock/York. In the James River,
industrial point sources contribute 12.7 percent and, in the upper Bay,
Delmarva 20.6 percent.
Table IV.12(c) presents the industrial and municipal contribution to the
total drainage basin load. The industrial contribution to the total TP load
ranges from 3.2 percent in the Susquehanna to 13.8 percent in the James. The
TN industrial load ranges from 5.8 percent in the Susquehanna to 30.7 percent
in the Rappahannock/York. From this information, it can be concluded that
although industrial point sources of nutrients may be significant in local
areas, overall their relative contribution to the Bay is minor in comparison
to the loadings from municipal point sources.
The loadings indicated as being below the fall line are intended to
represent the point source load to the tidal Bay system in excess of that
already included in the computations of Section III. These data were employed
to compute the total estimated seasonal and annual mass loading of nitrogen
and phosphorus species to the tidal Chesapeake Bay system. They are shown in
Table IV.13. This table shows that nitrogen and nitrogen species constitute
the largest proportion of nutrients reaching the tidal Bay from point
sources. Because each season contains approximately equal numbers of days,
seasonal loads (based on daily flows) do not reveal large differences.
Climatelogical and other influences (e.g., infiltration/inflow) were not
considered in breaking out seasonal loads in this analysis.
201
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TABLE IV.12(a). ESTIMATES OF NUTRIENT LOADS FROM MUNICIPAL AND INDUSTRIAL POINT
SOURCES FROM ABOVE THE FUNCTIONALLY-DEFINED FALL LINE
(LBS/DAY EXCEPT FLOW IN MGD)
Drainage
Basin
Susquehanna
(0212)
Upper
Chesapeake
Bay and
Delmarva
(0213)
Potomac
(0214)
Rappahannock/
York
(0215)
Water Quality
Parameter
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BODS
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Above the fall line
Municipal
105899
16018
11504
48098
33502
14596
24353
9149
329
64
7
4
41
16
25
8
7
.3
29972
2883
2555
13089
8616
3760
6049
3014
87
355
55
42
310
112
198
69
43
2.4
Industrial
6517
397
2720
2320
540
2721
119
5236
3871
1917
Total
112416
164 L5
50818
35822
24893
64
7
4
41
16
25
8
7
0.3
32693
3002
18325
12487
7966
355
55
310
112
69
(continued)
202
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TABLE IV.12(a). (continued)
Drainage
Basin
James
(0216)
Water Quality
Parameter
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Above the fall line
Municipal Industrial Total
7349
1574
1218
3730
3280
450
2567
713
24
71
3
7.4
7.4
7420
1577
3737
3287
2567
203
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TABLE IV.12(b).
ESTIMATES OF NUTRIENT LOADS FROM MUNICIPAL AND INDUSTRIAL POINT
SOURCES BELOW THE FUNCTIONALLY-DEFINED FALL LINE
(LBS/DAY EXCEPT FLOW IN MGD)
Drainage Water Quality
Basin Parameter
Susquehanna
(0212)
Upper
Chesapeake
Bay and
De Imarva
(0213)
Potomac
(0214)
Rappahannock/
York
(0215)
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BODS
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Below the fall line
Municipal Industrial Total
134
34
29
85
71
14
58
13
.6
54824
8224
5781
26406
12916
9482
10404
4303
164
50277
6700
5251
57489
26764
30298
23445
9263
502
2675
576
458
1542
1196
346
922
273
10.4
609
133
294
5
9271
789
6857
6602
3822
984
815
1666
2009
204
2537
95
823
690
345
743
167
379
76
64095
9013
33263
19518
14226
512(31
7515
59155
28773
23649
5212
671
2365
1886
1267
(continued)
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TABLE IV.12(b). (continued)
Drainage Water Quality Below the fall line
Basin Parameter Municipal Industrial Total
BODS 74688 17971 92659
TP 10346 1906 12252
James OP 7237
TN 43770 6044 47535
(0216) TKN 39303 4169 43472
N023 7216
NH34 32991 2295 35286
ORGN 6277
FLOW 231
205
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TABLE IV.12(c). ESTIMATES OF NUTRIENT LOADS FROM MUNICIPAL AND INDUSTRIAL POINT
SOURCES TOTALED ABOVE AND BELOW THE FUNCTIONALLY-DEFINED FALL
LINE (LBS/DAY EXCEPT FLOW IN MGD)
Drainage
Basin
Susquehanna
(0212)
Upper
Chesapeake
Bay and
Delmarva
(0213)
Potomac
(0214)
Rap pahannock/
York
(0215)
Water Quality
Parameter
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
BOD5
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Above and
Municipal
106033
16052
11533
48183
33573
14610
24411
9162
330
54888
8231
5785
26447
12932
9507
10412
4310
164.3
80249
9583
7806
70578
35380
34058
29494
12277
589
3030
631
500
1852
1308
544
991
317
12.8
below the fall
Industrial
7127
530
3014
2325
540
11952
749
6857
6602
3822
3705
934
6902
5880
2121
2537
95
823
690
345
line
Total
113160
16582
51197
35898
24951
66840
8980
33304
19534
14234
83954
10517
77480
41260
31615
5567
726
2675
1998
1336
(continued)
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TABLE IV.12(c). (continued)
Drainage
Basin
James
(0216)
Water Quality
Parameter
BODS
TP
OP
TN
TKN
N023
NH34
ORGN
FLOW
Above and below the fall line
Municipal Industrial Total
82037
11920
8455
47500
42583
7666
35558
6990
256
18040
1909
3772
4176
2295
100077
13829
51272
46759
37853
207
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TABLE IV.13. TOTAL ESTIMATED AVERAGE SEASONAL AND ANNUAL NUTRIENT LOADINGS
FROM POINT SOURCES TO THE TIDAL PORTIONS(l) OF THE CHESAPEAKE
BAY SYSTEM
Daily Winter Spring Summer Fall Annual
Constituent (Thousands of Pounds) (Millions of Pounds)
TN 142.7 12.8 13.1 13.1 13.0 52.1
N023 47.4 4.26 4.36 4.36 4.31 17.3
NH34 74.5 6.70 6.85 6.85 6.78 27.2
TKN 93.7 8.44 8.62 8.62 8.53 34.2
TP 29.6 2.67 .2.72 2.72 2.70 10.8
OP 18.8 1.69 1.73 1.73 1.71 6.85
^'Discharges entering the system downstream of the functional fall line as
described in this Section.
208
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SECTION V
BOTTOM FLUXES OF NUTRIENTS
CONCEPTUAL FRAMEWORK
The bottom sediments of Chesapeake Bay and its tributaries constitute a
large reservoir of nutrients available for potential release to the water
column. The nutrients enter the sediments primarily as organic and
inorganic particulates that settle out of the overlying water. Biological
and chemical reactions convert the organicallly-bound nutrients to
inorganic forms, reaching an equilibrium distribution between a soluble
phase in sediment interstitial (pore) water and a particulate phase
adsorbed onto the sediment solids. Thus, the sediments represent a sink
capable of retaining a portion of the nutrients settling out of the water
column. But they also represent a source because part of the remineralized
nutrients diffuse out of the sediments through the pore water, part is
advected out via sediment disturbance by burrowing animals or physical
resuspension; and those remineralized on the sediment surface escape
directly to the overlying water.
The sediments are a complex environment so, for analytical purposes, we
adopted a simplified conceptual framework, shown in Figure V.I. We will
consider the sediments to have discrete layers distinguishable by the
chemical and biological processes occurring in each. Figure V.I diagrams a
vertical section of sediment. The organic fluff layer is composed of
colloidal material and fine particles that are unconsolidated, have a
density near that of water, and may be resuspended and transported by near-
bottom currents. The underlying, compacted surface layer is somewhat more
consolidated material that is not readily resuspended in the water column,
and its surface is oxidized when the overlying water contains oxygen. If
the overlying water becomes anoxic, so does the compacted surface layer.
The largest portion of the sediments is the compacted, anoxic layer, which
is subject to biological processes in the upper 15 inches or so. Various
parts of this Section will refer to this conceptualization.
Two methods will be used to estimate the rate of nutrient release from
the sediments to the water column. The first makes use of the sediment
gravity core samples taken during the course of the Chesapeake Bay Program
(Hill and Conkwright 1981, Tyree et al. 1981, Bricker1 1981) as well as
those from the U.S. Geological Survey's Potomac River Project. The second
approach uses measurements of nutrient release into domes placed on the
bottom as part of the Bay Program's nutrient dynamics study. These two
methods will be used to compute ranges of potential nitrogen and phosphorus
flux.
PORE WATER STUDIES
The lower limit for potential nutrient flux out of the sediment is
estimated from the pore water studies; other factors, like bioturbation, may
^-Personal Communication: "Benthic Flux of Nutrients from Pore Water
Studies," O.P. Bricker, Northeast Research, U.S. Geological Survey,
Reston, VA, October, 1981.
209
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OVERLYING WATER COLUMN
ORGANIC FLUFF
COMPACTED SURFACE
LAYER
COMPACTED ANOXIC
LAYER
Figure V.I. Conceptual diagram of estuarine sediment column.
210
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increase the actual nutrient flux over that described by pore water study.
Over 100 cores taken in the main Bay were analyzed for nutrient content.
The rates of potential nutrient diffusion out of the sediment were then
calculated for each CBP segment (see Figure V.I) based on the concentration
gradients in the sediment, the porosity of the sediment, and a
characteristic coefficient for molecular diffusion determined by ion
activity and the diffusing characteristics of the molecules. The results
appear in Table V.I. Nitrogen is released primarily as ammonium at
calculated rates of 0.5 to 8.8 millionth of a pound of nitrogen per square
foot per day. The winter values are the arithmetic mean of values for the
other seasons, since no cores were taken in winter. This information was
then extrapolated to the entire segment by multiplying the values in Table
V.I by the area of the Bay bottom in each segment composed of more than 50
percent organically-enriched mud (functionally, areas that have less than
50 percent sand). The total daily potential release per segment was then
multiplied by the number of days per season to obtain the seasonal input to
each segment from the sediments as shown in Table V.2. The total nitrogen
and phosphorus input from the sediments for each season appears in the
right hand column, and the total annual input for each segment appears at
the bottom of Table V.2. The minimum potential annual inputs from the
sediment are 32.2 million pounds (1045.9 x 1Q12 micro moles) of nitrogen
and 7.44 million pounds (100 x 10^2 micro moles) of phosphorus.
TABLE V.I. POTENTIAL NITROGEN AND PHOSPHORUS UNIT AREA DIFFUSION FROM
SEDIMENT PORE WATERS (UNITS ARE 10"6 POUNDS PER SQUARE FOOT PER
DAY AS N OR P)
Segment
Spring
NH4+
P04-3
Summer
NH4 +
P04~3
Fall
NH4+
P04-3
Winter^)
NH4+
P04-3
CB-1
4.5
0.006
1.4
0.55d:
6.3
0.082
4.1
0.21
CB-2
0
0
1
' 0
1
0
1
0
.5
.27
.8
.43
.4
.095
.3
.27
CB-3
1.6
0.55
3.5
0.77
1.6
0.78
2.2
0.70
CB-4
5.2
1.1
5.0
0.53
1.3
1.5
3.8
1.0
CB-5
3.7
1.4
3.5
0.85
3.7
0.84
3.6
1.0
CB-6
2.8(1
0.58(
3.2d
0.10
3.6
0.18
3.21
0.29
CB-7
) 1
i) o
) 4
(DO
8
0
4
0
.0
.21
.3
.68
.8
.14
.7
.35
CB-8
2.8(1
0.58(
)
1)
3.2(1)
0.55(
2.3
0.16
2.8
0.43
1)
calculated as mean of other measurements taken is same season
(across columns)
•'Winter values calculated as mean for other seasons in each segment (down
columns) because no winter data were taken.
211
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TABLE V.2. POTENTIAL NITROGEN AND PHOSPHORUS MASS DIFFUSION FROM SEDIMENT PORE
WATERS FOR EACH SEGMENT (UNITS ARE THOUSANDS OF POUNDS N OR P)
Segment (DcB-2
Spring
NV
P04~3
Summer
NH4+
P04-3
Fall
80
41
283
68
CB-3
647
211
1355
300
CB-4
2710
559
2618
280
CB-5
2279
818
2156
518
CB-6
770
164
893
27
CB-7 CB-8 Total Bay
400
89
1724
280
43
7
22
7
6929
1889
9051
1480
NV
P04~3
Winter
NH4+
P04~3
Total Annual
NH4+
P04~3
222
14
191
41
776
164
616
300
862
266
3480
1077
647
750
1940
518
7915
2107
2279
505
2187
614
8901
2455
986
48
862
818
3511
1057
3511
55
1848
136
7483
560
37
3
43
7
145
24
8298
1675
7933
2400
32211
7444
io values are indicated for segment CB-1 because no substantial area in
that segment is composed of organically-enriched mud (less than 50 percent
sand).
On a seasonal basis, ammonium and phosphorus behave differently.
Ammonium is released year-round, regardless of whether the overlying water
and compacted surface layer are oxygenated or anoxic (Taft 1982) .
Phosphate, however, seems to be trapped by the compacted surface layer when
it is oxygenated, and released rapidly when it becomes anoxic. Therefore,
phosphate release by pore diffusion should be most significant during
summer in regions of the Bay where the overlying water is anoxic.
Moreover, release should be a two-step event. In step one, a large mass of
phosphorus, approximately equivalent to that which has accumulated in the
compacted surface layer during the previous nine months of oxygenated
conditions, is released rather quickly. In step two, diffusion out of the
pore water continues at a slower rate, governed by concentration gradients
and sediment characteristics, for the period of anoxia in the deep water.
This concept can be tested by calculating the amount of phosphate that
would be trapped in the compacted surface layer during fall, winter, and
spring within the bottom region subjected to anoxia. If this amount of
phosphate were released at once into the volume of anoxic water, it would
produce a phosphate concentration of 0.22 mg/L. The observed phosphate
concentration shortly after the onset of deep water anoxia is about 0.124
212
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mg/L (Taft 1982, Figure 5). So our estimate exceeds, but is reasonably
close, to the observed values. This result suggests that the concept is
basically correct, but that the system is not operating as a simple on-off
release mechanism. Also, our calculatioan does not account for transport
out of the deep water to the surface layer, which does occur and would make
the observed values less than the calculated ones.
In light of this behavior, and for the purpose of the seasonal
comparison of various phosphorus sources made in Section VIII, the
assumption that the calculated annual flux of phosphorus from the pore
waters is released in the summer months appears to be reasonably well
supported.
DOME STUDIES
Direct measurements of nutrient release from the sediments were made
with diver-installed domes in five locations in the main portion of the Bay
during August 1980 and May 1981. The dome technique measures both
diffusion of nutrients (primarily ammonium since the domes were placed in
oxygenated bottom water) and remineralization on the sediment surface. It
could also include nutrient release caused by burrowing animals if they
were covered by the dome. Thus dome measurements give the upper limit for
potential nutrient release from the sediments.
The dome results appear in Table V.3. The spring values for both
nutrients are less than the summer values with phosphate flux being zero in
all but the northern most segment. Although the compacted surface layer
was oxygenated, phosphate release was observed in summer but not in
spring. This result suggests that diffusion is blocked by, and
remineralization is minimal in, the compacted surface layer and the organic
fluff layer during spring. The latter may be due to low temperatures and
correspondingly low biological activity. Both nutrients show marked flux
rates in summer reflecting increased biological activity in the surface
layers probably stimulated by warmer temperatures.
The magnitude of nutrient remineralization in the two surface layers
can be obtained as the dome release minus the calculated diffusion from
pore water. With the use of the data in Tables V.I and V.3,
remineralization in the surface-sediment layers accounts for 80 to 90
percent of the nitrogen release and for 30 to 90 percent of the phosphorus
release in summer (except for segment CB-3, which has a lower dome rate
than diffusion rate). For purposes of this analysis, we consider that the
processes by which nutrients are remineralized on the sediment surface are
similar to those operating in the water column. Sorption of remineralized
nutrients onto sediment particles could occur, but would not influence our
conclusions, because the dome flux rates were determined from measured
nutrient concentration changes.
213
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TABLE V.3. NUTRIENT RELEASE FROM THE SEDIMENTS MEASURED UNDER DOMES
(UNITS ARE 10~6 POUNDS PER SQUARE FOOT PER DAY)
Segment
Spring
Summer
CB-2 CB-3 CB-4 CB-5 CB-6 CB-7 CB-8
3.3
0.5
4.1
0
4.2
0
5.5
0
5.5
0
5.5
0
5.5
0
NH4+ 12
P04~3 0.6
7.0
0.5
46
6.1
18
1.5
18
1.5
18
1.5
18
1.5
TABLE V.4. NUTRIENT RELEASE IN EACH SEGMENT CALCULATED FROM DOME STUDIES
(UNITS ARE THOUSANDS OF POUNDS)
Segment CB-2 CB-3 CB-4 CB-5 CB-6 CB-7 CB-8 Total Bay
Spring
4H
NH- +
524
68
1602
0
2187
0
3357
0
1509
0
2218
0
92
0
11489
68
Summer
NH4+ 1910
P04~3 95
2741
177
23900
3137
11026
955
4959
409
7300
614
308
20
52144
5407
SUMMARY
The upper and lower limits for nutrient release from the sediments have
been established for the main portion of Chesapeake Bay. The lower limits,
from diffusion calculations (Table V.2) , are about 32 million pounds of
nitrogen (as ammonium) and 7.4 million pounds of phosphorus (as phosphate)
per year. The upper limits can be estimated from the spring and summer
dome studies (Table V.4) by multiplying the spring values by three, to
account for winter and fall, and adding the product to the summer values.
The result is 86.6 million pounds of nitrogen and 5.6 million pounds of
phosphorus. The difference in the nitrogen values (54.6 million pounds)
represents regeneration in the unconsolidated sediment layer. The
similarity of values for phosphorus suggests suppression of diffusive flux
and dominance of regeneration in the unconsolidated layer during
experimental measurements. There is clearly a need for more field studies
on sediment processes.
The relationship between benthic and other nutrient sources is shown in
Chapter VIII. For example, during the summer the bottom is the major
source of ammonium and orthophosphorus (Table VIII.4b).
214
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SECTION VI
NUTRIENT FLUXES AT THE MOUTH OF CHESAPEAKE BAY
Since Chesapeake Bay receives ocean water at its mouth, it also
receives nutrients from the ocean. However, it is not clear whether there
is net gain or loss of nutrients at the ocean boundary. Nutrient transport
at the mouth is dependent on the direction and magnitude of water flow, and
on the nutrient concentrations in the water. The long term net flow is out
of the Bay and is equal to the riverflow minus evaporation, plus
precipitation input. However, over any short time interval, meteorological
conditions can drive water into or out of the Bay continually for several
days at a time. These short term variations make it difficult to calculate
long term nutrient transport.
Calculations are also complicated by the structure of water flow at the
mouth. Within the Bay, the fresher, lighter river water overlays the
saltier, heavier ocean water. At the mouth, however, the basin geometry
and the earth's rotation interact so that the ocean water inflow often
occurs at all depths on the north side with outflow on the south side of
the mouth. Thus, the two-layer structure is side by side rather than top
and bottom.
As part of the Chesapeake Bay Program, an intensive study of the mouth
region was made in July 1980. Current measuring devices were deployed at
five locations across the mouth for 38 days. Nutrient measurements were
made at each current meter location for eight consecutive days during the
deployment.
When the current meter data are averaged over the 38 days beginning
June 23, 1980, the net. flow, less tidal currents, is obtained. Figure VI.1
shows net flow along the bottom into the Bay on both the south (left) and
north side. (Positive velocity equals inflow.) Net outflow occurred at
the surface all across the mouth and from the surface to the bottom near
the middle of the mouth. These results differ somewhat from the flow
structure expected from previous work (Boicourt, in progress), but we will
use them for flux calculations, because nutrient data were collected
concurrently with the flow measurements.
The nutrient fluxes were calculated from nutrient concentrations
measured within isotachs shown in Figure VI.1. The measured concentrations
were integrated over the area between isotachs to give nutrient fluxes for
each range of current velocity. These values were then summed to give
fluxes into and out of the Bay.
If the net water fluxes are multiplied by nutrient concentrations, the
nutrient fluxes are obtained. Table VI.1 shows the nutrient fluxes
calculated in this x^ay. The net fluxes of organic carbon and total
nitrogen were out of the Bay, whereas total phosphorus and suspended solids
fluxes were into the Bay for this period. For the reasons mentioned above,
it is difficult to extrapolate this information to seasonal or annual
fluxes, but a comparison with another kind of information can be made.
Table VI,2 shows the fluxes calculated from a very simple box model
approach (Taft et al. 1978), using unpublished data collected during
several periods in 1975-1976. It can be seen that the flux of particulate
nutrients for 1975-1976 was generally out of the Bay. The values for the
215
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particles alone are much higher than both particle and total fluxes for
July 1980. Comparing the suspended solids flux for July 1980 of +55,000
Ibs./day (+290 g's"1) (Table VI.I) with the total particulate organic
fluxes for August 1975 and 1976 (Table VI.2) shows a difference by about a
factor of ten. The net flux of suspended solids is into the Bay, whereas
the net particulate organic flux is out of the Bay. This could be
reasonably explained if incoming material were enriched with inorganic
particles, and if outgoing material were enriched with organic particles
such as phytoplankton.
Assume that the values in Table VI.2 are too high, because they are
derived from measurements made ten miles inside the Bay rather than at the
mouth. Further assume, however, that the net flux is out and the relative
differences among the seasons represented in Table VI.2 are approximately
correct. That is, the spring flux of organic carbon is higher than the
summer flux by about 1.5 times. We can than construct an approximate flux
of total carbon out of the Bay by multiplying the total organic carbon flux
of -695,250 Ibs./day (-3650 g's"1/!) by 1.5 for spring. The winter flux
is likewise taken as 1.5 times -695,250 Ibs./day (-3650 g's"1). We can
assume the fall flux equals the summer values for lack of better
information.
The average annual flux then is:
Summer -695,250 Ibs./day (-3650 g's"1)
Fall -695,250 Ibs./day (-3650 g's"1)
Winter -1,040,250 Ibs./day (-5475 g-s"1)
Spring -1,040,250 Ibs./day (-5475 g's"1)
TOTAL -3,471,000 Ibs./day (-18,250 g's"1)
AVERAGE - 867,750 Ibs./day (- 4,562 g's"1)
Thus, the net flow of organic carbon out of the Bay is estimated to be
867,750 Ibs./day (4562 g's"1) for a full year or 316 million pounds per
year (1440x10** g-yr"1). If we then apply the same reasoning to the
other nutrients, we calculate the net outflow of nitrogen to be 3 million
pounds per year (12.6x10° g'yr"1), and the net inflow of phosphorus
to be 1.7 million pounds per year (7.9x10^ g'yr"1).
The difference in sign between the suspended solids and total
phosphorus fluxes, on the one hand, and the remaining nutrient fluxes, on
the other, is interesting and can be explained. The suspended solids data
contain both organic and inorganic particles. Since the net flux of
organic particles seems to be out of the Bay, the observed inflow must be
due to inorganic sediments entering the Bay from the ocean. This
interpretation is consistent with ideas put forth by Schubel concerning net
sediment transport into Chesapeake Bay from the ocean. The net inflow of
phosphorus from the ocean to the Bay is consistent with the notion that
nitrogen is limiting to phytoplankton biotnass in the ocean, so that
phosphorus may be present in excess in the ocean water entering the Bay.
It may also be sorbed onto suspended sediment particles entering the Bay.
217
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It should be clear to the reader from this summary of the available
data that our understanding of transport through the Bay mouth is still
quite rudimentary. The calculations made here should be used to form
additional scientific questions focused on improving insight into this
important aspect of nutrient dynamics in Chesapeake Bay.
At any rate, the net flux of nutrients to the Bay from the ocean
appears to be small enough related to the other sources that it can be
ignored for calculating nutrient sources to the Bay system without the
introduction of a major error. Although minor on a Bay-wide scale,
however, oceanic flux of nutrients may be of local importance.
TABLE VI.1, NUTRIENT FLUXES ACROSS THE MOUTH OF CHESAPEAKE BAY IN JULY
1980 (UNITS ARE THOUSANDS OF POUNDS PER DAY)
POSITIVE VALUES INDICATE FLUX INTO THE BAY
Total Organic Carbon
Total Nitrogen
Total Phosphorus
Total Suspended Solids
Particulate Organic Carbon
Particulate Organic Nitrogen
Flux In
*- 1170
* 184
H 14
H 3,969
* 247
»• 33
Flux Out
1846
190
13
3,914
348
49
Net Flux
676
6
+ 1
+ 55
101
16
TABLE VI.2.
FLUXES OF PARTICULATE MATERIAL AT THE BAY MOUTH CALCULATED
WITH A BOX MODEL (UNITS ARE THOUSANDS OF POUNDS PER DAY)
POSITIVE IS INTO THE BAY (l)
Time
February 1975
May 1975
August 1975
February 1976
April 1976
August 1976
C
+1890
- 874
- 461
-6016
- 446
- 373
N
+ 265
- 122
- 76
- 67
- 63
- 60
P
+ 13
-6
-4
-3
-3
-3
Chi a
+4
-7
-0.6
-1.4
-1.1
-1.1
Total
+ 2,168
- 1,002
541
- 6,086
512
- 436
^'Information in table from unpublished data (Taft). Box model concept
to be published in Spring 1982.
218
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The minimal flux of nutrients out of the Bay has profound implications
for management. Nearly all of the materials that enter the Bay remain
there; nutrients trickle out of the Bay mouth at a very slow rate. Thus,
even if nutrient loads were dramatically reduced, Bay-wide improvement of
water quality would be very slow. It would take many years for the
accumulated mass of nutrients to leave the system.
219
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SECTION VII
PRIMARY PRODUCTIVITY IN CHESAPEAKE BAY
Primary productivity is the rate of organic carbon production from
inorganic carbon by plants and constitutes an important source of nutrition
to Chesapeake Bay. For purposes of this Section, only phytoplankton
productivity is considered. The productivity by submerged aquatic
vegetation (SAV) is covered in the synthesis paper on SAV (part III).
The basic data set used here for primary productivity calculations was
collected on bi-monthly cruises during 1972 and 1973 (Taylor 1982). Values
measured at single stations have been averaged over the regions shown on
the map in Figure VII.1. Further, the measurements have been integrated
over various depths of euphotic zone according to location in the Bay.
The single station measurements and multiplying factors for surface
area and euphotic zone depth are shown in Table VII.1. As one might expect
productivity is generally greater in summer than in winter by factors of
five to 20, depending on region, as well as on higher light levels and
temperatures in the summer. Also, annual average productivity per square
foot is higher in the upper Bay than lower, because of the greater
availability of nutrients. However, owing to the proportionally greater
area of the lower Bay, total productivity is greater in the lower Bay
regions. Productivity is about equally divided between the states with 30
x 108 Ibs. C/yr (14 x 1011 gC/yr) in Maryland (Table VII.1, Regions
I-VII) and 32 x 108 Ibs. C/yr (15 x 1011 gC/yr) in Virginia (Regions
VIII-IX) for a total of 62 x 108 Ibs.C/yr. (29 x 1011 gC/yr).
The amount of nitrogen and phosphorus required to support this amount
of productivity can be estimated from the ratio of C:N:P in phytoplankton.
This ratio is commonly taken to be 106:16:1 by atoms (Redfield ratio).
The nitrogen requirement estimated from the Redfield ratio is 11 x
108 Ibs. N/yr. (5.2 x 10^1 gN/yr), and the phosphorus requirement is
1.5 x 108 Ibs. P/yr. (0.7 x lO*1 gP/yr) . These requirements are met,
in part by inputs from rivers, the atmosphere, point sources, and the
sediments and, in part, by recycling of organic materials into inorganic
nutrient forms. Table VII.2 shows the annual total nitrogen and phosphorus
inputs compared with the amount required to support the observed
phytoplankton primary productivity. The annual inputs are 302.8 million
pounds of nitrogen and 30.2 million pounds of phosphorus. Accounting for
the estimated net flux at the mouth and the nutrient "stored" in the water
column yields 380.0 million pounds of nitrogen and 38.4 million pounds of
phosphorus either in the Bay or entering it annually. The requirements to
support phytoplankton primary productivity are, as a minimum, three times
greater than the supply for nitrogen and four times greater for
phosphorus. This additional amount of nutrient must be supplied by
recycling in the water through the mechanisms discussed in Chapter 2 of
this part, including grazing and decomposition of organic matter.
The seasonal relationships between phytoplankton productivity (Table
VII.3) and nutrient inputs is shown in Tables VII.4 through VII.7. In the
winter (Table VII.4), nitrogen entering the Bay potentially supports about
seven-tenths of the productivity in winter. This is shown by dividing
nutrients in, or entering the Bay, by those required to support primary
220
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Figure VII.1.
Map of Chesapeake Bay showing regions in which primary
productivity measurements have been averaged.
221
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productivity. Nitrogen supports about one-half of the productivity in
spring (Table VII.5), about one-tenth in summer (Table VII.6), and about
one-fifth in the fall (Table VII.7). Incoming phosphorus potentially
supports about two-fifths of the productivity in winter, about one-quarter
in spring, about one-fifth in summer, and one-eighth in the fall.
Nutrients entering and leaving the system as migrating finfish could not be
evaluated. The nutrients in fish caught, amounts to about eight million
pounds N and one million pounds P annually, but these values are not:
included in the Tables.
The nutrient estimates were made assuming that all of the inputs are
thoroughly mixed in the Bay, an incorrect assumption. Most nutrients are
probably retained in the tributaries for a considerable length of time.
Moreover, most of the incoming nutrients seem to enter the sediments rather
quickly. Note also that the estimates of production are only for the Bay
proper; the tributaries have not been included.
222
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TABLE VII.1. PRIMARY PRODUCTIVITY MEASUREMENTS AND FACTORS USED TO
CALCULATE ANNUAL AVERAGE PRODUCTIVITY FOR CHESAPEAKE BAY
DEVELOPED FROM DATA BY FLEMER 1970 AND TAYLORl 1973
I
II
III
IV
V
VI
VII
VIII
IX
2/73
1.8
374
344
611
481
339
320
-
315
4/73
x 10~6
677
5049
1366
891
891
891
713
-
6/73
pounds
6237
2257
1722
1129
1426
1960
1188
1010
8/73
10/73
12/73
C/ft2/day
6653
6118
3089
4752
2317
2851
2079
1485
2376
2257
1541
1188
1960
1426
1307
1485
386
1960
1485
499
653
594
1307
653
Av.
6273
2784
2998
1636
1490
1264
1340
1319
990
S
U
R
F
A
C
E
A
R
E
A
(106)
(£t2) (
—
3809
2066
5853
3680
7371
4186
14246
22284
E
U
P
H
0
T
I D
C E
P
Z T
0 H
N
E
[ft.)
—
15
15
15
18
18
20
20
24
E
U
P
H
0
T V
I 0
C L
U
Z M
0 E
N
E
(109)
(ft3)
1.0
57
31
88
66
133
84
285
535
Total
A
N
N
U P
A R
L 0
D
A U
V C
E T
R I
A 0
G N
E
do8)
(Ibs-C)
5.7
3.4
5.3
3.6
6.1
4.1
13.7
19.3
62.2
Personal Communication: "Primary Production Data for the Chesapeake Bay,
1973," W.R. Taylor, Chesapeake Bay Institute, Shady Side, MD, January, 1982.
223
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TABLE VII.2. RELATION BETWEEN ANNUAL PLANKTON PRODUCTIVITY AND
ANNUAL NUTRIENT INPUTS
Required to support^ •*•'
Primary Productivity
Annual input from (2)
Atmosphere
Fluvial sources
Point sources
Sediments
Total inputs
Net Flux at the mouth (3)
Net inputs
Total Nutrient in the water^'
Nutrients in or entering
the Bay annually
Nutrients recycled^'
% Productivity supported by
available nutrients
% Productivity supported by
recycling
Total N
Millions
1100
40.4
178.1
52.1
32.2
302.8
- 3.0
299.8
80.2
380.0
720.0
34.6%
65.5%
Total P
of Pounds
150
1.64
10.3
10.8
7.44
30.2
+ 1.7
31.9
6.5
38.4
111.6
25.6%
74.4%
(1)Calculated from Table VII.1
Table VIII.1
Chapter VI
(^'Estimated as the product of average concentrations of readily-
available algal nutrients and water volume. The nutrient forms
are: available nitrogen = nitrate and ammonium
available phosphorus = soluble reactive phosphorus
Inorganic nutrient forms regenerated from organic forms by
grazing, decomposition, and other processes.
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TABLE VII.3. SEASONAL PRIMARY PRODUCTIVITY IN CHESAPEAKE BAY
Season
Spring
Summer
Fall
Winter
% Annual productivity
20
45
25
10
108 pounds C/season
12.4
28.0
15.6
6.2
TABLE VII.4. RELATION BETWEEN WINTER PHYTOPLANKTON PRODUCTIVITY AND
NUTRIENT INPUTS
Required to support
Primary Productivity
Input from
Atmosphere
Fluvial sources
Point sources
Sediments
Total inputs
Net Flux at the mouth
Net inputs
Total Nutrient in the water
Nutrients in or entering
the Bay
Nutrients recycled
% Productivity potentially supported
by available nutrients
% Productivity supported by
recycling
Total N
Millions of
110
6.2
51.4
12.8
7.9
78.3
- 0.9
77.4
18.2
95.6
14.4
86.9
13.1%
Total P<
Pounds
15
0.2
3.0
2.7
5.9
+ 0.3
6.2
0.5
6.7
8.3
44.7%
55.3%
(1)
Source is Tables VII.2 and VII.3 for Total N and Total P.
225
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TABLE VII.5, RELATION BETWEEN SPRING PHYTOPLANKTON PRODUCTIVITY AND
NUTRIENT INPUTS
Required to support
Primary Productivity
Input from
Atmosphere
Fluvial sources
Point sources
Sediments
Total inputs
Net Flux at the mouth
Net inputs
Total Nutrient in the water
Nutrients in or entering
the Bay
Nutrients recycled
% Productivity supported by
available nutrients
% Productivity supported by
recycling
Total N Total P
Millions of Pounds
220
42.<
30
16.2
72.2
13.1
6.9
108.4
- 0.9
107.5
18.2
125.7
94.3
57.1%
0.51
4.21
2.72
7.4
+ 0.3
7.7
0.5
8.2
21.8
27.3%
72.7%
226
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TABLE VII.6, RELATION BETWEEN SUMMER PHYTOPLANKTON PRODUCTIVITY AND
NUTRIENT INPUTS
Required to support
Primary Productivity
Input from
Atmosphere
Fluvial sources
Point sources
Sediments
Total inputs
Net Flux at the mouth
Net inputs
Total Nutrient in the water
Nutrients in or entering
the Bay
Nutrients recycled
% Productivity supported by
available nutrients
% Productivity supported by
recycling
Total N
Millions
497
12.2
25.1
13.1
9.1
59.5
- 0.6
58.9
22.8
81.7
415.3
16.4%
83.6%
Total P
of Pounds
68
0.6
1.4
2.7
7.4
12.1
+ 0.2
12.3
5.0
17.3
50.7
25.4%
74.6%
227
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TABLE VII.7. RELATION BETWEEN FALL PHYTOPLANKTON PRODUCTIVITY AND
NUTRIENT INPUTS
Required to support
Primary Productivity
Input from
Atmosphere
Fluvial sources
Point sources
Sediments
Total inputs
Net Flux at the mouth
Net inputs
Total Nutrient in the water
Nutrients in or entering
the Bay
Nutrients recycled
% Productivity supported by
available nutrients
% Productivity supported by
recycling
Total N Total P
Millions of Pounds
277
72.7%
38
5.9
27.9
13.0
8.3
55.1
- 0.6
54.5
21.0
75.5
201.5
27.3%
0.3
1.5
2.7
4.5
+ 0.2
4.7
0.5
5.2
32.8
13.7%
86.3%
228
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SECTION VIII
SUMMARY AND CONCLUSIONS: THE MANAGEMENT QUESTIONS ANSWERED
This section is divided into two sub-sections. The first synthesizes the
results of Chapters II through VI, presenting annual and seasonal loadings
from all sources, and computing the total Bay-wide nutrient and sediment input
budgets. The second half of the chapter contains a restatement of the
pertinent Management Questions listed in the Introduction (Section I).
Following each question is a statement of answers that draws upon the data
presented here as well as upon other sources that are as complete, technically
correct, and editorially succinct as possible within the limitations of the
authors capabilities.
ANNUAL AND SEASONAL LOADINGS OF NUTRIENTS TO THE BAY FROM MAJOR SOURCES
The nutrient loading estimates from each source have been accumulated and,
in some cases reformatted to develop estimates of the total nutrient inputs to
the tidal Chesapeake Bay system. The results have been depicted in terms of
the total mass flux into the tidal system for the year and each of the
seasons. As previously stated, the months included in each season are as
follows:
WINTER: December, January, February (90 days)
SPRING: March, April, May (92 days)
SUMMER: June, July, August (92 days)
FALL: September, October, November (91 days)
ANNUAL: December - November (365 days)
The sources included in the synthesis are Atmospheric, Fluvial, Point
(below fall line), and Bottom. As mentioned at the end of Chapter VI, the
ocean has been eliminated from consideration as a source for the purposes of
this paper because the net flux was insignificant. The annual and seasonal
nutrient input budgets are presented in Table VIII.l(a) through VIII.5(a).
The fraction that each source represents of the annual (or seasonal) total
for each constituent has been computed, expressed as a percentage, and
included as the "b" section of each Table [Tables VIII.l(b) through VIII.5(b)].
TABLE VIII.l(a). AVERAGE ANNUAL NUTRIENT AND FLUVIAL SEDIMENT INPUT TO THE
WATER COLUMN OF THE TIDAL CHESAPEAKE BAY SYSTEM
(MILLIONS OF POUNDS)
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Sediment (SED)
Atmospheric
Sources
40.4
14.5
8.91
25.9
1.64
0.40
Fluvial
Sources
178.1
111.5
9.06
58.6
10.3
3.24
6630.
Point
Sources
52.1
17.3
27.2
34.2
10.8
6.85
Benthic
Sources
32.2
32.2
32.2
7.44
7.44
Total
302.8
143.3
77 .4
150.9
30.2
17.9
6630.
229
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TABLE VIII.l(b). PERCENTAGES OF ANNUAL NUTRIENT LOADINGS FROM VARIOUS SOURCES
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Atmospheric
Sources
13.3
10.1
11.5
17.2
5.4
2.2
Fluvial
Sources
58.8
77.8
11.7
38.8
34.1
18.1
Point
Sources
17.2
12.1
35.2
22.7
35.8
38.2
Benthic
Sources
10.6
41.6
21.3
24.7
41.5
TABLE VIII.2(a). AVERAGE WINTER NUTRIENT AND FLUVIAL SEDIMENT INPUT TO THE
WATER COLUMN OF THE TIDAL CHESAPEAKE BAY SYSTEM
(MILLIONS OF POUNDS)
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Sediment (SED)
Atmospheric
Sources
6.16
2.95
2.06
3.21
0.21
0.09
Fluvial
Sources
51.4
32.2
2.62
16.8
2.97
0.933
1830.
Point
Sources
12.8
4.26
6.70
8.44
2.67
1.69
Benthic
Sources
7.93
7.93
7.93
Total
78.3
39.4
19.3
36.4
5.85
2.71
1830.
TABLE VIII.2(b). PERCENTAGES OF WINTER NUTRIENT LOADINGS FROM VARIOUS SOURCES
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Atmospheric
Sources
7.9
7.5
10.7
8.8
3.6
3.3
Fluvial
Sources
65.7
81.7
13.6
46.1
50.8
34.4
Point
Sources
16.3
10.8
34.7
23.2
45.6
62.3
Benthic
Sources
10.1
41.1
21.8
230
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TABLE VIII.3(a). AVERAGE SPRING NUTRIENT AND FLUVIAL SEDIMENT INPUT TO THE
WATER COLUMN OF THE TIDAL CHESAPEAKE BAY SYSTEM
(MILLIONS OF POUNDS)
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Sediment (SED)
Atmospheric
Sources
16.2
4.70
3.45
11.5
0.51
0.10
Fluvial
Sources
72.2
45.3
3.73
23.6
4.29
1.28
2870.
Point
Sources
13.1
4.36
6.85
8.62
2.72
1.73
Benthic Total
Sources
6.93 108.
54.
6.93 21.
6.93 50.
7.
3.
2870.
4
4
0
6
52
11
TABLE VIII. 3 (b). PERCENTAGES OF SPRING NUTRIENT
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Atmospheric
Sources
14.9
8.6
16.5
22.7
6.8
3.2
LOADINGS
Fluvial
Sources
66.6
83.3
17.8
46.6
57.0
41.2
FROM VARIOUS SOURCES
Point
Sources
12.1
8.0
32.7
17.0
36.2
55.6
Benthic
Sources
6.4
33.1
13.7
TABLE VIII.4(a). AVERAGE SUMMER NUTRIENT AND FLUVIAL SEDIMENT INPUT TO THE
WATER COLUMN OF THE TIDAL CHESAPEAKE BAY SYSTEM
(MILLIONS OF POUNDS)
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Sediment (SED)
Atmospheric
Sources
12.2
4.70
1.89
7.47
0.60
0.11
Fluvial
Sources
25.1
15.8
1.26
8.18
1.42
0.49
955.9
Point
Sources
13.1
4.36
6.85
8.62
2.72
1.73
Benthic
Sources
9.05
9.05
9.05
7.44
7.44
Total
59.5
24.9
19.05
33.4
12.2
9.77
955.9
231
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TABLE VIII.4(b). PERCENTAGES OF SUMMER NUTRIENT LOADINGS FROM VARIOUS SOURCES
Constituent
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Atmospheric
Sources
20.5
18.9
9.9
22.4
4.9
1.1
Fluvial
Sources
42.2
63.6
6.6
24.5
11.7
5.0
Point
Sources
22.0
17.5
36.0
25.8
22.3
17.7
Benthic
Sources
15.2
47.5
27.1
61.1
76.2
TABLE VIII.5(a). AVERAGE FALL NUTRIENT AND FLUVIAL SEDIMENT INPUT TO THE WATER
COLUMN OF THE TIDAL CHESAPEAKE BAY SYSTEM
(MILLIONS OF POUNDS)
Constituent
Atmospheric Fluvial Point Benthic Total
Sources Sources Sources Sources
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
Sediment (SED)
5
2
1
3
0
0
.91
.12
.51
.78
.30
.12
27
17
1
9
1
0
975
.9
.7
.42
.06
.49
.53
•
13
4
6
8
2
1
.0
.31
.78
.53
.70
.71
8.
8.
8.
30
30
30
55
24
18
29
4
2
975
.1
.1
.0
.7
.49
.36
•
TABLE VIII.5(b). PERCENTAGES OF FALL NUTRIENT LOADINGS FROM VARIOUS SOURCES
Constituent
Atmospheric Fluvial Point Benthic
Sources Sources Sources Sources
Total Nitrogen-N (TN)
Nitrite + Nitrate Nitrogen-N (N023)
Ammonia Nitrogen-N (NH34)
Total Kjeldahl Nitrogen-N (TKN)
Total Phosphorous-P (TP)
Orthophosphorus-P (OP)
10.7
8.8
8.4
12.7
6.7
5.1
50.6
73.4
7.9
30.5
33.2
22.5
23.6
17.9
37.7
28.7
60.1
72.5
15.1
46.1
27.9
The reader should be cautioned that the sum of the individual seasonal
totals (Tables VIII.2(a) - VIII.5(a)) will not always agree exactly with the
annual totals shown in Table VIII.l(a). The reason for this is that the
annual load shown for the fluvial sources column of Table VIII.l(a) represents
the results of the regression model equations applied in Section III for
annual loads that are developed independently of the individual seasonal
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models. The annual loads are not simply the sum of the four seasonal model
outputs, therefore, and any differences between the computations using the
annual model and the sum of the individual seasons are an artifact of the
regression analysis. The difference between presented annual values and the
sum of the four seasons is usually less then one percent.
Examination of the data presented in Tables VIII.l(a) through VIII.5(b)
reveals some interesting, if not new, information about the loading mechanisms
that effect the Bay system. The need to look beyond annual loadings into the
seasonality of loading patterns is evident. Shown below are the deviations
from the seasonal loadings for nitrogen and phosphorous that would be
"expected" if the annual loads (Table VIII.1) were distributed evenly into
seasons.
TABLE VIII.6. SEASONAL DISTRIBUTION OF NUTRIENT LOADINGS
Nutrient
TN
TN
TN
TN
TP
TP
TP
TP
Season
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
"Expected"
Value
74.7
76.3
76.3
75.5
7.45
7.61
7.61
7.53
Actual
Value
78.3
108.4
59.5
55.1
5.85
7.52
12.2
4.49
Percent of
Expected Value
104.8
142.1
78.0
73.0
78.5
98.8
160.3
59.6
% Deviation
+4.8
+42.1
-22.0
-27.0
-21.5
-2.0
+60.3
-40.4
In other words, the expected loads are defined as those that would be
computed by applying an average annual loading rate expressed as daily loads
(Ibs/day) to the number of days in each season. These values are useful as a
device to elucidate the importance of seasonal considerations of nutrient
loading dynamics.
An immediate point of interest when studying Table VIII.6 of seasonal
deviations is that while the spring freshet carries a large nitrogen and
phosphorous load, a disproportionately large amount of the annual nitrogen
budget is delivered [Table VIII.3(a) and VIII.3(b)]. The reason that
phosphorous appears to remain close to the "expected" value is because the
effect of the spring freshet load is offset by the very large pulse of
phosphorous (seven million pounds) released from the sediments during the
period of bottom-water anoxia in early summer [Table VIII.4(a)]. A secondary
reason for this effect is that the ratio of total nitrogen to total
phosphorous in runoff is in excess of three times greater then the TN:TP ratio
of the point source load.l point source loadings of total phosphorous are
usually double those in runoff in summer and fall [Table VIII.4(a) and
VIII.5(a)], about equal in the winter [Table VIII.2(a)], and about half as
TN:TP for runoff varies from 17 to 19 while the TN:TP for point sources is
4.8.
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great as the runoff TP load during the spring [Table VIII.3(a)] because of the
effect of the freshet. In contrast, nitrogen from runoff always exceeds that
from point sources with the greatest deviation occurring in the spring [Table
VIII.3(a)] when the nonpoint source nitrogen flux is probably more than four
times greater than the point source nitrogen flux. En summary, the largest
portion of the annual nitrogen loading budget enters the tidal system during
the winter-spring period, and the largest portion of the annual phosphorous
budget enters during the spring-summer period. This seems to support. Taft's
observation that biomass within the euphotic zone in the Bay is most likely
controlled (limited) by phosphorous in the spring and nitrogen in the summer
(See Chapter 2 of this part).
The nitrogen being discharged from both fluvial and point sources; is
predominately nitrite-nitrate. However, a larger portion of the total
nitrogen load from point sources is in the ammonia phase than for nonpoint
sources [Table VIII.l(b)]. In fact, point sources discharge much more ammonia
than fluvial sources every season, even during the freshet [Tables VIII.2(b)
to 5(b)]. This load of ammonia, plus the input from the bottom would support
the hypothesis that nitrate is transported conservatively (without changes in
form) through the upper Bay in the spring because of phytoplankton preferences
for ammonia (see Chapter 2). If phytoplankton growth in the upper Bay has
sufficient ammonia-nitrogen for support of the population then
nitrate-nitrogen will transport to the lower Bay without being utilized. With
large fluvial loads occurring in the late spring, we can expect the lower Bay
to receive these loads in a form readily available for algal assimulation, a
condition which is apparent from field monitoring data.
NUTRIENT BUDGETS
With the information assembled in Tables VII.2 and VIII.1, it is possible
to construct annual budgets for nitrogen and phosphorus transport. Such
budgets, of course, suffer from uncertainties in the data, but are useful for
visualizing the relative importance of sources and sinks for nutrients. The
greatest uncertainty in our budgets occurs in the exchange between the Bay and
the ocean. Since data are scanty, our estimates are based on defendable, but
imperfect, assumptions. The amount of nutrient loss to the sediments in each
budget was determined by subtracting the difference between the sum of the
inputs and the sum of the outputs. Therefore, it has an uncertainty equal to,
or greater than, the uncertainty in the ocean exchange estimate. Even with
the uncertainties, the budgets reflect what happens in the estuary: It is
filling with sediments; it is trapping nutrients.
Figure VIII.1 depicts the annual nitrogen and phosphorus budgets for
Chesapeake Bay. Two important features, as discussed above, are exchange at
the ocean boundary and the net amount of nutrient removal by sedimentation.
For both nutrients, the transport across the boundary with the ocean is
approximately balanced. This means that most of the nitrogen and phosphorus,
entering from the land and the atmosphere, remain in the system. Some
nutrient is stored in the water but, since water column concentrations do not
increase dramatically from one year to the next, most incoming nutrient must
go to the sediments during the annual cycle. The sedimentation values in
Figure VIII.1 are net rates, indicating permanent burial of about 300 million
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Atmosphere
(40)
River Transported
Input (178)
Direct Discharge »
(52) P
N2 Fixation
(0.025)
N20, NH3 Loss
(0.040)
1 T
Loss (85)
Ocean
^ Input
* (83)
1
Sedimentation
(300)
Atmosphere
(1.6)
Benthic
Input
(32)
(7.4)
A.
River Transported ^
(10.3) P
Direct Discharge fc
(10.8) P
Sedimentation Benthic
(31.9) Input
Loss (5.81
F"
Ocean
A Input
' (7.6)
B.
FIGURE VIII. 1. Annual (a) nitrogen and (b) phosphorus budgets for Chesapeake
Bay. (In millions of pounds)
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pounds of nitrogen and 31.9 million pounds of phosphorus annually. About 10
percent of the nitrogen and 23 percent of the phosphorus is returned to the
water column from the sediments.
The nitrogen input to the Bay by nitrogen fixation is not well known, but
it should be small compared to other inputs since nitrogen fixation rates in
the water are vanishingly small. We estimate 25,000 pounds per year net input
from marshes. The nitrogen loss to the atmosphere as ^0 and NH3 gas is
also probably small. Few measurements have been made from which we estimate
an annual loss of 40,000 pounds per year from the estuary. We hope future
research will refine these estimates.
Neither budget accounts for nutrient gains or losses as fish, crabs, and
birds migrate through the system. In the absolute sense, the numbers are no
doubt large, but relative to the other inputs and losses, they should be
small. By inspection, if all excess nutrients were leaving in the form of a
harvestable fishery, eutrophication would not be the problem it is becoming in
Chesapeake Bay.
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• 2. What percentage of the nutrients is from point sources?
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Management Questions and Answers
Below and on the following pages are a restatement of the nine Management
Questions and the answers as could best be derived from the available
information.
1. What is the atmospheric contribution to nutrient input?
The atmospheric nutrient contribution that enters directly upon tidal
waters is at least 40 million pounds of nitrogen and 1.6 million pounds of
phosphorous each year [Table VIII.l(a)]. This load constitutes about 13
percent of the annual nitrogen, and five percent of the annual phosphorous
input budgets [Table VIII.l(b)]. Seasonally, atmospheric sources may make up
as much as 20 percent of the seasonal total nitrogen (winter) input and five
percent of the seasonal total phosphorous (summer) input and as little as
seven percent of the total nitrogen load and three percent of the total
phosphorous load in the winter and spring [Tables VIII.2(b) to VIII.5(b)].
On an annual basis, about 20 to 25 percent of the total nitrogen load
entering tidal waters comes from point sources basin-wide [Table VIII.Kb)].
This percentage range would hold even if all of the point sources load
discharged above the Fall Line were transported directly to the tidal system
(a very conservative assumption since losses undoubtedly occur in transport,
especially during the summer). The proportions are relatively invariant
throughout the year, reaching the lower end of the range in the spring and the
upper end in the summer and fall.
To make a reasonable estimate of the percentage of the phosphorous load
deriving from point sources, some manipulations of the riverine loading models
developed in Chapter III were performed. Low flow values were chosen for each
of the major tributaries-'-, and the total phosphorous load expected to occur
at these flows were computed. This total flow (sum of all three tributaries)
was about 9660 cubic feet per second. Note from Table IV.12(a) that the total
point source flow entering above the Fall Line is about 688 cfs. The total
phosphorus load computed to be carried to the tidal system at a stream
discharge of 9660 cfsd is about 1950 Ibs./day or about 0.7 million pounds per
year. If the extremely conservative assumption is made that all of this load
derives from point source discharges and is summed with the 10.8 million
pounds of point source phosphorous discharged per year below the Fall Line,
the total point source contribution of phosphorous is computed to be about 40
percent of the total annual phosphorous input budget of around 11 million
pounds per day. Seasonally, the point source contribution of phosphorous
makes up as much as 65 percent of the fall total phosphorus input budget and
as little as 25 percent of the summer total phosphorous input budget.
The "daily discharge that is greater than or equal to the flows that occur
10 percent of the time" was computed for each major tributary. They are:
Susquehanna, 6640 cfsd; Potomac, 1690 cfsd; James, 1330 cfsd.
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3. What percentage of nutrients is from nonpoint sources and how do they vary
over time? -
To discuss nonpoint sources within the structure of this paper, we define
three categories of diffuse sources. They are:
i) Atmospheric contributions
ii) Land runoff/base flow contributions
iii) Benthic contributions
Categories i) and ii) are covered separately elsewhere in this Section
under the discussions of other Management Questions. For the purpose of
answering this Management Question, we define nonpoint sources as the sum of
land runoff and base flow (groundwater discharge) which is carried by fluvial
processes to the tidal Bay system. Contributions from the coastal plain are
not considered.
On an annual basis, the mean total nonpoint source nitrogen loading is
about 50 to 55 percent of the total input budget, or about 160 to 177 million
pounds of nitrogen per year [Tables VIII.l(a) and VIII.l(b)], making this the
single largest external source of nitrogen loading to the Bay. Seasonally,
the variation in the nonpoint source nitrogen loading is quite dramatic,
ranging from about 23-25 million pounds in the summer (36 - 39 percent of the
total source load) to around 69 - 71 million pounds in the spring (63 - 66
percent of the total spring nitrogen load) . The dominant species of nonpoint
source nitrogen at the Fall Line is always nitrite-nitrate, making up
consistently between 62 and 64 percent of the total nitrogen from this source.
On an average annual basis, the nonpoint source loading of phosphorous is
about 30 to 34 percent of the total phosphorous input budget, ranging from
around 9 to 10 million pounds per year. As much as 65 to 70 percent of this
load on an annual basis is in the suspended phase, meaning most of the
phosphorous is being carried to the Bay associated with particulate matter and}
therefore, not immediately available for phytoplankton utilization.
Seasonally, the nonpoint phosphorous contribution probably varies from about
1.2 to 1.4 million pounds (only about 10-11 percent of the summer total
phosphorous budget) in the summer to about 4 million pounds in the spring,or
55 percent of the total spring input budget of phosphorous from all. sources.
The very low percentage of the load eminating from fluvial sources in the
summer is mainly due to the dominant effect of benthic sources of phosphorous
released in that season.
4. What are the pollutant runoff rates for particular land uses?
This is the only management question to be answered in the paper for which
the source information upon which the answer is based is not contained within
the text. The information upon which this answer is based may be found in the
EPA Chesapeake Bay Program Information Series Nutrient; Summary 3: "Assessment
of Nonpoint Source Discharge to Chesapeake Bay" (unpublished). The data
presented in that report are the results of a preliminary analysis of the data
from the Chesapeake Bay Program Intensive Watershed Studies (IWS).
The analysis performed on the data used the volume-weighted mean
concentrations of storm event runoff, computed for the GBP studies (Hartigan,
1981) along with some typical expected average annual runoff volumes for
various land use/soil texture combinations, to generate generalized annual
pollutant loadings for various classes of land use. These data are presented
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in Table VIII.6. Although the analysis, in its preliminary state, necessarily
produced overlapping ranges of runoff loading rates among land uses, the data
in Table VIII.6 allow us to assign order of magnitude rankings for the land
uses studied by areal loading rate. The generalized rankings are shown in
Table VIII.7.
In all cases, the highest unit area loading rates were generally exhibited
by cropland sites and the lowest by forest sites.
(N.B. The rankings shown in Table VIII.7 are a very broad generalization!)
TABLE VIII.7, CONCENTRATION, MG/L (TOP LINE), AND LOADING RATES, LBS/AC/YR
(BOTTOM LINE), FOR TOTAL SUSPENDED SOLIDS, TOTAL PHOSPHORUS,
ORTHOPHOSPHATE. TOTAL NITROGEN, AND NITRITE-NITRATE FROM VARIOUS
USES OF LAND(1'(2)
Land Use
Cropland^3)
Pasture
Forest
Residential
SED
46.5-3202.8
10.54-2460.83
145.20-669.70
16.45-303.50
9.40-71.5
0.53-48.60
38.00-634.4
47.40-2395.1
TP
0.21-12.49
0.05-9.78
0.38-1.12
0.04-0.51
0.06-0.23
0.00-0.16
0.10-1.66
0.13-5.22
OP
0.01-2.77
0.01-2.20
0.06-0.14
0.01-0.06
0.00-0.04
0.00-0.03
0.02-0.17
0.03-0.54
TN
1.3-22.2
0.75-17.59
2.20-6.20
1.25-2.81
0.40-1.10
0.02-1.00
0.70-2.8
0.87-8.82
N023
0.02-16.20
0.02-12.90
0.30-1.71
0.03-0.78
0.01-0.48
0.00-0.33
0.26-0.90
0.32-2.84
'•^'Volume-weighted concentration data from preliminary analysis by NVPDC,
concentration in milligrams per liter. Personal Communication:
"Volume-Weighted Mean Concentrations of Storm Event Runoff from EPA/CBP
Test Watersheds," J.P. Hartigan, Regional Resources Division, Norther
Virginia Planning District Commission, Falls Church, VA, October 13, 1981.
^'Loading rate computed by CBP staff, in Ibs./ac./year.
"•-^'Cropland includes primarily conventional and minimum till with some no-
till land practices.
TABLE VIII.8. GENERALIZED RANKING OF LAND USES BY UNIT AREA RUNOFF LOADING
RATE (1 = HIGHEST RATE, 4 = LOWEST RATE)
Land Use
Cropland
Residential
Pasture
Forest
TN
1
2
3
4
N023
1
2
3
4
TP
1
2
3
4
OP
1
2
3
4
SED
1
2
3
4
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For instance, one of the cropland sites in the southern portion of the
western shore produced less nitrite-nitrate per acre than one of the forest
sites on the upper Eastern Shore. Although this example may be anomalous, it
illustrates that there is overlap in the data and that the rankings shown are
general in nature and by no means apply to all sites on all soil types. They
are intended to give indications of which land uses, in general, have the
highest loading rates and which uses have the lowest rates, relative to one
another.
Within the class of developed land use types such as residential and
commercial uses, it has been shown (Smullen, Hartigan, and Grizzard 1978;
Smullen 1979, NVPDC 1979) that there is a direct relationship between
intensity of land use, often measured as the imperviousness of a site, and the
unit area loading rate yield of nutrients. A ranking of the urban uses by
loading rate is shown in Table VIII.8.
TABLE VIII.9, RANKING OF URBAN LAND USES BY UNIT AREA LOADING RATE* FOR
NUTRIENTS (HIGHEST LOADING RATE = 1, LOWEST LOADING RATE = 7)
Land Use Ranking
Central Business District 1
Shopping Center 2
High-Rise Residential 3
Multiple Family Housing 4
High Density Single Family Housing 5
Medium Density Single Family Housing 6
Low Density Single Family Housing 7
In general, urban uses exhibit higher unit area loading rates of nutrients
than forest or pasture uses and lower rates than cropland uses. Exceptions to
this "rule of thumb" are that pasture typically will yield slightly higher
rates than the very low-density residential uses and that well-managed,
low-tillage cropland uses on pervious soils can yield lower rates than some of
the more intensive urban uses.
5. What percentages of nonpoint source nutrient loadings can be attributed to
particular land uses?
Although it was relatively easy to sort out the point source from nonpoint
source loadings in answering questions 2 and 3, it is more difficult to
determine, with any level of precision, the fraction each land use contributes
to the overall nonpoint load. We first must accept two basic assumptions to
facilitate the estimate, and they are: (1) that the land uses are
homogeneously distributed above the fall line; and (2) that baseflow loadings
(groundwater contributions) of nutrients may be considered a constant
background load, and the nonpoint load is measured as surface runoff and
(Smullen, Hartigan, and Grizzard 1977)
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interflow! nutrient loadings. The homogeniety of land use assumption is
considered reasonable because most of the urban population resides on the
coastal plain (below the Fall Line) and, with the exception of the mountainous
areas, the agricultural and forest lands in the basin are fairly evenly
distributed. This assumption is necessary because the closer a source is to
the Bay, the more effect its loading will have upon the water quality of the
system. Thus, it is important that no large mass of a particular land use
type above the Fall Line be closer than any other type or there would be a
skew of the loadings at the Fall Line reflecting that skew in the land use
distribution. The second assumption is necessary because we just don't
intuitively understand the functional relationship between land use and the
quality of groundwater discharge on basins the size of the Potomac, James, and
Susquehanna.2 We do know isolated facts — such as, the more fertilizer
applied, the greater the opportunity for increasing groundwater nitrate levels
and the resulting baseflow nitrate loadings in the stream. For the purpose of
this analysis, it is enough to accept that for land uses that don't involve a
lot of impervious cover, the baseflow loadings will move reasonably well with
the runoff loadings. That is to say, that land uses exhibiting higher
nutrient runoff loadings will produce groundwater discharge loadings equal to
or greater than those from uses exhibiting lower runoff nutrient loadings.
The land uses above the Fall Line of the Chesapeake basin are about:
60-65 percent forested, 15-20 percent cropland, 8-12 percent pasture, 3-5
percent urban/suburban, and 2-14 percent other. These are rough estimates
made from existing land use maps and will adequately serve the purpose of this
"order-of-magnitude" analysis. Land use/nutrient loading rate relationships
developed locally within the Chesapeake basin (Smullen, Hartigan, and Grizzard
1978, Smullen 1979, NVPDC 1979) used for this analysis are shown below:
Land Use
Percent in Basin
Estimated
Loading Rate (Ibs./ac./yr.)
Cropland
Pasture
Forest
Urban/ Suburban
15-20
8-12
60-65
3-5
TN
8-18
2-6
.5-2
4-10
TP
1.5-5
.3-. 5
.05-.!
1-2
•'•Interflow is the lateral movement of water through soils to streams at
shallow soil depths during and directly after storm events. It is of short
duration and, for our purposes, can be considered to be part of the runoff
hydrograph.
f\
zThis is a good example of why assessments such as this are best made with
mathematic models. They facilitate the orderly sorting out of base flow,
runoff, and interflow and allow the analyst to handle groundwater
contributions by inspection of observed flow data.
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The unit area loading rates shown above were weighted by the fractions of
the land areas in each use and the following ranges of loading fractions were
obtained:3
Land Use
Percent of Nonpoint Source Load
TN TP
Cropland
Pasture
Forest
Urban
45-70
4-13
9-30
2-12
60-85
3-8
4-8
4-12
In summary, agricultural cropland appears to produce the largest fraction
of the nonpoint source load from above the fall lines by at least a factor of
two for both nitrogen and phosphorous. This is partly due to a high unit area
loading rate for cropland and mostly due to the large percentage of the land
area in this use. Forest loadings of nitrogen are the next highest percentage,
and this is entirely due to the large fraction of the watershed still being in
forest land. Urban/suburban and pasture lands above the Fall Line produce
approximately equal loads.
By inspection, the percentages shown above would change very little if the
Coastal Plain areas were included. Although the three major metropolitan
areas (Washington, B.C., Richmond, Virginia, and Baltimore, Maryland) would
increase the total amount of urban land area, this increase would probably be
offset by the large rural land areas of the eastern and western shore portion
of the Coastal Plain. At any rate, even if the proportion of urban area
doubled, cropland would still be the largest nonpoint source nutrient load by
an approximate factor of three.
6. What are the nutrient loadings from the Fall Line?
The nutrient loadings from the Fall Line are shown in Tables III.. 10 and
again in Tables VIII.2 through VIII.5. The values for total nitrogen and
total phosphorus are shown again below in millions of pounds.
Annual
Winter
Spring
Summer
Fall
178.1
10.3
51.4
2.97
72.2
4.29
25.1
1.42
27.9
0.47
TN
TP
The percentage of the annual above fall line load produced in each season are
shown below:
Winter
Spring
Summer
Fall
TN
TP
28.9
28.8
40.5
41.7
14.1
13.8
15.7
4.6
best and worst case assumptions were used along with some common sense
judgment. For example, the lower range of cropland loading was produced by
assuming the lowest loading rate/percent land use combination for cropland
and the middle value of the ranges for all other uses.
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From the data presented, it can be seen that the largest fraction of the
fluvial nutrient load (40 percent of both nitrogen and phosphorus) is
discharged to the tidal system during the spring. Observation of the data in
Table III.10 shows that a large fraction of these spring loads are in forms of
nutrients that are readily available for aquatic plant uptake , with 68
percent of the nitrogen as ammonia or nitrite-nitrate and 34 percent of the
phosphorus as orthophosphorous. This is important since the spring is the
critical start-up period for the phytoplankton growing season, the aquatic
plant growth that will dominate, in part, the dissolved oxygen and chlorophyll
conditions in the Bay through the summer and into the early fall. As noted
elsewhere in this chapter, the predominant upstream source of the riverine
transported spring nutrient load is probably runoff and groundwater discharge
from agricultural lands. The next most important source of nitrogen (but
probably lower by almost an order of magnitude) in spring river discharge from
above the fall line is probably runoff and groundwater discharge from the
melting of the snow-pack in the physiographic provinces upstream of the
Piedmont (see Figure III.2).
The summer is the period during which the plankton growth in the Bay
reaches the annual maximum (see Chapter 2 of this part). The fluvial
transported nutrients play a lesser role during this period, providing only
about 39 percent of the readily available nitrogen forms of plant nutrients
and only about 5 percent of the readily available phosphorus. Plankton
communities flourish during this period primarily by recycling nutrients
already in the water column (put there in part by the spring fluvial process)
as noted in Chapter VII (Table VII.5); and secondarily by the supply of
nitrogen from atmospheric, point and benthic sources and by the supply of
phosphorus from point and bottom sources.
7_ What do the bottom sediments contribute to nutrient inputs?
On an annual basis, bottom sediments contribute 32 million pounds of
nitrogen and seven million pounds of phosphorus [Table VIII.l(a)]. This makes
up about 10 and 25 percent of the annual nitrogen and phosphorous budgets,
respectively [Table VIII.Kb)]. However, the nitrogen contributed from the
benthic source is predominately ammonia and makes up about 45 percent of the
total annual Bay-wide contribution of this nitrogen species, which is most
preferred by aquatic plants. More than 50 percent of the externally supplied
water column ammonia produced during the spring and summer comes from the
benthos.
The sediments have their most dramatic effect on the nutrient input budget
as a source of phosphorous in the summer. As discussed in Chapter V, most of
phosphorous migrating up through the sediments via the pore waters is probably
chemically fixed by iron in the overlying oxygen-rich waters and held in a
fluff layer as a small particle, or floe. This process occurs during most of
the year (late fall, winter, spring). However, when the oxygen in the lower
layers of the Bay waters is depleted for periods during the summer, most of
the phosphorus incorporated or stored during the rest of the year is probably
released over a very short period of time. The result is that as much as 62
percent of the phosphorous input to the Bay in the summer could come from this
source. Other than recycling, the bottom source is probably the single
largest factor in the supply of phosphorous for summer primary productivity.
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8. What are the flux rates of nutrients from the bottom sediments; and how do
they vary seasonally?
The benthic flux rates for nitrogen range from as low as 0.5 pounds of N
per square foot per day in portions of the upper Bay in the spring to as high
as 5 pounds of N per square foot per day in portions of the upper Bay in the
spring and summer. The annual seasonal Bay-wide average flux rates for
nitrogen are shown below:
Nitrogen Benthic Flux of Nitrogen
(Thousands of Pounds Percent of
per day) Annual Average
Winter
Spring
Summer
Fall
Annual Average
88.1
75.3
98.4
91.2
88.3
100
85
111
103
As can be seen above, the summer period exhibits the highest flux rate of
nitrogen from the sediments, and the spring the lowest. The nitrogen is
moving out of the sediments the fastest when the standing crop of
phytoplankton is the largest, and it is being produced in a form readily
available for plant uptake.
As discussed previously, the seasonal variation of phosphorous flux from
the sediment to the water column is severe, with about 85 percent of the total
annual input being released rapidly sometime from late May to mid-June, with
most of the other 15 percent released from that time through late summer.
An educated guess at the maximum Bay-wide phosphorous release rate is that
it might be as high as one-half million pounds a day during the period of the
rapid onset of bottom-water anoxia. This rate probably levels off to about
16,000 pounds per day by late summer and down to near zero by sometime in late
fall.
9- Given the estimated loadings of nutrients for each of the sources, which
will be the most important in terms of their effects on the Bay system?
This is a difficult question to answer because there are so many potential
effects on the Bay system that could result from variations in nutrient
loadings. Some effects are understood well; some not: so well, and some are
unknown. However, to provide an answer to this question, we will consider the
potential effects on Bay-wide primary production which might result from
variations in the amounts of nutrients entering from various sources.
On an annual basis (Table VII.2), probably only about 20-30 percent of the
Bay proper primary production is supported by nitrogen and phosphorous
entering the water column from external sources. We will assume, for this
exercise, that nutrient recycling rates by phytoplankton would vary only
moderately in response to changes in external nutrient supply. Given this
assumption, it can be seen from the data in Table VIJ.2 that even as much as a
50 percent reduction in both point and nonpoint source annual nutrient
loadings may result in as little as a 10 percent reduction in Bay-wide primary
production. Seasonally, this effect could decrease to only a 5 percent
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reduction in summer production in response to a 50 percent reduction of summer
point/nonpoint nutrient loading. If these loading reductions were sustained,
production would probably decrease futher as the nutrient reservoir in the
sediments depleted over time. These estimated decreases of primary
production in the short-term approach the detection limit of our ability to
assess such reductions.
The important point in this discussion is that changes in lower Bay water
quality (essentially meaning the great majority of the Bay that lies below the
mouth of the Patuxent) in response to changes in nutrient inputs would
probably take place slowly over decades. However, the upper portions of the
Bay and the tidal tributaries would be much more responsive to change in
nutrient loads than the main Bay. The nutrient loads that the main Bay
receives must travel through these smaller, heavily impacted areas of the
system.
The nutrient inputs are diluted as they move towards the lower Bay as a
function of ever increasing volume. In addition, the surface area available
for contributing nutrients from the sediments is much greater in the main Bay
than in the upper portions of the system, resulting in much larger bottom
releases of nutrients. These factors and others create a situation in the
main Bay that tends to buffer or dampen water quality response to changes in
anthropogenic nutrient loadings. It is, therefore, reasonable to expect the
water quality of the upper areas (tidal fresh areas) of the system to respond
more quickly to load reductions than the areas of the lower main Bay.
The apparent improvement in the water quality of the upper Potomac in
response to decreased nutrient loadings over the last decade would seem to
support this concept. Even though some unknown amount of that improvement is
probably due to differing climatic conditions over the last ten years, some
degree of the improvement is most likely due to the decreases in the external
nutrient supply from POTW's. We would not expect to see immediate changes in
lower Bay water quality due to that reduction of loading and, in fact, have
not. Such a change could only be seen over a much longer period of time and
to a lesser (diluted) extent. This situation would seem to support the
concept that if we manage the local ("near field") problems, the main Bay
("far field") will, in time, respond in kind. An aggressive policy of water
quality improvement in currently adversely impacted areas should insure the
maintenance of a nondegradation condition in the main Bay.
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LITERATURE CITED
Bricker, O.P., G. Matisoff, and G.R. Holdren Jr. 1977. Interstitial Water
Chemistry of Chesapeake Bay Sediments. Basic Data Report No. 9, Maryland
Geological Survey, Department of Natural Resources, Baltimore, MD.
Correll, D.L., T.L. Wu, J.W. Pierce, M.A. Faust, K.M. Lomax, J.C. Stevenson,
and M.S. Christy. Rural Non-Point Pollution Studies in Maryland.
EPA-904/9-78-002, U.S. Environmental Protection Agency, Washington, DC.
Cronin, W.B. 1971. Volumetric, Areal and Tidal Statistics of the Chesapeake
Bay Estuary and its Tributaries. Special Report No. 20., Chesapeake Bay
Institute of the John Hopkins University, Shady Side, MD.
Flemer, D.A. 1970. Primary Production in the Chesapeake Bay.
Chesapeake Science, Vol. 11, No. 2, pp.117-129.
Gambell, A.W., and D.W. Fisher. . Occurrence of Sulfate and Nitrate in
Rainfall. Journal of Geophysical Research, Vol. 69, pp 4203-4210.
Guide, V., and 0. Villa, Jr. 1972. Chesapeake Bay Nutrient Input
Study. Technical Report 47, Central Regional Laboratory, U.S.
Environmental Protection Agency, Annapolis, MD.
Hill, J.M., and R.D. Conkwright. 1981. Chesapeake Bay Earth Science
Study: Interstitial Water Chemistry. Prepared in cooperation with the
U.S. Environmental Protection Agency Chesapeake Bay Program by the
Maryland Geological Survey, Department of Natural Resources, Baltimore, MD.
Lang, D.J. 1981. Water Quality of the Three Major Tributaries to the
Chesapeake Bay, January 1979 - April 1981 — Estimated Loads and
Examination of Selected Water-Quality Constituents. Water Resources
Investigations - Unpublished Records, U.S. Geological Survey, Towson, MD.
(Draft)
Lang, D.J., and D. Grason. 1980. Water Quality Monitoring of Three Major
Tributaries to the Chesapeake Bay - Interim Data Report. Water -
Resources Investigations 80-78, U.S. Geological Survey, Towson, MD.
Neter, J., and W. Wasserman. 1974. Applied Linear Statistical Models.
Richard D. Irwin, Inc., Homewood, IL.
Northern Virginia Planning District Commission and Virginia Polytechnic
Institute and State University. 1977. Occoquan/Four Mile Run Non-Point
Source Correllation Study: Technical Report for the Period December 1,
1976 - February 28, 1977. Prepared for Metropolitan Washington Water
Resources Planning Board, Washington, DC.
Northern Virginia Planning District Commission and Virginia Polytechnic
Institute and State University. 1978. Occoquan/Four Mile Run Non-Point
Source Correllation Study. A Final Report. Prepared for Metropolitan
Washington Water Resources Planning Board, Washington, DC.
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Northern Virginia Planning District Commission. 1979. Guidebook for
Screening Nonpoint Pollution Management Strategies. Prepared for the
Metropolitan Washington Council of Governments, Washington, DC.
SAS Institute. 1979. SAS User's Guide: 1979 Edition. SAS Institute, Inc.,
Gary, NC.
Smullen, J.T. , J.P. Hartigan, and T.J. Grizzard. 1978. Assessment of Runoff
Pollution in Coastal Watersheds. In: Coastal Zone '78; A Symposium on
the Technical, Environmental Socio-Economic and Regulatory Aspects of
Coastal Zone Management. American Society of Civil Engineers, New York,
NY. pp 840-857.
Smullen, J.T. 1979. A Simple Empirical Model of Runoff Pollution for
Environmental Planning. M.S. Thesis, Rutgers University, New Brunswick,
NJ.
Stensland, G.J. 1980. Precipitation Chemistry Trends in the Northeastern
United States. In: Polluted Rain. Plenum Press, New York, N.Y.
Taft, J. L., A. J. Elliott, and W. R. Taylor. 1978. Box Model Analysis of
Chesapeake Bay Ammonium and Nitrate Fluxes. In: Estuarine Interactions,
ed. Martin L. Wiley, Academic Press.
Taft, J. L. 1982. Nutrient Processes. This Volume.
Tyree, S.Y., M.A.O. Bynum, J. Stouffer, S. Pugh, and P. Martin. 1981.
Chesapeake Bay Earth Science Study: Sediment and Pore Water Chemistry.
Prepared in cooperation with the U.S. Environmental Protection Agency
Chesapeake Bay Program by the Department of Chemistry, College of William
and Hary, Williamsburg, VA. (Draft).
U.S. Environmental Protection Agency - Chesapeake Bay Program. 1982.
Assessment of Nonpoint Source Discharge to Chesapeake Bay. Information
Series Nutrient Summary 3. USEPA-CBP, Annapolis, MD. (In Press)
Uttormark, P.O., J.D. Chapin, and K.M. Green. 1974. Estimating Nutrient
Loadings of Lakes from Non-Point Sources. EPA-660/3-74-020. U.S.
Environmental Protection Agency, Washington, DC.
Virginia Polytechnic Institute and State University. 1978. Occoquan/Four
Mile Run Runoff Pollution Field Study (Fourth Quarterly Report). Prepared
for the Northern Virginia Planning District Commission, Falls Church, VA.
Virginia Polytechnic Institute and State University. 1981. Progress Report,
Evaluation of Management Tools in the Occoquan Watershed. Prepared for
Virginia State Water Control Board, Richmond, VA.
Wade, T.L., and G.T.F. Wong. 1981. Chemistry of Wet and Dry Fall in Lower
Chesapeake Bay. Prepared for the U.S. Environmental Protection Agency
Chesapeake Bay Program, Annapolis, MD.
247
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Ward, J.R., and D.A. Eckhart. 1979. Nonpoint-Source Discharges in Pequea
Creek Basin, Pennsylvania, 1977. Water Resources Investigations 79-88,
U.S. Geological Survey, Harrisburg, PA.
Wolman, M.E. 1968. The Chesapeake Bay: Geology and Geography. In:
Proceedings of the Governor's Conference on Chesapeake Bay. September
12-13, 1968. pp. 7-48.
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APPENDIX A
METHODOLOGY FOR COMPUTATION OF NUTRIENT AND SEDIMENT LOADS
TRANSPORTED TO THE BAY BY RIVERS
The dependent or response variable in each of the models is based upon
the flow - weighted daily mean concentration of the constituent for which
the model is being formulated. This was done to normalize the effects of
observations taken on the rising versus falling limb of a storm
hydrograph. To determine flow-weighted concentrations for days when
multiple observations were collected, the products of the concentration for
an observation and the instantaneous flow recorded for that observation
were summed over all the observations in a day, and that sum was divided by
the sum of the instantaneous flows. This is shown in equation A-l:
Cj = - Ci q£ (eq. A-l)
i = 1
i = 1
where Cj = flow-weighted mean daily constituent concentration
G£ = individual constituent concentration observation (mg/1)
q^ = instantaneous discharge at time of observations 'c' (CFS)
n = number of observations in day 'J1.
For the special case of n = 1, that is only one observation taken on a
particular day (e.g., a base flow observation), the mean daily
concentration is simply set equal to the observed concentration, or Cj =
G£, after equation A-l.
Model Formulations: Models were developed using the basic least squares
regression normal error model (Neter and Wasserman, 1974) stated as:
Y£ = BQ + B^i + ei (eq. A-2)
where BQ and B^ are parameters
Y£ and X^ are known constants (dependent and independent
variables)
e£ are independent N(0,s2)
(The dependent variable Y^ is based on Cj, Equation A-l)
All model formulations attempted are based upon the simple linear
regression model (eq. A-2) or the use of some remedial measure involving
transformations of the data. Transformations were chosen either to
linearize the regression function (semi-logarithimic or fully-logarithmic)
or to stabilize the error term variance. Full descriptions of the
methodologies and validity of these approaches can be found in Neter and
Wasserman (1974) or most basic linear statistical models texts.
In all, twelve separate models were tested, made up of three sub-groups
with arithmatic, semi-log transformation by each axis, and
log-transformations on both axes performed within each sub-group. All
249
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logarithms are taken as Napierian logarithms. The model formulations are
described below.
Concentration Models: The basic form of this model sub-group is the
relationship between the mean daily, flow-weighted concentration of a
constituent (C, mg/1) versus the mean daily discharge. (Q in cubic feet
per second per day [Cfsd]). The four models investigated are shown below:
i) C versus Q
ii) ln(C) versus Q
iii) C versus ln(Q)
iv) ln(C) versus ln(Q)
Loading Rate Models: The basic form of this model sub-group is the
relationship between daily constituent loading rate (LR, Ibs/day), computed
as the product of the flow-weighted constituent concentration for the day,
the mean daily discharge for the day, and a conversion factor, versus the
mean daily discharge (Q, cfsd)l. The four transformations investigated
are shown below:
i) LR versus Q
ii) ln(LR) versus Q
iii) LR versus ln(Q)
iv) ln(LR) versus ln(Q)
It is noted that a functional relationship exists between the mass of
pollutant washed off and discharge that is inherent in the determination of
the dependent variable term for this model. It follows that the use of the
least squares method may not result in the best linear unbiased estimation
of the data in the Gauss-Markov theorem sense. 2 Although other biased or
nonlinear estimation approaches such as distribution-free or non-parametric
statistics might yield smaller variances, the least squares approach was
chosen for its simplicity and ease of application. It is also noted that
although the coefficients of determination developed from these models
remain useful for comparison with other models, the 't1 tests for the slope
may not be useful for comparison with the other models because of the
suspected bias in the relationships.
Variance-Stabilizing Transformation Models: The basic form of this
sub-group involves a transformation to stabilize error variances. Residual
analysis through scatter plot observations of the C versus Q type models
(above) suggested that in many cases the variance of the error was
increasing with the volume of discharge. That is, the relationships
appeared to have heterosadastic tendencies, exhibiting non-constant
variance over the range of observed flows. Therefore, the estimator BQ
nutrient loading rate is computed as:
LR = K x C x Q
where LR = Nutrient loading rate ( Ibs/day)
K = Conversion factor equal to 5.38 (liter-sec. -Ib/mg.-f t^-day)
C = Nutrient concentration in mg/1
Q = Mean daily discharge in cubic feet per second
^That is to say, the least squares estimator may not have a minimum
variance within the class of linear, unbiased estimators.
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and Bj^ (eq. A-2) , though still unbiased, are no longer minimum variance
unbiased estimators. Neter and Wasserman (1974) suggest a transformation
of the form:
Y'= Y and X' = ^ (eq. III-3, III-4)
X X
to minimize the variance. The general form, then, of this group of model
is as follows:
i) (C/Q) versus (1/Q)
ii) ln(C/Q) versus (1/Q)
iii) (C/Q) versus ln(l/Q)
iv) ln(C/Q) versus ln(l/Q)
Neter and Wasserman point out that this transformation is really
equivalent to using weighted least squares and further indicate that the
relationship remains unbiased. Regression statistics ("t1 tests) remain
fully useful.
Regression Analysis
The correlation coefficient for each of the models described above were
computed at each site for the water quality parameters listed in Table
A.I. The coefficients of determination for the Susquehanna, Potomac and
James models are shown in Table A.2, A.3 and A.4. Only models exhibiting
coefficients in excess of 0.50 are shown.
TABLE A.I. WATER QUALITY VARIABLES INCLUDED IN REGRESSION ANALYSIS
Water Quality Parameter
Total Nitrogen (as N)
(Particulate & dissolved)
Dissolved Nitrogen (as N)
Total Kjeldahl Nitrogen (as N)
Total Nitrite plus Total Nitrate
Nitrogen (as N)
Total Ammonia Nitrogen (as N)
Total Phosphorus (as P)
STORET No.
600
602
625
630
610
665
Variable Name
TN
DN
TKN
N02 + N03
or N023
NH3 + NH4
or NH34
TP
(Particulate & dissolved)
Dissolved Phosphorus (as P)
Total Orthosphosphorus (as P)
Suspended Sediment
666
70507
80154
DP
OP
SED
The Tables (A.2, A.3, and A.4) show that poor fits (r2 0.50) were
found in almost all cases for the concentration-versus-discharge models.
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In most cases, visual inspection of scatter diagrams allows a case to be
made for heteroodasticity and, for this reason, the variance-stabilizing
transformation were favored in selecting appropriate models.1 Only when
correlation coefficients were significantly below 0.65 or *t' tests
(H0;B;L = 0) indicated that B^, the slope, was not significantly
different from zero at the 95 percent confidence level was a loading rate
model chosen.
•'•During the course of examination of the concentrations predicted by each
of the models over the range of flow observed in the period of record, it
was determined that the arithmetic form of the variance-stabilizing
transformation (C/Q versus 1/Q) yielded unrealistically high values for
discharges in excess of those observed during the period of the monitoring
program. The log-log transformation of this model [ln(C/Q) versus
ln(l/Q)] proved to be much better behaved in predicting concentrations for
these higher flows. The curves produced with this transformation "flatten
out" very quickly as flows approach those at the upper limit of the
discharge data observed during the field program. Therefore, only the log
transformed versions of the variance-stabilizing transformation were:
considered for cases exhibiting heterosodasticity.
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TABLE A.2, REGRESSION MODEL RESULTS FOR THE SUSQUEHANNA RIVER AT CONOWINGO,
MD (1578310) RESULTS DISPLAYED ONLY FOR MODELS EXHIBITING
COEFFICIENTS OF DETERMINATION IN EXCESS OF 0.50
Water Quality
Constituent
TN
DN
N023
NH34
TKN
Model
C/Q vs. 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (l/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
r2
.948
.503
.916
.852
.722
.611
.933
.972
.518
.926
.832
.742
.618
.931
.927
.382
.887
.859
.668
.694
.906
.575
.558
.611
.713
.916
.551
.805
.644
.707
.850
d.f.
86
86
86
86
86
86
83
66
66
66
66
66
66
66
86
86
86
86
86
86
86
87
87
86
86
87
87
87
87
87
87
(continued)
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TABLE A.2. (continued)
Water Quality
Constituent Model r2 d.f.
TP C vs. Q
In (C) vs. Q
C/Q vs. 1/Q
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
.518
.503
.863
.565
.696
.792
.885
87
97
87
87
87
87
87
DP C/Q vs. 1/Q .565 88
In (C/Q) vs. In (1/Q) .778 85
LR vs. Q .597 88
In (LR) vs.Q .612 85
In (LR) vs. In (Q) .797 85
OP In (C/Q) vs 1/Q .512 60
In (C/Q) vs. In (1/Q) .639 66
In (LR) vs.Q .600 66
In (LR) vs. In (Q) .730 66
SED In (C) vs. Q .677 96
C/Q vs. 1/Q .542 93
In (C/Q) vs 1/Q .667 93
LR vs. Q .550 93
In (LR) vs.Q .741 93
In (LR) vs. In (Q) .665 93
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TABLE A.3. REGRESSION MODEL RESULTS FOR THE POTOMAC RIVER AT CHAIN BRIDGE,
WASHINGTON, DC (1646580) RESULTS DISPLAYED ONLY FOR MODELS
EXHIBITING COEFFICIENTS OF DETERMINATION IN EXCESS OF 0.50
Water Quality
Constituent
TN
DN
N023
NH34
TO
TP
DP
Model
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. In (Q)
In (LR) vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs. In (1/Q)
In (LR) vs.Q
In (LR) vs. In (Q)
In (C/Q) vs 1/Q
In (C/Q) vs. In (1/Q)
In (LR) vs. In (Q)
r2
.847
.551
.776
.856
.571
.914
.704
.597
.681
.840
.721
.717
.592
.913
.637
.618
.804
.637
.869
.707
.682
.580
.565
.719
.531
.849
.510
.588
.549
.847
.576
.718
.801
d.f.
64
64
64
64
64
64
63
63
63
63
63
63
63
63
64
64
64
64
64
61
80
80
80
80
80
80
80
79
79
79
77
77
77
(continued)
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TABLE A.3. (continued)
Water Quality
Constituent Model r2 d.f.
OP C/Q vs. 1/Q .583 56
In (C/Q) vs. In (l/Q) .622 47
In (LR) vs.Q .573 47
In (LR) vs. In (Q) .696 47
SED C vs. Q .515 60
In (C) vs. Q .512 60
In (C) vs In (Q) .658 60
LR vs. Q .796 60
In (LR) vs.Q .640 60
In (LR) vs. In (Q) .879 60
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TABLE A.4, REGRESSION MODEL RESULTS FOR THE JAMES RIVER AT CARTERSVILLE, VA.
(2035000) RESULTS DISPLAYED ONLY FOR MODELS EXHIBITING
COEFFICIENTS OF DETERMINATION IN EXCESS OF 0.50
Water Quality
Constituent
TN
DN
N023
NH34
TKN
Model
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
LR vs. In (Q)
In (LR) vs. In (Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
r2
.769
.679
.633
.817
.842
.728
.523
.909
.861
.728
.713
.894
.720
.713
.909
.530
.509
.759
.816
.568
.614
.824
.646
.525
.551
.725
.653
.617
.509
.665
.786
.727
.862
d.f.
54
54
54
54
54
54
54
54
38
38
38
38
38
38
38
56
56
56
56
56
56
56
49
56
49
49
55
55
55
55
55
55
55
(continued)
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TABLE A.4. (continued)
Water Quality
Constituent
TP
DP
OP
SED
Model
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
C/Q vs. 1/Q
In (C/Q) vs 1/Q
C/Q vs In (1/Q)
In (C/Q) vs. In (1/Q)
In (LR) vs. In (Q)
C vs. Q
In (C) vs. Q
C vs. In (Q)
In (C) vs In (Q)
LR vs. Q
In (LR) vs.Q
In (LR) vs. In (Q)
r2
.781
.718
.522
.669
.715
.758
.762
.873
.754
.588
.908
.626
.526
.581
.809
.725
.537
.815
.511
.631
.539
.535
.723
.841
.647
.903
d.f.
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56
56
56
56
56
56
56
56
56
56
56
56
56
48
46
48
46
46
71
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SUMMARY AND CONCLUSIONS
Increased population and changed land uses (deforestation, agriculture,
urbanization) in the Chesapeake Bay watershed have caused increases in
nutrient and sediment loads to the Bay system over the past 50 years. The
challenge facing water quality managers is to restrict excessive nutrient
addition as efficiently as possible, at the most effective times and
locations, and for the least expense. The Nutrients projects of the
Chesapeake Bay Program, discussed in this Synthesis Paper, were designed to
help managers meet this challenge by increasing their understanding of the
nutrients problem, its sources, and important processes.
THE NUTRIENT ENRICHMENT PROBLEM
Many areas of the Chesapeake Bay system have a serious nutrient
enrichment problem. Our studies indicate that the upper Bay, between
Turkey Point and the Bay Bridge, upper Potomac, upper Patuxent, and upper
James are heavily enriched; the mid-Bay, lower Patuxent, lower Potomac,
Rappahannock, York and middle James Rivers are moderately enriched. These
areas are considered to be enriched, because chlorophyll a_ levels are
elevated over historical levels.
Nutrient enrichment results in enhanced phytoplankton production and
higher levels of organic matter in the water column. Decomposition of
excessive organic matter results in depletion of oxygen from deeper waters,
posing a hazard for bottom-dwelling animals.
Nutrient enrichment also alters the composition of phytoplankton
species. Such changes have been shown to affect fisheries species
composition in other systems, and may have the same effect in Chesapeake
Bay.
The increased turbidity resulting from nutrient enrichment decreases
the amount of light available for submerged aquatic vegetation (SAV), and
has been implicated in their decline.
Solving the Problem: The Importance of Nutrient. Processes
The extreme solution to nutrient enrichment problems is to eliminate
the entry of excess nutrients to the Bay system. However, because of
social and economic restraints, this is not possible. Instead, we must
restrict the particular nutrients most responsible for the problems, at the
most effective times and places. To do this requires an understanding of
nutrient processes.
Seasonal factors determine the times at which nutrient restriction is
the most effective. The availability of nutrients follows an annual
cycle. In spring, heavy flows bring a substantial amount of nitrate into
the Bay. In summer, deoxygenation of deep water results in release of
phosphate from bottom sediments and the accumulation of phosphate and
ammonium in bottom waters. In the fall, re-oxygenation of deep waters
results in loss of phosphate from the water column and oxidation of
ammonium to nitrite and nitrate.
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Nutrient limitation of phytoplankton growth is a function of nutrient
availability and the intrinsic requirements of phytoplankton. Healthy
phytoplankton require carbon, nitrogen, and phosphorus in certain ratios.
The nutrient in least supply with respect to the requirements of
phytoplankton will limit their growth. Nutrient limitation occurs only if
other environmental conditions (like light availability) are satisfactory;
when too little light is available, for example, light becomes the limiting
factor. When a nutrient is limiting, addition of that nutrient will
stimulate phytoplankton growth.
Phosphorus is potentially limiting in the tidal-fresh reaches of the
Bay throughout the year (sediments of tidal-fresh segments do not become
anoxic, so phosphorus is not released from them). In the remainder of the
Bay system, phosphorus is potentially limiting in spring and fall; nitrogen
is potentially limiting in summer. Light is limiting in winter and in
situations of high turbidity.
Whether increases in algal production result in problems depends, in
part, on nutrient cycling. Water column nutrient cycling processes, such
as hydrodynamics and grazing, help remove excess plankton biomass from the
system. Decomposition, on the other hand, depletes the system of oxygen.
Regeneration of inorganic nutrients through these processes provides a
source of nutrients for phytoplankton growth.
Nutrient cycling processes in the sediments affect levels of nutrients
in the water column. Phosphorus is removed from the water column by
adsorption to iron and manganese compounds, to be released in summer from
anoxic areas. Ammonium fluxes into, or out of, the sediments, depending on
pore water concentrations and oxidation state.
Marshes and Bay grasses contribute to nutrient recycling by taking up
nutrients during their growing season (periods of peak availability.) and
releasing nutrients during the winter through decomposition. Thus, they
act as nutrient buffers.
Once the role of specific nutrients in specific times and places is
understood, nutrient sources must be known before exact and economical
solutions to nutrient problems can be developed.
Nutrient Sources: The Key to Comprehensive Control
On an annual basis, atmospheric contribution to the tidal waters of the
Bay system make up about 13 percent of the nitrogen and five percent: of the
phosphorus. In winter, up to 20 percent of the nitrogen may come from
atmospheric sources.
Point sources contribute up to 25 percent of the nitrogen and 40
percent of the phsophorus annually. While the nitrogen contribution varies
little during the year, the phosphorus contribution may be as much as 65
percent in the fall.
Nonpoint sources (land runoff/base flow) contribute up to 55 percent of
the nitrogen annually, the largest source of this nutrient to the Bay
system. In spring, nonpoint sources contribute up to 66 percent of the
total nitrogen. Nonpoint sources of phosphorus make up about 34 percent of
the annual total; in spring the contribution is about 55 percent. The land-
use contributing the most to these percentages, both on a unit area basis
and as percentage of the total, is cropland.
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Bottom sediments contribute about 10 percent of nitrogen and 25 percent
of phosphorus annually. The nitrogen contribution, primarily as ammonia,
is more than 50 percent in spring and summer. The bottom of the Bay is the
largest contributor of phosphorus in the summer, supplying as much as 62
percent of this nutrient.
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Appendix A
GBP Nutrient Enrichment Projects
Definition of Chesapeake
Bay Problems of Excess-
ive Enrichment or Eutro-
phication
Evaluation of Management
Tools in Two Chesapeake Bay
Watersheds in Virginia
Evaluation of Water Quality
Management Tools in the
Chester River Basin
Intensive Watershed Study
(Patuxent River Basin)
An Assessment of Nonpoint
Source Discharge, Pequea
Creek Basin, Lancaster County,
Pennsylvania.
Modeling Philosophy and
Approach for Chesapeake Bay
Program Watershed Studies
Fall Line Monitoring of the
Potomac, Susquehanna, and
James Rivers
Land Use and Point Source
Nutrient Loading in the
Chesapeake Bay Region
Chesapeake Bay Circulation
Model
L. Eugene Cronin
Bruce Nielson
Andrew McErlean
Donald Heinle
Kenneth Webb
Jay Taft
Robert V. Davis
Thomas Grizzard
Bruce Nielson
Howard Wilson
Charles Bostater
Howard Wilson
Charles Bostater
Robert J. Bielo
Janice Ward
Robert Ambrose
David Grason
David Lang
Benjamin J. Mason
Robert Shubinski
Chesapeake Research
Consortium
Virginia State Water
Control Board
Maryland Water Resources
Administration
Maryland Water Resources
Administration
Susquehanna River Basin
Commission
U.S. EPA Environmental Re-
search Laboratory, Athens,
Georgia
Water Resources Division,
U.S. Geological Survey
Geomet, Incorporated
Water Resources Engineers, Inc.
Water Quality Laboratory
for Chesapeake Bay and its
Subestuaries at Hampton
Institute
Larry T. Cheung
Hampton Institute
Chesapeake Bay Nutrient
Dynamics
Jay Taft
Chesapeake Bay Institute
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PART III
TOXIC SUBSTANCES
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1R. Bieri, 0. Bricker, R. Byrne, R. Diaz,
G. Helz, J. Hill, R. Huggett, R. Kerhin,
M. Nichols, E. Reinharz, L. Schaffner,
_ D. Wilding, and C. Strobel
• Technical Coordinator
• Duane Wilding
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CONTENTS
Figures 265
Tables 268
Sections
1. Introduction 272
2. Findings from Studies on Metals 277
Sources
Industries and POTWs below the fall line 277
Atmospheric sources 279
Urban runoff 283
River sources 284
Distribution and Concentration of Dissolved Metals 290
Distribution and Concentration of Metals in Suspended
Material 296
Distribution and Concentration of Metals in Bottom
Sediments 303
Metals in Interstitial Water 303
3. Findings from Studies on Organic Compounds 310
Sources 310
Organic Compounds in Bottom Sediments 311
Organic Compounds in Oysters 316
Conclusions 319
4. Patterns of Toxic Metal Enrichment 321
Interpretation of Processes Affecting Metal Distributions . . 321
Metal Enrichment 322
Historic metal inupt recorded in sediments 324
Metal-Sediment Relationships 326
5. Findings on Sediments and Biota 328
Character of Bed Sediments 328
Texture 328
Water Content 329
Carbon and Sulfur 329
Patterns of sedimentation 331
Benthic Organisms 333
Character of benthic fauna 333
Community composition 334
Vertical distribution 334
Bioturbation 334
Biological sediment mixing and fate of toxicants. . 335
6. Toxic Substances and Biota 339
Exposure Assessment 339
Toxicity Studies 339
Histopathology 339
Sediment bioassays 339
Effluent toxicity tests 340
7. Conclusions, Interpretations, and Management
Implications 342
8. Research Needs 346
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Literature Cited 349
Appendices
A. Inventory of project data discussed in this report ... 359
B. Summary of data sources for trace metals in the Chesapeake
Bay and tributaries 362
C. Summary of data sources for organic chemicals in the
Chesapeake Bay and tributaries 364
D. Areal distribution of sediment type in Chesapeake Bay; from
data of Kerhin et al. (1982) and Byrne et al. (1982) ...... 365
E. Summary of Chesapeake Bay toxic source assessment and
bioassay tests 366
F. Results of fish bioassays for effluent samples by species . . . 372
G. Results of invertebrate bioassays for effluent samples by
species • 372
H. Results of bacterial and grass bioassays 373
I. Results of Salmonella/Microsomal assays for mutogenicity of
Chesapeake Bay effluent samples 374
J. Results of mammalian cellclonal acute cytotoxicity assay .... 375
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FIGURES
Number Page
1 Graph of age versus metal content of Cu and Zn showing
historical increase of "excess" metal concentration due to
atmospheric deposition in Chesapeake Bay core 4 (Helz et al.
1981) by comparison to Farm River Marsh concentrations 282
2 Temporal variations of: (a) Susquehanna River discharge at
Conowingo Dam; (b) corresponding Fe; and (c) Mn
concentrations, dissolved, suspended, and total. Data based
on instantaneous measurements and samples at peak inflows . . . 287
3 Plot of: (a) dissolved Mo content versus salinity, and (b)
dissolved Cr content versus salinity for samples from surface
water along the Chesapeake Bay length, June-July 1979 291
4(a) Ratio of dissolved Cu concentration in surface water to
dissolved Cu concentration in bottom water versus salinity. . . 293
4(b) Ratio of dissolved Mo concentration in surface water to
dissolved Mo concentration in bottom water versus salinity. . . 293
5(a) Plot of the ratio of dissolved Cu concentrations in surface
water to bottom water versus the ratio of surface salinity
to bottom salinity 295
5(b) Plot of the ratio of dissolved Mo concentration in surface
water to bottom water versus the ratio of surface salinity
to bottom salinity 295
6 Longitudinal-depth distributions of mean metal concentration
per gram of suspended material, along the axis of Chesapeake
Bay, for (a) Cd, (b) Cu, and (c) Pb. Relatively high zones,
shaded 297
7 Distribution of metal content in surface suspended material
with distance along the Bay axis. Median values and range of
concentrations from all available observations. Shaded zone
indicates magnitude of departure between median values and mean
values for Fe-corrected average shale, open circles 298
8 Distribution of metal content in near-bottom suspended
material with distance along the Bay axis. Median values and
range of concentrations from all available observations.
Shaded zone indicates magnitude of departure between median
values and mean values for Fe-corrected average shale, open
circles 299
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Number Page
9 Distribution of Cu content in bottom sediments of (a) bulk
bed sediment, unfractionated, and (b) the less than 63 u size
fraction, fractionated 304
10 Distribution of Zn content in bottom sediments of (a) bulk
sediment, and (b) the less than 63 u size fraction 305
11 Vertical profiles of Si02, PO^, HC03, Mn, Fe, and NH4 in
interstitial water composition for a station in central
Chesapeake Bay, September-November 1978 307
12 Distribution of Chemical Sedimentary Environments in Chesapeake
Bay, based on data of Hill and Conkwright (1981) 308
13 Typical gas chromatogram of a sediment sample 312
14 Chart of station locations and bar graph representing
concentration sums of all resolvable peaks for organic
compounds in sediments, spring samples 1979 313
15 Chart of station locations and bar graph representing
concentration sums of all resolvable peaks for organic
compounds after normalizing for silt and clay content,
spring samples 1979 314
16 Chart of station locations and bar graphs representing
concentrations sums of all resolvable peaks for organic
compounds in oysters, spring samples 1979 315
17 Distribution of PNA, benzo(a)pyrene, in channel sediments
from Baltimore Harbor and the Patapsco River. Relative
concentration relates to height of column at each location. . . 313
18 Longitudinal distribution of enrichment factors for Cu, Mn,
Pb, and Zn in bed sediments along the length of Chesapeake
Bay. Zn enrichment zones shaded 323
19 Metal/aluminum ratios, Zn/Al, Cu/Al, for three cores from
northern and central Chesapeake Bay, cores 4, 18, and 60.
Dates in ^lOpj-, years; departure of metal/aluminum and
metal/iron ratios from background in each core, shaded 325
20 Relationship of percent water content to percent mud content
for surface sediment samples from the southern Bay 330
21 Sedimentation zones in areas of fine sediment, greater than
40 percent clay with greater than 1.0 m of shoaling per 100
years, in the Bay proper 332
22 Distribution of percent bioturbation in sediments, Fall 1978. . 335
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TABLES
Number
1 Point source loadings of metals from industries and publicly
owned treatment works (POTWs), in counties below the fall line
for Cr, Cd, Pb, C, Zn, Fe, in metric tons per year 278
2 Atmospheric input of selected metals to Chesapeake Bay .... 280
3 Total Excess Metals 283
4 Urban runoff loadings from major metropolitan areas of the
Chesapeake Bay region 284
5(a) Average annual loadings for selected dissolved metals at
monitoring stations on the Susquehanna, Potomac, and James
Rivers 285
5(b) Annual and long-term mean annual flows for the Susquehanna,
Potomac, and James Rivers 286
5(c) Comparison of CBP loadings from the Susquehanna River with
those from Carpenter et al. (1975) 288
5(d) Metal loading rate factors for the Susquehanna, Potomac, and
James River drainage basins 289
6 Data for capacity/inflow ratios and percentage of suspended
sediment trapped 290
7 Source inventory of metal influx to Chesapeake Bay, metric
tons per year 292
8 Summary of mean and median dissolved metal concentrations
and range of Bay-wide values, ug per ml. Data from Kingston
(1982); cruise of June-July 1979 296
9(a) Summary of mean metal concentrations and range of Bay-wide
values per gram of suspended material, left and weight per
volume of suspended material, right. Data from Nichols
(1981) for eight cruises along the Bay length between months of
March and September 1979 and 1980 300
9(b) Mean, median, and range of metal content for one cruise along
the Bay length, June-July 1979. Data from Kingston (1982). . 300
10 Flux estimates of selected dissolved constituents from
Chesapeake Bay bed sediments mm/cm^/yr 309
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Number Page
11 Relationship of bulk chemical analyses of metals (Helz et
al. 1981) versus sediment parameters (Byrne et al. 1981)
by stepwise regression . „ . . . 327
12 Summary of histological abnormalities found in Macoma
balthica clams from upper and lower Bay tributaries. Data
represent number of clams with abnormalities; parentheses
indicates the percent of total from the River 340
13 Toxicity tests performed on industrial effluent . . 341
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aerosol:
anoxic:
anthropogenic:
As
bioecology:
Cd
Ce
Co
Cr
Cu
diagenesis:
dpm cm" 2
Eh
fall line:
Fe
ft3/8ec
Hg
interstitial:
lithology:
loads :
Mn
Mo
Technical Glossary
A colloidal solution in which a substance in which the
other is dispersed, is a gas.
Total deprivation of oxygen.
Of human origin and development.
arsenic
The science that deals with the interrelations of
communities of animals and plants with their environment.
cadmium
cesium
cobalt
chromium
copper
Physical and chemical changes occurring to sediments
during and after the period of decomposition up until
the time of consolidation.
distintegrations per minute per square centimeter
oxidation-reduction potential
Geographical line indicating the beginning of a plateau,
usually marked by many waterfalls and rapids.
iron
cubic feet per second
mercury
Of, forming, or occurring in small or narrow spaces
between things or parts.
Science of rock structures.
Quantity of a constituent per unit per time.
manganese
molybdenum
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ml
Ni
oxic:
Pb
ppt
ps=
Sc
Sn
synergism:
Th
U
ug ciri~2
Zn
metric tons
nickel
applied to a soil layer from which much of the silica
that was combined with iron and alumina has been leached,
lead
parts per thousand
expression of sulfur ion content
scandium
tin
The property or condition of working together, such as
muscles together effecting a certain motion, or of
hormones, or medical substances.
thorium
uranium
micrograms per centimeter
zinc
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SECTION 1
INTRODUCTION
This part of the CBP Synthesis Report summarizes and integrates the
research findings and recommendations of 13 projects of the Chesapeake Bay
Toxic Substances Program performed between July 1978 and October 1981. The
following sections describe research on potentially toxic substances, or
toxicants, in water-sediments and selected biota. The subjects considered
include a brief review of metals, their sources, distribution and behavior,
and then a review of sources and distribution of organic chemicals.
Finally, information concerning the significance of toxicants in the Bay
and their pattern of enrichment is provided. Most information synthesized
in this report can be traced to its origin in scientific project reports
listed in Appendix A.
The last three decades have witnessed some disturbing changes in
Chesapeake Bay. Some biotic components are less abundant than in the past
and are below natural levels. Oyster reproduction has diminished
throughout the Bay. Of particular concern is the virtual disappearance of
rooted aquatic plants over a large portion of the Bay floor. Fish, such as
shad and striped bass, once spawned in astronomical numbers; but in recent
years, they have declined severely (Cronin 1977). Taken together, these
changes are cause for concern.
An understanding of what is happening, and why, to grass, bass, shad,
and oysters still eludes scientists, though toxic substances are strongly
suspected to be at least partially responsible. The lessons learned from
DDT and PCB contamination show that toxicants can cause substantial
ecological damage, ranging from reproductive failure in fish and birds to
inhibition of photosynthesis in phytoplankton. The outbreak of
neurological illness with 52 deaths caused by mercury (Hg) poisoning of
shellfish in Japan amplifies the fact that toxic contamination in seafood
resources can reach humans. Release of Kepone into the James River in
Virginia, resulted in closure of the estuary to fishing for years, with an
enormous economic loss and a need for a large-scale, expensive cleanup.
Chlorine, a widely used biocide in sewage treatment plants, is strongly
suspected of causing massive fish kills in the James River in 1973 (Douglas
1979).
Toxic substances are usually defined as chemicals or chemical
compounds that can poison living plants and animals, including humans, or
impair physical or chemical processes. Two classes of toxic substances
pose a threat to the Bay environment: inorganic and organic compounds.
The inorganic materials are the metals. They can be produced and delivered
to the Bay by natural processes as well as by human activities.
Potentially toxic metals include arsenic (As), cadmium (Cd), chromium (Cr),
copper (Cu), mercury (Hg), tin (Sn), and zinc (Zn). Many of the organic
compounds are products of human activities. However, a few polynuclear
aromatic compounds (PNAs) can occur naturally, and thus augment the
synthetic compounds. The main classes of organic compounds are pesticides,
phthalate esters, polynuclear aromatic hydrocarbons, metalorganic
compounds, alkyl-benzines, plasticisers, polychlorinated biphenyls (PCBs),
and other halogenated hydrocarbon compounds.
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Assessing the effects of toxic substances on biota has always been a
difficult task. Effects range from rapid death, or acute toxicity, to
gradual reductions in spawning success, or chronic toxicity. Months, or
years of careful observations may be required to determine chronic effects
for one chemical on one species. Effects of chemical mixtures on several
species or a community are even more difficult to detect. The environment
may also experience synergistic and antagonistic effects through exposure
to two or more chemicals. In addition, toxic effects can be masked by wide
fluctuations in natural conditions. In the laboratory, scientists have
attempted to simulate effects of chemicals on the natural environment by
subjecting single organisms, or a limited number of organisms, to
toxicants, and observing the cause-and-effeet relationships. But transfer
of this information to interpret changes in entire faunal communities, with
their wide variability within species, has achieved only limited success.
Because it is difficult to specify cause-and-effect relationships
between toxicants and Bay resources, we attempted, during the Chesapeake
Bay Program, to determine areas where levels of toxicants are high (above
standards or threshold levels), and then relate these levels to known toxic
effects. This evaluation will give us some insight into the existence of
toxicity problems.
In summary, some trends recognized at the onset of the Program caused
us to believe that the status of toxic substances in the Bay should be
studied. These trends included: (1) decline of biotic components in the
past three decades (Cronin et al. 1977); (2) increases in the number of
potentially toxic chemicals being synthesized, produced, and used in the
region (Huggett et al. 1977); (3) discharge of large amounts of potentially
toxic substances (Brush 1974); (4) increase in population growth and
industrial activity; (5) accumulation of toxicants in the sediments and
biota, including commercial food species, many thousand-fold more than in
ambient concentrations in the water (Huggett et al. 1974b, Huggett et al.
1977); and (6) carcinogenic nature of many organic compounds found in the
Bay. At the same time the Bay is an important environmental resource for
fisheries, wildlife, and recreation. Since controlling the threat of toxic
substances to viable ecological resources requires new knowledge of their
sources, distribution, and fate in the Bay ecosystem, we studied these
factors.
Before the initiation of the CBP, information en metals and organic
compounds was scarce. Data on the existence of metals were limited to the
distribution and abundance of some trace metals in the northern Bay and
several western tributaries. Likewise, available information on organic
compounds consisted of levels of some chlorinated hydrocarbons (DDT, PCBs)
and Kepone found in selected bivalves, fish, phytoplankton, and sediments
of some parts of the Bay and tributaries. The CBP studies not only support
and systematically expand this knowledge, but add information on sources of
metals and organic compounds to the Bay, their behavior in the estuary, and
impacts on resources.
Published information on potentially toxic metals in the Bay prior to
the Chesapeake Bay Program, and from other studies, is summarized in
Appendix B. Of note are studies of the Cu and Zn in oysters and sediments
of the James and Rappahannock Rivers (Huggett et al. 1974a) that indicate
differences in concentration gradients of the metals between sediments and
oysters. Additionally, Carpenter et al. (1975) revealed marked temporal
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variations of the dissolved and suspended metals, Fe, Mn, and Zn,
discharged over an annual cycle by the Susquehanna River. Our studies
support these findings as discussed in Section 2. Villa and Johnson (1974)
and Johnson and Villa (1976) reported high concentrations of metals in
Baltimore Harbor and the Elizabeth River. By using a mass balance of
metals for Northern Chesapeake Bay, Helz (1976) found that at least half of
the Cd, Cr, Cu, and Pb input comes from human sources. Further assessment
of contributions from human sources is presented in Section 2. Goldberg et
al. (1978a), in a study of northern and central Chesapeake Bay, revealed
anthropogenic fluxes of metal concentrations in upper parts of sediment
cores. Since this study showed that sediment puts material into the
system, we assessed sediments as a source. (See Section 2 for discussion
of our results). The status of knowledge on biological effects of metals
is presented by Frazier 1972, Cronin et al. 1974, Hansen et al. 1974, and
Tsai et al. 1979. These studies indicate a biological toxicity problem
that was cursorily studied by the CBP (see Section 6).
Prior information on synthetic organic compounds in the Bay is scant.
Many synthetic compounds have been only newly created, with the necessary
analytical instruments to detect them only recently developed. Of note
(Appendix C) is the EPA National Estuarine Monitoring Program between 1965
and 1972, utilizing oysters (Munson and Huggett 1972). Additionally,
Munson (1973) found that Chester River bed sediments, suspended sediment,
and shellfish stocks contained chlorinated hydrocarbons derived from
Chesapeake Bay. The Upper Bay Survey (Munson 1975) provided data on
chlorinated hydrocarbon (PCBs, Chlordane, and DDT) sources and
concentrations in suspended material and bed sediments as well as in
shellfish and zooplankton. This study gave insights into routes and rates
of transfer. Section 2 of this paper expands on this information. A
consolidated listing of toxicants found in Chesapeake biota, water, and
sediment, and a listing of toxicant data files is provided by CRC (1978).
The intensive studies of Kepone in the James Estuary after 1975 provide
detailed data for a single toxicant in a single tributary estuary. They
cover studies of biota (Roberts and Bendl 1980, Huggett et al. 1980,
Huggett and Bender 1980) and sediments (Trotman and Nichols 1978, Lunsford
1981, Nichols et al. 1979).
Brush's (1974) inventory of sewage treatment plants lists information
on sources of toxicants. Additionally, the EPA-States National Pollutant
Discharge Elimination System (NPDES), which began in 1973, contains
extensive file data on metals and a few organic compounds discharged from
point sources such as industrial effluents and sewage treatment plants.
In 1978 the CBP initiated research on toxic substances, aiming to
provide new information and the data base necessary to manage toxic inputs
to the Bay. It is the first comprehensive effort to address problems of
potentially toxic substances in the Bay on a regional scale. Specifically,
we attempted to:
o determine the present distribution and concentration of selected
toxic substances in Bay sediments, water, and biota;
o assess the present input rates of potentially toxic substances to
the Bay, their location, and composition;
o identify the major transport paths for toxic substances, their
chemical behavior, and sites of accumulation; and
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o determine the impacts of potentially toxic substances on the Bay
ecosystem.
The chisf studies were of four main types:
(1) Baseline Inventory
An assessment of the spatial distribution of sediments, biota,
water characteristics, and toxic substances, (what toxic
substances are present? where are they located?) and in what form
or state (organic, inorganic, dissolved, particulate?) (Are they a
problem?)
(2) Source Assessment
An identification of sources and estimation of the potential toxic
inputs discharged by industry, sewage treatment plants, and the
atmosphere.
(3) Behavior and Fate
An assessment of the mechanisms and routes of transport, sites of
accumulation, chemical behavior, and likely biological impacts.
(4) Synthesis
A summary of research findings and integration of toxic substances
with system components.
The program elements are interrelated scientifically by treating the
Bay as a geochemical system with reservoirs. Sources, sinks, and pathways
of material transports (such as air, water, and sediments) are the
principal reservoirs inventoried; dissolved materials and biota are the
main interacting components. As toxic substances are transferred between
reservoirs and components, and from sources to sinks, they proceed along
characteristic pathways, undergo transformation, and accumulate in viable
and sedimentary constituents.
Research plans focused on toxic substances in the sediment reservoir,
because toxicants have a great affinity for fine-grained sediment (which
has a large surface area for sorption per unit mass) . Levels in the water
column may, in some cases, be important, but our work concentrated on
sediment reservoirs because toxicants have a long residence time in
sediments, build up to high concentrations, and are easily detected.
Although toxic substances discharged in dissolved form can have a direct
impact, their effect is believed to be short-lived because of rapid water
movement and constant dilution. Consequently, sediments have a longer
residence time in the Bay than dissolved substances. Thus, they can build
up high concentrations of toxicants.
Growth of the region has increased the supply of sediment delivered to
the Bay and, when combined with toxic substances, poses a significant
problem to the Bay environment. Clearing land for agriculture and
development has accelerated watershed erosion (Wolman 1967) and increased
loads of suspended sediment (Schubel and Meade 1974). Suspended sediment
creates turbidity which can decrease light penetration and adversely affect
aquatic plants and primary production. As sediment fills channels and
harbors, it creates a need for dredging and for disposal of contaminated
sediment.
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As in the previous part on nutrient enrichment, this section was
written around several questions relevant to those interested in managing
water quality of the Bay. The three basic questions addressed in this
paper are:
Is there a toxic chemical problem in the Bay?
What is the distribution of toxic chemicals in the Bay?
What are the sources and loadings of pollutants of concern?
A more detailed list of these questions, with their answers, appears as the
final section of this paper. The answers are drawn from the paper and
serve as a summary of the technical material from a manager's perspective.
They should concisely support Section 6, Conclusions and Research Needs.
276
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SECTION 2
FINDINGS FROM STUDIES ON METALS
This chapter explains the results from CBP research on sources of
metals to the Bay and their distribution and concentration in the estuary.
The first part on sources discusses inputs of metals from industries and
publicly owned treatment works (POTWs), the atmosphere, urban runoff, and
three principal tributaries of Chesapeake Bay. The remaining sections
summarize results from CBP studies on the concentration of metals in the
Bay. Once in the estuary, the behavior of metals depends on how they
respond to the Bay's chemical, biological, and physical processes. Some
metals, for example, will become dissolved in the estuarine water. Others
will associate with suspended matter, while certain amounts and types will
be found in bottom sediments and interstitial water. This section deals
with metals partitioned in all of their phases.
SOURCES
The CBP initiated studies to assess the input of metals from several
major sources to the Bay. These sources are: industries and POTWs,
atmospheric deposition, urban runoff, and three of the Bay's principal
tributaries. Approximate loadings were computed for these sources to
provide an estimate of the relative contributions each source makes.
Industries and POTWs Below the Fall Line
Rates of metal input from point sources in the Bay drainage basin were
estimated for industries and POTWs below the fall line from data obtained
between 1974 and 1980. Information from the National Enforcement
Investigations Center (NEIC) of the U.S. Environmental Protection Agency
(EPA) was used to place in priority the toxic dischargers from the
approximately 5000 point source dischargers in the entire Chesapeake Bay
basin. It was determined that there are 1000 major toxic dischargers, of
which 122 are located below the fall line. For these 122 industries,
loading estimates were computed for selected metals we found in relatively
high concentrations in Bay sediments.
Concentration of metals in various industrial effluents was obtained
from EPA effluent sampling data from Resources for the Future in the
"Pollution Matrix Lookup Routine." Concentration values were assigned
based on the industry's Standard Industrial Classification (SIC) code. The
discharge rates for each industry were obtained from data collected for an
EPA project referred to as the "Industrial Facilities Discharger File"
(IFD). Loadings of metals in metric tons per year were computed by
multiplying the effluent discharge rate (in millions of gallons per day
[MGD]) by the concentration of the various metals milligrams per liter
(mg/L), applying the appropriate conversion factors. However, when
assigning effluent concentration values, the industries discharging cooling
water were assigned concentrations representative of cooling water, not
waste water. Those industries discharging cooling water and process
277
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278
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waste water were assigned concentration values approximately 85 percent
less than those industries in the same SIC code but discharging all process
wa s t e wa t e r.
Loadings from POTWs were computed by multiplying discharge flow rates
(MGD), obtained from the EPA 1980 Needs Survey, by concentration values
obtained from results of pilot-scale studies conducted by the EPA Municipal
Environmental Research Laboratory (MERL) (Petrasek 1980). Discharge flow
rates are compiled in the Needs Survey for use in Congressional allotment
of construction grant funds to upgrade or expand existing POTWs.
Computation of loadings showed that discharge of metals is greatest in
areas of high industrial activity and large population centers. With the
exception of Fe, all of the metals listed in Table 1 have established
criteria levels. These levels vary for each metal and for chronic versus
acute toxicity. In localized areas, such as Baltimore Harbor and Elizabeth
River, the quantities of metals discharged create situations with a strong
potential for high aquatic toxicity. For example, in Baltimore Harbor,
metals are discharged in moderate amounts; but because of low flushing
rates (10 percent renewal rate) (Sinex and Helz, unpublished), these metals
concentrate in Harbor waters. Although we have no data to demonstrate the
severity of the problem in the water column, Sinex and Helz (unpublished)
have shown from bottom sediment samples that the bulk of metals discharged
in the Baltimore Harbor does, in fact, remain in the Harbor.
The distribution of metal loadings for POTWs and industries (Table 1)
shows that discharges of Cd, Cr, Cu, Fe, and Zn from POTWs and industries
in Baltimore County and Baltimore City far exceed those from other
counties. Lead from POTWs in Baltimore City is higher than in other
counties. Substantial inputs from POTWs are also noted for Cr, Fe, and Zn
in Richmond City, Norfolk City, and Hopewell City. Lead is notably large
in industrial discharge from Louisa County. Taken as a whole, industrial
loadings are more than twice as large as treatment plant loadings.
Atmospheric Sources
Pollutants from the atmosphere can deposit directly as dryfall (dust)
and as dissolved constitutents in precipitation (rain, snow, hail).
Because we lacked data on the dryfall component of atmospheric deposition,
no estimate of dryfall loading to the Bay is made in this section.
However, Lazrus et al. (1970) and Davis and Galloway (1981) have done some
work on dryfall atmospheric deposition of metals. Lazrus et al. (1970)
showed that the deposition of metals from the atmosphere varies by a factor
of three or less between North Carolina and Northern Virginia. Thus, the
atmospheric deposition over the Bay is probably fairly uniform. Based on a
residence time of 4.7 days for small aerosols (particles <^ 1 u) and a
predominantly easterly air flow, Davis and Galloway (1981) revealed that
atmospheric contaminants may reach the Bay from industrialized areas of the
midwest. Deposits in industrialized areas, such as Baltimore, consist of
heavy particulates that settle out rapidly, as well as small aerosols that
rain out in the vicinity of the city. Thus, the concentration of metals in
dryfall around Baltimore decreases with distance from the city (Baltimore
Regional Planning Council, unpublished data), but such industrial centers
constitute only a small percentage of the Bay's area.
CBP funded projects investigated atmospheric inputs to the Bay from
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precipitation. Two sources were used to evaluate atmospheric loads —
storm data from the Maryland Geological Survey and marsh cores. Data from
the Maryland Geological Survey's sampling of six storm events from April to
September 1981 were used to compute atmospheric loadings listed in Table
2. Because the areal variability of the deposition rate from each storm
could not be determined at this time, we developed loading estimates that
assume uniform concentrations over the entire Bay. Omitted from these
estimates are dryfall loading rates and deposition that occur on the land
surface in the drainage basins, eventually reaching the Bay or tributaries
from surface runoff. Because of these limitations, the values presented in
Table 2 are conservative estimates of total atmospheric deposition.
TABLE 2. ATMOSPHERIC INPUT OF SELECTED METALS FROM WETFALL TO CHESAPEAKE
BAY AND TRIBUTARIES
Metals
Volume1-
Weighted
Concentration
(ug/g)
Main Bay2
(metric tons/
year)
Main Bay and
Tributaries^
(metric tons/
year)
Cd
Cu
Fe
Mn
Ni
Pb
Zn
0.23
2.20
6.85
1.77
1.95
2.66
65.20
2
16
50
13
14
19
467
3
28
87
22
25
34
825
1
2
3
Based on sampling from six storm events. Data from
Maryland
Surface
Surface
Geological
area of Main
area of Bay
Survey (Conkwright et al. 1982).
Bay = 6,500 km2.
& Tributaries = 11,500 km2-
Loadings computed using average annual precipitation of
1.1 meters.
Results from these studies show that quantities of metals entering Bay
waters from atmospheric deposition are significant. The concentrations of
metals in the atmosphere are proportional to the total mass of the metals
released into the atmosphere from fossil fuel combustion, manufacturing
processes, and many other anthropogenic and natural processes. The input of
Zn, as shown in Table 2, is high because of its high emissions from fossil
fuel combustion and other manufacturing processes like plating and cement
production (Forstner and Wittman 1979). The total load of Zn from the
atmosphere is at least double the amount from point source (Table 1). This
suggests that some of the remote areas of the Bay, where anthropogenic
contamination is assumed to be negligible are, in fact, areas receiving heavy
inputs of metals, especially Zn. Other areas receiving high amounts of
280
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metals must also absorb elevated levels from the atmosphere, thereby worsening
the problem.
Marsh deposits can record the atmospheric flux of trace metals deposited
over time, thus providing another estimate of atmospheric input. The surface
of the high marsh, Spartina patens, which is exposed to the atmosphere 95
percent of the time, retains most all atmospheric inputs. Although marsh
cores from the Bay are scarce, McCaffrey and Thomson (1980) can estimate the
atmospheric flux to the Bay from another core from Farm River Marsh, in Long
Island Sound, Connecticut. In the Farm River Marsh core, all of the metals
are assumed to have been deposited from the atmosphere. The concentration of
these metals (Cu, Pb, and Zn) from the marsh samples was divided by the
concentration of 210pb present in the sample. All of the ^lOp^ £n t^e
marsh samples is assumed to have been deposited from the atmosphere (Helz et
al. 1981). The metal to 210pb ratio from the marsh core is then assumed to
be similar for the Helz cores, because the deposition rate between Long Island
and the Bay is probably nearly the same. Therefore, by knowing ^lOp^
concentrations in the Chesapeake cores, and applying the ratio from the marsh
core, an estimate of the atmospheric contribution of these metals can be made.
In the northern Bay, core 4 (Table 3) shows that approximately 10 percent
of the Cu (Cu/210Pb Cu) and five percent of Zn (Zn/210Pb Zn) is supplied
from the atmosphere. However, in other cores from the central Bay (not shown)
about 25 percent of the Cu and 13 percent of the Zn is of atmospheric origin.
Consequently, the atmosphere becomes an important source in zones distant from
sources of water pollution. When atmospheric and water pollution occur
concurrently, the trend of "excess" metal over the background for the marsh,
representing the atmospheric flux, is similar to those of Bay sediments as
shown in Figure 1. Thus, atmospheric sources contribute to the increase of
excess metals with time.
The trend, observed in Figure 1 for Zn in core 4 and in the Farm River
marsh core, shows that Zn appears to be decreasing from a maximum value
occurring around 1930 to 1940. The recent decrease could be due to an
alteration in manufacturing processes or shifts in fossil fuel consumption
(burning more oil instead of coal), thereby releasing less Zn to the
atmosphere.
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COPPER
ZINC
0 50 100 150 200
1980-k-n ' ' ' '
0 50 100 150 200
1940-
1900-
1980-
1940-
1900-
1860-
1820-
1860-
1820-
o Chesapeake Bay
Core 4
* Farm River Marsh,
Conn.
Figure 1. Graph of age versus metal content of Cu and Zn showing
historical increase of "excess" metal concentration in
Chesapeake Bay core 4 (Helz et al. 1981), by comparison
to Farm River Marsh concentrations (McCaffrey and
Thomson 1980).
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TABLE 3. TOTAL EXCESS METALS IN CHESAPEAKE BAY CORES CONTRASTED WITH FARM
RIVER MARSH
210Pb Standing Cu Zn Cu/210Pb Zn/210pb
Core Crop (dpm cm-2)2 (ug cm-2) (ug cm-2)
4
18
60
7
10.5
10.0
793
630
644
3000
1500
1500
113
60
64
428
142
150
Farm River Marshl 13 19
1From Benniger (1978).
cm~2 - decays per minute per square centimeter.
Urban Runoff
As previously discussed, the deposition of airborne pollutants to the Bay's
surface may be an important transport mechanism. Another pathway by which
atmospheric pollutants enter the Bay is urban runoff. Some rainwater (and
dust) deposited in urban areas eventually reaches the Bay. This transport is
facilitated by the high percentage of paved surface area in urban regions.
Flowing over the roads and other impervious and pervious surfaces, runoff
accumulates certain metals in dissolved and particulate phases, notably Pb
from the combustion of leaded gasoline, Zn from the abrasion of tires, and Cu
and Cr from automobile brake shoes.
Although urban runoff is usually considered a nonpoint source, on a
Bay-wide scale, loadings from the three major cities in the Bay area are of
sufficient magnitude to represent major localized point sources. Table 4
shows annual loadings of metals from Baltimore, Hampton Roads, and Washington,
DC runoff. Loadings were computed from data supplied by Hartigan (October 21,
1981, memorandum). Concentrations of metals in runoff were derived by
averaging results from runoff data collected during the Metropolitan
Washington NURP study and an early 208 monitoring s*tudy in the Occoquan River
and Four Mile Run basins of Northern Virginia. Surface runoff volumes were
obtained by assuming that soils are sandy loam and by computing values for the
various land use categories based on 1967 hourly rainfall record (rain gage at
Washington National Airport) .
The loading values listed in Table 4 show that urban runoff is a
significant source of metals. Metals exhibiting the highest loadings are Fe,
Pb , and Zn. Iron is not considered a toxic metal; loading values are included
only for comparison. The high Pb and Zn values reflect local sources of these
metals such as automobile exhaust, incinerators, refuse, and other urban
activities that generate dust, gases, and other noxious by-products. Since
rain is the major component of runoff, the concentrations of metals in rain
and other forms of precipitation will also cause high metal loadings in urban
runoff.
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TABLE 4 URBAN RUNOFF LOADINGS FROM THREE MAJOR METROPOLITAN AREAS OF
CHESAPEAKE BAY (AREA VALUES IN METRIC TONS/YEAR)
Metro Area
Baltimore
Norfolk/
Newport News/
Hampton
Washington,
DC
Total
Cd
5
1
_!_
7
Cr
3
4
_4
11
Cu
3
2
_4_
9
Fe
291
213
473
977
Mn
5
3
_7
15
Ni
6
4
IP.
20
Pb
35
26
50
111
Zn
19
15
29.
63
River Sources
An estimate of annual loadings of selected metals at the fall line of
three rivers, the Susquehanna, Potomac, and James, was derived from samples
collected approximately bi-weekly to monthly by the U.S. Geological Survey
between October 1978 and April 1981 (Lang and Grason, unpublished).
Loading values were computed, using one of the methods described below.
Prediction Model—
Various mathematical models were used to fit a relationship between
concentration (C) and flow (Q) or loading rate (LR) and flow. The various
models used were as follows: C versus Q, ln(C) versus Q, C versus ln(Q),
ln(C) versus ln(Q), C/Q versus 1/Q, ln(C/Q) versus 1/Q, C/Q versus ln(l/Q),
ln(C/Q) versus 1/Q, LR versus Q, ln(LR) versus Q, LR versus ln(Q), and
ln(LR) versus ln(Q). A concentration and/or loading rate was then computed
for each day, using the best model and observed daily flow rates. These
daily loadings were then summed for the total annual loading.
Sum of Averages—
To obtain loadings using this method, a flow weighted, mean daily
concentration was first calculated as follows:
cmean = t(Cinst)(Qinat)]
^inst
This value was then multiplied by mean daily flow to obtain a daily
loading. Daily loadings for each month were then averaged to give an
averge daily loading for that month. These averages were then multiplied
by the number of days in the month to give a monthly loading.
The monthly loadings were averaged to give an average monthly loading.
Where no samples were taken in a month, the monthly average was used for
these months, and the monthly loadings were summed to give a yearly loading.
Mean or Median Value from Sampling Data Applied to Long-Term Mean Annual
Flow—
This method involved using the mean or median value of the various
parameters as reported by the USGS (Lang and Grason 1980) and the long-term
mean annual flow to compute the loadings.
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The loadings and the computation method used for each metal are listed
in Table 5(a). The discharge flows for these years and the long-term mean
annual flows are listed in Table 5(b) . The flow rates for 1979 were
significantly above normal for all three rivers and, for 1980, were
somewhat less than normal except for the James which was approximately ten
percent higher than the long-term mean annual flow. Therefore, the
computed average loading for these years is probably slightly higher than
normal.
TABLE 5(a).
ESTIMATED AVERAGE ANNUAL LOADINGS FOR VARIOUS METALS FROM THE
MAJOR TRIBUTARIES OF CHESAPEAKE BAY FOR 1979-1980 PERIOD*
(VALUES IN METRIC TONS/YEAR) (FROM LANG AND GRASON 1980)
Parameter
Susquehanna
Conowingo Dam
Potomac
@ Chain Bridge
James
@ Cartersville, VA
Totals
Al-D
Al-S
Al-T
As-T
Cd-T
Co-T
Cr-T
Cu-T
Fe-D
Fe-S
Hg-T
Mg-D
Mn-D
Mn-S
Mn-T
Ni-T
Pb-T
Zn-T
6,509
156,061
161,618
82
65
59
383
390
1,844
192,422
23
232
7,552
7,326
14,469
229
174
837
(2)
(2)
(2)
(2)
(3)
(2)
(3)
(2)
(1)
(2)
(2)
(2)
(2)
(2)
(2)
(1)
(3)
(1)
1,724
36,061
37,626
13
4
39
105
86
839
76,227
-
61
86
1,929
1,933
109
102
322
(2)
(2)
(2)
(2)
(2)
(1)
(1)
(1)
(2)
(2)
(1)
(3)
(3)
(3)
(1)
(3)
(1)
2,631
30,890
33,884
20
6
48
63
41
567
27,783
6
31
104
2,277
2,327
64
31
285
(2)
(2)
(2)
(1)
(3)
(2)
(3)
(1)
(1)
(1)
(2)
(2)
(2)
(2)
(2)
(1)
(3)
(1)
10,864
223,012
233,128
115
75
146
551
517
3,250
296,432
29
324
7,742
11,532
19,229
402
307
1,444
*Values listed represent the mean of 1979 and 1980 calender year loadings.
(l) Computed using a model
(2) Computed using sum of averages method
(3) Computed using the reported mean or median value applied against the
long term mean annual flow
D - Dissolved
S - Suspended
T - Total
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TABLE 5(b): ANNUAL AND LONG-TERM MEAN ANNUAL FLOWS FOR THE SUSQUEHANNA,
POTOMAC, AND JAMES RIVERSl
Susquehanna
Potomac
James
1979
Calendar Year
(ft3 sec-1)
52,200 (+34%)2
20,400 (+79%)
12,000 (+70%)
1980
Calendar Year
(ft3 sec-1)
28,400 (-27%)
11,000 (- 3%)
7,790 (+10%)
Long Term
Average
(ft3 sec-1)
38,900
11,400
7,050
iData from U.S. Geological Survey, unpublished
2Values in parenthesis represent the percent difference from the long-term
mean annual flow.
Table 5(a) lists loading values for 13 metals of which several — Al,
Fe , Mg, Mn — are not considered toxic. Some of these metals, such as Al
and Fe, are contributed primarily from natural erosion processes and cannot
indicate pollution. All of the metals in this list occur in crustal
material and, therefore, are naturally found in rivers. This makes it
difficult to determine the natural from the anthropogenic contributions, a
subject more fully discussed in Section 4. It is important to mention,
however, that even though some metals are contained in naturally-occurring
soil and crustal material, the rate of this sediment entering the river may
be dramatically enhanced by farming and other rural and urban activities.
Of importance to note in Table 5(a) are the high loadings for Cr, Cu,
and Zn. These values reflect contributions from point and nonpoint
sources, erosion, and other sources. Zinc values are particularly high and
may be the direct result of the observed high concentrations of Zn in the
precipiation that falls on these drainage basins. Of the three rivers, the
Susquehanna produces the highest loadings, primarily because of the higher
flows in this river.
Concentrations of total metal content in the rivers vary with total
suspended material and with river flow. As shown in Figure 2, the
concentration of suspended Fe at high inflow is more than 20 times the
concentration at low inflow, and Mn is more than 15 times the concentration
at low inflow. Some metals, like Mn, also exhibit seasonal changes in
partitioning between dissolved particulate concentrations (Figure 2).
Particulate Mn is more dominant than dissolved Mn in spring, summer, and
fall—a trend associated with influx of decaying organic matter in winter
(Carpenter 1975). Such changes in partitioning and the varying metal
concentrations with sediment loads make determination of loading estimates
difficult.
A comparison of the 1980 loadings on the Susquehanna River with values
computed by Carpenter in 1965-1966 is presented in Table 5(c) . These data
show that loading values for Cd, Cu, Fe, and Zn are very similar.
Manganese shows a slight increase, but Co and Ni show moderate to high
decreases. The most notable change is the Cr loading that was
286
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o
o>
CP
en
10-
8-
6-
4-
2-
(a) RIVER DISCHARGE
128 SUSQUEHANNA
TIME
SERIES
LONGITUDINAL SECTIONS
I 1 I I 1 I I I I I I \11 t 1
. 13,400
6-
2-
0
800-
600-
400:
200 :
(b) IRON,
SUSPENDED
4600
SUSP'D.
4700
TOTAL
(c) MANGANESE
JTOTAL DISSOLVED
SUSPENDED
U F M A M J JASOND'J F M A Mi
! 1979 ! 1980 !
Figure 2. Temporal variations of: (a) Susquehanna River discharge at
Conowingo Dam, and corresponding (b) Fe, and (c) Mn
concentrations, dissolved, suspended, and total. Data from
Lang and Grason (1980) bised m instantaneous measurements
and samples at peak inflows.
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approximately 300 percent higher in the 1980 estimates than in the
1965-1966 estimates.
Comparison of the loadings from the three rivers in Table 5(a)
indicates that the Susquehanna contributes a greater proportion of metals
than the Potomac or James. To provide an estimate of the relative yield
(or load per unit area) from these river basins, loading rate factors were
computed by dividing the loadings listed in Table 4 by the area of the
drainage basin above the fall line for each river system. These values are
listed in Table 5(d) . Generally, the Susquehanna appears to be no more
enriched than the Potomac or James. Although certain metals are more
enriched in one river system compared to the other two, the differences are
significant for only several metals and may be largely explained by errors
in sampling or loading computation.
TABLE 5(c). COMPARISON OF COMPUTED LOADINGS FOR THE SUSQUEHANNA RIVER WITH
THOSE OF CARPENTERl (LOADINGS IN METRIC TONS/YEAR)
1980 Annual Loadings Percent Difference
Computed Loadings with Reported by Carpenter2 From Carpenter
Metal Flow = 28,400 ft3 sec"1 Flow = 28,012 ft3 sec"1
Cd
Co
Cr
Cu
Fe
Mn
Ni
Zn
2
20
220
106
36,500
6,100
150
570
2
90
50
100
40,000
5,000
200
600
0
-78
+340
+6
-9
+22
-25
-5
1Carpenter, J. H., W. L. Bradford, and V. Grant (1975).
^Sampled approximately one mile downstream from Conowingo dam every week
for the period of April 1965 through August 1966.
Although rivers are a major source of metals, it is not known what
proportion of these loadings enter the Bay. Monitoring on the Susquehanna
generated loading values for the river just prior to discharge into the
Bay, but the James, Potomac, and many other tributaries discharge into
fresh water, tidal, and brackish-water reaches of substantial length.
Prior studies of eight Bay tributaries indicate that the bulk of
suspended sediment is trapped within the tributaries—for example, in the
Back River (Helz et al. 1975), the Chester (Palmer 1974), the Choptank
(Yarbro 1981), the Patuxent (Keefe et al. 1976), the Rappahannock (Nichols
1977), and the James (Nichols 1972, O'Connor 1981). Entrapment of sediment
is recorded either by direct measurements of suspended sediment transport,
or by historical shoaling rates with an evaluation of these rates in
relation to inputs of suspended sediment from different sources.
288
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TABLE 5(d).
METAL LOADING RATE FACTORS FOR THE SUSQUEHANNA, POTOMAC, AND
JAMES RIVER DRAINAGE BASINS* (VALUES IN METRIC TONS/KM2)
Metal
Susquehanna
Potomac
James
Al-D
Al-S
Al-T
As-T
Cd-T
Co-T
Cr-T
Cu-T
Fe-D
Fe-S
Hg-T
Mg-D
Mn-D
Mn-S
Mn-T
Ni-T
Pfa-T
Zn-T
Basin Area (ktrr)
240
5,759
5,964
3
2
2
14
14
68
7,110
1
9
279
270
534
8
6
31
27,100
149
3,119
5,255
1
1
3
9
7
73
6,594
5
7
167
167
9
9
28
11,560
420
4,937
5,415
3
1
8
10
7
91
4,440
1
5
17
364
372
10
5
46
6,257
Values computed by dividing loadings listed in Table 5(a) by the area of
the drainage basin above the USGS monitoring station.
The ability of these rivers to trap river-borne sediment was determined
by calculating a capacity inflow ratio, using intertidal volume for
capacity, and potential inflow (drainage area times annual precipitation)
for inflow assuming all precipitation is runoff. As indicated in Table 6,
tributary estuaries such as the Rappahannock and Choptank act as very
efficient sediment traps. Therefore, if most of the sediment is trapped in
the estuarine portion of these rivers, then the bulk of river-borne
toxicants that are adsorbed to the sediment are also likely trapped.
Despite the high efficiency of these rivers to trap sediment, some sediment
will escape, especially during storms. At such times, these rivers and
other similar areas should be monitored for exceptionally high levels of
toxicants.
289
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TABLE 6. DATA FOR CAPACITY/INFLOW RATIOS AND PERCENTAGE OF SUSPENDED
SEDIMENT TRAPPED
System
Capacity/Inflow
Sed. Trapped
Source
Rappahannock
Choptank
0.7
2.0
90%
92%
Nichols (1977)
Yarbro (1981)
Susquehanna
- Northern
Chesapeake Bay
0.04
75%
Biggs (1970)
A summary of total metal influx to Chesapeake Bay and its tributaries
from different natural and anthropogenic sources is presented in Table 7.
The estimates are products of two quantities, average metal concentration
and rate of discharge. Accuracy of the data varies with the number of
measurements per unit time, seasonal variations in constituent composition,
and many other factors. This table shows that the sum of industrial and
municipal wastewater loadings (point sources) represents a major
contribution of metals to the Bay. Rivers are the only other source that
exceed the point sources. However, the loadings from rivers actually
represent a combination of the other sources that discharge into these
rivers above the point where loadings were estimated. That is, the
river-loading estimates contain some fraction of anthropogenic and natural
contributions and become a pathway for these sources. From the results
shown in Table 5(d), it appears that the relative proportions of the metal
sources in these river systems are fairly uniform. However, because point
sources do contribute to some part of the river loadings and are also one
of the major sources for the Bay, this suggests that for most metals, point
sources are probably the major source to the Bay, with loadings from urban
runoff and shoreline erosion significant for some metals.
The upper Bay and the upper reaches of the Potomac and James estuaries
are critical areas for fish spawning and other biological activities. From
our studies of metal concentrations in the Bay (discussed in Section 3 and
Section 4), we know that the Northern Bay does exhibit elevated metal
concentrations. Therefore, the Susquehanna River represents a major source
of metals, causing the Northern Bay to have elevated concentrations.
DISTRIBUTION AND CONCENTRATION OF DISSOLVED METALS
Some of the metals, entering the Bay from any one of the sources
previously discussed, will dissolve in the estuarine water. In this form,
metal data are available for Cd, Ce, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sc,
Th, U, and Zn in surface water and bottom water for one sampling cruise
during June-July 1979 (Kingston et al. 1982).
Kingston's data show that a correlation exists between metal
concentration and salinity for Cr, Mo, and U (Figure 3a, Figure 3b).
Uranium and Mo concentrations increase linearly with increasing salinity
and approach average seawater concentrations at the upper end of the
290
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o>
o>
(a) MO
8
r2 - 0.84
048
8r (b)Cr
r2 = 0.76
16 20 24 28 32
%
• •
Vv^i • i* io
02 4 6 8 10 12 14 16 18 20 22 24
SALINITY, ppt.
Figure 3. Plot of (.&) dissolved Mo content versus salinity, and (b)
dissolved Cr content versus salinity for samples from surface
water along the Chesapeake Bay length, June-July, 1979. Data
from Kingston (1982).
291
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TABLE 7. LOADINGS OF METALS FROM THE MAJOR SOURCES AND PATHWAYS TO
CHESAPEAKE BAY (VALUES IN METRIC TONS/YEAR)
Source
Industry
Municipal
Wastewater
Atmospheric
Urban Runoff
Rivers
Shore Erosion
Cd
178
6
3
7
75
1
1
(66)
( 2)
( 1)
( 2)
(28)
( 1)
Cr
200 (19)
200 (19)
10 ( 1)
551 (53)
83 ( 8)
Cu
190
99
28
9
517
29
(22)
(12)
( 3)
( 1)
(59)
( 3)
Fe
2,006
625
87
977
199,682
57,200
(1)
(1)
(1)
(1)
(77)
(22)
Pb
155
68
34
111
307
28
(22)
(10)
( 5)
(16)
(43)
( 4)
Zn
167
284
825
63
1444
96
( 6)
(10)
(29)
( 2)
(50)
( 3)
•^Values in parenthesis represent percent of total loading
salinity range. This trend indicates that marine waters are the source of
these metals, and that the concentration gradient is a result of dilution
of marine water by river runoff. It also indicates that these metals are
not significantly involved in chemical or biological processes in the Bay.
By contrast, Cr concentrations decrease as salinity increases to a value
approximating average seawater concentration at the upper end of the
salinity range. This relationship indicates that river runoff is the major
source of Cr, and that dilution by marine water controls dissolved Cr
concentrations in the estuary. The scatter in the Cr data, however, is
much greater (Figure 3b) than that for Mo, possibly indicating the
influence of other processes in addition to dilution by marine waters.
All of the other dissolved metals investigated, Cd, Ce, Co, Cu, Ni, Pb,
and Zn, are significantly affected by processes other than dilution.
Therefore, plots of dissolved metal concentration versus salinity show
little correlation. Cadmium, Cu, Ni, Sn, and Zn tend to decrease in
concentration with increasing salinity, although there is much scatter in
the data. Differences in metal concentrations in relation to salinity may
arise from varying strength of sources (marine versus freshwater, or
others), fluctuating chemical behavior (oxidizing versus reducing, salinity
differences), hydrodynamic mixing patterns, and other factors.
Patterns of enrichment emerge from plots of the ratio of dissolved
metal in surface water to dissolved metal in bottom water, versus salinity
of the surface water (Figure 4). If surface waters are enriched (contain
elevated concentrations) in a metal, the ratio is greater than one; if
bottom waters are enriched, the ratio is less than one; if the surface and
bottom concentrations are the same, the ratio is equal to one. For
example, in Figure 4a, the dissolved-Cu-concentration-in-near-surface-water
samples to dissolved-Cu-concentration-in-near-bottom-water ratios are
mostly greater than one, and significantly greater than one in the 10 to 15
292
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ppt range of salinity values. This suggests that the mid-Bay (where
salinities range from 10 to 15 ppt) has much higher Cu concentrations in
the surface waters, relative to the bottom waters. Salinity indicates the
relative position along the estuary where enrichment occurs. The term
enrichment refers to the concentration of the metal in the surface water as
a function of concentration in bottom water. This ratio does not indicate
absolute concentration and cannot be used as an index of abnormal metal
content.
Figure 5a compares the ratio of dissolved metal concentration in
surface water to dissolved metal concentration in bottom water, with the
ratio of surface water salinity to bottom-water salinity. On these plots,
a salinity ratio of one indicates there is no halocline and, therefore,
little or no stratification. The data displayed in Figure 5 can be divided
into four quadrants. For example, in Figure 5(b), the ratios of
dissolved-Mo-concentrations-in-near-surface-water samples to
dissolved-Mo-concentrations-in-near-bottom-water samples, appear to fall
primarily in the bottom, left-hand quadrant. This indicates that Bay
waters display a tendency for Mo concentrations to be higher in salty,
bottom waters than surface waters. If the ratio exceeds one, the surface
water is more saline; if the ratio is less than one, the bottom water is
more saline. As in the previous graphs, a metal ratio greater than one
indicates surface enrichment, whereas a ratio less than one indicates
bottom enrichment.
Plots like those of figure 5b show that Cu, Ni, and Zn are strongly
enriched in surface waters, particularly under conditions of strong
halocline development. Under the same conditions, Co, Cr, and Mo are
strongly enriched in bottom waters. Similar data show that Cd is enriched
in low-salinity surface water. Cobalt shows enrichment in surface waters
of salinity up to approximately eight ppt, and in bottom waters over the
salinity range from eight to 15 ppt. Chromium is enriched in surface
waters up to 15 ppt salinity and in bottom waters from eight to 20 ppt.
Copper, Ni, and Zn are strongly enriched in surface waters from five to 18
ppt. Uranium is enriched in bottom waters in the range seven to 15 ppt.
Table 8 summarizes univariate statistics for near-bottom and
near-surface dissolved metal concentrations throughout Chesapeake Bay as
sampled and analyzed by Kingston et al. (1982). Because of the high
precision and accuracy used in these analyses, the information in Table 8
represents data generated for the first time for several metals in Bay
waters. These numbers, then, are "benchwork" values from which to compare
future numbers, and can indicate potential increases or decreases in
contaminated areas.
The NBS investigations (Kingston et al. 1982) analyzed particulate as
well as the dissolved concentrations in the sample. This information
provides better understanding of how the various metals partition between
dissolved and adsorbed phases. Dissolved metal concentrations are very
important, because this phase is completely biologically available.
Therefore, some of the maximum values shown in Table 8 may be hazardous to
aquatic life in Bay waters where these high concentrations are found.
294
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TABLE 8. SUMMARY OF MEAN AND MEDIAN METAL CONCENTRATIONS AND RANGE
OF BAY-WIDE VALUES (UG/L) (DATA FROM KINGSTON ET AL. 1982)
CRUISE OF JUNE-JULY 1979.
Dissolved
Cd
Co
Cr
Cu
Fe
Mn
Mo
Ni
Pb
Sc
Sn
Th
U
Zn
N*
45
102
102
79
102
102
102
102
102
102
9
39
102
102
Mean
0.05
0.07
0.17
0.66
3.12
13.88
3.26
1..21
0.11
0.0006
0.86
0.001
0.93
1.19
Median
0.04
0.05
0.11
0.48
1.63
3.34
2.93
1.15
0.05
0.0005
0.86
0.001
0.88
0.42
Range
0.007-0.101
0.01-0.56
0-1.68
0.15-2.25
0.09-71.67
0-388
0.61-8.68
0.5-2.59
0-1.59
0.0002-0.002
0.31-1.61
-
0.13-2.57
0-11.11
*N is number of samples treated.
DISTRIBUTION AND CONCENTRATIONS OF METALS IN SUSPENDED MATERIAL
Chesapeake Bay Program research has shown the distribution of metals in
suspended material displays marked longitudinal and vertical gradients.
Although concentrations were highly variable between samples and surveys,
the mean metal content per gram of material exhibits distinct trends
(Nichols et al. 1981). Content of the metals, As, Cd, Cu, Pb, Hg, Ni, Sn,
and Zn, reached a maximum in near-surface suspended material of the central
Bay, shown in Figures 6a, 6b, and 6c. Because this part of the Bay is an
area of high biological activity, elevated levels of these metals could
threaten biota there. The concentrations for these metals were higher than
farther landward near major sources in the Susquehanna River mouth and
Baltimore Harbor zone. Particularly high maxima or "hot spots" were
observed for Cu and Cd (Figure 7 and Figure 8). The mean concentrations
for Cu and Cd were five to 10 times greater than the Susquehanna River
mouth. Secondary maxima occurred in the main Bay off Baltimore Harbor for
surface concentrations of Cd, Mn, Ni, Pb, Sn, and Zn (Figure 7 and Figure
8). High levels of metals at these "hot spots" indicate areas of possible
toxic impacts.
Metal concentrations were higher in surface and mid-depth suspended
material than near the bottom, a trend resulting in stratified
distributions. For example, Cu, Ni, Sn, and Zn concentrations were higher
in surface than in near-bottom water in the same zone by a factor of two or
more. Again, these results indicate where unnatural levels of metals can
occur, with a consequence of increased risk of toxicity.
296
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RIVER
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METALS IN SUSPENDED MATERIAL
SURFACE
STATION
221918 16 14 1312 II 10 9 8 765 2 I
30
200
6
5
4
3
2
I
0
400
300
I
200
100
0
ARSENIC
I- AVERAGE SHALE,
F« CORRECTED
CADMIUM., izio M60
IRON
LEAD i480
J6667
280 240 2OO 160 120 80 40 0
•« DISTANCE, km
STATION
221918 16 14 1312 II 10 9 8 76821
8
7
6
f:
3
2
10
9
8
*:
4
3
2
400
_ 300
I
200
IOO
O
60
! 40
MERCURY
1320
MANGANESE
6.9U.6*
pyri Departure
*^* from A»g
Shale
NICKEL 420 480 770
ZINC
280 240 200 160 120 80 40 0
•< DISTANCE, km.
Figure 7. Distribution of metal content in surface suspended material with
distance along the Bay axis. Median values and range of concentrations
from all available observations of Nichols et al. (1981). Shaded zone
indicates magnitude of departure between median values and mean values
for Fe-corrected average shale, open circles.
298
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METALS IN SUSPENDED MATERIAL
NEAR-BOTTOM
STATION
221918 16 14 1312 II 10 9 8 76521
CADMIUM
20
•|
400
300
200
o
400
3OO
O>
* 200
100
0
ARSENIC
COPPER
.172 JTS
IRON
280 240 200 160 120 80 40 0
« DISTANCE, km
STATION
221918 16 141312 II 10 9 8 76521
^300
200
100
0
60
? 4°
20
MANGANESE
n Departure fn
Average Sha
from
Shale
AVERAGE SHALE,
Fe CORRECTED
NICKEL
TIN
280 240 200 160 120 80 40
< DISTANCE, km
Figure 8. Distribution of metal content in near-bottom suspended
material with distance along the Bay axis. Median values and
range of concentrations from all available observations of
Nichols et al. (1981). Shaded zone indicates magnitude of
departure between median values and mean values for
Fe-corrected average shale, open circles.
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Concentrations of metals in suspended material changed with season.
Seasonal changes were marked by a 10-fold increase in surface Cu
concentrations between March to April and May to August (Nichols et al.
1981). Zinc was higher in March to April than at other times, whereas Pb
was highest during June. Table 9(a) summarizes the mean metal
concentrations and range of values at all sample depths throughout the Bay
(Nichols et al. 1981). Table 9(b) , from Kingston et al. (1982), supports
these values.
TABLE 9(a). SUMMARY OF MEAN METAL CONCENTRATIONS AND RANGE OF BAY-WIDE
VALUES, PER GRAM OF SUSPENDED MATERIAL, LEFT; AND WEIGHT PER
VOLUME OF SUSPENDED MATERIAL, RIGHT (DATA FROM NICHOLS ET AL.
1981) FOR MORE THAN 550 SAMPLES AND 8 CRUISES ALONG THE BAY-
LENGTH BETWEEN MONTHS OF MARCH AND SEPTEMBER 1979 AND 1980
Metal
Mean
Metal
Mean
As ug/g
Cd ug/g
Cu ug/g
Fe ug/g
Hg ug/g
Mn ug/g
Ni ug/g
Pb ug/g
Sn ug/g
Zn mg/g
13.00
14.16
127.96
3.11xl07
3.89
2880
95.80
160.30
17.97
750
0.55-100.00
0.12-790.00
9.90-570.00
0.29-17xl07
0.5-59.00
80-46,000
4.80-770.00
21.00-730.00
0.25-290.00
100-7100
As ug/L
Cd ug/L
Cu ug/L
Fe mg/L
Hg ug/L
Mn ug/L
Ni ug/L
Pb ug/L
Sn ug/L
Zn ug/L
0.32
0.14
1.84
88xl05
0.035
65.13
2.00
2.27
0.20
11.02
0.006-5.00
0.003-3.80
0.068-17.00
1.0-1200xl05
0.01-0.47
0.48-1000.00
0.03-34.00
0.10-15.00
0.01-4.80
0.55-94.00
TABLE 9(b). MEAN, MEDIAN, AND RANGE OF METAL CONTENT FOR ONE CRUISE ALONG
THE BAY-LENGTH (JUNE-JULY 1979) (DATA FROM KINGSTON 1982)
N*
Mean
Median
Range
Cd
Co
Cr
Cu
Fe
Mn
Mo
Ni
Pb
Sc
Sn
Th
U
Zn
51
102
102
102
102
102
12
102
96
102
-
100
86
90
0.018
0.24
0.75
0.65
342.45
38.16
0.08
0.57
0.75
0.11
-
0.10
0.029
2.15
0.008
0.06
0.23
0.36
131.50
19.20
0.03
0.27
0.23
0.04
-
0.04
0.012
0.73
0.001-0.11
0.17-2.37
0-5.31
0.1-4.69
14-2911
1.2-349
0.01-0.25
0.03-5
0.01-7.3
0.003-0.93
-
0.002-0.68
0.002-0.192
0-15.2
*N is number of samples treated.
300
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Concentrations of metals and other chemical constituents can be
expressed in several ways, including concentration expressed as weight of
the specific metal per unit weight of suspended material, and per unit
volume of water. The expression used depends on the substance (water or
sediment) being analyzed. Discussion of metal concentrations thus far has
been based on concentrations expressed on a weight per weight basis.
However, when metal distributions reported as weight per volume are
examined, the metal concentrations are directly proportional to the
concentration of total suspended material. Therefore, mean metal
concentrations of As, Fe, Mn, Ni, Pb, Sn, and Zn were highest in the zone
of the turbidity maximum where suspended sediment concentrations are
highest (Nichols et al. 1981). Likewise, near-bottom metal concentrations
of most metals were usually higher than surface concentrations, resulting
in stratified distributions.
In addition to seasonal variations, metal concentrations were highly
variable on short-time scales. For example, concentrations of Cu and Pb
per gram of suspended material from the turbidity maximum zone of the
northern Bay, varied more than two-fold over a tidal cycle. By contrast,
Fe, Mn, and Zn varied within relatively narrow limits. These fluctuations
are associted with large fluctuations of suspended material entering the
Bay, and moderate fluctuations of particle size and organic content as
tidal currents resuspended sediment from the bed. Such short-term (tidal)
changes added to long-term (seasonal) variations produce wide ranges in
metal content. These variations must be taken into account for planning
metal samplings for monitoring and meaningful interpretation of data.
Despite the wide spatial and temporal variations of metal
concentrations, many metals correlated statistically with each other,
allowing the potential use of one or several as predictors. For example,
from the VIMS cruise series (Nichols et al. 1981), Fe-Mn, Cu-Zn, and Ni-Zn,
Ni-Fe, and Zn-Fe had r > 0.80. Many metals from the NBS cruise (Kingston
et al. 1982) also correlated with each other: Co, Cr, Fe, Sc, Th, Zn, Cu,
Mn, Pb, and Ni with r>0.90. These associations reflect the affinity of
metals for suspended material through adsorption or uptake, and show that
many metals display similar behavior. Metals like Mo, U, and Cd did not
correlate, however, because they tend to stay in solution. The similar
behavior of these metals can be used to predict the occurrence of unknown
concentrations when only one metal is known. Moreover, Fe was found useful
as a surrogate element since it is naturally abundant. Iron also varies
within relatively narrow limits throughout the Bay. Its use for
normalizing enrichment factors is demonstrated in a separate section.
A comparison of the mean metal content of the dissolved fraction and
the corresponding particulate fraction per volume of suspended material
[Table 9(c)] reveals several significant trends. The ratio of dissolved to
total metal content provides an index to the mobility of the metal, and
thus its availability to biota. For example, Mo and U are dominately in
dissolved form in both surface and bottom water, whereas Co, Fe, Mn, Pb,
Sc, and Th are dominately in the particulate form. Note that Zn displays
much higher percentages in surface water than in bottom water. Therefore,
samples of surface water alone are not indicative of the dissolved Zn
content in bottom water. By contrast, Mn (both particulate and dissolved)
is much higher in bottom water than in surface water in summer. This trend
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probably reflects mobilization and release of Mn from central Bay sediments
during summer anoxia. The index provides an indication of which metals
organisms are exposed to in summer. Since dissolved metals generally have
a shorter residence time in the Bay than particulate metals, the index
further predicts that metals like Mo and U will likely escape the Bay
whereas Co, Cr, Fe, Mn, and Sc are most likely retained in the estuary.
The fate of other metals probably varies with natural biochemical and
sedimentological processes native to the Bay.
DISTRIBUTION AND CONCENTRATION OF METALS IN BOTTOM SEDIMENTS
During the Bay Program, surface sediments were analyzed for As, Cd, Co,
Cr, Fe, Hg, Mn, Ni, Pb, and Zn by Helz et al. (1981) and Nichols et al.
(1981). All of these metals are more concentrated in the fine fraction
« 63 um) of bottom sediments than in bulk samples and show that the
Susquehanna River is a major source of most metals. Figure 9 illustrates
the Cu distribution in bulk and in C 63 um surface sediments of the Bay.
Copper in the fine fraction decreases seaward from the Susquehanna mouth,
indicating a river source. Copper also decreases eastward across the Bay,
suggesting that seaward transport carries contaminated sediment seaward
along the western shore. This pattern is consistent with the observed
salinity pattern and net circulation of the Bay. An alternate cause of the
western shore enrichment is the input from Baltimore Harbor and western
shore tributaries.
Zinc distribution in bulk and fine sediments is illustrated in Figure
10. Zinc values in the silt-clay fraction are highest in the Bay off of
Baltimore Harbor and decrease both landward and seaward, suggesting that
Baltimore Harbor is a source of Zn to the Bay. Two mechanisms may be
responsible for metal transport from the Harbor in particulate form: the
estuarine circulation and dredge spoil disposal. More than 4.6 million
cubic meters of dredged material have been disposed in the Bay off the
Harbor (Schubel and Williams 1976). However, from the metal distributions,
it is not possible to identify the magnitude of either of these
mechanisms. Tidal action may be partially responsible. However, we do not
feel it is a dominate factor and believe the data suggest riverine
sources. The bulk Zn distribution displays relatively high concentrations
in the lower Bay off the Rappahannock mouth. The high clay content of
these sediments is probably responsible for the elevated concentrations
observed in bulk samples.
Chromium and Pb exhibit surface sediment distribution patterms similar
to Zn with maximum concentrations occurring in the fine fraction off
Baltimore Harbor. The distribution of the metals Mn, Fe, Co, and Ni mirror
Cu distributions, with highest values found in the northern Bay and along
the western shore. Metal to Fe ratios of bottom sediment decrease with
distance seaward from the Susquehanna River, indicating the river is a
major source of Mn, Ni, and Zn.
METALS IN INTERSTITIAL WATER
Until recently, the massive reservoir of materials contained in the
bottom sediments of the Bay has largely been ignored as a potential source
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75° 30
DISTRIBUTION OF COPPER.p
IN UNFRACTIONATED SEDIMENT
DISTRIBUTION OF
COPPER, ppm
IN FRACTIONATED SEDIMENT
•># 1
= -. 45'
Figure 9. Distribution of Cu content in bottom sediments of (a) bulk
bed sediment, unfractionated, and (b) the less than 63 u
size fraction, fractionated. Data from Helz et al. (1981).
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77°
DISTRIBUTION OF ZINC, ppm
IN UNFRACTIONATED SEDIMENT
DISTRIBUTION OF
ZINC, ppm
IN FRACTIONATED SEDIMENT
Figure 10. Distribution of Zn content in bottom sediments of (a) bulk
sediment, and (b) the less than 63 u size fraction. Data
from Helz et al. (1981).
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of nutrients and trace elements. Previous investigations, Berner (1979)
and Bricker and Troups (1975), show a substantial transfer of trace metals
from the sediment to the water column. The principal vehicle for
transporting this material from the sediment to the overlying water is the
interstitial or pore water (water contained in the sediment). Many of the
constituents of interstitial waters are derived from chemical reactions of
water with the solid material of the sediment.
The constituents and parameters measured on 97 cores by Hill et al.
(1981) and Tyree et al. (1981) are:
Na+, K+, NH*. Ca++, Mg++, F~, Cl~, N0~,
NO", PO^, S0~, S0~, HCO~, pH, pS~, Eh,
Conductivity, Fe, Mn, and SiO..
A subset of these cores was analyzed for the trace metals Pb, Cd, Cu, and
Zn. Figure 11 is a graphical presentation of some core data of a
representative station.
The transport of dissolved constituents across the sediment-water
interface proceeds in response to concentration differences. Constituents
migrate from areas of high concentration to more dilute areas according to
Pick's law (Lerman 1979). Generally, the concentration of nutrients (such
as NH£, P04, and HCO§) and trace elements in the interstitial
water exceeds the concentration in the overlying water column. Thus, the
gradient predicts that these materials are transported from the sediment
into the water column.
The chemical sedimentary environment controls the concentration of
constituents in the interstitial water that, in turn, controls the
transport of materials between the water column and sediment, and within
the sediment. Three major chemical sedimentary environments have been
identified for the main portion of the Bay: the northern Bay; the central
Bay, including upper and lower parts; and the southern Bay, including two
subsections (Figure 12). The chemical environments are classified
according to a set of parameters, which influence and reflect the redox
state of the sediment. These parameters are: major ionic composition of
the interstitial water; organic carbon content of the sediment; reduced
sulfur content of the sediment; degree of SO^ reduction; Eh; and the
concentrations of dissolved sulfide species, Fe, Mn, and NH£. The
three environments correspond to Berner's (1981) method of classification
of sedimentary environments.
The northern Bay, as shown in Figure 12, is primarily characterized
by: (1) ratios of the major ion concentrations that differ in comparison
to ratios from marine-dominated environments, (2) high organic carbon
content (five to six percent), (3) absence of dissolved sulfide species,
(4) complete ( 80 percent) reduction of available SO^, and (5) the
most positive Eh values in the Bay. The primary chracteristics of the
central Bay environment are: (1) intermediate to high organic content (two
to five percent), (2) high concentration of dissolved species, (3) variable
degree of SO^ reduction between cores, and (4) the most negative Eh in
the Bay. The southern Bay characteristics are: (1) low organic carbon
(zero to two percent), (2) essentially no S0£ reduction 0^20 percent),
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v-/
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Figure 12. Distribution of chemical sedimentary environments in
Chesapeake Bay, based on data of Hill and Conkwright
(1981).
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(3) very little detectable NH£, and (4) and Eh more positive than the
central Bay, but more negative than the northern Bay.
Estimates of the transport of material, with respect to the
sediment-water interface, according to the three major chemical sedimentary
environments, are presented in Table 10. The ranges include seasonal
changes of temperature and salinity, which can markedly effect the chemical
environment. The fluxes calculated from the concentration gradients
generally indicate: (1) NH^,' HC03, and PO^ are added to the
overlying water column in the northern and central Bay; (2) Fe and Mn are
transported to the overlying water column in the northern Bay, but
stabilized in the sediments in the central and southern Bay; (3) sediments
contribute sulfide (HS~) to the overlying water of the central Bay, and
(4) P0£ is stabilized in the sediments of the southern Bay. The trace
metal data indicate that the concentration of the metals in the interstitial
water corresponds to the chemical sedimentary environments, but the
concentration gradient profiles are too complicated for a simple Pick's law
estimate.
TABLE 10 GENERAL ESTIMATED RANGES OF FLUXES DIVIDED ACCORDING TO CHEMICAL
ENVIRONMENT, VALUES EXPRESSED AS u MOLS/M2/DAY
Fe++ Mn++ HCO P0 HS
Northern
Bay + 50-+700 - 20-+70 -100-+60 +800-+3000 + 30-+80 **
Central
Bay +200-+2000 -100- 0 - 60-+30 +100-+20,000 - 20-+70 +400-+30,000
Southern
Bay ** - 30 — 10 -30--10 * -100 — 20 *
** - Chemical species below detection limits in these areas
* - Core data did not fit the simplified model used to estimate the fluxes
Note: Positive flux values reflect transport into the overlying water
column; conversely negative values reflect transport into the
sediment.
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SECTION 3
FINDINGS FROM STUDIES ON ORGANIC COMPOUNDS
The following chapter explains the results from CBP research on the
distribution and concentration of organic compounds in Chesapeake Bay.
Since polynuclear aromatic compounds (PNAs) constitute the largest
proportion of toxic synthetic substances entering the Bay (and are also
listed on EPA's Pollutant list), much of the CBP research focused on these
compounds. Other organic compounds, including dieldrin, terpenoid, DDT,
and other pesticides were detected. However, extensive, quantitative
analyses were performed on PNAs. In this section, sources of PNAs to the
Bay are discussed, followed by results of analyses on levels of organic
compounds found in bottom sediments and oysters. The remainder of the
chapter interprets these results and considers important factors affecting
the distribution and abundance of organic compounds.
SOURCES
The major source of most of the organic compounds (PNAs) entering the
Bay is the burning of fossil fuels, coal, oil, and wood. Sources from the
Patapsco River also produce compounds made up of substituted benzenes.
These compounds are also released in industrial processes such as coal
liquefication and gasification (Bjoreth and Dennis 1979, Cooke and Dennis
1980) . Simple substituted aromatic compounds are assembled at high
temperatures (combustion gases) to produce PNA compounds, with different
compounds dependent primarily on the combustion temperature and secondarily
on the fuel source. As indicated by PNA analysis of old sediments
deposited prior to human's use of fossil fuel, very few aromatic compounds
were produced by organisms. Most PNA compounds produced by combustion
differ from those in oil or in the complex polymeric network of coal in
that combustion products are generally not substituted.
Specific sources of PNAs in the Bay region include vehicles burning
gasoline and diesel oil, coal and oil fired power plants, coal and oil
fired heating industrial plants, oil and wood home heating, and forest and
refuse fires. PNA compounds can be transported from the locations of the
sources to the Bay by air-borne particulates containing PNA (smoke and
exhaust), airborne volatile PNAs, water-borne particulates (sediment)
containing land runoff and river-borne PNAs, and compounds carried in
solution by rivers and land runoff. Some small amounts of PNAs are
produced in the Bay by the combustion of vessel fuels.
Within the Bay, large concentrations of PNAs were found at the mouths
of rivers. Some small subestuaries, like the Elizabeth River and Baltimore
Harbor, with very high industrial actvity and population density, can also
produce high local PNA concentrations. PNA compounds are probably
continuously increasing throughout the Bay, because these many sources
repeatedly produce PNA that is stable over long periods in the Bay water
and sediments. A final source of PNA to the Bay is long-range atmospheric
transport by Northern Hemisphere air currents. Chesapeake Bay is receiving
air-borne PNA in vapor and particulates introduced in other regions of the
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United States or other Northern Hemisphere countries. Contributions to PNA
concentrations in the Bay from such long-range sources are probably uniform
from place to place, because the Bay and its watershed area (which together
serve as a PNA collection basin) are small with respect to the areal extent
of single air masses.
ORGANIC COMPOUNDS IN BOTTOM SEDIMENTS
Analyses of sediment samples collected for the Bay Program during the
spring and fall of 1979 (Bieri et al. 1981) revealed that over 300 organic
compounds were abundant enough to either be identified or given a surrogate
name by assigning a relative retention time. Only a small percentage of
these 300 is not toxic in certain amounts. In some samples, the complexity
and abundance of compounds present were so great that many individual
species at relatively low concentrations were undoubtedly not detected. It
is, therefore, probable that thousands of compounds were present. An
example is presented in Figure 13, which is an actual gas chromatogram
showing individual peaks. These peaks represent at least one compound
superimposed on a background of peaks from numerous compounds of lower
concentrations. This is commonly called an unresolved complex mixture.
The distribution of organic compounds in bottom sediments (Figure 14)
is presented as bar graphs representing summed concentrations on a
logarithmic scale of chromatographically resolvable compounds eluting in
the "aromatic" fraction. The figures show that the highest total
concentrations are encountered in the northern portion of Chesapeake Bay.
Furthermore, samples from Stations 2, 4, 6, 7, 10, 11, and 12 in the lower
Bay are almost devoid of these compounds. However, with the exception of
the fall 1979 sample from Station 9, samples from river mouth stations,
numbers 1, 3, 5, and 8, contained substantial sums—between 100 and 1000
parts per billion (Figure 14).
To demonstrate that the northern Bay and the river mouths have
unnaturally high levels of organic compounds, it is necessary to account
for variations in sediment character. Fine-grained sediments usually
contain higher organic concentrations than coarse sediments, and this can
explain some of the anomalous distributions. In general, sediment samples
from the northern Bay and the major river mouths contained a higher
fraction of silt and clay than elsewhere. When the samples are normalized
for silt and clay content the distributions (Figure 15) change in the
concentration sums in the northern Bay with the exception of Station 27,
Fall 1979. In the lower Bay, only Stations 1, 3, 9, 11 and 12 have
increased. Without further analyses of samples collected within the
subestuaries, it is impossible to determine whether high concentrations in
sediments collected near the major river mouths were due to sediment grain
size or unnaturally high inputs from upstream. Normalizing the northern
Bay data did not substantially change the distribution pattern. With the
exception of the fall Station 19 sample, there is a trend of increasing
concentrations from below the Potomac River mouth toward the Baltimore
Harbor mouth. North of Baltimore, the concentration sums decrease and then
increase to another maximum toward the Susquehanna mouth. Inside the
Susquehanna mouth (Station 27) samples showed considerable variation
between spring and fall, differences that may arise from variations of
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SEDIMENT SUM OF ALL PEAKS, ppb
c
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26
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Figure 14. Chart of station locations and bar graph representing
concentration sums of all resolvable peaks for organic
compounds in sediments, spring samples 1979. Data from
Bieri et al. (1981).
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'24
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SEDIMENT NORMALIZED TO SILT/CLAY
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Figure 15. Chart of station locations and bar graph representing
concentration sums (ppb) of all resolvable peaks for
organic compounds after normalizing for pilt and clay
content. Spring samples, 1979. Data from Bierl et al. (1981)
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23J
19..
14.
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OYSTERS
SUM OF ALL PEAKS, ppb
IOZ
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Figure 16. Chart of station locations and bar graphs representing
concentration sums of all resolvable peaks for organic
compounds in oysters, spring samples, 1979 (Bieri et al.
1981).
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river flow that scour sediments during high spring flow and deposit
sediment during low fall flow.
The trends for PNAs follow the trends for sums of all concentrations:
(l) the concentrations are higher in samples from the northern Bay than in
the southern Bay; (2) in the southern Bay, highest concentrations are found
near river mouths; (3) concentrations tend to increase up the Bay from the
Potomac River mouth toward Baltimore Harbor; and (4) the Susquehanna River
mouth sediments show considerable variability, but can reach extreme
concentrations. Data displayed for several individual members of the PNA
family show even more clearly that a concentration maximum occurs in the
northern Bay in the vicinity of Baltimore Harbor, suggesting that this area
is an important source of PNA families (Bieri et al. 1981)
ORGANIC COMPOUNDS IN OYSTERS
In addition to sediments, oysters were also collected during the Bay
Program and their tissue was analyzed for organic compounds. The gas
chromatograms of oyster tissue extracts were much less complex than those
of sediments, with the concentration of individual compounds substantially
lower. The graphs for oysters (Figure 16) show no longitudinal trends like
those in sediments (Bieri et al. 1981). In addition, methyl esters of fatty
acids were present in most samples, as were some ketones. We hypothesize
that many of these compounds have a biogenic or natural origin. Since they
are often present in higher concentrations than identified pollutants, the
summed concentrations may not represent a realistic pollutant content in
oysters. Therefore, we examined the number of compounds detected and their
distributions rather than their sums. Altogether, we identified 127
organic compounds. Oysters collected at the mouth of the James River
contained 94 of these compounds. Oysters collected from Occohonnock Creek
(Station 7) contained 27, and those from near Baltimore Harbor (Station 22)
had 24. The oysters that contained the next highest numbers of compounds
were from Holland Point (Station 20) with 23 compounds, and Onancock Inlet
(Station 10) with 19 compounds. Although this analysis suggests that these
areas have the highest contamination of organic compounds in oysters, there
is no apparent reason why oysters from the Occohonnock Creek, Holland
Point, and Onancock Inlet should compare to the James River and Baltimore
Harbor, where sediment concentration of organic compounds is greatest. It
is very likely that salinity or some other physical or chemical factor is
influencing the levels of organic compounds in oysters.
If only the most concentrated compounds are considered, a similar
pattern emerges. There were 42 compounds detected whose individual
concentrations exceeded 50 ppb. The samples from the James River mouth
(Station 3) contained 29 percent of these. The next highest were from
Baltimore Harbor (Station 22) with 24 percent. These were followed by
Station 10 with 21 percent, Station 20 with 17 percent, and Station 7 with
14 percent. In summary, the following sequence emerges from abundance of
compounds: James River ^Occohonnock Creek">near Baltimore Harbor> Holland
Point7 Onancock Inlet. For individual compound concentrations greater than
50 ppb: James River >near Baltimore Harbor VOnancock Inlet> Holland Point >
Occohonnock Creek. In both cases the same five stations emerge as being
the highest.
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Although the presence of oysters in these Locations indicates that
numbers and levels of organic compounds in their tissue are probably not
lethal, elevated concentrations can reach biota higher in the food web.
Oysters and other invertebrates can store organic compounds in their
tissue, passing on that amount to consumers. These organisms, in turn, may
accumulate harmful levels.
Comparison of the compounds detected in the oysters with those found in
nearby sediments showed little correlation (Bieri et al. 1981), indicating
that oysters are not so useful as sediments to monitor the Bay for organic
compounds. In sediment samples, the most abundant compounds were PNAs.
With the exception of dibenzo-thiophene, fluoranthene, pyrene, and
benzo(e)pyrene, none were detected in oysters. This could be due to the
compounds not being biologically available to the oysters; or the oysters
may depurate them very rapidly, or metabolize them to other compounds that
were not identified.
ORGANIC COMPOUNDS IN BALTIMORE HARBOR
The CBP's sampling effort in Baltimore Harbor was identical to the work
previously discussed for the main Bay. In addition, the GBP funded the
Monsanto Research Corporation (MRC) to sample the major industrial and POTW
dischargers in Baltimore Harbor. Together these two projects provided a
mechanism by which the compounds found in Harbor sediments could be traced
to possible sources in industrial and POTW effluents. Concentrations of
the organic compounds in the Harbor sediments were generally much higher
than those samples from the Bay. Additionally, many of the compounds found
in the sediments were also detected in the point source dischargers.
Forty-one bottom sediments were collected from the Patapsco River and
Baltimore Harbor during spring 1981 (Bieri et al. 1981). The PNAs dominate
the aromatic compounds in the river as in samples from Chesapake Bay
proper. In some cases, the concentrations were ten to twenty times higher
than the highest found in the Bay. The concentrations of the PNAs within
the river also vary drastically with location. This suggests that there
are either point sources of PNAs or non-uniform water circulation and
sediment type that cause the organic compounds to accumulate more in
specific areas. It is likely that a combination of these two factors is
responsible for the distributions.
Figure 17 represents the concentrations of one of the PNAs,
[benzo(a)pyrene], normalized to silt and clay content, in the channel
sediments from the Patapsco River. It is obvious that there are several
areas where relatively high levels exist. Point sources may be partially
responsible for the anomalously high concentrations that at one location
reach 5.5 ppm. The benzo(a)pyrene concentration in Bay sediments is
depicted by the cylinder farthest to the right. The concentration here is
about equal to that of the station next closest within the Patapsco, 260
ppb versus 290 ppb, respectively. This suggests, but does not prove, that
the peak of PNAs found in the Bay near the Patapsco River mouth could be
the result of transport from the Patapsco.
One sample from the Patpasco River gave a very anomalous gas
chromatographic fingerprint that was dominated by an abundance of compounds
with relatively low rentention times and high concentrations. The
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FERRY BAR CURTIS BAY GRAVITY CORE STATIONS
Figure 17. Distribution of PNA, benzo(a)pyrene in channel sediments
from Baltimore Harbor and the Patapsco River. Relative
concentration relates to height of column at each
location.
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compounds were not PNAs. Mass spectrometrie analysis and comparison with
EPA-NIH Mass Spectral Data Base showed that they were composed of
substituted benzenes. The mass spectrometry data files were searched to
see if these compounds were present at any other locations but had been
hidden by more concentrated PNAs. The search showed that several of the
substituted benzenes were either definitely present, probably present, or
not present. The substituted benzene, 6-phenyldodecane, has a widespread
distribution within the Patapsco River, and data indicate that sediments in
the adjacent Bay also probably contain it. The sample with the highest
concentration was collected landward from the river mouth.
Effluent sampling data generated by Monsanto Research Corporation
(1981) showed that an effluent collected very near the sediment station
contained substituted benzenes and, specifically, 6-phenylododecane. Using
this compound as a tracer, we must conclude that organic compounds can
enter the Patapsco River from point sources, travel throughout the river,
and probably into the Bay. The fact that 6-phenyldodecane was only
"probably present" in the two eastern most samples prevents stating that
this is definitely the case, but it is difficult to conceive of a mechanism
that would totally stop the eastward migration of the compound at the mouth
of the River. It is not surprising that these two stations yield data that
are less definitive than the others, because they are in the Bay where more
mixing and dispersion occurs, and they are farthest from the source.
The methodology developed through the Bay Program for analyzing organic
compounds within sediment of Chesapeake Bay has tremendous potential as an
analytical tool for tracking known and unknown organic compounds in the
system. The technique essentially generates a chromatographic
"fingerprint" of the peaks found in the sample. These peaks are "tagged"
by co-injecting relative retention markers and labeling each peak with a
relative retention number. This becomes important when an unknown peak is
found in a point source discharge and also in nearby sediment or resident
fish tissue. This information allows one to "flag" potential problem
compounds that may be building up or bioaccumulating in the Bay system.
The technique was used in Phase II of the Monsanto Research Corporation
Source Assessment Effluent Analysis and IMS sediment and oyster tissue
analyses. A wealth of data on organic compounds is now available in the
CBP data banks, and can be used for years, even decades to come.
In summary, the basis for our argument, stating that some of the
organic compounds in the northern Bay sediments come from the Patapsco
River, is that (1) PNA concentrations along the Bay rise near the Patapsco
River mouth, (2) concentrations are much higher in the Patapsco River than
in the Bay, and (3) the distribution of 6-phenylododecane is wide spread.
Additional identification of compounds found in Harbor and Bay sediments
and detected in the point source effluents has been done, but will not be
discussed further in this paper.
CONCLUSIONS
Results from studies on organic compounds show that Chesapeake Bay
contains many polynuclear aromatic hydrocarbons with lesser amounts in Bay
oysters (Bieri et al. 1981). Because PNA compounds are fairly stable, they
are transported by current flow and sediment motion to other locations in
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the Bay. In general, PNA compounds associate with sediment particles,
partitioning in such a way that concentrations on sediment particles are
much higher than in solution.
The influence of a local PNA source on PNA concentrations in the Bay
will depend on the proximity of the source to the Bay, the magnitude of the
source, the prevailing wind and water runoff patterns, and the
characteristics of Bay sediments and current in the local region.
From this information, it can be expected that PNA concentrations in
the Bay should be highest in areas of sedimentation near industrial
regions, high population density areas, and power plant sites. Gradually,
over a period of years, diffusion, advection, and sediment transport will
spread PNA compounds over wider areas of the Bay. Although PNA transport
from potential sources to sinks in the Bay can be described, quantitative
measures of concentrations and transport rates are scant and inadequate.
The question which must be answered is: are the concentrations
primarily the result of human activity or do they occur naturally from
sources such as natural oil seeps or forest fires? The distribution and
abundance of the PNAs within the Bay and the Patapsco River indicate that
human activity is mainly responsible. The established origin of most
unsubstituted PNAs (perylene is an exception) in high temperature reactions
(Badger 1962, Schmelz and Hoffman 1976, Youngblood and Blumer 1975, Hase
and Hites 1976) leaves little doubt about this fact. Since such
pyrosynthesized PNAs can travel considerable distances (Lunde and Bjorseth
1977, Lunde et al. 1976), their occurrence is widespread. This may explain
the presence of such PNAs in the relatively pristine areas of the Ware and
Rhode Rivers, where chrysene concentrations range from 26 to 110 ppb, and
benzo(a)pyrene from seven to 100 ppb. The majority of these PNAs, however,
likely settle close to the source and, from there, reach the Bay by runoff
and river transport.
With the increasing combustion of fossil and other carbonaceous fuels,
it is likely that the PNA levels in the Bay will increase. Unfortunately,
the toxicity data required to assess the resulting impact on the Bay's
biota are inadequate. We do not know the toxicities of the individual
components, much less the combinations, and we do not know if they are
available to the biota. But the fact that many of them are carcinogenic,
mutagenic, and teratogenic to mammals is enough cause for concern.
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SECTION 4
PATTERNS OF TOXIC METAL ENRICHMENT
A limited, but important aspect of GBP research on metals in the Bay
includes several studies on factors affecting their distribution and
concentration. The dynamic nature of the Bay largely influences the
behavior of metals and, consequently, their threat: to the estuary. This
section describes studies conducted on some of the behavioral aspects of
metal inputs. It includes sections on processes affecting metal
distribution; enrichment of metals above natural levels; historical trends
in metal enrichment; and the important relationship between metals and
sediment.
INTERPRETATION OF PROCESSES AFFECTING METAL DISTRIBUTIONS
Chemical substances like trace metals are continuously added to
estuaries by inflowing tributary rivers, shoreline erosion, the coastal
marine environment, the atmosphere, and the biosphere. Much of this
material, dissolved and particulate, consists of the natural products of
weathering, erosion processes, and of biological activity. In addition,
anthropogenic products and wastes enter the estuary either directly in
effluent discharges or by nonpoint source runoff. A large proportion of
both the natural and anthropogenic material is intimately associated with
sediments, particularly those of fine particle size and large surface
area.
Suspended material is not only a reservoir for metals, but a vehicle
that carries metals from their source to their depositional sink. It is an
exchange medium for scavenging and removal of toxic metals from the water
column. The metal distributions per liter of water show that the z:one of
the turbidity maximum is the most enriched (elevated above natural levels)
part of the suspended material reservoir (Nichols et al. 1981).
Additionally, time-series observations show that much material is
resuspended from the bed, and that river-borne material is most likely
trapped in the convergence of seaward-flowing river water and
landward-flowing estuarine water. Enrichment is enhanced by small particle
size (5~1lu) of the material and by the relatively long residence time of
particles in this zone.
In the central and lower Bay, metals borne on suspended material can be
transported along two pathways, a hydrodynamic route, and a bioecologic
route. The hydrodynamic route is revealed by dispersion patterns of metals
in bottom sediments (Helz et al. 1981), whereby seaward transport from
potential sources is indicated along the west side of the Bay. This route
is in accord with the path of estuarine flow and the salinity regime.
Landward transport through the lower Bay is indicated from metal
distributions of Cr (Helz et al. 1981) that extend landward from the Bay
mouth along the eastern side.
The relatively enriched metal content of central Bay surface water
suggests that metals like Cd, Cu, Ni, and Pb follow a bioecological path.
Because the enriched zone is generally an area of high suspended organic
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loads with more than 50 percent combustible organic material, it seems
likely that the metals are assimilated from solution by phytoplankton or
from suspension by zooplankton. Once in the food chain the metals can be
further enriched (or bio-magnified) in fish or filter-feeding shellfish.
METAL ENRICHMENT
Both nonpoint and point sources contribute metals and many organic
compounds to the Bay and tributaries from anthropogenic sources (Huggett et
al. 1974b, Helz 1976, Brush 1974). These levels are superimposed on a
background of natural concentrations. To assess the impact of human
activity and control amounts reaching the Bay, it is critical to
distinguish natural from anthropogenic levels.
Some organic compounds occur rarely, or not at all in nature, and their
presence and concentration in sediments is direct evidence of anthropogenic
input. The metals, however, occur both naturally and anthropogenically.
For a given concentration of metal, there is no direct way to determine the
portion that is natural and that which is anthropogenic. One method is to
derive a ratio of the metal in question to a baseline metal also contained
in the sample. The baseline metal should have no known anthropogenic
source and should be naturally abundant so that no known pollution sources
could significantly affect its concentration. The accuracy of this method
can be verified by statistical tests. The precision would require
comparison to known standards, which for this particular measurement, do
not exist. Therefore, we cannot verify the precision and have not, at this
time, determined the accuracy of this method.
Two metals, Al and Fe, were chosen to derive the ratios for determining
anthropogenic levels of metals. Scandium was used by Kingston et al.
(1982) in suspended sediment samples, because it is believed to have no
anthropogenic sources. Aluminum and Fe were used in bottom sediments, and
Fe was used in fluid mud samples. Concentrations of metals in these
samples were normalized using Sc, Fe, or Al in ratios with concentrations
of the metals in average crustal or shale material. For example, the ratio
of Fe in average shale to Fe in Bay sediment and also to the concentration
of metal in crustal material, yields an expected value for Bay sediment.
The complete relation is:
EF = (X/Fe) sediment sample
(X/Fe) crust or shale
Where X/Fe is the ratio of the concentration of metal X to Fe in the
sediment sample and in the crust.
The advantage of this geochemical baseline level is that it provides a
standard for comparing data throughout the Bay. It assumes that the
Chesapeake drainage basin is representative of average crust, and that a
uniform crustal average exists throughout the region. Consequently, it
does not account for local metal variations. Because the method is
chemical, it is independent of sediment physical properties like particle
size; it is affected, however, by compositional changes such as varying
organic content within sediment.
Analyses show that enrichment factors in bed sediment for Cd, Co, Mn,
Pb, and Zn are largely greater than two, and occasionally reach seven in
the Baltimore-Susquehanna River area (Figure 18). For As, Cr, Cu, Hg, Ni,
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and Sn, factors are largely less than two or close to baseline factors
throughout the Bay proper. Seaward of the Bay Bridge (Annapolis) factors
generally diminish, but Cd, Pb, and Zn are greater than two. The
longitudinal distribution of values does not display a maximum in the Bay
near Baltimore, an expected increase if metals were emanating from
Baltimore. Instead, the values mainly decrease from the Susquehanna River
mouth, suggesting a river source (Helz et al. 1981). If the Susquehanna
watershed is not naturally enriched compared to average crust, then the
enrichment is affected by direct contamination from industrial and
municipal sources or from acid mine drainage.
Bed sediments within the Patapsco River, Baltimore Harbor, are markedly
enriched in Co, Cr and Zn (Sinex et al. 1981). Longitudinal distributions
of enrichment factors, show that Cr increases with distance landward, and
Zn is enriched throughout the Harbor. The Elizabeth River, Hampton Roads,
is notably enriched in Zn with Zn/Al ratios of six to 25 (Sinex et al.
1981).
Enrichment factors for Cd, Cu, Pb, and Zn in surface suspended material
of the central Bay are much greater than in bed sediments of the northern
Bay. Metal/Fe ratios range from 10-118 for Cd, 12-27 for Cu, 37-51 for Pb,
and 16-74 for Zn. The high enrichment factors in the central Bay are
associated with high percentages of organic matter, probably produced by
plankton metabolism. Additionally, the metal content of central Bay
suspended material exceeds the content of oceanic phytoplankton more than
nine times for Cd and Zn, and more than 19 times for Cu, Ni, and Pb.
Historic Metal Input Recorded in Sediments
Some sediments in the Bay reveal trends in metal enrichment. In
sediments deposited in anoxic waters, no benthic macrofauna are present.
Therefore, the sediments remain relatively undisturbed and may record the
history and rate of change of metal influx. When a core of such sediments
is analyzed for trace metals and dated by ^lOp^ chronology, the vertical
changes reveal variations in metal input. This approach assumes no
diagenetic migration of metals through the length of the core. In oxic
environments, however, burrowing activities of benthic organisms can
disturb the record of sedimentary sequences, create an "artificial"
distribution, and influence vertical trace metal distributions.
The vertical distribution of 210pb and metal concentrations (Helz et
al. 1981) and the degree of bioturbation have been carefully examined for
selected sediments of the Bay. Cores 4, 18, and 60 (Figure 19) exhibit
exponential 210pb profiles, low ^lOp^ depth-integrated concentrations,
and low or moderate bioturbation. They also show no metal peaks and
display a relatively uniform rock structure. In addition, core 4 has
13'Cs data that verify the ^lOp^ sedimentation rate. Metal/aluminum
ratios for the three cores, and 210pb chronology are presented in Figure
19. All three cores show Zn enrichment in the Zn/Al ratios near the core
surface, with maximum enrichment occurring at about 1940 in core 40 and
about 1960 in cores 18 and 60. The first appearance of excess
concentrations is also temporally displaced down the Bay from 1890 in core
4, to 1920 in cores 18 and 60. If the source of this excess Zn is fluvial
(or anthropogenic) and up-Bay, then it takes about 20 years for the metals
to be transported 80 kilometers between core 4 and core 18, a nominal rate
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Figure 19. Metal/aluminum ratios, Zn/AI and Cu/AI, for three cores
from northern and central Chesapeake Bay, cores^^A 18,
and 60. Data from Helz et al. 1981. Dates in Pb
years; departure of metal/aluminum and metal/iron ratios
from background in each core, shaded.
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of four kilometers per year.
When interpreting concentration profiles from sediment core samples, we
must be sure that the vertical concentration gradients are not a result of
diagenetic processes that may alter the chemical environment within these
sediments. Interstitial water data of Hill and Conkwright (1981) on
oxidation-reduction (redox) potential and pH values were examined to
provide an indication of the magnitude of the various chemical diagenetic
processes in the sediment core samples. These data reveal no correlations
between redox and pH, and metals, so we assume that the upward changes for
the metal/aluminum ratios are not diagenetic; that is, there has been
enrichment of trace metals with time. It is not now possible, and may
never be, to assign a specific cause or source to these metal increases.
However, we can speculate that human activity in the watershed and Bay has
been sufficient to cause widespread perturbations. Deforestation for
agriculture, mining, industrial pollution, the construction of three
hydropower dams in the 1920s and 1930s, the construction of the sea-level
Chesapeake and Delaware Canal, air pollution, domestic sewage, floods, and
hurricanes probably all contribute to the changes observed.
Metal enrichment ratios in surface sediments vary in known geological
patterns in the Baltimore-Susquehanna River zone as shown in Figure 18.
The ratios increase near the surface of cores with time, matching those
patterns in Figure 19. These results show that the northern Chesapeake
sediments are experiencing important anthropogenic sources for Co, Cu, Ni,
Pb, and Zn.
METAL - SEDIMENT RELATIONSHIPS
Analyses of metal concentrations and sediment characteristics performed
during the CBP reveal a close association between metal content and certain
sediment parameters. Ninety-six paired samples of surface sediments from
the southern Bay metals and sediment parameters were subjected to stepwise
regressions of metal content and sediment parameters. Every metal analyzed
had a significant correlation with at least three independent variables
(Table 11). Every metal had the highest correlation with percent silt and
clay; metals in southern Bay sediments were dominantly associated with the
fine particulate fraction. Over 30 years of research in other estuaries
has consistently verified this finding (Forstner and Whittman 1979).
Correlations with latitude represent axial variation and with longitude,
lateral variation that, in turn, may reflect origins. These sources can be
either up-bay or western-shore rivers, or an association with salinity that
is higher seaward and along the eastern shore, than along the western
shore. The regression equations are useful for predicting the metal
content of bed sediments in the southern Bay when only sediment size
analyses are available.
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TABLE 11. RELATIONSHIP OF BULK CHEM ANALYSES OF METALS (HELZ ET AL.
UNPUBLISHED) VERSUS SEDIMENT PARAMETERS (BYRNE ET AL.
UNPUBLISHED) BY STEPWISE REGRESSION
Metal
R2
Stepwise Regression
Ranked Parameters2
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
.856
.763
.885
.797
.822
.738
.850
.791
.769
Silt, Clay, Latitude
Silt, Clay, Carbon, Latitude, Longitude
Silt, Clay, Mean Size, Latitude, Longitude
Silt, Clay, Mean Size, Longitude
Silt, Clay, Mean Size, Carbon, Latitude,
Longitude
Silt, Clay, Carbon, Latitude, Longitude
Silt, Clay, Carbon, Latitude, Longitude
Silt, Clay, Carbon, Latitude, Longitude
Silt, Clay, Mean Size, Carbon, Latitude,
•Longitude
Significant at .0001
parameters are percent silt, percent clay, mean size, percent
organic carbon, percent sulfur, percent H20, Latitude, Longitude.
Parameters were not ranked when they did not meet a 0 . 15 significance
level.
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SECTION 5
FINDINGS ON SEDIMENTS AND BIOTA
This section describes results of CBP research on aspects of sediment
and biota that influence the fate and transport of metals in the Bay. The
first part discusses physical and chemical characteristics of sediment, as
well as patterns of sedimentation. The second half of the section
describes the character of benthic animals in the Bay and how their
activities influence the availability of toxic chemicals.
CHARACTER OF BED SEDIMENTS
Because of the close association between metals and sediment, the
character of bottom sediment (including its texture, water content, carbon
and sulphur content), and sedimentation rates were determined in detail
(Kerhin et al. unpublished, Byrne et al. 1982, Carron 1979).
Information about the surface sediments was derived from more than 4000
samples collected on a 1.0 to 1.4 Km grid. Grain size of the sand fraction
was analyzed by a Rapid Sediment Analyzer, and the clay and silt fractions
were analyzed by settling and pippette withdrawal and a Coulter Electronic
Counter. Total carbon and sulfur were analyzed in a LEGO induction furnace
equipped with a gasometric carbon analyzer and an automatic titrater.
Water content was determined gravimetrically by weight loss on drying.
Texture
Sediment texture is characterized by its particle size, with sand the
largest and clay the smallest component. Bay sediments are differentiated
into 10 classes according to the percentages of sand (0.063-2mm), silt
(0.004-0.063 mm), and clay (0.0006-0.004 mm), following Shepard (1954). Of
the three end members, sand covers 57.4 percent of the total Bay surface
area; silt and clay less than 2.2 percent, whereas the rest of the area
consists of mixtures of sand, silt, and clay. Of the total sand area (3600
Km2), 60 percent lies in Virginia. Sand, together with mixtures of sand,
silty-clay, and sandy-silt types, cover 85 percent of the total Bay area,
with nearly all the silty clay in Maryland and most silty sand in Virginia.
The distribution of sediment types in the Bay is controlled by the kind
of material supplied and by the processes at the site of deposition. In
the northern Bay, with the exception of the Susquehanna Flats, the
predominate sediment type, silty clay, accumulates in the vicinity of a
potential source, the Susquehanna River. As the Bay becomes wider seaward
and the relative influence of river-derived sediment decreases, sand and
clay eroded from banks and shores are the most abundant sediment. Sand
accumulates in more energetic zones, for example, on shoals less than about
six meters, and close to its shore source. Silty clay, by contrast,
resides in deep water greater than about 10 meters, a less energetic zone
of inhibited wave stirring on the bed. This fine-grained sediment includes
river-borne as well as marine material, shore sediment, and some skeletal
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material produced in the central Bay itself. The basic pattern of sand on
the shoals and silty clay at greater depths is interrupted by patches of
mixed sediment, silty sand, clayey sand, and sand-silt-clay. A linear zone
of clay at intermediate depths along the western side, between the South
River and the Potomac represents a terrace exposure of old Coastal Plain
formations. Similarly, a large zone of sand on shoals along the eastern
side, between Bloodsworth-Smith and Tangier Islands, is probably relic
sediment.
Sediments of the southern Bay are distinctly coarser than elsewhere.
Silt predominates over clay and, therefore, zones of fine sediment in deep
water are clayey-silt or sandy-silt. Sand resides on shoals less than 12
meters and in channels of the Bay entrance. Locally, deep channels greater
than 20 meters that are scoured by currents are floored by coarse sand.
Water Content
Sediments with high clay and silt content have a correspondingly high
water content and thus, potentially high toxicant content. The mean water
content of surface samples expressed as percent of wet sediment by weight,
range from 16 to 83 percent for Maryland (Kerhin et al. unpublished) and
from 13 to 75 percent for Virginia (Byrne et al. unpublished). The mean of
all samples in Maryland is 47.4 percent and 30 percent for Virginia. A
plot of water content versus mud (clay and silt) content for Virginia
sediments is shown in Figure 20. This graph shows a linear trend whereby
water content increases with increasing mud content. A similar trend was
revealed for Maryland except for clay samples from the relic terrace zone
of the upper middle Bay, an area with relatively less water content for a
given clay content. The high water content of fine sediment (greater than
about 64 percent dry weight or equivalent to a density of 1.30 g/cnr*)
defines fluid mud that is a sub-reservoir for toxicants.
Carbon and Sulfur
Organic carbon and sulfur affect the fate of toxicants in sediments by
determining the redox state of the sediments after deposition. When
organic matter and sulfate of seawater is reduced, hydrogen sulfide (^S)
is produced, and metal sulfides (as Fe2SO^) are formed and concentrated
in the sediment. Thus, they are more available to biota.
Organic carbon in bed sediments averages 2.2 percent dry weight for
Maryland and 1.0 percent for Virginia. The bulk analyses of organic carbon
include organic matter of plant and animal tissues as well as skeletal
parts. Isolated high values reaching 10 percent in the northern Bay are
attributed in part to- bituminous coal particles. The organic carbon
content shows a preference for fine sediment (Byrne et al. unpublished).
Regression analyses indicate strongest associations with clay fractions.
Consequently, organic carbon content is higher (greater than three percent)
in the deep central Bay, where fine sediment accumulates, than in the
nearshore zones of sandy sediment. Inner parts of tributary embayments
like Mobjack Bay and Pocomoke Sound contain more than three percent organic
carbon content. The distributions of organic carbon content reveal two
main sources: the Susquehanna River for the northern Bay and primary
production for the central Bay. Mid-Bay organic carbon levels are the
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Relationship of percent water content to percent mud
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result of high biological activity (primary production) in this area. The
high productivity levels produce elevated carbon concentrations in the
water, ultimately causing high levels of detritus (organic matter
containing high organic carbon content) to be deposited and mixed with
bottom sediments. The Susquehanna River contains high carbon levels from
natural detrital matter (leaves, humus, fecal material, etc.), pollution
sources (such as POTWs), and other natural and anthropogenic carbon sources
in this drainage basin.
The bulk analyses of sulfur measure the total reduced sulfur in the
form of sulfide and metal compounds, organic sulfides, and sulfate residues
of interstitial waters. Sulfur content of northern Bay sediments is
relatively low, less than 0.5 percent for most samples (Kerhin et al.
1982), whereas the middle Bay has one to two percent. Anomalously high
values found in the main channel off the Choptank River are believed to be
caused by the flux of sulfur out of nearby or underlying Miocene sediments
(Kerhin et al. 1982). This is indicated by the interstitial water
chemistry that exhibits positive down-core sulfide fluxes. Sulfur content
of samples from Virginia is generally less than 0.5 percent except for deep
zones south of the Potomac River mouth.
Sulfur in the sediments is derived from two main sources, seawater and
decomposition of proteins in organic detritus. Relatively high sulfur
content of middle Bay sediments is probably derived from landward-moving
oceanic water as well as by deposition of phytoplankton degradation
products from near-surface water. Sulfur content increases with organic
carbon content in most Bay samples except the northern Bay which has
relative low sulfur content and high organic carbon. This relation probaby
relates to a terrigenous influence of waste from the Susquehanna River.
Patterns of Sedimentation
Changes in water depth of the Bay were established by comparing depth
soundings on old charts. These changes relate to sediment deposition and
erosion. Charts of Virginia provided good coverage between 1850-1860 and
1950-1960, but in Maryland some were surveyed after 1900, and the record of
depth changes spans 30 years (Carron 1979, Byrne et al. 1982, Kerhin et al.
1982) .
Charts of the northern Bay generally show that shoaling areas
(long-term filling in greater than 0.5 meters per century) exceed deepening
areas. Changes greater than 2.5 meters per century are recorded locally in
the channel near Tolchester and off Kent Island, Maryland (Figure 21). As
the channel deepens farther seaward, high shoaling ("/>2.5 meters per
century) occurs locally on the channel floor of the upper and lowe'.r middle
Bay. The deepest holes of the channel leading through the central Bay are
sites of depth increase or erosion, in excess of two meters per century.
Farther seaward, erosional zones are also recorded in deeper parts of the
main channel near Cape Charles and in the north-entrance channels to the
Bay.
Zones flanking the main channel display many variations that relate to
bathymetry and geology as well as to modern sedimentary processes. For
example, inner parts of marginal shoals are deepening, an indication of
erosion, but outer (channel-ward) parts show no change or slight shoaling.
In a general way, the change from deepening to shoaling relates to the
concept of erosion of a marine shoreline as it approaches adjustment to
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KEY
[[] >80% SILT a CLAY
•»>l.0m SHOALING PER
Figure 21. Sedimentation zones in areas of fine sediment, greater
than 40 percent clay, with greater than 1.0 m of shoaling
per 100 years, in the Bay proper. Data from Byrne et al.
1982 and Kerhin et al. (1982).
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modern wave processes. The material eroded from the shore or inner
shallows must be transported either laterally or channel-ward where it is
deposited in deep, less energetic zones along the adjacent channel. The
maximum shoaling rate in Virginia occurs in water depths of eight to 12
meters. For example, the clay terrace off Calvert County is largely
erosional. It contains shoaling patches of sand along nearshore parts,
suggesting offshore transport of eroded shore sand. Variable patterns on
the "sand shield" around Tangier and Smith Islands, either slight deepening
or shoaling in depths less than seven meters, indicate the constant
reworking of sediments by wave action, local shoreline sources of sediment,
migration of longshore bars, and relic sedimentary features. Other areas,
like the steep eastern side of the main channel south of Core Point, have
alternating patterns of shoaling and deepening that suggest slumping of the
channel wall. This is confirmed by sub-bottom profiles that show slump
scars at the slope break of the eastern channel wall and multiple sediment
layers on the nearby channel floor.
The Chesapeake entrance and Bay floor, extending landward about 40
kilometers, is predominately shoaling (Figure 21). Most deposition occurs
on elongate shoals; some occurs on flanks of the large Horseshoe Shoal, the
main Chesapeake channel floor, and the lower part of old Plantation Flats.
Most of the shoaling material is fine to very fine sand, probably derived
from the Bay entrance on adjacent shores and inner shelf, and transported
landward by the net residual bottom flow.
Toxicants may be expected to accumulate in areas of fine sediment
shoaling. The rate of toxicant accumulation will vary from place to place
in proportion to the shoaling rate (Figure 21). By contrast, deep channels
where erosion is active, are poor places to dump waste materials because
the currents would remove them. Areas in which the channel is stable or
shoaling are the best sites for disposing waste materials.
BENTHIC ORGANISMS
Benthic organisms act with physical processes to either enhance or
inhibit movement of toxic material. They can redistribute dissolved
toxicants in interstitial water or mix contaminated sediment within the
bed, as well as between the bed and overlying water. Through their feeding
and burrowing activities, they can bury new surface sediment or expose
older deposits. At the same time, their activity can stabilize surface
sediments through binding or tube building. On the other hand, they can
mobilize sediment by decreasing compaction and increasing water content.
By feeding and filtering suspended sediment and by excretion, they produce
fecal material and, in turn, promote sedimentation.
Character of Benthic Fauna
The distribution of benthic organisms in Chesapake Bay has been
documented in a number of studies (Boesch 1977a, 1977b; Holland et al.
1977; and Loi and Wilson 1979), most of which indicate that both physical
(salinity, substrate type, depth) and biological (competition and
predation) factors influence the distribution and abundance of the
macrobenthos. The wide range of habitats sampled in this study affords the
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opportunity to make generalizations concerning species distribution on a
Bay-wide basis. To avoid the confounding effects of seasonality on
community structure, fall 1978 and summer 1979 collections were considered
separately in a numerical classification analysis (Diaz and Schaffner 1981,
Reihnarz and O'Connell 1981).
Community Composition
Of the animals sampled in the Bay, polychaete annelids were the most
abundant and diverse taxonomic group, consisting of 23,797 individuals and
95 species. Crustaceans were second in abundance and diversity with 10,427
individuals and 48 species, and molluscs were third with 5,088 individuals
and 43 species. Miscellaneous groups were represented by 310 individuals
and 17 species.
Although the number of species did not change drastically from fall
1978 to summer 1979, a great disparity existed between the number of
individuals and the relative composition of fauna collected. Some of this
disparity is explained by an increase in the percentage of muddy stations
sampled in the summer relative to the fall. More importantly, summer
collections, particularly in the lower Bay, contained large numbers of
juvenile polychaetes that were presumably recruited to the sediments during
the spring. Low abundances in fall collections may result from the heavy
predation pressure, by blue crabs and fish, exerted on these populations
throughout the summer (Virnstein 1977).
Species Diversity
Mud habitats were generally less diverse and had fewer species than
sand or mixed-sediment habitats. In some cases, these results related to
the fact that stations were located in deep channels or sound areas where
periodic oxygen depletion resulted in a depauperate fauna (Diaz and
Schaffner 1981, Reinharz and O'Connell 1981).
Vertical Distribution
The majority of macrobenthic organisms, in all salinity regimes and
sediment types, were found in the upper 10 centemeters of the sediment
column. Generally, mixed or sandy sediments had the greatest percentage of
deep-living organisms. Most of the organisms below 10 centimeters are
annelids.
Bioturbation
Evidence from both the vertical distribution studies and x-radiography
suggests that nearly all of the benthic communities in the Bay have the
potential to move and mix sediments, which in turn can affect the fate and
distribution of sediment-bound toxicants. The modifications of physical
structure in sediments by organisms (bioturbation) fall into three
categories: (1) the construction of tubes as dwelling structures, (2) the
abandonment and subsequent filling-in of old tubes, and (3) general
sediment disturbance and mixing from locomotion. Analyses of the degree of
bioturbation'as estimated from x-radiography of box cores indicate that
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levels of bioturbation and types of biogenic structures vary depending on
both salinity regime and sediment type (see Reinharz et al. 1980, Nilson et
al. 1980).
Sandy habitats in the Bay are generally restricted to the head and
mouth of the Bay as well as to some areas along the eastern shore.
Physical structures preserved in these regions include cross-bedding
patterns and ripple lamination. In shallow, high energy regions of the
upper Bay, some of these structures have been completely disrupted because
of wave action. Sands in the lower Bay generally have a uniform
bioturbated sediment fabric, reflecting movement and mixing by communities
composed of a highly mobile fauna.
Mud habitats are most abundant in the lower salinity regimes of the
Bay, north of the Rappahannock River. Physical structures dominate the
muddy sediments of deep channels and holes at the mouths of major rivers.
Stressful fluid mud substrate and periodic summer anoxia allow only the
temporary settling of opportunistic species.
Muds in shallower regions are less likely to suffer anoxic conditions
and have a more diverse fauna for mixing sediments. In all areas of the
Bay, biogenic structural diversity is greatest in shallow mud habitats.
Bay-wide patterns in degree of bioturbation, based on x-rays of
sediment cores, are summarized in Figure 22. Sediments are highly
bioturbated (90-100 percent) throughout most of the Bay. Areas where
bioturbation is low include the uppermost oligohaline reaches of the Bay,
deep channels, sounds, and river mouths that are presumably subjected to
periodic oxygen depletion and often characterized by fluid mud substrate.
Biological Sediment Mixing and Fate of Toxicants
Evidence from both the vertical distribution studies and x-radiography
suggests that nearly all of the benthic communities in the Bay have the
potential to move and mix sediments and, in turn, influence the fate and
distribution of sediment-bound toxicants. Several studies (Rhoads 1963,
Gordon 1966) have measured particle mixing rates of common marine
invertebrates of shallow-water North Atlantic habitats and have found them
to exceed annual sedimentation rates. Depending on local sedimentation
rates, sediment-bound toxicants may be retained in the upper sediment
layers as a result of biological activities.
Areas of high sedimentation rate (generally in the oligohaline salinity
regime of the upper Bay [Figure 21] and in some channel areas) were
generally found to have low levels of bioturbation. Thus, the fate of
sediment-bound toxicants in these areas would probably be primarily
controlled by non-biological physical factors such as storms. The fate of
toxic materials in the mud habitats of the central and lower Bay, where
bioturbation averages greater than 90 percent, would probably be influenced
by biological mixing. The probability for retention of toxicants in
surface-sediment layers in these habitats seems high because of the
turnover of sediments by animals.
The effect of bioturbation on the vertical distribution of heavy metals
in the sediment is revealed by depth distribution of radioactive lead.
This isotope, 210 Pb, is delivered uniformly to the Bay from atmospheric
sources. Once in the sediments, its concentration is proportional to the
rate of sedimentation and time because it radioactively decays. The deeper
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77° 30'
38°
45' "
36°;
45'
PERCENT
BIOTURBATION
Fall
75° 30'
38°
45'
36°
45'
Figure 22. Distribution of percent bioturbation in sediments, fall
1978. Data from Diaz and Schaffner (1981), Reinharz and
O'Connell (1981).
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the sediment, the less 210pfc (Helz et al. 1981). This is found to be the
case in areas where there is little or no bioturbation; for example, in the
deep muddy channels of the middle Bay. However, in areas of high
bioturbation there is a zone of uniform 210pt, concentration that
corresponds to a biologically active zone where animals are mixing the
sediments. Such areas were found in the upper and lower Bay where
bioturbation caused mixing of sediments down to levels equivalent to 50
years of deposition. Therefore, in these areas toxicants are not likely to
be buried.
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SECTION 6
TOXIC SUBSTANCES AND BIOTA
An important question remaining in the GBP's investigation of toxic
substances is whether or not levels found in the Bay are harmful to the
many organisms living there. Although assessing the toxicity of metals and
organic compounds was not part of the CBP's original scope of work, a
limited evaluation of some metals and organic compounds was done. Further
assessment of the problem is presented in the third CBP final report,
Characterization of Chesapeake Bay (in progress). Specifically, the
characterization report includes discussion of levels of organic compounds
and metals in the water column and bed sediment, with a separate section on
Kepone in the James River.
This section addresses toxicity studies done during the research
portion of the Bay Program. It includes results from the CBP's exposure
assessment, experiments on histopathology of a native bivalve, and
bioassays of sediment and industrial effluent.
EXPOSURE ASSESSMENT
This discussion only addresses concentrations of toxic chemicals in the
water column measured during the CBP Toxic Substances Program, and for
which we have EPA criteria. The EPA Ambient Water Quality Criteria
Documents (EPA 1980) for priority pollutants, lists the criteria values.
These are expressed as the total recoverable concentration in the water
column, including dissolved, plus the potentially biologically available
fraction associated with suspended sediment. Assuming that any metal
attributable to enrichment is potentially biologically available to biota,
we can calculate the "available" concentration of that metal. Adding this
to the concentration of dissolved metal produces a reasonable, and probably
conservative, estimate of the total recoverable value.
Except for the Baltimore-Susquehanna River mouth zones, no metal
exceeded the EPA criteria in the Bay proper. Above Baltimore, several
stations barely exceeded the 24-hour average (chronic) criteria for Cd or
Cu. The criteria violated are based on subtle chronic effects of sensitive
species, the impact of which is not understood, and the calculated
concentrations exceeded these criteria only marginally. These violations
alone do not necessarily imply a serious ecological impact. Additionally,
there is some evidence that organisms can acclimate to toxic substances,
thereby lowering their sensitivity to those toxicants. On the other hand,
there may be species that are more sensitive than the species tested. In
addition, synergistic interactions may greatly increase the toxicity of a
pollutant, thereby affecting the biota even at sub-criteria levels.
Although this assessment does not show immediate ecological impacts,
the toxicity of some Bay sediment (see section on Sediment Bioassays) and
the proximity of metal concentrations to EPA criteria values (recommended
levels for water) indicate that north of Baltimore the Bay may border on
toxic impacts. Additional loadings of toxic substances to these waters
may, therefore, prove harmful to the biota.
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TOXICITY STUDIES
Histopathology
Diaz et al. (1981) conducted preliminary studies on populations of the
bivalve, Macoma balthica, to determine potential toxic effects. [See
"Characterization of Chesapeake Bay" in progress for more complete
analyses.] Macoma balthica is an infaunal species that burrows to 30
centimeters deep in soft mud. Although not a commercial species, Macoma
was selected because it has varied feeding habits in both surface deposits
and suspended material, and it is ubiquitous. Seven hundred and forty
clams were analyzed for abnormalities from relatively contaminated sites of
the Patapsco and Elizabeth Rivers and from relatively uncontaminated sites
of the Rhode and Ware Rivers. Of the 740 clams examined, only 26
pathogenic cases, or 3.5 percent, were found (Table 12). No statistical
relationship is evident between the pathogenic conditions and the river
system in which the clams reside, indicating that the data do not reveal
any adverse effects of sediment-associated contaminates.
Sediment Bioassays
Since many potential toxicants accumulate in the sediments at
concentrations higher than in the water column, preliminary bioassays were
performed on sediment from 70 sites throughout the Bay and selected
tributaries including the Patapsco and Elizabeth Rivers. The infaunal
amphipod Repoynius abronius, a species considered sensitive to sediment
contamination, was collected from relatively uncontaminated sediment and
water from Oregon. Repoynius abronius was placed in test sediment from the
Bay, and in the relatively uncontaminated sediment for control, at the EPA
Marine Science Center, Newport, Oregon. The samples were split and run in
both quiet (non-stirred) and stirred, aerated, overlying water of 25 ppt
salinity. The stirring action was induced to release interstitial water
and obtain a common salinity in all samples. After ten days, the number of
survivors were recorded from sieved samples.
The highest mortalities, greater than 90 percent, occurred in stirred
and non-stirred samples from the upper reaches of the Patapsco and
Elizabeth tributaries and from the northern Bay, particularly in the zone
between Baltimore and the Susquehanna River mouth. As shown in sections
III and IV, sediments from this zone are generally more enriched in metals
and organic compounds than elsewhere. The results of these experiments
conclude that toxicants may cause experimental mortality.
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TABLE 12. SUMMARY OF HISTOLOGICAL ABNORMALITIES FOUND IN MACOMA BALTHICA
CLAMS FROM UPPER AND LOWER BAY TRIBUTARIES (DATA REPRESENT
NUMBER OF CLAMS WITH ABNORMALITIES; PARENTHESES INDICATE THE
PERCENT OF TOTAL FROM THE RIVER)
Total Clams
Examined
Upper Bay
Pa taps co River
Rhode River
Lower Bay
Elizabeth River
Ware River
Totals
404
189
83
64
740
Number
of Pathogenic Cases
Dermo
7(1
2(1
1(1
2(3
12
.73)
.06)
.21)
.12)
Bacteria
1(0.25)
1(0.53)
0(0.0)
0(0.0)
2
Glandular
Cysts
1(0.25)
5(2.65)
1(1.21)
5(7.81)
12
Total
9(2.23)
8(4.23)
2(2.41)
7(10.93)
26
Effluent Toxicity Tests
Of an estimated 5000 discharges in the Chesapeake region, approximately
1000 are considered to have the potential for discharging toxic material
based on criteria established by the National Enforcement Investigation
Center of the U.S. Environmental Protection Agency. As part of the CBP
Source Assessment Program, effluent from fifty of these dischargers was
sampled and characterized in terms of major chemical species (down to 1-10
ppm) and their potential toxic effect on biota as determined by bioassay
tests. The selections were based on industries with the highest potential
for toxicity (not known toxicity problems). The criteria for ranking the
industries were based on flow rate of effluent and expected concentration
of chemicals in the effluent. The bioassays were conducted to evaluate, or
indicate toxicity of the effluent. The dischargers from which effluent was
sampled during the Program are shown in Appendix E. This appendix also
shows the many different bioassays performed and the experimental results.
Values of results are expressed as percentages of diluted effluent that
caused death for various species tested. The EC50, LC5Q, [or SC2Q,
EC5Q (Effluent Concentration)] is the percentage of effluent that would
inhibit growth by 50 percent. LC50 (lethal concentration) is the
percentage of effluent that caused a 50 percent kill of the species.
SC20 is the percentage of the effluent that stimulated growth by 20
percent. Bioassays were performed on fish, several invertebrates,
bacteria, and seagrass. Table 13 shows the kinds of tests used.
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TABLE 13. TESTS USED FOR MEASURING POTENTIAL TOXICITY OF INDUSTRIAL
EFFLUENT
Organism Test
Fathead minnow 96 hr. LC50
Sheepshead minnow 96 hr. EC50
Daphnia sp. 48 hr. LC50
Mysid shrimp 96 hr. LC50
Thalassia sp. 3-wee'k EC50
Marine bacteria EC50 Microtox
Results: Bioassays of Fathead minnows and Sheepshead minnows were tested
at minimal, low, moderate, and high toxicity values (NT-75, 50-75, 25-49,
and 0-24 respectively, Appendix F). Twenty percent of the effluents
sampled exhibited moderate to high toxicity, whereas 80 percent exhibited
minimal to low.
Invertebrate bioassays of Daphnia and mysid shrimp were tested at
minimal, low, moderate, and high toxicity values, NT-75, 50-75, 25-49, and
0-24 respectively (Appendix G). With the results of these two bioassays
combined, approximately 30 percent of the effluents sampled indicated
moderate to high toxicity. In addition, the mysid shrimp appeared more
susceptible than the Daphnia to the toxic substances found in the effluents,
A Marine Bacteria Bioluminescence Bioassay indicates that 50 percent of
the effluent samples were moderate to highly toxic. However, a bioassay on
Thalassia (Sea Grass) displayed little or no effect from the effluents
(Appendix H).
Mutagenic and cytotoxic effects were tested by utilizing
Salmonella/microsomal (Ames Test) spot tests and plate incorporation assays
(not listed in Table 13). These were performed on filtrates and extracts of
10 effluent samples. No mutagenic response was observed in the pour-plate
assay with the particulate recovered from sample filtration (Appendix I).
A positive mutagenic response in sample A108 Filtrate I was observed using
the plate assay. The spot test of effluent sample A104 Filtrate I showed
an increase in revertants over the control, but no clear positive response.
The Chinese hamster ovary (CHO) mammalian cell cytotoxicity assays
showed that effluent samples from A105, A106, Al10 exhibited medium level
toxicity for the sample as received; A100 showed low toxicity in samples
A102, A103, A104, A106, A108, and Al10 (Appendix J). Acetone extracts of
the particulate showed low or very low toxicity ratings for samples A100,
A103, A106, A107, A108, and AllO. Samples A101 and A109 showed no toxicity
for any of the three types of sample.
In summary, effluent bioassays on fish, invertebrates, and bacteria
indicate that 20 to 50 percent of the effluents sampled had moderate to
high toxicity. A greater risk of toxicity in the Bay is generally
associated with high effluent toxicity.
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SECTION 7
CONCLUSIONS, INTERPRETATIONS, AND MANAGEMENT IMPLICATIONS
The following abbreviated statements are organized to review the key
observational findings (underlined) followed by an interpretation and
management implication(s).
METALS
1. The Bay receives metals from human and natural sources through rivers, the
atmosphere, and industry. The rivers are a dominant pathway for Cr, Cu, Fe,
and Zn; industry is a dominant source of Cd, and the atmosphere is a
significant pathway for Pb and Zn. Metal input to the main Bay is greatest
from the Susquehanna River.
Metal input from rivers is relatively high because of large contributions
from geologic weathering and soil erosion of fine sediment in the drainage
basins. Additionally, rivers supply metals from municipal and industrial
effluents and, indirectly, from atmospheric deposition on the drainage basin.
The Susquehanna River is a strong pathway because of its relatively large
water and sediment discharge.
The Susquehanna is the only river that discharges directly into the Bay.
Main tributaries, like the James and Potomac, discharge into estuaries that
entrap sediment and sediment-borne toxicants.
2. Bay water contains the metals, Mo and U, mainly in dissolved form (> 90
percent of total metal), and they positively and linearly correlate with
salinity. The metals Cd, Co, Cr, Cu, Ni, Pb, and Zn occur both in dissolved
and particulate form (between 10 and 90 percent are dissolved), whereas more
than 90 percent of the Fe, Mn, Sc, and Th occurs in particulate form.
Relatively high concentrations of Mo and U are probably controlled by
alkalinity of Bay water and by dilution of seawater with river inflow. The
concentrations of metals Cd, Co, Cr, Cu, Pb, Ni, and Zn are controlled by
complex interactions of chemical solubility, sediment adsorption, and
bioconcentration; Fe, Mn, Sc, and Th distributions are mainly a function of
sediment adsorption-precipitation reactions. Metals in dissolved form are
diluted, mixed, and flushed through the Bay and, therefore, their effects are
short-lived. Metals in particulate form, however, have a longer residence
time in the Bay and can build up to high concentrations through
bioaccumulation and sediment adsorption.
The relevant management practice is to monitor and control metals
discharge while taking into consideration the different solubilities,
bioavailability, and adsorption properties of the different metals. Through
consideration and understanding of these properties, one can better regulate
the type, amount, and location of allowed discharges. As an example,
dissolved metals are readily taken up by plankton, whereas particulate metals
are likely consumed by suspension feeders or benthic filter feeders. Adverse
effects, however, will vary with the chemistry of the metal and the response
of the organism to the metals.
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3. Concentrations o£ As, Cd, Cu, Hg, Ni, Pb , Sn, and Zn per gram of suspended
material are maximal in near-surface suspended material of the central Bay.
Enrichment factors range: Cd, 10-118; Cu, 12-27; Pb, 37-51; and Zn, 16-74.
The percentage of organic matter in this zone is generally higher than
elsewhere.
The association of a relatively high content of metals with organic matter
in the same zone suggests that biological activity is the proximal cause of
accumulation. The metals can be derived from multiple sources, natural or
anthropogenic.
Control of bioaccumulations can be affected by changes in water quality
that will reduce productivity. These changes include lower light, increased
turbidity, lower nutrient input, and reduced mixing. However, some biota,
such as phytoplankton, require certain metals, like Mn for photosynthesis.
Other metals such as cupric ions, with extreme reactivities, interfere with
uptake of essential metals. Because metals, sediments, and nutrients are
interrelated, they need to be managed together. Piecemeal management of
single components cannot succeed.
Most control measures have focused on near-field discharges and immediate
effects. There is a need to manage for subtle changes and "far-field"
effects. Processes leading to bioaccumulation and particle concentration in
the turbidity maximum need to be taken into account in any effective
management plan. Moreover, water, particulates, sediments, and biota should
be managed as a dynamic system in which trace metals are continually being
repart itioned.
4. Secondary maxima of Cd, Mn, Ni, Pb, Sn, and Zn concentrations per gram of
suspended material are found in near-surface water of the Bay off the Patapsco
River.
These secondary "hot spots" suggest that metals are derived in part from
the Patapsco River and Baltimore Harbor via near-surface currents or, for
another part, by periodic resuspension from old dredged material on the Bay
floor.
The relevant management practice is to stabilize potential sources of
contaminated sediment from the Harbor either by removing future dredged
material from the system or by stabilizing the natural sediment through
consolidation, dewatering, or grass cover.
5. Sediments from the northernmost part of the Bay floor are enriched
relative to average crustal shale in Cd, Co, Cu, Mn, Ni, Pb, and Zn by factors
of two to eight. Cd, Pb, and Zn are enriched throughout the main Bay by
factors of two to six relative to average shale.
The Susquehanna River is a distinctive primary source of metals in bed
sediments of the northernmost Bay. This is confirmed by similar enrichment
factors and similar metal-Fe ratios in the river and northern Bay. The metals
are sequestered in fine sediment and associated with river-borne organic
material. Since enrichment factors diminish markedly with distance iseaward
from Kent Island, contaminated sediment is probably not transported seaward of
the Patapsco mouth in quantity. This assumes diagenetic processes are not
contributing significantly to the seaward reduction of enrichment. Instead,
metals mainly accumulate in the turbidity maximum zone where suspended
sediment is trapped. Once deposited, the metals can be resolubilized and,
thus, released from contaminated sediment and potentially available to the
biota.
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Because the Bay system is complex, it requires a fairly sophisticated
input of technical information about the system being managed. It should be
managed with a scientific data base and a knowledge of processes affecting
behavior transport and fate of potential toxics. Therefore, effective
management decisions should be coupled to monitoring data and scientific
knowledge of processes.
The new information on distribution of enriched bed sediment provides data
with which to broadly classify potential dredged material. Such a
classification provides input for decisions on dredged spoil management — its
best use, disposal techniques, or dumping sites.
6. The Bay floor is a major sink for metals and organic compounds. More than
60 percent of the total input of Fe, Mn, Ni, Pb, and Zn is retained in the bed
sediments.
Bed sediments in the central and northern Bay are enriched with metals,
(Cu, Pb, Zn) to depths of 14 to 26 cm, representing about 60 to 90 years of
deposition. Metal enrichment reaches a peak between four and 18 cm (1930 and
1960) and diminishes toward the surface.
The enriched metal peaks in the northern Bay probably represent peak metal
loading from a dominant source, the Susquehanna. The influx was first felt in
the northern Bay and later in the central Bay. Zones of fast sedimentation
are sensitive to contamination. When metals are buried deeper than the zone
of active diagenesis, they may be effectively immobilized and thus unavailable
to biota.
Since sediments record long-term changes in metal loading, they can
provide an indication of future trends if the depositional flux is coupled to
the input flux. Whereas analyses of water samples from contaminated zones may
not detect some toxic chemicals in small amounts, sediments with toxic
substances that are strongly sorbed can build up to levels and thus be readily
detected.
7. Major transport pathways for metals follow either a hydrodynamic route or
a bioecologic route. The principal sinks for toxics are located in
near-source zones where fine sediment accumulates.
The hydrodynamic route through the northern Bay follows the pattern of
estuarine circulation; that is, seaward through the river and upper estuarine
layer, and landward through the lower layer. This route leads to entrapment
of contaminated sediment near the inner limit of salty water close to its
major source the Susquehanna River. Secondary sinks of accumulation occur in
less energetic zones: the central Bay axial basin and inner reaches and
mouths of tributaries that promote moderate to fast sedimentation and
accumulation of fine sediment.
8. More than 300 organic compounds were detected in Bay sediments. Most were
PNAs having anthropogenic sources, and many compounds are among EPA's priority
pollutants.
The organic compounds tend to associate with fine suspended material in
the water and accumulate on the Bay floor as the suspended material settles.
Because of their polarity, some organic compounds may occur in dissolved form,
but they are below the detection limit of most present-day instrumentation.
Significant concentrations of priority pollutants are cause for concern about
sources and effects on Bay ecology.
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9. Concentrations of organic compounds in bed sediment are greatest in the
northern Bay. Seaward from the Patapsco River, concentrations decrease to the
Potomac River mouth. In the southern Bay, concentrations near tributary
mouths are greater than elsewhere.
The Susquehanna River is a source of many organic compounds. The
compounds are likely supplied from pollution sources and atmospheric
deposition on the drainage basin, and they accumulate in the turbidity maximum
zone where fine sediment is trapped. Accumulation at tributary mouths relates
either to the accumulation of fine sediment or to scurces of contamination in
the tributaries.
If contaminates have distinctive point sources as industrial discharges
they should be controlled pursuant to Federal and state policy.
10. Concentrations of organic compounds are higher and more variable in the
Patapsco River than in the main Bay.
A Patapsco River source of organic compounds is indicated by the
distribution of concentrations that are high in landward parts of the river.
Additionally, they vary as the location of sources varies within the river.
Most PNAs, however, are widespread, mixed, and lack specific sources. Part of
the contaminated sediment is trapped within Baltimore Harbor and the Patapsco
River, but some escapes to the Bay. This is revealed by the occurrence of a
Patapsco derived compound, 6-phenylodecane, in the main Bay. Since
concentrations diminish seaward from the river mouth and down Bay, dispersion
of significant quantities is probably low.
11. More than 120 organic compounds were detected in oysters from the Bay.
The compounds, methyl esters, fatty acids, and ketones, were present in most
oysters, but PNA's were scarce.
The organic compounds in oysters may have a biogenic or natural origin.
Because the composition in oysters differs from sediments, and has fewer PNAs,
oysters are of lesser importance for general monitoring of organic compounds
in the Bay. The oyster, however, can be useful for monitoring specific PNA
compounds as benzo(a)pyyrene which is a suggested carcinogenic compound or an
oyster metabolite.
12. Bay-wide bioassays reveal that sediments from inner reaches of the
Patapsco and Elizabeth Rivers and from the northern-most Bay have a higher
toxicity than elsewhere.
Effluent bioassays of fish, invertebrates, and bacteria indicate that 20
to 50 percent of the effluents sampled had moderate to high toxicity.
The occurrence of relatively high toxicity and low survival rate generally
relates to zones of high metal content and high organic compounds in bed
sediments close to major sources. We speculate that high sediment toxicity is
produced by a combination of high metal content and high loads of org,anic
compounds. It remains to be determined what acceptable levels of sediment
pollution the Bay resources can endure. Generally, a greater risk of toxicity
in the Bay is associated with high effluent toxicity, unless organisms can
adapt to certain concentration levels.
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SECTION 8
RESEARCH NEEDS
Chesapeake Bay is a very complex estuarine system, and our knowledge of
hydrodynamic, sedimentological, and bio-ecological processes is limited.
The data gained in this study point to gaps in our knowledge that deserve
future research.
1. Inasmuch as results show that some sediment-associated toxicants occur
outside major harbors (the Patapsco River and Hampton Roads) and seaward of
Kent Island, it remains to be determined how much material presently
escapes the harbors and northern-most Bay. Is the contaminated sediment
outside the harbors a product of disposal activities or presently escaping
near-source contamination zones? Do harbor contaminates contribute to
up-Bay, or up-tributary, contamination zones by landward transport?
2. Since results show maximal pa-rticulate concentrations of abnormally
high Cd, Cu, Pb, and Zn in surface waters of the central Bay, a location
far from major sources, it remains to be determined how they get there.
The distribution of metal in various states (dissolved, colloidal,
particulate; organic or inorganic) must be determined together to
demonstrate how the metals are partitioned on a seasonal basis. We must
learn if metals stimulate production of organic matter like plankton or, by
contrast, affect the health of organisms in the central Bay. And, does
bio-accumulation and turnover make the metals more or less mobile?
3. Whereas the present research deals mainly with metals and organic
compounds supplied to the Bay at more or less normal conditions, episodic
events may control their distribution. Floods, hurricanes, and storms can
produce exceptional conditions for massive resuspension and dispersal of
sediment-borne metals. Observations are needed to study the impact of
short-term events with respect to the following: How much sediment and
toxicant are released or mobilized by an event compared to average
conditions? What are the corresponding effects on marine resources? How
long does it take to recover, decontaminate, or come to a new chemical
equilibrium?
4. Synthesis results reveal that atmospheric inputs of potentially toxic
material can compose a significant portion of the total toxic load. It
appears that atmospheric inputs are relatively important in areas far from
contamination sources, especially for metals like Cd, Cu, and Pb, and the
organic compound like PNAs. We must determine, in detail, the magnitude
and extent of atmospheric inputs relative to water-borne inputs. With
increasing use of fossil fuels, are atmospheric imputs increasing the total
toxicant input to the Bay despite controls on water-borne inputs? There is
a need to determine if atmospheric inputs are from distant sources and
homogeneous, affecting the entire Bay. Because atmospheric dry and wetfall
collects on salt marshes, and the flux can be recorded by marsh deposits,
attention should focus on high marsh sediments that reflect atmospheric
influence. The historical record combined with monitoring should provide
an early warning of increasing anthropogenic inputs from the atmosphere.
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5. To ascertain the validity of data acquired, future efforts should
account for variability of field sampling through a rigorous statistical
sampling plan. This study reveals that the concentrations of metals and
organic compounds can vary widely with location, especially in suspended
material. Verifying results are needed to account for short-term tidal
variations; fortnightly, neap-spring changes; and seasonal as well as
non-periodic changes of episodic events.
6. Chesapeake Bay has, at least on one occasion, been the recipient of the
direct disposal of pesticides like Kepone (Huggett et al. 1980).
Fortunately, the quantities were small and the assimilation capacity large
enough so that no adverse effects on the biota were noted. The disposal of
such compounds in this manner was, and is, illegal. This indicates that
laws alone are insufficient to protect the Bay and that chemical monitoring
is necessary. The chemical monitoring of effluents and sediments collected
near outfalls shows that more effort of this type is needed to prevent
future "Kepone episodes" (Bieri et al. 1981). Key sinks in the Bay also
require monitoring. Because some dissolved toxicants are difficult to
detect in near-source zones, monitoring of peripheral sediment sinks having
fast deposition can provide an early warning of increased loading. (For
details see separate Monitoring Recommendations, Flemmer et al.,
unpublished)
In this study over 300 organic compounds were analyzed, but results
indicate that "thousands of other compounds are present at low
concentrations." Therefore, monitoring needs to account for a wide
compositional range of organic compounds having low concentrations. These
data are needed to establish valid baselines as well as to detect anomalous
concentrations of pollutants before they build up. To guide State water
pollution control authorities, an effluent toxicity characterization
program is needed to screen industrial effluents for toxic chemicals and to
determine their degree of toxicity, both acute and chronic.
7. Additional toxicity data are needed to evaluate impacts on the Bay's
living resources and to formulate diagnostic criteria that are generally
accepted. Little is known about the toxicity of individual components, and
less is known about the toxicity of populations or communities. .Host
bioassays have examined acute effects; little is known about long-term
chronic effects. Moreover, the Bay ecosystem is complex and dynamic,
involving the interactions of physio-chemical parameters and biological
components with time. We need to know if the toxicants found in the Bay
are biologically available. Once organisms are exposed to toxicants, can
they adapt to certain concentration levels? Most bioconcentrations have
been treated as static levels in tissues of organisms. Some organisms,
however, accumulate toxicants quickly, whereas others that metabolize
slowly can accumulate toxicants slowly but to high levels. Therefore,
bioaccumulation needs to be examined as a dynamic equilbrium determined by
the metabolism rate.
8. A major problem for future research is determining the relative
capacities of different parts of the Bay to assimilate toxicants. Although
a numerical model can predict the distribution and resulting concentration
of a given input and its residence time, toxicants are subject to
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transformation and building up through biological and sedimentological
processes. A single concentration level value applied to the entire Bay is
not a universally valid criteria for control because it does not take into
account the characteristics of the receiving segment. We need to know the
relationship between the contaminate concentrations and their toxic effect
on the biota in each receiving segment. This requires much better data and
a greater understanding than now exists. In particular, we need to
overcome the difficulties of: (l) making accurate measurements of diverse
and potentially toxic compounds at very low concentrations; (2) measuring
the toxicity effects of chemicals on organisms; and (3) making valid
interpretations by comparing laboratory results and field observations.
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APPENDIX B
SUMMARY OF DATA SOUCES FOR TRACE METALS IN
CHESAPEAKE BAY AND TRIBUTARIES
Area
James, York,
& Rappahannock
Rivers
Potomac River
James River
Northern Bay
(1974)
Patapsco River
& Balto. Harbor
Northern Bay
(1974)
Northern Bay
Northern Bay
& Susquehanna
Central Bay
Back River
Northern Bay
Rappahannock
River
Reference
Huggett et al.
(1971)
Pheiffer (1972)
Huggett
& Bender (1975)
Owens et al.
Villa &
Johnson (1974)
Sommer & Pyzik
Cronin
(1974)
Carpenter
Matisoff (1975)
Helz et al.
(1975)
Helz (1975)
Huggett et al.
(1975)
Metals
Hg
Ag,Ba,Cd,Co,Cr,
Cu,Fe,Li,Mn,Ni,
Pb,Sr,V,Zn
Cu,Zn
B,Ba,Ce,Cr,Mn,V
Zn,Zr
Cd,CrsCu,Hg,Mn,Ni
Pb.Zn
Co,Cu,Ni,Pb,V
Fe,Mn,Zn
Co,Cr,Cu,Fe,Mn,Ni,
(1975)
Zn.Cd.Pb
Fe.Mn
Cd,Cu,Fe,Mn,Pb,Zn
CdsCo,Cr,Cu,Pb,Fe
Mn.Ni, Zn
Cu.Zn
362
THE
Component
Bed Sediments
Bed Sediments
Oysters & Bed
Sediments
Bed Sediments
Bed Sediments
Bed Sediments
Bed Sediments
Dissolved and
Suspended
Sediment
Interstitial
Sediment &
Water
Bed Sediments
Bed Sediments
Bed Sediments
-------
Area
Northern Bay
Rhode River
Elizabeth
River
Northern Bay
Patapsco River
& Balto.Harbor
Northern Bay
Northern Bay
Northern Bay
(APPENDIX B,
Reference
Matisoff et al.
(1975)
Frazier
(1976)
Johnson &
Villa (1976)
CONTINUED)
Metals
Cd,Cu,Fe,Mn,Zn
Patuxent River Ferri (1977)
Schubel and
Hirschberg (1977)
EPA-440/5-77-015A
Goldberg et al.
(1978)
Eaton et al.
(1979)
Eaton (1980)
Cd,Co,Cr,Cu,Fe,
Mn,Ni,Pb,Zn
Cr,Cu,Ni,Pb
As,Cd,Cr,Cu,Hg,
Mn,Ni,Pb,Zn
Fe,Mn,Ni,Pb,Zn,V
Mn
Fe,Ti,Zn
Component
Bed Sediments
Cd,Cr,Cu,Hg,Pb,Zn Bed Sediments
Bed Sediments
Bed Sediments
Bed Sediments
Bed Sediments
Dissolved Bed
Sediments
Suspended
Sediments
363
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APPENDIX C.
SUMMARY OF DATA FOR ORGANIC CHEMICALS
IN CHESAPEAKE BAY AND TRIBUTARIES
Area
Chesapeake Bay &
Selected Tribs.
James,
Rappahannock,
& Potomac Rivers
Chester River
Northern Bay
Cape Charles,
Lynnhaven Bay
James River
James River
Reference
Munson &
Huggett (1972)
Barnard (1971)
Munson (1973)
Munson (1975)
Goldberg et al.
(1978)
U.S. EPA (1978)
Huggett (1980)
Organic Chemicals
DDT compounds
DDT compounds
PCBs,
Chloradane,
DDT
PCBs
Chloradane
DDT
PCBs
DDT compounds
PNAs, DAHs
Kepone
Kepone
Component
Oysters
Fish
Sediments
Shellfish
Sediments
Shellfish
Zooplankton
Oysters
Soil, water,
Bed sediments
Bed sediments
& biota
James River
James River
James River
Huggett &
Bender (1980)
Lunsford (1980)
Nichols &
Gutshall (1981)
Kepone
Kepone
Ke pone
Biota, Bed
sediments ,
Suspended
sediments
Bed sediments
Bed sediments
364
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APPENDIX F
RESULTS OF FISH BIOASSAYS FOR EFFLUENT SAMPLES BY SPECIES
Toxicity Index
Minimal
75-NT2*
Low
Moderate
25-49
High
0-24
Totals
Fathead Minnow
14
3
2
3
22
Sheepshead Minnow Totals
3 17
3
2
3
3 25
^9
*• NT is not toxic; a 100% effluent concentration did not kill 50% of the
test species.
APPENDIX G.
RESULTS OF INVERTEBRATE BIOASSAYS FOR EFFLUENT SAMPLES BY SPECIES
Toxicity Index
Minimal
75-NT2*
Low
50-74
Moderate
25-49
High
Totals
Daphnia (Magna)
9
2
2
2
15
Mys id Shrimp
18
8
4
11
41
Total
27
10
6
_13
56
*NT2 is not toxic; a 100% effluent concentration did not kill at least
50% of the test species.
372
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APPENDIX H.
RESULTS OF BACTERIAL AND GRASS BIOASSAYS
Toxicity Index Microtox (Marine Bacteria) Thalassia (Sea Grass)
Minimal 5 6
75-NT
Low 1
50-74
Moderate 1
25-49
High __5
12 6
373
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APPENDIX I.
RESULTS OF SALMONELLA/MICROSOMAL ASSAYS FOR MUTOGENICITY OF
CHESAPEAKE BAY EFFLUENT SAMPLES
Plant Number/Sample
Filtrate I*
A101
A102
A103
A104
A106
A107
A108
A109
Filtrate II**
A100
A105
A110
Particulate *** - Acetone
A100
A101
A102
A103
A104
A105
A106
A107
A108
A109
A110
Spot Test
(-) negative
(-) negative
(-) negative
(-) inconclusive
(-) negative
(-) negative
(-) negative
(-) negative
0
-
-
Extract
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Not performed
Plate Incorporation
(-) negative
(-) negative
(-) negative
(-) negative
(-) negative
(-) negative
(+) positive
(-) negative
_
-
-
negative
negative
negative
negative
negative
negative
negative
negative
negative
negative
negative
* Filtrate I - Filtrate from initial filtering through a .45 u filter.
** Filtrate II - Filtrate I passed through a 0.2 u filter.
*** Particulate - Material retained on polyester drain disc and a 5 u
teflon filter.
374
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APPENDIX J.
RESULTS OF MAMMALIAN CELL
CLONAL ACUTE CYTOTOXICITY ASSAY
Neat Effluents
Sterilized by
Filtered
Sterilized
Antibiotic Addition Effluents
Sample
Number
A100
A101
A102
A103
A104
A105
A106
A107
A108
A109
A110
EC50,a
pL/mL
150
ND
Ce
ND
ND
25
45
ND
C
C
55
Toxicity EC5Q Toxicity
rating pL/mL rating
LC NDd
ND
200 L
200 L
250 L
MS ND
M 200 L
ND
200
ND
M 200
Particulate
Extract, Acetone
Concentrate
EC5Q,bToxicity
pL/mL rat
600
ND
ND
700
ND
ND
300
650
700
ND
300
ing
L
VLf
L
VL
VL
L
aEffective concentration at 50% killing
Normalized to toxicity of particulate extracts recovered from 1,000 mL
of neat sample.
cLow, 60-600 pL/mL.
No toxicity found at highest concentration tested and with no
contamination.
eMicrobial contamination; toxicity not determined.
fVery low, 600pL/mL
SModerate, 6-60PL/mL
375
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PART IV
SUBMERGED AQUATIC VEGETATION
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Robert J. Orth
_ Kenneth A. Moore
• W. R. Boynton
K. L. Heck, Jr.
W. M. Kemp
J. C. Means
T. W. Jones
J. C. Stevenson
Richard L. Wetzel
Robin F. VanTine
Polly A. Penhale
Technical Coordinators
Walter Valentine
David Flemer
376
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INTRODUCTION
This part of the GBP's scientific synthesis summarizes and integrates
almost three years of research on the occurrence of submerged aquatic
vegetation (SAV) in Chesapeake Bay, the role and value of SAV in the
Chesapeake Bay ecosystem, and major factors controlling SAV's past and
future survival. The four chapters comstituting the SAV part draw on the
findings of over a dozen separate research projects, each of which has
produced a final report containing a detailed account of research design,
methods, and results. These projects are listed in Appendix A. In
addition to CBP-funded research, this part includes information from other
research as well as from personal communications.
The CBP included SAV as a critical research area because of its
ecological role and value, its precipitous decline during the 1970's, and
the urgent need to discover why the grasses were disappearing. The life
history of SAV and its decline in Chesapeake Bay have been fully presented
in a 1978 Summary of Literature on SAV in Chesapeake Bay (Stevenson and
Confer). The papers presented here seek to further clarify the SAV
problems presented in the 1978 Summary and to suggest reasons for its
decline.
Four features of SAV's role in the Bay — food source, habitat,
nutrient buffer, and sediment trap — illustrate its ecological
importance. As a food source, SAV had a partly documented, partly assumed
role in the ecology and economy of Chesapeake Bay. SAV is eaten by ducks,
geese, and some fish, and it contributes to the detritus-based food web.
SAV also provides habitat for many organisms—nurseries for juvenile stages
of some fish species; refuge for molting blue crabs, other invertebrates,
and certain fish species; a stable habitat for infauna; a substrate for
epiphytic plants and animals; and a habitat for all fauna subsisting
directly on SAV and its epiphytes, or the detritus derived from them.
Additionally, SAV was thought to buffer nutrients in the Bay by absorbing
nutrients from the water column during spring runoff and releasing them in
autumn as detritus. SAV was also considered to be a nutrient "pump,"
taking up nutrients from the sediment through its roots and releasing them
as detritus. Other presumed functions of SAV were the baffling of water
movement, causing sediment to settle to the bottom, and the binding of
sediment, helping to mediate shoreline erosion.
The most compelling evidence for the decline of SAV during the 1970's
is an upper-Bay annual summer submerged vegetation survey conducted by the
U.S. Fish and Wildlife Service and the Maryland Department of Natural
Resources and an aerial mapping survey of the lower Bay SAV conducted by
the Virginia Insitute of Marine Science (VIMS). The Maryland survey shows
that 28.5 percent of 640 sample stations had SAV in 1971, whereas only 21
percent had SAV in 1972, 10.5 percent in 1973, and 14.9 percent in 1974
(Kerwin et al. 1976). This survey covered the entire Maryland portion of
the Bay, except the Potomac River, making it by far the most extensive
survey available. The aerial survey of lower Bay SAV shows dramatic
declines in the Rappahannock, Piankatank, and York Rivers between 1971 and
1974 (Orth and Gordon 1975). The 1970"s decline was especially alarming
because it affected all areas and all species, though not all to the same
degree, something not observed in previous distribution shifts. The only
other documented major perturbations were the decimation of eelgrass
(Zostera marina) in the 1930's presumably caused by a disease organism and
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the outbreak of Eurasion milfoil (Myriophyllum spicatum) in the late 1950's
and early 1960's. These changes directly affected only one species.
In our search for reasons for the Bay-wide SAV decline, we assumed that
one or more fundamental properties of the Bay ecosystem were being
altered. Disease was ruled out because it probably would not have affected
all species. Point sources of pollution, although they may have been a
contributing cause, were probably not the direct underlying cause because
of their localized nature. We conjectured that herbicides from
agricultural runoff were directly harming SAV, that sediment loading was
increasing turbidity thereby decreasing the amount of light available to
SAV, and that nutrient loading to the system was stimulating the growth of
phytoplankton, which were further shading the SAV and competing for
nutrients. One of the disturbing features of these working hypotheses was
that they pointed to a gradual and fundamental change in the Bay, thought
to be brought about largely by the increased human activity associated with
a population growth of more than 100 percent in the Bay area during the
last 40 years.
Following the decision to include SAV as a study area in the CBP, a
Plan of Action that set forth the goals and objectives of the study was
developed. The study's ultimate goal was to develop a plan for managing
the Bay system to maintain SAV as a viable resource. To meet that goal, we
conducted basic research on the structure and function of SAV-based
ecosystems, including inventories of the biota and observations of ambient,
abiotic variables in SAV beds and at nearby sites that were devoid of SAV
but otherwise similar. In addition to observations of the natural
ecosystem, manipulative studies were designed in the field and laboratory
on system dynamics. These manipulative studies aimed at better
understanding the role and value of SAV and the factors controlling its
growth and survival. This latter information would elucidate cauises of the
recent decline in SAV, as well as the requirements for future survival.
Finally, interpretation of aerial photography and analysis of SAV seeds in
Bay bottom cores were to be used to investigate current and past
distribution and abundance of SAV. This information would put in
historical perspective the magnitude of the current decline and provide a
baseline against which to measure future changes.
The following four papers are organized around fundamental questions of
interest to someone charged with managing this valuable resource. The
first question is: Is there a problem concerning SAV in Chesapeake Bay?
To answer this, one first must show that there has been a decline in SAV
that is different in character or degree from natural fluctuations. The
first paper addresses this point. Second, one must show that SAV has some
value and that its loss will have negative ecological and economic
impacts: the subject of the second paper. If there is a problem, the next
question must be: What caused it? As stated above, we explored various
hypotheses about the decline. Separate papers (three and four) are devoted
to herbicides and light as they were thought to be the most likely causes.
A list of the detailed Management Questions and answers appears at the end
of the SAV synthesis.
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abiotic:
anoxia:
biotic:
copepod:
denitrification:
detritus:
dinof1age11ate:
fluvial:
halocline:
nonpoint source:
point source:
primary producitivity:
rotifer:
Secchi depth:
watershed:
Technical Glossary
Without life, inorganic.
Total deprivation of oxygen.
Of life, or caused by living organisms.
Small, sometimes parasitic, Crustacea living in either
salt or fresh water.
Single-celled organism, mainly marine and often with a
cellulose shell.
Accumulation of disintegrated material, or debris.
Single-celled organism, mainly marine and often with a
cellulose shell.
Of, found in, or produced by a river.
A level of marked change, especially increase, in the
salinity of seawater at a certain depth.
Source of a nutrient or other constituent coming from
diffuse areas such as pasture and forests, and
atmosphere.
Source of nutrients or other constituents coming from
a distinct source such as a pipe from a sewage
treatment plant.
The amount of organic matter made in a given time by
the autotrophic organisms in an ecosystem.
Microscopic invertebrate animal found mostly in fresh
waters, having one or more rings of cilia at the front
end to the body.
Depth at which a Secchi disk can be seen. The Secchi
disk is an instrument for measuring the light
attenuation of natural waters.
The area drained by a river or river system.
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TECHNICAL SYMBOLS
C
cm
CW
d
g
h
ha
kg
km
L
LAI
m
M
ug-at
uE
umoles
MLW
mm
NADPH2
nm
pMax
ppb
ppm
ppt
sec
y
Celsius
centimeter
carapace width
day
gram
hour
hectare
kilogram
kilometer-
liter
leaf area index
meter
molar
microgram atom
micro-Einstein
micro-moles
mean low water
milimeter
coenzyme reducing carbon dioxide
to sugar in photosynthesis
nanometer
maximum rate of photosynthesis
parts per billion
parts per million
parts per thousand
second
-- year
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DISTRIBUTION AND ABUNDANCE OF SUBMERGED AQUATIC
VEGETATION IN CHESAPEAKE BAY: A SCIENTIFIC SUMMARY
by
Robert J. Orth and Kenneth A. Moore
Virginia Institute of Marine Science
of the College of William and Mary
Gloucester Point, Virginia 23062
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CONTENTS
Figures 383
Tables 384
Sections
1. Introduction 385
2. Methods 387
3. Present Distribution 389
4. Past Distribution 394
Historical Trends (1700-1930) 394
Recent Past (1930-1980) 395
The Eelgrass Wasting Disease 1931-1932 395
The Milfoil Problem 1959-1965 395
The Bay-wide Problem 1960-1980 398
1965 400
1965-1970 400
1970-1975 403
1975-1980 412
5. The Atlantic Coast 415
6. Worldwide Patterns 417
7. Conclusions 419
Literature Cited 423
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FIGURES
Number Page
1 Map of Chesapeake Bay showing the lower, middle, and
upper zones
388
2 Map of the mouth of the East River and a portion of Mobjack Bay
showing changes in SAV distribution from 1974-1981 390
3 Location of regions impacted by Eurasian watermilfoil 397
4 Population fluctuations of watermilfoil compared to the
dominant native species 399
5 Distribution of SAV in Chesapeake Bay - 1965 401
6 Distribution of SAV in Chesapeake Bay - 1970 402
7 Distribution of SAV in Chesapeake Bay - 1975 404
8 Trends in SAV occurrence in the Maryland portion of
Chesapeake Bay 406
9 Trends in SAV occurrence in six areas in the middle Bay
zone 408
10 Changes in the distribution and abundance of SAV at the
Mumfort Island area in the York River 409
11 Trends in SAV coverage in the lower zone of Chesapeake
Bay 413
12 Distribution of SAV in Chesapeake Bay - 1980 414
13 Pattern of recent changes in the distribution of SAV in
Chesapeake Bay 420
14 Location of sections of the Bay with the greatest SAV decline. . 421
383
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TABLES
Number Page
1 Species Associations of SAV in Chesapeake Bay 386
2 Numbers of Hectares of Bottom Covered with SAV in
Chesapeake Bay, 1978 391
3 Numbers of Hectares of Bottom Covered with SAV in the
Lower Bay Zone, 1971-1980 392
4 Changes in Harvested Scallops, 1928-1981 396
5 Percent of Sampled Stations Containing SAV in the Maryland
Section of Chesapeake Bay . 405
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SECTION 1
INTRODUCTION
The Chesapeake Bay, with its extensive littoral zone and broad salinity
regime of 0 to 25 ppt, supports many different species of submerged aquatic
vegetation (SAV) (Anderson 1972, Stevenson and Confer 1978, Orth et al.
1979). Approximately ten species of submerged vascular plants are abundant
in the Bay, with another ten species occurring less frequently. In many
areas, more than one species is found in a particular bed of SAV because of
the similarity in the physiological tolerances of some species. Between
regions of the Bay, salinity appears to be the most important factor in
controlling the species composition of an individual bed of SAV (Stevenson
and Confer 1978), while sediment composition and light regime are important
factors in controlling the distribution of SAV within regions of the Bay.
All species, regardless of the salinity regime, are found in regions of the
Bay's littoral zone and are located in water less than two to three meters
deep (mean low water - MLW), primarily because of low levels of light that
occur below these depths (Wetzel et al. 1981).
Three associations of SAV can be described in Chesapeake Bay based on
their salinity tolerances as well as on their co-occurrence in mixed beds
of SAV (Table 1) (Orth et al. 1979, Stevenson and Confer 1978). The first
association, consisting of Najas guadalupensis (bushy pondweed),
Ceratophyllum demersum (coontail), Elodea canadensis (waterweed), and
Vallisneria americana (wildcelery), contains species that can tolerate
fresh to slightly brackish water and are found in the upper reaches of the
Bay and in the tidal freshwater areas of the Bay tributaries. The second
association, including Ruppia maritima (widgeon grass), Myriophyllum
spicatum (Eurasian watermilfoil), Potamogeton pectinatus (sago pondweed),
Potamogeton perfoliatus (redhead grass), Zannichellia palustris (horned
pondweed), and Vallisneria americana (wildcelery), is tolerant of slightly
higher salinities than the first group. This group is found in the middle
reaches of the Bay and its tributaries. The third group, consisting of
Zostera marina (eelgrass) and Ruppia maritima (widgeon grass), is tolerant
of the highest salinities in the Bay and is found in the lower sections of
the Bay and its tributaries.
Since 1978 SAV has been the subject of an intensive research program
funded by the U.S. Environmental Protection Agency's Chesapeake Bay Program
(EPA/CBP). SAV was determined to be a high priority area of research in
this program because of its high primary productivity; its important roles
in the Chesapeake Bay ecosystem — a food source for waterfowl, a habitat
and nursery area for many species of commercially important fish and
invertebrates, a shoreline erosion control mechanism, and a nutrient
buffer. Most importantly, research was focused on SAV because of the
dramatic, Bay-wide decline of these species in the late 1960's and 1970's.
385
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TABLE 1. SPECIES ASSOCIATIONS OF SAV IN CHESAPEAKE BAY AND ITS
TRIBUTARIES BASED ON THEIR SALINITY TOLERANCES AS WELL AS THEIR
CO-OCCURRENCE WITH OTHER SPECIES (COMMON NAME OF EACH SPECIES
GIVEN IN PARENTHESIS)
Group 1 Group 2 Group 3
Ceratophyllum demersum Myriophyllum spicatum Ruppia maritima
(coontail) (Eurasian watertnilfoil) (widgeon grass)
Elodea canadensis Potamogeton pectinatus Zostera marina
(common elodea) (sago pondweed)(eelgrass)
Najas guadalupensis Potamogeton perfoliatus
HTouthern naiad) (redhead grass)
Vallisneria americana Ruppia^ maritima
(wildcelery) (widgeon grass)
Vallisneria americana
(wildceleryl
Zannichellia palustris
(horned pondweed)
One of the main elements of the SAV program was to examine the current
distribution and abundance of submerged grasses in Chesapeake Bay using
aerial photography to map the vegetation. In addition, the historical
record of aerial photography was examined for recent evidence (less than 40
years) of alterations in SAV abundance, and a biostratigraphic analysis of
sediment was performed to detect evidence of longer term (greater than 40
years) alterations in the abundance or species composition SAV beds in
several locations within the Bay. A comparison was made to answer basic
questions on the magnitude of the present decline of SAV as compared with
documented historic declines, and to determine whether the curent: decline
was part of a natural cycle or a decline attributed to recent non-cyclic
perturbations.
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SECTION 2
METHODS
The accurate delineation of SAV communities to analyze their
distribution and abundance is difficult, especially when the areas of
interest may incorporate hundreds of miles of shoreline that are subject to
turbid water conditions. These communities are not static, but represent
dynamic elements whose distribution and abundance can vary in both space
and time. Distinct differences in SAV beds can be observed in time frames
of less than two months. To avoid the problems associated with labor-
intensive field surveys that provide only a limited view of SAV
distribution, remote sensing techniques (aerial photographs) were used to
acquire a synoptic view of the existing beds of SAV.
In 1978, the entire shoreline of Chesapeake Bay and its tributaries,
from the Susquehanna Flats to the mouth of the Bay, was flown with light
planes equipped with mapping cameras to acquire aerial photographs of all
existing beds of SAV. Beds of SAV observed on the aerial film were mapped
directly onto U.S.G.S. topographic quadrangles, and the areas of each bed
were determined with an electronic planimeter (see Orth et al. 1979, and
Anderson and Macomber 1980 for detailed information on methodologies used
for this work). Field surveys of selected sites corroborated information
observed on the aerial photographs and provided species information.
Aerial photography comparable to that obtained in 1978 was acquired in 1980
and 1981 for Virginia's SAV only.
Data on the past distribution and abundance of SAV in the Bay were
acquired from several sources: aerial photographs of the Bay's shoreline
and near-shore zone dating back to 1937; reports of field surveys conducted
by state and Federal laboratories, as well as by individual scientists
throughout the Bay area; studies on the biostratigraphical analysis of
estuarine sediments for seeds and pollen of SAV species (Brush et al. 1980,
1981); and anecdotal information supplied by watermen, landowners, and
other interested citizens who had observed changes in the abundance of SAV
in numerous areas of the Bay during the last 40 years.
We have organized the discussion of SAV distribution into three zones
(Figure 1). The area between the mouth of the Bay to a line stretching
from the mouth of the Potomac River to just above Smith Island will be
referred to as the lower Bay zone; the area between Smith Island and
Chesapeake Bay Bridge at Kent Island will be referred to as the middle Bay
zone; and the area between Chesapeake Bay Bridge and Susquehanna Flats will
be referred to as the upper Bay zone. These zones have distinct salinity
regimes that influence the type of SAV community that will grow within each
area. The salinity within each zone roughly coincides with the major
salinity zones of the estuaries: polyhaline (18-25 ppt), lower zone;
mesohaline (5-18 ppt), middle zone; oligohaline (0.5-5.0 ppt), upper zone.
Despite the fact that the major rivers (James, York, Rappahannock, Potomac,
and Patuxent) as well as the smaller tributaries (for example, Choptank,
Chester, and Piankatank) of the Bay have their own distinct salinity
patterns, the distribution of the grasses in each river will be discussed
within the zone where it connects to the Bay proper.
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SECTION 3
PRESENT DISTRIBUTION
The results of the 1978 SAV aerial survey and mapping of the entire Bay
and its tributaries documented the existence of significant stands of
vegetation (Orth et al. 1979, Anderson and Macomber 1980). A total of
16,044 ha (39,629 acres) of bottom was found to be vegetated. Table 2
presents area values for major sections within each zone.
In the lower Bay zone (Figure 1) where salinities range from 16-18 ppt
to 25 ppt, two species predominated: eelgrass (Z. marina) and widgeon
grass (R. maritima). Horned pondweed (Z. palustris) was present, but
occurre~infrequently. In 1978, there were approximately 9400 ha (23,218
acres) of bottom covered with SAV in this zone. This included 46 ha (114
acres) of SAV that were found in the Chickahominy River, a fresh to
brackish water tributary of James River. These areas ranged from very
dense to very sparse in SAV coverage. The largest and most dense grass
flats were concentrated in several main regions: (1) along the western
shore of the Bay from just north of the James River to the Rappahannock
River, especially in the region of Mobjack Bay; (2) behind protective
sandbars along the Bay's eastern shore; and (3) in the shoal area between
Tangier Island and Smith Island. The SAV bed between Tangier and Smith
Island was the single, most extensive vegetated area in the entire Bay,
with a total area coverage of 2394 ha (5912 acres) or 26 percent of the
total vegetated bottom in the lower zone and 15 percent of the total
vegetated bottom in the entire Bay. 1980 data for the upper Bay were not
available.
Updated aerial photographs taken of the lower Bay in 1980 and 1981
indicate a decrease in abundance in 1980 followed by slight rebounding in
1981 (Table 3). The pattern of change determined for one section of the
Mobjack Bay area since 1974 (Figure 2) illustrates a decrease in vegetation
in the outer, generally deeper portions of the beds, a common pattern in
areas where the vegetation has declined. It is significant to note that in
one intensively sampled site in the York River a general increase in
vegetation abundance was observed from 1978 to 1981. Examination of this
site revealed that this increase was a result of a large number of
seedlings, many with seed coats still evident, that were growing only in
the most shallow areas of this location. Subsequent rapid growth and
spreading of the seedlings are indicative of the potential importance of
seeds to the reestablishment of the vegetation (Orth and Moore, in press).
In the middle zone of the Bay (Figure 1), SAV was found to shift from
Zostera-Ruppia dominated beds to the lower salinity Potamogeton,
Zannichellia, Vallisneria, and Myriophyllum beds. This zone contained
4,546 ha (11,229 acres) of bottom covered with SAV in 1978. The greatest
concentration of vegetation (77 percent of 3500 ha) was located in the
Little Choptank River to Eastern Bay area of the eastern shore (Table 2).
Only five percent or 227 ha (561 acres) of the vegetation occurred between
the Little Choptank River and Smith Island. An equally small amount [six
percent or 273 ha (674 acres)] occurred along the western shore of the Bay
389
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TABLE 2. NUMBERS OF HECTARES OF BOTTOM, COVERED WITH SUBMERGED AQUATIC
VEGETATION IN 1978 FOR DIFFERENT SECTIONS WITHIN THE THREE ZONES
IN THE CHESAPEAKE BAY (NUMBERS OF HECTARES ROUNDED OFF TO NEAREST
WHOLE NUMBER)(DATA FROM ORTH et al. 1979, ANDERSON AND MACOMBER
1980)
Zone
Section Hectares Totals
1. Susquehanna Flats110Upper
2. Upper Eastern Shore (Elk, Bohemia, and Sassafras
Rivers) 29
3. Upper Western Shore (Bush, Gunpowder, Middle, Back
and Magothy Rivers, and Baltimore 2098
Harbor) 484 hectares
4. Chester River 1475
5. Central Western Shore (Severn, South, and West Rivers,
and Herring Bay) 241
6. Eastern Bay (Wye, East, and Miles Rivers) 1800
7. Choptank River (Harris and Broad Creeks, Tred-Avon
and Little Choptank Rivers, and
Trippe Bay) 1740 Middle
8. Patuxent River 3
9. Middle Western Shore (Herring Bay to mouth of Potomac
River) 11 4546
10. Lower Potomac River Section (Nanjemoy Creek to mouth hectares
of Potomac) 541
11. Middle Eastern Shore (Honga River to Smith Island and
including Fishing Bay, Nanticoke,
Wicomico, and Manokin Rivers) 210
12. Tangier Island Complex (includes from Smith Island and
Big Annemessex River to
Chesconessex Creek) 3759
13. Lower Eastern Shore (Chesconessex Creek to Elliots
Creek) 1991 Lower
14. Reedville (includes area from Fleets Bay to Great
Wicomico River) 364
15. Rappahannock River (includes Rappahannock and 9354
Piankatank Rivers, and Milford hectares
Haven) 93
16. New Point Comfort Region 271
17. Mobjack Bay (includes East, North, Ware, and Severn
Rivers) 1785
18. York River (Clay Bank to mouth of York) 157
19. Lower Western Shore (includes Poquoson and Back
Rivers) 925
20. James River (Hampton Roads area only) 9
391
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TABLE 3. NUMBERS OF HECTARES OF BOTTOM, COVERED WITH SUBMERGED AQUATIC
VEGETATION IN 1971, 1974, 1978, 1980, AND 1981 FOR DIFFERENT
SECTIONS IN THE LOWER BAY ZONE (NUMBERS OF HECTARES ROUNDED OFF TO
NEAREST WHOLE NUMBER)(* INDICATES SECTIONS THAT WERE NOT MAPPED
THAT YEAR) (DATA FROM ORTH AND GORDON 1975, ORTH et al. 1979,
AND UNPUBLISHED DATA)
Year
Section 1971 1974 1978 1980 1981
Tangier Island Complex
(includes from MD-VA border to
Chesconessex Creek) * * 2814 2420 2794
Lower Eastern Shore
(Chesconessex Creek to Elliots Creek) * * 1991 1370 1691
Reedville
(Includes area from Windmill Pt. to
Smith Pt.) * * 364 31 133
Rappahannock River
(Includes Rappahannock and Piankatank
Rivers, and Milford Haven) 1273 68 93 3 43
New Point Comfort Region 168 233 271 182 207
Mobjack Bay
(Includes East, North, Ware, and Severn
Rivers) 1294 1593 1785 1317 1275
York River (Clay Bank to mouth of York) 493 141 157 135 142
Lower Western Shore
(Includes Poquoson and Back Rivers) 1620 1069 925 1002 996
James River (Hampton Roads area only) * 7 9 0 0
TOTAL FOR LOWER BAY ZONE 8,409 6,460 7281
from the mouth of the Potomac River to Chesapeake Bay Bridge, including the
South, Severn, Rhode, and West Rivers. The Patuxent River had virtually no
vegetation with only three ha (7.4 acres) being observed along the entire
length of the river. A small amount [12 percent or 545 ha (1346 acres)] of
the total vegetation in this zone was found in the Potomac River in the
vicinity of Nanjemoy Creek, Port Tobacco River, Mathias Point Neck, and
Mattox and Machodoc Creeks, at a distance of 50 to 100 km from the river's
mouth. These beds fringe the shoreline on the lower portions of the creeks
and the Potomac River proper, near U.S. 301 bridge, and are dominated by P_._
perfoliatus and V. americana. This was the only vegetation found along the
entire length of the Potomac River, except for small pockets of SAV that
existed at the heads of several small marsh creeks (Carter and Haramis
1980, Carter et al. 1980). In addition, this is the only area of
comparable vegetation found along any of the Bay's major western
tributaries (James, York, Rappahannock, Potomac, and Patuxent Rivers).
Less intensive surveys in 1979 showed only slight decreases from the 1978
distributional patterns to those in 1979, but considerable declines in 1981
were observed throughout the middle zone of the Bay (personal information
from unmapped data).
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The upper zone of the Bay (Figure 1) contained 2098 ha (5182 acres) of
substrate covered with SAV in 1978 (Table 2), with the species association
shifting from Group 2 to Group 1 (Table 1). Susquehanna Flats had 110 ha
(272 acres) of vegetation in 1978, most of which occurred in scattered
beds. This was a very small area when compared to abundance of SAV in the
late 1960s and early 1970s. Only two species were present on the Flats in
1978, Eurasian watermilfoil (M. spicatum) and wildcelery (V. americana);
eleven species were found by researchers in 1971 (Bayley et al. 1978).
Approximately 23 percent of the total bottom area covered with SAV in this
zone was in the Gunpowder, Middle, Bush, and Magothy Rivers located along
the western shore, whereas almost no vegetation was present in the Elk,
Bohemia, and Sassafras Rivers on the eastern shore. About 70 percent [1469
ha (3628 acres)] of the total bottom area covered with vegetation was
present in the Chester River and Eastern Neck area. The Chester River area
contained a diverse assemblage of SAV, with seven species recorded during
the 1978 survey. Less intensive surveys in 1979 show little change in
distribution patterns from 1978, but surveys in 1981 indicate considerable
declines in this zone.
In summary, the survey of SAV in the Bay in 1978 indicated the presence
of many apparently healthy beds in various sections of the Bay. There
were, however, large sections devoid of almost all vegetation where, in
earlier years (1965-1970), luxuriant beds persisted (see Figure 5).
Tributaries with major reductions of SAV included portions of the York,
Rappahannock, Potomac, Patuxent, Choptank, Chester, and Piankatank Rivers.
SAV populations in other areas along the main stem of the Bay, including
Susquehanna Flats, the area between Smith Point on the Potomac River, and
Windmill Point on the Rappahannock River, and an area between Smith Island
and Eastern Bay, which includes many smaller rivers, have also significantly
declined. More recent evidence from ground truth surveys and aerial
photographs taken from 1978 to 1981 indicate that this decline has
continued in certain areas. This suggests a widespread but complex pattern
of recent major decline, involving the entire spectrum of SAV communities
found in the Bay, from the mouth of the Bay to Susquehanna Flats at the
head of the Bay.
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SECTION 4
PAST DISTRIBUTION
A detailed discussion of past trends of SAV distribution and abundance
is hindered by the lack of adequate data for many sites over a long period
of time. A review of the available historical information indicates that
SAV has generally, in the past, been very abundant throughout the Bay. In
the last 50 years, however, there have been several distinct periods where
SAV, in some large portions of the Bay, has undergone major fluctuations,
although SAV populations have been known to undergo erratic oscillations
within small areas (Stevenson and Confer 1978).
HISTORICAL TRENDS (1700-1930)
The pattern of SAV distribution and abundance in the Bay during this
period was determined primarily from indirect evidence, pollen and seed
analysis, and qualitative observations. Aerial photography can usually
provide good evidence for the presence of SAV, but was not generally
available until the late 1930s. If it can be assumed that less
urbanization during this period resulted in better water quality throughout
the Bay and its tributaries (Heinle et al. 1980), conditions may have been
more favorable for the growth of SAV.
Biostratigraphical analysis of sediments for SAV seeds and pollen from
Furnace Bay (Brush et al. 1980), a small embayment off Susquehanna Flats,
indicates the continuous presence of SAV seeds from the 17th century.
However, there appear to have been some changes in species of SAV (for
example, declines of Najas spp.) corresponding to changes in land use, such
as deforestation. Increased erosion and sedimentation from these practices
possibly resulted in more turbid water conditions and, thus, the eventual
decline of species less adapted to low light levels.
The Potomac River, the largest tidal tributary in the Bay, historically
contained numerous species of SAV that were very abundant. Several species
(wild celery, coontail, naiad, and elodea) were reported in the vicinity of
Washington, B.C. in one of the earliest accounts (Seaman 1875). Cumming et
al. (1916) provided a map of the Potomac River below Washington, DC that
showed the river having a narrow channel and wide shallow margins that he
reported to be extensively vegetated with curly pondweed (P_. crispus),
wildcelery (V. americana), and coontail (C. demersum). Many other pondweed
species were reported at mouths of tributaries below Washington, D.C.
(Hitchcock and Standley 1919), indicating the widespread presence of SAV
species in the tidal portion of the Potomac River.
Eelgrass (Z. marina) apparently underwent some decline in Chtisapeake
Bay area in the late 19th century, although the magnitude of the decline
was never quantified. Cottam (1934, 1935) states that a guide from the
Honga River Gunning Club reported on the decline of eelgrass in Dorchester
County, Maryland in 1893-1894. Cottam also reports an interview with a
member of the Maryland Game Commission who commented on the decline of
eelgrass in Chesapeake Bay in 1889 (at the time of the Johnstown Flood) and
stated that it was 25 years before eelgrass fully recovered. Cottam
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documents other declines of eelgrass along the east coast of the U.S. —
one as early as 1854. From these accounts, it appears that eelgrass has
undergone several fluctuations during this period (1700-1930), suggesting
some irregular, though undefined, perturbations on the system.
In summary, evidence suggests that in the Bay: (1) SAV was apparently
much more widespread from 1700 to 1930 than it is today; (2) SAV had been a
persistent feature of shallow water habitats, although there may have been
some localized shifts in species composition of the beds; and (3) abundance
of eelgrass has apparently undergone changes several times.
RECENT PAST (1930-1980)
With an increased awareness of the value of SAV as a food source for
waterfowl wintering in the Bay and observations of major fluctuations in
the Bay and elsewhere, researchers placed more focus on the distribution
and abundance of SAV during this period. This research led to the
availability of more quantitative information; as a result, a much greater
perspective can be obtained. During these last 50 years, there have been
two distinct events in which significant changes occurred within individual
species of SAV: (1) the eelgrass wasting disease in the 1930's; and (2)
the watermilfoil (M. spicatum) problem in the late 1950's and early
1960's. Even far more dramatic are the changes in SAV populations in the
Bay in the 1960's and 1970's, when, unlike the eelgrass and milfoil events,
all species in almost all areas of the Bay were affected to some degree.
The following three sections discuss each of these periods.
The Eelgrass Wasting Disease (1931-1932)
The most documented decline of a species in the Bay was that of
eelgrass in the early 1930's. This decline was recorded not only in the
Bay area, but also along the entire east coast of the U.S. and the west
coast of Europe (Cottam 1934, 1935; den Hartog 1970; Rasmussen 1977).
Cottam (1934) comments, based on information from his surveys of historical
records and personal inquiries of fishermen, watermen, and scientists, that
"in the memory of man there has been no period of scarcity at all
comparable to the present one (1931-1932 compared to other past periods)."
The extent of the decline in Chesapeake Bay was never quantified, but
aerial photographs taken in 1937, five to six years after the height of the
decline, are available for almost all of the shoreline in the lower Bay. A
review of many areas in the lower Bay and subsequent mapping of six sites
(Orth et al. 1979) shows areas of bottom in shallow water covered with
large amounts of submerged vegetation (it was assumed to be eelgrass based
on knowledge of present day patterns and anecdotal information from
long-time residents of these areas). All six areas showed subsequent
increases in later years up to 1972. Although quantitative information is
lacking prior to the wasting disease, we assume that the vegetation present
in 1937 represented partial recovery from the height of the decline in
1931-1932. Cottam (1935) confirmed our conclusions from aerial photographs
when he reported that Chesapeake Bay eelgrass was showing "an encouraging
change, with a few localized areas fast approaching the normal."
395
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One indication of the magnitude and severity of the decline of
eelgrass, experienced not only in Chesapeake Bay but also along the east
coast of the U.S. and the west coast of Europe, was found in the coastal
lagoons on Virginia's seaside. These areas contained dense beds of
eelgrass that supported a large bay scallop industry. The post-veliger
larvae of the scallop require eelgrass as a setting substrate (Outsell
1930). Without eelgrass, there can be no scallops because a scallop Lives,
at the longest, two years, and a change or disappearance of eelgrass
results in rapid shifts of the scallop population. Indeed, this is what
happened (Table 4). The commercial fishery that resulted in a harvest of
over 14,000 kg per year in the late 1920s and early 1930s completely
declined in 1933, over a span of just two years. Eelgrass has never
recovered in the seaside bays as compared with Chesapeake Bay and many
other areas where it had substantially declined (Cottam and Munro 1954),
nor has the scallop industry ever returned.
TABLE 4. CHANGES IN AMOUNT OF SCALLOPS (SHUCKED MEAT) HARVESTED FROM THE
DELMARVA PENINSULA FROM 1928-1975 (COLLATED FROM U.S. FISHERIES
DIGEST)
Year Harvested scallops (kg shucked meat)
1928
1929
1930
1931
1932
1933
1934
k
1981
5,050
16,038
25,549
17,170
9,220
0
0
^
0
The Milfoil Problem (1959-1965)
A second major period of extensive SAV fluctuation in the Bay was the
large increase in Eurasian watermilfoil (M. spicatum) in the late 1950's
and early 1960's (Stennis 1970, Bayley et al. 1978, Stevenson and Confer
1978b). The area affected by the milfoil was restricted to the upper Bay
area and a large section of the Potomac River (Figure 3). The intolerance
of milfoil to high salinity water limited its downward expansion in the
Bay, but reasons for its sudden expansion in abundance during this period
are not well understood. Until 1955, milfoil was found only sporadically
in the Bay, apparently introduced from Europe to the U.S. between 1880 and
1900 (Rawls 1978). Biostratigraphic evidence substantiated its recent
arrival to Chesapeake Bay (Brush et al. 1980). Milfoil seeds were found in
sections of sediment cores from Furnace Bay near Susquehanna Flats and
dated only to approximately 1935, though sediments from the cores had
recorded events, including the presence of other SAV species, to 1770.
396
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Milfoil increased Bay-wide from 20,200 ha (49,894 acres) in 1960 to
40,500 ha (100,035 acres) in 1961 (Rawls 1978). In contrast, the 1978
baywide SAV survey found that only 16,000 ha (39,525 acres) of bottom were
covered by all SAV species combined. In creeks along the Potomac River,
the milfoil reached densities so high that it was considered a nuisance,
and attempts to eradicate it with applications of 2-4 D were initiated
(Rawls 1978).
The Susquehanna Flats area typifies the changes noted during the rapid
expansion of milfoil. In 1957, a survey conducted of SAV found that
milfoil did not occur at any sampling stations. Subsequently, it was found
in one percent of these stations in 1958, 47 percent in 1959, 82 percent in
1960, and 89 percent in 1961 and 1962. After 1962, milfoil declined in the
Flats, with slight increases in 1966 and 1967. The most serious effect
associated with the rapid increase in milfoil was a decline in other native
species such as common elodea (E. canadensis), naiad (N. guadalupensis),
and wildcelery (V. americana). The decline of native species is shown in
Figure 4. For example,this graph shows that in 1963 abundance of native
plant material was below 50, while abundance of watermilfoil was over 200.
Bayley et al. (1978) suggest that the decline of native species was due to
competitive exclusion by milfoil. As milfoil declined, these native
species returned, but were found at a lower density and covered less area
than prior to the milfoil expansion (Bayiey et al. 1978).
The Bay-wide Problem (1960-1980)
In the 1960's and 1970's a number of field surveys and aerial surveys
were conducted to estimate the distribution and abundance of SAV in the
Bay. These estimates, when considered with the results of the SAV
distribution projects funded by the Bay Program, reveal dramatic results.
The combined data show a pattern of vegetation decline that includes all
species in all sections of the Bay and a present abundance of vegetation
that may be at its lowest level in recorded history.
The results of this recent decline were first evident in changes in
diving duck populations in the Bay (Perry et al. 1981). Two species, in
particular, the canvasback (Aythya valisineria) and the redhead (Ay t hy_a
americana), have shown significant population declines in the last 10 years
in the Bay despite increases in the overall North American and Atlantic
flyway populations. These two duck species have traditionally used SAV as
food (Stewart 1962). The decline in their preferred food source presumably
led to the decline in the total number of ducks found in the Bay. Since
the SAV decline, canvasbacks have altered their feeding habits to include
clams, and redheads still feed predominantly on vegetation.
To illustrate the major changes of SAV populations that have occurred
in the Bay area in the last 20 years, we have delineated SAV distribution
on a Bay-wide basis at five-year intervals beginning in 1965 and
subsequently in 1970, 1975, and 1980 (Figures 5, 6, 7, and 12). 1965 was
chosen as a starting point because of the lack of complete information for
Bay-wide determination prior to 1965; the compounding problem of the
explosion in the late 1950"s of Eurasian watermilfoil, which declined by
1965; and the relatively abundant Bay-wide distribution of SAV during this
time, apparent from archival photographs and anecdotal information. Though
the scale of the map is small in relation to the generally small size of
398
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r 16
300 H
TOTAL NO. OF ALL SPECIES
EURASIAN WATERMILFOIL
(abundonce)
DOMINANT NATIVE AQUATICS
(abundance)
-Vallisneria americana
-Najas spp
-Elodea canadensis
N /,
/ V
58 ' 59 ' 60 ' 61 ' 62 ' 63 ' 64 ' 65 ' 66 ' 67 ' 68 ' 69 ' 70 ' 7 I ' 72' 73' 74 ' 75
YEARS
Figure 4. Population fluctuations of watermilfoil compared to the
dominant native species and total number of species found
on the Susquehanna Flats from 1958-1975 (figure adapted
from Bayley et al. 1978).
399
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most SAV areas, the changes that occurred in SAV distribution in each of
the five-year intervals were sufficiently dramatic so as to appear quite
distinct in the respective figures. Note, for example, the large changes
in abundance of SAV in Susquehanna Flats area, Patuxent, and Potomac Rivers
from 1965 to 1975. We are aware that the small scale is not suitable for
small populations of SAV related to the size of the entire Bay, but the
overall changes in SAV on a Bay-wide basis are more easily perceived on
this size map. Though in some respects the following maps are qualitative,
they represent the culmination of a large effort to incorporate whatever
quantitative data were available with the most reliable qualitative data.
These maps are the first effort to place into perspective the complex
changes that have been observed in SAV populations over the last 20 years.
1965—
In 1965, SAV was quite abundant throughout the Bay and in all of the
major tributaries (Figure 5) despite the compounding effects of the milfoil
problem in the early 1960's (Bayley et al. 1978). One area, however, that
had been reported to have abundant SAV (Gumming et al. 1916), but no longer
contained any, was the freshwater tidal portion of the Potomac River
(Carter and Haramis 1980, Carter et al. 1980). The SAV of this area
apparently declined in the 1930s and had all but disappeared by 1939
(Martin and Uhler 1939). The lower reaches of the Potomac still contained
abundant stands of vegetation in 1965 based on evidence from aerial
photographs of the Coan, Yeocomico, and lower Machodoc Rivers and from
personal accounts of local watermen. In addition, an intensive benthic'
survey for the soft shell clam, Mya arenaria, in the lower Potomac in 1961
revealed abundant stands of SAV. The lower reaches contained eelgrass,
while numerous brackish water species abounded farther upstream
(Pfitzenmeyer and Drobeck 1963).
1965-1970—
By 1970 there were still substantial stands of SAV throughout the Bay
but evidence indicates some major losses had occurred in several areas
(Figure 6). Vegetation in the entire Patuxent River had all but completely
disappeared (R. Anderson, personal communication) by 1970, with declines
being first noted in the mid-19601s. Anecdotal accounts indicate that
populations of eelgrass adjacent to Chesapeake Biological Laboratory at the
mouth of the Patuxent River were severely depressed in the late 1960's and
gone by 1970. The vegetation in the lower Potomac River evidenced in
aerial photographs of the 1960's was also almost completely absent. In
addition, vegetation in many of the eastern shore upriver sections of the
Choptank, Chester, Gunpowder, and Bush Rivers, as well as in the entire
Nanticoke and Wicomico Rivers in the middle and upper Bay zones, was absent
or in very reduced abundance (Boynton, personal communication).
SAV in some localized areas around the Bay, including Susquehanna Flats
(Bayley et al. 1978) and the Chester River area (Anderson and Macomber
1980), had increased in coverage from 1965 to 1970, though not to previous
levels. The increase in these years may have been the result of the
reemergence of native SAV species in response to the decline of milEoil
(Bayley et al. 1978).
One of the first significant surveys of the upper Bay during this
period was that conducted by Stotts from 1967 to 1969 (Stotts 1970). Over
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Figure 5. Distribution of SAV in Chesapeake Bay - 1965,
401
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Figure 6. Distribution of SAV in the Chesapeake Bay - 1970,
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1,000 transects were sampled from the Virginia - Maryland border to
Susquehanna Flats. The survey findings indicate that many areas contained
significant beds of vegetation, especially in the more southern locations,
from the Choptank River to Smith Island. Stotts reported, however, that
large declines of SAV occurred in July and August in several locations
north of the Choptank and that SAV did not appear as robust as in the more
southern areas, indicating that these systems were being stressed by
environmental factors. Examination of aerial photographs taken in
September, 1970, shows large beds of vegetation in the same areas where SAV
was reported to be abundant by Stotts1 survey, especially in the lower
reaches of the Chester River, Eastern Bay, Little Choptank River, Honga
River, and Bloodsworth Island.
In contrast to the declines evidenced during this period in the
upstream, low salinity regions of the Bay and its tributaries, the higher
salinity regions vegetated with eelgrass and widgeon grass showed as yet
little evidence of any deterioration. Aerial photographs document that
extremely dense beds characterized much of the shoreline of the lower Bay
and its tributaries, and many areas showed a continued increase in coverage
since the 1930's (Orth and Gordon 1975, Orth 1976, Orth et al. 1979).
1970-1975—
By 1975 the Bay-wide situation for SAV had changed dramatically along
the entire length of the Bay proper (Figure 7). Indeed, the abundance of
vegetation in 1975 represented what we feel was, until then, the lowest
recorded abundance of vegetation in Chesapeake Bay and its tributaries as
far back as records indicate. The decline of SAV that first began in the
mid-1960s and continued to the early 1970's, was now observed in all
sections of the Bay, with some areas affected more than others. This
decline also appeared to accelerate after Tropical Storm Agnes influenced
the Bay in June 1972.
Much of the information available for this period for the upper and
middle Bay zones is from the 644 station survey of SAV conducted once a
year in Maryland waters beginning in 1971 by the Maryland Department of
Natural Resources and the U.S. Fish and Wildlife Service (Kerwin et al.
1977; unpublished files). Their data showed that SAV declined in the
surveyed areas between 1971, when 28.5 percent of the stations were
vegetated, and 1973, when 10.5 percent of the stations were vegetated
(Table 5, Figure 8). SAV fluctuated at comparatively low levels from 1974
to 1975, decreasing to 8.7 percent in 1975. The number of major areas with
no SAV increased from five in 1971 to 11 in 1975, an increase of 100
percent (Figure 1 and Table 5). This survey also shows that individual
sections of the Bay had not exhibited a uniform trend, but that the head of
the Bay and lower eastern shore have fared the worst, while the middle
sections of the Maryland eastern and western shores fared the best.
Large reductions in vegetation were observed immediately after Agnes,
in July and August, 1972, in many sections of the upper Bay zone (Figure
7), principally the Elk, Bohemia, Sassafras, Back, Middle, Magothy, and
Chester Rivers, Howell and Swan Point, Susquehanna Flats, and the
headwaters of the Bush and Gunpowder Rivers (Figure 7 and Table 5) (Kerwin
et al. 1977). In addition, sections of the middle Bay zone, primarily
those in the northern end, such as the Severn River, appeared to be rapidly
denuded of grasses. The species that were most affected were the fresh and
403
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Figure 7. Distribution of SAV in the Chesapeake Bay - 1975
404
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brackish water species: coontail (C. demersum), common elodea (E.
canadensis), southern naiad (N. guadalupensis), wildcelery (V. americana),
sago pondweed (P. pectinatus), and redhead grass (P. perfoliatus) (Table 1),
Vegetation in the middle and lower zones of the Bay started to decline
in 1973. In the middle zone, regions affected were: the Choptank and
Little Choptank Rivers, James Island, Manokin River, Big and Little
Annemessex Rivers, and Bloodsworth and Smith Islands. Species affected in
these areas included many of the same low salinity species that were
rapidly lost from the upper Bay section in 1972 as well as the higher
saline species, eelgrass and widgeon grass. The decline of SAV at some
locations on the lower eastern shore where eelgrass and widgeon grass had
predominated is shown in Figure 9.
In the lower zone, where data are available primarily from detailed
aerial photographs (Orth and Gordon 1975, Orth et al. 1979), vegetation in
the York, Rappahannock, and Piankatank Rivers, as well as in many small
tributaries, was reduced substantially during this period (Figure 7). To
highlight the changes that occurred with SAV communities in the lower Bay,
six areas were mapped for historical changes in the distribution and
abundance of SAV (Orth et al. 1979). These changes are shown in detail for
one of the sites: Mumfort Island in the York River (Figure 10). SAV
coverage in the lower Bay generally increased at all these sites from the
1930s to 1970; there was a marked decline beginning around 1970 (Figures 10
and 11). Our data, especially for the York River, indicated that the
decline of SAV occurred in the summer of 1973, as evidenced by the presence
of large beds of SAV in April 1973 that were absent in April 1974.
Comparison of means indicated that there were significant differences
between pre-1972 and post-1972 coverages at Parrott Island in the
Rappahannock River (p=0.001), Mumfort Island in the York River (p=0.002),
and East River in Mobjack Bay (p=0.038). At Jenkins Neck at the mouth of
the York River, where the trend was more gradual, regression analysis
indicates a significant decline (p=0.02). At Fleets Bay, just above the
mouth of the Rappahannock River, regression analysis indicates the decline
was significant (p=0.019). Only Vaucluse Shores on the eastern shore
showed no significant decline (p=0.14).
Several distinct patterns in the decline of vegetation in the lower Bay
are evidenced. First, it appears that losses of vegetation were greatest
in all the areas where eelgrass formerly reached its upriver or upbay
limits. For example, eelgrass beds disappeared from the Maryland portion
of the eastern shore while remaining in the Virginia portion. Along the
western shore of the lower Bay, SAV beds declined the most in the northern
areas and least in the southern areas. Within the major tributaries, SAV
disappeared, leaving only some beds at the mouths of the rivers. In nearly
all the small creeks and tributaries where eelgrass beds continued to exist
in 1975, the former distribution included areas further upstream. Second,
in addition to the upstream-downstream movement, it appears that the
vegetation declined in the deeper, offshore sections of the beds rather
than in the shallower, nearshore areas (Figure 2).
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1975-1980'---
Between i')7S u\\-i
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stations at the Smit;
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o b s e r v f; '.i, >* >; „; t •• p * f c •
levels (Figure ''-}},
the number ut a7-eas
percent of the total
compared vita five a
In the lower
.'.shore FrosiT the
r enva i. n e d s •;. in i 1 a r
vpce offset
i :s '-'or iack 3.=. y
Kay-'* ick- status of SAV appeared to be one of
- . are,'-; of the Bay (Figure 11). The upper
artment of." Natural Resources continued to
t: tons vt'jjetareci wlch 3AV with a trend toward
&ca), A smalJ increase was
i u vg e 11, •. t •- a r.c: i r: VP ;; -• t a f-<: d
:: a, id Figure '. / . All sites, where
' r- '.rom 'Jie lower eastern shore, was
..•ue'". to decline to much lower
polu1'. was r.h« corit inual increase in
l\ Ey J^BO, I® areas, or 62
th.is .survey now contained no SAV,
( !'abla ^ and Figure S) .
the mapped areas of the western
Jar.es ;
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Figure 12. Distribution of SAV in Chesapeake Bay - 1980.
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SECTION 5
THE ATLANTIC COAST
There is little evidence to suggest that there have been recent
significant changes in SAV distribution along the east coast of the U.S.
comparable to those documented for Chesapeake Bay. The uniqueness of the
Chesapeake Bay estuary, with its extensive littoral areas and marked
salinity gradient makes comparisons difficult. In addition, only recent
interest, by the scientific community and management agencies in SAV
communities, has resulted in any significant work on the historic
distribution of SAV in other areas.
Eelgrass is a species distributed widely along the coastline of the
eastern United States and Canada, from North Carolina to Nova Scotia. As
mentioned in the previous section, eelgrass populations underwent a
dramatic reduction along the east coast of the U.S. in the 1930"s. This
decline had dramatic effects on waterfowl populations, fisheries, and
shoreline erosion. Declines in other years were noted by Cottam (1934,
1935), but recovery always followed these declines in most of the reported
areas. At present, North Carolina, which has extensive beds of eelgrass
located within its bays and sounds, with a few beds found along the tidal
rivers, is attempting to determine the present distribution of SAV in the
region. Researchers in the area report no apparent widespread changes in
eelgrass distribution in the last 10 years (M. Fonseca, G. Thayer, personal
communication). There have been localized changes in eelgrass beds, but
these have been due to physical perturbations by man or to other localized
distrubances. Davis and Brinson (1976) report on the distribution of SAV
in the Pamlico River, but again report no significant, recent changes in
their abundance. In South Carolina and Georgia there are, at present, no
significant stands of SAV, primarily because of the very turbid conditions
that exist in the estuaries found there.
North of Chesapeake Bay there appears to be no SAV in the Delaware Bay
at present, and data on whether it ever occurred there are not available.
In New Jersey, SAV beds dominated by eelgrass and widgeon grass are found
in the sounds located to the west of the barrier islands (Good et al. 1978,
Macomber and Allen 1979). There is a lack of historic data on SAV in the
region but, again, there is no direct evidence of any large scale changes
in the existing beds.
New York researchers indicate no reports of significant losses in
eelgrass beds; on the contrary, eelgrass appears to be increasing in
abundance (Churchill, personal communication).
Rhode Island SAV beds persist in many of the small tidal lagoons
adjacent to Long Island Sound. These systems still contain abundant
vegetation and apparently have not undergone recent significant alterations.
In Massachusetts, Maine, Canada, and Rhode Island, there have been no
reports of changes in SAV communities. Accurate data are lacking, however,
because there are no scientists presently involved in any extensive SAV
research programs.
In summary, it appears that the declines in eelgrass or other SAV
species in the Bay are not part of a widespread and synchronous loss of
vegetation along the east coast of the U.S., although these conclusions are
415
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hampered by the lack of comprehensive data on the current and historical
distribution of SAV in other areas. It is most likely that the water
quality problems affecting the distribution of grasses in the Bay are
regional in nature, involving the Bay, its tributaries, and their drainage
basins.
416
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SECTION 6
WORLDWIDE PATTERNS
As in Chesapeake Bay, many coastal and estuarine regions of the world
contain varying amounts of shallow water areas that support SAV beds
ranging from large, very dense areas in the Caribbean to small, sparse
areas in some European countries. The grass beds around the world occur
under a wide range of physical, chemical, and biological parameters. Yet
despite these differences, they share a common ground in their functional
roles in their respective ecosystem: a habitat and nursery area, a food
source for waterfowl, a sediment stabilizer, a nutrient buffer, and a
source of detritus. Recent interest in SAV systems worldwide has
paralleled the increasing interest in the role and value of Bay SAV systems
and an interest in their proximity to industrialized areas, causing them to
become increasingly stressed by man-made perturbations. Recent examples
from the Netherlands (Nienhuis and DeBree 1977, Verhoeven 1980), England,
(especially some very pertinent examples from freshwater areas) (Wyer et
al. 1977, Eminson 1978, Phillips et al. 1978), Wales (Wade and Edwards
1980), Scotland (Jupp and Spence 1977), Denmark (Sand-Jensen 1977, Kiorboe
1980), France (Peres and Picard 1975, Maggi 1973, Verhoeven 1980), Israel
(Litav and Agami 1976), Australia (Cambridge 1975, Larkum 1976), Japan
(Kikuchi 1974a, 1974b) and the Virgin Islands (Van Epoel 1971), suggest
that losses in SAV communities are highly correlated with changing water
quality conditions. In many of the above examples, where SAV has been
described as greatly reduced or declining, this reduction has always been
associated with decreasing water clarity as a result of increased
eutrophication, with subsequent increases in epiphytes and phytoplankton
due to sewage or agricultural inputs, or as a result of higher loads of
suspended sediments due to dredging or runoff from deforested areas.
On the other hand, increases in water clarity have been shown to result
in expansion of SAV. The diking of the Gravelingen estuary in the
Netherlands resulted in a salt water lake with reduced currents and no
tidal effects. This resulted in a reduced total suspended solid load, and,
thus greater light penetration. Subsequently, eelgrass increased almost
400 percent in 10 years and was found in water depths of up to five meters,
far deeper than before the diking (Nienhuis 1980).
Large reductions of SAV communities have also been associated with
natural causes of diseases. The eelgrass wasting disease of the 1930s,
which resulted in massive declines of eelgrass along the east coast of the
U.S. and west coast of Europe was originally attributed to a disease
organism, Labyrinthula, but later attributed to climatalogical changes in
temperature (Rasmussen 1973, 1977). In Australia, decline of SAV was
attributed to migrating sand waves that smothered the grasses (Kirkman
1978). However, the more recent declines cited in the literature have been
associated with man-induced alterations rather than with natural ones.
There are still vast areas of SAV in many parts of the world,
particularly in the Gulf of Mexico, the Caribbean, and Australia that are
not presently affected by industrial or urban development [one area in
southern Florida was estimated to have 500,000 ha (1,235,000 acres) of
turtlegrass (Thalassia testudinum) (J. Zieman, personal communications)].
417
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In those areas where development has occurred, SAV communities declined,
especially in deeper beds, because of the reduction in quantity of light
a pattern that parallels the situation in Bay SAV communities.
418
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SECTION 7
CONCLUSIONS
The period of 1965 to 1980 represents what we feel was an unprecedented
decline of SAV in Chesapeake Bay. Loss of SAV communities was first
observed in the late 1960's in the upper Bay areas, and in particular, the
Patuxent, lower Potomac River (SAV beds in the freshwater tidal portions
had been absent since the 1930"s), and the upper reaches of some of the
smaller tributaries (for example, the Chester and Choptank Rivers). By
1970, almost all the vegetation in the Patuxent River and lower Potomac
River was gone. The decline of SAV in the Bay accelerated in the early
1970s and continued through 1980, with the most rapid decline occurring
from 1972 to 1974. Several sections in the Bay that once contained
abundant SAV virtually had none by 1980 (for example, the Patuxent,
Piankatank, and Rappahannock Rivers); other sections had only small stands
remaining (for example, the Potomac and York Rivers, and Susquehanna
Flats). In addition to this trend of SAV populations declining from
"up-estuary" to "down-estuary", it appears that within individual beds the
declines occurred first in the areas of greatest depth.
The present abundance of all SAV species in the Bay [16,000 ha (39,520
acres)] is probably the lowest level recorded in the Bay's history. Figure
13 shows this cumulative pattern of decline over the last 20 years, with
the arrows representing the former to present limits of distribution.
Figure 14 outlines these sections of the Bay where SAV has been most
severely affected.
SAV in the Bay has experienced other large scale changes in the recent
past, although none involving so great a spectrum of species types. In the
1930's, a decline of SAV primarily involved eelgrass except for ttie tidal
freshwater portion of the Potomac River where all SAV species disappeared.
Eelgrass gradually returned to all areas of the Bay, but there has been
little regrowth of SAV in the upper Potomac. In the late 1950's and early
1960's, the sudden rapid expansion of Eurasian watermilfoil created
problems by choking many waterways in sections of the Potomac River,
Susquehanna Flats, and western tributaries of the upper Bay.
On a much broader latitudinal scale, the entire east coast of the
United States and the west coast of Europe, eelgrass populations also
declined during the 1930's. This decline was subsequently followed by a
gradual return in most areas. Near Chesapeake Bay, in the shallow lagoons
behind the barrier islands of the Delmarva Peninsula, the eelgrass has
never recovered. This has drastically affected the scallop industry that
was associated with this species of SAV. Regarding the decline of SAV in
the 1960's and 1970's in Chesapeake Bay, there is little evidence yet to
suggest that a simultaneous decline occurred with SAV communities in other
areas along the east coast of the United States. Reports indicate that on
a worldwide basis, despite their abundance in certain areas, SAV
communities are becoming increasingly affected by man-induced
perturbations, declining in areas where there is extensive industrial
and/or urban development.
Given the current situation, a very important question can be raised as
to the ability of these systems to return to their previous levels of
419
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abundance in the Bay. Indeed, recovery may not occur because the current
levels of SAV are so low or non-existent that natural recruitment via
vegetative propagation or seed dispersal may be limited. Recent success
with SAV transplantation experiments, moving whole plants into denuded
areas in the Potomac River and lower Bay, indicates that these regions may
now be capable of supporting SAV (Orth et al. 1981; V. Carter, personal
communication). Thus, transplanting SAV may be a viable method, and in
some areas the only way, for the reintroduction of these plant communities.
The future of SAV in Chesapeake Bay is one of uncertainty. We know
that historically there have been several periods of SAV decline in the
Bay. The vegetation has returned to some areas; others have remained
barren. The pattern of continued decline of SAV in the Bay over the last
20 years suggests a chronic deterioration of water quality. Unless the
complex interaction of factors leading to this deterioration can be
understood and reversed, SAV communities in many areas may remain a part of
the Bay's past.
422
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LITERATURE CITED
Anderson, R. R. 1972. Submerged Vascular Plants of the Chesapeake Bay and
Tributaries. Chesapeake Sci. 13:587-589.
Anderson, R. R., and R. T. Macomber. 1980. Distribution of Submerged
Vascular Plants, Chesapeake Bay, Maryland. Final Report, U.S. EPA
Chesapeake Bay Program. Grant No. R805970. 126 pp.
Bayley, S., V. D. Stotts, P. F. Springer, and J. Steenis. 1978. Changes in
Submerged Aquatic Macrophyte Populations at the Head of the Chesapeake
Bay, 1958-1974. Estuaries. 1:171-182.
Brush, G. S., F. W. Davis, and C. A. Stenger. 1981. Sediment Accumulation
and the History of Submerged Aquatic Vegetation in the Patuxent and
Ware Rivers: A Stratigraphic Study. U.S. EPA Final Report, Grant No.
R80668001.
Brush, G. S., F. W. Davis, and S. Rumer. 1980. Biostratigraphy of
Chesapeake Bay and its Tributaries: A Feasibility Study. U.S. EPA
Final Report, Grant No. R205962. 98 pp.
Cambridge, M. D. 1975. Seagrasses of Southwestern Australia with Special
Reference to the Ecology of Posidonia australis in a Polluted
Environment. Aquat. Bot. 1:149-161.
Carter, V., and G. M. Haramis. 1980. Distribution and Abundance of
Submersed Aquatic Vegetation in the Tidal Potomac River—Implications
for Waterfowl. In: Bird Populations—A Litmus Test of the
Environment. J. F. Lynch, ed. Proc. Mid-Atlantic Nat. Hist. Symp.
Audubon Nat. Soc., Washington, D.C. pp. 14-19.
Carter, V., J. E. Paschal, and G. M. Haramis. 1980. Submersed Aquatic
Vegetation in the Tidal Potomac. In: Proc. Conf. Coastal Zone 1980.
ASCE/Hollywood, Florida, pp. 17-20.
Cottam, C. 1934. Past Periods of Eelgrass Scarcity. Rhodora. 36:261-264.
Cottam, C. 1935. Further Notes on Past Periods of Eelgrass Scarcity.
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Cottam, C., and D. A. Munro. 1954. Eelgrass Status and Environmental
Relations. J. Wildl. Mgt. 18:449-460.
Gumming, H. S., W. C. Purdy, and H. P. Ritter. 1916. Investigations of the
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Dept., U.S. Public Health Service Hygenic Lab. Bull. No. 104. 231 pp.
Davis, G. J., and M. M. Brinson. 1976. The Submersed Macrophytes of the
Pamlico River Estuary, North Carolina. Water Resources Res. Inst.
Univ. North Carolina, Rep. No. 112. 202 pp.
423
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Eminson, D. F. 1978. A Comparison of Diatom Epiphytes, Their Diversity
and Density, Attached to Myriophyllum spicatum in Norfolk Dykes and
Broads. Brit. Phycol. 13:57-64.
Good, R. E. , J. Limb, E. Lyszczek, M. Miernik, C. Ogrosky, N. Psuty, J.
Ryan, and F. Sickels. 1978. Analysis and Delineation of the Submerged
Vegetation of Coastal New Jersey: A Case Study of Little Egg Harbor.
Rutgers University, New Brunswick, N.J. 58 pp.
Outsell, J. S. 1930. Natural History of the Bay Scallop. U.S. Bur. Fish
Bull. 46:569-632.
Hartog, C. den. 1970. The Seagrasses of the World. Verhandel, Afd.
Naturk. Koninklyke Ned. Akad. Van Werenscl. Tweede Reeks, Dul 39, No.
1. 275 pp.
Hitchcock, A. S., and P. C. Standley. 1919. Flora of the District of
Columbia and Vicinity. Contrib. from the U.S. National Herbarium Vol.
21, Smithsonian Inst., 329 pp. & 42 pi.
Heinle, D. R., C. F. D'Elia, J. L. Taft, J. S. Wilson, M. Cole-Jones, A. B.
Caplins, and L. E. Cronin. 1980. Historical Review of Water Quality
and Climatic Data from Chesapeake Bay with Emphasis on Effects of
Enrichment. U.S. EPA Final Rep. Grant R806189. 128 pp.
Jupp, B. P., and D. H. Spence. 1977. Limitations of Macrophytes in a
Eutrophic Lake, Loch Leven. II Wave Action, Sediments and Waterfowl
Grazing. J. Ecol. 65:431-466.
Kerwin, J. A., R. E. Munro, and W. W. A. Peterson. 1977. Distribution and
Abundance of Aquatic Vegetation in the Upper Chesapeake Bay,
1971-1974. In: The Effects of Tropical Storm Agnes on the Chesapeake
Bay Estuarine System. J. Davis, ed. Chesapeake Research ConsortLum,
Inc. Publication No. 54. The Johns Hopkins Univ. Press, Baltimore.
pp. 393-400.
Kikuchi, T. 1974a. Japanese Contributions on Consumer Ecology in EeLgrass
(Zostera marina) Beds, with Special Reference to Trophic Relationships
and Resources in Inshore Fisheries. Aquacul. 4:145-160.
Kikuchi, T. 1974b. Marine Submerged Vegetation in Seto. Naikai. 1971.
Census by Nasei Regional Fisheries Research Laboratory, Hiroshima,, 39
pp. with English translation.
Kiorboe, T. 1980. Production of Ruppia cirrhosa Grande in Mixed Beds in
Ringkobing Fjord (Denmark). Aquat. Eot~. 9:135-143.
Kirkman, H. 1978. Decline of Seagrass in Northern Areas of Moreton Bay,
Queensland. Aquat. Bot. 5:63-76.
424
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Larkum, A. W. 1976. Ecology of Botany Bay I. Growth of Posidonia
australis in Botany Bay and Other Bays of the Sydney Basin.Australian
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Litav, M., and M. Agami. 1976. Relationship between Water Pollution and
the Flora of Two Coastal Rivers of Israel. Aquat. Bot. 2:23-41.
Macomber, R. T., and D. Allen. 1979. The New Jersey Submerged Aquatic
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Maggi, P. 1973. Le Probleme de la Disparition des Herbiers a Posidnies
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Nienhuis, P.H. 1980. The Eelgrass (Zostera marina) Subsystem in Brackish
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Nienhuis, P. H., and B. H. DeBree. 1977. Production and Ecology of
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Abundance of Submerged Aquatic Vegetation in the Lower Chesapeake Bay,
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Phillips, G. L., D. Eminson, and B. Moss. 1978. A Mechanism to Account for
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Wade, P. M., and R. W. Edwards. 1980. The Effect of Channel Maintenance
on the Aquatic Macrophytes of the Drainage Channels of the
Monmouthshire Levels, South Wales, 1840-1976. Aquat. Bot. 8:307-322.
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ECOLOGICAL ROLE AND VALUE OF
SUBMERGED MACROPHYTE COMMUNITIES:
A Scientific Summary
W. R. Boynton
University of Maryland
Center for Environmental
and Estuarine Studies
Chesapeake Biological Laboratory
Box 38, Solomons, MD 20688-0038
and
K. L. Heck, Jr.
Academy of Natural Sciences of Philadelphia
Philadelphia, PA
(SAV Habitat Value Chapter)
U.S. Environmental Protection Agency
Chesapeake Bay Program
Annapolis, Maryland
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CONTENTS
Figures 430
Tables 431
Sections
1. Introduction 432
2. The Importance of SAV Production 434
Approach . . 434
Background 434
Seasonal Patterns of Biomass and Production in Chesapeake Bay. . . 437
Analysis of the Components of SAV Community Production 442
SAV Production in the Context of Estuarine Ecosystems 442
Comparison of SAV with Other Major Sources of Organic
Matter to the Bay 445
Food-Web Utilization of SAV 447
3. The Habitat Value of SAV Species in Chesapeake Bay 454
Strategies and Methods Used in CBP Habitat Studies 454
Results from Experiments on SAV as Food
(in Situ Animal Abundances) 455
Invertebrates 455
Finfish 456
Blue Crabs 458
Studies on SAV as Protection 459
4. Influence of SAV on Sediment Dynamics 461
Review of Sediment Processes 461
Role of SAV in Sediment Processes 463
Chesapeake Bay Program Studies ... 464
Comparison of Sediment Sources with Deposition in SAV beds
in Chesapeake Bay 467
Light Limitation of Photosynthesis 469
5. Nutrient Processes in SAV Communities 472
Nutrient Concentrations and Fluxes 472
Nutrient Regulation of SAV growth 479
Nitrogen Fixation, Nitrification, Denitrification 480
Nutrient Release and Oxygen Demand Associated with SAV
Decomposition 482
Comparison of Nutrient Buffering Capacity of Sav with
Important Nutrient Sources 484
6. Summary 487
Literature Cited 493
429
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Figures
Number Page
1. Map of Chesapeake Bay showing upper and lower Bay intensive SAV study
sites. f 433
2. A comparison of Chesapeake Bay submerged aquatic vegetation (a) net
productivity, and (b) biomass, with selected values from Alaska,
temperate and tropical areas 436
3. Seasonal patterns of above-ground biomass of SAV in Chesapeake Bay. . . . 438
4. Seasonal patterns of the root to shoot biomass ratios of selected
species of submerged aquatic vegetation for (a) high salinity, (b)
mid-salinity zones, and (c) the seasonal pattern in the leaf area index
(LAI) for a high salinity area 439
5. Seasonal patterns in the submerged aquatic vegetation net community
production 441
6. Net community production of submerged aquatic vegetation dominated by
(a) Zostera and (b) Ruppia 443
7. Hypothetical seasonal pattern and relative availability of organic
matter to food webs in the Chesapeake Bay 446
8. (a) Average monthly fish densities, for Parson Island and Todds Cove
for vegetated and non-vegetated (reference) areas and (b) seasonal fish
weight distribution at Todds Cove for vegetated and non-vegetated
areas 457
9. Major physical sediment processes in Chesapeake Bay 462
10. Differences between vegetated and non-vegetated habitats for suspended
sediment and attenuation coefficient during a tidal cycle. ........ 465
11. Relationship between submerged aquatic vegetation biomass and rate of
sediment deposition 468
12. Relationship between surface light intensity, and light attenuation in
the water column (expressed as attenuation coefficients) 471
13. Nutrient flux at Todds Cove, Choptank River, 24-25 July 1980 for
Ammonia-Nitrogen and Dissolved Inorganic Phosphate 473
14. Comparisons of weight loss, respiration rate, ammonia-nitrogen, and
dissolved inorganic phosphate release for representative species of
SAV, algae, and Spartina alterniflora 483
15. Decomposition rates of P. perfoliatus estimated using in situ litter
bags .486
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Tables
Numb er
1. Net Submerged Aquatic Vegetation Community and Values Attributable to
Various Autotrophic Components for Chesapeake Bay and Other Areas. . .
2. Estimated Magnitude of Three Sources of Organic Matter to Chesapeake
4. Net Sedimentation Rate for Locations in Chesapeake Bay and Selected
5. Estimated Annual Sediment Deposition in SAV Communities Relative to
6. Summer Littoral Zone Light Attenuation Coefficients in Chesapeake Bay.
7. Estimated Inputs of Nitrogen to the Upper Chesapeake Bay from Riverine
and Sewage Sources and Uptake of Nitrogen by Submerged Aquatic
431
Page
_._SP_
. 444
447
46S
469
.470
486
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SECTION 1
INTRODUCTION
Documentation of past distribution and abundance of submerged aquatic
vegetation (SAV) within Chesapeake Bay began in the late 1800's, but
information was sparse until the 1950's when surveys were initiated in the
upper reaches of the Bay. Recent analyses of SAV seed distributions in
sediment cores taken from various locations in the Bay (Brush et al. 1980),
and reviews of old aerial photographs (Anderson and Macomber 1980, Orth
1981) confirm the concept that over historical time SAV was a diverse,
abundant, and widespread feature of Chesapeake Bay. However, in the last
two decades drastic changes in this component of the Bay ecosystem have
occurred. The results of annual field surveys, several aerial surveys, and
recent field studies all support the conclusion that SAV in the Bay has
changed in species density, diversity, abundance, and distribution. This
decline might be of minor concern if it involved the disappearance of only
one or two species of SAV, or if the decline were part of a normal
ecological cycle from which SAV would recover. Dana indicate, howesver,
that the majority of SAV species has been negatively affected, that, the
recent decline is not a part of a repetitive cycle, and that this
phenomenon is Bay-wide. The documentation of this decline, coupled with
consideration of possible ecological and commercial implications, provided
the motivation to initiate intensive studies of the role and value of SAV
communities in Chesapeake Bay. Locations of major study sites for the Bay
Program research in Chesapeake Bay are indicated in Figure 1.
Current information concerning SAV communities indicates that they
possess several important ecological features. Of these, four distinct
hypotheses were examined in the Bay Program: (1) estimating the magnitude
of SAV organic matter production available to food webs; (2) examining the
habitat value of SAV to infaunal and juvenile nekton species; (3)
estimating the role of SAV in modifying, reducing, and serving as a sink
for nearshore sediments; and (4) examining the role, of SAV in modifying
nutrient dynamics of nearshore areas. This paper discusses these
hypotheses.
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PARSON ISLAND-1
STUDY SITE
TODDS COVE
TUDY SITE
CHESAPEAKE
BIOLOGICAL LAB
HORN POINT
ENVIR LABS
, SHORES
STUDY SITE
Figure 1. SAV intensive study sites for the upper and lower Bay.
433
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SECTION 2
THE IMPORTANCE OF SAV PRODUCTION
APPROACH
In this section, the importance of SAV production (both above-and-
below-ground biomass) is assessed from several points of view. First, the
magnitude of SAV organic matter production in the Bay is compared with
values obtained from global literature. This information sets the range of
values in the Bay against major variables such as latitude and
environmental gradients. Second, seasonal patterns of biomass and
production of major regions of the Bay are examined. This analysis
provides insight into the timing of environmental controls (such as
temperature and salinity) and into the availability of SAV community
organic matter to the food web. Third, the magnitude of production among
various autotrophic components (such as Bay grass, attached epiphytes,
benthic microflora, macroalgae, and phytoplankton) is compared, because SAV
total community production results from the additive nature of these
components. Fourth, the relative contribution of organic matter by major
sources (riverine input, marshes, benthic algae, phytoplankton, and SAV) to
the Bay system is estimated. For the upper Bay (mouth of the Potomac River
to the head of the Bay), we compared the magnitude of three major sources
of organic matter in 1960 (pre-decline of SAV) and 1978 (post-decline of
SAV). Finally, we assessed how organic matter produced by SAV is used in
Chesapeake Bay food webs.
BACKGROUND
In numerous reviews, the productivity (or rate of biomass accumulation)
of submerged aquatic macrophyte communities has been characterized as among
the highest recorded for aquatic systems. For instance, McRoy and McMillan
(1973) state "a seagrass meadow is a highly productive and dynamic
ecosystem; it ranks among the most productive in the ocean." Phillips
(1974) reports that productivity for the seagrass Thalassia testudinum (a
tropical species) ranges from 200 to 3,000 gCm~2y-l and,for Zostera
marina (a temperate species), values up to 600 gCm~2y™J- have commonly
been recorded. (Organic carbon is assumed to approximate 50 percent of the
plant material on a dry weight basis.) These rates are comparable to those
reported for such productive terrestrial systems as tropical rain forests
and intensive agricultural fields (Odum 1971). Compared with available
measurements of phytoplankton productivity (Boynton et al. 1981a), a major
source of organic matter in many aquatic food webs, SAV rates are truly
indicative of highly productive ecosystems. In some cases, SAV produces so
much biomass that eradication is necessary. For example, in Chesapeake Bay
during the 1960's, Eurasian milfoil (Myriophyllum spicatum), a non-native
species, showed high biomass production at nuisance levels, and research
focused on control through herbicides and mechanical removal (Rawls 1965).
Reviews of SAV distribution in Chesapeake Bay conducted by Orth (1981)
and Anderson and Macomber (1980), appraisal of archival aerial photography,
and anecdotal comments by long-term residents of the area all indicate that
434
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SAV was once a ubiquitous component of the Bay system (in at least a
qualitative fashion); the Bay-shore was fringed in a productive,
habitat-rich green wreath. Although considerable scientific research has
been conducted on several species of SAV (Thalassia testudinum, the
tropical turtlegrass and Zostera marina, the temperate eelgrass), many
characteristics of the freshwater-brackish species in Chesapeake Bay have
received little attention prior to the late 1970' s (Stevenson and Confer
1978). Since then, considerable effort has been expended in documenting
biomass, productivity and other faunal characteristics, habitat values,
relationships of productivity to food-web utilization, and nutrient
requirements of SAV. This work was done when SAV was in a period of severe
decline, particularly in the upper Bay. Therefore, results summarized here
may have an inherent bias because SAV is now only a small component of the
Bay system; however, we believe that our results present an appropriate
perspective that adjusts for potential bias.
Values of net biomass production (Pa) observed in Chesapeake Bay appear
to be quite similar to those observed in other temperate and semi-tropical
SAV systems distributed over large latitudinal and environmental gradients
(Figure 2). Values of Pa in this global sampling ranged from about two to
20 g02m~2cT~l, and typical values were in the range of three to seven
g02m~2cj-l. Conversion of oxygen values to organic matter (assuming a
photosynthetic quotient of 1.25, which is the ratio of oxygen evolved to
carbon dioxide fixed photosynthetically and the carbon equivalent of
organic matter of 0.5) gave typical values from about two to four grams of
organic matter m~^d~^- . These values are comparable to those associated
with intensive agriculture and other highly metabolic ecosystems (Penfound
1956, Odum 1971). The highest average value found in the literature was
for Z. marina (in Alaska) of about 20
In sharp contrast to the comparability of Pa values between SAV
systems, estimates of SAV biomass showed high variability. For example,
SAV biomass ranged from just a few g m~2 in some Chesapeake Bay
communities to over 7000 g m~^ in a Thalassia meadow in Puerto Rico
(Figure 2). Estimates of SAV biomass within the same system (Figure 2)
also exhibited a large range. For example, biomass of Zostera in Alaska
and Thalassia in Florida varied by factors of three to six. McRoy and
McMillan (1973) suggest that such gradients reflect differences in local
environments that promote or inhibit the accumulation of large standing
stocks. In general, the highest standing stocks of SAV occur in areas
where the water is relatively clear (light penetrates to the bottom) , deep
enough to allow for substantial vertical growth, and devoid of excessive
wave action.
A second observation suggested in Figure 2 is that average biomass (and
even maximum biomass) estimates in Chesapeake Bay communities are low
relative to those reported for other areas. Average values of Zostera and
Ruppia in the lower Bay were generally below 200 g m~^j and values for
Potomageton pectinatus and P. perf oliatus in the upper Bay were generally
below 100 g m~2. A quantitative evaluation of this observation is not
possible because of the nature of available data; however, several reasons
can be suggested. At the present time, sufficient light to support
vigorous growth of SAV does not penetrate much beyond one meter in most
littoral regions of the upper Chesapeake (Boynton et al. 1981a) . Thus,
growth is restricted to very shallow regions where there is a limited water
435
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LOCATION SPECIES
ALASKA
TEMPERATE AREAS
Temp. Ave. Mixed Sp.
Rhode Islond Zostera
Zostera
Beauf ord, N.C. Zostera
SEMI-TROPICAL
Silver Sp., Flo. Mixed sp.
North Florida inoiossto
CHESAPEAKE BAY
High Salinity Zostera
Ruppia
Mixed sp.
(
LOCATION SPECIES
ALASKA
Zostera
TEMPERATE AREAS
England Zostera
Nova Scotia Zostera
Rhode Islond Zostera
N.Carolina Zostera
TROPICAL AREAS
Puerto Rico Tho/oss/o
Florida Thalassia
CHESAPEAKE BAY
(
a
20
••MBMHMH
===-
^^^ MEAN VALUE
••••••••••• O"^ MAXIMUM
VALUES
' i i i | 1 I i i | i
) 5 10
NET PRODUCTIVITY, g 02 rrf 8d~'
Summer Averages
b
1800
'
m 1020
* 2060
" \ANNUAL MEAN
TST6
V
>T
m ^ANNUAL RANRF
• O* MAXIMUM VALUES
• r\^
— \J
r i | i . |
) 300 600
BIO MASS, grrf2(dry wgt.)
Mean & Range
Figure 2. (a) SAV net productivity and (b) biomass in Chesapeake
Bay and other SAV systems with selected values from Alaska,
temperate, and tropical areas. Data from Kaumeyer et al.
1981, and McRoy and McMillan 1973.
436
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column to support the vertical development of SAV, and the potential for
wave, thermal, and waterfowl grazing stresses is maximized. In previous
years (pre-1960) when light penetration was not so restricted, SAV in the
upper Bay may have grown in waters of greater depth and were characterized
by higher standing stocks.
SEASONAL PATTERNS OF BIOMASS AND PRODUCTION IN CHESAPEAKE BAY
Understanding seasonal patterns of primary production and standing
stock is important in developing a better knowledge of SAV community
dynamics. Productivity patterns provide insight to critical periods of SAV
growth and to factors potentially limiting growth. Periods of high and low
biomass indicate times of enhanced habitat and availability of organic
matter to Bay food webs. Data concerning SAV were scarce prior to the
initiation of the Chesapeake Bay Program; further work will refine the
detail of the patterns reported in this section.
Estimates of SAV above-ground biomass based on a few locations (mean of
three to six replicates and random quadrant of 0.10 to 0.25 m^) for
several species in the lower and upper Bay and for one introduced species
are summarized in Figure 3. In a comparative sense, several things are
apparent. First, peak biomass of M. spicatum, Z^ marina, and R. maritima
occurred in decreasing order, and biomass of R. maritima approximated that
of P. pectinatus and P. perfoliatus. Second, with the exception of M.
spicatum, mean biomass values were consistently higher in the lower Bay,
often by a factor of two or more. Third, in the lower Bay, above-ground
biomass persisted through winter months, but in the upper Bay above-ground
material was present only during the warmer months. Finally, periods of
peak biomass appeared to occur earlier in the year (June) in the lower Bay
than in the mid-salinity zone (July to August).
Recent declines in SAV may have created changes in these biomass levels
and seasonal patterns. It appears, however, that the SAV decline has been
more severe in the upper Bay than in other locations (see chapter 1 of this
Part). Quantitative information concerning biomass levels or seasonal
persistence prior to the initiation of the decline is unavailable; however,
anecdotal information suggests that general biomass values were higher in
the upper Bay than they are at the present time. Data presented in Figure
3 for a mid-salinity site (Eastern Bay) support this idea.
Estimates of below-ground biomass, expressed as root .-shoot ratios (RSR)
differ both seasonally and geographically. They indicate that a higher
proportion of the photosynthetic output of the plant is going into
non-photosynthetic tissues (roots and rhizomes) that act as overwintering
components (Schulthorpe 1967, Lipschultz et al. 1979) and sites of nutrient
uptake (Penhale and Thayer 1980). Values of below-ground biomass were
generally higher in the lower Bay than in the upper Bay, indicating that,
for a unit of above-ground biomass, considerably more root-rhizome material
was present in lower-Bay SAV communities (Figure 4). Furthermore,
root-rhizome material was clearly present throughout the year at lower Bay
sites. In the upper Bay, the situation is not so clear because of the
limited sampling. At a site in the Choptank River (P. perfoliatus
dominated), below-ground biomass persisted through at least part of the
winter months; however, in a mixed R^ maritima and P. pectinatus bed in
Eastern Bay, below-ground biomass was not evident in late fall. Field
437
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200-
y
CO
500-
250-
HIGH SALINITY ZONE (25-30%o)
Vaucluse Shores, Va.
*--^.
/ • Zostera
MID-SALINITY ZONE (I0-20%o)
Eastern Bay S Choptank R.
Ppectinatus Q
R. maritima
1979
MID-SALINITY ZONE (10-20 %o)
Choptank R
Myriophy//um spicatum
Study
Terminated
J ' M '~M ' J ' S ' N I J M M J S N
1977
1978
_2
Figure 3. Estimates of above-ground biomass (gm dry weight) in high
and mid-salinity zones of Chesapeake Bay. Data from Kemp
et al. 1981, and Wetzel et al. 1981.
438
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(a) HIGH SALINITY ZONE
Vaucluse Shores, Va.
3-
2-
cc
i-
o
o
V)
I I
1979
Till I
I960
l.O n
0.5-
(b) MID-SALINITY ZONE
Choptank River
P per foliofus -»
I
Myriophyllum L
3-
- 2
\ I I I I I I I I
1977 1977
(c) LEAF-ARE A INDEX, LAI
High Salinity Zone :••...••-
\
Zostera
.•••"V X^Mixed
Ruppia
J'M ' M' j '
1979
J ' M ' M ' J ' S ' N
1980
Figure 4. Seasonal patterns of root:shoot biomass ratios of selected
species of SAV for (a) high salinity and (b) mid-salinity
zones. (c) Shows the seasonal pattern in LAI for a high
salinity area. Data from Kemp et al. 1981, and Wetzel et al.
1981.
439
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observations confirmed that below-ground structures of SAV in the upper Bay
appeared poorly developed relative to those in other areas of the Bay and
very poorly developed relative to tropical Thalassia meadows. The low root
to shoot ratios recently observed in the upper Bay may be indicative of
stressed plants.
The leaf-area index (LAI), or the amount of photosynthetic surface per
unit of biomass, is a fundamental characteristic of SAV community
structure. LAI differences between SAV communities demonstrate the
importance of light in regulating SAV communities and their adaptability to
different light regimes. Increases in plant density can lead to potential
increases in photosynthesis to a point, but can also lead to decreases in
light availability through mutual shading. Data reported by Wetzel et al.
(1981) exhibit differences between different SAV communities. Average LAI
values are greatest in a mixed Zostera and Ruppia bed followed by
successively lower values in pure stands of Zostera and Ruppia (Figure
4c). At the study site, the Ruppia bed was located in shallow water; the
mixed and Zostera beds were at successively greater depths. The authors
attribute the pattern in LAI to differing light regimes in these areas: the
shallow Ruppia bed may have been photo-inhibited; the mixed bed near to
optimal; and the deep Zostera bed intermediate because of insufficient
light. Dennison (1979) reports a similar pattern for a Zostera bed and
underscores both the importance of light in regulating SAV communities and
the adaptability of SAV to different light regimes.
In addition to different mean LAI values, SAV communities exhibited
differences in the vertical distribution of these values. In the Ruppia
bed, values were greatest near the bottom of the canopy, presumably because
of photo-inhibition nearer the surface. In the deeper, mixed, and Zostera
communities, maximum LAI values were observed closer to the surface,
probably owing to reduced light availability at greater depths. The
maximum LAI values observed by Wetzel et al. (1981) were on the lower end
of values reported for other seagrass communities (Jacobs 1979, Aioi 1980,
Gessner 1971), suggesting that at least in these beds self-shading was not
a major factor limiting light availability.
Estimates of seasonal net production rates (Pa) for SAV communities in
the upper and lower Bay are summarized in Figures 5 and 6. In the
mid-salinity environment, values of Pa correlate well with temperature,
light, and SAV biomass. In general, rates were high during July and August
when SAV biomass, light, and temperature were high and decreased sharply to
lower values during the colder months. Figure 5 emphasizes the difference
in community net production in vegetated and non-vegetated littoral areas.
Clearly, during those periods of the year when SAV is present (May to
September), the rate at which new organic matter is created is considerably
higher in vegetated littoral areas.
Additional insights concerning the metabolic characteristics of SAV
communities can be gained by comparing the ratio of Pa (new organic matter
created during the day) to respiration (Rn: consumption of organic matter
during the night). Data indicate that Pa:Rn is greater than 1.0 during the
early SAV growth periods and that Pa:Rn is less than 1.0 during the late
summer and fall. This observation suggests that most SAV biomass is
generated in the early growing season; during the summer and fall, high
daytime rates of Pa are observed, but the daily net production is consumed
during the hours of darkness. Essentially, the metabolic demands of
440
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z
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Q
O
ir
a.
UJ
z
2
O
O
10-
5-
(a)CHOPTANK RIVER
TODOS COVE
SAV
"COMMUNITY
NON-VEGETATED
COMMUNITY
M
' S ' 0 ' N ' D
1980
5-
(b) EASTERN BAY
PARSON IS.
SAV
COMMUNITY
NON-VEGETATED
COMMUNITY
M
M
'
J
1979
J ' A T
N
-2 -1
Figure 5. Net SAV community production in gO_m d , including
estimates of non-vegetated community production for (a)
Todds Cove and (b) Parson Island.
1981.
441
Data from Kemp et al.
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non-photosynthetic organisms, or heterotrophs, and plant respiration
matches or slightly exceeds the generation of new organic matter.
Estimates of macroscopic heterotroph abundance (infauna, epifauna, and
finfish for example) correlate with this pattern in that general abundances
are low early in the growing season, but increase rapidly (as do metabolic
demands) as the season progresses.
Seasonal patterns of Pa for a Zostera and Ruppia community in the lower
Bay are given in Figure 6. Distinctive patterns emerge for each
community. Rates were high in the Zostera community in the spring and fall
with a summer minimum, but rates were highest in the Ruppia bed during the
summer. The seasonal shifts in maximum growth may partly explain the
successful coexistence of these two species. The values given in Figure 6
are in hourly units derived from measurements made prior to midday.
Afternoon values were generally lower and often indicated a heterotrophic
condition (Wetzel et al. 1981). The reason for this strong diel pattern in
Pa is not known, but nutrient or C02 limitation is suspected.
ANALYSIS OF THE COMPONENTS OF SAV COMMUNITY PRODUCTION
This section places the various autotrophic components into iperspective
by comparing the relative contribution of organic matter produced by
various autotrophic components of SAV beds, including epiflora, macroscopic
algae, and benthic flora. Each component contributes a certain amount to
the overall production of the community and provides a more or less
desirable food source for the associated heterotrophic community.
Because of technical problems, temporal and spatial variability, and
the time-consuming nature of the measurements, there appear to be only a
few such studies available with which to compare results obtained in
Chesapeake Bay. Estimates of production and bioraass attributable to
various autotrophic components of SAV communities are given in Table 1.
However, from areas outside of Chesapeake Bay, available data suggest that
epiphytes and macro-algae constitute a significant and, at times, a
dominant feature of SAV community production and biomass.
Data from Chesapeake Bay are preliminary, but inspection suggests that
epiphytic primary producers can constitute a substantial portion of the
total community Pa. As we have shown earlier (Figure 5), phytoplankton
production can also substantially contribute to overall SAV community
production. There is little data to suggest that epiphyte or macro-algae
constitute a substantial portion of community biomass.
One of the problems in interpreting these data involves the high
variability associated with measurements of benthic and epiphytic
production rates (Murray, pers. comm.). Apparently, short-term (day-week)
changes in bottom sediments due to wave and tidal action can radically
change benthic and epiphytic community structure and associated rates.
Thus, estimation of seasonal or annual importance is particularly
difficult. However, preliminary evaluations suggest significant, although
not dominant, roles for epiphytes associated with SAV.
SAV PRODUCTION IN THE CONTEXT OF ESTUARINE ECOSYSTEMS
The importance of SAV production can also be assessed in terms of its
contribution of organic matter to an estuarine system. In the shallow
442
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f
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a
JAN
MAR
MAY
JUN
SEP
NOV
MONTH
I
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-2 -1
Figure 6. Net SAV community production in mgCLm d dominated by
(a) Zostera and (b) Ruppia in the lower Chesapeake Bay.
Dots are mean values; bars are standard deviations.
443
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estuarine systems near Beaufort, N.C., studies were conducted on four major
primary producers, with results pointing to the potential importance of
seagrasses. Wetzel et al. (1981) summarize these studies and report annual
productivity estimates of 66, 249, 330, and 73 gCm~2y-l for
phytoplankton, salt marshes, Zostera, and SAV epiphytes, respectively.
Orth et al. (1979) report that SAV is an important autotrophic component in
certain areas of the lower Chesapeake Bay. Stevenson (personal
communication) estimates that some 40 percent of in situ production in
Chesapeake Bay could be attributed to SAV in 1963, but only six percent
could be assigned to SAV in 1975. Decreasing SAV abundance, especially in
the upper Bay, make present estimates of SAV contributions to in situ
productivity even smaller than the 1975 figures.
Estimates of relative seasonal contributions of sources of organic
matter to the upper Bay provide insight into the seasonal stability of the
food supply to food webs and form the basis for further evaluation of the
nutritional quality of the various sources (Figure 7). These trends were
developed from various kinds of information including the work of Flemer
(1970), Biggs and Flemer (1972), Heinle et al. (1977), Kemp and Boynton
(1980), Taft et al. (1980), Kemp .et al. (1981), and Wetzel et al. (1981).
Figure 7 suggests that because of the diverse sources, the organic matter
supply to the upper Bay is relatively constant throughout the year and may,
in part, explain the high productivity of the estuarine system (Nixon
1980). During the late winter and spring, it appears that upland drainage
is the dominant source of most organic matter; in late spring and summer,
phytoplankton production assumes a dominant role; in early fall SAV may
have been an important source in the past; and in the winter the input of
marsh vegetation via ice scouring and transport to the Bay may be important
in some regions. Benthic microalgae are probably not significant primary
producers due to the typically short euphotic zones encountered in the Bay
(light limitation) and the high rates of sediment deposition and
resuspension that deter community development.
COMPARISON OF SAV WITH OTHER MAJOR SOURCES OF ORGANIC MATTER TO THE BAY
A simplified organic matter budget is presented in Table 2 for the
upper portion of Chesapeake Bay (upstream at the mouth of the Potomac
River) for two periods (1960 and 1978). SAV was a distinctive and
quantitatively important feature of the Bay during the early 1960's, and
severely restricted in 1978.
This budget indicates that SAV may have been an important source of
organic matter to low and mid-salinity portions of the Bay. During the
1960 period, we estimated that phytoplankton production was comparable to
SAV production, and each of these was larger than riverine input. Some
evidence indicates that between 1960 and 1978 both phytoplankton production
and riverine input increased (Heinle et al. 1980, Boynton et al. 1982),
with SAV production much lower during the late 1970's. Our estimates
indicate that in the upper portion of Chesapeake Bay, SAV contributed about
30 percent of organic matter production during the 1960's when SAV was
abundant, and on the order of four percent in 1978.
Because of high variability, these estimates are only guides as to the
relative importance of various sources of organic matter in the low and
mid-salinity portions of Chesapeake Bay. Considerable year-to-year
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HIGH-
00
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LOW-
PHYTOPLANKTON
/ \--MARSHES
"^BENTHIC
ALGAE
WINTER
SPRING
l I I I I
SUMMER FALL
SEASON
Figure 7. Hypothetical seasonal pattern and availability of organic
matter to the Chesapeake Bay food web.
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TABLE 2. ESTIMATED MAGNITUDE OF THREE SOURCES OF ORGANIC MATTER TO
CHESAPEAKE BAY FOR TWO TIME PERIODS (ALL VALUES ARE IN UNITS
OF gCy-lxlO11)
Source3
Phytoplanktonb production
SAV productionc
Riverine input^
Time Periods
1960
3.8 (56)
2.2 (33)
0.8 (11)
6.8 (100)
1978
3.8 (79)
0.2 (4)
0.8 (17)
4.8 (100)
a Includes area of Bay and tributaries above the mouth of the Potomac
River (1.5 x
b Annual rate of production estimated at 250 g C m~2y-l (Flemer 1970).
c Annual production estimated at 360 g C m~2y-l based on rates
reported by Kaumeyer et al. (1981) and Wetzel et al. (1981) for a
180-day growing season. Areal distribution of SAV estimated at
6xl08m2 in I960 (Rawls, in prep.; Stevenson, pers. comm. ) and
0.7xl08m2 in 1978 (Anderson and Macomber 1980).
d Riverine input of organic matter from Biggs and Flemer (1972).
variability in the absolute amounts delivered from riverine sources occurs
and probably varies by a factor of one to two. Boynton et al. (1982) have
also shown that phytoplankton productivity in the mid-salinity portion of
Chesapeake Bay can vary by as much as a factor of three. The year-to-year
variability in SAV productivity has not been evaluated, although
observations by Orth (1981) indicate that there is some degree of
fluctuation. Despite the probable errors involved in this calculation, it
seems that in the early 1960 's SAV was a significant autotrophic component
in the upper Chesapeake Bay, but at the present time is a minor component.
An important ecological consequence is the possiblity of less food for
higher trophic levels such as fish.
FOOD-WEB UTILIZATION OF SAV
SAV can enter animal food webs either through direct grazing of living
plants or consumption of SAV detritus at some point in decomposition
processes. Several techniques have been used to establish the degree to
which SAV is used as a food source but, unfortunately, each has substantial
limitations. The most widely used technique is direct visual
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identification of material in the digestive system. This technique is
relatively simple, but analyses are often time-consuming, and the degree to
which food items can be identified is often limited to larger items that
are resistant to digestion. A second approach involves a relatively
expensive chemical technique in which the ratio of stable Cl2:cl3
isotopes is determined for both plant food items and associated predators.
The technique is based on different plant groups having characteristically
different Cl2:cl3 ratios. Animals feeding on a particular plant will,
in time, approximately reflect the food source ratio. This technique is of
limited value in establishing SAV food-web relationships because there are
several primary producers associated with SAV communities, each of which
has a distinctive Cl2:cl3 ratio (Bunker et al. 1981b) .
In spite of these limitations, several substantial results have emerged
using these techniques to link SAV production to utilization in Bay food
webs. Perhaps the most definitive linkage is between SAV and waterfowl.
Direct grazing on SAV by waterfowl seems to be important both in Chesapeake
Bay and elsewhere, and grazing in itself can impact the distribution of SAV
locally. McAtee (1917) reports that generally, SAV is excellent food for
waterfowl, that leaves, stems, roots, and rhizomes are all commonly used,
and that P. perfoliatus is a particularly desirable species. Conversely,
SAV can also be significantly affected by waterfowl grazing. For instance,
Jupp and Spence (1977) reports that waterfowl grazing reduces SAV bLomass
by a factor of one to five in certain areas of Loch Leven, Scotland,, and
that overall, grazing removes about 20 percent of SAV biomass from the
Loch. In Chesapeake area, Rawls (in preparation) notes that feeding by
swans can transform a field of clover to "a hog wallow" overnight.
Intensive grazing by swans during the 1980-1981 winter was probably partly
responsible for the poor 1981 growth of P. perfoliatus at one of our
intensive study sites in the Choptank River (Todds Cove site).
Studies of the dependence of Chesapeake Bay waterfowl on SAV for food
have been conduced by Wilkins (1981), Rawls (in prep.), Perry et al. (1976)
and Stewart (1962); results have been summarized by Stevenson and Confer
(1978) and Munro and Perry (1981). Vegetable matter is an extremely
important food item for waterfowl in the upper Chesapeake Bay (Table 3).
Of some 2,747 birds examined by Rawls (in prep.), 78 percent of food
material was vegetable. Several species of SAV (P. perfoliatus, R.
maritima, M. spicatutn, and N. guadalupensis) were prominant items averaging
about 23 percent by volume in the diet of all waterfowl species
considered. The birds analyzed in this study were collected between 1958
and 1968 during fall and winter hunting seasons. That so many birds
contained significant quantities of SAV clearly indicates that SAV in the
upper Bay persisted far longer into the fall and winter seasons than it
does now. A shortened growing season, such as we now see in the upper Bay,
is another index of stress on SAV.
Munro and Perry (1981) also developed long-term (1972 to 1980) SAV and
waterfowl distribution data to test the hypothesis that variations in
waterfowl populations were related to variations in SAV abundance. Though
they found few statistically significant relationships between these two
factors, they observed that the most important waterfowl wintering areas
were also the most abundantly vegetated areas in recent years (lower
Choptank and Chester Rivers and Eastern Bay). Munro and Perry further
suggest that waterfowl have adapted to the SAV decline primarily by
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wintering elsewhere in the Atlantic Flyway and that future increases in SAV
abundance will produce positive responses in waterfowl populations. In
Loch Leven, Allison and Newton (1974) found a very good correlation between
SAV abundance and waterfowl densities, and Hocutt and Dimmick (1971) found
P. pectinatus to be the preferred food of some waterfowl species. Along
similar lines, Wilkins (1981) reports that waterfowl use of SAV areas in
Virginia is greater than in non-vegetated zones. Feeding studies suggest
that waterfowl grazing on SAV-associated invertebrate populations is
sufficiently intense (2 to 25 g m~2 dry material removed per year) to
influence infaunal densities.
Aside from the direct grazing pathway by which SAV can enter food webs,
the vast majority of studies, including those in the Chesapeake, indicate
that most SAV material enters food webs through detrital pathways, den
Hartog (1967), for instance, states that direct grazing is not an important
feature of SAV communities; Ott and Maurer (1977) found that only a small
fraction of Posidonia oceanica was consumed while live. Mann (1971), Day
(1967), and Harrison and Mann (1975) all reached similar conclusions that
agree with the general finding that direct grazing in most macrophyte-
dominated aquatic systems is small. Mann (1972) and others indicate that
SAV (and macrophytes in general) are a relatively poor source of food while
alive because of low nitrogen content. Mann (1972) suggests the following
scheme:
Thus, the process of decomposition of leaf litter in coastal
waters may take the following form. There is an initial period of
autolysis during which soluble materials leach out. Bacteria and
fungi then colonize the material and begin to render soluble by
enzyme action some of the previously insoluble material. The
micro-organisms absorb a proportion of the material they digest,
and some escapes. Populations of predators such as ciliates and
nematodes begin to build up. Macrobenthic organisms begin to tear
off pieces of the plant material with its attached community of
micro-organisms. They strip off the micro-organisms as the
detritus passes through their guts, the feces are recolonized and
the process is repeated by coprophagy. The cumulative result of
this process is a steady reduction in particle size, with a
consequent increase in surface-area-to-volume ratio, an increase
in microbial populations and a reduction in the Carbon:Nitrogen
ratio of the detritus.
In Chesapeake Bay, food web dependence seems to follow this pattern.
Brooks et al. (1981), in a study of a seagrass bed in Virginia, report that
seabass, pipefish, pigfish, and white perch are epibenthic feeders
utilizing amphipods and shrimp that are, in turn, detrital feeders. Data
further indicate that large predators (weakfish, bluefish, and sandbar
sharks) entered the SAV bed with little food in their stomachs and left
after feeding. Food items for these predators can generally be traced back
to a detrital source, some fraction of which is probably SAV in origin.
Again there was little evidence of direct grazing based on stomach
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TABLE 3. FOOD HABITS OF WATERFOWL IN THE UPPER CHESAPEAKE BAY,
MARYLAND a>b (FROM STEVENSON AND CONFER 1978)
Waterfowl Animal Vegetable Total
species food food (percent)
(percent) (percent)
Predominant: foods
percent total volume
Canvasback
47.76 51.85
Redhead
23.40 76.59
Lesser Scaup 47.56 52.47
Bufflehead 67.42 32.59
99.61 19.65 Baltic clam
18.42 Corn
16.32 Soft-shelled clam
14.29 Redhead grass
7.44 Widgeongrass
99.99 29.29 Corn
15.19 Redhead grass
14.74 Widgeongrass
10.53 Soft-shelled, Baltic, and
Mitchell's clams
6.73 Conrad's false mussel
100.03 20.48 Widgeongrass
12.32 Soft-shelled clam
11.59 Corn
10.85 Redhead grass
6.89 Mussel
100.01 13.52 Widgeongrass
11.85 Redhead grass
10.00 Barnacle
8.52 Fish
7.22 Mud crabs
Goldeneye
63.09 36.87
Mallard
5.00 94.80
99.96 19.44 Mud crab
17.67 Corn
14.88 Soft-shelled clam
9.22 Barnacle
9.00 Bivalves (unidentified
fragments)
99.80 24.14 Corn
10.41 Redhead grass
8.17 Widgeongrass
9.13 Other submerged
macrophytes
1.64 Conrad's false mussel
1.31 Soft-shelled clam
a Based on waterfowl gizzards collected during 1959-1968 hunting seasons
b Rawls (in press)
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TABLE 3. (continued)
Waterfowl Animal Vegetable Total Predominant foods
species food food (percent) percent total volume
(percent) (percent)
Black Duck 6.44 93.54 99.98 17.52 Corn
15.50 Redhead grass
14.20 Widgeongrass
8.40 Milfoil
1.91 Conrad's false mussel
1.76 Amphipods
Canada Goose 0.00 100.00 100.00 32.42 Grasses (Gramineae)
29.61 Corn
6.97 Milfoil
5.11 White clover
2.99 Crab grass
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analyses. In an extensive study of feeding habits in upper Bay SAV
communities, Bunker et al. (1981a) found little evidence of direct grazing
by fish, although some SAV seeds and plant leaves were found in stomachs.
Energy flow appeared to enter food webs as detritus and pass through
epifaunal and infaunal invertebrates to small and large fish. Carr and
Adams (1973) and Adams (1976) report similar results for fish communities
in Thalassia and Zostera beds. Bunker et al. (1981a) note that many
epifaunal species that are important food items are also closely associated
with SAV.
Attempts were also made to quantify food sources of the invertebrate
community using stable carbon isotope techniques to more closely relate SAV
to foodweb production. While other investigators have reported some
successes with this technique, studies in the lower Bay by van Montfrens
(1981) and Bunker et al. (1981b) in the upper Bay yielded interesting but
ambiguous results. The basic problem was that there were four or five
available sources of organic matter (SAV, phytoplankton, epiflora, benthic
microflora, and sediment detritus) each having a different 13g ratio.
Thus, unless an invertebrate had an extreme ^C ratio (either high or
low) there were an unlimited number of solution to the feeding equation.
With a few exceptions, most animals had intermediate values (-13 to -18)
suggesting that they were feeding on a mixture of detrital sources or a
single detrital source with an intermediate ^C value. In contrast to
this, Fry and Parker (1979) reported that SAV detritus was an important
feature of the organic matter supply in Texas seagrass systems. They found
that inshore animals had less negative ^C ratios (-8.3 to -14.5) than
did offshore animals (-15.0 to -19.0) and that the differences corresponded
to the less negative and more negative ^C ratios associated with SAV (-7
to -12.2) and phytoplankton (-20 to -26), respectively. There appear to be
several possible reasons for the differences in Chesapeake Bay and the
Texas studies. First, SAV in Texas were a dominant component of the
aquatic system and thus abundant SAV detritus was probably available
through most of the year. In contrast, SAV are presently a marginal item
in Chesapeake Bay. Furthermore, visual inspection of our study sites
indicates that most of the SAV biomass is probably rapidly exported from
littoral areas prior to becoming detrital particles of appropriate sizes.
Thus, animals in Chesapeake Bay SAV beds may not have sufficient
opportunity to feed on detrital SAV such that their *-3Q ratios closely
reflect SAV ratios. Secondly, phytoplankton are a dominant feature of
Chesapeake Bay and we have demonstrated that SAV communities can
effectively filter plankton from the water column via their baffeling
effects on currents (Boynton et al. 1981b). Thus, there is an effective
supply of nutrient-rich organic matter with a very negative ^C ratio
(-22) available to SAV food webs. In view of the above circumstances, it
is not surprising that ^C ratios did not clearly indicate SAV detritus
to be of dominant importance in Chesapeake Bay littoral zone foodwebs.
In summary, the majority of studies suggest that SAV is available
primarily as detritus and, in some localities, is very important. Because
of the complexity of organic matter sources in Chesapeake Bay and the
current marginal distribution of SAV, a quantitative assessment of SAV
importance as a food source was not possible. However, CBP results show
that SAV in the Bay is probably used by heterotrophs of one type or
another, and that SAV's physical structure concentrates other foods
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(phytoplankton, epiphytic algae, benthic microalgae) for animal consumption.
From a Bay-wide perspective, several recent studies provide additional
support for this argument. Kemp and Boynton (1981) constructed seasonal
and annual carbon budgets for three meter and six meter depth zones in the
mid-salinity portion of the estuary and found that on an annual basis
virtually all carbon inputs were used. They conclude that "despite the
considerable interactions both within the benthic community...and between
the benthos and other parts of the estuarine ecosystem... photosynthesis
ultimately limits...metabolism." If heterotrophic metabolism is organic
matter limited, it follows that SAV would also be used if, as has already
been shown, this material is a suitable food source. Boynton et al.
(1981c) have also shown that, in most portions of the Bay, the amount of
organic material being sequestered into deep sediments is a small fraction
(three to five percent) of that being produced in overlying waters, again
suggesting that if suitable organic matter is available, it will tend to be
refined. Thus, loss of SAV production may well lead to loss of animal
production.
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SECTION 3
THE HABITAT VALUE OF SAV SPECIES
IN CHESAPEAKE BAY
It is generally accepted that meadows of SAV serve as primary nursery
habitats for a diverse assemblage of commercially valuable biota and forage
species. Though many sampling studies have documented impressive numbers
of animals in vegetated areas, the mechanisms underlying the proposed
nursery role of SAV beds have only scarcely been elucidated. The two most
obvious explanations for the great abundance of SAV-associated organisms
are that SAV provides them with food and shelter.
These two features are supported by past research. It is clear that
SAV beds are among the most productive systems known (McRoy and McMillian
1977), and it is equally clear that most of this production is not grazed
by resident organisms (Ogden 1976). Instead, SAV detritus (Mann 1972, Klug
1980) and SAV epiphytes (Morgan 1980) provide most of the energy available
to secondary consumers in SAV beds. Recent studies, using ^Q.13c
ratios to trace the source of carbon present in secondary consumers, show
that SAV-derived carbon provides a significant fraction of the energy used
by secondary consumers in Texas turtlegrass meadows (Fry and Parker 1979),
but a rather small fraction in a newly established North Carolina eelgrass
bed (Thayer et al. 1978). To date there have been no comparative studies
of the growth rate of organisms living in (versus outside) SAV meadows.
Thus, only indirect generalizations can be made regarding the relative
importance of SAV-derived carbon for the growth and survival of associated
fauna.
Growing evidence suggests, however, that SAV protects its fauna from
their predators. For example, Nelson (1979) shows that eelgrass provides
amphipods significant amounts of protection from predatory finfish, and
Stoner (1980) shows that several kinds of benthic plants provide amphipods
protection from finfish. Plant surface area affords the best estimate of a
plant's protective ability. Recently, Heck and Thoman (1981) found that
turtlegrass and several species of red algae provide significant amounts of
protection to tethered crabs in field trials, and that both artificial and
live eelgrass provide grass shrimp (Palaeomonetes pqgio) significant
amounts of protection from predatory killifish (Fundulus heteroclitus).
STRATEGIES AND METHODS USED IN CBP HABITAT STUDIES
Against this background of published information, a series of studies
was designed to determine the extent to which SAV beds in Chesapeake Bay
serve as sites of densely aggregated animal species (indicating the use of
SAV for food) and as areas providing, through the physical presence of the
plants themselves, important amounts of shelter from predators for a wide
range of invertebrate and fish species.
Several field sampling studies were funded under the CBP to answer the
first question. One study compared standing stock and secondary production
of all macrofaunal ( > 0.5 mm) organisms that inhabited the bed with
similar estimates for nearby unvegetated bottoms (lower Bay). A second
study, with similar aims, was done at two upper~Bay eastern shore beds of
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mixed species composition (Parson Island and Todds Cove, Maryland). Both
these studies used a variety of sampling techniques, including seining,
trawling, and gill netting, depending on the size and mobility of the
target species. A third sampling study compared the use of the upper Bay
eastern shore grass bed at Parson Island by commercially important fishes
and blue crabs with a lower-Bay eelgrass bed, near the mouth of the York
River, and with unvegetated habitats. Trawling and gill-net sampling were
used in this study.
Field and laboratory experiments were also conducted to investigate the
ability of SAV to provide animals with shelter and protection from
predators. Field experiments used exclusion cages to evaluate the
intensity of predation by fishes and blue crabs on infaunal populations in
vegetated versus unvegetated habitats. By excluding predators from certain
areas, we estimated what predation-free infaunal population densities would
be in both vegetated and unvegetated areas. Then, by comparing ratios of
standing crop in vegetated and unvegetated areas before and after caging,
we estimated the amount of protection provided by vegetation in natural
conditions. In the lower Bay, caging experiments were performed at the
eastern shore Vaucluse Shores site; in the upper Bay, caging experiments
were carried out in the Todds Cove portion of the Choptank River.
Laboratory microcosm experiments were conducted to estimate the amount
of protection provided by SAV for infaunal bivalves, shrimps, crabs, and
fishes. The first set of experiments was designed to test the ability of
low, medium, and high density artificial eelgrass blades and rhizome mats
to provide protection for the infaunal bivalve Mulinia lateralis and for
juvenile blue crabs (Heck and Thoman 1981). Predators were adult blue
crabs. This set of experiments was conducted in wading pools (2.43 m in
diameter x 0.45 m in height) with recirculating water. The second element
used larger tanks (3.66 md x 0.9 mh) to examine protection for spot
(Leiostomous xanthurus) and silversides (Menidia menidia) by medium and
high densities of artificial eelgrass. Predators used were summer flounder
(Paralichthys dentatus) and weakfish (Cynoscion regalis). Laboratory
studies were also performed to evaluate the protection artificial and
living eelgrass, and living widgeongrass provided grass shrimp.
Experimental tanks were 1.3 md x 0.3 mh, and recirculated water was used.
Predators were killifish (Fundulus heteroclitus). Controls in all of these
experiments involved identical treatments conducted in unvegetated tanks.
Though these laboratory studies are similar, each was designed to
investigate different aspects of predator-prey relations in vegetated
habitats. These factors included studying the importance of prey escape
behavior, predator-prey size in relation to the size of SAV patches, and
differences in the amount of protection provided by different species of
SAV.
^N SITU ANIMAL ABUNDANCES
Invertebrates
In both the upper and lower Chesapeake Bay, field study results
indicate that infaunal abundance and diversity were higher in vegetated
than unvegetated areas. In the lower Bay, polychaetes dominated eelgass
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and widgeongrass areas, and bivalves dominated unvegetated sites, although
a large overlap in species composition existed between the two types of
habitats. These differences in dominant taxa are due partly to the type of
bottom. Muddy sediments deposited in seagrass beds favor deposit feeders
such as polychaetes; the sandy sediments in non-vegetated areas favor
suspension-feeding bivalves. Some of the other differences in species
composition occur because epifaunal, grass-blade associated invertebrate
species inevitably occur in sediment samples from SAV areas, even though
they are not residents of the infauna. Greater abundances in SAV areas are
due primarily to the large numbers of polychaetes, oligochaetes, isopods,
and grass-blade organisms collected at these sites.
In the upper Bay region, polychaetes dominated both SAV and unvegetated
sites, although numbers were greater in vegetated areas, as were overall
abundances of oligochaetes and isopods. Bivalves were more abundant: in
unvegetated areas in spring, but became more abundant in SAV beds during
summer (Bunker et al. 1981c, Ejdung et al. 1981). Amphipod abundances were
greatest at the unvegetated site and in the lower Bay. These differences
reflect the suitability of fine sediments for deposit feeders in SAV areas
versus the suitability of sandy sediments for suspension feeders in
unvegetated areas.
There were also some notable differences in the abundances of organisms
as related to salinity. Diversity was much lower at the low salinity (7 to
11 ppt) sites in the upper Bay than at the higher salinity (14 to 22 ppt)
site in the lower Bay. For example, maximum density at the high salinity
eelgrass site was 90,000 individuals per m^. The reason for the
relatively low infaunal abundances at the low-salinity site is not known.
Because unvegetated habitats support a virtually non-existent epifauna,
(defined as the animal assemblage growing on SAV and other emergent bottom
features), only vegetated habitats were sampled for epifaunal organisms.
Epifaunal density was higher at the more densely vegetated Todds Cove bed
than at the Parson Island bed. However, epifaunal densities per g SAV
(excluding polychaetes) were very similar at the two sites, ranging from
around 50 to 200 individuals per g SAV biomass. The isopod Erichsonella^
attenuata was dominant in Parson Island collections, and gastropods and
tanaids were dominant at Todds Cove. Amphipods, grass shrimp, and
chironomids were present at both sites (Staver et al. 1981).
Epifaunal abundances at the eelgrass sites in the lower Bay were much
higher than those found at the low salinity SAV sites in the upper Bay even
though polychaetes were not included in the upper Bay sampling. Numbers
ranged from around 20 individuals per g SAV in November to more than 9,200
individuals per g SAV in April. Dominant species included isopods,
gastropods, polycahetes, and barnacles (Diaz and Fredette 1981).
Differences in salinity between the two intensively studied areas were
probably responsible for the large abundance of barnacles in the lower Bay
and at least partly responsible for differences in total abundance between
s ites.
Finfish
Finfish sampling in the protected Todds Cove bed and the exposed Parson
Island site (Figure 8) found greater abundances and species richness in
vegetated than unvegetated bottoms, with greatest numbers occurring in the
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(d)FISI
24-
20-
7 16-
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protected SAV area. Fish densities at Todds Cove are among the highest yet
reported in the literature (Lubbers et al. 1981).
In addition, a plot of average weight per individual (Figure 7) during
the summer period suggests that the SAV bed at Todds Cove was continually
used as a nursery area for small fish while larger sized individuals
predominated in unvegetated reference areas. However, Heck (personal
communication) often found fish abundance (as indicated from otter trawl
samples) to be as large on sandy bottoms as in SAV at the Parson Island
site. This difference occurred because of the chance catch of schools of
spot (Leiostomous xanthurus) over sandy areas, and probably because SAV
abundance dropped precipitously during the course of the study. Large fish
predators such as bluefish and cownosed rays were found in both vegetated
and unvegetated habitats and, in both studies, more fish were taken at
night than during the day. There was little indication that the low
salinity SAV beds serve as nursery areas for commercially valuable finfish,
although any conclusion concerning such values might be biased due to the
severely depressed distribution of SAV in the upper Bay.
Fish sampling programs in lower Bay eelgrass meadows on the York River
and at Vaucluse Shores found much greater abundances and species richness
in these higher salinity SAV beds than on nearby unvegetated bottoms, and
much greater night than day catches (Brooks et al. 1981). Some large fish
predators, such as weakfishes and sandbar sharks, seem to forage most often
over vegetated bottoms while others, such as bluefish, appear to forage
indiscriminately over both vegetated and unvegetated areas.
The main conclusion of these studies on fish, that fish communities are
richer in vegetated than unvegetated areas, was expected, because similar
results have been found previously in other SAV habitats in North Carolina
(Adams 1976), Florida (Livingston 1975), and Texas (Hoese and Jones 1963).
What was not expected was the finding that few commercially important
finfish use the SAV beds as significant nursery habitats. This result is
surprising, because many juveniles of commercial species such as sea bass,
snappers, and groupers use SAV as nursery areas in latitudes south of
Chesapeake Bay (Adams 1976, Livingston 1975, Weinstein and Heck 1978). The
role of SAV for commercial fishes in the Chesapeake Bay system seems to be
largely that of a rich foraging place for adults although, once again, it
is important to emphasize that the current restricted distribution of SAV
may bias these conclusions. For instance, major spawning and juvenile
habitats for striped bass once existed in the upper Bay (Susquehanna
Flats), an area that was densely populated with SAV. More representative
patterns of commercial fish use of SAV habitat might best be evaluated
through historical correlations of SAV and juvenile fish distributions;
this is being done in the CBP's environmental characterization.
Blue Crabs
Information on blue crab abundances was collected at the same time
fishes were sampled at intensive study sites. Investigators found low
numbers of juvenile blue crabs in the upper Bay, but extremely large
numbers of blue crabs in eelgrass meadows of the lower-Bay. Up to 10,000
times as many blue crabs were found at the lower Bay than upper-Bay SAV
sites. Studies by Heck (personal communication), which used identical
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sampling techniques in both low and high salinity SAV beds and adjacent
unvegetated areas, found lower Bay crab numbers ranging from a few to a
thousand times more abundant than the upper Bay beds during the spring and
summer months. In addition, most of the crabs in the high salinity
eelgrass beds were juvenile females ( <^ 100 cm CW) that constituted the
breeding stock of future generations. Blue crab densities in unvegetated
areas were found to be as large or larger than those recorded from upper
Bay SAV beds. In contrast, far fewer crabs were taken on sand than in SAV
at the lower-Bay site. This difference in sand versus SAV crab abundances
between sites is probably due to the presence of many juveniles at the
eelgrass site, most of which require SAV for protection from predators.
The adult crabs in upper Bay SAV beds apparently do not require vegetation
for protection, except when molting, and occur on both vegetated and
unvegetated bottoms. The sampling gear used to collect crabs in both
locations was not efficient for collecting molting crabs. Thus, the role
of upper Bay SAV in providing protection to molting crabs may have been
greatly underestimated.
The conclusion drawn from these studies is that there seems to be only
a very limited blue crab nursery role played by upper Bay SAV beds. Lower
Bay eelgrass beds, however, serve as primary blue crab nursery habitats and
support very large numbers of juvenile blue crabs throughout the year.
STUDIES ON SAV AS PROTECTION
Results of soft-bottom predator exclusion experiments are often
difficult to interpret because of several commonly encountered problems,
including an inability to completely exclude predators from caged areas and
accurately estimate the effects that the presence of the cage itself
produces on the physical environment (Virnstein 1978, Dayton and Oliver
1980, Peterson 1979) . Caging studies conducted in Chesapeake Bay
encountered these problems, and the results of these studies, therefore,
must be interpreted with caution and circumspection.
Caging experiments in the lower Bay show that infaunal densities
increased in caged areas, and that this increase was most pronounced on
unvegetated bottoms (Orth 1981). There was little evidence that cages
altered the physical environment by changing sedimentation patterns,
although predators did periodically invade caged areas. Epifaunal
densities were higher in caged than uncaged areas shortly after the
installation of cages in eelgrass, but shading by cages subsequently
reduced eelgrass biomass and also led to declining epifaunal numbers.
Caging studies conducted in the upper Bay were less conclusive than
those conducted in the lower Bay. Some evidence suggests that predation
may be important in reducing infaunal densities; however, technical
difficulties, such as small fish passing through the cage walls, weaken the
results.
The first element of experimental predation studies shows that, in the
presence of artificial vegetation and rhizomes, juvenile blue crabs
received a significant amount of protection from predation. The infaunal
bivalve Mulinia lateralis, however, received very little protection from
either the artificial leaves or rhizome mat. The second element shows that
the predators Paralicthys dentatus (summer flounder) and Cynoscion regalis
(weakfish) captured progressively fewer spot (Leiostomous xanthurus), and
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silversides (Menidia tnenidia) as vegative cover increased from 0 to 22
percent (Orth 1981).
The second study (Heck and Thoman 1981) found that dense amounts of
artificial and live eelgrass, and live widgeongrass, provided grass shrimp
with significant amounts of protection from fish predators. Low and medium
densities of SAV did not provide much shelter. Furthermore, widgeongrass
provided greater protection per unit of surface area than either Living or
artificial eelgrass.
The seemingly disparate results of these microcosm experiments can be
understood within the following framework. Mobile epibenthic animals, such
as fish and blue crabs in the former study, and grass shrimp in the latter
study, do derive protection from predators in the presence of SAV»
However, the amount of protection received is probably a function of plant
surface area. Thus, SAV species with finely branched leaves and high
surface areas should provide better protection for prey taxa than plants
with simple leaves, all other factors being equal. Infaunal species, such
as burrowing bivalves, should generally receive less protection from
predators than epifaunal species of SAV habitats. For shallow burrowing
species like Mulinia lateralis, SAV beds provide little or no protection
from predators. However, for species that burrow below the SAV rhizome
mats, there should be reduced predator success in vegetated habitats
compared with that in unvegetated areas.
This hypothesis explains the results of the microcosm experiments and
is amenable to further testing and verification. It is likely, however,
that a number of other unstudied variables, such as size of predator and
prey in relation to SAV dimensions and the foraging strategy of the
predators, also influence predator-prey relations in SAV beds.
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SECTION 4
INFLUENCE OF SAV ON SEDIMENT DYNAMICS
Sediment processes in estuarine and coastal systems have been the focus
of numerous studies in the past several decades. Results of such studies
indicate that sediment processes strongly influence light attenuation in
the water column, produce shoaling or scouring, affect the composition of
benthic invertebrate communities, and influence the exchange of materials
between sediments and overlying waters. The sediment processes which
produce such effects can be characterized as a cycle that includes the
following components: (1) yield of "new" sediments from land erosion,
runoff, and shoreline erosion; (2) deposition of suspended sediments; (3)
resuspension of deposited sediments due to tidal and wave action and; (4)
transport of resuspended sediments to different locations.
The resuspension-deposition [(3) - (2)] portion of the cycle dominates
littoral zone sediment dynamics and can affect the health of SAV. A higher
cycling rate increases seston levels and reduces light availability to
SAV. This cycle is shown diagramatically in Figure 9 and suggests the
probable magnitude of different portions of the cycle in deep and littoral
estuarine areas. The diagram shows that wave action is the major source of
energy to resuspend unconsolidated sediments in the littoral zone, and
tidal energy provides the major force to resuspend and transport sediments
in deep water. The relative contribution of major new sources of sediment
to the Bay include material washed in from the watershed and shoreline
erosion. Most shoreline material enters the deposition and resuspension
cycle from the margins of the Bay, whereas fluvial sources follow the deep
water transport path.
REVIEW OF SEDIMENT PROCESSES
Aspects of sediment dynamics and turbidity patterns have received
considerable attention in Chesapeake Bay. Net sedimentation rates have
been repeatedly estimated for various portions of the open Bay (Biggs 1970,
Schubel and Hirschberg 1977, Brush et al. 1981) and for some tributaries
(Roberts and Pierce 1976, Yarbro et al. 1981). Increases in turbidity have
been documented for both the open Bay (Heinle et al. 1980) and for some
tributaries (Kemp 1980). The increases are apparently due to increased
algal stocks and seston levels. In a crude fashion, the decline of SAV
communities in northern Chesapeake Bay parallels increasing trends in
turbidity and nutrient loading. However, most of this work has been done
in deep areas of the Bay region. In this summary, we have focused on
vegetated and non-vegetated littoral areas less than two meters in depth.
In addition, previous measurements have largely been devoted to estimating
net sedimentation rates, and as Oviatt and Nixon (1975) have pointed out,
only a small fraction of total "sediment activity" is measured when such
estimates are made.
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Study Area
Sediment Cycling Depth,tn
Rate, g m~2y-l
Reference
Naragansett Bay
Departure Bay, B.C.
Surf Zone, California
Buzzards Bay, Mass.
York River, Va.
Upper Patuxent River
Lower Patuxent River
Littoral Zone, Non-SAV
Littoral Zone, SAV
7
3
7 -
6
8
2
3
3
0
- 18 x
x 103
330 x
x lO^
x 103
x 105
- 6 x
- 4 x
- 3 x
103
106
105
105
10^
7
32
2
15
4 -
10-12
1 -
1 -
6
2
2
Oviatt &
Stephens
Shepard,
Rhodes &
Haven &
Boynton
Boynton
Boynton
Boynton
Nixon, 1975
et ai. 1967
1963
Young, 1970
Mo ra 1 e s -Al amo ,
et al. 1981b
et al. 1981b
et al. 1981b
et al. 1981b
1972
WATERSHED
RUNOFF
TIDAL
ENERGY
SHORELINE
EROSION
LITTORAL
ZONE WAVE
ACTION
RESUSPENSION-
DEPOSITION CYCLES
IN ® LITTORAL 8
® DEEP-WATER ZONES
Figure 9. Major physical sediment processes in Chesapeake Bay showing
sources and energy for sediment transport.
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TABLE 4.
SEDIMENTATION RATE IN ram y"1 AT SEVERAL LOCATIONS IN CHESAPEAKE
BAY AND OTHER SELECTED ESTUARIES
Study Area
Narragansett Bay
Delaware Bay
Patuxent Estuary
Upper
Upper
Lower
Lower
Chesapeake Bay
Upper
Upper
Mid
Mid
Mid
Net Sedimentation
Rate, mm y~l
0.3 - 0.4
1.5
37.0
4.0 - 7.0
4.0
5.0 - 10.0
4.5 - 9.0
6.0 - 10.0
1.5
1.1
0.9 - 1.2
Technique
Mass Balance
Not available
Mass Balance
Pollen Dating
Pollen Dating
Sediment Traps
Pb210
Pollen Dating
Pollen Dating
Mass Balance
Pb210
Reference
Farrington 1971
Oostdam & Jordan 1972
Roberts & Pierce 1976
Brush et al. 1981
Brush et al. 1981
Boynton et al. 1981
Hirschberg & Schubel
1979
Brush et al. 1980
Brush et al. 1980
Biggs 1970
Hirshberg & Schubel
1977
A considerable number of measurements of net sedimentation rates and
sediment cycling rates (summation of resuspension-deposition) were made in
estuarine environments using a variety of techniques. We summarize some of
these measurements in Table 4 with special emphasis on Chesapeake Bay. Net
sedimentation estimates for areas in the tidal Bay system ranged from 0.3 to
37 mm y~l. This broad range is not surprising in view of the strong
gradients in seston concentration and sediment input rates encountered in
estuarine systems. In the turbid upper section of Chesapeake Bay, for
example, estimates ranged from 4.5 to 10 mm y~l; in the mid-salinity region,
rates ranged from 0.9 to 1.5 mm y~^. A similar pattern was evident in the
Patuxent River. To compare the magnitude of net sedimentation with sediment
cycling rates (i.e. deposition-resuspension-deposition), accumulation rates
(in mm) were converted to a weight basis. On this basis, net sedimentation in
Chesapeake Bay ranged from about 600 to 6,000 g m~2y-l of dry sediments.
In sharp contrast to these values, sediment cycling rates were far higher,
especially in shallow water environments, and indicate that cycling dominates
sediment processes. Significantly, an estimate from an SAV community
(Choptank River) was among the lowest we encountered in estuarine systems and
illustrates the importance of these communities in stabilizing sediments at
the surface.
ROLE OF SAV IN SEDIMENT PROCESSES
Several previous investigations have led to an understanding of the
mechanisms by which SAV can modify sediment substrates (Ginsburg 1956,
Ginsburg and Lowenstam 1958, Wanless 1981). Specifically, the rhizome-root
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complex can stabilize sediments, and the physical structure of seagrass blades
and epiphytes can slow currents, allowing sediments to settle. This complex
can also substantially reduce current-and-wave-induced resuspension.
Considerable evidence suggests that SAV can play an important role through
those mechanisms in nearshore sediment dynamics. Scoffin (1970) found that
dense beds of Thalassia protected bottom sediments from current speeds up to
70 cm sec~l; extensive bottom-sediment erosion did not begin until current
speeds reached 150 cm sec~l. In Florida, Ball et al. (1967) found that
bottom erosion was minimal in seagrass covered areas following the passage of
a hurricane, but exposed sand areas were extensively modified. Also in
Florida, Wanless (1981) found sedimentary sequences that probably resulted
from trapping and consolidation of suspended particles by SAV. He states that
the vertical sediment record indicates increased trapping of storm-generated
sediments and decreased bedload transport as SAV became established. In a
Zostera bed in Denmark, Christiansen et al. (1981) infer, from inspection of
sediment cores and historical SAV distributions, that the Zostera die-back in
the 1930's resulted in disturbance and mobilization of nearshore sediments and
a movement of sediments into a local harbor. Moreover, Christiansen
determined that coastal morphology was stable during periods when eelgrass was
present, but significant changes occurred when it was absent.
In the Chesapeake area, Orth (1977) reports that sediment particle
diameter decreased, and organic matter content and irifaunal densities
increased in bottom sediments in areas with SAV compared with those that did
not have such coverage. Based on these findings and observations that showed
less sediment disruption during storms in vegetated zones and less dispersion
of dyed sand patches, Orth concludes that SAV is effective at trapping and
consolidating suspended sediments. It appears that substantial beds of SAV
can effectively modify littoral zone sediment dynamics through sediment
trapping and consolidation of sediments at the surface. Because sediment
processes may be most active in littoral zones, sediment processes in deeper
areas may also be affected by lateral transport and deposition (Webster et al.
1975).
CHESAPEAKE BAY PROGRAM STUDIES
We hypothesized that SAV communities can play a significant role in
modifying littoral zone light regimes by baffling of wave and tidal currents,
thus reducing sediment resuspension. Conversely, we hypothesized that high
turbidities in some areas of the Bay have contributed to the decline of SAV
communities. Chesapeake Bay Program studies were designed to (1) document
patterns of light attenuation on several time scales (seasonal, diel, tidal
cycle) in littoral communities having SAV and in those not having SAV; (2)
relate observed light attentuation patterns to concentrations of materials in
the water column to identify the relative importance of light attenuating
factors; and (3) examine the potential of SAV communities as natural sediment
traps.
Data on suspended sediments and light attenuation from intensive study
sites are presented in Figure 10. This figure shows differences between
vegetated and non-vegetated areas plotted against tidal stage for Todds Cove
in the Choptank River and Parson Island sites in Eastern Bay. These plots
indicate that as turbid offshore waters enter SAV beds on rising tides,
sediments are effectively removed, thus increasing light transparency,. It
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HIGH
V)
o
UJ I
Z '
5 2
tr o
UJ q>
u. o>
t >
0 c
o
LJ in
O >
o
o>
o>
TIDAL HEIGHT
(a) SESTON CONCENTRATION
20-
60-
40-
20-
0-
(b) EXTINCTION COEFFICIENT
0
Low Tide
T
3
T"
9
TIME , hours
High Tide
\2
Low Tide
Figure 10. Percent difference between vegetated and non-vegetated habitats for
(a) suspended sediment and (b) attenuation coefficient during a tidal
cycle.
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appears that by high tide, turbid inflowing waters have exceeded the filtering
capacity of the bed. As tidal height decreases, the bed apparently
effectively filters sediments because the gradient between vegetated and
non-vegetated areas again increases to a maximum.
Other qualitative observations show that SAV varies in its ability to
decrease turbidity. Boynton et al. (1981b) found that areas with SAV,
dominated by P. perfoliatus (a highly branched species), were more successful
at decreasing turbidity than at a site where P. pectinatus (a thin-bladed
single leaf species) dominated. Even under conditions when SAV biomass was
comparable between the two areas, it appeared that P. perfoliatus was more
effective in clarifying surrounding waters. On several occasions, turbid
water was observed entering a P. pectinatus bed; turbidity increased rapidly
in the P. pectinatus sections, but remained considerably lower in the P.
perfoliatus areas. Visually, the P. perfoliatus beds appeared as clear areas
against a turbid background.
Other qualitative data show that water clarity is affected by the size of
an SAV bed. On several occasions, Boynton et al. (1981b) noted turbidity
gradients within an SAV bed. Turbidity was greatest at the edge of the bed
and decreased with distance into the bed. It seems that for a given off-shore
turbidity regime there is a "critical bed size" above which SAV can
effectively modify the local environment in a fashion favorable for continued
growth (reduce seston levels; increase light penetration). Small SAV beds may
not be able to so modify local light regimes and would thus be disadvantaged
if light is limiting growth.
Interpretation of data concerning sediment cycling in littoral zones is
quite difficult. Boynton et al. (1981b) hypothesized that there would be
substantial differences in the amount of material collected in both surface
and bottom cups of sediment traps deployed in SAV beds and non-vegetated
reference areas. They anticipated that the structure of SAV would effectively
reduce resuspension and hence values from the bed would be markedly lower. In
fact, while values from the SAV bed were lower, dramatic differences were not
consistently evident. It is possible that most resuspension - deposition
occurred during storm events and that during these events wave energies were
high enough to overcome the baffeling effect of SAV in these marginal
communities, leading to substantial deposition in all areas. Further
inspection of climatic data may clarify this possibility. Another possibility
is that material collected in cups in the SAV area was a mixture of
resuspended materials and true sedimentation, while resuspended material made
up the bulk of the collection in the reference area.. Substantial reduction in
seston-based turbidities (Figure 9) support this suggestion.
In spite of the lack of large differences betwen SAV and references area
collection, there was a reasonably consistent pattern evident with respect to
collection rate and SAV biomass, particularly for the bottom collection cups
(Figure 10). Both surface and bottom cups had small collection rates when
biomass was above 150 g m~^ and rates five to 10 times higher when biomass
was bewlow 50 g m~2. When viewed in this fashion, it appears that
resuspension is clearly reduced in proportion to SAV biomass.
Given the dynamic nature of the sediment-water interface in littoral
environments, estimates of net sediment retention/compaction are exceedingly
difficult to obtain and clearly beyond anything that, can be inferred from
sediment traps. A crude estimate can, however, be obtained utilizing the
seston data presented earlier. If we attribute the tidally related changes in
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seston concentration to dposition, then seasonal estimates can be made. If we
take 90 mg L~l as an estimate of mean seston concentration in littoral
reference areas (Boynton et al. 1981b) and, as suggested in Figure 9, assume
that approximately 50 percent of the suspended material is deposited on each
tide, then daily deposition can be estimated. Taking six months as the period
when substantial SAV biomass is present allows expansion of diel estimates to
seasonal estimates. This procedure yields daily deposition rates of about 63
g m~2d~l and seasonal estimates (180 days) of 1200 g m~2. Assuming that
there is about equivalent to 0.2 cm per growing season. The potential errors
associated with such a calculation are obvious, but it is interesting that
such a reasonable value emerges. Little information is currently available to
suggest whether or not this material is sufficiently consolidated to be
considered as lost to the sediment deposition-resuspension-deposition cycles.
For example, we do not know if material deposited during the summer period
when SAV are present is subsequently lost when SAV die-off in the early fall.
Considering the important role of roots and rhizomes in this process and the
low below-ground biomass observed in Chesapeake Bay SAV communities, it seems
doubtful if this material is permanently consolidated at present, although it
may have been in the past.
Some evidence suggests that SAV can cause sediment to compact, thus
preventing resuspension of sediments. Net sediment retention-compaction can
be crudely estimated by using the suspended sediment data presented earlier.
If we attribute the tidally related changes in seston concentration to
deposition, then seasonal estimates can be made. If we take 90 mg L~l as an
estimate of mean suspended sediment concentration in littoral reference areas
(Boynton et al. 1981b) and, as suggested in Figure 10, assume that
approximately 50 percent of the suspended material is deposited on each tide,
then daily deposition can be estimated. Taking six months as the period when
substantial SAV biomass is present allows for expansion of diel to seasonal
estimates. This procedure yields daily deposition rates of about 63 g
m~2d-l and seasonal estimates (180 days) of 1,200 g m~2. Assuming that
there is about 0.6 g cm~3 of inorganic material in consolidated sediments,
this deposition is equivalent to 0.2 cm per growing season.
The potential errors associated with such a calculation are obvious, but
it is interesting that such a reasonable value emerges. Currently, little
information is available to suggest whether or not this material is
sufficiently consolidated to be lost to the sediment
deposition-resuspension-deposition cycles. Because of the important role of
roots and rhizomes in this process and the low below-ground biomass observed
in Chesapeake Bay SAV communities, it seems doubtful that this material is
permanently consolidated at present. However, SAV biomass levels
characteristic of the early 1960's may have been high enough to prevent
significant resuspension of bottom sediments. Likewise, root-rhizome
structure of these times may have more effectively consolidated bottom
sediments.
COMPARISON OF SEDIMENT SOURCES WITH DEPOSITION IN SAV BEDS IN CHESAPEAKE BAY.
To place the sediment-trapping characteristics of SAV in the context of
larger-scale sediment processes in Chesapeake Bay, we have developed a series
of calculations that compare the magnitude of two major sediment sources to
the deposition rate observed in SAV communities (Table 5).
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'E
o>
UJ
oc.
2
O
(-
CO
O
Q,
UJ
Q
I-
2
UJ
Q
UJ
CO
1000-
500-
0-
NEW SEDIMENTS
BOTTOM VALUES
SURFACE VALUES
0
50 100 150 200
SAV BIOMASS, grrf2 (dry weight)
250
i'igure 11. Relationship between SAV biomass and sediment deposition (adapted
from Boynton et al. 1981b).
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TABLE 5. ESTIMATED ANNUAL SEDIMENT DEPOSITION IN SAV COMMUNITIES RELATIVE
TO SEVERAL SEDIMENT SOURCES IN CHESAPEAKE BAY FOR 1960 AND 1978.
(ALL VALUES IN METRIC TONS PER YEAR x 10&)
Sources
Riverine Input3
Shoreline Erosionb
Total
Deposition in SAV CommunitiesC
Time
1960
0.491
0.375
0.866
0.72
Periods
1978
0.491
0.375
0.866
0.08
alncludes Bay and tributaries above the mouth of the Potomac River
(1.5 x I09m2).
"Annual estimates of riverine and erosional sediment inputs from Biggs
(1970). Assumed that inputs were relatively constant between time periods,
cDeposition in SAV communities estimated to be 1200 g m~2y-l (Boynton
et al. 1981; Ward, pers. comrn.)
Major sediment sources include riverine input and shoreline erosion to
the portion of Chesapeake Bay above the mouth of the Potomac River. We
assume that estimates developed by Biggs (1970) are representative of both
the early 1960's and late 1970's periods. The amount of sediment deposited
during the SAV growing season was calculated from data of Boynton et al.
(1981b), who estimate that some 1,200 grams of sediment may have been
deposited per square meter of SAV community over an estimated 180-day
growing season. Table 5 indicates that a large percentage of sediment may
have been deposited in SAV communities during the 1960 period. However, in
the late 1970's, when SAV distributions were severely reduced, the amount
of deposition was less than 10 percent of the input. Although this
calculation is preliminary, it suggests that SAV in the past may have
played an important role in sequestering sediments in Chesapeake Bay, and
that the amount of sediment presently deposited in SAV communities is small
relative to estimates of sediment input.
LIGHT LIMITATION OF PHOTOSYNTHESIS
Although there appear to be emerging patterns concerning the role of
SAV in modifying littoral zone turbidity and sediment cycling processes, it
is still necessary to establish relationships between ambient light
intensities and functions of SAV growth. Kemp et al. (1981) conducted a
number of experiments to establish SAV responses (photosynthetic rate) to a
range of light intensities. The two species investigated were P.
perfoliatus and M_^ spicatum. They found that light saturated
photosynthesis occurred at about 500-600 uEinsteins for both species, and
that about 150 uEinsteins provided enough light to reach 50 percent of the
maximum rate of photosynthesis (1/2 Pmax is similar to the Michaelis-Menten
half saturation constant).
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To extend these data to broad geographic regions of northern Chesapeake
Bay, we examined attentuation coefficients characteristic of several
locations during growing seasons (May to September). In Figure 12, a
typical summer light intensity (just below the water surface) of 1,000
uEinsteins was attenuated using a range of attentuation coefficients (1.0,
2.0, 3.0) so as to display the light energy reaching various depths. Also
plotted on the diagram (dashed horizontal lines) are the light intensities
at Pmax, 1/2 Pmax, and 1/4 Pmax for _£._ perfoliatus. Thus, if an
attentuation coefficient of 1.0 was observed, sufficient light to maintain
light saturated photosynthesis reached a depth of 0.6 meters. The depth at
which sufficient light penetrates to maintain photosynthetic rates at 1/2
Pmax is also given for various locations (Table 6).
These data suggest that in most locations light saturated
photosynthesis does not occur in water depths greater than 0.25 to 0.5
meters. Moreover, sufficient light does not penetrate beyond 1.0 meter to
maintain photosynthetic rates at 1/2 Pmax. Thus, it appears that only in
the most shallow or most clear environments is light not limiting to SAV
photosynthesis. These calculations may underestimate the limiting role of
light because they are based on a subsurface light intensity of 1,000
uEinsteins, a value reached mainly during the middle of a typical summer
day. On overcast days and in the early morning and late afternoon, values
are considerably lower, and the depths of Pmax would be more shallow.
Additional work, now in progress, may allow the development of better
relationships between photosynthesis and light, as well as between
photosynthesis and biomass.
TABLE 6. LITTORAL ZONE LIGHT EXTINCTION COEFFICIENTS DURING THE SUMMER
IN CHESAPEAKE BAY DEPTHS AT WHICH 1/2 Pmax OCCURS ARE SHOWN
DATA FROM TWILLEY 1981
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Location
Upper Bay
Lower Bay
Tributaries
Upper Patuxent
Lower Patuxent
Eastern Bay
Lower Choptank
Extinction
Coefficient
2.2
2.4
2.4
3.5
1.7
1.3
1.9
Depth 1/2 PMax
0.8
0.7
0.7
0.5
1.1
1.4
0.9
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1000
tn
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Figure 12.
Relationship between surface light intensity and light
attenuation of the water column, expressed at attenuation
coefficients (K). Data from Boynton et al. 1981.
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SECTION 5
NUTRIENT PROCESSES IN SAV COMMUNITIES
This section summarizes current knowledge of the effects of SAV
communities on littoral zone nutrient regimes. Submerged vascular plants
have two potential sources of nutrients available for uptake and
incorporation into new biomass. Dissolved nutrients in the water can be
taken up by leaves and stems, with some species using sediment nutrient
reservoirs. SAV can also modify chemical conditions in sediments so that
oxidized and reduced conditions prevail and can lead to several
transformations of nitrogen and phosphorus.
This section addresses four categories of nutrient processes
including: (1) nutrient concentration and fluxes in SAV communities; (2)
nutrient regulation of SAV growth; (3) nitrogen transformations, including
fixation, nitrification, and denitrification; and (4) nutrient releases
associated with decomposition processes.
NUTRIENT CONCENTRATIONS AND FLUXES
Recent studies in Chesapeake Bay and global literature support the
notion that SAV communities buffer nutrients by removing them from the
water column, thus reducing concentrations. Pertinent examples from
studies in Chesapeake Bay include the work of Twilley et al. (1981) and
Kaumeyer et al. (1981). Twilley conducted a series of water quality
measurements in the Choptank River estuary, an eastern shore tributary.
Measurements were taken along the longitudinal axis of the estuary on a
monthly basis from April through September. At one point adjacent to an
intensively studied SAV community, water quality measurements were taken in
an SAV bed in waters of moderate depth (4 m), and along the longitudinal
axis of the estuary (deep water). Throughout this period, nutrient
concentrations were consistently and dramatically lower in littoral, as
opposed to deeper, sections along that sampling transect. Specificially,
ammonium concentrations were one to 10 times lower, nitrate two to 10 times
lower, and orthophosphate generally two to four times lower in the SAV
community than in deeper offshore waters. Similar results were obtained at
the Parson Island site, where nutrient concentrations appeared to be lower
in an SAV community than in adjacent offshore waters (Kemp et al. 1979).
An important ecological implication of these findings is that SAV may
compete with phytoplankton for nutrients, thus reducing potential excessive
algal blooms.
To elucidate mechanisms causing nutrient concentrations to be lower in
the littoral zone, Kaumeyer et al. (1981) initiated a series of studies
using a variety of sampling chambers in an SAV bed in the Choptank River
estuary. The chambers were spiked with different levels of ammonium,
nitrate, and phosphate, and concentrations of these nutrients (as well as
dissolved oxygen) were measured hourly over six to 12 hour periods during
both day and night. A typical set of results is given in Figure 13.
Nutrient concentrations rapidly decreased from initial-spiked
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90-i
(Q)NON-VEGETATED ( Depth 0.127m)
SPIKED 80//g-at IH
16 pq-at r'POj
cr
UJ
CD
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90-i
60-
30-
0
T 1 1 1
(C)SAV (Depth 0.51m)
Figure 13.
I I I I I
22 23 00 01 OZHrs.
NIGHT
Chamber nutrient flux at Todds Cove, Choptank River,
July 1980 for ammonia-nitrogen and dissolved inorganic
phosphate. Day and night nutrient concentrations in
experimental chambers all given for (a) non-vegetated
sites, (b) plankton, and (c) vegetated sites.
473 thru 4 77
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concentrations to lower levels, and generally returned to near-ambient in
less than 24 hours. Uptake rates, in most cases, depended on nutrient
concentrations in the chambers. In addition, Kaumeyer et al. found where
littoral communities were exposed to both nitrate and ammonium, both forms
of nitrogen were taken up, although ammonium was generally taken up
somewhat faster. These investigators did not attempt to partition uptake
between plankton, benthos, and SAV, but apparently uptake rates were fast
in all littoral zone communities investigated. These results suggest that
there are mechansisms, not restricted to SAV, through which nutrients,
entering the littoral zone, can be rapidly removed. Howard-Williams (1981)
reports similar results from dosing a dense bed of P. pectinatus. He found
that this community could rapidly reduce nutrient concentrations, and that
filamentous algae associated with SAV were responsible for most of the
phosphorus uptake.
In addition to these studies, substantial observational and
experimental evidence indicates that SAV removes dissolved nutrients from
the water column at a high rate. Mickle and Wetzel (1978) investigated
SAV-nutrient exchanges in laboratory systems containing Scirpus and
Myriophyllum. In these flow-through systems, nitrate and ammonium were
introduced, and output concentrations monitored. Ammonium and nitrate
concentrations decreased substantially after passing through SAV,
particularly in the Myriophyllum beds. We conclude that littoral SAV
systems are effective in damping higher concentrations entering the
littoral zone following rainfall events. McCord and Loyacano (1978)
further found that Chinese water chestnut (Eleocharis deucis) in freshwater
ponds is effective in removing nitrate and ammonium from the water column.
In their studies, ponds with water chestnut had lower concentrations of
both nutrients and phytoplankton. Net nitrogen removal rates were
estimated to be in the range of 4 mg m""^"!. Twilley et al. (1981)
found that nutrients (ammonium, nitrate, and dissolved inorganic phosphate)
are removed at substantial rates from brackish-water ponds dominated by P.
perfoliatus and R. maritima.
Although it appears that SAV reduces nutrient concentrations, existing
evidence suggests that when loading rates and concentrations of nutrients
reach certain levels, SAV is no longer effective. In fact, SAV can be
stressed at these elevated levels of nutrients through several mechanisms.
For example, Jupp and Spence (1977) found that in Loch Leven, Scotland, the
diversity of SAV was reduced from about 23 species in 1910 to about 12 in
1975, and that this pattern of decreased diversity and abundance generally
paralleled the increase in cultural eutrophication. They found that when
phosphorus levels approached 2 ug-at I~l, algal stocks increased
(particularly blue-greens), while SAV distribution, species diversity, and
abundance decreased to very low biomass levels (0 to 20 g m~2). They
further suggest that algal blooms may decrease SAV vigor through
attenuation of light and increases in pH. Chlorophyll levels in Loch Leven
were reported to exceed 200 ug I~l, a concentration far in excess of
those normally found in Chesapeake Bay at this time. They found that SAV
tended to recover when chlorophyll levels were decreased to the vicinity of
20 to 40 ug I"1.
In summary, Jupp and Spence (1977) constructed the following story
concerning the effects of cultural eutrophication on SAV distribution.
These events are similar to the sequence of decline in Chesapeake Bay SAV.
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Increased loading of nutrients to Loch Leven, in particular phosphorus,
increased algal stocks that led to a decrease in available light, both
through attenuation in the water column and through fouling on SAV by
epiphytic species. The light restriction led to a restricted depth zone in
which SAV species could flourish, and this, of course, was in shallower
water. This restricted zone of growth was in an area where SAV was
subjected to increased stresses by both wave action, and decreased light
due to resuspension of littoral sediments and intensive grazing by
waterfowl.
In other studies, similar results were found. Mulligan et al. (1976)
found that SAV subjected to very high levels of nitrogen and phosphorus
fertilization (4,000 g-at L~l of nitrogen, 25 ug-at L~l of phosphorus)
were eliminated in pond ecosystems. They conclude that high loading rates
of nitrogen and phosphorus favor phytoplankton stocks. Similar conclusions
were reached by Sand-Jensen (1977) and Phillips et al. (1978). In the
Chesapeake Bay area, experimental work by Twilley et al. (1981) suggests
that loading rates, resulting in initial nitrogen (N) and phosphorus (P)
concentrations of 60 and 6 ug-at L~l, respectively tend to favor the
development of algal stocks and the elimination of SAV.
Thus, it appears that the role of SAV in buffering nutrient
concentrations in the nearshore zone has at least two aspects. If loading
rates are moderate, SAV (and other littoral zone components) can rapidly
decrease these concentrations to low levels. If loading rates and
resulting concentrations are sufficiently high, SAV is disadvantaged and,
in some cases, lost from the system and replaced by a phytoplankton
component.
NUTRIENT REGULATION OF SAV GROWTH
Over the past fifty years, considerable (though sporadic) research has
been directed toward understanding sources from which SAV obtains
nutrients. Various studies indicate that root uptake is the major
mechanism through which nutrient demands are met (McRoy and Barsdate 1970,
Cole and Toetz 1975, Nichols and Keeney 1976, Twilley et al. 1977). In
contrast to this, other evidence suggests that foliar uptake, under some
conditions, is the predominant pathway (Nichols and Keeney 1976, Cole and
Toetz 1975). We suggest that nutrient uptake is facultative in that if
nutrient concentrations in the water column are very low, and adequate
nutrient reserves exist in the sediment, then root uptake will dominante.
Alternatively, if adequate nutrients are present in the water column, then
foliar uptake will predominate.
To define ammonium uptake kinetics (Marbury et al. 1981), experiments
were conducted in the upper Bay using P. perfoliatus. Foliar uptake
matched classical Michaelis-Menten kinetics for both day and night
conditions, with root uptake also partially described by these kinetics.
In several experiments, Marbury found that K,,, (KJJ, is the substrate
concentration with the rate of nutrient uptake's one-half of the maximum
uptake) approximates 15 u moles and corresponds to an uptake rate of
approximately 0.19 to 0.31 mg N g of plant~lhr~l. These rates are
comparable with those reported by other authors for several different
species of SAV (Nichols and Keeney 1975, McRoy and Alexander 1975, Cole and
Toetz 1975). During periods of rapid growth (May-July), total
479
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concentration of inorganic N in the water column often approaches or
exceeds values of K^, and the interstitial concentrations of ammonium are
in the range of one to three m moles. Because of this, it is doubtful that
nitrogen limits submerged macrophytes in the mid-salinity and brackish
water portions of Chesapeake Bay. (Marbury, personal communication). To
the contrary, both observational and experimental evidence indicate that
nutrient loading, particularly of N, may be sufficiently high to favor the
replacement of SAV communities by phytoplankton (Phillips et al. 1978,
Twilley 1981).
In the lower Bay, SAV growth may be somewhat more regulated by nutrient
availability. Orth (1977) added large amounts of commercial N and P
fertilizer to the sediment surface in Zostera beds and found significant
increases in length, biomass, and number of stems. Sediments were sandy
and may have had low concentrations of interstitial nutrients as has
previously been reported for such sediments. This, coupled with
characteristically low-nutrient concentrations in the water column, may
produce nutrient-limited growth.
NITROGEN FIXATION, NITRIFICATION, AND DENITIRIFICATION
This section discusses three important processes in the nitrogen
cycle: nitrogen fixation, nitrification, and denitrification. SAV's
ability to convert dissolved nitrogen gas into an organic form ("fixing")
is important during times of inorganic nitrogen impoverishment.
Nitrification is the bacterial-mediated oxidation of ammonia to nitrate in
the presence of free oxygen; denitrification is the reverse process of
bacterial-mediated reduction in the absence of free oxygen. These last two
processes provide energy to certain bacteria depending on whether the
environment is aerobic or anaerobic.
These three processes are of ecological as well as of water quality
significance, because they represent sources and sinks of nitrogen and may
reflect the potential for regulating phytoplankton growth in many areas of
Chesapeake Bay. A substantial range in N-fixation rates has been observed
in seagrass communities. It appears that in nutrient-poor waters (low
ambient concentrations of N in both the water column and in sediments), SAV
growth can be N-limited (Patriquin 1972). Much of the nitrogen used in SAV
growth may be supplied by N-fixation (e.g., Capone et al. 1979). Patriquin
(1972) reports high rates of N-fixation in Thalassia beds, and Patriquin
and Knowles (1972) conclude, based on studies in a variety of Thalassia
beds in the Caribbean, that most of the N requirements are supplied by
fixation. Fixation rates in these studies range between two to 10 mg-at
irf 1 d~ 1, rates that are capable of supporting most, if not all, of the;
calculated N demand.
In contrast to these results, Lipschultz et al. (1979) report low rates
of N-fixation in seagrass meadows in the Choptank River estuary. In the
areas investigated by Lipschultz, nitrogen was abundant in the water
column, and sediment reserves were substantial. Thus, it appears that
N-fixation is facultative in the sense that if severe N-limitation exists
in environments otherwise amenable to seagrass growth, N-fixation becomes a
prominent feature. Conversely, in those systems, such as the mid-salinity
and brackish zones of Chesapeake Bay, where abundant reserves of ammonium
are contained in interstitial waters, N-fixation is simply not required.
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Unfortunately, less is known about the rates of nitrification and
denitrification in seagrass ecosystems. To our knowledge, the only
published information available at this time is the work of lizumi et al.
(1980). In this study, a Zostera bed was investigated using N^-5
techniques. The authors report that rates of denitrification ranged from
0.5 to 1.2 x 10~9 g-at g'^h"-'-, and that nitrification rates were
quite similar. When these values are converted to an areal basis,
denitrification and nitrification are important aspects of the
sediment-water nutrient cycle. lizumi et al. (1980) report that high
nitrification rates are directly coupled to denitrification, as expected,
because the entry product (nitrate) to the denitrification pathway is the
end product of nitrification. Moreover, they found that nitrification in
anoxic sediments was made possible by the transport of oxygen from the
foliar portion of SAV to the root zone. Thus, there were small microzones
of oxidized sediment in which nitrification could proceed. After nitrate
was produced, it diffused into the anoxic zone, where denitrifying bacteria
rapidly transformed nitrate to nitrogen gas.
In studies conducted in an SAV community in the Choptank River and in
brackish-water experimental ponds, Twilley et al. (1981) found that
denitrification rates in both areas ranged from 50 to 100 uM m~2d~l;
however, rates tended to be lower in SAV than in non-vegetated littoral
zones (although such differences were not statistically significant).
Jenkins (personal communication) found much higher rates of denitrification
(about 200 to 300 ug-at N m'^d"1) in deeper portions of Chesapeake Bay
waters in the spring when nitrate was abundant in overlying waters. Rates
were low or undetectable at other times of the year when nitrate was not
present in the water column. Evidence that nitrification rates are
substantial in SAV communities is accumulating from studies of SAV beds in
the upper Bay, and these rates appear to be substantially higher than
nitrification rates in soft-bottom communities lacking SAV.
What then are the mechanisms responsible for these observations? At
this point, it seems that oxygen produced in the foliar portions of SAV is
translocated to the roots and from the roots into the interstitial waters,
supplying the oxygen needed to support nitrification. Although the nitrate
produced could be used in denitrifiction, evidence at this point indicates
that other processes may out-compete denitrification for this nitrate.
Recent studies by Terlizzi (personal communication) of diel nitrogen
cycling in P. perfoliatus-dominated microcosms (700 liter with natural
estuarine sediments and water) showed that nitrate concentrations increased
in the roots during the daylight hours and decreased at night with a
concomitant appearance of nitrite. They suggest that the oxygen produced
in this reaction was used in support of root respiration at night, yielding
nitrite. The eventual fate of the nitrite produced in these roots is not
currently known, although some of it leaked from the roots into the
interstitial and overlying waters; the nitrite had nearly vanished by the
return of daylight. Whether or not nitrite was oxidized to nitrate or
reduced to nitrous oxide or nitrogen gas is presently not known. Thus, in
contrast to the studies of lizumi et al. (1980), these results suggest that
denitrification is important in deep waters when nitrate is abundant in the
water column. In SAV communities, measurements of denitrification have, by
and large, indicated that rates are small. Nitrification, on the other
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hand, appears to be enhanced by the translocation of oxygen to the root
zone, but all of the nitrate produced does not appear to enter the
denitrification pathway.
NUTRIENT RELEASE AND OXYGEN DEMAND ASSOCIATED WITH SAV DECOMPOSITION
A great deal of evidence points to the importance of submerged and
emergent macrophytes as a source of detritus available to coastal and
estuarine heterotrophs. Paralleling this, there is a considerable amount
of scientific literature concerning the decomposition and release of
nutrients for some higher plants, and in particular, decomposition
characteristics of Spartina. Surprisingly, less is known about
decomposition characteristics of submerged macrophytic vegetation. Several
studies are available, however, that are pertinent to a discussion of the
decomposition process.
In addition to the role of SAV as a detrital food-source, the relative
impact of decomposing plants has been investigated in terms of oxygen
utilization. We hypothesized that submerged aquatic vegetation serves as a
temporary nutrient sink in that during the growth of SAV, N and P are taken
up from either the water or sediment, depending on local conditions, and
incorporated in SAV biomass. However, SAV decomposes; during this process
oxygen demand is exerted, and nutrients are presumably released back to the
water column.
Data from studies comparing SAV with phytoplankton and a macrophytic
alga suggest that SAV decomposition exerts a small oxygen demand, tending
to retain nutrients to a greater extent than other plants. Some
experiments investigated the extent of the oxygen demand exerted during the
decomposition process and the rapidity with which nutrients are released to
the water column. Results are summarized in Figure 14 (Twilley, personal
communication). In these experiments, a variety of primary producers,
characteristic of the Chesapeake Bay system including Ulva and Spartina,
were placed in small laboratory microcosms and allowed to decompose over a
90-day period. At frequent intervals, oxygen concentration, rate of oxygen
concentration change, and ammonium and orthophsophate concentrations were
monitored. As indicated in Figure 14, the dry-weight loss expressed as a
percent per day was highest in phytoplankton and jjlva, somewhat less in
three SAV species, and lowest in Spartina. The mean dry-weight loss per
day developed in these experiments was only slightly lower than those
observed in field studies. Spartina and phytoplankton species had the
highest rates of oxygen utilization; rates for the three SAV species
(Milfoil, Potomageton, and Rup pia) were the lowest. These results suggest
that SAV exerts only a small oxygen demand on a daily basis over the
decomposition period. This observation is important because in some parts
of Chesapeake Bay, bottom waters become anoxic during the summer because of
excessive deposition of labile organic material (primarily of phytoplankton
origin).
Nutrient releases from SAV species and Spartina were low relative to
the release observed for phytoplankton cultures and Ulva. After 70 days of
incubation in microcosms, the ammonium concentrations in experimental
systems of Milfoil, Potomageton, Ruppia, and Spartina were on the order of
one to two ug-at L~l, while phytoplankton and Ulva decomposition resulted
in concentrations in excess of 10 to 14 ug-at L~l. A similar, although
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RATE OF
WEIGHT LOSS
_- 15-
o
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III «
O
Q.
10-
r
—
—
(
50
^
z
o
H
Z
Q.
O
I—
I
Q.
)
O
^
^
r -
— i
_,
6
-<
2
|
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c
J*
•^
Q,
1
1 —
^
9.
a
^
PO* RELE/
(DAY
1
\S
70
^
^
a
^
10
20
30
40
Figure 14. Comparisons of weight loss, respiration rate, ammonia-
nitrogen release and dissolved inorganic phosphorus
release for representative species of SAV, algae (Ulva),
and marsh grass (Spartina alterniflora).
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not quite so radical, difference was also noted for orthophosphate. After
70 days of incubation, phosphate concentrations in the phytoplankton tanks
were about 50 ug-at L~l, while in the SAV and Spartina microcosms
concentrations ranged from about 9 to 15 ug-at L~l.
Harrison and Mann (1975) conducted decomposition experiments in the
laboratory using Zostera blades exposed to 20°C (68°F) temperatures.
They observed that Zostera lost up to 35 percent of its dry weight in 100
days in decomposition. The decomposition rates for whole leaves and
particles less than one millimeter were approximately 0.5 percent and one
percent a day. Leaching of organic matter was responsible for a large
fraction of organic matter loss. In terms of the nutrient content of
detrital material, the addition of bacteria markedly increased the nitrogen
content of organic matter, but did not substantially change the decay rate
of detrital particles. The addition of protozoa with the bacteria
increased both the nitrogen content and the decay rate of detritus; C:N
ratios changed from about 20:1 in living blades to a minimum of 11:1 in
detrital particles subjected to bacterial and protozoan treatments.
Harrison and Mann further found that total organic matter, dissolved
organic C, particulate organic C, and N were also highest in new Zostera
leaves and decreased rapidly after death.
In studies using the same species, Thayer et al. (1977) found that
during senescence, N content decreased and subsequently increased as blades
became detrital. They attributed this action to microbial growth and
further speculated that most of the nitrogen increase was due to microbial
immobilization of N from surrounding waters. If bacterial immobilization
of dissolved N is a general feature of the decomposition process, then it
represents yet another mechanism by which SAV can reduce ambient nutrient
concentrations in the water column.
In studies conducted in Chesapeake Bay, Staver (personal communication)
placed above-ground portions of living P_._ perfoliatus in three-millimeter
and one-millimeter mesh nylon bags and suspended these in the field. Bags
were retrieved at different times, and the amount of SAV material remaining
was measured. Results of these studies indicate that, at the temperatures
commonly encountered [25 to 30°C (77 to 86°F)], decomposition in these
bags was rapid, averaging about two percent a day (Figure 15). Although
C:N ratios of this material are not available, we expect that over time the
N content of remaining material would increase. Although data concerning
decomposition and the nutritive status of decomposing material are far from
complete, evidence from other areas indicates that as submerged macrophytic
material dies, there is an initial loss in many components, including N,
followed by an increase in N content, probably mediated by bacterial
incorporation of N from the surrounding medium. This material probably
serves as an adequate food source for many heterotrophs that ingest
detrital particles, metabolize the microorganisms, and excrete the detrital
fragment.
COMPARISON OF NUTRIENT BUFFERING CAPACITY OF SAV WITH IMPORTANT SOURCES
To evaluate the potential nutrient buffering role of SAV in the context
of Bay-wide nutrient sources, we have developed a crude budget for which
the magnitude of nitrogen sources to the upper Chesapeake Bay are compared
with the amount of nitrogen incorporated into SAV biomass during a normal
growing season.
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100
JULY-AUG
1980
3mm MESH
I mm MESH
20 40
DAYS OF DEPLOYMENT
Figure 15.
Decomposition rates of :P. perfoliatus estimated using in situ
litter bags. Data were collected in the vicinity of the
Todds Cove study site in the Choptank River (Staver,
personal communication).
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As indicated in Table 7, something on the order of five percent of the
total nitrogen input to the upper Chesapeake Bay could have been
immobilized by incorporation into SAV biomass during the 1960's. An
extremely small percentage of total nitrogen input may be immobilized by
SAV uptake at the present time (0.5 percent). Estimates of sewerage input
during the 1960's were not available, and we were not able to contrast SAV
uptake relative to sewerage input. However, it is interesting to note that
SAV uptake in the 1960's could account for approximately 50 percent of the
present sewerage input. Uptake represents only one of several possible
mechanisms used by SAV to buffer the nutrient regime in estuarine waters.
As indicated earlier, denitrification may represent a substantial sink,
although at this point the exact magnitude of this process remains
unclear. It should be pointed out that Table 7 provides no estimate of
atmospheric input; however, it probably approximates 10 to 12 percent of
the total value for 1978 (Smullen et al. 1982).
TABLE 7. ESTIMATED INPUTS OF NITROGEN TO THE UPPER CHESAPEAKE BAY FROM
RIVERINE AND SEWAGE SOURCES, AND UPTAKE OF NITROGEN BY SAV
(ALL VALUES ARE IN UNITS OF KgNy^xlO6)
(MACOMBER 1980; STEVENSON, PERSONAL COMMUNICATION)
Sources Time Periods
1960 1978
Riverine Input3
Sewage Inputs^3
Total
SAV Uptake0 (During growing season)
50
d
2J 50
2.4
50
5.3
55.3
0.3
aRiverine source of nitrogen calculated using regression relationships
between Susquehanna River flow and nutrient concentrations (Guide and
Villa 1972).
^Sewage input data from Smullen (personal communication)
cUptake calculated using N content of SAV of 2% and SAV Standing crop of
200 gM~2 for both time periods. Areas of SAV coverage were estimated as
600x!06m2 and 66xl06m2 in 1960 and 1978, respectively (Rawls, in
prep.; Anderson and Macomber 1980; Stevenson, personal communication).
"Not available.
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SECTION 6
SUMMARY
Four distinct processes related to the ecological role and value of SAV
were examined in the Chesapeake Bay Program: (1) estimating the magnitude
of SAV organic matter production and availability to local food webs; (2)
examining habitat value of SAV to infaunal and juvenile nekton species; (3)
estimating the role of SAV in modifying, reducing, and serving as a sink
for nearshore sediments; and (4) examining the role of SAV in modifying
nutrient dynamics of nearshore regions.
As we have shown in previous sections of this report, it appears that
SAV influences each of these processes. However, the importance of the SAV
component in the Bay community at the present time is probably small
because of the restricted distribution of this vegetation. At one time,
SAV probably played a substantial role in organic matter production,
habitat maintenance, and sediment and nutrient dynamics. The purpose of
this section is to highlight findings concerning the role of SAV in the
above processes and to place processes associated with SAV in the context
of large portions of Chesapeake Bay.
ORGANIC MATTER PRODUCTION AND UTILIZATION
The productivity rates of SAV communities in Chesapeake Bay are
comparable to with those observed in other SAV systems distributed over
large latitudinal ranges and environmental gradients. Net productivity
values associated with several types of SAV in Chesapeake Bay were as high
as those reported for other species in other areas. In sharp contrast to
the comparability of production values between SAV systems, estimates of
SAV biomass exhibited a large over all range, and substantial differences
were evident within the same type of system. In general, higher standing
stock values of SAV occurred in areas where the water is relatively clear,
deep (enough to allow for substantial vertical growth of SAV), and devoid
of extensive wave action. Moreover, average biomass (and even maximum
biomass) estimates in Chesapeake Bay were low relative to those reported
for other areas. For instance, average values of Zostera and Ruppia in the
lower Bay were generally below 200 g m~2; values for Potomageton
pectinatus and P_._ perfoliatus in the upper Bay were generally below
100 g m~^. At the present time, sufficient light to support vigorous
growth of SAV does not penetrate much beyond one meter in most littoral
regions of the upper Chesapeake Bay. Thus, growth is restricted in very
shallow regions where there is a limited water column to support the
vertical development of SAV, and the potential for wave, thermal, and
waterfowl grazing stresses is maximized. In earlier years (pre-1970) when
light penetration was not so restricted, SAV in the upper Bay may have
grown in waters of greater depth and been characterized by higher standing
stocks.
Comparison of SAV biomass for several species in the lower and upper
Chesapeake Bay has made several differences apparent: (1) peak biomass of
M. spicatum was greater than Z. marina, and the biomass of this species
was greater than R. maritima; T2~) the peak biomass of R. maritima, P.
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pectinatus and P^_ perfoliatus approximated each other; (3) with the
exception of M. spicatum, mean biomass values were consistently higher in
the lower Bay, often by a factor of two or more; (4) in the lower Bay,
above-ground biomass persisted through winter months, but in the upper Bay,
above-ground material was present only during the warmer months; and (5)
periods of peak biomass occurred earlier in the year (June) in the lower
Bay than in the mid-salinity zone (July to August). We do not have
quantitative information concerning biomass levels or seasonal persistence
prior to the initiation of the decline. However, ancedotal information
suggests that biomass values were higher in the upper Bay than they are at
the present time and persisted through the fall months.
Submerged aquatic vegetation can enter heterotrophic food webs either
by direct grazing of living plants or by consumption of SAV detritus. The
majority of studies conducted suggest that SAV is an adequate food item,
that it is primarily available as detritus and, in some localities, it may
be a dominant food source. Several substantial results link SAV production
to use in Bay food webs, with perhaps the most definitive connection
between SAV and waterfowl. Numerous authors found that vegetable matter
was an extremely important food item for waterfowl in the upper Chesapeake
Bay. Furthermore, the most important waterfowl wintering areas are also
those most abundantly vegetated. It appears that direct grazing on SAV by
waterfowl is important both in the Chesapeake and elsewhere, and that
grazing in itself can locally impact the distribution of SAV.
Aside from this direct grazing pathway, the vast majority of studies,
including those in Chesapeake Bay, indicate that most SAV material enters
food webs through detrital pathways. For example, in the lower Bay, sea
bass, pipefish, pigfish, and white perch are epibenthic feeders, using
amphipods and shrimp that are, in turn, detrital feeders. Data further
indicate that large predators enter SAV beds with little food in their
stomachs and leave after feeding. Food items for these feeders can
generally be traced back to detrital sources, some fraction of which is
probably SAV in origin. In an extensive study of feeding habits in the
upper Bay, little evidence was found for direct grazing by fish on SAV,
although some SAV seeds and plant parts were found in stomachs. Energy
flow appears to enter food webs as detritus and to pass through epifaunal
and infaunal invertebrates to small and large fish. Numerous epifaunal
species, which are important food items for many consumers, were also
closely associated with SAV.
Because of the complexity of organic matter sources in Chesapeake Bay
and the current marginal distribution of SAV, a quantitative assessment of
SAV's importance as a food source is not possible. However, it is
reasonable to argue that the available SAV is used by heterotrophs, and
that SAV's physical structure concentrates other foods (phytoplankton,
epiphytic algae, and benthic macroalgae) for animal consumption. Studies
conducted concurrently with SAV research indicate that on an annual basis
virtually all carbon inputs in Chesapeake Bay were utilized by heterotrophs
of one sort or another. Thus, if heterotrophic metabolism is
organic-matter limited, it follows that SAV would also be used if, as has
already been shown, this material is a suitable food source. Furthermore,
loss of SAV production may well lead to loss of fishery production,
especially if production by phytoplankton fails to compensate for the loss
of food to higher trophic levels.
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HABITAT VALUE OF SAV
Studies in the upper and lower Chesapeake Bay indicated that infaunal
abundance and diversity is higher in vegetated than in unvegetated areas.
Because unvegetated habitats support a virtually non-existent epifauna,
epifaunal densities were naturally higher at the vegetated sites and were
important food items in Chesapeake Bay food webs.
Finfish sampling at sites in the upper Bay indicate greater abundances
and species richness in vegetated than in unvegetated bottoms; fish
densities were among the highest yet reported in the literature. In
addition, average weight per individual during the summer period was low in
SAV communities as compared with unvegetated areas, suggesting that SAV
communities are continually used as nursery areas for small fish, and
larger-sized animals predominate in unvegetated areas. Fish sampling
programs in the lower Bay also found greater abundances and species
richness in eelgrass meadows than in nearby unvegetated bottoms. Some
large fish predators, such as weakfish and the sandbar shark, foraged most
often over vegetated bottom, whereas others, such as bluefish, appeared to
forage indiscriminately over both vegetated and unvegetated areas.
The main conclusion of these field studies is that fish communities are
richer in vegetated than unvegetated areas. However, few commercially
important finfish were found to use SAV beds as significant nursery
habitats. The role of SAV for commercial fishes in the Chesapeake system
seems to be largely that of a rich foraging place for adults, and not that
of a nursery habitat although, once again, it is important to emphasize
that the current restricted distribution of SAV may bias these
conclusions. (For instance, major spawning and juvenile habitats for
striped bass once existed in the upper Bay in an area that was densely
populated with SAV.) More representative patterns of commercial fish use
of SAV habitat might best be evaluated through historical correlations of
SAV and juvenile fish distributions.
Information concerning blue crab abundance was collected at the same
time fish were sampled at sites in the upper and lower Chesapeake Bay.
During comparable months, up to 10,000 times as many blue crabs were found
at the lower Bay site. In addition, most of the crabs in the high-salinity
eelgrass beds were juvenile females that constituted the breeding stock for
future generations. The conclusion drawn from these studies is that SAV in
the upper Bay serves as a very limited blue crab nursery. Lower Bay
eelgrass beds, however, serve as primary blue crab nurseries, supporting
very large numbers of juvenile blue crabs throughout the year. It should
be noted, however, that upper Bay SAV beds may well provide a protective
habitat for molting adult blue crabs.
Experimental studies involving exclusion of predators from certain
areas of SAV beds indicate that predation rates on some infaunal taxa were
lower in vegetated than unvegetated areas, and predation rates on epifaunal
species seemed to be lower in SAV habitats than elsewhere. Laboratory
microcosm experiments supported the notion that SAV provides less
protection for infauna than it provides for epifauna of SAV beds. It also
seems that artificial eelgrass provides protection roughly equivalent to
that of live eelgrass, and that SAV species with finely divided leaves
provide (other factors being equal) more protection than do SAV with
simple, unbranched leaves. It is clear that SAV-associated animals do feed
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in the beds, and that the food supply is considerably greater in SAV
communities than in other available habitats.
SEDIMENT PROCESSES
Results of recent studies indicate that SAV can substantially influence
sediment dynamics in littoral zones. Specifically, SAV stabilizes
sediments; slows currents, allowing sediments to settle (which increases
light penetration into the water column); and substantially reduces
current-and-wave-induced resuspension. In Chesapeake Bay, Orth (1977)
reports that sediment particle diameter decreased, and organic matter
content and infaunal densities increased in sediments in areas with SAV, as
compared with those that did not have such coverage. Other findings and
observations showed less sediment disruption during storms in vegetated
zones, and less dispersion of dyed sand patches. Based on this information
it was concluded that SAV is effective at trapping and consolidating
suspended sediments.
Data developed at intensive study sites in the upper Chesapeake Bay
indicated that as turbid water entered SAV beds on rising tides, sediments
were effectively removed, increasing light transparency. It appears that
by high tide, turbid inflowing waters normally exceed the filtering
capacity of SAV beds. As tidal height decreases, the bed effectively
filters sediments, and the turbidity gradient between vegetated and
non-vegetated areas again increases to a maximum. In addition,
resuspension was reduced in SAV communities with the reduction proportional
to SAV biomass.
Because of the dynamic nature of the sediment-water interface in
littoral environments, estimates of net sedimentation are exceedingly
difficult to obtain. A crude estimate was made from observations based on
differences in seston concentrations inside and outside SAV beds. These
calculations indicated that daily deposition rates of sediment were about
63 g m~2(j~lj yielding seasonal estimates on the order of 1,200 g
m~2. if we assume that there is about 0.6 g cm^ of inorganic material
in consolidated sediments, this deposition is equivalent to about two
millimeters per growing season. At the present time, we do not know if
material deposited when SAV was present is subsequently lost when SAV dies
in the fall. Considering the important role of roots and rhizomes in the
process of sediment consolidation and the low below-ground biomass observed
in Chesapeake Bay SAV communities, we doubt that this material is
permanently consolidated at present, although it may have been in the past.
To place the sediment-trapping characteristics of SAV in the context of
larger-scale sediment processes in Chesapeake Bay, we have developed a
series of calculations that compare the magnitude of two major sediment
sources with the deposition rate observed in SAV communities. Major
sediment sources include riverine input and shoreline erosion to the
portion of Chesapeake Bay above the mouth of the Potomac River. The amount
of sediment deposited during the SAV growing season was based on the data
of Boynton et al. (1981b). They estimated that some 1,200 grams of
sediment were deposited per square meter of SAV community over an estimated
180-day growing season. A large percentage of sediment input could have
been deposited in SAV communities during the 1960 period. However, in the
late 1970"s, when SAV distributions were severely reduced, the amount that
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could have been deposited was reduced to something less than 10 percent of
the input. Although this calculation should be considered preliminary, it
suggests that SAV in the past may have played an important role in
sequestering sediments in Chesapeake Bay, and that the amount of sediment
deposited in SAV communities at the present time is small relative to
estimates of sediment input. Presumably, the difference in sediment
trapped in 1960 versus 1978 is spread over the bottom of the Bay, with some
part available to resuspension.
NUTRIENT PROCESSES IN SAV COMMUNITIES
In an earlier section of this report, we argued that SAV communities
are capable of buffering nutrients between littoral and pelagic zones of
the estuary. Recent studies in Chesapeake Bay tend to support this
notion. Measurement of nutrient concentrations in offshore areas and in
SAV communities indicates that nutrient concentrations are consistently
lower in the SAV communities. In addition, experimental studies involving
the addition of nutrients to SAV communities indicate that nutrients are
rapidly removed from the water column; ambient nutrient levels are
reestablished 12 to 24 hours after additions. It has not been determined,
however, which autotrophic component is most responsible for the uptake of
these nutrients.
Several experimental studies were also conducted to examine rates of
nitrification and denitrification in SAV communities. These experiments
attempted to quantify the potential of SAV as a nutrient sink. In studies
conducted in an SAV community in the Choptank River and in brackish water
experimental ponds, we found that both areas exhibited substantial
denitrification rates (50 to 100 ug-at m~2d~l) and rates tended to be
lower in SAV than in nonvegetated littoral zones. Studies in the upper Bay
also showed that nitrification rates are substantial in SAV communities.
These rates were higher in SAV areas than in soft-bottom communities not
having SAV. Although nitrate produced from this reaction could be used in
denitrification, evidence at this point indicates that other processes may
out-compete denitrification for this nitrate.
In addition to the role of SAV as a detrital food source, the relative
impact of decomposing plants on oxygen utilization and nutrient release
rates was investigated. We found that Spartina alterniflora and
phytoplankton species had the highest rates of oxygen utilization, and
three SAV species had the lowest rates. These results suggest that SAV
exerts only a small oxygen demand on a daily basis over decomposition
periods. This observation is important in that bottom waters in some parts
of Chesapeake Bay become anoxic during the summer because of excessive
deposition of labile organic material.
Nutrient release rates from SAV species and Spartina were low relative
to release rates observed for phytoplankton cultures and Ulva. After 70
days of incubation, ammonium concentration in experimental systems of SAV
was one to two ug-at L~l, while phytoplankton and Ulva decomposition
resulted in concentrations in excess of 10 to 15 ug-at L~l,
respectively. These data suggest that SAV exerts a small oxygen demand
while decomposing and tends to retain nutrients relative to phytoplankton
and to the one macrophytic alga tested.
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To evaluate the potential nutrient buffering role of SAV in the context
of Bay-wide nutrient sources, we developed a crude budget in which the
magnitude of nitrogen sources to the upper Chesapeake Bay were compared
with the amount of nitrogen incorporated into SAV biomass during a normal
growing season. About five percent of the total nitrogen input to the
upper Chesapeake Bay could be immobilized via incorporation into SAV
biomass during the 1960's. In contrast, an extremely small percentage of
total nitrogen input (0.5 percent) could be immobilized via uptake by SAV
at the present time.
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HERBICIDES IN CHESAPEAKE BAY AND THEIR EFFECTS
ON SUBMERGED AQUATIC VEGETATION:
A Synthesis of Research Supported by U.S. EPA
Chesapeake Bay Program
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§W. M. Kempl
J. C. Means2
T. W. Jones1'3
9 J. C. Stevenson1
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I^The University of Maryland Center for Environmental and
Estuarine Studies (UMCEES), Horn Point Environmental
Laboratories, Cambridge, MD.
j§ 2UMCEES, Chesapeake Biological Laboratory, Solomons, MD.
_ ^Biology Dept., Salisbury State College, Salisbury, MD.
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December 1981
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CONTENTS
Page
Figures 505
Tables 507
Section
1. Introduction 508
2. Rationale for Selection of Compounds Studied during CBP .... 512
Herbicide Chemistry and Use 512
Rationale for Selection 517
3. Distribution of Herbicides in the Bay 518
Open-Bay concentrations 518
Tributary concentrations 518
Runoff concentrations 521
Other runoff studies in the Bay region 523
Major factors affecting runoff ... 523
4. Environmental Behavior of Herbicides 526
Sorption reactions ... 526
Herbicide degradation 529
5. Toxicity of Herbicides in the Estuary 535
Toxic mechanisms . 535
Toxicity to animals 536
Mutagenicity ,. . 536
SAV phytotoxicity 537
Effects on Photosynthesis and Respiration , . 538
Effects on Population, Biomass, and
Physiomorphology 546
Other Factors ,. . 551
Acute versus chronic exposure . 551
Mode of uptake 551
Combined stresses 552
Metabolites 553
6. Summary and Implications 556
Summary of research findings . . 556
Did herbicides cause the SAV decline? 557
Are herbicides a problem? 557
Literature Cited 560
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FIGURES
Number
1. Trends in herbicide use in the United States between 1949 and
1976 509
2. Schematic representation of the fate, transport, and effects of
herbicides in the Chesapeake Bay region 510
3. Estimated use of major herbicides in (a) Maryland and Virginia
and (b) the Choptank watershed from 1975 513
4. Concentrations of atrazine and linuron along salinity gradients
in (a,b) Chesapeake Bay and (c,d,e) the Choptank River for summer
months in 1977 and 1980 519
5. Atrazine concentrations: (a) spatial distribution along the
Rappahannock River and (b) temporal concentrations in headwaters
of Severn River for 1979 and 1980 520
6. (a) spatial distributions of atrazine and linuron in the Choptank
River-Estuary and (b) temporal patterns of atrazine concentra-
tions in runoff from Choptank and Horn Point watersheds for spring
1981 522
7. Effects of (a) basin slope and (b) time-interval to first runoff
event on the loss of atrazine from agricultural fields, where loss
is taken as percent total applied that runs-off to watercourse . . . 524
8. (a) Freundlich adsorption isotherms for atrazine on estuarine
colloids, sediments and agricultural soils. (b) Effects of
salinity on adsorption coefficients (KQC) for estuarine sediments
and colloids 528
9. Approximate persistence in soil (i.e., time until ^90 percent of
initial application disappears from site) for nine herbicides used
in Chesapeake Bay region 530
10. Loss of 14c-ring labeled atrazine from experimental systems, and
percent of total residuals as parent compound and as two major
metabolites 532
11. Atrazine mass-balance after one, three, and 30 days in experimental
microcosms containing estuarine water and sediments along with the
submerged macrophyte, Potamogeton perfoliatus 534
12. Typical results showing apparent photosynthesis over time for
experimental microcosms containing Potamogeton perfoliatus treated
with atrazine (0-1 ppm) 539
13. Ratio of apparent photosynthesis to night respiration for
Potamogeton perfoliatus treated with two levels of atrazine (and
control) 541
14. Typical patterns of diel 02 under iri situ domes covering Zostera
marina communities tricated with atrazine and shading in Guinea
Marsh, VA 542
15. Regression of "loss in apparent photosynthesis" versus herbicide
(atrazine and linuron) concentrations for three species of
submerged estuarine macrophytes 547
16. Summary of measurements of plant biomass in duplicate microcosms
containing (a) Potamogeton perfoliatus and (b) Myriophyllum
spicatum treated with linuron (0-1 ppm) 548
17. Effects of atrazine on mortality and average height of Zostera
marina in estuarine microcosms after 27-day exposure 550
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FIGURES (Cont'd)
18. Effects of plant vigor (as indicated by peak experimental values
of apparent photosynthesis) on the response of Potamogeton
perfoliatus at 25 ppb atrazine 554
19. Correlation between an index of potential diffuse loadings
(watershed area/estuarine volume) and percent occurrence of
submerged macrophytes at randomly chosen stations visited in 1974 . 558
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TABLES
Number
1. Chemical Properties of Major Herbicides in the Chesapeake Bay
Region 514
2. Uses of Major Herbicides in the Chesapeake Bay Region 516
3. Summary of Atrazine Degradation Rates in Agricultural and
Estuarine Environments 533
4. Mutagenicity of Major Herbicides in the Chesapeake Bay Region . . . 537
5. Summary of Selected Structural Characteristics of Potamogeton
perfoliatus Populations in Microcosm Communities Treated with the
Herbicide, Atrazine (Cunningham et al. 1981a) 549
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SECTION 1
INTRODUCTION
The widespread use of herbicides for weed control in the last several
decades has contributed substantially to expanding agricultural production
in North America. Annual applications of herbicides in the United States
currently amount to some 175,000 metric tons active ingredients. The
dramatic increase in herbicide use since 1950 has followed a general
pattern of exponential growth as seen in Figure 1. Also depicted in this
figure is the ever increasing importance of the _s-triazine herbicides (and
in particular atrazine) between 1960 and 1975.
Inevitably, a fraction of the herbicides applied to agricultural fields
is transported to nearby watercourses by runoff and subsurface interflow.
Significant concentrations of these compounds have been observed in
streams, lakes, and estuaries throughout North America (Richard et al.
1975, Truhlar and Reed 1976, Newby et al. 1978, Frank and Sirons 1979,
Hermann et al. 1979). Since many of these compounds are also registered
for aquatic weed control (individually or as part of a formulation), there
appears to be considerable potential for inadvertent damage to non-target
plant species in the hydrosphere.
Submerged aquatic vegetation (SAV) in Chesapeake Bay has undergone a
marked decline throughout the estuary since the mid-1960s (Stevenson and
Confer 1978). Both the piedmont, and coastal-plain portions of the Bay's
watershed are actively farmed, and herbicide use in this region has
generally followed trends in the rest of the United States. The general
coincidence in timing of events (that is, introduction of j5-triazines
versus the initial decline in SAV) led to a serious concern among
scientists, resource managers, and other citizens of the region as to the
potential role that these herbicides may have played in the loss of SAV in
Chesapeake Bay.
The U.S. Environmental Protection Agency's (EPA.) Chesapeake Bay Program
(CBP) established SAV as one of three major themes of a multi-year research
effort. Causes of the SAV decline, with considerable emphasis placed on
investigating the interactions between herbicides arid SAV in the estuary,
were among the issues addressed in this program. Numerous aspects of
herbicide fate, transport, and effects were examined in this research. The
interrelationships among various processes and the potential linkage
between herbicide application and effects on SAV are depicted in Figure 2.
Some of the herbicides placed on agricultural fields percolate into
subsurface waters where they reach a sorption equilibrium with soil
particles and are taken up by weeds. The herbicide compound usually kills
the weeds. A portion of the compound degrades to various metabolites, and
a portion enters the estuary through runoff, leaching, and streamflow.
Some of the herbicide may be volatilized and/or transported with dust,
thereupon entering the estuary through fallout. The herbicide may then be
taken up by SAV, causing them phytotoxic stress. In the estuary, the
herbicide partitions to sediment and water in response to the physical
factors of salinity, pH, and temperature as well as to the specific
chemistry of the sediment and herbicide. Again, some of the herbicide is
lost to degradation.
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c
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LJ
Q
O
CD
OC
LU
X
NONTRIAZINE
HERBICIDES
1950
1955
I960
I
1965
1970
1975
YEAR
Figure 1. Herbicide use in the United States. (Data are
from Eichers et al. 1978 as adapted in Stevenson
et al. 1981.)
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In the following pages, the results of herbicide-related research from
the CBP are synthesized. First the nature of these herbicides and the
rationale for selection of two compounds for intensive study is discussed,
then these results are examined in the context of the conceptual framework
of Figure 2 and in relation to pertinent research done elsewhere. Finally,
the overall implications of these research findings are evaluated in terms
of the role of herbicides in the SAV decline.
511
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SECTION 2
RATIONALE FOR SELECTION OF COMPOUNDS STUDIED IN THE CHESAPEAKE BAY PROGRAM
A wide assortment of herbicides is used within the Chesapeake Bay
watershed, and it would be impossible to study all of them in detail. It
was decided that initial research should, therefore, focus on the two major
compounds. All pertinent criteria, in terms of potential impact on SAV,
were considered, and atrazine and linuron were chosen. In this section we
discuss the general chemistry of the important herbicides in the Chesapeake
Bay region, as well as patterns of their use. We then present the
rationale for selecting these two particular compounds for intensive study.
HERBICIDE CHEMISTRY AND USE
There are over 140 herbicidal compounds listed in the current Herbicide
Handbook (Weed Science Society of America, 1980), which probably represents
the majority of those weed-control substances registered with EPA. Eight
compounds from six chemical groups were chosen for discussion here, based
on amounts of each used in the Bay region. The annual use-rates for major
herbicides in 1975 are summarized in Figure 3(a) for Maryland and Virginia,
and Figure 3(b) for the Choptank River watershed. Clearly, the four most
heavily used compounds are atrazine, alachlor, linuron, and simazine.
Application rates are also shown for six additional compounds, of which
four have been chosen for further discussion.
Many of the important herbicides are produced by chlorination of
aromatic compounds, including 2S4-D and dicamba; other compounds include
chlorinated aliphatic acids, heterocyclic derivatives, and organometals
(Mrak 1974). In Table 1, some chemical properties of herbicides, grouped
in terms of their ionic and acidic nature, are summarized. Water
solubility, molecular weight, and vapor pressure are presented. In
addition, octanol-water partition coefficients (KQW) are listed to
provide a relative index of the compound's hydrophobicity. The Kow is
highly correlated with the ability of an herbicide to bioaccumulate, or be
biologically incorporated across a membrane lipid bilayer. The uses of
these compounds depend largely on their chemical characteristics. Several
key aspects of herbicide use in the Chesapeake Bay region are provided in
Table 2. Various information is compiled here, including the year that the
herbicide was introduced for public use, the main crops (in Maryland and
Virginia) with which it is used, and the associated planting and tillage
practices, as well as the timing and rate of application.
The cationic and acidic herbicides are generally more water soluble
than the others (Table 2). Paraquat, as a salt, is highly soluble in
water, but virtually insoluble in organic solvents; 2,4-D is more generally
soluble. The js-triazine compounds (atrazine and simazine) are among the
least water soluble with moderate organic solubility; trifluralin dissolves
readily in octanol, but not so readily in water. Compounds with high vapor
pressure, such as dicamba, are more likely to volatilize under wet
conditions and enter the hydrosphere with precipitation; the ^-triazines,
with their low vapor pressure, are less likely to follow that route of
transport.
512
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513
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Paraquat is highly sorbed, tending to adhere essentially irreversibly
to surfaces of soil particles. Hence, it is used as a "contact" herbicide,
sprayed directly on the weed foliage. It is used at low application rates
before planting of the crop, particularly with no-till farming and double
cropping (Table 2). The postemergent herbicides, such as 2,4-D and
dicamba, must >>~ highly specific to broad-leaf weeds, and are, thus, used
primarily with corn and small grains at low application rates. The
js-triazines are also effective in control of broad-leaf weeds and are very
versatile, being applied at relatively high rates both pre- and post-
emergence of corn, under either conventional or no-till conditions.
Linuron and alachlor are also versatile compounds with a wide range of
uses, although linuron is associated most closely with soybeans.
RATIONALE FOR SELECTION
At the outset of this research program in the spring of 1978, six
criteria were used for selecting the two herbicidal compounds for focus
during the CBP. These criteria are related to the fate-and
effects-pathways described in Figure 2. Starting with total application to
agricultural lands in the Bay region, we considered how long the herbicide
persists on the field (that is, available for runoff to the estuary). The
solubility and actual percentage of each compound transported into
surrounding waterways suggest something about its relative mobility. In
1978 there was a distinct paucity of information concerning either the
actual concentrations of these compounds occurring in the Bay, or their
toxicity to SAV, but we used what scant data were available. Necessarily,
the weighting of these factors was relatively subjective, representing our
perception of importance and reliability of information. A ranking among
the six most important herbicides led to the following: atrazine,
alachlor, linuron, paraquat, trifluralin, and 2,4-D. It might be noted
that though its current use is substantially reduced, 2,4-D was included
here because it was one of the most common compounds used in the 1960's.
Simazine was not considered in this ranking because of its close similarity
to atrazine.
By these criteria, atrazine ranked clearly as the major compound with
trifluralin falling to the bottom of the list. The relative importance
among the other four herbicides was virtually indistinguishable, and each
probably deserves further scrutiny in its own right. Nevertheless, we
selected linuron as the other substance for CBP focus, primarily because of
its relative longevity reported for agricultural soils, and because it is
associated so closely with soybean production. Over recent years, corn and
soybeans have become the most important crops in the region, and the two
selected herbicides, atrazine and linuron, are, respectively, most
significant for those two crops.
517
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SECTION 3
DISTRIBUTION OF HERBICIDES IN THE BAY
This section summarizes observed concentrations of atrazine and linuron
in Chesapeake Bay and its tributaries, and attempts to relate these
concentrations to runoff rates. We will initially examine concentrations
along the axis of the main Bay and then move into successively higher-order
tributaries toward the source-waters that drain agricultural lands.
OPEN-BAY CONCENTRATIONS
The maximum concentrations of atrazine and linuron reported in either
the open waters of the main-stem Bay or a first-order tributary, such as
the Choptank and Patuxent Estuaries, between 1976 and 1980 were about 3.5
ppb (surface water). In Figures 4a and 4b, we present data for the main
Bay for June and July of 1977 and 1980 (from Austin et al. 1978, Newby et
al. 1978, Means et al. 1981b). Concentrations of atrazine and linuron
never exceeded about 1.3 ppb, and were generally highest at lower
salinities. Patterns of concentration-versus-salinity exhibited
nonconservative behaviors, probably reflecting either non-steady-state
input conditions or significant sources other than the Susquehanna River
(Stevenson et al. 1981). General trends for the two years were quite
similar.
TRIBUTARY CONCENTRATIONS
Herbicides were also monitored in two major estuarine tributaries of
the Bay. Mixing diagrams of herbicide concentration-versus-salinity are
also provided for 1980 data from the Choptank River (Figure 4c, 4d, 4e).
The absence of a relationship in the June data was probably owed to the
meager runoff that occurred in late May through June of that year, and the
small runoff experienced during July generated a weak relationship for that
month. Linuron concentrations were relatively high at the head of the
estuary as well as at about 13 ppt salinity, suggesting runoff sources both
up-river and down-estuary. Linuron concentrations in June and July were
virtually undetectable, and the higher August values correspond to the July
planting of double-cropped soybeans. Zahnow and Riggleman (1980) reported
no detectable aqueous concentrations of linuron in the Choptank and other
tributaries in 1977 to 1978, although some herbicide was found in up-river
sediments. Atrazine was measured at numerous stations throughout
Virginia's Bay waters, and two longitudinal profiles along the Rappahannock
River are presented in Figure 5a for June and August of 1979. Highest
values were 3.5 ppb in the freshwater reaches; estuarine concentrations
never exceeded 1.0 ppb (Hershner et al. 1981).
Samples were obtained for analysis of estuarine sediments and suspended
particulate matter at most stations in the Bay and tributary surveys.
Atrazine was detected periodically in estuarine sediments at low
concentrations (about 5.0 ppb) in Maryland waters (Means et al. 1981b).
Similarly, sediment concentrations were rarely detectable in Virginia,
although one value in excess of 30 ppb was reported for a sample from the
518
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Figure 4. Concentrations of atrazine and linuron in Chesapeake Bay for
IJune and July of 1977 and 1980 and in the Choptank River for
June through August of 1980. (Data for 1980 are from Means
et al. 1981b; and for 1977 from Austin 1978, and Newby et al
m 1978.)
1
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10 AUGUST 1979
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DISTANCE FROM MOUTH (km)
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1980
Figure 5. Concentration of atrazine (a) in the Rappahannock River,
Virginia; and (b) in runoff from the Severn River, Virginia
(Hershner et al. 1981). Inches of rainfall for April and
May are also shown in this figure.
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head of the tidal creek portion of Severn River (Figure 5b) (Hershner et
al. 1981). Atrazine concentrations were never detected in suspended
estuarine solids sampled in the field during 1980 (Means et al. 1981b).
It seems surprising, at first, that herbicide concentrations in the
Choptank were no greater than those observed in the main Bay during 1980
surveys, in view of the far shorter transit time between field and estuary
in the tributary. The spring of 1980, however, was a period of
extraordinarily low runoff, particularly in the eastern shore region; total
rainfall for May and June was 8.8 cm (3.5 in). Precipitation in the
Choptank watershed for May and June of 1981 was 26.2 cm (10.3 in), much
greater than the previous year and even slightly greater than normal, with
a 20.4 cm (8 in) average for 1971-1980. Thus, 1981 represents a year when
relatively high herbicide concentrations would be expected in the estuary.
RUNOFF CONCENTRATIONS
Means et al. (1981b) monitored atrazine and linuron concentrations
during base flow and after all runoff events in spring and summer 1980-1981
at the creek and small embayment draining a 94 ha (232 acres) experimental
watershed at Horn Point Environmental Laboratories (HPEL). These data (for
1981) are summarized in Figure 6a. Herbicide concentrations were also
measured in the Choptank River headwaters and estuary after a major storm
in mid-May 1981 (Figure 6b). Concentrations of atrazine in the river
reached 9.0 ppb and exceeded 2.0 ppb well into the estuary. Linuron
concentrations of 2.0 to 3.0 ppb were found in both fresh and brackish
waters, with no apparent relation to salinity. Such high values of linuron
were unexpected, since this event preceded soybean planting, and they
probably represent localized runoff from treated fields of small grains.
Atrazine concentrations in 1981 runoff from the HPEL watershed (draining
primarily corn fields) reached peak levels of about 20, 45, 10, and 13 ppb
during the four spring runoff events described in Figure 6a.
Concentrations at the drainage creek during the same period in 1980
exceeded 3.0 ppb for only one short event (May 1), when peak values were
18.3 ppb. The flow in the Choptank headwaters at Beaver Dam exhibited a
marked maximum (9.0 ppb) only during the first two closely spaced events in
1981. Concentrations as high as 20 ppb were observed once in the small
estuarine embayment (Lakes Cove) receiving direct runoff from the HPEL
watershed.
Rainfall during the spring of 1980 was considerably greater on the
western shore of Virginia, where almost 10 cm (3.9 in) of rain fell during
the eight-day period April 25 to May 2. Hershner et al. (1981) monitored
for atrazine in the headwaters of the Severn River (draining extensive
agricultural land), and reported maximum concentrations of about 16 ppb
during the runoff generated by two successive downpours of 3.0 cm (1.2
in). These data are provided in Figure 5b. Somewhat higher concentrations
were reported by Hershner et al. (1981) for 1979, with four values above 10
ppb measured at a small tidal creek in the upper Severn River during an
April runoff event. One extreme value (108 ppb) was observed during this
episode in a drainage creek. The wet spring of 1981 was not studied in
Virginia, but it appears that general spatial and temporal distributions of
herbicides are similar in upper and lower Bay regions, both being highly
responsive to hydrologic conditions.
521
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Figure 6. (a) Temporal patterns of atrazine concentrations in runoff
from Choptank watershed (spring), and (b) spatial distribution
of herbicides in Choptank River and estuary (May 10-13, 1981)
(Means et al. 1981b).
522
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OTHER RUNOFF STUDIES IN BAY REGIONS
Herbicide concentrations in the Rhode River on Maryland's western shore
have been intensively studied. Correll et al. (1978), Wu et al. (1977),
and Wu (1980) reported 1976 concentrations and runoff rates for atrazine
and alachlor in the Rhode River basin and estuary. In general, their
results are consistent with those of Means et al. (I981b) and Hershner et
al. (1981), where peak runoff concentrations of dissolved herbicide were
about 35 ppb and 3.0 ppb for atrazine and alachlor, respectively. They
also reported concentrations of herbicides sorbed to suspended solids,
which were periodically on par with the dissolved form but were in excess
of values observed by Means et al. (1981b). Herbicides found in Rhode
Estuary never exceeded 1.0 ppb (dissolved) for either compound. Atrazine
has also been measured by the U.S. Geological Survey in the Susquehanna
River (at Harrisburg and Conowingo) and several small tributary creeks for
1978-1980 (Ward 1980 quoted in Stevenson et al. 1981). Concentrations were
generally in the range of 1.0 to 5.0 ppb, though one exceptionally high
value (68 ppb) was found at Goods Run in May 1980.
Wu (1980) estimated that about one percent of the atrazine and 0.2
percent of the alachlor applied to agricultural fields in the Rhode River
basin entered the watercourse. These runoff rates are within the range,
but on the low side, of values reported in the literature (Wauchope 1978).
Of almost 50 estimates of atrazine runoff compiled by Schueler (1979) from
various North American fields, we calculate a mean of 2.6 percent from a
range of 0 to 17 percent. Much less information is available for alachlor
and linuron; however, reported values range from 0.02 to 14 percent and
appear to be near (slightly less ) atrazine values. Data from the HPEL
flume have not yet been analyzed in terms of percent losses, but these
forthcoming values may add some insights to this issue.
MAJOR FACTORS AFFECTING RUNOFF
Numerous factors influence the rate and concentration of herbicide
runoff and should be considered when interpreting results from the
Chesapeake Bay region. Among these factors are: chemical nature of the
compound; slope of the land; rainfall intensity, duration, and timing; soil
type; plant cover; and drainage density. Slope and precipitation are
particularly important factors that can profoundly influence runoff. We
have plotted overall percent loss of atrazine applied to the field, versus
the topographic slope of the field, for six different sites in the Eastern
and Central United States in Figure 7a. There is considerable scatter in
these data, because variables other than slope are also operative.
Nonetheless, there appears to be a positive relationship that follows a
hyperbolic, or logistic shape, with greatest effects found in the region of
five to 10 percent slope. Although comparison of data from different
watersheds must be viewed with caution, one might infer that runoff data
from the coastal-plain portions of the eastern and western shores of the
Bay (generally less than about six percent slope) may be comparable to one
another.
Another important consideration is the time interval between
application of herbicide to the field and a given rainfall-runoff event.
Herbicide concentrations are highest in the first runoff and generally
523
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I
Q.
Q.
8
6-
(a)
u 4 —
x
X
X
o
cr
u.
2-
I WHITE etal. 1967
2 HALL 1974
3 RITTER etal. 1974
4 SMITH etal. 1974
5 WU etal. 1977
6 LONGDALE et ol. 1978
0
T I
5 10
SLOPE OF LAND (%)
I
15
•o
05
o.
Q.
UJ
LL
O
DC.
8-
6-
4 -
2-
(b)
\
o
.ATRAZINE CONCENTRATION
(Smith etal. 1978, quoted in
Wauchope 8 Leonard 1980)
to 2
ATRAZINE
LEAKAGE
3o
-100 _
WHITE etal. 1967
HALL 1974
LANGDALE et ol. 1978
TRIPLETT etal. 1978 °4
30
30
.a
a.
a.
u_
O
- 10
a:
H
z
UJ
o
o
o
10
I
30
I
40
20 30 40 50
DAYS TO FIRST RUNOFF EVENT
Figure 7.
(a) Effect of basin slope on loss of atrazine, and (b) effects
of time interval to first runoff event on atrazine loss from
agricultural fields.
524
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decrease exponentially in subsequent events, as indicated for atrazine by
the solid line in Figure 7b. This effect is the result of several factors,
including degradation, plant uptake, leaching, and depletion of initial
mass; it emphasizes the fact that highest herbicide concentrations occur in
the period shortly after field application. Wauchope and Leonard (1980)
have used literature data to develop an empirical function that generalizes
this relation:
Ct = AR(1 + 0.44t)-!'6 (1)
where Ct is the runoff concentration at event time t, R is the
application rate, and A is the availability index (a function of the
chemistry of the particular compound). Moreover, the total amount of
herbicide transported into surrounding watercourses over the whole season
is also a function of the timing of the first runoff event after
application (Figure 7b, dashed line). A similar, first-order decay
function generally describes this relation. The data compiled in this
figure suggest that if no runoff occurs within the first 10 days after
application, total atrazine loss to the watercourse will probably be less
than one percent of that applied, while runoff within three days following
application can lead to seven percent loss. Thus, both the concentration
and total amount of herbicide entering the estuary may depend largely on
the time interval between herbicide application and rainfall-runoff events.
525
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SECTION 4
ENVIRONMENTAL BEHAVIOR OF HERBICIDES
Two key processes that determine the fate of herbicides in the
environment are adsorption and degradation. As suggested in Figure 2,
these processes occur in both terrestrial and aquatic (estuarine)
environments. Before the initiation of CBP research in 1978, very little
was known about the nature of these processes as they occur in estuaries.
Hence, parallel experiments were designed to examine adsorption and
degradation in simulated estuarine and soil systems, representative of
typical conditions in the Bay and its watershed. Emphasis was placeid on
atrazine, although experiments were also performed with linuron and other
compounds. Atrazine degradation appears to proceed more rapidly in systems
with sediments and/or soil, than with water alone, and Jones et al. (1981b)
have postulated that most of the degradation may be preceeded by sorption,
followed by desorption. Hence, the two processes are intimately coupled.
SORPTION REACTIONS
The adsorption of dissolved herbicides to solid surfaces proceeds as a
function of aqueous concentration (O until an equilibrium is achieved
between C and the adsorbed concentration [x/m, where x is the weight of
herbicide adsorbed to solid (micrograms), and m is the weight of solids
(grams)]. The equilibrium relation is often described using the Freundlich
equation,
x = (Kd)(C)l/n (2)
m
where n is a constant describing the shape of the equilibrium relation, and
K^ is the sorption coefficient (for example: Giles et al. 1960, Bailey
and White 1970, Kempson-Jones and Hance 1979, Travis and Etnier 1981).
High K(j values indicate a stronger tendency for adsorption. Several
studies suggest that organic matter in the substrate tends to be the
controlling factor for adsorption of many non-polar organic compounds such
as herbicides (Bailey and White 1964; Karickhoff et al. 1979; Means et al.
1979, 1980). Therefore, it is convenient to normalize K
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1.0). The Koc were about 10 times greater for colloids (2,000-14,000)
than those for sediments (200-400), which were in turn generally greater
than those obtained for soils (100-200). Values of KQC for linuron with
sediment and colloidal matter from the Patuxent River were 3.4 times
greater than for atrazine with the same substrates. This relationship is
almost identical to the relationship between the two compounds for soils,
where linuron Kocs were 3.9 times greater. These values of Koc for
colloids appear to be consistent with the findings of Wu et al. (1980), who
reported that estuarine surface microlayers at Rhode River were typically
enriched with atrazine by a factor of about 10 to 30 over bulk water
concentrations. If it is assumed that this enrichment is due to sorption
by the hydrophobic colloidal matter concentrated at this air-water boundary
with associated organic carbon of 5.0 ppm, then the KQC values would be
about 2,000 for the samples of Wu et al. (1980).
Correll and Wu (1981) have reported Kd values ranging from 5.0 to 260
(depending on C) for atrazine dissolved in distilled water and adsorbed to
Rhode River estuarine sediment. These values are two to 100 times greater
than those of Means et al. (1981a) and other investigators. The highest
K^'s of Correll and Wu would correspond to KQCs of Means et al., only
if the Rhode River sediment were 50 percent organic carbon. They do report
extremely high organic carbon percentages; however, even these are too low
(five to 27 percent) to explain the differences (Correll et al. 1978).
Moreover, their data imply that Freundlich isotherms would be non-linear in
the same general concentration range as that given by Means et al. (1980)
and others and, using their data, we calculate n = 2.3 with Kj = 126
(Equation 2). It is difficult at this point to resolve these discrepancies.
The adsorption of atrazine and linuron has been extensively studied on
a wide variety of soils (Talbert and Fletchall 1965, McGlamery and Slife
1966, Green ^nd Obien 1969, Harris and Warren 1967, Weber et al. 1969,
Bailey and White 1970, Grover and Hance 1970, Hurle and Freed 1972, Colbert
et al. 1975, Hiltbold and Buchanan 1977, Dao and Lavy 1978). A number of
factors have been identified that influence the adsorption of these
compounds to soils, including pH, temperature, moisture, electrolytes, and
organic matter. Of these factors pH and salinity were examined to
determine their potential effects on herbicide adsorption under estuarine
conditions. Salinity exerted a small (five percent) negative effect on
adsorption with sediments between 5.0 and 15 ppt, but the overall effect
from 0 to 15 ppt was erratic and probably nonsignificant (Figure 8b). For
colloids, on the other hand, salinity between nine and 19 ppt appeared to
have a substantial negative effect (29 percent). This pattern was
consistent between experiments (where salinity was manipulated) and field
observations (where salinity varied along the estuarine axis), but was
opposite to that which would be predicted as a result of "salting-out" of
the hydrophobic herbicide. This finding suggests that salinity affects
more the nature of the colloidal material than the solubility of the
herbicide (Means and Wijayaratne 1981). It was found that pH also
influenced Koc for colloids with atrazine and linuron. Both herbicides
exhibited maximum KQC at a pH approximating that of the estuarine
environment from which water and colloids were taken. Increasing or
decreasing pH by one unit (that is, between pH 7.0 and 9.0) caused a 2.0 to
20 percent decrease in KQC for the two herbicides, although at pH 5.0 to
6.0 KQC dropped by 25 to 35 percent.
527
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(a) FREUNDLICH ADSORPTION
ISOTHERMS FOR ATRAZINE
ESTUARINE
SEDIMENTS
ESTUARINE
COLLOIDS
AGRICULTURAL
SOILS
in
•a
o
O
o
X
a>
^
a>
in
o
o
T
024 6 8 10
EQUILIBRIUM SOLUTION CONCENTRATION, ^g ml"1
5-
2-
0-
(b) SALINITY EFFECTS ON Koc FOR ATRAZINE
-ESTUARINE
SEDIMENTS
'ESTUARINE
COLLOIDS
-i 1 1 1-
4 8
12
16
24
SALINITY, ppt
Figure 8. (a) Freundlich adsorption isotherms for atrazine and (b)
effects of salinity on K for atrazine, from laboratory
experiments (o) and fiel8°observations (x) normalized to
laboratory conditions. (Means et al. 1980, Means and
Wijayaratne 1981.)
528
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The implications of these sorption data are that atrazine and linuron
are readily susceptible to runoff and leaching from agricultural fields,
even without particulate soil erosion. Control of soil erosion alone will
not control atrazine transport to the estuary. Means et al. (1981) suggest
that once in the estuary, dissolved atrazine will adsorb readily to
suspended sediments and colloidal material. Sediment-sorbed atrazine will
move only through resuspension and sediment transport; colloidal-bound
herbicide may travel great distances and concentrate in organic film at the
air-water interface, typical of coastal waters, particularly during the
fall. The expected fate of linuron would be analogous, except less would
leave the field in dissolved form, but more would adsorb to estuarine
particles.
HERBICIDE DEGRADATION
An important factor contributing to the potential toxicity of
herbicides, such as atrazine and linuron, is the longevity of these
substances in the field or estuary. Numerous studies have described the
kinetics of atrazine degradation in various soil environments, and a wide
range of physical factors (such as pH, temperature, moisture, clay, and
organic content of soils) has been shown to affect this process (for
example, Swanson and Dutt 1973; Best and Weber 1974; Hiltbold and Buchanan
1977; Hance 1979; Kempson-Jones and Hance 1979; Kells et al. 1980). Direct
experiments were conducted for atrazine degradation in flasks with
estuarine water and sediments maintained in natural light under field
temperatures (Jones et al. 1981b) . We also monitored atrazine and linuron
concentrations in laboratory microcosms [25 L (6.6 gal) and 700 L (184.9
gal)] over eight weeks and thus, indirect estimates of degradation were
obtained (Cunningham et al. 1981a, 1981b).
Much of the information on herbicide longevity developed by agronomists
and soil scientists refers to persistence in agricultural soils (that is,
the time required for 90 percent or more of the compound to disappear from
the site of application). Reported values of "field persistence" result
both from degradation and mobility of the compound. Nonetheless, to the
extent that mobility may not vary excessively among the compounds,
persistence provides a rough estimate of relative degradation rates in the
field. A summary of persistence data (defined as above) for nine
herbicides important in the Chesapeake Bay region is presented in Figure 9
(Stewart et al. 1975). Except for paraquat (the persistence of which is
largely related to its highly sorptive nature), the £-triazines, atrazine
and simazine, are the most persistent of these compounds. Thus, it appears
that atrazine is among the more persistent herbicides in common use, and
understanding its degradation should provide a conservative perspective on
herbicides in general.
Herbicide degradation is often described as a first-order decay process
Ct/C0 = e~kt (4)
where ct is the amount of the compound remaining at time t; Co is the
initial amount and; k is a decay rate coefficient. Others have suggested
that higher order processes better describe the herbicide degradation (for
529
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PARAQUAT
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/////////////////////////////////////////////A
ATRAZINE
1
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example, Hamaker 1972; Kempson- Jones and Ha nee 1979) so that the more
general relation applies
Ct " tco 1"n + (n-Dktl-n (5)
where n is the apparent order of reaction. The overall rate of reaction is
often described by the half-life (.^1/2^ > °r time required for
disappearance of 50 percent of the original substance. This Tj/ 2 is
equal to (0.693/k) for first-order reactions.
Atrazine can degrade through chemical and biological processes into
metabolites, some of which may be toxic. The degradation of atrazine to
its metabolites can occur through: chemical hydrolysis to hydroxyatrazine;
dealkylation to either the de-ethylated, deisopropylated, or deaminated
atrazine forms followed by hydrolysis; or conjugation. The dealkylations
and ring cleavage are generally considered to be biologically
(enzymatically) mediated, but the hydrolysis to hydroxyatrazine is
controlled by physical parameters, most notably pH (Armstrong et al.
1967). Ring cleavage of atrazine is a very slow process, typically causing
losses of only a few percentage points over several years; however, prior
hydrolysis to hydroxyatrazine does increase the rate of ring cleavage
(Armstrong et al. 1967). The biological degradation is performed by soil
fungi and bacteria, with the organisms using mainly the side-chains as
carbon sources, nitrogen sources, or both (Kaufman and Blake 1970).
The degradation of ^C ring-labeled atrazine in two estuarine
water-sediment microcosms (from Choptank and Tangier) and two soil systems
(well-drained Sassafras and poorly drained Mattapex) was compared over an
80-day period under high- and low-oxygen tensions (Jones et al. 1981b) . In
the estuarine systems, total residues moved from water to sediments over
the course of the experiment, and the relative percentage of parent and
daughter compounds changed rapidly during the first several weeks (Figure
10). The initial degradation products generated in the estuarine systems,
as revealed by thin-layer chromatography and autoradiography , appeared to
be the same as for the soil systems, with hydroxyatrazine being the major
short-term metabolite. By the 21st day of the experiment, the percentage
of total extracted residues corresponding to atrazine, monodealkyalted
atrazine, and hydroxyatrazine were 65, 10, and 25 for the Choptank, and 15,
eight, and 77 for the Tangier (the estuarine systems); 66, 5.0, and 29 for
the Sassafras, and 93, 2.0, and 5.0 for the Mattapex (the soil systems).
Atrazine degradation was far more rapid in the estuarine systems than
in the soils. Half-lives for the herbicide ranged from three to nine days
in overlying estuarine water, and 15 to 20 days for estuarine sediments, as
compared with 330-385 days for agricultural soils. A portion of the
residues adsorbed to sediments and soils was nonextractable, and these
half-life estimates employed the conservative assumption that extractable
and nonextractable residues were similarly distributed among the three
major metabolites. Oxygen tension appeared to have negligible effect on
atrazine degradation; however, the low oxygen systems were not completely
anoxic. The relative degradation rates of atrazine in the three
environments, as observed in this experiment and other studies from the
literature, are summarized in Table 3, where mean half-lives are 14, 45,
and 180 days, respectively, for estuarine water, aquatic sediments, and
agricultural soils. Thus, atrazine is less likely to be a problem in the
531
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estuary, because it rapidly degrades; however, because the herbicide's
half-life on farmland soils is longer than in the estuary, it remains
potentially available for runoff long after application.
TABLE 3. SUMMARY OF ATRAZINE DEGRADATION RATES IN AGRICULTURAL AND
ESTUARINE ENVIRONMENTSa
Environment Half-life (days)b
Mean Range
Agricultural Soils 180 10-1200
Aquatic Sediments 45 6-145
Estuarine Water . 14 3-30
Summarized after Jones et al. (1981).
required for 50 percent degradation of original compound.
Herbicide data from our estuarine microcosm phytotoxicity experiments
(Cunningham et al. 1981a, 1981b) indicated that overall disappearance of
atrazine from the water-sediment environment occurred somewhat more slowly
than in the estuarine flask systems of Jones et al. (I981b), but still more
rapidly than for soils (Figure 11). Half-lives of atrazine were on the
order of 60-80 days in the microcosms. The slower decomposition in these
systems may be a function of the fact that the experiments were performed
in artificial lights, which would contribute less to photodecomposition
(Jordan et al. 1964), or perhaps higher pH and/or reduced organic
substrate. A value of f.\/2 from similar microcosm data of Correll and Wu
(1981) was calculated to be about 30 days, which is closer to the combined
sediment-water T^/2 °f 10 to 20 days from Jones et al. (I981b).
Microcosm experiments involving linuron indicated much faster degradation
of this herbicide, with T^/2 = 10 days (Cunningham et al. 1981b), a
result consistent with the relative persistence of the two compounds in
soil (Figure 9) .
It appears that atrazine is a relatively good agricultural weed-control
compound, in that it persists in soils (where it can perform its designed
function) 10 times longer than in the estuary (where nontarget species
might be exposed to its toxic effects). Apparently, atrazine is one of the
more persistent herbicides in use, and its half-life in the estuary is at
least s.ix times greater than linuron. This 6:1 relationship is similar to
the 3.5:1 relationship reported for the persistence (time for 90 percent
disappearance from field application) of these two compounds in the field.
Therefore, the field persistence data (such as Figure 9) may, in some
cases, provide a crude index of potential estuarine longevity.
533
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SECTION 5
TOXICITY OF HERBICIDES IN THE ESTUARY
In this section the toxicity of herbicides used in the Chesapeake Bay
region is considered. The major concern is herbicide phytotoxicity to SAV,
particularly in Chesapeake Bay. We also review other aspects of herbicide
toxicity for animals, algae, and emergent aquatic plants, as well as
mutagenic action of these compounds. We begin with a general review of the
known mechanisms of toxicity, again emphasizing atrazine and linuron.
TOXIC MECHANISMS
Herbicides can kill plants by interfering with photosynthesis,
respiration, and other aspects of plant metabolism. The major herbicides
in use today can be categorized as to their site of action. Four sites are
recognized: the chloroplast, the mitochondria, protein synthesis, and
membrane permeability. Of these, the chloroplast-related group of
herbicides are in the widest use in the Chesapeake Bay watershed. Two
herbicides in this group are atrazine and linuron. Both of these compounds
appear to inhibit the Hill reaction of photosynthesis at the same location
within the chloroplast, stopping electron transport leading to the
production of the reduced cofactor (NADP^) for the fixation of C02«
There is disagreement among investigators as to the exact location of this
attack (Ebert and Dumford 1976), but most concede that it is between the
initial electron acceptor Q in photosystem II and plastoquinone (Gysin and
Knusli 1960, Moreland and Hilton 1976). More specifically, recent
information indicates that both atrazine and linuron compete for the same
protein-binding site on the thylakoid membrane, possibly causing a
conformation change, blocking electron transport (Brewer et al. 1979).
The fact that the site of inhibition is within the chloroplast itself
can dictate the relative toxicity of a compound or its organic solubility.
The lipoid-rich membrane environment of the chloroplast makes penetration
of more polar compounds difficult, thus reducing their access to the
binding site. In the case of atrazine, the daughter products show a
decreasing phytotoxicity in the order of de-ethylated atrazine >
de-isopropylated atrazine > hydroxyatrazine. This toxicity inversely
correlates with their relative polarities (Lamoureux et al. 1970) and the
order relates to how soluble herbicides are. Therefore, solubility data
can provide some insight into relative toxicity.
Resistance to photosynthetic inhibitors in plants is manifested either
in the ability to degrade the parent compound to nontoxic metabolite(s), to
complex the compound through conjugation, or to acquire altered binding
sites on the chloroplast membrane through genetic selection. Degradation
of the parent compound may be enzymatically or nonenzymatically
controlled. Corn contains the compound benzoxazinone that nonenzymatically
hydrolyses atrazine to hydroxyatrazine. Corn also contains enzymes that
degrade atrazine to its dealkylated products. Sorghum can conjugate
atrazine by a glutathione s-transferase enzyme, which removes the chlorine
from the molecule, allowing a bond to form between the triazine ring and
the sulfur of glutathione (Shimabukuro 1968). Pfister et al. (1979)
535
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suggest that plant species may develop resistance to herbicides by the
evolutionary selection of altered binding sites on the chloroplast
membrane. Theoretically, SAV might develop resistance to herbicides
through similar genetic mechanisms which provide a means of increasing
degradation of the herbicide within the plant cells, or tying it up.
TOXICITY TO ANIMALS
Since the toxic mechanisms for many of the important herbicides act
directly on the chloroplast, it would be anticipated that effects of these
compounds on heterotrophic organisms would be substantially less (Stevenson
et al. 1981). Toxicity data for various estuarine animals tend to support
this hypothesis. For example, the fiddler crab, Uca pugnax, was observed
to withstand concentrations up to 100 ppm atrazine with no demonstrable
effects in bioassays (Davis et al. 1979). Only at 1,000 ppm was the
escape-response ability of fiddler crabs damaged, so that normal activities
in the saltmarsh ecosystem were impaired. Even when fed cordgrass
(Spartina alterniflora) containing atrazine, box crabs showed little
behavioral response (Pillai et al. 1979). Similarly high levels of
atrazine resistance have been reported for mud crabs, Neopanope texana
(Newby et al. 1978). Shrimp and oysters have been shown to be somewhat
more sensitive to atrazine in bioassay experiments, with shrimp exhibiting
30 percent mortality in 96 hours at 1.0 ppm atrazine, and oysters showing
no effects at this concentration (Butler 1965).
MUTAGENCITY
An increasing concern in recent years has been the discovery of the
mutagencity of pesticides and/or pesticide metabolites. The issue has been
complicated further by the instances in which a nonmutagenic parent
compound can be activated by either plant or animal metabolism into a
mutagenic substance. Herbicides, like most pesticidal compounds, often
contain chlorine or bromine substituents, aromatic rings, and amine
groups. These functional moieties have often been associated with
mutagenic activity in organic molecules. It should be noted that, in some
cases, mutagenicity has been associated with a trace byproduct from
commercial production of the pesticide (that is, dioxins in 2,4-D and
nitrosamines in trifluralin). A summary of available information on the
mutagencity of the major herbicides used in the Chesapeake Bay region is
presented in Table 4. The issue of genetic toxicity of the herbicides was
not addressed in any of the research funded by the CBP-SAV program. It
remains, however, an important question that needs to be considered in the
future.
536
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TABLE 4. MUTAGENICITY OF MAJOR HERBICIDES IN CHESAPEAKE BAY REGIONS
Compound Relative Mutagenicity
Sodium Azide ++
Atrazine +
Simazine +
Cyanazine +
Diquat NT
Paraquat NT
2,4-D
Dicamba
Trifluralin
Linuron
Alachlor +
Propachlor +
Comment s
plant activated
plant activated
plant activated
dioxin contaminant,
by-product +++
nitrosoamine,
by-product ++
plant activated
plant activated,
synergistic enhancement
with triazines
aSource
^Symbols: +++ extremely large effect; ++ large effect; + some effect;
- no effect; NT not tested
PHYTOTOXICITY FOR ALGAE AND EMERGENT PLANTS
Phytoplankton vary widely in their susceptibilities to atrazine, with
toxic concentrations ranging from 20 to 1,000 ppb (Stevenson et al. 1981).
Davis et al. (1979) reported that 100 ppb atrazine caused some effects on
mixed algal assemblages from coastal waters. For the diatoms,
Thallassiosira and Nitzschia, the LDjQ was 1,000 ppb. Reductions in cell
density of 10, 90, and 100 percent were obtained at concentrations of 20,
200, and 500 ppb, respectively, for the chlorophyte, Chlamydampnas spp.
(Loeppky and Tweedy 1979, Hess 1980). Pruss and Higgins (1974) reported no
lasting effects on algal populations in a lake treated with 100 ppb
simazine. Chlorella pyrenoidosa possesses a high degree of resistance to
atrazine, where 1,000 ppb were required for 50 percent reduction in
chlorophyll-a_ (Kratky and Warren 1971). Metz et al. (1979) found similar
resistance for Chlorella strains, which was attributed to the ability of
this species to exist heterotrophically. Bryfogle and McDiffett (1979)
showed that productivity in algal cultures treated with 400 ppb simazine
was actually enhanced, although species diversity was reduced with
537
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resistant ChloreHa strains dominating the experimental systems.
Atrazine effects on Spartina alterniflora have been studied extensively
by Davis et al. (1979). Cordgrass biomass was unaffected at 10 ppb; at 100
ppb, a 34 percent reduction in biomass was observed; at 1,000 ppb,
approximately 46 percent of biomass was lost. Apparently, Spartina has
some detoxification capability for atrazine, by a mechanism similar to that
of sorghum (Pillai et al. 1977). Thus, laboratory studies suggest that
neither algal nor marsh grass populations would be seriously damaged at
atrazine concentrations in the range observed in Chesapeake Bay; however,
herbicide treatment could conceivably contribute to phytoplankton species
shifts that allow monospecific bloom conditions.
SAV PHYTOTOXICITY
The crucial relationship in this discussion is the potential phytotoxic
effect of herbicides on SAV. Two herbicides, atrazine and linuron, were
tested against SAV species Potamogeton perfoliaUis (a dominant native) and
Myriophyllum spicatum (an exotic that was extremely abundant just before
initial SAV decline in 1964). Though historically important in Chesapeake
Bay, both of these species are of freshwater origin. The effects of
atrazine on the marine and estuarine seagrasses, Zostera marina and Ruppia
maritima, have also been tested (Hershner et al. 1981). Experimental
exposures ranged from incubations of six to 24 hours both in situ and in
vitro, to five weeks in laboratory microcosms of three sizes and designs.
Similar microcosm studies were performed by Correll and his colleagues,
using atrazine with three additional Bay species: Potamogeton pectinatus,
Zannichellia palustris, and Vallisneria americana. Thus, a broad data base
now exists on this topic, with seven species, two herbicides, and six
experimental designs.
Effects on Photosynthesis and Respiration
The general response of P. perfoliatus to atrazine treatment in
laboratory microcosms is shown in Figure 12 (Cunningham et al. 1981b),
where mean values for apparent photosynthesis, Pa (net C^ production
during the day), are given for microcosms under control, and under six
herbicide dosages over a nine-week experimental period. The shaded portion
of each graph represents the departure of actual metabolic rates from
expected values (based on both pretreatment and control data). Similar
data have also been reported for atrazine effects on M. spicatum, and for
linuron toxicity to both SAV species (Cunningham et al. 1981b) . In
addition, P. perfoliatus response to low concentrations (1.0 to 25 ppb) of
the atrazine was retested.
In general, the response patterns of SAV to herbicides were similar to
that shown in Figure 12, where marked decreases in photosynthesis were
observed at concentrations greater than 50 ppb, with some less pronounced
effects at lower concentrations. Myriophyllum, however, exhibited slightly
greater resistance to atrazine, but virtually identical response to linuron
as compared with P. perfoliatus. At 5.0 ppb atrazine, Pa for M. spicatum
was actually enhanced over controls. Recent short-term experiments
indicated that the Pa response of _R._ maritima to atrazine was similar to
that of P. perfoliatus (Jones, unpublished data). Simple two-way analysis
538
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WEEK OF EXPERIMENT
Figure 12. Summary of measurements of apparent photosynthesis for
microcosms containing Potamogeton perfoliatus treated with
atrazine (0 to 1 ppm). Data points are means of duplicate
measurements on duplicate systems (n = 4) (Cunningham et al.
1981b).
539
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of variance suggests that effects were always significant (p < 0.05) for
concentrations greater than 50 ppb, and sometimes significant at 5.0 ppb;
however, further statistical analysis is still in progress.
At all concentrations less than 50 ppb, Potamogeton Pa exhibited a
trend of recovery toward control levels after the second post-treatment
week. The same pattern was found for M. spicatum with atrazine, and for
both species with linuron. For both species, however, incipient recovery
from linuron treatment occurred after the first post-treatment week. Rates
of recovery were similar in all cases, being about 0.5-1.5 mg
The ratio of apparent photosynthesis to dark respiration (Pa:R)
provides a measure of the energy balance for plants and has been used as an
index of stress. The point where Pa just equals R is termed the
"compensation point"; Pa:R > 1 indicates net growth, and Pa:R
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for 34 varied experiments. Some differences were found between atrazine
and linuron effects, and among the three SAV species. Of all species,
Zostera exhibited the greatest effect at low herbicide levels, with an
apparent threshold concentration (intercept of x-axis) of about 1,0 ppb; M.
spicatum was the most resistant with a threshold of about 6 ppb. This
model predicts that at 10 ppb atrazine, the resulting reductions of SAV
Pa for Myriophyllum, Potamogeton, and Zostera would be approximately 0,
17, and 33 percent, respectively. Thus, in the lower-Bay waters small
concentrations may have greater effect on SAV (that is, Zostera)
photosynthesis.
Correll and his colleagues (Correll et al. 1978, 1978; Correll and Wu
1981) have reported other herbicide-SAV experiments for Chesapeake Bay
plants. They have investigated atrazine effects on a second species of
Potamogeton (P. pectinatus) and on 7^*_ marina, as well as on two additional
freshwater genera (Zannichellia palustris and Vallisneria americana). They
have also reported some results of linuron effects on Z. palustris.
Time-course experiments (21-48 days) have been performed for a range of
herbicide concentrations. In general, the patterns of responses reported
are similar to those in Figure 15, where, for example, linuron effects seem
to be greater than those of atrazine. Correll's results, however, appear
to suggest considerably greater resistance to atrazine for all test
species. For example, the maximum effect found for any species at 75 ppb
was for Z. palustris, which exhibited about a 40 percent reduction in Pa,
and the minimum effect reported by Cunningham et al. (1981b) was 42 percent
for M_._ spicatum at 100 ppb atrazine. Moreover, two of four species tested
exhibited significant enhancement of Pa by 75 ppb (Correll and Wu 1981).
One of those enhanced species was Z. marina, the same plant that Hershner
et al. (1981) reported never exhibited less than 47 percent reduction in
Pa at 100 ppb for five experiments.
Few other comparable data are available in the literature. Walker
(1964) reported that Potamogeton sp. was effectively controlled in fish
ponds (that is, removed from ponds for at least two months) with treatments
of 0.5-1.0 ppm simazine. Herbicide bioassay experiments with the submerged
vascular plants, Myriophyllum brasiliense and Elodea canadensis, showed
that oxygen evolution was suppressed (25 and 40 percent less 02,
respectively) by simazine at concentrations of 120 ppb (Button et al.
1969). Fowler (1977) has shown, more recently, that effects of a related
^-triazine herbicide (DPX 3674) on Myriophyllum verticillatum and P_._
pectinatus could be detected at 125 ppb. Stevenson et al.TT981) have
reported some unpublished data of J. Forney for E. canadensis, where a one
percent growth inhibition was found at 3.2 ppb atrazine, and a 50 percent
inhibition occurred at 80 ppb.
Effects on SAV Population, Biomass, and Physiomorphology
Total SAV biomass responded to herbicide treatment in a manner
analogous to plant photosynthesis. Typical biomass data from microcosm
experiments are provided in Figure 16, where P. perfoliatus exhibited
significant reduction in plant matter at concentrations greater than 50 ppb
linuron, and M. spicatum followed a secular decrease in biomass when
exposed to linuron concentrations from 5.0 to 1,000 ppb, although the loss
was significant (compared with control) only at concentrations greater than
546
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O ATRAZINE/Potamogeton perfoliatus
(NUMBERS REFER TO DIFFERENT
EXPERIMENTS)
D LINU RON / /? perfoliatus
• ATRAZIN E /Zostera marina
® tdRhZ\NE/Myriophyllum spicatum
(3 LINURON/A/. spicatum
Myriophyllum ( r 2 = 0.91)
ALL DATA
Y= 35.7X - 14.4
= 0.89)
(r2=O.89)
I 10 100
HERBICIDE CONCENTRATION (ppb!
1000
Figure 15.
Effects of herbicides on SAV photosynthesis. Numbers
adjacent to points for atrazine/_P. perfoliatus indicate
different experiments. (Data are compiled from Cunningham
et al. 1981a, 1981b; Jones et al. 1981a; and Hershner et al,
1981.)
547
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100 ppb. A slight, but insignificant increase in biomass was found at 5.0
ppb for M. spicatum. These data are from the final week of the experiment,
and time-course effects of herbicide dosage on biomass lagged metabolic
responses by one to two weeks. Ratios of above:below-ground biomass were
generally unaffected by herbicide treatment, but shoot density was enhanced
at moderate dosage (100 ppb) and sharply reduced at high doses (Table 5).
Although above:below-ground biomass ratios can be an index of stress, none
was found in this case. Hershner et al. (1981) reported only small,
insignificant effects on Zostera shoot height, density, leaves-per- shoot,
and mortality at atrazine concentrations less than 100 ppb after 27 days,
whereas marked effects were apparent at 1,000 ppb (Figure 17). However, P.
perfoliatus exhibited significant etiolation of stems and increases in
chlorophyll a_ content of leaves at 100 ppb atrazine (Table 5), both of
which are typical responses to light stress.
TABLE 5. SUMMARY OF SELECTED STRUCTURAL CHARACTERISTICS OF POTAMOGETON
PERFOLIATUS POPULATIONS IN MICROCOSM COMMUNITIES TREATED WITH THE
HERBICIDE, ATRAZINE (CUNNINGHAM ET AL. 1981a)a
Treatment
Structural13 Control Low High
Characteristic (0.1 ppm) (1.0 ppm)
Chlorophyll-a 28+8 158 ^ 16 114+5
(mg m~2)
Foliar Biomass (Ba) 44.3 + 17.1 24.3 + 8.7 0
(g d.w. m~2)
Rhizobial Biomass (Bb) 40.0 + 12.9 20.0 + 8.6 0
(g d.w. m~2)
Ratio, Bb:Ba 0.93 _+ 0.22 0.94 _+ 0.54
Unit Length of shoots 24 53 63
(cm g~l)
Shoot density 468 495 134
(no. m~2)
aData are from samples taken in the final (6th) week of the experiment.
"Given are mean values +_ standard deviation, where n = 12 for chlorophyll
and n = 6 for biomass. Values for shoot length and shoot density are
measurements from harvest of entire plant population for duplicate micro-
cosms at each treatment.
Correll and Wu (1981) examined the effects of atrazine on V. americana
in some detail, after initial screening experiments indicated that it was
the most sensitive of the four species they examined. They monitored
mortality, vegetative reproduction, and leaf growth as indices of herbicide
stress; they observed about a 35 to 40 percent increase in mortality above
control at 12 ppb atrazine, with similar losses of reproduction and
growth. No significant effects were seen at 3.2 ppb atrazine. This effect
549
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a) ATRAZINE-INDUCED MORTALITY
OF ZOSTERA MARINA
b) ATRAZINE-INDUCED
CHANGES IN HEIGHT OF
7. MARINA
CONTROL O.I I 10 100 1000
ATRAZINE CONCENTRATION (ppb)
Figure 17. Effects of atrazine on (a) percent mortality of Zostera
and (b) height of Zostera (Hershner et al. 1981).
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of 12 ppb is reasonably consistent with the decreases in biomass that were
found for P. perfoliatus at 50 ppb (either linuron or atrazine), where up
to 60 percent reduction (for example, Figure 16) occurred (Cunningham et
al. 1981b). Correll and Wu (1981), however, found almost a 40 percent
increase in mortality of Vallisneria at 12 ppb atrazine, but only a 20
percent decrease in Pa at 75 ppb. It would seem that effects on Pa
should be greater than those on survivorship, since reduction in
photosynthesis does not necessarily lead to death, whereas the inverse is
true. We have no explanation for this apparent inconsistency.
Other Factors Affecting Phytotoxicity
To place these bioassay experimental results into proper perspective,
it is necessary to consider several factors that influence the ultimate
effect of herbicides on SAV.
Acute Versus Chronic Exposures—
Somewhat surprisingly, the relative toxicities of herbicides to SAV
appeared to be independent of exposure-time. Experiments involving
incubations of six to 24 hours (Jones et al. 1981b, Hershner et al. 1981)
yielded results virtually identical to those obtained from exposures of
four to five weeks (Cunningham et al. 1981a, 1981b). In the linuron
experiments, dose-response patterns closely followed those for atrazine,
even though only 10 percent of the parent linuron remained after a
four-week period. On the other hand, Pa of Potamogeton treated with 50
ppb atrazine dropped to 35 percent of controls two weeks after treatment,
but recovered to 70 percent of control levels two weeks later, even though
herbicide concentration remained at 75 percent of initial levels (Figure
12). Thus, it appears that the initial short-term exposure to herbicides,
at a given concentration, largely determines the subsequent pattern of
stress and recovery.
Based on recently-conducted, time-series measurements of l^C-labeled
atrazine uptake by P. perfoliatus, it appears that most uptake occurs
within one to two hours, and no additional incorporation can be measured
after two days of exposure to constant concentrations (T. Jones,
unpublished data). This finding suggests that, in nature, even ephemeral
exposure of SAV to herbicides, such as that following a runoff event, can
induce the same general phytotoxic response and recovery as observed in the
batch microcosms experiments (Figure 12). The rate at which P. perfoliatus
loses previously-incorporated herbicide is currently being examined at
University of Maryland Center for Environmental and Estuarine Studies
(UMCEES) with continuous, subsequent exposure to herbicide-free water.
Apparently, the metabolic recovery shown in Figure 12 involves some sort of
enzymatic detoxification rather than depuration (active or passive removal
via excretion or some other means).
Mode of Uptake—
Jones et al. (I981b) reported that P. perfoliatus uptake of
l^C-labeled atrazine could occur either through shoot or root pathway,
although shoot uptake appeared to dominate. This finding is generally
consistent with findings of previous investigators. Aldrich and Otto
(1959), for example, reported that P^ pectinatus was equally capable of
551
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either root or shoot incorporation of 2,4-D-l-C, and Funderburk and
Lawrence (1963) found that simazine was also taken up through both routes
by the SAV, Heteranthera dubia, but that other herbicides showed no
root-to-shoot translocation through the stem. Frank and Hodgson (1964)
also reported uptake of fenac by both roots and shoots of P_._ pectinatus,
but little or no translocation in either direction. Hence, while some
herbicide uptake by SAV roots is possible, limited ability to translocate
up the stem reduces the importance of this mechanism for chloroplast-active
compounds such as atrazine and linuron. In addition, the relatively high
adsorptive tendency of these herbicides to sediment surfaces may reduce the
herbicide exposure of roots.
Atrazine uptake by P._ perfoliatus occurs hyperbolically, as a function
of external concentration (Ce). At Ce less than about 450 ppb internal
plant concentrations of atrazine, C^, were less than Ce, while C^
approaches Ce at about 500 ppb. Moreover, as G£ approaches Ce, Pa
approaches zero. Thus, atrazine incorporation does not follow a strict
Fickian diffusion at low herbicide concentration, although the first-order
process is approximated at Ce<500 ppb (Jones et al. 1981b).
It had been postulated that herbicides bound to suspended sediments
and/or colloids, which subsequently settled on SAV leaf surfaces,
represented a potential mechanism for magnifying the concentrations to
which plants are exposed. However, recent experiments have indicated that
P. perfoliatus shows little or no uptake of atrazine from herbicide-bound
sediments placed on SAV leaves (T. Jones, unpublished data). In addition,
Correll and Wu (1981) found that atrazine concentrated in surface
microlayer films exhibited no greater phytotoxicity than the same quantity
mixed in a large water-volume bathing SAV in microcosm experiments.
Combined Stresses—
Although it is important to understand the individual effects of
herbicide stress on SAV, many environmental factors act simultaneously on
the plants in nature. Therefore, the significance of combined effects of
herbicide-herbicide, herbicide-light, and herbicide-nutrient interactions
must be considered.
Some preliminary investigations of atrazine-linuron combinations with
P. perfoliatus suggest that 25 ppb of each herbicide reduced Pfl more than
50 ppb of either herbicide combination for the last two post-treatment
weeks. However, there was no difference estimated by the Colby (1967)
formulation for the first two post-treatment weeks (Cunningham et al.
1981b). Additional experiments with herbicide combinations are in
progress, but these results are not yet available. The agricultural
weed-control literature contains some information on combined herbicide
effects, but these reports are also inconclusive. For example, Horowitz
and Herzlinger (1973) found that only one out of seven combination
experiments with diruon, simazine, trifluralin, and fluometurn at 0.1 and
0.5 ppm exhibited significant synergism. Akobundu et al. (1975) observed
synergistic action between atrazine and alachlor, but this nonlinear effect
was small. Appleby and Somabhi (1978) investigated the reported
antagonisms between atrazine (or simazine) and glyphosate and found that
the interaction was due more to the physical binding in spray solution than
to any biochemical mechanism. At this point, the importance of
herbicide-herbicide synergisms for SAV toxicity in the Chesapeake Bay
552
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region is unclear; however, the effect is probably small.
A consistent pattern of interaction between light and herbicides has
been observed for SAV and other plants. When subjected to 30 percent
shading, the relative response of Z._ marina to atrazine treatment (Figure
14d) was markedly reduced as compared to 100 percent light (Hershner et al.
1981). When the effects of atrazine (50 ppb) on P^ perfoliatus
photosynthesis were tested over a full range of light intensities, it was
found that the relative toxicity (reduction in Pa) is greater at
less-than-saturating light intensities (T. Jones et al., unpublished
data). Hodgson and Otto (1963) showed that two species of Potamogeton were
more sensitive to contact herbicides at high, rather than low light
intensities, and similar results have been reported for algae (McFarlane et
al. 1972) and weeds (for example, Hammerton 1967). This relationship
probably exists, because the more active chloroplasts operating at high
light levels are more susceptible to herbicidal damage. In a related
experiment, we observed that epiphytic sediments significantly reduced
atrazine uptake by j>. perfoliatus leaves (T. Jones et al., unpublished
data). This effect may be attributable to a combination of physical
buffering and sorption by epiphytic sediments, as well as the
light-herbicide relationship mentioned above.
Under conditions of nutrient sufficiency, which occur for SAV
throughout most of the upper and middle Bay, nutrient additions would be
expected to show little effect on herbicide phytotoxicity. This conclusion
was reached after a series of recent experiments. However, SAV grown for
months in microcosms can experience nutrient (or CC^) limitation (Kemp et
al. 1980) and thus provide a simple way of addressing the question of
nutrient limitation. In Figure 18, the results of four different atrazine-
Potamogeton experiments are summarized in a manner that may reveal such a
relationship. A negative trend was found between herbicide toxicity at 25
ppb and maximum Pa at full incubator light intensity (150 uE
m~2s-l). it might be inferred that nutrient limitation (or some other
environmental stress reducing peak Pa) increases herbicidal action on
SAV. The potential effect of nutrient-induced epifloral growth attached to
SAV on herbicide stress has not been examined, but it might be expected to
act in much the same fashion as did epiphytic sediments.
Metabolites of Herbicides—
One herbicide-SAV issue that has yet to be addressed in this research
is the potential toxicity of herbicide metabolites, or degradation
products. In a previous Section, it was shown that the dealkylated
daughter products of atrazine degradation occur at persistently low levels
« 10 percent of original atrazine) in soils, sediments, and water.
Various investigators have shown that the dealkylated degradation products
of atrazine retain some toxicity (although considerably less than the
parent compound) to terrestrial plants (Shimabukuro 1968, Kaufman and Blake
1970). The carry-over toxicity, which has been reported for atrazine-
treated fields from one year to the next, has been attributed by some to
the persistence of the N-de-ethylated metabolites. Both Sirons et al.
(1973) and Dao et al. (1979), for example, have reported carry-over
toxicity after atrazine application to croplands for as long as two years.
At present, the toxicity to SAV from metabolites of atrazine and other
herbicides is not known, nor are the levels of these compounds in the
553
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Figure 18. Effects of plant vigor on atrazine response for _P. perfoliatus
(Cunningham et al. 1981b). ~
554
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I environment. Although the potential for metabolite build-up in estuarine
sediments may appear remote, the issue remains the one major gap in our
understanding of the overall herbicide-SAV issue.
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SECTION 6
SUMMARY AND IMPLICATIONS
SUMMARY OF RESEARCH FINDINGS
In this paper we have highlighted the results of extensive research
supported by EPA-CBP to investigate the behavior of agricultural herbicides
in an estuarine environment, particularly in relation to Chesapeake Bay's
dwindling communities of submerged aquatic vegetation. The relative,
potential importance of various herbicidal compounds in relation to SAV was
considered, and atrazine and linuron were selected for primary focus. The
watercourses in this coastal region have been systematically sampled for
herbicide concentration from the mainstem Chesapeake Bay, to primary
tributaries, to secondary bays and coves, to creeks that drain agricultural
fields. Maximum observed concentrations of these two major herbicides in
the four levels of tributaries were about four ppb, 7.0 ppb, 20 ppb, and
100 ppb, respectively. High herbicide concentrations of about 10 to 20 ppb
were observed to occur in estuarine waters for ephemeral periods of two to
eight hours. The length of time between herbicide application to the
cropland and the first rainfall-runoff event, and the extent and intensity
of rainfall, are key factors governing the transport of herbicides from the
field to the estuary.
The degradation of atrazine in estuarine environments appears to occur
far more rapidly than in agricultural soils, with half-lives of two to 26
weeks, respectively. The longevity of linuron is less than that of
atrazine and, in fact the latter compound appears to be one of the most
persistent herbicides used in the watershed. Atrazine exhibits moderate
tendency for adsorption to soils and estuarine sediments. Most of the
herbicide running off from field to watercourse does so in the dissolved
form, rather than bound to soil particles, and most of the atrazine in the
estuary is similarly found in the dissolved state. Estuarine colloids have
about 10 times greater ability to bind atrazine than do sediments and
soils. Salinity and circum-neutral pH appear to exert little influence on
herbicide-sediment sorption; however, increased salinity does tend t:o
decrease the proportion of herbicide bound to colloidal matter.
Atrazine brings about a dramatic stress response for several species of
SAV at concentrations of 50 to 100 ppb. At these concentrations,
reductions of photosynthesis are always significant, and full recovery of
photosynthetic rates may not be attained. The relation between percent
loss of photosynthesis and herbicide concentration generally follows a
semilogarithmic function for all species and both compounds tested. This
model predicts threshold toxicities at herbicide concentrations ranging
from 1.0 to 7.0 ppb. Combining all experimental data for three species and
two herbicides yielded a highly significant regression (r^ = 0.89), which
predicts about 10 to 20 percent loss of SAV photosynthesis at 5.0 to 10.0
ppb herbicide. Similar herbicidal effects were observed for plant
structural characteristics.
Experiments with P_._ perfoliatus and atrazine indicate that herbicide
uptake, which is a function of external concentration, proceeds to
equilibrium within one hour, and that depuration (loss of herbicide) upon
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exposure to clean water occurs very slowly, with toxic effects still
apparent after days of cleasing. Reduced light level (above compensation
light) and/or presence of epiphytic sediments appear to decrease the
relative stress effect of herbicide on SAV, but nutrient deficiency and
plant senescence may tend to increase herbicide effects. There are
currently few data to support the hypothesis that combinations of two or
more herbicides act in any other than an additive fashion. The potential
toxicity of herbicide metabolites (degradation products) to SAV is a matter
about which very little is known.
DID HERBICIDES CAUSE THE SAV DECLINE?
From the evidence that has been compiled here, the answer to this
question is most likely no. Herbicide concentrations in excess of 20 ppb
were not found in estuarine waters in various surveys since 1977, under a
range of situations, including those which approach worst-case runoff
conditions. Under such extreme conditions, concentrations of 10 to 20 ppb
were observed, but rarely lasted more than four to eight hours. Although
exposures to 20 ppb (of one hour or more) will cause significant loss of
productivity, full metabolic recovery would be expected within one to four
weeks following initial contact. Moreover, herbicides degrade rapidly in
the estuarine environment, with half-lives measured in days and weeks;
residual concentrations do not appear to build up in sediments. The
hypothesized mechanisms of increasing SAV exposure to herbicides via
concentration of the compounds in epiphytic sediments or surface-layer
films do not appear to represent significant factors. One of the caveates
that remains unresolved is the fact that very little is known about
estuarine concentrations and SAV toxicities of major herbicide
metabolites. The de-ethylated daughter products of atrazine degradation do
tend to persist for months under estuarine conditions, and weed-control
literature attributes carryover toxicity (after atrazine application) to
this metabolite.
ARE HERBICIDES A PROBLEM?
Ephemeral herbicide concentrations in excess of 5.0 ppb do occur
periodically in some estuarine water that once contained extensive SAV
beds. In general, such concentrations appear to cause losses in SAV
productivity of 10 to 20 percent, even when exposures are brief (about an
hour), and recovery may take days to weeks. The effects of repeated,
brief exposures to such concentrations are not known. A reasonable
assumption, however, would be that if the time interval between runoff
events (which might yield such deleterious concentrations) is greater than
SAV recovery time, then the partial loss of photosynthesis may persist.
Such reductions in SAV productivity will definitely add to the generally
stressed conditions that these plants currently experience in the estuary.
The sources of most of these stresses include such factors as salinity
extremes, waterfowl grazing, uprooting by cownose rays, and turbulent
waters or violent wave action caused by major storm events, as well as
water-column turbidity and the accumulation of epiphytic materials.
Herbicide-induced loss of productivity (though minor) could act in concert
with many of these stressors to create intolerable conditions for SAV
existence.
557
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en
h-
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or
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EASTERN BAY
\
CHESTER
RIVER
-CHOPTANK RIVER
Y= 23.7- 26. 4X
( r2 = 0.91)
PATUXENT
RIVER
WICOMICO xv NANTICOKE
RIVER
RIVER
I 10
POTENTIAL DIFFUSE LOADING, m2 m3
Figure 19. Correlation of potential diffuse loadings and percent occurrence
of SAV in 1974 (Stevenson and Confer 1978).
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The source of herbicidal compounds to Chesapeake Bay is agricultural
runoff. There appears to be a relationship between potential loadings
(that is, watershed area divided by estuarine volume) of nonpoint, or
diffuse-source materials (including herbicides, nutrients, and sediments),
and SAV abundance in six major tributaries (Figure 19). This correlation
suggests that the greater the loadings from runoff, the more extensive the
decline has been.
Although the development of recommended farming practices is well
beyond the scope of this research endeavor, it is hoped that these research
results and their environmental implications will be considered by the
agricultural community in the evolution of improved farming approaches.
The importance of agriculture in the socio-economic milieu of the
Chesapeake region is unquestionable. Our recommendation is simply that the
estuarine resource values be considered in concert with the land-based
values to develop balanced patterns of human enterprise.
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Eastern North America. D.L. Correll, ed. Smithsonian Institute Press,
Washington, DC. pp. 707-724.
Wu, T.L. , L. Lambert, D. Hastings, and L). Banning. 1980. Enrichment of
the Agricultural Herbicide Atrazine in the Microsurface Water of an
Estuary. Bull. Environ. Contam. Toxicol. 24:411-414.
Zahnow, E.W., and J.D. Riggleman. 1980. Search for Linuron Residues in
Tributaries of the Chesapeake Bay. J. Agric. Food Chem. 28:974-978.
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LIGHT AND SUBMERGED MACROPHYTE COMMUNITIES IN
CHESAPEAKE BAY: A SCIENTIFIC SUMMARY
by
Richard L. Wetzel, Robin F. van Tine, and Polly A. Penhale
Virginia Institute ot Marine Science
and School of Marine Science College of William and Mary
Gloucester Point, Virginia 23062
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CONTENTS
Figures 570
Tables 572
1. Introduction 573
Background 573
The Research Program on Light and SAV: An Overview . . . 575
2. Light in Chesapeake Bay 578
General Characteristics of Estuarine Optical Properties . 578
Light Attenuation in Chesapeake Bay 583
Comparison of Light Attenuation in Vegetated and
Unvegetated Sites in the Bay 585
Historical Data Bases and Optical Properties of the
Chesapeake Bay 588
3. Light and Photosynthesis in Chesapeake Bay SAV Communities. 600
General Review of Photosynthesis 600
Photosynthesis of Submerged Vascular Plants in Relation
to Light and Temperature 601
Photosynthesis-Light Studies in Chesapeake Bay 604
P-I Relationship of Major Species 604
Microcosm Studies 609
I_ti Situ Studies of Community Response to Light .... 609
4. Summary 621
Literature Cited 624
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FIGURES
Number Page
1. Path of light from the atmosphere to benthic estuarine
macrophytes 580
2- Downwelling spectral quanta irradiance in a Zostera bed 581
3. Diffuse downwelling spectral attenuation coefficients for
Chesapeake Bay 584
4. Lower Chesapeake Bay light study stations 535
5. Diffuse downwelling spectral attenuation coefficients for
vegetated and unvegetated sites 5gg
6- Downwelling PAR attenuation coefficients for vegetated and
unvegetated sites 589
7. Historical Chesapeake Bay Secchi disk values 590
8. Summary of the historical chlorophyll a_ data for the upper and
lower Chesapeake Bay 592
9. Historical chlorophyll a_ data for three regions of
Chesapeake Bay ....... 593
10. Enriched areas of Chesapeake Bay 593
11. Diagramatic photosynthesis-light curves 602
12. Photosynthesis-light curves for two upper Chesapeake Bay
species 605
13. Photosynthesis-light curves for two lower Chesapeake Bay
species 606
14. Vertical distribution of leaf area index for Ruppia and
Zostera 610
15. Total chlorophyll in Ruppia and Zostera leaves 611
16. Suspended solids, light availability, and Potamogeton
photosynthesis 612
17. The effect of light flux on upper Chesapeake Bay SAV
photosynthesis „ 613
18. Diagramatic representation of light flux and calculated
photosynthetic parameters for an upper Chesapeake Bay site . ,. 615
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FIGURES (Continued)
f Number Page
19. Apparent productivity and light flux at a Ruppia site °
f 20. Apparent productivity and light flux at a Zostera site 617
121. Apparent productivity versus light flux for three sites in the
lower Chesapeake Bay 618
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TABLES
Number
1. Comparison of PAR Attenuation Coefficients inside and
outside an SAV bed 591
2. Secchi Disc Data, upper Chesapeake Bay 594
3. Chlorophyll £ Concentrations in the lower Potomac River .... 595
4. Freshwater Flows and Hurricanes in Chesapeake Bay 596
5. Suspended Sediment Transport in the Susquehanna River 597
6. Photosynthetic Parameters for Ruppia and Zostera 607
7. Literature Review of Photosynthesis-Light Experiments 608
8. In situ Oxygen Productivity and Light Experiments 619
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SECTION I
INTRODUCTION
The initial focus of submerged aquatic vegetation (SAV) research in the
U.S. Environmental Protection Agency (EPA), Chesapeake Bay Program (CBP)
was evaluation of the structural and functional ecology of these
communities. In the upper Bay, Myriophyllum spicatum and Potamogeton
perfoliatus are the dominant species; the dominant species in the lower Bay
are Zostera marina and Ruppia marititna. Studies centered on various
aspects of productivity (both primary and secondary), trophic structure,
and resource utilization by both ecologically and economically important
species. Much of the initial research was descriptively oriented because
of a general lack of information on Chesapeake Bay submerged plant
communities. These investigations created the data base necessary for the
development of ecologically realistic simulation models of the ecosystem.
Following these initial studies, the research programs in both Maryland and
Virginia evolved toward more detailed analyses of specific factors that
potentially limit or control plant growth and productivity. Previous
results indicated certain environmental parameters and biological processes
that possibly limited and controlled SAV distribution and abundance.
Specifically, these included light, nutrients, herbicides and fouling
(epibiotic growth). Laboratory and field studies were devoted in the later
phases of the CBP-SAV program toward investigating these interactions.
This work is among the first studies in North America to investigate light
quality as a major environmental factor affecting the survival of sea
grasses.
The overall objectives of this later work were to evaluate more
precisely environmental and biological factors in relation to submerged
aquatic plant community structure and function. Both the published
literature and the results of CBP-SAV program studies indicate that the
interaction of these environmental parameters, together with other physical
and biological characteristics of the ecosystem, determine the longer term
success or failure of SAV communities (den Hartog 1970, den Hartog and
Polderman 1975, Williams 1977, Wetzel et al. 1982).
BACKGROUND
A major goal of CBP-SAV research was to investigate the response of Bay
grasses to various environmental variables. Studies centered on the four
dominant submerged aquatics in the Bay. Understanding the relationship
between environmental factors and the productivity and growth of SAV was
determined to be the first step necessary in attaining the overall goals of
the management program. Natural and man-made changes in environmental
quality may favor one species or another, or result in alteration of the
entire community. The basic responses of the grasses, as well as the
entire community, must be determined before environmental change can be
evaluated in terms of specific management criteria.
Studies in the various CBP-SAV research programs that address
environmental regulation and control of SAV communities focused on nutrient
regulation [primarily nitrogen as ammonium (NHj) and nitrate
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(NC>3)], light and photosynthesis, and other biological and
physical-chemical factors influencing light energy distribution.
The results of studies in the lower Bay communities suggest a net
positive response to short-term nutrient additions and support the
observation by others that these communities are nutrient limited (Orth
1977). The most consistent positive response is associated with Ruppia
dominated communities, and the most variable is associated with the deeper
Zostera community (Wetzel et al. 1979). In contrast, Kemp et al. (1981b)
observed that upper-Bay SAV communities did not appear nutrient limited,
but were perhaps limited by suboptimal light conditions. These results,
together with community metabolism studies, suggest that light and the
environmental factors controlling available light are key factors governing
plant community growth and productivity. Light-temperature-turbidity
regimes and their interaction may explain, in large part, observed
variability in distribution and abundance. Changes in these parameters,
governed by either natural or man-induced events and, perhaps, determined
over longer time scales, influence variation in distribution and abundance
in Chesapeake Bay ecosystem as a whole.
Throughout Chesapeake Bay, submerged aquatic plant communities exhibit
a distinct zonation pattern from the shallower inshore high-light area to
the deeper, low-light area of the beds. These characteristic distribution
patterns also suggest different physiological responses to and control by
local environmental conditions, principally light.
Studies were initiated in August, 1979, on lower-Bay Ruppia-Zostera
communities and continued for an annual cycle to investigate the effects of
light and temperature on specific rates of seagrass photosynthesis. The
experiments were l^C uptake studies in which plants were removed from the
sediment, placed in a set of screened jars, and incubated in a running
seawater system using ambient sunlight. The plants were exposed to 100,
50, 30, 15, 5, and 1 percent of ambient light to determine the effect of
light quantity on photosynthesis. Experimental designs comparable with
these were also conducted for upper-Bay species. Results are discussed
later in this paper in Section 3.
In conjunction with these studies, measures of leaf area index (LAI)
were also conducted. Physiologically, the photosynthesis-light
relationship determines the light levels at which SAV can grow and
reproduce, that is, succeed. A greater leaf area exposed to light results
in greater productivity; however, light reaching the plants is not only
determined by physical factors controlling light penetration through the
water column, but by plant self-shading. Maximum plant biomass can in part
be related to leaf area. The leaf area index (plant area per sediment
surface area) estimates maximum leaf density and thus potential area
available to intercept light (Evans 1972, cited in McRoy and McMillan 1979).
Leaf surface area also provides a substrate for epiphytic growth. Leaf
area samples were collected to characterize the three main vegetation zones
typical of lower-Bay communities. These data were used to provide a more
accurate description of light penetration through the plant canopy as well
as to evaluate potential morphological adaptation of the plants to various
light environments. To complement these specific l^C studies and LAI
measures, field studies were completed to determine the effect of j.n situ
light reduction through artificial shading. Light reductions of 70 to 20
percent of ambient were used. The results of these studies support the
574
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hypothesis that total community metabolism is governed by, and is very
sensitive to, available light. During the course of these investigations,
light data collected in the field for various environmental (climatic)
conditions indicated that natural light reductions of these magnitudes were
common. To determine the overall effects of light reduction, specific
factors were investigated more thoroughly using both laboratory and in situ
experimental approaches for light-photosynthesis relationships, as well as
studies that determined those environmental variables controlling light
energy distribution and availability to the plant communities.
Studies initiated during the later phases of the CBP-SAV research
program investigated the effects of epiphytic growth and metabolism, and
the interactive effects of light and acute exposure to the herbicide
atrazine. Studies on epiphyte colonization were along two lines: the
epiphytic community as a primary producer and food source, and as a
competitor with the vascular plant community for available light.
Experiments completed suggest that the epiphyte community at times
dominates metabolism of the community and limits light available for
vascular plant photosynthesis. What remained to be determined was what
environmental conditions favor colonization, and at what point does the
resulting colonization stress the vascular plant.
These various research activities provide a data and information base
that serve management needs and identify specific research areas where
additional information is required for integration and synthesis. The work
proposed in the later part of the CBP-SAV program centered on filling what
were considered major gaps in information and the data base. The synthesis
report that follows is directed to our current state of understanding of
light energy properties and distribution in Chesapeake Bay and to the
relation of this information to past and current knowledge about SAV
community growth and survival.
THE RESEARCH PROGRAM ON LIGHT AND SAV: AN OVERVIEW
It has been the working hypothesis of the Chesapeake Bay Program-SAV
group that changes in such water quality variables as suspended
particulates (both living and non-living), dissolved substances, and
nutrients alter, directly or indirectly, underwater light regimes in such a
way as to limit benthic macrophyte primary production. Plants absorb light
energy for the process of photosynthesis, converting water and carbon
dioxide into organic compounds. White light (visible sunlight) is composed
of a spectrum of colors that are used selectively by green leaves based on
the plant's specific pigment complexes. Chlorophyll requires mainly red
and blue light for photosynthesis; these wavelengths are absorbed, and the
green and yellow bands are reflected. The accessory pigments also absorb
in the blue region.
As light penetrates the water column, the energy content and spectral
quality are changed by absorption and scattering. Water itself, dissolved
substances, and particulate materials are responsible for both the
absorption (conversion into heat energy) and the scattering of light.
Selective absorption and scattering by these factors result in attenuation
of specific light wavelengths causing a "color shift" (Kalle 1966, Jerlov
1976). Scattering, the change in direction of light propagation, returns
some of the incident radiation toward the surface and thus further reduces
the total light energy available to support photosynthesis. Phytoplankton
575
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act as both scattering and selectively absorptive and reflective particles
and are in direct competition with other primary producers for the same
wavelengths of light—the red and blue bands.
The temporal and spatial distribution of particulate materials and
dissolved substances are largely determined by climatic variables and
biological processes. Wind velocity and direction, tidal amplitude and
frequency, current velocity, rain, and land runoff all interact to induce
variations in water quality parameters and subsequently the spectral
composition of light in the water column (Dubinsky and Herman 1979, Kranck
1980, Anderson 1980, Thompson et al. 1979, Scott 1978, Riaux and Douville
1980).
Based on these general premises, the light research program encompassed
four basic facets: (1) description of the submarine light environment
together with measures of various water quality parameters; (2) description
of climatic and oceanic forcing functions; (3) detailed studies of
photosynthesis-light relations by individual species and for entire SAV
communities; and (4) analysis of the relationships and correlations among
the above data and other available information. The measurement and
collection of light, water quality parameters, climatic and oceanic forcing
functions were made simultaneously with the light-photosynthesis
investigations. Studies on both shores of the upper and lower Chesapeake
Bay in vegetated and non-vegetated regions were undertaken.
Characterization of the light environment was accomplished using a
Biospherical Instruments Model MER-1000 Spectroradiometer (Booth and
Dunstan 1979). Specific attenuation in 12 biologically important
wavelengths and integrated photosynthetically active radiation (PAR) values
were calculated from these data. The spectral irradiance measurements were
made in quantum units as suggested for biological studies by the Special
Committee on Oceanographic Research (SCOR) of the International Association
of Physical Oceanographers (IAPO).
There is a paucity of data on spectral irradiance in marine
environments (Jerlov 1976) . There are even fewer studies reporting data
for estuarine waters, Chesapeake Bay being no exception. Burt (1953,
1955a, b), using a shipboard spectrophotometer, analyzed filtered seawater
samples from Chesapeake Bay and concluded that the primary factor in Light
extinction was the filterable, particulate matter. Seliger and Loftus
(1974) studied the spectral distribution of light in shallow water in a
subestuary in the upper Bay in July and found a marked reduction of light
in the 400-500 nm region of the spectrum. Champ et al. (1980) report an
observed "orange-shift" for measurements made in the upper Bay during
August, 1977, using a submersible solar illuminance meter equipped with
optical filters. They suggest that there is a continuum of spectral shifts
toward the penetration of longer wavelengths from oceanic to coastal to
estuarine waters. This corroborates and extends Kalle's "yellow shift"
theory (Kalle 1966). Kalle contends that the shift to longer wavelengths
is more pronounced as the concentrations of suspended particles increases.
These investigations make up, in large part, the only complementary data
base and, to our knowledge, no data exists in and around SAV habitats.
Broad band (PAR) transmittance was determined with a Montedoro-Whitney
in situ combination beam transmissometer and nephelometer. The
transmittance data were used to calculate the attenuation coefficient
"defined as the absorption coefficient plus the total scattering
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coefficient" (Jerlov 1976, Kiefer and Austin 1974). van Tine (1981) found
significant correlations between absence of submerged aquatic vegetation
and low transmittance values in an estuary in the Gulf of Mexico.
Total particulate matter (TPM), particulate organic matter (POM),
particulate-ATP, particulate chlorophyll £, particulate inorganic matter
(PIM) were monitored in light spectral studies. These various measures
were used to estimate phytoplankton, zooplankton, detritus, and inorganic
fractions of the TPM.
Wind velocity and direction, water current velocity, tidal stage and
depth were determined concurrently with the other measures. Kiley (1980)
suggests a close relationship between wind and current for the York River.
In an effort to explain turbidity values, Williams (1980) calculated
significant positive correlations between wind and turbidity for upper-Bay
subestuaries. Ginsburg and Lowenstam (1957) and Scoffin (1970) showed a
baffling effect of SAV on currents that caused particulate matter to settle
out, generally improving the local light environment. Collection and
analyses of these data formed the basis for characterization of the natural
light environment and of the factors that are principal controls.
Various lines of evidence, as discussed earlier, suggest light in
general as a major factor controlling the distribution and productivity of
seagrasses. Preliminary studies demonstrated both potential nutrient and
light quantity effects on plant community metabolism. In the later phases
of CBP-SAV research, both field and laboratory studies were designed and
carried out in a more quantitative sense on photosynthesis-light relations
in Chesapeake Bay SAV communities.
For the field approaches, the entire SAV community and its interactions
were included in experimental designs. Short-term shading experiments
reflected the community response to daily variations in light quantity due
to such natural phenomena as cloud cover, tidal stage, and storm events.
Long-term shading studies reflected community response to possible
situations where water quality deteriorates to the point where light
penetration is reduced. The purpose of these studies is to estimate at
what point, relative to light quantity, the SAV communities would die out.
For the latter effort, sets of neutral density mesh canopies were placed in
selected SAV areas for long term studies. Shaded and control areas were
studied at regular intervals over the course of these experiments (1-2
months). With this design, community metabolism and various plant
community parameters (e.g., leaf area index, chlorophyll a^ and b_, biomass,
and other plant meristic characters) were measured. Studies were carried
out in spring, summer, and early fall, 1981, to include the major growth
and die-back periods.
Past research programs in the CBP-SAV program resulted in several
hypotheses that might explain both the short and longer term survival of
Bay grasses. Among these, the potential for light, including those
variables influencing light, or more specifically light-energy
distribution, as a major environmental variable controlling SAV
distribution, growth, and survival was postulated. The intent of the
remaining sections of this report is to provide the general characteristics
of light in natural aquatic systems with emphasis on Chesapeake Bay; to
summarize the research results throughout the Bay relative to light and Bay
grasses; and to discuss the potential for light or light-related casualty
of Bay grass declines.
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SECTION 2
LIGHT IN CHESAPEAKE BAY
GENERAL CHARACTERISTICS OF ESTUARINE OPTICAL PROPERTIES
The study of the interaction of solar energy with estuarine waters
necessitates not only an understanding of the properties of light and
water, but also of the myriad living and non-living entities, both
dissolved and suspended, which affect the propagation of light in aquatic
environment s .
The sun emits electromagnetic radiation in discrete packs or quanta (Q)
of energy called photons. The energy content (£.) of each quantum is
directly proportional to the frequency
and indirectly proportional to the wavelength (70,
€= h-6
, /^
where rl- is Planck s universal constant, and <*. is the speed of light in a
vacuum. This means that quanta of shorter wavelengths contain more energy
than quanta of longer wavelengths.
The complete spectrum of downward irradiance for incoming solar
radiation at the top of the atmosphere, at sea level, and at several water
depths is illustrated in Figure la. Most of the energy reaching the
earth's surface is contained within the shorter wavelengths (0.4 to 1 u or
400 to 1,000 nml). Not surprisingly, this region includes the
wavelengths of greatest biological importance, that is, 400 to 700 nm, the
photosynthetically active region of the spectrum termed PAR or PHAR. There
is almost no energy outside the PAR region at a depth of 1 m. Most of the
"missing" energy has been converted to heat by absorption. Only four to 11
percent of incident irradiance between 300-700 nm is reflected from the
surface or backscattered out of the water column (called albedo) (Clark and
Ewing 1974).
The properties and concepts in optical oceanography are usually divided
into two mutually exclusive classes, inherent and apparent. Inherent
properties, such as absorption and scattering, are independent of changes
in insolation (incoming light), whereas apparent properties, such as
underwater irradiance, vary with changing solar and atmospheric conditions.
As light passes through the water column, its energy content and
spectral quality are changed by absorption and scattering due to water
itself, dissolved substances, and suspended particles. The combined effect
of these processes is termed attenuation. The spectral distribution of the
total attenuation coefficient (o() , measured with the beam transmissometer ,
generally shows high attenuance at both ends of the PAR. Since o^ is an
aggregated coefficient, it is informative to consider the component
parameters that cause the observed attenuance.
1 1 nm = 10-3 um = 10-9
m
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Scattering is the change in direction of light propagation caused by
diffraction, refraction, and reflection due to particles, water molecules,
'and dissolved substances. Scattering is wavelength dependent, but in an
irregular and complex manner. Absorption is a thermodynamically
irreversible process wherein protons are converted to thermal, kinetic, or
chemical energy; photosynthesis is an example. Much of the attenuance in
the long wavelengths is due to the water itself, as shown by James and
Birge (1938) for pure water and by Clarke and James (1939) for filtered
seawater (see Figure 1). The effect of sea salts on attenuance is
insignificant. Pure water or pure seawater show a constant light
attenuation. Of course, natural water bodies (particularly estuaries) are
not pure, but contain constantly varying particulate and dissolved
substances. Burt (1958), using uncontaminated filtered seawater samples,
was able to determine the attenuance due to dissolved substances. By
subtracting this from the total attenuation coefficient of non-filtered
seawater, he was able to calculate the light attenuance due to particulate
matter. The energy of blue and red wavelengths is selectively absorbed by
particles, as shown in the example given by Prieur and Sathyendranath
(1981) (Figure Ib). The shorter wavelengths are also attenuated by yellow
substance or Gelbstoff (see Figure Ib), the collective name given to a
complex mixture of organic compounds by Kalle (1966). Gelbstoff is formed
from carbohydrates resulting from organic matter decomposition. Sources
are both allocthonous (swamps, marshes, land runoff) and autocthonous
(planktonic and benthic organisms). Flocculation of fine suspended and
colloidal materials in estuaries probably promotes the reaction, as does
the presence of amino acids (Kalle 1966).
The apparent optical properties of a body of water result from the
measurement of natural light fields underwater, that is, the measurement of
in situ radiant flux. Irradiance (E) (the flux of light per unit area) is
usually collected with a flat circular opal glass (or plastic) diffuser
(2 T> collector). The diffuser is designed so that light received from all
angles is transmitted to the sensor according to Lambert's cosine law. In
other words, the irradiance transmitted is proportional to the incident
radiant intensity multiplied by the cosine of the angle of incidence.
Jerlov (1976) reports that the ratio of cosine collection of downwelling
irradiance (E
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LU
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8-1
SURFACE INSOLATION
400 500 600
WAVE LENGTH (nm)
700
Figure 2. Downwelling spectral quanta irradiance at the surface and at
several depths (Z) above the canopy of a Zostera marina bed on
the eastern shore of lower Chesapeake Bay (Vaucluse Shores)
at 1230 E.S.T. on a cloudy April day. The scale for the
insolation is on the right (Wetzel et al. 1982).
581
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constituents cause specific spectral attenuation patterns. As these
constituents change both temporally and spatially, the resultant spectral
absorption pattern changes. Prieur and Sathyendranath (1981) have
attempted to classify water bodies based on combinations of these factors.
The diffuse downwelling (or vertical) attenuation coefficient2
expresses the decay of irradiance as an exponential function,
- In
kd =
(22 - z^)
where E£ is the irradiance at depth Z£; E^ is the irradiance at depth
Z;L; and (7*2 ~ zl) is tne distance between the two measurement depths
in meters. The units of K^ are m"^-.
If (Z2 - Zi) brackets the air-water interface, it will include the
effects of reflection and inflate the estimate of K^. K^ calculated
between depths measures the effects of inherent properties of the layer of
water on the propagation of light through that distance. Because this
distinction is not always specified in the literature, it is sometimes
difficult to compare attenuation values. The well-defined spectral
attenuation coefficient (K^ or X) is a particularly useful parameter for
comparing underwater irradiance between water bodies, seasons, and
wavelengths. Because K^ varies with depth in shallow water (10 m),
comparisons should be made at the same depths. Figure Ic shows a typical
spectral distribution of both E^ and K^ over the PAR in a Chesapeake
Bay grass-bed. The distribution is a result of the additive effects of the
attenuations and scattering of seawater, dissolved substances,
non-chlorophyllous particles, and phytoplankton (see Figure Ib). Pierce et
al. (1981) determined, by step-wise multiple linear regression, that
chlorophylls a_ and c_ and inorganic particles explain most of the observed
variation in spectral attenuation in the Rhode River Estuary (upper
Chesapeake Bay).
The diffuse attenuation coefficient (K
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portions to which higher plants such as seagrasses respond the most
efficiently. The mean quantum action spectrum for 50 species of higher
plants is presented in Figure Id (Inada 1976). A photosynthetic action
spectrum is produced by exposing a plant to controlled amounts of energy
(or quanta) at discrete wavelengths and by measuring its photosynthetic
response. The action spectrum in this figure is normalized to the highest
observed photosynthetic rates for red light. The curve presented here is
an approximation of the likely action spectrum for seagrasses. A major
peak falls in the 400-500 nm (blue) range, a region in estuarine waters
where very little light is available because of absorption by inorganic
particles, phytoplankton, and Gelbstoff.
Temporal variations in light distribution, both in the atmosphere and
underwater, are due directly and indirectly to the relative motions of the
earth, moon, and sun. The distance between the earth and sun and between
the earth and moon determines not only the amount of energy received by the
earth, but also the depth of water through which it must travel to reach
the seagrasses. The seasonal distribution of nutrients and the resultant
plankton blooms and runoff (with particulate and dissolved loads and
changed salinity regimes) also cause temporal variations in estuarine
underwater optical properties. Storms and wind increase land runoff,
currents, and waves. In shallow areas, this action increases
resuspension. Scott (1978) found that it took 11 days for the submarine
irradiance to return to pre-storm levels in an estuary in Australia. In
littoral regions, average submarine light conditions may be partly
controlled by the interaction of the local coastal morphology with
prevailing wind patterns.
Diurnal variations have two components: solar elevation and tidal
variation (amplitude and frequency). Since the interface between water and
air is a boundary between media of different optical densities, an
electromagnetic wave striking it splits into a reflected and a refracted
wave. Reflection of combined sun and skylight from a horizontal, flat
surface varies asymptotically with solar elevation between three to six
percent at angles greater than 30° from the horizon. Below 30°, the
reflectance increases dramatically up to 40 percent at 5°. Reflection
below 30° is wavelength dependent. The longer waves are reflected more
because the changing quantity of diffuse atmospheric light at low sun
angles (Sauberer and Ruttner 1941). Wave action, on the other hand,
reduces reflection at low angles.
Tidal cycles in estuaries not only change water bodies and their
associated seston and dissolved components, but also cause resuspension of
sediments and differences in depth. These are, of course, highly
idiosyncratic for specific systems (Burt 1955b, Scott 1978).
LIGHT ATTENUATION IN CHESAPEAKE BAY
A comparison of diffuse downwelling spectral attenuation coefficients
reported for Chesapeake Bay and its tributaries is presented in Figure 3
along with Jerlov's (1976) most turbid coastal water classification curve
(Type 9). For Chesapeake Bay, the earliest measurements of kcj(^k) were
made by Hurlburt (1945) (Figure 3a). His values fall in the lower range of
more recent in situ measurements. The shaded areas in Figure 3a represent
the range of values measured by Wetzel et al. (1982) from March through
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ecu. < —
pOUJ *
LL. Q. uj
OT< Z
< co z
UJ UJ
<
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to a;
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flj
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NOIiVnN3ilV
584
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I
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I
July, 1981, in shallow regions of the lower Bay (O m). Jerlov's curve
falls in these observed ranges, showing that the data fall within the range
of the most turbid coastal waters. Champ et al. (1980) conducted a light
characterization survey of Chesapeake Bay during August, 1977. Their mean
values are shown in Figure 3a along with their specific site measurements
in and near the mouths of the Sassafrass, Patuxent, Potomac and Chester
Rivers in Figure 3c. Their mean values fall within the upper ranges
measured in the lower Bay (Wetzel et al. 1982).
Pierce et al. (1981) intensively monitored the Rhode River during 1980
and 1981. Their annual mean attenuation values for an upriver station and
one at the mouth are plotted in Figure 3b. The upriver station was found
to be consistently more turbid, presumably because of its proximity to
autocthonous sources. Attenuation at both stations was higher for green,
yellow, and red wavelengths than observed in the lower Bay; however,
attenuations in the shorter wavelengths were in the same range. Maximum
penetration was at 575 nm and minima at 775 and 425 nm. Lower Bay maxima
were similar, and minimum measured was at 410 (775 was not measured).
Seliger and Loftus (1974) derived curves from 4 TV irradiance measurements
in the Rhode River that generally agree with the measurements of Pierce et
al. (1981), except in region 500 to 700 nm. Their measures fall within the
observations made for the lower Bay (Wetzel et al. 1982). The differences
noted in the 500 to 700 nm range may be due to upwelling irradiance
measured by the spherical collector.
Results of the August, 1977, survey by Champ et al. (1980) are shown in
Figure 3c. Their attenuation measurements in the turbidity maximum zone at
the mouth of the Sassafras River are the highest reported for the Bay. As
noted, there is nearly no available light below 500 to 600 nm. Wetzel et
al. (1982) observed similar, very high attenuations in the blue region (400
to 500 nm) at lower-Bay sites during a spring runoff event following a
major rain storm. The attenuation of green wavelengths (~500 to 550 nm) in
the summer was much higher at the mouths of the Patuxent and Potomac Rivers
(upper Bay) than at the mouths of the York, Severn, and Ware Rivers (lower
Bay). Figure 4 illustrates the lower Bay sampling stations.
A summary of the recent Chesapeake Bay data on diffuse downwelling 2IT
irradiance attenuation coefficients indicates a severe attenuation of light
energy in the photosynthetically important (400 to 500 nm blue, and 700 to
775 nm near infrared) regions of the spectrum. Attenuation in the short
wavelengths was particularly marked in the turbidity maximum region of the
Bay at the mouth of the Sassafras River, and at the mouth of the Patuxent
River during August (Champ et al. 1980) and at lower-Bay sites during
spring runoffs (Figure 5). The mean Bay attenuation coefficients
calculated by Champ et al. (1980) are about 1.0 m~l higher than Jerlov's
(1976) most turbid coastal water classification.
Comparison of Light Attenuation in Vegetated and Unvegetated Sites of the
Bay
An analysis of the spectral attenuation coefficients at shallow sites
in the lower Chesapeake was undertaken to determine if correlations existed
between the presence or absence of benthic macrophytes (Zostera marina and
Ruppia maritima) and specific spectral patterns (Wetzel et al. 1982).The
specific question, what are the light quality differences between vegetated
585
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Figure 4. Locations of lower Bay stations (Wetzel et al. 1982).
(1) Mumfort Is., York R. (2) Allen's Is., York R.
(3) Guinea Marshes (4) Mouth of Severn R., Mobjack Bay
(5) Four Point Marsh, Ware R. Mobjack Bay.
586
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1
1
1
1
1
1
1
1
1
1
1
1
IB
1
1
1
1
1
••
3-
*^**
'E
H 2"
2
UJ
O
u.
u_
y 1-
o
0
2
O
1-
§ 0-
2 4-1
UJ
K
1-
O
S 3-
UJ
2
1 2-
UJ
(/)
u.
u.
Q i-
0-
4C
UNVEGETATED SITES
MUMFORT IS
\
\\
\ \JULY
\ \
• \
MAY\ V
\ \
V "» •--•
^vAPRIL ~~»~ •"""
X-., ^.,,.--'
t
\ MAY, SEVERN R.
\ '
\ IRUNOFF
\ 1
\
\ '
JULY\ 1
\ 1
\ 1
\ i
\
x, ,--."::-
VAPRIL \ '*•»-,--' / ~~»
^^^ X» -- -"*"
^^\ ^» • — *
^^^^-^^^
VEGETATED SITES
! GUINEA MARSH
(RUNOFF
MAY'
i
i
•^ JULY 1
^^
\ '
\
\ 1
\ 1
\ ;
\ |
^ ,
\v *\ ^***^
^^2^^^
FOUR POINT MARSH
\
\iiiiv (I* A r>^u
\JULT • MAKLH
\
\ APRIL
. \ MAY
\ \
. \ J 1 1 1 V
\ \ JULT
\ \
\ \
RUNOFF\ ^
\ \
\ \
• Ns ^* *
\ ^*~»"""
•
\
^•^ \ MAY
APRIL>--.^ ^x ^,^1^
50 500 600 700 400 500 600 7C
WAVELENGTH IN NANOMETERS
Figure 5. Mean monthly diffuse downwelling spectral attenuation
coefficients for vegetated and unvegetated sites in the
lower Chesapeake Bay. All coefficients calculated for the
depth interval 0.1 to 0.5 m. Mumfort Island (York River) and
Severn River sites: unvegetated. Guinea Marsh and Four Point
Marsh (Ware River) sites: vegetated (from Wetzel et al. 1982).
587
-------
and unvegetated sites, was addressed. The sites (Figure 4) were chosen
because of their varied vegetational histories (Orth et al. 1981). The
Mumfort Island (York River: Station 1) and Severn River (Station 4) sites
are presently unvegetated. The Guinea Marsh (Station 3) and Four Point
Marsh (Ware River: Station 5) sites have seagrass beds. Both the Severn
River and Four Point Marsh sites are affected by agricultural runoff (C.
Hershner, personal communication). The Allen's Island site, Station 2, is
presently unvegetated, but has recently been replanted by Orth and
associates. Twelve wavelengths (410, 441, 488, 507, 520, 540, 570, 589,
625, 656, 671, 694 nm _+ 5 nm) and total PAR were analyzed at depths of 0.1
and 0.5 m. Downwelling irradiance (E^) was measured as Quanta nm~l
cm~~2 sec"!, each reading representing the mean of 250 scans. Diffuse
downwelling spectral attenuation was calculated between 0.1 and 0.5 m.
The mean spectral attenuation values ranged from about 0.2 to 9.0
m~l. Integrated PAR attenuation varied from about 0.5 to 1.6 m~l
(Figure 6). A clear seasonal pattern of extreme attenuation of blue
wavelengths was evident at all sites beginning in May. This was probably
due to a combination of increased particulates associated with runoff
events and seasonal plankton blooms.
Mean PAR attenuation coefficients were found to be significantly lower
(mean difference of 0.47 m~l) in vegetated than in unvegetated sites
during May, 1981 (Figure 6). This was due to a lower attenuation in the
500 to 700 nm region of the spectrum at vegetated sites (Figure 5), despite
the effects of high blue attenuation due to runoff. A significant
difference among sites based on PAR attenuation coefficients was also
observed in July; however, one vegetated site (Four Point Marsh) was
grouped with the unvegetated sites having higher attenuation (Figure 6).
This was due to the increased attenuation of wavelengths above 500 nm at
the Four Point Marsh site during July. The only general light quality
differences between vegetated and unvegetated sites that was evident from
these analyses were the reduced attenuation in the 500 to 700 nm region at
vegetated sites during May.3
Kaumeyer et al. (1981) measured a significant difference in PAR
attenuation coefficient inside and outside SAV beds at Todds Cove, Md.
during July, August, and September, 1980. The vegetated areas were from
0.4 m~l to approximately 2.0 m~l lower. Significant differences were
not found in attenuation inside and outside grassbeds at the Parson Island
study site. Table 1 summarizes the results of their studies.
Historical Data Bases and Optical Properties of Chesapeake Bay Waters
Most of the historical light data for Chesapeake Bay has been collected
by Secchi disc. This method is not ideal, but can be used to indicate
trends. Heinle et al. (1980) reviewed Secchi disc light data for both
mid-Bay and the Patuxent River, which was chosen because of the extensive
data base (Figure 7). Transparency has decreased since the 1930's,
o
J Subsequent measurements and analyses extend and corroborate this conclu-
sion. Not only is the mean violet and blue attenuation lower in
vegetated sites but the variation is also less (see Wetzel et al 1982).
588
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1
1
•V
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2.0-
O
| 1.5-
UJ
Q
[-,
r^
V)
+i
~E
1-
z
UJ
O
U.
U. i r\.
UJ '•<"'
O
O
Z
o
K
Z
UJ
^_
<
cc
z 0.5-
UJ
5
k*i ikdC-rNBY 1^
1 MUWrV/'il 13
ALLENS IS.
SEVERN R. T
FOUR PT. MARSH
MUMFORT IS.
(UNVEGETATEO)^, <
\'^^^ /
Ji / *•
1 /
// T L / ALLEN8 IS
// 1 / (VEGETATED)
// ,..-• / i
GUINEA MARSH ..•••// / •*•
(VEGETATED).. •••' /'
•-'' //
// /
jf' /
s /
_ ,'' J. /FOUR PT MARSH
T ^'y / (VEGETATED)
¥ SEVERN R /
J_ (UNVEGETATED) /
MARCH APRIL MAY JUNE JULY
MONTH
Figure 6. Mean monthly downwelling PAR attenuation coefficient ± 1
standard error of the mean for vegetated and unvegetated sites
in the lower Chesapeake Bay (from Wetzel et al» 1982).
589
•
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0)
E
a.
UJ
o
4-
3-
2-
0
2.0-
10-
- 0.5-i
o
o
LJ
CO
\
O 1974-77
• 1936-40
A I960, 1961, 1964
A MEDIAN 8/22pts
A-iA RANGE 7/25 pts
I I
I I
I
T
SECCHI DISC
x+ I S E
(d.f)
1936-1939
HEINLE/NASH
\ 1968- 1970
FLEMERet 01(1970)
F M A
M JJASON D
2.5-
2.0-
1.5-
1.0-
0.5-
o
m
>' S
A
A
** J"
\ *" A
A A
1
0
I I I I T
* 6 8 10 12
SURFACE SALINITY (%0)
14
Figure 7. Historical Chesapeake Bay Secchi disc values (from Heinle el: al.
1980, and references therein). (a) monthly mid-Bay means. (b)
monthly means Patuxent River estuary (from Mihursky and Boynton 1978)
(c) Patuxent River Secchi depth versus salinity, July.
590
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Table 1. COMPARISON OF MEAN PAR ATTENUATION COEFFICIENTS INSIDE AND OUTSIDE
_ OF VEGETATED AREAS AT TODDS COVE, MD., 1980 (KAUMEYER ET AL. 1981)
Month Location
June SAV 2.6 + 0.20
Reference Site 2.5 +_ 0.75
July SAV 2.5 + 0.30
Reference Site 2.9 +_ 0.70
August SAV 1.8 + 0.56
Reference Site 3.1 +_ 0.33
September SAV 1.9+0.34
Reference Site 3.8 + 0.96
especially during the winter in the mid-Bay region (Figure 7a). An
increase in turbidity, as estimated by Secchi disc measures, has been quite
dramatic in the Patuxent (Figures 7b, 7c). Mid-1970's Secchi disc data for
rivers in the upper Chesapeake Bay are reported in Table 2 from Stevenson
and Confer (1978). The values are generally low G'.l.O m) and are similar
to those reported for the Patuxent during the 1960's and 1970's (Figures
7b, 7c).
Increases in chlorophyllous pigments, due to phytoplankton blooms
caused by increased nutrients, can have a severe effect on light
attenuation in the photosynthetically critical blue and red spectral
regions (Figures Ib, Id). Historical chlorophyll data for Chesapeake Bay
and Patuxent River are summarized in Figures 8 and 9. Chlorophyll
concentrations have increased dramatically in the upper and mid-Bay since
the early 1950's. Concentrations as high as 100 to 200 ug L~l were not
unusual. In contrast, lower-Bay concentrations have not significantly
changed (Figure 8b). Concentrations in the Patuxent River have increased
591
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ou —
70-
60-
5 50-
o|
_ 40-
JZ
O
30-
20 -
10-
O-1
i
0 CBI 1949-195!
A CBI 1964- 1966
0 CBI 1969 - 1971
• EPA 1969-1971
1
1
o
at c JA tf Jp ,
|I26 I
(1970)
1 £
1
'V
CO "-fl ^ G-TV ^^Q
1 1 1 1
,
L
f\
I
1
'
1
D
1
|240
I
/
1
c
i
1
\
d
a
I1"
I
(19631
1
1
TT
[ I
a
i
,
n
y
i
1
i.
•vLJ
1
i
rg " ^
i i
I (1965!
L
1 1
]
D
'
(_
{ g
~ I
UPPER 0
BAY
A
C
C
^
^
\
A
C.
.
1
i <:
A
^ i A f-
i o ! I T
§ J'n^ 4S
3 c«j
1 1
30-
01
a.
O
20-
10-
0-
O FLEISCHER etal, (1976) 1973 DATA
O CBI 1949-1951 -Potomac to Roppahannock (744)
• CBI 1949-1951 Lower Bay Below Rappahannock (724,707)
• PATTEN etal, (1963)
A CBI 1964-1967 (746)
G CBI 1969-1971 (744,7445)
• CBI 1969-1971 (724,707) •
LOWER
IB l<
•
JIFIMIA1MIJ'J
MONTHS
^fH D
Figure 8. Summary of historical chlorophyll a data for the Chesapeake Bay.
(a) upper Bay. (b) lower Bay (Redrawn from Heinle et al. 1980)
592
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.c
Q.
O
O
.C
a.
01
.c
a
o
o
.c
100
80
60
40
20
100
80
60
20
100
80
60
40
20
a
Jan , Feb, Mar
• Lower Marlboro
O Benedict Bridge
Q Queen Tree Landing
b
May, June, July
Aug ,Sept, Oct
1962 64 66 68 70 72 74 76 78
YEAR
Figure 9. Summary of historical chlorophyll a_ data for three regions of
the surface waters of the Patuxent R., Md. (a) January-March
(b) May-July (c) August-October. (Cross hatching is to clarify
general trends for each site.) (Redrawn from Heinle et al. 1980)
593
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Table 2. AVERAGE SECCHI DISC DATA (cm) BY RIVER SYSTEM, MARYLAND
CHESAPEAKE BAY, 1972-1976a (AS REPORTED IN STEVENSON & CONFER
1978)
River System
Elk and Bohemia
Rivers
Sassafras River
Ho we 11 and Swan
Points
Eastern Bay
Choptank River
Little Choptank
River
James Island and
Honga River
Honga River
Bloodsworth Island
Susquehanna Flats
Fishing Bay
Nanticoke and
Wicomico Rivers
Manokin River
Patapsco River
Big and Little
Annemessex Rivers
Gunpowder and Bush
River Headwaters
Pocomoke Sound ,
Maryland
Magothy River
Severn River
Patuxent River
1972
33.0
34.3
33.8
67.3
60.7
64.5
70.1
78.2
73.7
64.5
49.5
55.4
94.2
73.7
109.7
42.9
101.6
83.8
97.3
80.3
1973
35.1
52.3
75.4
62.5
62.5
59.4
64.0
67.3
87.6
65.5
77.0
58.9
94.7
80.0
92.7
38.3
82.0
97.3
70.4
80.8
1974
-
-
-
76.5
84.3
66.8
74.2
72.6
94.7
82.6
85.6
65.8
101.3
67.8
96.3
46.7
-
73.4
79.5
61.5
1975
25.7
29.2
61.2
54.6
61.5
63.8
67.1
68.8
177.0
33.8
75.7
61.0
107.4
-
88.1
-
96.8
-
-
66.8
1976
36.3
51.1
57.7
75.9
64.3
78.5
73.4
67.8
83.3
76.5
54.1
58.9
81.0
70.1
85.1
53.8
85.9
74.4
86.4
62.7
Continued
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Table 2. AVERAGE SECCHI DISC DATA (cm) BY RIVER SYSTEM, MARYLAND
CHESAPEAKE BAY, 1972-1976a (AS REPORTED IN STEVENSON & CONFER
1978) (CONTINUED)
River System 1972 1973 1974 1975
Back, Middle and
Gunpowder Rivers 79.5 75.7 73.2 75.4
Curtis and
Cove Point 45.2 77.0 81.8 58.9
South, West and
Rhode Rivers 74.7 66.0 61.2 48.5
Chester River 76.2 73.4 100.1 87.9
Love and Kent
Points 89.7 74.7 117.6 72.1
Smith Island,
Maryland 78.5 76.2 89.7 139.4
Average 70.1 71.1 79.5 76.2
1976
61.2
73.7
67.1
85.1
89.9
87.6
71.4
significantly in both the upper and lower portions (Figure 9), especially
during late spring and early summer (Figure 9b). Levels in excess of 100
UgL"! were common in the summer throughout the 1970's — this is twice
the concentration measured during the previous decade.
In addition to the thoroughly documented increased chlorophyll £
concentration in the Patuxent, there have also been increases in most of
the other tributaries of the Bay. Chlorophyll £ concentrations in the
Choptank, Chester, and Miles Rivers of the middle eastern shore are 1.5 to
Table 3. RANGES OF CONCENTRATIONS OF CHLOROPHYLL a (ug 1~1) AT SURFACE
AND BOTTOM DEPTHS IN THE LOWER POTOMAC RIVER DURING 1949-1951,
AND 1965-1966 (HEINLE ET AL. 1980)
Month
January
March- April
May
July
October-November
1949-1951
Surface
1-2
10-21
3-6
3-5
1-9+
Bottom
1-2
12-27+
9-24+
1-2+
1-7
1965-1966
Surface
3.2-4.6
1.1-20.0
5.8-13.2
9.0-13.8
9.3-24.0
Bottom
3.1-5.0
1.1-9.5
4.3-9.8
1.0-1.8
3.6-11.0
595
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2.0 times higher presently than earliest data show. There have been
upstream increases in the Magothy, Severn (Md.), and South Rivers.
Concentrations up to 100 uL~^were measured in the upper Potomac in the
mid-1960's. Concentrations in the lower Potomac were generally higher in
the 1960's than 1950, except in March and April (Heinle et al. 1980).
Increased chlorophyll a concentrations have also been measured in the
Rappahannock and York Rivers during the last few years. The upper James
has had high concentrations similar to the upper Potomac since the
Table 4. ANNUAL MEAN FRESHWATER FLOWS AND OCCURRENCE OF HURRICANES TO ALL
OF CHESAPEAKE BAY (CUBIC FEET PER SECOND) FOR 1951-1979 (HEINLE
ET AL. 1980).
Year
1951
1952
1953
1954 Hurricane
1955 (2) Hurricanes
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972 Hurricane
1973
1974
1975
1976
1977
1978
1979 Hurricane
Bay Annual
Average
82,100
94.300
72,800
58,700
73,400
76,000
64,400
81,400
66,400
77,300
78,000
64,800
52,400
61,900
49,000
53,300
77,200
60,100
54,900
77,200
79,000
131,800
95,200
76,900
103,100
84,400
80,100
91,300
113,800
5- Year
Average
76,260
73,100
61..220
64,540
97,180
92,400
mid-1960"s, but the lower River still does not. Dense algal blooms have
been noted in the Elizabeth, Back, and Poquoson Rivers of the lower Bay.
Heinle et al. (1980) summarized the state of the Bay graphically in
terms of enrichment that they defined as deviations in concentrations of
chlorophyll a. from historic, natural periods of stability or steady state
596
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concentrations. Figure 10 shows the regions of the Bay that are
categorized as moderately or heavily enriched. Many of these areas have
experienced declines in Bay grasses on a time scale overlapping the
enrichment.
Changes in dissolved organic materials, inorganic particulate matter,
and allochthonous organic particulate matter in the Bay are mainly
determined by inputs (runoff) of freshwater to the tributaries and by
additional input due to storm events. Table 4 summarizes annual mean
freshwater flow to the entire Bay and major storms during the period
1951-1979. In addition to adding large amounts of sediment to the water
column, major storm events increase nutrient loads that favor phytoplankton
blooms.
Suspended sediment transport and discharge of the Susquehanna River,
the major source of freshwater to the Bay, are given in Table 5.
Table 5. SUSPENDED SEDIMENT TRANSPORT AND DISCHARGES OF SUSQUEHANNA RIVER
(GROSS ET AL. 1978)
Calendar Year
1966
1967
1968
1969
1970
1971
1972
Agnes, 24-30 June 1972
1973
1974
1975
Eloise, 26-30 Sept. 1975
1976
Annual suspended sediment
(millions of metric tons
Above Dam
1.5
1.7
1.7**
nd
2.0
1.4**
11.3
7.6
3.2
1.7
3.8
1.6
nd
discharged
per year)
Below Dam
0.7 (60%)*
0 . 3**
nd
0.32 (60%)*
1.1**
1.0
33
30
1.2 (54%)*
0.8 (53%)*
11
9.9
1.2
nd = no data
* Percent discharged during annual spring flood
** Records incomplete for the year
Gross et al. (1978) suggest that one-half to two-thirds of the suspended
sediment discharge of the Susquehanna is deposited behind the dams or in
the lower reaches of the river during years of low flow and no major
flooding. During major floods, however, these deposits are eroded and
transported into the Bay. Thus, dams effectively increase the amount and
variability of sediment discharged under flood conditions.
It is evident that major storms, such as hurricanes, significantly
increase freshwater input, but there is also an apparent wet-year, dry-year
cycle imposed on the data. The five-year-flow averages (Table 4) suggest a
mid-19601s depression followed by an increase through the 1970"s. Although
these data have not been rigorously analyzed, it is apparent that long-term
changes and/or cycles in climatic conditions (rainfall, temperature, and
597
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Figure 10. Portions of the Chesapeake Bay considered enriched by Heinle
et al. 1980. Enrichment is defined as increase in chlorophyll a_
levels from historic, natural periods of stability.
598
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major storms) influence water quality and optical properties of Bay
waters. However, cause and effect relations are still poorly understood
and resultant optical properties of Bay water are determined and controlled
by multiple influences: runoff; nutrients; suspended particulates (both
living and dead); and, as the principal driving forces, the general
climatic regime.
599
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SECTION 3
LIGHT AND PHOTOSYNTHESIS IN CHESAPEAKE BAY SAV COMMUNITIES
GENERAL REVIEW OF PHOTOSYNTHESIS
Photosynthesis is the process in which light is used as the energy
source for the synthesis of organic compounds. Three basic steps are
involved in the process: (1) absorption of light energy by photosynthetic
pigments; (2) processing the captured light energy to produce the compounds
ATP and NADPH; and (3) the reduction of C02 using ATP and NADPH and the
production of carbohydrates. The first two steps are light-dependent and
are collectively referred to as the "light reaction". The third step is
light-independent and termed the "dark reaction".
The photosynthetic pigments have characteristic light energy absorption
spectra in the photosynthetically active region, 400 to 720 nm.
Chlorophyll £ absorbs light more effectively at higher wavelengths (>600
nm); accessory pigments such as chlorophyll b_, carotenoids, and others are
more effective at shorter wavelengths (<600 nm) . Chlorophyll £ and the
accessory pigments absorb and transfer light energy at varying efficiencies
to specialized chlorophyll £ molecules (P700) where they are used directly
for biochemical reactions.
The photochemical reactions are driven by units of light energy called
photons (quantum energy). The quantum energy is a function of wavelength;
quanta of shorter wavelengths contain more energy than quanta of longer
wavelengths. Light energy transferred to P700 is raost efficient as it is
used directly in the photosynthetic system; light energy transfer by
chlorophyll £ and accessory pigments is less efficient. The quantum yield,
the moles of 02 produced or C02 fixed per photon of light absorbed, is
used to estimate the transfer efficiency.
The light utilization spectra of a particular species is called the
action spectra, a characteristic curve obtained by combining the light
absorption spectra and the quantum yield of intact plant cells. The action
spectra is an important feature because it reflects the ability of a
species to adapt to various light spectral regimes (Figure Id). This is of
particular importance when considering photosynthesis of submerged plants.
In aquatic environments, spectral shifts in light energy result from the
water itself, suspended organic and inorganic material, dissolved organic
compounds, and other water column constituents (discussed in Section 2).
A general approach to the investigation of photosynthesis is to
construct light saturation curves for various species (Figure lla). An
examination of photosynthesis-light curves (P-I curves) shows that
photosynthesis (P) increases with increasing light to a point of optimal
irradiance (lOpt) where, over a range of irradiance, the photosynthetic
system is saturated and maximum photosynthesis (Pmax) occurs. At higher
irradiance, there may be a depression in the photosynthetic rate, termed
photoinhibition. The initial slope of the curve (AP/AI or<*) and Pmax are
the two major parameters used in describing P-I curves (Jassby and Platt
1976). Alpha («0 is a function of the light reaction of photosynthesis and
is an estimator of the quantum yield. Pmax is a function of the dark
reaction and is influenced by environmental factors or the physiological
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state of the plants (Parsons et al. 1977). The term Ik, proposed by
Tailing (1957), is the irradiance at which a linear extension of the
initial slope intercepts Pmax. 1^ is regarded as indicative of the
plant's adaptation to its light regime (Steeman-Nielsen 1975). Ik is
irradiance where P = 0.5 Pmax and is similar to the Michalis-Menten
half-saturation constant. Ic is the irradiance at the compensation
point, where photosynthesis equals respiration (P = R).
Characteristic P-I curves are shown in Figure lib. Plants adapted to
high and low light environments, termed sun and shade species, exhibit
different P-I curves. Sun species (curve 3) generally exhibit higher
pmax values than shade species, which exhibit greater and lower Ic
values (curves 1 and 2). In the aquatic environment, with reduced
availability of light, species exhibiting shade-type photosynthesis
(greater photosynthetic rates at low light intensities) are at an advantage.
PHOTOSYNTHESIS OF SUBMERGED VASCULAR PLANTS IN RELATION TO LIGHT AND
TEMPERATURE
In situ studies of submerged angiosperms point to the important role of
light in seagrass production and distribution (Jacobs 1979, Mukai et al.
1980). In a study of Zostera in Denmark, Sand-Jensen (1977) showed a
positive correlation between leaf production and insolation over a nine
month period. Biomass and photosynthesis rates of Posidonia declined with
depth near Malta (Drew and Jupp 1976); this was probably due to decreased
light penetration with depth. In before and after studies of an estuary
that was closed to the sea, Neinhuis and DeBree (1977) report that the
Zostera population increases in density and extends to a greater depth;
they suggest that this is probably due to an increase in water transparency.
In situ light manipulation experiments provided evidence of the
importance of light to seagrass production. For example, at the end of a
nine-month study during which ambient light was reduced by 63 percent, in
situ Zostera densities were only five percent of that of the control
(Backman and Barilotti 1976). In similar studies, Congdon and McComb
(1979) report that lower than ambient light levels result in lower Ruppia
biomass; as shading duration increases, higher light levels are required to
sustain a high biomass.
Studies involving the epiphytic community, those organisms directly
attached to submerged angiosperm blades, suggest that epiphytes have a
detrimental effect because they shade the macrophytes. Both Kiorbe (1980)
and Phillips et al. (1978) provide data to indicate that epiphytic
development suppresses macrophyte growth. Sand-Jensen (1977) reports that
Zostera photosynthesis is reduced by up to 31 percent due to a decreased
penetration of light and inorganic carbon through the epiphytic community
to the seagrass blades. Johnstone (1979) hypothesizes that the rapid
linear growth of Enhalus leaves (up to two cm day~l) is related to a
shading effect from epiphytes. In contrast, the data of Penhale and Smith
(1977) suggest that an epiphytic community may be beneficial in certain
environments. For Zostera exposed at low tide, epiphytes prevent
desiccation damage by trapping a film of water, and probably reduce the
photoinhibitory effect of high light.
In addition to light, temperature also influences submerged macrophyte
distribution and productivity rates (Biebl and McRoy 1971, Drew 1978). The
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Pmox yr ~.
(A
O
O
£
Q.
0
a
Compensation
Point (P=R)
"Opt
P max
en
a>
V)
O
'o
.c
Q-
1 I and 2
Figure 11. Diagramatic photosynthesis-light relationships. See text
for description of parameters.
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biogeography of marine and brackish water plants points to a temperature
effect on worldwide distribution; for example, genera such as Zostera,
Ruppia, Phyllospadix, and Posidonia occur mainly in temperate zones while
genera such as Thalassia, Syringodium, and Halophila occur mainly in
subtropical and tropical zones. Drew (1979) reports that the Pmax of
four seagrass species collected near Malta increases in direct proportion
to temperature, up to temperatures [30 to 35°C (86 to 95°F)] where
tissue damage occurred; decreases are not observed at environmental
temperatures. In contrast, Penhale (1977) observed a decline in Pmax
from 22 to 29°C (71.6 to 84.4°F) for Zostera in North Carolina where
environmental temperatures reach 34°C (93.2°F). The co-existence of
species such as Ruppia and Zostera in the lower Chesapeake Bay may be a
result of differential responses to both temperature and light, as
apparently is the case in a Myriophyllum-Vallisneria association described
by Titus and Adams (1979). They report that a greater for temperature
tolerance Vallisneria, in conjunction with the temperature dependence of
photosynthesis, results in a temporal partitioning of production.
Vallisneria apparently favored in midsummer conditions; Myriophyllum spring
and fall conditions.
Sun and shade species have been described for submerged macrophytes
(Spence and Crystal 1970a, 1970b; Titus and Adams 1979). Sun species
generally exhibit higher Pmax values than shade species that exhibit
lower Ic values, and lower dark respiration rates. Certain species can
adapt to a wide range of light conditions. Bowes et al. (1977) cultured
Hydrilla under high and low irradiances; subjecting the plants to high
light increased the Iopt value four-fold. Plants grown under low light
achieved Ic and 1^ at lower intensities.
In seagrass systems, pigment relationships generally vary with light
quantity or with position within the leaf canopy. The adaptive capability
of seagrass pigment systems to the light environment has been shown in
various studies. For example, Wiginton and McMillan (1979) report that the
total chlorophyll content is inversely related to light for several
Caribbean seagrasses collected at various depths. For seagrasses cultured
at several light levels, the total chlorophyll content increased with
decreasing quantum flux (McMillan and Phillips 1979, Wiginton and McMillan
1979),. Within individual meter-long Zostera leaves, the chlorophyll £ to
chlorophyll b_ ratio varied significantly, with the lowest ratio at the
basal portion of the plant (Stirban 1968). In a detailed study of
chlorophyll relationships in a Zostera system, Dennison (1979) observed no
substantial variation in total chlorophyll content within the leaves as a
function of depth of the leaf canopy in integrated samples along a depth
gradient within the bed. The chlorophyll £ to chlorophyll b_ ratio,
however, decreased from the apical to basal portion of the leaves.
Although the physiological photosynthesis-light relationship ultimately
determines the light levels at which plants grow, the morphology of
individual plants and the community canopy structure may play an important
role in production and species distribution. In a study of Myriophyllum
and Vallisneria, Titus and Adams (1979) observed that the former had 68
percent of its foliage within 30 cm (11.7 inches) of the surface, and the
latter had 62 percent of its foliage within 30 cm of the bottom.
Myriophy1lum, an introduced species, has often displaced the native
Vallisneria; a contributing factor is probably the ability of Myriophyllum
to shade Vallisneria. In a detailed community structure analysis of a
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monospecific Zostera community across a depth gradient, Dennison (1979)
concludes that changing leaf area is a major adaptive mechanism to
decreasing light regimes.
PHOTOSYNTHESIS-LIGHT STUDIES IN CHESAPEAKE BAY
Investigations of photosynthesis-light relationships carried out
through the Chesapeake Bay Program can be categorized into three general
experimental designs. In the first, P-I curves were constructed for the
four dominant species in Chesapeake Bay system: Myriophyllum spicatum and
Potamogeton perfoliatus in the upper Bay, and Zostera marina and Ruppia
maritima in the lower Bay. These experiments used whole plants or leaves
subjected to various light intensities (created through the use of neutral
density screens) and various temperatures.
The second approach used microcosms in which the effects of various
concentrations of phytoplankton and suspended solids on light penetration
and on Potamogeton photosynthesis were determined.
The third experimental design involved in situ community metabolism
measurements under a wide range of natural light regimes. In certain
experiments, neutral density screens were used to shade the community on a
short-term basis. The experimental design and methods for each of these
studies are detailed in Kemp et al. (1981b) and Wetzel et al. (1982).
P-I Relationship of Major Species
P-I curves were constructed for whole plants of M. spicatum and P_._
perfoliatus at 21°C (69.8°F) (Kemp et al. 1981b) (Fi"gure 12). Both
species exhibited the characteristic photosynthetic response to light with
light saturation occurring between 600 and 800 uE m"~2 sec~l.
Myriophyllum exhibited a greater Pmax and a greater 1^ than
Potamogeton; however, the two species exhibited similar 0( . Although these
species occur in the same general locale, they do not form dense, mixed bed
stands where they would be in direct competition for light.
The photosynthetic response to light and temperature was determined for
isolated Z. marina and R_._ maritima leaves (Wetzel et al. 1982). Since
these species co-exist in the lower Chesapeake Bay, an evaluation of
photosynthetic parameters of each species might suggest competitive
strategies. Experiments carried out at six temperatures and under natural
light indicate that light saturation of Zostera occurs about 300 uE m"2
sec~l while that of Ruppia occurs about 700 uE m~2 sec""-*-.
Differences in Pmax between Zostera and Ruppia were observed and appear
related to temperature. At warmer temperatures, Ruppia exhibits a higher
^max than Zostera; the situation is reversed at colder temperatures
(Figure 13). A summary of the data shows that Ruppia exhibits the greater
pmax at temperatures greater than 8°C (46.4°F) (Table 6). A
comparison between the two species shows that Zostera generally exhibits a
greatercf; this suggests a competitive advantage for Zostera at lower light
levels.
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QJ
cr
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MYRIOPHYLLUM SPICATUM
I 200
600
LIGHT INTENSITY, M EINSTEINS m's
1000
.-2.-1
Figure 12. Photosynthesis-light curves for two species of upper Chesapeake
Bay submerged vascular plants (from Kemp et al. 1981c).
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AUGUST 29, 1979
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Table 6. PHOTOSYNTHETIC PARAMETERS FOR RUPPIA MARITIMA AND ZOSTERA MARINA
LEAVES AT VARIOUS TEMPERATURES. THE LIGHT IS THE TOTAL LIGHT
FLUX DURING THE 4h 14C INCUBATIONS (FROM WETZEL ET AL. 1982)
TEMP
°C
LIGHT
P(mg C g-1 IT1)
max
Ruppia Zostera
INITIAL SLOPE
Ruppia Zostera
1
8
12
18
21
28
5.0
22.1
15.1
21.8
14.5
12.0
2.15
3.12
3.91
2.60
3.82
2.39
2.66
3.25
2.15
2.15
3.55
1.31
0.18
0.41
0.16
0.35
0.27
0.52
0.70
1.41
0.55
0.34
0.27
0.69
The data from these experiments relate to how plants capture light and
process it, and suggest mechanisms for the species distribution of Ruppia
and Zostera in the lower Chesapeake Bay. The results also show that
temperature largely influences the distribution of these plants. Ruppia
forms single species stands in shallow intertidal to shallow subtidal areas
where high light and high temperatures are prevalent during the summer.
Ruppia is generally more efficient at the higher light and temperature
regimes in these habitats. Zostera, which has the greater depth range, is
adapted to much lower light conditions as indicated by the lower light
saturation point and greater which is a function of the dark reaction under
optimal environmental conditions or a function of the inhibitor under
supoptimal conditions, ranged from 0.9 to 3.7 mg C g~l hr~l. 1'^
ranged from 110 to 225 uE m~2 sec"1 and 1^ from 70 to 350 uE m~2
sec
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Table 7. SUMMARY OF PHOTOSYNTHESIS-LIGHT EXPERIMENTS FOR SELECTED
SUBMERGED AQUATIC ANGIOSPERMSa (FROM KEMP ET AL. 1981c)
Plant Species
•maxL
Light Parameters0
' d
Reference
Zostera marina
M ii
n it
Thalassia testudenum
n n
Cymodocca nodosa
Halodule uninervis
Syringodium filiforme
Ruppia maritima
Vallisneria americana
Ceratophyllum demersum
Ranunculus pseudofluitas
Myriophyllum spicatum
Potamogeton pectinatus
P. perfoliatus
1.5 140 230 28 Drew 1979
2.2 170 220 -- Penhale 1977
1.2 167 280 -- McRoy 1974
1.3 184 345 -- Sand-Jensen 1977
1.7 225 320 145 Buesa 1975
2.5 170 210 — Capone et al. 1979
2.6 140 220 50 Beer and Waisel 1979
1.5 130 175 40 Drew 1978
1.6 140 220 50 Beer and Waisel 1979
3.7 225 290 120 Buesa 1975
1.9 123 236 30 Nixon and Oviatt 1973
2.2 130 100 — Titus and Adams 1979
3.2 135 80 30 Van et al. 1976
2.2 130 230 — Guilizzoni 1977
3.3 115 150 20 Westlake 1967
2.8 215 180 -- Titus and Adams 1979
1.9 110 70 25 Van et al. 1976
1.3 200 290 30 Kemp et al. 1981c
0.9 195 350 60 Westlake 1967
1.1 140 230 25 Kemp et al. 1981c
Most of these data were interpolated from graphical relations provided
by respective authors.
Pmax is light-saturated photosynthetic rate in mg C g~l h~l , where
Q£ production data were converted to C assuming PQ = 1.2.
Light variables: I'j^ = half-saturation constant; IK = intersection
of initial slope and Pmax; IQ = light compensation point where
apparent production approaches zero. Light data converted to PAR units
( uE m~2 sec~l) assuming 1 mW cm~2 = 2360 Lux = 0.86 cal cm~2
"-*- =
46 uE
sec
"-"-
d Values for IQ are not available for experiments using the 14 C method
which cannot measure negative net photosynthesis.
That submerged angiosperms have similar photosynthetic patterns is
useful from the management point of view where decisions often must be
based on information from only one or two species. However, to answer
detailed questions concerning species competition or species adaptations,
it is necessary to determine the interrelationship of photosynthetic
patterns, pigment complement, plant morphology, and community canopy
structure .
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Thus, features in addition to photosynthetic parameters help determine
plant community photosynthesis. Canopy structure and chlorophyll content
were determined for a Ruppia-Zostera bed in the lower Chesapeake Bay
(Wetzel et al. 1982). Both Ruppia and Zostera showed a concentration of
leaf area (surface available for light absorption) at the lower portion of
the canopy where less light penetrates (Figure 14). The wider the bar, the
more concentrated the leaf material. This probably allows for a greater
overall net community photosynthesis than if there were a uniform vertical
distribution of leaf area. Highly significant differences were observed
between the vertical stratification of leaf area of Ruppia and Zostera.
Ruppia exhibits much greater leaf area than Zostera at the lower canopy (0
to 10 cm above substrate); this probably contributes to its success in the
mixed bed areas where it is shaded by Zostera.
Preliminary estimates of pigment content of Ruppia and Zostera suggest
differences between species (Figure 15). The highest concentrations of
chlorophyll are at mid-canopy for Zostera and at top-canopy for Ruppia
(Wetzel et al. 1982). Ruppia also showed a higher total chlorophyll
concentration than Zostera. This higher chlorophyll concentration in
combination with its canopy structure are adaptations that contribute to
Ruppia's success in mixed bed areas. These estimates give us information
on how changes in light quantity (from water quality changes) will affect
the success of mixed SAV beds.
Microcosm Studies
The microcosm studies of Kemp et al. (1981b) show a negative effect of
suspended sediments on Potamogeton photosynthesis (Figure 16). Two
concentrations of fine sediment particles «64 m in diameter,
representative of particle size in nature), kept in suspension with
recirculating pumps, reduced light availability in the two treatments and
resulted in significantly lower photosynthesis of Potamogeton compared with
a control. Kemp et al. attributed about half the decrease in productivity
of treated systems to the accumulation of epiphytic solids on the plant
leaves. Further consideration of the microcosm data involved calculating
regressions between chlorophyll £ or filterable solids and light
attenuation coefficients. From these, it was concluded that in the
northern Bay, the effect of light attenuation by phytoplankton would be
small, however, the effect of suspended sediments on photosynthesis would
be significant.
In situ Studies of Community Response to Light
The effect of light on plant community metabolism was investigated in
upper and lower Chesapeake Bay grassbeds. In both areas, community
metabolism was estimated as oxygen production in large, transparent
incubation chambers. During these experiments, detailed measurements of
light energy (PAR) reaching the plants were made. In some experiments,
neutral density screens similar in design to the 14C studies on
individual species were used to decrease available light.
A summary of the upper Bay Potamogeton community response to light is
presented in Figure 17, which includes estimates from both early (May) and
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AUGUST 1980
cc
K-
co
m
ID
CO
o
cc
50-
40-
30-
20-
10-
Ruppia BED
Ruppia m ariti ma
Zostera BED
Zostera marina
0
MIXED BED
Rupp/a marifima
MIXED BED
Zostera marina
I 20 I
LEAF AREA INDEX
i
2
Figure 14. Vertical^istribution of one-sided leaf area index (
plant m substrate) for Ruppia and Zostera at three
vegetated sites on the Eastern Shore, Virginia (from
Wetzel et al. 1982).
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40-1
0
Ruppia
mg Chi. g fresh wt
Figure 15. Vertical distribution of total chlorophyll for Ruppia and
Zostera from a mixed bed area on the Eastern Shore, Virginia.
Values ± standard error, n = 3 (from Wetzel et al. 1982).
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APPARENT PHOTOSYNTHESIS
GHT, ju Em"2 s
SS
o
P
en
O
-t»
O
ro
O
(Q )
PHOTOSYNTHETIC
RESPONSE TO
SEDIMENT LOADING
CONTROL
-(b)
en
O
mg f
O
O
en
O
HIGH TREATMENT (H)
.. L.... i
LIGHT AVAILABILITY
(c)
SUSPENDED SOLIDS
2 4 6 8 10
TIME OF EXPERIMENT, DAYS
Figure 16. Effect of (c) total suspended solids (TSS) on (b) light
availability and (a) rate of photosynthesis of P(3tamogeton
perfoliatus (from Kemp et al. 1981).
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late (August) periods in the growing season (Boynton, unpublished data).
The Ic of the plant community occurs at about 200 uE m~2 sec~l, and
data suggest that the community is not light-saturated in the ranges of
measured in situ light flux. If the community were light-saturated, the
rate of change would approach zero (Pmax) with the line in Figure 17
leveling off. An analysis of the seasonal trends suggests no differences
in the regression of light and community metabolism between seasons.
Based on these and other studies, Keinp et al. (1981b) conclude that
grass communities in the upper Bay are often light limited. For example,
actual subsurface light data and three theoretical light extinction
coefficients were used to calculate light penetration to a depth of 0.5 m
above the substrate; a depth below which Potamogeton grows (Figures 18a,
18b). Photosynthetic parameters, Ic, l\, and Pmax were calculated
from a P-I curve (Figure 18c). These parameters are identified for each
light penetration curve and suggest that for much of the daylight period,
the plant community is light-limited or undersaturated, as it is not
operating at Pmax. At early morning and dusk periods of the day, the
community is apparently heterotrophic (i.e., no net production).
In the lower Bay, community metabolism studies were carried out in
three areas: Ruppia-dominated, Zostera-dominated, and a mixed
Ruppia-Zostera area (Wetzel et al. 1982). These studies were conducted
under a wide range of in situ light regimes and under artificial shading
conditions. The shallow Ruppia areas exhibited higher light and
temperature regimes than the deeper Zostera areas; the mixed bed was
intermediate between the two.
Short-term shading experiments resulted in a general decrease in
community metabolism for both Ruppia and Zostera communities. For the
Ruppia site, apparent productivity increased with increasing light to a
midday peak and decreased during the early afternoon (Figure 19). Based on
P-I curves, Ruppia was light-saturated during much of the day and was not
photoinhibited. The unexplained afternoon depression that occurred while
light was increasing may be due to increased community respiration rates
under these high summer temperatures. A similar pattern was observed for
the Zostera site where shading also resulted in decreased apparent
productivity (Figure 20). In contrast, the afternoon depression in
productivity rates of the Zostera bed was not so dramatic as in the Ruppia
bed. This trend in Zostera seemed to follow the decreasing light
availability unlike the response in Ruppia. These results are similar to
those found throughout the study and support previous conclusions that the
two communities are physiologically (i.e., temperature and light response)
quite different.
Plots of apparent productivity versus light flux at the top of the
canopy were used to compare all three habitats (Figure 21). Differences
among the three sites were characteristically observed for these summer
experiments. Both the Ruppia and the mixed bed areas showed decreases in
apparent productivity at the highest light fluxes. The Zostera site, which
did not receive the high light that other sites received, showed no
decrease in rates. P-I curves for the seagrass species showed no
photoinhibition, even at high summer temperatures, and suggested that the
Pmax of Ruppia should be greater than Zostera at this time of the year.
As evidenced by its high apparent productivity rates, Zostera appears
adapted to lower light levels. The erratic pattern of data points and the
greater number of negative rates for Ruppia strongly suggest different
community behavior. At the community
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1500-
1000-
500-
E
LJ
H
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250-
500-
AIR-WATER INTERFACE
iuiiiiiiiiiiiiiiiiiiiiiiip
t ^X. ^Sm.
0900
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X
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o
Q.
I
Q_
1200
TIME (hr)
1500
3-
2-
^ perfoliatus
200 600
LIGHT FLUX i
1000
Figure 18. Diagramatic representation of (a) surface and underwater light
flux at Todds Cove, upper Chesapeake Bay calculated for three
light extinction (K) coefficients. (b) I , I and P
calculated from P-I curve of Potamogeton perfoliatusmtr:rom
Kemp et al. 1981c).
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level, the differences may be due to differences in community respiration
rates, plant species photorespiration rates, or the photosynthetic pattern
of other primary producers such as macro- and microalgae. The mixed bed
site shows an intermediate pattern, suggesting an interactive effect of the
presence of both species of seagrass. Under the influence of changes in
water quality, these data show that mixed beds would probably survive
better than a bed containing a single species.
A summary of linear regression analyses of apparent productivity versus
light flux at the top of the canopy for the three areas is presented in
Table 8. At the community level, the correlation coefficient, r, is
strongly influenced by season, with the lower values generally observed for
the winter months. These are the times of year of clearest water, and the
specific rate of 02 productivity asymptotically approaches Pmax-
Therefore the linear relationship does not adequately describe the
Table 8. APPARENT 02 PRODUCTIVITY AND LIGHT: LINEAR REGRESSION
ANALYSIS FOR LOWER BAY STUDIES (FROM WETZEL ET AL. 1982)
[mg 02 m~2 h"1
DATE
14 Feb
21 Feb
19 Mar
29 Apr
2 May
2 Jun
5 Jun
9 Jul
16 Jul
19 Aug
23 Sep
7 May
11 Jul
21 Aug
25 Sep
26 Sep
AREA
80 Zostera
80
80 "
80 "
80 "
80 "
80
80 "
80
80
80
80 Ruppia
80
80
80 "
80
N
33
36
31
20
11
20
30
57
76
16
27
10
83
26
10
16
f\
vs. uE m z h~
m
68
.1
78.0
65
280
582
307
286
96
124
89
108
363
52
385
242
323
.4
.5
.2
.1
.5
.5
.2
b
86
157
105
-183
-267
-472
-309
-147
- 67
- 84
-159
-357
- 47
-434
- 79
-194
1 (AT CANOPY TOP)]
.5
.1
.5
.8
.2
.1
.5
r uE E
0.372
0.360
0.210
0.778
0.823
0.681
0.765
0.425
0.542
0.793
0.435
0.980
0.215
0.770
0.806
0.532
a-2
0
0
1
1
1
0
0
1
0
0
1
0
0
h'1 uE
-
-
-
.650
.459
.54
.08
.52
.541
.947
.48
.983
.899
.13
.326
.602
m-2sec-l
-
-
-
181
127
427
300
423
150
203
411
273
250
313
90.
167.
6
2
619
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Table 8. (CONTINUED)
[mg 02 m~2 h"1 vs. uE m~2 h"1 (AT CANOPY TOP)]
DATE AREA N m b r uE nT2 h"1 uE m~2sec~1
5 May
14 Jul
80
80
Mixed
_
28
50
89
77
.7
.9
-189
- 48.9
0
0
.607
.553
2
0
.11
.627
585
174
1
N = number of observations
m = slope
b = y-intercept
r = correlation coefficient
Ic = estimated light compensation point (x-intercept)
photosynthetic response. This is true for all measures taken at or near
'max-
In the Zostera community, maximum rates occur in the spring and early
summer. Over this period, the estimated community light compensation point
progressively increases, because of increased respiration, to the point that
daily community production is negative. This corresponds to the
characteristic midsummer die off of Zostera in these areas (Wetzel et al.
1981). Except for the studies carried out in winter and early spring,
(February and March), the community as a whole is light-limited.
The Ruppia community dominates the higher light and temperature areas of
the bed. Maximum rates of apparent photosynthesis occur during the summer,
and they corroborate the earlier conclusions that Ruppia has both higher
Pmax and Ic characteristics. Some data suggest that community respiration
increases in early afternoon during high light and temperature conditions.
These conditions are prevalent at midday low tides during July and August.
Overall, Ru_£p_i_a-dominated communities in the lower Bay appear adapted to
increased light and temperature regimes and do not appear light-limited in the
Vaucluse Shores study area.
For Chesapeake Bay system as a whole, these data and similar studies
completed in upper-Bay communities suggest the extreme sensitivity of Bay
grasses to available light. These data also agree very well with information
on other geographical areas and species. The general conclusion is that light
and factors governing light energy availability to submerged aquatic vascular
plants are principal controlling forces for growth and survival.
620
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SECTION 4
SUMMARY
The apparent optical properties of estuarine water create, in general,
a light-limited environment for the process of photosynthesis. Water in
itself, suspended particles, and dissolved compounds all interact to both
attenuate total photosynthetically active radiation as well as to
spectrally shift (selectively absorb) wavelengths most important for
autotrophic production. Plant pigment systems, in general, are adapted for
efficient light-energy capture in relatively narrow bands. In many cases,
it is precisely these wavelengths that are most rapidly attenuated in the
estuarine water column.
However, data on spectral characteristics and specific waveband
attenuation in estuarine and coastal environments are lacking. Our summary
of available data, Section 2, indicates that few studies have been
completed that characterize these optical properties of estuarine waters
and even fewer that can evaluate the data in terms of potential control on
rates of photosynthesis. It is difficult, therefore, if not impossible at
the present time, to speculate as to the importance or generality of
specific waveband attenuation relative to photosynthesis and to autotrophic
production in Chesapeake Bay as well as in other estuaries. It has only
been within the past few years that submarine spectral irradiance studies
have become technologically feasible, and this is reflected in the general
paucity of information.
Studies in Chesapeake Bay indicate reductions in both light quality and
quantity at selected study sites and during various periods of the growing
season for submerged aquatic plants. Recent measures of diffuse
downwelling attenuation coefficients (Section 2) in lower Bay communities
indicate a severe attenuation of light energy in the photosynthetically
important violet blue (400 to 500 nm) region and in the near infrared (700
to 775 nm) region of the spectrum. Also for the March through July period
of study, there appears to be a progressive increase in attenuation in
these spectral regions.
Comparison of vegetated and non-vegetated areas in Chesapeake Bay with
regard to light quality and quantity suggests some improvement (lower
attenuation) in the vegetated areas, although the data are quite variable.
In the upper Bay, Kaumeyer et al. (1981) report significant differences for
one site and not for another. In the lower Bay, comparison of four sites
(two vegetated and two non-vegetated) indicates some differences in light
quality. There are at these lower Bay sites, some improvements in
attenuation in the 400 to 500 nm region in spring months (see recent report
by Wetzel et al. 1982 for an updated analysis of this and additional
data). The only definitive light quality differences between the sites was
reduced attenuation in the 500 to 700 nm region in vegetated areas during
spring, an important period in the growth of Zostera dominated
communities. Diffuse downwelling attenuation in some photosynthetically
sensitive spectral regions is severe. This, coupled with the general
increase in attenuation during the growing season and at higher
temperatures, indicates the plant communities are undoubtedly light
stressed.
621
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There is a much larger data base on plant response to total available
light energy (PAR) for Chesapeake Bay as well as for other bodies of
water. The dominant plant species in the Bay show the classical,
hyperbolic photosynthetic response to increasing PAR. Specific plant
response studies suggest physiological differences among species. The
dominant upper Bay species, Myriophyllum spicatum and Potamogeton
perfoliatus, light-saturate between 600 and 800 uE m~2 sec~l,but
differ in Pmax and 1^. M^ spicatum appears adapted to higher light
conditions than P^ perfoliatus. In a similar manner, the dominant lower
Bay species, Ruppia maritima and Zostera marina, appear physiologically
different with regard to light response. R_._ maritima is adapted to high
light and temperature; Z. marina is adapted to lower light regimes and is
stressed at higher, summer temperatures.
In situ studies of entire plant communities in both Maryland and
Virginia indicate that the communities are, in general, operating under
sub-optimal light conditions. There was no apparent light saturation
reached for upper-Bay communities; that is, net apparent community
productivity did not asymptotically approach a maximum value. Studies in
lower-Bay communities suggest that Z. marina is light-limited the majority
of its growing seasons and only in more shallow R. maritima areas did the
community photosynthetic response become light-saturated. These results
indicate that, at least in terms of total PAR energy and probably because
of the extreme attenuation in the 400 to 500 nm region noted earlier,
submerged plant communities in Chesapeake Bay as a whole are light-stressed.
Historical data relative to light (turbidity and indirectly, nutrients)
and to past distribution and abundance on submerged aquatics indicate
progressive Bay-wide changes in systems structure and function. Heinle et
al. (1980) and Orth et al. (1971) discuss these in detail. In terms of Bay
grasses and the light environment, two overall conclusions of these reports
are particularily important. Heinle et al. (1980) note and document the
generalized increase in nutrients (and loadings) and chlorophyll
concentrations in major tributaries of Chesapeake Bay over the past several
decades. Orth et al. (1981) conclude, for roughly the same time scale,
that the general pattern of disappearance of submerged plant communities
follows a "down-river" pattern. It also appears that upper-Bay and western
shore lower-Bay communities have been the most severely impacted. These
conclusions, together with our studies on the light environment and
photosynthesis-light relations in SAV ecosystems, suggest that total PAR
and factors increasing diffuse downwelling attenuation in the 400-500 nm
region are principal driving functions controlling plant growth and
survival. The specific factors at present that appear to have the greatest
impact are suspended particles, both organic and inorganic, which are
controlled, in large part, by climatic conditions (runoff and nutrient
loading) and indirectly by associated changes in physical-chemical regimes
(salinity and temperature).
In summary, it appears that Bay grasses are living in a marginal light
environment, and that progressive changes in water quality as discussed by
Heinle et al. (1980) will further stress plant communities. To conclude
622
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that light has been singularily responsible for recent declines in the
vegetation goes beyond the data available. The data do indicate, however,
the extreme sensitivity of vegetation to both qualitative and quantitative
reductions of available light, and that over the past several decades water
quality throughout the Bay, particularily in the tributaries, has
progressively declined. Further changes in these parameters can only
affect Bay grasses in an adverse way. Results show that SAV can adapt to
changes in the availability of light. Long-term shading experiments (in
progress) will address this question further.
623
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Appendix A
CBP Submerged Aquatic Vegetation
Distribution of Submerged
Vascular Plants in
the Chesapeake Bay
Distribution and Abundance
of SAV in the Lower
Chesapeake Bay, 1978, 1979
Distribution of Submerged
Aquatic Vegetation in
Chesapeake Bay, Maryland
Biostratigraphy of the
Chesapeake Bay and its
Tributaries
Zostera Marina; Biology
Propagation and Impact
Herbicides
Submerged Aquatic
Vegetation in the
Chesapeake Bay: Its Role
in the Bay Ecosystem and
Factors Leading to its
Decline
The Functional Ecology of
Submerged Aquatic
Vegetation in the Lower
Chesapeake Bay
Value of Vegetated Habitats
and Their Roles as Nursery
Areas and Shelter from
Predation
Assessment of Potential
Impact of Industrial
Effluents on Submerged
Aquatic Vegetation
Effects of Recreational
Boating on Turbidity and
Sedimentation Rates in
Relationship to Submerged
Aquatic Vegetation
Factors Affecting, and
Importance of Submerged
Aquatic Vegetation in
Chesapeake Bay
Richard R. Anderson
Robert J. Orth
Robert J. Macomer
Grace Brush
Robert J. Orth
J. Court Stevenson
W.M. Kemp
W.R. Boynton
R.L. Wetzel
R.J. Orth
J.V. Merriner
K.L. Heck, Jr.
G.E. Walsh
Jerome Williams
Herman Gucinski
W. Valentine
Projects
American University
Virginia Institute of
Marine Science
Chesapeake Bay
Foundation
John Hopkins University
Virginia Institute of
Marine Science
U. of MD, Center for
Environmental and
Estuarine Studies
Virginia Institute of
Marine Science
Academy of Natural
Sciences of
Philadelphia
U.S. E.P.A. Gulf
Breeze Environmental
Research Labs.
U.S. Naval Academy
U.S. Fish and Wildlife
Service
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Submerged Aquatic Vegetation:
Distribution and Abundance
in the Lower Chesapeake Bay
and Interactive Studies of
Light, Epiphytes, and
Grazers
Environmental Regulation
of Zostera marina and
Ruppia maritima: Growth
and Metabolism
Robert J. Orth
R. L. Wetzel
Virginia Institute of
Marine Science
Virginia Institute of
Marine Science
Synthesis of Ecological
Research from U.S. EPA's
Chesapeake Bay Program:
A Continuing Effort
1981-1982.
W.M. Kemp
W.R. Boynton
J.D. Stevenson
J.C. Means
U. of MD, Center for
Environmental and
Esturarine Studies
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SUMMARY AND CONCLUSIONS
As previously indicated, the rationale for conducting an intensive
study of SAV was founded in the perceived fact that the distribution and
abundance of the Bay grasses had significantly declined during the early
1970s and the intuitive feeling that the Chesapeake Bay ecosystem was
healthier when the grasses were more abundant. The general feeling was
that an overall degradation of the quality of the Bay's estuarine and
riverine waters was, in some way, involved in the decline. Overall, the
SAV research was based on a series of questions explained in the
introduction to this part. This summary highlights the findings and
conclusions from the CBP-SAV research as synthesized in the previous
chapter, and attempts to answer these questions.
Although there is no scientific way to measure the exact distribution
of SAV throughout the Bay some 50 or 100 years ago for use as a baseline
against which to compare current populations, selected areas were studied
using archival aerial photography and biostratigraphic analysis of bottom
cores. Essentially, this work revealed that an unprecedented decline in
SAV populations occurred during the period of 1965 to 1980. The decline
was not species-specific, and therefore, was not felt to be the result of
disease or some similar natural perturbation.
Overall, the pattern of the decline appears to have been "down river",
(from up river, down to the lower estuarine portion, and from up-estuary to
down-estuary). The significance of this pattern is that these up-estuary
regions have, over time, been the areas subjected to the most rapid
urbanization and development.
Additionally, personal communications of Dr. Robert Orth, who conducted
the majority of the SAV distribution studies, suggests little evidence that
a simultaneous decline has occurred in other areas along the east coast of
the United States. Still, there does appear to be growing indications that
throughout the world, SAV communities are becoming increasingly stressed in
areas where there is extensive industrial and/or urban development.
Having documented that there has been a decline in SAV distribution and
abundance in the Chesapeake Bay, the next critical question is "are the
grasses a valuable component of the ecosystem?" The Chesapeake Bay Program
sponsored research that investigated the role and value of SAV in the
context of Bay grasses (1) contribution of organic matter to local food
webs, (2) habitat to infaunal and juvenile nekton species, (3) role as a
sink for sediments, and (4) role in nearshore nutrient dynamics.
The contribution of SAV to heterotrophic food webs is by either direct
grazing of living plants, or by consumption of detritus. It is known that
SAV serves as a food source for several waterfowl species. With the
decline in SAV populations, those waterfowl have switched to another food
source or occur in reduced numbers in the Bay.
Studies indicate that most SAV material enters the food webs through
detrital pathways. Data indicate that large predator fish feed in SAV
beds, and that their food items, e.g., amphipods, shrimp, are detrital
feeders whose food source probably includes some fraction of SAV. Many
epifaunal species in the estuary, which are important food items for many
consumers, are closely associated with SAV.
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weeks following initial contact. Moreover, herbicides degrade rapidly in
the estuarine environment, with half-lives measured in days and weeks, and
residual concentrations do not appear to build up in sediments. The
hypothesized mechanisms of increasing SAV exposure to herbicides through
concentration of the compounds in epiphytic sediments or surface-layer
films, do not appear to represent significant factors. The one caveate
which remains unresolved is the fact that very little is known about
estuarine concentrations and SAV toxicities of major herbicide
metabolites. The de-ethylated daughter products of atrazine degradation do
tend to persist for months under estuarine conditions, and the weed-control
literature attributes "carry-over" toxicity (after atrazine application) to
this metabolite.
Ephemeral herbicide concentration in excess of five ppb do occur
periodically in some estuarine water that once contained extensive SAV
beds. In general, such concentrations cause losses in SAV productivity of
10 to 25 percent, even when exposures are brief (about an hour); recovery
may take days to weeks even without ambient herbicides. The effects of
repeated, brief exposures to such concentrations are not known. However,
if the time interval between runoff events (which might yield such
concentrations) is greater than SAV recovery time, then partial loss of
photosynthesis may persist. Such reductions in SAV productivity will
definitely add to the generally-stressed conditions that these plants
currently experience in the estuary. Herbicide-induced loss of
productivity could act in concert with many of these stressors to create
intolerable conditions for SAV existence.
Being plants, SAV require light to grow and survive, and the apparent
optical properties of estuarine water create, in general, a light-limited
environment for photosynthesis. Chesapeake Bay studies indicate reductions
in both light quality and quantity during SAV growing season. Diffuse
downwelling attenuation coefficients in lower Bay communities indicate a
severe attenuation of light energy in the photosynthetically-important blue
(400 to 500 nm) region, and in the near infrared (700 to 775 nm) region of
the spectrum.
Historical data relative to light (turbidity, and indirectly,
nutrients) and past distribution and abundance on SAV, indicate progressive
Bay-wide changes in systems structure and function,, In terms of Bay
grasses and the light environment, two overall conclusions are
particularily important. It has been noted and documented that a
generalized increase in nutrients and chlorophyll a concentrations in major
tributaries of the Chesapeake Bay has occurred over the past several
decades. It has also been concluded that for roughly the same time scale,
the general pattern of disappearance of submerged plant communities follows
a "down-river" pattern. It also appears that upper-Bay and western-shore-
lower-Bay communities have been affeced most severely.
These conclusions, together with our studies on the light environment
and photosynthesis-light relations in SAV ecosystems, suggest that total
PAR and factors increasing diffuse downwelling attenuation in the 400-500
nm region are principal driving functions controlling plant growth and
survival. The specific factors that, at present, appear to have the
greatest impact are suspended particles, both organic and inorganic, that
are largely controlled by climatic conditions (runoff and nutrient
loading), and indirectly by associated changes in physical-chemical regimes
(i.e. salinity and temperature).
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In summary, it appears that Bay grasses are living in a marginal light
environment, and that progressive changes in water quality will further
stress the plant communities. To conclude that light has been singularly
responsible for recent declines in the vegetation goes beyond the data
available. The data do indicate, however, the extreme sensitivity of the
vegetation to both qualitative and quantitative measures of available
light. The data further imply that over the past several decades water
quality throughout the Bay, and particularily in the tributaries, has
progressively declined. More changes in these parameters can only affect
Bay grasses in an adverse way.
Following three years of research, we conclude that SAV exists in a
stressed environment. The sources of those stresses include such natural
factors as salinity extremes, waterfowl grazing, uprooting by cownose rays
and major storm events, as well as man-induced stresses such as
water-column turbidity, accumulation of epiphytic materials resulting from
nutrient enrichment and exposure to agricultural chemicals. The natural
stresses do not appear to be responsible for the presently reduced
populations of Bay grasses, because SAV has always been subjected to these
pressures and the historic record, as we have been able to reconstruct it,
does not reveal previous declines of such magnitude.
The issue as far as light is concerned is not simply of suspended
material, both inorganic and organic, in the water. Recent observations
and studies indicate that the growing nutrient enrichment of the Bay's
waters is stimulating the growth of epiphytic material. Combined, the
increased epiphytes and suspended materials may be the most significant
cause of the reduced SAV populations. At this time the results of
investigations into this issue are being analyzed.
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DISCLAIMER
This report has been reviewed by the Office of Research and Development
and Office of Water Programs, U.S. Environmental Protection Agency, and
approved for publication. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
•frU.S. GOVERNMENT PRINTING OFFICE: 1982 - 509-660
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