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ACI!JITY, NLfl I FfS ND I D ALS IN T1T PHERIC PPECIPIT. TIflfl
(i’/ER FLORIDI\: DEPUSITI1) PATTE}RNSJ ‘EC W I 1i S,
PI11J ECOL(X I CAL EFFECTS.
BY
PATRICK L . BREZONIKI U-tARLES 11 HENDRY, JR., ERIC . FDGERTc I, AJ’UJY L.
SCHULZE, AND 1HCP AS L . CRIs AN
DEPARTMENT OF Fj\IvI RONMENTAL ENGINEERING Sc I ENCES
UNIvERsrr ’ OF FLORIDA
GAINESVILLE, FLORIDA 32F11
U , S. Eiw I RONtiENTAL PROTECTION [ GENCY
1 F iCE OF RESEARCH AND flEVELOPMENT
CORVALLIS ENV I RONtIENTAL RES EJ’RCH LABORATORY
CCRVALUS I OREGON 0733 ’)
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ThBLE cF C1 ft FtS
!\BSTRACT
PICKNCkIL GEME N TS
SECTI( !S
1. SIJV YiARY OF CONCLUS I DN i_ I
2. PECcIIENDATIDNS 2- 1
3. INTRODUCTION 3- 1
L 1 NUTRIENT AND MINERAL DEPosITIoN BY RAINFALL 4— 1
HISTORICAL NUTRIENT flATA LI- 1
SAMPLING PROC URES AND 1 NALYTICAL METHODS Li — 2
RESULTS AND DISCUSSION
NUTRIENTS 9
MAJOR MINERALs
MINOR MINERALS
5. THE ACIDITY OF RAINFALL IN FLORIDA 5- 1
EXPER I MENTAL METHODS 5- 1
SPATIAL TRENDS IN PCIDITY AND PELAT RARANETERS 5- 3
NET, BULK, AND DRY DEPOSITION OF PCIDIC AND BASIC SPECIES 5—31
TEMPORAL PATTERNS IN PRECIPITATION ACIDITY 5-9
SOURCES OF I\Tfr SPHERJC SULFUR IN FLORIDA
Acm PAINFALL IN FLORIDA: A PERSPECTIVE 5-52
6. EFFECTS OF PCIDIFICATION ON SOFTWATER LAKES IN FLORIDA
PREvIous STUDIES ON EFFECTS OF PCID PRECIPITATION ON
P UATIC ECOSYSTEMS - 1
DESCRIPTION OF THE SruDY REGIONS AND LAKES C-19
SAMPLING AND AMAL’(TICAL METHODS 5- 19
RESULTS OF LAKE STUDY: ‘ 1 ATER CHEMISTRY 5-72.
RESULTS OF LAKE SURVEY: BIOLOGICAL (( UNITIES
ProP 1
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PNE
7 PEFER 1CES 7— 1
t FPE!\O ICES A—i
P ix I PNALYTICAL f’ ETHODS A—i
!\PPENDIX I I VOLU E_1LA1EIGHT MEAN CONCENTRATIONS AND
ANNUAL DEPOSITION RATES FOR EACH SITE DURING THE
PROJECT PERIOD
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ACKNOWLEDGEMENTS
We wish to thank the large number of graduate students and assistants
who participated in the project and shared the analytical load with the
project staff. Special thanks go to the following persons: Forrest E.
Dierbérg (fluoride analyses; throughf all study), William Fish (nutrient ar
trace metal analyses), Michael Hanson (aluminum analyses; lake sampling),
and Alan Hubbard and Cinthia Ward (nutrient analyses; data reduction).. Ht h
Prentice, Jack Tusc.hall, and Charles Fellows were in charge of the water
chemistry laboratory during various phases of the project and assisted in
sample analysis.
Dr. Steven Bloom of the Department of Botany provided much asaistanc
for the statistical analysis of biological data.
This project would not have been possible without the excellent coopera—
tion and assistance of the persons who maintained our precipitation collec ors
and sent us rainfall samples from all over the state of Florida. We grate—
fully acknowledge the persons listed below.
Site Person __________
Bahia Honda Mr. Bill Green
Bradenton Mr. Russell W. Owens
Belle Glade Mr. O’Neal Akers
Chipley Dr. R. B. Christmas
Clewiston Mr. J.M. Hyder and
Mr. C. Brobston
Corkscrew Swamp Dr. Michael Duever
Fort Myers Mr. Charles D. Hendry, Sr.
Hastings Mr. Louis Wallis
Jacksonville Mr. Jack Schabel
Jasper Mr. W.1I. Davis, Jr.
Jay Mr. D.T. Blackman
Lake Alfred Dr. Robert Koo
Lake Apopka Dr. C.A. Conover
Lake Placid Mr. David B. Johnston
Lisbon Mr. Greg Frazier
Marineland Mr. Robert L. Jenkins
Affiliatior
Ranger, Bahia Honda Stat rk
AREC- IFASk
ARE C- IFAS
Poultry Evaluation Cente r - IF.
Army Corps of Engineers
Corkscrew Sw p Sanc.tuarT’
AREC—IFAS
National Weather Service
City of Jasper Utility D npartm
AREC- IFAS
AREC- IFAS
AREC—IFAS
Archbold Biol. Station
Burrell Lock
Mar Inc land
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Site Person Affiliation
Miami Dr. Jackson L. Fox
Stuart Mr. Robert Burson
Tallahassee Drs. L.C. Boueres and
M.O. Andreae Florida State University
Winter Garden Mr. Frank Dudley Winter Garden Marina
*AREC.IFAS = AgriculturaL Research and Education Center of the Institute
for Food and Agricultural Science, University of Florida
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ABSTRACT
Nitrogen deposition via atmospheric precipitation averaged 0.75 g/a 2 —yr
(range =0.32—I.I3) at 24 sampling:sites over the state of Florida during
the one year period ay 1,. 1978 to April 30, 1979. Comparable values for
total phosphorus are 17—111 and 50 tng P/m 2 -yr. Highest deposition rates
occurred in agricultural areas and lowest rates in coastal and forested areas.
Concentrations of N and P forms were higher in summer (convective) rains
than in winter (frontal) events. Wet—only input accounted for 68 and 81%
of the total (wet plus dry) deposition of NH—N and N0—N, but dry fallout
was more important for organic nitrogen (53% of total input) and especially
for phosphorus (80% of total input). Inorganic forms &H, NO 3 , soluble
reactive (ortho) phosphat accounted for most of the nitrogen and phosphorus
in rainfall. Statewide deposition rates of nitrogen and phosphorus are be-
low the loading rates associated with eutrophication and water quality de-
gradation. The average nitrogen loading from bulk precipitation approached
the “permissible” loading criterion of Vollenweider, and boch nitrogen and
phosphorus loadings exceeded permissible loading criteria at a few agricul-
tural sites. Whereas the atmosphere is an important source of nitrogen for
nutrient budget purposes, it is less so for phosphorus, especially if dry
fallout of locally—derived dust particles is not considered.
The acidity of rainfall in Florida has increased markedly in the past
25 years, and average concentrations of nitrate and sulfate have risen
correspondingly. Annual average pH values less than 4.7 now occur over the
northern two—thirds of the state, and all but the extreme southern areas of
I
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the state have acidic rainfall. Summer rainfall has average :pH values 0.2—
0.3 units lower than winter rainfall; excess sulfate coneentr.atjong are
higher at most sites during summer. Sulfuric acid accounts f or about 70% of
the observed acidity and nitric acid accounts for the remaind er. The spatial
variation in hydrogen ion content of Florida bulk prec1p1cati n was accounted
for by the following two va iab1e regression model:
[ HI 6.1 + 0.54 [ so I - 0.35 [ Ca 2 ], R 2 0.75
where subscript xs refers to nomnarine—derived materiaL. Ar nium and
nitrate ions are more evenly distributed (geographically), a I do not account
for the observed spatial trends in acidity. Local (within —st te) emissions
of SO 2 (and NO) seem to control the acidity oE florida rainf;all. The
annual deposition of H+ is about 250—500 equivalents per hect are over the
interior portions of northern Florida; this range is about one. —third to
one—half the deposition rate for H’ over the northeastern Uni .ted States.
The pH levels of softwater lakes in north—central Flor1d.a have declined
by up to 0.5 units over the past 20 years; no changes have be n observed in
softwater lakes of south—central Florida. Aluminum levels in rease with
decreasing pH, but maximum levels found (100—150 iig/L) probably are not high
enough to cause fish toxicity problems. A tread of decreasin chlorophyll a
with decreasing pH was observed in a survey of 20 soft ater 1.zikes; total
phosphate levels also decreased with decreasing pH, but this trend does not
entirely explain the pH—chlorophyll a trend. The major change in phytoplankton
populations with change in pH was a replacement. of blue—green algae by green
algae under acidic conditions. Species numbers and phytop1an .zton abundance
also declined with decreasing pH, but the data set exhibited 7nuch scatter.
Although trends were noted in zooplankton and beuthic inverte brate popula-
tions along a pH gradient, both species composition and total abundance
ii
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trends were relatively subtle. Results indicate that acidic conditloos
(as low as pH 4.6 4,7) do not have major impacts on community struc re in
Florida lakes.
111
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CHAPTER 1. SU .ARY A D CONCLUSIONS
The results of this project can be suimnarized into the foLlowing taajo
conclusions-. For detailsonthe findings and thefacts on which they are
based, thereader is referred to the main body of the report (Chapters4 tG
6).
ATMOSPUERIC LOADINGS OF NUTRIENTS AND MINERALS
1. Bulk precipitation is an important source of nitrogen for both
terrestrial and aquatic systems. Average annual loadings of total aitroge * for
24 sampling sites in Florida ranged from 0.3 to 1.1 g/m 2 —yr during the st idy
period, with a grand (statewide) mean of 0.75 g/m 2 —yr. About 70% of the
nitrogen was in inorganic forms (ammonium and nitrate) that are readily
available for plant growth. Deposition rates were highest in rural agricul-
tural areas (0.88 g/m 2 -yr) and lowest in coastal areas (0.58 gIm 2 -yr)
2. Concentrations of all nitrogen forms in bulk precipitation were
higher in sucuner convective showers than in winter frontal rains; statewide-
racio of summer/winter concentrations ranged from 1.4 (nitrate) to 1.9
(ammonium and organic N). These results reflect a combination of higher
biogenic emissions from soils during warmer weather, greater fixation of
NO 2 by lightning in summer, and more efficient washout by turbulent convec—
tive showers.
3. Wet deposition (rainfall) accounted for about 70% off the total in-
organic nitrogen in bulk precipitation but only about 50% of the organic N
deposition. The balance represents dry fallout of particulate nitrogen foi aS.
4. Few data are available for historical comparisons, but available
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data suggest that the mean concentration of inorganic nitrogen forms in wet—
only precIpitation has increased about three—fold in Florida over the past
20 years.
5. In comparison with critical nitrogen loading rates fot lake eutro-
phicat on, the annual deposition of total N at all 24 collection sites were
below the values associated with eutrophic conditions (assuming nitrogen
-
the limiting nutrient). The statewide average deposition rate was about
75% of the “permissible” loading rate for shallow lakes suggested by
Vollenweider (1968); deposition rates for several agricultural locations
slightly exceeded the permissible criterion but none approached the eutrophic
loading criterion.
6. Bulk precipitation has significant levels of total phosphate; the
statewide annual average was 38 i.ig/L, and the mean deposition rate was
50 mg P/m 2 —yr. On a concentration basis, summer rains had about 1.5 times
as much phosphate as winter rains. Land use had an important effect on
atmospheric deposition rates for total phosphorus. Rural (non—agricultural)
and coastal sites had the lowest rates ( 7 and 31 mg P!m 2 —yr, respectively),
and agricultural sites had the highest rates (66 mg/rn 2 —yr).
7. Whereas most of the total atmospheric deposition of inorganic ni-
trogen comes down in rainfall rather than dry fallout of particulate matter,
the opposite is true for phosphorus. At four sites with separate wet—fall!
dry—fall collectors, wet deposition accounted for an average of 63 percent
of the deposition of total nitrogen, but it accounted for only 20% of the
deposition of total phosphorus. Thus, most of the phosphorus in bulk precipi-
tation is dry fallout, presumably of wind—blown particles of dust and soil. Thes ’
particles probably are large, are not transported large distances and thus do not
1—2
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represent a source of new phosphorus for terrestrial ecosystems.
8. The statewide bulk deposition of total phosphorus is only one half
the permissible loading rate for the lakes that are most vulnerable to
eutrophication (shallow lakes with long hydraulic residence times). In most
areas of Florida, bulk-precipitation supplies only about 12—16%ofthe-làad—-
ing required to induce eutrophic conditions.
9. Sodium and chloride concentrations are highly correlated in Florida
rainfall and occur at Cl/Na ratios near that for seawater (1.8). Concentra-
tion isopleths for both ions follow the outline of the peninsula, with values.
increasing toward the coast. Seasalt is the major (and likely the only
significant) source of these ions in Florida rainfall.
10. Average sulfate concentrations in rainfall ranged from about 0.4
to 1.2 tng/L (as S), and about two thirds of the total deposition of sulfate
was by rainfall. Deposition rates ranged from 7 to 11 kg S/ha—yr, indicating
that the atmosphere serves as a significant source of sulfur to soils in
Florida.
ACIDITY OF PRECIPITATION
1. Rainfall throughout Florida is acidic, with average values for all
but a few stations in south Florida being less than geochemical neutrality
(pH ‘\ 5.7). Single rainfall events a.s low as pH 3.9 have been measured at
Gainesville, and the lowest pH of a bulk precipitation sample (collected
weekly or biweekly) was 3.73 (at Jay in the western panhandle during August
of 1978).
2. A definite geographic pattern exists for acid deposition in the
state; mean annual pH values (volume—weighted) for 1978—79 were around 4.6--
4.7 throughout the panhandle and northern two—thirds of the peninsula. Mean
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annual values south of Lake Okeechobee were around 5.0 or above.
3. Neutralization of bulk precipitation was found for coastal sites,
but wet—only precipitation collected near both the Gulf and At lantic coasts
was approximately as acidic as inland stations of comparable latitude.
Partialnéutrallzati6n 6fà fdi tj i coa tal iaih apparently restilts f orn
dry depositiot of alkalineparticles èontaining calciom carbo ate of local
(terrestrial) origin. Analysis of the ionic composition of cc astal bulk
precipitation indicates that sea spray is not the agent of neu tralization.
Sea—salt sulfate levels were only modestly elevated compared t o inland bulk
precipitation, and the calculated amount of sea—salt calciwn carbonate is
too low to account for the neutralization.
4. A seasonal pattern was found in precipitation acidity- throughout
the state, with summertime pH values averaging 0.2—O..3 units lower than
wintertime values. Possible reasons for the differences inclu4e (1) in-
creased summertime emissions of SO 2 and NO (caused in part by- seasonal de-
mands for air conditioning), (2) greater thunderstorm activity- in summer,
resulting in greater fixation of ? O by lightning, (3) enhance d scavonging
efficiency of summer convective showers compared to winter frc ntal storms,
and (4) differences in the frequency and size of individual ra in events be-
tween summer and winter. Further studies are needed to evalu2te the itnpor—
tance of some of these factors.
5. Granat—t.ype analysis indicates that about 70% of the rainfall
acidity in Florida is derived from sulfuric acid and 30% from nitric acid.
+
A multiple regression equation involving [ H ] as the dependent variable arid
[ so 1 and [ Ca 2 t as independent variables explained about 75% of the
variance in hydrogen ion concentration over the statewide netwcork. The sub—
1—4
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script xs refers to the fraction of the ions of non—marine origin. Thus
the pH of rainfall in Florida primarily reflects the degree to which sul-
furic acid has been titrated by terrestrial calciuui carbonate.
6. f?ulk precipitation throughout northern and central Florida de-
posited 250—500 equiv H±/ha vr during 1978—79. Thisrepresents about one
third to one half of the annual deposition of H 4 in the heavily impacted
northeastern United States. Comparable values for excess sulfate are 7—li
kg/ha—yr in Florida and l3 kg/ha-yr in the northeastern U.S. (10 year
average for Hubbard Brook, N.H.). Thus Florida ecosystems receive 50—90%
of the excess sulfate from the atmosphere as their northern counterparts.
7. Although historical data are lacking on the pH of Florida rainfall,
calculated values for rainfall pH during the mid—1950s indicate wet—only
precipitation was not acidic then. Moreover, present values of sulfate de-
position in northern Florida are up to four times higher than values for
the early l950s. Scattered information for the pH of rainfall at Gainesville
are available from 1973 to the present, and no long—term trends are apparent
i this record.
8. In spite of the north—south gradient of decreasing rainfall acidity,
long—range (Interstate) transport of acid precursors is not a wholly satis-
factory explanation for acid precipitation in Florida. A substantial por-
tion of the H SO and HNO must be derived from in—state emissions of SO
24 3 2
and NO, which are widespread and substantial. These conclusions are sup-
ported by several lines of evidence, including the fact that summer rain-
fall throughout the entire state is more acidic than winter rainfall. From
a meteorological viewpoint, peninsular Florida is isolated from the rest of
the United States during summer. Large—scale weather patterns for the
peninsula come from the southeast (Caribbean) or southwest (Gulf of Mexico)
1—5
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during summer, and cold fronts from the north rarely penetrate the state
during this period.
EFFECTS OF ACID PRECIPITATION FLORIDA LAKES
1. k large number. of soft—water lakes occur in the sand—hill highlat d .s
region of peninsular Florida. Based on comparison of historical and currer t
data on a group of 12 such lakes in northern Florida and a group of 8 soft—
water lakes in south central Florida, pH has decreased by up to about 0..5
units in many of the northern soft—water lakes, whereas no temporal trends
could be discerned for the southern group. The northern (Trail Ridge) Iak s
lie about 40—50 km east of Gainesville in a region receiving rainfall with
a (volume—weighted) average annual pH of 4.5—4.7. The southerrr (Highlands
Ridge) lakes lie northwest of Lake Okeechobee, near the current southern
terminus of pronounced rainfall acidity. Corresponding decreases in aTha—
unity and increases in sulfate concentration were observed in the northerrt
lakes.
2. The 20 survey lakes h2d annual average pH levels ranging from 4.72
to 6.80, but otherwise had generally similar characteristics (soft uater
oligotrophic to mesotrophic nutritional conditions). The group thus served
as a good data base to evaluate the effects of acid precipitation on vu.lrier—
able aquatic ecosystems in Florida.
3. general trend of increasing aluminum with decreasing pH was foune
in the 20 Florida lakes. However, maximum values (lOO -l5O ig/L) were belo
the levels associated with fish toxicity and may explain the occurrence of
largemouth bass and several other common game fish species in lakes with pI
values below 5.0.
4. A general trend of increasing chlorophyll a concentration with in—
1—6
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creasing pH was found. However, total phosphate concentration also tended
to rise with pH. The trend of greater oligotrophic conditions in more
acidic lakes may be caused by lower rates of nutrient cycling at lower pH,
or it may reflect watershed nutrient loading factors that just happened to
correlate with lake pH. Further studies are needed on this point.
5. The number of phytoplankton species and their abundance in a lake
decreased with increasing acidity, but much scatter occurred for both para-
meters. Although the data are fairly limited, a trend of increasing phyto—
plankton abundance with increasing pH was found for a series of lakes with
similar levels of phosphate. The lake survey also indicated that species
composition varied along a pH gradient, with green algae replacing blue—greens at
low pH. In lakes with pH values of 4.5—5.0, 60% of the algae were green
(Chlorcphyta), and 25% were blue—green (Cyanophyca). Corresponding values
for lakes in the pH range 6.5—7.0 were 31% green algae, 63% blue—green algae.
6. Similar trends were found in the zoop1ankton i.e. a significant de-
crease with phi; the trend exhibited considerable scatter. In general, the number
f zooplankton species found at a given H was greate: than the number found
in temperate lakes of comparable pH. Six species of zooplankton were domi-
nant at all pH levels, and five other species were always present but never
dominant. Two types of mutivariate analysis (principal component and c1ust: r
analysis) showed that the zooplankton populations could be grouped along pH
gradients, but the population differences with pH are relatively subtle.
Rare species showed greater differences with pH than did common species.
7. Mo clear trends were seen in either the diversity or the abundance
of benthic invertebrates with pH, and the differences that were found among
the lakes may reflect differences in trophic. conditions more than direct
effects of pH.
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8. Limited information has been obtained on fish popu1atio in acidic
Florida lakes. No species replacement or disappearance trends were found.
Condition factors relating weight and length indicated that the fish in
acidic lakes are in poorer condition than those in less acidic lakes,
possibly reflecting decreased availability-of food in acidic lakes. Breed—
ing populations are-still being maintained in the most acidic lakes. No
evidence of gill necrosis was found in any fish, reflecting the relatively
low concentrations of aluminum in the lakes.
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CHAPTER 2. RECOMMENDATIONS
This project has resulted in a thorough characterizatiom of the role
of atmospheric precipitation as a source of nutrients and min erals. The as-
sembled data base will be usef i1 asabenchmark for future condftions and
as input to local and regional—scale nutrient budgets. A fe questions re-
main unresolved with regard to atmospheric sources of nut’rier .ts, and further
work should be done to address these.
This size dIstribution of atmospheric phosphate partic1e- ’s should be
determined, and work should be done to characterize the chemitzal form of
phosphate in these particles. This information will be usefu l to clarify
questions regarding the atmospheric residence time oE suspend. d phosphate
and the distance that such particles travel in the air. Such information
is necessary to determine whether the enhanced collection of çohosphate in
bulk precipitation (compared to wet—only precipitation) repre ents a new
(external) source of phosphate for a given site or merely is ;nart of an in—
terrial cycle of wind-induced suspension and particle depositic:rn in the
immediate vicinity of a bulk precipitation collector.
Regarding atmospheric deposition of nitrogen, further stt ndies should
focus on rates of gaseous deposition (i.e. N H 3 and NO 2 uptake by plant,
soil and water surfaces). These processes were found to make large contri-
butions to a mass balance model of nitrogen in peninsular FloLida ( esser and
Brezonik 1980 a,b), but these models calculated gaseous deposftion using
literature values for deposition velocities and measured leve Zs of these
gases in the atmosphere of Florida. Direct measurements of and O2 d c-
position need to he done under a variety of meteorological cor ditions and
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for a variety of land use and vegetation types. Such work is diffia lt and time—
consuming, but it is necessary to evaluate the model calculations. Further
measurements of ambient NH 3 and NO 2 concentrations in rural and coastal
areas also are needed to refine model calculations.
The acidity of rainfall in Florida has been well documented by this
project (e.g; Brezonik et al. 1980). Continued monitoring of pH and as-
sociated parameters in rainfall should be undertaken on a network of sam —
pling stations around the state. Such information is needed to determine
temporal changes in the severity of the problem at a given site and to de-
termine changes in geographic distrtbutioa (e.g. the spread further southward
of rainfall acidity). Because Florida’s population is still increasing at
a rapid rate, demands for electric power and fossil fuel consumption are in-
creasing more rapidly than in most other states. The shift to coal—fired
power plants that is occurring in Florida (as in the rest of the United
States) is further reason for continued careful monitoring of rainfall.
The source of acidity in Florida precipitation has not been resolved completely,
although evidence presented in this report indicates that emissions of SO 2
and NO within the state are largely responsible. Large—scale modeling and
field—measurement studies on acid precursors will be needed to refine esti-
mates of long—distance transport into the state.
The lake studies conducted as part of this project have described the
effects of increased acidity on corrmunity structure in softwater lakes.
Further studies should emphasize the effects of pH changes on metabolic pro—
cesses—--nutrient cycling and productivity in these lakes. The effects of
acidification on fish populations need to be quantified. Reasons for the
relatively low concentrations of aluminum in acidic Florida lakes should
2—2
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be determined. Virtually nothing is known about the effects of acid rain—
fall on the sandy, poorly—buffered soils commonly occurring in Florida..
Studies should be undertaken on the effects of acid rainfall on soil ch —
Istry and soil microbiology. Studies on effects of acid precipitation on
agricultural crops in Florida (e.g. citrus, pine forest, vegetables, sugar
cane) should be conducted. These studies would focus on direct effects of
air—borne acid impacting upon the foliage and fruit of such vegetation during.
various pahses of their growth cycle and indirect effects which could occur
with soil acidification. Finally, holistic watershed—level studies need to
be undertaken to deter-mine the relationship between acidic inputs to the
poorly buffered soils of Florida and the movement of acidity related sub—
stances into ake, and streams.
2—3
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CHAPTER 3 INTRODUCTION
The chemistry of rainfall has been studied for over a cer .tury. tut m riy
questions remain about itsimportartce-in biogeochemical cycles and in trans--
port.of pollutants from ;he atmosphere to terrestrial and aquatic eL systems.
Because the nitrogen cycle involves several volatile or gaseous compounds,
the importance of atmospheric reactions and transfers in this cycle has been
recognized for a long time. Measurements of the inorganic nitrogen content
of rainfall date back to the latel9th century. Much less information is
available on levels of organic nitrogen and other “rock—bound” nutrients
(e.g. phosphorus) in rainfall. Moreover, information in the literature ex-
hibits a wide variation in concentrations of nutrients both spatially and
temporally in rainfall. Causes for this variability are not explained in
the literature.
The role of rainfall as a transport mechanism for various pollutants
such as heavy me.tals and acidity has be€ n recognized in recent years, and a
considerable volume of data has been assembled on the pH of rainfall in
Scandinavia and the northeastern United States. The deleterious effects of
acid rainfall on aquatic systems in temperate climates also has been docu-
mented. Analysis of geographic and long—term temporal trends in acid preci-
pitation indicates that acid precipitation is a potentially very serious en-
vironmental problem of international magnitude. Previous acid rainfall studies
in the United States have been skewed geographically to the Northeast, where
the problem apparently is most severe. Little information is available on the
extent of the problem in other areas, such as the Southeast. Edaphic condi-
tions in their region, and especially in Florida, suggest a high susceptibility
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for deleterious ecological effects, and demographic patterns suggest that
this region may experience increasingly acidic precipitation in the future..
Information on the role of other atmospheric deposition processes, namely
particulate and gas deposition, in nutrient and pollutant transport is much
less-deiinitive. The project that. this--repo t summarizes was undertaken to eval—-
uatc the role of atmospheric deposition processes in the transport of nutrients,
minerals, and certain pollutants (primarily acidity) to the earth’s surface.
Most of the results presented in this report are based on two large
scale field studies. The first, a statewide sampling network for bulk and
wet—only precipitation, was used to evaluate the importance of rainfall and
dry fallout as sources of nutrients, minerals, and acidity to Florida eco—
systems. The network was established to allow analysis of the influence of
surrounding land—use patterns on deposition rates of these substances; sam-
piers were located in urban, agricultural, forested, coastal, and pristine
areas. Transects were established to evaluate north—south and east—vest
(coastal—inland) gradients in deposition patterns. Details of the sampling
procedures and results are presented in Chapters 4 and 5. The network pro-
vided valuable information on nutrient and mineral deposition patterns (Chap—
ter 4), and yielded the first comprehensive analysis of the acid rainfall
problem in the state of Florida (Chapter 5).
The second field effort involved a sampling program on 20 softwater lakes
in north—central and south—central Florida. Routine lirnnological measurements,
complete chemical analysis, and analysis of the biota were done on each lake
to evaluate the effects of acidification on Florida lakes. Phytop1 anktoc,
zooplankton and benthic invertebrate communities were analyzed for species
diversity and abundance; results of the lake studies are presented in Chapter 6..
Two other aspects of atmospheric deposition precesses were studied during
3—2
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this project but are not presented in this report. The intpo’tt:ance of gas
(NU 3 and t.0 2 ) deposition in the cycling of nitrogen was evalu. ited by means
of a mass balance model of nitrogen in peninsular Florida.. T the results of
this model are presented elsewhere (Messer and Erezanik 1980 a,b), and they
indicate that these processes may be major sources of ui og to terrestriaL -
and aquatic ecosystemsin Florida. Field studies are mder ’ay to verify the
dep sition luxes calculated in the mass balance model.
The trace heavy metal content of bulk precipitation and . ithin—storm
variability on the heavy metal content of rainfall a1.s were determined dur-
ing this project. In a related ptoject, deposition patterns ere determined
for various heavy metals in sediments of ten 1ake sampled a part of the
survey on acidification effects. Results of the trace metal tudies are
still being assembled for a thesis and will be published separ.ately.
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CHAPTER 4. NIJTRIENT AND MINERAL DEPOSITION BY RAINFALL
The primary purpose of this phase of the study was to evaluate the
role of precipitation as a source of nutrients to aquatic and terrestrial
ecosystems in Florida. Emphasis was placed on nitrogen and phosphorus forms,
but all major-minerals were measured- in rainfall, and results are presented
here for deposition of mineral ions, as well. A number of studies have
re.ported on the chemical composition of precipitation in Florida; wever,
most of the studies had limited objectives and involved only a few para-
meters, a few sampling locations, or short sampling periods. Comprehensive
data on the chemical composition of rainfall in Florida thus are lacking.
The most important previous studies are described below.
HISTORICAL NUTRIENT DATA
Junge (1958) and Junge and Werby (1958) reported on the major ion con-
tent (including and N0 3 ) of wet—only rainfall collected during 1955—56
at four Florida locations (Tallahassee, Tampa, West. Palm Beach, and Jackson-
ville), as part of a nationwide study of precipitation chemistry. A second
national sampling network (Lodge et al. 1969) existed from 1960 to 1966 and
reported data on major ions, inorganic N, and trace metals in wet—only pre-
cipitation for a station in Tampa. -
The nutrient content (i.e. nitrogen and phosphorus forms) of Florida
rainfall has been measured by a number of investigators in various Florida lo—
catiOns over, the past- decade, primarily-in relation to efforts to determine.
nutrient budgets for lakes in eutrophication studies. Brezonik et al. (1969)
measured inorganic and organic N and P in bulk precipitation collected du-
ring 1968 at a rural site 40 kin east of Gainesville and computed atmospheric
loadings to several isolated, pristine lakes in that area. Nutrient budget
studies (Joyner 1971) on Lake Ok echobee, the largest lake in Florida, yielded
4 —1 -
-------
data on bulk precipitation collected near the lake during 1969.
Nutrient budget and mineral cycling studies on a mixed hardwood forest
(Ewel et al. 1976) and cypress wetlands (Bourne 1976; Hendry 1977) inc1ud d
nutrient measurements on rainfall in the north central Florida area.. Caggiani
and Lamonds (1978) andBurton etal. (L978Ystudied the effects of high. ay
construction on nutrient inputs to lakes in Orlando and Tallahassee, and
both studies included nutrient measurements on rainfall. Lamonds and Merr-itt
(1976) determined the nutrient content of bulk precipitation at two sites
along the proposed cross—Florida Barge Canal (central Florida) during 1975 -
Mattraw and Sherwood (1977) conducted urban runoff studies in the Fort Lau er--
dale area and reported nutrient analyses of rainfall collected in that ar : .
Finally, rainwater samples were collected over South Florida during the 19 3
Florida Area Cumulus Experiment (Wisniewski and Cotton (1978)). These samp las
were collected both at the ground surface and by aircraft at the cloud—bas
level (600m). The historical data on nutrients in Florida precipitation
are summarized in Table 4—1; in general, the various studies show large var i—
ability. Because of the large number of different locations and short sam-
pling periods involved in these studies, it is difficult to infer trends.
However, recent data for wet—only precipitation indicate that there has be’*en
a substantial (three—fold) increase in inorganic nitrogen levels compared to
those found 25 years ago (Junge 1958).
SANPLI G PROCEDrJRES A D ANALYTICAL METHODS
A. Precipitation Monitoring Network .
In order to assess the regional variations in atmospheric fluxes of nu-
trients to lakes and soils, a statewide precipitation monitoring network wa
established in fall of 1977. The network consIsted of 24 collection station
from Jay in the panhandle near Pensacola, to Bahia Honda in the lower Keys.
The locations of the sampling sites i the Florida Atmospheric Deposition
4—2
-------
Collection Sampler —
Reference Period Location(s) Type 1 N03—N TIN TON TN Ortho P Total P
Junge (1958) 1955—56 Tallahassee W 40 50 90
W. Palm Beach
Jacksonville
Lodge et. al. 1960—66 Tampa W 80
(1968)
Brezonik et. al. 1968 rural nortit— B 80 120 200 180 380 12 29
(1969) central Fla.
Joyner (1971) 1969 Moore Haven B 260 120 380 310 690 23 40
Schneider et. al. 1969 Winter Garden B 180 180 160 430 59
(1969)
Ewel.et. al. 1971—73 rural north— B 100
(1976) central Fla.
Wisniewski and 1973 rural south B 150 150 300
Cotton (1978) Fla.
south Fla. C 230 180 410
Miami B 280 260 540
Caggiani. and 1972—74 Orlando B 640 340 980 560 1540 100 140
Lamonds (1978)
Bourne (1976) 1974 Gainesville B 200 100 300 250 550 50 150
Mattraw and 1974—75 Fort Lauder— B 120 270 390 130 520 17 26
Sherwood (1977) dale
Burton et. al. 1974—75 Tallahassee B 170 290 460 17 37
(1978)
W 110 190 300 5 29
-------
a\Ie 4-4 . ( ont x uec
Collection Sampler
Reference Period Location(s) Type 1 NH4—N N03—N TIN TON TN Ortho P Total P
Lamonds and 1975 Central Fla. B 310 210 520 390 910 35 50
Nerrit (1976)
Hendry and 1977—79 Gainesville B 120 230 350 470 820 24 85
Brezonik (1980)
W 100 190 290 410 700 19 34
Ranges 80— 90.- 200 . 160— 380 12— 29
640 340 980 560 1540 100 140
W 40— 50— 80— 5— 29—
110 190 300 19 34
.p-
B = Bulk; W = Wet—only; C = Cloud.
-------
Study (FADS) are shown in Figure 41. Table 42 gives the cc xoty in which
each station is located, its coordinates and starting date o f operation.
The large number of collection sites permit mt pretati c1 of the rain-
fall data in terms of various demographic, land -use, and. geo raphtc para-
meters. Urban and semi-urban-sites are represented by Miami Gainesville,
Tallahassee, Jacksonville, and Fort Myers. Rural sites in predominantly
fcres ted areas include Bronson, Lake Placid, Corkscrew Swamp, and Waldo.
A number of sites are in areas of intensive agriculture: }tastings (potato
farms); Lake Alfred, Lake Apopka (citrus); Bradenton (vegetab les); Belie
Glade, Clewiston (sugar cane); Chipley (chicken . farm); and. Mc Arthur Farms
(dairy cattle). Coastal stations include Cedar Key, Marine1 nd, Stuart, and
Bahia Honda Key. Three collection transects were organized w ithin the state
so that the distribution and trends in rainfalL chemistry couJ.d be intensively
studied. One transect extends the length of the peninsula fr om Jasper, near
the Georgla border, to Belle Glide, south of Lake Okeechobee. A second tran-
sect was established east—west across the northern part of thee state (Marine—
land to Cedar Key), and a third transect consists of a serie5 of collectors
(east—west) across south Florida (Stuart to Ft. Myers), with za clustering of
sites around Lake Okeechobee. Many of the FADS statiorts are’ fl.ocated at and
operated in conjunction with University of Florida agricu.ltur 1 research
station that collect climatological data. Twenty stations hacje collectors
designed for bulk precipitation (Likens 1972), and four sites were equipped
with automatic Aerochem Metrics Model 101 wet/dry collectors that collect
the wet and dry fractions separately. Samples were collected bi—weekly at 20
of the sites either by us or by technicians at the research s;tations, who mea-
sured the rainfall amount over the collection period and mai1 d the samples to
our lab for analysis. Samples at three stations (Jay, Jackso - ville, and Miami)
were collected weekly, and samples at Gainesville were col1ec zed on an event
4—5
-------
AP Apopka w.tfdry)
BA Bisd. ton
BG Bell. GI d. (w,t/dry)
BH Ban a Honda
BN Brori,on
CH Ch pl.rY
CK CadeiXty (wit/dry)
CL C1ew on
CW Cork rsw Swamp
FM Fort Myers
CV Ga,n.will. (wit/dry)
HA Haitrngs
JA Jack,on’pjlle
JS Jasp.r
JY Jay
LA Like Alfred
Li’ L k. Ptacid
LI Lisbon
MC MacArthUr F.cms
Mt Miami
ML Miirjnelifld
ST Stuart
TA TalIaiia *
WD Waldo
ML
Figure 4—1. Location of sampling stations in the Florida
Atmospheric Deposition Study Network.
TA
Js
K YSTQ STATIONS
WD
GV HA
BN
CK
LI
AP
LA
MG
LP
a
/
BH
1
0
4—6
-------
Table 4—2 . Location of Stations in the Florida Ac nosperhic Deposition Study
Network.
Starting
Station County Coordinates Date of Operat on
w
Apopka Orange 81°30’ 28°40’ 7/77
Bradenton Manatee - 82°30’ 27°30’ 3/78
Belle Glade Pa1 - E each- 80°L+0’ •26° 45’ 12/77
Bahia Honda Monroe 81°1O’ 24°40’ 11/77
Bronson Levy 82°45’ 29030! 12/77
Chipley Washington 85°30’ 30°50’ 4/78
Cedar Key Levy 83°0’ 29°10’ 12/77
Clewistori. Hendry 81°0’ 26°45’ 12/77
Corkscrew Collier 81°40’ 26°30’ 1/78
Fort Myers Lee 810501 26045! 11/77
Gainesville Alachua 820201 29°30’ 7/76
Hastings Sc. Johns 81°30’ 29°45’ 11/77
Jacksonville Duval 81°45’ 30030! 8/78
Jasper Hamilton 82°50’ 30°30’ 4/73
Jay Santa Rosa 87010! 30°45’ 4178
Lake fred Polk 81°50’ 28°LQ’ 1/78
Lake Placid Highlands 810301 27010! 12/77
Lisbon Lake 81045! 28°50’ 3/77
MacArthur Okeechobee 80040! 27°20’ 1/78
Miami Dade 80°15’ 25°50’ 11/77
Marineland Flagler 81°i0’ 29°40’ 11177
Stuart Martin 60015? 27 10’ 4/78
Tallahassee Leon 84°lS’ 30030! 1/73
Waldo A.lachua 82°l5’ 29°40’ 4/78
* All stations were sampled until fall of 1979. A modified network consiscing
of 16 stations sampled weekly is still in operation during 1980.
4—7
-------
basis. Dryf all samples were collected by adding 300 4 of deionized water
4’
to the bucket and scrubbing the bucket with a clean/lastic glove to dislodge
particulates. Analyses were then run on the rinsings.
B. Analytical Methods .
Analytical, methods fo r chemical determinations of the precipitation
and dryf all samples are summarized in Appendix 1. In general, analyses were
performed according to Standard Methods (APRA 1976) and/or the EPA water
analysis manual (U.S. EPA 1976). Inorganic nitrogen forms (NR 4 +, N0 2 ’, N0 3 )
were determined by automated methods on a Technican AutoAnalyzer; soluble
reactive phosphate (SRP) (roughly equivalent to orthophosphate) was determined
manually with a Beckman Model DBG spectrophotometer and 4—cm cell, using the
single reagent colorimetric method. Total Kjeldahl nitrogen and total phos-
phate were determined by manual (semi—micro) digestion in test tubes, followed
by colorimetric analysis for animonium ion (AutoAnalyzer) and orthophosphate
(manually) on the neutralized digestate. Cation analyses were done by flame
atomic absorption spectrophotonietry following procedures recommended in the
instrument manual (Varian, 1973).
RESULTS AND DISCUSSION
A lntrothxction .
Solute concentrations generally are inversely related to the quantity
of rainwater falling during a storm. Computing volume—weighted averaged
concentrations tends to equalize the importance of light rains, having rel-
atively high concentrations and heavy rains, in which constituents are
iore dilute. Volume—weighted concentrations are calculated by:
j: 1
vi
jx 1
4—9
-------
where C 1 = constituent concentration (mg/L) and
V 1 rainfall amount (cm).
Sus ary results of statewide volume—weighted mean concentrations and
loadings for major ions and nutrients in bulk precipitation are presented in
Table 4—3. Volume—weighted tnean concentrations of all parameters at each
site and annual depositions are given in Appendix 2. Annual loading rates
were calculated by multiplying the volume—weighted concentration for each
constituent by the total rainfall over the given time period.
The period, Ma.y 1978 through April 1979, represents the first full year
during which the entire sampling network was in existence; thus this period
was selected for detailed discussion in this report. As shown by Table 4—3,
the values of mean concentrations and loadings for this period are close to
those found over the entire 2 year study. The month of May also represents
the beginning of the su er (rainy)’ season in Florida, and consequently May
is a convenient starting point for an annual study.
B. NUTRIENTS
The results and discussion of atmospheric deposition of nutrients is
divided into six sections: (1) geographical variation of atmospheric fluxes
of nitrogen and phosphorus; (2) speciation of the N and P forms in precipi-
tation; (3) seasonal variations in the nutrient content of rain; (4) relative
importance of dry fallout and wet deposition as sources of nutrients; (5) com-
parisons of present concentrations and fluxes with historical data; and (6)
examination of the significance of atmospheric nutrient deposition relative
to critical loading rates for lake eutrophication.
1. GEOGPLAP [ IICAL VARIATION OF NUTRIENT DEPOSITION
NITROGEN
Deposition of nitrogen by bulk precipitation at the 24 sites during
the period ranged from 0.32 g N/rn 2 — yr at Bahia Honda Key to 1.13 g N/rn 2 — yr
4-9
-------
Table 4—3 . Statewide Nean Concentrations and Loadings by Bulk Precipitation for Various Periods during the
Two Year Study.
Study Calendar Calendar Total Study’
Period 5/78—4/79 1978 1979 1978 + 1979
Number of Samples 595 531 603 1,134
Number of Bulk
Sites 22 21 22 21
Parameter Conc.’ Loa ing 2 Conc. Loading Conc, Loading Conc. Loading 3
Na 1.18 1.49 1.06 1.17 1.37 1.99 1.19 1.58
K 0.21 0.28 0.22 0.27 0.18 0.25 0.18 0.26
Mg 0.16 0.20 0.15 0.17 0.19 0.27 0.16 0.22
Ca 0.65 0.86 0.59 0.72 0.62 0.87 0.58 0.80
S0 1.81 2.45 1.90 2.43 1.69 2.54 1.75 2.49
CL 2.21 2.80 2.05 2.27 2.55 3.71 2.27 2.99
NH —N 0.18 0.24 0.21 0.27 0.14 0.22 0.17 0.25
N0 —N 020 0.27 0,23 0.29 0.18 0,27 0,20 0,28
TON 0,17 0 ,23 0,18 0.23 0.14 0,2]. 0.16 0,22
saP ,026 .034 .OiO .038 .016 .022 .021 .030
Ti’ .03 .OSQ ,O 5 ,057 0 9 0( 2 .03 , 05Q
- Volume—weighted Mean Concentration; all Values are mg/L,
2 Loading rates are g/m 2 —yr
Average Annual Loading over the two year period.
-------
at Belie Glade (Figure 4—2A). The Bahia Honda site represents an almost
completely maritime regime, while the Belie Glade site is located in the
Everglades Agricultural District, a large area of sugar cane plantations and
vegetable farms. Mean deposition of nitrogen over all 24 sites was 0.76 g N/rn 2 —
yr.
Brezonik (1976) concluded, that bulk precipitation deposits fro ‘1. to
2.0 g/m 2 —yr of total nitrogen over large areas of the United States, and
that deposition rates outside the range of 0.5 to 3.0 g/m 2 —yr are likely to
occur only under unusual circumstances. Deposition rates across Florida
fall in this range (Figure4-2), except at two pristine sites, Bahia Ronda Key
as discussed above, and Corkscrew Swamp (0.45 g/in 2 —yr), a remote Audubon
sanctuary, located in the Big Cypress Swamp in south Florida.
Table4.-4suminarizes the mean deposition of TN at the stations grouped
according to the dominant land use in the immediate area. Deposition rates
were lowest at coastal and non—agricultural rural lècations, and highest
loadings occurred at sites in dominantly agricultural regions. The latter
sites received about 50% more loading of nitrogen than did the coastal sites.
PHOSPHORUS
Deposition of total phosphorus by bulk precipitation in Florida (Figure
4-2B)’ranged from 17 (Bahia } onda Key) to 111 tng P/n1 2 —yr (Jasper), with 51.
mg P/rn 2 —yr as the mean for all sites. The site at Jasper is in an area of
phosphate mining, and the observed high deposition rate likely reflects the
mining activities. In general, highest deposition rates were recorded at
agricultural locations, and lowest rates occurred at rural and coastal sites
(Tabie.4—4) Atmospheric deposition of total phosphorus at the former sites
was more than double that at the latter sites. According to Chapin and
Uttorrnark (20), atmospheric phosphorus fluxes usually range from 0.1 to 1.0
kg/ha—yr (10 to 100 mg/m 2 -yr); the results in Figure 2 B al1 in this range,
4—li
-------
B
3c 49
58 88
Figure 4—2.
(A) Total nitrogen deposition (gN/i i 2 —yr) and (B) Total phosphorus deposition (mg F/m 2 —yr) in bulk
precipitation across Florida, May, 1978 to Apr11, 1979. At sites equipped with wet/dry eol1ector
the urn of the wet an4 d y depo it1or is shown.
A
—
0.32
•17
-------
Table ‘—! Dt p:st . r r ;,-:Jt
phosphorus at s . r s group accpr’cti
to dornthant laud e in th ea.
TN TP
/1n 2 —yr mg/m 2 —yr
Coastal
0.58
31
Urban
0.76
50
Rural
(non—agricultural)
0.62
27
Rural
(agricultural)
0.88
66
State
0.75
51
4—13
-------
B
A
CK
0.40
0.30 mg N/L 5O J / . .gP/ l
r; —i 0.20 oJ
H 0.10 LEGEND SCALE
M o.oo
legend scale /
‘ S
Figure 4 -3, (A) Volume—weighted average concentrationfi of NO—, NIf -, and organic nitrogen and
(13) Vo1ume—we ji VecI ver e oncencratini oC r n c nU orginic pl phoru in
i)ulk precipl.cat{on. Por clarity, not all ait a are atwwn
1•
-------
3. sE’ASONAT VARIATIONS IN THE NUTRIENT CONTENT OF PRECIPITATION
NITROGEN
Rainfall in Florida generally follows a bimodal seasonal pattern, with
most of the rain occurring in the summer and winter months. Summer
rainstorms are convective events; winter rains generally are associated
with cold fronts moving down the peninsula. S ring and fall generaUy are
dry seasons, and thus it is convenient to compare Florida rainfall chemistry
on a suimner/winter basis. The sim er values are for the months Nay to
October, while the winter values are for November to April. As slx n in
Table 4—5, concentrations of both inorganic and organic nitrogen are greater
in summer (convectIve) rain storms than in winter (frontal) events. Aver-
aged over all sites, ammonium and TON concentrations in sununer raios were al-
most double the winter levels, and N0 3 and TN were 40 and 70% higher, respec-
tively. The greater concentrations in summer rain may have resulted from three
factors: Increased biogenic emission of gaseous nitrogen compounds due to
higher summer soil temperature; nitrogen fixation by lightning, which fre-
quently is associated with summer storms; and/or more efficient wasl ut of
substances in the highly turbulent convective storms.
Plots of monthly (volume—weighted) average concentrations of N0 3 and
NH 4 in bulk precipitation do not show such pronounced seasonal
trends as might be expected from the summary data in Table 4—5. Figure 4—4
shows monthly variations in these ions and monthly amounts of rainfall at
three sites distributed across the state: Jay (in the northwest corner),
Gainesville (in the north central part of the peninsula), and Miami (in
southeast Florida). Although concentrations at Jay (Figure 4-tEA, and Gaines-
ville (Figure 4—RB) were higher during the summer months than the winter
months, highest concentrations occurred in a few samples collected during
spring and fall, when there was little rain. These high values likely reflect
4—16
-------
Table 4—5. Statewide annual and summer/winter (volume—weighced)
mean concentrations of nitrogen and phosphorus in
bulk precipitation. All values in JgI1.
Annual
.
Summer
•
Winter
Summer
Ratio: -
Winter
NH —N
180
230
120
1.9
N0 3 —N
200
230
160
1.4
ORG N
170
210
110
1.9
TN
550
670
390
1.7
SRP
26
32
20
1.6
Org P
12
15
10
1.5
TP
38
47
30
1.6
4—17
-------
30
20
10
0.00
3O
c 20
a
a: 10
0
z
E
E
I - )
C
a:
Figure 4—4.
1978 1979
MONTH
Monthly volurae—weighte .d mean concentrations
NO (Dashed Line), and rainfall at Jay (A),
Miami (C) from May, 1978 to April, 1979.
of NF [ t (Solid Line),
Gainesville (B), and
0.80
0.60
A
0.40
t
I’
/ ‘
p.
I
0,00
0.80
0.60
B
0.40
0.20
--.
-
0.80
C
j ‘
I4
S.’
I 11%
I ‘‘‘‘
,
15
0
5
M J J A S 0 N D J F M A
-------
atmospheric buildup of contaminants during these dry periods. A seasonal
(summer/winter) pattern is not discernable at subtropical Miami (Figure 4—4C),
with highest concentrations occurring during the drier months.
PHOSPHORUS
As shown in Table 4—5, volume—weighted average concentrations for SRP
and ORG—P are 60 and 70% higher, respectively in the summer months compared
to the winter months. Monthly plots of SRF and TP for Jay and Gainesville
(Figure 4—5A and B) show a pronounced decline in monthly mean values during
the winter months (Dec., Jan., Feb.) for both SRP and TP. However, the levels
of SRP and TP at Miami (Figure 4—SC) were greatest during these months. As
was true for the nitrogen species, the driest months generally had the highest
concentrations of both SR.P and TP.
4. COMPARISON OF WET VS. DRY DEPOSITION OF NUTRIENTS
NITROGEN
Wet/dry collectors yield information concerning the mechanism of depo-
sition for nutrients. Table4-6dummarizes results for the wet and dry depo-
sition of total nitrogen at the four sites with wet/dry collectors. Mean
deposition of TN by wet—only input over all four sites was approximately
double the average dryfall input. The highest total deposition occurred at.
Belle Glade, while the coastal site at Cedar Key had the lowest TN deposition
of the four wet/dry sites. The dryfall collector at Belle Glade generally
collected the largest amounts of particulate matter among the four sites,
especially during fall and winter, when the sugarcane fields were burned
prior to harvesting. At these times, the dryfall collector had noticable
amounts of black soot.
The manner in which the forms of nitrogen are partitioned between wet
and dry fallout is illustrated in Table4— . Deposition of ammonium and ni—
4—19
-------
LL -Hn-
TiTr 3°
-è —‘.‘..--
I•p
r r :. -
-.
.
/ 1k F
\ L
-
——-- -— — -
L _
rj
—
4i
Figure 4-5. Monthly Voiume... 1eighted r ean concen atjons of SRP and TP at
Jay (A), Gainesville (B) and Miami (C) from Ma: , 1978 to
April, 1979.
4—20
- ‘ .-.-.
F
- -a
—— -—---- --1”-
- 44-- .—3.-- - -5 -
T
a
—.
i —
— - 1
i
- ; - - - - .-- -
- r
-— —— —- -
—-—--,- -
- --. ——.-
-r
—4-—
I F
I
:
:
I— I
- I r
A I
: :. ?.
r
ILL’
1
I-i
k ’J
7
rr
A
T f’
T
- I 1
—a L -J I
p T :
) ‘I
TEL J
. —
-N
:
-rrry; n- -•-r-r ---;;-r-
--T tT - - -—-r --
LL L £ F. _______ .J_ L
-------
Table 4—6. Wet aud dry deposition of total nitrogen and phos-
phorus at sites with wet/dry collectors.
Site
/To
Wet
tal Nitrogen
(g/m 2 —yr)
Dry Total
Thea
(1
Wet
1 Phosph
g/m 2 —yr
Dry
orus
)
Total
Gainesville
0.63
0.28
0.91
16
42
58
Cedar Key
0.52
0.25
0.77
6
18
24
Apopka
0.47
0.34
0.81
9
48
57
Belle Glade
0.64
0.49
113
12
84
96
mean
0.57
0.34
0.91
11
48
59
4—21
-------
Table 4—7. Relative deposition of nitrogen and phosphorus forms by wet
versus total (wet plus dry) deposition at the four wet/dry
collection sites .*
Location
NH
NO 3
TIN
Org N
TN
SPY
Org P
TP
Gainesville
(urban)
88
70
74
59
69
40
19
28
Cedar Key
(Coastal)
82
62
69
61
68
33
20
25
Apopka
(agric.)
70
74
72
33
58
20
11
16
Belle Glade
(Agric.)
83
67
72
38
57
15
9
13
Average
81
68
72
48
63
27
15
20
*Values are % deposition by “wet—only” precipitation (lOO x load—
ing from wet o1lector)/tota1 loading (wet plus from dry).
-------
trate by wet—only input averaged 81 arid 68%, respectively, of the total de-
position (wet + dry). Thus for these two substances, rainfall was the pre-
dominant deposition mechanism. Atmospheric precursors of ammonium and ni—
trate in rainwater are gases (NH 3 and NO) and secondary aerosols (parcicu—
lates formed by gaseous reactions, e.g. NH NQ 3 ,. NH 4 HSO 4 ). These=aerosols
are very small (<1 rni) arid thus do not settle from the atmosphere as dryfaul.
They are hygroscopic, however, and as a result they are important as con-
densation nuclei for rain drop formation.
While wet—only input is the major mechanism for inorganic nitrogen de-
position, it is less important for the input of organic nitrogen; only 47
of the average atmospheric input of organic nitrogen was from wet deposition.
At Gainesville and Cedar Key,ca. 60% of the TON deposition was by wet input,
while at Apopka and Belle Glade, TON deposition via wet input was only about
357.. As discussed above, the Apopka and Belle Glade sites are located in
areas of intensive agriculture, and atmospheric deposition in these areas
seems to reflect activities such as plowing and harvesting that introduce
relatively large (hence rapidly settling) particles into the atmosphere.
Dryfall of soil—derived particles thus appears to be an important mechanism
for organic nitrogen input, while rainfall is more important for inorganic
nitrogen deposition.
PHOSPHORUS
Data summarizing the wet and dry deposition of phosphorus at the four
wet/dry sites are presented in Tables4-6and4-7. The Belle Glade collector
2
recorded the highest (wet plus dry) deposition of total P (96 mg/rn —yr),
while the coastal Cedar Key collector measured the least deposition (24 mg/
2
in —yr). The mean (wet plus dry) deposition of total P for the four collec-
tors was 59 rng/m 2 -yr (Table 4-6)-.
4—23
-------
Dryfall input of phosphorus was more important ti an wet precipitation,
accounting for 80% of the total deposition averaged over the four sites
(Table 4—7). The reverse was true for nitrogen (see above discussicn).
Only 15% of the organic phosphorus (operationally defined here as total
phosphate minus soluble reactive phosphate [ SRI’]) was deposited via rainfall,
wrilie 27% of the SRI’ was from rainfall . To ál phosphorus deposition at the
agricultural Belle Glade site was 87% via dryfall and only 13% by rain
(Table 4—7. Since phosphorus is a nonvolatile element, its cycle generally
is limited to rock—soil—water phases. Atmospheric deposition of phosphorus,
therefore, occurs primarily by gravitational settling of particles that
enter the atmosphere by various activities (e.g. argriculture, mining,
fires). The high dryfall deposition of phosphorus (relative to wet
input) at the agricultural Apopka and Belle Glade locations demonstrates
the importance of land—use activities on atmospheric deposition of terrigenous
substances.
5. HI5 ORICAL COMPA I3GN
Historical data are available for the wet—only deposition of inorganic
nitrogen to compare with the present data. Chapin and Uttorinark (1976) con-
structed an isopleth map of inorganic nitrogen flux using Junge’s (1958) data
for ammonia and nitrate in wet—only precipitation. The map shows a flUx of
inorganic nitrogen of 0.10 to 0.15 g/m 2 —yr across the southeastern U.S., in-
cluding Florida. Inorganic nitrogen fluxes via wet—only precipitation mea-
sured in this study range from 0.32 to 0.44 g/m 2 —yr, with a mean of 0.39
g/m 2 —yr. The annual mean concentration of TIN in 1955—56 averaged over the
£ our Florida sites in Junge’s study was O.0 mgIL, while Lodge et al. (1968)
found a volume—weighted mean TIN concentration of 0.08 tug NIL In wet—only
precipitation at Tampa during the period 1960—66. Although there have been
numerous studies of bulk precipitation across Florida since the Lodge et al..
4—24
-------
study, only two wet-only investigations have been. reported LTable 4-1 ).
Burton et al. 1978) found 0.30 mg/L Tfl1 In wet—only’ precipitaition collected
during 1974—75 at Tallahassee, while Hendry and BrezonLk (19841fl reported
0.29 mg/L TIN in Gainesville wet—only precipitation (1976—771 Averaged
ove ’ the 4 wet-only collection. sites in this study,, the Tfl concentration
was si i1ar to the above values: (0.28 ing N/L); thns the mean concentration
of inorganic nitrogen in wet-only precipitation and corresponding flux have
increased about three-fold in Florida over the last two decad es.
In bulk precipitation TIN averaged 0.38 mgJL over all the sites, ranging
from 0.28 (Corkscrew) to 0.59 (Chipley) mg/L. Historical dat (Table 4-1)
for TIN in bulk precipitation in Florida ranged front 0.20 to 0.98 mg/L.
With such large variability due to a number of d.i.fferent sam ilirtg locations,
no historical trends can be inferred concerning the levels of TIM in bulk
precipitation. Fewer data are available for TON levels in FLorida,
precipitation (Table 4-1) and the values again show a large rm nge, 0.16 to
0.56 mgJL. The state—wide mean (all sites) for TON in. this st ’udy was 0.17 mg/L
which is near the low value of the above range.
Average total phosphorus CT?) concentration was 38 jig/L for all the bulk
precipitation sites, with a range of 29 to 59 gJL for indiv±dl.ual sites. Pre-
vious studies (Table 4-1) have reported a large range (29-140 rg/L) of TP
values at various locations over the last ten years. As menti oned earlier,
this large variation likely is due to d1.fferent locations and short (< 1 yr)
sampling periods.
6. SIGNIFIcAf7C ’ OF N AND P LOADINGS RELAT.P1 TO W ’ ErJr ?OPHr 4TION
The atmospheric loading rates of total nitrogen and phosphorus found
at each bulk precipitation site can be examined in the context of critical
nutrient loading rat s for lake eutrophication. Figure4-6i1lu. trates the
relationship between the bulk loading rates of N and P at each sire and the
4—25
-------
TROGEN
E
Pt-
PHOSPHORUS
400
300
(5)
E (I)
U
P(5)
2
PCI)
2.0
1.5
0.5 tOO
SITES
Figure 4—6. Loadings of nitrogen (open bars) and phosphorus (closed bars) by hulk precipitation
at each sampling site. Statewide everags loading. shown by dashed 1iiie . ermi sib1e
(P) and Excessive (E) loading criteria for nitrogen are for lakes with mt an depth
< 5 m (Vollenweider 1968). Loading criteria for nitrogen are for two values of areal
water loading (q 1 and 5 m/yr) as given by Vollenwtdder (1975).
20O
E
z
0
0
-J
AP OH 6G BA ON CK CH CL CW FM GV HA JA JS JY LA LP LI NC ML MI ST.TA WD
-------
critical loading rates developed by Vollenweider (1968, 1975). The state—c ide
mean (averaged over all the sites) deposition rate is also shown In the fig—
ure. For both nitrogen and phosphorus, the statewide mean races are below
the “permissible” values defined by Voilenweider. However, the rates at
several predominantly agricultural sites did exceed the “permissible” levels.
While atmospheric inputs of N and P by t-hemselves- would not produce the
water quality problems generally associated with lake eutrophicatiou, the
higher deposition rates may support substantial standing crops of phytop1a k—
ton. Moreover, the mean loading rate for nitrogen from bulk precipitation
is about 757, of the total “permissible’ loading and about 37 of the nitro-
gen loading rate associated with the onset of eutrophic conditions.
Thus even rather low contributions of nitrogen from surface water sou’ es
may be sufficient either to make nitrogen non-limiting or to induce eutro-
phic conditions, assuming nitrogen were the limiting nutrient. The above
calculations also do not consider the atmospheric nitrogen inputs from gas€ us
absorption or from rainfall that reaches a lake via runoff in the watershed;
f or further discussion of these aspec\ts see Messer and Brezonik (1980b) . T e
high rates of nitrogen deposition from the atmosphere, coupled with the rela-
tive mobility of nitrogen (compared to phosphorus) in terrestrial systems,.
help to explain why nitrogen seldom is observed to be the limiting nutrient
in lakes.
For phosphorus the situation is somewhat different. The statewide mear
loading is half the permissible rate for lakes that have q (areal water
loading rate) = 1 m/yr, and only one fourth of the permissible loading for
lakes with q = 5 rn/yr. Most Florida lakes have q 5 values < 5 rn/yr. Figure
4 6 suggests that atmospheric deposition alone supplies only about 12 to
16% of the loading required to cause eutrophic conditions in Florida lakes.
4—27
-------
C. MAJOR MINERALS
1. SODIUM, CELORW ’ AND SULFATE ’
Volume-weighted average concentrations of sodium and chloride concentra-
tions are plotted in Figure 4-7A and 4-SA. The concentration isopleths for
both Na and C1, roughly follow the outline of the peninsula. This is no t
surprising since the source of the NaC1 in rain and dryfall across Florida
is the Atlantic Ocean and Gulf of Mexico. In fact, the Cl/Na ratios in
bulk . precipitation (Figure 4-7B) across the state are close to the ratio
of these ions in seawater (1.8) Sites with precipitation ratios less than
1.8 indicate Na enrichment, while ratios greater than 1.8 indicate Cl enrich-.
ment relative to sea salt. The mean ratio for the state (22 sites) is L83.
The concentrations isopleths (Figure 4-7A and 4-8A) are more closely spaced
on the west than east coast of the state, indicating a sharper concentration
gradient. The east coast (Atlantic) is a high-energy coastline and salt
particles are carried farther inland than is the case along the west coast
and panhandle.
The input of NaC1 appears rather constant over time. Junge and Werby
(1958) reported Na concentrations at Jacksonville and Tampa of 0.96 and
063 mg/L, respectively for 1955-56. Sodium concentrations at sites (Jackson-
ville and Bradenton) in this study near the earlier sampling locations were
1.08 and 0.51 mg/L, respectively.
Sulfate (S0 4 2 - S) concentrations in bulk precipitation (Figure 4-8B)
ranged from 1.18 ( arine1and) to 0.38 mg/L (Corkscrew Swamp). Sulfate in
rainfall originates from three sources; (1) marine-derived sulfate from
sea-salt aerosols, (2) biogenic emission to the atmosphere and subsequent
oxidation of reduced sulfur compounds (H 2 S, dimethyl sulfide, dimethyl disul-
fide), and (3) anthropogenic emission of sulfur compounds (SO 2 , particulate
SO 4 ). Sulfate deposition was princi al1.y by wet processes (average of about
4—28
-------
7.1
B
(A) Volume—weighted mean concentrations of sodium (mg/i) 1n bulk
precipitation and (B) Cl/Na wt/w t concentration ratios (Volume—
weighted values) in bulk precipitation in Florida, May 1978—
April 1979.
A
1.55
1.6
1.7
Figure 4—7.
-------
0.32
1.18
Figure 4—8.
Volume—weighted mean concentrations of (A) chloride and (B) sulfate
(as sulfur) in bulk precipitation In Florida, May, 1978 — Apr13,,, 1979.
All concentrations in mg/i.
0
00
A
2.81
0.65
0.56
B
0. 7 0.59 0.59
0.62
0.6S
0.39
I
-------
759 of the total deposition (Table 4-8), with dry deposition rates higher
during the winter months than the summer months (Table 4-9). The importance
of wet versus dry deposition for sulfate, the relative importance of the above
sources for sulfate in Florida precipitation, and the relationship of sulfate
to rainfall acidity are discussed in greater detail in.Chapter 5.
2. CALCrUM 2 MAG VEgIUZ4 AND POTASSIUM
Highest levels of calcium generally were recorded in the southern half
of the state (Figure 4-9A). Calcareous deposits (lirnestones) in this area
are located just a few feet below the surface of the top soil, and they out-
crop in some areas south of Lake Okeechobee. Mining of these deposits for
use in concrete manufacturing is extensive in south Florida.
Calciuxn\ in rainwater arises from terrestrial sources; i.e. the ocean pro-
vides only small amounts of Ca 2 to the atmosphere; this matter is discussed
further in Chapter 5 relative to the factors affecting rainfall acidity in
Florida. As a result of this terrigenous origin, isopleth patterns for Ca
are not similar to those for Na and CL. Although the highest volume-
weighted average concentration of Ca 2 in bulk precipitation occurred at
Marineland on the Atlantic coast (Figure 4-9A), calcium derived from sea-salt
particles accounted for only about 0.34 mg/L of the total Ca 2 concentration;
i.e. 1.30 mg/L is “excess” calcium. The high level of Ca 2 in the rain at this
site is likely due to combination of wave-action on the outcroppings of
coquina (limestone) rock along the coast and wind-driven suspension of cal-
careous particles in coastal soils. The historic buildin in St. Augustine
(16 km north of Marinelartd) are constructed in large part of naturally-
occurring coquina. A high ‘excess” Ca 2 ’ (0.72 mg/L) also was recorded at the
entirely maritime site, Bahia Honda in the lower Keys (Figure 4-9). This excess
Ca undoubtedly arises from the limestone rock which forms the archipelago
known as the Florida Keys. Calcium and the associated carbonate-bicarbonate
4—31
-------
Table 4—8. Wet and dry deposition of minerals at the wet/dry collection sites Values are in g/m 2 —yr.
Gainesville
Cedar Key
Apopka
Belle Glade
Wet
Dry % by wet
Wet
Dry
%
by wet
Wet
Dry
%
by wet
Wet
—
Dry % by wet
Sodium
0.35
0.24
59%
1.96
0.48
80%
0.40
0.33
55%
0.59
0.47
56%
Chloride
0.67
0.46
59%
3.63
0.82
82%
0.77
0.53
59%
1.22
0.99
55%
Calciutu
0.38
0.67
36%
0.47
0.40
54%
0.32
0.31
51%
0.70
1.71
29%
Magnesium
0.06
0.07
46%
0.25
0.08
76%
0.06
0.06
50%
0.08
0.15
35%
Potassium
Sulfate(s)
0.12
0.65
0.06
0.25
67%
72%
0.14
0.72
0.06
0.13
70%
85%
0.10
0.66
0.15
0,16
40%
8.0%
0.15
0.51
0.20
0.25
43%
67%
-------
Table 4—9. Dry Deposition of Minerals on a (Summer/Winter) Seasonal Basis. All Values are g/m - .yr.
Deposition Rate
2
(g/m —yr)
Location Na+ CL Ca+ 2 sö —s
Gainesville
Winter 0.27 0.51 0.69 0.07 0.06 0.25
Summer 0.19 0.40 0.57 0.09 0.06 0.25
Cedar Key
Winter 0.57 1.00 0.41 0.09 0.06 0.14
Summer 0.25 0.65 0.32 0.06 0.06 0.12
Apopka
Winter 0.37 0.58 0.39 0.07 0.13 0.19
Summer 0.33 0.53 0.21 0.05 0.11 0.14
Belle Glade
WInter 0.56 1.18 1.95 0.18 0.23 0.31
Summer 0.33 0.71 1.53 0.10 0.14 0.18
-------
1.64
.08
1 05
Figure 4—9.
Volume—weighted mean concentrations of (A) calcium and (B) magnesium in bulk
precipitation in Florida, May 1976—April 1.979. Al -i - c onc r4tionb iti mg/i,
A
B
.18
.1?
.0 5
•14
.5
. O. 80
.28
I
2
-------
species are important parameters controlling the acidity (pH) of precipitation
in south Florida. The pH of Florida rainwater results from cc plex inter--
actions of atmospheric acids (l-l 2 SO 4 and HNO 3 ) with terrestriaflly-derived
bases (e.g. CaCO 3 ); see chapter 5 for a detailed discussion o Florida rain-
fall acidity an&elemerits controlling the pH of Florida precipitation.
In general;inagnesium levels in hulk precipitation (Figu e4-9B) cor-
relate with calcium concentrations (Figure 4-9k). Highest Mg 2 levels were
found at the southern sites, and high values also were measurt d for coastal
locations. Seasalt supplies a substantial proportion of the fg 2 in coastal
precipitation at coastal location. In fact all of the magnesium in rain at
the four coastal sites (Cedar Key, Bahia Honda, Stuart, and trineland), is
derived from seasalt ( in seawater is 0.12).
Potassium arises in rainfall principally from soil-derive d particles.
Concentrations of K were highly variable over the bulk precipitation sites
(Figure 4-10), and they seem to reflect nearby land use activ ities. Lowest
average concentrations were found at the two most pristine locrations (Lake
Placid and Corkscrew Sanctuary), while somewhat higher levels were recorded
at agricultural locations (Clewiston, Hastings).
3. WET AND DRY DEPOSITION OF MINERALS
The relative importance of wet vs. dry input of minerals is summarized
in Table 4-8. Sodium and chloride deposition at all four wet/’dry sites
bccurred primarily by wet-only input. Atmospheric sea-salt p urticles are
highly hygroscopic and thus are important as condensation nuc l ei for rain drop
formation. No simple trend in deposition mechanism can be see n for Ca 2 , ? g 2 ,
and K , and either wet or dry processes dominated depending on the site. For
example, at the highly-agricultural Belle Glade site, total deposition of all
three metals was largely by dry fall (Table 4-8), but at Apopk.a and Cedar Key,
wet and dry deposition of Ca 2 was about equal. A strong sea5 onal-dependence
4—35
-------
0.26 0 .2L
0.16
igure 4—10.
Volume—weighted concentrations of potassium in bulk precipitation
across Florida(May. 78—May 79).. All values are mg/i.
0. t9
0.f 3
4—36
-------
was found in the dry deposition of the five minerals (Table 4—9), with dry—
fall input during the winter months being greater than that in the summer.
This trend likely reflects a lower frequency of rainevents during that sea5on
compared to the summer rainy season.
4. Comparison of Wet +Dt7 and Bulk Deposition Rates for Major Minerals .
Two different ty;esof collectors (i.e. wet/dry and bulk) were employed
in the precipitation network, and it is of interest to determine whether
the wet plus dry deposition rates (from the wet/dry collectors) correspond
to the. bulk deposition rates for various species. Assuming that wet depos ;—
tion did not vary witb. collector type, two questions are raised regarding d ry
deposition. The first involves collector height; bulk collectors in the
network were located 2 m above ground, a concentration gradient exists
between 1 and 2 m, then there may be a corresponding deposition gradient
between the two collectors.
The second question involves shape: bulk collectors are. conical,
while the wet/dry collectors and cylindrical. The flow of air aro-und
the two collectors is different, and thus the rate of turbulent deposi-
tion also may differ. This problem is not completely distinct from that
of reference height, because wind speed and eddy diffusivity are functions
of height. However, the intent here is simply to point out the gross
differences between collectors and then to determine whether these differences
might be responsible for inconsistent deposition rates.
Adequate data are available at two sites (Gainesville and Orlando)
to compare adjacent wet/dry and bulk collectors, and deposition of major
cations and anions in the two types of collectors are surunarized in Table
4—10. Generally, the agreement between wet/dry and bulk collectors is
acceptable. Deposition of sulfate and nitrate, which both originate as
gases or sub—micron particles, was the same in both types of collectors at
4—37
-------
Table ./ 0 Comparison of loading rates of maic)r ionic species as dct:e i-mined by wet/dry
and bulk precipitation collectors.
_____________— Annual Deposition (kg/ha ) ______________
+ + + +2 +2 + excess
Location H Na K Ca Mg NI!,—N NO 3 S Cl
Gainesville
Wet + Dry 0.24 5.79 1.65 10.0 1.43 1.85 3.55 24.5 11.3
Bulk 0.27 5.25 1.58 8.5 1.15 2.33 3.44 24.4 10.0
Wet + Dry x 100 89 110 104 118 124 80 103 100 113
to Bulk
Orlando
Wet ± bry 0.19 7.43 2.00 6.18 1.20 1.52 3.16 23.1 13.3
Bulk 0.22 6.71 2.07 5.49 0.71 1.97 3.18 23.8 10.1
Wet +Drv x 100 86 111 97 113 169 77 99 100 132
Bulk
-------
the two sites. Deposition of hydrogen ion and a onium was lower ia both
wet/dry collectors than in the nearby bulk collectors. The difference
+
in ri deposition reflects large cation excesses (hence by inference,
alkalinity) in the dry bucket. The wet deposition of 11+ alone was
higher in both cases than the bulk deposition. In the calculation of
total loading from wet/dry collectors, the alkalinity was assumed to
titrate a stoichiometric amount of H+. The ainmonium discrepancy is
unexplained, but may signify either a positive gradient in the vertical
direction o simply differences in NH 3 interaction with. the two collector
surfaces.
Ca+Z and Ng+ 2 deposition rates are consistently higher for the wet/dry
collectors than the bulk collectors. This may reflect the difference in
collector heights and suggests the presence of a concentration gradient
of suspended soil species near the ground. Assuming that most of the
Ca+ 2 and Mg+ 2 deposited in the collectors is associated with carbonate,
the excess of these ions in the wet/dry collectors, relative to the bulk
collectors, explains the observed underestimate of 11+ deposition in the
wet/dry system.
Sea—salt (Na+ and C1) deposition was also higher in the wet7dry
collector. Although this could be due to association of NaC]. with soil
particles, this explanation seems unlikely since it would necessitate a
relatively high percentage of Na+ and Cl in soil dust. This is unlikely
due to the differential solubilities (leaching rates) of terrestrially—
derived and oceanic species. The fact that deposition of most particulate
species was higher in the wet/dry collectors suggests that the shape and
height of tile bulk sampler may contribute to turbulent scouring of the funnel
and thus to low deposition rates.
4—39
-------
Despite the aforementioned differences between the wetfdrw and bulk
deposition rates, the results are generally comparable. Nost species were
deposited to the two collectors with less than 20% difference,., and for
several species differences were only a few percent. Unless ampling
requirements are very stringent, it seems that either collectcr will yield.
an adequate description of atmospheric deposition. Ftrthermor a, deposi-
tion patterns are reflected in the consistent manner by the c Uectors.
Both. collection systems indicate that deposition at Gaineswille was
higher than that at Orlando, while Na+, Cl and depositiot! was higher
at Orlando than Gainesville. Theproblems associated with de position
of particulate species may be overcome, or at least dTirvtnishe _±t, by adjust-
ment of collector height and by careful selection of saiiipLin location.
5. Comparison of Bulk Precipitation and Throughfall
Bulk precipitation at the Waldo site, 10 kn NE of Gainesville, was
collected atop a 20 m (65 ft) steel tower which extended throi ugh the tep of
the forest canopy. Concurrent with these collections, throug afal1 also was
collected at the base of the tower, below the tree Canopy. As; shown in Table
4- lI, distinct chemical differences were found between the builk precipitation
and throughfall. On an annual, volume-weighted average basia, throughfall
contained elevated concentrations of all chemical species exce”pt I-U’ . and
NH 4 - N. On a seasonal basis, summer (May 1978 - Oct. 1978) differences in
concentration between the two types of samples were relatively small, and
nutrient concentrations were approximately the same in the t ’ sample types.
Concentrations found in the winter months (Oct. 78 - Apr. 78),.. however, were
much higher in throughfall than in bulk precipitation (except for I-U’ ).
This likely reflects the fact that the leaves on the trees (pr iLari1y cypress,
Taxodium distichuin ) die in the late fall and minerals are mor easily leached
4—40
-------
Table 4—il . ComparisOn of Major ions, conductivity, and nutrients in bulk precipitation and throughfali
on an annual and a sunmier/winter basis at the Waldo site.
Annual Summer Winter
Bulk Throughfal l Bulk Throughf all Bulk Throughfall
rag/L 24 19 32 18 16 19
(p11 4.62) (p11 4.73) (pH 4.49) (pH 4 74) (pH 4.80) (pH 4.72)
Specific
Conductance MS/cm @ 25C 18.1 29.9 20.7 19.7 15.4 42.3
Na 0.59 1.57 0.51 0.Z1 0.67 2.60
rng/L 0.20 0.59 0.30 0.52 0.09 0.67
mg/L 0.08 0.33 0.06 0.19 0.09 0.50
Ca mg/L 0,30 1.34 0.31 0. 33 0.28 1.96
S0 mg/L 2.15 3.18 2.31 2.88 i.99 3.55
CL mg/L 0.99 3.24 0.69 1.02 1.31 5.94
m1 N mg/L .144 .121 .094 .054 .197
N0 N mg/L .202 .219 .231 .232 .3.70 .203
TON rngIL 0.24 0.34 0.30 0.32 0.17 0.37
SRP g/L .014 .017 .021 .019 .007 .015
.025 .030 .041 .039 .009 .019
-------
from the leaf tissue. Ewel et al. (1976) found increased mineral levels
(Ca, Mg, K, and P) in both throughfall and stemfiow compared to bulk precipi-
tation collected in a north Florida mixed hardwoods forest, and they’ attri—
buted the higher levels to leaching of the plant tissue. Ewel et al. a1so
reported higher levels of the four minerals in throughfall collected in the
winter than summer.
Hendry (1977) found higher levels of major ions including hydrogen and
N and P forms in throughfall than in bulk precipitation collected during 1976—
1977 in a cypress dome north of Gainesville. The higher concentration of
hydrogen ion (lower p11) may have been due to leached Qrganic acids, since the
TOC levels in throughfall were approximately double those of bulk precipit iition.
Crona.n and Schofield (1979) recently reported higher l-I levels in through f .1l
than in bulk precipitation collected on Mount Moosilauke, New Hampshire. The
lowered pH corresponded to increased concentrations of organic anions in
the throughfall.
The throughfall samples collected in this study generally contained
visibly colored organic materials; thus some leaching was occurring, but th e
extent of this, relative to simple washing of accumulated particulates and
absorbed gases from the canopy, is unknown.
D. MINOR MINERALS
1. SILICA
Volume-weighted mean silica (Si0 2 ) concentrations in bulk precipitatio’n
(Figure 4-11) ranged from 14 (Lisbon) to 63 ugh (Ft. Myers). Silica levels
for most of the sites (coastal, northern and central) were about 20 to 30 g/l,
and highest values were recorded for three south Florida sites, Ft.. Myers,
Clewiston and Miami, This pattern is similar to calcium (Figure 4-9A) and
it indicates input of terrigenous substances.
4—42
-------
22
2S
T,.c..,2r V /I Vo1u s—vaLgh ad .sn cooeoeratjon, of S O 2 to bulk pr.cipteacion
in Florida OF l 78 — April 1979.
23
22
31
14
23
26
4—43
-------
2. Fluoride
Detectable levels (> 20 pg/i) of fluoride were found in rainfall samples
from only 4 sites: Bradenton (28 pg/i), Lake Placid (29 pg/i), Lake Alfred
(82 pg/i), and Jasper (SSpg/l). All four sites are located in or near areas
ofphosphat mining and the processing of phosphãte into phosphoric icid for
use in fertilizers. This processing involves-the addition of acid to apitita
rock (Ca 10 (P0 4 ) 6 X 2 ; X = OH or F) with the resultant release of fluoride as
gaseous hydrogen floride. (HF). Tatera (1970) estimated the annual emission
of fluoride to the atmosphere at i0 3 tons by this process. No estimates, how—
ever, are available for particulate (dust) emissions from the mining and pro-
cessing of fluoroapatite.
4—44
-------
Chapter 5.
The Acidity of Rainfall in Florida
The atmosphere has long been known as an important pathway in the
cycling of nutrients and minerals (Junge 1958; Lodge at. al. 1968). Numerous
recent studies also have shown that many pollutants have signifLcant atmospheric
pathways. Acid precipitation is perhaps the most widely known a xample of
this phenomenon, and its occurrence throughout the northeaster-n United States
has been reported widely (e.g. Cogbill & Likens. 1974). The gec.cgraphic pro-
gression of acid rainfall southward and westvard has been descr bed elsewhere
(Liken. 1976; Likens et. al., 1979). However, relatively litt1 . information is
available on the geographic and temporal distribution of acid pr ecipitation in
Florida. Two recent studies demonstrated the occurrence of acid rain at -
Tallahassee (Burton at. al. 1978) and Gainesville (liendry & Bre zortik
1930); rainfall at these locations is about 25 to 30% as acidic as the rain
in severely affected areas of the Northeast. Nevertheless, pu&!.ished data do
not delineate the areas of acid precipitation in Florida; nor dc they indicate
the relative importance of oceanic aerosols and biogenically pro.•’duced sulfur
to Florida rainfall chemistry.
This chapter summarizes results on rainfall acidity (a nd related
parameters) obtained frorn’the ‘statewide precipitation chemistry network des-
cribed in Chapter 4. This chapter describes spatial and temporm 1 trends of
rainfall acidity in the State of Florida, delineates the southea stern boundary
of acid rain in the United States, and discusses the origin and composition of
substances affecting the acidity of Florida precipitation.
EXPERIIIENTAL METHOD S
The Florida Atmospheric Deposition Network (FADN) had 24 precipitation
collectors (20 bulk, 4 wet/dry) located primarily at state agric’ultural and
5—1
-------
NOAA climatological stations, extending from the wester anhand1e of the state
to the southern Keys (see Figure 4—1). Precipitation samples and rainfall
data were gathered at these stations and sent to the University of Florida
for analysis. Sample collection was performed on an event basis at Gaines-
ville, weekly at the vertices of the state (Jay, Jacksonville, Miami), and
biweekly at all other tocations. Rô itine chemical analyses relevant to this
+ + 2+ 2+ -
chapter include major- cations (Na .K , Mg , Ca , N EI 4 +), major anions (Cl
S0 , NO —), pH, and specific conductivity.
Chemical analyses of rainfall samples were done according to
accepted methods (see Appendix 1 for details) using either standard methods
(APRA 1976) or EPA (1976). The pH of rainfall samples was determined as soon
as samples were received in the laboratory, using an Orion Model 801 pa meter
equipped with a Corning #476002 reference electrode and Corning 476O24 pH
e1ectrod calibrated at pH 4.00 and 7.00 with Fisher certified buffer solu-
tions. Major anions were analyzed by automated (AutoAnalyzer) procedures:
sulfate by the rnethylthymol blue method, chloride by ferric thiocyanate, and
nitrate by the copperized—cadmium wire reduction method. Ammonium ion also
was measured by an AutoAnalyzer, using the indophenol method; and other cations
(Na, K, Mg, Ca) were determined by atomic absorption spectrophotometry, using
a Varian Model 1200 spectrophotometer and instrument settings and procedures
recommended by the manufacturer (Varfan 1973).
5—2
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SPATIAL TRKNDS IN ACIDITY AND RELATED PARAMETERS
Concentrations and depositions of the various acid—mediating species
in Florida rainfall, for a number of time periods (i.e. calendars 1978 and
1979, 1978 through 1979, and the intensive year), are summarized in Table
5—i. Tabulated values represent averages for all bulk collectors operative
during the time period of interest. The following discussion will be limited
to the intensive study year Oiay 1978 — April 1979), during which all 24
monitoring sites were in operation.
A. patia1 Distribution of Acidity . Results for the sampling year (May 1973 —
April 1979J show that precipitation is distinctly acidic over most of Florida
(Figure 5—1). With few exceptions, sites north of Lake Okeechobee had annual
(vo1u e—weighted) pH values in the range of 4.6 to 4.8, while those south of
the lake had acidities approaching geochemical neutrality.
Episodes of acid precipitation (pH<5.O) were observed at a -il sites
except Bahia Honda, McArthur Farms, Clewiston and Fort Myers (Figure 5—1).
The first of these sites, far into the Florida Keys, is separated from major
point sources of sulfur and nitrogen oxides by at -ieast 100 km and, in spite
of seasonally variable local automobile traffic, probably approximates back-
ground conditions for the eastern United States.
The high pH. values in bulk precipitation at Fort Myers arid MaArthur
+2 2—.
Farms probably reflect local effects of cement mining (elevated Ca and SO 4 )
and cattle ranching (elevated NH 4 +), respectively. High. sodium and calcium
concentrations in Clewiston rainfall indicate probable contamination by- lake—
spray from eutrophic Lake Okeechobee (pH>8.O). These three sites thus show
evidence of locally—neutralized rainfall acidity.
Precipitation collected at Lake Placid and Corkscrew Swamp is pro—
bably more representative of that occurring over most of South.Florida.. Both.
5—3
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Table 5—i Summary of concentrations arid depositions of 11+ and acid—mediating species in rainfall during
various study periods.
Time Interval N11 4 + Ca2+ excess —SO 4 2 NO 3
Time Interval C* C D C D C D C D
Calendar 1978 11.6 161. 15.0 192. 29.6 360. 34.2 446. 16.3 209.
(4.94)
Calendar 1979 13.5 215. 10.2 154. 31.0 437. 27.9 424. 12.6 189.
(4.87)
Calendar 1978—79 12.4 362. 12.4 339. 28.9 759. 30.2 840. 14.1 387.
(4.91)
Intensive year 11.9 170. 12.7 173. 32.6 430. 31.7 433. 14.1 191.
(May 1978 — April 1979) (4.92)
* Concentrations are averages for all operative sites, units are nieq!L.
Depositions (D) are averaged over all sites, units are EQ/HA.
-------
Figure 5—1. Volume—weighted mean pH of precipitation throughout
Florida, May 1978—April 1979.
5.71
S .GN’5.52/
5.42
Cc ?
5.4 1
5 —5
-------
s: [ tes are pristine, at least 50 km from point sources of SO 2 and O, and well
protected from surface disturbances associated with. agriculture nn.d transporta—
tion. Bulk precipitation pH values for the study year were 4..95 at Lake
Placid and 5.15 at Corkscrew Swamp. In all likelihood, the area receives
even higher levels of acidity in rainfall. Based on three monthts of wet—only
rainfall data frotn Corkscrew Swamp. The volume—weighted teea p of rainfall
probably is less than 5.0 at least this far south in Flo ida.
Highly acidic events (pH<4.O) occurred at several uortI ern sites
during the study period. The most acidic event (pE 3.76) occurrn d at Jay in
August, 1978. Storms with pE 3.93 were collected at Gainesville In September,
1978 and February, 1979. These events were brief and intense, ai id because of
law rainfall amounts, they correspond to average, or even s n. 11 ydrogen ion
loadings.
In northern Florida, a strong pH gradient is apparent aear coastal
areas. Bulk precipitation at Cedar Key (on the Cull Coast, 100 lcm SE of
Gainesville) was only half. as acidic as that at Bronson (50 km i iland); and
rainfall at Marineland (on the Atlantic coast) had less than one—third the
acidity of rainfall at Hastings (15 1 inland). There are sever.d possible
explanations for the coastal neutralization effect: direct tit. ation with
marine aerosols, dilution or displacement of polluted air masses by relative-
ly clean maritime air, and enhanced deposition of terrestrially—derived alka-
line particles. The first mechanisms is of limited sigtiificance- . as a simple
calculation shows. The volume—weighted average concentration o.f sodium at
Marineland was 9.0 mg/L (more than 4x that of any other site). he amount
of sea—salt corresponding to this sodium concentration represent about
2.0 i ieq/L of oceanic bicarbonate, or oniy 30% of the obser red difference in
concentration between Marineland and Hastings. LFor the state as a whole,
5—l i
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the diroct input of sea—bicarbonate to rainfall amounte;u to less tha t G.25
eq/L.
Inspection of Table 5—2 shows that concentrations of cxcess’-sulfate
and nitrate were similar at neighboring coastal and inland sites. Coastal
rainfall thus is not less acidic than inland rainfall for lack of typically
acidic species.
Ammonium and calciun (actually its basic counterions) could be
responsible for the reduction in precipitation acidity at coastal sites.
A onium was present in fairly constant amounts at the two sets of inland—
coastal sites in question (Table 5—2), and indeed concentrations of NH
varied only slightly on a statewide basis (see Chapter 4). Calcium, on the
other hand, was present at significantly higher concentrations at coastal
sites than at the adjacent inland sites. If carbonate was the associated
counter on, it would have been deposited in sufficient quantities to account
for the p11 differences between coastal and inland sites.
Thus it appears that the commonly invoked principal of rainfall
neutralization by sea salt is not of great significance for Florida precipi-
tation chemistry. Noreover, daily land—breeze wind patterns did not signif i—
cantly alter the deposition of acidic species at coastal locations; similar
levels of nitrate and excess—sulfate occurred at the two inland and two
coastal sites (Table 5—2). The distinguishing feature of coastal rainfall
in north Florida Is elevated calcium concentrations, the counterion of which
is presumably responsible for high pE values.
The predominant ionic constituents in Florida precipitation vary.
considerably from location to location; however, the salient geographic trends
are clarified when the sites are organized into northern, southern and coastal
groups (see Figure 5—2). The northern group of 12 precipitation collectors
includes all inland sites’ north of Bradenton; and and SO ’ donninated
5—7
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Table 5—2. Comparison of acid—base chemistry of bulk precipitation at two
coastal—inland pairs of sites in north Florida.
Concentration ( eg/L)
Site 11+ N}1 4 + Ca+ 2 Excess—SO 4 NO 3
Cedar Key 9.1 8.2 25.8 24.4 12.1
(100 in from Gulf)
Bronson 18.2 10.3 15.8 27.7 10.9
(50 km from Gulf)
Marineland 3.0 7.4 82.0 26.8 17.7
(100 in from Atlantic)
Hastings 17.4 7.5 17.0 32.8 11.6
(25 km from Atlantic) _______________________________________________________
-------
I
I I —
40 30 20 0 0 10 20 30 40
40 30 20 0 0 0 20 30 40 —-
i t
200 50 CC 50 0 50 00 50 200
S 0 -
N 0.
HC O
3
2
S
N 03
C1
HCO 3
2 -
so
4
N 03
H C 03
Figure 5—2. Chemistry of precipitation collected at (A) northern, (B)
southern and (c) coastal locations. Units are ueq/L.
IORTHERN
SOUT}4ERN
n:8)
Ca
+
Na
NH4
Cc
I I
-I
NH E
COASTAL
(fl 4)
Ca
Na
NH
5— 9
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precipitation chemistry at these sites, represe Lng 43Z of the cations and
60% of anions, respectively. Compared to the northern sites, precipitation
at southern locations (8 inland sites) exhibited a pronounced decrease in
acidity, accompanied by a large increase in calcium and the appearance of
substantial amounts of bicarbonate. Marine species (Na+, Cl) cont ibatc:d
significantly to the ionic loading at these ites, indicating the tr nsi ion
from a terrestrial—dominated to a maritime—dominated atmosphere in the southern
region of the peninsula. Sulfate levels were about two thirds as high. as in
northern precipitation, but levels of nitrate (derived from NO that is
emitted somewhat isotropically from mobile sources) and ammoniuin were
similar in the two groups of sites. The north—south differential in SO con-
centrations would be much larger if the Bradenton site had not been included
in the southern group. This site had one of the highest (volunie-.weighted)
2—
mean SO 4 concentrations in the state (1.88 mg/L) and apparently is
influenced by large emissions of SO 2 in the Tampa Bay region.
Only at coastal. locations (i.e. sites <5 km from the Atlantic Ocean
or Gulf of Mexico) did sea salt constituents dominate the chemical composition
of precipitation. Nevertheless, these four sites (two northern: Cedar Key
and Marineland, and two southern: Stuart and Bahia Honda) show greater
similarity to their inland counterparts than simple ionic balances suggest.
Deviation from geological neutrality was minimal at these sites, but the
cause of this, as previously mentioned, does not involve marine aerosols
directly. Significant excesses of calcium, sulfate, axnmonium and nitrate were
found at all sites, after subtraction of the sea—salt component.
Ignoring sea—salt species, southern—coastal precipitation resembles
southern—inland precipitation. Northern—coastal rainfall, with, the exception
of calcium and biocarbonata, likewise is similar to northern—inland rainfall.
The exposed soils associated with coastal and southern areas apparently
5—10
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foster entrainment of carbonate species (soil dust, shell fragme nts, lime—
stone particles) in bulk collectors. Considering wet -only’ precipitat:ion,
there is a high resemblance between northern—inland and northerr!i—coas-tal pre -
cipitation. For example, at Cedar Key wet—only samples were more than twice
as acidic as corresponding bulk samples. Similarly, wet—only pr ecipitation
collected lOOm from the ocean on Cape Canaveral had a pH of 4.SEi (B. Madsen,
University of Central Florida, pars. con ri., 1979), which is ver-y close to
our value of 4.60 for Orlando, over 50 km inland.
B. Spatial Trends in Deposition of Acidity .
Deposition of acidity via bulk precipitatIon in. FLori a (Figure 5—3)
ranged from 497 eq/h.a. at Jay to 2Ll eq/ha at MacArthur Farms, a nd averaged
182 eq/ha statewide. The extreme deposition at Jay reflects a combination of
Inter sity and volume factors. Jay had the most acid, bulk precipitation (weighted
mean pH-4. 62) in the network, as wall as the heaviest precipftat:ian (206 cm),
during the study year.
At McArthur Farms, the situation was completely revers. ed. Rainfall
pH was near geochemical neutrality, and rainfall amount, corraspondingly, was
the lowest in the state.
Loadings of at the northern locations (n=’1 4 ) were :more than
three times those of the southern locations (n l0), 272 eQ ha amd 82 eq/ha,
respectively. This latter value is only 2.6 times greater than would be
contributed by the average annual southern rainfall at a pH of L6.
lu general, loadings mirror the concentration distrib tion over the
state; however, as in the case of the extremes previously discu ssed, there
is some perturbation due to interaction between the concentratic n field and
the rainfall field. This effect will be explored further in a PLater section.
5—11
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Figure 5—3. Acidity deposition (eq H 7ha) throughout Florida, for the
period May 1978—April 1979.
2$
6$
-. 38
I
5-12
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C. Spatial Trends in Sulfate Concentrations .
Sulfur occurs in precipitation almost exclusively as sulfate ion
(SO 4 ). This fact is attributable to the high. levels of SO 4 aerosols in
the atmosphere, relative to other sulfur species, as well as the fact that
most other forms of sulfur are rapidly oxidized to SO 4 in aqueous So 1t.L—
tion.
Sulfate can be partitioned- into two classes on the basis of origin:
sea — SO 4 and excess — SO 4 . The first of these refers to the sulfate
present as a component of sea—salt, and is determined by the following
expression; (SO4 se . 0.25 x(Nat); where all Na in precipitation is
assumed to be of oceanic origin.
Excess — Sulfate ,s that sulfate having any source other than the
ocean (i.e. total — S0 4 minus sea — SO 4 ). On a global scale, the major
precursors of excess — SO 4 —’ are anthropogenic SO 2 emissions and biogenic
emissions, consisting primarily of R 2 S, DMS and DMDS. Currently, these
two sources of sulfur are thought to contribute about equally to the world
sulfur cycle; however, the former is usually dominant in areas of high popula-
tion density and industrial activity. The relativ-e importance of these t ri
sources on Florida precipitation will be treated in a later section..
A further distinction, between excess — SO 4 and sea — SO4 -- lies
in the fact that only excess — SO 4 is an acififying species itt precipitatioti .
Numerous rainfall studies (Coghill & Likens, 1974; Cranat, 1972) have shown
that excess — SO 4 is the dominant mineral acid in acid rain (p 1 1<5. 6 ), Sea —
so , on the other hand, is not associated with H+, due to the high pH of
the ocean. Based on the Ionic composition of seawater, sea — S0 is pre-
dominantly associated with Na+ and (to a lesser extent) Mg 2 . The spatial
5-13
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distribution of excess — S0 4 and sea — SO in Florida precipitation there-
fore merits separate discussion.
Concentrations of excess — sulfate in the state varied considerably
from north to south (Figure 5—4a). In northern Florida, concentrations ranged
froth 1.17 mg/L (átCedar Key) to 2.34 mg/L (at Jasper), and averaged 1.72 mg!L.
Southern values, except for Bradenton ( whichis effected by Tampa area emis-
sions), were distinctly lower, averaging only 1.14 mg/L. The three most pris-
tine southern sites, Bahia Honda, Corkscrew Swamp, and Stuart, had concentrations
of excess — S0 4 below one mg/L: 0.89, 0.96 and 0.98 mg/L, respectively.
Thus, a factor of two differences occurred in the distribution of potent a11y
acidifying excess — sulfate concentrations around the state.
Sea—salt sulfur is a less significant component of Florida rainfall
chemistry than might be inferred from the peninsular nature of Florida and its
extensive coastline. As shown in Figure 5—4 , sea — S04 concentrations
were small everywhere in the state, except for the coastal periphery. Con-
centrations ranged from 0.09 mg/L, at Tallahassee and Jay, to 2.25 mg/L,
at Marinelartd, and averaged 0.27 rng/L (or 187. of excess — SO 4 , statewide).
The average sea — S0 4 concentration for the four coastal site.s
(Marineland, Bahia Honda, Stuart, Cedar Key) was 0.95 mg/L, and only Marine—
land, had higher sea — SO4! than excess — SO 4 . Inland sites, in contrast,
averaged 0.11 rag/L sea — SO 4 -, or only 7% of excess — SO 4 concentrations
The rapid disappearance of sea — SO 4 in rainfall with distance from the
coast implies that oceanic aerosol particles are relatively large. The
atmospheric lifetime of such aerosols thus is short, as a result of rapid
gravitational settling.
5—14
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Figure 5—4. Volume—weighted mean concentration of (A) excess—SO and
(B) sea—SOt, for the intenaive study year. Units are mg/L. (These
figures to be reduced and displayed on same page).
S
1.13
1.06
a
I,’
a
0.89
/
5—15
-------
26
0.09 0.19
6
r,&.
0.57
a
5—16
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D. atia1 Trends in Sulfur Deposition .
Deposition of sulfur in bulk precipitation at the 24 sites during
the 12—month study period ranged from 12.1 kg/ha at Jay to 4.2 kg/ha at
Corkscrew Swamp Sanctuary. As in the previous section on concentrations,
it Is meaningful to decompose the total—sulfur deposition into its sea—
sulfur and-exc ss—sulfurcomponents,-andto stratify the siteson the basis
of northern, southern, and coastal locations.
Annual deposition of excess—sulfur (Figure 5a) thus was high at
northern sites (mean—7.8 kg/ha), intermediate at southern sites (raean .5.2 kg/ha),
and lowest at coastal sites (tnean—4.4 kg/ha). The order is reversed for
sea—sulfur (Figure55b), where coastal sites, has the highest input, followed
by southern, and then northern locations.
Excess—sulfur dominates sulfur deposition at all locations except
Marineland, where large quantities of sea—salt are deposited near the tur-
bulent coast. The ratio of excess—sulfur to sea—sulfur deposition at this
site was 0.57, whereas that at inland Jay was 18.3. The corresponding ratio for
the entire state was 5.8.
Annual deposition of excess—sulfur across the extrem northern
portion of the state (Jacksonville, Jasper, Tallahassee, Chipley, Jay)
averaged 9.5 kg/ha, which is similar to the value of about 10 kg/ha reported
by Whelpdale & Galloway (1980) f or the entire eastern United States.
Excess—sulfur deposition is considerably lower only a short distance
( “50 km) south, where the Cedar Key—Bronson—E{astings--Marineland transect
(See Figure 4—1) exhibited an average annual deposition of 5.8 kg/ha, within
a relatively narrow range (5.35—6.41 kg/ha).
Still further south, excess—sulfur deposition rose substantially.
At the Bradenton, Lisbon and Lake Alfred sites annual deposition averaged 8.5
kg/ha. This return to a higher rate of sulfur deposition may involve local
5—17
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4
Figure 5—5. Annual deposition (kg/ha) of (A) excess—S and (B) sea—S
across Florida. (These figures to be reduced and shown on
same page)
A
a
.1
a a.. a
5—18
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B
rIG. &-S
0.68
0.44
0.39
9i
0.75
0.56
0.65
67
0.72
0.50 [ )
I.2
B
/
p 1
.-.,. a.03
5—19
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surface activities. However, a more likely source of the exces .s — sulfur
increment is the Tampa area,, where more than 20% of statewide sulfur emis-
sions originates.
The undisturbed sites located south of Bradenton (La k. Placid,
MacArthur, Stuart, Miami Bahia Honda) had. much lower annual d positioa rates
of excess sulfur. The average for this group of sites was onl:,v 4.1 kg/ha, and
values ranged from 3.2 kg/ha at Bahia Honda to 4.8 kg/ha at Lake Placid.
Considering the state as a whole’ analysis of the va ious groups
of monitoring stations suggests a general trend of decreasing e xcess—su1face
deposition along the north—south axis. Super—imposed on this r attern is
a region, within the central portion of the state, which is infrluenced by
Tampa area emissions.
E. Acid—Mediating Species in Florida PrecIpitation .
Ionic balances and Granat—type calculations indicate that sulfuric
and nitric acids account for the strong acidity of north Florici La rainfall.
Sulfate contributes about 2.0—2.5x H+ as nitrate while chloride is highly
associated with sodium and other sea—salt cations and does not influence
acidity. Total acidity titrations of Gainesville precipitationi (Hendry and
Bre n k 1980) demonstrated that samples with ambient pH 1eveI below 5.0
are dominated by strong acid species. The free acidity in suchi samples
averaged about 80% of the total acidity, comparable to values reported
for several northeastern locations.. As notedby Galloway et alJ.. (1976), weak
acids encountered during a titration dissociate well above the initial pH
of the rain sample, and thus do not contribute to the observed pH of rainfall.
+ 2-
Regression of H against excess—SO 4 for 52 GainesviLle wet—only rain
samples collected from May 1978 — April 1979 gave a high r 2 (G_.70). A
similar analysis using volume—weighted annual mean values for aill 24 sites
5-20
-------
resulted in a much lower r 2 (0.25). Multiple regressions of versus
excess—SOt and other parameters taken one at a time did not improve the
correlation, until Ca 2 + was added to the expression. Regression of
2- 2+ + 2-
against xs—S0 4 and xs—Ca yielded the equation: H = 6.l O.54 (xs--S0, )
—0.33 (xs—Ca ), R 2 0.75. Similar results were obtained earlier for
Gainesville wet—only precipitati&i by Hendry and Brezonik (1980). Arrunonium
and nitrate do not contribute to the explanatiOn of H+ levels significantly
because they are distributed more or less isotropically in precipitation
over the state (see Chapter 4). On the other hand, excess—sulfate and calcium
vary considerably from site to site statewide; thus these two species and
the degree of neutralization between them determine the pH of Florida pre-
cipitation. The endpoint of such an acid—base titration has been attained
over most of Florida; i.e. the natural constituents (buffers) tending to resist
change in precipitation acidity appear to have been overcome, especially in the
northern part of the state.
F. The Influence of Rainfall Variability on Network Results .
Up to this point, concentrations and loadings of species have been
presented, and geographic trends have been discussed, without reference to the
variability of statewide precipitation. Since atmospheric deposition is a
function of both concentration and rainfall amount, the examination of loading
patterns necessarily requires consideration of rainfall patterns, as well.
The purpose of this section is t d termine the influence of spatially vari-
able rainfall on the chemistry of the precipitation network, and to investigate
the manner in which temporally variable rainfall (i.e. deviation from annual
norms) effects precipitation chemistry at individual sites.
The first of these topics can be addressed by considering the
amount of rain collected at the 24 monitoring stations during the study period.
5—21
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As show-n in Figure , the 12—month rainfall was uniform over the central por—
tion of the state, relatively high in the Panhandle, and relatively low in t he
southern extremes. The average rainfall for the 14 northern and 10 southern
sites was 140 an and 127 an, respectively. This 9% difference in rainfall
between the two groups of sites is- small relative to the concentrationfdepos-i--
tion differentials observed for many species. Thus, it can be inferred that
rainfall amount is not a major factor contributing to the disparate results
for northern and southern Florida.
The relationship between statewide deposition values and rainfall
amounts was further tested by regression of annual loadings against weighted—
mean concentrations and yearly precipitation at all 24 sites. Results of
this analysis show that concentration is the dominant variable In the deposi-
tion of all major anions and cations (including the various nutrient forms).
The above findings suggest the regional concentration/deposition
pattern is real, and not an artifact of rainfall variability; however, there
are a number of potential difficulties with the method of spatial averaging.
Most important is the possibility that systematic effects are incorporated,
rather than eliminated, by such an averaging process. For example, this effe nt
could occur as the result of a significant departure from the average annual
rainfall over an entire region (e.g. North Florida vs. South Florida). When
only a single year of chemical data is available, this possibility is more
serious, because there is no way to smooth results by averaging several yearl:y
values that represent a range in annual precipitation.
Insight into the reasonableness of the data for the individual
monitoring sites can be obtained by comparing observed rainfall with long—
term annual averages. The ratio of observed to average precipitation can
5—22
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Figure 5—6.
A. 12 month rainfall totals (cth) for stations in the Florida
Atmospheric DepositIon Study, May 1978—June 1979. (These
figures to be reduced and shown on same page)
B. Above data normalized to 10—year average (1969—1978) rain-
fall at identical, or nearly, locations.
A
139
145
139 136
122
136
133
156
108
135
108
I
1
5—23
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13.
- -. 0.87
5—24
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be used to infer the true (long term) average concentrations ar id average
depositions, assuming that two limiting cases bound the re1ati nship between
rainfall chemistry and rainfall amount.
In the first case, abnormal rainfall is considered t be a function
of the size of the average event. A wet year would have largerr events than
usual; hence solute concentrations would tend to be low (compa red to the
average year). The converse would be true for a dry year. Th IS relationship
follows from our experience at Gainesville, where the concentr:ations of
H+, excess—SO 4 2 and NO 3 - were found to obey the- following exprression:
[ solute] a
where rain is the size of an event, and b is in the range 055 to 0 65 •
In the other limiting case, high or low annual rainf all can be
construed as simply a function of event frequency. For Gaiueswtlle precipitation,
no apparent relationship has been found between H , SO 4 2 , NH 4 -3-, NO 3 — concentra-
tions and the period of time between events. Rainfall concent:rations, then,
will be taken as invariant with respect to event frequency.
By combining these limiting assumptions, a range of tarpected con-
centration/deposition values can be estimated for the individu al sites, as a
function of annual precipitation. For years with below averag rainfall (i.e.
R/R (R/ThT° 6 ° (R/ ) 040 > DID < (R/ ), 1 ” 00 and for p.aars with above
average rainfall (i.e. R/R>l.00) we have:
C/C < 1.00; (R/RY”°°> DID > (R/R) 04
Referring to Figure 6]., it is apparent, on the basis of rainfall
alone, that a number of sites may have experienced somewhat unt.isual rainfall
chemistry during the study period. Jay, for example, was extr€ nely wet,
5—25
-------
indicating that long—term average concentrations might be higher by as much as
15%, and deposition values lower by 10—20%. For all remaining northern sites,
correction factors amount to less than 10%, and so there is little real ad-
vantage to their use.
The situation is different for the southern sites as rainfall
was far from average in this part of the state during l978—1979. Seven of
the ten sites received significantly less than average rainfall, while
two received somewhat more than average. Clewiston and Miami were the driest
sites, with just under 75% of the normal annual rain. For these extreme
locations, representative concentration values may be as low as 73% of
those reported, while deposition values may be 13—35% higher. Correction
factors for the other sites are lower than this, but are still significant
in most cases.
The mean northern and southern rainfall amounts were 99% and 89%, res-
pectively, of the long—term average. Since the anomalous value for the
southern sites raises the possibility that rainfall was systematically in-
volved in spatial trends, corrected loadings were calculated for all sites,
using excess—SO 4 2 as an example species. Resultant deposition was essentially
unchanged for the north Florida group, but deposition may have been up to
13% higher for the south Florida group. Despite these corrections, the
excess—SO 4 2 deposition remained statistically higher (p
-------
minor influence on the overall geographic trends in concentration and deposition.
Second, the 1978—79 observations deviate in certain instances from expec.tatiJn;
in a general sense, however, they are representative (especially for norther- n
Florida) of what might be observed during a year of normal (average) precipi—
tation.
G. Variations in Precipitation Chemistry within the Vicinity of Gainesville .
The statewide-precipitation network described above has provided
useful information on meso—scale trends in precipitation chemistry, but by
itself it does not address the question of local (micro—scale) variability i
precipitation chemistry. In addition, the statewide network had no paired
stations to compare urban and non—urban rainfall quality for a given area (i.e.
a city and its surrounding’ countryside), although such sites are of interes;t
to obtain information on the geographic extent of urban influence on precipita—
tion chercistry. Consequently, a mini—network of precipitation collectors was
established, and sampled on a weekly basis during the period July—September,
1979. This consisted.. of a line of three bulk rainfall collectors, spaced
at approximately 3 km intervals and extending due south from Gainesville to
Paynes Prairie, the dry bed of the former and ephemeral Alachua Lake.
With access controlled by the Florida Department of Natural
Resources and no inhabitants on the prairie, Paynes Prairie is an ideal
setting for the collection of rural precipitation. The collectors were
located at least 2 km from the nearest well—traveled road and from any agric’ .il—
tural activity.
The reference collectors for this study were a wet/dry and a
bulk sampler at the University of Florida campus in southwest Gainesville,
5—27
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a semi—urban site with considerable automobile traffic within a few hundred
meters in any direction and a small (‘ 5O car) parking lot within 10 in of the
collectors. The campus sewage treatment plant is 250 in north of the collectors.
The only significant point sources of sulfur oxides in the area are 3 km due
east and 15 km northwest of campus... Rainlall sampling at this site was per—
formed on an event basis, as described earlier.
The 10—week volume—weighted mean concentrations of H+, N4, Ca+ 2 ,
S0 4 2 and NO 3 for the four sites (Table 5—3) show that the three Paynes
Prairie rain collectors yielded similar chemical data. For the rural stations,
exhibited the broadest concentration range (3.9 peq/L), corresponding
to a pH difference of 0.06 units, but this range is only slightly larger
than the inherent uncertainty in pH measurements ( ‘ O.03 units). Concentrations
of the remaining major ions were within their respective analytical uncertain-
ties, with the exception of N]-(, which ranged from 3.7 ieq/L at site 2 to
6.3 ,ieq/L at site 1.
There is no evidence of contamination or of local sources for
any of the species analyzed at the Paynes Prairie sites. Rainfall amount
was the only parameter exhibiting any sort of a trend, (a monotonic decrease
with distance from Gainesville), but there was no correlation of this trend
with rainfall chemistry.
Comparison of the rural Paynes Prairie results-with those for
Gainesville (semi—urban) bulk precipitation show that the latter environment
appreciably disturbs the bulk deposition of numerous species. This is demon—
2+ 2-
strated by substantial increased in Ca and SO 4 levels, and a reduction
of acidity at the Gainesville site. Calcium (actually its counter—ion) is
clearly indicated as the neutralizing species of the semi—urban bulk precipita-
tion, i.e. it is the only cation with a sufficient concentration gradient
5-28
-------
Table 5—3. Comparison of acidic arid basic species in Gainesville and Paynes
Prairie precipitation, collected 7/12 — 10/1/79. Nu !thcrs in paren-
theses correspond to distances, in kilometers, from Gainesville
site.
Concentration (meg/L)
Location Rainfall pH fl+ + Ca+ 2 SO 4 NO 3
(cm)
Gainesville wet 41.9 4.49 32.3 6.7 7.3 25.2 14.4
Gainesville bulk 41.9 4.65 22.4 7.1 17.6 32,? 15.6
Paynes Prairie #1 39.8 4.57 26.8 6.3 5.0 24. 11.9
(4)
Puyne Prairie #2 38.3 4.57 26.8 3.7 6.1 26.7 13.1
(7)
Pa nes Prairie //3 36.8 4.51 30.7 5.4 5.9 25.6 13.9
(10)
-------
between the Gainesville and Paynes Prairie sites. The correlattion of hIgh
2+
SO and Ca in Gainesville bulk precipitation suggests that, in the absence
of a strong SO 2 or particulate sulfate concentration gradient ttetween Gainesv.ille
and Paynes Prairie, high. bulk precipitation so , [ valves in towni may result from
scavenging of SO 2 by locally higK levels of particulate Cafl.
The nitrogen species NR and NO appear to be sliglkt.ly influenced
by Gainesville, the former probably by the nearby sewage treat:i nt plant, and
the latter perhaps, by automobile traffic in the urban area. iEbwever, the
magnitude of the differences is small, and their sign.ificante ;i.s uncertain.
For the most part, there is a high degree of similarity betwee a the Gainesville
wet— only and the Paynes Prairies bulk precipitation., suggestiii g that the dryfall
component at the rural sites is less significant than that i town.
Gainesville wet—only precipitation did have higher c oncentrations
of several species than the Payries Prairie sites, however (Tab le 5—3). was
significantly higher at the semi—urban site whil’e CaZ+ and NO 3 were marginally
higher. These results underscore the fact that vet collectors also are
affected by local perturbations of the enviroruuent_ Comparing, the Gainesville
wet—only and bulk results, it is clear that the wetfdry collector is capable
of filtering out the greater part of local influences-
o conclusions can be derived from the utini—netwoç J. First,
the impact of the urban areas on precipitation chemistry is de:pendent on the
type of sampling (wet/dry or bulk) perforried. Relative to the University
of Plorida site, its proximity to Gainesville exerts an itaporOnt influence
on bulk precipitation but only a minor influence on wet—only precipitation.
Second, the perturbations of rainfall chemistry caused by Gairt esvi1le are
of limited spatial extent. At the nearest Paynes Prairie site (4 km from
5-30
-------
,Ihe Gainesville site), the impact of Gainesville is not discernible from
the random variability of the measured parameters. Atmospheric contaminants
generated within Gainesville thus blend smoothly into the regional back-
ground, either by dispersion or deposition mechanisms, over a scale length
of less than 4 km.
WET, BULK, AND DRY DEPOSITION OF ACIDIC AND BASIC SPECIES
A. Comparison of Wet and Bulk Precipitation Chemistry .
Wet—only precipitation was more acidic than bulk precipitation
throughfout the state; pH values of wet rainfall were 0.2—0.4 units lower
than those of nearby bulk samples (Figure 5—7).
The relationship of rainfall acidity to rainfall amounts indicates
some differences between the two methods of collection. For wet—only
samples (Figure a), hydrogen ion concentration decayed rapidly with rain-
fall amount, and leveled off, in the vicinity of 10—20 .ieq/L for large
(>2 cm) events. The plot for bulk events differs in that the vertical limb
of the previous relationship is absent and many small storms were almost
completely neutralized. Concentrations of H+ in bulk precipitation tend
to increase with the amount of rain collected up to about 2 cm of rainfall,
then level off in the same manner as the wet samples. Apparently, the
content of the initial rainfall (1—2 cm) is neutralized by an alkaline component
of dryfall, most likely carbonate.
Comparison of wet deposition with bulk (wet plus dry) deposition
at five sites (Table 5—4) shows that nitrate, sulfate and ammonium are asso-
ciated with an acidic wet phase, while calcium is predominantly a component
of dry deposition. The anion associated with calcium thus neutralizes rain-
fall in bulk collectors and is largely responsible for differences observed
between neighboring wet and bulk samplers (Figure 5—7). At Gainesville,
the average precipitation event (2.50 cm of rain) deposited 600 and 450 ueq
5—31
-------
4.75/4.63
Figure 5—7. Comparison of annual weighted—mean pH of bulk (above slash)
and wet—only (below slash) precipitation. Locations are,
from north to south: Gainesville, Cedar Key, Apopka, Belle
Glade.
4.80/4.60
5.6 /5.2 .1
I
5—32
-------
20 A
0 •
100
0
0
80
H 4
(ueq/L)
0
60
00
0
0 0
a. 0
40
0
0 a
0
I 0
0 0
20 • ••
0 0 • • •
0 I I 0
• •0
. 0
0
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
RA INF. L L( cm)
00 B
80
H ’
(ueq/L)
0
60
0
40
o is,
o a
0 0
S
20
0 0 0
0 • •
0 5
S C,
0 0 • a
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
Røint ll (cm)
Figure 5—8. Relationship of concentration to rainfall amount for winter
() and summer (o) wet—only events (A) and bulk events (B) col-
lected at Gainesville.
-------
Table 5—4.
Relative loadings in et versus total (wet + dry) precipitation. Values
correspond to 7 deposition from t—only precipitation.
Locat:ion
+
H
+
Na
+
K
+2
Ca
+2
Hg
NH 4 —N
N0 3 —N
Excess
S0 4
Cl
Gainesville
100
59
59
31
40
88
68
74
61
(semi—urban)
.
Orlando
100
57
55
52
45
73
74
•
77
61
(Agricultural)
Belle Glade
100
59
60
40
45
85
•
72
75
60
(Agricultural)
Cedar Key
100
81
72
54
69
82
62
8t
81
(Gulf Coast)
Cape Canaveral
100
18
18
24
19
71
61
71
17
(Atlantic Coast)
-------
H+11n 2 in wet and bulk collectàrs, respectively. The differenc’ e is almost
exactly balanced by the 147 . eq/m 2 of bicarbonate deposited (o n the basis
of cation excess) in statewide dryf all samples between collect.: ions.
B. Dry Deposition of Acidic and Basic Species .
• Dry deposition is well knot n as an important uechan ism of nutrient
and mineral imput to ecosystems (see Chapter 4). The term ‘dr—y depositionr
embraces a variety of interaction mechanisms between surfaces (sinks) of
variable resistance to deposition, aerosol particles over a br oad size
range and gaseous species of widely desparate re. ictivities. D ;ry deposition
involves two distinct physical processes: eddy and gravitatio caal deposition,
The first of these addresses the transport of gases and sub—tni ron particles
to receptor surfaces via turbulent eddies. Gravitational depo .sition is simply
the settling of relatively large (> 2 rn) particles due to graviLtational
forces that impart high settling velocities to these particles..
The purpose of this section is twofold: 1) to exan,iLne the
significance of dry deposition versus wet deposition for specie s related to
acid precipitation, and 2) to determine the influence of seasorri on dry
deposition rates.
Annual loading rates of alkalinity, excess—SO 4 2 , tO, Ca 2 , N H
to dryfall collectors at five locations within the state are st uiiarized in
Table 5—5. Alkalinity was inferred by ionic balance and presurr ably reflects
carbonate species. This parameter represents an appreciable fr-action of the
total dryfall loading at all sites. eposition rates of CaZ+, excess—SO 4 2 ,
and alkalinity follow t e pattern Belle Glade > Gainesville > C edar Key Apopka
area, though agricultural activity ( ugarcane, winter vegetabi es), where
large quantities of particulate matter are injected into the atjr sphere. The
Apopka area, though agricultural, is planted largely to citrus,. vhich requires
substantially less tillage than do the crops grown at Belle Gla :de.
5—35
-------
Table 5—5. Annual dry deposition of acid—mediating species at 4 Florida sites.
Deposition (EQ/HA )
Location t½lka linlty* Ca 2 + NH 4 + SO 4 2 NO 3
Gainesville 173. 315. 19.3 159. 57.1
Orlando 105. 152. 29.1 104. 49.2
Cedar Key 90. 182. 18.5 84.2 72.3
Belle Glade 741. 868. 21.2 153. 872
* Alkalinity inferred from net excess of analyzed anions. Valve for Belle Gaide is proba1 y several—fold
over—estimate, due to high deposition of soil organic matter (associated with Ca 2 +) at thi8 site.
-------
Inorganic nitrogen species are relatively minor components of
dryf all. Except for Belle Glade, NHI, and NO 3 were deposited more or less
uniformly throughout the state, suggesting that the atmospheric sources of
NH and NO are either quite diffuse or remote from the collection sites.
3 x
The relative importance- of wet and dry deposition for- species
that affect rainfall acidity is summarized in Table 5—4. Hydrogen ion,
excess—SO 4 2 , NO 3 and NH are highly associated with an acidic wet phase.
Being gases, or sub—micron aerosols, these species have insignificant settli ng
velocities and small dry deposition rates. The nature of the collector
buckets also may affect dry depositibn of these species; this topic is
addressed later.
The terrestrial species Ca 2 + is deposited primarily through dry
processes. Apparently Ca 2 + occurs in the atmosphere in supra—micron partic1 s
which have significant settling velocities. Furthermore, the dryfall bucket
is near ( ‘ l m) to the source of these species (the soil), and it probably is
influenced by steep concentration gradients near the surface.
Dry deposition rates for the major inorganic species were generally
higher during winter than summer (Table 5—6). The striking exception to
this is NH, of which two—thirds is deposited during the summer. This pre-
sumably reflects enhanced evolution of N E 3 from soils during the warm months...
The seasonally disparate deposition rates for most species at Belle Glade
are the result of local agricultural practices. During the winter and early
spring months (primarily January to April), burning of sugarcane fields resu Lts
in suspension of large amounts of particulate matter in the atmosphere. The
deposition rates of soil species are enhanced directly by this process. Cropb
burning has recently been shown to release most of the sulfur contained in
vegtative tissue (J. Ewel, Univ. Fla. pers. comm. 1979), and deposition of
5—37
-------
rable 5—6. Comparison of winter (Nov—Apr) and summer (May—Oct) dry deposition of
major ionic species.
Seasonal deposition (kg/ha) —.
Location Na+ Ca+ 2 Mg+ 2 N1i —N N0 3 —N SO 4 Cl
Gainesville
Winter 1.35 0.27 3.46 0.36 0.09 0.42 3.82 2.53
Summer 0.95 0.27 2.84 0.46 0.18 0.38 3.82 2,01
Orlando
Winter 1.83 0.64 1.97 0.35 0.21 0.36 2.84 2,9:1,
Summer 1.67 0. 3 1.06 0.25 0.19 0.33 2.14 2, 4
Cedar Key
Winter 2.84 0.29 2.04 0.46 0.09 0.53 2.18 5,Q
Summer 1.79 0.27 1.59 0.29 0.16 0.48 1.83 3.26
Belle Glade
Winter 2.80 1.15 9.70 0.91 0,08 0.60 4.68 5,90
Summer 1.65 0.71 7.65 0.49 0.22 0.62 2.67 3.57
-------
SO 4 2 also may be enhanced by this practice, first by the release of SO 2 and
second by the attachment of SO 2 to, particulates generated in high concentra-
tions by the burning process.
High wintertime deposition rates for Ca+ 2 , at the other sites, may
be the result of seasonally high winds. For sea—salt. species, this seasonal
trend results in increased atmospheric injection as well as rapid transport
inland (See Chapter 4, Table 4—9). Soil species such as Ca 2 also should
have augmented suspension and deposition rates due to seasonally high surface
turbulence.
Frequency of precipitation may also influence dry deposition rates.
All other factors being equal, the more often the atmosphere is cleansed by
rain, the lower the time—averaged concentration of contaminants. Precipita-
tion events occur approximately once a week during the winter, in Florida,
and two to three times a week during the summer. Therefore the levels of
various pollutants, particularly those preferentially scavenged by washout
processes (eg. Ca+ 2 ), should be lower during the summer. Insufficient sea—
soani data on atmospheric concentrations are available, as yet, to test the
validity of this concept.
TE iPORAL PATTERNS IN PRECIPITATION ACIDITY
A. Seasonal Trends .
Summer rains (May—Oct) are more acidic (by 0.2—0.3 pH units) than
winter rains (Nov—Apr) throughout the state (Figure 5—9). In summer, the pH
4.7 isopleth encompasses all of the panhandle and about half of the peninsular
portion of the state, and there is no geo—chemically neutral rain (pH>5.6)
anywhere in the state. During the winter, the pH 4.7 isopleth is displaced
to the north of the state and is replaced by a pH 5.0 contour. Geochetnically
neutral rain occurs in large areas of the southern peninsula during this
season.
5—39
-------
Figure .-9.
Volume—weighted mean concentration for summer (May—Oct) ap yint r
(Nov—Apr) across Florida. For clarity, not all sites are depicted;
statewide means (all sites) are shown in legend.
or
ww
30
LEGEND SCALE
+
H,
J .Leq/L
a
-------
The seasonal and spatial dichotomies of Florida precipitation
are underscored in Figure 5—10, which illustrates monthly volume—weighted
mean concentrations of }f’, xs—S0 4 2 ’, and NO 3 for the northern (n14) and
southern (n—l0) sites during the 1978—79 one—year period. As previously
stated, was higher in northern sites than southern sites, and was highest
in the north during the summer months. Southern precipitation varied less
in concentration from month to month, but was clearly higher in summer
than in winter.
In the north, excess SO 4 2 and NO 3 exhibited similar seasonal
patterns. Excess S0 4 2 levels were consistently high during summer (May—Oct)
and low during winter (Nov—Apr). The lowest concentrations occurred, as with
during the relatively dry months of transition between convective and
frontal storm activity (November, December and April).
Nitrate concentrations generally adhered to the pattern of high
summer and low winter values. During the dry months of November and April,
however, levels of N0 were elevated rather than reduced. The contrasting
behavior of excess—S0 4 2 and N0 3 during these 2 months reflects the fact
that dryf all represents a greater proportion of NO 3 deposition (33%) than
of excess SO deposition (24%).
There were no clearly defined seasonality of excess SO and
NO 3 concentrations in south Florida precipitation. The transition months
exhibited the lowest values for these two ions, but the average winter con-
centration did not differ significantly from the average summer concentrations.
Both excess—SO 4 2 and N0 3 were as high (or higher) in southern—
winter precipitation as in northern—winter precipitation, a reversal of the
5—41
-------
20 •----- •‘•
‘ ___\
-J
C.)
4-
60
-i
a-
40
0
C l,
20
C ’-)
C,,
IJJ
0
><
0
30
20
-J
—s-
0
C)
-l0
r()
0
,
, \
/ “
i
-------
summer—time relationship between the two groups of sites. Frontal precIpita-
tion occurs in Florida approximately once a week during winter, and these wide-
spread systems of rainfall probably confer a degree of homogeneity to winter-
time precipitation chemistry. Additionally, southern areas receive less
rainfall than northern areas during winter (because the cold fronts weaken
as they p ogress southward).
Despite the seasonal concentration variations described above,
the deposition of H+, ezcess—SO and NO 3 was considerably higher at both
northern and southern location during summer than winter(Table 5—7). In the
north, wintertime depositions of the, ions were 29—34% of the annual total,
and winter rains accounted for 43% of the yearly rainfall. The inequality
of winter/summer deposition thus was a function of both seasonal precipitation
and concentration differential at northern sites. In south Florida, winter
time deposition of H , excess—S0 4 2 and NO 3 were 25—32% of the annual
total; these values are similar to the seasonal rainfall disparity (winter
rainfall was 28% of annual total).
B. Sequential Sampling within Rainfall Events .
In an effort to elucidate the infrastructure of winter and surrmier
events, several frontal and convectional storms were sampled sequentially on
a wet—only basis by uncovering and rinsing a funnel on the roof of Black Hall
immediately prior to the onset of rainfall. Subsamples (2 L), corresponding
to 0.05 cm of precipitation, were collected for the first 1.0 cm of each
event; thereafter, 50 ml . samples were taken until cessation of rainfall.
+ + + +2 +2 + -
Each fraction was analyzed for H , Na , K , Mg , Ca , NR , SO 4 NO 3
Cl and conductivity.
Results of the chemical analyses indicate that temporal features
of both convectional and frontal events can be complex. H+ concentration,
for. example, did not necessarily decrease during the course of an event,
-------
Table 5—7. Seasonal deposition of acidic and basic species in bulk precipitation
at northern, southern and coastal Florida locations.
Deposition (eq/ha)
+ + +2
Location Season Rainfall H NH 4 Ca Excess—SO 4 NO 3
(cm)
Northern Winter 59.9 81 58 161 162 62
(n = 12)
Summer 80.0 187 139 159 361 1)53
Annual 140 269 197 320 523 215
Ijfl
Southern Winter 37.8 17 33 192 88 443
(n = 8)
Summer 88.7 67 105 280 253
Annual 126 84 138 472 341 176
Coastal
(n 4) Winter 51.5 30 26 281 113 64
Summer 84.1 40 87 300 198 108
Annual 136 70 113 581 311. 172
-------
as might be expected from the classical “washout cu-ve exhibjtted 2n Figure
5— a. Rather, and other ions (generalized in the figure by conductivity)
were observed to increase, decrease or oscillate rapidly withi .n events
(Figure 5—al). No clear—cut differences between frontal and ecinvectional
storm types are evident, based on the sampling performed to da re.
÷ ÷ + +2
During most of the events,, the major ions CR N H 6 , Na , Ca
SO 4 , NO 3 , Cl) generally behaved coherently, i.e. concentrat ions rose
and fell in harmony with variations in conductivity. Regressicon analysis,
however, showed that correlations among certain ions consisteartly were good,
while others were poor. Na+, excess—S0 4 , NO 3 and NR 4 +, for . ample,
correlated well with H ; the soil—derived elements (Ca+Z, gg+Z K+),
the other hand, correlated poorly with H+.
The above findings indicate that different processe (i.e. rainout
and washout) may affect those species apparently associated wi ih and those
not associated with during an event.
For example, Ca 2 + is derived from the ground in the form of
particles with large mass—median diameters, and thus is easily and rapidly
scavenged by below—cloud processes (washout). Particulate—suiffate in the
Florida atmosphere on the other hand, occupies a range of very iall particle
sizes (Ahlberg et al. 1978), and is poorly removed via washout...
The above fact may present an important clue to the source of
acidic species ( 2 S0 4 , HN0 3 ) in winter (frontal precipitation.. Frontal
events that occur in Florida during winter are generated by the collision of
a cold dense air mass of arctic or polar origin with a warm, htrimid air
mass of maritime provenance. In the process, the warmer, unst cble air is
uplif ted, causing condensation of moisture and precipitation ( yers 1974). Due
to the different source regions of the two air masses, only the’ uplifted
5—45
-------
4.5
4.3
4. 1
3.9
00
5.3
5.1
4.9
4.7
4.5
43
4.1
0.0
0.5 1.0 1.5 2.0 2.5
RAIN (cm)
0.5 1.0 1.5 2.0
RAIN (cm)
60
50
40
30
20
10
0
30
25
20
l5
I0
5
0
=
0
70
47 60
45 50
4.3 40
4.1 30
39 20
37 JO
0.0
Figure 5—11. Temporal variation of pH and conductivity within 3 events
sequentially sampled at Gainesville.
5—46
0.1 0.2 0.3 0.4 0.5
RAINFALL (cm)
I
E
0
0
-c
E
C )
c i
C
C
0
-c
C
C
0
0
(-)
a)
cD.
C’)
5i
4.9
4.7
p. ..
I S.
/
F____S._ .-S.
‘ ,. • \ /
,I
\_ .1
r
\. ,•
A
I’
/
/ / ‘
•, ‘
/ ‘ p..—
I, I
t —., I
I.
/ I V
/ I
/
-------
(maritime) air has a significant burden of sea—salt species (e.g. Na+ and
C1), and thus these are deposited in frontal precipitation only by the.
process of rainout. Based on the correlation of sea—salt and acidic species,
deposition of the latter forms probably follows the same mechanism. The
bulk of the H+, excess—SQ 4 = and NO 3 in frontal precipitation thus may-
originate in the southern air, rasher than the northern, or midwestern, ail-;’
the acid species and their precursors thus appear to be primarily of local
origin. Of course, this scheme is an oversimplification because there is
mixing between northern and southern air masses when they come into contact.
The degree of mixing is of interest in determining the proportion of local
vs. imported (northern) pollutants in Florida wintertime precipitation.
SOURCES OF ATMOSPHERIC SULFUR IN FLORIDA
Estimates of the global significance of biogenic su.lfur emissions
are numerous and controversial (Erikkson 1960; Kellogg et al. 1972;
Friend, 1974; Cranat et al. 1976). Florida has extensive areas of potential
importance for biogenic su fur emissions, and consequently it seems appropriate
to attempt an assessment of the contributions of anthropogenic and biogenic
sulfur in the Florida atmosphere. Approximately 20% of the state (3 x io 6
is occupied by wetlands:’., fresh and salt water marshes and swamps and. poorly—
drained soils (Smith et al. 1973; Coultas, 1976; Coultas & Gross 1972;
Coultas 1978). The most productive of these areas (tidal flats and mangrov’m
swamps), occur predominantly in southern coastal areas, where conditions of
available organic carbon and sea—sulfate, coupled with high year—round tempa ’—
atures, could give rise to considerable biological sulfate reduction.
Published experimental data on emissions from such areas are
scarce, in general, and non—existent for Florida. Emission estimates
are further complicated by the fact that a wide variety of experimental desi ns
5—47
-------
has been employed in reported studies. Nevertheless, the available data
have been synthesized (Table 5—8) to give a general overview of the potential
emissions of biogenic sulfur in Florida, and the results indicate a range
of annual biogenic sulfur emissions of about 770—51,800 metric tons, (or
0.05—3.34 kg S/ha) statewide. These figures could be higher if temperature
differentials, or other factors, enhance the. rates of biogenic sulfur
emission in Florida. On the other hand, if slowly—oxidized organic sulfur
species (e.g. COS, CS 2 ) were the predominant emissions from wetland areas,
most of this sulfur would be exported from the state before it could be
oxidized to SO 2 .
Another means of generating biogenic emission figures involves the
use of areal emission rates developed by various authors to balance global
sulfur budgets. These “calculated” emission factors range from about 0,53
kg S/ha—yr (Granat et al., 1976) to about 3.8 kg S/ha—yr. (Friend 1973).
Multiplying these factors by the area of the state yields annual emissions
of 8,200—60,000 metric tons—S, which agrees fairly well with the previous
reckoning.
The above figures are small compared to anthropogenic sulfur emissions
within Florida. Statewide sulfur emissions for 1975 were 500,000 metric tons
(32.3 kg S/ha). The geographic distribution of these emissions was very
uneven; 85% of total emissions occurred in the northern 58% of the state,
and county—wide average emissions ranged from 1.2 to 428 kg S/ha—yr (Fig.
5—12).
In comparison, wet and bulk sulfur deposition values for 1978—79 were
83,000 and 100,000 metric tons, respectively. Estimated biogenic emissions
amount to no more than 72% and 55% of wet and bulk deposition (and perhaps
5—48
-------
Table 5—8. Inventory of Florida wetlands and potential blogenic sulfur emissions.
Potential Total
7 Emission 2 Emission
Wetlands Area* (m ) Rate (mg—S/rn —yr) (Tons—S/yr)
Freshwater Swamps, 1.2 x 1010 <10 — 100 120 — 1200
Marshes
Poorly—drained organic 1.6 x 1010 <10 — 100 160 — 16Q0
Soils
Tidal tnudflats 3.0 x — 30Q 30,000
Mangrove Swamps 1.9 x
-------
A
50-tOO
O0- 200
Figure 5—12.
County—wide emissions of SO 2 across Florida fcr 1978. Units
are kg—S/ha—yr. Statewide mean is 32. kg—SIha—yr; mean of
underlineated county emissions in 6.2 kg—S/ha—yr.
<25
2550
200
0
5—50
-------
much less). Moreover, the geographic distribution of biogenic emission
shows little correspondence with the observed pattern of excess—SOdeposi—
tiori. Consequently, biogenic sulfur probably plays only a small role in
Florida precipitation chemistry.
Anthropogenic emissions, on the other hand, are more than. six times
wet deposition and five times bulk deposition, and distribution of high emis-
sions correlates roughly with the areas of high rainfall deposition of
2—
excess—SO 4 .
This is not to say that biogenic sulfur is not a constituent of
Florida precipitation; however, if it is the dominant sulfur species in
precipitation anywhere in the state, it is only in areas remote from signifi-
cant point sources (where the presence of strongly acid precipitation
(pH 5.0) is yet to be observed).
We also do not imply that sources of sulfur outside the state fail
to contribute to sulfur loadings within Florida. Nonetheless, there are
several reasons to suspect that such emissions are of limited importance.
First, emissions of SO 2 within Florida are substantial and amount to roughly
40% of emissions in Ohio, which ranks first nationally (EPA, 1976). Second,
during summer Florida is isolated ineteorologic.ally from large northern
SO 2 sources by the prevailing synoptic weather patterns (southerly air flow).
This period corresponds to one of heavy deposition of excess SO and
enhanced precipitation acidity throughout the state (see Figure 5—9 and
Table 5—7). Unless a mechanism exists for significant diffusion counter
to the direction of advective transport, there is little reason to believe
that much of the sulfur in summertime precipitation originates in the midwest.
Lastly, as mentioned in the sequential sampling section, there is some
5—51
-------
evidence that much of the sulfur in winter (frontal) precipitation is also
of local origin. Consequently, out—of—state sources probably account for
much less than 50% of annual sulfur deposition in Florida.
ACID RAINFALL IN FLORIDA A PERSPECTtVE
A. Historical Trends in Florida Precipitation Chemistry
The historical record o.f precipitatIon chemistry in Florida ue —
fortunately is incomplete, and there is no exact way to establish the date
when acid rain first appeared in the state. However, two rainfall studies
conducted in the inid—1950s do yield some insight concerning man’s alteration
of precipitation during the past quarter century.
Junge’s well—known study of U.S. prepipitation (Junge & Werby, 1953)
included five Sites that are comparable to sites in the current Florida net-
work. Although pH was not measured in the former study, the chemical anaLys s
in other respects were complete enough to estimate H+ concentrations via
ionic balances. Comparison of annual volume weighted—mean concentrations of
hydrogen ion, excess SO 4 2 and NO 3 for 1955—56 and 1978—79 (Table 5—9)
indicate that the levels of these species at each site have increased markedly
over the 24 year period. A deficiency of measured anionic equivalents
compared to measured cationic equivalents was found for each of Jungers Florilda
sites, suggesting that bicarbonate (an unmeasured species) was present in
the rainfall of that period. Consequently, although exact pH values cannot
be computed from Junge’s data, the results indicate that Florida rainfall
was at or about geochemical neutrality (pH>5.6; H+<2.5 1eq/L). Th average
increment of excess—sulfate plus nitrate (23.5 ieq/l) over the period is
sufficient to account for the average increase in hydrogen ion C 15 eq/L).
It should be noted that this analysis compares wet—only data (Junge’s) with
5—52
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Table 5—7. Conpnri 01 pr1ram’: tcrs r l t d i the ocidi t v of lt’ridn rainfall
ri l95 —A a d 1’)7$—7 ,.
Wei hted—Henn Concentration ( eq/L )
___________________ It e: ce—S0 fl3 —
1 5f 1979 1956 1979 195b J97(j
Mobile, AL/Jay <2.5 24.0 16.0 34.7 2.6 13.9
Tallahassee <2.5 17.4 18.8 33.0 2.9 13.9
.Ia . ksonvi11e <2.5 18.3 27.9 43.5 2.9 1 .2
Tampa/Bradenton <2.5 20.1 28.8 36.4 2.7 14.3
. Palm Bch./Stuart <2.5 6.9 13.5 20.1 4.1 12.1
&an <2.5 17.3 21.0 33.5 3.1 14,1
1979/1956 >8.4 1 . 6 t 4 . 5 t
Pr. tnn concentration Inferred via anion/cation balance.
* Present iota ore for hulk r cipitation (rainfall collectors open at all tines),
whereas 1956 data are for rainfall—only (collectors open to atmosphere only durintz
rain events). Adjacent wet—only ( ‘) and hulk (B) collectors at Cainesville in the
studs’ have yielded the following volume—weighted concentrations (íü peq/1): excess
sulfate, 35.1 (B) and 26.6 (u), 81W = 1.3; nitrate 1 16.9 (B) and 13.6 (W), B/W 1.24.
Thus Uf [ erences in collector type do not wholly explain the increases in concentrations.
-------
bulk precipitation data (ours). Because concentrations in bulk precipitation
are somewhat different than those in wet—only precipitation (cf. Figures 5—8),
this leads to a magnification of the current excess of sulfate and nitrate
compared to the levels found in 1955—56. in contrast, the 24—year increment
of probably is underestimatecL, since wet precipitation typically
is more acidic than bulk precipitation.
The other historical study, conducted by the USDA (Jordan et al.,
1959) tD evaluate atmospheric inputs of sulfur to southeastern soils, also
had five sites comparable to present ones. Annual loadings (kg S/ha) of
sulfate in bulk precipitation for the two studies (Figure 5—13) increased at
all five sites between 1952—55 and the present. Atmospheric loadings in
the northern part of the.state have increased by 3—4 fold, while deposition
in southern Florida has increased marginally, and perhaps not significantly.
Assuming that sea—sulfur and biogenic sulfur emissions have remained rela-
tively constant over the period, anthropogenic sulfur emissions are the
cause of the increased deposition at northern sites.
Wet—only precipitation events have been collected for over three
years, in Gainesville. Monthly weighted riean pH values for the period
January 1977 — December 1979 (Figure 5-14) fail to indicate any recent trend
in precipitation acidity. Annual weighted mean p 1- I values of precipitation
for 1977, 1978 and 1979 are 4.51, 4.62 and 4.56, respectively. The uniformity
of these results suggests that the current data base can function as a
sensitive barometer for gauging future changes in precipitation chemistry.
B. Comparison of Florida and Northeastern Precipitation
Comparison of precipitation loadings of N+ and related parameters
for Florida and Hubbard Brook, New Hampshire show that the acid rain
phenomenon is considerably more intense in the ortheast. Two factors
5—54
-------
B
Figure 5—13. Atmospheric sulfur deposition at 5 hIstorical (1952—55) and
current (1978—79) precipitation sampling locat-ions. Means for
both studies are depicted in legend.
I I
c J
LO
15
10
J kgS/hr’yr
0J
LEGEND SCALE
• •
5—55
-------
5.50
5.25
5.00
4.75
4 .5(
425
4OC
pH
J f m a m j j a s a n d j f m a in j j o $ o n d j f ma m j j a; ç n d
1977 1978 - 1979
Fi ure S--lA, Montl ly )ited r ean pi! of (‘ ainesvi11j wec—onl pr c1p1t ticr co11 ct d from
-------
quantitatively responsible for this difference. First, the levels of acidify”—
ing substances (excess—sulfate and nitrate) are somewhat lower in Florida rain.
At northern, southern and coastal sites in Florida (Figure 5—2), the sum of
these anions is 53, 38, and 43%, respectively of the 10—year average values
reported for Hubbard Brook, NH (likens etal.,. 1977). Second calcium
(and presumably carbonate) occurs at much hi&her concentrations (34 fQld) it
Florida rainfall.
The effect of these two circumstances is especially apparent at the
coastal and southern Florida sites. The rain at these sites typically is
only slightly acidic compared to geologically neutral rain (i.e. pH 5.6—5.7) -
Were it not for the excess of calcium In Florida rain compared to levels in
rainfall of the north eastern United States, all of Florida would now be
receiving acid precipitation: northern areas would have a pH of about 4.5, a;nd
southern sites would exhibit pH levels of about 4.7.
Because Florida generally receives more rainfall than the Northeast.,
annual deposition of acidity and related species is closer to northeastern
values than concentration data alone suggest. The site at Jay, for example,
received slightly over 200 cm of rainfall during the study year, resulting
in the deposition of 500 eq H+/ha and 11.5 kg S/ha. Corresponding values at
take Apopka, where the rainfall amount was near normal for the state, are:
136 cm 7 342 eq H+/ha and 6.6 kg S/ha. At Hubbard Brook, the deposition of
these species averaged 97Oueq H+/ha (Likens, 1976) and 12.7 kg S/ha (Likens
et al. 1977) in the 10—year period 1964—65 to- 1973—74. Thus northern Fiorid
receives about one—third to one—half of the hydrogen ion deposition and 50 to
90% of the sulfate deposition as that in the most impacted region of the Unit ed
States.
5—57
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Chapter 6. Effects of Acidification on Softwater Lakes in Florida.
A total of 20 lakes in two geographical regions were selected for sam-
pling during 1978—79, for a variety of physical, chemical and biological
parameters. The sampling was designed to evaluate chemical and ecological
- impacts of acidic, precipitation on sensitive aquatic systems. The lakes were
selected on the basis of two main criteria: 1) softwater, making the lakes
susceptible to acidification, and 2) availability of historical data to
determine whether there have been any measurable changes (i.e. decreases
in lakewater pH and alka1 nity) over the last decade or so.
This chapter describes the sampling program we conducted on these lakes,
temporal trends in chemical composition of the lakes over the past 20 years,
and the variations in composition of the major trophic groups in the lakes
as a function of pH.
Previous Studies on Effects of Acid Precipitation on Aquatic Ecosystems
Acid rain in North America and Europe has contributed to the acidif i—
cation of many aquatic habitats, with subsequent effects on the biota
(Gorham 1976; Eornbeck at al. 1976; Oden 1976; )verrein l976 Sc io iei .c l976
and Likens et al. 1979). With increased acidity, effects have been documented
for all trophic levels and include reduced species richness, deformities,
reproductive failures, retarded growth rates and deteriorated health. In
6—1
-------
some severe cases the complete loss of an entire class of orgRnisms can be
traced to increases in acidity (Beamish 1976; Stokes and Hutchinson 19Th a nd
Andersson et a].. 1978).
Much valuable information on the effects of increased acidity on
aquatic systems has been obtained from studies of acid mine drainage (Harp
and Campbell 1967 and Parsons J.968, 1976).: Although the rate of acidif i—
Cation by mine drainage is often more rapid than by acid rain, the general
responses by the biota are often similar.
The impact of acidification on lakes in Norway has Led to the develop—
‘flent of a comprehensive project by the Norweigan Research Council (Braekke
1976) designed to investigate the effects of air pollutants on soil, vege—
tation, water, and freshwater fish (Overreirt 1976). Literature reviews
On the responses of aquatic organisms to increased acidity are presented ir
IFAC (1969), Giddings and Galloway (1976), and Wright (1976)_
plankton
Effects of increased acidity on phytoplankton communities include
reductions in species richness and alterations in the proportions of the
5 Pecies present (Leivestad et al. 1976). As species richness decreases,
5 pecies normally found in low abundance often disappear, while acid tolerarnt
5 Pecies such as Euglena . increase in dominance. In a study of growth
rates of 34 species of freshwater algae, Moss (1973) found Euglena gracilis
am Eunotia . to be very acid tolerant and to survive at pH 3.65 and 3.9
respectively. Leivestad et al. (1976) reported that periphytic algae becoT
dominant in acidic streams. In their study, the periphytic diatom Tabellat-la
and the green alga Mougeotia . accounted for 70% or more of
the total number of algae cells in a stream acidified to pH 4.0 — 4.3. Ver-y
periphytic algae were found in streams at pH 6.0. The high abundance
6—2
-------
of periphytic algae in the acidic stream, resulted in a higher algal biomass
at pH 4 than pH 6.
The effects of increased acidity on phytoplankton communities can be
caused by direct physiological damage or synergistic interactions between
acid and toxic-substances such as heavy metals (Stokes and Hutchinson 1976).
Giddings and Galloway (1976) have suggested that increased free CO 2 concen-
trations in acidic lakes could favor some species while inhibiting others.
• Changes in pH have been shown to affect interspecific competition in
Phytoplankton. In a study by Kroes (1971), the inhibitory effect of Chioro —
ellipsoidum on Chiamydomonas globosa was found to be the result of a
change in pH brought about by C. ellipsoidum.
k c phytes
Nacrophyte co uunities in temperate lakes have been shown to be greatly
reduced in species richness by acid precipitation (Hultberg 1976). In a
Study by Grahn (1976), the natural vegetation of an oligotrophic lake in
Sweden was reduced from Lobelia dortmanna, Littorella uniflora and Isoetes
Sris to a monoculture of Sphagnum .
i jc Productivity
Acid precipitation has the overall effect of decreasing the productivity
a body of water (Grahn 1976). This process is known as oligotrophication
and involves a decrease in available plant nutrients caused by chemical and
biological changes in acidified systems (Overrein 1976). Planktonic produc—
tilrlty is reduced by large mats of Sohagmun because of theIr ability to
concentrate cations and their formation of a physical barrier between the
Sediment and the water column (Grahn 1976). Another aspect of oligotrophi—
catj 0 involves a reduction in the rate of biological decomposition of
matter. Andersson et al. (1978) have shown a replacement of bacteria
6—3
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by fungi as the major agents of biologic decomposition in acid waters. This
replacement has the overall effect of decreasing nutrient recycling and thus
lowering productivity.
, pplankton
Zooplankton communities have been shown to be adversely affected by
acid precipitation;with decreases in species diversity and ab indartce of
individuals occuring in acidified lakes (Hagen and Langeland 1973; Eendreyet
al. 1976). Sprules (1975) reported that pH was the factor having the major
effect on the structure of zooplankton communities. The greatest effect was
flOted in lakes of pH 5.0 or less, where many species were completely
eli jnated. Some acid—tolerant species were found by Sprules to occur
throughout the pH range (3.8 — 7.0) observed in’his group of lakes, in-
Cluding Mesocyclopsedax, Cyclops bicuspidatus, Diaptomus minutus, Holopedium
.&i e m and Bosmina p. Species absent from lakes of pH 5 or less were
2.PPcyci. prasinus, Diaptomus oregonensis, Leptodora kindtii and several
8 Pecies of Daphnia .
When determining the acid tolerance for a particular species, both the
PH level for survival of-adults and the pH at which reproduction stops must be
Considered. Dayis and Osburn (1969) conducted tolerance studies on 1)aphnia pulex
and found a survival time of at least 32 hours over a wide range of pH (4.3 —
10.4). However, the organisms reproduced successfully only within the pH
range 7.0 — 8.7. Consequently, Daphnia is not commonly found in acid waters.
°fl the other hand, Yan. (1979) found the small cladoceran Bosmirta longirostris
comprised 89% of all adult crustacea in a group of acidified Canadian lakes.
Because of the reduced biomass (resulting in part from the small size of
dominant species), Yan proposed that zooplankton exert less control over
Phytoplankton communities in acid—stressed lakes than in neutral lakes.
6—4
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The ability of some zooplankton species to adapt to acid Ltc conditions
was demonstrated by Parsons (1968). In this study, ac.id and non—acid waters
were found to contain some of the same species. When individluals from a
Species common to both types of water were removed from the monacidic water
and subjected to acidic conditions, a high rate of mortality was observed.
. thic Invertebrates
Benthic invertebrate populations have lower species rich tness and re-
duced numbers of individuals in acidic waters (Tomkjewjcz andl Dunson 1976).
Harp and Campbell (1967) found that Chironomus plurnosus was tLhe only chiro—
notnid established in water of pH 6.0 or below. The presence of C. plumosus
Was also highly correlated with the presence of leaf litter aind sediment type.
Gastropods are sensitive to low pH, as demonstrated in. a . study by 4 kland
(1969) in which snails were absent from Norwegian lakes with a pH below 5.2.
Benthic c staceans such as amphipods are an important food s ource for many
fish, and they are adversely affected by high acidity (HutchLnson and.
Havas 1979). Advoidance of acidic conditions by Gammarus pule x was shown by
Costa (1967). G. pulex showed negative responses to pH leveLs of 5.4 or less,
With graded advoidance between 5.6 and 6.4. Bell (1971) foum.d caddis flies
to be most acid tolerant with mean 30—day survival limits off pH 2.45 to 3.38
and a 50% failure of emergence at pH 5.9.
Losses of commercial and sport fishing from many lakes in Scandinavia
have been reported (Wright and Snekvik 1978). Similar losses in the north—
easte United States and Canada have been reported (Parsons 1968; Beamish
and Harvey 1972; $cho f1 eld 19Th) The lc’3s.of fish popu1atio ns from acidic
waters can be traced to a number of factors 4 such as increased toxicity of heavy
metals, ionic imbalances, and especially increased concentrat.ions of aluminum
6—5
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in acidic waters (Schofield 1979; Packer and Dunson 1970).
In studies by Leivestad et al. (1976) and Wright and Snekvik (1978),
reproductive failures were noted prior to the loss of fish populations from
acidic lakes. Beamish (l974,l97 ) found abnormally low levels of serum
calcium jn the ovaries of female trout exposed to low pH levels. Females
With low calcium levels failed to release their ova for fertilization and re—
absorbed ch of the ovarian tissue back into their bodies (Beamish 1 ?74)
Acid precipitation can contain high concentrations of heavy metals and
increase leaching of cations from soils (Beaniish and Harvey 1972; Schofield
1976; Cronan and Schofield 1979; Maimer 1976). Among the metals associated
With acid precipitation, aluminum has been shown to exert detrimental effects
on organisms at high concentrations (Dickson 1978). Dickson (1978) suggested
that unsuccessful attempts to restock some Swedish lakes with rainbow trout
after the pH had been increased by liming may be due to al mtimtq çicj.ty.
However, aluminum is highly insoluble at neutral pH, and it should precipitate
rapidly in limed lakes.
Parsons (1976) proposed that three major parameters be investigated in
assessing the impact of increased acidity on an ecosystem: 1) quantitative
analysis of populations, 2) community structure and 3) the ability of the
‘7arious species to establish a complete life cycle.
6—6
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DESCRIPTION O THE STUDY REGIONS AND LAKES
Two groups of soft—water lakes were chosen for study of the effects
of precipitation on lake water chemistry and biology; a northern group (Trail
Ridge Group) of 13 lakes in the Alachua, Clay, and Putnam Counties and a
group of 7 lakes (Highlands Ridge Group) in Highlands County in south-centxa.L
‘lorida. Figure 6—1 shows the location of the. two lake groups, and Table 6 —i
lists each lake, its surface area, elevation, and county location.
pçgraphy
The two lake districts are topographically similar. Each group is
located along a ridge (the Trail Ridge (north) and Highlands Ridge (south) )
Within the topographic division of the state known as the Central Highlands
(Clark et a],. 1962). The Trail Ridge extends southward along the Bradford—
Clay County line as a series of hills, with the highest elevation being 75 in
(250 ft) above MSL just south of Kingsley Lake. From this point, the land
elopes in a southerly direction and fans out into a wider area of sand—
hiii 5 dotted with lakes. The Highland Ridge is a narrow, elongated area of
rolling uplands containing numerous hills and lakes, extending from nL rth—
Western Highland County, southwestward almost to the Glades—Highlands Cour ty
line, and ranges in elevation from about 60 in (200 ft) to 12 in (40 ft)
above MSL.
12
The two regions are also geologically similar (Figure 6—2), underlain
bY several hundred feet of unconsolidated to semiconsolidated. marine and
non_marine deposits of sand, clay, marl, gravel, limestone, dolomite, and
dolomiti limestone. The oldest formation penetrated by water wells in
both areas is the Lake city limestone of Eocene Age (Clark et al. 1964; 3i hop
1956). The Eocene series is comprised, in add1..tion tc the Lake City limes . one,
6—7
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, I * S S S -
• TJ
61. Location of the lakes in
the survey.
TRAIL RIDGE LAKE DISTRICT
:F• C.U t5VtLL
L. Co .p. s
AV ?A K
L Lc tta
3E3q LNC
Jos phtn
G’z. — is
J z
PJ cid
L.
HIG.A?’ Co.
HIGWL.ANDS . IDGg L.\KE DLSTRCT
-------
Table 6-1. Locations and Physical Data on Lakes in Survey.
Lake
•
Surface
Area
(ha)
Mean
Depth
(m)
aximum
Depth
( T n)
(m
Elevad
above
on
MSL)
Location
(County)
?revt
St :d
(ReF.
Trail Ridge Group
216
3.6
5.8
45
Alachua
Aitho
derson—Cue
8
2. 0
4 . 6
38
Putnam
5 , 6
Brookl
256
5.7
10.4
35
Clay
;L,3
Cowpen
223
3.7
8.8
21
Putnam
C
Galilee
34
3.5
5.8
27
Putnam
6
Geneva
650
4.1
8.8
32
Clay
1,3
Johnson
140
4.0
27
Clay
1
Kingsley
l very (Sand Hill)
:Magnolia
652
500
83
7.3
4.8
8.0
26.0
12.0
15.0
54
40
38
Clay
Clay
Clay
1,
1,4
1,6
M Cloud
10
2.0
5.0
27
Putnam
5 ,6
Santa Rosa
42
8.1
13.4
30
Putnam
6
Sheeler
7
17.0
49
Clay
iands Ridge Group
35
147
216
1403
494
191
1329
8.3
4.0
2.9
6.0
2.0
8.0
20.0
8.0
8.0
12.0
3.0
3.0
17.0
34
24
21
22
22
30
28
Highlands
Highlands
Highlands
Highlands
Highlands
Highlands
Highlands
7
2
3,7
7
3
T
innie
Clay
rrancjs
June (Stearns)
Josephine
Letta
çid (Childs)
.) Clark et al. (1964). Semi—annual sampling 1957—60.
) liennessey and Holcorub (1967); Holcomb (1968), (1969); Duchrow (1970,71,72); Holcomb and
Starling (1913). Annual sampling 1966—73.
) Holcomb (1968,69); Duchrow (1970,71,72); Holcomb and Starling (1973). Annual Sampling
1967—72.
‘ ) Duchrow (1970,71,72); Holcomb and Starling (1973). Annual sampling 1969—72.
) Erezonik et al. (1969). Biweekly and monthly sanpling 1967—68.
:) Shannon (1970). Quarterly sampling 1969.
: ) Milleson (1978). Quarterly sampling 1974—76.
6—9
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-
L
b r
I 1
{11
j- J
I —
ILY4Z
/L/’/J /
4i 7T
(a)
LLTHOLOGY
r ,’. —1
.; ‘,
S and
Sand--Marl—Clay
[ 1
I I I
Limes tone
GEOLOGY
Pleistocene
Deposits
H I
Hawthorne
Formation
LI
Ocala Group
Avon Park
L irn e stone
Figure 6—2. Geologic cross_sections of the (a) Trail Ridge L.ake Disrict
(Clark et al. 1962) and (b) Highlands Ridge Lak District
(Bishop 1956).
+300-
+200
+100 -
0.
-100
-200
-300
-400
-500
(b)
-------
of the Avon Park and Ocala Group limestones, which collectively are referred
to as the Florida Aquifer, and are the major source of fresh water jpplies in
the state. The top of the uppermost limestone layer, is approximately 30 m
(100 ft) below mean sea level in the Trail Ridge area and 120 — 150 m (400 -
500 ft) below MSL in the Highlands Ridge.
The relatively thick and impermeable Hawthorne formation (Miocene
Series), which consists chiefly of thick clays and clayey sands overlying the
Ocala Group, is a confining bed that holds water under artesian pressure in
the Florida Aquifer. The high terraces that form both the Trail Ridge and
Highlands Ridge consist of loose sands deposited on the Hawthorne Formation
during the interglacial stages of the Pleistocene. The sand deposits
forming the surface of th ridges have been reworked by wind and wave action,
but ancient sand dunes and sand bars are well preserved.
The lake regions exemplify typical karst topography, with many circular
to elliptical basins among the sand hills. Lake basin formation along the
ridges resulted from the dissolution of the underlying limestone beds and the
collapse of the impervious Hawthorne layer and overlying veneer of
Pleistocene sands. The basins subsequantly filled with wat r from precipi-
tation, resulting in perched, soft-water lakes in the sand deposits above
the confining Hawthorne formation.
Soil Characterization
The sand deposit of the Central Highlands region is classified as an
entisol (Asatatula fine sand—quartzipsamment), an excessively drained soil
with very highly permeability. Native vegetation, reflecting the nutrient-
poor status of the sands, primarily consists of mixed turkey and scrub oak
and sand pine. A typical soil profile for this region from the surface (A
horizon) to 300 cm depth (C6 horizon) generally consists of grey to light
6—11
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brown fine to coarse sands, strongly acidic, WILiI a cation—exchange capacity
(CEC) of 1 meq/i00 g or less and zero percent. base saturation (Carlisle et al.
1978). The soil thus has very little neutralization capacity toward acidic
precipitation.
Description of individual study lakes
The surface areas and elevations presented in Table 6—i are from data
published by the U.S. and Florida Geological Surveys, Water Resources Di-
vision, or from interpretation of topographic maps when no other informaticrn
was available. Some of the lakes undergo severe fluctuations in lake stag
during times of excess and below normal rainfall. The severe drought of
1955—57, for example, caused Lake Brooklyn at Keystone Heights to be ioweru d
7 in (20 ft) and reduced to one—half its normal size (Clark et al. 1964). be
areas and elevations given in Table 6—i are for normal lake stage levels. The
lakes are described below in order they appear in that table:
1. Lake Aitho, located near Waldo in Alachua County, is in the
Santa Fe River drainage basin. It has a surface area of 216 ha at an
elevation of 45 in MSL. Lake depth at the m14—lake sampling station was
5 in. The lake drains through the Santa Fe Canal into Little Santa Fe Lake_
There is some residential development along the shoreline, but most of th
shoreline is lined with cypress that grades rapidly into pine forset in th€
uplands. The lake is moderately colored because of runoff of humic material
from the surrounding forest.
2. Anderson—Cue lake, in Putnam County, has an area of 8 ha at a
surface elevation of 37 in. The lake level was low during this study and
its area was reduced by almost 50% compared to normal conditions. Depth a
the mid-lake station during this study was 3.8 in. The lake has no influen
or effluent streams and obtains its water from direct precipitation and
6—12
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sübsurf ace seepage. Its small drainage basin is delineated by the surrounding
high sand hills with elevations of in. There Is no human habitation in
the drainage basin.
3. Lake Brooklyn in Clay County near the town of Keystone Heights,
is the fourth lake in a chain forming the upper Etonia Creek Drainage Basin
(Clark et al 1963). It has a surface area of 256 ha at its normal stage.
It is underlain by extremely permeable soils, and its level receeds as much
as 7 in during years of below average rainfall. During this study the lake
was at a very low stage, having received below normal rainfall for several
consecutive years. The depth at the sampling station was 5 in. There is
residential development along the south and southwest shore of the lake
while the north shore is relatively free of development.
4. Lake Cowpen, located in Putnam County, has an area of 223 ha at
20 in elevation and was 4 in deep at the sampling station. The lake was ex—
tremely low during the study and primarily consisted of several circulnr
pools. Sampling was done at the center of the largest of these pools where
there was a public boat ramp. There is some residential development along
the portions of the shoreline.
5. Lake Galilee is also located in Putnam County approximately 4 kin
east of Lake Cowpen. It has an area of 34 ha at an elevation of 27 in. Lake
Galilee was also low during the sapmling period, but its level was less
affected by the drought than the level in Lake Cowpen was. The depth was
3 m at the mid—lake sampling station. There are a few residents along the
south shore of the lake.
6. Lake Geneva is located in Clay County just south of the town of
Keystone Heights. The depth at the sampling site was 5.5 in. It is the
largest lake (650 ha) in the Etonia Creek Drainage Basin (Clark et al. 1964).
6—13
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It receives drainage from a chain of 5 upstream lakes, during years of
average or above average rainfall. Lake Geneva is almost completely sur-
rounded by residential development.
7. Lake Johnson (140 ha) is located in Gold Head Branch State Park
in Clay County. It recei”es- influent—flow frog Gold Head Branch Creek which
arises from rainfall percolating through sandhills having elevations of 65 in
in the immediate area. The lake depth at the sampling station was 3.3 in.
The only development along the shoreline is a swimming and picnic area and
several rental cottages.
8. Kingsley Lake (Clay County) is 26 in deep at its deepest point and
is thought to be the deepest lake in north Florida (Clark et al. 1964).
The lake is nearly a perfect circle with an area of 652 ha. Water level
fluctuation is small (only - 1 in during the period 1945 to 1963) compared
to nearby Lake Brooklyn. There is moderate residential development along
the north side of the lake.
9. Lake Lowery (Sand Hill Lake) located in Clay County is the second
of a chain of lakes in the Etonia Creek basin. It receives flow from Blue
Pond, and its surface outflow goes into Magnolia Lake. Lake Lowery has a
surface area of 500 ha and a maximum depth of 12 in. The depth at the sampling
station was 7 in. The shoreline is completely natural (forest) with the
exception of a boat ramp.
10. Lake Magnolia, located near Lake Lowery, is the third lake in the
Etonia Creek Basin Chain. During years of average or above average rain-
fall the lake supplies water to Lake Brooklyn through Alligator Creek. It
has an area of 83 ha and a maximum depth of 15 in. The depth at the sampling
station was 15 in. The shoreline also is in a natural state, with no develop—
merit other than a boat ramp.
6—14
-------
11. Lake McCloud (Putnam County) is approximately 750 r.i1 north—east
of Lake Anderson—Cue. It is totally enclosed, with surroundiing sand hills
rising to elevations of 45 m. There are no influent or efflutent streams.
The lake was low during this study, and the depth at the mid—lake station
was 5 m. Normally, it has a surface area of 10 ha at an elev ’ation of 90 ft.
There is no human habitation in the drainage basin..
12. Lake Santa Rosa (Putnam County) is a seepage lake • ith an area
of 42 ha at an elevation of 30 m. It was also losi during thus study, and
the ends of docks and piers u-era 10 — 20 in from the edge of the water. The
depth at the mid—lake station was 10 in. There are numerous p ermanent and
seasonal cottages in the drainage basin.
13. Lake Sheeler is a small (7 ha) seepage lake near L uke Johnson
in Gold Head Branch State Park (Clay County). It is nearly c ircular with
a deep (17 in) conical—shaped basin. The extreme- clarity and depth of the
lake make it attractive for SCUBA diving and the park reserve s it for
this sport. The watershed and shoreline is completely undeve 1oped except
for a trail to the water’s edge.
14. Lake Annie (Highlands County) has a surface area of 35 ha at an
elevation of 34 in. The lake is part of the Archbold Biologitral
Station preserve; its drainage basin is uninhabitated and con sists totally
of native vegetation. The basin is of typical sinkhole formation, being
nearly circular and quite deep (20 in). A small stream flows from the north
side of Lake Annie into Lake Placid.
15. Lake Clay is situated approximately 1 km east of Lake June in
Highlands County and has a surface area of 148 ha. Sampling as pertormed
at the mid—point of the deepest pool of the lake, where the d. . pth was 7.5 m.
Lake Clay drains northward into Josephine Creek which flows tc Lake
6—15
-------
Istokpoga. Lake Clay is completely surronded by residential development.
16. Lake Francis, located 5 km northwest of the town of Lake Placid
(Highlands County), is in a chain of lakes. It receives surface flaw from
Lake Placid and June to the south, and drains north through Josephine Creek
to Lake Istokpoga. Lake Francis has a surface area of 216 ha at surface
elevation of 21 m. The depth at the mid—lake station was 8 in. The shore— -
line consists of approximately equal residential development and native
vegetation.
17. Lake June or June—in—Winter (formerly Lake Stearns), located in
Highlands County, receives water from Lake Placid via Catfish Creek to the
south, and its water drains northward through Stearns Creek. Th& lake is
the largest in this study, with an area of 1403 ha. The depth at the mid--
lake station was 7 m. Land use along the north and south shorelines
is predominantly residential, while citrus groves occupy the eastern shore-
line. The west shore is primarily native vegetation.
18. Lake Josephine (Highlands County) is relatively shallow, with
the depth at the mid—lake station being 3.5 in. At an elevation of 21.5 in
it has a surface area of 494 ha. It receives water from Wolf and Jackson
Creeks and overflows through Josephine Creek into Lake Istokpoga. Resi-
dential development occupies the south side of the lake, and trailer camps
occur along the east side. Native vegetation and improved pasture are
found to the north.
19. Lake Letta, the northern—most of the Highlands Ridge Group, is
located near the town of Avon Park. At an average lake stage of 30 in it
has a surface area of 191 ha. Lake Letta was low during this study, and
the depth at the mid—lake station was 2.5 in. The lake has two inlet streams
and drains into Bonnet Lake. The east and north shore of the lake is resi—
6—16
-------
dential and the southern and eastern shore is dominated by native vegetation.
20. Lake Placid (formerly Lake Childs) is south—southwest of the
town of Lake Placid in Highlands County. It is the second largest lake
in this survey with a surface area of 1329 ha. It receives water from
Lake Annie and drains northward through Catfish Creek to Lake June. The
depth at the mid—lake station was 7.5 m. The shoreline along the western
and northern edge is primarily residential, and citrus groves and native
vegetation predominate along the eastern and southern shores, respectively.
Previous Lake ‘Studies
Historical data exist for all the study lakes, except Lakes Sheeler
and Annie (Table 6—2).Data for some of the Trail Ridge lakes date back over
two decades.
Clark et al. (1964) reported lake water chemistry data for semi-
annual sampling of lakes Brooklyn, Geneva, Magnolia, Lowery (Sand Hill),
Johnson, and Kingsley in the Trail Ridge Lake District. The sampling survey
was initiated in July, 1957, and ended in September, 1960. Included in the
anaylses were pH, major ions, and nutrient forms.
Ten years later, the Florida Game and Fresh Water Fish. Commission as
part of a state-wide survey of Florida lakes reported data on pH, major ions,
and nutrient forms for five of the Trail Ridge lakes (Brooklyn, Geneva, Lowery,
Kingsley, and Altho) and three lakes (Francis, June, and Letta)in the Highlands
Ridge Group. Sampling was performed on an annual basis from 1966 to 1973
(HennesSeY and Holcomb 1967; Holcomb 1968, 1969; Duchrow 1970, 1971, 1972;
Holcomb and Starling 1973).
Brezonik et al. (1969) conducted intensive sampling of Lakes Anderson
Cue and McCloud located in the Trail Ridge District during 1967-68 and re-
ported data for pH, major ions, and nutrient forms. Sampling was biweekly
6—17
-------
Table 6-2. historical pi 1 , alkalinity and sulfate data for the Trail Ridge Lake Group.
Lake
*
1957—60
**
1963—69
+
1967—72
1-F
1978—79
pH
mgJL
Alk.
as CaCO 3
2
SO 4
mg/L
pH
m8/L
Alk.
as CaCO 3
, ,
S0
mg/L
pH
mg/L
Alk.
as CaCO 3
.
S0
mg/L
pH
mg/L
Alk.
as CaCO 3
2
SO 4
mg/L
Brooklyn
5.5
2.5
4.1
5.5
0.5
4.0
5.1
0.9
3.2
5.0
,
4.6
Lewery
5.4
2.5
2.0
5.3
0.3
3.8
5.1
0
2.5
5.2
0
3.4
Magnolia
5.6
2.5
2.4
5.5
0.4
3.3
5.1
0
3.0
Ceneva
5.4
1.6
5.8
6.3
1.2
5.4
6.1
4.3
6.0
6.1
6.5
9.0
Kingsley
6.3
5.7
4.9
6.9
5.7
5.2
6.6
7.0
5.1
6.7
10.8
7.3
Johnson
5.5
2.5
2.5
5.2
0
2.1
Anderson-Cue
4.8
0
4.4
4.9
0
5.2
Cowpen
5.4
0.4
5.8
4.9
0
13.9
Galilee
5.6
0.6
6.1
5.0
0
11.8
McCloud
4.9
0
4.5
4.7
0.
6.8
Santa Rosa
5.2
0.3
4.7
5.1
0
5.3
* 8emi— nqua1 sampling during 1957—60 (N 6); Clark et a].. (1964).
** Sampling every four months during 1968—69 [ N 3; except Anderson—Cue, flcCloud (N 6); Geneva,
Kingsley (N 5)J Shannon (1970).
+ Annual samplinb 1967—72 (W 6); Holcocnb (1968, 1969); Duchrow (1970, 1971, 1972).
++ This study. Sampling during 1978 (ti’ 4).
-------
during 1967 and on a monthly basis during 1968.
Shannon (1970) and Shannon and Brezonik £1972) conducted quarterly
sampling of 55 north—central Florida lakes during 1969, including all the
Trail Ridge Group of lakes in this study, except lakes Johnson and Sheeler.
Milleson (1978) recently conducted a survey of seven lakes in Highlands
County, including four lakes studied in this project (Placid, June, Clay,
and Josephine). Sampling was on a quarterly basis during the period 1974—76,
and included major ions, pH, and nutrient forms.
SI ’flPLING AND ANALYTICAL METHODS
The 20 lakes were sampled on a seasonal (quarterly) basis beginning in
spring (April — May) 1978 and ending in winter (January — February) 1979.
A m d—1ake sampling station was selected in each lake at either the deepest
part of the lake or the center of the largest pooi, if the lake consisted
of several pools. The same station was used on all four sampling dates.
Temperature and dissolved oxygen were measured with a YSI Model 51A oxygen
meter at three depths in the water column, surface (0.5 tn), midway between
the surface and bottom, and 1 m from the bottom. Secchi Disk transparency
was also measured at each sampling station.
Water samples for chemical analyses were collected with an acrylic
Kemmerer sampler at the three depths described above, and a composite sam-
ple was taken by mixing equal volumes of water in a plastic bucket. Samples
for nutrient analyses were preserved with 1 mL saturated HgCL 2 /L, placed
on ice in the field, and stored at 4°C in the laboratory. An aliquot of
the preserved sample was filtered in the laboratory for analysis of inorganic
nutrients.
6—19
-------
Field pH measurements were made usi
rig odel 401 onalyzer field
pH meter on the composite sample following standardization with two (pH 4.0
and 7.0) buffers at ambient water temperature.
Analytical methods for chemical determinations on lake water s p1es
are summarized in Appendix Analyses were performed according to standard
methods (AP} A 1976) and/or the EPA water analysis manual (EPA 1976). Analy—
‘4 4 ses for inorganic nutrient forms, chloride, and sulfate were run by automated
methods cn an AutoAnalyzer, except for orthophosphate (i.e. ttsoluble reactive
phosphate”), which was done manually using the single reagent method. Total
Kjeldahl nitrogen and total phosphate were determined by manual semi—micro
digestion of unfiltered samples followed by colorimetric analysis for am—
rnonium (indophertol method on AutoAnalYzer) arid orthophosphate (manual single
reagent method) on the neutralized digestate.
Samples for chlorophyll analysis were collected at 0.5 tn for lakes <5 a
and at the top, middle, and bottom of the water column for Lakes >5 m by a
2.2 L Keimnerer sampler. Samples for lakes >5 tn were composited with depth,
and a single chlorophyll sample was taken. All samples were placed in opaque
plastic bottles and stored in ice. In the laboratory, a minimum of 100 mL of
sample was filtered through Whatman 4.25 CF/A glass fiber filters. To the
final tnL of sample, 5 drops of aqueous saturated magnesium carbonate were
added. The filters were placed in glass test tubes containing 5 teL of acetone
and ground with a Wheatori tissue grinder. The ground samples were stoppered,
and extracted in the dark at —14°C for 24 h. The extracts were filtered
through glass fiber filters using a Millipore Swinnex filter attachment and
disposable syringes, and the filtrates were brought to final volume of 10 teL
with acetone. Absorbance was read on Beckman DBG spectrophotometer according
to Standard methods (API -IA 1976). Chlorophyll a is the active form of the
pigTneflt (i.e. total chlorophyll corrected for phaeophytifl EAPPA 1976]).
6—20
-------
Phytoplankton samples (80 niL) were co 1 y
at 0.5 m for lakes < 5 in and at the top, midd1 and bottom of the water column
of lakes > m. Samples were taken in the center of each lak e, placed in
screw...cap glass bottles, and preserved with 2 m l. of acidified Lugol’s solution.
In the laboratory, sample aliquots were allowed to settle in .:an UterrnohLL
chamber and identified using a tltLitrofl inverted microscope tis- ing taxonomic
keys in Whitford and Schumacher (1973), Cooke (1967), Weber ( 1971), Prescott
(1954), and Smith (1950).
Zooplartktort samples were obtained by a vertical tow throc’ugh the entire
water column near the center of each lake with a number 20 80 ) preserved
10% buffered forinalin and identif led using taxonomic keys fri Edmoridsori (1959)
and Perinak (1953). At least 100 individuals were counted in ach sample under
a dissecting microscope at 250x. Zooplarikton biomass was obt. ained by
multiplying the number of individuals for each species by an ipprotr±ate biomass
Conversion factor (Duxnont et al. 1975).
Two habitats of benthic invertebrate- .cot unities were sarmpled in each
lake. Duplicate grabs were taken at both a shallow—sand stat on and a deep-
mud Station. The importance of substrate characteristics in the distribution
of berithic communities has been pointed Out by Bloom et al. (11972), Parsons
(1968), and Mahadevart et 31. (1977). Samples were taken with, a Ponar grab
(Powers and Robertson 1967) with a sampling area of 0.02 in 2 a;nd a penetration
of about 10 cm in mud (slightly less in harder substances suc as sand).
Samples were washed in the field through a 0.66 n mesh sieve to remove excess
Sediment. Remaining organisms were preserved in IOZ formalir i and stained with
rose bengal. Samples were sorted in a white pan in the 1aborrm tory and Iden-
tified using both a dissecting and a compound microscope. Bic mass measurements
were determined for each lake station. All individuals from i single Ponar
sample were placed in a tared crucible and dried at 150 0 C for- 24 h to determine
dry weights. Ash—free dry weights were determined by cotnbust .i.ng samples in a
muffle furnace at 550°C for one hour. Statistical analysis w as conducted
6—21
-------
using a package of computer programs developed by Bloom et al. (1977) on an
Arndahl 470 at the University of Florida.
RESULTS OF LAKE STUDY: WATER CH nI STRY
Discussion of the water chemistry of the 20 survey lakes is best accom-
plished by segregating the lakes into groups according to pH. In the original
selection of lakes for study, a geographic grouping (Trail Ridge vs. Highlands
Ridge) was used, reflecting the difference in precipitation acidity (Figure 5—1)
at the northern (Trail Ridge) site compared to the southern site (Highlands
Ridge). However, a one—way ANOVA and Duncan’s multiple range test (SAS; Barr
et al. 1976) indicate that the lakes (Figure 6—3) also can be divided into
two groups based on pH (i.e. acidic and non—acidic). The boundary pH be-
tween the two groups is 5.6, which coincidentally is the geochemical equili-
brium pH of pure water in contact with atmospheric CO 2 . The grouping based
on pH compares closely with the geographical grouping (Table 6—1), except that
the three largest lakes of the Trail Ridge group, Kingsley, Geneva, and Aitho,
were grouped with the Highlands Ridge lakes. These three Trail Ridge lakes
have higher pH levels than the other Trail Ridge lakes, possibly because of
their size, depth, and extent of shoreline development. The following dis-
cussion thus divides the 20 lakes into two groups: an acidic lake group (pH
< 5.6) and an non—acidic group (pH > 5.6).
Lake Transparency
As discussed earlier, the lakes located along the Trail and Highlands
Ridges were formed in basins consisting of sandy deposits, and they have little
or no input of surface runoff. Thus these lakes have the most transparent
waters of any lakes in the state. Except for two highly colored lakes, Aitho
and Josephine, which had mean annual color levels of 194 and 154 CU, most of
the lakes had color values of 20 CU or less. Both Aitho and Josephine are
a typical of the other Ridge lakes in that cypress wetlands are located .iithin
6 —2.7
-------
GROUPING MEAN pH N lAKE
A 6.795 4 Francis
A
A 6.742 4 Kingsley
A 6.7 10 4 Clay fl Jfl L4 G 1JP
A 6.670 4 June
A
A 6.535 4 Placid
A
A 6.497 4 Letta
B 6.145 4 Geneva
B
B 6.142 4 Josephine
B
C B 6.025 4 Aitho
C
C 5.752 4 Annie
— — —
0 5.245 4 Johnson
D
E D 5.195 4 Lowery
E D
E 0 5.140 4 Sheeler
E 0 5.097 4 Magnolia 4 IIJ 1i EEGJP
E D 5.057 4 Rosa
E D
B D F 5.025 4 Brooklyn
E D F
E D F 4.980 4 Galilee
E D F
E D F 4.940 4 Anderson Cue
E F
E F 4.857 4 Cowpen
B F
F 4.715 4 McCloud
Figure 6—3. Duncan’s multiple range test for the annual mean pH of the surve
lakes. Mean lake pH values with the same letter are not signifi—
cantly different at the .05 level.
6—23
-------
their watersheds, and colored water containing huxnic material flows from these
swampy areas into the lakes. Lowest color concentrations were recorded for
two pristine, extremely clear lakes, Sheeler (ECU) and Annie (7CIJ). Average
turbidity levels also were very low in the lakes, ranging from 0.6 NTIJ (Sheeler
and Cow-pen) to 4.9 NTU (Josephine). Values for most of the lakes were less
than 2 NTU.
As expected for lakes having low color and turbidity levels, transparency
(Secchi disk) values were high. For example, Lakes Sheeler, Santa Rosa, and
Magnolia (in the Trail Ridge group) had average Secchi transparency depths of
7.9, 5.9, and 5.3 in, respectively. Lake Annie (in the Righiands Ridge) had
an average Seechi depth of 5.5 in. The two colored lakes, AJ.tho and Josephine,
had the lowest mean Secohi values of all the lakes, 104 and 67 cm, respectively.
Greatest Seochi depth values generally were recorded in the winter and spring
months. Water levels for several of the Trail Ridge lakes were at a 20 year
low as a result of several years of below normal rainfall. Consequently, the
Secchi disk sometimes was visible resting on the bottom of some of the lakes.
This was particularly true for lakes Cowpen and McCloud.
Major Ion Composition
The ionic composition of surface waters is a function of contributions
from surface and subsurface runoff within the drainage basin, atmospheric pre-
cipitation, and the balance between evaporation and precipitation. In soft-
water lakes such as those of the Trail- and Highlands ridge districts, the
relative abundance of cations and anions is often given as (Wetzel 1975):
Cations: Na > Ca > Mg > K;
Anions: Cl > SO 4 > HCO 3 .
Table 6—3 lists the mean concentrations and standard deviations of major ions
in the two lake groups, and Figure 6-4 presents the average contributions (equiva -
6—24
-------
Table 6—3. Means and standard deviations of major ions and
specific conductance in the two lake groups.
Parameter
F.+ pg/L
Specific iS/ctn
Conductance @ 25 C
+
Na mg/L
+2
Ca mg/L
+2
Mg mgIL
K mg/L
A1+ 3 pg/L
Cl mg/L
so 2 mg/L
HCO 3 mg/L
Acidic Group*
10 Lakes (N=40 )
10.5± 5.0
(pH 4.98)
41.5 ± 18.2
2.88 ± 1.27
0.99 ± 0.75
0.54 ± 0.27
0.57 ± 0.35
58 ± 29
5.51 ± 1.94
5.51 ± 1.94
0
Non—acidic Group*
10 Lakes (N ’40)
0.62 ± 0.62
(pH 6.21)
92.9 ± 39.8
5.92 ± 2.13
3.67 ± 1.52
2.15 ± 1.36
2.03 ± 1.67
23± 15
11.10 ± 3.55
13.01 ± 6.51
8.66 ± 5.28
* Means for the two groups are significantly different (P < 0.0001
in each case) for each parameter, based on one—way ANOVA (Barr
et al. 1976>.
6—25
-------
lent basis) of the major ions to the total cation and anion equivalents. For
each parameter listed in Table 6—3 there is a statistically ;ignificant differ-
ence between the mean values in each lake group.. The ionic bar graphs show
good agreement between the sums of the major cation and anion equivalents.
Additionally, theoretical conductivities were calculated frc the mean ionic
composition of each lake group. These values, compare closely to the mean
measured conductivities for the two groups:
Specific Conductance
uS/cm (at 25°C)
Actual Calculated %. Error
Acidic Group 41.5 38.2 8%
Non-acidic Group 92.9 89.3 4%
The bar graphs in Figure 6—4 illustrate that on an peq/ 1 L basis, the
order of dominance of cations in both groups of lakes is the same as that
given above for typical softwater lakes. The cations in bot}u lake groups are
dominated by sodium on both a mg/L and a ueq/L basis. Sodiwr comprises 50
and 39% of the cationic equivalents in the acidic and non—ac’i.dic groups,
respectively. The contributions of calcium (20%) and nagnes:i.um (18%) are
approximately equal in the acidic group as well as in the nota-acidic group;
Ca (27%) and Mg (26%). Potassium is the least important of zhe major cations
and contributes 6-8% of the cationic equivalents in the two ro.ups. Hydrogen
(H+) and aluminum ion provide small contributions ( c 5% eacl- t) to the cation
equivalents of the acidic lake group.
The major anions in the acidic lake group are chloride (c1) and
sulfate (S0 4 2 ), which comprise 57 and 43 i of the total anior equivalents,
6-26
-------
100
p EQ / L
I
SCALE
CATIONS Na+ Ca 2 + 1 Mg2+
ANION S
CATIONS
ANIONS
C1_ -504: --
ACIDIC LAKE GROUP
NON—ACIDIC LAKE GROUP
Figure 6—4. Distribution of major cations and anions in the two study lake groups.
-------
respectively. In the non—acidic group the major anion species are C l. (43%)
S0 4 2 (37%) and bicarbonate, HC0 3 (20%), but there is no contribution by
HC03 to the anion component for the acidic group. The low bicarbonate levels
that existed in these lakes in the 1950s and l960s have been titrated by- in—
puts of acidic precipitation over the last decade. This matter is discussed
in greater detail in the section dealing with historical lakewater chemistry
trends.
Specific conductance values fr nthe survey lakes were low, as expecte.dI
for soft-water lakes. All the lakes had annual mean values less than 150 S/c ,
and 9 of the 20 lakes had mean values less than 50 VS/cm (Figure6.-5). The
mean conductivity for the acidic group was 41.5 uS/cm (range of 19 to 78 pS/ rii).
For the non-acidic group the mean was 92.9 uS/cm (range of 35 to 147 iS/cm).
As shown in Figure 6—5 the lakes with the higher pH values also tended to
have higher conductivity values indicating somewhat harder, more buffered
waters.
The u an pH of the acidic lake group was 4.98, and annual means ranged
from 4.71 ( ‘1cCloud) to 5.21 (Johnson). The mean for the non-acidic group was-
6.21, and annual means ranged from 5.73 (Annie) to 6.70 (Clay). The lowest
measured pH during the study was 4.60 for McCloud (winter), while the highes z
value was 7.02 for Francis (fall). Seasonal variations generally were less
pronounced for the acidic lake group than the non-acid group. The very acidic
Lake McCloud, for example, had pH values that ranged from 4.60 (winter) to
4.82 (spring), while Lake Francis, a non-acid lake, had pH values ranging
from 6.35 to 7.02(spring and fall, respectively). The larger seasonal fluc-
tuations of pH in the non-acidic lakes likely reflect higher productivities
in these lakes than the acidic lakes. As shown in Table &-3there is a statis-
tically significant difference between the mean pH values of each group.
2-28
-------
0
H
0
0
—4
0
0
c i i
Q)
H
Cu
0
(I
0
Cu
4 J
cc i
(I )
ci )
0
0
0
4J
H
ci)
c i )
C l)
0
4.50 5.00 5.50 pH 6.00
c c i
ci)
0
125
a, -.- ,
i
,-_) c c l
75
50
25
N c
‘ . 0
6.50
7.00
Figure 6—5. Annual mean specific conductance as a function of p11 for the 20. survey lakes,.
-------
i utrient Forms
To properly assess the effect of acidification on the biota and pro-
ductivity of the survey lakes it is necessary to also consider nutrient
levels in the lakes. The most important nutrients controlling the produc-
tivity of.. lakes are pho.sphorus and nitrogen. Silica concentrations can be
important in controlling algal species composition, i.e. in limiting the
growth of diatoms.
Table 6—4 presents the means and standard deviations of major phosphorus
forms in each lake group. In the acidic lake group, annual average soluble
reactive phosphate (SRP) levels ranged from 4 (Sheeler) to 18 ig/L (Anderson—
Cue) and total phosphate (TP) concentrations ranged from 7 (Sheeler) to 40
ug/L (Anderson—Cue). In the non—acidic group, SRP ranged from 4 pg/L (Annie)
to a high of 27 iig/L (Josephine). The annual average TP concentration also
was lowest in Annie (8 .ig/L) and highest in Josephine (68 3igIL). Statistical
analysis (ANOVA) showed no significant difference (0.05 level) between the
mean SRP concentrations in the two lake groups, but a significant difference
was found for the TP and ORG/P levels (Table 6—4).
Mean and standard deviations for the major forms of nitrogen in the two
lake groups are listed in Table 6—4. Average inorganic nitrogen concentra-
tions (in mg N/L) in the acid lake group ranged from 0.037 (Cowpen) to 0.37
(Anderson—Cue), while the range in the non—acid group was 0.026 (Annie) to
0.106 (Placid). Organic nitrogen levels (in mg N/L) ranged from 0.10 (Cowpert)
to 0.46 (Anderson—Cue) in the acid lake group and from 0.23 (Annie) to 0.68
(Josephine) for the non—acid lakes. Statistically significant differences
between the means of each group were not found (Table 6—4) for the inorganic
species (NH 4 , and NO 3 ), but TON and TN levels were different (at the
0.0001 and 0.005 levels, respectively).
6—30
-------
Table 6—4. Means and standard deviations of nutrients in tthe
two lake groups.
Probabuity*
Parameter Acidic Group. Non—acidic Group means are not
10 •lakes (N=40) 10 lakes (N 4O) diffe..rent
NH —N pg/L 72 ± 99 4]. + 48 .(08 12
N0 3 —N jig/L 21 ± 41 16 ± 17 4158
TON ug/L 199 ± 131 405 ± 193 ..(000l
TN pg/L 292 ± 219 462 ± 196 0O05
SRP pg/L 7 ± 6 10 ± 11 ..0940
TP .ig/L 16 ± 12 26 ± 22 .W109
ORG P pg/L 9 ± 9 16 ± 19 .M1353
TOO mg/L 4.6 ± 3.4 7.0 ± 39
Si0 2 ig/L t 59 ± 341 420 ± 416 . 481
*probabjljtjes listed are from ANOVA (Barr et al. l97€ ) on the
annual means for each parameter in each group If P (.05, means
are accepted as statistically different.
6—31
-------
Silica concentrations can be important in controlling productivity in
fresh waters especially if the phytoplankton population is composed largely
of diatoms. As shown inTable t—4,the mean values of Si0 2 in the two lake
groups are similar, •and. the large standard deviations for each mean indicate
considerable scatter in Si0 2 concentrations within the groups. For example,
Si0 2 mean concentrations ranged from 51 (Cowpen) to 950 ig/L (Lowery) in
the acid lake group, and in the non-acid group silica ranged from 115 (Geneva)
to 1180 iig/L (Josephine). Consequently, statistical anlysis indicated no
significant difference in mean Si0 2 between the two groups of lakes.
Since significant differences were found in the mean levels of organic
constituents (TON, OR , TOC) and total nutrients (TN, TP) between the two
lake groups (Table5..4), the non-acidic lakes (with higher values for these
parameters) would appear to bemore productive than the acidic lakes. As
discussed in a later section, the difference in chlorophyll a levels between the
two lake groups support this conclusion. Reasons for the increased levels of
total and organic nutrients in the non—acidic lakes are not certain, but
it may reflect lower rates of uineralization in acidic waters. On the other
hand, the lower nutrient concentrations may simply reflect lo rer nutrient
loading rates to the acidic lakes, many of which are in small oristine water-
sheds. Further studies are necessary to evaluate these alternate explanations.
Aluminum
Atmospheric inputs of acidity (H 2 S0 4 and HNO 3 ) to the drainage basins
of lakes results in increased weathering and mobilization of metals within
the watersheds of the lakes. In noncalcareous soils, increased deposition
of acidity leads to increased concentrations of dissolved aluminum in surface
and ground waters (Cronan and Schofield 1979; Gjessing et al. 1976). An
important ecological consequence of increased aluminum levels in lake waters
— 32
-------
is the loss or diminution of game fish populations because of the toxic
3+ 2+
effect of free aluminum ion (Al ) and its hydroxo—cotnplexes (A1OH , A1(O ) 2
Laboratory studies have shown that brook trout exhibit a toxic response when
aluminum levels are above 200 iig/L in the pH range 4.4 to 5.9.
Since the watersheds of the Trail and Highlands Ridge lakes are typic.ally
noncalcareous, aluminum analyses were included in the hemicai det rminatI ns
of the lakes. The mean aluminum concentrations and within-year ranges for
each lake are presented as a function of the mean lakewater pH in Figure 6—6.
Highest aluutinurn levels were found in the lakes with the lowest mean pH values.
The average aluminum concentration for the acidic lake group was 58 pg/L,
while the mean for the non—acidic group was 23 pg/L. These mean values ar
statistically different at the 0.0001 level (Table 6—3). The mean aluminurn
concentrations ranged from 116 (Cowpen) to 33 .xg/L (Sheeler) in the acidic
lake group and 43 (Annie) to 24 iig/L (Geneva) in the non—acidic group. The
highest Al concentration found during the survey was 150 iig/L in Lake owp- n
in winter of 1978. Since precipitation contains very little aluminum
( < 10 i ig/L), the aluminum levels in the lakes have resulted from leaching
of soils within the watersheds.
Analysis of historical trends in chemical composition of the lakes
Water chemistry data on some of the lakes In the Trail Ridge region
are available for over a 20 year period, and thus it is possible to examin
the results of the present lake survey in a historical context. P owever.
it should be pointed out that in most cases the historical record is rathc r
sparse. No measurements are available for many years, and the number of
samples collected in any year was very small (one or two) for most of the
historical studies. Table 6—2 lists data on oH, alkalinity (mgIL as CaCO ,
and sulfate for eleven of the Trail ridge lakes in a generally chronologic l
6—33
-------
5.50 6.00 6.50
pH
Acidic Lake Group
Nonacidic Lake Group
-J
C
0
4- ,
S.-
4- )
C
C.’ Q)
U
I_.) C
4 :..
E
C
1
I-
a’
-J
150
125
100
75
.50
25
0
5.00
Figure £—6.
lng . un : n tafl a it entratton of aluminum un function of HI for the survey i tken
-------
sequence. These parameters were chosen for historical comparison because
they most likely would reflect lakewater chemistry changes brought about by
increased deposition of acidic precipitation. Approximately 70% of the free
acidity in precipitation in Florida is H 2 S0 4 (see Chapter 5). The data
indicate that changes in water chemistry have occurred for all the lakes
within the time period of the data collection. Except for Lakes Geneva and
Kingsley, the lakes show a decrease in pH and/or alkalinity, presumably due
to atmospheric inputs of sulfuric and nitric acids. Increases in the S0 4 2
content of the lakes are also evident for most of the lakes. Interestingly,
Lakes Geneva and Kingsley show increases in both pH and alkalinity over the
past 20 years. These lakes are the largest of the Trail Ridge lakes (Table 6—1),
and they have experienced extensive shoreline developement during this time
period. There apparently are no historical data on Lake Sheeler with which
comparisons may be made.
Previous data for Lakes June, Francis, and Letta (Highlands Ridge)
collected during 1967-72 (Holcomb 1968,69; Duchrow 1970,71,72) indicate these
lakes have shown little change in pH and-alkalinity over the last 10 years..
It has been estimated (Likens et al. 1979) that lakes with about 80 . eq/L
of HC0 3 (alkalinity equal to 4.0 mg/L as CaCO 3 ) and a pH of approximately
6.5 will lose their bicarbonate buffer to the point where the lakewater p1.!
drops below 5, if the long-term mean pH of precipitation is about 4.3. Less
acidic precipitation could bring about similar changes in lakes with originally
lower bicarbonate levels. As shown in Table&—2,the alkalinity of the soft-
water Trail Ridge lakes has essentially been completely titrated by acidic
precipitation. Consequently, these lakes are very sensitive to further acidic
inputs.
6—35
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Results of Lake Survey: Biological Communities
Phytoplankton and Ch1 phyll
As the base of the aquatic food chain, phytoplankton are an essential
component of lake ecosystems. Variations in the number of inc- 1ividua1s, in
species richness, or in productivity may affect all tropic 1e ,ie1s. The
effects of increased acidity on phytoplankton communities inciLude a decline
in species richness, a reduction in algal abundance, decrease’v.i algal productivit,
and a replacement of blue—green algae by green algae as the d minant phyto—
plankters (Lackey 1938; Leivestad et al. 1976; Yan and Stokes 1978).
The concentration of total phosphorus (TP) is important rto the productivity
of phytoplankton communities (Vollenweider, 1968). The mean lfl’ concentration
in the 10 acidic lakes was 15 pg/L, whereas the less acidic gr oup had a mean
of 26 ‘ .ig/L (Table 6—4). The concentration of phosphorus in Li .tke water can
be decreased by lowering pH in part because rates and efficienicies on nutrient
recycling from organic matter are thought to be lower under ac:idic conditions
(Oral-in 1976). However, most of the lakes in the nonacid group’ are in water-
sheds with moderate cultural development (including some orang e groves).
Watersheds of lakes In the nonacidic group generally have le ss cultural de-
velopment, and the lower concentrations of TP in the acidic latkes thus are
likely due to a combination of increased acidity and reduced c:ultural impact.
Chlorophyll a
Mean annual chlorophyll a concentrations (corrected for ephytin) from
the 10 acidic lakes (Table 6—5) was 2.74 mg/rn 3 , and the mean f.or the 10 non—
acidic lakes was 10.0 mg/rn 3 . Concentrations of chlorophyll a decreased with
decreasing pH (Figure 6—7a), although the data exhibit a fair amount of
scatter. The mean chlorophyll a concentration in the 5 pH int:ervals (Figure
6—36
-------
Table 6—5. Summary of phytoplankton data for the 20 study lakes.
Number Individuals 2 Ch1oro hyll a
Lake pH of (!//mL) mg/mi
Species* -
McCloud 4.71 12 7,340 0.9
Cowpen 4.84 9 2,940 1.3
Anderson—Cue 4.89 9 10,870 2.8
Galilee 4.96 12 5,650 2.9
Brooklyn 5.01 8 4,330 3.0
Rosa 5.05 12 3,390 2.2
Shee le.r 5.09 11 3,730 1.0
Magnolia 5.10 10 5,460 1.1
Lowery 5.19 12 4,510 1.1
Johnson 5.20 13 8,520 2.5
Annie 5.72 12 8,890 1.5
Aitho 6.00 17 8,680 5.5
Josephine 6.07 22 25,580 11.0
Geneva 6.12 11 4,730 35
Letta 6.37 19 24,540 10.5
Placid 6.40 17 9,590 7.2
June 6.64 18 9,720 9.7
Francis 6.66 21 24,160 10.9
Kingsley 6.68 12 9,070 2.7
Clay 6.69 16 15,080 12.7
* Mean values for four sampling periods
1. Mean number of species encountered for four sampling periods.
2. Mean values for four sampling periods
6—37
-------
15
• A.
r4
0 •S
Ic
S
0
0
‘-4
C.)
j 5_
I I
0
4.5 5.0 5.5 6.0 6.5 7.0
pH
ic- B.
C I I I
‘-4
0
.4
0
‘-4 5•
4.5—5.0 5.0—5.5 5.5—6.0 6.0—6.5 6.5—7.0
pH
Number of lakes 4 6 2 4 4
Figure 6—7. Annual average chlorophyll a vs. pH (A) and as means of lakes
within five pH intervals (B) for the 20 survey lakes.
6_ 38
-------
6—7b) more clearly demonstrates the definite trend of decreasing chlorophyll a
with decreasing pH. Using a Kruskal—Wallis rank sum test, the lakes were
shown to contain statistically different concentrations of chlorophyll a
(a = .005).
In add1tion to a pH—chlorophyll relationship, a phosphorus—chlorophyll
relationship alsO can be discerned in Figure 6—8. However, the absence of
lakes with low pH and high total phosphorus concentrations in the sample
group precludes the definition of a response surface for pH, total phosphorus,
and chlorophyll a over the entire pH range (4.5 — 7.0) in the data base. A
sufficient range of TP values exists for lakes with relatively high pH (i.e.
values > 6.0) to demonstrate an overall trend of increased chlorophyll a with
increased total phosphorus. The limited data for lakes with low pH also sug-
gest a similar trend of increasing chlorophyll with increasing phosphate content.
Species Richness and Abundance of Phytoplankton
A reduction in the number of phytoplankton species found in a given sample
decreased (Table 6—5), but as shown in Figure 6—9a, a considerable amount of
scatter exists in the relationship, especially for lakes with p1-I > 6.0. In
the less acidic lakes, hydrogen ion concentration exerts less control over
phytoplankton community than in lakes of lower pH. Using a Kruskal—Wallis rank
sum test, the 20 lakes were found to contain statistically different number of
phytoplankton species (a .005).
The mean number of species in the 10 acidic’ lakes (pH < 5.2) was 10.8,
with a range of 8 to 13, and the mean number of species on the non—acidic
lakes (pH > 5.7) was 16.5, with a range of 11 to 22. y grouping the 20
lakes Into five pH intervals (Figure 6—9b), the decrease in number of species
with decreasing pH is depicted more clearly. The mean number of species in—
creased progressively from 10.5 in the most acidic group of lakes to 17.0 in
the least acidic group of lakes.
6—39
-------
16
(UI
r
>
0
0
L)
(U
a)
>
>-
Throe dimensional plot of chlorophyll a level as a function of p 1t and total phosphate
levels in the 20 lakeB,
I
0
12
10
0
6
0
4
2
0
Figure 6—8,
-------
20- A.
C i ,
0)
- ‘-4
C)
C)
Co
tl.
0
‘ .1
0)
8
0)
00
c i ,
0)
0
4 -J
0
4-4
0
Co
0)
rI
c i
0)
0-
Co
4-4
0
0)
.0
E
z
Nunber of
lakes
Sc -
so —
c
20
15
10
5
0
0 I I
4.5 5.0
5.5 6.0
pH
I
6.5 70
Figure 6—9.
Average number of species of phytoplartkton vs. H (A) and bar
graphs of average number of species and average number of in-
dividuals per lake within five pH intervals (B) for the 20 sur-
vey lakes.
• e e*
S
S
S
• 5 5
S
I I
B.
r
‘5
S
‘4
4
1
3 -
4.5—5.0 5.0—5.5
4 6
2
5.5—6.0 6.0—6.5 6.5—7O
4
4
6—41
-------
Similarly, the number of phytoplankton individuals decreased with
decreasing pH (Figure 6—10), but again the data are highly scattered. Using
a Kruskal—Wallis rank sum test, the 20 lakes were found to have statistically
different phytoplankton abundances ( .0005). The mean number of individuals
from the 10 acidjc lakes was5,670/mL, witha range of 2,940 to 10,900/tuL. The
mean number of iñdividals from the nonacidic lakes was 14,000/rnL, with a range
of 4,730 to 25,600/mL. The mean number of phytoplankton individuals in each
of the 5 pH intervals (Figure 6—9b) more clearly illustrates the increase in
the number of individuals in the pH range of 6.0 — 7.0.
The isometric plot in Figure 6—11 illustrates the dependence 01 phytoplankton
abundance on both pH and total phosphorus concentration. The absence of lakes
with low pH and high total—phosphorus in the data base again precludes definition
of the complete response surface. Based on available data, phytoplankton
abundance increased wIth increasing pH\at all levels of total phosphorus
encountered in the 20 study lakes. A similar but less complete trend of in-
creasing phytoplankton abundance with increasing total phosphorus was observed
at all pH intervals.
The ability of acidic conditions to decrease the concentration of
available plant nutrients (such as phosphorus) has been proposed (Dickson,
1978; Grahn 1976; Anderson et al. 1978). The consistently low total phosphorus
levels in all acidic lakes except Anderson—Cue, plus reports in the literature
of decreased recycling of nutrients in acidic lakes suggest a causal relationshi7
between the low ph sphorus co icentration and low pH. of the lakes. Anderson—Cue
lake was the site of a previous eutrophication experiment (Brezonik et. al.
1969) and received relatively high inputs of phosphorus for several years.
Further studies are needed to define the relationship among phosphorus,
chlorophyll, and lake acidity.
6—42
-------
30
5.0 0 6.5 7.0
Figure 6—10. Phytopiankton density (number of individuals per mL) vs. ptt
f or the 20 survey lakes.
•6—43
-------
0
q,l
0
S
28
24
20
16
12
8
4
Chlorophyll a
(rnglL)
.5
Three dimensional plot of phytoplankton density as a function of pH and total phosphate levoic
in the 20 survey lakes.
0
0
Figure 6—11.
-------
p cies Composition
One of the most obvious changes in the composition of phytoplankton
communities, both in previous studies (Yan 1975) and in the present investi-
gation, is a replacement of blue—green algae as the dominant group at high
pH by green algae as the. dominant .roup at low pH. In lakes of pH 4.5 5.0
(Figure 6—12), green algae made up 60% of the total number ef phytoplankton
individuals, while blue-green algae contributed 25%. In lakes of pH 6.51 — 7.0,
green algae were responsible for 31%, whil.e blue—green algae made up 63% of
the total number of individuals. Similar results were obtained by Yan and
Stokes (1978), who found an increase in the ratio of green algae to blue—
green algae with increasing acidity.
A decrease in the number of rare species was strongly associated with
decreasing pH, as shown in the species list in Table 6—6. Highly acidic lakes
were dominated by Staurastrum flp., Scenedesmus p.’ AnkistrodeS falcatus,.
Peridinium inconspicuum and several species of small coccoid green algae.
Blue—green algae were sparse in the acidic lakes and were represented mainly
by Oscillatoria limnetica and Anacystis incerta . Other algae found In the
acidic lakes included Euglena Oocystis and Chlamydomonas p. Diatoms
were also rare in the acidic waters, with Tabellaria a• as the dominant
genus and Navicula and Melosira as the principal subdominants. The nonacidic
Florida lakes contained more rare species and greater numbers of blue—green
species such as Amigdalum quadridentata, Anabaenà pp., Spirulina laxissima
and Microcystis aeruginosa .
The species composition of the study lakes was similar to that for lakes
of comparable pH reported in the literature. Almer et al. (1974) found
ChlamydOmofla!L PerIdin inconspicuUtfl , and Oocystis as the dominants
in acidified lakes of Scandinavia.
A— 5
-------
1 -i
0
C.)
‘-4
0
0
‘-I
C.)
C)
‘-4
4 1
-.4
80
60
40
20
Number of lakes
Figure 6-12.
4.5—5.0 5.0-5.5 5.5—6.0
4 6 pH 2
6.0—6.5 6.5—77.0
4 4
fl
cyauop iytta
All othe s
Relative abundance of. major phytoplankton taxa in th lz kes grouped
within five pH intervals.
6—46
-------
Table 6—6. Phytoplankton distribution with pH from 20 Florida study 1ak s.
Phytoplankton 4.5—5.0 5.0—5.50 5.51—6.0 6.01-6.5 6.51—6 7
Stczuras trwn app. x x
Synedesnrus x
Lyngbya X X x x x
Oecillatoria limnetic X x x x
Peridiniurn incthnspicum x x x x x
Chroomonas ap. X x x x x
Ankistrodewnua faloatus x x x x x
Selenastrwn minutuin x x
hlädcmonac X X X x x
Elakatothrix gelatinosa x
Rhabdoderr a sp. X X x x
Anacystis incerta X X X X X
Glee theca linearis x x
Penats diatom sp. X X x x K
Tabellaria sp. X X X
Closteriwn sp. X X X X
Euglenasp. X X X X X
5,nall gr. coccoida x x x X K
Oocystis pusilia X X X X K
Dinobryon sp. X X X X
Anacys ti a riontczna X X X X
Phacus sp. X X X
Cosmariz’ii app. X X X X
Te adOn minimwn x x x x
Croococcus lZ-P?lflf3ticuS X X X
synedra x X X K
Kirchnierolla contorta X X X X
Arnigdalum quadridentatcz X x X X
Closteriopsis X X X X
Dactylococopis rhaphidioides x
Crucigenia tetr apodia K X x x
Microcystis aeruginosa X X
Chiorella sp. X X X X
Centric diatom sp. x x x X
Gciirphcsphaericz lacustris x
pseudotetraspora sp. X X
GonyoatomWfl semen x
Spiru li-na laxiasima X X X
Aehanothece n! -dulcrns
Aster-one 7 la forrnasa X x x
Anabasna sp. X X K
Melosira herzoqii x x x
RhizcSoZeflW sp. x x K
Chiorogoniwn eZ.ongotum x
Oscillator-a angustissima x x
Anacystis the rmalis x x
E’chinosphaerilla P• x
Gieocapsa rupestri-s
Staurodesmus dijectus
Schizothrix calcicola K
Mallomonas sp. X K
-------
The overall effects of increased acidity on the phytoplanktoa coutmuxtitie i
of Florida lakes thus include a reduction in number of species and individuals
and lower chlorophyll a. Blue—green algae were found to be dominant in non—
acidic lakes,while green algae were the most common group in the acidic lak s.
The effects of pH onthe phytoplanktort community are confounded in part
by a trend of lower concentrations .of total phosphorus in more acidic lakes..
laikton
Zooplankton community structure in the 20 study lakes was analyzed based
on the number of species, abundance of individuals, and the distribution of
individuals among the various species. In addition, two common multivariate
statistical techniques were used to reduce the dimensionality of the data ar d
to generate trends from the complicated data base. The first method involved
classification of the zooplankton communities in the 20 study lakes based on
cluster analysis and a calculated similarity matrix. The second method invo1 ved
ordination, i.e. extraction of principal coordinates or axes for the 20 lake&
from the multidimensional hyperspace based on their zooplankton communities.
These statistical methods show correlations between environmental factors and
biotic responses but do not imply causation. If similar trends are depicted by
each technique, a stronger correlation between pH and zooplankton communities
can be deduced.
Zooplankton Community Structure
Reduced species richness is often associated with acid—stressed environ-
ments. As the number of species decreases, the rare species are lost, and
species that can tolerate the altered environmental conditions increase in
dominance. Increased acidity in freshwater systems has been associated with
general decrease in the number of zooplankton species (Yan 1979; Sprules 1975;
Parsons 1968). In the present study, the mean number of zooplankton
— I c
-------
species in the noriacidic group was 19, while in the acidic group only 14
species were found (Table 6—7). The Kruskal—Wallis rank—sum test indicated
that the number of zooplankton species in the various lakes was statistically
different at 0.005. The distribution of species richness across 5 pH
intervals (Figure 6—13) showed.a mono onic increase in the number of species
from the second lowest pH interval (13.5 species at pH 5.0 — 5.5) to the
highest interval (19.5 species at pH 6.5 — 7.0). The most acidic group
(pH 4.5 — 5.0) had approximately the same number of species (13.7) as the
next pH interval. The range of species richness was relatively small over
the entire pH spectrum, suggesting that pH does not have an overwhelming
effect on zooplankton diversity in Florida lakes.
The number of zooplankton species found in the present study is much
higher than the numbers reported in other studies on lakes of comparable pH.
In a study of acidic lakes near Sudbury, Ontario, Yan (1979) found about
half as many zooplankton species in lakes with pH values comparable to the
acidic Florida lakes. Leivestad etal. (1976) found that numbers of zoo—
plankton species in acidic Norweigan lakes were two to three times lower
than those observed in the present study. Lower concentrations of toxic
heavy metals that are often associated with acid precipitation may be re-
sponsible for the higher species diversity found in Florida lakes, but fur-
ther studies are necessary to evaluate this hypothesis. In addition, sub-
tropical lakes in Florida are not subjected to the harsh seasonal fluctuations
that occur in temperate lakes. The range of temperature in the Florida lakes
was about 12 to 30°C during the year of sample collection. All 20 lakes are
oligotrophic or mesotrophic, and none exhibited anoxic conditions in the
water column. With such moderate environmental conditions, the adaptive po-
tential of organisms to an external stress such as increased acidity may be
enhanced.
The population density of zooplankton also ,has been shows to decrease
-------
Number of
lakes
30
25
C ),
c i
( I
ci
‘I ,
(44
0
c i
E
5
15
10
4.5—5.0 5.0—5.5 5.5—6.0 6.0—6.5 6.5—7.0
pH
4 2 4
Figure 6—13.
6
4
300
._#sJ ,_,
U ,
i_ J’J
0
150
0
1::
0
Average number of species (per lake) and average number of
zooplankton individuals per liter for the 20 lakes grouped
Into five pH intervals.
6—50
-------
with decreasing pH (Yan 1979; Yamamoto 1972; Parsons 1968),.. The mean
abundance of zooplankton in the 10 acidic Florida lakes (Tabi e 6—7) was
7.5 x 1O individuals/rn 3 (range 3.0 — 13.8 x 10k), while the corresponding
values for the lOnonacidic lakes were 14.5 x 1O and 3.8 —3 .2.6x 1O 4 . The
scatter in population values at a given pH precludes delineat ion of a simple
trend between zooplankton population density and p 1 1 (Figure 6—14), but the
Kruskal-WaLLis rank—sum test indicated significant differences (n = 0.005)
between the mean number of individuals in the lakes.. Althoug..h a histogram
of mean zooplankton numbers for the five pH intervals suggest .s a trend of
increasing numbers with increasing pH, large and overlapping terror bars were
found for each interval.
The abundance of zooplankton in the lakes was influenced by phyto—
plankton density, as shown by the correlation between zoop1an ton numbers
and chlorophyll levels in Figure 6—15. Since chlorophyll lev .els increased
with increasing pH, the modest trend noted between zooplanktot i abundance and
p1-I may reflect changes in overall lake productivity rather th n direct effects
of pH on zooplattkton growth and survival rates.
Mean annual zooplankton biomass (Table 6—7) was calculated from species
counts and conversion factors obtained from the Literature (Dt .unont et al.
1975). Mean annual biomass for the 10 acidic lakes was 93 mg/ m 3 (range: 24
to 175 mg/rn 3 ). The mean biomass in the ten nonacidic lakes w s 123 mg/rn 3
(range: 49 to 268 mg/rn 3 ). Zooplankton biomass displayed trer ds similar to
those observed for zooplankton abundance. Much of the variatiLon between pH
intervals associated with zooplankton biomass, reflects change s in the pro-
portions of species of differing sizes.
Of consIderable importance in evaluating the effects of increased
acidity on zooplankton communities is the change in species cc . rniposition with
6—31
-------
Table 6—7. Summary data on zooplahkton and related diversity indices in
the 20 Florida lakes.. 1
Shannon— Evenness Modified
I t
Weaver (H/H ) Simpson s
Number Individuals Biomass Index Index
Lake pH of species #/m 3 mg/rn 3 (H) (SI*)
MeCloud- 4.71 11 79,400 116 0.86 0.77 0.82
cowpen 4.84 13 •-30,-500 24 0.86 0.73 0.82
Anderson—Cue 4.89 14 135,500 170 0.87 0.70 0.82
Galilee 4.96 17 86,400 110 0.99 0.76 0.87
Brooklyn 5.01 12 137,800 120 0.85 0.72 0.8].
Rosa 5.05 13 77,900 175 0.66 0.55 0.69
Sheeler 5.09 12 33,200 33’ 0.86 0.75 0.83
Magnolia 5.10 15 47,300 57 0.83 0.66 0.81
Lowery 5.19 15 45,400 60 0.95 0.77 0.86
Johnson 5.20 14 79,000 64 0.89 0.73 0.83
Annie 5.72 16 108,900 72 0.81 0.63 0.79
Aj.tho 6.00 18 70,400 49 0.93 0.71 0.84
Josephine 6.07 20 326,400 268 0.97 0.71 0.85
Geneva 6.12 18 93,500 132 0.89 0.67 0.83
Letta 6.37 18 150,200 92 0.89 0.67 0.80
Placid 6.40 17 154,300 103 0.94 0.74 0.84
June 6.64 21 201,600 137 1.07 0.78 0.88
Francis 6.66 23 194,300 190 1.03 0.74 0.85
Kingsley 6.68 15 109,800 66 0.86 0.68 0.80
Clay 6.69 19 38,400 120 0.95 0.71 0.83
Counts and biornass are averages of four (quarterly) samples. Diversity indices
are calculated from mean counts of the four sampling dates.
6—52
-------
S
300
250
200
150
100
S
50
S
0 I I
4.5 5.0 5.5 6.0 6.5 7.0
pH
Figure 6-14. Average number of zooplankton individuals vs. pH.
6—53
-------
I 1 I I I t I 1
4.0 6.0 8.0
10.0
Chlorophyll a (mg/rn 3 )
Figure 6—15.
Relationship between zooplankton population density and
chlorophyll a concentration in the 20 survey lakes. Data
are averages for the four sampling dates.
250
200
150
0
.1
a
.
r 2 - 0.61
0
0
2
12.0
6—54
-------
pH. A group of acid—tolerant species was dominant in all lakes (from pH
4.71 to pH 6.69) and consisted of Diaptomus floridanus, Cyclops varicans,
Bosmina longirostris, Daphnia ambigua, Keratella cochlearis and Mesocyclops
edax (Table 6—8). Other speèies that were found at all pH.levels but were
not dominant included Tropocyclops 2rasinus, Leptodora kindti, Trichocerca
multieninus, Conochilus unicornis and POlyarthra vulgaris . The majority of
the species restircted to lakes of high pH were rotifers, and these were rare,
even in thelakes where they were found. One notable exception is Asplanchna
sp., which occured consistently in lakes with a pH greater than 6.0.
A similar group of zooplankton species dominates both acidic and non—
acidic lakes in Canada (Sprules 1975). The dominant acid—tolerant species
reported by Sprules include Mesocyclops edax, Cyclops bicuspidatus thornasi,
Diaptomus minutus, Holopedium gibberum, Diaphanosoma leuchtenbergianum and
Bosmina j. Five of the dominant genera found by Sprules also were found to
be acid—tolerant in Florida. Daphnids have been reported to be absent from
acidic lakes in several studies (Yan 1979; Parsons 1968), but Daphnia arubigua
was present at all pH levels in the Florida lakes and had a yearly mean
abundance of 6 x 10 3 /m 3 in the most acidic lake (pH 4.71).
In order to obtain overall trends of species composition with increasing
acidity, the percentage of total number of species contributed by copepods,
cladocerans, and rotifers was calculated. Rotifers were the major zoo—
plankters in every pH interval (Figure 6—16a), but their contribution de-
creased from 58% to 357. of the total number of species from the least acidic
to the most acidic group of lakes.. Copepods were the principal subdominant
group at all pH intervals and displayed an inverse trend to that of the
rthtifers, i.e. an increase in importance with decreasing pH (21% of the total
species at p1-1 6.5 — 7.0 and 35% of the total species at pH 4.5 — 5.0).
6—55
-------
hie 6—S. Composite species list from 20 Florida lakes
our quar ers.
oc era
.teila cochisaris
cthocerca ‘flu 1 ti crinus
lyarthra vulgoris
ichocerca longice ta
tO jhilu8 Unicornis
cztelZa taurocephula
ilicottla sp.
c hi onus quadridenta ta
whi onus hauanaensis
linja sp.
riostyla ap.
achi onus angu lan s
rate 1 la quadrata
zchi onus cczlyciflorua
eoso,na sp.
Btropus sp.
Iomatus sp.
ttyias patulus
ochiloideS sp.
?ans sp. _______
XXX
XXX
Xx
x x x
xx
XxxxXX
xxxXXx
x XXX
x xxx
x
XX
XX
XXXXxT
x x
x
x
x
K
Xx
xx
Xx
x
Acid lakes
pH
4.7
Non—Ac td lakes
0 )
(1) ) —
o G) 4 i ,—4 .S
4) r . 4 0
o ,—4 0
o a
.c Q
to 5.2 5.7
c j
‘.4
,—4 3
r . 4 C .i C I) )
CT3 4) 4) ‘ .4 0
Cl) 4) O IJ
0 .c 0 0 -4
C ) U) < <
to
‘.4
- -
1. > • . 4
) ) I -I J 4)
C C C
04 ) 0 ‘—I n
) 0 ‘ )
6.7
C l )
r4
C) C l)
CC) C CC)
i - —
0
aptomus floridanus
C10p3 VaP1 CcUZS
6ocyclops edax
opocyc lops prasintw
‘a&ilua ep..
pepodi te
up iii
K X X.X
x x- •x x
XXXx
XX X
x x.x - x
XxXx
XXXX
XX
xx
XX
XX
XX
xx
XX
xx
X
.X X X X
xXXX
XXX X
xx X
XXXX
xXXX
xXXxx
XxXxX
XxXxx
x xxx
Xxx
XxxXX
xxXxX
c x x x
_x x x
y< x x x
x x x
- x
H X X X
M X X X
x
X
X
X
X
x
mina longiros tin-s
phnia ambigua
todora kindtii
‘czture CZ.odoceran
idorus sphaerwUs
nrinopsis die tersi
1phano8O7fla brachyurwn
x’iodaphnia reticulata
r acephalus st’.
lopedium arn’zzcnicwn
x
X
X
x
X
xx
xx
xx
XX
XX
x
x
K
x x x
x
c x x
Xx
XX
X
X
X
X
K
XXX
X X
X
xxx
XXX
XXX
x
X
XXX
x
XXX
x
x x
X X
x
X
XXXx
XXX
XX X
x x x. x
X X
Xxxx
XXXx
X
X X
X
x
x x x x x: x x x x
X X X X X X X X X
x x x x x x x x x
x x x x x: x x x X
xx xx xx x
I X X
XXI i(XXXX
x X X
Xx
X XX
XX X
X X
x
x
X
X X
x X
X
x
akes listed in order of increasing pH. X indicates the species was found in the lake at
east once during the four quarters.
-------
Number of
lakes
cladocerans
80
60
40 -
20 -
B.
N
N
N
N
N
4.5—5.0 5.0—5.5
4 6
5.5—6.0
pH
2
6.0—6.5 6.5—7.0
4 4
copepods
cladocerans
Rot if e r s
t ure 6—16. Average percent contributions of three na or groups of zooplankton to the
total number of speciec (A) and total number of individuals (B) for the 20
survey lakes grouped .nto five pH .r c: ’lc.
A.
80
60
40
20
4.5—5.0
4
5.0—5.5 5.5—6.0
pH
6
2
4
6.0—6.5 6.5—7.0
4
copepods
Rotifers
-------
Cladoceran importance remained fairly constant across all pH intervals and
represented between 18 and 22% of the total number of species.
Trends in the percentage of the total number of individuals contributed
by the three major groups of zooplankton over the five pH intervals are more
complicated (Figure 6—16h). In acidic lakes (4.5 — 5.5), copepods contri-
buted the largest proportion of the total zooplankton abundance (63 to 71Z),
and rotifers contributed only 21 to 30%. Cladocerans made up only 8 to liZ
of the total zooplankton abundance in the acidic lakes. In the p11 range
5.51 — 6.5, copepods declined in dominance, while rotifers increased to 46Z
of the total. individuals, but the percentage contribution of each zooplanktnn
component in the pH range 6.5 — 7.0 was nearly identical to that found in
the most acidic group of lakes. Based on these results, no clear trends irk.
the percent of total zooplankton abundance can be detected across the pH
spectrum.
Species diversity indices have been widely used to describe b1oti .
communities in ecological studies (Sanders 1968; Pielou 1969). In the
present study, three diversity measures (Table 6—7) were calculated fr,m the
mean annual zooplankton data for the 20 lakes. Simpson s Index
[ si* = I n (N —1)/N(N(N 1)1 defines the probability that two individuals
selected at random will be of the same species (Simpson 1949). in the
present study we report Sl = 1.0 — SI so that values of 1 and 0 correspond
to total eveness and extreme skew, respectively. In addition, both the
Shannon—Weiner function Cu’ = p log (1/P.)] and evenness [ H’/H’niax] wer’a-
computed.
The mean value of SI* from the acidic lakes was 0.82, and the mean
value from the nonacidic lakes was 0.83; thus based on this index, no
differences in the zooplankton communities can be discerned between the
6—56
-------
acidic and nonacidic lakes. The mean value of H’ for the acidic lakes
was 0.86, and the mean value for the nonacidic lakes reflects their greater
species richness. The two groups of lakes had nearly identical evenness
measures (E 0.71 for the acidic lakes; E 0.70 for the nonacidic lakes).
Since H’ has both an avenness and a species richness component, the higher
H’ for the nonacidic lake group thus reflects a higher number of species.
Overall, the similar mean values for the three measures of diversity for the
two groups of lakes indicates that little difference exists in the species
diversity of the zooplankton communities of acidic and nortacidic Florida lakes.
Classification of Zooplankton Communities
Cluster analysis was used to identify patterns in the zooplankton
communities associated with increased acidity. This method assumes that
some general set of controlling factors is acting on the biotic community.
Thus, the various species assemblages act as a natural bioassay, permitting
the detection of major influences exerted by environmental and biological
parameters. Conclusions drawn from this multivariate technique, as well as
those from the univariate techniques used earlier in this section, are cor-
relative and do not prove causation. Sneath and Sokal (1973) dIscussed the
principles and techniques of classification’in detail, while Poole (1974) has
reviewed methods for cluster analysis. Czekanowski’s similarity index was
used to measure the similarity between the various zooplankton communities
(Cormack 1971). Recent studies (Bloom 1979) have demonstrated the superiority
of this index over other indices to accurately group assemblages of known
similarity. The zooplankton data were log transformed CX’ la(x -1- 1), and no
standardization was used. Two types of classifications were generated:
standard (Q—rnode) analysis, which clusters the lakes according to the simil-
arity of their species composition, and reverse (R- .mode) analysis, which clusters
the species according to their similarity of occurrence. Both analys’ s were
rn -
-------
performed using quantitativ actual count) data and qualitative (presence—absence)
data. The former thus includes information on the relative dominance of
species, while the latter disregards abundance.
Results of the cluster analyses are presented as dendrograms, in which
groups of similar objects are depicted by the joining of lines into progres-
sively larger groups.. The dendrogram generated from Q—mode quantitative
classification of quarterly zooplankton data from the 20 lakes (Figure 6—17)
shows a strong effect of seasonality on zooplankton communities; clusters of
highest similarity generally comprised of various lakes within a single
season. At a arbitrarily defined similarity level of 63Z, 11 groups of two or
more stations were defined, along with a number of solitary stations. Clusters
g, h, i, j and k are comprised primarily of acid lakes, and a single season
(fall, winter, or spring) dominated each cluster. Two nonacidic lakes
(Kingsley and Geneva) also are included in this group. Clusters b and e are
mostly from the summer quarter and are made up of both acidic and nonacidic
lakes. Clusters c, d and f are dominated by nonacidic lakes from all four
quarters. The overall trend suggests that a greater difference in zooplank—
ton communities exists between the acidic and nonacidic groups during the
fall, spring and winter quarters and that a higher level of similarity exists
during the summer. Results of Q—mode classification based on presence—absence
data followed the same patterns described for the quantitative data. The level
of similarity of the various groups was higher because the effect of dominance
was removed by considering only presence—absence data.
In order to assess the overall yearly trends in zooplankton communities,
a classification was conducted on the yearly mean data. A dendrogram obtained
from the mean annual quantitative data (Figure 6—18) shows that two major
groups are formed at the 68% similarity level. One group is composed of seven
lakes with a p 1 - I range of 6.00 to 6.69. The second group contains ten acidic
6—60
-------
LETT WF
LONE r
LTO SF
FrIAN JLI
PNDO SLI
L TT U
1LCL IJ
JOHIl SLI
C A U
SH E k
)IAGN SF
JIJNE SP
tN1j if
CENE U
tLRr S F ’
LETT ‘
JOSE SP
rFIAN S F
LAC NFi
CL r
COMP ’
HEE SU
GALl SU
CLPI SU
LOHE 5IJ
:j NC SLI
I ’1 GN 51.1
RNNI S I’
NNI NF
GALl S F
PNIil FL
S CW kJP
JUNE U
LPC ;P
AL1f U
LEIt L
JOSE SL
FR tJ FL
CLAJ ’ FL
JuSE FL
JUNE FL
IIJ3E J lPi
4LTO i ;P ,
PLAC U
PLF C EL
FF P • HF:
JUNE HF
OUF FL
LOWE FL
NOU FL
ALTO F
Mkc.u U
CONF’ SF
¶IEE S ’
4F1Nf F’
8POK II
ROSS
KINC, UF
BFOK SF
AHDC1 -.iP
GENE F
JOHN N
MCCL FL
F O A FL
c i Oo IFi
rlNG FL
GENE FL
C. LI FL
F1( FL
M ’. N FL
MCCL SF
JOHIl FL
CS EF;
MCCL kIFI
COUP HA
SHEE HF
LCNE HR
C LI HF;
100
75
Level of Similarity
6—17. Dendrogram of the 20 lakes based on quarterly quantities z’3oplankton data.
ames oct the left represent lakes and seasons sampled.
-------
ALTHO
LETTA
v)
JUNE
CLAY
C.-,
F FRANCIS
JOSEPHINE
PLACID
ANDERSON
BROOKLYN
KINGSLEY
GENEVA
LU WE RY
ANNIE
(11
tJJ
— GALILEE
MAGNOLIA
JOHN SON
MC C LOU D
ROSA
COWP EN
SHE EL ER
Similarity Index
Pigure 6—18. Dendrogram of the 20 lakes classified using quantitative.zooplanktOfl
data (annual average population distributions).
pH
6.0
-------
lakes (mean pH 4.71 to 5.2) and three nonacidic lakes. The latter three
lakes all are considerably more oligotrophic than the other nonacidic lake ,
suggesting that the zooplankton communities are heavily influenced by phytc’—
plankton abundance.
An R—mode cluster analysis using quantitative data on the relationshj s
among the species found in the 20 lakes (Figur 6—19) shows that the group
of acid-tolerant species that were dominant at all pH levels grouped to—
gether at a high level of similarity. These six species, along with copepc dites
and nauplil, constitute a group delineated at the 87% similarity leveL
Species groups were added to this central group of dominant acid—tolerant
individuals in order of decreasing occurrence and abundance.
Ordination of Zooplankton Communities
Ordination methods are useful in extracting information on underlying
factors or trends from a complicated data base. Ordination techniques sucl
as principal component analysis and factor analysis have been used in both
terrestrial and aquatic studies (Bray and Curtis 1957; and Shannon and
Brezonik 1972). In the present study, principal coordinate analysis (PCOR)
was applied to log—transformed data from the 20 study lakes, and a series of
principal axes were calculated to account for the variance within the placer—
ment of the stations. The principal axes are linear combinations of the
variables that explain the maximum possible variance in the original data.
In simple terms, the principal axes can be considered as new (derived)
variables that reduce the dimensiona1it of the original data set. The de-
rived variables can be considered as underlying factors explaining the var1a-
tions in the measured variables. For further explanations of ordination
techniques, see Cowers (1966), Sneath and Sokal (1973), and Poole (1974).
Principal coordinate analysis of the zooplankton data was dote using
the computer program described in Bloom et al. (1977). The zooplankton
G—63
-------
Figure 6—19.
fr1 ThJlDM 5F
El. FACH1
H. HOLOPE
C. RETICU
LECArt ‘
P _Ei
L. P 1ELL
P. P TIJLtJ
COtJDC 3P
.
B. 1JIJ OAI
. CRL(C1
C. PHREF
M’JNriS 3P
. fiRvI:1 u
E GP P
JIJV. CL 4D
K. TP JROC
KELLL 3P
1 . !1IJLrtI
r. LO iGi C
r. F 3iN
LEPcJSP
0. PML IGU
C. V RIC
B. LIJNGt R
0. rL 9 o
Cc’?EPC’D I
I. CIJCMLE
r. ‘f’JLO
r: .! ‘
r,. c L.rI ._.
FILIrI
6. ArIC JLI
E . D ETEF
P
rJ Iq0F q
10 ii
Deridrogram from an R—rnode classifieatjoo of zooplankto taxa, based on
annual average population densities in the 20 lakes.
6-64
Level of Similarity
U
-------
counts for each lake were first log—transformed (to obtain normal distribu-
tions), and Z—scores for each species were then computed so that all variables
had means of zero and unit variance. Figure 6—20a presents a three dimensional
view of’ the 20 lakes plotted on the first three principal axes. These axes
account for 54% ôf the variance in thedaea, which is rather good for such a -
complicated’ data base. The overlap of several of the lakes in Figure 6—20a
obscures some of the information, and the exact location of each lake on the
three axes can be obtained from Figures 6—20b and c, which show cross—sectional
views of the 20 lakes on planes representing axes I and II, and I and III,
respectively.
Two math groups of lakes are visible from Figure 6—20b, a dense group of
13 lakes and dispersed group of 7 lakes. The smaller group contains only
nonacidic lakes, and the other group consists of ten acidic and three non—
acidic lakes. These two groups of lakes agree in composition with the two
groups obtained in the cluster dendrograrn (Figure 6—18), further indicating
a difference in the zooplankton communities of the two groups of lakes. With-
in the group of seven nonacidic lakes, three lakes (Josephine, Francis and
June), are located away from the rest of the group, and they had the highest
numbers of individuals and the greatest number of species of all 20 lakes.
A further similarity between the clustering and ordination results is the
relative positions of Lake Cowpen and Lake Sheeler. Both lakes are highly
acidic with low—color content, and both had reduced species richness and low
zooplanktori abundance. These lakes were the last to be added to the cluster
of acid lakes (Figure 6—18), and both are grouped together (and at some dis—
tance from the other acidic lakes) in the ordination graphs (Figure 6—20a—c).
The overall pattern depicted by the multivariate analyses suggests that
a difference exists between acidic and nonacidic lakes, but low productivity
nonacid lakes are grouped with the acid lakes.
-------
13.
6
C.
17
73 7
. -L 14
19
2
70163 7 5
Figure 6—20.
Principal coordinate analysis of study lakes based o t zooplankton
community structure. A. Placement of lakes on Eirs 3 principal
axes. B and C. Placement of lakes on first and sec cnd and first
and third principal axes, respectively. For lake nur iber code, see
Table 6—1. Black circles represent overlapping lake. .
12
(1)
I
6
5
7 12
17 13
4 2
Principal Axis I
A.
PrincipaL Axis I
6
6—66
-------
Benthic Invertebrates
Community structure of the benthic invertebrate asserablages fran the 20
study lakes was analyzed based on species richness, abundance of individuals
and species diversity. In addition, both cluster analysis and ordination.
were used to detect differences in the stnictureof the benthic communities
among the 20 study lakes.
pecies Richness
Reductions in the number of benthic species have been related to in-
creases in acidity in lakes (Parsons, 1968; Leivestad et al., 1976). The
present data also indicate a slight reduction in the mean number of benthic
specLes with increasing acidity (Table 6—9). The mean number of species in
the 10 acidic lakes (pH <5.6) was 24.6 (range of 21 to 30), and the mean in
the 10 nonacidic lakes (pH >5.6) was 26.6 (range 17 to 37). The mean num-
ber of benthic species within the 20 lakes was found to be statistically
different using a Kruskal-Wallis test (oL .005). The mean number of species
showed considerable variation between lakes •in both the acidic and nonacidic
groups. The nonacidic group of lakes exhibited the greatest
variability, a fact that can be attributed to the greater trophic diversity
of this group. Lakes with the highest numbers of species routinely were
the most productive. Arranged according to the five previously established
p11 intervals, a bimodal pattern of species richness emerges with the great-
est number of species occurring in -lakes of either the highest or lowest
pH (Figure 6—21). Such a distributioc suggests that species richness in the
study lakes is controlled by factors other than pH.
The importance of sediment characteristics as a controlling factor for
6— 7
-------
b1e 6—9. Summary of data on benthic invertebrates and related diversity indices
for 20 Florida lakesJ
Number Individuals Biomass Shannon- Modified Evern’ ess In.
of 2 2 Weaver Index Simpson Index
pH Species (#/m ) ) (H’) ) }r [ H i ax
C1 ud. 4.71 28 5380 0.354 0.88 0.81 0.61
wpen 4.84 30 2130 0.168 1.05 0.85 0.71
erson—Cue 4.89 25 3720 0.364 0.85 0.75 0.61.
i].ilee 4.96 24 1450 0.403 1.06 0.88 0.77
rooklyn 5.01 26 1100 0.320 1.14 0.81 0.90
sa 5.05 23 3990 0.376 0.87 0.80 0.64
ee1er 5.09 23 2950 0.428 0.75 0.73 0.55
gno1ia 5.10 21 2590 0.557 0.75 0.76 0.57
wery 5.19 23 940 0.223 1.03 0.86 0.16
hnson 5.20 23 980 0.335 1.02 0.85 0.75
nie 5.72 17 2860 0.299 0.59 0.60 0.48
tho 6.00 17 1240 0.080 0.69 0.68 0.56
Dsephine 6.07 33 2130 0.596 1.85 0.56 .71
eneva 6.12 24 690 0.127 1.05 0.86 3.76
tta 6.37 25 1220 0.331 1.12 0 90 0.80
.acid 6.40 27 1940 0.728 1.04 0.86
tine 6.64 37 2330 0.705 1.05 0.84 0.67
iancis 6.66 32 2490 0.632 0.99 0.86 0.66
ingsley 6.68 22 1980 0.254 0.83 0.77 0.62
6.69 32 3960 0.457 0.80 0.53 0.73
a1ues are averages for the four sampling periods.
6—68
-------
Number species
Number individuals minus C. punctlpenñis
30
cI-
0
0
0
z
umber of lakes
4.5—5.0 5.0—5.5 5.5—6.0 6.0—6.5 6.5—7.0
4
6
pH
2
4
4
Figure 6—21. Mean number of species of benthic invertebrates and their mean
population density for the 20 lakes grouped into five p1-I intervals.
Number of C. purttipenuis
6
E
0
—4
—I
S
4 -
- -1
-o
t’- 1
0
4-4
20
z
— 69
-------
benthic community structure has been well—established by Harp and Campbell
(1967) and Bloom et al. (1972). The wide variation in species richness at
all pH levels in this study may in part be attributed to interbasin varia-
tions in sediment characteristics. Based on the previously established pro-
ductivity — pH relatioiiship, organic deposition and thus sediment organic
content may be expected todecrease with decreasing pH. Thus, species re-
quiring a highly organic substrate for either deposit feeding or burrow
formation may be excluded from lower pH lakes. The variations in the benthos.
response within a given pH interval is a reflection of the fact that the or-
ganic content of sediments is influenced by allochthonus organic inputs
from the watershed, as well as autochthonous production.
Finally, both the quality and quantity of food may limit benthos distribu-
tion. Filter—feeding species may be eliminated from low pH lakes due to the
generally lower algal concentrations in these lakes. In addition, bacteria,
which are known to be an important dietary component for some benthic in-
vertebrates, are in reduced concentrations in acidic habitats. (Anderson
at al. 1978).
Number of Individuals
A reduction in the total number of benthic individuals has been associ-
ated with increased acidity (Lackey 1938; Harp and Campbell 1967). Results
from the present study (Table 6—9) indicate a high degree of variability among
the 20 study lakes, with no clear reduction in the abundance of benthic in-
vertebrates being associated with increased acidity. The mean number of
benthic invertebrates in the 10 acidic lakes (pH <5.6) was 2,520/m with a
range of 936 to 5.380/rn 2 ; and nonacidic group (pH >5.6) had a mean of
2
2,080/rn , with a range of 692 to 3,96 /m
6—70
-------
When grouped into five pH—intervals, benthic invertebrate abundance
displays a bimodal pattern with the most acidic lake5 and the least acidic
lakes containing the greatest number of individuals (Figure6.—-zi), The present
results demonstrate a decline in abundance in moderately sci&ic lakes (pH
5.5—6.0), but do not delineate a linear reduction in benthic iuvertebra tes
with decreasing pH.
Larvae of the dipteran, Chaoborus punctipennis , were often collected in
benthic samples and were counted as part of the benthic invertebrate assemblage
in the present study. C. punctipennis is known to be associated with bottom
sediments during the day and to migrate up through the water •coluorn at night
(Roth 1968). Elimination of this species from our benthic cQ4WltS decreased
the total number of in.dividuals at all pH levels but failed tto change the
genaral abundance—pH relationship discussed above.
Biomass of Benthic Invertebrates
Biomass of benthic invertebrates (ash—free dry weight) g enerally de-
creased with decreasing pH in the 20 Florida lakes (Table 6—9;). Mean biomass
for the 10 acidlc. lakes was 0.32 g/m 2 and for the 10 nonacidic’ lakes was
0.42 g/rn 2 . The large variation in biomass of benthic invertetbrates in the
lakes ( Figure 6—22) suggests that additional factors besides pH are influencing
the distribution of the benthos.
pecies Div e s .fl
Species diversity was calculated separately for each of cthe 20 lakes as
Shannon—Weiner (H’), evenness, and Simpson (SI*) indices. Tho 10 acidic lakes
had a mean value for log H’ of 0.94 and a range of 0.75 to 1. 4, but the 10
nonacidic lakes had a slightly lower mean value for H’ of 0.90 and a range of
0.59 to 1.12 (Table 6—9). Thus, no clear relationship betwee !n Shannon—Weiner
-------
100C
E
!. 750—
c r3
0
E
° 500
•1-4
S
0•
o
- .S
S
250
S
0
4.5 5.0 5.5 60 6.5 7.0
pH
Figure 6—22. Mean biomass of benthos (ash—free dry weight) vs. pH
the 20 survey lakes.
6—72
-------
diversity and pH could be delineated.
Mean values for the modified Simpson’s index (Table 6—9) were 0.82
(acidic lakes) and 0,86 (nonacidic lakes). Simpson’s index is sensitive t
dominance by a few species. The slightly higher value for SI* from the 10
nonacidic..lakesreflects a more even distribution of individuals among the
various species. Overall, very little difference exists between the two
lakes groups in reference to the three measures of diversity, and no stron
relationship could be established between these indices and pH.
Community Composition
The relationship of individual species or groups of species to pH can
provide useful data on the response of benthos to acidification. A group cif
acid tolerant species was found to dominate invertebrate assemblages at all
pH levels: Limnodrilus hoffmeisteri, Hyalella azteca, Bezzia setulosa , tha o—
borus punctipennis, Coelotanypus tricolor, Procladius ., Stictochironomu&
devinctus, Cladotanytarsus sn., and Tanytarsus Other species also occtrrred
at all pH levels but were never present in large numbers (Table 6—10). Clti-rouom.i
larvae were an important component in the benthic communities of all study
lakes and accounted for nearly 50% of the number of total individuals as well
as a majority of the species in the acidic lakes. Chironomids were found i i
all nonacidic lakes but accounted for a smaller portion of the individuals
and species richness than in the acidic lakes. A replacement series of ma3.Dr
invertebrate groups was noted along the pH gradient (Figure 6—23). Oligochnetes
and amphipod increased in importance with increasing pH, but chironomids
and molluscs decreased with increasing pH, with no individuals of the 1att
group found in lakes with ‘a pH <6.0.
Decapods such as Palaemonetes paludosus were only found in lakes with
6—73
-------
anism
ge8ia tigrina
fl7nOd lu8 hoff i3teri
inbriculu8 S .
lobdella sp.
tlinobd 1 la ap.
t.8idiu.7fl Sp.
rbicuZa flunrin ca
xpcra sp.
stia sp.
id. Plecopot ra
donotides sp.
8a sp.
icola lirnosa
rczulus deflectus
t’ipar’us int. rt .ruS
al-ella aztec2
‘angonyx Sp.
urz narus sp.
Zaernonet s po ludosus
.rtrnocyth re s .
zgen-z a etc.
frnphue willicvr soni
Ldymope s .
genius breuistylus
ithemis sp.
cror’n.ca 8p.
nrpetrwn sp.
ptocella ep.
ychomia ep.
id. Tricoptera
ethira ep.
dropti lidae
zz -ia setuloscz
ohorus punctipennis
ocladius sp.
UPUG Z •
labesn yicz porajanta
e lotan ,’pus tricolor
elotonypus scapularicz
topynia sp.
a lauterbornie 1 la ep.
ironor us attenuatus
ptochi ronorrr s fuluus
ischia viridulus
achironomus
ctjnate l Lae
lypedil ?Jn hczlteral.e
lyped-l cn calaenum
x
x
x
x
xxx
x
x
x
xx
xxx
xx
xxx
xxx x
x x
xxxxxxx
xxxxx x
xx
xxxx
x
x xx
x xx
xx
x
x
x
xx
x
x
x
xxxx
xxx
x
x
x
xxxx
xx xx x
x
x
x
xxx
xx
x
xx
xx
xx
xx
xx
x
xx
xxx
able 6—10. Composite species list of Benthic invertebr.. from 20 Florida lakes.
Lakes listed in order of increasing pH.
C)
0
C)
C
0 C) •1-4 ., -
U) 0) r4 0) 4 0 .C c -‘-4 ‘-4
o 0) I- 4 . ) . .—4 C -1 (1) 0) C. > cc -,-4 ci )
0) r4 0 C 0) C C) r-4 0 C i 0) 1-) C) 0) C C
o 0 ‘C) 4 0 U) 0) 0 U) 4.J C 3
o o c Cr) 0 C Cc3 0 0 C r-4 0 0) 0 —4 0 ,-4 ‘-1
Z 0 < e (‘ Z .- - x < zo . -,
x x xx
xxxxxxxxxxxxxxxxx
x xx xx-xxx• xx x x
xx xx
xx
xx
x x x
xxx
xx •x -
xxx
x
x
x
XXXXXXXXXXXXXXXX
x x x
x
XXXXXXXXXXXXXXX
x x x
x
x
x
x
x
x
xx
x
x
x
x
x
x
x
x
xxxxxxxxxx
x
xxxxxxxxxx
xxxxxxx
xxx
xxx
xx
xxx.xxxxxxx xxxx
xxxxxxxxxx xxx xx
x x x
x xxxx
xxxxx
xxxxxx
x
xx
xx
xx
x
x
x. x
xx
xx
xx
xxxx xx
XXXXXXXXX
x
x
x
x
x
x
xxxx
x x
-------
Table 6—10. continued.
yptotendipessenilis X X X X X x x>:x x x x x x x x x x x
ictochironomus devinctu X X X X X x x x x x x x x x x x x
crotendipe leueoscelis X X x x x x x x x x x x
udochironomus sp. X X X X X X X X X X x x x x
ntaneu2lcz sp. X X
nfeZdia 3 p. x x x x
raciadopelma sp. x x
odotanytca’3u3sp. X X X X X X X X X X X X X X X X X XX X
nytc.rsus XXXXXXXXXXXXXXXXXXXX
neternpe llina sp.
r licz ap. X
iotcrnypus sp. X X
ectroclodius sp. X X x X X
atendipes sp. x
hocladinae x x x
ironornidaspwpcz xxxxxx xxxx XXXXXX x
ectrotanypus ep. X X
eudodicvnesa per trzax x
chooladius sp. x
totopUs sp.
ttia op. X X X
lerucella op. X X
.loepu8 op. X X X X X X X
°deosuo op. X x
6—75
-------
4.5—5.0 5.0—5,5 5,5—6.0 6.0—6.5 6.5—7.0
6 4
4
Figure 6—23.
Percent contribution of selected groups of benthic invertebrates to the total number
of benthic individuals in five pH intervals from 20 Florida lakes.
4
Oligochacta
Mollusca
Aniphipuda
Ephemeroptera
B. setulosa ; C. puntipennis
Chironomidae
All others
0
L)
0
4 -4
0
41 )
U
0
0
41)
1 1
80
60
40
20
Number of lakes
p h
2
-------
high pH. In most cases, species restricted to nonacidic lakes were found
in low numbers when present. Conversely, several rare taxa were found only
in acidic lakes: Macromia ., Psychomia ., Zavrelia . and Pseudodiamesa
per tnax .
The benthic assemblages •of all 20 Florida lakes were dominated by a
group of species whose distribution appeared tobe independent of pH. Indi—
vidual species confined to either acidic or nonacidic lakes never consticuted
a major component of the benthos in any lake. Thus, changes in the parti-
tioning of Individuals among species rather than the wholesale replacement
of species was the principal response of benthic invertebrates to increasing
acidification.
Classification of Benthic Communities
Benthic data were classified by standard (Q—mode) analysis using
Czekanowski’s Similarity Index on log transformed quantitative data from
the 20 study lakes. A Q—mode classification of quarterly quantitative
benthic data (Figure 6—24) did not demonstrate the same high degree of sea—
sonality displayed from a similar analysis of zooplankton data. The majority
of lakes, both acidic and nonacidic, showed a stronger interbasin similarity
than intrabasin similarity when considering all four quarters of data. Two
major groups can be identified from the Q—mode analysis (Figure 6—24); group
A is composed of nonacidic lakes, and group B is composed principally of
acidic lakes. The remainder of the dendrograrn consists of a large number of
very small clusters of both acidic and nonacidic lakes linked to groups A
and B at decreasing levels of similarity. Such a loose pattern of associa—
6-77
-------
-78
JIJNE HR
RLT(J SR
ALTF’ FL
Pr IO D SU
FRAN SU
JUNE SP
PLAC F
ALTO 51J
AI’INI SU
CLA I FL
JUNE SU
n wr sp
t rIE U
rLAT SF
AL1 P
ANL’P F
LIJH U
JOSE P
KING SF
SHEE SP
SHEF FL
coNr 3U
rowr F
&JHP V i
A rhE H R
H R
ALT ] HR
MAGN U
MCCL P
8POK SF’
GENE F
‘o3 HF
NNi FL
ANN I HR
FOP-IN HR
LiliE SF-
PLAC 3 1J
FOP-IN FL
ANOG FL
MCCL SU
HICL FL
FnA I HF
KINE FL
ANN! SF
FRAN EL
MCCL HR
, ‘ FRAN SP
\ LETT U
K LEfT fl.
LLAr lIr l
I J’J$E FL
JIJIJE FL
PLAC F
\PLAC 14
LFTT HR
0K FL
LONE FL
LOi iç i- i ;
KINu IJ
MAGN SF
GENE EL
JOHN SF
MACN HR
JOHN 5
ROSA Sr
G 1LI T U
rALI FL
R0I< SW
GAL! HF
MACN FL
R ’J5A SW
ROSA EL
rOSA HR
SHEE SU
AIIOIJ HR
SHEE HF;
1 013
Figure 6—24. Dendrogram of the 20 lakes based on quantitative data
for benthos. Names on the left represent lakes and sg son
50
Level of Similarity
-------
tion suggests that the structure of the benthic community is controlled less
by pH than by additional factors, including substrate heterogeneity.
ClassifIcation of the 20 study lakes using a Q—mode analysis of quan-
titative benthic data expressed as a yearly mean (4 quarters combined) per
each lakes (Figure 6—25) identified two distinct clusters, one composed of
acidic lakes (A) and one composed of nonacidic lakes (B). Six lakes, 2
acidic and 4 nonacidic, did not cluster within either group A or B. Two of
these six lakes, Annie and Sheeler, are very oligotrophic and are considerably
deeper than the other study lakes.
Ordination of Benthic Invertebrate Data
Principal coordinate analysis based on Gower’s distance measure, unit
variance standarization, and log normalized data resulted in a central lake
group with a small number of lakes some distance away (Figure 6—26a). This
three dimensional representation of the lakes plotted on the first three
principal axes accounted for 37% of the variance in the data. Lake Cowpen
(6) and June—in—Winter (12) show a high degree of dissimilarity from the re-
maining 18 lakes. Lake Cowpen (mean pH 4.84) contained the highest aluminum
concentrations of the 20 study lakes (Figure 6—6). Tricopterans and two
species of chirononiids ( Tariytarsus . and Pseudochironomus p.) were higher
in Cowpen than other lakes, but Chaoborus punctipennis , a major dominant in
both the acidic and nonacidic lakes, was totally absent. Lake June—in—Winter
(mean pH 6.64) contained the greatest number of total species as well, as
greatest number of species and abundance of molluscs.
The exact location of individual lakes in the central cluster of Figure
6—26a can not be defined because of the overlap of lakes. This problem can
be overcome by examining the position of individual basins on axes two and
three (Figures 6—26bc) relative to principal axis one. Two clusters are de—
6—79
-------
1
Sheeler
Rosa
Anderson—Cue
Mc Cloud
Magnolia
Johnson
Lowery
Galilee
Brooklyn
Lo tta
cneva
Cowpen
iac id
1 ings ley
Clay
June
Francis
Josephine
Annie
Aitho
75
Level of Similarity
Figure 6-25. Dendrogram of the 20 lakes classified on the basis of mean annual data
fnr benthos populations. AC is an acid roup NA a nonacid grouo of 1 1 er
6—SO
100
___ Li
I_
I I
50
-J
-------
B.
C.
20 18
1 8
12
11
14
7
H
H
H
C I ,
H
‘ -4
H
C)
2O
16
6 4
U ____
15 179 8
2
I
Principal AxSis I
re 6—26.
Principal coordinate analysis of study lakes based on bentJiic invertebrate
community structure. A. Placement of lakes on first thre e principal axes.
B and C. Placement of lakes on the first and second and first and third
principal axes, respectively. For lake number code see Ta b1e 6-4. Black
circles represent overlapping lakes.
H
H
CI,
C )
‘ - 4
.Ct
H
C )
H
6
10
14
TI
.5 7
Principal Axis I
A.
H
H
H
U,
H
x
—1
6—81
-------
fined from a combination of the first and second principal axes (Figure 6—26b),
one composed of 6 nonacidic lakes (cluster A) and one composed of 9 acidic
and 3 nonacidic lakes (Cluster B). This arrangement suggests a correlation
between the composition of henthic communities and pH. The inclusion of
three lakes with high pH and relatively low productivity i.e. Lake Geneva
(14), Annie (11) Aitho (12). in the acidic cluster also suggests a cor-
relation between trophic state and the structure of benthic communities.
The position of the 20 study lakes on the first and third axes (Figure
6—26c) shows a high degree of similarity between the acidic and nonacidic
cluster of lakes. No clear distinction is visible between the two groups of
lakes with reference to their position along the third principal axes, sug-
gestIng that most of the variation in the benthic data from the 20 lakes
that can be correlated with pH is explained along the first two principal
axes.
In summary, both classification and ordination techniques demonstrated
a general trend of greater similarity in the benthic communities of lakes
with similar pH. These drita do not indicate that a detrimer tal effect is
being exerted by decreased pH on the benthic biota. More complete studies
are needed to determine specific responses by the benthic invertebrates to
increased acidity.
6— 2
-------
FISH
Several preliminary studies on the fish populations in acidified Florida
lakes also were undertaken as part of the present project. A qualitative
survey of the fish fauna of Lake Sheeler (mean annual pH 5.09) was conducte-d
w±th SCUBA during the summer of 1979. The narrow littoral zone wasdominated
by mosquito fish ( Gambusia affinis ) and secondarily by centrarchid finger-
lings. The pelagic fauna, although somewhat sparse, was comprised of sever a1
species of ceutrarchids, including bream ( Lepomis macrochirus ) and large—
mouth bass ( Micropterus sairnoides) , and one unidentified species of ictalur’ id
catfish. Largemouth bass ranged in length from approximately 25 to 60 cm.
Adult largemouth bass were collected from Lakes McCloud (mean annual
pH 4.71) and Anderson—Cue (mean annual pH 4.89) in July, 1979. A conditior
factor (K), relating body length (L, in mm) to body weight (W> in g) was
calculated according to the formula: K 105 W (Nikolsky (1963). Fish bodty
L 3
weight per unit body length (and thus the condition factor, K) should increase
in response to enhanced growth conditions. The mean K values for largemout i
bass from McCloud and Anderson—Cue were 1.00 (n = 3) and 1.19 (n 6), re-
spectively. These values are in contrast to a K value of 2.17 calculated
by Chew (1974) for largemouth bass in Lake Weir, Florida (mean annual pH 6.5),
suggesting that the fitness of largemouth bass declines with lake acidifica—
tion. This trend is not surprising given that aquatic productivity and thu: .
the food supply of these secondary carnivores should decrease with decreas-
ing pH. Consequently, fish populations may have to rely increasingly on
allochthonous organic matter to sustain them (Yamamoto 1972).
The age of individual bass was determined from microscopic examination
of scale annuli. The individual fish ranged in age from two to four years
old; thus although Anderson—Cue Lake has been acidic (pH <5.0) for at least
6—83
-------
the past 10 years (Table 6—2), reproduction of largemouth bass has continuech
These data are in contrast to those of Beamish (1976) indicating that small-
mouth bass (Micropterus dolornieui) , a congeneric of largemouth bass, failed
to reproduce in Ontario lakes with pH <5.5—6.0.
Cronan and Schofield (1979) att dbuted both the observed gill necrosis
and the general impoverishment of the fish fauna in acidified Adirondack
lakes to recent increases in aluminum mobilization within the watersheds as
a result of acid precipitation. Some physical damage to fish has been as-
sociated with Al concentrations as low as 100 ug/L, but the most serious
effects have been reported at Al levels above 200 pg/L. Wright and Snekvik
(1978) suggested that increased calcium concentrations may ameliorate the
deleterious effects of increased acidity on fish populations by reducing
sodiura loss from blood. Calcium concentrations generally declined with in-
creasing acidity in the 700 Norwegian lakes they examined. Based on this
survey, Wright and Snekvik concluded that fish could be expected in lakes
with pH values >4.5—5.5 and calcium concentrations >1—4 mg/L.
Based on the findings of Cronan and Schofield (1979) for Adirondack
fishes, we also examined the gills of the bass for signs of necrosis associated
with lake acidification. No evidence of either gill necrosis or of other
physical deformities were found in any specimen. The lack of a response may
reflect differences in water chemistry between Florida lakes and north—temperate
lakes of comparable pH, where responses were noted. If fish populations re-
spond more to concentrations of heavy netals and cations than to pH directly,
then observations of breedIng populations of largemouth bass in Florida at
pH values lower than those required by congenerics in temperate lakes may be
explained. Fish reproduction should not be impaired by either the low
aluminum concentrations (mean 58 i.tgIL) or the moderate calcium levels (mean
1.0 mg/L) found in acidic Florida lakes. However, it should be noted that
-------
these are preliminary observations, and that further studies are needed on
the distribution, fertility and growth of fish in acidic Florida lakes, as
welt as on the forms and levels of aluminum in the lakes. The effect of in-
creased temperature on the response of fishe in subtropical Florida lakes
to acidification also is unknown.
6—85
-------
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Analytical Methods for Chemical and Physical Parameters on Rain and Lake Samples.
Parameter Method Reference
pH
Orion Model 801 lonalyzer in the lab. An Orion Model 401 lonalyzer in the
field.
Conductivity
Beckman Model RC 16B2 conductivity bridge.
APHA
(1976)
Dissolved Oxygen
YSI Model 51A Oxygen Meter, Hydrolab Monitor, or Winkler wet chemical technique.
APHA
(1976)
Temperature
YSI t1odel 51A Oxygen Meter or Hydrolab Monitor.
Color
Sample centrifuged and compared against standard chioroplatinate solutfoTt at
420 mm on a Bausch and Lomb Spectromic 88.
APHA
(1976)
Turbidity
Hach Turbidimeter Model 2424 standardized with formaziri suspensions.
APHA
(1976)
Alkalinity
Titration with standard acid using color indicators.
APHA
(1976’
Total Kjeldahl
Manual semi—micro digestion followed by analysis of ammonium on neutrali c d
Nitrogen (TKN)
samples by alkaline phenol method on AutoAnàlyzer.
EPA
(1974)
-------
Sulfate
Chloride
Aluminum
Fluoride
Cations (Calcium,
Magnesium, Sodium,
Potassium)
Technicon Meth
#186—72W
APHA (1976)
APHA (1976)
APHA (1976)
APHA (1976)
EPA (1974)
Parameter
Method
Reference
Ammonium
Alkaline phenol method on AutoAnalyzer.
EPA (1974)
Nitrate
Cadmium (wire) reduction method on AutoAnalyzer.
Stainton (1975)
Total Phosphorus
Sample digested with ammonium persulfate, and measured using the single
molybdenum blue test on an unfiltered sample.
reagent
APHA (1976)
Orthophosphate
Measured at 880 nrn using the molybdenum blue test on a filtered sample.
APHA (1976)
Total Inorganic
Measured by combusting samples in a Beckman Model 915 TOC Analyzer with
analysis
and Organic Car—
in a Beckman Model 865 Infrared Analyzer. TC — IC = OC.
APHA (1976)
bon
Silica
Molybdenum blue method on Technicon AutoAnalyzer. (Analogous to manuel
method in APHA 1975)
Methylthymol blue method on Technicon AutoAnalyzer
Ferricyanide method on Technicon AutoAnalyzer
Eriochrome Cyanine R Method on Technicon AutoAnalyzer.
Orion Model 96—09 Specific Ion Electrode
Varian Model 1200 atomic absorption spectrophotometer.
-------
APPENDIX II
Volume—weighted mean concentrations and A ua1 Deposit ion Rates for
each site during the project period.
-------
- - - — — — . UILW .L V à JU LIL. I_ J .J *
position rates by site. (See end of appendix for explanation of symbols and
units).
005 SITE 1)ATL F 61N PH CON NA P. P10 C6 NH4 1103 804 CL OP TP 11.N
I APO ! ’Y.A WET
2 0033A k2 : r. KEY
3 U -LLC C 5Z WET
4 3Ic,’1 fiTQt1
5 !iC .:, ’ .3N
6 C1 L; .r KEY 8U_ , .
7 c. LE\
S CL. W15T0
9 C AE . 0 ;4
10 F74T PIYE
I CA’I .5 L.E OULK
12 C01 CVILLE WET
1) HASTINS
‘6 1
15 J.\Y
15 L/ ’ ’L I1 FRE0
17 : ?i .Ci3
3 LI 3
17 ‘i ‘ 1 81S
20 P. - ‘ , EL- 13
21 MI 1
22 STLART
1970 1013. 0 4. 57
19713 100.0 5.54
1’/73 10/. 0 5.24
i9’O 179.0 4.72
j773 137.0 4.02
9/u 13•/. 0 5. 12
1 U 14 . 0 4. 63
5711 107.0 5.60
EOLP . 3923 95. 8 5. 14
19/3 147.0 5.84
31/0 1340 4 04
17’3 134.0 4.66
197P. 119.0 5.07
1771 130 0 4 Cd
19/3 202.0 4. 58
1978 131.0 4.76
I #1 8 1’3 C, 4 95
17 0 1(9 0 4 09
17/fl 103 0 5 75
17/1.1 101 0 5 65
I’773 100.0 5.52
1973 95.4 5. 12
17.7
27.5
11.2
36.0
13.3
21.5
20.0
18.5
11. 4
16.6
136
13.5
17.5
21 4
19.
22.0
12 8
16 9
37 4
76 1
18. 1
23.9
0. 244 0. 0’/4
2.540 0 226
0. 346 0. 102
0. 34’1 3. 141
0.262 0. 114
I. 260 0. 101
0.245 0. 216
0-020 0.239
0. 434 0. 089
0. 43 0. 252
0 267 0 108
0. 187 0.071
0.64:-! 0.412
0 356 0 054
0. 282 0.089
0.501 0.133
0 34 0 0135
0 50 0 1,1
0 032 0 1 36
8 470 0 !t. .t
0.932 0. 2/2
2. 160 0. 3i0
0. 029
0.290
0.0.16.
0. 039
3.031
0. 16.3
0 036.
0 146
0. 053
0. 137
0051
0.031
0.117
0 ‘06
0. 0’4
0 152
0 014
0 019
0 C ’ S
I (.10
0. 176
0 2 .7
0. 106 0. 113 0.250 1.61
0. 803 0.090 0. 157 ItO
0 460 0. 120 0.212 1. 13
0.400 0 311 0. 160 3.78
0.203 0.179 0.161 1.57
0. 3 t 3 0. 311 0.211 1.64
0. 23 0. 4 )5 0. 353 2.37
1.030 0.240 0.267 1.95
0. 005 0. 099 0. 1 5 1. 02
1.230 0. 137 0. 12? 1.77
0 438 0 155 0 Z .38 I 57
0. 195 0. I!) 0. 209 1.32
0.274 0 233 0.176 1.91
0 871 0 264 0 313 2 98
0. 203 0.214 0 232 2.07
0.701 0.307 0.348 2.28
0 20/ 0 97 0 1 .4 I 2d
0 295 0 3 1 0 2.6 1 9 .
0 900 0 244 0 721 1 7
1 510 0 163 0 3 55
0.399 0. 137 0. 199 1.62
0.434 0. 177 0. 165 1. 49
0. 560 0. 005
4 720 0 009
0. 747 0 007
0. 700 C ’. 018
0 052 0.014
2.490 0. 053
0. 453 0.035
1.510 0.038
0. 890 0. Q
0.982 0. 0 2
0 51/ 0 )24
0. 608. 0 007
1.240 0 085
0 A.M 0 092
0. 481 0.012
C. 38 0.044
0 630 0 010
3 .?0 (1 0-.i
I 0 0 028
18 700 0 3.’
1.870 0. 018
4.000 0. 029
0.010
0.014
0.010
0.025
0.033
3.070
0 C64
0.057
0. 023
0 046
0 034
0.013
0005
0 104
0.020
0.0 2
0 C13
0 .157
0 8
0 0-.
0. 03]
0 030
0 223
0 2
0 272
0. 329
0 316
0 4C5
0 5:
0 494
0. 204
0 3
0 2/,
0 25 .
0
0 5C.
0. 0 . 7
0 .2
0
0 32
0 3
3. 35
0. 2 2
H
OI 0N 000P INOROW
TOTh
. U60 14
00 u)CI’
0E504 EXSO4 SESOEP
EX5OEP
03•10L2
! 3 P
1 0 C37t2 153
2 0 0(20 ‘2. 2 3
3 0. ;Cc( ’: 44
0 C ‘
S 0.C;5 306
6 3
01 . .3 ..3
K o. -C2:. ’Y ii-i
S 3 ( I -, .,
tO 0 :,144
ii 0.( l44314
12 C. . . -C ‘13775
13 0. 0’70O. ’6 114
14 0 jC (O )j)SO ’
is c ’ o :6_o7
16 Li. 0 ‘21 73/80
17 o.u2: 21l:2z7
13 0.JC ;25
1 C ‘I 3
20 0. o
2 0 2C3
22 C. 0C .2C ’37 65B
0 02 0.005 0.383
0 0 30 0. (305 0. 255
C. i: 2 0. 003 0. 332
0 1 0 00/ 0 299
0.137 0(119 0.240
0 I. / o 12 0 562
0 0 9 0 7 /8
02’ j.039 0.507
0 C (.1) 0 204
C’ P, ’ (I. 014 0.319
0 215 0.010 0.413
0 1 3 0.036 0.322
0.212 0.070 0.459
0 7- 14 0.017 0. 577
0 1 0 o’ 3 0 4 6
0 154 0. ( 4 0.655
S i .9 0.000 0.331
0 1 0 0.020 0.575
0 ...2 C,? 0 4 / .
0 210 ) 0 / 0 450
0 3 £ 0 5 0 336
0. ii 0 009 0. 342
0.471
0. 325
0. 404
0 517
0.477
0 o 9 9
0 9 j3
0781
0 339
0. 518
0.623
0.4t5
0.671
0.221
0 579
0. 819
0.470
0.725
0 653
0 660
0 5 4
0. 527
26. 9133
288-10
5 7544
19 Oa ’.b
15 1356
7 s . Lj
23 4 34 2
2.3119
7 •‘4 4
1. 4!1’4
14.4544
21 0776
0,511.1
13. 1626
26 3027
17. roo
11.2202
12.8825
j 7703
7 2307
3 02..i,
7. 5858
290. tOO
7F1 030
90. 344
311 u/7
207.353
101 9 ”5
7
27.300
69 401
21. 240
1v3.6.U9
293. 160
101.2.15
171. 373
521 314
227.
132.008
140.419
39 205
22 0 11
30 200
72. 380
0. 00100
0 63500
0. 02650
0. 08725
C. 06550
o 31500
0. 06125
0. 2050 D
0 10050
0. 11325
0 06873
0. 04675
0. lt .o50
0. 00900
0. 07C20
0. 12525
0. 00350
0. 00900
0. 15050
2. 11750
0 23300
0. 54000
1. 54100
0. 96500
1. 04350
1. 69275
1. 50450
I. 32500
2. 301375
1. 74500
0.91150
1. £!‘/.‘/S
1. 501, /3
1.27325
I. 74’i5O
2. 871 (0
1. 99950
2. 15475
I. 19850
1.90100
1. 21950
1. 43050
1. 00730
0. 9501.0
0.21980
2. 11267
0. 45288
0. 52359
0. 0i4 12
1. 43: 90
0. 203”8
0. 74403
0. 3.le.’4t 3
0. 6s 0
0. : ii.s
0. 2 3t(. 2
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0. 3 5O7
0. 47470
0. 54692
0. 34235
0. 32337
0. 54)00
7. 12652
0. 77667
1. 71720
5. 1764
3. 2187
. 46*0
10. *03 1
6. 8”0 ’5
6. 05 ’)3
11 2329
4. 3402
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1i .1L ’ .JJ
9 4331
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4. 0 C2
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4 6323
3.0219
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16 0000
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21. 5090
23
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15. 7440
21. 6912.
14 ?
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36330)
1. . 214 .
IS Kr,L . ’
2 2.2:3CC
3 1 . 3l’3
4 2 5:390
5 I.2 .1 ’23
6 2 .i7 ’ ; (
1 3
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to a
1 ) I. 64/20
12 0 95l40
1)
14 3. 3 ’DZ ’1
15 J.797:..
1 /. . . 0043)
17 1.04310
10 1. 35130
19 2. oo oo
20 0.37010
21 2.32000
22 3. 03372
25
8. 2 ?t
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- ‘ 5/3
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s. ; ?
4. 5 .
3. o :.o
3
I’.ODCP Coos ) ’ NH4DEP NO330P CLEEP ORDEP TPDOP T) (t4OEI ’ TI4DEP 030Is ’EEP C CPDEP
7 3)12 2.0o’Ji 1.22040 2.7000 6060 0.07100 0.10200 2.386330 5 0910 1 3664 0 2 40O
2. cooo 1.. (:3:33 0 913000 1 5700 47. ;‘oo C. 07300 0. 14000 I. 70000 3 3600 0000 0 02•: ’oa
0.72;? 7. P6,7 I. (€1400 3.3234 11.720 0. 10190 0. 11700 . 4. 27040 7. 5180 .. .Ci34 0.04710
0 ‘ a / 1 J0 1 6 (693 3 3652 12 6/3 0 32220 C l 44/10 5 0d910 9 2 J 3 4o2
0 L .,7 2 ill! 2. 1 . ,) 2 20 ’J 7 0 1 4110 0 45 10 4 32r ”0 6 5367 1 (76.9 0 21 ;0
O :‘:i3 4. 5,31 4. CC .070 2. Li5 C7 34. 113 3. 794 .0 0 9 3O 6. 30260 9. 176.3 I 0749 0. l 443
0 .3 / is C. C . . 00 S $ 30 C. 814 C) 51100 0 9 ) .s lO 0 03000 13 183.0 1 97 J 0 1 3.13
1.5714 11.5540 2.61430 2.9103 16.451 0.41420 0.1.2130 5.011460 0 2549 ‘.7606 0.23710
0 . ., 7 . ‘ .‘19 0 94142 1 7/.3 8 5 6 0 ,Ot. 0 17160 1 9j432 3 7266 1 fO .. ’ / 0 1C 30
2 013/ 10 JIS) 2 01390 2 6754 14 ..35 0 4/040 0 67620 4 93920 7 6146 v ’l 0 OC LC
0. 7023 0. 0512 2.07700 3.4572 7.732 0. 32160 0. 46560 4.95000 8 4153 3 61.110 3. 12420
0 is1 ,‘ ‘133 I 51420 2 0006 5 417 0 093o0 0 174 ”0 3 4j040 6 2110 Sl 2 0 uO O
1. ‘ 3 3 3.36770 2.0944 14. 758 0. 77)50 1.01450 5.89030 7.9049 2 5226 0. 239)0
$ 1 2 2 2 8
I. 4417! 23. 2311 4. C.2170 4.5523 12. 530 0.57340 0. 09000 4. 17310 1 . 72e .9 . 1484 0. _ 14 ..0
0.4132 2.1.4.6) 2.42310 2.0172 7.347 0.12300 0.22140 4.OC’ (EO 6.0270 1.5687 0,C’7240
0. ss.;x 3. ;‘1s5 3. SCoIG 2. 4.014 7. 321 0. 44690 0.752)0 5. 22110 7.9025 . 6350 0. oos:o
0 610(3 10 4 34 2 33 .i’3 2 3068 13 392 0 2( 00 0 51040 4 6 ..6O 7 0524 2 04ç4 0 2J7 )
10. 2010 15. 2310 1. 64633 2. 9795 163. 670 0.27273 0. 44440 3. 7o730 6. 7460 2. 1310 0. 17170
1. 2320 8. 9930 1. 3700-3 1. 9930 10. 700 0. 19000 0. 33000 3. 60500 5. 0400 . 4600 0. 1 :ooo
2.5472 4.1404 2.o8658 1.5741 38. 160 0.27666 0,36252 3,45348 3.0276 .7649 0.Oooat
-------
A. Calendar Year 1978 c nt....
035 SITE
?3 TALL -4EE
24 u;i 1.0
25 WA D3 T0U0) F . .L
i-I
DATE ir4 PH C0 N .
1’ /3 133 4.78 17.2 0.327
: i/3 1:14 4. 58 19. B 0. 591
19/0 100 4.80 29.3 1.530
UHCD INORGN TOTN
0. 009 0. 444 0. 548
0.017 0.335 0.697
0.016 0.415 0.827
CADLP K-I4OEP NO3OEF
2.3902 3.323
3.13324 1.5410 2.940
14.5000 1.3600 2.590
23
24
25
c S
.3
23
OR ...N
0. 104
0. 382
C. 412
0. 0030173’BO
0. C0002?5423
0. 0000153459
/ .D P MO2EF
3. 0334 0. . 3S4
3. 8443 0. 9782
7. 3300 3. 5000
K flQ CA NH4 N33 S04 CL OP TP TY
0. 203 0. 048 0. 497 0. 194 0. 200 1. 59 0. 0 2 0.012 0.021 0. 298
0. 272 0. 0/3 0. 2138 0. 113 0. 220 2. 01 0. 842 0. 015 0. 035 0. 477
0. 733 0. 350 1. 450 0. 0. 2 9 3. 32 3. 220 0.022 0. 038 0 3 8
U 0H EOHDEP 5E504 EXSO4 SESDEP EXSDEP SO4DEP t ADEP
17.3790 231.128 0.08173 1.80 5 0.38242 8.01857 25.137 4.3491
27. 5423 369. 067 0. 14775 2. 09225 0. 63995 9. 34532 30. 016 7. 9194
15.8489 153.409 0.38750 2.93250 1.29167 9.77500 33.200 13.3000
CLOEF OPOEP TPDEP ThNCEF ThDEP RONDEP 0RG DEP IHNOEP
11. 0036 0. 1396 0.2793 3. 9634 7. 2394 1. 0832 0. 1197 5. 9052
11.2828 0.2412 0.4690 6.3910 9.339B 4.8 G$ 0.2270 4 48’I0
32. 2000 0. 2200 0. 3900 3. 6800 8. 2700 4. 1200 0. 1600 4. 1500
-------
B. Calendar year 1979, Volume—weighted average annual concentrations and deposition
rates by site. (See end of appendix for explanation of symbols and units).
1) 6 T h RAIN PH
CON
NA K M C CA I ’IH4 N03 $04
CL t1I TP
04 1 EP
SITE
0.169 1.230 0,551 0 003 0 010
i
2
3
.;
S
B
r7
10
11
12
13
34
15
37
.3
F’
70
i
22
APcI 3cA W!T p 179 131 4.63 13.6 0.243 0.061 0.037 0.221
13A. A H31 DA IkEY Fy’79 103 6. 17 52.9 4.200 0. L59 0. 595 2. 040
E:.t:E CLAE ’E WET 1919 138 5.49 11.9 0.818 o.o ;o 0 097 0.714
E TC i p177 136 4.77 17.5 0.719 0. 144 0.100 0.600
1:C . l’il ? 17 ,5 4.62 14. 1 0. 290 0. OStI 0. 042 0.302
7 - .A3 70/ BOOK i 9 *12 4.60 22. a i. 340 0.031 3. 162 0. ) 7
..EI i.E7 j’)7 1 132 4.61 23.4 1.100 o. O ’f 0 147 0. 311
7’,3F- .Sf 1979 174 4.76 10.4 0 229 0. 0/31 0,33) 0. 102
:13I2 1979 114 5.37 16.3 1.050 0. 16’? 0.193 0.742
., 7’2 EW SWAIP 00* K *9/7 159 5. 18 15.6 0.612 0. *28 0. 124 0. 658
CC. ’CC W SI4AMP WET i97 139 4.93 7 S 0.161 0.036 0.020 0.142
FF4T K3 : 3 j ’/9 134 5.43 14.2 0.491 0.133 0.126 1.180
3AINSVTLLE BULK j919 164 4.83 15.9 0.316 0 070 0.G5 7 0.517
GAP .53 1LLE WET 1919 164 4.53 14.8 0.235 0.04* 0.042 0.217
I3A: .1:1. 1’,79 353 4.78 16.3 0.693 0.111 0.097 0.275
. w.5!9R 1179 *36 5.13 16.3 0.309 0. 225 0.03? 0. 759
J . C,’ .SJNV1LLE p 1 ’1 157 4.69 20.4 0 7 4 0. 160 0. 304 0.444
724 4.53 131.0 0.4)0 0. 0’13 0.060 0.332
L ALF E8 1 1, 1 125 4 70 Il, 1 3 3 . j 0 0” 0 0/3 0 4331
L;4 7L6C10 1’17? *55 4.94 10.6 0.431 0. 079 0.062 0.2)7
;o3C ‘,‘;? 146 4.95 15.2 0.317 0. 13) 0 062 .3. 395
ft C1 .RThUR FA2MS 1977 illS 3.22 14.9 0. 697 0. 115 0. 093 0.676
0.091
0. 102 0. 106 2.320 7. 530 0. 006 0. 012
0.205 0.190 1.090 1.250 (3 0.03 0.014
0.142 0.252 1.970 1.290 0. clo O.C33
0. 090 0. 187 1.210 0. 583 0.003 0. 009
0. 068 0. 187 1. 600 2. 630 0. 003 0. 023
0.076 0.159 1.620 2.400 0.003 0. 2.35
0.178 0. *37 1. 150 0.467 0. 005 0.014
0.196 0.16 3.430 1.900 0.0)7 C.058
0.151 0.235 1. 670 3.500 0.0)0 0. 023
0.050 0.125 0.496 0,568 0.005 0.009
0.098 0.162 1.410 1.040 0.037 0.023
0.306 0.2*0 1.710 0.676 0.008 0 0*3
0.093 0.180 3.250 0.453 0.003 0.006
0.103 0.151 3.300 1.433 0.018 0.024
0.316 0.201 2. 130 0.634 0.047 0. 1*5
0. 341 0. 166 1.960 3.4’,) 0.035 0.02?
0.172 0.371 3. 870 0. 767 0,006 0.0
0 112 0 176 1 870 0 8 7 0 0 8 3 033
0.053 0. 125 0.933 0.03* 0.005 0 0)1
0.226 0 200 3 470 0,823 0.042 0.050
0.313 0.179 I. 290 1.330 0. 020 0.033
EXEO4 SESDEP çXSDEP
029
ThN H F’BN DROP INORON TOTN 000W CHDEP
094
0. 06075
1
2
3
4
5
,
7
9
7
13
11
12
‘3
14
5
15
j7
11
19
2)
21
22
0. 36 0. )ooo234 ’: ’ ) 0. 265 0. 007 0. 260 0. 525 23. 4423
0 r 3 C ‘ ‘. ‘-1 0 0 ’ 0 OOa 0 203 0 370 0 6 61 984
r .3 0 (C ’ . ,‘, 0 C ’3 0 011 0 305 0 4 3 3 2 59 44 658
0 ..CY 3 0’,. 14 c i. ,5 0.017 0. 394 0. SF’ là. 9i 24 230. 98*
C. ‘ ) -C 3 0 121 0 006 0 267 0 403 23 9002 131 039
r , j Th3 7 ‘ . 1 7 0 05 0 5 0 192 ...6 *131 331 569
tj I C’ 3.1€ ij 0 V’ 7 0 O0 0 J4 0 “/3 10 9530 4o/ j9
C’ 2 / C J( 3.3 0 C 0/’ 0 (0? 0 316 0 3.44 1/ 3700 302 277
0 302 0 0000 7 ’ 5.7, 0 107 0. OF’ 0. 35* 0. 42 (1 4. 2651) ‘*0. 630
C i 211 0 0307’ 7 0 120 0. 008 0. 305 0 506 6 6069 105. 060
0 74.’. 0 Co33 174 5 0. *1.0 0.004 0.2*3 0371 11.7470 i06.939
0 2 0 0 c:: ’2. . 37P4 0. 167 0.006 0.260 0.427 3.7154 9. 706
0 0 CC . . ..3’ 0 126 0 007 0 316 0 44 22 3072 3/7 ISO
• ‘I 0 0 ’ O 0 1-4 0 003 0 273 0 3 11 29 512* 402 ? ‘iP
0 279 0. 02L:Z1’1.’C 0. 376 0.036 0. 254 0. 420 17. 3700 2o5. 304
0 4E7 0 0 C3’ ”4!’l 0 171 0 063 0.537 0.803 7.41:31 100.015
0 271 0. 3)6:1:.;! 14 0. 735 0.024 0. 307 0. 542 20. 4174 320. 31.3
0 24? 0. 060 o ::o .’ 0.01.’ 0.014 0. 343 0. 420 26. 3077 sp i. 180
0 252 0 0Z1%S07.l . (1. 1*0 0.017 0.317 0. 427 19. 9126 271. 356
0. 169 0.00031 1•33I& 0.1*5 0.036 0.178 0.294 11.4015 377.964
0 2 0 C ;j . 3 0 *3’. (3 321) 0 434 0 570 II 2 €2 161 915
0. 021 0 000o060730 0. 208 0. 018 0. 492 0. 700 8. 0256 9). 397
3 00000
0 15450
0. 37973
0 07000
0 23200
C, 300
0 05/5
0. 26250
0. 21500
0 04025
0.12275
0 07900
0 03V ’S
0. 17275
0.09725
0. 19100
0. 10730
0. 31373
0.10775
0 12925
0. 17425
TY .tIDEF TNOOP 000208P 0R03’llEP ISEP ’
023
NODP 0r’2F 8*3’ 000EP NH4DEP NO3OEP CLDEF IW&EP
6.8775 3.4715 C’ 0137 3 4C’ 6
1
2
3
4
5
6
7
0
?
1u
ii
F’
1)
14
1.
1
7
ti
i
0
2
7, 302 0 751* 0,4041 2,8951 1,1921 2,2339 7.213 0.0393 0.1310
4... 3 21 4 o I 21 u12 0 0’06 1 9159 77 5 ? 0 0610 0 1’36
0 55 1 2420 3.21 9 8532 2. (5290 2.4840 37. 250 0.0414 0. 19 )2
9. 77) 1. 7564 I : ( ‘0 9.2430 1. S312 3. 4272 37. 544 0 2176 0. 4438
3 8 ! 4 0. 5301 0. 0/96 4. 1876 1. 1040 2.8082 8.0*8 0 0414 0. 1242
17 63 ’3 1. 0672 2. 3.8*4 4.0444 0. 0976 ‘. 4694 33. 660 0. 0376 0. *056
15 576 1.0423 3. r, ,3 4. 1052 0 9903 2.0938 31. 600 0.0:378 0.0340
3 93 3 37 3 3 L/42 3. 3663 3 0972 2.3330 0. 128 0. 0870 0.2436
11973 192c . 1 , 2.2( 6.4303 2.2230 1 7754 23.660 0.4210 0.63134
13 0 3 2 0. 52 1 r,, 10 .6 2 .4009 3 7365 3 953 0 47/0 0 6032
2 363 0. 5724 C : iJ 3 2 2578 1. 3992 1.9075 8. 999 0. 07c5 0. 143*
57 ’ I 3 2 3 1 15 0 :0 i 1132 2 17t t3 13 035 0 2’Th3 0 3022
5. 10? 1. 14530 1. .%‘. ‘ t3 8. 47*33 1.7384 3. 444€ , 11. Olt 0. 01 )4 0.2132
3 3 2 0 ..J 0 3 3 SOtI I 5 1.2 2 9 0 7 -.‘9 0 €4 2 0 O 34
0 1. ’ I J’ 1 1.. I 4 .375 1 57 ”? 2 3*02 21 573 0 2754 0 3o/2
3 1 ,04 10 Oi’ ’4 4 978 2 77,Oo Ii &‘? U 639” 1 b6 O
11 9 5 2 §320 t ‘ , 9/08 2137 3 . 062 21 39.3 0 2355 0 8123
‘3 v . 7,7 195 i. :443 6.7644 3 61.20 3.0304 I?. 203 0. 1344 0.4400
o 168 1. 3323 0. 982 5.9663) 3.9332 2.3000 ii. i:;s 0.2178 0. 4400
6. 60 1. 2245 0 ‘iOIO 3. 6735 0.0215 1. 9373 12. 6110 0. 0175 0. 1 ’/05
7 :40 1. 9413 0. 9062 5.7670 3. 2996 3. 0368 12. 016 0.61)2 0. 7:300
10. 503 1. 7825 3. . 30 30. 4730 4.8515 2. 7745 20. 615 0. 3100 0. 1.990
1 8s52 3 8130 0 s4 0 0 8 2
3.9054 6.3894 3.0744 0. *6113 1. 7130
4. 1752 7. 6024 2.2440 0.23*2 5 )164
2.9318 5. 5202 1. 0318 0 cO :2 3. 7372
2. 7060 5. 1744 I. 0004 3. I i 3. 2 tO
2 7984 4.8972 I. (5304 C. 0254 3 C .28
4. 4710 6. i35 8 1.’ )/ C’. 1’ 5 4’ 10
3.4428 5.2212 1.2*93 0.2I ’J 4.00*4
4 3 59 8 04 4 1 ‘2 ’) C’ 1272 6 13 ’ 4
3 9314 5. 090? 2 5*22 C’. 0618 3. 3267
3 10 5 7738 7 2) 3 0 3
3. 8C 8 7. 2463 2. 0684 8. 1349 3. 16.24
3 03 o . )09 2 ‘ Th . . 0 €39 4 4w’.
4 . 0/ S 2 6’ I CilO 3 i
6 6133. 9 ) 5 2 32 0 9. . .C 7 ‘.332
5 9012 5 3 ’ . 4 3 ‘ 5 C’ 17631 4 3’.
5. 3776 9.4000 3. 7233 0. II3 7. t .C32
3.4272 5.5072 I. 496Q 0. 23j7 4. 3112
2.6193 4. 70 1. 79u3 0. 09j i 2. 7 73
5. 2052 8. 3220 1. 1056 0. 1*40 8. 33 ,4
0 071.5 10. 21.30 3.2240 0. 2790 7. 62 0
1. 27C00
0. 9)550
1. 79025
I. 14000
I. 34500
.1. 32330
3. 09275
I. 16750
3. 45200
0. 45675
1.20725
3. 63100
I, 17375
1. 12125
2. 02275
1. 78900
1.71230
1. 53625
0. 02325
1. ‘340/5
1. 11375
0.265
3. 635
0. 7*07
0. £349
o. :&i o
1.4740
1. 2700
0. 3)70
0. 9775
1. J 5 s 4
0. 21)3
0. 3.3 3
0.4339
0 20C’?
0. 0310
0. 4.39
0. 9056
0.2327
0.6157
0. 3367
0. 6290
0. IOU)
5. 1057
4. 30”)
4. 3U )
8 1156
5. 2440
5 0*805
5. o260
6 3379
4. 4343
7. c .9’J / .
2. 4*55
5. 747’!
8. 7,363
8. 5522
5. 7473
9. 2151
9. 25753
7747
7. 0550
4.757’.
6. 52 0
. 7847
lo 1130
23
15 641)
26 7973
it.. e ,3 .)
22 1 ’)
2*. 1130
20. 0100
18. .1.5
.5 55 3,)
7. £ .-4
16. & 4’D
22. 0442
11 0.3’)
2? 7.33
3 ), 7700
43 7425
22 7120
14 4305
21.4423
p7. 9753
-------
B. Calendar year 1979 contInued...
035
ShE DATE RAIN PH CON NA V. 310 CA N314 NC 504 C L . OP TP
23
24
25
2a
27
23
ARJNELAN0 1979 190 5.28 101.0 13.000 0.661 1.540 1.740 0.091 0.201 4.36 23.900 0.019 0.028
t1IA i1 3919 110 5.36 36.9 1.260 0.085 0.184 0.759 0.097 0.140 1.24 2.580 0.009 0.010
STW.RT 19/9 166 5.02 14.6 1.220 0.070 0.155 0.341 0.096 0.147 1.23 2.300 0.008 0 014
1 LLf AS5EE 1979 204 4. 71 12. 7 0.286 0.082 0.052 0.338 0.063 0. 135 1.31 0. 586 0.006 0.012
WALrO 2ULR 1’f/9 164 4.75 25.8 0.551 0 080 0.077 0.251 0.215 0.177 1.81 1.090 0.010 0.015
WALDO ThR000I4F.LL 1979 123 4.67 38. 7 2. 360 0. 656 0. 457 1.690 0. 063 0. 192 3. 63 4.860 0. 011 0.016
c:S
Thw H 08039 o o 33908039 TOTN UEQH EOI4DEp £8804 6X804 OESOEP EXOSEP
23
24
25
26
27
29
0. 242 0. 0000054954 0. 151 0.017 0. 292 0. 443 5. 4954 86. 827 3. 25000 1. 13000 17.1167 5. 8460
0.233 0. 000ao.;i&1/ 0.136 0.009 0.237 0.373 4. 1687 45. 856 0.31500 0.92500 1. 1550 3. 3q17
0.227 0. 030C095499 0. 131 0.006 0.243 0.374 9.5499 158. 529 0. 30503 0.92500 1. 6677 5. 1183
0.213 0. 000019493.1 0. 150 0. 006 0. 198 0.348 19. 4984 397. 766 0.07150 1. 23850 0. 48 2 0. 4210
0. 363 0. 0003177829 0. 153 0.006 0. 392 0. 545 17. 7020 291. 638 0. 13775 1.67225 0. 7530 9. 1436
0. 343 0. 0030213796 0. 255 0. 005 0. 200 0. 535 21. 3796 262. 969 0. 59000 3. 24000 2. 4390 13. 23340
03$
NAOE cDEF ioo:- CADEP NH4D ? NO3DEP CLDEP OPDEP 1 D2P TKNDEP TUOEP CRC !CEP O 0P E? 1 N5E
23
24
5
26
27
20
205. 400 13. 6025 2.1. 3320 27. 4920 1.4375 3. 1758 377. 620 0. 3002 0. 9 .88 3. 6236 6.994 2. 3252 0. 2686 4 612
‘. E .D 0 9-Q 0’43 8 349 . 1 06/0 1 5- uu Z 3bD 0 0990 0 1900 2 S630 4 1030 2 4 .60 0 0 0 2 6 ) 0
23. 252 1.4940 2. /30 5.65 ,06 I. 5936 2.4402 i3. 300 0. 1328 0. 2324 3. 7502 6.2084 2. 1746 0. 099 4. 028
5.834 1.6725 1.0608 6.8952 1.2052 2.7540 11.954 0.1224 0.2440 4.3452 7.0992 3.0600 0.1224 4.0302
9036 1.3120 1.2623 4.1164 3.5280 2.9028 17.712 0.1640 0.2460 6.0352 8.9380 2.5092 0.0020 6.4269
25. 0213 8. 069 5. 6211 20. 7070 1. 0824 2.3616 59. 778 0. 1353 0. 1968 4. 2169 6. 5305 3. %345 Q. Q835 3. 4440
C 40 OP
62. 608
12
20., 8
28. 724
2 . 34
47. 109
-------
project perlou,
C. Volume—weighted coucentr tions nd torol deposition over two year
1978 and 1979. (See end of appendix for explanation of synibols).
DATE Ri , 71 P14 CON
023 SITE
I . 0P; . t.ET
2 1 EY
2 :12_La CLA0 IJET
4 :.T . . ! ;
S
‘: ; ,U r ’EV I3OLK
7 CE2 . ‘5Y
S CWI- : .E,
9 01.E . ST32
33 2o ’ . ’.o :. .5I1i ’ OUL Ik
ii ‘ 0 4 o ,
12 c: . .’: ! La 0 .0 . . c
2 3 2 ,\!7 .1Sy ILLO IET
14
25 ): , ?L
1 , ..Ai
17 L ,’J.E ALF?EtI
19 L ’ .E FLA 2&
1 q
2 , r ’ . -Tt ’ .R FA 4 ’15
2 1 “;.-4
2 1;I - ,7
7F0 79
7 32.75
73’.79
71 :&79
70 579
702.79
72579
707.79
7 ( .79
7 4 : 0 ,79
72579
781.79
22.7’ )
707:79
70979
71579
72 .79
7 ,3 579
7eL7?
239
295
315
278
269
2 s9
32 ( 3
223
2 “ 8
243
272
2 .1,7
2713
26 ’3
289
210
4. .1
5.08
5. 29
4.74
4.72
4. 74
4, 52
4. 71
5 47
5. 1).
5. 60
4. 73
4 59
4. E7 !3
5. 03
4. 58
4. 13
4. “5
4. 92
5. 44
8. 40
8. 44
15.3
28. 8
11.4
18 7
13.7
22. 3
23. 4
14. 1
17. 3
13. 0
11). 5
1:.. 2
14. 2
1 . C
27. 4
32. ,5
111. 9
71. 1
lc.. 3
io. :
5 : , 7
i7. 4’
0 (1 C , 1*24 1303 734 CL C “P
0.243 0.070 0.034 0204 0.101 0204 1.39 0555
2.830 0 ,5 ’) 0.208 0.E 19 0.098 0. iS ’? 1.8-1 4 070
0. 612 0 0’I ’ 0. (156 0. 519 0. 143 0. : ‘04 1. ;2 C 4302
0.528 0 243 0. 4)1.2 0 527 0. 225 0.227 1 3 . 0 970
0. 270 0. 3 (1(3 0. 03 . 0 249 0 133 0. 172 1 40 0 585
2. 310 0. 100 0 i o 0. 365 0. 183 0. is 1.87 2 o
1. i 0 (3.07’? 0.147 0 311 0.075 0.159 1.67 2 400
0.Z13 0.12’? 0.034 0209 0.283 0.224 1.82 0.452
0. 9313 0. 13’! 0. 170 0. ‘/00 0. 217 0. 211 1. 8 / 1 73
0.3’ 7 0.091 0.079 0 4317 0.125 0.1’03 2.23 I 120
0.471 0. 197 0.132 230 0.119 0. 273 1 40 1.’C’l2.
0. 204 0. 0:37 0. 024 0. 480 0. 129 0.232 2. .14 0 . 133
0. 197 0.04 0. 037 0. 207 0. 102 0 i94 1. 2u C 4)3
0. 888 0.254 0. 106 0 374 0. 103 0. 1o3 1. 1.1 1. 330
0 1?0 0 C (75 0 / ‘ /H 0 2 8 0 0 .sO 2 V’ 0 6
0.371 0 ,4 o.oo: 0.223 0. p.19 C i95 1.92 ‘ ‘7./.54
0 ‘ .“43 0 1 3 I I I 0 o3 (3 27. 0 289 1 91 1 ( .7,
0.003 3.3)12 0.000 0.034 0.228 0.1’12 1.0’ ? o .245
0..’. 12 0 2 .1 1 1s. 134 0 331 0 292 0 2J3 1. 1 . o :‘o7
0. ,’4 is , 0.1 , s ) 3.o02 O.2’14 (‘.003 I 14 I
10.9310 0. 77u 2.300 1. e,7s3 (3, 104 1. 244 3.99 23 ‘ .3
1. j1( , 1 0. :59 0. 0L 0. 805 0. 118 0. I s O 1.42 7
UL0 C (1H’JSP 500(14 EXSJ4 805OU 02r
cos
H
Qi443 2
O1 ’GP .
lU300N
T0T ’i
1
2
0 E ?
0 0
C. ‘244171
0 C 7.1’
0. 198
0 000
0. OOa
0 005
0 :03
0 281
0. 503
0 337
24. 5471
2 7 4
51.1.1.. b 3
.S ‘ 1
3
0.775
C -3T027 l2 ()8
0.235
0.005
0.304
0.477
5. 1708
151.09
4
S
0
9
3.:;’?
C ’ 87
‘0 “ I”
0 .: :2
‘2. 071
( 73
0. (-7’ 3410
0. 4202 ’1*) .
C “ l 1070
(‘‘‘02 2’ 230
0 1700: ‘.00
C -
0 194
0. 134
0 137
0. 107
3. 093
0103
0.012
0.0331
0 00(3
0 (302
0.016
0019
0.342
0. 303
0 31 . 1.
0. 234
0.471
0435
0.531.
0. ‘13’?
0 510
0. 3171
0. 5,75
06r ’
20 35)0
39. 0040
IS 0
:0.. 330
19 .1.54
2..
573 21
524.00
30, ...0
3 I, 3’)
6.3.95
/ 486
2
,j
12
13
34
15
1’.
17
S
19
3
21
22
‘“1
c ,.:o
C ’ : i
31
0. 312
0 ‘.“4
0 293
0. 3
“ I
0 27
0.471
0. ‘. -2
0 241)
3 .’ 7)4
o..o::’•ooOl’,
00 I
“C ‘0 )
(3 ‘1 C2’,
0.2003.025
0. 00C01 002/
C. Cr :,30:239
3.,1 “
2’ C ,I ..(07
. ‘
C. 0.’C’ 2
(3. L 4 . .I .‘ .003
02 1
0.204
0 188
0 1J3
0. 2931
0. 194
o 0.99
0 336
o 121
0.143
Cj397
0. 178
0. 109
0010
0.310
0 0)9
0 004
0. 023
Q. 050
0. 012
o o o
0 007
0.021
0.020
0. 01 /p
0. Q2
03i
0.292
0 k1
0 296
0.3181
0. 1)30
0 ‘ i3 ’3
0. 401
0. 260
0 325
0.477
0. 3o3
C. /54
0432
0 475
0 3 ”7
0
0. 844
0.734
0. 433
(3. . 1.37
0 38
0.670
0 4.74
0.
C ,. .473
e . ’ ?L3
2 5339
11 09
7 .0
13. 11.28
‘I .3:101)
23. 3077
113 /009
11 0..
32 0027
3 :0)043
:3 9013
3 6308
1 7 L.4
70 sr
. .34 “0
? ‘ /3
35’). 81
042. 7 ’1.
1200. ‘19
•1”7. 20
3i1 .2
‘423.’/2
92.99
4031. ; ,1
7... ...1)
0 004
0 3)”
0 c.0 ,
(3 027
0 (j .04
0. 225
0. 90)
1 ’ 0l
‘.4 ) .‘
0. 000
o. c:
0. 0; .3
0 CO
0. 0;
C’
0 ‘::
0 C 3
0. ca ’
1’. 94 1
C.’ .,
I... 4:, ,j
0. 000
733 .70:
: .j
3’3 (.4.3
5 . :
.44 ,,.‘3
.4,.
4.; ‘7 :’ ,
7 1 3
‘00
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5,: 4 -. 4
343 .14’
29.
0 027
0 0:4
0 (‘11
( 3
o 2.’::
( 3 000
(3 C..,
0 0:2
0 (‘ ‘
o c r
o 323
o ‘ :3
C (.00
0 0:3
0. 1 2
.3 0.0
0 .. :0
4. u : .
3. -7 .7
‘3 0 -
0
0 005
137’
14
1 :73
( ‘15
00
13 ?r
2’ 102
. 44’.’
0. 02373
0. 5’3/00
0. 10200
0. 17:970
0. 00750
C l. 32730
C?. 2’/1 C0
47, (. ‘ . .73
0. 0:1305
0. 14925
0. 1 j775
0. O73S0
t,, 04525
0. 21.700
C ), 09410
0. 09318
0.. 32953
0. 0’; 7 )13
0. 1C)r ’5
C) 1(30 ))
2 72300
(3 2’115O
1. 3’5 ’23
0. 9005(7
I. 02700
1. 73100
. :‘jOso
1. 34250
I. 3030)
1. “2125
1. 45 ,’.’/5
1. 12(3711
1. 4.0021)
1. 5 . 1/ 1 10
2.22071)
1. 42300
2. 32550
2.02225
I 05050
0. 479:300
1. 70e ,’/5
1. ) ‘/Os.h ’4
2. 2. ”o ’(0
3. 2421)0
43. 4043
4 44/3
1. 0123
1. 71045
0. .1.10/
2. 53 0.
2. 450
i. io.;’o
1.
1. 307’?
0 7301
0. 63’,?
3. 8142
0. 1.i379
4. 3170
I. 0.1.35
O C s . . ’?
43. 6174
3.4124
p: .. 79
4. S’ilS
20 (8”?
t £
10. 2(00
18 1173
12
12 C- 0 ’/7
31 (80.’
t . . 7’,.,
33
9
23 ‘)27
I_ o -.c’
20 7234
131 ‘1039
20 l j
5
16 4o’i4
9 “ ‘..
14 2’6’4
32’ 31 1 .’7
7.4771)
2(311P ,.0OLi CIa2) NH.1OE / N000EP CLPL1 001,CP
I ‘ 2 79715
2 . 2/:’)
-2 4. 51.- .
5 2 423.,
7 1’ 2251
8 1 1000
9 4
20 3’ •75
13 3 00.7
12 2. 3900
13 1 80”2
j4 1.
15 0.2510
23 4 23)44
00 7133”:
00’ 2 .0000
00 4. 21.5
73. 4 0’/: .5
:1 30 1137
22 3 5453
0 (‘22’.
S 2110
. : ‘ :‘‘:
1 ./ ’/ .l
C ’
:3
1. 0370
3 7110
2, 014 5
3. ;‘oso
0.00002
2 20:1.
2
2 227’)
2 71 )73
2. (lo?
i. ‘ .;773
2 .00/0
7
33 , 1 .f ’0
3. /...0
TPDEP T3Cr1D3r T2 ;D1.P C2l014 #0P (‘00 -SEP
4 92134
17 0204
: ‘
26. ‘G08
6. 04/5
9. 200738
8. :3589
• 6300
20 0730
13. 1435
34 5630
14. 3(40
6 1896
7. 4023
21. 22523
12. (‘.07)3
1 ,7 110)5
S .0 172
S 4005
02 4078
42 2170
11. 3145.)
2.4139
I 9894
I
3. 3?5
4. 2;2i ’
2 0170
8. 4150
A. 92 /i
3 0390
3. :343’)
3. 8442
3. 0396
5.
7. 9:188
8 0s24
5. 9274
3. 200.2
7. 4460
7. 2052
.2 116
2
4. 8756
3. 0277
4i, 0 33
c, JOb
4, 723
5 2724
4. 2771
6. J4S -)
4 ‘/053
5. 1785
4. (3613
0. 913.9
5. 71112
4. ‘0038
6. 3040
0. 3370
6. ‘/153
3, 947,7
5.9425
s. oo i
6. OV1S
3 00.20
13 284
913, 853
10. .1.74
.,.3 “‘1,
IS. 1. l7
67. ‘/013
4. 5 0
14. 7)4
‘0) 1
0(3 5/ .0
20. 301
10. 774
22. 903
0 .. 275
17. 077
7 t : 0
23. 428
700’ 711
)C, 7/3
003. 5.: 2
833. 1)40
47. 043
0. 0 ’P 6
0. 20:7/
C’. I’1/ )
(1
0 24/5
0. 6771
0, 0007
0. 5120
0. 671.3
C .. 4331.
0. 7o2
0. 4172
0 2190
I. ‘ . 113 20
1. LisO
0.
0. (.01(:
0. 1”) 31.
1.
C. silO
C ’. 5vo7
0 2730
p. o o
0. 2’142
0. 5714?.
9, 234477
0 23145
1. (‘240
1. 24 ( 10
0 to,U3
C .. “/833
0. 6084
o O 22
2 .2400.
3 0001.1
0. ( .520
I 3:0’)
0. 300/0
1. 1.210
I. 1572
1.0101
o. 57100
7 1462
3 6134
11 1205
“,(
. 347”)
8. 7o20
1.2. 0303
C 0/04
5 87:95
O 1)14:1
C. 7’.’IO
7. 0030
10. 3632
12 1434
12. 2.0.4
“1 5 :.tio..
6. . .-1 :!
13 1438
12. 7 .0/31
7. 8228
0. 4050
32
8 0411
1 5200’
‘I
3 1:00
C
.
10 337..
14 l. ’/ ’
26 ‘‘
7’ 0’ 7’1
173. 7”(’
3 - ‘ I
3 d ’ :03
:‘
.00’”
C) .‘1
.‘
00 11- .-.
9
:
0000.
C:
r
1 )3 4200
3. 100 ’)
0 4227
9
13
1’
21.000’)
:1 00315
0 .00:9
1. 700:
3
IC 71.
15
4
0.1/72
312200
32
7) 5 5 3 -2
9
14 79:2
5 3 .19o
10 1041
5.217’. .
t
(1
14
20
4.’7i9
4
14
:2
1...
i , .
7
30.
37(0:-C
00”;,l
3 ‘008
. 4 l ”4-
3 10:1
:0
00’’
17 73 ,01
14. I t4
9 9333
8 lOll
4 302
3 9493
0. :000
0. 4i44
3 :1.2:
4
0. ‘, 4.
-------
C. Project period (1978—79) continued...
00 SITE OATZ UAIN PH CON NA
V
10 CA N114 N03 $04 CL OP
TP T.
23
24
25
2.
0t S
STL’A T 7S .77 t
TALL iAF E 70.’79 237
AL0 7.3’.79 298
I.JAL O T0U0 FALL 73 79 223
H ORCU DROP
3.05
4.73
4.66
4.71
JNOROfl
10.2 1.580 0.170
14.6 0.304 0.171
17.4 0. 567 0. 1 9
33. 5 1. 790 0. 434
TOTl UEDH
0.I /0 0.377 0.327 0. 154 1.33 2.960 0.OIA
0.050 0.407 0.120 0. 305 1.58 0.6n,2 0 ooa
0.070 0.265 0. 174 0. 1 5 1.99 0. 91J 0. Oti
0.400 1. 550 0. 120 0. 226 3.60 3. UlO 0 Olb
EGMbEP 3C304 EXOO4 SEC1X P EXSDFP
0.024 0.27 /
0. ti . 0 250
0. 022 0.412
0. C 7 0. 430
0 EP AC:
2)
26
0 0 25 0. 152 0.008
3 09 130 0 008
0 ‘ 1 . 32J 0 0
0. Q 2c 94 0 3 0.012
0.251
0 305
0 389
0. 344
0.433 0.9123
0 435 3 07
0 607 21 ‘3778
0. 884 29. 4q84
212616 Q. 9 00 0.9)500 3.43650 8 3345
41 315 0 07600 I 40.00 0 60020 13 ‘_J
6.1 53 0 i 175 1 041125 1 40305 18 3593
404 635 0. 44750 3. 5230 3 32842 23 .133
14 713 4I.23Z 0
07_ .‘
,
0 263 9 c’
‘
iC0tP ,ADEP
l H40EP
NO3OEP CU CP
0F’DEP TPOEP TKNDEP TI DCP CR0N0E
0RC?0 ° I1 5CP
23
2..
5
2
4 6 56 5. 1676 9 397
.. C5’7 1 2r.’ ) 9 s45
4. 72 2 2 2259 7. 0970
14. *3J2 9.9200 34. 5850
3.3347
2 8440
5. *052
2.6760
4.0394 77.2560
4 3045 28 4034
5. 0110 29. 2934
5. 0390 94. 9630
04176 0.6264 7.2619 31.3013 3. 9672
0 1Lh’ 0 .1i’,2 S 92.iO 10 3095 3 •)Rio
0. 3 374 0. ALi 4 12. 2776 28. 00116 7. 0924
0. 3560 0. 6021 9. 7674 14. 0072 7. 0914
020r 3 7 34I
0 l ’ .s 7 .. 5
. :9 0 10. 9962
ç). 2453 7. 7i.
-------
- - - __, .— —a — - 1i07
1, 1978 to April 30, 1979. (See end of appendix for explanation of symbols and
units) -
SITE
SeIiIA I-’CNDA .EY
OILLE C LADE WET
CE1’ . ( V.EV 13 LI - .
ç; iii W5T
C .! -‘LEY
71
514 5UAIP 80L 14 .
F T ! YE25
(67 . ’ILLE OULK
SVILLE WET
M6SI i:JOE
.jAV
L ’ . ’ E .LFRED
LAV PLACID
I. I s3C 1
i-I. --c TIi 7l FARMS
J5LAND
1 N I-I
CL
0. 624
4. lilO
0. 090
0. ‘174
0. 610
2. 810
2. 610
0. 513
2. 070
1.270
1. 030
0. 6 i17
0. 487
1. DsO
1.1370
0. 681
0. 629
1. C ’40
0. 7c 3
0. 7.
1. 5e 0
I -’. Q0
OP
0.004
0.010
0. 006
0.010
0. 013
0. 0 0
0. 001
0. 052
0. 044
0. 009
0. 034
0. 024
0.007
0. 0c 2
0. 027
0. 065
0. C’09
0. 0:31
0. C 9
0. o o
0. 022
Q. C -25
TP
0. 037
0 C -1&
o 009
C.. 017
0 022
0 0 6
0. 054
0 0 2
0 064
0. 019
0 045
0. 012
o 0 11
o 0’2
0. 037
0. 079
3 014
0 0 0
3. 017
0. 049
0. C40
0. 039
CATS RAIN PH CON NA K MG CA NH4 1103 S04
78—79 125 4. 60 16. 6 0.319 C.. 076 0.049 0. 235 0.090 0.206 1. 50
70-79 108 5. 45 25. 9 2. 260 0. 430 0. 248 0. 802 0.083 0. 129 1. 45
70-79 137 5.21 11.5 0.4:33 0. 108 C) 060 0.511 0. 109 0.203 1. 14
713-79 256 4. 70 17.0 0. 514 0. 122 0. 062 0. soa 0. 109 0. 200 1.80
73-79 136 4.74 13.8 0.3 -10 0.121 0.044 0.314 0.144 0.152 1.41
/(i -79 139 5. 04 21. 8 1. 350 0. 163 0. 180 0 315 0.252 0. 170 3. 56
,o-79 139 4.74 20. 1 1.410 0. 103 0. 165 0.343 0.097 0. 234 1.55
70-79 151 4. 76 16.3 0.278 0. 173 0.043 0. 275 0.335 0. 267 1. 94
7B--79 129 5.81 20.2 3.160 0.241 0.221 1.080 0.247 0.250 1.68
-/0-79 110 5.15 12.0 0. 05 0.0137 0.004 0.443 0.035 0.191 1.13
711-79 161 5. 79 15. 6 0. 506 0. 256 0. 125 1. 180 0. 121 0. 162 1. 64
379 145 4. 75 13. 9 0. 3o2 0. 109 0. 079 0. SliD 0. 161 0. 237 1. 77
711-79 145 4.63 24.4 0.243 0.076 0.0-12 0.264 0.110 0,170 1.34
7 79 122 5. 00 17. 5 0. 740 0. 292 0. i24 0. 339 0.248 0. 162 1. 76
73-79 122 4. 74 22. 9 1. 000 0. 147 0. 143 0. 670 0. 136 0. 227 2. ‘36
713—79 139 4.97 10.5 0.371 0.209 0.094 1.040 0.202 0.247 2.43
70-79 207 4. 42 17. 7 0. 264 0 107 0. 031 0. 30? 0. 176 0. 195 1. 70
7(3-79 133 4. 74 21. 1 0. 506 0. 14’. 0. 139 0.017 0.276 0.217 2. 04
73-79 135 4.95 11.7 0.441 0.076 0.045 0.252 0.168 0.140 1.17
7Q-’/9 136 4. 80 17.2 0. 493 0. 152 0,052 0. 404 0.292 0.234 1.07
78-79 103 5.71 17.13 -0.1103 0.173 0.100 1.010 0.229 0.204 1.33
‘/8-79 125 3. 33 75. 2 9. 020 0. 626 1. 030 1.640 0. 103 0.248 3. 54
OhON CROP ItIORCN TOTN 02014 EQHDCP 53504 EX534
0.079 0.003 0.2c6 0.375 23.1(89 313.9136
0.087- 0.006 0.212 0.299 3.3431 30. 320
0. 150 0. 003 0. 312 0. 470 4 1660 04. 474
0. 351 0.007 0.309 0. 460 19. 9526 311. 261
0. 172 0. 009 0. 296 0. 460 18. 1970 247. 479
0. 140 0. 006 0. 402 0. 562 9. 1201 126. 770
0. 142 0. 003 0.232 0. 373 113. 1970 252. 938
4.. 035 0. 020 0. 592’ 0. 6(17 17. 3700 262. 409
0. 193 0. 020 0. 497 0 690 2. 4347 31. 420
0.134 0.010 0276 0.410 7.0790 77.1374
0.203 0.011 0.703 0.406 1.6210 26. 111
0.1131 0.008 0.398 0.339 17.7020 257.851
0. 130 0.004 0. 300 0. 430 23. 4423 339. 913
0.257 0.010 0.410 0.667 10.0000 122.000
0.312 0.010 0.363 0.675 18 1970 222.004
0. 135 0. 014 0.449 0.604 10.7152 140. 941
0. 090 0. 005 0.371 0. 461 23. 90133 496. 550
0. 158 0. 019 0. 493 0. 6”&9 lB. 1970 242. 020
0. 133 0. 01.8 0. 330 0.441 11.2202 151. 472
0. 122 0.019 0. 326 0. 648 15. 84107 213. 5-15
0. 366 0. 018 0. 433 0. 599 1. 94 -12 21. 050
0. 185k 0. 014 0. 331 0. 2. 9512 36. O O
r-12l1 ’P CADEP N1-I4DEP NO3DCP CLOEP DPDEP TPDEP
o::s
4
0
6
7
1 ’
9
10
11
13
14
14
17
39
19
20
22
C i i 3
3
4
5
B
9
1 -3
11
13
14
15
16
17
IS
19
20
2
3
4
S
a
7
S
9
20
U
23
1
ii )
i)
C C000251139
C.. 06 .0C.35 ’1 (3I
0. 0CC00 6 15LCi
0. C31 ’i’? 52 6
0. OOC 1I .I ’7/0
0. ocC. ’ . .’, I 701
0. 0050101970
0 0)51/3T’ . .’)
0. (1:jC0..’ .-I ’/
0 - .J-’’C’ /‘ .‘/ ‘/1.
0. C ’ 60 1 - 2 13
Q. 05001/75713
0. 00)6234-323
0. 005-010000-)
0. 0 . .010 1970
O 060010/152
0. 0050225033
& 023012 1’lYO
0 5063115302
0. 050-)1 5-1i39
0. C6i00 19490
0. 32 .”,,629512
0. 139
0 17-)
C. 267
0. .50
0. 3I .
0372
o 229
0 ‘133
3. 4 •3
0 5 19
0. .24
0. 3?2
0. 24-3
0. 605
0. 4’.3
0. 317
0 2116
0. 422
0. 301
0. 414
0. 555
0. 233
3. 98’!
4 4C’B
5. .59
0. 019
4 624
2 1.145
19- ‘ 9
4 253
14 ‘B
7. 1.35
8. 47
5. i49
t .2 ’3
9. 028
13 176
‘ - :.
I ‘.,l’)
7. 7’i-%
l . #53
6. 705
3 072
112. 700
0. 07975 1. 50025
0, 32229
6. 2510
19 71.0
0. 56500 0.05300
0.10075 1.03125
0. 12850 1.75150
0.00500 1.32500
0. 30750 1. 17250
0. 33200 1. 19750
0.06950 1. 67050
0. 2 000 I 57C00
0. 17123 0 -#7675
0. 1265.0 1. 51550
0. 0905-0 1. 67550
0. 06075 1. 27925
0. 18500 1.57500
0. 27000 2. 09000
0.09275 2. 33723
0.09100 1.66900
0. 14650 I. 13)350
0. 11025 1. 01473
0. 12325 1. 74675
0. 20075 1. i 25
2. 25500 1. 2E300
2. 0 ’3400
0.40002
0. ttJIIO
0. 33533
1. 7 - 5 3
(.65325
0. 34987
1. 237 i
‘ C. 62/9
0. 67ECii
0. 4:174?
C). 293
0.75233
1. 09900
0. 43j76
0. 2790
0. 04S’
0. 49612
0, SSE73
C. 72270
9. 3953
3. lIioO
4.7094
9. 107.3
6. 0067
5. 432o
5 5404
9. 4141
a. 6967
3. 1537
13 1224
5. 1176
6. lOJO
6 4013
8 4553
10. 6593
11.5161
8.39-IS
4. 7L 9
7. 5136
4. OoSJ
5. 2542
15. 18
27 213
15-. I?13
21. 26
21 146
..s 5- 1 4
ss. os;
12 10-)
.. - 1 )4
25. 10
19 433
21.472
2; 772
52 7/7
3 .432
27. 132
i S 775
45 432
14. 3 4
44. 250
TKNDEP TNOE° 000II6EP 0130 1’23P 1r:o&3 .
0 csco 0 0155 3.1373 1.1250 2.5750 7.1300 0.0500 0.01375 2.1125 4 .6575 0.9373 0 0375 3.7(-30
4 C10( 2 6 /.4 0 6816 0 0964 1 3,32 4. 144 0 . E .0 0 17211 1 filSO 3 ‘,2 0 5 3 ’ 1O 2 C 3 2 2 S
r,7 -73 a. i .s ; ’o 7.0007 I. 4933 2. 7911 32. 39’.) 0.0322 0. 1233 3. 6579 6. 4393 2 1646 0 (j41 I 4 274;
(. 0J2 0. ‘,-t’/0 7.9248 1. 7004 3 1200 15. 294 0. 1560 0. 2o52 4. 0560 7. 17 ) 2. 255 0. 1C92 4 325-4
1. 6-i53 C) 56114 4.2976 1.95134 2.0672 13. 296 0. 173.3 0. 2902 4. 2976 . 31143 3D9 0. l24 4 C?-
2 2 07 5. :120 7. 1565 3. 22-18 2. 3 30 39. 059 0. 6950 0. 7734 5. 4460 7. E l l i S . 2249 0. 5034 5. SE-
1. 4317 1 . 1135 4.7677 %. 3433 1.8628 36. 279 0.01139 0.0336 3.3221 5 1-147 1- 9733 0.4.17 3. 2109
2 .-t 1 0 1’#.) 4 1523 5 0505 3 12037 7 776 0 3332 0 6 , 142 6 49 .iO 20 ..‘17 I 4-- . ’3 0 - 13 8 - ,7
I I. 05-3 2. 0730 13.8240 3.1616 3.2000 28. 496 0,58:32 0.0192 5 6300 8- ‘ .20 2.4 34 0. 7 ) O 6 362
0 5 /0 0. ‘,1-40 1.0130 0. ‘1350 2 iOib 13. 970 0. 09’ 0 0. 2090 2. 4090 4 51.10 1. 4/4 0. :00 3. 42 5-
4. 1216 2. D I I ’S 10 9980 2.9481 2. .082 6. 383 Q.3474 0 7245 5. 2164 7. 824o 3. 2 -C3 i77t 4.
1. 56-35 11463 p.5260 2.3345 3.4365 9.961 0.3400 0.4640 4.6690 . 1055 2.32 . L7’/iO
I. i070 O.60’O 3.8230 (.5950 2.7550 8.771 ° ‘.L°’ 5 0.1595 3.41300 6 2353 1 - 8s5 .êl3 4 5 )
5 ‘.51711 4.1330 3’ 0236 1.9764 18. 2 0. .564 0. C734 6. 1611) 5 74 3. (35 - 127.) s. oss:
(. 7 34 I. /446 12. 1741) j. 4592 2. 7694 22. 1 114 0. 3294 0. 4’. 4 3. 4655 8. ..3o0 3. 0 ( 4 . 125.) 4. 45.3-
J r t I 3( 24 451 .. 0/? 4331 9 30 0 9(123 C,.fl 4 9 ’3 0 3-/ ’5 2 I 4 1’/44 6
. . cro 0 ‘c i ’ ;
‘ 1411/ 1 U# 6/03 2 8 . .6 13 632 0 - 1_ 0 c . O 0 111 6
§ 1? 2 18 8 t £
I. C6 ..,4 1.0500 10. 9000 2. 4732 2. 2032 16. 1140 0.2:376 0. 4320 4. 2660 6’ 46-12 1. 79213 0. 1944 4. Lb 4
7. 021.0 13. 1530 20. 5000 1. 2 ’/5 3. 1000 220. 000 0. 3125 0. 4073 3. 6000 6. 7000 2. i12b 0. 171.0 4. 3675
-------
D. Project period (May 1978—April 1979) continued.
cos
5ITE DATE
1.58 2. 3 0
23
24
25
25
7
P 1 1 6 2 11 721-79 112 5.48 19. 1
S1U RT 7u —79 117 5. 16 21.4
TALL ’24A S E 70--79 141 4.76 15.0
W61 .D(J $ULI& 7(1—79 139 4. 62 18. 1
w L&o ThN0UC2- ( ALL 78-79 105 4. 73 29, 9
1.260 0.263
2.240 0.276
0. 350 0.262
0. 538 0. 196
1. 570 0. 593
UEOH
0. 157 0.952 0. 118
3.201 0.474 0. 141 0. 1 9 2. 52 4. 90
0. 057 0. 436 0. 259 0. 194 1. 67 0. 742
0. 077 0. 297 0. 144 0.202 2. 15 0. c2
0. 32 ? 1. 340 0. 121 0. 219 3. 16 3. 30
1D P 6C504 EX$84 SESOEP XSDEP
005
iitPl H U12CN ORCI INORGP4
TOrN
17800 4. 72267
23
:4
5
26
27
0. 337 0. 0000034674 0. 271 0. 010 0. 283
0.322 0.000036?103 0.101 0.000 0.310
3 . 39 0.0000173733 0.230 0.010 0.333
0. 303 0. 0000229023 0. 236 0. 011 0. 346
0.463 0. 0000138227 0. 342 0. 013 0. 340
0. 554 3. 4674
0.491 6.9183
0.493 17.3780
0. 502 23. 5003
0. 602 I(J. 6209
33. 835 0. 3150 1.
80.944 0.5600 0.9600 2.1800 3.74400
245.030 0.0875 1.3325 0.41125 74377 ’
333. 438 0. 1470 2. 0030 0. 60110 9. 2 1057
195 319 0. 3925 2. 7875 1. 37375 9. 7562
DROFOOF IN7 . .rEP
065
L.0 P P D P tiOLY° CAPEP NH4DEP NO3DEP
OLDEP DP3 ’
TPDEP ThNDEP TNDEP
8.2048 3. 0352 0. 2016 a 1696
23
2..
25
26
27
14. 1120 2. 945f 1 7 34 10. 6.624 1.2992 1, 9704
23 2020 3 2292 2 J/7 S 54.i3 I s4 1/ 1 9773
4. 9350 3. 6942 0. 8337 0. 1476 2. 2419 2. 7354
0.1732 2.7522 1.0/03 4.1233 2.0018 2.0018
16. 4550 5. 2265 3. 4345 14. 0700 1.2705 2. 2995
26. 6560 0. 2240
49 023k) 0 2 /4
10. 4622 0 1033
1 .768B 0.1946
34. 1250 0. 1785
0. 4.
0 3510 3 7 74 S 74’.7 2 1177 0 0136 3 70
0. 3243 4. 0749 6.6103 1. 6330 0. 1410 4. 9773
0.3475 5.2820 8.0698 3.2304 O.1S 9 4,6094
0.3150 4. 6615 7. 1610 3. 5910 0. 1385 3. 5700
0? TP
C .. C38
0. 033
o
0 07 :5
0. o: ,o
0. 020
0. c22
0 013
0. 314
0. 017
17. 693
17. 704
23. 5 7
29. 835
33. 393
-------
APPEN1)IX KEY
RAIN = Rainfall (cm)
PH = —Log [ a,d+J (unitless)
CON Specific conductance ( /cm @25%)
MA Sodium (mg/L)
K Potassium (mgIL)
MG Magnesium (tng/L)
CA Calcium (mg/L)
NH4 Axnmonium nitrogen (mg/L)
N03 Nitrate nitrogen (mg/L)
S04 Sulfate (mg/L)
CL = Chloride (mg/L)
OP Ortho—phosphorus (mg/L)
TP Total phosphorus (rnglL)
TKN Total Kjeldahl nitrogen (mg/L)
H Hydrogen ion (gIL)
OB.GN = Organic nitrogen (rnglL)
ORGP Organic phosphorus (mg/L)
INORGN = Inorganic nitrogen (mgIL)
TOTN Total nitrogen (tngiL)
UEQH Microequivalents hydrogen ion ( ieq/L)
EQHDEP Hydrogen deposition (g!ha—yr)
SESO4 = Sea (Marine—derived) sulfate (mg/L)
EXSO4 Excess (non—marine) sulfate (tng/L)
SESDEP = Sea sulfate—sulfur deposition (kg/ha—yr)
EXSDEP = Excess sulfate—sulfur deposition (kg/ha—yr)
SO4DEP Sulfate deposition (kg/ha—yr)
NADEP = Sodium deposition (kglhà—yr)
KDEP = Potassium deposition (kg/ha—yr)
MGDEP = Magnesium deposition (kglha—yr)
CADEP = Calcium deposition (kg/ha—yr)
NH4DEP = Ammonium nitrogen deposition (kglha—yr)
NO3DEP — Nitrate nitrogen deposition (kg/ha—yr)
CLDEP = Chloride deposition (kg/ha—yr)
OPDEP = Ortho—phosphorus deposition (kg/ha—yr)
TPDEP Total phosphorus deposition (kg/ha—yr)
-------
TI NDEP Total kjeldahl nitrogen deposition (kg/ha—yr)
TNDEP Total nitrogen deposition (kg/ha—yr)
ORGNDEp Organic r itrogen deposition (kg/ha—yr)
ORGPDEP Organic phosphorus deposition (kg/ha—yr)
INNDEP = Inorganic nitrogen deposition (kglha—yr)
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