Ecological Research Series
  WATER QUALITY CRITERIA  RESEARCH  OF THE
     U.S. ENVIRONMENTAL PROTECTION AGENCY
Proceedings of an EPA-sponsored Symposium
                                  Environmental Research Laboratory
                                 Office of Research and Development
                                 .S. Environmental Protection Agency
                                       Corvallis, Oregon 97330

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                 RESEARCH REPORTING SERIES

 Research reports of the Office of Research and Development, U.S. Environmental
 Protection  Agency, have been grouped into five  series. These five  broad
 categories were established to facilitate further development and application of
 environmental technology. Elimination of traditional  grouping was consciously
 planned to foster technology transfer and a maximum interface in related fields.
 The five series are:

      1.    Environmental Health Effects Research
     2.    Environmental Protection Technology
     3.    Ecological Research
     4.    Environmental Monitoring
     5.    Socioeconomic Environmental Studies

 This report has been assigned to the ECOLOGICAL RESEARCH series. This series
 describes  research on the effects  of  pollution on humans, plant and animal
 species, and materials.  Problems are assessed for their long- and short-term
 influences. Investigations include formation, transport, and pathway studies to
 determine the fate of pollutants and their effects. This work provides the technical
 basis for setting standards to minimize undesirable changes in  living organisms
 in the aquatic, terrestrial, and atmospheric environments.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.

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                                        EPA-600/3-76-079
                                        July 1976
WATER QUALITY CRITERIA RESEARCH OF THE
 U.S. ENVIRONMENTAL PROTECTION AGENCY

    Proceedings of an EPA-sponsored Symposium on
      Marine, Estuarine and Fresh Water Quality —
         presented at the 26th annual meeting
              of the AIBS, August 1975
                   compiled by

            Technical Information Office
     Corvallis Environmental Research Laboratory
              Corvallis,  Oregon 97330
     CORVALLIS ENVIRONMENTAL RESEARCH LABORATORY
         OFFICE OF  RESEARCH AND DEVELOPMENT
        U.S. ENVIRONMENTAL PROTECTION AGENCY
              CORVALLIS, OREGON 97330

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                            DISCLAIMER
This report has been reviewed by the Corvallis Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved for
publication.  Mention of trade names or commercial products does not
constitute endorsement or recommendation for use.
                                ii

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                         FOREWORD


     The mission of the Environmental Protection Agency  (EPA)
is primarily one of a regulatory nature, with responsibility
for establishing and enforcing environmental standards.  The
establishment of standards must be preceded by, and based on,
sound, defensible research data.  The Office of Health and
Ecological Effects within the Office of Research and Development
administers a variety of research programs to develop information
necessary for the establishment of such standards.  The major
emphasis of this research has been directed toward the develop-
ment of scientific information for the establishment of water
and air quality standards.  More recently, however, research
expertise increasingly is being directed toward the total
environmental picture (holistic or ecosystem approach), to
develop a sound basis for evaluating the ecological consequences
of all aspects of environmental pollution.

     Proceedings of the two symposiums appearing in this text
were organized under the National Environmental Research Center
managerial mode.  Subsequent reorganization has rendered each
laboratory (exception noted on title page of papers) an inde-
pendent entity with its own central research theme; in most
cases similar to the one under the NERC mode.  Therefore,
questions concerning research activities of the EPA, in
research areas appearing in these proceedings, should be made
directly to the laboratories.  Inquiries concerning other
aspects of water and air related ecological effects research
are invited.   These may be made to the EPA Office of Health
and Ecological Effects, 401 M Street, SW, Washington, D.C.
20460 (RD-683).
                                 oy/yAlbert, M.D.
                                Deputy Assistant Administrator
                                Health and Ecological Effects
                                Office of Research and Development
                             iii

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                         PREFACE


     Early in 1975, the American Institute of Biological
Sciences  (AIBS) invited the National Environmental Research
Center  (NERC), Corvallis to participate in its 26th Annual
Meeting to be held on the Oregon State University campus
during 17-22 August 1975.  A. F. Bartsch, Director of the
Center, accepted the invitation and Spencer A. Peterson,
NERC staff ecologist, was charged with organizing a one-
day symposium on the NERC research program.

     At the time the invitation was extended, a diversity of
research work was being conducted by the nine laboratories
associated with NERC Corvallis.  Research programs included
ecological effects of various pollutants on freshwater,
marine, and terrestrial ecosystems.  Presentation of research
papers in all of these areas during one day was considered to
be impractical.  Therefore, a decision was made to limit the
presentations to marine and freshwater research areas since
they were dominant at the time and to focus on water quality
criteria research.  The symposium was divided into a fresh-
water and a marine segment.  Each was designed to present a
cross-sectional representation of the types of research being
conducted at the NERC-associated laboratories and was not
meant to be all-inclusive.  The freshwater program centered
around the transport and biological modeling capabilities of
the laboratories, cold climate aquatic biology, trophic
status of lakes in the Eastern United States, and the impact
of toxic substances on the freshwater environment.  The
marine program centered on microbial and abiotic degradation
processes, the problem of trace metals, the effect of toxic
organics on the marine environment and the feasibility of new
stress-measuring methodology.
                             iv

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                               CONTENTS


                                                                  Page

FOREWARD                                                           iii

PREFACE                                                             jv

MARINE AND ESTUARINE WATER QUALITY RESEARCH
OF THE ENVIRONMENTAL PROTECTION AGENCY

     Structural Analysis of Stressed Marine Communities
     R.C. Swartz, J.D. Walker, W.A. DeBen and F.A. Cole              3

     Trace Metals in the Oceans:  Problem or No?
     Earl W. Davey                                                  13

     Persistence in Marine Systems
     Kenneth T. Perez                                               23

     Criteria for Marine Microbiota
     V.J. Cabelli, A.P. Dufour, M.A.  Levin, Paul Haberman           31

     Impact of Chlorination Processes on Marine Ecosystems
     D.P. Middaugh and W.P. Davis                                   46

     Techniques to Assess the Effects of Toxic Organics on
     Marine Organisms
     David J. Hansen                                                63

     The Effect of Subtle Temperature Changes on Individual
     Species and Community Diversity
     William C. Johnson II and Eric D. Schneider                    77

FRESHWATER QUALITY CRITERIA RESEARCH
OF THE ENVIRONMENTAL PROTECTION AGENCY

     Models for Transport and Transformation of Malathion in
     Aquatic Systems
     James W. Falco, Donald L. Brockway, Karen L.  Sampson,
     Heinz P. Kollig, and James R. Mauds ley                         97

     Shagawa Lake Recovery Characteristics as Depicted by
     Predictive Modeling
     D.P. Larsen and H.T. Mercier                                  114

     A Mathematical  Model of Pollutant Cause and Effect in
     Saginaw Bay, Lake Huron
     William L. Richardson and Victor J. Bierman,  Jr.               138

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                                                            Page

Mathematical Model  of Phytoplankton Growth and Class
Succession in Saginaw Bay, Lake Huron
Victor J. Bierman,  Jr. and William L. Richardson              159

Implications of Resource Development on the North Slope
of Alaska with Regard to Water Quality on the
Sagavanirktok River
Eldor W. Schallock                                             174

Lake Eutrophication:  Results from the National
Eutrophication Survey
Jack H. Gakstatter, Marvin 0. Allum and James M. Omernik      185

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      MARINE AND ESTUARINE WATER QUALITY RESEARCH
           OF THE ENVIRONMENTAL PROTECTION AGENCY

                               Eric Schneider, presiding
Director,  Environmental Research Laboratory--Narragansett

  Structural  Analysis  of Stressed Marine Communities
       R.C. Swartz, J.D. Walker, W.A. DeBen and F.A.  Cole

  Trace Metals in  the  Oceans:  Problem or No?
       Earl W.  Davey

  Persistence in Marine Systems
       Kenneth T.  Perez

  Criteria for Marine  Microbiota
       V.J. Cabelli, A.P.Dufour, M.A.Levin, Paul Haberman

  Impact of Chlorination Processes on Marine Ecosystems
       D.P. Middaugh and W.P.  Davis

  Techniques  to Assess the Effects of Toxic Organics  on
  Marine Organisms
       David  J. Hansen

  The Effect  of Subtle Temperature Changes on Individual
  Species  and Community Diversity
       William C.  Johnson II and Eric D. Schneider

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       Structural Analysis of Stressed Marine Communities

                 R.C. Swartz, J.D. Walker, W.A. DeBen,
                            and F.A. Cole*
                               ABSTRACT
           Pollution  often causes major changes in the structure
           of marine  communities.  The impact of sewage sludge on
           macrobenthic  assemblages in the New York Bight and in
           experimental  microcosms  is described as an illustration
           of the  effects of stress on species composition, density,
           diversity  and heterogeneity.  Structure analysis provides
           an exceptionally good method for assessing ecological
           alterations at specific sites, but quantitative criteria
           such  as  diversity indices should not be used as universal
           regulatory standards.  Field surveys should be closely
           coordinated with laboratory investigations of the toxi-
           city  and accumulation of pollutants from those species
           which dominated community structure and function prior
           to human perturbation.
                              INTRODUCTION
      Variations  in species composition, density, diversity, and spatial -
 temporal  heterogeneity of multispecies assemblages are often used as
 indicators of  the effects of pollution on marine community structure.
 Sometimes only one aspect of structure, usually diversity, is presented
 as  the  sole  biological criterion of stress.  We will  review the need for
 more  comprehensive structural analyses and their relationships with other
 branches  of  pollution ecology, especially multispecies bioassays.  For
 illustrative purposes, data are given from field and laboratory investi-
 gations of the effects of sewage sludge on the marine macrobenthos.
*Corvallis Environmental  Research Laboratory,  U.S.  Environmental  Protection
Agency, Newport Field Station, Newport,  OR  97365

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                               METHODS

NEW YORK BIGHT SAMPLES

     To illustrate different methods of structural  analysis, two repre-
sentative samples were selected from a macrobenthic survey of the New
York Bight.  Sample S was collected in the apex of  the Bight near the
center of the sludge dumping site (40°23.8'N, 73°42.5'W)  on 24 August
1973 and sample A at a relatively clean site approximately 23 km south
of Fire Island, New York (40°25.6'N> 73°11.TW) on  23 August 1973.  The
samples were collected with a 0.05m2 Smith Mclntyre grab  and sieved
through a 1.0 mm screen.  Animals retained on the screen  were preserved
in formalin and later identified to the species level.

INDICES OF COMMUNITY STRUCTURE

             S    ,
Density:     Z   n-/0.05m2
            i=l   1

Diversity:

     Area! Species Richness:    S/0.05m2
     Simpson's (1949) Index of Dominance  (S.I.):
                                    S     n./n.-l\
                      1- S.I. = 1 - Z     ]( 1   >
                                    1=1    N(N-l)

     Information Theoretical Diversity  (Shannon-Weaver Equation):

                           i            s
                      H' =^.(N log  N -  I nj  log n^)


Fauna!  Heterogeneity:

     Czekanowski  or Bray-Curtis Dissimilarity Index:

                      D.I.  = 1  - W

    where  W =  sum of lesser n-f/N for  each species  found  in  both  samples
                                              th
           n-j = number of individuals  of the  i    species

          N = total  number  of  individuals in a sample

          S = total  number of species in a sample.

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SLUDGE-BENTHOS EXPERIMENT

     Digested municipal sewage sludge was obtained from the Bay Park
Sewage Treatment Plant, East Rockaway, New York.  Sediments and test
specimens were collected in the lower Yaquina Bay, Oregon.  The sedi-
ments were autoclaved and placed in a 3 cm deep layer at the bottom of
a polyethylene box (25 1 capacity, 1200 cm2 bottom area).  The tanks
received a continuous flow of seawater entering at the surface at one
end and exiting through a stand pipe at the opposite end.  Animals were
introduced to the tanks 48 hr before the sludge.  The seawater was turned
off for 45 min while the sludge was added and allowed to settle.   Dissolved
oxygen concentration reached a mimimum of 3 mg/1  during this period.

     The same sludge sample was used in the first two experiments, con-
ducted 11-25 February 1974 and 1-15 April 1974.  In the first, the poly-
chaetes Eupolynmia crescentis (5 individuals) and Glycinde polygnatha
(17); the molluscs Clinocardium nuttallii (11), Macoma nasuta (40), and
Transanella tantilla (25); and the amphipod Co r oph i urn sp i ni cp rn e_ (50)
were placed in two control tanks (no sludge) and three test tanks in
which sludge layers of 4, 20, and 45 mm were deposited.  In the second
experiment the same number of individuals of all of the above species
except E_. crescentis were placed in two control and four test tanks re-
ceiving 1, 4, 5, and 8 mm layers of sludge.  In both experiments  sedi-
ments were sieved 14 days after the sludge was deposited and all  living
individuals were recorded.

     The third experiment was conducted 1-15 July 1974 with a different
sludge sample from the same treatment plant.  The polychaete Glycinde
polygnatha (20 individuals); the molluscs Clinocardiurn nuttaTJii  (10),
Macoma n"as~uta (40), Transanella tanti 11 a (15), and Cry^ptomya"caTifornica
(10); the amphipods Corophium spim'corne (50) and Paraph oxus epistomus
(17); and the cumacean Lamprops quadripiicata (6) were placed in  two
control tanks and six test tanks each of which received a 4 mm sludge
layer.  One of the test tanks was sacrificed 1, 2, 4, 7, 10, and  14 days
after the sludge was deposited.  Both controls were sacrificed after
14 days.

                        RESULTS AND DISCUSSION

SPECIES COMPOSITION

     The species composition, density, diversity, and dissimilarity of
macrobenthic collections at the sludge ground (station S) and a relatively
clean station (A) are given in Table 1.  With the exception of Capitella
capitata, at least one individual of all species found at S was also pre-
sent at A.  The fauna at S appears to be composed of the stress-tolerant
remnants of a more diverse benthic assemblage found in clean sandy sedi-
ments throughout much of the New York Bight.  In particular, the  gammarid
amphipods were abundant at A, but absent at S.  The extreme dominant at
S, Capitella capitata, has never been found in several hundred grabs taken
in the vicinity of A.

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     Total reliance upon indicator species as criteria of marine pollution
is undesirable, but the concept should not be ignored,  the polychaete,
C. capitata. is an opportunistic species that can rapidly increase in abun-
dance during environmental disruptions.  It  is a cosmopolitan species often
found in areas of dredging, marine construction, cannery wastes, and sewage
deposits  (Reish 1959, Wass 1967, Eagle and Rees 1973).  Surveys by the
National Oceanic and Atmospheric Administration (1972)  also indicated that
the absence of amphipods was a good indicator of the  effects  of sludge  dumping
in the Bight.
     TABLE 1.  SPECIES COMPOSITION, DENSITY,  DIVERSITY, AND
               DISSIMILARITY OF MACROBENTHOS  COLLECTIONS AT
               THE SLUDGE GROUND  (STATION S)  AND A  RELATIVE-
               LY CLEAN STATION (A) IN THE NEW YORK BIGHT
          Station S
      Taxon
 Number of
Individuals
 Capitella  capitata   916
 Cancer irroratus        7
 Unid.  Nemertean         3
 Cerebratulus  sp.        2
 Unicola  irrorata        1
 Nucula proxima          1
Total No. of Species   6
Total No. of
  Individuals
    930
Species Diversity (H1) 0.04
1- Simpson's Index
     of Dominance
                                         Station A
Taxon
               Trichophoxus  epistomus
               Spi ophanes  bombyx
               A can th oh aus ton us" intermedius
               Foraminiferan No. 1
               Acanthohaustorius spinosus
               Pseudunico1 a  obTTquua
               Unicola  i/rorata
               Cerebratulus  sp.
               Nucula proxlrna
               Phyllodoce  maculata
               Acan th oh aus tori us_ mi1|si
               Echi narcTi ni us parma
                                Unid. Nemertean
                                C1ymen_eJJ_a zonal is

                                Plus 11 separate species
                                   represented by one
                                  individual
     0.03
 Number of
Individuals

     36
     29
      8
      6
      4
      4
      4
      3
      3
      3
      2
      2
      2
      2
                              11

                              25


                             119

                               1.03


                               0.84
            Dissimilarity Index between Stations S and A = 0.98

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     _It is difficult to define the exact relationship between indicator
species and specific environmental factors.  These species may not be
tolerant to all forms of pollution.  The success of stress tolerant species
may be due to the elimination of  less resistant competitors or predators
rather than a preference for altered habitats.  The disappearance of stress
sensitive indicators may be caused by factors other than human perturbation.
However, if the more abundant organisms at a site are typically associated
with stressed ecosystems, it is probable that environmental conditions have
deteriorated.  Wass (1967) suggested a pollution index based on the ratio
of the number of individuals of tolerant and intolerant species.  Applica-
tion of the indicator concept at  the multi-species level is preferable to
reliance upon a single species such as Capitella capitata.

DENSITY

     The higher density of individuals at station S is due to the great
abundance of Capitella capitata.  Excluding that species only 14 specimens
were collected at S, whereas 119 were found at A (Table 1).

     Density comparisons based on the total number of individuals in entire
collections can be misleading if  different phylogenetic and trophic assem-
blages are combined.  Many of our samples from station A are dominated by
a very large (1-4 mm) arenaceous  foraminiferan (Astrorhiza sp.?).  It seems
unreasonable to include this species when comparing macrobenthic densities.
Changes in the abundance of individual or closely related groups of species
can be sensitive to minor ecological changes.  Watling e_t aj_. (1974), for
example, found that sludge dumping off Delaware Bay had not caused serious
environmental damage, although the density of Nucula proxima, a deposit
feeder, had increased substantially due to organic enrichment of the sediment

DIVERSITY

     Species diversity is a function of the number of species (richness)
and the distribution of individuals among the species (evenness) (Lloyd
and Ghelardi, 1964).  This is a very broad ecological concept for which
a plethora of quantitative indices have been proposed.

     Areal species richness or species density can be expressed as the
number of species (S) collected per unit effort or area.  This is the
most basic concept of relative niche diversity.  As a richness estimate,
species density is preferable to  catch of species per unit number of
individuals (numeric species richness) because the latter is strongly
influenced by evenness patterns.  Species density obviously is not an
estimate of the total  number of species in a community and it is valid
only for comparative study.   Constant sampling effort can usually be in-
corporated into survey designs and S's for different samples can be di-
rectly compared.

     The degree of dominance by the more abundant species is an important
characteristic of the evenness of distribution of individuals among the
species.   As dominance increases, "effective" diversity will decrease
even when the species density does not change.  Simpson's (1949) index
gives the probability that two individuals drawn at random and without
replacement from a multispecies assemblage will belong to the same species.
                                     7

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It is a good measure of dominance and its complement is positively related
to diversity.

     To many ecologists species diversity implies an integrated measure of
both richness and evenness.  The most popular index of  "overall" diversity
is the Shannon-Weaver equation  (H1).  Because richness  and evenness  are not
necessarily correlated and have basically different theoretical significance,
H' may not always provide an adequate diversity  analysis.

     All aspects of diversity were substantially less  at  station S than at
station A  (Table 1).  Species density decreased  from 25 to 6  species,  H'
from 1.03  to 0.04, and the complement of Simpson's Index  from 0.84 to  0.03.
These  data demonstrate a major  deterioration in  benthic community structure.
The  analysis of species composition and density  indicate  the  differences  in
diversity  are due to the absence at S of many stress intolerant species and
the  presence of a very large number of Capite11 a capitata.

FAUNAL HETEROGENEITY

     The Bray-Curtis index is sensitive to differences  in species compo-
sition and the relative abundance of individual  species.  The extremely
high value (0.98) between S and A clearly demonstrates  the major differ-
ence between these assemblages  (Table 1).

     Analysis of faunal heterogeneity is more useful when applied to surveys
which  include a  large number of stations.  Dissimilarity  between all  possible
pairs  of samples can be calculated and the results expressed  in dendrograms
which  show hierarchial relationships between site clusters.   Species clusters
can  also be  identified from the interspecies similarity of distributions  be-
tween  stations.  A variety of dissimilarity indices and clustering strate-
gies are discussed by Clifford  and Stephenson (1975).   Boesch (1973) gave
a good example of the application of this kind of analysis in marine pollu-
tion research.

SLUDGE-BENTHOS EXPERIMENT

      In the  first two experiments, the survival  of all  species was reduced
when exposed to sludge layers >8 mm for two weeks (Table  2).   Recovery of
living Corophium spinicorne, Clinocardium nuttallii, and  Transanella
tantilla in  test tanks receiving 4 or 5 mm sludge layers  was  substantially
less  than  in the controls.  Only 4 C_. spinicorne survived when exposed to
1  mm of sludge while 21-37 of the 50 seeded specimens  were recovered from
the  control  tanks.  These results show that l') the response  of the macro-
benthos is  proportional to the  quantity of sludge deposited,  2) all  species
are  not equally sensitive to sludge, and 3) a very thin layer of sludge
(1 mm)  can  affect some species  over a short period of  time (14 days).  It
is not certain whether the impact is due to toxicity or indirect effects
such as burial or changes in sediment size distribution.  The design only
crudely simulates the deposition of the settlable sludge  fraction on the
bottom.  Under field conditions, currents or wave action  might keep  a
larger proportion of the sludge in the water column.

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                   TABLE 2.   SURVIVAL IN A MACROBENTHIC SPECIES  ASSEMBLAGE  EX-
                             POSED TO SEWAGE LAYERS OF 1-45  mm FOR TWO  WEEKS
Individuals
Seeded
Species
Eupolynmia crescentis 5
Glycinde polygnatha 17
Corophium spinicorne 50
Macoma nasuta 40
Transanella tantilla 25
Clinocardium nuttallii 11

Individuals Recovered
Controls Sludge Layer (mm)
I II III IV 1 4 4 5 8 20 45
42*-- --2--00
15 17 16 14 13 10 15 12 8 6 1
35 42 21 37 4050110
39 37 39 39 37 35 19 29 9 1 1
18 21 24 21 20 15 2 3 0 0 0
99 11 11 7000000
*0nly 4 Glycinde seeded in Control II

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     The third experiment was designed to determine if there was a tem-
poral pattern of mortality following exposure to a 4 mm sludge layer.
Interestingly, there was no substantial difference in survival of all
species between control and test tanks after 14 days (Table 3).  Failure
to  reproduce the results of the first two experiments might be attribut-
able to variations in the toxicity of sludge from the same treatment
plant since a different sample was used in the third experiment.  If this
is  true, source control of toxicants in some sewage sludges might signif-
icantly reduce their environmental impact.

     These experiments demonstrate the feasibility of conducting multi-
species bioassays with ecologically important species collected from
ocean disposal sites.  This permits a much closer coordination between
field and  laboratory investigations than is possible with many conventional
bioassay organisms.

EFFICACY OF COMMUNITY STRUCTURE ANALYSIS IN POLLUTION RESEARCH

     No single aspect of community structure provides an unequivocal
criterion  of biotic response to stress.  In particular, total reliance
on  diversity indices should be discouraged because of their insensitiv-
ity to changes in the species composition.  Further, the assumption that
diversity  always decreases in response to ecological alteration is not
always true.  Fish species diversity sometimes increases in the vicinity
of  ocean outfalls and thermal discharges (Grimes and Mountain, 1971;
Turner, Ebert and Given, 1966).  It is thus impossible to establish a
particular diversity index value as a universal regulatory standard for
an  unacceptable level of pollution.  However, diversity should be employed
as  an important part of a more comprehensive investigation of community
structure.

     Analysis of the condition of biotic assemblages in stressed areas
has several advantages over other methods in pollution ecology.  The
biotic resource to be protected is examined directly.  There is no un-
certainty about extrapolating laboratory results to field situations.
Structural characteristics such as species composition, density, diver-
sity, and heterogeneity are sensitive to individual and synergistic
effects of all forms of natural and pollutional stress, some of which
may not be immediately apparent.  Spatial-temporal community patterns
can indicate both environmental impact and recovery following pollution
abatement.

     We do not advocate community structure analyses as the "best" method
of assessing ecological alterations.  They should be closely coordinated
with experiments on the toxicity and bioaccumulation of specific pollu-
tants.   Similarly, bioassay organisms should represent the dominant taxo-
cenes which would occur in the absence of pollution at the stressed site.
Neither field nor laboratory studies by themselves can provide an adequate
basis for regulatory decisions.
                                   10

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TABLE 3.  SURVIVAL IN A MACROBENTHIC SPECIES ASSEMBLAGE EXPOSED
          TO A 4 mm LAYER OF SEWAGE SLUDGE FOR 1  - 14 DAYS.
Species
Glycinde polygnatha
Corophium spinicorne
Paraphoxus epistomus
Lamprops quadriplicata
Macoma nasuta
Transanella tantilla
Clinocardium nuttallii
Cryptomya caliform'ca
Individuals
Seeded
Individuals Recovered


14 14
Controls
20
50
17
6
40
15
10
10
19
48
15
5
36
15
9
10
17
46
14
6
34
14
10
10
Exposure Time (da\
1 2
/

17
40
14
6
36
15
10
10

20
44
15
5
35
15
9
9
/s)



4 7 10 14
I mm Sludge Layer

20
37
13
4
34
13
6
10
14
43
14
4
30
14
9
10
17
31
14
3
33
13
9
10

17
40
15
6
32
13
8
9

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                              REFERENCES
Boesch, D. F. 1973.  Classification and community structure of macro-
     benthos in the Hampton Roads area, Virginia.  Mar.  Biol.  21:  226-244.

Clifford, H. T. and W. Stephenson.  1975.  An introduction to numerical
     classification.  Academic Press, New York.  229 p.

Eagle, R. A. and E. I. S. Rees.  1973.  Indicator species—a case for
     caution.  Mar. Poll. Bull.  4: 25.

Grimes, C. B. and J. A. Mountain.  1971.  Effects of thermal effluent
     upon marine fishes near the Crystal River steam electric station.
     Florida Dept. Nat. Resources.  Prof. Pap. Ser. No.  17.  64 p.

Lloyd, M. and R. J. Ghelardi.  1964.  A table for calculating the
     equitability component of species diversity.  J. Anim. Ecol.  33:
     217-225.

National  Marine Fisheries Service.  1972.  The effects of waste disposal
     in the New York Bight.   Final Report.  Section 2:   Benthic studies.
     Sandy Hook Sports Fisheries Mar. Lab. Highland, New Jersey.
     Final Rept. Feb. 1972, 277 pp.  NTIS Rept. No. AD739532.

Reish, D. J.  1959.  An ecological study of pollution in Los Angeles -
     Long Beach Harbors, California.  Allan Hancock Found. Occ. Pap.
     No.  22.  119 p.

Simpson,  E. H.  1949.  Measurement of diversity.  Nature 163:  688.

Turner, C. H., E. E. Ebert, and R. R. Given.  1966.  The marine environ-
     ment in the vicinity of the Orange County Sanitation District's
     ocean outfall.  California Fish & Game 52:  28-48.

Wass, M. L.  1967.  Indicators of pollution.  In Pollution and Marine
     Ecology, T. A. Olson and F. J. Burgess (eds.).  Interscience Pub!.,
     John Wiley & Sons, N.Y., pp. 271-283.

Watling, L., W. Leathern, P. Kinner, C. Wethe, and D. Maurer. 1974.  Evaluation
     of sludge dumping off Delaware Bay.  Mar. Pol. Bull.5: 39-42.
                                   12

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                    Trace Metals in the  Oceans:
                           Problem or No?

                            Earl W. Davey*


                               ABSTRACT
          Increased input of mercury to the estuarine  environ-
          ment resulted in bioaccumulation in marine food  chains
          that affected man (Irukayama, 1966).  Toxic  effects of
          other metals on marine animals have been  demonstrated
          under laboratory conditions.  However, cause and ef-
          fect between elevated environmental metals levels  and
          toxicity to marine animals has yet to be  conclusively
          demonstrated under field conditions.  Municipal  waste
          water treatment plants, dredging and spoiling activi-
          ties, and the dumping of sewage sludge and industrial
          wastes are the major sources of metals to the marine
          environment.  These sources are likely to increase in
          the near future unless the Federal Water  Pollution Con-
          trol Act Amendments of 1972 (PL-92-500) are  carefully
          enforced.
                             INTRODUCTION
     Estuaries, because of the fact that they are landward  extensions of
the sea, have become centers of industrial,  commercial,  and related activ-
ities.  As a consequence, estuaries have received an  increasing  input of
metals due to the result of by-products of modern industry  and technological
advancement.  Metals can be introduced indirectly from contaminated rivers
and land runoff or directly by pumping from land based industries and muni-
cipalities, ship or barge discharges and aerial  fallout  (Merlini, 1971).
When viewed as a whole, ocean systems appear to  be beyond compromise in
relation to its ability to dilute elemental  introductions due to man's ac-
tivities -- after all, the continental masses are continually bathed in
their oceans and seas.  Where then do problems occur?
*Environmental Research Laboratory,  U.S.  Environmental  Protection Agency,
Narragansett, RI  02882


                                    13

-------
     Ocean waters, especially estuaries, are not uniformly mixed and
lack^of uniform dilution can cause local concentrations of metals.
Metals tend to be concentrated at air-sea, sediment-water, or fresh-
water-saltwater interfaces and boundaries between water and living or
dead particles (Fig. 1).  Some metals discharged even  in small quantities
can be accumulated to alarming and lethal levels by certain marine
biota.  Seafoods harvested by man can become extensively impacted when
excessive metals are added to the sea.  A classic example of  the human
aspect of the problem first received considerable attention when mer-
cury poisoning occurred in Japan in 1953 through consumption  of con-
taminated fish and shellfish (Irukayama, 1966).

     It must also be recognized that it is not necessarily the total
amount of a metal present in seawater or marine sediments but the form
of  the metal which may be important to consider with respect  to the
effects metals may manifest on marine biota.  Metals in seawater can be
operationally characterized as particulate (metals associated with par-
ticles larger than 0.45y) or dissolved metals (<0.45y).  Dissolved metals
can be categorized further as in organically associated, organically
bound, i.e. chelated, or metal-organic compounds.  Dissolved  metal forms
are likely to interact with most marine biota; however, the  effects  may
differ if the metals are organically bound.  If a metal such  as copper
is  chelated, there may be a reduction in metal toxicity response by or-
ganisms such as marine phytoplankton; whereas, if the  metal is an organ-
ometallic  like methy!-mercury, this compound is more toxic than the in-
organic form and  can also be concentrated in food chains.  Particulate
metals, probably  occurring in high levels near industrial outfalls or
ocean  clumping activities, are likely to affect filter  feeding organisms
which  ingest and  concentrate particulate matter.  Consequently, the form
of  the metals may be the dictating factor in the response of  marine biota
to  heavy metals.

                        METHODS AND MATERIALS

     Trace elements are essential to all life systems; yet excess amounts
are toxic.  Also, non-essential elements such as mercury, cadmium, lead,
etc.,  can be toxicants and bioaccumulated to large quantities to affect
organisms within marine food chains including man.  Therefore, a matrix
of  existing toxicity and body burden data using marine species  (including
various life stages) as one axis and metals (including various chemical
states and modes  of application) as the other has been formulated in order
to  assess, broaden, and validate the data base needed  for criteria deci-
sion making.  The metals matrix helps to point out information gaps, thereby
defining research goals; and it provides a basis for comparing metal levels
and their modes of application in laboratory toxicity  and bioaccumulation
studies with levels and pathways defined in metal-problem areas in the
natural environment.

     A summary of two metals matrices which were constructed  mainly from
literature reviews by Ketchum et al. (1972), Eisler (1973), more recent
additions from the open literature, and in-house experiments  performed

                                    14

-------
                            Aerial fallout of PM
AIR-WATER
INTERFACE
                           SOM, PM
            FOOD CHAIN
SEDIMENT-
      WATER
INTERFACE
\
               SM(lo)
               SOM(lo)
               PM(hi)-*-
               sal>30%0
                                           PM(lo)
                                           SM(hi)
                                           sal>IO%o
                                                 PM (hi)
                                                 SM(lo)
                                                 sal
-------
at the National Marine Water Quality Laboratory (NMWQL) are presented
in Tables 1 and 2.

                               RESULTS

     The metals matrix indicates that there is information on only 36
elements and of these only 18 have toxicity data  listed and of the 18
perhaps only four (Cd, Cu, Hg, and Zn) are sufficiently documented to
formulate good criteria.  Since the NMWQL has had to respond to unex-
pected requests for elemental toxicity and bioaccumulation data, in
order to anticipate future requests, we have undertaken an in-house
program to develop acute and chronic marine bioassay information on a
wide spectrum  of  elements.

     However,  because there is infinite variety of  combinations of marine
biota versus elemental compounds, a number of elements can be eliminated
from consideration in the following categories:

     1.   Elements such as mercury with sufficient information for good
         water quality criteria

     2.   Major constituents of seawater s.a. Na,  Mg, Cl,  $0)4

      3.   Major constituents of marine organisms s.a. C, H, N, 0

     4.   Noble gasses, i.e. He, Ne, etc.

      5.   Elements which  are short half-life isotopes

      6.   Rare  earths

     The  remaining,  approximately fifty elements, can  be  listed in priority
 according to  the  following considerations:

      1.   Known toxicity  to man

      2.   Information  indicating elemental impact  in the marine environment

      3.   The  form of  the element in seawater

      4.   No  information  available

     On  the  basis of  these considerations, elements are chosen for short-
 term,  acute  bioassays.   Acute bioassays involve a rapid response of a
 single  species to increasing concentrations of a  toxicant.  The results
 of the  acute  bioassay are reported as the median  tolerance limit (TLm of
 TL5o) which  signifies the concentration of toxicant that  kills 50% of the
 organisms  within  a specified time span, usually in  96  hours.  Organisms
 for acute  bioassay are being selected from a wide range of representative
 marine  phylla  and growth stages.
                                    16

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              TABLE  1.   MATRIX OF ELEMENTS VERSUS MARINE  BIOTA RESPONSE
Element
Aluminum
Antimony
Arsenic
Beryl lium
Cadmium
Chromium
Cobalt
Copper
Germanium
Gold
Iron
Lead
Manganese
Mercury
Nickel
Selenium
Silver
Yttrium
Zinc
Environmental
Oceans
Clean
0.01
0.0005
0.003
0.0000006
0.0001
0.000005
0.0001
0.003
0.00006
0.000004
0.0013
0.00003
0.005
0.00003
0.002
0.0004
0.00004
0.003
0.01
Spp. (Phyla)
Tested
4 (3)
2 (2)
6 (4)
1 (1)
34 (7)
13 (5)
1 (1)
48 (9)
2 (1)
1 (1)
1 (1)
14 (7)
2 (2)
43 (8)
17 (4)
5 (2)
9 (5)
1 (1)
28 (8)
Organism
Redfish
Algae
Copepod
Mummichog
Oyster
Algae
Copepod
Diatom
Diatom
Pinfish
Diatom
Ciliate
Oyster
Oyster
Algae
Copepod
Copepod
Oyster
Annelid
Most Sensitive Response
Level
88*
3.5
0.1
0.0001
0.015
0.0001
0.01
0.001
1.0
0.069
0.027
0.15
16.0
0.0056
0.0°D2
0.01
0.0033
0.001
0.05
Death
Inhib. cell div.
72hr LC5Q
Deer. enz. act.
Slow sex. devel .
Deer, culture yield
72hr LC5Q
Inhib. growth
Inhib. growth
Death
Cell clumping
Inhib. growth
LC50 of embryos
48hr LCcQ of emryos
Inhib. growth
96hr LC5Q
72hr LC5Q
Abnormal larvae (98%)
Abnormal larvae
* all  concentrations expressed  in mg/kg

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                            TABLE 2.   MATRIX OF  ELEMENTS  VERSUS  MARINE BIOTA  BIOACCUMULATION
00
Element
Aluminum
Antimony
Arsenic
Barium
Beryl lium
Bismuth
Cadmium
Cerium
Ces i urn
Chromium
Cobalt
Copper
Gold
Iron
Lanthanum
Lead
Manganese
Mercury
Molybdenum
Nickel
Plutonium
Polonium
Rubidium
Ruthenium
Samarium
Scandium
Selenium
Silver
Strontium
Thorium
Tin
Titanium
Uranium
Vanadium
Yttrium
Zinc
Spp. (Phyla)
Tested
7 (1)
42 (10)
88 (12)
3 (1)
1 (1)
1 (1)
136 (12)
16 (5)
20 (6)
30 (4)
34 (7)
101 (8)
3 (1)
73 (8)
4 (2)
102 (7)
51 (5)
198 (15)
5 (3)
45 (6)
38 (7)
1 (1)
6 (3)
11 (7)
15 (3)
20 (-4)
11 (5)
18 (4)
18 (5)
5 (3)
2 (2)
6 (2)
1 (1)
6 (2)
2 (2)
130 (10)
Organism
Phytoplankton
Octopus
Squid (gills)
Phytoplankton
Phytoplankton
Phytoplankton
Abalone (digest, gland)
Fish
Algae
Zooplankton
Zooplankton
Squid (liver)
Mollusc
Annelid
Fish
Algae
Algae
Algae
Zooplankton
Zooplankton
Algae
Fish
Algae
Sponge
Annelid
Annelid
Octopus
Squid (liver)
Algae
Octopus
Phytoplankton
Phytoplankton
Fish
Pteropod
Mollusc
Mollusc
Level
Reached
5000*
0.92
198
262
8.4
7.7
1162.7
64
0.64
260
110
15,160
282
42,800
57
3100
226
7400
36
480
21,000 (CF) #
61 pCi/gm wet wt
2.3
10,000 (CF)
3.6
26.4
71
1044
4160
9.2
101
940
21
290
1000 uCi
99,220
Toxic
to
Man
_
+
+
-
+
+
+
-
-
+
-
-
_
_
_
+
_
+
_
_
+
+
-
_
_
_
+
-
.
+
-
-
+
-
_
-
                          * all values in mg/kg, except where noted
                          # CF - concentration factor
                          Toxic to Man: + yes; - no

-------
     Elements having low TLso are in turn chosen for long-term chronic
bioassays.  Chronic bioassays involve a continuous  exposure to a  sublethal
concentration of the toxicant.  In the chronic bioassay,  any biological
response, such as reduction of growth or reproduction,  behavior change,
histopathological change, etc., can be used to monitor  the effect of the
element or the species.  Also, test organisms are analyzed to determine
possible bioaccumulation of the element which could in  turn indicate a
potential pathway back to man.

                               DISCUSSION

     A definite need exists to carefully inventory  all  natural  and man-
made element sources which might impact the marine  environment.   Table 3
is a generalized inventory.  Assessing potential ocean  pollutants (Robinson,
et al., 1974) has presented an extensive and important  approach for bud-
geting pollutants; however, the report deals only with  the metals iron,
copper, and plutonium and concludes that plutonium  is the only element of
potential global pollution.  Similar assessment should  be made for all
elements; however, these assessments should be focused  at more localized
areas, such as coastal or estuarine areas as well as on a global  scale.
These inventories would highlight elements of major environmental concern
which should be carefully bioassayed in the laboratory.  Also, these
budgets should point out specific areas of high metal impact in the
United States.

     Field investigations of metal impacted areas throughout the  U.S. are
necessary in order to determine the extent, fate and effects of metals on
marine biota.  Have metals per se directly or indirectly  caused environ-
mental  damage and, if so, to what extent?  What are the inputs, rates,
routes, and reservoirs of metals within impacted areas?  Special  consid-
eration should be given to areas of:

     1.  Mining activities

     2.  Smelters

     3.  Industrial outfalls, especially metal plating  industries

     4.  Sewage outfalls

     5.  Desalinization plants

     6.  Offshore ocean disposal areas for industrial wastes, sewage
         sludge, and dredge spoils

     However, Cross and Duke (1974) have emphasized that  it is essential
that present efforts be continued and new efforts initiated to determine
baseline levels of trace metals in marine organisms and the environmental
variables that affect them.  These studies should be conducted not only
in contaminated environments such as Long Island Sound, New York  Bight,
and the Southern California Bight, but also in relatively pristine or
uncontaminated environments.  The concentration of  any  trace metals can


                                    19

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 TABLE  3.   INORGANIC CHEMICALS TO BE  CONSIDERED  AS POLLUTANTS OF THE MARINE ENVIRONMENT


                                          World  production
Element          Natural cone in          metric tons/year          Routes of entry          Pollution
_____       sea water uq/1                 (1968)                into the sea            categories

H  (acids)        pH=8 (alk=0.0024)                ?                      D,A                    III c
Be                     0.001                      250                    U                       IV c ?
Ti                     2                    1,000,000                    A ?                     IV b ?
V                      2                        9,000                    A                       IV a ?
Cr                     0.04                 1,500,000                    R(U)                    IV c ?
Fe                    10                  480,000,000                    D,R                     IV c
Cu                     1                    5,000,000                    D,R                     IV c
Zn                     2                    5,000,000                    D,R                    III c
Cd                     0.02                   15,000                    A,R                     II c
Hg                     0.1                       9,000                    A,R                      I b
Al                    10                    8,000,000                    D,R                     IV c
CN                     -                          ?                      D,R                    III c
Pb                     0.02                 3,000,000                    A,R                      I a
P                      -                          ?                      D                       IV c
As                     2                      60,000                    D                       II c
Sb                     0.45                   60,000                    U                       IV c
Bi                     0.02                     3,800                    U                       IV c ?
Se                     0.45                     1,000                    U                      III c ?
F                  1,340                    1,800,000                    D,R                     IV c ?

D dumping, A through atmospheric pollution,  R  through rivers (runoff) or pipelines
U unknown
I-IV order of decreasing menace; a worldwide,  b  regional, c local (coastal, bays, estuaries, single dumping).
Referenced from FAO Fisheries Reports,  No. 99  Suppl.  1.  Report of  the seminar on methods of detection, measure-
ment and monitoring of pollutants in  the  marine  environment:  Inorganic chemicals, Panel 3.  Dyrssen, D.,
C. Patterson, J. Ui and G.  F. Wei chart

-------
be highly variable both within and between species and influenced by a
number of environmental variables.  Until we understand the variability
that exists in healthy ecosystems, it may be difficult to identify a
contaminated ecosystem.  Also, because trace metals occur naturally in
the marine environment as a result of weathering and volcanic activity,
the problem of determining the contribution of anthropogenic additions
of trace metals to natural levels in marine organisms is more difficult
than with halogenated hydrocarbons or refined petroleum products.

     Other questions concerning potential metal pollutants which need
to be answered are as follows:

     1.  Are certain industries, such as power plants, producing exces-
         sive metal inputs which should be controlled?

     2.  Can elemental transformations occur within marine areas to
         produce more lethal and/or bioaccumulated compounds such as
         methyl-mercury?  If so, which elements are capable of trans-
         formation and under what circumstances?

     3.  Dredge spoils removed from navigational channels are often
         taken from areas which act as traps for sediments laden with
         river and estuarine bourne waste.  What are the long-term
         effects of these ocean dumped dredge materials upon the
         cleaner shelf areas?  How should ocean dumped materials be
         handled to lessen environmental impact in disposal areas?

     4.  Liquid effluents from waste water treatment plants probably
         will be a major contribution of trace metals to estuarine
         and coastal waters during the next several decades.  Efforts
         should be made to evaluate the impact that these discharges
         will have on concentrations of trace metals in harvestable
         marine species that complete a major portion of their life
         cycle in coastal areas.

     According to Schroeder (1973) environmental pollution by toxic
metals is a much more serious and insidious problem than is pollution
by organic substances such as pesticides, weed killers, sulfur dioxide,
oxides of nitrogen, carbon monoxide, and other gross contaminants of
air and water.  Most organic substances are degradable by natural pro-
cesses; no metal is degradable.  Elements in elemental form or as salts
remain in the environment until they are leached by rains into rivers
and into the sea.   Therefore, every effort must be made to slow down
the environmental  build-up of those elements which are toxic and can
cause degenerative diseases.

     The solution  to problems of metal waste disposal might be expected
to be dilution into the vastness of sea.  However, because metals can
be concentrated by geological, chemical, and especially biological pro-
cesses in the sea, the solution to metal disposal problems is not dilu-
tion.  The solution must be to stop pollution at its source by the
development of the proper technology to control and recycle metal wastes.
Hopefully, metal wastes entering the marine environment should be reduced
if application of the Federal Water Pollution Control Act Amendments of
1972 (Public Law 92-500) to apply the best available technology to mini-
mize environmental pollutants are carefully enforced.
                                    21

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                              REFERENCES
Cross, F.A.  and T.W.  Duke.   1974.   Trace metals.  In:  6.V.  Cox (ed.)f
     Marine  Bioassays.   Marine Technology Society, Washington, D.C.:
     308 p.

Eisler, R.   1973.   Annotated bibliography on biological effects of
     metals  in aquatic environments.   (No.  1-567) U.S.  Environmental
     Protection Agency Report R3-73-007; 287 p.

Irukayama,  K.  1966.   The pollution of Minamata Bay and Minamata
     disease.  In:  Third International Conference on Water Pollution
     Research.  Water Pollution Control Federation, Washington, D.C.:
     13 p.

Ketchum, B.   1972.  Marine aquatic life and wildlife.  In:  Water
     Quality Criteria 1972.   National  Academy of Sciences, Washington,
     D.C.:    594 p.

Merlini, M.   1971.  Heavy-metal contamination.  In:  D. Hood (ed.),
      Impingement of Man on the Oceans.  Wiley-Interscience,  New York,
     N.Y.:    738 p.

Robinson, E., L. Falk, B. Ketchum, and S. Piotrowicz.  1975.  Metallic
     wastes.  In:   E. Goldberg (ed,).  Assessing Potential  Ocean Pollu-
     tants.   National Academy of Sciences,  Washington,  D.C.:  438 p.

Schroeder,  H.A.  1975.  Elements and Living Systems.  Plenum Press,
     New York:  360 p.
                                    22

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                    Persistence in Marine Systems

                            Kenneth  T.  Perez*


                                 ABSTRACT


           When various  stressors  and/or disturbances are applied
           to a system,  regulatory agencies are  confronted with
           the problem of determining what  resulting systems
           changes  are "acceptable".  In general, previous studies
           have been arbitrary or  unrealistic.   We have attempted
           to overcome the above  inadequacies by:  (1) viewing
           systems  as holistic, (2)  assuming that some systems
           can be miniaturized for experimental  purposes, and (3)
           attempting to define the  persistence  limits of a system.

           Experimental  microcosms simulating a  complex marine
           coastal  system are  described.  Some preliminary results
           of such  systems to  different artificial sewage stresses
           are also presented.
      Ecologists  today  more  than ever before are being asked to predict
 the  consequences  of  changes  in total systems caused by various disturb-
 ances.   A  possible strategy  for establishing limits for such changes is
 the  subject  of this  paper.

      Conceptually, two general system responses are possible when a dis-
 turbance of  some  intensity and duration is relaxed:  the system either
 recovers its  "original" structural and functional state, i.e., it per-
 sists or_ it  does  not recover, i.e., the changes due to the disturbance
 are  irreversible.  This view is similar to that of Rolling (1973) but
 more  explicitly stated by Innis (1975).  Given that the system persists,
 one  is also  interested in the speed of recovery.  Thus, the limits for
 systems  change proposed in this communique are the ability to recover
 to some  previously defined state or control condition.  If system changes
 were  confined to  the limits for recovery then the resource or system
 would be maintained by definition.
*Environmental Research Laboratory, U.S.  Environmental  Protection Agency,
Narragansett, RI  02882
Co-investigators in this study are Scott  Nixon,  Candice Oviate and Jan  Northby
nf +ha I In i \;QVC i" +\/ n-f Dhnrlci Tclan/H
of the University of Rhode Island.

                                    23

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     The establishment of persistence  limits based upon previous theor-
etical studies  is  subject to  question.  The data base and principles from
which most complex models are formulated  is derived from components- of a
system (May, 1973; Patten,  1971).   These  components are usually experi-
mentally isolated  from the system  as a whole before dynamical studies are
performed.  The point is, if  systems are  holistic (Gallopin, 1971), then
even given a detailed knowledge  of its parts will not enable the descrip-
tion of the total  system.  It had  been shown (Walters & Efford, 1972)
that a complex model  derived  from  isolated components of a system pro-
vided limited dynamical  information.

     Experimental  field studies  of the recovery of disturbed systems are
(1) few in number and (2) difficult to perform and interpret.  First, it
is extremely difficult to impose or relax disturbances on natural marine
systems.  Second,  one is usually not allowed to jeopardize the system for
experimental purposes.  Third, because of the problems in replicating
systems and/or knowledge of other  uncontrolled disturbances, the estab-
lishment  of cause and effect  relationships is difficult.

      Previous studies of laboratory microcosms have had major shortcomings.
To my knowledge, no persistence  measures  as described above have been made,
In fact,  most of the microcosms  lacked a  full complement of species (see
Levandowsky, in press); those that did (e.g., Odum and Chestnut, 1970;
Whittaker,  1961) failed to provide sufficient physical properties (e.g.,
turbulence, water turnover) resulting  in  systems changes not observed in
similarly impacted areas in the  field.  One of the unique properties of
natural systems is their complexity.   I would ask, "Why has this property
been  minimized by the majority of  microcosm studies?"  Presented below is
an experimental marine system which attempts to overcome many of the in-
adequacies  of previous studies.
                        Average Seasonal Light
                          Quality  and Quantity
      Narragansett
         Bay Water
       Benthic Tank
        Pelagic Tank
                                  •i i.
                                  ""' Rotating
                                      Paddle
Exhaust

Air Pump to
Circulate
Pelagic Water
though the
Benthic Tank
              Figure 1.   Experimental microcosm.
                                    24

-------
     Our microcosms consisted of an interconnected pelagic and  benthic
phase (Fig. 1).  Pelagic water was continuously circulated over the
benthic community.  The size of the pelagic phase (150 1)  was dictated
by our resources.  However, the surface area of the benthos  (167 cm2)
was based upon the surface area to volume ratio in Narragansett Bay.
All container surfaces were scrubbed daily so that the only  surface
area available for settling was the benthic sediments  (i.e.,  the 167  cm2).
Natural changes in surface temperatures in the microcosms  were  reproduced
by continuously passing Bay water on the outside of the microcosms.   Sal-
inity was monitored weekly.  However, the West Passage of  Narragansett
Bay, the system being simulated, exhibits small salinity changes (<2  o/oo)
Natural turbulence leyels in each tank were simulated  by adjusting the
speed and reversing time of paddles such that the dissolution rates of
"sour ball" candy was approximately equal to that of the Bay (Table 1).

     TABLE 1.  DISSOLUTION RATES (gm/min) OF "SOUR BALL" CANDY
               IN NARRAGANSETT BAY (NB) AND RHODE ISLAND SOUND
               (RIS) DURING CALM AND WINDY PERIODS AND IN  THE
               EXPERIMENTAL MICROCOSMS
          NB                        RIS                      Experimental
   0 cm wave height         30-60 cm wave height              microcosms
X        0.174                     0.246                       0.153

RGE   0.168-0.178               0.233-0.264                 0.150-0.160

N          6                         6                           4
As a result of the continuous mixing, no differences in water chemistry
existed between the top and bottom of the tanks.   This  condition  is  simi-
lar to that found in the West Passage of the Bay.   Water turnover (10  1/48
hrs) was based upon the flushing time of the Bay  (Kramer, 1975)  and  was
accomplished by the removal and replacement of 10  liters of water every
48 hours.  All water was hand-carried so as to eliminate mechanical  damage
due to pumping.  Light regimes were based upon the quality and quantity  of
light found at 3 m, the depth at which the average light intensity for the
water column occurred in West Passage during early spring.  Because  light
is effectively extinguished on the bottom of the  Bay, all benthic chambers
were dark.

     The biotic composition of the microcosms was  based upon densities per
unit volume for the pelagic phase and per unit area for the benthic  phase.
This meant, for example, that fish larvae were experimentally excluded
from our systems since the highest densities found in West Passage was
5xlO~3/l.  However, some larvae were observed in  our tanks and probably
entered during the egg stage for we screened our  water to lOOOy for  pur-
poses of reducing replicate variability.  It should be  noted that the
inclusion of pelagic macroscopic forms such as ctenophores and fish  larvae
                                    25

-------
is possible; while ctenophores are major predators in the Bay they were
not present in any significant numbers during this time of the year (early
spring).  The benthic organisms were collected from an anchor dredge,
screened of large living and dead material through V mesh, diluted with
seawater and mixed uniformly, allowed to settle in the benthic chambers
with flowing seawater for five days prior to place in the pelagic tanks.
Animal macrofauns (<1 mm) in the benthic chambers were counted at this
time and any large organisms not found in the boxes due to sampling error
were added in appropriate densities to each box.  The seawater in the tanks
was intermixed for three weeks before any experiments were performed.

     The objectives for our first experiment were to (1) compare different
variables in the microcosms to the field, and (2) to determine the persis-
tence (as defined above) of the microcosms exposed to fixed (i.e., time
independent) levels of domestic sewage (the disturbance).  The sewage was
collected locally in large volume, partitioned to 500 ml fractions and then
frozen.  The sewage was added, following the three week intermixing period,
to  the  tanks initially at three concentrations, 0.01, 0.1 and 1.0%; control
tanks received deionized water in proportions equal to the high sewage tanks.
However, the amount of sewage added thereafter only took into account the
48  hour seawater additions, i.e., the simulated influx water volume.  There
were three  replicates for each test condition and the control.

     Some of the variables in the microcosms were measured continuously,
others  discretely.  The latter were the structural descriptions for the
benthos (macro- and meiofauna) and plankton.  Specific size (1-50U) fre-
quency  distributions of "particles" were made three times a week using-a
modified Coulter counter.  Continuously measured variables in the water
column were ATP, nutrients (NH3, N03, N02, P04) and chlorophyll (in vivo
fluorescence and extracted).  Measures of ATP, S=, C02, particulate organic
carbon  (POC), and trace metals in sediments, and POC, DOC, dissolved or-
ganic carbon (DOC), total organic nitrogen, total metabolism, nitrogen,
and carbon  fluxes in the pelagic phase are in progress.  As a general com-
ment, we have found that the methods for measuring ATP in the sediments
and DOC, POC in the water column require close attention with respect to
accuracy.

     The species richness of our microcosms prior to sewage addition was
representative of field levels using the above density criteria.  The num-
ber of phytoplankton species ranged from 10-12.  While we did not count the
number of holo and meroplanktonic species at the start of the experiment,
Martin  (1964) averaged 19 such species during the early spring over a three
year period in West Passage.  The benthic macrofauna consisted of 10 species.
The largest organism in the benthos was a polychaete worm, Nephtys, 4-5 cm
in  length.   The meiofauna (<1 mm) and bacteria were not enumerated at this
time.

     We found a reasonable correspondence between the Bay and control ATP
levels (Fig. 2), thus suggesting realism of our microcosms with respect to
the pelagic bacteria and phytoplankton.  The reason for the slightly higher
ATP concentrations in the controls as compared to the Bay during the inter-
mixing period (Table 2) is unknown; this relative difference remained, how-
ever,  during the sewage exposure despite increases in Bay concentrations,
                                    26

-------

-------
i.e., the controls appeared to follow the Bay but slight "constant" dif-
ferences existed.  Differences between the sewage tanks treated alike also
existed.  However, it was possible to detect significant (« = 0.05) non-
linear changes in ATP for all sewage levels over time.  During the inter-
mixing period all tanks had equal ATP concentrations.  A direct relation-
ship between ATP and sewage addition was observed most of the time following
the intermixing period.  Chlorophyll concentrations  (Fig. 3) showed similar
results although the differences between the Bay and the control tanks were
greater.

     TABLE 2.  AVERAGE ATP CONCENTRATIONS (ygm/1) FOR NARRAGANSETT
               BAY (NB) AND LABORATORY MICROCOSMS PRIOR TO AND DUR-
               ING EXPOSURE TO DOMESTIC SEWAGE
                 "Intermixing period" (17 days)    Sewage exposure period (98 days)

                  x           Sx            n       x            Sx          n
NB

control
0.01%
0.1%
1.00%
sewage
sewage
sewage
1
2
2
2
2
.54
.52
.40
.31
.40
0.1
0.1
0.1
0.1
0.1
35
78
19
14
68
5
7
7
7
7
2.
3.
4.
6.
8.
27
71
26
46
39
0
0
0
0
0
.200
.309
.194
.410
.334
42
43
43
43
43
     The  "sinks" for the high productivity in the pelagic phase were (1)
 the  48 hour losses  (i.e., flushing) and (2) the benthos.  After 98 days of
 sewage, the benthic communitites exposed to high sewage were characterized
 by high organic layers at the sediment surface (36.9 mgC/1) as compared to
 the  controls  (24.9 mgC/1).  Polydpra lignae, a polychaete worm, occurred
 in moderate density due perhaps to high sediment sulfide concentrations (a
 sulfide bacterium almost completely covered the surface).  It should be noted
 that such a community was the result of organic loading and not low water
 column oxygen levels, since oxygen concentrations near or exceeding satur-
 ation (67-107%) of pelagic water was continuously circulated over the surface
 of the sediments.  The benthic communities treated with intermediate sewage
were dramatic; high densities of Polydpra were immediately evident.  Tube
 densities of 20-30/cm2 were "found.  Presumably, lower organic loads with low-
er sediment anaerobiosis possibly either (1) provided "optimal" conditions
 for Polydora to dominate and/or (2) excluded competitors and/or predators.
The real contrasts to the high and intermediate sewage levels were found in
 the control and low sewage tanks.  Almost no Polydora were present (1 tube/
 cm2) in the control and low sewage tanks, but rather the initially stocked
 community represented by Nephytys and Yoldia.  As a result of these findings,
 cursory surveys of the benthos along a sewage gradient were made in Narra-
gansett Bay.  Areas suspected of high pollution were devoid of most living
material in the sediments.  However, in slightly polluted areas  densities
 (5-25 tubes/cm2) of Pol.ydora similar to that found in our intermediate sew-
age microcosms were observed.   Unpolluted locations  showed benthic commun-
ities similar to that of the control  tanks  with Polydora  at  very low densities
                                   28

-------
       80
       60
    o>
NS
   m
   Q_
   O
   01
   O
   O
      40
       20
        0
              Bay wafer
              Control tanks
              Low sewerage
              Medium
              High
         0
Figure 3.
            f25
50          75
     TIME,.Days
100
|l25
                  Mean pelagic chlorophyll ^changes in Narragansett Bay and experimental microcosms
                  prior to and during sewerage addition.

-------
(0-1 tube/cm2).  This preliminary result suggests that the laboratory sim-
ulation of this marine system is somewhat realistic.   Field determinations
of nutrient and organic loading and its relationship to benthic communities
is required before any further conclusions are made.

     The main objective of this study is yet to come.  Systems changes, as
described above, have occurred as a result of the disturbances applied.
The question now is, will the disturbed systems return to the structural
and functional state of the "control" systems once the sewage input is re-
laxed?  If so, then what is the time course?  — weeks, months, years?  We
will continue to monitor the systems and follow their recovery since the
recent cessation of sewage.
                               REFERENCES
 Gallopin,  G.C.   1971.  A  Generalized Model of a Resource-Population system.
      I  General  Properties Oecologia (Berl.) 7:  382-413.

 Holling,  C.S.   1973.   Resilience and Stability of Ecological Systems.
      Ann.  Rev.  Ecology and Systematics 4:  1-23.

 Innis,  G.   1975.   Stability, Sensitivity, Resilience, Persistence.  What
      is of Interest?   Proc. Siam-Sims Confer:  S.A. Levin  (Ed.) Ecosysterns
      Analysis and  Prediction, pp. 131-140.

 Kramer, J.   1975.  Analysis of a Plankton Based Temperate  Ecosystem:  An
      Ecological  Simulation Model.  Univ. Rhode Island, Ph.D.

 Levandowsky, M.  In Press.  Multispecies cultures and Microcosms.  In
      Marine  Ecology (Ed.) 0. Kinne.

 May,  R.M.   1973.   Stability and Complexity in Model Ecosystems.
      Princeton  Univ. Press, Princeton, N.J.

 Martin,  J.H.  1964.  A study of the Relationships Between  the Environment
      and the Zooplankton of Narragansett Bay.  URI, Masters, pp. 109.

 Odum, H.T. and A.F. Chestnut.  1970.  Studies of Marine Estuarine
      Ecosystems  Developing with Treated Sewerage Wastes, Annual Report
      for 1969-1970.  Institute of Marine Sciences, Univ. of North
      Carolina, Chapel Hill and Moorehead City, N.C., 1-363 p.

 Patten, B.C. (Ed.)  1971.  Systems Analysis and Simulation in Ecology.
      Vol. 1, Academic Press, N.Y., 607 p.

Whittaker, R.H.  1961.  Experiments with Radiophosphorous Tracer in
      Aquarium Microcosms.   Ecol. Monbgr.  31:  157-187.
                                    30

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                  Criteria for Marine Microbiota

              V.J. Cabelli, A.P. Dufour and M.A. Levin*
                        and Paul W. Haberman**
                             INTRODUCTION


     The examination of estuarine and coastal  waters  for microbial  indi-
cators of quality can be and, in some instances, already is  important  in
assessing the ecological and human health impact of industrial,  agricul-
tural and sanitary pollutants discharged therein.   Such  pollutants  may
affect microbial activities in marine ecosystems in a number of  ways.
Toxic organic and inorganic chemicals can destroy  those  microorganisms
responsible for essential biological transformations  such as minerali-
zation, nitrification, etc. or those which act as  food sources for  higher
life forms.  Nutrients discharged into the water from sewage or  industrial
wastes or man-induced changes in the physical  environment may permit the
multiplication of pathogens for fish or other marine  fauna.   On  the other
hand, toxicants and changes in the physical conditions may affect the  sus-
ceptibility of the fauna to microbial infection and disease. The activi-
ties of marine microorganisms themselves are important in that some species
degrade pollutants such as pesticides, detergents  and other  organic molecules,
some accumulate pollutants and pass them up through the  food chain, and some
activate certain chemicals to more toxic forms, i.e., methyl mercury.

     Unfortunately, in most of the interactions noted above, the relation-
ships among the pollutant, the adverse ecological  effect and some microbial
indicator thereof have not been quantified sufficiently; and, hence, micro-
bial guidelines and standards are not available.  This,  of course,  is  under-
standable because of the complex interrelationship involved.

     Pollution associated effects on human health  are more amenable to quan-
tification.  There are a number of microbial pathogens of man which can be
discharged into receiving waters via fecal wastes  or  which can multiply
therein under the influence of nutrient pollution.  However, in  terms  of
microbial activity, there is only one target species  (man),  two  routes of
transmission (recreational use of marine waters and consumption  of  marine
biota as food), and two basic processes (infectious disease  and  bionitoxi-
cation).  The above factors notwithstanding, a major  constraint  in  quanti-
fying health effects and modeling dose-response relationships stems from the
logistic and ethical restrictions placed on studying  the target  species, man.
^Environmental Research Laboratory—Narragansett, U.S.  Environmental  Protection
Agency, West Kingston, RI  02881
**Center for Policy Research, New York, NY
                                   31

-------
      Because  of  the  above considerations, the directness and immediacy of
 the  impact  on man  via his health and well being, and man's egocentricity
 as a species, it is  not surprising that human health effects guidelines
 and  standards for  water quality generally have antedated those for ecolo-
 gical  effects by a number of years.  Furthermore, it is both understandable
 and  defendable that  such microbial guidelines and standards have been set
 forth  based upon a limited quantity of epidemiological data.  The reality
 is that  the construction of waste disposal systems will continue and that
 receiving water  criteria are needed so that they may be translated into
 effluent guidelines  and standards, including the degree of treatment re-
 quired,  the siting of sewage outfalls, and the locating of sludge disposal
 areas.

      As  used  in  the  studies to be described, a health effects, recreational
 water quality criterion may be defined as a scientific or objective require-
 ment of  a condition  to be fulfilled for the protection and promotion of the
 health and  safety  of the public.  It is a set of facts or data upon which a
 decision or judgement may be based.  Many such criteria are developed through
 intensive and extensive epidemiological studies1'2.  The criteria may be used
 in two ways.  They can be extrapolated into guidelines and standards for post-
 ing  or closing beaches as "unsafe" for use.  A more desirable use of the
 criteria, since  it increases rather than decreases the available resource, is
 their translation  into effluent guidelines and standards as noted above.

      Figure 1 is a graphic representation of the health effects, recreational
 water quality criteria as defined above.  It is a slightly modified version
 of that  described  by Cabelli and McCabe  .  The salient point is that a cri-
 terion is expressed  as a quantitative relationship between some index of health
 effects  among swimmers to some measure of the quality of the water.  Once an
 "acceptable risk"  is determined, an appropriate guideline can be extrapolated
 from the criterion.  The setting of an "acceptable risk" has social and eco-
 nomic  implications as well as the health effects input inherent to the criter-
 ion.  Therefore, the two translations may, and probably will, have different
 "acceptable risk"  levels and, hence, different guidelines and standards.

      Existing criteria, guidelines, and standards at the local, state and
 national level have  been reviewed elsewhere4 as have the data base required
 for  their development, the types of experimentation or observation which can
 be used  to  produce the data, available Information, and the shortcomings of
 this information2'5.  As of 1969 when the present study was designed or even
 1972 when it  was initiated, the available epidemiological data came primarily
 from Stevenson's prospective studies6, Moore's restrospective study7 and some
 scattered case reports8'9.  The analysis of a recreation associated outbreak
 of shigellosis along the Mississippi River below Dubuque, Iowa10 provided
 some additional  data.  For a number of reasons none of these studies indi-
 vidually or together provided the totality of the required epidemiological
 and microbiological  data.

     The United  States Environmental  Protection Agency has  responded to the
need for additional  data by a long term epidemiological-microbiological
program whose objective is  to define  the relationships  noted earlier.   The
overall program  calls for (1)  a three year study  at  selected New  York  City
beaches to   define the relationships  (including  a  pretest  of  the epidemio-
 logical and microbiological  methods),  (2)  trials  at some  "subtropical

                                     32

-------
                                         B -
acceptable risk

background illness
             WATER QUALITY INDICATOR DENSITY

Figure 1.  Graphical illustration of health effects water quality criteria and their
         extrapolation to guidelines.

-------
location to examine the variable of climate, (3) the development of a math-
ematical model (the regression line and confidence limits of the relation-
ship described in Figure 1), and (4) spot testing of the model at a number
of geographically distinct sites.  The findings to be presented summarize
the data obtained during the first two years of the program.

                          EXPERIMENTAL DESIGN

     The study being conducted at the New York City beaches is a prospec-
tive epidemiological investigation in which (1) the potential participants
(primarily family groups) are approached at the beach in the course of week-
end trials, and individuals who swim in the midweeks immediately before and
after a trial are eliminated from the study, (2) swimming is rigorously de-
fined as significant exposure of the head and face to the water, (3) measure-
ments for a number of potential water quality indicators are made during the
course of the trials at the test beaches, and (4) follow-up information con-
cerning symptomatology and demography is solicited by phone some 8-10 days
after a trial (Table 1).  The experimental design and the rationale for its

          TABLE 1.  SEQUENCE OF EVENTS FOR EPIDEMIOLOGICAL-
                    MICROBIOLOGICAL TRIALS
 Day of     Day
  Week    Number
        Acti vi ty
          Function
Saturday    1
(Beach Interview, Water
 Sampling)
Sunday      2


Monday      3



Monday     10
(Beach Interview, Water
 Sampling)

Reminder Letter
Phone or mail Interview
 (a) Obtain name,address, phone,  etc.

 (b) Reject pretrial midweek swimners

 (c) Query on beach activity

 (d) Assay of water samples

    As Above


 (a) Provide name of physician

 (b) Reminder to note illness

 (a) Obtain illness information

 (b) Reject post-trial  midweek
    swimmers

(c) Obtain demographic information
                                    34

-------
use have been described elsewhere5.  In the first two years of the New
York study two sites (beaches) were used.  The first beach, located at
Coney Island around 22-24th Street (Figure 2), was desianated as "barely
acceptable" (BA) and was the most polluted beach available which was not
posted as unsafe for swimming.  The second, located at Arverne or Riis
Park at the Rockaways, was designated as "relatively unpolluted" (RU) and
was the least polluted beach available at which the populations were demo-
graphical ly similar to the BA beach.  Thereby, attack rates for symptoms,
symptom groups (i.e., gastrointestinal, respiratory, "other") and a "sev-
erity index" (stayed home, stayed in bed, sought medical advice) was ob-
tained for the four groups (swimmers and nonswimmers at both beaches) and
for the various demographic subgroups (sex, age, ethnicity, socioeconomic
status).  The symptoms for which information was solicited are given in
Table 2.  The soliciting of health effects information in the context of
symptoms rather than specific disease is consistent with the first basic
tenant of the experimental design, i.e., there would be no prejudgement
as to which diseases were "important" in the context of swimming assoc-
iated health effects.

     TABLE 2.  SYMPTOMS FOR WHICH QUERIES WERE MADE
Gastrointestinal

Vomiting
Diarrhea
Stomachache
Nausea

"Other"

Fever (>100°C)
Headache (more than few hours)
Backache

General
Sunburn
Skin rash, itching skin
Red, itchy, or watery eyes
Respiratory

Sore throat
Bad cough
Chest cold
Runny or stuffed nose
Earache or runny ears
Sneezing, wheezing, tightness
  in chest

"Severity" Index

Home because of symptoms
In bed because of symptoms
Medical help because of symptoms
     The second tenant of the study was that the "correct" indicator would
be treated as an unknown; this required density measurements and, at times,
the development of enumeration methods for a number of potential water
quality indicators.  Water samples, used to obtain the density measurements,
were collected at "chest level" from two sites at each beach about every two
hours during the period of maximum swimming (11:00 a.m.  to 5:00 p.m.).  A
number of potential indicators are listed in Table 3 along with designations
as to those for which measurements have or will be made.  A review of po-
tential health effects water quality indicators and the methods used for

                                    35

-------
u>
        UPPER
         BAY
                         BROOKLYN
        LOWER
          BAY
      01234
                        J*
                   20th St.
         I  I   I
    KILOMETERS
COME
    ATLANTIC  OCEAN
      Figure 2.  Test beaches at Coney Island ("barely acceptable") and the Rockaways ("relatively
              unpolluted") in New York City.

-------
their enumeration is beyond the scope of this report.   This h
by Bonde'l.  Such a review, including usage rationales is bei
for publication.  Papers describing the enumerative
developed for this program have been published '2-179
preparation.
                                  has  been  done
                                   ng  prepared
                          methods  used in or
                           and others  are in
     TABLE 3.  POTENTIAL HEALTH EFFECTS WATER QUALITY INDICATORS
        Indicator
Status
Indicator
Status












a -
b -
C «•
d -
e -
Total Col i forms
Fecal Col i forms
E. coli
Klebsiella
Enterobacter-
Citrobacter

Enterococci

C. perfringens
C. albicans
Bifidobcateria
examined in 1973
examined in 1974
to be examined i
may be examined
examined in 1973
a
a
a
a

a

a

b
c
c
and 1974
n 1975
in future
, discontinued
Enterovi ruses d
Coliphage c
Salmonella
Shi gel la d
P. aeruginosa a

A. hydrophila a

V. parahemolyticus b







                               RESULTS

     The pretest (Phase I) trials conducted during the summer of 1973 con-
firmed the applicability of the epidemiological  and microbiological  method-
ology5.  Although the study population contained only 1300 individuals,  a
statistically significant increase in the rate of gastrointentinal  (GI)
symptoms for swimmers relative to nonswimmers was observed at the "barely
acceptable" but not the "relatively unpolluted"  beach (Table 4).  Cochran's
chi square method as descrived by Fleiss'8was used for the statistical
analysis.  Increases in respiratory, "other" and "severe" symptoms also were
obtained at the Coney Island beach, but these were not statistically signi-
ficant at the P=0.05 level.  With the exception  of respiratory symptoms,
smaller increases (swimmer minus nonswimmer) were obtained at the Rockaways
beach.  The microbiological findings were described previously^.

                                    37

-------
     TABLE 4.  SYMPTOM RATES BY CATEGORY FOR 1973
                                      Symptom Rate  in  Percent  at

     Symptom Type                Coney Island            Rockaways
                             S        NS      A     s        MS
                            474      167           484       197

       Resp.                 12.9     10.2   2.7    18.0a'b   11.7    6.3

       GI                     7.2 a     2.4   4.8     8.1       4.6    3.5

       Other                  9.9      6.6   3.3     9.1       8.6    0.5

       "Severe"               5.9      4.2   1.7     6.0       5.6    0.4


^Significantly (P = 0.05) higher than nonswimmers.

 Significantly (P = 0.05) higher than other beach.

S-Swimmers; NS-nonswimmers;  ^-difference;  Resp.-respiratory;  Gl-gastro-
intestinal; Other-general symptoms;  "Severe"-stayed home, stayed in  bed
or sought medical help.

     The 1974 findings (Table 5)  essentially confirmed the 1973 results.

     TABLE 5.  SYMPTOM RATES BY CATEGORY FOR 1974.
Symptom Rate in Percent at
Symptom Type

Resp.
GI
Other
"Severe"
Coney Island
S NS A
1961
7.2
4.2 a
7.3
3.8
1185
6.4 0.8
2.6 1.6
6.7 0.6
2.9 0.9
S
2767
8.3
3.9
8.6
3.0
Rockaways
NS A
2156
7.8
3.5
7.7
2.6

0.5
0.4
0.9
0.4
Significantly (P=0.05)  higher than  nonswimmers.

 Significantly (P=0.05)  higher than  other beach.

S-Swimmers;  NS-nonswimmers;  A-Difference; Resp.-respiratory;  Gl-gastro-
intestinal;  Other-general  symptoms;  "Severe"-stayed  home, stayed  in  bed
or sought medical  help.

                                   38

-------
Although the differential rates for most of the symptom categories were
lower in 1974, because of the larger study population a statistically
significant increase in the rate of 61 symptoms among swimmers relative
to nonswimmers again was obtained at the "barely acceptable" beach.  In
addition, the most sensitive portions of the Coney Island population were
identified as children, Latin Americans and low to middle socioeconomic
status individuals.  Finally, the validity of the responses obtained as
to gastrointestinal symptomatology was examined by calculating the rates
of those symptoms considered highly reliable (all instances of vomiting;
diarrhea only when "severe" or with fever; stomachache and nausea only with
an accompanying fever) for each of the subgroups and comparing these to
overall GI rates for the corresponding groups.  The trends, and in most
cases the statistical significance, were comparable.   These findings were
important in demonstrating that certain differences probably were not spur-
ious, in confirming the acceptability of the methodology, and in identify-
ing the sensitive portions of the population for future studies.  In addition,
there are aspects and implications of the data relating the health effects
of swimming per se, year to year variability in the nonswimming ("Background")
rates of gastrointestinal symptomatology, and demographic differences in re-
porting symptoms which will be considered in a later publication.  However,
this type of analysis does not speak to the overall objective of the program,
that is, defining the relationship or association of health effects to water
quality indicators as described in Figure 1.

     In the context of the present experimental design, the data can be
analyzed to yield the criteria in two ways.  It can be obtained from re-
gression analysis of the data obtained during a given summer by consider-
ing the symptom rates and the corresponding indicator densities for each
trial (day) as a single point on the line; in this instance, one capitalizes
on temporal (day to day) and spacial (distance) variability in pollution
levels reaching the beaches.  The second approach is to analyze the data
across summers.  Thereby, the overall  symptom rates and associated indica-
tor densities for all the trials at each beach during a given summer are
combined to yield a single data point.

     Correlation coefficients for the differential rate of gastrointestinal
symptoms against the various water quality indicators were obtained from the
1974 data as shown in Table 6.  The regression lines for £. coli, Klebsiella
and fecal coliforms, the indicators with the highest correlation coefficient,
are shown in Figure 3.  Another set of regression lines should be obtained
from the 1975 data.

     When the data were examined across summers, four points were obtained
for each indicator (Figure 4).  Since an additional two points should be
obtained from the 1975 trials, a statistical analysis was not attempted.
However, inspection alone confirms the close relationship of GI symptoma-
tology to _E.  coli  densities, although  fecal streptococci, Klebsiella and
Aeromonas hydrophila also produced close fitting lines.  The regression
lines for both total  and "severe" GI symptoms  against E_.  coli densities
are shown in Figure 5.  It is of interest that the "IE.  coli" lines ob-
tained by both methods of analysis were quite  similar;  the differential
rates for total  GI symptoms associated with mean E_. coli  densities of
200/100 ml  were 3.8 and 3.6%.
                                     39

-------
                  4 .
JS
o
zo  0
OK
?i  4
^-:  2
_i
< cc
^£  o

a: ^  4
U. L_
t<   «
o o:   *
                         Klebsiello  sp.
             Fecal  Conforms
                                            o
                            o
                         E. coli
                                             10                      100
                                   MEAN DENSITY/100 ml of WATER, PER  TRIAL
                                                                                1000
            Figure 3.
          Relationship of the differential  rate of gastrointestinal symptoms  (swimmers  minus
          nonswimmers) to the mean density  of  the water quality indicators as obtained  from
          the trial by trial  analysis of 1974  data.  The lines were drawn from a least  squares
          analysis.  The three regression lines are for the  three indicators which gave the
          best correlation coefficients: E_.  col i, 0.771; fecal coliforms, 0.673; Klebsiella,
          0.664; »-Rockaways,  A-Coney Island.

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10

2 o
^c
>2
3>o
z i-
o°- 10
Z5
±z
*- 0
c/>~
^e>
<§•
•-a. K)
z_
WS2
or2"
£u 0
u- |_ U
lfb<
o o:
10

o
Enterobocter- Citrobocter


A
. ° A

Total coliforms


^

-
A.hvdroDhila A 1973 CONEY ISL.
o 1973 ROCKAWAYS
A 1974 CONEY ISL.
o 1974 ROCKAWAYS
j*^* — ^^

P.aeruginosa




: . ° A*
Fecal coliforms Klebsiella

-

^
o
• A

Fecal streptococci

-
^
< 1^1 i 1 1 1 1 1 i i i i 1 1 1 1 1 i i i 1 1 1 1 1
1 10 100



A __
Q ^
A 	 • 	 • " A

E. coli


^tL— 	 *"
L^-.— r-i i 1 1 1 1 A i it i i 1 1 1 1 i i i i i i 1 1
10 100
                  MEAN  INDICATOR  DENSITY  PER  100 ml
Figure 4.  Relationship of the differential rate of gastrointestinal symptomatology  to indi-
          cators densities as obtained from the analysis of 1973  and 1974 data.  Each point
          represents  the overall GI symptom rate and mean indicator density for all the
          trials conducted at the beach during that summer.

-------
          50
          30
to
     COT

-------
     TABLE 6.  RELATIONSHIP OF INDICATOR DENSITY TO THE
               DIFFERENTIAL (SWIM-NON-SWIM) ATTACK RATE
               FOR GASTROINTESTINAL SYMPTOMS (1974)*
          Indicator                           Correlation Coeff.(r)


     I- Co1i                                          0.711

     Klebsiella                                       0.664

     Fecal Coliforms                                  0.673

     Total coliforms                                  0.549

     Fecal streptococci                               0.453

     Pseudomonas aeruginosa                           0.191


*0btained from six trials at Coney Island (BA) and Rockaways  (RU)  beaches.

     The high attack rate of 3-4% above background (nonswimmers)  appears
to be somewhat disturbing.  However, it must be borne in mind that the
individuals in question neither died or required hospitalization.   In  all
probability most of these cases would not have been reported  to public
health authorities except in an "outbreak" situation.  Nevertheless,  they
do represent a measureable and, hopefully, predictable health effect whose
economic and social import must be considered in setting an  "acceptable
risk".  As noted previously, additional data should be forthcoming from
trials being conducted at the New York City beaches during the summer  of
1975 and at a "subtropical" site the following year.   Therefore,  a complete
statistical analysis of the health effects vs indicator data  obtained  to
date was not attempted; and the information to follow is meant to be  des-
criptive and indicative of the relationships which can be expected.

     The overall  program to develop health effects recreational water
quality criteria is far from complete.  However, the data obtained thus
far are quite encouraging.  E_. coli and fecal streptococci appear to  be
the best indicators examined thus far; and, if the data being obtained
this summer are consistant with the findings to date, interim criteria
should be available in 1976.  "Subtropical" site selection is in progress;
and the nature of the model is envisioned, that is, the regression line of
GI symptomatology vs E_. coli or fecal streptococci densities  and the  con-
fidence limits around the line.

-------
                                   REFERENCES

 1.  Mood,  E.W.   Health  Criteria  for  the Quality of Coast Bathing Water.
          Report of the  Special Advisory Committee on Health Criteria for
          the Quality of Recreation Waters with Special Reference to Coastal
          Waters and Beaches, World Health Organization.  December, 1974.

 2.  Cabelli, V.J., M. A.  Levin and A.  P. Dufour.  Recreational Water Quality
          Criteria.  Submitted to  Critical Reviews in Environmental Control.

 3.  Cabelli, V.J.  and L.J.  McCabe.   Recreational Water Quality Criteria.
          News of Environmental Research in  Cincinnati.  November 11, 1974.

 4.  Mechalas, B.J., K.K.  Hekimian, L.A. Schinazi and R.H. Dudley.  1972.
          An investigation into recreational water quality.  Water Quality
          Criteria Data  Book, Volume  4.  18040 DAZ 04/72 Environmental Pro-
          tection Agency.

 5-  Cabelli, V.J., M.A. Levin, A.P.  Dufour  and L.J. McCabe.  1974.  The
          Development of Criteria  for Recreational Waters.   International
          Symposium on Discharge  of Sewage from Sea Outfalls.

 6.  Stevenson,  A.M.  1953.  Studies  of bathing water quality and health.
          Jour.  Am. Pub. Health Assn.   4_3:529.

 7.  Moore, B.  1959. Sewage contamination  of coastal bathing waters in
          England and Wales.  A bacteriological and epidemiological study.
          J. Hyg.  57_:435.

 8-  Flynn, M.J. and D.K.B.  Thistlewayte.  Sewage Pollution and Sea Bathing.
          Second International Conference on Water Pollution Research, 1964.

 9-  Ciampolini, E.  1921.   A study of the typhoid fever incidence in the
          health center  district  of New Haven.  Unpublished Report.

10-  Morbidity and  Mortality Weekly Reports.  Shigellosis Associated with
          Swimming  in the  Mississippi  River, National Center for Communicable
          Disease,  U.S.D.H.E.W.,  Vol.  23, No. 46, 1974.

11.  Bonde, G.J.   1966.    Bacteriological Methods for Estimation of Water
          Pollution.   Hlth.  Lab. Sci.  3i, 124.

12.  Levin, M.A.  J.R.  Fischer, and V.J. Cabelli.  1974.  Quantitative Large-
          Volume Sampling  Technique.   Appl.  Microbiol. 28, 515.

13.  Cabelli,  V.J.   1973.   The Occurrence of Aeromonads in Recreational Waters,
          Abst.,  ASM.  p.  32.

14.  American  Public Health  Association.  Standard Methods for the Examination
          of Water  and Wastewater.  13th ed, 1971.American Public Health
          Association Inc.,  New York.


                                        44

-------
15.   Levin,  M.A.  and V.J.  Cabelli.   1972.   Membrane  filter  technique  for
          enumeration of Pseudomonas  aeruginosa.   J.  Appl.  Microbiol.  24:864.

16.   Dufour, A.P.  and V.  J.  Cabelli.   1975.   Membrane filter  procedure for
          enumerating the  component  genera  of the  Coliform  group  in seawater.
          J. Appl.  Microbiol.   29_:826.

17.   Levin,  M.A.,  J.R.  Fischer,  and  V.J.  Cabelli.  1975.  Membrane filter
          technique for enumeration  of Enterococci in marine  waters.   J. Appl
          Microbiol.  30;66.

18.   Fleiss, J.L.  Statistical  Methods for Rates  and  Proportions.  John Wiley
          and Sons.  1973.   New York  City p.  109-114.

-------
               Impact of Chlorination Processes
                     On Marine Ecosystems

                    D.P.  Middaugh and W.P.  Davis*


                               ABSTRACT
          The use of chlorine  as  a  disinfectant  and antifoul ing
          agent is reviewed.   Chemical  reactions of chlorine in
          aquatic environments are  discussed, with particular
          emphasis on the formation of  halogenated organic  con-
          stituents in freshwater and marine systems.  Studies
          of the effect of chlorinated  sewage effluents and cool-
          ing water from generating stations on  marine organisms
          and ecosystems are  summarized.
                             INTRODUCTION
     Chlorine gas has been used as  an  industrial  bleaching  agent since
1800 and has become one of the most versatile  chemicals  known.  In  fresh-
water it is used in drinking and recreational  water  as a disinfection
agent, a biocide for slime and fouling control, and  in the  treatment of
municipal wastes to control  pathogens.  In  these  applications, vast quan-
tities of chlorine are used, and find  their way into natural ecosystems.
The toxicity desired in disinfection and biocide  applications can contin-
ue on with undesirable effects on wildlife  and the environment.  Recent
detection of halogenated organics in the drinking water  of  80 cities un-
derscores the need for responsible  assessment  of  the management and effects
of our chlorination processes, and  the environmental costs  incurred.

     Some of the most accurate statistics on the  rate of chlorine use exist
for the State of Maryland.   Chlorine discharge from  Maryland into the Chesa-
peake Bay is presently estimated to be 1.1  x lO1*5 g/yr from municipal sewage
treatment plants and 0.1  x 1010 g/yr from power generating  facilities (Block
and Helz, 1975).  It is estimated (but still to be confirmed experimentally)
that 1  percent of these totals may  become halogenated organic compounds
which would persist in the environment (Jolley, 1973).   Thirty-three other
states  border marine ecosystems where  some  form of chlorine discharge cur-
rently persists.
*Environmental Research Laboratory—Gulf Breeze,  U.S.  Environmental  Protection
Agency, Bears Bluff Field Station, Wadmalaw Island,  SC  29487

                                   46

-------
     The purpose of this paper is to compile the scarce data presently
available for chlorine effects upon aquatic life relevant to estuarine
and marine ecosystems.  The chemistry of chlorine is briefly reviewed
to point out some of the unique features of chlorination in marine waters.
Although some data exist on the effects or residual chlorine and a limi-
ted number of by-products upon specific organisms, virtually no informa-
tion is available on transport processes, persistence, bioaccumulations
and the fate of halogenated compounds from chlorination processes.

                         CHEMISTRY OF CHLORINE

     Chlorine is presently manufactured by a variety of methods, including:
the electrolysis of brine,

     2NaCl + 2H20 + electnc current >  2NaOH + C12  + H2

the salt process,

     3NaCl + 4HN03 	" 3NaN03  + Cl2  + NOC1 + 2H20

and the hydrochloric acid oxidation process,

     4HC1 + 02 450"650°C > 2C12 + 2H20.

CHLORINE IN FRESHWATER SYSTEMS

     Chlorine gas dissolves rapidly in  water and hydrolyses,
     C12 + H20  <     • HOC1 + H  + Cl .

     This hydrolysis is nearly complete and only when the pH is  below 3.0,
or the chlorine concentration over 1000 mg/1  is there any measurable  quan-
tity of molecular chlorine present.  The oxidizing capacity of chlorine is
retained in the hydrolysis product, hypochlorous acid.   Hypochlorous  acid
dissociates to form,

                         HOC! *=r H+ + CIO".

This reaction is pH dependent.  For a neutral  pH (7.0)  at 20°C,  the equi-
librium is approximately 75 percent HOC! and 25 percent CIO".   For a  pH of
8.0, the reverse is true with approximately 25  percent HOC1 and  75 percent
C1(T (Sawyer and McCarty, 1969).

     The addition of hypochlorite salts  to water forms  hypochlorite ions
followed by hypochlorous acid,

                     Ca (C10)2 =  Ca   +2 Clo",
                      i
and                  H  + CIO"  «	  HOC1.

If ammonia or organic amines are  present in the water,  they will  react with
hypochlorous acid to form

                                    47

-------
chloramines,

     NHs + HOC1  = NH2C1  + H20.

     Like the ionization of hypochlorous acid to H + + CIO ~, the reaction
rate between ammonia and hypochlorous acid is pH dependent, occurring
most rapidly in solutions with  a pH of 8.3.   This reaction  is also depen-
dent upon temperature and the ratio of ammonia to hypochlorous acid.

     Monochloramines react with hypochlorous acid to form di- and tri-
chloramines,
and
     NH2C1 + HOC1 = NHC12 + H20,
     2NH2C1 + HOC1 = NCI 3 + H20.
Low pH favors a shift in eguilibrium toward the formation of di- and tri-
chloramines.  Fair et al.  (1948) determined that at pH 5.0, the ratio was
16 percent monochloramine and 84 percent dichloramine.  For a pH of 8.0,
the ratio was 85 percent monochloramine and 15 percent dichloramine.  Tri-
chloramine is found in significant quantities only at pH values of less
than 4 (McKee and Wolf, 1963).

     Ingols et al. (1953) determined that hypochlorous acid and monochlor-
amine in freshwater will react with various, organic constituents.  Some of
these reactions resulted in the formation of organic monochloramines al-
though none were persistent (Table 1).  The formation of chlorinated organic

     TABLE 1.  SUMMARY OF REACTIONS OF CHLORINE WITH ORGANIC
               COMPOUNDS IN FRESHWATER (MODIFIED FROM INGOLS
               ET AL. 1953)
 Organic Substrate
Hypochlorous Acid
    Monochloramine
Alanine

Cysteine

Glycylglycine

Glycylglycylglyci ne


Tyrosine

Hemi n
  Pyruvic Acid

  RS03H

  Oxidative

  Hydrolysis and
  Deaminization

  Ketone

  Violent Change
Organic Monochloramine

RSSR
Terminal Organic
Monochloramine

Organic Monochloramine

Irreversible Addition
or Oxidation
                                    48

-------
compounds during chlorination of sewage effluents and power plant cooling
waters has,firecently been documented (Jolley, 1973; Jolley et al.  1975).
Isotopic   Cl tracers and high-resolution anion-exchange chromatography
were used to separate over 50 chlorine containing constituents from chlor-
inated secondary effluents.  Seventeen of these were tentatively  identified
and quantified (Table 2).

     TABLE 2.  TENTATIVE IDENTIFICATIONS AND CONCENTRATIONS OF
               CHLORINE CONTAINING CONSTITUENTS FROM CHLORINATED
               SEWAGE EFFLUENTS (MODIFIED FROM JOLLEY, 1973)
             Identification                   Cone, of Organic
                                              Compound yg/1


     5-Chlorouracil                                  4.3
     5-Chlorouridine                                 1.7
     8-Chlorocaffeine                                1.7
     6-Chloroguanine                                 0.9
     8-Chloroxanthine                                1.5
     2-Chlorobenzoic Acid                            0.26
     5-Chlorosalicylic Acid                          0.24
     4-Chloromandelic Acid                           1.1
     2-Chlorophenol                                  1.7
     4-Chlorophenylacetic Acid                       0.38
     4-Chlorobenzoic Acid                            0.62
     4-Chlorophenol                                  0.69
     4-Chlororesorcinol                              1.2
     3-Chloro-4-Hydroxybenzoic Acid                  1.3
     4-Chloro-3-Methyl Phenol                        1.5


CHLORINE IN MARINE SYSTEMS

     Major sources of chlorine contamination in the marine environment are
related to postchlorination of secondary sewage effluents with outfalls
located on coastal and estuarine waters, and chlorination of seawater used
for cooling of thermal electric generating plants (White, 1972, 1973; Mar-
kowski, 1959).

     The addition of chlorine to seawater results in a complex series of
chemical reactions, the most obvious one frees bromine,

                      C12 + 2Br" = 2C1" + Br2.

This reaction goes to completion and is the basis for the manufacture of
bromine from seawater (Lewis, 1966).

     The industrial extraction of bromine from seawater requires that the
pH be reduced below 3.0, so that molecular chlorine can release molecular

                                    49

-------
bromine.  The hydrolysis products from adding chlorine to seawater, HOC!
and CIO , will also release bromine from the bromide ion in the form of
hypobromous acid and hypobromite ion,
                      CIO" + Br  = BrO  + Cl  ,
and
                      BrO" + H" i=" HOBr.

Houghton (1946) has also suggested that chlorination of water containing
free ammonia and bromine may result in the formation of bromamines.  Jo-
hanneson (1958) added chlorinated water to a sodium-ammonium salts solu-
tion buffered to pH 8.3.  This resulted in the  formation of monobromamine
and some monochloramine.  The addition of sodium hypochlorite solution
produced mostly monochloramine.  The hypochlorite in solution apparently
reacts with both the bromine and ammonia,

                      CIO" + Br" = BrO" + Cl",
and
                      CIO" + NH3 = NH2C1 + OH".

Injection of chlorine gas may result in localized acidity, favoring the
first reaction above, which is rapid at pH values of less than 8.0.  The
second reaction is favored when chlorine is added as sodium hypochlorite
since there is no accompnying reduction in the  normal pH of 8.0-8.3.

     When ammonia is present in seawater, it will react with hypobromous
acid to form monobromamine.  Monobromamine in turn will react with hypo-
bromite ion to form dibromamine,

                      NH3 + HOBr = NH2Br + H20,
and
                      NH2Br + BrO" = NHBr2 + OH".

     In addition, monobromamine at near neutral pH will form monobrom-
ammonium which dissociates into ammonium ion and free bromine (Johanneson,
1960).
                               ,+
                      NH9Br + H  *        NH-Br"1
and                     L                   6


     Block and Helz (1975) have prepared a reaction series model to illus-
trate the theoretical  degradation processes occurring after the addition
of chlorine to natural, saline waters (Figure 1).  Compounds in each suc-
cessive level can give rise to ones on a lower level.  In general, com-
pounds occurring on lower levels will not contribute to the formation of
those in the levels above.

     The reaction occurring between levels I and II is a result of chlorine
decay from a diatomic  gas to hypochlorous acid, hypochlorite ions and sodium
hypochlorite.  As pointed out by Moore (1951) and Lewis (1966), this reaction
occurs rapidly and goes to completion within seconds after the addition of
chlorine.   The inclusion of sodium hypochlorite within level II is based on
the results of work by Sugam and Helz (1975, unpublished manuscript).

                                   50

-------
  II
 III
  IV
                                                   Cl.
                                                   HOC1,  OC1", NaOCl etc.
                                                   NH2C1,  NHC12, NH2Br,

                                                   NHBr2,  BrO", HBrO
                                                   Organic chlorine and

                                                   bromine compounds
                                                   Cl",  Br"
      Figure 1.  Degradation processes for chlorine in saline waters
                 (modified from Block and Helz, in preparation)
      The  chemical  composition  and  abundance of products formed from level
 II  to level  III is a  function  of physical and chemical parameters of the
 water including but not  limited to temperature, pH, ammonia, and bromine,
 available as reaction components.  In seawater it is possible that the
 predominant  species would be bromamines, especially if NH.  ions are less
 abundant than Br"  ions.                                  4

      Level IV includes halogenated organic constituents which may be formed
 by  level II  or level  III species,  including chloramines, hypobromite and
 bromamines.  The stable end products in level V occur through a diverse
 group of mechanisms taking place in steps I-IV.
     Charge balance results in one atom of Cl passing from level I to le-
    V to each atom passing from level I to level II.  Reduction of hypo-
chlorite by Br~ or Fe^  and Mrr  may release Cl ~ from level II to level V.
Movement of Cl" from level III to level V can also occur in a number of
ways, the most obvious, suggested by Laubusch (1971), involves the des-
+ „,.„.•.,•	-c _ui	,•„„ ...u__ *i.- ""-      ratio is large.
vel
truction of chloramines when the
     Some of the chlorinated organics identified by Jolley
sistent and the decay from level IV to level V is probably
relative to decay from levels I through III to level V.
                                                           (1973)
                                                           a slow
are per-
process,
                                    51

-------
            TOXICITY OF CHLORINE IN ESTUARINE ENVIRONMENTS

     The relative toxicity of chlorine in water is related to the amount
and proportions of free and residual  chlorine.  Several  investigators have
found that free chlorine is generally more toxic to freshwater organisms
than chloramines (Douderoff and Katz, 1950; Merkens, 1958), even though
the toxicity of the various forms of chlorine were of the same order of
magnitude.  Rosenberger (1971)  and Basch and Truchan (1973), found that
dichloramine was more toxic than monochloramine in freshwater.  A com-
prehensive review paper by Brungs (1973) summarizes the  toxic effects of
residual chlorine on freshwater aquatic organisms.

     In seawater, Holland et al. (1960) determined that  dichloramine is
apparently more toxic than monochloramine and that the chloramines were
more toxic than free chlorine.   These findings may reflect the complex
chlorine-bromine reaction kinetics suggested by Johanneson (1958, 1960)
and Lewis (1966).

CHLORINE TOXICITY TO MARINE PHYTOPLANKTON

     The effects of chlorination and thermal pollution on phytoplankton
productivity have been investigated in some detail (Table 3).  Carpenter
et al.   (1972) observed an 83 percent decrease in the productivity of
phytoplankton passed through the cooling system of a nuclear generating
plant on Long Island Sound.

     TABLE 3.  SUMMARY OF TOXIC EFFECTS OF CHLORINATED
               WASTES AND WATER ON MARINE PHYTOPLANKTON.
Species
Phytoplankton
Chlamydomona
Skeletonema
costatum

Phytoplankton
Phytoplankton
Toxicant
used
C12 injection
hypochlorite
solution

hypochlorite
solution
Cl- injection
Measured
residual
chlorine
mg/1
0.05-0.40
0.69-12.9
0.18-2.4
0.32
0.01
0.075-0.25
—
Duration
of
Test
12 hrs +
4 hrs incu-
bation
5 min
5 min
2 min
45 min
24 hrs
15 min
Effect(s)
50-98% loss
Of productivity
Reduced growth
rate
None up to 0.29
mg/1 ; greater
amounts inhibit-
ed growth
55% decrease in
ATP
77% decrease in
ATP
50% decrease in
growth
91% reduction in
photosynthesis
Reference
Carpenter et
al. (1972)

Hirayama and
Hirano (1970)
Gentile et al .
unpublished da
(1972, 1973)
Hamilton et al
(1970)
                                    52

-------
     Intake water was chlorinated at a rate of 1.2 mg/1  with  a  residual
of 0.4 mg/1 measured at the discharge.  Addition of 0.1  mg/1  chlorine  at
the intake with nondetectable residuals at the outfall  decreased  produc-
tivity by 79 percent.  Essentially no decreases in productivity were ob-
served when phytoplankton passed through the cooling system without
addition of chlorine.  Hirayama and Hirano (1970)  measured the  effect  of
chlorination on the photosynthetic activity of Skeletonema costatum and
found that cells were killed when subjected to T.5 to 2.3 mg/1  chlorine
for 5 and 10 minutes.

     Gentile (1972, 1973 unpublished data, National  Marine Water  Quality
Laboratory, West Kingston, RI) observed a 55 percent decrease in  the ATP
content of marine phytoplankton exposed to 0.32 mg/1  residual chlorine
for two minutes and a 77 percent decrease after 45 minutes of exposure
to chlorine concentrations as low as 0.01 mg/1.  A 50 percent depression
in the growth rates of 10 species of marine phytoplankton exposed to
chlorine concentrations ranging from 0.075 to 0.25 mg/1  for 24  hours was
also measured.

     Morgan and Stress (1969) used photosynthetic  rates  to evaluate the
response of estuarine phytoplankton passed through the  cooling  system  of
a steam electric power station on the Patuxent River, Maryland.   The photo-
synthetic rate increased with an 8°C rise in temperature when ambient  wa-
ter temperatures were 16°C or less.  Inhibition occurred when ambient  tem-
peratures were above 20°C.  In a related study, conducted at  the  same  site,
Hamilton et al. (1970) measured a 91 percent decrease in primary  produc-
tivity during intermittent chlorination.

CHLORINE TOXICITY TO INVERTEBRATES

     Muchmore and Epel (1973) investigated the effects  of chlorination of
wastewater on fertilization in marine invertebrates  (Table 4).  Unchlor-
inated sewage (from the Pacific Grove, California  STP)  was a  weak inhibi-
tor of fertilization in the sea urchin, Strpnqylocentrotus purpuratus.
Exposure of gametes of the sea urchin to^a 10 percent unchlonnated
sewage-seawater mixture typically reduced fertilization success by 20  per-
cent.  A 0.5 percent dilution of moderately chlorinated sewage  (11 mg/1
TRC undiluted)  significantly reduced fertilization.   It was also  deter-
mined that chlorination had more effect on sperm cells  than on  eggs.   Eggs
incubated for 5 minutes in a 0.77 mg/1 hypochlorite  solution  and  subse-
quently washed to remove the hypochlorite showed no  reduction in  fertility.
Incubation of sperm at a 0.07 mg/1 hypochlorite concentration resulted in
a loss of fertilization ability.  This was attributed to a loss of sperm
motility which  was not restored after washing to remove the hypochlorite.
Gametes of the echiuroid, Urechis caupcu and sperm of the annelid worm,
Phragmatopoma caliform'ca, were not as sensitive to  chlorine  toxicity.

     A number of power plant related studies have  been  conducted  to deter-
mine the effect of chlorination of seawater on fouling  organisms. Waugh
(1964) observed no significant difference in the mortality of oyster lar-
vae, Ostrea edulis, exposed to 5 mg/1 chlorine for 3 minutes  at ambient
temperature, computed to control mortality.  Exposure of larvae to thermal
stress (10°C above ambient) and 10 mg/1 chlorine for 6  to 48  minutes also
had no significant effect on survival 64 hours after treatment.  Barnacle
                                    53

-------
nauplii, Eliminius modestus, showed more acute sensitivity to chlorine.
Residual chlorine concentrations in excess of 0.5 mg/1  caused heavy mor-
tality and reduced growth for survivors.

     TABLE 4.   SUMMARY OF TOXIC EFFECTS OF CHLORINATED
               WASTES AND WATER ON MARINE INVERTEBRATES
Species Toxicant
used
Stronaylo- chlorinated
centrus sewage effluents
purpuratus
(gametes)


Urechis
caupo
(gametes)

Phrogmatopoma
californica
(sperm)

Elminius residual
modestus chlorine

Melita Cl, injection
nitida i


Gammurus sp.


Bimaria
franciscana
Balanus sp.
Acartia tonsi
Anemones residual
chlorine



Mussels




Barnacles




My til us Cl,
edulis infection
Measured
residual
chlorine
mg/1
0.02
0.11

0.03
0.13

0.2

1.0

0.2

1.0

2.0

5.0
2.5



2.5



4.5
2.5
2.5
10.0


2.5
1.0
10.0


2.5
1.0
10.0


2.5
1.0
0.02
0.05
Duration
of
Test
5 min
5 min

5 min
5 min

5 min

5 min

5 min

5 min

10 min

3 min
5 min
3 hrs
48 hrs
96 hrs
3 hrs



4 days
5 min
5 min
1. 2, 4, 8
hrs/day for
10 days
8 days
15 days
1, 2, 4, 8
hrs/day for
10 days
5 days
15 days
1. 2, 4 hrs/
day for 10
days
4 days
7 days
A few hrs
Effect(s)
None
100% inhibition
of fertilization
None
99% inhibition
of fertilization
22% inhibition
of fertilization
100% inhibition
of fertilization
22% loss of
motility
86% loss of
motility
Death and inhib-
ited growth
None
None
27% mortality
72% mortality
97% mortality
25% mortality
96 hrs after
exposure

None
80% mortality
90% mortality
None


100% mortality
100% mortality
None


100" mortality
100% mortality
95-100% mortality


100% mortality
100X mortality
Detachment and
migration
Reference
Muchmore and
Epel (1973)












Waugh (1964)


McLean (1972,
1973)









Turner et al .
(1948)













James (1967)
                                   54

-------
     McClean  (1973) simulated the conditions encountered by marine organ-
isms passing  through a power plant on the Patuxent River, Maryland.  In-
take chTorination to 2.5 mg/1 residual, entrainment for approximately 3
minutes and sustained exposure to elevated temperatures for up to 3 hours
were used as  experimental parameters.  While barnacle larvae, Balanus sp.
and copepods, Acartia tonsi, were not affected by a 3 hour temperature
stress of 5.5 and 11°C above ambient; exposure to 2.5 mg/1 residual chlorine
for 5 minutes at ambient temperatures caused respective mortality rates of
80 and 90 percent.  The amphipod, Melita nitida, and the grass shrimp,
Palaemonetes  pugio, showed  a delayed death response after exposure to 2.5
mg/1 TRC for  5 minutes.  Near 100 percent mortality was observed for both
species 96 hours after exposure to the chlorine residual.  McLean (1972)
showed that established colonies of the euryhaline colonial hydroid, Bimeria
franciscana. were not greatly affected by 1 and 3 hours of exposure to
4.5 mg/1 TRC.

     Turner et al.  (1948) determined that continuous treatment of seawater
conduits with 0.25  mg/1 chlorine prevented fouling during a 90 day interval
when the flow velocity was  52 cm/second or less.  Intermittent treatment
with 10 mg/1  residual chlorine for 8 hours a day was ineffective in pre-
venting fouling by  anemones, mussels and barnacles.

     James (1967),  working  in Great Britain, observed that residual  chlor-
ine concentrations  of 0.02  and 0.05 mg/1 caused detachment and movement
of mussels in the direction of water flow through an aquarium with eventual
elimination of the  mussels.  He concluded that the most effective way to
prevent fouling by  mussels was not to kill, but to discourage settling in
cooling water systems by continuous low level chlorination.

     Markowski (1960) compared the occurrence of marine organisms on con-
crete slabs placed  in the intake and outfall canals of an electric gener-
ating plant.  Chlorine was  injected into the condensers of this plant for
two hours a day at  a concentration between 1 and 2.5 mg/1.  No vegetation
was observed  growing in the intake canal where dense animal populations
occurred (predominantly invertebrates, Coelenterata and Polyzoa).  The
outfall canal contained a prolific growth of algae, Enteromorpha sj^. but
fewer invertebrates.  Balanus improvisis, which was col 1 ected witFsome
regularity from the intake  canal was never observed in the outfall canal.
The mollusk,  Eubranchus sp. was more abundant on the intake slabs than in
the outfall.

CHLORINE TOXICITY TO ESTUARINE FISH

     Tsai (1968, 1970, 1975) has observed decreases in the abundance and
occurrence of brackish water fish species in certain areas of the Upper
and Little Patuxent Rivers  receiving chlorinated sewage effluent.  Tsai
suggests that chlorinated sewage effluent may also block the upstream mi-
gration of such semi-anadromous species as the white catfish and white
perch.  He attributed the "blocking effect" to chlorination products
rather than reduced dissolved oxygen or pH resulting from organic decom-
position of the effluent (Table 5).

     Tsai  (1973)  measured the diversity index of fish  upstream and downstream
of 98 sewage treatment plants in Virginia, Maryland and Pennsylvania.   Sewage
treatment plants  were categorized as  Type I engineering facilities (sludge

                                   55

-------
            TABLE 5.   SUMMARY  OF  TOXIC  EFFECTS OF CHLORINATED WASTES
                      AND  WATER ON  MARINE AND FRESHWATER FISHES
Species
Cyprlnus
carpi'o
eggs
(Freshwater)
Freshwater
and brackish
fishes

L. xanthurus
Morone sp.
Pomatomus
saltatrix
C. regal is
Brevoortia
tyrannus
L. xanthurus


0_. nerka
0. gorbuscha
^Freshwater)
£. gorbuscha
0. tshawytscha

Morone
americana
Menidia
menidia
F. hetero-
cli tus
Trinectes
macula tus
Pleuronectes
platessa
eggs
larvae

Toxicant
used
4-Chlororesor-
cinol
5-Chlorouracil
(0.001 mg/1)
chlorinated
sewage effluents


chlorinated
sewage effluents





sodium hypo-
chlori te

chlorinated
sewage effluents

residual
chlorine

residual
chlorine






free chlorine?




Measured
residual
chlorine
mg/1





0.6-2.0


0.07-0.28






0.09
0.14
0.28
0.02-0.026
0.16

0.5
0.5

0.08

0.08

0.03

0.03

0.04-0.08
0.70
0.12
0.032
0.026
Duration
of
Test
3-7 days




Long-term


May-June, 1973






96 hrs
24 hrs
6 hrs
24 hrs
72 hrs

80 min + 10°C
10 min + 10°C
thermal shock
10 m1n

10 min

10 min

10 min

8 days
72 hrs
96 hrs
48 hrs
96 hrs
Effect(s)
Reduced hatch




Decreased popn.
size and diver-
sity
Probable kill
5-10 million
fish




50% mortality
50% mortality
50% mortality
100% mortality
100% mortality

50% mortality
50% mortality

Avoidance.

Avoidance

Avoidance

Avoidance

None
50% mortality
50% mortality
50% mortality
50% mortality
Reference
Gehrs et al .
(1974)


Tsai (1968, 1970,
1973)


Virginia State
Water Control
Board (1974)




Virginia Inst.
Marine Science
for VSWCB (1974)
Servizi and
Martens (1974)

Stober and
Hanson (1974)

Meldrim et al.
(1974)






Alderson (1972)




activation, aeration,  sedimentation  and  filtration) with effluent  chlorina-
tion; Type II engineering facilities with  chlorination  and  an effluent hold-
ing lagoon and Type III  engineering  facilities with a lagoon and effluent
chlorination at the lagoon outlet.   Reductions in  the number of fish, num-
ber of species and the species  diversity index were significant downstream
of Type I and III  plants.  These  reductions were attributed to total residual
chlorine levels and turbidity.  Diversity  indices  showed no significant
changes in downstream  areas associated with Type II plants.

     Massive fish  kills  occurred  on  the  James River, Virginia during May-
June, 1973 (Virginia State Water  Control Board,  1974).  Species affected
by the kill included spot, Leiostomus  xanthurus; white  perch, Morone amer-
i cana; bluefish, Pomatomus saltatrix;  grey seatrout, Cynoscion regal is and
menhaden, Brevoortia tyran'nus.  A majority of the  fish  kill in the James
River occurred adjacent to sewage treatment plants.  Total  residual chlor-
ine (TRC) levels as high as 0.7 mg/1 were  observed in the James.   Effluents
from both plants showed more than 3.0  mg/1  TRC.

                                    56

-------
     Distress symptoms of fish dying included,  spiral  swimming patterns,
broken vertebral columns, listless floating,  inverted  swimming,  distension
of the air bladder in some, loose body scales,  mucous  on the  skin  and  hem-
orrhaging along the fins and body surface.

     Live box tests conducted adjacent to the James  River sewage treatment
plant (STP) demonstrated a correlation between  rates of effluent chlorina-
tion and mortality of juvenile spot and croaker.   With an average  daily
chlorine feed of 1200 pounds (total flow of water was  approximately  10 mgd
during tests) and a measured residual  chlorine  level of 3.0 mg/1,caged
fish suffered 100 percent mortality within  20 hours.   After a cutback  to
a chlorine feed rate of approximately  400 pounds  per day, only 20  percent
mortality was observed among caged fish after 20  hours.

     On-site aquaria tests confirmed the results  of the cage  tests.  Water
from an area adjacent to the outfall of the James River (STP)  was  pumped
through aquaria containing juvenile spot.  Mortalities ranged from 91  to
100 percent after 40-85 minutes of exposure prior to the cutback in  chlor-
ination.  After chlorination rates were reduced,  mortalities  were  0-26
percent after 120 minutes of exposure.

     Continuous flow laboratory bioassays were  also conducted.   The  96
hour LC§Q for juvenile spot was estimated at  0.09 mg/1 TRC.   The esti-
mated 24 hour LC5Q was 0.14 mg/1  and the 6  hour LC50,  0.28 mg/1  TRC.

     Separate field studies on the spot, Leiostomus xanthurus, found up
to 40 percent of juveniles from the 1973 year class exhibited deformities
in the vertebral column.  These abnormal forms  are identifiable  as a dis-
tinct year class in 1975 population samples from  the Chesapeake  Bay, (Chao
Labbish, personal communication).

     A study of the effect of chlorinated sewage  effluents on sockeye
salmon, Onchorhynchus nerka, and pink  salmon, 0_.  gorbuscha, has  been
conducted by Servi-zi and Martens  (1974).  They  used three study  sites  to
conduct cage bioassays.  The first, Site I, was adjacent to a primary
treatment plant with effluents chlorinated  following settling and.dis-
charged through a 600' pipe line directly into  the receiving  stream.
Site II was on a stream receiving wastes from an  activated sludge  plant
in which chlorinated effluents were discharged  into a  large effluent
holding lagoon and retained for 30 to  60 days.  Site  III was  located on
a stream receiving effluents which were chlorinated as they left a non-
aerated lagoon.

     Measured chlorine residuals  in the receiving stream at Site I ranged
from 0.02-0.26 mg/1.  These concentrations  resulted in 100 percent mor-
tality of caged sockeye fingerlings placed  30,  60 and  250 feet below the
effluent discharge point.  Additional  tests indicated  that the primary
effluent without chlorination was also toxic.  However, fish  exposed to
the unchlorinated effluent lived ten times  longer than ones exposed  when
effluents were being chlorinated.  Toxicity of  the unchlorinated effluents
was attributed to MBAS and ammonia.

     Tests at Site II indicated that chlorinated  effluents retained  for
30 to 60 days were not toxic to sockeye fingerlings  and alevins  and  pink
salmon alevins after 26 days of exposure.

                                    57

-------
     In tests at Site II, with fingerling sockeye salmon,  chlorinated
sewage effluents (measured TRC 0.85 mg/1) resulted in 50 percent mor-
tality after 48 minutes.   Fifty percent mortality occurred after 13
hours of exposure to the  unchlorinated effluents.  Sublethal  exposures
of fingerling sockeye salmon to the effluents from Site III (1-3 hours
of exposure to 0.22 mg/1  TRC) resulted in gill  damage, including  hyper-
pi asi a, swollen epithelial cells, and separation of epithelium from
pillar cells.

     The toxicity of chlorine and heat to pink, Oncorhynchus  gorbuscha,
and Chinook salmon, 0_. tshawytscha, has been determined by Stober and
Hanson (1974).  Juveniles of each species were  tested in seawater at five
residual chlorine concentrations, ranging from  0.05-1.0 mg/1, and four
temperatures from t 0-10°C.  Salmon were exposed to each matrix for 7.5-
60 minutes.  A decrease in the tolerance of both species to residual
chlorine was observed with increased temperature and exposure time.  The
most toxic effect was observed at a t of 9.9-10°C where the LT^Q (lethal
time for 50 percent mortality) ranged from approximately 10 minutes at
0.5 mg/1 TRC for chinooks to 80 minutes for pinks.

     Meldrim et al. (1974) in flowing water bioassays studied the effect
of chemical pollutants on estuarine organisms.   They found that white
perch, Morone americana,  consistently avoided TRC levels as low as 0.08
mg/1 at temperatures from 7-17°C.  Silversides, Menidia menidia, also
avoided 0.08 mg/1 TRC at  temperatures from 8-28°C but showed  a preference
for 0.08 mg/1 TRC when fish acclimated to 7°C were exposed at 12°C.  Mum-
mi chogs, FundijUjs he^terocjjjtus, and hog chokers, Trinectes maculatus,
avoided TRC  levels as low as 0.03 mg/1.

     Alderson (1972) found that the 48 and 96 hour Tlm of free chlorine
for plaice larvae, Pleuronectes platessa, was 0.032 and 0.026 mg/1 res-
pectively.  Eggs were not affected when exposed to 0.075 and  0.04 mg/1
free chlorine for 8 days, indicating that the egg membrane gives consider-
able protection over long periods.  The 72 and  192 hour Tlm for eggs was
0.7 and 0.12 mg/1 TRC respectively.

     Gehrs et al. (1974)  tested the sensitivity of carp eggs, Cyprinus
carpio, to two of the compounds identified by Jolley, 4-Chlororesorcinol
and 5-Chlorouracil.   Significant reductions in  the hatchability of non-
water hardened carp eggs  were observed in concentrations of each compound
as low as 0.001  mg/1.

     In California,  Young (1964) observed tumor-like sores around the
mouth of white croakers,  Genyonemus 1ineatus, collected near  the Hyperion
sewage outfall  in Santa Monica Bay.  While there was no direct evidence
to link the occurrence of lesions with chlorinated sewage  effluents, a
general decline  in fitness of croakers and other species found in close
proximity to the outfall  area was observed.
                                   58

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     eggs and larvae of plaice, Pleuronectes  platessa  L.  In:  Marine
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Basch, R.E. and J.6. Truchan.  1973.   Calculated  residual chlorine con-
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Block, R.M. and G.R. Helz.  1975.   Biological  and  chemical  implications
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Brungs, W.A.  1973.  Effects of residual  chlorine  on aquatic life.  Jour.
     Wat. Pollut. Contr. Fed. 45(10): 2180-2192.

Carpenter, E.J., B.B. Peck and S.J. Anderson.   1972.   Cooling water
     chlorination and productivity of entrained phytoplankton.  Marine
     Biology 16: 37-40.

Doudoroff, P. and M. Katz.  1950.   Critical review of  literature  on the
     toxicity of industrial wastes and their  components to  fish.  Sew.
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Fair, G.M., J.C. Morris, S.L. Chang,  I.  Weil,  and  R.P. Burden.  1948.
     Chlorine as a water disinfectant.   Jour.  Amer.  Water Works Assoc.
     40:  1051-1061.

Gehrs, C.W.,  L.D. Eyman, R.L. Jolley  and J.E.  Thompson.  1974.  Effects
     of stable chlorine-containing organics on aquatic environments.
     Nature 249:  675-676.

Gentile, J.H., J. Cardin, M.  Johnson  and  S. Sosnowski.  1972.  The effects
     of chlorine on the growth and survival of selected species of estuarine
     phytoplankton and zooplankton.  Unpublished  manuscript, National Marine
     Water Quality Laboratory, West Kingston,  RI.

Gentile, J.H., S. Cheer, and N. Lackie.   1973. The use of  ATP in the
     evaluation of entrainment.  Unpublished  data.   National Marine Water
     Quality Laboratory, West Kingston,  RI.

Hamilton, D.H., D.A. Flemer,  C.V.  Keefe,  and  J.A.  Mihursky.  1970.
     Power plants:  Effects of chlorination on estuarine primary  productivity.
     Science 169:  197-198.

Hirayama, K.  and R.  Hirano.  1970.  Influence  of  high  temperature and
     residual chlorine on marine phytoplankton.   Marine Biology 7: 205-213.
                                    59

-------
Holland, G.A., J.E. Lasater, E.D. Neumann, and W.E. Eldridge.   1964.
     Toxic effects of organic and inorganic pollutants on young salmon
     and trout.  State of Washington, Dept. of Fish Res. Bull.  No.  5,
     264 p.

Houghton, G.U.  1946.  The bromine content of underground waters.  Part
     II:   Observations on the chlorination of water containing free
     "ammonia and naturally occurring bromide.  Jour. Soc. of Chemical
     Industry  65:  324-328.

 Ingols, R.S.,  H.A. Wyckoff, T.W. Kethley, H.W. Hodgen, E.L. Fincher,
     J.C. Hildebrand, and J.E. Mandel.   1953.  Bactericidal studies of
     chlorine.  Industrial and Engineering Chemistry 45: 995-1000.

 James, W.G.  1967.  Mussel fouling and use of exomotive chlorination.
     Chem. and Ind.  24: 994-996.

 Johanneson, J.K.   1958.  The determination of monobromamine and mono-
     chloramine in water.  Analyst 83:  155-159.

 Johanneson, J.K.   1960.  Bromination of Swimming Pools.  Am. Jour.
     Publ. Health  50: 1731.

 Jolley, R.L.   1973.  Chlorination effects on organic constituents in
     effluents from domestic sanitary sewage treatment plants.   Ph.D.
     Dissertation, Univ. of Tennessee.   339 p.

Jolley, R.L.,  C.W. Gehrs, and W.W. Pitt.  1975.  Chlorination  of cooling
     water:  A source of environmentally significant chlorine-containing
     organic compounds.  Proceeding of the 4th National Symposium on
     Radioecology, Con/all is, Oregon.

Laubusch, E.J.  1971.  Chlorination and other disinfection processes.
     In:  Water Quality and Treatment.    Am. Water Works Assoc.  654 p.

Lewis, B.G.  1966.  Chlorination and muscle control.  I_.  The  Chemistry
     of chlorinated seawater.  A review of the literature.  Central
     Electric  Res. Lab., Lab. Note No.  RD/L/N/106/66.

Markowski, S.   1959.  The cooling water of power stations:  A  new factor
     in the environment of marine and freshwater invertebrates.  Jour.
     Animal Ecol.  28: 243-258.

Markowski, S.   1960.  Observations on the response of some benthonic
     organisms to power station cooling water.  Jour. Animal Ecol.
     29:  349-357.

McKee,  J.E.,  and H.W. Wolf.  1963.  Water Quality Criteria. 2nd Ed.,
     Publ. 3A, Calif. State Water Quality Control  Board, Sacramento.  548 p,

McLean, R.I.   1972.  Chlorine tolerance of the  colonial  hydroid, Bimeria
     franciscana.   Chesapeake Sci. 13:  229-230.

                                    60

-------
McLean, R.I.  1973.  Chlorine and temperature stress  in estuarine  in-
     vertebrates.  Jour. Wat. Pollut.  Contr.  Fed.  45:  837-841.

Meldrim, J.W., J.J. Gift, and B.R. Petrosky.   1974.   The effect  of
     temperature and chemical pollutants on the behavior of several
     estuarine organisms.  Icthyological Assoc. Inc.  Bull.  No. 11:1-129.

Merkens, J.C.  1958.  Studies on the toxicity of chlorine and chloramines
     to the rainbow trout.  Water and Waste Treatment Jour.  7:150-151.

Moore, E.W.  1951.  Fundamentals of chlorination of sewage  and wastes.
     Water and Sewage Works  98:  130-136.

Morgan, R.P., and R.G. Stress.  1969.   Destruction of phytoplankton  in
     the cooling water supply of a steam electric station.   Chesapeake
     Sci. 10: 165-171.

Muchmore, D., and D. Epel.  1973.  The effects of chlorination of  waste-
     water on fertilization in some marine  invertebrates.  Marine  Biology
     19: 93-95.

Rosenberger, D.R.  1971.  The calculation of acute toxicity of free  chlorine
     and chloramine to coho salmon by multiple regression analysis.  Thesis,
     Michigan State Univ., East Lansing, Michigan.

Sawyers, C.N., and P.L. McCarty.  1969.  Chemistry for Sanitary  Engineers.
     2nd Ed., McGraw-Hill, New York.

Servizi, J.A., and D.W. Martens.  1974.  Preliminary  survey of toxicity
     of chlorinated sewage to sockeye and pink salmon.   Pacific  Salmon
     Fisheries Comm. Progress Report No. 30:  1-42.

Stober, Q.J., and C.H. Hanson.  1974.   Toxicity of chlorine and  heat to
     pink, Onchrhynchus gorbuscha and Chinook salmon,  0_.  tshawytscha.
     Trans. Amer. Fish. Soc.  103 (3):  569-576.

Sugam, R., and G.R. Helz.  1975.  Apparent  ionization  constant of  hypo-
     chlorous acid in seawater.   Unpublished manuscript,  Univ. of  Maryland,
     College Park, Maryland.

Tsai, C.  1968.  Effects of chlorinated sewage effluents  on fishes in
     upper Patuxent River, Maryland.  Chesapeake Sci.  9(2):  83-93.

Tsai, C.  1970.  Changes in fish populations  and migrations  in relation
     to increased sewage pollution in Little  Patuxent River,  Maryland.
     Chesapeake Sci. 11(1): 34-41.

Tsai, C.  1973.  Water quality and fish life  below sewage outfalls.
     Trans. Amer. Fish. Soc.  102(2): 281-292.

Tsai, C.  1975.  Effects of sewage treatment  plant effluents  on  fish:
     A review of the literature.  Chesapeake  Research  Consortium.
     Publ.  No. 36: 1-229.

                                   61

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Turner, H.J., D.M. Reynolds, and A.C. Redfield.  1948.  Chlorine and
     sodium pentachlorophenate as fouling preventives in seawater
     conduits.  Indus, and Engin. Chem. 40: 450-453.

Virginia State Water Control Board.   1974.  James River Fish Kill 73-025.
     Bureau of Surveillance and Field Studies, Division of Ecological
     Studies.  61  p.

Waugh, G.D. 1964.   Observations on the effects of chlorine on the larvae
     of oysters, Ostrea edulij^ L., and barnacles, Eliminius modestus,
     Darwin.  Ann. Appl.  Biol. 54: 423-440.

White, G.C.  1972.  Handbook of Chlorination.    Van Nostrand Rheinhold
     Co.  New York 744 p.

White, G.C.  1973.  Disinfection practices in  the San Francisco Bay Area.
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     Calif. Fish and Game 50(1): 33-41.
                                    62

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               Techniques to Assess the Effects of
              Toxic Organics on Marine Organisms

                           David  J.  Hansen*


                              ABSTRACT

          Acute static or flow-through bioassays generally
          have been used to set marine water quality stan-
          dards, but few new bioassay techniques are avail-
          able to determine long-term effects of one or more
          toxicants on survival,  growth and  reproduction of
          individual species of mollusks,  arthropods or fish
          and on communities of estuarine  organisms.  Not
          only has the duration of bioassays increased from
          96 hours or less to periods of from one month to
          two years, but the complexity has  increased as well.
          Effects of toxicants on the entire life-cycle of an
          oviparous estuarine fish,  Cyprinodon variegatus, can
          now be studied; one bioassay with  endrin has been
          completed.  This fish typically  develops from an
          embryo to maturity in 10 weeks,  with about 70% sur-
          vival overall.  Females produce  an average of eight
          eggs per day and fertilization success exceeds^0%.
          Effects of a polychlorinated biphenyl, Aroclor^l254,
          and a pesticide, toxaphene, on developing communities
          of estuarine animals have  been investigated.  These
          studies provide data for prediction of pollution-
          induced shifts in composition of estuarine animal
          communities.

                             INTRODUCTION
     Bioassays are probably  the  most  useful technique available to the
biologist for predicting the potential  hazard of a chemical.  Bioassays
vary considerably in complexity  and utility and each procedure has its
own particular advantages and disadvantages.  They range from relatively
simple acute static and  flow-through  bioassays, to complex chronic entire
life cycle and community bioassays.   Flow-through acute bioassays usually
provide a more sensitive measure of stress than do static bioassays whereas
entire life cycle and community  bioassays provide a better estimate of
"safe" concentrations from which water  quality criteria can be derived.
*Environmental  Research Laboratory,  U.S.  Environmental Protection Agency,
Gulf Breeze, FL  32561
                                  63

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     In spite of the importance of developing sound marine water quality
criteria to protect aquatic life, the quantity and quality of sound re-
search aimed at evaluating effects is limited.  Results of a recent sur-
vey conducted by the Water Quality Committee of the American Fisheries
Society indicated that the funds and manpower spend on research to develop
water quality criteria were comparatively small and that bioassays were
of short duration and predominantly used freshwater fishes.  The Committee
on Water Quality Criteria of the National Research Council summarized
marine bioassay data for a total of 70 organic chemicals in Table 6, pages
484 to 508 of the Blue Book, 1972 (NAS-NAE Committee on Water Quality
Criteria, 1972).  A summary of this appendix (Table 1) helps to quantify
the findings of the American Fisheries Society Committee.  All of the 317
experiments with phytoplanters were static tests.  Of the 332 experiments
with estuarine animals only 12 percent were flowing water bioassays, only
16 percent included statistical treatment and few received chemical analyses
to determine the actual concentration of the chemical in the test water.
Significantly, less than two percent of all of these bioassays upon which
water quality criteria may be recommended were dynamic tests lasting longer
than 96 hours and no tests were on a complete life cycle of an animal or
on communities of organisms.

     TABLE 1.  BIOASSAY METHODS USED TO OBTAIN TOXICITY DATA
               ON THE EFFECTS OF ORGANIC CHEMICALS ON MARINE
               ORGANISMS AS REPORTED IN APPENDIX III, TABLE 6,
               P. 484-590 OF "WATER QUALITY CRITERIA," 1972 -
               THE BLUE BOOK
 Organism
Totals
          Kinds  and Numbers  of  Bioassays
                       Static
              <96 hrs.
327
                                      Dynami c
              <96  hrs.
            <96 hrs.
                    <96 hrs.
Plants
An i ma 1 s
37
290
280
53
0
29
0
13
333
29
13
     The purpose of this paper is to describe some recent improvements in
bioassay procedures used at the Gulf Breeze Environmental Research Labor-
atory  (GBERL) to test the effect of toxicants on estuarine animals.  These
are:   (1) improved techniques for conducting constant-temperature and-
salinity acute bioassays in which the concentration of the toxicant is
measured and the data are treated statistically;  (2) in-house and extra-
mural  bioassays on sensitive larval stages of crabs and shrimp;  (3) de-
velopment of methods to bioassay a portion, or the entire life cycle, of
grass  shrimp (Palaemonetes pugio) and the sheepshead minnow (Cyprinodon
variegatus) and" (4)development of methods to assess the effects of
toxicants on entire communities of benthic macroinvertebrates.
                                    64

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                             CONCLUSIONS


1.  Acute 96-hour flow-through bioassays should be conducted using uni-
    form methods on representative species from several phyla of estuarine
    organisms.  Use of uniform methods with appropriate statistical and
    chemical analyses makes comparisons between tests reliable.  Recent
    acute bioassays indicate that previous tests have underestimated acute
    toxicities of many organic chemicals.

2.  In addition to acute bioassays, information is needed on the effects
    of chemicals on sensitive life-stages and entire life-cycles of es-
    tuarine organisms, as well as on communities of organisms, in order
    to set sound water quality criteria.  Some methods necessary to con-
    duct these experiments are available and additional procedures are
    presently being developed.

                         BIOASSAY TECHNIQUES

ACUTE BIOASSAYS

     Acute toxicity experiments are usually conducted to determine the
quantity of chemical that will adversely affect a certain percentage of
the test organisms in a short period of time.  This information is.used
to make comparisons of relative toxicity and relative sensitivity.' Com-
parisons become most reliable if bioassay methods are uniform and the
tests are conducted to obtain statistically valid data supported by chem-
ical analyses of the test water.  Data from this type of bioassay, al-
though more difficult and costly to obtain than data from simpler screening
tests, are required by EPA because of the Agency's regulatory responsibilities

     Acute bioassay methods used at 6BERL have changed since joining EPA.
When our laboratory was part of the Bureau of Commercial Fisheries, Jack I.
Lowe was in charge of the acute bioassays.  From 1963 to 1972 he conducted
flow-through bioassays that usually lasted 48 hours on over 200 chemicals
on oysters, penaeid shrimp, fishes and occasionally crabs.  His data were
used to help in pesticide registration and to develop label restrictions.
Acute flow-through bioassays are now being repeated on some of these chem-
icals to provide 96-hour LC50 data backed by statistical and chemical
analyses.  The results of recent experiments continue to show that panaeid
shrimp are usually more sensitive to the chemicals tested than oysters,
grass shrimp or estuarine fishes (Table 2).  The acute toxicity of these
chemicals, except methoxychlor, in our tests exceeded that of acute bio-
assays published in the Blue Book (NAS-NAE Committee on Water Quality
Criteria, 1972).

     Recent acute bioassays have been conducted using water of constant
temperature and salinity to improve comparisons of the results of these
tests.  Bioassays of DDT, heptachlor (99%), heptachlor epoxide, lindane
and methoxychlor in Table 2 were all conducted at 2.5°C and 20 °/oo salinity.
The salinity was controlled by an inexpensive device in which appropriate
amounts of fresh and saltwater were added through solenoid valves that were
controlled electrically by a photocell  that sensed changes in water density
detected by a floating hydrometer (Bahner and Nimmo, 1975a).  This device
has been used successfully for periods of up to 9 months to maintain con-
stant (±1 °/oo) salinity in bioassays.
                                    65

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     TABLE 2.  NINETY-SIX HOUR LCSO'S AND 95% CONFIDENCE INTERVALS
               FOR THE SPECIES OF ESTUARINE ORGANISM MOST SENSITIVE
               TO SELECTED ORGANIC CHEMICALS IN FLOW-THROUGH BIO-
               ASSAYS.  USUALLY THE AMERICAN OYSTER, TWO FISHES AND
               TWO ARTHROPODS WERE TESTED.  CONCENTRATIONS IN WATER
               WERE MEASURED BY ELECTRON-CAPTURE GAS CHROMATOGRAPHY
CHEMICAL
Chlordane
DDT*
Dieldrin
Endrin
HCB
Heptachlor
(74%)
Heptachlor
(99%)*
Heptachlor
Epoxide*
Lindane*
Methoxychlor*
Toxaphene
SENSITIVE
SPECIES
Pink Shrimp
Brown Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pink Shrimp
Pinfish
96 HOUR
LC50 (yg/1)
0.4(0.3-0.6)
0.1(0.1-0.2)
0.7(0.4-1.2)
0.04(.02-.05)
>25
0.1(0.07-0.1)
0.03(0.02-0.04)
0.04(0.001-0.1)
0.2(0.1-0.2)
3.5(2.8-4.4)
0.6(0.5-0.7)
REFERENCE
Parrish et^ al_. ,
Schimmel e_t al . ,
Parrish et aj . ,
Schimmel e_t aj_. ,
Parrish et al . ,
Schimmel ejt aj_. ,
ii
n
ii
Bahner and Nimmo
Schimmel ejt al_. ,

1975
unpubl .**
1973
I974a
1974
unpubl .**
n
n
M
, 19755
unpubl -**
 *Less than five species of estuarine animals tested.

**Steven C. Schimmel, Gulf Breeze Environmental  Research Laboratory, Gulf
  Breeze, Florida 32561

SENSITIVE LIFE STAGE BIOASSAYS AND ENTIRE LIFE CYCLE BIOASSAYS

     Chronic bioassays on sensitive life stages  and on entire life-cycles
of estuarine organisms are usually conducted to  determine the quantity of
chemical that can be tolerated by an organism throughout its  life or during
a critical portion of its life.  Data from this  type of bioassay are es-
pecially important in deriving water quality criteria.  Water quality
criteria are most frequently obtained by multiplying the 96-hour LC50 of
the most sensitive species tested by an arbitrary application factor, to
protect that species--and hopefully, the ecosystem-- from chronic effects
of a pollutant.  The arbitrary application factor for persistent pollutants

                                    66

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is usually about 0.01 (NAS-NAE Committee on Water Quality Criteria, 1972).
Scientifically derived application factors can be obtained by comparing
data from acute bioassays and bioassays in which a fish or invertebrate
is exposed to the chemical throughout its entire life cycle.  The factor
is obtained by dividing the concentration not affecting survival, growth
or reproduction in entire-life-cycle bioassays by the 96 hour LC50 for
that species (Mount and Stephan, 1967; Eaton, 1973).

Sensitive Life Stage Bioassays

     Marine toxicologists have not been able to experimentally derive
application factors based on exposures throughout a marine animal's life
cycle because techniques for maintaining cultures throughout entire life
cycles were lacking.  Therefore, it is necessary to develop and use meth-
ods that provide toxicity data on sensitive stages of the life-cycle of
saltwater species.  Our laboratory has funded grants or contracts to look
at the effects of pesticides on larval development of dungeness crabs,
Cancer magister; blue crabs, Cal1i nectes sapi dus; and a mud crab, Rhithro-
panopeus harrisii.  Chemicals that are being or have been investigated in-
clude captan, carbofuran, chlordane, DEF, malathion, methoxychlor, mirex,
propanil, trifluralin, 2,4-D and juvenile hormones.  We also supported
research on the effects of methoxychlor and mirex on embryo, larval, ju-
venile and adult striped mullet, Mugil cephalus (Lee et al., 1975).
                                  i
     Research on sensitive stages of estuarine organisms at GBERL is pri-
marily on larval and postlarval grass shrimp (Palaemonetes pugijj). and
embryos and fry of the fishes Cypri nodon yari eqatus. Fundulus si mil is, £_.
heteroclitus, Leiqstomus xanthurus, Menidia menidi a and Morone saxatilis.
Recently published papers on this research irTcTude"those of Hansen et al.,
(1975), Middaugh et al.,  (1975), Parrish et al. (1975) and Schimmel et al.
(1974a, b).  This research has primarily been on the effects of toxicants
in water on development and survival of early life-stages.  Recent research
(Hansen et al., 1973) on the effects of a PCB, Aroclor 1254 in the eggs of
the sheepshead minnow, C. van'eqatus, indicated that certain concentrations
of PCB in eggs are lethal to embryos and fry (Figure 1).  If this PCB af-
fects other fishes similarly, residues exceeding 5 parts per million in
eggs would decrease survival of fry.

Entire Life Cycle Bioassays--
     Chronic, entire life-cycle bioassays are routinely conducted by fresh-
water toxicologists, but saltwater toxicologists have only recently developed
similar procedures.  Freshwater chronic bioassays can be conducted with blue-
gills (Lepomis macrochirus), fathead minnows (Pimephales promelas), brook
trout (Salvelinus fontinaTis), water fleas (Daphm'a magnaj and other fishes
and invertebrates (Eaton, 1973).

     Chronic bioassays using the estuarine fish Cyprinodon yariegatus are
possible (Schimmel and Hansen, 1974).  This oviparous fish develops from
an embryo to maturity in about 10 weeks, with about 70% survival  overall.
The fish spawns readily in an aquarium, producing about 8 eggs per day
(Figure 2).  Total egg production seems unrelated to fish size but fre-
quency of spawning and egg fertility appear to be size-dependent  (Schimmel
and Hansen, 1974).  Females begin producing eggs at 27 mm standard length.
                                    67

-------
1OO
 50%
HATCH
                        AROCLOR  1254  IN

                        EGGS (jug/g)
      EMBRYOS
    Figure 1.  Effect of Arocloi®1254 in eggs of sheepshead
             minnows on the survival of embryos and fry.
                        68

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In one experiment,  19 fish  less  than  35  mm  long  produced an average of
8.2 eggs per day, and 15 fish  35 mm and  longer averaged 7.8 eggs per day.
The smaller fish produced eggs more consistently (50% of the days vs. 31%)
with greater fertility (94% fertility  vs. 79%) than the larger fish.  As a
result of this and other information,  a  tentative method for entire life-
cycle bioassays using this  fish  has been suggested  (Hansen and Schimmel,
1975).  Recently, sheepshead minnows were exposed to endrin and to hepta-
chlor to determine the effect  of these pesticides on reproduction.

     Sheepshead minnows were exposed to  0.025, 0.077, 0.12, 0.31 or 0.77 yg/1
of endrin measured in water during  an  entire  life cycle bioassay that lasted
25 weeks.  This bioassay consisted  of  three parts:  (1) the exposure began
with embryos and continued  through  embryonic  development, hatching of fry and
growth of the fry to adulthood;   (2) continued exposure of adult fish to moni-
tor spawning success, including  egg production and fertility; and  (3)  the
bioassay ended following a  28-day exposure of embryos and fry obtained  from
spawning fish.  The apparatus  used  was that of Schimmel et al., (1974b) and
the methods were similar to those of Hansen and  Schimmel~Tl9T5).
      6O
      so
   y  40
   O
  w  30
  >-
  u
  Z
  Ul
  D  20
  O
       1O
                                         AVERAGE NUMBER =8.O
                       1-10     11-20     21-30    31-40    41-50

                    NUMBER  OF  EGGS  PER  DAY
          Figure  2.  Number of eggs spawned by breeding pairs of
                    sheepshead minnows (Cyprinodon variegatus).
                                   69

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     Sheepshead minnows were affected by endrin in this entire life cycle
bioassay (Table 3).  Embryos in 0.31 and 0.72 yg/i of endrin hatched sooner
than embryos in water free of endrin.  Fry in 0.72 yg/i began to die one
day after hatching and all were dead by day 9.  Fry in 0.31 yg/l began to
die two days after hatching and over half were dead by day 12.  Survival of
juvenile fish was unaffected.  Survival of spawning females was reduced in
0.31 yg/1 and their eggs were less fertile than were those of control females,
Survival of fry from eggs spawned by fish exposed throughout their life to
0.31 yg/1 - and possibly 0.12 yg/1 - was decreased.

     TABLE 3.  EFFECTS OF ENDRIN ON SHEEPSHEAD MINNOWS (CYPRINODON
               VARIEGATUS) EXPOSED THROUGHOUT THEIR ENTIRE LIFE-
               CYCLE.CONCENTRATIONS OF EXPOSURE WERE:  CONTROL,
               0.025, 0.077, 0.12, 0.31 and 0.72 yg/1
Generation Life Stage
F- Embryo
Fry

Juveniles
Effect Concentration, yg/1
Early hatching
Death
Decreased growth
No effect
0.31, 0.72
0.31, 0.72
0.31

                Adults
Death of spawning



F2




Embryos and
fry
females
Decreased fertility
of eggs

Death
0.31

0.31

0.31
     The effects of technical heptachlor on reproduction and development of
Cyprinodon variegatus was studied in a similar experiment, except that it
began with juvenile fish rather than embryos.  Measured concentrations of
exposure were 0.71, 0.97, 1.9, 2.8 and 5.7 yg/l  of technical heptachlor
(heptachlor and trans-chlordane) and a control.   In the first four weeks
of the experiment, some juvenile fish died in 2.8 and 5.7 yg/i  of technical
heptachlor.  Thereafter, few fish died until the reproductive portion of
the experiment began at week 8.  Heptachlor also affected reproduction by
reducing number of spawnings, number of eggs, fertility of the eggs and
survival of fry from fertile eggs.

     Experiments are being conducted to determine techniques required to
conduct entire life-cycle bioassays  with the grass shrimp (Palaemonetes
pugio).  The effect of light and temperature on  initiation and success of
spawning has been investigated.  Larval and postlarval  shrimp have been
used in bioassays to determine effects of certain PCB's on larval develop-
ment and metamorphosis.  Results indicate that grass shrimp will  spawn
readily, larvae will develop successfully, the species  will  be sensitive
to toxic chemicals and, therefore, would be excellent for entire  life-cycle
bioassays.
                                    70

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COMMUNITY BIOASSAYS

     Bioassays can be used to predict how communities  of estuarine organisms
will respond to a toxicant.  Bioassays in which only one species  or organism
is exposed to a chemical can be used to predict how a  community may respond
if a number of species from various phyla have been tested under  similar con-
ditions.  Predictions from this type of data are questionable,  particularly if
little is known about how species interact in the community.   Predictions can
also be made using data obtained from field studies, but these  predictions may
also be questioned because of problems with inadequate controls and lack of
replication.  An alternative approach is to conduct laboratory  studies  in
which communities of organisms are exposed to a chemical and  effects  deter-
mined.  This approach can be valuable if laboratory communities resemble ones
in the field and if enough replicates and concentrations are  used so  that
statistical analyses can be made and trends observed.

     I have completed two bioassays to determine the effects  of Aroclo 1^1254,
a polychlorinated biphenyl (PCB), and toxaphene, an insecticide,  on the devel-
opment of estuarine communities.  The numbers, species and diversity  of ani-
mals that grew from planktonic larvae in contaminated  aquaria were compared
with those that grew in identical aquaria that were not contaminated.   In each
bioassay, sea water with its natural complement of plankton flowed into each
of 10 replicate sand-filled aquaria for each of three  toxicant  concentrations
and a control.  Planktonic larvae colonized the sand and walls  of each  aquar-
ium.  At the end of the experiments—4 months for the  PCB, 3  months for toxa-
phene--organisms were collected in a Imm-mesh sieve, preserved  and later
identified.

     Aroclor(B)l254 altered the composition of communities of  estuarine  ani-
mals that developed from planktonic larvae in salt water that flowed  through
10 aquaria contaminated with 1 or 10 yg/1 (Hansen, 1974).  Communities  that
developed in 10 control  aquaria and 10 aquaria that received  0.1  yg/1,  of PCB
for four months were dominated (>75%) by arthropods, primarily  the amphipod
Corophiurn yolutator (Figure 3).  In aquaria receiving  1  and 10  yg/1 , the num-
ber of arthropods decreased and the number of chordates, primarily the  tunicate,
Molgula manhattensis, increased; over 75% of the animals in 10  yg/1 aquaria
were tunicates.Numbers of phyla, species, and individuals (particularly
amphipods, bryozoans, crabs, and mollusks) were decreased by  the  presence of
this PCB, but there was  no apparent effect on the abundance of  annelids,
brachipods, coelenterates, echinoderms or nemerteans (Table 43.   The  Shannon-
Weaver index of species  diversity was not altered by Aroc1orCvl254.
     TABLE 4.  EFFECT OF AROCLOR®1254 ON THE NUMBER OF PHYLA,
               SPECIES AND INDIVIDUALS AND ON THE SHANNON-WEAVER
               INDEX OF SPECIES DIVERSITY IN COMMUNITIES OF ES-
               TUARINE ORGANISMS THAT DEVELOPED IN SAND-FILLED
               AQUARIA IN A 4 MONTH BIOASSAY

                                    	  Aroclor®1254  (,.9/1)	
                         Control       0.1             1                10
Phyla
Species
Individuals
Species diversity
9
52
1776
1.82
7
34
2043
1.26
7
43
1421
2.21
5*
25*
657
1.70
*Statistically different from controls,  cc =  0.05.
                                    71

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                          AROCLOR   1254
10O
    CONTROL
                                   (MSI/I)
1O.O
    Figure 3.  Effect of Aroclor® 1254 on the structure of communities of estuarine organisms

-------
     In a similar experiment, the insecticide toxaphene also altered the
structure of communities that developed in sand-filled aquaria.   Concen-
trations of exposure were 0.1, 1  and 10 yQ/1.  The number of mollusks
(primarily gastropods) tripled, annelids [primarily capitellids)  doubled
and arthropods were almost eliminated in aquaria contaminated by  10  yg/1
of toxaphene (Table 5).   Similar numbers of pelecypods were  found in all
aquaria, however, the height (distance from hinge to distal  valve edge)
of Morton's cockles (Laevicardium mortoni) was significantly reduced by
10 yg/1 of the insecticide (Figure 4).

     TABLE 5.   AVERAGE NUMBER OF ANIMALS IN 10 CONTROL AQUARIA
               AND 10 AQUARIA THAT FOR THREE MONTHS RECEIVED
               0.1, 1 OR 10 ug/1  OF TOXAPHENE.  RANGE IN PARAN-
               THESIS
                                                Toxaphene
  Phylum           Control               0.1            1.0             10.


Mollusca        124(65-146)         170(98-274)     142(65-237)    373(245-489)

Annelida         56(19-97)            62(33-90)       66(31-126)    110(82-182)

Arthropoda       32(2-257)           155(1-523)        9(1-63)       0.4(0-1)

Coelenterata      3(0-21)             3(0-19)        10(0-44)

Other             0.1(0-1)             0.1(0-1)
                                   73

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    40
     20
ui
Q.
z
111
D
o
     40
     20
            EFFECT  OF  TOXAPHENE  ON  HEIGHT
                            OF COCKLES
            CONTROL
            N=437
             1.0 MO/ I
             N = 467
  0-1 MO/1
  N = 554
            10.0
            N = 431
          04   8   12   16  20
04   8   12  16  20
                        HEIGHT    (MILLIMETERS)

      Figure 4.  Effect of toxaphene on the height (distance from hinge to
               distal edge of valve) of Morton's cockles collected  from
               a community of estuarine organisms.
                        40
                        20
                        40
                        20
                                74

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                              REFERENCES


Bahner, Lowell H. and Del Wayne R. Nimmo.  I975a.   A salinity controller
     for flow-through bioassay.  Trans. Am. Fish.  Soc.  (In press).

Bahner, Lowell H. and Del Wayne R. Nimmo.  1975b.   Methods to assess  com-
     binations of toxicants, salinity and temperature on estuarine  animals.
     Proc. 9th Annu. Conf. on Trace Substances in  Environ. Health,  Columbia,
     Missouri, June 10-12, 1975.  (In press).

Eaton, John G.  1973.  Recent development in the use of laboratory  bioassays
     to determine "safe" levels of toxicants for fish.   In Bioassay Tech-
     niques and Environmental Chemistry.  Glass, Gary E.H["Ed.).   Ann  Arbor
     Science Publishers, Inc.  Ann Arbor, Mich.  48106.

Hansen. David J., Steven C. Schimmel  and Jerrold Forester.  1973.   Aroclor^
     1254 in eggs of sheepshead minnows:  Effect on fertilization success
     and survival of embryos and fry.  Proc. 27th  Ann.  Conf.  S.E. Assoc.
     Game Fish. Corrni.  1973.  p. 420-426.
Hansen, David J.  1974.  Aroclor^'1254:  Effect on composition of developing
     estuarine animal communities in the laboratory.   Contrib. Mar.  Sci .
     18:  19-33.

Hansen, David J. and Steven C. Schimmel.  1975.  Entire life-cycle bioassay
     using sheepshead minnows (Cyprinodon variegatus).   Fed.  Regis-.  40 (123),
     part II:  26904-26905.
Hansen, David J^and Steven C. Schimmel  and Jerrold Forester.   1975.   Effect
     of Aroclor(B)l016 on embryo, fry, juvenile and adult sheepshead minnow
     ( Cypri nodon van' egatus ) .   Trans. Am. Fish.  Soc.  (In press).

Lee, Jong H., Colen E. Nash and Joseph R. Sylvester.   1975.   Effects  of
     mirex and methoxychlor on striped mullet, Mugi 1  cephalus  L.   U.S.
     Environmental Prot. Agency, Ecol . Res. Ser.   EPA-660/3-75-015, 18pp.

Middaugh, D.P., W.R. Davis and R.L.  Yoakum.  1975.  The response  of larval
     fish, Leiostomus xanthurus, to  environmental  stress following sub-
     lethal cadmium exposure.   Contrib.  Mar.  Sci.  (In press).

Mount, Donald I. and Charles E. Stephan.  1967.   A method for establishing
     acceptable toxicant limits for  fish-malathion and the butoxyethanol
     ester of 2, 4-D.  Trans.  Am.  Fish.  Soc.   96(2):   185-193.

NAS-NAE Committee on Water Quality Criteria.   1972.  Water Quality Criteria,
     1972.  Ecol. Res. Ser. xx + 594 pp.  U.S. Environmental  Protection
     Agency, EPA-R3- 73-033 March 1973.  U.S.  Gov.  Print. Office,  Wash.,
     D.C.  20402.

                                    75

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Parrish,  Patrick R.,  John A.  Couch,  Jerrold Forester, James M.  Patrick,
     Jr.  and Gary H.  Cook.   1973.   Dieldrin:   Effects on several  estuarine
     organisms.   Proc.  27th  Annu.  Conf.  S.E.  Assoc.  Game Fish Comm.  1973.
     p.  427-434.

Parrish,  Patrick R.,  Steven  C.  Schimmel, David J.  Hansen, James  M.  Patrick,
     Jr.  and Jerrold  Forester.  1975.   Chlordane:   Effects on several  es-
     tuarine organisms.   J.  Toxicol.  Environ.  Health. (In press).

Schimmel, Steven C.  and David J.  Hansen.  1974.   Sheepshead minnow
     (Cyprinodon variegatus):  An  estuarine fish  suitable for chronic
     (entire life-cycle)  bioassays.   Proc.  28th  Annu. Conf. S.E.  Assoc.
     Game Fish.  Comm.   (In press;.

Schimmel, Steven C.,  Patrick  R.  Parrish, David J.  Hansen, James  M.  Patrick,
     Jr.  and Jerrold  Forester.   1974a.   Endrin:   Effects on several  es-
     tuarine organisms.   Proc.  28th  Annu.  Conf.  S.E.  Assoc. Game  Fish.
     Comm.  (In  press).

Schimmel, Steven C.,  David J. Hansen  and Jerrold  Forester.   1974b.
     Effects of Aroclor(B)l254 on  laboratory-reared embryos  and  fry  of
     sheepshead minnows  (Cypri nodon  van' e gat us) -   Trans. Am.  Fish.  Soc.
     103(3):  582-586.
                                    76

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        The Effect of Subtle Temperature Changes on
          Individual Species and Community Diversity

                      William C.  Johnson  II   and
                          Eric  D.  Schneider*


                               ABSTRACT

          Decisions about the regulation  of thermal additions
          in aquatic systems  have often been  based on acute
          or chronic high temperature  effects on  individuals
          from various life stages of  selected species, but
          rarely on populations or communities (Mihursky, 1969).
          This paper offers a synthesis from  a variety of data
          bases that demonstrated consistent  response of bio-
          logical  systems to  long-term, low level temperature
          change.   Profound effects of subtle prolonged temper-
          ature displacement are  demonstrated at  the species,
          and community levels  of biological  organization.


                             INTRODUCTION

     For the past decade there  has been a controversy as to whether or not
artificial temperature alteration  should  be considered a type of pollution.
It is of interest that Congress (SR 92-500) considers artificial thermal
perturbations as pollution and  requires the United States Environmental
Protection Agency to develop  regulations which assure maintenance of bal-
anced and indigenous populations  within the area  of thermal discharge.
Temperature is known to be a  key  physical controlling parameter of biolo-
gical systems.  Latitudinal distributions of  organisms is usually a direct
reflection of the temperature gradient that exists between the poles and
the equator.  Therefore, one  might hypothesize that in any locale, a per-
sistent temperature change may  lead to a  biotic change with the possible
loss of desirable species and replacement by  others.  This paper identifies
the data base which substantiates  this hypothesis.  These data have been
generated previously by studies related to abundance of commercially valu-
able species, power plant impact  studies, and pelagic foraminiferal studies

                               METHODS

     In order to demonstrate  consistent response  of biological systems to
long-term, low level  temperature  change,  it is necessary only to look at
existing models derived from  commercial species abundances and power plant
impact studies with a new point of view.  However, utilization of foramin-
iferal data requires some manipulation.
*Environmental Research Laboratory,  U.S.  Environmental  Protection Agency,
Narragansett, RI  02882
                                   77

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     Analyses  of the foramini feral  data  were  designed to determine the
relationship between species diversity of trigger core tops and piston
core tops  and  the surface water temperatures  overlying those cores.
These core top samples represent recent  sediments.  A history of marine
geology has established the fact that the conditions during deposition
generally  correlate well with the present environmental conditions.

     Foraminiferal species diversity is  calculated from relative abun-
dance for  the  data sets of Kennett  (1967) and Imbrie and Kipp (1971).
Using these data the Shannon-Wiener index,  fl,  was calculated according
to the formula:
                      fi = -£ pi log pi
where s = the  number of species, pi  =  the proportion of the i    species
in the total number of species, and  N  =  the total number of individuals.
The diversity  values were taken directly from Williams and Johnson (1975).

     The summer-winter average temperatures presented by Williams  and
Johnson (1975) were used.  A simple  arithmetic mean was calculated from
the summer and winter temperatures presented by Imbrie and Kipp (1971).
For each of Kennett's (1967) sediment  core locations the same  temperature
term was calculated by averaging summer  and winter values from the ocean-
ographic atlas of Schott (1935).  Regressions of temperature and diversity
values were made by the least squares  method of linear regression.
                             DISCUSSION

     Figure  1  depicts a hypothetical  relationship between success  or  abun-
dance of an  individual, a population, or community assemblage,  and temper-
ature.   The  determination of the upper and lower thermal  limits, of the
                                  "OPTIMUM CONDITION
                                         LOWER RESPONSE RATE
                                         TO TEMPERATURE THAN
                                       .  AT EXTREME
   Q
   _l
   LU
      DECLINE
WITH SMALLTEMPERATURE
INCREASE
                 LfRAPID INCREASE
                 ^U/ITU <
                   WITH SMALL
                   TEMPERATURE INCREASE
       COLD
               HOT
           TEMPERATU RE (DURING A CRITICAL PERIOD)
Figure 1.  The  hypothetical relationship between temperature and an indi-
           vidual's, a  species', or community  success.  Different rates of
           response for the different levels of biological organization
           within  their tolerated range are  suggested.

                                  78

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optimum, and of the temperature range that can be tolerated by the  indivi-
dual, a species, or the community are of ecological  importance.   Bradshaw
(1961), through experiments on foraminifera,  suggested that such  a  curve
is skewed toward the warmer temperatures at the species  level.   Indeed,
data presented herein indicate a similar tendency toward skewing  at the
community level.

     Temperature may have intensified effects during particular  life history
stages of different species.  Such effects are often a result  of  direct re-
lationships between critical biological  processes and physiological  effects
of temperature.  Rates of processes or timing of critical  events  are two
types of biological variables affected (Jeffries and Johnson,  1974).

     Another important consideration with respect to temperature  change is
the alteration of community structure and composition.   Consider  a  hypothet-
ical assemblage of five species which have different ranges, optima,  upper
and lower limits, and rates of response  to temperature  (Figure 2).   Commun-
ity structure is predicted at two points within the  temperature  range by
measuring the relative heights of the individual  curves  at these  tempera-
tures, with species interaction not taken into account.   The resulting pre-
diction shows very different community structure at  the  two temperatures.
The magnitude of temperature change required  to cause such dramatic biotic
shifts is the question which will  be treated  here.
    UJ
    o
    o
    z
    13
    CD
     UJ

     I
     UJ
     a:
IUU
80
60

40
20
o

-
_

—
-









\ \
C


B











D
C

E



T, T2
HIGH
/^N.
          LOW
                                  TEMPERATURE

   Figure 2.   Hypothetical  temperature  ranges  for five  species and their
              relative abundances  throughout their  respective ranges.
              Theoretical  community  composition  at  two  temperatures  is
              predicted by the relative species' abundance at the two
              temperatures.

                                   79

-------
     Direct prediction of community composition from this type of figure
would not be warranted if significant species interaction were to occur.
Species interaction is nearly always present, although the amount and kinds
of such interaction have been difficult to predict in natural  situations.
An example of this difficulty is the effect that predation by the green crab,
Carcinus maenas, had on soft clams, Mya ajenaria, in Maine (Glude, 1954).
Here, a slight climatic warming of approximately 2°C led to the introduction
of the green crab, which eliminated entire year classes of the soft clam.

COMMERCIALLY VALUABLE SPECIES DATA

     A valuable source of information concerning temperature-biotic relation-
ships may be found in the analysis of fishery catch  data.  Table 1 (Jeffries
and Johnson, 1975) summarizes the responses of eight marine species to tem-
perature change when univariate models (Dow, 1973) and a bivariate model
(Flowers and Saila, 1972) are applied to catch statistics for these species.
Figure 3 demonstrates the extreme thermal  sensitivity of Hawaiian corals'
reproductive success (Jokiel  et ^1_., 1974).  A generalized two compartment
temperature model  is presentecPin Figure 4 (Jeffries and Johnson, 1975).
Their specific winter flounder model (Figure 5)  demonstrates  how tempera-
ture may affect a  species abundance through two independent mechanisms.
1.0
2 .8
0
z
w
OT
Ul
o
o .6
W
Ul
H
O
^^
o A
o
o:
Q.
Ill
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tr
ui 2
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0







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•


\
. ^/ \

• i^M
                       18      22      26      30
                             MEAN TEMPERATURE °C
Figure 3.   Net reproductive  success  of  Hawaiian  corals  over  an  experimental
           temperature  range.   Note  the limited  temperature  range  for  the
           optimal  reproductive success.  (Figure from Jokiel, e_t al_.,  1974)
                                    80

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             TABLE 1.   CHANGES IN ABUNDANCE OF SEVERAL SPECIES  PREDICTED  FROM A  1°C  INCREASE  IN THE GRAND MEAN,
                       ANNUAL SEA-SURFACE TEMPERATURE (MAINE).   (TABLE  FROM  JEFFRIES AND JOHNSON,  1975)
00
Author
Dow
(1973)
Flowers
and
Saila
(1972)
Species Change
hard clam +73.4
Mercenaria mercenaria
oyster +51.0
Crassostrea virginica
lobster +15.2
Homarus americanus
shrimp -75.0
Panda! us boreal is
scallop -37.5
Placopecten magellanicus
soft clam -36.8
Mya arenaria
sand worm -32.5
Nereis virens
bloodworm -22.4
Glycera dibranciata
lobster +14.6
Homarus americanus

Basis of annual
comparison; total Average
yield relative to catch
mean temperature (metric T)
- UNIVARIATE MODELS -
Same year 83.3
3 yr later 1.2
3
same year 8.3 x 10
4 yr later 139
6 yr later 135
5 yr later 1.9 x 103
same year 239.2
same year 179.7
- BIVARIATE MODEL -
TQ & T_678{ 9.4 x 103t
Observation
period
1939-1967
1951-1967
1939-1967
1939-1949
1954-1967
1941-1965
1940-1966
1949-1967
1949-1967
1947-1967
rf
.770**
.822**
.627**
-.505*
-.743**
-.643**
-.812**
-.669**
.889**
Effect
Winter
survival ,
near N limit
molting,
recruitment
spawning,
early survival ,
near S limit
predation
on spat
spawning,
early
survival
TQ: molting,
recruitment;
/""TO • Go i I y
winter
mortality
       *significant at the 95% level
      **significant at the 99% level
of probability;     tcalculated from data  presented  by  Dow  (1973);
of probability     t"T is the mean annua1  sea-surface temperature
             y'        present year;
                     T-678 ^s the sum of t^ie mean annua^  sea-surface
of the
                                                                temperatures  for 6,7,  and 8 years  previous  to  T  .

-------
             TEMPERATURE EFFECTS ON ENTIRE LIFE OF A SPECIES


                               A SUNDANCE


                    EARLY PERIOD                REMAINDER OF LIFE

             DIRECT TEMR EFFECTS           DIRECT a INDIRECT TEMP EFFECTS
                                            A.IFAT LIMIT OF RANGE

            I SPAWNING ACTIVITY              I.MAX OR MIN TEMPERATURES
                                          BEYOND ACCEPTABLE LEVELS
           2.EGG VIABILITY
                                         2.MATURATION (REPRODUCTIVE)
           3. DEVELOPMENT
                                            B. AND IN GENERAL
           4. SUCCESS OF METAMORPHOSIS
                                         3.SUCCESS IN COMPETITION
           5. CRITICALTIMING OF MET.
                                         4. GROWTH RATE 8 FEEDING RATE

                                         5. PREDATOR RELATIONS
                                          (CRAB 8 CLAM)

                                         6. MATURATION TO ADULT (LOBSTER)

                                         7. LONGEVITY

                                         8. MIGRATIONAL PATTERNS

                                         9. EFFECT ON HABITAT

Figure 4.  Biological  evaluation of a generalized  bivariate temperature
           model of species abundance.  Climatic temperature change is
           the basis for this  model.  (After  Jeffries and Johnson, 1975)
     Taylor et_ _al_. (1957) noted a close relationship between shifts of the
geographic ranges in marine fishes and other species in the Northwestern
Atlantic and climatic warming.  Dow (1964, 1967, 1969, 1971, 1973) has been
a key contributor on this topic by observing a relationship between temper-
ature and catch statistics of eight commercially valuable marine species.

     Considering the response model of Figure 1, the logical question is, at
what rate does species abundance respond to a given prolonged temperature
change.  Jeffries and Johnson (1974, 1975) have attempted to quantify the
abundance of several single species with respect to temperature change
(Table 1).  These data suggest that as little as a one degree centigrade
positive displacement from the long-term mean coastal surface temperature,
may result in significant changes in species abundance, ranging from +73.4%
to -75%.  The extreme response rates are for populations near their thermal
limits, while those living closer to their temperature optimum generally
show smaller change with this temperature rise.

     Other models of abundance for marine fish species have been developed
which use temperature as an influential term.  Sissenwine (1974, 1975),  for
instance, developed fisheries models for yellowtail flounder in New England
which incorporated an important temperature effect.  His models indicate
extreme sensitivity of recruitment and growth to minor temperature change
(+ 1°C).

                                     82

-------
     Temperature can play an exaggerated role during the early life history
of many species.  Figure 3 demonstrates this sensitivity in  Hawaiian corals
(Jokiel  et. dj_., 1974), where an optimum reproductive range of only 2°C was
observed.   Baird (1953) suggested that there was a similar sensitivity dur-
ing the spawning of the giant scallop, Placopecten magellanicus. a temperate
species.   A similar effect has been identified by Jeffries and Johnson (1975)
in modeling the winter flounder population, Pseudopleuronectes americanus,
in Narragansett Bay, Rhode Island.  Thus,  data from both temperate and
tropical  locations support the hypothesis  of ecologically significant early
life history temperature sensitivity for a variety of species.

     A quantitative bivariate population model can give more information, in
some instances, than univariate counterparts by offering more insight into
the effects of temperature at different times of a species life history.  A
generalized and a specific model are presented in Figures 4  and 5.  Flowers
and Saila  (1972) employed a similar bivariate temperature model  to describe
lobster abundance in Maine.  These two different types  of models  are applied
here only  with respect to their value in pointing out apparent temperature
sensitivity of life stages  and without bias toward any  particular scheme o1
modeling.
                              of
           TEMPERATURE EFFECTS ON WINTER FLOUNDER
                 (PSEUDQPLEURQNECTES AMERICANUS)
                    JEFFRIES AND JOHNSON (1975)
                             ABUNDANCE
                     'I
              APRIL TEMP.
            30 MONTHS PRIOR
                TO CATCH
            DIRECT EFFECTS

            I. DEVELOPMENT
              RATE
            2.SURVIVALRATE
 TEMP HISTORY FROM MAY,
29 MONTHS PRIOR TO CATCH
 THRU SEPT., FIRST MONTH
        OF CATCH
   INTERACTIONS

   I.COMPETITION
    FOR RESOURCES
  2.PREDATION
Figure  5.  A specific  bivariate temperature model  for  the abundance  of
          winter flounder (Pseudopleuronectes americanus) developed by
          Jeffries  and Johnson (1975).Possible  biological  interactions
          are suggested.
                                 83

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POWER PLANT  STUDIES

     A second  source of data on the effect of temperature on populations
and communities  is that found in the literature  concerning power plant im-
pact.  Figure  6  depicts the effect of temperature  on  the relative abundance
of benthic microalgae in Hawaiian waters (Jokiel et. a\_., 1974).  Figure 7
(Jokiel et. al_.,  1974) shows that in selected species  systems, Hawaiian
macroalgae standing crop drops nearly five fold  with  an increase in tem-
perature of  4.3°C.
  HIGH
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<
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^>
CD
111
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ee
   LOW
 Figure 6.
                                              A  NJTZCH1ATE
                                                 DIATOMS

                                              B  FILAMENTOUS
                                                 GREENS

                                              C  NAVICULATE
                                                 DIATOMS

                                              D  FILAMENTOUS
                                                 BLUE-GREENS
                                          30
                                          34
                      TEMPERATURE °C
The effect  of temperature on the abundance of benthic microalgae
on Hawaiian waters.  This figure resembles Figure 2 and demon-
strates  the theorized community shift.   (Figure from Jokiel
et al_.,  1974)
     From Figure 6 one  can see that two of the subtropical  algal types have
optimal ranges of less  than  5°C.  It is also of interest to note that this
figure resembles Figure 2 and that temperature displacement results in com-
munity shifts as hypothesized.  Beyond these algal  species, the entire
marine communities in Hawaii and Florida have been  observed to undergo major
species compositional changes as a result of prolonged local warming from
heated power plant discharge (Jokiel <2t aj_., 1974,  Roessler et. aj_., 1974).
Caution should be applied when using a tropical response to thermal stress
as indicative of a general pattern, as this biota typically lives  close to
their upper thermal  limit.   However, these data agree with  the temperate
examples already cited  (Taylor e_t aj_., 1957, Jeffries and Johnson, 1974).

     A marked increase  or decrease in net macroalgal  production resulting
from persistent temperature  displacement could be responsible  for  some of
the observed fauna!  changes  (Roessler e_t al_., 1974).   Although the direc-
tion of change is probably not typical, limitations of macroalgal  production
                                   84

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                      30 DAYS SUMMER AMBIENT ("27"C) 30DAYS STRESS

                         500
                                      |    | OTHERS


                                       H| ACANTHOPHORA

                         4001-         ^H ULVA
                         300
                      o
                      UJ
                      *  200
                          100
                               TANK 10
                                26.7
                          TANK 7
                           28.5
TANK 4
 29.6
TANK I
 31.0
                           AVERAGE TEMP.'C DURING STRESS PERIOD
Figure 7,
Hawaiian  macroalgae  standing crop at  four experimental  tempera-
tures.   Note the dramatic decrease  in  biomass with only a 4.3°C
shift.  (Figure from  Jokiel  et_ al_. ,  1974)
                    3.5 r
                    2.7
                  x
                  UJ
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                  to 1.9
                  CL
                  Ul
                  CL
                  UJ
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                  o
                    0.3
                   -0.5
                                               •  •  •
                             -5.0
                                       0.0
                                               5.0
                                                       10.0
                                                                15.0
Figure 8.
                        TEMPERATURES
Scatter  diagram of Shannon-Wiener diversity values, calculated for
the Kennett data set  (1967), plotted  versus the summer-winter aver-
age temperature.  Note  the linear trend  of increasing  diversity
with  increasing temperature.
                                      85

-------
with increased ambient temperatures in the tropics provide an example (Fig-
ure 7).  It is worth noting from this figure that there is a significant
shift in relative abundances of the three different groups of algae over
the observed temperature range (4.3°C).   Thus, in addition to altered pro-
ductivity, a shift in species composition occurs which affects the amount
and quality of algal habitat afforded to a segment of the animal community.

FORAMINIFERAL INVESTIGATIONS

     Another data source showing sensitive temperature-fauna! interaction
is the foraminiferal data base.  The optimal and total temperature ranges
for eighteen species of foraminifera are presented in Table 2 (Be' and
Tolderlund, 1971).  The effect of temperature as an independent variable
on the Shannon-Wiener diversity index values (R) for the foraminiferal
abundance data of Kennett (1967), Imbrie and Kipp (1971), and Williams
and Johnson (1975) are shown in Figures  8, 9, and 10.  Figure 10 also shows
the faunal composition of three cores with average temperatures near the
mean of the diversity data set.  Figure  11 summarizes those data by drawing
in the individual regression lines.

     TABLE 2.  AVERAGE TOTAL AND OPTIONAL SURFACE TEMPERATURE
               RANGES FOR EIGHTEEN SPECIES OF PLANKTONIC FORA-
               MINIFERA IN THE ATLANTIC  AND INDIAN OCEANS (BASED
               ON DATA FROM BE'AND TOLDERLUND 1971)
                                                  Average Range
     Species Name
Optimum °C
Total °C
Globigerina pachyderma
G. quinqjjeloba
G. bulloides
Globorotalia inflata
G. truncatulinoides
G. crassaformis
G. hirsuta
G. menardii
Globigerinita glutinata
Globoquadrina dutertrei
Orbulina uni versa
Globigerinella aequi lateral is
Hastigerina pelaqica
Globigerinoides ruber
G.. conglobatus
G. sacculifer
Pulleniatina obliquiloculata
Candeina nitida
8.2
7.9
9.2
5.4
2.5
1.0
8.0
3.4
2.3
2.5
5.7
3.0
7.0
7.5
4.4
3.0
19.4
18.9
26.0
23.5
16.7
8.5
8.2
12.4
25.7
16.7
17.5
15.4
12.2
14.8
11.8
13.4
10.0
7.4
                  Grand Average
    5.1
  15.5
                                    86

-------
   3.5
X
UJ
Q
t 3.0
o>
(T
UJ
Q
a:


UJ
   2.5
   2.0
i
to
    1.5
       18.0
                 20.0
22.0
24.0
26.0
28.0
   DIVERSITY  VS. SUMMER-WINTER AVERAGE  TEMPERATURE
                          IMBIEaKIPP(l97l)


 Figure 9.  Scatter diagram of  Shannon-Wiener diversity values, calculated
           for the Imbrie and  Kipp data  set (1971), plotted against the
           summer-winter average temperature.   Note that at summer-winter
           average temperature greater than 18.5°C, there is a decline in
           species diversity.
                                 87

-------
  4.0
'5 3.4
x
U)
Q
Z
                                             FAUNAL COMPOSITION AT 3 TEMPERATURES

                                                    HOO
 Q

 £E
   2.2
 UJ
 z
 o
   1.6
 X
 V)
   1.0
         4.0       8.0       I2JO       16.0
                    TEMPERATURE °C
20.0
10.4  12.6
145
          TEMPERATURE°C
          (AVERAGE 12.0 °C)
  Figure 10.   Scatter diagram of Shannon-Wiener diversity  values  of Williams
              and Johnson (1975)  plotted with respect  to  the  summer-winter
              average temperature.  Here, as in Figure  8,  there  is an increase
              in species diversity with increased  temperature.  Faunal  compo-
              sition at three temperatures is presented as well.   The faunal
              composition at 14.5°C was calculated by averaging  data from two
              cores.  Note the faunal shifts, additions, and deletions of
              species as the temperature changes.
                                     88

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    -404       8      IE       16     20     24

          SUMMER-WINTER AVERAGE TEMPERATURE °C

     AUTHOR              NO. PTS.  OCEAN             _r
   I. IMBRIE8 KIPP(I97I)     18   N a S ATLANTIC   .834
  2. IMBRIE»KIPP(I97I)    41    N 8 S ATLANTIC    .805
   3. KENNETT (1967)        33   SW PACIFIC       .928
   4. WILLIAMS a JOHNSON  20   S INDIAN         .973
                      (1975)
28
Figure 11. Individual  regression lines of diversity versus summer-winter
         average temperature.  Note their close correspondence despite
         different sources of data.  These lines approximate the shape
         of the hypothetical community response curve demonstrated in
         Figure 1.
                              89

-------
     Investigators  in the micropaleontological  field pioneered the inves-
tigation of the effects  that small  scale temperature fluctuations  have on
the abundances of individual species.   As early as  1935,  Schott made the
observation that pelagic foraminifera  could be  utilized as  markers of cli-
matic change.   Other early investigators (Ericson,  1959;  Ericson and Wollin,
1956) noted fauna!  changes in response to climatic  trends^   For those spe-
cies examined in Table 2, the range for the optima  is 5.1°C and the average
total range is 15.5°C.

     Kennett (1970), Ruddiman (1971), Imbrie and Kipp (1971), and Hecht
(1973) are but a few of the investigators who have  developed sophisticated
paleotemperature models  from relationships  observed between temperature and
living foraminiferal species assemblages.  Although developed to satisfy
quite another need, these models and their data bases underscore impact on
living foraminiferal populations resulting from minor, but  persistent, tem-
perature change.

     The foraminiferal data possibly demonstrate community  structure sen-
sitivity to long-term temperature changes.   This ubiquitous data base was
chosen because it lends itself to global comparisons.  Species diversity
is  used as an index of community structure.  Although species diversity
should not be considered a panacea for community studies, it can serve as
a  simple common denominator for comparing the voluminous  foraminiferal
data sets.

     The scatter diagrams (Figures 8,  9, and 10) show how well diversity
approximates linear trends with respect to temperature.  There is  a rapid
rate of change for each of the data sets.  It is notewrothy that signifi-
cant shifts of relative species abundances (Figure  10) occur even  within
the 4.0°C range examined.  This type of faunal  shift persists throughout
the data sets and is assumed not to be fortuitous in this example.

     Figure 11 demonstrates that a break in diversity occurs generally at
a  summer-winter average temperature of 18.5°C.   Thus, species diversity is
not linearly related to temperature throughout  the  entire temperature range
studied.  The overall shape of these lines  approximates the theoretical
shape of temperature's effect on community success  (Figure  1) with the mod-
ification of slight skewing toward the warmer temperatures.  This  W9uld
imply that species  at their southern limits and tropical  or subtropical com-
munities would have greater sensitivity to warming  trends than species well
within their temperature ranges and temperate or polar communities.

     In summation,  by applying available modeling tools to  completely dif-
ferent existing data sets, we demonstrate appreciable effects of long-term,
low level temperature change on species abundance and community structure
and composition.  This demonstration is achieved in a manner which is amen-
able to regulatory requirements generated by Public Law 92-500 (1972) in
sections 304 and 316a.  These laws direct the United States Environmental
Protection Agency to develop regulations to control thermal discharge with
limitations more stringent than necessary in order to assure the protection
and propagation of a balanced, indigenous population of shellfish, fish,
and wildlife in and on the body of water into which the discharge is made.

                                    90

-------
     Jeffries and Johnson (1974, 1975) have employed natural  fluctuations
of temperature as the stressor in their models.   As mentioned earlier,  part
of the east coast of North America has undergone short-term warming trends,
giving rise to changes in species abundance (Table 1).   With the building
of large scale thermal nuclear power plants on estuarine and coastal  waters,
we may see regional  temperature rises in the ranges discussed in this paper
(± 1°C).  Broecker  (1975) has projected that, because  of atmospheric C0?
increase, there will be a global warming of 1.1°C by the year 2010  A.D.
Such man induced warming coupled with nature's unpredictable fluctuations
should have appreciable effects on indigenous  marine populations.

     It is apparent that the biota is very sensitive to slight long-term
temperature alteration.  Seasonal cycles and daily fluctuations of  temper-
ature tend to obscure long-term temperature trends and  their biological
effects, which perhaps explains why many investigators  have overlooked  this
delicate, but dramatic relationship.  Data obtained from a global spectrum
form a basis of support for this suggested relationship.  Although  these
are preliminary findings, the same overbearing theme persists.

     In the future, we would hope to achieve predictive models.  At present,
the changes which have occurred, due to thermal  pollution or climatic changes,
have been somewhat unpredictable.  As mentioned earlier, newly introduced
predators may cause significant changes in the indigenous populations.


                             CONCLUSIONS

     Responses due to thermal perturbation, seen at the species level of
organization, include:

     1)  Species often have average yearly thermal ranges of about  5°C  when
         in natural  surroundings.  However, subtle shifts of ±1°C give  rise
         to marked changes in population abundances.
     2)  Response to temperature displacement  is appreciable in the resident
         biota.  Some species benefit by temperature change while others are
         adversely affected by the same.
     3)  Early life history stages may be particularly  sensitive to tempera-
         ture changes.

     The community level of organization appears, also, to be very  much
affected by temperature change, as shown by:

     1)  Entire communities have undergone significant  change when  prolonged
         low level warming occurs because of the discharge of heated effluents
     2)  Prediction of community changes is confounded  by unsuspected inter-
         action between species, as in the case of the  green crab and soft
         clam in Maine.
     3)  Species diversity changes with ambient temperature for certain  com-
         munity types.  Diversity in foraminiferal communities respond  ap-
         preciably to temperature change with  an apparent maximum at 18.5°C
         summer-winter average.

                                     91

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                           ACKNOWLEDGMENTS


     We thank Dr.  H.P.  Jeffries,  Dr.  D.C. Miller,  Dr.  J.P.  Kennett, and
D.F.  Williams who  offered advice  and  graciously  made  data available.
Dr.  O.K.  Phelps  critically reviewed the  manuscript and offered assistance.
F.T.  Short wrote the program for  the  computation of diversity indices.

                              REFERENCES


Baird, F.T.,  Jr.,  "Observations on  the Early  Life  History of the  Giant
     Scallop  (Pecten magellanicus)",  Res. Bull.  14 Maine Dept.  of Sea and
     Shore Fish..  (1953).

Be',  A.W.  and  D.S.  Tolderlund,  "Distribution  and  Ecology of Planktonic
     Foraminifera."  IN:   The Micropalaeontology of Oceans,  Edts. Funnel,
     B.M. and W.R.  RieSel, pp.  105-149  (1971).

Bradshaw, J.S.,  "Laboratory Experiments  on the Ecology of Foraminifera",
     Cushman  Found. Foram. Res. Contr.,  12,  pt.  3, pp. 87-106 (1961).

Broecker, W.S.,  "Climatic Change:   Are We on  the Brink of a  Pronounced
     Global Warming?",  Science, 189,  pp. 460-463 (1975).

Dow, R.L., "Changes in  Abundance  of the  Marine Worm,  G1ycera dibranchiata,
     Associated with Seawater Temperature Fluctuations' , Commercial Fisheries
     Review,  26. No. 8  (1964).

Dow, R.L., "Temperature Limitations on the Supply  of  Northern Shrimp
     (Pandalus borealisj  in Maine (USA)  Waters", IN:  Proceedings  of the
     Symposium on  Crustacea, Part IV, pp. 1301-1304 (1967).

Dow, R.L., "Cyclic and  Geographic Trends in  Seawater  Temperature  and
     Abundance of  American Lobster",  Science, 164, pp. 1060-1063  (1969).

Dow, R.L., "Periodicity of Sea Scallop Abundance Fluctuations in  the Northern
     Gulf of  Maine", National  Fisherman  Res.  Bull. No. 31, Maine  Dept.  of
     Sea and  Shore Fisheries (1971).

Dow, R.L., "Fluctuations  in Marine  Species Abundance  During  Climatic Cycles",
     MTS Journal.  7. No.  4, pp. 38-42 (1973).

Ericson,  D.B., "Coiling Direction of  Globierina  pachyderma as a Climatic
     Index",  Science.  130, pp.  219-220  (1959).

Ericson,  D.B. and  G. Wollin, "Micropaleontological and Isotopic Determinations
     of Pleistocene Climates",  Micropaleontology.  2.  pp. 257-270  (1956).

Flowers,  J.M. and  S.B.  Saila,  "An Analysis of Temperature Effects on the
     Inshore  Lobster Fishery",  J.  Fish.  Res.  Bd. Canada, 29. No.  8,
     pp.  1221-1225 (1972).
                                     92

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Glude, J.B., "The Effects of Temperature and Predators  on the Abundance of
     the Soft-Shell  Clam, Mya arenaria, in New England", Trans.  Am.  Fish.
     Soc. 84. pp. 13-26 (1954).                           	

Hecht, A.D., "A Model  for Determining Pleistocene Paleotemperatures  from
     Planktonic Foraminifera Assemblages", Micropaleontology 19. pp.  68-77
     ^ I y / o / •

Imbrie, J. and N.G.  Kipp, "A New Micropaleontological  Method for Quantitive
     Paleoclimatology:  Application to a late Pleistocene Caribbean  Core",
     IN:  The Late Cenozoic Glacial Ages, Ed. K.K.  Turekian, Yale University,
     flew Haven, pp.  71-182 (1971).

Jeffries, H.P. and W.C. Johnson, "Seasonal Distribution of Bottom Fishes
     in the Narragansett Bay Area:  Seven-Year Variations in the Abundance
     of Winter Flounder (Pseudopleuronects americanus)", J.Fish. Res. Bd.
     Canada. 31. pp. 1057-1066 (1974).

Jeffries, H.P. and W.C. Johnson, "Petroleum, Temperature and Toxicants:
     Examples of Suspected Responses by Plankton and Benthos in  the  Contin-
     ental Shelf", (In Press, 1975).

Jokiel, P.L., S.L. Coles, E.B. Guinther, G.S. Key,  S.V. Smith and S.J.  Townsley,
     "Effects of Thermal Loading on Hawaiian Reef Corals", EPA Project  18050
     DON, element 1B1022, (Progress Report, 1974).

Kennett, J.P., "Distribution of Planktonic Foraminifera in Surface Sediments
     Southeast of New Zealand",  Proc. 1st Int. Conf. Plankt. Microfossils, Geneva,
     pp. 307-322 (1967).

Kennett, J.P., "Pleistocene Paleoclimates and Foraminiferal  Biostratigraphy
     in Subantarctic Deep-Sea Cores", Deep Sea Research, 17, pp. 125-140 (1970).

Mihursky, J.A. (chairman) "Patuxent Thermal Studies—Summary and Recommendations"
     NRI Spec. Report. No. 1, pp.  1-20 (1969).

Roessler, M., D. Tabb, R. Rehrer,  and J. Garcia, "Studies of Effects  of Thermal
     Pollution in Biscayne Bay,  Florida", Ecological Research Series, EPA-
     660/3-74-014, 145 p.  (1974).

Ruddiman, W.F., "Pleistocene Sedimentation in the Equatorial Atlantic:  Strat-
     igraphy and Fauna! Paleoclimatology", Geological  Society of American  Bui 1 .,
     82, pp: 283-302 (1971).

Schott,  G.,  "Geographic des  Indischen und Stillen Ozeans",  Boysen, Hamburg,
     413 p.  (1935).

Schott,  W.,  "Die Foraminiferen in  dem Aequatorialen Tie!  des Atlantischen
     Ozens:   Deutsch Atlant.  Exped., 'Meteor1, 1925-1927",  Wiss. Ergebn, 3,
     pp. 43-134 (1935).
                                    93

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Sissenwine, M.P.,  "Variability in Recruitment and Equilibrium Catch of the
     Southern New  England Yellowtail  Flounder Fishery",  J.  Cons.  Int..
     Explor.  Mer.,  36.  No.  1,  pp.  15-26 (1974).

Sissenwine, M.P.,  "Yellowtail  Flounder Dynamics",  University of RI. Ph D
     Dissertation,  178  p.  (1975).	'

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                                   94

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               FRESHWATER QUALITY CRITERIA RESEARCH
            OF THE ENVIRONMENTAL PROTECTION AGENCY

                                   Donald Mount, presiding
       Director,  Environmental  Research Laboratory--Duluth

Models for Transport  and  Transformation of Malathion in
Aquatic Systems

     James W.  Falco,  Donald  L.  Brockway, Karen L. Sampson,
     Heinz P.  Kollig, and James  R.  Maudsley

Shagawa Lake Recovery Characteristics as Depicted by
Predictive Modeling
     D.P.  Larsen  and  H.T.  Mercier

A Mathematical  Model  of Pollutant Cause and Effect in
Saginaw Bay, Lake Huron
     William L. Richardson and  Victor J. Bierman, Jr.

Mathematical Model of Phytoplankton Growth and Class
Succession in  Saginaw Bay, Lake  Huron
     Victor J.  Bierman, Jr.  and  William L. Richardson

Implications of Resource  Development on the North
Slope of Alaska with  Regard  to  Water Quality on the
Sagavanirktok  River
     Eldor W.  Schallock

Lake Eutrophication:   Results from  the National
Eutrophication  Survey
     Jack H. Gakstatter,  Marvin  0.  Allum and
     James M.  Omernik

                  95

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            Models for Transport and Transformation
                 Of Malathion in Aquatic Systems

                 James  W.  Falco,  Donald  L. Brockway
                Karen L.  Sampson,  Heinz  P. Kollig, and
                          James R.  Maudsley*
                               ABSTRACT
          A mathematical  model  has been developed for predicting
          the fate and transport  of malathion in riverine aquatic
          ecosystems.   Two  competing degradation pathways were
          modeled—alkaline hydrolysis and microbial breakdown.
          Incorporating data obtained from previous laboratory
          studies, the model was  used to verify proposed degrada-
          tion mechanisms by predicting the behavior of malathion
          in the AEcoS, a physical system designed to simulate en-
          vironmental  conditions  as closely as possible.  Although
          in general  results were similar for the two systems,
          rates measured in the environmental simulator were slow-
          er than those measured  in laboratory studies.
                             INTRODUCTION
     The fate and  transport of  toxic substances in aquatic ecosystems  has
been the subject of numerous studies over the years.  Field studies  are  un-
dertaken to estimate the  persistence of the toxic materials under natural
conditions  and laboratory studies are undertaken to study the persistent
pollutants.  In  recent years mathematical modeling has also become a useful
technique in the study of environmental pollution.  As modeling capabilities
have improved, mathematical models have been applied with increasing fre-
quency to interpret the results of both laboratory and field experiments
and to extrapolate results obtained to other ecosystems.
*Environmental  Research Laboratory,  U.S.  Environmental Protection Agency,
Athens, GA  30601

                                     97

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     Such a model was developed to describe the fate and transport of
malathion {0,0-dimethyl S-(l ,2-dicarbethoxy)ethylphosphorodithioate}, an
organo-phosphorus pesticide widely used for control of mosquitos and ag-
ricultural insect pests.  A number of laboratory studies have been done
to determine the pathways and rates of chemical and biological degradation
of the insecticide.  Ferguson (1975) reviewed the available literature con-
cerning malathion including its chemistry, pharmacology, toxicity, fate and
significance in the environment, and production and use.

     Koivistoinen and Aalto (1970) have reported pseudo-first-order rate
coefficients for chemical hydrolysis of malathion as a function of pH
ranging from 1 to 9 and of temperature ranging from 20°C to 70°C.  Under
alkaline conditions, malathion hydrolyzes to form predominantly dimethyl
phosphorodithioate and dimethyl phosphorodithionate.  Wolfe e_tal_. (in
press) have done a detailed study of chemical degradation pathways and
nave estimated rate coefficients for intermediate product degradation as
well as for malathion hydrolysis.  They note that at low temperatures mala-
thion monoacid is formed as an intermediate product that is more stable
than the parent compound and consequently has a potential environmental
impact.

     Paris ejt a]_. (1975) completed a microbial degradation study in which
mixed bacterial cultures isolated from the field were inoculated into me-
dium containing malathion as a sole carbon source.  From the rate data ob-
tained, malathion degradation was modeled using Monod kinetics (Stumm-
Zollinger and Harris, 1971), and maximum degradation rate, half-saturation
constant, and yield factor were obtained by least squares fit.

     All laboratory studies are simplifications of the actual  phenomena
occurring in nature.  They are well-defined and controllable, but suffer
from the fact that they contain only a few compartments and consequently
important systems interactions may be unobserved.  In field studies, how-
ever, the extreme variability and uncontrollability make mechanistic stu-
dies of the ecosystem difficult.  A physical model, the Aquatic Ecosystem
Simulator (AEcoS), has been developed to bridge the gap between laboratory
and field studies.  The facility was designed to simulate the complexity
of natural field systems as closely as possible, thus providing the realism
of a field study with the controllability of a laboratory system.

     To test the mathematical model, results obtained by Wolfe e_t al_. (in
press) for chemical hydrolysis of malathion and results obtained by Paris
et^al. (1975) for microbial degradation were incorporated into the model.
Based on simulations using laboratory coefficients a series of AEcoS ex-
periments were run to verify the proposed mechanisms.
                        MATERIALS AND METHODS

     The facility used in the experiments consisted of a channel, 19.5 m
long by 46 cm wide by 46 cm deep, enclosed in an environmentally controlled
chamber.   A detailed description of the facility has been presented by
Sanders and Falco (1973).

     Bacterial  cultures were kindly supplied by Doris F. Paris, Environ-
mental  Research Laboratory, U.S. Environmental Protection Agency, Athens,
                                     98

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Georgia.  In all  experiments, bacteria were continuously inoculated into
the channel  inlet from a chemostat as shown in Figure 1.  Bacterial cul-
tures were maintained in the feed chemostat on 1/100 strength nutrient
broth to which was added malathion in quantities to sustain a nominal  chemo-
stat effluent concentration of 0.5 mg/1.

            Figure 1.  End view of the channel showing bacteria feed
                      system.
     The water supplied to the channel  was once deionized and once distilled,
In microbial  degradation experiments,  compounds were  added in the  ratios
shown in Table 1,  and in quantities  designed to sustain the inlet  concen-
tration of o-POit phosphorus at 90 yg/1, N03 nitrogen  at 300 yg/1,  NH3  nitro-
gen at 450 yg/1, glucose at 6.0 mg/1,  and malathion at 1.0 mg/1.   Secondary
reagent grade (97% pure) malathion,  provided by American Cyanamid  Co.,  was
used.  All other compounds were reagent grade.

                                     99

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     TABLE 1.   RELATIVE  AMOUNTS OF COMPOUNDS  IN NUTRIENT MEDIA



           Compound             Ratio to Amount of (NHit)2SOt+ Added


    Na2HP04«7H20                           0.195 mg/mg

    KH2 P04                                99.4 yg/mg

    KN03                                   1-02 mg/mg

    MgS04-7H20                             10.3 yg/mg

    Glucose                                1.39 mg/mg

    Hunter's Trace Solution                0.938 yl/mg
     In the alkaline hydrolysis experiments,  the same nutrient composition
was used with two exceptions:   the solution contained no glucose and the
ratio of nitrate to ammonia was increased from 0.667 to 1.   Absolute con-
centrations of nutrients at the inlet to the  channel were maintained at
30 yg/1 o-PO^ phosphorus, 150  yg/1 NHq nitrogen, and 150 yg/1  N03 nitrogen
during the hydrolysis experiments.   Iris buffer was also added continu-
ously in the channel inlet to  maintain desired inlet pH.

     The feed system that supplied nutrients  and malathion  to the channel
consisted of two closed 40-liter carboys, one containing concentrated nu-
trient solution and one containing concentrated malathion solution.  For
alkaline hydrolysis experiments a third carboy was used to  supply the
channel with tris buffer.  These solutions were pumped to the channel in-
let by peristaltic pumps, which regulated the supply of nutrients and
malathion.  Nutrient stocks were autoclaved after preparation and malathion
solutions were filter-sterilized after preparation.  A bacterial contamin-
ant, however, was found in some malathion stocks that filter-sterilization
did not eliminate.  To eliminate this contaminant, an aliquot of acetone
was mixed with the malathion sample and the mixture was allowed to stand
for approximately one hour, during which the  bacteria cells were lysed.
Acetone was removed by evaporation.

     The nutrient feed system  for the chemostat was similar to the channel
feed system with the exception that only one  carboy containing both nutri-
ent and malathion was used.  Influent nutrient broth concentration was se-
lected to yield approximately  1 x 108 bacteria/ml in the chemostat effluent.
Flow rate through the chemostat was set at 1  ml/min and consequently the
bacteria count in the channel  influent was 1.9 x 105 cells/ml.

     The procedure for start-up of microbial  degradation experiments was as
follows:

     1.  Filled chemostats were inoculated with bacteria and allowed to

                                     100

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         stand for 24 hours to develop the culture.

     2.  Channel flow was set at 0.525 liters/min and paddle wheel rota-
         tion speed was set at 2 rpm.

     3.  Chemostat flow was started and effluent stream was directed into
         channel inlet.

     4.  Twenty-four hours after the start-up of chemostat flow, nutrient
         and malathion flows into the channel inlet were started.

     5.  The channel was operated at least eight days to allow the system
         to come to steady-state.

     The procedure for start-up of chemical degradation experiments was the
 same as for the microbial degradation experiments with the exception that
 steps  1 and 3 were deleted and nominal channel flow was set at 1.31 liter/
 min.

     In the first microbial degradation experiment, both air and inlet water
 temperatures were set at 22°C.  In the second experiment, temperatures were
 set at 27°C, and in the third and fourth experiments, temperatures were set
 at 32°C.  All chemical degradation experiments were carried out at 27°C.

     During the transient period of all tests, chemical determinations and
 bacteria counts were measured at nine equally spaced sampling locations
 along  the length of the channel at least once a day.  During the steady-
 state  period, four sets of chemical determinations and bacteria counts were
 made at each of the nine sampling stations.  Determination of o-OPi* phos-
 phorous, N03 nitrogen, NH3 nitrogen, and glucose were accomplished by an
 automated auto-analyzer system described by Kollig (in preparation).  Mala-
 thion  analysis was accomplished by extracting water samples with 2,2,4-tri-
 methylpentane (isooctane) and analyzing the extract by gas-liquid chromatog-
 raphy.  Determinations were performed using a Tracer MT550 GC with a nickel
 63 electron capture detector.  A 1.8 meter long by 0.64 cm diameter column
 packed with a 3% S.E. 30 on 80/100 mesh Gas Chrom Q was used at a column
 oven temperature of 220°C.

     Viable bacteria concentrations were estimated by plate counts (Stan-
 dard Methods, 1965).  Tryptone-glucose-extract agar was used as plating
 medium and the cultures were incubated at 32°C.  Species existing in water
 samples taken during two microbial experiments were confirmed as

                •  Flavobacterium meningosepticum
                •  Xanthomonas species
                •  Comanonas terrigeri
                •  Pseudomonas cepacia

     A low background level of other bacteria (three Bacillus species) was
 observed during the experiment.

     Water temperatures were recorded at the nine sampling stations at least
once per day during each experiment.

-------
Water flow rate and relative humidity were also recorded daily.


                          MATHEMATICAL MODEL

     The continuity equation describing the movement and transformations
of material is well known.  For one dimensional incompressible flow des-
cribing the flow regime in our channel experiments and in many natural
riverine ecosystems, the equation is


        9C.     D 32C.        v  3C.
        _L  =    	L   -      —L   +   S.  ±  £ R..
                                ax         n     j  1J
where         C.      =  concentration of constituent  i

              D       =  dispersion coefficient

              R..     =  rate of production or elimination of constituent  i
               1J        by pathway  j

              S.      =  source strength of component  i

              t       =  time

              x       =  distance in the direction of flow
In equation 1, no distinction is made between point source loads and non-
point source loads.  A point source load is simply described by a Dirac
delta function.

     The major effort in modeling is usually directed toward development of
an adequate representation for R.JJ.  In the case of malathion, two competing
processes occur, namely, alkaline hydrolysis and bacterial degradation.

     Wolfe et_ aj_. (in press) modeled the degradation of malathion by alka-
line hydrolysis as a second-order reaction, i.e.,

              Rhydrolysis =    klCOHCM                             (2)


where         k.      =  second-order rate coefficient

              CQM     =  concentration of hydroxide ion

              C^      =  concentration of malathion

They note that two competing temperature dependent reactions occur.  An
elimination reaction favored at elevated temperatures results in the pro-
duction of diethyl fumarate and 0,0-dimethyl-phosphorodithioic acid.  The
                                     102

-------
second reaction, favored at low temperatures, results in an intermediate

malathion monoacid product that has environmental significance because of

its persistence in the environment.


     In modeling alkaline degradation, therefore, we have separated the

rate coefficient into two contributions
                                    kelim     +     khydrol
Using the data provided by Wolfe et a! .  (in press), we fit each of the

coefficients to the following equations:
                  kel1n,     '       A,  exp  <-i>                (4)
                  k,,  ,   =       B,   exp  {- S2.}                (5)
                   hydrol            l     H     T                  ^  '




where       Als A2, B19 and B2 are fit coefficients and



            T     =     Temperature (°K)





     Paris et_ al_.  (1975) proposed two models to describe the bacterial

degradation of malathion.  For the first they used the standard Monod ex-

pression for growth of an organism and limiting substrate utilization.

The malathion degradation equation for this model is





                   RMal     =     " VCB'CM                       (6)


                                   Y(K  + CJ
                                      m    M

where       Y      =  yield coefficient



            ym     =  maximum degradation rate



            K      =  half saturation constant
             m


            CD     =  bacteria concentration
             D


     The corresponding equation for bacterial growth  on malathion is




                 n          _   ^m'^R'^M                           (7}
                  Bacteria      -^—-—-                           ^''
                                     103

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The second model  proposed is a simple second-order equation, which assumes
that microbial degradation can be described by the equation
                      RMal
where          k2     =    specific microbial degradation rate


     In the model we have developed, equation 6 has been generalized to
account for degradation by any number of species i as follows:
                  R.,

                    j
and microbial growth has been generalized to account for utilization of j
carbon substrates simultaneously as follows:

                             y. . C. C.
                  R..   .  s  1J  3  J                              (10)

                   "      J K1J + CJ


A flow sheet of the computer program developed for the model is shown in
Figure 2.  Input data include length of river reach, average velocity, and
longitudinal dispersion coefficient.  For the finite difference equation used
to approximate equation 1, the river reach is divided into 56 equally spaced
segments.  First- and second-order spatial gradients at all interior points
are approximated by a third- order central difference approximation (Salvadori,
1961 ).   Spatial derivitives are approximated in the first segment of the
reach by a sixth-order forward difference equation and in the last segment
of the reach by a sixth-order backwards difference equation.  Time integra-
tions are accomplished by a Runge-Kutta technique developed by Shampine and
Watts (1974).  Calculations of chemical reaction rates are accomplished in
a separate subroutine as are calculations of microbial growth and degrada-
tion rate.  Thus, other mechanisms for kinetic rates can be substituted into
the program with a minimum of effort.

     Initial conditions are read in for each of 56 segments of the river reach.
Two different inlet boundary conditions can be applied.  The first assumes no
dispersion upstream of the inlet reach.  This boundary condition gives reason-
able results when large non-point source or point source loads are simulated.
The second set of boundary conditions assumes that the concentration at the
inlet is a known constant.  This second assumption appears to give reasonable
results when small downstream inputs are simulated.  No dispersion at the end
of the river reach is always assumed.  Source strengths are assumed to be
constant in the current version of the program and are read in at the begin-
ning of the execution for each of the 56 segments.
                                    104

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    READ INPUT DATA
    READ INITIAL AND
  BOUNDARY CONDITIONS
 READ SOURCE STRENGTHS
   CALCULATE RATE OF
  CHEMICAL DEGRADATION
   CALCULATE  RATE OF
 MICROBIAL DEGRADATION
    CALCULATE  RATES
      OF TRANSPORT
   EXECUTE TIME  STEP
       INTEGRATION
  PRINT CONCENTRATION
        PROFILES
                        NO
           STOP
           END
                                      T  =  T + AT
                                 T       =  T      + T.
                                  PRINT      PRINT    1
Figure  2.  Flow diagram  for malathion degradation program.

                        105

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     To compare results obtained from AEcoS experiments with laboratory
results, the data had to be fit to the mathematical model.  Assuming that
steady-state has been attained, equation 1 can be rewritten as
                      .             +

                 IJ
To obtain a satisfactory least squares fit of the data, malathion concen-
tration data and bacteria counts were averaged over the steady-state period.
The averaged values were substituted into a finite difference approximation
to equation 11 to calculate a rate for bacterial growth and malathion de-
gradation at each of the seven interior sampling stations.  Since only nine
data points were available, a second-order central difference was used to
approximate first and second spatial derivatives at the five most interior
points.  A fourth-order forward difference approximation was used at the
second sampling location, and fourth-order backward difference approxima-
tion was used at the eighth sampling location.

     The seven rates were then fit to either equation 2 or equation 7 by a
nonlinear least squares fit using a Marquardt-Levenberg iterative curve-
fitting algorithm (Knott, 1972).


                       RESULTS AND CONCLUSIONS

     Typical simulation results are shown in Figures 3, 4, 5, and 6.  Fig-
ure 3 is a plot of malathion concentration versus time of travel that would
result under flow conditions in which longitudinal dispersion is small and
degradation is attributable to alkaline hydrolysis.  The effect of tempera-
ture variation is quite large.  Figure 4 shows the effect of pH on malathion
concentration profiles.  A change in pH has a dramatic effect on the rate of
hydrolysis.  Figure 5 shows malathion concentration profiles as a function
of the glucose concentration at the inlet of the reach.  All of these model
simulations were obtained using coefficients reported by Paris et al_. (1975)
and Wolfe et_ £l_. (in press).

     By comparing the rates of malathion degradation by alkaline hydrolysis
and microbial action, combinations of environmental conditions can be de-
fined in which either hydrolysis or microbial degradation is the dominant
pathway of malathion breakdown.  Figure 6 illustrates this comparison.  At
high pH and low bacteria counts, alkaline hydrolysis is the major degrada-
tion pathway.  At low pH and high bacteria counts, microbial degradation is
the major degradation pathway.

     Typical  results from alkaline degradation experiments (pH 8.25) con-
ducted in AEcoS are shown in Figure 7.  Second-order rate coefficients for
malathion degradation calculated from least squares fit of AEcoS data are
compared in Table 2 with coefficients determined in the laboratory-  Rate
coefficients  calculated from AEcoS experiments are approximately 26% lower
than those obtained in the laboratory.

                                    106

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0-0
0
         4          8         12        16

            TIME  OF  FLOW,  days


Figure 3. Effect of variation in temperature on alkaline degra-
       dation of malathion.
                                                        20
16-0
                                      TEMP = 27°C
0-0.
     -pH = 8-0
                       pH=7-4 pH = 7-2  pH =7-1
                                                  pH=7-C
    0
           10        20        30        40

             TIME  OF  FLOW,  days
                                                   50
     Figure 4. Effect of variations in pH on alkaline degradation of
            malathion.

                          107

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                                    0-095 mg/l  GLUCOSE
                    0-47 mg/l  GLUCOSE


                     0-95 mg/l GLUCOSE
       0-0
                       TIME  OF FLOW,  days
           Figure 5.  Effect of variations in utilizable carbon loads on
                   microbial degradation of malathion.
            TEMP - 27°C
pH
    8
    7
    6-
    5-
                                                          X
                                                           /
                                      /
                                  /
                                 /
       CHEMICAL DEGRADATION ^—»
       MORE  THAN 75% OF      '
       TOTAL               x
                          /   /   /
                                                                /
                                                              X
                                                               /
CHEMICAL DEGRADATION/
MORE  THAN 50%     /
OF TOTAL
                  X
                                               /_
                                                V
                                    /
                                 /
                                  /
                               /
                              /
                       / BACTERIAL  DEGRA-
                      /   DATION MORE THAN
                     A    50% OF TOTAL

                   '  I
                 /  BACTERIAL DEGRADATION
                /   MORE THAN 75% OF TOTAL
10      10      10°
 BACTERIA  CONG
                10       10
           ,  bacteria/ml
                                                       10
10'
           Figure 6.  Comparison of microbial  and alkaline hydrolysis
                   degradation pathways.
                                108

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                    0-6
                                          pH  8'25

                                          TEMP = 27°C
                     0-0
                                             I
                                _L
                             0'5      1-0      1-5      2-0

                             TIME OF FLOW, days
    Figure 7.  Typical steady-state malathion concentration profile
               observed in AEcoS during alkaline degradation study.
     TABLE 2.  COMPARISON OF RATE COEFFICIENTS FOR ALKALINE
               DEGRADATION BETWEEN LABORATORY AND AEcoS STUDIES
pH k
7.5
8.25
;i (M«sec~
3.
4.
i
)
86
1
2
(AEcoS Study)
± 0.
± 0.
11
47
ki (M-sec
5
5
-1)
.4 ±
.4 ±
(Laboratory
0.
0.
1
1
Study)


     Typical  results for microbial degradation are shown in Figures 8 and 9
The decline of bacteria concentration down the length of the channel indi-
cates that the rate of utilization of malathion as an energy source is too
slow to fulfill the metabolic requirements of the organisms.  Consequently,
to describe the dynamic behavior of the microbial population, a death term
was added to the model
  where
             =   -k-CB

k  =  specific death rate

                 109
                                                                       (12)

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4-0
                                              pH<6-8
                                              TEMP = 27°C
                   TIME OF  FLOW,  days
         Figure 8. Typical  steady-state bacteria concentration profile
                observed in AEcoS during microbial degradation study.
                                     pH<6-8
                                     TEMP  =  27°C
                                     BACTERIA CONG =
                                         3-0 x I0  cell/ml
                          23
                   TIME  OF  FLOW,  days
         Figure 9.  Typical steady-state malathion concentration profile
                 observed in AEcoS during microbial  degradation study.
                               110

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Values obtained for specific death rates by a least squares fit of bacteria
data from each experiment are shown in Table 3.

     TABLE 3.  SPECIFIC DEATH RATE FOR BACTERIA CULTURES USED
               IN AEcoS MICROBIAL DEGRADATION EXPERIMENTS
                    Temperature
k (min"1) x 10"1*
22°C
27°C
32°C
0.98
1.86
0.10
0.72
     Glucose fed into the channel inlet was effectively utilized at the point
of injection.  Consequently, equation 12 described the total  change in bac-
teria concentration down the length of the channel.  The only apparent effect
of variation in glucose input was in regulating the size of the bacterial
.population at the channel inlet.  Second-order rate coefficients for microbial
degradation of malathion calculated from least squares fits of AEcoS data
are compared in Table 4 with coefficients evaluated in the laboratory.  The
values calculated from AEcoS experiments are again lower than values ob-
tained in laboratory studies.  Reproducibility of results was fair for the
one test replicated at 32°C.

     TABLE 4.  COMPARISON OF RATE COEFFICIENTS FOR MICROBIAL
               DEGRADATION BETWEEN AEcoS AND LABORATORY STUDIES
                 K2  (AEcoS Study)        k2  (Laboratory Study)
Temperature   (1 org^hr'1)  x  10~12     (1  org^hr"1)  x  10"12
22°C
27°C
32°C

0.59 ± 0.31
1.3 ± 0.52
0.77 ± 0.46
1.38 ± 0.58

4.9 ± 2.1, 2.5a


Coefficient calculated from Monod constants reported by Paris et aj_. (1975)
 and malathion concentration of 0.8 mg/1.

     Flask experiments and background tests conducted in AEcoS, indicated
that bacteria entering the system from chamber air and inflgwing water sup-
ply made no significant contribution to malathion degradation.  Their con-
tribution to the total bacterial population was also small (less than 10%
of the total population).
                                     Ill

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     The difference in degradation rates  between chamber experiments and
laboratory experiments cannot be attributed to changes in non-limiting
nutrient concentrations in the case of microbial degradation; in flask ex-
periments varying the amounts of non-limiting nutrients produced no detect-
able effect on the rate of degradation.   The difference in rate of degrada-
tion in the case of hydrolysis reaction  could be due to differences in the
buffers used.

     We suggest an alternative explanation.   In laboratory studies reported,
solutions were well-mixed, i.e., systems  were characterized by high turbu-
lence levels.   In AEcoS experiments,  the  turbulence levels were low.  The
low level of turbulence introduces the possibility of mass transport limi-
tations to the degradation of malathion by  bacteria.   Hydrolysis of malathion
may be similarly affected, although it is less likely because of the molecular
nature of the  reaction.  Further experimentation would be required to deter-
mine the source of the differences in these experiments.

     A few further tests must be done to  gather additional  background data
for the microbial system under study.   The  next major system scheduled for
testing includes an algal  component.   In  this series  of experiments, a green
and a blue-green algae will  be added  to the bacterial  system and its effects
on malathion degradation rate will  be studied.

     The results of the experiments completed in the AEcoS were similar
to those obtained in laboratory studies.  However, the rates of the two
processes studied in the AEcoS were significantly lower than those ob-
tained in laboratory studies.  For valid  extrapolation of laboratory re-
sults to field situations, phenomena  causing this reduced rate should be
studied.  If it is due to mass transport  limitations, the effect will be
even more important for fast processes, e.g., phosphorus  cycling.
                                     112

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                              REFERENCES
American Public Health Association, Inc.   Standard Method for the Examin-
     ation of Water and Wastewater 1965.   1965.

U.S. Environmental Protection Agency.   Initial  Scientific and Minieconomic
     Review of Malathion.  EPA Report 540-1-75-005.  1975.

Koivistoinen, P. and H. Aalto.  Malathion Residues and Their Fate in  Cereals.
     Nuclear Techniques for Studying Pesticide  Residue Problems.   Proceedings
     of a panel, Vienna, December 16-20,  1968.   International Atomic  Energy
     Agency, Vienna.  1970.

Knott, G.D. and D.X. Reece.  MLAB:  A Civilized Curve-Fitting System.
     Proceedings of the Online "72 International  Conference, Brunei Uni-
     versity, England.  September, 1972.

Kollig, H.P.  An Automated Chemical Analytical  System for an Aquatic  Eco-
     system Simulator.   Environmental Research  Laboratory,  Athens, Georgia.
     In preparation.

Paris, D.F., D.L. Lewis, and N.L. Wolfe.   Rate  of Degradation of  Malathion
     by Bacteria Isolated From an Aquatic System.   Environmental  Science
     and Technology.  9(2):  135-138,  1975.

Salvador!, M.G. and M.L. Baron.   Numerical Methods in Engineering.
     Prentice-Hall, Inc., Englewood Cliffs,  New  Jersey,  p. 65-95.   1961.

Sanders, W.M. and J.W. Falco.  Ecosystem  Simulation for Water Pollution
     Research.  In:  Advances in Water Pollution  Research.   Pergamon  Press,
     New York.  p. 243-253.  1973.

Shampine, L.F. and H.A. Watts.  Global Error Estimation  for  Ordinary  Dif-
     ferential Equations.  Sandia Laboratories  Report SLA-74-0198.  Sandia
     Laboratories, Albuquerque,  New Mexico.   1974.

Stumm-Zol linger, E. and R.H.  Harris.   In:  Organic Compounds in Aquatic
     Environments.  Faust, S.J.  and J.V.  Hunter  (eds.).  Marcel  Dekker,  Inc.,
     New York.  Chapter 23.

Wolfe, N.L., R.G. Zepp, J.A.  Gordon,  and  G.L. Baughman.   The Kinetics of
     Chemical Degradation of Malathion in Water.   Environmental Research
     Laboratory, Athens, Georgia.  In  press.
                                    113

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             Shagawa Lake Recovery Characteristics
                As Depicted by Predictive Modeling

                     D.P. Larsen and H.T. Mercier*

                              ABSTRACT

          Predictions  obtained using several mass balance models
          describing  changes  expected in lake phosphorus concen-
          trations  resulting  from an external phosphorus supply
          reduction to Shagawa Lake were compared with observa-
          tions.  Two of  the  models predicted a rapid recovery of
          the lake  and underestimated present wintertime phos-
          phorus  concentrations by about 50%.  A third model which
          includes  an algal biomass component projected similar
          wintertime  total  phosphorus concentrations but showed
          how internal sources of phosphorus can delay the attain-
          ment of this level.  Two of these models were used to
          project lake phosphorus concentrations expected if
          wastewater  phosphorus concentrations were allowed to
          increase  from the present 50 yg/1 to 400 yg/1 and 1.0
          mg/1.   Both suggest that at effluent concentrations of
          1.0 mg/1, the lake  would exhibit phosphorus concentra-
          tions  often associated with a eutrophic state.

                             INTRODUCTION

     The use of mathematical  models as tools to assist in understanding
the dynamics of aquatic ecosystems as well as to predict their responses
to man induced perturbations  has increased dramatically in recent years.
A partial  listing of  aquatic  ecosystem model's includes those developed
and used by 85 investigators  responding to a survey inquiry conducted
during 1974 (Parker and Roop, 1974); many others exist.  Models which
describe lake trophic state and algal dynamics (reflecting trophic state)
have been  developed at several levels of complexity.  Vollenweider (1969,
1975) has  advocated single  compartment phosphorus mass balance .models on
the premise that lake phosphorus concentrations provide an estimate of
trophic state and algal concentrations.  Others have expanded and elabo-
rated this type  of model  with good success.

     Slightly more  complex  phosphorus lake models have dealt with a two
compartment (particulate  and  dissolved), vertically stratified (epilim-
inion and  hypolimnion) system (Snodgrass and O'Melia, 1975; Imboden,
*Corvallis  Environmental Research Laboratory, U.S. Environmental Protection
Agency,  Corvallis,  OR   97330

                                   114

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1973, 1974).  These models are more effective when considering seasonal
changes in phosphorus levels and might be more effective when predicting
average phosphorus concentrations  (usually taken as values observed at
vernal circulation).  More complex models describe the interrelationships
between various components of aquatic ecosystems including nutrients,
algae, herbivores, carnivores, and decomposers (Chen, 1970; Park, et
al., 1974; Thomann, et al., 1975; Baca, et al., 1974).  These models may
have three spatial dimensions, but are often one or two dimensional.

     At Shagawa Lake, Minnesota, an opportunity exists to test the
predictive capabilities of representatives of these models of several
levels of complexity in describing the lake's response to a large-scale,
man induced, environmental perturbation:  the phosphorus supply to
Shagawa Lake was reduced to about 20% of its former level by removing
essentially all of the wastewater phosphorus which could enter the lake.
This report compares results of predictions using models developed by
Vollenweider (1969, 1975), Snodgrass and O'Melia (1975), and a simplified
epilimnetic algal model similar to those developed by Thomann, et al.
(1975), and Baca, et al. (1974) with observations in the lake.  In
addition, since it is unlikely that the wastewater phosphorus removal
efficiency will continue at its present level because the operation is
expensive, projections using higher wastewater phosphorus concentrations,
up to 1.0 mg/1 (the Minnesota State Standard) are included.

     Shagawa Lake, a shallow (mean depth 5.7m) lake located in north-
eastern Minnesota, has received wastewater from the city of Ely since
about 1880 when the development of mining and logging industries attracted
hundreds of settlers.  As a result the lake became eutrophic.  A tertiary
wastewater treatment plant designed to reduce effluent phosphorus concentra^
tions to 50 yg P/l, (a 99% reduction) became operational in early 1973.
Since wastewater accounted for approximately 80% of the total supply of
phosphorus to Shagawa Lake from surface sources, (the remainder origi-
nating primarily from natural sources), its removal  should cause a
dramatic change in lake conditions.  Detailed background of the project
and documentation of nutrient loads and limnological  characteristics of
Shagawa Lake can be found in Larsen and Malueg (.1975), Larsen, et al.
(1975), Malueg, et al. (1973), Malueg, et al. (1975), and Schults,
Malueg, and Smith (1975).

                     VOLLENWEIDER MODEL

     Based upon earlier work (Biffi, 1963;  Piontelli  and Tonolli, 1964)
Vollenweider (1969, 1975) developed a mass  balance model for total
phosphorus in lakes to include external supplies, loss through the
outflow and sedimentation.   He chose to describe sedimentation as a
function of the amount of phosphorus in the lake, proposing the following
equation:
                               115

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                      '  *p - <>w + V


where [P] = total phosphorus concentration in the lake (M L   )

      si   = volumnar phosphorus supply (ML   T  )

      p   = hydraulic washout coefficient (T  )
       w                                  _1
      a   = sedimentation rate constant (T  )

      t   = time (T).

Assuming constant £  , p , and a , a time dependent solution to equation

(1) can be obtained analytically as


     [P(t)] - [Pje -(pw + V*    f    -^- (1 - e -(pw + V*) (2)
                u                       Mw    p

     Assumptions are:  a well-mixed lake, constant lake volume, outflow
concentration equivalent to lake concentration, equivalent inflow and
outflow rates, and no net supply from the sediments.  An important point
is that this model is essentially an accountability statement, i.e.,
material in the lake occurs as a balance between supplies and losses.
The only hypothesis contained in equation (1) is that sedimentation is a
function of the amount of phosphorus in the lake (Vollenweider, 1975).
Models of this general nature have been described often (Dillon, 1974).

     The solution, equation (2), to equation (1) depends on an experiment-
ally difficult to determine sedimentation rate coefficient, a .  Dillon
and Rigler (1974) and Sonzogni, et al. (1975) have proposed alternative
means to obtain its value.  These methods were used to estimate a  ; the
results are summarized in Table 1.  Other variables and coefficients can
be determined experimentally.

     Equation (1) was solved using flow and phosphorus loading data for
1973 and 1974 (see Malueg, et al., (1975) for flow and loading calculation
methods).  For projections beyond 1974, projected wastewater  flows and
phosphorus concentrations were added to average natural flow  and phospho-
rus concentrations (based upon data obtained during 1972 and  1973).
Model response was compared with wintertime total phosphorus  values.
Springtime concentrations are usually used for comparisons because a
lake is likely to be well mixed at this time, but in Shagawa  Lake,
concentrations change rapidly shortly after ice-out.  For example,
during the three weeks subsequent to ice-out in 1973, mean total phospho-
rus concentrations declined from 63 yg/1 to 44 yg/1.  During  the interval
from mid-December to mid-January each year, mean concentrations changed
                               116

-------
only slightly, and  hence, were  taken as  better representatives of mean
conditions.  These  mean  values  were determined as follows.  Each week a
volume-weighted average  lake concentration was calculated from vertical
profiles  (1.5 m depth  interval)  located  at three stations in the lake.
These weekly values were then averaged over the interval from mid-
December  to mid-January.

     Figure 1 compares the expected response of Shagawa Lake to reduced
phosphorus input using this model with the wintertime total phosphorus
values.   One run displays the expected lake response treating total
phosphorus as a conservative substance (a =0; termed the hydraulic
washout model); the second run  includes  the deposition term (a =0.852
  -1                                                          "
yr   ; termed the phosphorus washout model).  Both runs suggest that
Shagawa Lake should respond rapidly to the reduced phosphorus supply,
attaining a stable  state within  two years.  The expected time required
to reach  95% of a steady state  value can be used as a measure of the
responsiveness of lakes  to changed inputs.  This is usually given as
three times the phosphorus retention time (T =l/(p +a )) or 1.3 yr for
                                            p     w  p
Shagawa Lake using  the values summarized in Table 1.  Hence, this model
suggests  that a new stable state should  have occurred by mid-1974.  The
phosphorus washout  model suggests that mean lake concentrations should
be 10-12  yg/1 when  a steady state is attained if phosphorus deposition
is similar to that  observed during pretreatment years.  The hydraulic
washout model suggests a mean lake concentration of 17-20 yg/1, equiva-
lent to the mean influent concentration.   Sufficient time has elapsed
for the lake to have achieved a  new stable state.  Figure 1 suggests that
the lake  responded  rapidly; however, mean concentrations have not declined
to expected levels.  In  fact, mean concentrations are approximately
twice as  high as those predicted from the phosphorus washout model  and
are higher than those suggested  by the hydraulic washout model  alone.
There is  an indication that the  lake may have achieved a stable state,
since late 1974 winter time total phosphorus concentrations are similar
to those  during late winter 1975 (Figure 1).  This lake concentration
is higher than mean influent concentrations, hence must be maintained
by an internal supply of phosphorus.

     Although the lake has not responded entirely as predicted by these
washout models, it  is instructive to speculate on what can be expected
if the wastewater phosphorus concentration is altered from its present
level of  50 yg/1 to a higher level.   The steady state solution to
equation  (1)  can be written (Larsen and Mercier, 1975) as

                         [P] = [p] (1  - Rp)                      (3)

where [p] = average influent phosphorus concentration (M L" ) and
                                                 a
       R  = phosphorus retention coefficient = 	f—-
        P                                      pw    p
            (Vollenweider,  1975).

                              117

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     60
|   SOjjO
  „  40
Z)
cr
o
x
CL
c/)
O
X
CL
     30
     20
O    10
       0
            °°
           0
                0
                  o
                   o
                     o
                      °
                       o
                     •    00
                                       oooo        o
                                   oooo    ooooooo
                                     • •
                                    * *
                1973
  1974

YEAR
                                                    1975
    Figure 1.  Comparison of response of Vollenweider mass balance model

             with  lake observations.  Solid circles represent model run
             with  phosphorus deposition; open circles represent no depo-
             sition.  Lake observations are mean wintertime values (see

             text) j^ 1 standard deviation.
                               118

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     TABLE  1.   ESTIMATES  OF PW AND a  FOR SHAGAWA LAKE
                                  pw            gp
                                    -1             -1
                                      )         (yr  )
                  1971             1.85          0.67a

                                                0.88b

                  1972             1.26          0.82a

                                                0.93b


a)  determined from R  =     Pp_    =   1   -   Annual  Export  ± Lake  Change
                     P     p  + a                   Annual  P Import

    (Dillon  and Rigler,  1974).

b)  determined from steady state solution  of mass  balance model

    (Equation  1).   (Sonzogni, et al.,  1975).
     TABLE  2.   POTENTIAL  EFFECT  OF DIFFERENT  WASTEWATER  EFFLUENT
               PHOSPHORUS CONCENTRATIONS  ON MEAN  LAKE  CONCENTRATIONS
Wastewater
Effluent Cone.
yg/1
50

200

400
700

1000
% of
Natural Supply

6

22

45
79

113
Mean Influent
Cone.
yg/1
18

20

24
30

35
Expected Mean
Lake Cone.
yg/1
12
Meso-
13
trophic
16
20
Eutrophi<
23
                                    119

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This relationship expresses the concept/that the steady state lake
concentration will be equivalent to the mean influent phosphorus concen-
tration in the absence of deposition of phosphorus (i.e. if phosphorus
were a conservative substance).  The effect of phosphorus deposition is
to reduce the mean influent concentration and this effect can be expressed
as the phosphorus retention coefficient, that fraction of incoming
phosphorus which is retained by the sediments.

     Equation C3) was used to project the effect of alternative waste-
water effluent total phosphorus concentrations upon mean lake concentra-
tions.  The results, using total phosphorus effluent concentrations up
to 1.0 mg/1, are summarized in Table 2.  This analysis suggests that
wastewater effluent phosphorus concentrations of 700 yg/1 or greater
might produce a eutrophic lake while the present effluent concentrations
of 50 pg/1 might produce a lake of lower mesotrophic classification.  A
400 yg/1 effluent concentration, equivalent to about a 90% secondary
wastewater phosphorus reduction, might produce a mid-mesotrophic lake.
It is interesting to note that an effluent concentration of 1.0 mg/1
would provide a supply of phosphorus approximately equivalent to the
supply from all other sources.  The classification of lakes into trophic
categories is difficult; here the guidelines suggested by Vollenweider
(1968) and Dillon (1975) have been adopted.

     These projections provide an estimate of the state toward which the
lake might stabilize and are based upon the assumption that the sediments
will act as a net sink for phosphorus as they did prior to 1973.  If
this basic model is correct the recent wintertime total phosphorus
concentrations might typify lake characteristics at an effluent of 1.0
mg/1 after stable conditions have been attained.

                  SNODGRASS - O'MELIA MODEL

     Snodgrass and O'Melia (1975) proposed a more complex mass balance
model which includes particulate and ortho-phosphorus, divides the lake
into epi- and hypolimnia, each well mixed, and incorporates two seasons,
each 180 days.  One represents summer conditions during which stratifica-
tion occurs and the other hypothesizes a well mixed lake.  Lake processes
include:   conversion of ortho-phosphorus into particulate phosphorus,
sedimentation of particulate phosphorus, decomposition of particulate
phosphorus into ortho-phosphorus, and vertical exchange of material
across the epilimnion-hypolimnion boundary.  An effect of flocculation
was developed such that the net sinking velocity in deep lakes was
greater than that in shallow lakes.  Although they specifically state
that the model is applicable to lakes whose hypolimnia remain aerobic
throughout the year, it was instructive to apply the model to Shagawa
Lake, in which anaerobic conditions have regularly developed each year
during late winter (before ice-out) and during late summer.
                                120

-------
     The equations and model coefficients are summarized in Table 3.
Snodgrass and O'Melia estimated coefficients from the literature and
calibrated the model using Lake Ontario data.  The coefficients they
presented were used for the Shagawa Lake runs except those that were
site specific (e.g., mean depth, volume, etc.).  External water and
phosphorus supplies used were those observed for Shagawa Lake.

     Predicted year end total phosphorus concentrations were compared
with lake observations obtained during mid-December to mid-January as
before (Figure 2).  This interval was also selected to minimize the
effects of sediment phosphorus supply during anaerobic periods thereby
potentially minimizing the model constraint of aerobic conditions through-
out the year.  For the years prior to treatment (1968-1972), the model
results are quite close to observed values with the exception of the
single value for 1967-1968 when the model projects total phosphorus
concentrations of about 46 vg/1 and the lake mean during the only week
for which data were obtained was 28 yg/1.

     It is particularly encouraging that the lake observations and model
response for the last three pretreatment years (1970-1971, 1971-1972,
1972-1973) are in close agreement when sampling frequency had been
increased.  This agreement might occur because the phosphorus pulses
which occur in the lake during anaerobic intervals deposit rapidly
subsequent to circulation periods, hence, their effect on wintertime
averages is minimized.  However, model projections subsequent to treat-
ment are similar to those predicted by the Vollenweider model, suggesting
total phosphorus concentrations near 10 yg/1, substantially below observed
values.

                      EPILIMNION MODEL

     A three compartment model was constructed to describe the seasonal
changes in total phosphorus and algal phosphorus within the well mixed
epilimnion (5.25 m) of Shagawa Lake and to predict recovery of the lake
subsequent to treatment.  The model is a simplified version of those
developed by Thomann, et al. (1975) and Baca, et al. (1974).  The following
is a general description of the model structure; equations and coefficient
values are summarized in Table 4.

     The specific rate of growth of algae was related to solar radiation,
temperature, and soluble reactive phosphate; loss rates included the
effects of sinking, conversion into non-algal particulate phosphorus
(lumping the effects of zooplankton grazing and cell death) and washout.
A specific growth rate reduction factor, as a function of total daily
radiation, was generated by averaging Vollenweider's (1964) expression,
relating photosynthesis to light intensity, over a 24 hour day and the
mixed zone as elaborated by Fee (1973).  This integral  can be used to
evaluate relative photosynthesis over the euphotic zone for particular
values of physiological "constants" and various amounts of total daily
                               121

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TABLE 3.   EQUATIONS AND COEFFICIENTS FOR SNODGRASS-0'MELIA  MODEL  (1975) AS APPLIED TO SHAGAWA LAKE
  Summer                           Epilimnion  ortho-  and  participate phosphorus
              d[OPL                                   k..            k..
                                 - Q[OP]   -  pV[OP]
                                        e    eee
                                                        zt
              d[PPl
                                   QEPPJe + PeVe[OP]e  -  geAth[PPJe
                                   Hypolimnion  ortho-  and  particulate phosphorus
                                     th             th
              d[PP]h                                          k,.             k.
                                   - 9hAs[PP]h  -  rhVh[PP]h  +  J* Ath[PP]e  -  -
                                                             Hh             £t
  Winter                            Ortho-  and particulate  phosphorus
            V      -= zQjE'OPlj  - Q[OP]  - PeuVeuEOPj  + rV[PP]
            V       = zQjlPP]j  -  QEPP3 + PeuVeuEOP:i  "  rVlPPj  '  g

                                                                       (Continued)

-------
TABLE 3.  EQUATIONS AND COEFFICIENTS FOR SNODGRASS-O'MELIA
          MODEL (1975) AS APPLIED TO SHAGAWA LAKE (continued)
 Summer Stratification                             Winter Circulation
 ge = 0.1 rag/day                                   9 = gjl  + f(7 - 2^)3
 9h a 900 + fZ~h}                                  go = 0.05 ro/day
 9Q * 0.05 m/day                                   f = 0.05/m
 f = 0.05/m                                        I ,  = 10  ID for I >  10 m
                                                    eu              —
 kth = k = 0.005 I                                 7   = I for I < 10  m
 I~
 Sh
                                                   peu = 0.06/day
 pe = 2.0/day                                      r = 0.03/day

                  Coefficients Specific to Shagawa Lake

 Vg = 39 x 106 m3                                  As = 5.5  km2
 Ath = 5.5 km2                                     V = 53 x  106 m3
 Vh = 14 x 106 m3                                  Veu = 39  x 106 m3

 Ih = 2.54 m                                       Z = 5.25  m

                             List of Symbols
                                                     2
 A    Surface area of the sediment water interface (L )
                                                                     2
 Ath  Horizontal cross-sectional area of a lake at the thermocllne (L  )
 f    Flocculation coefficient (L~ )
 g    Sedimentation coefficient of entire lake (L/T)
 gh   Sedimentation coefficient in the hypolimnion (L/T)
 ge   Sedimentation coefficient in the epilimnion CL/T)
 grt   Sedimentation coefficient in the absence of flocculation CL/T)
  o                                                       o
 kth  Vertical transport coefficient in the thermocllne (L /T)
 p    Production rate coefficient in the epilimnion (T~ )
                                  123

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                 Table 3 (continued),  List of Symbols




p    Production rate coefficient in the euphotic zone, circulation


     model (T~ )
                                                2
Q    Volumetric rate of discharge from a lake (L /T)

                                                         3
Q.   Volumetric rate of inflow to a lake from source j (L /T)
 0                                                     1
r    Decomposition rate coefficient for entire lake (T  )


r.    Decomposition rate coefficient for the hypolimnion (T~ )
t    time
                             o

V    Volume of entire lake (L )
                                q

V    Volume of the epilimnion (L )

                                                        3
V    Volume of the euphotic zone in circulation model (L )
                                 3
     Volume of the hypolimnion (L )
1    Mean lake depth (L)


Z"eu  Mean depth of the euphotic zone, circulation model (L)


Z^   Mean depth of the hypolimnion (L)


Zth  Mean depth of thermocline region (L)


[OP] Concentration of orthophosphate (M/L )
                                                 «3

[PP] Concentration of particulate phosphorus (M/L )
                                124

-------
    60
    50
 CD
    40
T3
CD
 CD
 (/>
-Q
O
30
     10
                                    1972-73  \
                                      (7)
                    1971- 72 (7)
                    1968-69
1974-75 (7)
1970-71
  (6)
                                       T/
               I
         1973-74
           (6)
                                                   I969-7O
                                                      (2)
                                                1968
                                                 (I)
      0
            10
              20
      30
40
50
60
                    P  (Predicted) ,  pg/liter
      Figure 2,
          Comparison of predicted total phosphorus concentrations using
          Snodgrass-O'Melia model with lake wintertime concentrations.
          Solid line is 1:1 correspondence between predictions and obser-
          vations.  Dates mean wintertime values +_ 1  standard deviation
          and numbers of observations making up the mean are indicated
          for lake  observations.  See text for calculation methods.
                                 125

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TABLE 4.  EQUATIONS AND COEFFICIENTS FOR SHAGAWA LAKE EPILIMNION
          PHOSPHORUS MODEL
 Algae:
                          •CN-  + a  + P)  [A]

  Soluble Reactive Phosphorus:
                          Ke
      Ke = 301A] +0.75
      Kp = yg SRP/1
      N1 = 0.05 day"1
      N2 = 0.005 day"1
      CTI = 0.01 day"1
      a2 = 0.007 day"1
       V = 40 x 106 M3
                          +N2[PP] - PW£SRP]

  Non-Algal Particulate Phosphorus:

           d£PPj  =  PPIN   + NJA] - (N? + ay + PUI)EPP]
           ~ar~     "i        '         ^    *    w
                           Model  Coefficients
              =0.59 (1.066T)

 CLITE = 0-172 (1 - e-°-Q07TDR) + O.QQQ451TDR
                                 126
                                                (Continued)

-------
TABLE 4.  EQUATIONS AND COEFFICIENTS FOR SHAGAWA LAKE EPILMNION
          PHOSPHORUS MODEL — LIST OF SYMBOLS
 IA]
 CLITE
  [PP]
  PPIN
  w
  [SRPJ
  SRPIN
  T
  t
  TDR
  V
Concentration of algal phosphorus (M/L )
Fractional reduction in G^CO in epilimnion due to
availability of light
Maximum specific growth rate as a function of
temperature (T  )
Extinction coefficient [L  }
Concentration of SRP at which specific growth rate is
                           o
reduced to 1/2 maximum (M/L )
Conversion rate constant from algal phosphorus into
particulate phosphorus (T  )
Conversion rate constant from non-algal particulate
phosphorus into soluble reactive phosphorus (T~ )
                                                      o
Concentration of non-algal particulate phosphorus (M/L )
Supply of non-algal particulate phosphorus to epilimnion (M/T)
Hydraulic washout coefficient as a function of time (T  )
Settling rate constant for algal phosphorus (corresponding
to a settling velocity of 0.05 m/day) (T~])
Settling rate constant for non-algal particulate phosphorus
(corresponding to a settling velocity of 0.04 m/day) (T~ )
Concentration of soluble reactive phosphate (M/L )
Supply of SRP to epilimnion (M/T)
Temperature as a function of time (°C)
Time (T)
                                                   2
Total daily radiation as a function of time (gcal/L /T)
Epilimnion volume (L )
                                  127

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radiation distributed realistically throughout a daylight day.  Values
used for physiological "constants" were those reported by Fee  (1973).
The expression developed for the reduction factor is given in Table 3
and is similar in form to that presented earlier (Larsen, Mercier, and
Malueg, 1973).  Eppley's (1972) relationship between maximum specific
growth rate and temperature was used.   The hyperbolic expression commonly
used to express the relationship between the rate of uptake of a nutrient
and its concentration in the extracellular medium was used to express
the fractional reduction in specific growth rate related to nutrient
concentration.  First order rate kinetics were used to express the loss
of algal phosphorus to non-algal particulate phosphorus and through
sinking out of the epilimnion.

     External sources of soluble reactive phosphate were wastewater,
tributaries, and precipitation.  An internal supply was added to this,
mimicking the sediment and hypolimnetic supply (this supply is discussed
subsequently).  Particulate phosphorus was converted to soluble reactive
phosphorus using first order kinetics.  Soluble reactive phosphorus
losses were algal consumption and surface outflow.   Particulate phosphorus
originated from tributaries, wastewater and conversion from algae.
Losses were sinking, conversion into soluble reactive phosphorus and
outflow.

     An average water year was constructed from flow data (from all
sources) obtained during 1972 and 1973 to provide daily water input for
model runs.  Weekly soluble reactive and total  phosphorus loads deter-
mined during 1972 and 1973 for all natural sources (all sources excluding
wastewater) were averaged to produce weekly natural loads.  Thus the
flow and loading inputs to the model displayed  the same cycles each
year, representing average "natural" conditions.   During 1972 observed
wastewater loads were added to the natural loads; from 1973 onward,
wastewater loads were calculated as the product of an assumed concentra-
tion in the effluent and the average wastewater flow.

     The model was calibrated by manipulating the coefficients N-,, N2,

a-p and cr2 to fit the 1972-1973 average epilimnetic concentrations

observed in the lake.  Model coefficients were  initially estimated from
those presented in Thomann, et al. (1975) and Baca, et al. (1974) and
references therein.

     An initial estimate of the internal supply of phosphorus was avail-
able from mass balance calculations comparing supplies and losses of
total phosphorus with lake changes for the years  1970-1973.  This
estimate was necessarily a net supply and thus  provided a lower limit to
the supply of phosphorus from internal sources.  It was reasoned that
the lake sediments act like a capacitor, accumulating phosphorus during
the year and releasing it during the anaerobic  intervals.  For the
purposes of this model it was assumed that the  total internal supply for
the year was proportional to the previous year's  deposition.  The supply
                               128

-------
was evenly distributed during two weeks  in  late winter and ten weeks
during the summer, intervals during which anaerobic conditions have
developed in the lake.  For post-treatment years ft was reasoned that
the sediment phosphorus would washout, hence a constant of proportion-
ality greater than 1 was used.  A value  of  1.1 with an initial supply of
60 kg/day provided a good fit.

     Figures 3 and 4 compare calibrated  model runs with lake obser-
vations for total phosphorus and chlorophyll a_.  Algal phosphorus was
converted to chlorophyll a^ using a factor chlorophyll a, = algal^phosphorus^

based upon regressions of chlorophyll a_  on  particulate phosphorus for
lake observations.  This conversion ratio is lower than the more commonly
used 1:1 value (Thomann, et a!., 1975; Baca, et al., 1974).  The runs
presented are not necessarily the best fit  to the data in any statis-
tical sense, but represent runs which approach the actual pattern
observed.  Other combinations of coefficients could be used to produce
approximately the same results.  The selection of coefficients used to
produce these "final" runs is therefore  somewhat arbitrary, and although
techniques exist which provide parameter estimates based upon minimized
deviation techniques, they are somewhat  costly and thus have not yet
been tried.

     The model mimics the temporal pattern of total phosphorus and
chlorophyll ^although some differences  occur both in timing and magnitude
of pulses (Figures 3 and 4).  These differences probably occur because
year to year differences in timing of internal phosphorus pulses, initia-
tion of algal blooms and other factors were not included in the model.
The model is based upon average conditions and produces results which
might be expected in an average year.  The gradual decline in phosphorus
concentrations in the lake is mimicked by the model up through mid-1975
as is a decline in the magnitude of the  summer algal blooms.  It is
interesting that the model projects wintertime phosphorus levels of
about 20 yg/1 during 1974-1975, and appears to stabilize at wintertime
epilimnion levels similar to those projected by the previous models for
the entire lake (Figures 3, 5 and 6), but the time required to reach
this level is considerably longer than that projected by the other
models.  Mean values for the epilimnion  during the mid-December mid-
January are only slightly lower than the average lake levels used to
compare the previous models.

     The calibrated model projections of total phosphorus and algal
concentrations expected if wastewater concentrations were altered are
summarized in Figures 5 and 6.  The model was run until a stable pattern
occurred; the results displayed compared the effects of 50, 400, and
1,000 yg/1 total  phosphorus wastewater concentrations; (total phosphorus
was supplied in a ratio of 30% soluble reactive phosphorus and 70%
particulate phosphorus, consistent with  observations based upon propor-
tions in the present wastewater).  Data  obtained during 1974 are included
for comparison.   The model projections suggest that the total phosphorus
                                129

-------
           100
CO
o
       CD
           Figure 3.  Comparison of predicted  epilimnetic total phosphorus concentrations  (light line)
                     with lake observations.

-------
CO
        7O
        60-
   C   50-
        40
^   30

i
O
o:

q   20
         10
    o|
          0
                  1972
                                              1974


                                           YEAR
1975
1976
         Figure 4.  Comparison of predicted epilimnetic chlorophyll  concentrations (light line)

                   with lake observations.

-------
 0
Figure 5.
                                               50
                     TIME  ,  weeks
Sensitivity of epilimnion model response  (total phosphorus)
to different wastewater total  phosphorus  concentrations
(50,  400, 1000 yg/1) at model  stable state  (light lines)
compared with 1974 lake epilimnion observations.
                            132

-------
   o
Figure 6,
                                                50
                      TIME  ,  weeks
Sensitivity of epilimnion model response (chlorophyll  a_)
to different wastewater total  phosphorus concentrations
(50,  400, 1000 yg/1) at model  stable state  (light lines)
compared with 1974 lake epilimnion observations.
                             133

-------
pattern which might occur if wastewater effluent total phosphorus
concentrations were 1.0 mg/1 would be similar to that observed during
1974 with peak average values of about 60 yg/1 and wintertime concentra-
tions of about 20-25 yg/1.  Chlorophyll a_ concentrations might similarly
exist as they did during 1974 with peak average summertime concentrations
of 25-30 yg/1.  A wastewater effluent concentration of 400 -pg/1 might
produce conditions where total phosphorus concentrations slightly exceed
40 yg/1 during the summer and wintertime concentrations would be approxi-
mately 15 yg/1.  Summertime chlorophyll a_ values might be about 20 yg/1.
These projections rely upon the assumption that the lake will respond in
a fashion similar to the manner in which it has responded in the past.
Of particular significance are the projected phosphorus pulses which
drive the summer blooms.  These seem to be related to the generation of
anaerobic conditions in the bottom waters thus, if, at present wastewater
effluent levels, the deeper waters cease becoming anaerobic, a different
pattern might emerge.  It is also unknown whether higher wastewater
phosphorus concentrations (for example 400 yg/1) will continue to
promote anaerobic conditions, hence provide stimulation for summer algal
blooms.

                         DISCUSSION

     The Vollenweider and Snodgrass-O'Melia models predict lake phosphorus
concentrations considerably below observed values because these models
do not include mechanisms by which phosphorus is supplied from internal
sources, a feature which apparently controls the recovery of the lake to
some extent.  Vollenweider (1975) specifically stated that the mass
balance model he developed is inapplicable to situations in which there
is net annual internal  supply of phosphorus; Snodgrass and O'Melia
restrict the utility of their model  to lakes whose hypolimnia remain
aerobic throughout the year.  Nevertheless, it was instructive to apply
these models to compare their predictions with lake observations to
obtain a measure of the deviation of the Shagawa Lake response from
simple model predictions.   Both models suggest that wintertime total
phosphorus concentrations should be about 10 yg/1.  This value is a
reasonable expectation since mean influent concentrations are presently
about 18 yg/1, and lake concentrations are expected to be less than this
value after a stable state has been achieved.  An empirical  expression
which relates the retention of phosphorus by lakes to the hydraulic
washout coefficient (Larsen and Mercier, 1975) suggests that 45% of
Shagawa's influent phosphorus should be sedimented annually; therefore,
steady state concentrations should be approximately 10 yg/1  as suggested
by the above two models.  Also, total phosphorus concentrations in the
upper 10m of Burntside Lake, upstream of Shagawa Lake and uninfluenced
by urban activities, were approximately 9 yg/1 during 1974.   Thus these
models likely provide good indications of the expected level at which
the lake should stabilize.
                               134

-------
     The effect of  the  internal  source of  phosphorus  has  been to delay
the attainment of these predicted  levels.  This  effect  has been incorpor-
ated in the epilimnion  model by  establishing  the construct that the
internal supply of  phosphorus  is proportional to the  previous years
deposition.  A proportionality greater than 1 implies leeching from the
sediments, i.e. a store which  built over pretreatment years discharges
for sometime subsequent.  A value  of  1 or  less might also represent
sediment leeching since it is  likely  that  only a fraction of deposited
phosphorus is converted into soluble  form.

     The observed wintertime phosphorus concentrations might be the
result of an equilibrium between sediment  phosphorus and  lake phosphorus
maintained above expected levels by high concentrations of phosphorus
within the sediments.   This store  of  sedimentary phosphorus might be
depleted slowly, depending upon  such  characteristics as the size of the
reservoir (both as  available phosphorus within a unit volume of sediments,
and the depth within the sediments to which this phosphorus can release
into overlying water),  hydrodynamic characteristics of the overlying
water, mixing processes within the sediments  themselves, or the extent
to which the sediment-water interface continues to become anaerobic.  If
there is indeed a temporary or permanent equilibrium, the epilimnion
model does not include  mechanisms  to  describe it or its effect on lake
dynamics, as indicated  by the  fact that it predicts wintertime total
phosphorus concentrations similar  to  those of the other models but the
time taken to reach those levels is longer than simple models suggest.
The epilimnion model does show how, by pulsed inputs of phosphorus from
internal sources, average levels of phosphorus during wintertime can be
higher than those predicted by other models and how pulsed phosphorus
inputs during the summertime influence summertime algal biomass as i.s
expected during phosphorus limited conditions.

     There is a precautionary  note which must be considered when evalu-
ating models of complex systems which have been tuned by coefficient
manipulation, particularly if  the models are to be used for predictive
purposes.  The models are abstractions of processes thought to be impor-
tant in controlling the response of ecosystem; however, the model
calibration or tuning process  can hide failure to include some of the
important processes because model coefficients are often difficult to
verify in natural systems.  The experimental values of coefficients used
often display such  ranges that wide latitude is available in selecting
values during calibration to provide an acceptable fit to observed data.
Thus the determination  of the  validity of projections is a somewhat
subjective process and  predictive ability might be poor if important
processes are not included.

     Although models of  the nature of those presented in this paper are
simple representations  of complex systems and often include only estimates
of important rates or coefficients, they provide an indication of some
of the characteristics which can be expected in a lake.   Perhaps more
important,  they provide a framework against which processes within the
lake can be identified, particularly as deviations from model  results.
This can assist in designing or revising experimental approaches to
provide a more complete description of a lake's activity or response.

                               135

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                              REFERENCES

Baca, R. G., M. W. Lorenzen, R. D. Mudd, and L. V. Kimmel.   1974.
     A generalized water quality model for eutrophic lakes  and reservoirs.
     A report prepared for Office of Research and Monitoring, U.S. EPA,
     Washington, DC by Pacific Northwest Laboratories, Battelle, Richland,
     Washington.

Biffi, F.  1963.  Determining the time factor as a characteristic
     trait in the self-purifying power of Laga d'Orta in relation to
     continual  pollution.   Atti 1st. Ven. Sci. Lett. Arti.   121:31-136.

Chen, C. W.  1979.  Concepts and utilities o'f ecologic model.  J. Sanit.
     Eng. Div., Am. Soc. Civil Eng.   96:1085-97.

Dillon, P. J.  1974.   A critical review of Vollenweider's nutrient
     budget model and other related  models.   Water Resources Bull.
     10:969-989.

Dillon, P. J.  1975.   The  phosphorus budget of Cameron Lake, Ontario:
     The importance of flushing to the degree of eutrophy of lakes.
     Limnol. Oceanogr.  20:28-39.

Dillon, P. J.,  and F. H. Rig!er.  1974.   A, test of a simple nutrient
     budget model predicting the phosphorus  concentration in lake water.
     J. Fish. Res. Bd. Can.  31:1771-1778.

Eppley, R. W.  1972.   Temperature and phytoplankton growth  in the
     sea.  Fishery Bull.  70:1063-1085.

Fee, E. J.  1973.  A numerical model for determining integral  primary
     production and its application  to Lake  Michigan.   J. Fish.  Res.
     Board Can. 30:1447-1468.

Imboden, D. M.   1973.  Limnologische Transport- und Nahrstoff-modelle.
     Schweiz. Z. Hydrol. 35:29-68.

Imboden, D. M.   1974.  Phosphorus  model  for  lake eutrophication.
     Limnol. Oceanogr. 19:297-304.

Larsen, D. P.,  and K. W. Malueg.  1975.   Limnology of Shagawa Lake,
     Minnesota, prior to reduction of phosphorus loading.  Hydrobiologia.
     (In Press).

Larsen, D. P.,  K. W.  Malueg, D. W. Schults,  and R. M.  Brice.  1975.
     Response of eutrophic Shagawa Lake, Minnesota, U.S.A.  to point-
     source phosphorus reduction.  Verh. Int.  Ver. Limnol.   19:884-892.

Larsen, D. P.,  and H. T. Mercier.   1975.  Lake phosphorus loading graphs:
     an alternative.   Submitted to J. Fish.  Res. Board Can.

Larsen, D. P.,  H. T.  Mercier, and K. W.  Malueg.  1973.  Modeling algal
     growth dynamics in Shagawa Lake, Minnesota with comments concerning
     projected restoration of the lake.   In:  Modeling the  Eutrophication
     Process (E. J. Middlebrooks,  D. H.  Falkenborg, and T.  E. Maloney,
     eds.).  Proceedings of a Workshop held at Utah State University,
     Logan, September 5-7, 1973.  Published by the Utah Water Research
     Laboratory, Utah State University,  Logan, Utah.  p. 15-31.

                               136

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Malueg,  K. W., R. M.  Brice,  D.  W.  Schults,  and  D.  P. Larsen.   1973.  The
     Shagawa  Lake Project:   Lake  restoration  by nutrient removal from
     wastewater  effluent.  Washington,  D. C., Government Printing Office.
     Ecological  Research Series,  EPA-R3-73-026.  49 p.

Malueg,  K. W., D. P.  Larsen,  D. W.  Schults, and H. T. Mercier.  1975.  A
     six-year water,  phosphorus and nitrogen  budget for Shagawa Lake,
     Minnesota.  J. Environ.  Quality.   4:236-242.

Park, R. A.,  et  al.,   1974.   A  generalized  model for simulating lake
     ecosystems.  Simulation.   23:33-50.

Parker,  R. A., and  D.  Roop.   1974.   Survey  of aquatic ecosystem models.
     The Institute  of Ecology Publication.  131  p.

Piontelli, R., and  V.  Tonolli.  1964.   The  time of retention of lacustrine
     waters in relation to the  phenomena of enrichment in introduced
     substances, with particular  reference  to the  Lago Maggiore.  Mem.
     1st.  Ital.  Idrobiol.  17:247-266.

Schults, D. W.,  K.  W.  Malueg, and  P. D. Smith.   1975.  Limnological
     comparison  of  culturally eutrophic Shagawa Lake and adjacent oligo-
     trophic  Burntside Lake,  Minnesota.  American Midland Naturalist.
     (In Press).

Snodgrass, W. J., and C. R.  O'Melia.  1975.  A  predictive model for
     phosphorus  in  lakes.  Environmental Science and Technology.
     9:937-945.

Sonzogni,  W.  C., P. D. Uttormark,  and G. F. Lee.   1975.  The phosphorus
     residence time model:   theory  and  application.  Submitted to Water
     Research.

Thomann, R. V.,  D.  M.  DiToro, R.  P.  Winfield, and D. J. O'Connor.   1975.
     Mathematical modeling of phytoplankton in  Lake Ontario.   1.  Model
     development and  verification.   EPA-660/3-75-005.  Ecological
     Research Series.  Corvallis,  Oregon,   p. 177.

Vollenweider,  R.  A.   1965.   Calculation models of photosynthesis-depth
     curves and .some implications  regarding day rate estimates  in  primary
     production estimates.   Mem. 1st. Ital.  Idrobiol.  Suppl.   18:425-
     457.

Vollenweider,  R.  A.   1968.   Scientific fundamentals of the  eutrophigation
     of flowing waters, with particular reference to nitrogen and
     phosphorus as factors  in eutrophication.   OECD Technical Report
     DAS/CSI/68.27.   Paris,  France.  159 p.

Vollenweider,  R.  A.   1969.   Moglichkeiten und Grenzen elementarer  Modelle
     der Stoffbilanz von Seen.  Arch. Hydrobiol.  66:1-36.

Vollenweider,  R.  A.   1975.   Input-output models with special reference
     to the phosphorus loading concept in limnology.  Schweiz.  Z.  Hydrol.
     37:53-83.

                                137

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            A  Mathematical Model of Pollutant Cause
            And  Effect in  Saginaw Bay, Lake Huron

                     William L. Richardson- and
                        Victor J. Bierman, Jr.*


                             INTRODUCTION
     As part of the  joint  U.S.-Canadian Upper Great Lakes Study, the U.S.
Environmental Protection Agency, Large Lakes Research Station at Grosse
lie, has undertaken  an  intensive evaluation of the water quality process
in Saginaw Bay.  The project  includes field examination of water quality
and development of cause and  effect models for data interpretation.  These
models are designed  to  simulate the effect of nutrients on the growth,
composition, and distribution of phytoplankton biomass and will eventually
be used to simulate  the effect of  nutrient control alternatives.

     The primary emphasis  of  this  paper is the presentation of methodology,
including the practical considerations of applying an existing model struc-
ture to a new physical  system.  The existing model is the phytoplankton
chlorophyll-nutrient model  developed by O'Connor, et al. (1973).  This ap-
proach has evolved over the past decade largely through research support
from the U.S. Environmental Protection Agency and has recently culminated
in its application to Lake Ontario (Thomann, et al. 1975).  The computer
program, which implements  the Lake Ontario model (LAKE-1), has been modi-
fied to represent the physical system of Saginaw Bay.  First, model output
using the Lake Ontario  biological  parameters will be shown.  This output
will then be compared to model output using a set of biological parameters
determined for Saginaw  Bay.   These parameters were based on a series of
numerical experiments.  The results of this comparison are preliminary and
do not necessarily represent  the exact dynamics or kinetics of the bay.

              SAGINAW BAY  WATER QUALITY CHARACTERISTICS

     Although small  in  comparison  to Lake Huron, Saginaw Bay is an impor-
tant water resource  serving as a source of water supply for municipal and
industrial uses, for sport and commercial fishing, recreation, waste dis-
posal, and navigation.  The Bay has a surface area of about 2500 square
kilometers and a 21,000 square kilometer drainage basin (Figure 1).  The
basin supports a population of 1.2 million (1970 census) and a variety of
land uses including  large  industrial and urban centers.  The basin also
contains extensive agricultural, recreational, and natural areas.
*Environmental  Research Laboratory--Duluth,  U.S.  Environmental Protection
Agency, Large Lakes Research  Station,  Grosse lie, MI  48138

                                   138

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Figure 1.   Saginaw Bay Basin and five model segments
                        139

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     The hydrodynamics of the bay are such that Ayers et al.  (1956) con-
cluded that the bay acts like an estuary.   Fish and Wildlife  Service drift
bottle studies concluded that circulation  is variable and closely related
to meteorlogical conditions.   Northeast winds for example, can drive water
into the bay which results in water level  fluctuations near Saginaw River
of over one meter (USDI 1956).

     The physical, chemical,  and biological  dynamics in Saginaw Bay are
very complex.  Because of the dynamic interaction with Lake Huron, large
water quality gradients extend from the Saginaw River, the primary source
of material input, to the outer extremities  of the Bay.  Chloride levels
in 1974 varied from 39 mg/1  near the Saginaw River to 2 mg/1  near Lake
Huron.  Chlorophyll a. concentrations (an indirect indication  of phytoplank-
ton biomass) were recorded in the range of 1 to 82 mg/1 in 1974 (Smith,
1975).

                       GENERAL MODELING PROCESS

     The water quality processes for large,  complex natural systems can be
considered to consist of two primary components, 1) physical  transport  and
2) biological-chemical processes.  A common  approach is to develop separate
process models independently and merge results into a final water quality
management model (Figure 2).   The resolution of either model  component de-
pends on the purpose or application of the model.  For a general  indication
of future water quality trends for planning  purposes, simple  biological and
chemical models averaged over space and time  are appropriate.  If more
resolution is desired to answer other specific questions, then the model
components must be sub-divided to provide  more precise simulations.

     Complex ecosystem models have been structured by several theorists but
these have remained primarily research models with little or  no field cali-
bration or verification (Middlebrooks et al., 1973).  Factors limiting the
complexity of ecosystem models include computer size and execution time, as
well as data acquisition and analysis.  Expansion of the simple modeling
framework to include more physical, chemical, and biological  resolution is
continuing as part of the EPA Great Lakes  research program.  Bierman (1975)
has structured a four class  phytoplankton  model which contains more detailed
nutrient-phytoplankton interaction kinetics.  Thomann, et al. (1975), has
structured a 67 segment model for Lake Ontario.  These models represent the
next generation of verified  ecological models.

     In the case of Saginaw  Bay, the primary question concerns the effects
of material load reduction on water quality  parameters such as dissolved
solids and biomass.  The modeling approach applied herein is  a simple eval-
uation tool for making such  assessments.  The space scale considered is on
the order of 10-30 kilometers and the time scale on the order of seasons.

                           MODEL PRINCIPLES

     The key principle used  in the modeling  of material transport is mass
balance.  The model equations  for physical, chemical, and biological sys-
tems conserve mass in both space and time.  The computer program which im-
plements these equations accounts for and  traces materials from their spatial
                                    140

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                          GROSSE ILE LAB MODELING PROCESS
Nutrients
Sunlight
Temperature
  Geometry
  Chloride
 Wind
 Geometry
 Temperature
                        Chemical—Biological Process
                             Chlorophyll a
                        Chemical—Biological Process
                           Multi-Species Biomass
  Course Grid
Chloride Transport
     Model
                                  I
    Fine Grid
  Hydrodynamic
   Process Model
                                                               Water Quality
                                                            Management Models
                                                          Further Research
                                                            Refinements
        Figure 2.  Mathematical  modeling  process diagram.

-------
points of input to their final  export points.  If the material  is conser-
vative, the transport mechanisms are totally physical.  If the material is
non-conservative, such as nitrogen and phosphorus, the transport mechanisms
also include chemical and biological reactions.  A mass balance equation in
finite difference form for a water body divided into n finite completely
mixed segments is given by Thomann et al.  (1975):


             [V] d(s)k  =  [A]   (s.) ± (S)  ± (W)                (1)
                 ~dT~            K       K      K


where

          v = n x n diagonal matrix of volumes, (L)

          (s,,) = n x 1 vector of material  concentration

          [A] = n x n matrix of advective  and dispersive transport terms

          (S,) = n x 1 vector of kinetic  interaction terms

          (W)k = n x 1 vector of material  sk inputs


     This system of equations accounts for the mass of a substance k in each
model segment which is equal to the mass entering minus the mass leaving,
plus or minus mass produced or lost within the segment.

PHYSICAL TRANSPORT

     The first phase of model development  for large, dynamic water systems
is usually devoted to quantifying the circulation.  This has been done for
Saginaw Bay by tracing a conservative substance, chloride, through the sys-
tem by adjusting transport parameters in equation 1 until  a reasonable com-
parison is obtained between computed and measured chloride concentrations
(Richardson 1975).

BIOLOGICAL-CHEMICAL PROCESSES

     The general scheme of nutrient/chlorophyll a dynamics for a single
segment has been adapted from O'Connor, et al. (T973) (Figure 3).  The spe-
cific system scheme used for Saginaw Bay adapted from Thomann et al. (1975)
includes eight state variables  with their  interactions (Figure 4).  This
model is a simplification of a complex biological-chemical system where
phytoplankton biomass is represented by chlorophyll a_ which is used primar-
ily because of the ease of measurement and availability of data.  Phyto-
plankton carbon is specified using carbon-chlorophyll stoichiometry obtained
by experimental data and is the element which zooplankton consume along with
other nutrients contained in the phytoplankton.  The nutrients, phosphorus
and nitrogen, are also accounted for and traced through the phytoplankton and
zooplankton by specifying stoichiometry relationships with carbon.  The model
assumes all  other nutrients to be in sufficient supply so as not to limit
phytoplankton growth.
                                    142

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                             Material Sinks
                                 (m/T)
                                              Physical Transport
SS
N
0   PHYTOPLANKTON
    CONCENTRATION
SS
       NUTRIENT
    CONCENTRATION
                              Zooplankton
                                (m/L3)
                               f
                             Prey
                               I
             \
            Grazing
           J_
                             Phytoplankton
                                (m/L3)
 Nutrient    ...    ,,
Limitation   Nutnent Use
                               Nutrients
                                (m/L3)
         TIME
TEMPERA TURE
                                                      TEMPERATURE
                            SOLAR RADIATION
                              Material Inputs
                                  (m/T)
                                 TIME
  Figure 3.  General  nutrient-phytoplankton model interactions.
••••

Carnivorous
<
Zooplankton
PNC
Herbivorous Zooplankton
TPNC


Phytoplankton
1
1



N
N
J P


Organic
N itrogen
t"

Orga
Phospt
P 1
1

^ Ammonia
Nitrogen

N

^

nic
lorus
L


Available
Phosphoru;
1


Nitrate
Nitrogen
t-



  Figure 4. Specific  model  biological-chemical  interaction
            diagram  (Thomann 1975).
                               143

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     The biological-chemical  equations have been developed and reported
by Thomann et al.  (1975) and the details will  not be repeated here.  How-
ever, in summary the key assumptions of the kinetic expressions will include:

     1.  Phytoplankton growth rate is a function of temperature, light and
         nutrients and uses Michaelis-Menton product kinetics.  A maximum
         growth rate is computed from the temperature relationship and then
         reduced by the product of the nutrient and light limitation terms.
         The death rate is a function of zooplankton grazing and endogeneous
         respiration.  Both of these processes are temperature dependent.
         The dead phytoplankton return to the non-living organic nutrient
         pools and the grazed phytoplankton become part of the zooplankton
         biomass.   Phytoplankton can also leave the system by sinking to the
         sediment.

     2.  Herbivorus zooplankton growth rate is a function of the grazing
         efficiency, grazing rate, and available phytoplankton, and follows
         a Michaelis-Menton form (i.e., the growth rate reaches an asympote
         as phytoplankton concentration increases).  The death rate is a
         function of temperature and the grazing rate of the carnivorous
         zooplankton.  Grazed zooplankton biomass and nutrients become part
         of the carnivorous zooplankton biomass whereas the dead zooplankton
         biomass and nutrients return to the non-living organic pools.

     3.  The growth rate for carnivorous zooplankton is a function of grazing
         rate and efficiency and the death rate is a function of temperature
         only.  Dead zooplankton return to the appropriate material pools.

                      APPLICATION TO SAGINAW BAY

SEGMENTATION

     The bay was divided into five (5) segments shown in Figure 1.  This seg-
mentation scheme was chosen after considering such factors as water quality
gradients, morphology, spacial resolution desired, and available research
time.

MATERIAL LOADINGS

     The primary source of material  input to Saginaw Bay is the Saginaw Ri-
ver.  The .loadings provide the forcing functions, (W), to the mathematical
model (Equation 1) and must be defined for each state variable during the
entire period for which the model is run.  For this investigation loadings
were computed by the product of river discharge and material concentration.
The U.S. Department of the Interior (1975)   provides daily discharge in-
formation for the four major tributaries to the Saginaw River including the
Cass, Tittabawassee, Shiawassee, and Flint Rivers.  Meaningful flow measure-
ments can not be made near the mouth of the Saginaw River since the river
behaves like an estuary and reacts hydraulically to the fluctuations in the
bay water levels.   This can cause flow stagnation and reversals which make
stage recordings meaningless for flow computations.  Therefore, the daily
measured flows from the four major tributaries were added along with a com-
puted flow representing the ungaged portion of the basin (about 24% of the
total basin).
                                    144

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     The material concentrations were obtained from the Michigan Water
Resources Commission bimonthly sampling station at Midland Street in Bay
City about five miles upstream from the mouth of the river, the Cranbrook
Institute of Science (1975) sampling stations at the Dow Chemical Co.
water intake (samples about every two or three days) about a mile upstream
from the mouth and from the Cranbrook Station at Midland Street (sampled
once or twice per month).  During low flow periods, June through December,
the Dow intake is influenced by the diluting effect of the bay, therefore
these data were used only for the peiod of January through June.  For days
when a sample was collected a  daily load was computed as the product of
the daily average flow and the grab sample concentration.  These points
were connected by straight line segments to provide a continuous time series
for the entire year of 1974.  These are shown in Figure 5 for each state
variable including chloride.

Circulation --

     The circulation pattern in the bay was obtained by mathematically
tracing the transport of chloride from Saginaw River through the five
segments.  The details of this approach have been presented by Richardson
(1975).  In summary, having measured the chloride loads from the Saginaw
River and the average segment concentrations, the transport dispersion
and the advection terms in the mass balance equation are adjusted (Figure
6) until computed chloride concentrations match the measured in the five
segments (Figure 7).  The measured chloride time series is the cruise by
cruise average of chloride measurements.  A simulation is acceptable when
the computed concentration falls within a range of plus and minus one stan-
dard deviation of the mean.  Note that this criterion has not yet been met
at all times in each segment.  This is especially the case in segments 1
and 3, the smallest and most dynamic.  However, these comparisons are suf-
ficiently accurate during this initial phase.  The degree of further refine-
ment will depend on the results of biological-chemical modeling and the
resolution obtained.

Initial Results --

     As a starting point, an initial simulation was obtained from the modi-
fied Lake Ontario "LAKE-1" computer program.  Only those parameters unique
to Saginaw Bay in 1974 were changed.  These included segmentation, advective
and dispersive transport terms, boundary conditions, initial conditions,
segment temperatures, segment light extinction, and segment depth.  The Sag-
inaw Bay physical characteristics are listed in Table 1.  The first run was
made using the verified Lake Ontario biological-chemical parameters (Thomann
et al. 1975).  To simplify this presentation only the results for Segment 3
are shown (Figure 8).

     To compare the computed concentrations (model output) with those measured
(actual data), the data for all sampling stations in a model segment (Figure
9) were combined for each sampling cruise and the mean and standard devia-
tion computed.  This was easily facilitated by the use of the EPA data system,
STORET.  The cruise means and standard deviations were inputted to the LAKE-1
graphics subroutine and plotted along with the computed results for each of
comparison.
                                     145

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                     Sag in aw River
               MATERIAL LOADS TO SAGINAW BAY
£  .  250
|s   200

f sl150
egS'lOO
                            o
                                       1974 ORGANIC PHOSPHORUS
                                                LOAD
                                     40   120   200   280  360
                                            1974 ORTHOPHOS-
                                              PHATE LOAD
40    120    200    280   360
                                     40
                                           120   200    280  360
    1974 NITRATE LOAD
                            S   4
                            5   i
40    120    200    280   360
         DAYS
                                        1974 CHLORIDE LOAD
                                    40
                                                     120   200   240    360
                                                        DAYS

       Figure  5.   Saginaw  River material  loads  to Saginaw  Bay.
           MODEL CALIBRATION PROCESS
                               INFLUENCE FROM
                                 LAKE HURON
   SEGMENTATION
   Depth   D
   Area    A
   Volume V
   Length  L
                              BAY CIRCULATION
                              Advection    Q
                              Dispersion    £

                              BAY CHLORIDE CONCEN-
                               TRATIONS CM
   CHLORIDE LOADINGS Wk
        INPUT
                     A   v\D\ L
                  COMPUTE CHLORIDE
                   CONCENTRATION
                         C,
 Figure 6. Physical transport model  calibration process.
                          146

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25
                  -h-I-
   J'F'M A'M'J'J'A'S
100
 50
   j 'F'M'A'M'JV/VSO N  D
25
   J'F'M'AVJ'J^'S'O'N'D
                               1974SAGINAWBAYCHLORIDE'
  I Cruise average ± SD (mg/l
 «•— Computed (mg/l)
25
                                 -i-TW-M—•
   j T'M'A'M'J'J'A'S oVD
                            50
   j'F'M'AMJ  JASON  D
       Figure 7.  Comparison  of 1974 computed  and measured chloride concentrations in
                 five model  segments.

-------

    80


    60


    40


    20


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      J  FMAMJ  J ASON.D
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IT.
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  TABLE 1.  SAGINAW BAY MODEL PHYSICAL PARAMETERS
Segment Interacting
Segment

1
2
3
2
3
4
3
5
4
5
Lake Huron
5
Lake Huron
Segment
Volume
3
894


5890


1270

7880


9390

Average
Depth
m
3.85


7.33


3.74

13.22


15.15

Light Ext.
Coef.
m-1
1.5


1.0


1.0

.5


.5

Intersegment
Area
m2 x 103

123
35

137
133

35

499
323

769
    SAGINAW BAY
1974 Sampling Network

  Legend    o Boat Station
          A Water Intake
    —I	h Model Segments
                                                10 Ml
        Saginaw River

        Figure 9.  Saginaw Bay  1974  sampling network.

                           149

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     The initial results (Figure  8)  reveal the following:

     1.  Computed phytoplankton grow too early in the year which results in
         bad timing for the spring and fall peaks as compared to the data.

     2.  As a result of the early phytoplankton growth, computed zooplankton
         appear too soon which shifts the entire zooplankton time series.
         Too much computed zooplankton biomass could be one of the factors
         which reduces the computed phytoplankton levels relative to the
         observed values.

     3.  The reaction rates for conversion of organic nitrogen and ammonia
         to nitrate are too low.  This is apparent because the computed con-
         centrations of total  kjeldahl nitrogen and ammonia are higher than
         the measured and that for nitrate is too low.

     4.  The poor timing and insufficient growth of phytoplankton result in
         poor timing for orthophosphorus.  Computed orthophosphorus appears
         to be another limiting factor for the computed phytoplankton peak
         during the summer.

     5.  Total phosphorus appears to be too low in the  fall.  This  could be
         caused by incorrect loss rates and/or by an inaccurate total phos-
         phorus load.

Calibration --

     The calibration process proceeds similarly to that described previously
for chloride except there are 16 biological-chemical parameters to  adjust
compared to only only two transport parameters.  This process is not a curve
fitting exercise in a statistical sense;  rather, it requires an understanding
of the cause and effect relationships inherent in the system and knowledge
of a reasonable range of values for each  parameter (O'Connor, et al. 1973).
As each parameter is altered keeping all  others constant, perception of the
sensitivity and importance of each is obtained by the analyst which further
increases his insight and intuition.  One problem arising, however, is the
practicality of assimilating all of the information generated.  Computer
output must be reduced to graphs, and graphs of simulations overlaid to
depict the alterations.  The analyst soon becomes overwhelmed having to
perceive eight state variables, for five  segment, for numerous calibration
simulations.

     To simplify this process  the emphasis was given to chlorophyll a^ in
segment 3.   This reduces-the number of graphs from forty to just one for
each simulation.  A few of the more important initial sensitivity simula-
tions are shown in Figure 10 compared to  the base run.   The results of
these sensitivity runs revealed the following:

     1.  No single alteration of any of the principal parameters appears
         to have a significant effect on  the magnitude  of the computed
         phytoplankton chlorophyll jj.

     2.  A reduction of 75% in the phosphorus-chlorophyll a^ ratio (from
         .001 to .00025 mg per yg chlorophyll a) has the most significant
         single impact primarily in summer chlorophyll  peak.

                                    150

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    80
 cn
CL.
O
O

O
o
    60
    40
    20
     0
             30     60      90     120    150    180    210   240   270    300    330

                                            JULIAN DAY

      Figure 10.  1974 phytoplankton chlorophyll ^concentration sensitivity simulations  including:
        a  —^—Base simulation
        b  —.—.—.—Phosphorus-chlorophyll  a^ ratio of  .00025
        c  • • «  'Carbon-chlorophyll ratio of  .025 and herbivorous zooplankton grazing rate  of .2
        d  	Organic nitrogen and ammonia  nitrogen decomposition rates of .01
         e  x-x-x-xAll  above except phos-chlor ratio of .0005 and phytoplankton settling  rate of .05

-------
       3.   Only after altering the phosphorus-chlorophyll a_ ratio, carbon-
           chlorophyll a_ ratio, herbivorous zooplankton grazing rate, and
           nitrogen decomposition rates concurrently does the chlorophyll
           ia increase significantly.

       4.   To fit the data, the organic nitrogen to ammonia, and ammonia to
           nitrate decomposition rates must be increased by an order of mag-
           nitude over those used for Lake Ontario.

       Once these required alterations were determined, additional sensitivity
  simulations were made from this new base.  The best comparisons (at the time
  of this  report) of observed versus computed for the eight state variables
  and five segments are shown in Figures 11 through 17.  As these show, more
  effort remains to obtain an acceptable calibration.  The parameter values
  for this final run are listed in Table 2.  In particular, as Figure 13 shows,
  computed levels of orthophosphorus are too high in all segments throughout
  the year.  Also, it would be desirable to refine the chlorophyll ^simula-
  tion in Segment 3.
          TABLE 2.  BIOLOGICAL-CHEMICAL MODEL PARAMETERS
                                        Lake -j
                                      Ontario
                                                               Saginaw
                                                                 Bay
                                                          Units
Nitrogen
Phosphorus
Zooplankton
Phytoplankton
Carbon
Half-saturation constant               0.025   0.025
Organic nitrogen decomposition rate    0.0175  0.007
Ammonia to nitrate nitrification rate  0.002   0.015
Nitrogen-chlorophyll ratio             0.01    0.01
Half-saturation constant
Organic phosphorus decomposition rate
Phosphorus-chlorophyll ratio

Conversion efficiency
Endogenous respiration rate
Herbivorous zooplankton grazing rate
Carnivorous zooplankton grazing rate

Chlorophyll half-saturation constant
Endogenous respiration rate (at 20°)
Settling velocity
Saturated growth rate

Carbon-chlorophyll ratio
                                       0.002
                                       0.007
                                       0.001
                                                                       day",deg"
                                                                       day" deg"
                                                                           a
0.005
0.007
0.00025
                                                                       day" deg
                                                                               -1
0.6
0.001
0.06
0.06
0.6
0.001
0.04
0.04
day"
1/mg
1/mg
                                                                            deg"1
                                                                            C day  deg
                                                                            C day  deg
10
0.1
0.1
0.58
20
0.1
0.05
0.50
vg/i.
day"1
m/day
day"1
                                       0.05    0.025
 Ratio mg element to yg chlorophyll.

'Thomann 1975.
                                     152

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            Figures  11-17.   Final comparison of 1974 computed  and  measured material
                            concentrations.
  50
                                25
  O|JIF'MIA'M'J'J'AIS'O'N'D'\  "VF'M'A'M'JVA'S'O'N'D
                                                               25
                                   JF'M AM'j'J'A'S'O'N'D
 100
  50
J'F'MVM'J'j'A'S'O'N' D
                                 1974 SAG INAW BAY PHYTOPLANKTON
                                        CHLOROPHYLL;
                                  J Cruise average! SD lug/I)
                                 —• Computed (ug/l)
                                                              100
                                50
                                   J'F'M'A'M'J'J'A'S'O'N'D
                                  Figure 11
0.5
    j  F M A M J J'A'S'O'N'D
1.0
0.5
    J'F'M'A'M'J  J  A s'o  N  D
0.5
                                                         0.5
    J'F'M'A'M'J'J'A'S'O'N'D
                                 1974 SAG INAW BAY ZOOPLANKTON
                                          CARBON
                                                             J'F'M'A'M'J'J'A'S'O'N'D
    I Cruise average + SD (mg/l)
   — Computed (mg/l)
                                                              i.o
                               0.5
                                                             J'F'M'A M'J'J'A s o N D
                                   Figure  12
                                            153

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0.025
     j 'F'M'A'M'J'J'A'S'O'N'D
0.025
0.025
 0.05 -
0.025 -|
                    'N1 D
                          1974 SAGINAW BAY ORTHO-PHOSPHORUS
                                                   0.05
    u/ftffir>
     j'F'M'AWj'j'A'S'O'N'D1
                                                   0.025
     J'F'M'A'M'J'J'A'S'O'N' D
     JCruise average ± SO (mg/l)
     - Computed (mg/l)

      Figure 13
                                                                Ii
               I II  IT
    j 'F'M'A'M'J' J'A'S'O'N'D
    J  F MA MJ JASON D
    J  F M A M J  J A'S'O'N D
    j F M A'M j j A'S o N'D
                           1974 SAGINAW BAY NITRATE NITROGEN
 2.0
 1.0

                               ICruise average + SD (mg/l)
                              — Computed (mg/l)          Q


                               Figure 14

                                     154
                              J F'M AM J J A S 0 N D

-------
0.25
J'F'M'A'M'J'J'A'S'O'N'D
0.50
0.25
               J  JASON D
                           0.25
                                    J F'M A'M  J  J A'S O'N  D
0.25
  n T .  . li*** , TA.  .
     J'F'M'A'M'J'J'A'S'O'N'D
                                1974 SAGINAW BAY AMMONIA NITROGEN
                                                               0.50
                                                          0.25
                                      J Cruise average± SO (mg/l)
                                     -^ Computed (mg/l)
                                        Figure 15
                                                                               •fi"
                                                               r?M A M J  J  A S 0 N  D
 1.0
                         I I
    J'F'M'A'M'J'J'A'S'O'N D
2.0
 1.0
     J'F'M'A'M j  J  A s  o N  D
                                1.0
                                J'F'M'A'M'J'J'A'S'O'N'D
                                                                1.0
    J'F'M'A'M'J'J'A'S'O'N'D
                                ^1974 SAGINAW BAY TOTAL KJELDAHL
                                           NITROGEN
                               I Cruise average ± SD (mg/l)
                              — Computed (mg/l)

                                  Figure 16

                                         155
     JVM A'M J  J A'S 0 N'D

-------
0.05
    J'F'M'A^TJ J  A s o N D
0.05
                                                        0.05
 0.1
0.05
    j 'F'M A M j j  A s o N D
                            1974 SAG INAW BAY TOTAL PHOSPHORUS
                                                        0.1
     J F M A M J J A S 0 N D
      I Cruise average ± SD (mg/l)
      — Computed (mg/l)           o


         Figure 17
JT M A M J J  A S 0 N D
                                                            JTVA M J J  A S 0 N  D
                          DISCUSSION AND CONCLUSIONS

         Although additional effort remains to be expended, some general  conclusions
    can be drawn from the work done to date.  It is emphasized that the model  para-
    meter values reported herein (Table 2) have yet to be confirmed and checked  and
    only represent order of magnitude estimates at this time.

         It has been learned that substantial research resources are  required  to
    apply an existing computer program/model to a new physical system.  The  emphasis
    in modeling research is not on the writing of the computer program but rather on
    arriving at the basic workable kinetic structure and then calibrating this struc-
    ture to a given data set.  If a calibration can be obtained, the  model must  then
    be verified by comparing model results to an independent data  set-ideally  after
    the system has been perturbed (i.e., phosphorus loads altered).

         Although this effort was initially considered to be an  "application"  pro-
    ject, calibration and verification for a  new system require such a substantial
    effort, with no guarantee of success, that this work should be considered  as
    applied research.  Only after calibration and verification are obtained  can  a
    model be "turned over" to an engineering staff for use  in making  management  de-
    cisions.  The time required from project initiation to  final transfer to manage-

                                          156

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ment of any new system  is on  the order of one to  two years  if  all  required
data is available.

     The calibration/verification research,  itself, has side benefits which
are useful during the course  of the work.  The modeling process  requires a
systematic approach to  data collection and analysis.   It helps structure a
surveillance program and preliminary model results can be used to  gain  in-
sight into the data and help  in the management of surveillance and experi-
mentation programs.  The preliminary results reveal gaps in our  knowledge
for a particular system and are useful to direct  new study  and research.
As an example, the Saginaw Bay model has revealed possible  errors  in total
phosphorus loading in the fall.  This has led to  detailed inquiry of pos-
sible additional sources of phosphorus from  diffuse sources, release from
sediments, and from the atmosphere.  Inquiry was  made to regulatory agencies
on possible seasonal loadings from waste sources.  Additional work remains
to be done to quantify  the effect of dredging as  a possible source of phos-
phorus and more effort  needs  to be made on the method of sampling the Saginaw
River and accurately computing the loadings  to the Bay.

     Concerning model results, no specific conclusions can  be drawn as yet.
However, the model has  revealed Saginaw Bay  to be quite a different system
than Lake Ontario which reinforces intuitive conclusions made from observing
the data.  Decomposition rates used in the model  are higher as expected.
The phosphorus-chlorophyll a_  ratio apparently must be lower, especially in
the fall.  This indicates a possible need to alter the model structure.  Per-
haps this ratio is time-variable due to a shift in the dominant  plankton
forms.  Phytoplankton settling velocity appears to be lower than that for
Lake Ontario.  This is  reasonable because the hydrodynamics of the bay tend
to keep materials in suspension.  The initial phytoplankton growth was better
using a saturated growth rate of .5 per day  rather than .58 used for Ontario
and the Potomac models  (O'Connor, et al. 1973).   This may be an  artificial
compensation for lack of information on exact levels of solar radiation and
light extinction in the water under ice.  Alternatively, it could be accounted
for by species differences between the systems.   The zooplankton kinetics are
yet to be confirmed by  experimental research so the zooplankton  parameters
remain to be adjusted over large ranges.

     In conclusion, this effort represents a first EPA in-house  attempt to
apply an existing computer program/model which had been developed under
previous and ongoing EPA grants.  A close working relationship was estab-
lished between the grantee staff and the EPA research staff which resulted
in better communications and an overall enhanced  program for all of the
Great Lakes modeling research.

     The average chlorophyll a^ biomass model is a relatively economical
research tool which can aid in analyzing complex, limnological interactions
and has been useful in  guiding additional research and data gathering
activities.

                           ACKNOWLEDGEMENTS

     The authors would  like to express their gratitude to the many persons
who assisted with this  project.  In particular, we thank Nelson  Thomas and

                                    157

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Tudor Davies for their encouragement and support.   The assistance provided
by Richard Winfield at Manhattan College in implementing the computer pro-
gram was invaluable.  John Gannon from the University of Michigan Biological
Station, Pellston, Michigan, provided the zooplankton data and Elliott Smith,
Cranbrook Institute of Science, provided the chemical data.  We also thank
the staff of the Large Lakes Research Station at Grosse He for reviewing
the manuscript and Amy Torongeau for typing numerous drafts.
                              REFERENCES
Ayers, J.C., D.V.  Anderson, D.C.  Chandler,  G.H.  Lauff.   1956.   Currents
     and Water Masses of Lake Huron,  (1954)  Synoptic Surveys.   Ontario
     Department of Lands and Forests,  Division  of Research  and University
     of Michigan,  Great Lakes Research  Institute.

Bierman, V.J., Jr.  1975.  Mathematical  Model  of the Selective Enhancement
     of Blue-Green Algae by Nutrient  Enrichment.  In press.

Middlebrooks, E.J., D.H. Falkenborg,  and T.E.  Maloney (EDS.)   1973.
     Modeling the  Eutrophication  Process.  Ann Arbor Science.

O'Connor, D.J., R.V.  Thomann, and D.M.  DiToro.  1973.  Dynamic Water
     Quality Forecasting and Management.  Environmental  Protection Agency
     Ecological Research Series EPA-660/3-73-009.

Richardson, W.L.  1975.  An evaluation  of the  transport  characteristics
     of Saginaw Bay using a mathematical model of  chloride in  Mathematical
     Modeling of Biochemical Processes  in Aquatic  Ecosystems.   Ann Arbor
     Science Press (In press).

Smith, V. Elliott.  1975.  Annual Report—Upper  Lakes Reference Study:
     A Survey of Chemical and Biological Factors in Saginaw  Bay (Lake
     Huron).  Cranbrook Institute of  Science,  Bloomfield Hills, Michigan,
     for the U.S.  Environmental Protection  Agency, Grosse He  Laboratory.

Thomann, R.V., D.M. DiToro, R.P.  Winfield,  D.J.  O'Connor.  1975.   Mathe-
     matical Modeling of Phytoplankton  in Lake Ontario,  1.  Model  Develop-
     ment and Verification.  Environmental  Protection Agency Ecological
     Research Series  EPA-660/3-75-005.

U.S. Department of the Interior,  Fish and Wildlife Service.  1956.  Surface
     Current Studies  of Saginaw Bay and Lake Huron.

U.S. Department of the Interior,  Geological  Survey.  1974.  Water Resources
     Data for Michigan, Part 1.
                                    158

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          Mathematical  Model of Phytoplankton Growth and
          Class Succession in  Saginaw  Bay,  Lake Huron
                       Victor J. Bierman, Jr.  and
                         William L. Richardson*
                             INTRODUCTION


     Mathematical modeling techniques can provide a systematic basis  for
 a  research approach to the problem of cultural eutrophication and can greatly
 aid in the comparison of various management options.  From an applied stand-
 point, the general techniques of O'Connor et al.  (1973)  have been brought  to
 bear on a variety of different physical systems.   In particular,  Thomann et
 al. (1975) and Canale et al. (1973) have investigated phytoplankton-nutrient
 interactions in the Great Lakes.  Chen and Orlob  (1972;  have also developed
 such techniques and have used them to investigate, among other cases, the
 effects of wastewater diversion from Lake Washington.  From a research  stand-
 point, work is progressing on a number of systems models and component  models
 for purposes of gaining deeper insight with regard to chemical-biological
 processes that occur in natural systems (e.g., Middlebrooks et al.  [1973]).

     The present work is part of the International  Joint Commission's Upper
 Lakes Reference Study involving Saginaw Bay, Lake Huron.  The ultimate  goal
 of this work is to develop a mathematical  model which can be used both  to
 describe the physical, chemical and biological processes that occur in  Sagi-
 naw Bay and to predict the effects of reduced waste loadings.   Specifically,
 the modeling effort will focus on phosphorus, nitrogen and silicon  loadings
 to the bay and the resultant production of phytoplankton biomass.

     Model development is proceeding along two parallel  pathways.   The  first
 of these involves the development of research-oriented models  which include
 biological and chemical detail  but which,  for simplicity, do not  include any
 spatial detail.  The second pathway involves the  development of engineering-
 oriented water quality model  which mimics, as closely as practicable, the
 actual physical system, including spatial  detail.  At any given point in time,
 the water quality model will  contain those chemical and  biological  processes
 which have previously been investigated and developed using the spatially-
 simplified model.  There is constant feedback between the above two pathways
 and constant interaction between the entire modeling effort and the ongoing
 sampling effort on Saginaw Bay.
*Environmental  Research Laboratory--Duluth,  U.S.  Environmental  Protection
Agency, Large Lakes Research Station,  Grosse lie,  MI   48138

                                   159

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     Previous work (Bierman [1976]) involved a preliminary calibration of
a spatially-simplified, multi-class phytoplankton model to data from the
inner portion of Saginaw Bay.   Only chlorophyll and dissolved nutrient data
were considered, and sensitivity analyses were presented for several impor-
tant processes affecting the development of blue-green algae.

     The present paper involves the use of the same spatially-simplified
model.  The purpose of this work is to obtain a more refined calibration
using a data set that has been expanded to include total phosphorus, total
nitrogen, and total zooplankton biomass.   Also, finer time scales were used
for external nutrient loads, boundary conditions, and water circulation rates.
Ambiguities that can occur when calibrating an  ecosystem model are discussed,
in particular, those that can occur by using chlorophyll concentration as an
indicator of phytoplankton biomass.


                               SUMMARY

     A mathematical model of phytoplankton production has been applied to a
set of physical, chemical, and biological data from Saginaw Bay, Lake Huron.
The model includes four phytoplankton types, two zooplankton types, and three
nutrients:  phosphorus, nitrogen, and silicon.  The phytoplankton types in-
clude diatoms, greens, and both nitrogen-fixing and non-nitrogen-fixing blue-
greens.

     The purpose of this study was to obtain the best possible calibration
between model output and the existing data set.  This is one of the many
preliminary tasks which must be performed before such a model can ultimately
be used as a tool for making management decisions.

     The model output agreed reasonably well with the data for phytoplankton
chlorophyll, total nitrogen, and dissolved forms of phosphorus, nitrogen,
and silicon.  The model output did not agree well with the data for total
phosphorus during the latter part of the year, and the output showed a large
discrepancy with the total zooplankton data.

     Ambiguities persisted in the interpretation of the model output because
insufficient data were available.  The most serious problem was the lack of
simultaneous measurements of phytoplankton biomass and zooplankton biomass.
The existing phytoplankton data were available only in the form of chlorophyll
concentrations, a lumped parameter which can not be used to distinguish among
various functional groups of phytoplankton.  Another problem was the lack of
direct measurements for all of the rate coefficients in the model.  Given the
present state of the art, the latter problem is common to most ecosystems models


                   CONCLUSIONS AND RECOMMENDATIONS

     Output from complex ecosystems models is difficult to interpret unless
large amounts of experimental data are available.  Frequently, more than one
set of model coefficients will produce output which compares favorably with
experimental data.  For this reason, it is difficult to gain insight with
regard to cause-effect mechanisms.
                                    160

-------
     As the number of state variables for which there is comprehensive data
is increased, many coefficients in a model become more tightly constrained.
If an ecosystem model can be calibrated to a large number of simultaneous
and independent variables, its reliability as a tool for drawing cause-
effect inferences can be greatly increased.

     Continued development of sophisticated phytoplankton production models
will require detailed cell count and cell volume measurements.  Chlorophyll
measurements alone give no information with regard to the partitioning of
phytoplankton biomass among various functional  groups.  In addition, system
atic, comparative studies of phytoplankton-nutrient dynamics are required
for various functional groups of phytoplankton  in order to provide rate
coefficients for such models.

                            MODEL CONCEPTS

     The basic model  framework and preliminary  simulations appear elsewhere
(Bierman [1976] and DePinto et al.  [1976]).  The compartments in the model
are four phytoplankton, two zooplankton, higher predators, and three nutri-
ents (Figure 1).  The phytoplankton types include diatoms, greens, and blue-
greens, both nitrogen-fixing and non nitrogen-fixing.


1
1 I
i
! I
•4-1 |
I \
• L

,
HIGHER PREDATORS
L
ZOOPLANKTER
1

i t
ZOOPLANKTER
2
A V if A




DIATOMS

J
'


AVAILABLE
SILICON
i
s




NON-AVAILABLE
SILICON
A
i
i
i
i




GREEN ALGAE



1
1 1 1
1 1 1
BLUE-GREENS 1 BLUE-GREENS 1 ' ^,
(NONN-FIXING) \ (N-FIXING) 1 1
i i ]
1 -1
i _. i
i A
V T
AVAILABLE
PHOSPHORUS
AVAILABLE ATMOSPHERIC
NITROGEN NITROGEN
A *

NON-AVAILABLE
PHOSPHORUS
NON-AVAILABLE
NITROGEN
it4 i
          Figure 1.   Principal  compartments of the Saginaw
                    Bay eutrophication model.
                                    161

-------
     The motivation for a multi-class modeling approach is that different
classes of algae have very different nutrient requirements, for example,
diatoms need silicon and certain types of blue-greens can fix atmospheric
nitrogen.  In addition, at high concentrations, not all of these classes
have the same nuisance characteristics from a water quality standpoint.
Diatoms and green algae are grazed by zooplankton, but blue-green algae are
not significantly grazed and can form objectionable floating scums.

     A unique feature of the model is that cell growth is considered to be
a two-step process involving separate nutrient uptake and cell synthesis
mechanisms.  The motivation for this variable stoichiometry approach is that
an increasingly large body of experimental evidence indicates that the mech-
anisms of nutrient uptake and cell growth are quite distinct (e.g. Fuhs
[1969, 1971], Droop [1973], Caperon and Meyer [1972a, 1972b]).  The model
includes carrier-mediated uptake of phosphorus and nitrogen using a reaction-
diffusion mechanism, and possible intermediate storage in excess of a cell's
immediate metabolic need's.   Specific cell growth rates are assumed to be
dependent on the intracellular levels of these nutrients, in contrast to the
traditional Michaelis-Menten approach which relates growth rates directly to
extracellular nutrient concentrations.
                         MODEL IMPLEMENTATION

     A major problem in attempting to implement a complex chemical-biological
process model  is the lack of sufficient experimental data.  It is often pos-
sible that more than one set of model coefficients could produce an acceptable
fit between the model  output and a given data set.  In the transition from
single-class to multi-class models, this problem becomes particularly acute
because it is  no longer sufficient to ascertain a range of literature values
for a given coefficient.  Multi-class models necessitate the definition of
class distinctions within this range.  Given the present state of the art of
ecosystems modeling and associated experimental work, many of the coefficients
in such models must simply be estimated.

     The primary operational differences among the phytoplankton types in the
model are summarized in Table 1.  Principal phytoplankton coefficients are
summarized in  Table 2.   The working equations of the model and sensitivity
analyses of some of the most important coefficients have been presented in
Bierman (1976).

     One of the assumptions of the model is that cell biomass concentration
is a more accurate indicator of standing crop than is chlorophyll concentra-
tion.  In addition, chlorophyll is a lumped parameter and can not be used to
distinguish between different functional groups of phytoplankton.  For these
reasons, chlorophyll concentration does not appear in any of the kinetic
equations of the model.  However, the only available field data for phyto-
plankton in Saginaw Bay at-this time are chlorophyll concentrations.  In
order to relate the model output to these data, the output must be converted
to chlorophyll concentration.
                                    162

-------
     TABLE 1.  OPERATIONAL DIFFERENCES AMONG PHYTOPLANKTON TYPES
   Characteristic
      Property      Diatoms
                                            Phytoplankton Type
                           Blue-Greens     Blue-Greens
                         (non N2-fixing)   (Np-fixing)
 Greens
Nutrient
Requirements

Relative Growth
Rates Under Opti-
mum Conditions at
20°C

Phosphorus Uptake
Phosphorus,
Nitrogen,
Silicon
High
Phosphorus,  Phosphorus,     Phosphorus
Nitrogen     Nitrogen
Moderately
High         Low             Low
Affinity
Sinking Rate
Grazing Pressure
TABLE 2.

Low
High
High
PRINCIPAL

Low
High
High
PHYTOPLANKTON

High
Low
None
COEFFICIENTS
Phytoplankton
High
Low
None

Type
   Parameter
  Diatoms     Greens
             Blue-Greens     Blue-Greens
           (non Np-fixing)   (Np-fixing)
Maximum P Uptake
Rate (day)-'
Maximum N Uptake
Rate (day)-T
Saturation Light In-
tensity (ft. candles)
Maximum Growth Rate
at 20°C (day)'1
Milligrams Dry
Weight per Cell 0.
Sinking Rate
(meters/day)
0.502
0.125
1000
2.0
15xlO'6
0.20
0.502
0.125
1000
1.9
0.27xlO"7
0.10
0.588
0.125
500
1.2
0.25xlO"7
0.05
0.588
0.125
500
1.2
0.41xlO"7
0.05
                                    163

-------
     The computer program which actually implements the model is written in
FORTRAN IV and is structured in a form such that any number of phytoplankton
and zooplankton types can be simulated, along with any set of food web_inter-
actions among these groups.   The version of the model in Figure 1 consists of
20 simultaneous differential equations.  The solutions were obtained using a
fourth-order Runge-Kutta method with a time step of 30 minutes for the nutri-
ent kinetics equations and a time step of 3 hours for the growth equations.
For a 365-day simulation, approximately 4 minutes of CPU time are required on
an IBM 370/158 computer.  For the same simulation, approximately 45 minutes
of CPU time are required on the Grosse lie Laboratory's PDP-8/e minicomputer
with floating point hardware.

                          EXPERIMENTAL DATA

     The chemistry and chlorophyll data used were collected by Cranbrook In-
stitute of Science (Smith [1975]).  During 1974, 12 cruises were conducted
and samples were collected from 59 stations in Saginaw Bay.  Samples were
taken at 1 meter and at all depths from 5 meters to the bottom in 5-meter
intervals.  A total of 111 station-depth combinations were sampled on most
of the cruises.  Analyses were conducted for 21 chemical parameters, includ-
ing phytoplankton chlorophyll.  Since the present modeling study is re-
structed only to the inner portion of Saginaw Bay (Figure 2), only data from
the 33 field stations in this region were used.
          Figure  2.   Saginaw  Bay watershed  indicating  distinctions
                     between  inner  and  outer portions  of the bay.

                                    164

-------
     The zooplankton  data  used were  collected  on  the  above  cruises  at the
same station-depth combinations  as the  chemical data.   This  work  was  con-
ducted by the University of Michigan, Pellston Biological Station (Gannon
[1975]).  Zooplankton species counts were  converted directly to dry weight
concentrations and then integrated to the  level of the  two  functional  groups
in the model.  Work is progressing on phytoplankton species  counts  and cell
volume measurements.

     Nutrient loadings to  Saginaw Bay from the Saginaw  River,  the primary
source, were determined on the basis of a  field sampling  program.   For the
first half of the year, samples  were taken at  two- to three-day intervals
at the Dow Chemical Company water intake plant at the mouth  of the  Saginaw
River.  From July to  December, samples  were taken from  the Midland  Street
Bridge in Bay City every two weeks.  During this  period,  the  Dow  intake
plant was too strongly influenced by the bay itself.  The Midland Street
Bridge is approximately 5  miles  upstream from  the river mouth  and is not
influenced by the bay during this period.   Concentrations were  obtained for
chloride and total and dissolved forms  of  phosphorus, nitrogen, and silicon.
Daily flow rates were obtained from  the U.S. Geological Survey.

              BOUNDARY CONDITIONS AND FORCING  FUNCTIONS

     Since the physical system   under consideration is  only  part  of a  larger
physical system, Lake Huron proper,  the interaction between  Saginaw Bay and
Lake Huron is extremely important.   The predominant flow  pattern  in the bay
is counterclockwise with Lake Huron water  flowing in along the  north shore
and a mixture of Lake Huron water and Saginaw  River water flowing out  of  the
bay along the south shore  (Figure 2).   The concentrations of nutrients and
biota in the water which flows across the  indicated inner-outer boundary  are
examples of boundary  conditions  which must be  specified.  These concentrations
were determined using the  cruise data from two field stations  nearest  to  the
area of water inflow  from  the outer  bay.   Daily concentration  values were  cal-
culated by linear interpolation  between the cruise averages  for these  stations,

     Before the model can  be implemented,  various  quantities known  as  forcing
functions must be specified.  Conceptually,  the physical  system is  described
by a number of quantities  called state  variables  (Figure  1).   If, at a given
time, values are specified for each  of  these state variables,  then  the com-
plete state of the system  is known.  It is  desired to use the  model to calcu-
late the state of the system at  some future  time.  However,  in  order to do
this for the present system, various quantities such as water  circulation
rates, light, temperature, and external  nutrient  loadings must  be specified.
These quantities are forcing functions  and they are unique to  the physical
system under consideration.

External nutrient loads and water circulation  rates are the  most  important
forcing functions in the present study.  Total daily flow from the  Saginaw
River was calculated by summing  the primary  tributary gauges  and  the estima-
ted flow from the ungauged tributary area.   Daily nutrient loading  rates  were
calculated using the measured nutrient  concentrations on  that  day.  These
daily loading rates were then plotted and  time-series of  loading  rates were
generated by linearly interpolating between  all of the  significant  peaks  and
troughs.  For example, for total phosphorus, a series of  46  loading rates/
                                     165

-------
time-breaks was generated.  For orthophosphorus, a series  of  46  loading
rates/time-breaks was generated.  Water circulation  rates  between  the inner
and outer bay were determined by modeling chloride concentrations  in  the
bay and chloride loadings from the Saginaw River (Richardson  [1976]).   Time-
variable flows were used which corresponded to hydraulic detention times
ranging from 45 to 120 days for the inner bay.

                  RESULTS OF SAGINAW BAY SIMULATIONS

     Calibration results are presented in Figures 3-10.  Note  that this model
output is an attempt to describe an existing data set and  is  not intended  to
be predictive in nature.

     To obtain model output for chlorophyll a, the total biomass concentra-
tion for all four phytoplankton classes in tfie model was converted to chloro-
phyll ^concentration using 20 yg chlorophyll a/mg dry weight  biomass.   This
conversion factor was based on fresh weight biomass  and chlorophyll a  data
for Saginaw Bay (Vollenweider et al. [1974]), assuming that dry  weigFt biomass
is 20% of fresh weight biomass (Kuenzler and Ketchum [1962]).  However, these
data were collected at only one station in the inner part  of  the bay  on eight
separate cruises during the 1971 growing season.  These data  do  not necessar-
ily represent the average condition of the inner bay for 1974.

     Preliminary simulations of chlorophyll a in Saginaw Bay  (Bierman [1976])
showed that the model output was significantly higher than the data during
the month of June.  This problem has been eliminated in the present work (Fig-
ure 3) by using variable water circulation rates.  Richardson  (1976)  has shown
that two distinct flow regimes exist in Saginaw Bay, spearated by  a turbulent
transition period in June.  Previously, this high June flushing  rate  was not
modeled and only a constant, annual-average hydraulic detention  time  of 60
days was used.
          ^ 50
          en
          a.
            40
          re
          Q-
          o
          CC
          o
          3:
          o

          o
       30
            20
          o
          <->  10
          o
             0
            MEAN± Vz STANDARD DEVIATION


            	MODEL OUTPUT
          JAN ' FEB I MAR ' APR ' MAY ' JUN \ JUL ' AUG ' SEP ' OCT ' NOV ! DEC
                               TIME
Figure 3.   Corrected chlorophyll ^distribution for  1974 in Saginaw
           Bay,  inner portion, as compared to model  output.
                              166

-------
     The class composition of the model output indicates that the early
phytoplankton crops are dominated by diatoms and green algae and that the
broad Summer-Fall peak is dominated by blue-green algae (Figure 4).  A
similar successional pattern was observed in the inner bay by Vollenweider
et al. (1974).  Chartrand (1973) reported significant late-Summer crops of
Aphanizomenon, a filamentous, blue-green alga in the outer bay, which also
corresponds to model output.  It is not possible at this time to rigorously
calibrate the model at the level of the four functional groups of phyto-
plankton.  A more rigorous calibration depends on biomass data for each of
the phytoplankton classes.
 o
 o
     JAN  I FEB ' MAR ' APR ' MAY ' JUN '  JUL ' AUG ' SEP  ' OCT '  NOV ' DEC
                                 TIME
Figure 4.   Phytoplankton class composition of model output  in
           Figure  3.
     The model output for total zooplankton biomass is much lower than the
actual data (Figure 5).  This might indicate that the zooplankton kinetics
were modeled incorrectly because the model output for phytoplankton chloro-
phyll closely matches the actual data.  However, chlorophyll does not appear
in any of the kinetic equations of the model.  The phytoplankton-zooplankton
interaction is parameterized completely in terms of dry weight biomass.  Since
the only comprehensive phytoplankton data available at this time are chloro-
phyll data, neither the actual phytoplankton biomass nor the class composition
of this biomass are accurately known.  This uncertainty in the determination
of phytoplankton biomass could be an alternative explanation for the discrepancy
between the model output and the total zooplankton data.

                                    167

-------
    2.5
     2.0
Q_
O
o
M —
     1.5
O C71


5
     1.0
     0.5
 o
 o
               "  MEAN ± 1I2 STANDARD DEVIATION
                        MODEL OUTPUT
          JAN  I FEB I MAR ! APR ' MAY ' JUN  ' JUL '  AUG '  SEP ' OCT ' NOV '  DEC
                                      TIME
 Figure  5.   Total zooplankton biomass distribution for 1974 in Saginaw Bay,
            inner portion, as compared to model output.
     Model output for total  phosphorus  (Figure 6) and total nitrogen  (Fig-
ure 7) is reasonable, with  the  possible  exception of the late-fall period
for total phosphorus.  Since the  only external nutrient sources considered
were the Saginaw River and  Lake Huron,  the  present  results must be considered
preliminary in nature.  The  possible roles  of sediments and atmospheric sources
must be considered before a  complete picture of  the nutrient dynamics  in Sagi-
naw Bay can be obtained.
     The general
ures 8-10) agree
qualifications
forms.
  patterns  of the model  output  for  dissolved  nutrients  (Fig-
  reasonably well with  the  actual data.   However,  the above
for total  nutrients  must also be  applied  to the  dissolved
                                   168

-------
   100
 en
 a.
 o;
 o
    80
 £60
 o

 £ 40

 o

 £

 tE 20
 o
 o
               MEAN ± J/2 STANDARD DEVIATION
MODEL OUTPUT
      ' JAN I  FEB  I MAR ' APR ' MAY ' JUN '  JUL ' AUG '  SEP ' OCT ' NOV '  DEC

                                  TIME
Figure 6.  Total phosphorus distribution for  1974 in Saginaw Bay,  inner
          portion,  as compared to model  output.

   2500
 en
 a.
 o
 o
 Cd
<.

o
o
O
Z
O
o
   2000
   1500
   1000
    500
      0
                 MEAN ± V2 STANDARD DEVIATION
                        MODEL OUTPUT
                                       LL
        JAN  I FEB I MAR ' APR '  MAY ' JUN '  JUL  ' AUG '  SEP '  OCT ' NOV ' DEC

                                   TIME

Figure  7.   Total  nitrogen (TKN  plus  nitrate/nitrite) distribution  for 1974

           in  Saginaw Bay, inner portion,  as compared to model  output.

                                  169

-------
X
Q_
   cn
   n
     30
1/1 OO


<=> O
Ll_ X




h^ Q_


I—

LU
O

O
o
     10
                                      MEAN ± Vz STANDARD DEVIATION
                                             MODEL OUTPUT
        JAN I FEB IMAR ' APR ' MAYUUN '  JUL  ' AUG ' SEP ' OCT ' NOV ' DEC
                                 TIME
 Figure 8.   Dissolved  orthophosphate phosphorus distribution for 1974 in
    ocnn   Saginaw Bay, inner portion,  as  compared to model output.
    cXKJ
0
o
QL
O

    2000
    > 1500
o

I
h-
UJ
O
o
o
      500
       0
                                     MEAN ± lh STANDARD DEVIATION
                                            MODEL OUTPUT
          JAN  I FEB  ' MAR ' APR ' MAY ' JUN '  JUL ' AUG ' SEP '  OCT ' NOV ' DEC
                                     TIME
 Figure 9.  Dissolved  inorganic nitrogen (ammonia plus nitrate) distribution
           for 1974 in Saginaw Bay, inner portion, as compared to model  output
                                   170

-------
   1000
  en
  a.
 o 800
    600
 o
 CO
 uo

    400
 £ 200

 LU
 O
 o
MEAN + */2 STANDARD DEVIATION
         JAN I FEB I MAR ' APR ' MAY '  JUN ' JUL ' AUG ' SEP ' OCT '  NOV ' DEC
                                   TIME

 Figure 10.  Dissolved  silicon distribution for 1974 in Saginaw Bay, inner
            portion, as  compared  to model output.
                               DISCUSSION

     In general, ambiguities can occur when attempting to calibrate a math-
ematical model if the model contains  state variables or coefficients for
which there are no direct measurements.  This  is usually the case with eco-
systems models because the state of the art is still very primitive.  There
have been few comprehensive experimental programs designed to provide field
data and rate coefficients for such models.  The present model will be
refined as measurements for additional state variables and rate coefficients
become available.

     One of the causes for the discrepancy between the model output and the
total zooplankton data could be the lack of simultaneous measurements of
phytoplankton biomass and zooplankton biomass.  This problem is not neces-
sarily unique to multi-class phytoplankton models, but can also occur with
conventional chlorophyll models as well.  A multi-class approach merely adds
another dimension to this ambiguity because zooplankton are not considered
to graze all of the phytoplankton classes.  There is uncertainty in the
partitioning of the total phytoplankton biomass among the various classes,
as well as uncertainty in the total phytoplankton biomass itself.  The only
way to determine if resources should  be expended to refine the phytoplankton-
zooplankton interaction kinetics in the model  is to first obtain comprehensive
phytoplankton cell counts and cell volumes.  Such a determination is being
conducted for Saginaw Bay and the results will be incorporated in subsequent
versions of the model.
                                    171

-------
     The lack of direct measurements for all of the independent rate coeffi-
cients in a model can still result in model output which corresponds closely
to the actual data.  However, cause-effect inferences can only be made with
great caution in these cases.  In such circumstances, a model can be valuable
as a research tool if it is used to conduct sensitivity analyses for the pur-
pose of determining the most important coefficients.

     It should be noted that, as the number of state variables for which
there is comprehensive data is increased, many coefficients in a model become
more tightly constrained.   For example, phytoplankton sinking rates of 0.15
to 0.40 meters/day were used in preliminary calibration work which involved
only chlorophyll and dissolved nutrients (Bierman [1976]).  Using the present
expanded data set, it was  found that phytoplankton sinking rates could not
exceed 0.20 meters/day without causing a very significant discrepancy between
the model output and the total phosphorus data.  If an ecosystem model can be
calibrated to a large number of simultaneous and independent parameters, its
reliability as a tool for  drawing cause-effect inferences can be greatly in-
creased.  The present model will eventually be calibrated to at least 12 simul-
taneous and independent parameters and tested against similar comprehensive
data from the 1975 field sampling program on Saginaw Bay.

                           ACKNOWLEDGEMENTS

     The authors would like to thank John E. Gannon, University of Michigan
Biological Station, Pellston, Michigan, for providing unpublished zooplankton
data for Saginaw Bay.  Donald C. McNaught, State University of New York, Albany,
provided assistance in the interpretation and reduction of these data.  V.
Elliott Smith, Cranbrook Institute of Science, provided the chemical  and chloro-
phyll data for Saginaw Bay.  David M. Dolan, EPA, Large Lakes Research Station,
contributed many valuable  suggestions during this study.  The authors would like
to thank J. Kent Crawford, Nelson A. Thomas and David M. Dolan, all  from EPA,
Large Lakes Research Station, for reviewing the manuscript.


                              REFERENCES

Bierman,  V.J., Jr.   1976.   Mathematical Model of the Selective Enhancement
     of  Blue-Green Algae by Nutrient Enrichment.      In:  Modeling Biochemical
     Processes in Aquatic  Ecosystems.   (R.P. Cahale, ecITtor).  Ann Arbor
     Science Publishers, Inc.  Ann Arbor, MI  pp. 141-169.

Canale,  R.P., Nachiappan,   S., Hineman, D.J. and Allen, H.E.  1973.  A Dynamic
     Model for Phytoplankton Production in Grand Traverse Bay.  Proceedings,
     Sixteenth Conference  on Great Lakes Research, April 16-18, 1973.  Inter-
     national Association  for Great Lakes Research, Huron, Ohio  pp. 21-33.

Caperon,  J. and Meyer, J.   1972a.  Nitrogen-Limited Growth of Marine Phyto-
     plankton-I.  Changes   in Population Characteristics with Steady-State
     Growth Rate.  Deep Sea Research 19:  601-618.

Caperon,  J. and Meyer, J.   I972b.  Nitrogen-Limited Growth of Marine Phyto-
     plankton-II.  Uptake  Kinetics and Their Role in Nutrient Limited Growth
     of  Phytoplankton.  Deep Sea Research 19:  619-632.

Chartrand, T.A.   1973.  A  Report on the Taste and Odor in Relation to the
     Saginaw-Midland Supply at Whitestone Point in Lake Huron.   Saginaw
     Water Treatment Plant, Saginaw, Michigan.

                                    172

-------
Chen, C.W. and Orlob, G.T.  1972.  Ecologic Simulation for Aquatic Environments.
     Water Resources Engineers, Inc., Walnut Creek, California.  Report prepared
     for Office of Water Resources Research, U.S. Department of the Interior.

DePinto, J.V., Bierman, V.J., Jr. and Verhoff, F.H.  1976.  Seasonal  Phyto-
     plankton Succession as a Function of Species Competition for Phosphorus
     and Nitrogen.   In:  Modeling Biochemical Processes in Aquatic Ecosystems.
     (R.P. Canale,  edTtor).  Ann Arbor Science Publishers, Inc.  Ann  Arbor, MI
     pp.  141-169.

Droop,  M.R.   1973.   Some Thoughts on Nutrient Limitation in Algae.   Journal
     of Phycology 9:   264-272.

Fuhs, 6.W.  1969.   Phosphorus Content and Rate of Growth in the Diatoms  C.yclotella
     nana and Thai assiosira fluviatilis.   Journal of Phycology 5:   312-321.

Fuhs, G.W.,  Demmerle, S.D., Canelli, E. and Chen, M.  1971.  Characterization
     of Phosphorus-Limited Planktonic Algae.  Nutrients and Eutrophication:  The
     Limiting Nutrient Controversy.   Proceedings of a Symposium,  February  11-12,
     1971.  American  Society of Limnology and Oceanography and Michigan  State
     University,  East Lansing,  Michigan,  pp. 113-132.

Gannon,  J.J.   1975.   Crustacean Zooplankton in Saginaw Bay, Lake  Huron.  A
     report  to the  International Reference Group on Upper Lakes  Pollution,
     International  Joint Commission, Windsor, Ontario.

Kuenzler, E.J.  and  Ketchum, B.H.  1962.  Rate of Phosphorus Uptake  by
     Phaeodactylum  tricornutum.  Biological Bulletin 123:   134-145.

Middlebrooks, E.J., Falkenburg, D.H. and Maloney, I.E. (Eds).  1973.
     Modeling the Eutrophication Process.  Proceedings of a Workshop,
     September 5-7, 1973.  Utah Water Research Laboratory and Division
     of Environmental Engineers, Utah State University, Logan.  National
     Eutrophication Research Program, U.S. Environmental Protection Agency,
     Corvallis, Oregon.

O'Connor, D.J., Thomann, R.V. and DiToro, D.M.  1973.  Dynamic Water  Quality
     Forecasting and Management.  U.S. Environmental Protection Agency,
     Corvallis, Oregon, Ecological Research Series EPA-660/3-73-009.

Richardson,  W.L.   1976.  An Evaluation of the Transport Characteristics  of
     Saginaw Bay Using a Mathematical Model of Chloride.  I_n_:  Mathematical
     Modeling of Biochemical Processes in Aquatic Ecosystems.  (R.P-  Canale,
     editor).  Ann  Arbor Science Publishers, Inc., Ann Arbor, MI.  pp.  113-139.

Smith,  V.E.   1975.   Saginaw Bay (Lake Huron):  Survey of Physical  and Chemi-
     cal Parameters.   A report to the International Reference Group on  Upper
     Lakes Pollution, International  Joint Commission, Windsor, Ontario.

Thomann, R.V., DiToro, D.M., Winfield, R.P. and O'Connor, D.J.  1975.
     Mathematical Modeling of Phytoplankton in Lake Ontario.  I.  Model
     Development and Verification.  U.S.  Environmental Protection Agency,
     Corvallis Oregon, Ecological Research Series EPA-660/3-75-005.

Vollenweider,, R.A., Munawar, M. and Stadelmann, P.  1974.  A Comparative
     Review of Phytoplankton and Primary Production in the Laurentian Great
     Lakes.   Journal  of the Fisheries Research Board of Canada 31:   739-762.

                                      173

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          Implications of Resource Development on the
          North Slope of Alaska with Regard to Water
                Quality on the Sagavanirktok River

                        Eldor W. Schallock*


                              ABSTRACT


          The  Sagavanirktok (Sag) River, located on the North
          Slope  of Alaska is undergoing a rapid transition from
          an  isolated undisturbed river system to an accessible
          impacted watershed.   Impact is caused by:  1.  The de-
          mands  of rapidly expanding industry drawing heavily
          upon some of the available resources such as water and
          gravel; 2.  The extended arctic conditions that affect
          the  environment which include 8 months of winter (Octo-
          ber  through May), permafrost a few centimeters beneath
          the  surface, and annual"precipitation in the coastal
          province of about 14 cm; and 3.  The specific water
          quality characteristics of the river that are sometimes
          limited and critical.  During winter, stream discharge
          virtually ceases, dissolved oxygen concentrations are
          low  (1.2 mg/1), specific conductance may be high (1700
          umhos), and nutrients may be high (0.76 mg/1  nitrate
          as  nitrogen and 12.5 mg/1 silica).  The impact of in-
          dustry on these water quality characteristics may affect
          indigenous aquatic biota.


                            INTRODUCTION


     The Sagavanirktok (Sag) River, located on the North Slope  of Alaska,
(Figure 1) is  undergoing a rapid transition from an isolated, undisturbed
stream system  to an accessible impacted drainage.  This transition started
in 1968 with  discovery of oil  at Prudhoe Bay near the mouth of  the river.
It is continuing with the construction of the Trans-Alaska pipeline (Alyeska
Pipeline) which  traverses approximately 200 km (125 miles) through the heart
of the Sag River Basin.  Further transition is a promise for the  future with
the continued  search and development of oil and as the quest for  other natural
resources begins.  The anticipated completion 'of the bridge crossing the Yukon
River will complete the all-weather road connecting the Alaskan Arctic to  the
existing State road system and will enable additional access to the Sag River.
*Corvallis  Environmental  Research Laboratory, U.S. Environmental Protection
Agency, Arctic  Environmental  Research Station, College, AK  99701

                                   174

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                                             ARCTIC OCEAN
                                                            POINT
                                                            BARROW
Ln
                                                               FIGURE I.   MAP OF ALASKA SHOWING
                                                                          LOCATIONS OF STREAM SYSTEMS

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     This new prominence in the world of resources, and the linked acces-
sibility, is impacting a set of terrestrial and aquatic environmental con-
ditions that are substantially different from those in the contiguous 48
states.  It is impossible to discuss all of them with the interrelationships
here, but a few pertinent factors will set the environmental scene and re-
late to implications of resource development.


                               CLIMATE
     The Arctic climate may best be described as harsh when compared to
climates of most other areas.   Ambient air temperature, one of the dom-
inant features, is characterized by a mean annual range of -12°C (10°F)
to -7°C (19°F) (Watson, 1969)  and by severe winter temperatures as low
as -54°C (-65°F) in localized  interior areas.  As little as 10 cm (4 inches)
of precipitation may collect along the coast (Johnson et al., 1969), and
winter precipitation as snow is often redeposited by strong and persistent
winds (Watson, 1969).

     Another factor that contributes to the harshness is lack of solar ra-
diation during the winter.   Prudhoe Bay, which is near 70°M latitude, has
no direct sunlight from the middle of November to mid-January, but during
the summer  has continuous daylight from the middle of May to early August.

     The above factors affect  permafrost which becomes unstable when the
temperature equilibrium of the system is disturbed (Proceedings of the First
International  Conference on Permafrost, 1963).  All  of the Arctic is in the
continuous permafrost zone (Ferrians, 1969) with the thickness ranging up
to 396 meters  (1300 feet).

     Climate,  permafrost, and  geology of the area all affect the soil that
has developed, and vegetation  types that have adapted to this ecosystem.
Several  soil types have been described (Tedrow and Cant!on, 1958 and Tedrow
et al.,  1958).  These soil  types support different vegetative communities
which may have as many as 300  different species of plants (Johnson et al.,
1964).   These  plant communities in turn dampen the soil temperature extremes,
retard heat penetration, reduce the rate of soil and frost erosion and there-
by maintain the permafrost integrity (Johnson, 1963).


                            WATER QUALITY


     A baseline water quality  survey of the Sag River basin was conducted
by the Arctic  Environmental Research Laboratory in 1969-70.  The water qual-
ity of the river at that time  could be characterized as good during the
summer open water period.  Breakup and summer precipitation in the form of
spates can cause temporary changes and deterioration in the quality of some
parameters.  This, however, is usually a short-lived phenomenon and does not
create serious problems for the indigenous biota, or for the domestic and
industrial  users.  Breakup occurs during early June although the timing, mag-
nitude and related problems such as flooding are dependent upon a combination
of factors and may vary widely from year to year.

                                    176

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     Sag River water quality during winter differs substantially from sum-
mer.  The differences are caused by a complex interaction of geologic and
climatological factors that affect numerous water quality parameters.  Se-
lected summer and winter data are presented in Table 1.  These data are
similar to results obtained from the Colvilie, Kuparuk and Sag Rivers by
the U.S. Geological Survey in 1964 and 1972.


          TABLE i.  SELECTED WINTER AND SUMMER WATER QUALITY DATA
                   FROM SAMPLES COLLECTED FROM THE SAGAVANIRKTOK
                    RIVER 1969-1970
Parameter
Silica (mg/1)
Total phosphate (mg/1)
Nitrate (mg/1)
Ammonia (mg/1)
Calcium (mg/1)
Potassium (mg/1)
Sodium (mg/1)
pH
Specific conductance
(umhos)
Range During
0.6 -
0.01 -
0.05 -
0.02 -
Summer
2.7
0.05
0.15
0.09
10.0 - 42.0
0.15 -
0.40 -
7.6 -
80 -
0.75
1.3
8.1
240
Range During
3.6 -
0.01
0.09 -
0.01 -
89.0
0.7 -
2.6 -
7.2 -
660 -
Winter
12.5

0.76
0.18
95.0
1.97
9.0
7.7
1700
     Comparison of summer data to winter data in Table 1  shows  that several
water quality parameters deterioriated appreciably in winter.   In  many  in-
stances, the ranges found during the winter were significantly  higher than
those found during the summer.  These trends are supported by dissolved
solids and hardness data from the Colvilie and Sag Rivers by Feulner, et  al.,
1971.  These higher concentrations during winter are probably caused by a
combination of extrusion of salts during the freezing process,  accumulating
metabolites and salt water intrusion in coastal areas.

     Dissolved oxygen (DO) is often considered to be one of the critical
parameters affecting aquatic life but until recently was not considered to
be a problem in Alaska.  The data presented in Figure 2 indicate that DO
ranges from 9.9 mg/1 (91.7 percent saturation) to 13.3 mg/1 (95 percent
saturation) during the summer but extremely low concentrations  may be found
during the winter (1.2 mg/1; 8.2 percent saturation).  These concentrations
are comparable to other DO data on the rivers of the North Slope and to the
general spatial and seasonal DO patterns in the Chena, Chatanilca,  Tanana,
and Yukon Rivers of interior Alaska (Schallock and Lotspeich,  1974).
                                    177

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o
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at
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LU
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14



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10



 8




 6



 4



 2
   14
 01 12
£  10
(D

X
O  8

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i/i


Q  4
                                                  JUNE
          13X)0
                 1100
?6o'700560
        (mouth)

300       ido
                                                    JUNE
                               APRIL

                               /\
                              O
                                   o
                                                                   (moulh)
        S-1300       1100      900       700       500       300       100
               1200       1000       800       600       400       200


      Figure 2.   Dissolved oxygen and water temperature  data  from
                 13 stations on the Sagavanirktok River  (1969-1970).


      A consistent inverse relationship was found between water temperature
 and  concentrations of DO.  During the June study interval, the water tem-

 perature reached the recorded maximum of about 12°C  (54°F).   Water tempera-
 tures were generally highest in the foothill province near Sagwon  (Station
 700) about 104 km (65 miles) inland from Prudhoe Bay.
                                      178

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                             WATER QUANTITY


     Stream  discharges  and seasonal  timing of these discharges  are char-
acteristics  causing  great  concern both  in industry and in the  agencies
charged with  resource management.  Long periods  of low discharge  during
winter followed  by an increase  during spring and rapid decline  after break-
up are the "normal"  discharge patterns  of the Sag and  Patuliqayak  (Put)
Rivers (Figure 3).                                                     '
         (Both scales in thousands)
             (ft3/sec)
     Figure 3.  Seasonal discharge  in the Sagavanirktok  (Sag) and
                Putuligayak  (Put) Rivers from October 1973 through
                September  1974  (U.S.G.S. Data).

     Spring breakup accounts for the majority of the annual discharge.  In
the Put River, over 71 percent  of the annual volume is discharged between
June 1st and June 15th and approximately 94 percent of the annual volume by
June 30th.  In the Sag River, the results are not as dramatic if the same
comparisons are made because the seasonal high discharge pattern is bimodal.
Between June 1st and June  15th, over 16 percent of the total is discharged
while 10 percent is discharged  between June 16th and June 30th.  A higher
peak with shorter duration occurred  between August 16th and August 31st and
accounts for 20 percent of the  total.  The short term, high volume discharges
of both the Put and Sag Rivers  rapidly decrease to smaller volumes that ap-
parently originate from ground  water sources.   This smaller volume is reached
in July and October, respectively.   The Colville River, the largest drainage
on the North Slope, may discharge as much as 43 percent  of the annual runoff
in a 3-week period (Alexander,  et al., 1974).
                                    179

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     Some debate has focused on whether the discharge of North Slope ri-
vers during the winter is just extremely low or whether discharge actually
ceases in some instances.  In either case,  a limited volume of water is
available for man's use.

                        AQUATIC BIOLOGY

     Prior to discovery of oil at Prudhoe Bay,  little information has been
published on the life history patterns  of the indigenous fish and only oc-
casional   data were available on microbiological  or macrobenthic communities.
Since 1968, moderate effort has gone into examining various characteristics
of specific biological populations and  communities.

     Spawning areas, migration patterns and overwintering areas were chosen
as possible limiting factors to any population  of fish inhabiting the Sag
River.  The two most important fish in  the  Sag  River are the Arctic Char,
Salvelinus alpinus, and the Arctic Grayling, Thymallus arcticus.   Lake Trout,
Salvelinus namaycush, are also found in the river basin.

     Arctic char and grayling are generally distributed throughout the Sag
drainage but may be concentrated in localized areas of the Sag main stem or
its tributaries during the summer.  Some migrations such as the upstream mi-
gration of adult and subadult char during early summer are well documented
while other migrations are suspected but are not well documented.

     Spawning areas utilized by char and grayling are difficult to locate
because the char spawn in autumn when ice cover is beginning and grayling
spawn during the high water of spring.   Both fish establish redds in gravels
with specific characteristics.

     Overwintering of young-of-the-year and juveniles are also difficult to
determine.  Studies by the Alaska Department of Fish and Game and the U.S.
Fish and Wildlife Service documented overwintering populations in spring
areas that are primarily located in the upper Sag drainage and tributaries.
However, Furniss (1975) recently demonstrated that young-of-the-year and/or
juvenile fish are also utilizing the deep pools of the Sag River from Franklin
Bluffs to the coast.

     Members of the macrobenthic community  are  ubiquitously distributed along
the length of the river and are sensitive to water quality parameters because
the organisms are relatively immobile.   This community consists principally
of Plecoptera (stoneflies), Ephemeroptera (mayflies), Chironomidae (midges),
Trichoptera (cadisflies), and oligochaetes.  These organisms may number as
high as 400 per square meter (330 per square yard) during summer conditions
(Schallock and Mueller, 1970) and are the primary food items for most life
stages of fish.

     Unpublished data collected by Gordon during 1969-1970 showed that the
number of local coliforms present in the Sag River was low at that time.
However, his recent work (Gordon, 1975) on  the survival of enteric micro-
organisms in the Tanana River near Fairbanks reveals that the addition of
these microorganisms into a limited and closed system such as the Sag River
could be extremely dangerous to users.   This danger appears where numerous
activities are located along the drainage and the river is utilized as a
source of potable water.
                                    180

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                  RESOURCE AND MANAGEMENT  IMPLICATIONS

WATER APPROPRIATIONS

     Quantity and water quality are  problems on Alaska's North Slope.  Sea-
sonal discharge patterns and changes  in the water quality of North Slope
rivers have been  presented  during early discussion.  The demands for water
for both domestic and specific industrial  activities are stressing the limited
supplies.  This is causing  industry  to travel some distance to obtain water
and also to consider alternative sources  and techniques for obtaining water.

     The customary method for collecting  water has been to set up a pump sta-
tion at the river or to drill a hole  in the ice and utilize a tanker truck to
collect and transport the water.  Pipeline construction activity has resulted
in the demand for water to  increase  drastically; consequently some "watering
holes" have been  pumped dry.

     Initially water was collected from the river immediately adjacent to the
particular use.  However, this past winter water was hauled as far as 72 km
(45 miles) when it was not  available  in the immediate area.  In one instance,
holes were drilled through  the river  ice  on a grid system with holes as close
as 15 meters (50  feet).  Whenever water was found, radio communications to
identify the specific location were made  to the water truck.  The water truck
then came to the water hole and pumped until that particular hole was dry and
then the search for another water hole began.

     Tundra lakes have been considered as an additional source but these lakes
generally have small volumes of poor  quality water that must be treated to be
potable.

GRAVEL MINING

     Gravel mining is presently causing tremendous concern, for this activity
has not been given adequate regulation.   One has only to examine the variety
of endeavors utilizing gravel and the magnitude of its use is brought into fo-
cus.  All roads, airstrips, pads for  building, drill rigs and pipelines require
large amounts of gravel.  It is of particular important  in those areas where
a permanent gravel foundation is needed to maintain permafrost integrity.

     An accurate estimate of the gravel requirements for pipeline construction
was impossible before construction began.  Early estimates, however, placed the
amount near 4.6 million cubic meters  (6 million cubic yards) for the entire
pipeline while some Federal resource managers at the time estimated the amount
to be closer to 7.6 million cubic meters  (10 million cubic yards).   At the pre-
sent time, nearly twice this amount has been extracted from the lands adminis-
tered by the Bureau of Land Management on the North Slope alone (Dean, 1975).
It is now estimated that as much as 161 million cubic meters (210 million cubic
yards) have been used along the pipeline  and about 18 months of construction are
still remaining.

     Adequate amounts of suitable gravel  are not readily available in many areas
of the North Slope.   However, the Sag River and its tributaries provide a perma-
frost free "thaw bulb" wherein it is economically feasible to borrow gravel.  As
a result, gravel used for airstrips,  roads, pipeline pads and drill pads is being
removed only from these frost-free areas.
                                   181

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     Limited availability and resultant overhauls have increased the cost of
 gravel.  Gravel purchased from the material site for approximately 18 cents
 per  cubic meter (14 cents/cubic yard) may cost as much as $52 per cubic me-
 ter  ($40/cubic yard) by the time it is purchased, loaded, hauled, deposited
 and  spread at the deposition site.  The shortage of gravel and its increasing
 cost is causing industry to consider other methods and materials as a substitute

     Gravel mining can adversely affect the water quality.  It may cause ex-
 cessive suspended sediment and increased stream bed load if the mining opera-
 tion is improperly placed  and an effective settling pond is not provided.  The
 addition of sediment to a stream system may in turn prevent primary production,
 cover the macrobenthic community and cuase the fish to outmigrate or smother
 the  developing eggs and young-of-the-year.  Continued gravel mining from the
 flood plain of the Sag River may also cause hydrologic instability that would
 require a long time to equilibrate.  During this period of reestablishment,
 suspended sediment with its attendant problems would likely continue at above
 normal levels.

 WASTE DISCHARGE

     Waste discharges from permanent camps, temporary camps and drilling sites
 are  a serious threat to water quality of the Sag River.  The addition of
 oxygen demanding substances to an already severely depressed dissolved oxygen
 system would be disastrous.  Toxic substances, such as residual chlorine or
 chloramines, heavy metals and hydrocarbons, if released into the water course,
 particularly during the low flow periods, could rapidly eliminate desirable
 fish and macrobenthic organisms.  In addition, effluent containing enteric
 microorganisms from human waste that enters the river may well become a part
 of a downstream user's water supply.

 BIOLOGICAL IMPLICATIONS

     The Sag River is now experiencing the full impact of man's development
 of a nonrenewable resource in arctic Alaska.  What are the implications of
 water appropriations, gravel mining and waste discharge on the river system?
 The  most obvious implication is an adverse effect on the aquatic resources of
 the  river.  Overwintering populations of fish and macrobenthos will be impacted
 by water use in the Franklin Bluffs to Prudhoe Bay area.  Reliable reports have
 been received of fish being found in water holding tanks.  Other reports des-
 cribe instances where the operator pumping water into the tank truck would have
 to stop and clean the intake screen of fish carcasses.  Still other reports des-
 cribe invertebrates contained in water supplies.

     Low discharge during winter also magnifies the impact on the stream when
 it is used as the receiving water for domestic or industrial effluent.  Small
 volumes of water, low winter dissolved oxygen and high concentrations of dis-
 solved constituents all combine to create a system that is highly sensitive to
 an effluent containing oxygen demanding materials and/or toxic substances such
 as residual chlorine.  With the addition of enteric microorganisms into this
limited  and closed system, public health becomes a serious consideration where
 activities are located along the drainage and utilize the river as a source of
 potable water.

                                   182

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      Finally, aquatic organisms within the river system may  be  deleteriously
 affected by gravel  mining operations either through the direct  addition of
 sediment to the system or indirectly by hydro!ogical  instability.
                              REFERENCES
Alexander, V., D.C. Burrell, J. Chang, T.R. Cooney, C. Coulon, J.J.  Crane,
     J.S. Dygas, G.E. Hall, P.J. Kinney, D. Kogl , J.C. Mowatt, A.S.  Naidu,
     I.E. Osterkamp, D.M. Schell , R.D. Seifert, and R.W. Tucker,  1974.
     "Environmental Studies of an Arctic Estuarine System."  Final  Report,
     Institute of Marine Science, University of Alaska, College,  Alaska,
     Report R-74-1.  U.S. Environmental Protection Agency Research
     Grant No. 16100EOM.

Dean, T. , 1975.  Personal communications concerning gravel  mining on
     Alaskan North Slope lands administered by the Bureau of Land Management.
     U.S. Department of Interior, Bureau of Land Management, Fairbanks,
     Alaska.
Ferrians, O.J., 1969.
     Inv.  Map  #1-445.
                       Permafrost Map of Alaska.  U.S.  Geological  Survey
Feulner,  A.J., J.M. Childers, and V.W. Norman, 1971.  "Water Resources  Data
     for Alaska, 1971."  U.S. Geological Survey, 1972.   Publ .  Anchorage, AK.

Furniss, R. , 1975.  Personal communication concerning fish  overwintering areas
     and water appropriation in the Sagavanirktok River.  Alaska  Department
     of Fish and Game, Fairbanks,  Alaska.

Gordon, R.C., 1970.  Unpublished water quality data from the Sagavanirktok
     River, Environmental Protection Agency, Alaska Water Laboratory,
     College, Alaska.

Gordon, R.C., 1975.  Personal communication concerning  the  survival  of  enteric
     microorganisms in a subarctic river near Fairbanks,  Alaska.   Environmen-
     tal  Protection Agency, Arctic Environmental Research Laboratory, College,
     Alaska.

Johnson,  A.W., 1963.  "Ecology in Permafrost Areas."  Proceedings of First
     International Conference on Permafrost, presented  by Building Research
     Advisory Board, National Academy of Science, Washington, D.C., pp.  25-30.

Johnson,  A.W., L. Viereck, R. Johnson and R. Melchoir,  1964.  "The Vegetation
     and Flora of the Ogotoruk Creek—Cape Thompson Area, Alaska," Environment
     of the Cape Thompson Region, Alaska, Norman J. Wilimovsky,  Editor.  U.S.
     Atomic Energy Commission, Division of Technical Information, Oak Ridge,
     Tennessee,  pp. 277-363.
                                   183

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Johnson, P.R., and C.W.  Hartman, 1969.   "Environmental  Atlas of Alaska."
     Institute of Water Resources, University of Alaska, College,  Alaska, 111  p.

Netsch, N., 1975.  Personal  communication regarding water quality, water
     quantity and related problems in the Sag River.  Anchorage, Alaska.
     U.S.  Fish and Wildlife  Service,  Anchorage, Alaska.

 Proceedings of the First International  Conference  on  Permafrost,  1963.
      Presented by Building  Research  Advisory Board, National  Academy
      of Science, Washington,  D.C.

 Schallock, E.W.  and E.W. Meuller, 1970.   Unpublished  data  on  the  Sagavan-
      irktok River.  Environmental  Protection Agency,  Arctic Environmental
      Research Laboratory, College, Alaska.

 Shallock,  E.W. and F.B.  Lotspeich, 1974.  "Low Winter  Dissolved  Oxygen in
      Some  Alaskan Rivers."   U.S.  Environmental  Protection  Agency,  National
      Environmental Research Center,  Corvallis,  Oregon,  33  p.

 Tedrow, J.C.F. and J.E.  Cantlon,  1958.   "Concepts  of  Soil  Formation and
      Classification in  Arctic Regions."   Arctic, Vol.  11,  pp.  166-179.

 Tedrow, J.C.F.,  J.V.  Drew,  D.E.  Hill, and L.A.  Douglas,  1958.  "Major Genetic
      Soils of the Arctic Slope of Alaska."   J.  Soil Science.  Vol.  9,
      pp. 33-45.

 U.S.  Geological  Survey,  1964.  Compilation of Records of  Surface Waters  of
      Alaska,  October  1950 to  September  1960.  Anchorage,  Alaska.

 U.S.  Geological  Survey,  1972.   Water Resources  Data for  Alaska, 1971.
      Anchorage,  Alaska.

 Watson, C.D.  1969.  Climates  of the  States:   Alaska.   U.S.  Weather Bureau,
      Climatography of the U.S.,  No.  60-49, 24 p.
                                  184

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                Lake Eutrophication:  Results from
                The National Eutrophication Survey

                 Jack H. Gakstatter, Marvin  0.  Allum
                        and James M. Omernik*


                             INTRODUCTION


     In early 1972, the U.S.  Environmental Protection Agency  (EPA) initiated
the National Eutrophication Survey (NES)  program to:   (1) identify those
lakes and reservoirs in the contiguous  United States that receive nutrients
from the discharges of municipal  sewage  treatment facilities, and (2) deter-
mine the significance of these  point-source  nutrient inputs to the nutrient
levels and the primary productivity of  each  system.  After the program began,
additional federal  legislation  was passed  (Public Law 92-500), and NES ob-
jectives were broadened to include an assessment of the relationships of non-
point sources; e.g., land use,  to lake  nutrient levels and also to assist in
establishing water-quality criteria for  nutrients.


                          SELECTION CRITERIA
     Freshwater lakes and impoundments  in  the  Survey were selected through
consultation with EPA Regional  Offices  and state  pollution control agencies,
as well as related state agencies  managing fisheries, water resources, or
public health.   EPA established selection  criteria  to limit the type and
number of candidate water bodies,  consistent with existing Agency water goals
and strategies.   For 27 states  of  the eastern  United States where lakes were
selected prior  to passage of P.L.  92-500,  strongest emphasis was placed on
lakes faced with actual or potential  accelerated  eutrophication problems; i.e.
an artificially increased rate  of  algal  and/or aquatic plant production.  As
a result, the selected lakes:

     1.  were impacted by one or more municipal sewage treatment plants,
         either directly or by  discharge to an inlet tributary within
         approximately 25 miles of the  lake;

     2.  were 100 acres or larger  in  size; and

     3.  had mean hydraulic retention times of at least  30 days.
*Corvallis Environmental  Research Laboratory,  U.S.  Environmental Protection
Agency, Corvallis, OR  97330

                                   185

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However, these criteria were waived for a number of lakes  of particular
interest to the states.

     In the western states, these criteria were modified to reflect revised
water-research mandates, as well  as to address  more prevalent non-point
source problems in agricultural  or undeveloped  areas.   Thus each state was
requested to submit a list of candidate lakes  for the  Survey that:

     1.  were representative of the full  range  of water quality (from
         oligotrophic* to eutrophic*);

     2.  were in the recreational, water supply, and/or fish and wildlife
         propagation use-categories; and

     3.  were representative of the full  scope  of nutrient pollution prob-
         lems or sources (from municipal  waste  and/or  nutrient-rich indus-
         trial discharges, as well as from non-point sources).

     The size and retention time constraints  applied in the eastern states
were retained as was the waiver provision.

     In all cases, listings of potential  candidate lakes or reservoirs, pre-
pared with the cooperation of the EPA Regional  Offices, were made available
to the states to initiate the selection process.

     In total, the Survey includes 812 lakes  and reservoirs across  the con-
tiguous 48 United States.  Figure 1 shows the  distribution of the lakes and
reservoirs by state and the year during which  each water body was sampled.

GENERAL SURVEY METHODS

     Several kinds of information are required  as a basis  for management
decisions regarding the need for point or non-point source control  of phos-
phorus and perhaps other nutrients as well.  The Survey purpose is  to collect
the type of data which will provide a basis for such decisions  or at least to
provide a data base which can be supplemented with more detail, if required.
First, an annual nutrient budget is estimated  for each water body,  differen-
tiating between inputs originating from point  and non-point sources; second,
the existing trophic condition of the water body is evaluated by sampling;
and third, an algal assay is performed to determine whether phosphorus, ni-
trogen, or some other element is limiting primary productivity of the water
body.  The methods used to gather this information are described below.

     The operations aspects of the Survey are  shared by branches of two EPA
laboratories (46 people) and a small headquarters staff (3 people).  The
Environmental Monitoring and Support Laboratory at Las Vegas, Nevada (Las
Vegas-EMSL) is responsible for sampling each  lake, doing the associated an-
alyses, evaluating a portion of the data, and  reporting results.  The Cor-
vallis Environmental Research Laboratory (CERL) at Con/all is, Oregon is
responsible for coordinating the sampling of streams and sewage treatment
plants, analyzing the samples, and performing  the algal assay on lake samples
  Oligotrophic--low nutrient concentrations and primary productivity.
  Eutrophic--high nutrient concentrations and primary productivity.
                                    186

-------
Oo
             1975-152
               GRAND TOTAL-  812
                Figure 1.  Number of lakes and reservoirs  sampled in each state and year of
                          sampling by the National Eutrophication Survey.

-------
CERL also has major responsibility for evaluating the  lake,  stream,  and
point-source data and incorporating these data  into  a  report on  each lake.
The headquarters staff (Washington, D.C.) makes  the  initial  contact  with
each state water pollution control  agency to  explain the  function  of the
Survey and to cooperatively determine which  lakes and  reservoirs will  be
included.  They also contact each  State National  Guard to explain  the
function of the Survey and to request their  assistance in meeting  Survey
objectives by collecting monthly samples from selected tributaries to sur-
veyed lakes.  In addition, the headquarters  staff provides general  coordin-
ation and guidance to the operational aspects of the program.

     Because the Survey has to cover a large  geographical area in  a  rela-
tively short period of time, pontoon-equipped UH-1H  Bell  helicopters with
automated and manually-operated instruments  are  used to measure  the  water
quality of each lake.  Two helicopters - carrying a  limnologist  and  a
technician - are operated simultaneously, and a  third  helicopter is  used
for ferrying parts, equipment, and people.   The  sampling  teams from  the
Las Vegas-EMSL are supported by a  mobile analytical  laboratory,  chemistry
technicians, electronic specialists, and other  staff involved  with heli-
copter maintenance or program coordination.   The total  staff in  the  field
usually ranges from 12 to 14 people.

     Operating procedures involve  establishing  a work  center at  an airport
and then sampling all lakes within a 100-mile radius.   When  all  of the water
bodies within the area are sampled, the support  staff  moves  to a new central
location, and sampling begins on a different  set of  lakes.  In this  manner,
150 to 250 lakes have been sampled three times  each  year, and  the  sampling
will be completed on all of the 812 lakes in  a  four-year  period.

     Table 1 depicts the routine water-quality  parameters which  were selected
to characterize each lake and assess its trophic condition.   Parameter selec-
tion was based on the relevance of each parameter as a measure of  potential
and existing primary production.  Both the number and  the type of  parameters
measured were also limited to a certain extent  by the  operational  aspects of
the Survey.

          TABLE 1.  WATER-QUALITY  CHARACTERISTICS MEASURED
                         Physical-Chemical
          Alkalinity                      Nitrogen:
          Conductivity*                     Ammonia
          pH*                               Kjeldahl
          Dissolved oxygen                  Nitrate
          Phosphorus:                      Secchi  depth
            Ortho                         Temperature*
            Total

                             Biological

          Algal assay                      Algal  count and
                                           identification
                       Chlorophyll  £

          *Determined  on-site with  electronic probes.
                                   188

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     Concurrent with the lake sampling, the significant tributaries  and
outlet(s) of each lake are sampled monthly, totaling about 4,200 sampling
sites nationwide.  Volunteer National Guardsmen of each state, trained on-
site by EPA or state agency staff, collect and preserve the samples  at sites
pre-selected by EPA personnel.  The samples are shipped to CERL for  analysis
of the various forms of nitrogen and phosphorus (see Table 1).

     Through an interagency agreement, the U.S. Geological Survey estimates
flows for each sampled stream.  These data are used in conjunction with con-
centration values to determine nutrient loadings.

     A voluntary sampling program was established  through the respective
state water pollution control agencies to have plant operators collect
effluent samples from those municipal sewage treatment plants which  impact
Survey lakes—about 1,000 treatment plants.  The effluent samples are  col-
lected monthly, preserved, and shipped to the Con/all is laboratory for
nitrogen and phosphorus analyses.

     Specific procedures used in collecting, preserving, shipping, and anal-
yzing the various kinds of samples collected by the Survey are described in
National Eutrophication Survey Working Papers No.  1 (1974) and 175 (1975).

     Presently, the field portion of the Survey is almost completed  with the
last samples scheduled for collection in November, 1975.  Data analysis is
scheduled for completion in December, 1976.

                          RESULTS AND DISCUSSION

LIMITING NUTRIENTS

     For each of the surveyed lakes, an algal assay is performed on  a  sample
of lake water and, to supplement the assay findings, inorganic nitrogen to
dissolved orthophorus ratios are determined from the lake sampling results.
For the 623 surveyed lakes in states east of the Rocky Mountains, the  assay
demonstrated that with respect to algal growth requirements,  67% were  phos-
phorus-limited, 30% were nitrogen-limited and 3% were  either  limited by an
element other than phosphorus or nitrogen or the results were not conclusive
(Table 2).

     TABLE 2.  SUMMARY OF ALGAL ASSAY RESULTS FOR  SURVEYED WATER
               BODIES IN THE 37 STATES EAST OF THE ROCKY MOUNTAINS


     Limiting Nutrient          Number of Lakes     %  of all  Lakes
Phosphorus
Nitrogen
Other
417
186
20
67
30
3
                      Total           623                100%
                                    189

-------
     A higher percentage of phosphorus  limited lakes  would probably have
been found had the Survey not been mostly concerned with  lakes which were
impacted by municipal  wastes.  The algal  assay results  should, therefore,
be evaluated with some caution because  they reflect existing conditions
which often include man's impact on the nutrient regime.

     Municipal waste treatment plant effluents, for example, have an average
total nitrogen to total phosphorus ratio  of about 2.5 to  1 whereas natural
waters usually have a ratio in excess of  15 to 1.   The  relative abundance of
phosphorus provided in municipal effluents could change a lake from phosphorus-
limited to nitrogen-limited.   Such a lake could theoretically be changed back
to phosphorus-limited by reducing phosphorus inputs.

     Figure 2 is an indication of the significance of municipal wastes  to
the total annual phosphorus load to some  of the eastern lakes and reservoirs.
Of the 234 water bodies included in the frequency histogram, 135 receive
more than 20% of their annual total phosphorus load from  municipal sources.
    200

     175


 u   150

 -1   125
 u-
 °   100
 ce
 LU   ....
 CD   75
 2
 ID
 z   50

     25
         0-10   11-20  21-30 31-40  41-50 51-60  61-70  71-80  81-90  91-100

    PERCENT  OF  TOTAL  PHOSPHORUS  LOAD  FROM   MUNICIPAL  POINT SOURCES
    Figure 2.   A frequency histogram representing  the  percent of total
               annual  phosphorus load attributable to  municipal  wastes
               for a number of eastern U.S.  lakes  and  reservoirs.
                                    190

-------
If 80% of the phosphorus were removed from these discharges  bv treatment,
only 9 of the lakes would still receive more than 20% of their total  phos-
phorus load from municipal wastes as shown in Figure 3.
    200

     175
  IS  150
125

100

75

50

25
  2
          0-10   11-20  21-30  31-40  41-50  51-60 61-70  71-80  81-90 91-100
     PERCENT OF TOTAL  PHOSPHORUS LOAD  FROM  MUNICIPAL  POINT SOURCES
                           FOLLOWING  80%  REMOVAL


     Figure 3.  A frequency histogram representing the percent of
                total annual phosphorus load attributable to  municipal
                wastes after 80% effluent phosphorus reduction for a
                number of eastern U.S. lakes and reservoirs.
     The reduction or removal  of phosphorus  originating  from  municipal sources
does not guarantee that the trophic status  of the receiving lake will be sig-
nificantly improved.   That determination can only be  made  on  a  case-by-case
basis in which many factors, such as background phosphorus levels, the limit-
ing nutrient, lake morphometry, etc., are considered.   It  is  apparent, however,
that in many cases, eutrophic conditions are either the  direct  result of phos-
phorus from municipal wastes or at least are worsened by phosphorus  inputs from
these sources which could be readily controlled.
                                   19]

-------
TROPHIC CONDITION OF SURVEY LAKES

     About 80% of the lakes and reservoirs included in the first two years
of the Survey in the eastern United States were eutrophic.  This was not
unexpected since a large number of these water bodies were impacted by
municipal wastes.

     The classical terms, oligotrophic, mesotrophic, and eutrophic were used
to describe the trophic condition of each water body.  Based partly on ob-
servations during the first year of the Survey and partly on literature val-
ues, some general guidelines were developed for each of four key parameters
to assist us in assigning a trophic classification to each lake.  These
values are listed in Table 3.

          TABLE 3.  KEY PARAMETER VALUES ASSOCIATED HITH
                       THREE LAKE TROPHIC CONDITIONS
    Parameter
Oligotrophic   Mesotrophic   Eutrophic
Total Phosphorus (yg/1)
Chlorophyll a (yg/1)
Secchi depth (meters)
Hypolimnetic Dissolved Oxygen
(% saturation)
<10
<4
>3.7

>80
10-20
4-10
2.0-3.7

10-80
>20-25
>10
<2.0

<10
     If each of the four parameters from a given lake were within the range
of a specific trophic condition (e.g., oligotrophic)  then it was fairly cer-
tain that the indicated trophic condition appropriately described the lake.
Unfortunately, in many cases, all  the parameter values did not neatly fall
within one trophic classification; therefore, a relative index or ranking
system was also used.  This index included the four parameters shown in Table
3 (except that minimum dissolved oxygen concentrations were used) plus inor-
ganic nitrogen and dissolved orthophosphorus concentrations.  The index was
based on percentile rankings for each of the six parameters which were then
added together to produce a single index number.  Using this system, a large
number of lakes could be ranked in general order from most oligotrophic to
most eutrophic.  There were enough well-studied lakes included in the Survey
to allow us to determine approximately where the transition from oligotrophic
to mesotrophic and from mesotrophic to eutrophic occurred in the ordered list
of lakes.  This system was not without exception but did prove useful.  The
index is discussed in detail in National Eutrophication Survey Working Paper
No.  24 (1974).

PHOSPHORUS LOADING - TROPHIC CONDITION RELATIONSHIPS

     Another of the Survey objectives was to estimate annual phosphorus and
nitrogen loadings for each of the study lakes and to  examine relationships
between these nutrient inputs and the resulting trophic conditions.   Such
relationships are needed by lake managers to predict  trophic responses which
would result from either increasing or decreasing phosphorus loads.   They
                                   192

-------
would also give regulatory agencies a firmer basis for allocating total
phosphorus loads from point or non-point sources so that the desired tro-
phic condition of a lake or reservoir could be maintained or achieved.

     The Survey has not developed any original nutrient loading-lake res-
ponse relationships.  However, the data have been applied to models  recently
developed by other investigators.

     Prior to 1968 there were no models of general applicability which  re-
lated total phosphorus load to trophic condition in the receiving lake.   Now,
however, there are at least three which seem very promising.  These  models
are presented and compared using data collected by the Survey from twenty-
three lakes and reservoirs.  These twenty-three water bodies represent  a
cross-section of trophic conditions, mean depths, and mean hydraulic reten-
tion times.  All are located in northeastern and north-central  states except
for two reservoirs in Georgia and two in South Carolina.  In this group  of
lakes, six are oligotrophic, nine are mesotrophic, and eight are eutrophic.

     The three relationships (or models) which will be compared were devel-
oped by Vollenweider and Dillon (1974), Dillon (1975), and Larsen and Mercier
(1975), respectively.

     Vollenweider (1968), using existing data from a number of European  and
North American lakes, was the first to relate total phosphorus  loading  to
lake trophic condition.   He plotted annual total phosphorus loadings (g/mVyr)
against lake mean depths and empirically determined the transition between
oligotrophic, mesotrophic, and eutrophic loadings.

     Although this approach worked reasonably well for lakes with detention
times of several months  or longer, it did not account for the fact that  two
lakes with identical mean depths could have quite different hydraulic reten-
tion times and therefore different trophic responses to the same loading rate.
Subsequently, Vollenweider modified his initial relationship and based  his
revised model on considerations of a mass balance equation for  phosphorus.
The application of Vollenweider's revised model to the Survey lakes  is  illus-
trated in Figure 4.

     The observed loadings and trophic conditions of the 23 Survey lakes did
not fit the Vollenweider relationship very well.  Phosphorus loadings for
five of the eutrophic lakes plotted clearly within the eutrophic zone of the
Vollenweider relationship while loadings of two eutrophic lakes plotted  with-
in the mesotrophic zone  and one within the oligotrophic zone.  Loadings  for
five of the mesotrophic  lakes fell within the oligotrophic zone while the
remainder were within the mesotrophic portion of the Vollenweider relationship,

     Vollenweider's work was extremely important not only because he was
the first to investigate the loading-response relationship but  also  because
his original ideas interested others in this type of approach.
                                    193

-------



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CL
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n ni
1 1 1 1 1 INI 1 1 M II III I 1 1 1 1 Mil 1 1 1 II
D
4515
— —
— —

~ ..DANGEROUS ~
"EUTROPHIC" /
- 4512 S -
D // ^PERMISSIBLE
/
D 27A8 .S' /
// /
// /
- /X^A1316 S -
~ ^^ xA^seoe ~
	 ^ / s ' —
- 3639 ^^^701 x^- O 2314
_ 2750 __^-^ ^ D /AI3I8 -
- L(o)=0-30 	 0. — -"-^^^- ' ^^/
i - n ?n 	 • — — " — ' D 2618 -^" ^*" ^
, ,° m= 	 """^ ^-A27B4 "OLIGOTROPHIC"
L(°)'°-15 ^--A A 2306
	 	 —3303 O A 2313
- L(0) = O.IO - 27B2A A36I7 =

- 2694 O D 5539 ^\\
^1 A 2696 O Oligotrophic Lakes
O 2695 ^ Mesotrophic Lakes

_ D Eutrophic Lakes
i i i i i i I n I i i i i i 1 1 1 i i i i i i i n I i i i I
  O.I               1.0               10.0             100.0
       MEAN DEPTH (m)  / MEAN HYDRAULIC RETENTION TIME (yrs.)
Figure  4.  The Vollenweider relationship applied to a  number of eastern U.S.
          lakes and reservoirs sampled by the Survey.

-------
     Stimulated by Vollenweider's  earlier work,  Dillon  (1975) used the
mass balance modeling approach to  derive  the  relationship illustrated in
Figure 5.  Dillon's approach relates  lake mean  depth to a factor which
includes total annual phosphorus loading, the phosphorus retention coef-
ficient, and hydraulic flushing time.   The 23 Survey lakes fit the Dillon
relationship quite well as illustrated in Figure 5.  Two oligotrophic lakes
plotted in the mesotrophic zone and two mesotrophic lakes plotted in the
oligotrophic zone; however, observed  conditions  for the other lakes were
as predicted by the Dillon relationship.
            "EUTROPHIC"
                        D 27A8
                          D 2750
 E
 \
 o>
tr
 i
                                     D 2618

                                     D3639
    O.I -
                                       D27CI

                                045I2/    A 2313^     °23"
                                            02695

                                A'27B4  /  °23°9
                                 ^2762 /  03303
                                       A 2306
                                        AI3I8
                                                  "OLIGOTROPHIC"
   0.01
                                         O  Oligotrophic   Lakes
                                         A  Mesotrophic   Lakes
                                         D  Eutrophic  Lakes
                                               J_
                                      10.0

                         MEAN  DEPTH   ( METERS)
                                                                     100.0
    Figure 5.    The  Dillon  relationship applied to a number of eastern U.S.
                lakes  and reservoirs  sampled by the Survey.
                                    195

-------
     Larsen and Mercier (1975), working independently of Dillon, also
solved a mass balance equation for phosphorus to develop a relationship
between the average incoming phosphorus concentration and the phosphorus
retention coefficient.   The average incoming phosphorus concentration is
defined as the total  annual phosphorus load divided by the total hydraulic
inflow which is also  equivalent to:
where, L = annual  total  phosphorus
       P = hydraulic flushing time
       2 = mean depth (meters)
                                   areal  load (g/m /yr)
                                   (exchange/year)
     The Larsen and Mercier relationship  therefore  incorporates the same
variables as the Dillon  relationship  although  the  graphical  solution of
the mass balance model  for phosphorus  is  different.   Figure  6 depicts the
23 Survey lakes plotted  against the Larson-Mercier  relationship.   The fit
is very good and the relative  location  of each point on  the  graph is very
similar to Figure 5, the Dillon relationship.
  o
  oc
  UJ
  o
  o   IOO.O

  CO
  z>
  oc
  o
  X ~
  ft-
  O o»
       10.0
  o
  o
        1.0
                                                        D 2750
                          "EUTROPHIC"
                D 27A8
              "MESOTROPHIC"
                      O 2314
                                   D 4515
                                D 27CI^ A 2696
                          "AO-7Q/1       2313
                          A27B4 A |3i6
                                             1318
                                   2309
                                            A
                                        2306^02311   "OLIGOTROPHIC"
                                        O  Oligotrophic  Lakes

                                        A  Mesotrophic  Lakes

                                        D  Eutrophic  Lakes
                      J_
                            _L
_L
_L
_L
_L
_L
          0.0    O.I    0.2    0.3   0.4   0.5   0.6   0.7   0.8   0.9    1.0
                 PHOSPHORUS  RETENTION COEFFICIENT  ( RFyp)
                                                              EXPJ
    Figure  6.
               The  Larsen-Mercier  relationship  applied  to  a  number  of
               eastern  U.S.  lakes  and  reservoirs  sampled by  the  Survey.
                                   196

-------
     Since both the latter two models predict in-lake concentrations of
total phosphorus, the vertical distance from an observed point,  repre-
senting a lake, to one of the transitional lines is at least a semi-
quantitative measure of the degree of oligotrophy or eutrophy.

     The vertical distance from a given point to a transitional  line in
the Vollenweider relationship has less meaning in terms of the degree
of oligotrophy or eutrophy because the model does not directly relate
total phosphorus loading to in-lake phosphorus concentrations.

     In summary, the models developed by Dillon and Larsen-Mercier,  which
relate total phosphorus loads to lake phosphorus concentrations, should
prove to be useful lake management tools.  The Vollenweider model, at this
time, is probably less precise because it considers only total phosphorus
loading without regard to in-lake processes which reduce the effective
phosphorus concentration;  however, the model can be used to determine
approximate acceptable total phosphorus loads.

THE RELATIONSHIPS OF LAND USE TO NUTRIENT LEVELS

     Another of the Survey objectives is to examine, on a National scale,
the relationships of land use and other draining area characteristics to
stream nutrient levels and subsequently lake trophic status.

     Of the 4,200 sub-drainage areas sampled by the Survey across the United
States, about 1,000 were selected for a detailed study of land use and other
drainage area characteristics (see Figure 7).  Criteria for selecting the
1,000 stream sampling sites and associated drainage areas were:

     1.  Absence of identifiable point sources.

     2.  Availability of usable aerial photography (scale 1:40,000 to
         1:80,000) or exising land-use data.

     3.  Availability of accurate topographic maps for drainage  area
         delineation.

     4.  Sufficient land relief for clear delineation of drainage area
         1 i mi ts.

     5.  The need to encompass a variety of geographic and climatic  areas.

     Note that few, if any, of the selected drainage areas were  in Florida,
the Atlantic and Gulf coastal plains, or northern Minnesota.   These areas
were excluded from consideration because of the difficulty of accurately
defining drainage area boundaries due to low topographic relief, and, in
many cases, because of the strong influence of ground water.

     At the present time only the data from the eastern United States (east
of the Mississippi River) have been compiled, but the analysis of these data
is not complete.  Therefore only general results are presented.

                                   197

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00
                                                                                                                      DISTRIBUTION OF
                                                                                                                      N. E. S. LAND USE
                                                                                                                    STUDY DRAINAGE AREAS

                                                                                                                     Each ol the 1002 dels
                                                                                                                    reprrM'nl a Inbuiciry sampling
                                                                                                                    sile and ili associated
                                                                                                                    drainage area
                                                                                                                     72 73 and 74 refer lo
                                                                                                                    ihe yeari Inbulrjry sampling
                                                                                                                    began in each group of
                          Figure  7.   The  distribution of stream drainage  areas selected  by the
                                        National  Eutrophication Survey for land  use  studies.

-------
     Figure 8 summarizes the data collected from 473 eastern U.S. drainage
areas for total phosphorus and total nitrogen concentrations originating
from different land use categories.  The categories are defined as follows:

     1.  Forest; other types negligible

         a.  >75% forested (including forested wetland)
         b.  < 7% agriculture
         c.  < 2% urban

     2.  Mostly forest; other types present

         a.  >50% forest
         b.  not included in the forest category

     3.  Mostly agriculture; other types present

         a.  >50% agriculture
         b.  not included in the agriculture category

     4.  Agriculture; other types negligible

         a.  >75% agriculture
         b   < 7% urban

     5.  Urban

         >39% urban

     6.  Mixed; not included in any of the other categories

     Streams draining predominately agricultural areas have total  phosphorus
concentrations averaging about 10 times higher than those draining forested
areas (Figure 8).  The difference between total  nitrogen concentrations was
not as marked.  Streams in agricultural areas averaged nearly 5 times higher
total nitrogen concentrations than those draining forested areas.   It is in-
teresting to note that, based on the mean concentration values, phosphorus
would be expected to be limiting in surface waters draining either forested
or agricultural areas.  The total nitrogen to total phosphorus  ratio changes
 from 60 to 1 for forested areas to 31  to 1 for agricultural areas.   Gen-
erally phosphorus is the limiting nutrient when the N:P ratio exceeds 14:1.

     The nutrient loads per unit area of drainage for total phosphorus and
total nitrogen are shown in Figure 9.  The differences in exports  for the
different land use categories are not as pronounced as the nutrient  concen-
trations were.   Total  phosphorus export from agricultural lands was  only
317 times greater than from forested lands and total nitrogen export only
2.2 times greater.   The differences in  magnitude between stream loads and
stream concentrations are due to the differences in stream flows resulting
from the two types of land use.   The data suggest that stream flow per unit
of drainage area is somewhat higher for forested than for agricultural areas
This seems logical  since forested areas frequently are those which are un-
suitable for agricultural  purposes because of steeper slopes and relatively
thin soils.

-------
NUMBER
OF SUBS


 53  FOREST
      eihur ryp0si



 170  MOSTLY FOREST
      oihtr tfpfi pntfl



 52  MIXED




 11  MOSTLY URBAN
 96  MOSTLY AGRIC.
      orttfr ryp« freifnt



 91  AGRICULTURE
      olh»r rypn rmfligibt*
                                       MEAN  TOTAL  PHOSPHORUS  CONCENTRATIONS

                                                             vs

                                                       LAND  USE

                                                  DATA ON 473 SUBDRAINAGE AREAS  IN
                                                     EASTERN UNITED STATES
                                  0.014
                                               0.035




                                                  0.040


                                                                  0.066
                                                                                                     °-135
                                                     0.05
                                                          MILLIGRAMS PER LITER
                                                                                   0.10
                                                                                                                 0.15
ro
o
o
NUMBER
OF SUBS


  53  FOREST
      olhei lypei negligible



 170  MOSTLY FOREST




  52  MIXED
        11   MOSTLY URBAN
             other types present



        96   MOSTLY AGRIC.
              '
        91  AGRICULTURE
                                       MEAN  TOTAL  NITROGEN  CONCENTRATIONS
                                                             vs

                                                       LAND  USE
                                           DATA ON 473 SUBDRAINAGE AREAS IN

                                               EASTERN UNITED STATES
                                              1.O
                                                                     2.0

                                                          MIILIGRAMS PER LITER
                                                                                                                        4.170
                                                                                           3.0
                                                                                                                  4.0
                         Figure 8.   The  relationship  between total  phosphorus and  total  nitrogen

                                        concentrations in streams  and  land use  in the  eastern  U.S.

-------
NUMBER
OF SUBS


 53   FOREST
      OTAvr OPMfi



 170   MOSTLY FOREST




 52   MIXED




 11   MOSTLY URBAN
      M/Mr npn pruww



 96   MOSTLY AGRIC.
      Otter trt*3 pnsmm



 91   AGRICULTURE
                                                        TOTAL PHOSPHORUS   EXPORT

                                                                     vs

                                                               LAND  USE

                                                          DATA ON 473 SUBDRAINAGE AREAS IN
                                                              EASTERN UNITED STATES
                                            8.3
                                                                                                30.8
                                              10                      20

                                               KILOGRAMS PER SQUARE KILOMETER PER YEAR
                                                                                             30
                                                                                                               40
ro
o
     NUMBER
     OF SUBS


      53   FOREST
     170   MOSTLY FOREST
           otbmt type* prm**nt



      52   MIXED
      11   MOSTLY URBAN
           0f/w tyr** pmmr



      96   MOSTLY AGRIC.
           or/Mi- W»» prnmt



      91   AGRICULTURE
           «A«Y n^P«i rmgltgibl*
                                                     TOTAL  NITROGEN  EXPORT

                                                                 vs

                                                           LAND  USE

                                                      DATA ON 473 SUBDRAINAGE AREAS IN
                                                         EASTERN UNITED STATES
                                                                                                  788.6

                                                                              630.5
                                                                                                             J 982-3
                                                                     500

                                                     KILOGRAMS  PER SQUARE  KILOMETER PER  YEAR
                                                                                                               1000
                        Figure  9.  The  relationship between  total  phosphorus  and  total nitrogen  export

                                      in streams  and  land use in the eastern  U.S.

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     The pattern for orthophosphorus concentrations was very similar to
that for total phosphorus as shown in Figure 10.   Except with predomin-
ately urban drainage areas, of which there were only eleven, mean ortho-
phosphorus concentrations represented 40 to 43% of the total phosphorus
concentrations regardless of overall land use.   Orthophosphorus concen-
trations in streams draining agricultural areas were nearly 10 times the
concentrations in streams draining forested areas.

     Inorganic nitrogen exhibited quite a different pattern from total
nitrogen in that substantially higher (13.7X)  concentrations were observed
in streams draining agricultural  lands than in  forested lands (Figure 10).

     In streams draining forested areas, inorganic nitrogen constituted
about 27% of the total nitrogen,  however, this  increased to 76% in streams
draining predominately agricultural  areas.  Although the sample size (11
drainage areas) was relatively small, inorganic nitrogen made up about 98%
of the total nitrogen in streams  draining mostly urban drainage areas.   In-
organic nitrogen export was also  significantly  higher (5.6X) from agricul-
tural areas than from forested areas as shown  in  Figure 11.  The difference
probably reflects the use of inorganic nitrogen fertilizers and the high
water solubility of inorganic nitrogen  compounds.

     What conclusions can be drawn from these  general results?  First,
these data suggest that streams draining agricultural watersheds have
higher nutrient levels and therefore would be  expected to be more produc-
tive than those draining forested watersheds.   The increase in nutrient
levels is generally proportional  to  the increasing percent of the land in
agriculture.

     Second, the data indicate that  the inorganic portion (orthophosphorus)
of the total phosphorus component stays roughly at the 40% level regardless
of land use type, whereas, the inorganic portion  of the total nitrogen com-
ponent increases markedly from 27% for forested areas to 75% for agricul-
tural areas.  Inorganic nitrogen  in  streams draining mostly urban areas
represented a substantially larger fraction of the total nitrogen (98%),
however, the number of test areas was relatively small (11).

     Lastly, what uses can be made of the data  derived from this segment of
the survey?  Other than elucidating  the land use-nutrient level-eutrophi-
cation relationships, probably the two most important uses will be:  (1) to
provide a basis for a quick and relatively accurate method of determining
nitrogen and phosphorus concentrations and loadings based on land use and
other non-point source types of geographical characteristics, and (2)  to
provide a large nationwide collection of watershed data for testing other
methods of estimating nitrogen and phosphorus  levels in streams from non-
point sources.

                               SUMMARY

     The National  Eutrophication  Survey, which  was initiated in 1972 by the
U.S.  Environmental  Protection Agency, is in the first stage of collecting
data from over 800  lakes and reservoirs in the  contiguous United States.
In the eastern U.S., a large percentage of the  surveyed water bodies are
impacted by municipal  sewage treatment plant effluent and are in various

                                    202

-------
                NUMBER

                OF SUBS
                 53  FOREST
                 170  MOSTLY FOREST
                      Other types present



                 52  MIXED
                 11  MOSTLY URBAN
                       other tvoe* present



                 96  MOSTLY A6RIC.
                       other ffpes. pie tent



                 91  AGRICULTURE
                       Other types negligible
                                                 MEAN  ORTHOPHOSPHORUS  CONCENTRATIONS
                                                                       vs

                                                                  LAND  USE
                                                o.oi
                                                            DATA ON 473 SUBDRAINAGE AREAS IN

                                                                EASTERN UNITED STATES
                                0.033
                       0.027

                                                                      O.OS8
                                                               0.02
                                                                              0.03            0.04
                                                                              MILLIGRAMS PER LITER
                                                                                                            0.05
                                                                                                                            0.06
no
o
oo
                NUMBER

                OF SUBS
                  53   FOREST
                 170   MOSTLY FOREST
                       other types present



                  52   MIXED
                  11   MOSTLY URBAN
                  96   MOSTLY AGRIC.
                       othei fype* present



                  91   AGRICULTURE
                       other iype$ negligible
MEAN INORGANIC NITROGEN CONCENTRATIONS
                   vs

              LAND USE

       DATA ON 473 SUBDRAINAGE AREAS IN
           EASTERN UNITED STATES
                                                     J 0.67»
                                                                      dfaZl	J 3-190
                                                0.50
                                                               1.00
                                                                               1.50            2.00

                                                                              MILLIGRAMS PER  LITER
                                                                                                            2.50
                                                                                                                           3.00
                        Figure 10.   The relationship between orthophosphorus and  inorganic  nitrogen

                                        concentrations  in  streams and  land use  in  the  eastern U.S.

-------
NUMBER
OF SUBS


 53  FOREST
      other types negligible


170  MOSTLY FOREST




 52  MIXED




 11  MOSTLY  URBAN




 96  MOSTLY  AGRIC.




 91  AGRICULTURE
      other rrpes  negligible
                                                    ORTHOPHOSPHORUS  EXPORT
                                                                  vs

                                                             LAND  USE

                                                       DATA ON 473 SUBDRAINAGE AREAS IN
                                                           EASTERN UNITED STATES
                             T ™".
                                                              S                                 10

                                                                KILOGRAMS PER SQUARE KILOMETER PER YEAR
                                                                                                                                  15
ro
o
           NUMBER
           OF SUBS


            53  FOREST
                 other types negligible



           170  MOSTLY  FOREST




            52  MIXED
            11   MOSTLY URBAN
                  other types present



            96   MOSTLY AGRIC.
                  other types present



            91   AGRICULTURE
                  other types legligible
                                           INORGANIC NITROGEN EXPORT

                                                       vs

                                                   LAND USE

                                            DATA ON 473 SUBDRAINAGE AREAS IN

                                               EASTERN UNITED STATES
                                                  200
                                                                         400                    600

                                                               KILOGRAMS PER SQUARE KILOMETER PER YEAR
                                                                                                           800
                       Figure  11.   The  relationship  between orthorphosphorus  and inorganic  nitrogen

                                      export  in  streams and  land  use in the  eastern U.S.

-------
states of enrichment.  Phosphorus loads to a significant number of these
impacted lakes and reservoirs could be substantially reduced by controlling
phosphorus inputs from municipal sources.

     Primary production in 67% of the water bodies  surveyed east of the  Rocky
Mountains was phosphorus-limited and 30% were nitrogen-limited  according  to
algal assay results.  It is believed that the apparent nitrogen-limited  con-
dition was frequently the result of excessive phosphorus inputs from munici-
pal sources.

     Land use in the watershed was shown to be a significant factor in de-
termining levels of phosphorus and nitrogen in streams in selected areas
studied in the eastern United States.  Average total phosphorus concentra-
tions were about 10 times greater in streams draining agricultural  areas
than in streams draining forested areas; total nitrogen concentrations were
about 5 times greater.  The percentage of total nitrogen in the inorganic
form was substantially higher in streams draining agricultural  lands than in
those streams draining forested lands.

     Phosphorus loading data for 23 selected survey lakes were  applied to
three general models relating annual total phosphorus loading rates to lake
trophic conditions.  The "fit" of observed conditions to predictions made by
each model was compared and discussed.


                                REFERENCES

Dillon,  P.  J.  1975.  The phosphorus budget of Cameron Lake, Ontario:
     the  importance  of flushing  rate to the degree of eutrophy of lakes.
     Limnol. Oceanogr.  20:28-39.

Larsen,  D.  P. and H. T. Mercier.  1975.  Lake phosphorus loading graphs:
     an alternative.  National Eutrophication Survey Working Paper No.
     174.

U.S.  Environmental  Protection Agency.  1974.  Survey methods for lakes
     sampled in 1972.  National  Eutrophication Survey Working Paper No.  1.
     40 pp.

U.S.  Environmental  Protection Agency.  1975.  Survey methods, 1973-1976.
     National Eutrophication Survey Working Paper No. 175.  91 pp.

U.S.  Environmental  Protection Agency.  1974.  An approach to a relative
     trophic index system for classifying lakes and reservoirs.   National
     Eutrophication Survey Working Paper No. 24.  44 pp.

Vollenweider, R. A.  1968.  The scientific basis of lake and stream
     eutrophication with particular reference to phosphorus and nitrogen
     as factors in eutrophication.  OECD, DAS/CSI/68-27.  159 pp.

Vollenweider, R. A. and P. J. Dillon.  1974.  The application of the
     phosphorus loading concept  to eutrophication research.  National
     Research Council of Canada No. 13690.  42 pp.

                                    205

-------
         PAPERS PRESENTED BUT NOT AVAILABLE FOR PUBLICATION
A Method of Predicting Bioaccumulation Potential of Chemicals
     Oilman Veith. Environmental  Research Laboratory,
     U.S. Environmental  Protection Agency, Duluth, MN
Adverse Effects of Chlorine Disinfection on Aquatic Organisms
     William A. Brungs.   Environmental  Research Laboratory,
     U.S.  Environmental  Protection Agency,  Duluth, MN
                                 Z06

-------
                                  TECHNICAL REPORT DATA
                           (Please read Instructions on the reverse before completing)
 REPORT NO.
   EPA-600/3-76-079
                                                          3. RECIPIENT'S ACCESSION-NO.
.TITLE AND SUBTITLE  WA I h R QUALITY CRITERIA  RESEARCH OF THE
.S. ENVIRONMENTAL  PROTECTION AGENCY   Proceedings of an
PA-sponsored  Symposium on Marine,  Estuarine and Fresh-
                                                          5. REPORT DATE
                                                                July 1976
                                                           6. PERFORMING ORGANIZATION CODE
                 ?g^ented at  the 26th annua1 meeting  of
 . AUTHOR(S)
                                                           8. PERFORMING ORGANIZATION REPORT NO.
nvironmental  Protection Agency
 . PERFORMING ORGANIZATION NAME AND ADDRESS
 Corvallis  Environmental Research  Laboratory
 U.S.  Environmental Protection  Agency
 200  S.  W.  35th Street
 Con/all is,  OR  97330
                                                          10. PROGRAM ELEMENT NO.

                                                               1BA608
                                                          1 1. CONTRACT/GRANT NO.
 2. SPONSORING AGENCY NAME AND ADDRESS
 Corvallis  Environmental  Research  Laboratory
 Dffice  of  Research and Development
 U.S.  Environmental Protection  Agency
 Con/all is, OR  97330
                                                           13. TYPE OF REPORT AND PERIOD COVERED
                                                           14. SPONSORING AGENCY CODE


                                                                EPA-ORD
15. SUPPLEMENTARY NOTES
16. ABSTRACT

      These proceedings include  a  cross-sectional representation of the broad base
ecological  effects research programs  conducted by research  laboratories of the EPA
Office  of Health and Ecological Effects.   The presentations  focus on microbial and
abiotic degredation processes,  the  problem of trace metals,  the effects of toxic or-
ganics, and the feasibility of  new  stress-measuring methodologies in the marine environ
ment.   The freshwater segment of  the  symposium addresses  the transport and biological
modeling capabilities of the  laboratories, cold climate aquatic biology, lake trophic
states  in the eastern United States,  and  the impact of toxic substances on freshwater
systems.
 7.
                                KEY WORDS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
                              Bioassimilatior
                                              b.IDENTIFIERS/OPEN ENDED TERMS
                                                                           COSATl Field/Group
:reshwater
Marine
Estuarine
 hosphorus
Nitrogen
 race Metals
Cold Climate
Stream Flow
Toxicity
Bioassay
Communities
Microbiota
Chlorine
Ecosystem Mode
Malathion
Lake Restorati
Advanced Waste
  Treatment
Great Lakes
                                                  Water Quality Criteria
06/F
08/A,H,J
              Ecosystem Models  Phytoplankton
18. DISTRIBUTION STATEMENT


    Release to  Public
                                              19. SECURITY CLASS (This Report)
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                                                                         21. NO. OF PAGES
                                              20. SECURITY CLASS (This page)
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EPA Form 2220-1 (9-73)
                                             207
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