AN ABSTRACT OF THE THESIS OF
ROSS CHARLES KAVANAGH
(Name)
in
FISHERIES
(Major)
for the
MASTER OF SCIENCE
(Degree)
presented on
'
f(jc 6 (g"i3
(Date)
Title: A COMPARATIVE ANALYSIS OF FOUR OREGON COASTAL
LAKES ON THE BASIS OF DESCRIPTION, TROPHY AND
DENSITY -DEPDT FCTIONS
Abstract approved:
,1
Redacted for privacy
John R.Donaldn
Limnological data were collected from studies of four Oregon
coastal lakes: Devils, Siltcoos, Mercer, and Munsel. The lakes
were compared and analyzed on the basis of descriptive characteris-
tics, trophy, and density-dependent functions. Physiographic and
physio-chemical measurements, limnetic primary production estimates, and phytoplankton and zooplankton biomass estimates were
performed in an attempt to classify these four lakes on the basis of
their productivities.
On a trophic scale, based on limnetic primary production esti-
mates, Devils, Siltcoos, Mercer, and Munsel lakes wouldall be
classified as naturally eutrophic with Mercer and Munsel lakes bordering on the lower range of natural eutrophy. Descriptive lake
classification techniques and biomass estimates provided the same
relative conclusions for the four study lakes.
A literature review and a consideration of the data collected
during the present study revealed that no correlations can currently
be demonstrated between the measured relative growth rates of phyto-
plankton and a lake's trophic status. However, correlations may
theoretically exist between the relative growth rates of a single Htypel
phytoplankton population and lake trophy.
An analysis of the density-dependent functions of phytoplankton
in Munsel Lake suggested that temperature may have been a dominant
environmental factor governing changes in the relative growth rates
of
phytoplankton and ecosystem productivity of this lake. However,
nutrient availability must be considered the dominant environmental
factor governing the status of each of the study lakes on a scale of
oligotrophy through eutrophy.
Standard limnological techniques can be used to classify lakes
by trophy on the basis of density-dependent functions. However, the
resulting lake classification scheme isfairly insensitive to absolute
differences in the productivity of eutrophic lakes. Instead, the theory
of density-dependent functions may have more value when used to
analyze the dynamics of trophic processes.
An over-all conclusion is reached that precise lake classification
by trophy and the estimation of lake productivity are essentially
impossible tasks to perform because there is no universally acceptable
definition of what constitutes a lake's trophic status or productivity
and almost all presently used techniques to estimate these undefined
qualities are complicated, time-consuming, and inconclusive.
A Comparative Analysis of Four Oregon Coastal Lakes on
the Basis of Description, Trophy, and
Density-Dependent Functions
by
Ross Charles Kavanagh
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
June 1973
APPROVED:
Redacted for privacy
Asso$ te Profes'sor 'of Fisheries
in charge of major
Redacted for privacy
Head of Department of Fisheries and Wildlife
Redacted for privacy
Dean of Graduate School
Date thesis is presented
Typed by Clover Redfern for
Ross Charles Kavanagh
ACKNOWLEDGMENTS
I wish to express my sincere appreciation to Drs. John R.
Donaldson, Charles E. Warren, and Joe B. Stevens who served as
members of my graduate committee. My special thanks are reserved
for Dr. John R. Donaldson who directed the project and served as my
major professor during two long years of graduate school. Without
his direction, his inspiration, and his contagious enthusiasm, this
thesis could not possibly have been completed.
I am indebted to Drs. Charles E. Warren and Gerald F. Davis,
Department of Fisheries and Wildlife, for their views concerning
density-dependent functions; Dr. Raymond C. Simon, Department of
Fisheries and Wildlife, for use of liquid scintillation counting and
spectrophotometric equipment; Dr. Douglas W. Larson, State of Oregon Department of Environmental Quality, for making available
cer-
tairi unpublished research data; Dr. Carl E. Bond, Department of
Fisheries and Wildlife, for his advice and criticism on certain portions of this thesis; and Mr. Brian McCuhen, Computer Center, for
his revisions and adaptations of certain computer programs.
For specific information I would like to thank Drs. Herbert C.
Curl and Larry F. Small, Department of Oceanography; Dr. Harry
K. Phinney, Department of Botany; Messrs. James Hutchinson and
Steven Lewis, State of Oregon Game Commission; and Mr. Duane
Higley, Department of Fisheries and Wildlife.
The conscientious field and laboratory assistance of Messrs,
Ronald Jamison, Rolf Reichel, Duane Karna, Gary Keenan, Stanley
Gregory, David Liscia, Jeffery Morey, and Kenneth Brophy was much
appreciated.
I am most indebted to my wife, Nancy, for her patience,
encouragement, and support, both financial and moral.
This study was funded by the U. S. Department of the Interior,
Office of Water Resources Grant No. A-003-ORE.
TABLE OF CONTENTS
Page
INTRODUCTION
1
Study Objectives
Selection of Study Area
13
14
MATERIALS AND METHODS
15
RESULTS AND DISCUSSION
22
Phy s jo graphy
Geographic Region
Origin
Mo r phome try
Hydrology
Lake Sediments and Geology
Littoral and Shoreline Vegetation
Physio -Chemistry
Temperature, Dissolved Oxygen, and pH
Water Chemistry and Light
Trophic Environments
Limnetic Primary Production and Chlorophyll a
Estimates
Density-Dependent Functions
Theory
Application
A General Discussion
23
23
23
24
30
31
33
34
34
42
54
54
70
70
90
98
SUMMARY AND CONCLUSIONS
103
BIBLIOGRAPHY
108
LIST OF FIGURES
Figure
1.
2.
3,
Theoretical relationships between phytoplankton relative growth rate and its controlling and/or limiting
factor(s) in three lake systems of differing productivity.
Page
11
Theoretical relationships between phytoplankton bio-
mass, production, and growth rate in three lake systems
of differing productivity.
11
Theoretical relationships between phytoplankton biomass
and biomass of zooplankton within particular lake systems (solid lines) and among lake systems (dashed line).
12
4.
Bathymetric chart of Devils Lake, Oregon, showing
sample station location,
5.
Bathymetric chart of Siltcoos Lake, Oregon, showing
sample station location,
26
Bathymetric chart of Mercer Lake, Oregon, showing
sample station location.
27
Bathymetric chart of Munsel Lake, Oregon, showing
sample station location.
28
Temperature isotherms during the study period in
Devils Lake, Oregon.
35
Temperature isotherms during the study period in
Siltcoos Lake, Oregon.
35
Temperature isotherms during the study period in
Mercer Lake, Oregon.
36
Temperature isotherms during the study period in
Munsel Lake, Oregon.
36
Seasonal comparison of temperature. dissolved oxygen,
and pH profiles in Devils Lake, Oregon.
37
Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Siltcoos Lake, Oregon.
38
6.
7.
8.
9,
10.
11.
12.
13.
Figure
14.
15.
16.
17.
18.
19.
Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Mercer Lake, Oregon.
Page
39
Seasonal comparison of temperature dissolved oxygen,
and p1-I profiles in Munsel Lake, Oregon.
40
Annual means and ranges of physio-chemical features
compared among the study lakes.
43
Percent transmittance of incident light and extinction
coefficients compared among the study lakes.
44
Nitrogen isopleths during the study period in Devils
Lake, Oregon.
45
Nitrogen isopleths during the study period in Siltcoos
Lake, Oregon.
45
20. Nitrogen isopleths during the study period in Mercer
Lake, Oregon.
46
21. Nitrogen isopleths during the study period in Munsel
22.
23.
Lake, Oregon.
46
Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates
during the study period for Devils Lake, Oregon.
57
Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates
during the study period for Siltcoos Lake, Oregon.
58
24. Comparison of vertical profiles of phytoplankton photo-
25.
synthetic rates and ch1orophyfla biomass estimates
during the study period for Mercer Lake, Oregon.
59
Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates
during the study period for Munsel Lake, Oregon.
60
26. Phytoplankton production rates per in2 during the study
period in Devils, Siltcoos, Mercer, and Munsel Lakes,
Oregon.
62
Figure
Page
27. Approximate means and ranges of daily phytoplankton
28.
29.
primary production rates measured during the summer
and annually for the four study lakes compared with the
Rodhe (1969) scale for oligotrophic and eutrophic lakes.
63
Mean summer (June-Sept. , 1968-1971) unadjusted and
adjusted primary production rates of eight Oregon lakes
compared with the Rodhe (1969) scale for oligotrophic
and eutrophic lakes.
64
Comparison of phytoplankton assimilation numbers,
light, temperature, and nitrogen at the depth of maximum primary production during the study period in
Munsel Lake, Oregon.
79
30. Pos si.ble relationship between phytoplankton as similation
numbers and temperature at the depth of maximum primary production in Munsel Lake, Oregon.
31.
80
Theoretical relationships between phytoplankton bio
mass, production, and growth rate compared with
phytoplankton biomas s, productions and assimilation
numbers measured at the depth of maximum primary
production during the study period in Munsel Lake,
Oregon.
81
32. Seasonal progression of phytoplankton and zooplankton
biomasses during the study period in Munsel Lake,
Oregon.
86
33. Seasonal progression of phytoplankton and zooplankton
biomasses during the study period in Devils Lake,
Oregon.
91
34. Seasonal progression of phytoplankton and zooplankton
biomasses during the study period in Siltcoos Lake,
Oregon.
92
35. Seasonal progression of phytoplankton and zooplankton
biomasses during the study period in Mercer Lake,
Oregon.
93
Figure
36.
Theoretical relationships between phytoplankton biomass and biomass of zooplankton within particular
lake systems (dashed lines) and between lake systems
(solid line) compared with mean annual phytoplankton
and zooplankton biomasses measured for the four study
lakes.
Page
94
LIST OF TABLES
Table
Pge
1.
Morphology of four coastal lakes in Oregon.
29
2.
Total phosphorus concentrations (f.Lg/l P) at the surface
(0. 5 m) in four coastal lakes of Oregon.
51
Total dissolved phosphorus concentrations (p.g/l P) at
the surface (0. 5 m) in four coastal lakes of Oregon.
51
Mean summer (June-Sept. 1968-197 1) unadjusted and
adjusted primary production rates of eight Oregon lakes.
68
Conversion of sampling date codes to sampling dates,
82
3.
4.
5.
,
A COMPARATIVE ANALYSIS OF FOUR OREGON COASTAL LAKES
ON THE BASIS OF DESCRIPTION, TROPHY, AND
DENSITY-DEPENDENT FUNCTIONS
INTRODUCTION
Limnologists have long been concerned with the problem of lake
classification. Historically, their interests, though diverse, have
generally led them to the practice of categorizing all lakes with the
aid of two different, but parallel, conceptual approaches.
The first of these approaches is based upon a descriptive
philosophy. By description is here meant that the investigator would
primarily concern himself with the physiography (region, origin,
morphometry, hydrology, etc. and physio-chemical properties
(optics, heat, dissolved oxygen, alkalinity, hardness, specific conductance, total dissolved solids, nutrients, etc. ) of all lakes and
attempt to arrange them systematicallyon this basis.
This descriptive philosophy prevailed in the classification
attempts of the earliest investigators and was first exemplified by
the work of Forel (1892-1901). His thermal lake classification
scheme, as modified by Whipple (1927), became the prototype for a
whole series of lake types based upon thermal stratification, mixing,
bio-geochemical cycles, and origin. This descriptive approach is
still present today if one examines the works of Hutchinson (1957) and
Berg and Neff (1955). Hutchinson lists 76 lake types on the basis of
2
their region and origin while Berg and Neff have organized one of the
most useful thermal lake classification systems in use today.
Further examples of the descriptive philosophy are provided by
Birge and Juday (1911, 1931), Their earlier work showed that it was
possible to classify lakes on the basis of bound carbon dioxide and
they divided all lakes into those containing soft, medium, and hard
waters. Their later investigations of 72 Wisconsin lakes indicated a
possibility of classificationon the basis of the percent transmission
of solar radiation through a stratum of water 1 m thick and they
divided all lakes into those having low, low-medium, high-medium,
and high transmis sion characteristics.
The descriptivephilosophy has performed, and continues to
perform, a useful function in comparative limnology. It has allowed
us to attempt a preliminary sorting out of those lake systems which
are most alike, thus categorizing or classifying them, but, most
important, it has emphasized the truly unique nature of each individual
lake system. Des criptive approaches to lake classification have, as
an inevitable result, the collection of huge masses of often unmanageable environmental information. The difficulty of analysis of these
abiotic data led investigators to conclude that there were two inherent
factors limiting the utility of descriptive lake classification schemes:
(1) a problem of interpretation due to an inability to describe the
status of individual lake systems along a biological continuum and
3
(2) the lack of any central unifying principle or principles through
which man could comprehend the diversity of known lake types.
This realization became the genesis for the second conceptual
approach to lake classification: trophy. Trophy, from the Greek
trophë, or nutrition, eventually came to mean the relative nutrient
status of lakes and their resultant productivities.
In an effort to avoid ambiguity, it may be pertinent at this
point to define a few terms. In following discussions, the term pro-
ductivity will be employed in two patallel senses. By the word
productivity is here meant the basic capacity of an ecosystem to pro-
duce a product of interest, whatever the instantaneous level of its
production (Ivlev, 1945); however, reference to lake or ecosystem
productivity will mean the inferred over-all capacity of an ecosystem
to produce, based on selected product of interest productivities which
may be used as an index of ecosystem productivity. Production, of
course, refers to the total tissue elaboration of a population per unit
of area per unit of time, regar4less of the fate of that tissue.
With the advent of a trophic philosophy, limnologists began to
examine lakes on the basis of productivities and to speculate on the
possible causes and methodology of the phenomenon. The following
trophic categories were developed through a series of papers by
Naumami (1917, 1919, 1921, 1925, 1926, 1929, 1931, 1932),
Thienemann (.1918, 1921, 1925, 1926, 1927), and numerous
4
subsequent investigators: (1) oligotrophy (low nutrients
duction), (2) mesotrophy (intermediate nutrients
duction), (3) eutrophy (high nutrients
low pro-
intermediate pro-.
high production), and
(4) dystrophy (a usually unproductive trophic state in which a lake
system, though it may fill and die, seldom reaches a state of eutrophy
due to incomplete plant decay and the accumulation of humic mate-
rials).
The trophic philosophy of lake classification has largely satis-
fled the criticisms that were inherent in the descriptive classification
schemes. Using the trophic approach it is possible to examine the
status of individual lake systems along a biological continuum and
trophy has the unifying principle that all known lake types must
eventually fill and die through the accumulation of organic and
inorganic sediments; but, like the descriptive philosophy, it is not
without certain limitations in its use. Its most critical limitation
may be the basic problem in current lake classification theory: how
do we meaningfully and accurately measure the productivities of
aquatic ecosystems and how do we express such measurements in
terms not bound by arbitrary taxonomic categories?
The traditionaL concepts of lake classification by description
or trophy may be self-defeating because, so far, they have implied
that in order to understand and utilize, we must group. This is ironic
because the trophic conceptualization is also viewed as a continuum.
There is a current need in applied water pollution biology for a
method or methods through which investigators may quickly and
accurately assess actual and potential lake productivities. Current
lake classification concepts must evolve to meet the need of adequate
expres sion.
Thus far, there appear to be two general methods offering the
most promise for a solution to this dilemma of expressing continuous
trophic conditions, both of them involving possibilities for graphical
analyses: (1) the direct estimation of ecosystem productivity through
limnetic primary production measurements and (2) indirect estimation of ecosystem productivity through the use of indices of productivity.
Primary productivity estimates became possible with the development of the light bottle-dark bottle oxygen evolution technique
(Maucha, 1924). More recent primary production investigations have
centered on the use of the 14C assimilation technique devised by
Steeman Nielsen (1952), because it enables us to determine produc-.
tion in oligotrophic ecosystems with much greater precision (Raymont,
1963).
There still remains, however, the problem of determining
whether we are measuring gross or net production. The most recent
investigations suggest that the technique measures somewhere
between the two, and possibly nearer net production (Small, personal
communication). The estimation of either net or gross carbon fixation
is complicated by the simultaneous assimilation of organic (non)4C)
compounds, the unmeasurable release of non-particulate soluble products of photosynthesis, and the possible incomplete cellular recycling
of '4C-labeled respiratory CO2 (Fogg, 1969; Bunt, 1965). In any
event, limne tic primary production measurements can be used to
estimate the relative capacities of ecosystems to produce.
Rodhe (1969) has proposed a scale for differences in lake pro-
ductivity and trophy based on daily primary production estimates (to
be discussed in a later section). Oligotrophy is equated with production estimates of from 30-100 mg C
in2 day'.
Eutrophy is con-
sidered as being in the range o 300-3, 000 mg C m -2 day -1 , with
natural eutrophy occupying the range of 3001, 000 mg C
m2 day1
and polluted eutrophy being in the range of 1, 500-3, 000 mg C
m2 daj.
Rodh&s categorical use of the terms oligotrophy and eutrophy,
natural and polluted, may be arbitrary and subject to later qualification as more information becomes available; but his absolute scale
does allow one to assess lake productivity along a biological continuum
and has possibilities for graphical analysis.
Indices of productivity, the second general method of ecosystem
productivity estimation, is an attempt to estimate lacustrine productivities through the use of one of the two following approaches:
(1) demonstrated correlations between physiographic or physio-
chemical variables and productive levels, and (2) direct quantitative
7
measurements of levels of production.
The correlation approach has been used by numerous investiga-
tors. Thienernann (1927) believed that lake basin morphometry and
particularly mean depth could be a useful index of productivity.
Naumann (1932) stressed the importance of the chemical nature of
lake waters in determining their production. Deevey (1940) related
total phosphorus levels to plankton production and Moyle (1946) cor-
related fish production in a number of Minnesota lakes to their total
alkalinity and total phosphorus content. More recently, Northcote
and Larkin (1956) have shown through multiple regression analyses
that total dissolved solids (T. D.S,) was the only single physical or
chemical index of productivity which could be significantly related to
standing crops of plankton, bottom fauna, and fish in 100 British
Columbia lakes; but the relation was only valid for very large ranges
of T.D.S., such as was found province-wide.
Welch (1952), after considering such proposed productivity
indices as mean depth, rooted submerged vegetation, plankton, bottorn fauna, and the organic and chlorophyll content of water, con-
cluded that, thus far, no single satisfactory index of productivity had
been found. He found that there were always exceptions to the idea
that the richness of a lake (ecosystem productivity) might be esti-
mated by any single criterion. He did, however, imply that plankton
might be the most dependable index, if its various fluctuations could
be accounted for, and that, on the average, it was indicative of the
general nutritive condition of the water.
The second approach to indices of productivity is the direct
quantitative measurement of levels of production. Investigators have
long felt that in some, as yet incompletely defined manner, lake productivity might be expressed a a quantitative function of existing
biomasses of living material, the results of production. Thienemann
(1918) felt that the abundance and quality of benthic organisms (par-
ticularly chironomid larvae) and plankton might be used as an index of
productivity; and he as so ciated quantitatively poor plankton biomas se s
with oligotrophic lakes and abundant plankton biomasses with eutrophic
lakes. The investigations of Riley (1940), Deevey (1940), and
Findenegg (1942) showed that, for diverse lakes, there was often poor
agreement between plankton biomass levels and the 1akes supposed
trophic status, when these biomasses were calculated on a per unit
area basis; but when these biomasses were calculated on a per unit
volume basis for the trophogenic zone, the content per liter and the
trophic level were in good agreement (Ruttner, 1963).
Until very recently, there has been no proposed conceptual
framework through which we might organize and measure observed
relations between lake productivity and quantitative levels of production. Lindeman (1942) gave a fresh impetus to the field of trophic
dynamics by demonstrating the energy relations between trophic
levels in ecosystems exhibiting a relatively constant state of productivity. He also showed how the over-all productivity of a lake system
changes as it evolves from oligotrophy through senescence to a
climax forest. But his ideas on food relations, though revealing and
thought provoking, were of such an all encompassing, abstract, and
essentially unmeasurable nature that, by themselves, they offered
little significance for the formulation of improved systems of lake
classification.
Warren (1971) and Brocksen, Davis, and Warren (1970) have
proposed a technique for the graphical analysis of the densitydependence of predator and prey biomasses in ecosystems that are
food limited. The analytical technique may have significance for cur-
rent lake classification theory because it can also serve to estimate
the relative productivities of ecosystems, whether those productivities are changing or are static. The approach (after adaptation) is
outlined inFigures 1, 2, and 3. Originally, these general models
of density-dependent relations in trophic processes were developed
through studies of the growth rates, production, and biomasses of
trout, sculpins, and aquatic insects in laboratory stream communities
where the productivities of individual systems could be controlled
(Davis and Warren, 1965; Warren and Davis, 1967; Brocksen, Davis,
and Warren, 1968, 1970; Warren, 1971). However, the relationships
may be valid for any two dependent steps along a trophic pathway
10
(Figure 1). In addition, examination of Johnson's (1961) data on
sockeye salmon and zooplankton in British Columbia lakes showed
that the same general relationships may be generated in natural eco-
systems (Brocksen, Davis, and Warren, 1970).
In brief form, the general argument may be stated in the following manner. In an ecosystem which is food limited, predator growth
rates (production/biomass) will increase with increasing biomasses
of prey; and systems of higher productivity can be expected to maintam
both higher predator growth rates and higher prey biomasses
(Figure 1). Because the food available to any consumer in a food-
limited environment decreases as consumer biomasses increase,
consumer growth rates will decrease with increasing consumer bio-
masses. Consumer production will also bea function of consumer
biomasses because production is the product of growth rate and bio-
mass. Systems of higher productivity will exhibit higher mean
consumer growth rates, biomasses, and production (Figure 2). The
biomasses of prey organisms will decrease with increasing predator
biomasses within a system, a negative relationship. Systems of
higher productivity will exhibit higher predator and prey biomasses,
a positive relationship. The decreases in negative slope between
ecosystems as productivity increases indicates that in systems of
higher productivity, predator consumption becomes a less important
fate for prey biomasses (Figure
3).
Figure 1. Theoretical relationships between phytoplankton relative
growth rate and its controlling and/or limiting factor(s)
in three lake systems of differing productivity. (Adapted
from Brocksen, Davis, and Warren, 1970.)
Figure 2. Theoretical relationships between phytopla
production, and growth rate in three lake
differing productivity. (Adapted from Bro
and Warren, 1970.)
[Consumer(Predator or Prey) Growth Rat
PHYTOPLANKTON RELATIVE GROWTH RATE (Assim.No.)-'
/
30
C-4
(D0
-'I-.
/
/
/
/
/
-UI
/
/
/
/
/
//
4 <-
mO
/
/
-Dz
-'W
0
-'0
/
/
/
0I
cz
3G
/
r
m
CD rZ
/
WI
Ill
/
Xr
-
o >-4
(n z-
/
0
3
0
/
/
L!J
(Predator Growth Rate)
PHYTOPLANKTON RELATIVE GROWTH RATE (Assim.No.)"
0
If
II
II
00
\\I
4O
2
I
I \r \
4C
/
za
m
PHYTOPLANKTON PRODUCTION RATE
-
Consumer (Predator or Prey) Productio
\\\j
C,
<A
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LAKEC
I
LAKEB
(l)Z
7/
fi
Q
7
0k.-.
oz
LAKE A
"a--J
G)
a-I1
I0
ZOOPLANKTON BIOMASS
(Predator Biomass)
Figure 3. Theoretical relationships between phytoplankton biomass and biomass of zooplankton
within particular lake systems (solid lines) and among lake systems (dashed line).
(Adapted from Brocksen, Davis, and Warren, 1970; Warren, 1971).
N
13
The legends on the ordinates and abscissas of Figures 1, 2,
and 3 are intended to represent the probable relations between the
growth rates, production, and biomasses of phytoplankton and zooplankton in lakes, if phytoplankton are the principal prey of the
zooplankton. A further discus sionof the foregoing principles may be
found in Donaldson (1969).
Study Objectives
The over-all purpose of this study is to evaluate current lake
classification theory and to recommend, if possible, an improved
method or methods through which investigators may quickly and
accurately assess lake productivity.
The specific objectives are: (1) to describe and classify four
Oregon coastallakes on the basis of the early, descriptive philosophy
of lake classification, (2) to classify these lakes by trophy on the
basis of limnetic primary production estimates, (3) to review present
trophic analysis theory, as applied to primary production, and to
attempt an analysis of trophic processes on the basis of densitydependent functions, (4) to determine if standard limnological tech-
niques can be used to provide the information necessary for a trophic
classification of lakes on the basis of density-dependent functions,
and (5) to evaluate the relative merits and deficiencies of lake classi-
fication by description, limnetic primary production estimation, and
14
density-dependent functions.
Selection of Study Area
This study was funded by the U.S. Department of Interior,
Office of Water Resources Grant No. A-003-ORE. It is part of a
continuing program to classify the lakes of the State of Oregon on the
basis of their physical, chemical, and biological properties. Previous investigators have concentrated on lakes in the Oregon Cascade
Mountain Range (Larson, 1970a, b, c; Larson and Donaldson, 1970;
Malick, 1971). It was appropriate, therefore, to select a new study
area to broaden the published information about Oregon waters. The
coastal lake region was selected as the area having the next highest
priority on the basis of its intensive use by the public and its potential
for accelerated eutrophication. Transit time and an intensive sampling schedule limited the survey coverage to a maximum of four
lakes.
15
MATERIALS AND METHODS
During the summer of 1970, a preliminary limnological survey
was conducted on eight Oregon coastal lakes in order to select four
lakes suitable for the purposes of this study. Devils, Siltcoos,
Mercer, and Munsel lakes were the four study lakes chosen as a
result of two visits to each lake. Continuous limnological monitoring
of the four study lakes began in February, 1971 and extended through
January, 1972. Each lake was visited approximately once a month
except for June, July, August, and September, 1971, when it was
possible to visit each lake at about three week intervals. A detailed
listing of the exact sampling dates will appear in Results and Discussion, where coded sampling dates will be used in an analysis of
the predator-prey relations present in each lake.
All sampling was conducted at a single index station on each
lake.
In establishing a permanent station, consideration was given
to sampling convenience and the degree to which the site would be
representative of conditions within the limnetic zones of each lake.
In general, the index station was located at a point over the maximum
depth of each lake.
Thermal profiles were determined with a Whitney portable
thermometer (model TC-5A), having a scale calibrated in 0.
10
C
units. Temperatures were recorded at 0.5 m intervals to the bottom
16
of each lake.
Light attenuation data were obtained with a Kahi submarine
photometer (model 268 WA 310), having a spectral range (in sunlight)
of 400-640 mIJ.. Blue, green, and red filters, having spectral ranges
of 400-550 mp., 460-660 m, and 500-720 mid., respectively, were
used to determine therelative attenuation of these components of the
visible spectrum. The photometer readings were recorded at 0. 5 in
intervals in Devils and Siltcoos lakes
In Mercer and Munsel lakes
the recording interval was 0.5 m to a depth of 10 m; thereafter, the
recording interval was lengthened to 1 m. Light penetration was also
determined by meansof a standard (20 cm diameter) Secchi disc.
Water samples for chemical analyses were collected at the surface and at several evenly-spaced sampling depths extending to near
the bottom of each lake. The water analyses except those for
phosphorus and total dissolved solids, were conducted in a mobile
limnology laboratory within 6 hours after the samples were collected.
A Corning pH meter (model 7) and a Hach kit were used to determine
p1-I values. Specific conductance was measured with a Beckman con-
ductivity bridge (model RC-16B2). Total alkalinity was determined
colorimetrically, using bromcresol green-methyl red indicator solution. Total hardness was determined by EDTA titration.
Dissolved
oxygen was measured using the Winkler method (azide modification)
with PAO (phenylarsene oxide) as the titra.nt. Nitrogen (N) was
17
measured as NO3 or NO2 using a Hach kit.
Water samples for phosphorus and total dissolved solids
determinations were collected at a depth of 0. 5 m and analyzed in the
Oregon State University Limnology Laboratory. Total phosphorus is
defined here as the sum of all forms of phosphorus (organic and
inorganic, dissolved, colloidal-, or particulate) which have been con-
verted to orthophosphate by perchloric acid digestion, measured as
orthophosphate (PO4), and reported as p.g/l P. Total phosphorus
analyses were performed according to the procedures outlined in
Strickland and Parsons (1965), with the two following modifications:
(1) a 1 rather than 10 cm-path-length spectrophotometer cell was
used, giving a detection range of from 1.8 to 91 .i.g/l P in the Determination of Reactive Phosphorus (Low Levels) Section, and (2) glass
rather than polyethylene collecting bottles were used, after cleaning in
a solution of 1% HF in 2N HC1 as recommended by Hassenteufel,
Jagitsch, and Koczy (1963). Total dissolved phosphorus analyses
were performed by filtering water samples through 0, 45 i filters
before perchloric acid digestion. Phosphorus sampling was discontinued after 3uly 14, 1971 due to difficulty of analysis and loss of
samples. The method for determining total dissolved solids was
derived from the Standard Methods handbook (APHA, 1965).
Vertical zooplankton tows were performed and the samples
analyzed in a manner which would record the mean daily biomasses
of zooplankton per volume of lake water. Two replicate tows were
taken on eachsampling date with a no. 12 mesh net having an intake
diameter of 0. 5 m. Each tow was drawn from 5, 4, 10, and 17 m,
respectively, in Devils, Siltcoos, Mercer, and Munsel lakes. A TSK
(Tsurumi-Seiki Kosakusho Co.) flow meter was mounted in the net
intake so that a determination couldbe made of the exact quantity of
water passing through the net. The zooplankton samples were then
fixed in 5% formalin and transferred to Oregon State University for
dry weight determinations.
In the laboratory, each zooplankton sample was examined for
phytoplankton contamination and, when necessary, appropriate steps
were taken to effect separation. The most common algal contamination was that of large colonial forms in the samples from Devils and
Siltcoos lakes and separation was accomplished by pipetting the float-
ing algae from the surface of the formalin solutions. After separation,
the replicate zooplankton samples were combined and filtered through
tared no. 12 mesh screens, dried at 60°C for 24 hours, and weighed
with a Mettler balance (Lovegrove, 1962).
Phytoplankton biomass sampling was similarly performed and
the samples analyzed in a manner which would estimate the mean
daily biomasses of phytoplankton per volume of lake water (Strickland,
1960).
Water samples for chlorophyll a estimates were taken at the
surface and at from four to seven generally evenly-spaced sampling
19
depths extending to the same depths at which the vertical zooplankton
tows originated. The water samples were then immediately treated
with saturated MgCO3 to neutralize any acid produced by algal
decomposition (Strickland and Parsons,
4
1965).
Within a period of
hours, a specific volume of each sample was filtered through 0. 8
fL
filters in a Millipore filter apparatus. Additionally, a composite
sample was prepared and a specific volume filtered in identical fashion.
The composite sample was formed by combining the samples
from each of the sample depths in a ratio equal to that volume of
water which they represented in the total water column. The filters
were then placed in a desiccator and stored in a freezer compartment
at -25°C.
In the laboratory, chlorophyll a was extracted from the filter
papers by grinding each filter for 1 minute with a Sorvall Omnimixer and rinsing the homogenate into a centrifuge tube containing
10 ml of 90% distilled reagent grade acetone. Each tube was stop-
pered, shaken vigorously, and allowed to steep 18 hours in a dark
refrigerator. After this period of pigment extraction, the tubes were
centrifuged for
15
minutes at 8, 000 rpm. The supernatant liquid
from each tube was then decanted into a 1 cm-path-length spectrophotometer cell and the optical density of each sample was measured
at wavelengths of
750
m,
665 mp., 645
mj., and 630 m on a Beckman
spectrophotometer (model DB-G). The measured optical densities
were corrected against a blank spectrophotometer cell containing 90%
acetone and the chlorophyll a concentrations were calculated in
accordance with the equations of Strickland and Parsons (1965).
The mean daily biomasses of phytoplankton per volume of lake
water were computed by taking the mean of the two following esti-
mates: (1) the chlorophyll a estimate of the composite sample and
(2) the mean chlorophyll a estimate of the chlorophyll a estimates
from each sample depth, after integration by means of a computer
program.
Phytoplankton primary production was measured in situ using a
modification of a 1961
14
C technique developed by the Fisheries
Research Institute, University of Washington, Seattle (F. R. I. field
manual, section S6, carbon 14). Water samples were collected using
a metered crane and 2. 5 liter plastic Van Dorn type water samplers.
The sample depths were at the surface and at 1 m intervals in the two
shallower lakes (Devils and Si]±coos), at 0, 1, 2, 3, 4, 5, 6, 8, and
10 m depths in Mercer Lake, and at 0, 1, 2, 3, 4, 5, 6, 8, 10, 12,
and 17 m depthsin Munsel Lake.
A 125 ml glass bottle was filled with water from each sampling
depth, innoculated with 1 ml of a stock solution of Na2 14CO3 at
5. 0 p.Ci/ml, and returned to the depth at which it was drawn. Dark
bottles accompanied light bottles at every sampling depth in Devils
and Siltcoos lakes, and at evenly spaced intervals in Mercer and
21
Munsel lakes. The bottles were incubated for 4 hours (1000-1400 hr),
retrieved, placed in a dark box, and then filtered in the mobile
laboratory within 1 hour with a Millipore filter unit and 0. 8
filters. Uptake of
14
.i
C was measured at Oregon StateUniversity with
a Packard-Bell (model 2002) tri-carb liquid scintillation spectro-
meter. Calibration of the spectrometer and preparation of spectro.meter samples was performed in accordance with the methods of
Wang and Willis (1965).
A computer program was enlisted to integrate the resulting net
primary production rates at each depth in mg C m3 hr
and convert
them to mg C m2 hr. Approximate dailyprimary production rates
were calculated in accordance with the energy fractions (F) of
Vollenweider (1965) as modified by Platt and Irwin (1968). The 4-hour
in situ production measurements (mg C m2 4 hr') were divided by
an appropriate energy fraction (F) to convert them to
mg C
m2 day1. Appropriate energy fractions are presented for
the following months: January--0.70; February--0.64; March--0.51;
April--0.46; May--0.42; June--0.37; July--0.38; August--0.40;
September--0.50; October--0.54; November--0.60; December--0.72.
22
RESULTS AND DISCUSSION
The two following sections, Physiography and PhysioChemistry,
will provide an introductory description of the four study lakes and
will categorize them, when appropriate, according to the descriptive
philosophy of lake classification. The descriptions will concentrate on
abiotic properties; however, certain descriptive biotic information
will also be presented for convenience and to aid the reader in evaluating the basin environments. A majority of the physiographic data
have been extracted from McHugh (1972), Saltzman (1961, 1966), and
Oakley (1962a, b).
A further section, Trophic Environments, will concentrate on
the study lakes from a trophic point of view, including estimates of
their limnetic primary production rates and data on their densitydependent functions. A primary trophic analysis will be performed in
an attempt to relate phytoplankton primary production, phytoplankton
relative growth rates, phytoplankton biomasses, and zooplankton
biomasses to changes in ecosystem productivity.
In the final section, A General Discussion, the three previously
described methods of lake classification will be compared and evaluated. The discussion will recommend, where possible, those tech-
niques which appear to offer the most promise in the assessment and
interpretation of lake productivities.
23
Phys iography
Geographic Region
Each of the four study lakes are located on or within 2 km of the
central Oregon coast. Devils Lake lies adjacent to the town of
Lincoln City, in Lincoln County. Siltcoos, Mercer, and Munsel lakes
are clustered around the city of Florence, Oregon, in Lane County.
Florence is situated on the estuary of the Siuslaw River
Origin
The physical features of the Oregon coast north of Coos Bay
have been modified, to a large extent, by the interaction of riverine
alluviation, sand dune encroachment, and a rise in sea level during
the late Pleistoceneepoch. Small-volume coastal streams have been
flooded more quickly than their ability to alluviate their valleys.
Subsequent partial blocking of these drowned river valleys by shifting
coastal sand dunes has resulted in the formation of a number of fresh
water impoundments (Smith and Greenup, 1939; Baldwin, 1964). This
process of lake formation is particularly evident in an examination of
the coastal lakes near Florence, Oregon, where an extensive sand
dune complex forms an outer barrier. A similar situation is the
probable cause for the formation of Devils Lake near Lincoln City.
A lake classification by region and origin would place all four
24
of the study lakes into the following classification of Hutchinson
(1957): lakes associated with shorelines--Type 64, maritime coastal
lakes, ordinarily in drowned estuaries. Reid (1961) would simply
place all four lakes into the more general category of lakes developed
from shoreline activities.
Mo rphometr y
Bathymetric charts of the four study lakes are included in Fig-
ures 4, 5, 6, and 7. Comparative morphometric data are summarized
in Table 1.
Siltcoos Lake (elevation 2 m) lies the nearest to mean sea level
of any of the four study lakes. In addition, it has the largest area
(11.66 km2), volume (45.77 m3 x 106), shoreline length (47.63 km),
and shoreline development (3. 93). Munsel Lake is the deepest lake at
21.4 mand also has the greatestmean depth (10.4m). The shoal
areas (0 to 5 m deep) of Mercer and Munsel lakes have been calculated as being 15. 5% and 31%, respectively, of their total areas
(Oakley, 1962a, b). Calculations were not available for the shoal
areas of Devils and Siltcoos lakes. Devils, Mercer, and Siltcoos
lakes may be considered as having medium to high shoreline develop-
ment ratios. Both shoreline development and mean depth are frequently cited as being relative indices of ecosystem productivity.
J-.
I
DEVILS LAKE
DEE RIVER (outlet)
STATION
LOCAT ION
/2
7
/_Th
/2
-_---_..-
-.---
8
-, 4
20
4
'8
CR.
ROCK CR.
O
KILOMETER
STATUTE M1LE05
Figure 4. Bathymetric chart of Devils Lake, Oregon, showing sample station location. Map based on 1953
survey by the State of Oregon Game Commission, Portland, Oregon (map no. 920); contour
interval, 4 feet.
Figure 5. Bathymetric chart of Siltcoos Lake, Oregon, showing sample station location.
Map based on 1961 survey by the State of Oregon Game Commission, Portland, Oregon (map no. 1206); contour interval, 5 feet.
DAMLIN CR.
LEVAGE CR.
ME R CE R LAKE
MERCER CR. (outlet)
BAILEY CR.
'5
STATION
LOCATION
25
/7
/5 35
/
25
4
35
40+ A
4/
+
37
+
+1
+36
0
300
600
METERS
0
1000
FEET
2000
Figure 6. Bathymetric chart of Mercer Lake, Oregon, showing sample station location. Map based
on 1959 survey by the State of Oregon Game Commission, Portland, Oregon (map no.
1084); contour interval, 10 feet.
/0
MUNSEL LAKE
AIKERLEY CR.
30
40
\/5o
MLINSEL CR
(outlet)
60
STATION
J
+70
METERS
0
FEET
300
1000
Figure 7. Bathymetric chart of Munsel Lake, Oregon, showing sample station
location. Map based on 1959 survey by the State of Oregon Game
Commission, Portland, Oregon (map no. 1085); contour interval,
10 feet.
29
Table 1. Morphology of four coastal lakes in Oregon.
.a
Devils
Elevation, surface (m)
Area (km 2
Volume (m3 x 10 6
Depth, maximum (m)
Depth, mean (m)
Shoreline length (km)
(including islands)
Shoreline development
5
Siltcoos b
.
2
Mercer c
15
27
0.378
3.94
21.4
10.4
2.77
8.36
6.4
3.0
11.66
45.77
5.5
3.9
1.38
10.50
12.5
17.15
47.63
3.93
12.87
2.91
Munsel d
7.6
3.09
4.49
2.06
aDerived from contour map no. 920, O.S.G.C., Portland, Ore.
(Figure 4).
bSaltzman (1966); contour map no. 1206, O.S.G.C., Portland, Ore.
(Figure 5).
CSaltzman (1961), Oakley (1962b); contour map no. 1084, O.S.G.C.,
Portland, Ore. (Figure 6).
dOakley(1962a) Lewis (1971); contour map no. 1085, O.S.G.C.,
Portland, Ore. (Figure 7).
Siltcoos Lake has an almost flat cross profile while the other
lake basins are more varied with Devils and Munsel lakes having dis -
tinct regions of maximum depth. A lake classification by morphology
(Hatchinson, 1957) would result in the Siltcoos and Mercer lake basins
being called dendritic, Devils Lake either dendritic or lunate, and
Munsel Lake, most probably subcircular.
All of the lakes are, or have been in the past, subject to basin
modifications by shifting sand dunes driven by on-shore winds. The
northwest shoreline of Munsel Lake is adjoined by a substantial dune
complex.
30
Hydrology
Devils Lake has two tributaries, Thompson Creek and Rock
Creek (Figure 4). There is a single outlet, the Dee River, which
immediately flows into the Pacific Ocean, only a few hundred meters
distant from the lake. The nutrient input to the lake is probably high
because both tributaries flow through fields in which cattle are grazed.
In addition, nearly the entire shoreline is ringed with private residences, organizational camps, and boathouses. Nutrient input is
intensified by the run-off from fertilized, lawns and gardens and by the
proximity of septic tank drainfields for houses built close to the
water's edge (McHugh, 1972).
Siltcoos Lake has four major tributaries: Woahink, Fiddle,
Maple, and Lane Creeks (Figure 5). Woahink Creek drains Woahink
Lake, lying about 1 km north of Siltcoos Lake. Siltcoos River, the
outlet to Siltcoos Lake, flows a.bout 4 km to the Pacific Ocean. The
lake's drainage basin is about 116.5 km2 (Saltzman, 1966).
The surface water levels of Siltcoos Lake have fluctuated
greatly (about 4 m) in the past causing salt water intrusions up the
Siltcoos River and into the lake. A state engineer's report in 1960
indicated that reverse river flows were possible under high tide conditions if the lake level reached 1. 0 m mean sea level or lower
(Saltzman, 1966). Since 1963, the lake levels have been regulated to
31
some extent by the construction of a dam on the Siltcoos River bythe
International Paper Company. However, there is evidence, to be
presented later, that a salt water intrusion did occur during the study
period.
Mercer Lake is fed by three tributaries, Dahlin, Levage, and
Bailey Creeks (Figure 6). Its single outlet, Mercer Creek, flows
west into Sutton Lake, about 0. 8 km distant. Seasonal fluctuations of
the lake water level equal about 2 m and the total drainage area of the
three tributary streams is 18. 6 km2 (Oakley, 1962b).
Munsel Lake has a single major inlet, Aikerly Creek, and four
smaller unnamed tributaries (Figure 7). Aikerly Creek drains
Aikerly Lake, the southernmost body of water in a chain of three lakes
beginning 0.6 km north of Munsel Lake. The outlet of Munsel Lake,
Munsel Creek, flows 5 km south to join the Siuslaw River estuary.
Munsel Lake's drainage basin is 1.74 km2 and the entire drainage
area for the chain of four lakes, including the outlet stream, is
8. 52 km2 (Oakley, 1962a). Seasonal lake water level fluctuations are
about 1 m.
Lake Sediments and Geology
The sediments of Devils Lake are described as being composed
of mud and peat, with certain shoal areas characterized by deposits of
silt washed in after heavy rains (McHugh, 1972).
32
The soils surrounding the lake basins near Florence, Oregon,
are characterized as being sand, sandy loam, and Melbourne red
clay, as the dune complexes merge with the mountain-type shale and
rock of the foothills of the Coastal Mountain Range (Griffiths and
Yoeman, 1938). Saltzman (1961) described the bottom of Mercer Lake
as known to be composed predominantly of silt. Oakley (1962b) is
more specific, stating that in his bottom sample transects he found
mostly sand with a little fine gravel to a depth of about 5 m and sandy
muck or muck in 6 to 9 m samples.
Munsel Lake has a varied bottom composition as described by
Skeesick (1965). Pure sand extends outward from the west and north-
west shoreline to a depth of about 12 m. The south, east, and north
shores are predominantly clay with some interspersed rubble, again
to a depth of about 12 m. The deeper areas, the upper end of the
north arm, and the area near the mouth of Aikerly Creek is composed
of soft muck.
Siltcoos Lake has a bottom type composed mainly of silt, with
other bottom types probably comprising less than 1% of the total bottorn area (Saltzrnan, 1966). Aldrich (1953) supplied a more specific
limnological description, characterizing the Siltcoos Lake sediments
as belonging to the gyttja (specifically feindetritusgytj) group of lake
substrata. Fragments of decomposing detrital material are bonded
together with hurnic and mucilaginous substances.
33
Littoral and Shoreline Vegetation
Devils Lake is surrounded by extensive beds of both emergent
and submerged plants
Typha, Scirpus, Carex, Juncus,
Myriophyllum, and Potamogeton). Lemna, a floating aquatic plant, is
also prevalent (McHugh, 1972).
Siltcoos Lake has been the subject of a number of investigations
on the biology and control of its most dominant aquatic plant, the
Brazilian waterweed, Elodea (Anacharis) densa (Pitney, 1949; Aldrich,
1953; Kerns, 1955; Bond, 1955). The plant is capable of growth at the
lake's maximum depth (5.5 rn and, in the past (1951), it has covered
up to 90% of the lake's surface (Bond, 1955). At present, the situa-
tion is less critical with the weed probably covering less than 40% of
the area of the lake.
The two dominant emergent plants in Mercer Lake are the
western yellow water lily (Nuphar) and the water shield (Brasnia).
The shoreline has a dense tree and brush cover composed chiefly of
fir, cedar, spruce, hemlock, maple, salmonberry, salal, huckleberry, vinemaple, and rhododendron (Oakley, 1962b).
The northwest corner of Munsel Lake and much of its littoral
area has dense patches of water shield (Brasnia) along with smaller
patches of Nuphar and the pond weed (Potamogeton). Sedges (Carex),
willows (Salix), and buirushes (Scirpus) occur in swampy areas and
34
near the outlet (Oakley, 1962a; Hansen, 1963; Skeesick, l965). The
shoreline vegetation is similar to that of Mercer Lake.
ypio-Chemistry
Temperature, Dissolved Oxygen, and pH
Yearly temperature isotherms for the four study lakes are
included in Figures 8, 9, 10, and 11. Seasonal comparisons of their
temperature, dissolved oxygen, and pH profiles are presented in
Figures 12, 13, 14, and 15.
Devils and Siltcoos lakes (Figures 8,
9,
12, and 13) have
essentially quite similar orthograde temperature, dissolved oxygen,
and pH profiles throughout the year. Water temperatures and pH
increase through spring and summer while dissolved oxygen decreases.
Fall and winter periods show a gradual decrease in water temperatures and pH with a simultaneous increase in dissolved oxygen. Since
both lakes are shallow and subject to coastal winds, mixing is nearly
continuous throughout the year and no significant thermoclines or
chemoclines develop. The small changes in pH with depth are likely a
reflection of small shifts in the CO2 cycle caused by the instantaneous
rates of carbon uptake by algae at various lake depths.
Mercer and Munsel lakes (Figures 10, 11, 14, and 15) both
establish thermoclines and chemoclines seasonally. Winter and
35
DEVILS LAKETEMPERATURE(°C)
-S
5-
1972
971
Figure 8. Temperature isotherms during the study period in Devils
Lake, Oregon.
SILTCOOS LAKE
fQ0
f0
/40
(60
/90
200
1971
TEMPERATURE (°C)
22° 200 /80 /6° /4°12° /0°
90
70
1972
Figure 9. Temperature isotherms during the study period in Siltcoos
Lake, Oregon.
36
MERCER LAKE -TEMPERATURE (°C)
ii III ........
90
/00
Or
/40
9°/0° /20
i
i
/8° 200
/6°
22°22° 200
.
1.
.
I. .I
/8°
/6°/4° /2°
8° 7°
/0°
2
-S
E4
8
0
F
I
I
A
M
J
IA
j
I
971
I
S
I
0
I
N
0
J
972
Figure 10. Temperature isotherms during the study period in Mercer
Lake, Oregon.
MUNSEL LAKE TEMPERATURE (°C)
/40
0
/6°
20°
/8°
22°
)
200
II1tIIIIIlII II
/8°
/6° /4° /2° /0°
8°
0
8
12
2
6
F
M
A
M
I
j
I
1971
IA 15 lOt N
I))
J
972
Figure 11. Temperature isotherms during the study period in Munsel
Lake, Oregon.
37
pH
6.0
6.5
p/I
7.0
7.5
6.0
7.0
6.5
7.5
C
0,
o
SPRING
2
-SUMMER
2
3-
C
4
4pH
O.O.c
5
0
5-
pH
0.0
6
Temp.
6
Devils Lake
Devils Lake
July 13, 1971
April 17,1971
0
4
6.0
L
I
8
12
J
I
20
16
0
24
I
I
4
8
Temp.
12
16
mg/lifer, °C
mg/lifer, °C
pH
p/I
7.0
6.5
C).
)
7.5
70
6.5
20
7.5
.1
I
I
P1
4
I
Ii
FALL
0
0
II
a
4
3.
0
'1
S.
I
WINTER
1.
0
5.
1"
5,
pH
0.0.
p/I
0
0.0.
3.
Temp.
Devils Lake
Devils Lake
October 2, 1971
I
0
4
I
8
January 2,1972
I
12
I
16
mg/lifer, °C
Figure 12.
20
24
0
4
8
12
16
I
20
24
mg/liter, °C
Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Devils Lake, Oregon.
pH
6.5
pH
7.5
7.0
7.5
7.0
6.5
.1
''1
0
a SUMMER 0
SPRING
31-
I
pH
Silfcoos
Temp.
Siltcoos Lake
Lake
April 8, 1971
0
4
8
12
16
20
24
0
4
8
12
16
20
24
mg//i/er °''
mg//i/er, 0C
pH
I
Temp.
July 14, 1971
pH
6.0
0
I
6.5
7.0
7.5
01
I
o
-
0
I
FALL
3.
0
o
0.0.
pHE Temp.
0
4-
0
pH 0.0.
Siltcoos Lake
0
4
I
8
I
12
Siltcoos Lake
Temp.
October 3, 1971
I
WINTER
0
16
mg/liter, °C
20
January 3,1972
I
I
24
0
4
I
8
12
I
16
I
20
24
mg//i/er, °C
Figure 13. Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Siltcoos Lake, Oregon.
pH
p/-I
7.0
6.5
o6.0
7.5
2
2
4
'
7.0
6.5
6.0
7.5
0
0
SUMMER
0
/
6
I
/
Si
/
/
0
I0
40.
Temp.
I
0
I
4
I
8
pH
Mercer Lake
March 22,1971
I
12
/
16
-
--
20
-
4
24
8
mg/lifer, °C
16
24
20
pH
7
7()
-
12
mg//i/er, °C
pH
6.0
Mercer Lake
JulyI6,1971
Temp.
Il
1
I
0
4
*
I-FALL
0
'
5.
0
3.
0
WINTER
Lu
,//
0
pH 0.0.
).
0.0.
pH
Temp.
r Lake
Temp
Mercer Loke
Jonuory 5,1972
September 7, 1971
I
0
-
4
I
I
8
12
16
mg//if er, °C
I
-
20
24
0
4
8
I
12
__I
16
mg/llfer, °C
I
I
24
20
-
Figure 14. Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Mercer Lake, Oregon. Estimated
date of fall overturn was October 1, 1971.
40
pH
pH
7.0
6.5
7.5
6.0
0
7.0
6.5
7.5
I
I
SUMMER
SPRING
3.
3.
I/v
f 0/
5'
.10
L4J
sir
6-
I
Io
0
Temp00 pH
0.0 pH
Munsel Lake
-
April
I
0
2)
Munsel Lake
July 15, 1971
-
19, 1971
I
4
8
Temp.
I
16
12
20
24
0
4
mg/liter, °C
6.5
0
8-
0
2-
'I
00
16
20
24
pH
7.0
4
2
mg/liter, °C
pH
6.0
I
I
8
7.5
*FLL
7.5
7.0
6.5
.0
WINTER
0
4
0
6
12
'I
6cuJPH
16.
f!Ioo.
0.0.
Temp.
Temp.
20 -
I
0
4
8
I
12
Munsel Lake
October 4, 1971
I
16
mg/lifer, °C
I
20
20
I
I
24
Munsel Lake
January 4,I97
.
0
4
I
I
8
12
16
I
20
24
mg/lifer, °C
Figure 15. Seasonal comparison of temperature, dissolved oxygen,
and pH profiles in Munsel Lake, Oregon. *Estimated
date of fall overturn was December 1, 1971.
41
spring dissolved oxygen, pH, and temperature profiles are generally
orthograde while the summer and fall thermoclines present a barrier
to mixing. During the summer and fall, the dissolved oxygen and pH
profiles exhibit sharp decreases below the thermocline. The lowest
recorded dissolved oxygen determinations were 0.0 mg/i at a depth
of 10 and 17 m on September 3, 1970 and September 18, 1970, respec-
tiveiy, in Mercer and Munsei lakes. Dissolved oxygen minimums
recorded at the same depths during 1971 were 0.7 and 1.2 mg/l on
June 29, 1971 and September 6, 1971 in Mercer and Munsel lakes,
respectively. The thermoclines decreased with depth seasonally from
6 to 9 m and from 9 to 17 m, respectively, in Mercer and Munsel
lakes. The fall overturn in Mercer Lake was estimated to have
occurred on October 1, 1971 and in Munsel Lakeon December 1,
1971.
The thermal lake classification scheme of Berg and Neff (1955)
would place Devils and Siltcoos lakes into the following category:
I. Holomictic (fully mixed always or at regular intervals), A. Not
Stratifying (lakes too shallow to stratify directly). The Forel-Whipple
(1927) classification would categorize them as III. Tropical (surface
temperatures always above 4° C), Order 3. (bottom water temperature
similar to that of the surface with circulation practically continuous
throughout the year), even though many such lakes occur in the
Temperate Zone.
42
The Berg-Neff system (1955) would place Mercer and Munsel
lakes into the category of: L Holomictic (fully mixed always or at
regular intervals), B. Warm Stratifying (stratifying directly but not
inversely), 2. Temperate and Subtropical (stratified in summer and
early fall; homothermous and overturning throughout winter and early
spring). In the Forel-Whipple classification (1927) they would be
categorized as: III. Tropical (surface temperatures always above
4° C), Order 2. (bottom water temperature varying but not far from
4°C, with one circulation period in winter).
Water Chemistry and Light
The means and ranges of five physical and chemical properties
of the four study lakes are presented in Figure 16. Figure 17 details
two additional optical properties of the lakes, the percent transmission of incident light with depth, and the extinction coefficients of
white, blue, green, and red light. The data in Figure 17 were
selected from more than ten separate observations on each lake as
being representative of the lakes' average optical conditions. Figures
18,
19, 20, and 21 present yearly isopleths of the lakes' nitrogen con-
centrations (mg N as NO3 or NO2) while Tables 2 and 3 list the total
phosphorus and total dissolved phosphorus concentrations found in the
surface water.
Birge and Juday (1911) would classify all four of the study lakes
43
'239.7
0 51.0
1
I-
-
-S
-1
::
I
I!
20 -
9.
TOTAL ALKALINITY
0 TOTAL HARDNESS
I
I
I
I
DEVILS SILTCOOS MERCER MUNSEL
I
I
DEVILS SILTCOOS MERCER MUNSEL
0
1.
C..)
C')
F
C')
C')
DEVILS SILTCOOS MERCER MUNSEL
DEVILS SILTCOOS MERCER MUNSEL
Figure 16. Annual means and ranges of physio-chemical features
compared among the study lakes. Data for Siltcoos Lake
on November 7, 1971 is plotted separately.
44
-iJ
cZo1FrICIEMTs(g)
FL TER GLUE GREEN
-
1.972
1.19$
.949
.939
(.459
.949
.9(6
(.077
1.71$
(.052
.994
754
.240
.702
.723
(.0(3
(.711
(.069
(.007
.726
(.224
.709
.772
,
5
RED
1.03$
/
DEVILS LAKE
JSILTCOQS LAKE
AUGUST 18,1971
j AUGUST 19, 1971
SECCHI DEPTH: 1.7 meters
(.020
.972
0
25
50
(.790
.993
.979
0
.991
.901
75
-I
SECCHI DEPTH = 2.2 meters
I
0
tOO
I
25
.127
1.221
.720
.669
723
1.163
.673
.663
50
75
I
100
PERCENT TRANSMITTANCE OF INC/DENT LIGHT
C
0..TINCTIoN'FICIENTS (K)
EXTINCTION COEFFICIENTS (K)
NO FILTER BLUE
I
(4J
GREEN
RED
.337
.526
.394
.587
.394
.466
.356
.404
.367
.800
.365
.416
.572
.356
.470
-
.390
0
.561
.329
25
50
75
GREEN
RED
.542
.963
.593
.566
.8(6
.646
.540
.859
.541
0
.551
.569
MERCER LAKE
SEPTEMBER 7, 1971
SECCHI DEPTH : 5.6 meters
.369
0
-
MUNSEL LAKE
SEPTEMBER 6, 1971
SECCHI DEPTH: 6.75 meters
a -
5
rvO FILTER aLA/f
100
0
25
50
75
100
PERCENT TRANSMIT TANCE OF INC/DENT LIGHT
Figure 17. Percent transmittance of incident light and extinction coefficients compared among the study lakes.
45
DEVILS LAKENITROGEN (mg/I as NO3or NO2)
1971
1972
Figure 18. Nitrogen isopleths during the study period in Devils Lake,
Oregon.
SILICOOS LAKENITROGEN (mg/I as NO3 or NO2)
.50
.30
/0
0
0
.0/
/0
.80.90
0
2
3
41
F
I
M
IA
11111
I
M
I
I
j
lOIN lo
I
I
1971
4
I
II
4
1
1972
Figure 19. Nitrogen isopleths during the study period in Siltcoos
Lake, Oregon
MERCER LAKENITROGEN (mg/las
NO3 or NO2)
ESTIMATED DATE
OF FALL OVERTURN
I
972
1971
Figure 20. Nitrogen isopleths during the study period in Mercer Lake,
Oregon.
MUNSEL LAKE NITROGEN (mg/I as NO3 or NO2)
0r
.1/
.07
.03 .01
0
ESTIMATED DATE
OF FALL OVERTURN11
.
4
8
12
16
1971
972
Figure 21. Nitrogen isopleths during the study period in Munsel Lake,
Oregon.
47
as having "soft" waters. htgoftH water is defined as water averaging
less than 28 mg/i HCO3. Since the lakes all have mean surface pH's
ranging between 6.9 and 7. 1, their mean surface total alkalinities,
which range between 10.2 and 18.7 mg/i as CaCO3 (Figure 16), would
be predominantly composed of EJC03 and can be expressed as a range
of HCO3 between 12.4 and 22.8 mg/i. Griffiths and Yoeman (1938)
make the generalization that the waters of Oregon coastal lakes are
"extremely softu, quoting comparable total alkalinity figures for several of the study lakes. This term, "extremely soft", is reserved by
Wilson (1935) to include lakes with less than 10 mg/i HCO3 and should
probably remain unchanged in his sense.
An examination of the means and ranges of the five physio-
chemical features graphed in Figure 16 indicate a general trend or
ranking of the four lakes in the following manner: (1) Devils,
(2) Siltcoos, (3) Mercer, and (4) Munsel lakes. This ranking could be
representative of potential ecosystem productivity, if total dissolved
solids, total alkalinity, total hardness, and specific conductance can
be used as reliable indices of lake productivity. The mean secchi
depth o Mercer Lake departs slightly from the trend. However, percent transmission is a better measure of light penetration than secchi
depth and the above ranking is still intact in an examination of Figure
17.
There is evidence (Figure 16) that a salt water intrusion may
have occurred in Siltcoos Lake at some time between the sampling
dates of October 3, 1971 and November 7, 1971. Total dissolved
solids, total hardness, secchi depth, and specific conductance were
all increased dramatically on November 7, 1971. Total alkalinity
remained relatively unchanged, as would be expected with a sudden
increase in NaC1.
On the basis of the percent transmission of incident light (white)
through a stratum of water 1 m thick, Birge and Juday (1931) would
classify both Devils (35.4% transmission) and Siltcoos (43.4% trans-
mission) lakes as having low-medium transmission characteristics
(Figure 17). Mercer (60.7% transmission) and Munsel (67.0% trans-
mission) lakes would both be categorized as having high-medium
transmission characteristics. Low transmission is defined as being
in the range of 0-30%, low-medium transmission in the range of 3150%, high-medium transmission in the rangeof 51-70%, and high
transmission in the range of 71% and above.
The extinction coefficients (k) (Figure 17) of the four study lakes
also showed the same above ranking trend with Devils, Siltcoos,
Mercer, and Munsel lakes successively exhibiting lower extinction
coefficients, in that order. This occurred whether white (400-640 mg),
blue (400-550 mg), green (460-660
nlIL),
or red (500-720 mi.) light is
considered. The blue end of the light spectrum was absorbed most
quickly in all of the study lakes. Less than 10% of the blue light was
49
transmitted below about 1.0, 1. 5, 2. 0, and 4.0 m, respectively, in
Devils, Siltcoos, Mercer, and Munsel lakes. In each lake, the green
and red areas of the light spectrum were absorbed less quickly than
the blue area, but on a comparatively equal basis with each other
(considering any single lake). Less than 10% of the red and green
light was transmitted below about 2.0, 3. 0, 4.0, and 6.5 m, respectively, in Devils, Siitcoos, Mercer, and Munsel lakes. The transmission of 1% surface radiation corresponds roughly with the
compensation depth or the lower limit of the photic zone (Strickland,
1957).
Devils, Mercer, and Munsel lakes had 1% of the surface radia-
tion at depths of 4. 5, 8. 5, and 12.0 m, respectively, on the dates
sampled in Figure 17. The bottom of Siltcoos Lake (5. 0 m) received
2. 7% of the incident light (Figure 17).
The nitrogen concentrations (mg/i N as NO3 or NO2) of Devils
and Siltcoos lakes (Figures 18, 19) exhibit essentially orthograde
isopieths, indicating that the two lakes are well mixed throughout the
year. In both lakes the measured nitrogen reaches depletion near the
beginning of June and becomes detectable again near the beginning of
November. In Mercer Lake (Figure 20) the measured dissolved
nitrogen never quite falls to zero during the summer period, though
regions of the hypolimnion are devoid of dissolved nitrogen (as NO3 or
NO2) from July through September. Munsel Lake (Figure 21) shows a
seasonal progressive reduction of dissolved nitrogen with depth, until
50
the fall turnover restores this nutrient to the epilimnion. The mean
(composite) winter dissolved nitrogen concentrations of the four study
lakes were: Devils, 0.62 mg/i N; Siltcoos, 0.91 mg/i N; Mercer,
0. 96 mg/i N; and Munsel, 0. 12 mg/i N.
The mean total phosphorus concentrations (Table 2) at the sur-
face of the four study lakes also seem to parallel the ranking established in Figure 16. These total phosphorus determinations may be of
more significance than the mean winter dissolved nitrogen determinations as a relative index of lake productivity because total phosphorus
is a measure of the sum of dissolved, colloidal, and particulate
phosphorus, whether organic or inorganic, and all of these fractions
can be important in the nutrition of autotrophic algae. On February
13-15, 1971, total dissolved phosphorus to total phosphorus ratios
ranged from 1:5. 1 to 1:2. 1 (Tables 2, 3). This implies that over one-
half of the phosphorus measured on these dates in Devils, Siltcoos, and
Mercer lakes was present in colloidal and particulate fractions, much
of it possibly within the bodies of organisms.
The physio-chemical data presented in Figures 8 through 21 and
in Tables 2 and 3 are in general agreement with those reported by
Griffiths and Yoeman (1938), Clothier and Breuser (1959), Saltzman
(1961, 1966), Oakley (l962a, b), Hansen (1963), Lewis (1971), and
McHugh (1972). However, the present study has also recorded certain
subtle differences and additional information of a physio-chemical
51
nature which should be pointed out.
Table 2. Total phosphorus concentrations (ig/l P) at the surface
(0. 5 m) in four coastal lakes of Oregon.
Date
February 13-15, 1971
March 20-22, 1971
April 17-19, 1971
May 16-18, .1971
June 9-12, 1971
June 26-29, .1971
July 13-14, 1971
Devils
Siltcoos
Mercer
24.3
17.3
18.8
37.2
21.9
29.3
16.5
15.4
11.0
6.3
12.4
3.3
21.3
20.0
20.9
5.0
4.7
4.2
6.0
15.9
2.5.3
2.7.7
x25.2
Munsel
x
19.3
x
6.9
x
6.3
Table 3. Total dissolved phosphorus.concentrations (.Lg/l P) at the
surface (0. 5 m) in four coastal lakes of Oregon.
Date
February 13-15, 1971
Devils
Siltcoos
Mercer
4.8.
7.8
3.7
Munsel
The surface total alkalinity concentrations reported for Siltcoos,
Mercer, and Munsel lakes by Griffiths and Yoeman (1938) were 1.6 to
3.5 mg/i and 2.8 to 6.7 mg/i higher, respectively than the ranges
and means recorded for these lakes in the present study (Figure 16).
For instance, they report a sarface total alkalinity of 22.0 mg/i in
Siltcoos Lake on October 9, 1938. This concentration is 3. 5 mg/i
higher than the highest (18. 5 mg/i) and 6.7 mg/i higher than the mean
(15. 3 mg/i) surface concentration recorded here. Similarly, the 1938
52
study reports much higher (17. 5 to 30. 2 mg/i higher) total alkalinity
concentrations near the bottoms of Mercer and Munsel lakes than were
observed during frequent sampling of these depths during 1971.
A possible explanation for these differences in total alkalinity
concentrations could be that the three study lakes had significantly
higher epilimnetic algal production in 1938 than in 1971, resulting
(in Mercer and Munsel lakes) in severe hypolimnetic oxygen deficits
and increased hypolimnetic mineralization. However, it seems more
likely that any apparent differences are probably due to analytical
techniques. Griffiths and Yoeman (1938) used a portable chemical kit
while the analyses in the present study were done indoors understandard conditions.
Oakley (1962b) reports a total hardness in Mercer Lake on
August 15, 1960 of from 20 to 24 mg/i, considerably higher than the
highest (14. 0 mg/i) surface concentration reported in the present
study (Figure 16). His determinations, however, were made using
composite samples from four subsurface sampling depths, where
mineralization was presumably occurring. Oakley (1962a) again
reports a higher total hardness concentration (36 mg/i on August 29,
1960) for Munsel Lake than the highest surface concentration
(10.0 mg/i) recorded in the present study(Figure 16); and again, his
determinations were performed on a composite sample.
Lewis's (1971) report listing the chemical characteristics of
53
Munsel Lake, shows a mean total alkalinity and total hardness of
11.0 and 9.6 mg/i, respectively, for the period June through
September, 1967 and 1968, These figures are very compatible with
the present study (Figure 16), even though his analyses were per-
formed on composite samples. However, his mean total dissolved
solids (33. 8 mg/i) and specific conductivity (57. 5 mhos /cm) figures
fall short of both the means and ranges recorded in 1971 (Figure 16).
Hansen (1963) reports surface dissolved PO4 concentrations of
from 0.0 to 66 .g/l (0.0 to 19. 6 p.g/l P) and surface NO3 concentrations of from 0. 10 to 0. 11 mg/l (0.02 mg/l N) during February and
April, 1963, in Munsel Lake. His maximum surface dissolved PO4
concentration for Munsel Lake is more than three times higher than
the mean surface total phosphorus concentration (6. 3 p.g/l P) recorded
during the present study (Table 2).
McHugh (1972) reports surface dissolved PO4 concentrations of
from 10 to 20 g/l (3. 3 to 6. 6 ).Lg/l P) and surface NO3 concentrations
of from 0. 03 to 0. 04 mg/l (0. 01 mg/i N) on August 6, 1970 in Devils
Lake. The Environmental Proteötion Agency (Sanville, personal
communication), using a composite sample, measured 24.0 g/l total
phosphorus (as F) in Devils Lake on June 7, 1972. These nutrient
concentrations are fairly comparable with the present study (Figure
18, Tables 2 and 3).
It is difficult to place a definitive interpretation on the majority
54
of the above comparisons between the 1971 physio-chemistry of the
four study lakes and that reported by earlier authors. Too few analyses of certain nutrients (particularly phosphorus) have been undertaken. Perhaps the most that can be said is that thelakes' physio-
chemistries are highly dependent upon the individual analytical tech-
niques of previous and present investigators the seasons and years
investigated, and the actual state of ecosystem productivity at the
time the measurements were made. It does appear however, that
the lakes' physio-chemistries are sufficiently different to postulate a
tentative ranking of their productivities on the basis of such measure-
ments as total alkalinity, total hardness, total dissolved solids,
specific conductance, total phosphorus, and light transmission.
Trophic Environments
Limne tic Primary Production and Chlorophyll a Estimates
Data on the lakes' seasonal primary production rates and chlorophyll a biomass estimates are presented in Figures 22 through 28.
Figures 22, 23, 24, and 25 compare vertical profiles of phytoplankton
production and chlorophyll a. estimates on a per m3 basis. Figure 26
shows the lakes' vertical primary production rates integrated on a
per m2 basis. The lakes' daiLy prim.ary production rates in Figures
27 and 28 were computed using theenergy fractions (F) of
55
Vollenweider (1965) as modified by Platt and Irwin (1968).
The phytoplankton production rates in all four of the study lakes
exhibit degrees of photoinhibition or photooxidation at or near the
surface (Figures 22-25). This phenomenon is particularly evident
during the summer months when light intensities and water tempera-
tures have increased.
An examination of the primary production profiles, chlorophyll
a profiles, and light transmittances (Figures 17, 22-25) in each study
lake reveals that, on almost every sampling date, the point of maxi-
mum primary production occurred at light saturation, regardless of
the biomass of phytoplankton present at any depth. In Devils and
Siltcoos lakes (Figures 22,23), mixing is nearly continuous throughout
the year and varying production rates with depth seldom result in a
pronounced stratification of the phytoplankton. A degree of phytoplankton stratification occurred on September 4, 1971 in Devils Lake
(Figure 22) and on March 21, 1971 in Siltcoos Lake (Figure 23).
However, it can be shown, in both cases, that the rate of change in
production determining the depth of maximum production was due
more to changing light intensities with depth than due to the rate of
change in the chlorophyll a profiles. In both lakes, the assimilation
numbers (mg C
hr1
per mg chlorophyll a) on each date were maxi-
mum at the depth of maximum primary production.
In Mercer and Munsel lakes (Figures 24, 25) mixing is
56
incomplete during the summer and fall months. In both lakes, algal
cells sink to and then through the thermocline as the seasons progress,
resulting in a decline with depth in the chlorophyll a maxima. However, maximum production again occurs at near the point of light
saturation, regardless of the change in chlorophyll a estimates with
depth. The only exception to this rule may have occurred on June 29,
1971 in Mercer Lake (Figure 24) when production at the depth of
maximum production may have been more dependent upon the high
chlorophyll a biomass present there (55. 5 mg Chl a/rn3) than upon
varying light intensities.
The effect of photoinhibition upon production profiles is very
pronounced in Munsel Lake (Figure 25), occurring on every date
except November 9, 1971. However, judging from the clarity of the
lake and the production estimates recorded on other dates, we can
assume that maximum production was occurring at or near light
saturation on this date, even though the depth of maximum production
was at the surface. In both Mercer and Munsel lakes the chlorophyll
a profiles are essentially orthograde over the range of depth exhibiting
the greatest rate of change in primary production. This has the same
result, as in Devils and Siltcoos lakes, of determining that assimilation numbers reach a maximum at the depth of maximum production.
Integration of the lakes' primary production (per rn3) estimates
on a per m2 basis reveals that maximum primary production rates
57
3
I
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I
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0 5 tO 15 20 25
tO IS 2025
5
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7Ch/cm3
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2
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r
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Figure 22.
I
Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates during the
study period for Devils Lake, Oregon.
58
mq Chic
m3
mgCh/am3
rngCh/or,13
mgCh/om3
0 5
0 5
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5
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15 2025
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mg ChI. m3
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mg ni a in-3
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mg C
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Figure 23.
J
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mg C,,ihi'
2?
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mhr'1
Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates during the
study period for Siltcoos Lake, Oregon.
7 ChIc
U
I05
10
0/9
I
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U
3
I
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59
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)
110
115
0
Figure Z4. Comparison of vertical profiles of phytoplankton photosynthetic rates and chlorophyll a biomass estimates during the
study period for Mercer Lake, Oregon.
Oregon.
Lake,
Munsel
for
period
study
the
photosyn-
phytoplankton
of
profiles
vertical
of
Comparison
during
estimates
biomass
a
chlorophyll
and
rates
thetic
25.
Figure
mgCffT'5hr4
Cmhr1
mg
Cmhf"
mg
Chi
0mg
--mgCrri3h('
mgCh/4rñ3
rngCh/.rrf3
mChign3
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C
mg
7
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10
r,f"hr'
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ing
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mhf'
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60
61
occurred during the summer and fall in Siltcoos and Devils lakes
(Figure 26). Mercer Lake exhibited two discrete peaks in primary
production, the first during the summer and the second during the
late fall, just after the fall overturn. In Munsel Lake, primary production rates climb to a peak in midsummer, evidence some oscillation, and then decline through the fall and winter.
In an interpretation of FIgure 26, it should be noted that the
graphed primary production rates are instantaneous and that production may have varied considerably between the symbols connected by
dots. Furthermore, the assimilation numbers for each lake on each
date may vary in patterns quite different from that depicted in Figure
26. These two observations will become apparent in an analysis of
the density-dependent functions present in Munsel Lake to be discussed
in a later section.
In Figures 27 and 28 the four stady lakes are classified by
trophy according to a scale developed by Rodhe (1969) for lake produc-
tivities. Though this scale is meant to be used with daily primary
production estimates measured during the growing season, annual
means and ranges of these estimates arealso included (Figure 27). In
both figures, Devils, Siltcoos, Mercer, and Munsel lakes would be
classified as eutrophic, with Mercer and Munsel lakes bordering on
the lower range of natural eutrophy.
In Figure 27 the scale is logarithmic in order to include the
cj
.1
M
1970
r
lvi
M
M
lvi
1971
U
tJ
U
(972
Figure 26. Phytoplankton production rates per m2 during the study period in Devils, Siltcoos, Mercer, and Munsel
lakes, Oregon.
63
EUTROPHY
-OLIGOTROPHY
POLLUTED
NATURAL
RODHE SCALE-.-I
F
I
-1
'SUMMER
JUNE-SEPT. 1970,1971
DEVILS-.-
S
I
StLTC00S
MERCER-.-
I-
I
N8
1
N:8
N8
F
MUNSEL-.-
S
I
IJ:8
I
ANNUAL
JULY I970-JAN.1972
DEVILS-.SILTCOOS-i'-
Nl5
I
N:15
F
MERCER-E
MUNSEL-'-
NI3
S
I
N13
-I
JUNE-SEPT. 1968, JULY-SEPT. 1969
N6
ISI
CRATER-.-
I
ODELL-.WOAHINK-.-
WALDO-'-I
10
I
S
30
I
N9
N:4
I
50
N:II
tOO
300 500
1000 1500 3000 5000 10,000
mg C rti2day'
Figure 7. Approximate means and ranges of daily phytoplankton primary production rates measured during the summer and
annually for the four study lakes compared with the Rodhe
(1969) scale for oligotrophic and eutrophic lakes. *Summer primary production means and ranges for four other
Oregon lakes are included for comparison (Larson, 1970a).
Logarithmic scale used.
EUTROPHY
OLIGOTROPHY
POLLUTED
NATURAL
RODHE SCALEt-1
S
DEVtLS'
S
SILTCOOS
5
MERCER
S
MUNSEL.
0. - -S
*CRATER_,
0+ ------------------
*ODELL__.I
S
WOAHINK-"
UNADJUSTED
0 ADJUSTED
*WALOOS
____
I
I
o
I
too
I
I
300
I
I
500
I
I
I
I
I
Ii
MEAN SUMMER PR/MARY PRODUCT1ON RATES (rnq C m2dcy1)
of
Figure 28. Mean summer (June Sept. , 1968-197fl unadjusted and adjusted primary production rates
lakes.
Rodhe
(1969)
scale
for
oligotrophic
and
eutrophic
eight Oregon lakes compared with the
*(Larson, 1970a). Arithmetic scale used.
65
enormous range in individual production estimates present in a recent
study of four other Oregon lakes (Larson, 1970a). In Figure 28 the
scale is arithmetic in order that the true ranges of Rodhe's scale and
the above mean summer production estimates may be more easily
visualized.
The Rodhe trophic scale is a relatively recent development. It
is, perhaps, the first and only absolute trophic scale thus far proposed on the basis of limnetic primary production estimates. However, its utility for the classification of lakes in North America has
not yet met widespread testing. For that reason, I have summarized
all of the primary production estimatesrecorded through repeated
sampling of a number of lakes in Oregon (Figures 27, 28) in order
that the lakes' relative placement on this scale might be compared
with their relative descriptive characteristics. Two lakes, Crater
and Odell, appear to be incorrectly classified as their relative placement on the Rodhe scale does not agree perfectly with what their
relative classification might be if one were to classify them based on
descriptive characteristics.
On the Rodhe scale, Crater Lake would presumably be classified
as mesotrophic, bordering closelyon the lower range of natural
eutrophy (Figure 28). This classification may be very difficult for one
to accept intuitively because of the lake's extreme clarity, its recent
origin, and the absence of artificial enrichment. The lake has several
chemical characteristics (total dis solved solids, specific conductance,
total hardness, total alkalinity) (Larson, 1970a) that are higher than
some eutrophic ecosystems like Devils, Siltcoos, and Odell lakes;
yet, many people would agree that, at present, by no stretch of the
imagination can Crater Lake be considered eutrophic or even bordering on the status of eutrophy.
Similarly, it may be difficult to unequivocally accept the fact
that Odell Lake is in an extremely advanced state of eutrophy and
deserves to be called polluted, with all of the connotations frequently
associated with that term. Warren (1971) defines pollution as:
any impairment of the suitability of water for any of its bene-
ficial uses, actual or potential, by man-caused changes in the quality
of the water.
There may be periods during the summer in Odell
Lake when algal blooms become aesthetically displeasing; but at the
same time it has to be conceded that sport fishing is another important
use for the lake, a use which has not yet suffered the degree of
impairment implied by the Rodhe scale.
A search was undertaken to determine if therewere any
physi-
cal, chemical, or biological characteristics common to these two
lakes which might help explain the reasons why they seem inappropri-
ately classified by the Rodhe trophic scale. An examination of all
available data showed that Crater and Odell lakes were the only two
lakes in Figures 27 and 28 which had mean depths exceeding the mean
67
depths of their photic zones. This simplerelation may have an
important bearing on subjective interpretations of a lake's trophic
status.
Table 4 lists the mean depth
(Z) and mean depth of the photic
zone (Z) of eight Oregon lakes. Only in Crater and Odell lakes
does the fraction Z/Z pz exceed 1.00. The traditional concepts of
oligotrophic, mesotrophic, and eutrophic lakes have gradually
accustomed investigators to the idea that lakes of intermediate to
extreme depths are almost invariably oligotrophic or mesotrophic.
Gradual changes in a lake's trophic status are accompanied by a
simultaneous filling of its basin so that eutrophic lakes are usually
comparatively shallow. When a lake of intermediate to extreme mean
depth begins to show biological signs that it may be entering me so-
trophy or eutrophy, it is difficult to reconcile the relatively unchanged
morphometry of the lake's basin with an increase in a biological index
such as limnetic primary production.
As a graphic illustration of this problem in the trophic classification of lakes, the mean summer primary production estimates of
Crater and Odell lakes have been multiplied by the factor
Z/Z and
then additionally plotted in Figure 28. These adjusted primary pro-
duction estimates have the effect of reducing the trophic status of the
two lakes to what might be a more acceptable level, if the assumption
is made that their unad justed primary production estimates canbe ignored.
Table 4. Mean summer (June-Sept. , 1968-1971) unadjusted and adjusted primary production
rates of eight Oregon lakes.
Date
Devils
Siltcoos
Mercer
Munsel
Crater
Odell
Woahink
Waldo
Unadjusted
mg C/rn2 /day
583.4
677.7
389.9
336.3
257.0
Z
Z
Z
pz
pz
/Z
Adjusted
(mg C/rn2 /day)(Z pz JZ)
4.5 m
4.7 rn
3.0 m
3.9 m
*
*
*
*
7.8m
7.6m
*
*
10.6m
10.4m
*
*
0.298
0.422
76.6
711.6
325
m
41
m
292.9
**97.0 m
**17.3 m
**14.2 m
10.5 m
*
*
35. 5
**75. 0 m
38
*
*
1686.2
i-n
*Not calculated.
**Estimated from unpublished photometer and Secchi disc data (Larson, personal communication).
However, the unadjusted primary production estimates of Crater
and Odell lakes cannot be ignored. They are real measurements and
no sound biological reason can be developed to justify an adjustment
Any adjusted primary production estimates are simply fabrications to
fulfill the need to reconcile the fact that some lakes of intermediate
to extreme mean depth may sustain comparatively high limnetic
primary production estimates.
The causes for this phenomenon are varied; but in any specific
case it results in the productivity of a lake increasing faster than the
lake's ability to fill its basin. In the case of Crater Lake, its productivity has increased primarily through natural causes. According
to Phillips and Van Denburgh (1968) and Larson (1970a, 1972) nutrient
enrichment occurs (1) aerially, from precipitation, (2) subaerially,
from springs and surfacerunoff, (3) underwater, from the dissolution
of soluble materials along the ca.lclera walls, and (4) underwater,
from fumaroles and thermal springs. Since most of the water lost
from Crater Lake occurs by evaporation, nutrients become concentrated in the lake. In the case of Odell Lake, recent nutrient enrich-
ment has occurred primarily through cultural causes. The lake has
numerous homes and campgrounds situated on its shoreline, resulting
in a substantially increased load of nutrients (Larson, 1970a, 1972).
Thus lakes of intermediate to extreme mean depths can sustain
relatively high productivities, whether those productivities area
70
result of natural or cultural eutrophication; and the classification of
lakes by the Rodhe trophic scale has difficulty in reconciling intuitive
and traditional concepts of a lak&s trophic status with actual measurements of its limnetic primary production. A further discussion of
natural and cultural eutrophication will be presented later in A Gen
Discus sion.
Density-Dependent Functions
Theory. Study objective number three is to review present
trophic analysis theory, as applied to primary production, and to
attempt an analysis of trophic processes on the basis of dens itydependent functions. Several theoretical density-dependent functions
within and between lakes have been presented in Figures 1, 2, and 3.
Each figure requires an individual treatment concerning its significance and interpretation.
Figure 1 was adapted from relationships established between
mean instantaneous growth rates of sockeye salmon (predator growth
rates) and mean biomasses of zooplankton (prey biomasses) in three
lake systems of differing productivity. Between ecosystems mean
sockeye growth rates increased as ecosystem productivity increased
and, within a single ecosystem, mean sockeye growth rates decreased
with decreasing zooplankton biomasses (Brocksen, Davis, and Warren,
1970).
71
Relationships, very similar to those described for sockeye
salmon and zooplankeon, may exist between phytoplankton and their
prey, though they have yet to be demonstrated satisfactorily in natural
ecosystems. The following review and analysis of trophic processes
will consider how the theory of density-dependent functions may be
used in future interpretations of phytoplankton relative growth rates
(assimilation numbers, production/biomass), and will detail how the
density relationships of primary producers, their predators and their
prey, may be compatible with the density relations already estab-
lished for higher trophic levels.
I am aware that measurements of phytoplankton relative growth
rates have been variously recorded by prior investigators as any of
proassimilated or
the 12 following combinations: weight of
duced per weight of algae or weight of chlorophyll a or volume of
algae per m3 or per m2. For simplicity, and because the differences
in the above analytical techniques do not appreciably affect the sense of
following arguments, the two expressions phytoplankton relative
growth rate and phytoplankton assimilation number, will be used as
equivalents.
Limnologists and oceanographers have measured phytoplankton
assimilation numbers for many years. The general hypothesis has
been that, in some manner, phytoplankton relative growth rates are
related to light, temperature, and nutrient availability. Manning and
72
Juday (1941) recorded a mean phytoplankton assimilation number of
2 in their study of lakes in northern Wisconsin. Gessner (as cited by
Larson, 1970a) reports mean assimilation numbers of from 4 to 6.
In a later publication, a summary of previous studies, he (as cited by
Larson, 1970a) reports that a mean value of 3 has been determined
for phytoplankton populations in lakes.
General confusion presently exists in the interpretation of
recorded assimilation numbers. Ichimura (1958), in his study of ten
Japanese lakes, reports data that might easily be construed as proving a direct relation between lake trophy and the means of maximum
recorded assimilation numbers. He reports that his mesotrophic and
eutrophic lakes had means of the-jr maximum assimilation numbers
that were two and four times higher, respectively than his oligotrophic lakes. Ryther and Yentsch (1957) summarized previously
recorded oceanic assimilation numbers and found that the standard
deviation in any one environmental situation could be high. In addi-
tion, mean values from different situations showed more than a two
fold variation, i. e., from 2. 1 to 5. 7. A later study by Ryther and
Yentsch (1958) recorded a mean assimilation number of 3.7 at a depth
of 10 m for a single oceanic area. A considerable variation from this
mean of 3. 7 could not be traced to either variations in chlorophyll a,
available nitrogen and phosphorus, or temperature. Gessner (as
cited by Soeder, 1965) reports that, within limits, no general
73
correlation can be established between the trophic level of a lake and
the assimilation numbers of its phytoplankton at a given time.
Findenegg (1965), Elster (1965), and Soeder (1965) have made
what may be some important observations concerning the interpretation of phytoplankton assimilation numbers. Findenegg's (1965) study
reports an inverse correlation between mean algal biomass and mean
assimilation numbers between lakes of differing states of trophy.
However, no implication is made that there may be a causal relationship between assimilation numbers and lake trophy. Instead, and this
is an interesting point, he felt that the range of his recorded ass imilation numbers might very well be explained most simply by algal cell
size. The dominant species of algae in the oligotrophic lakes he
studied were mainly nannoplankton, having a very high ratio of surface
area to volume which facilitated the uptake of available nutrients. His
mesotrophic through eutrophic lakes exhibited increasing dominance of
large diatoms and large blue green algae which are less efficient cells
for nutrient uptake.
Elster's (1965) study of the assimilation numbers of a variety of
lakes again reports no provable causal relationship between lake
trophy and mean assimilation numbers. His mean of the recorded
assimilation numbers was always about the same, no matter what the
trophy of the majority of lakes he studied. He reflects on the above
surface area
volume ratio hypothesis but finds that that relation, for
74
his set of lakes, is less clearly evident. Only his most eutrophic lake
with dominant large algae had a significantly lower mean assimilation
number.
Soeder (1965) introduces an additional concept concerning the
interpretation of measured phytoplankton assimilation numbers. He
claims that endogenous factors can have an effect on the relative
growth rates of any single phytoplankton population and that, to a
degree, natural phytoplankton populations can grow in partial
synchrony. If and when synchrony in cell division occurs, it may
therefore be extremely important to know whether each and every
measurement of assimilation numbers was performed on a juvenile or
senile phytoplankton population and, just as important at what time of
the day the measurements were performed. Photoperiod can determine and maintain daily cell division &ynchrony causing an endogenous
variation in metabolic activity in natural phytoplankton populations.
The cumulative effect of photoperiod and cell age can therefore bias
the relative significance of measured assimilation numbers if the
measurements have been performed indiscriminately on partially
synchronized algal populations. According to Ruppel and Metzner
and Lorenzen (as cited by Soeder, 1965) the ratios, weight of
chlorophyll a algal dry weight and production biornass (as weight of
chlorophyll a or algal dry weight), will vary endogenously during the
life cycle of a synchronized algal population and seniTe cells will no
75
longer grow in direct response to their environment.
It seems quite evident that the reasons are clear why present
measurements of phytoplankton assimilation numbers cannot always
be directly correlated to changes in ecosystem productivity and the
trophic status of lakes. The positive relationships established between
sockeye salmon relative growth rates and zooplankton biomasses
between and within ecosystems of different trophic status were based
upon relative growth measurements of a single population reacting to
its environment and all such measurements were taken during a single
growth stanza of that population growing in synchrony. In the case of
relative growth measurements of phytoplankton in natural ecosystems,
since it would be difficult to measure the relative growth rates of a
single population reacting to its environment, the common practice
has been to measure relative growth rates which are really measurements of phytoplankton communities. Therefore, changes in relative
growth rates for phytoplankton communities cannot always be expected
to reflect changes in phytoplankton prey (light, temperature and
nutrients). Yet, in reality and on the average, phytoplankton cornmunity relative growth rates may indeed be reacting in direct response
to relative changes in their prey densities (light, temperature1 and
nutrients). The compounding factors of species diversity (causing
differences in cell size) and possible cell synchrony (causing sequential measurements to be taken during different growth stanzas) may
76
merely be masking the detection of a simple density-dependent function between phytopla.nkton communities and their prey.
The idea can be demonstrated theoretically by the following
example. Suppose that a series of lakes, ranging greatly in their
trophic status, were populated with a single species of planktonic
algae. No additional phytoplankton populations were present in each
lake. Each phytoplankton population was composed of the same
httypeu
algal species, that is, an algal species having characteristics that
were a composite of all the metabolic and physical characteristics of
every known planktonic algae. A sequence of relative growth meas-
urements weremadein each lake while each utypeu phytoplankton
population was growing in no semblance of synchrony. Simultaneous
measurements of light, temperature, and nutrient availability were
performed in each lake at various depths. It is very possible that the
same set of relations that were established between and within lake
systems for sockeye relative growth rates (predator relative growth
rates) and zooplankton biomasses (prey biomasses) would also be
established for the relative growth rates of our "type" algal populations (predator relative growth rates) and the integrated energy
stimuli of light, temperatures and nutrient availability (prey biomasses).
If the above hypothesis is valid, how may it aid in the interpretation of trophic processes of phytoplankton in lakes? Interpretative
77
boundary conditions must be set and the most obvious one is that no
serious interpretations of differencesin phytoplankton relative growth
rates should be attempted within or between ecosystems having widely
varying algal cell surface area : volume ratios. The effects of possible partial synchrony in algal cell division can, perha.ps, not be
avoided other than to disregard those relative growth measurements
which other supportive evidence may suggest were performed on
senile algal populations.
If Figure 1 is examined, it will be noticed that phytoplankton
relative growth rates are hypothetically related to changes in certain
controlling and limiting environmental factors: temperature, light,
and/or nutrients. The integration and cumulative effect of these
energy stimuli might also be theoretically considered as being a prey
biomass whose predator is the phytoplankton.
The concepts of controlling and limiting factors need clarification. The definitions preferred here are those used by Fry (1947) and
Warren (1971). Controlling factors are those environmental identities
which may govern an organism's metabolic rates by influencing the
state of activation of its metabolites. Temperature is such a con-
trolling factor and with increases in temperatures both an organism's
active and standard metabolic rates will be affected. When food
availability (nutrients and light) is relatively constant, increases in
temperature, up to an organism's optimum temperature for growth,
i.1
will cause concurrent increases in an organism's scope for growth.
The organism's relative growth rates will increase until its temperature optimum is reached (Warren, 1971, Figure 11-6). The temperature optima of a majority of phytoplankton species are generally 20° C
to 25°C (Fogg, 1966).
Limiting factors are those environmental identities which can
limit active metabolic rates by their unavailability. Decreases in
available food (nutrients and light) can be a limiting factor for an
organism's relative growth rates. An organism's scope for growth
will decrease at all temperatures with decreasing food availability
(Warren, 1971, Figure 11-6). However, for there to be a direct
relationship between temperature and an organism's relative growth
rates up to its temperature optimum, it would appear that food availability would have to remain relatively constant.
The following analysis of the trophic processes occurring in
Munsel Lake should be regarded as only an attempt to find order in
what is certainly a very complicated ecosystem. Therefore, the
tentative conclusions resulting from the exercise should only be
accepted by the reader with caution.
Figure 29 considers a possible relationship between phytoplankton assimilation numbers and light, temperatures and nitrogen
concentrations at the depth of maximum primary production in Munsel
Lake. All data graphed in Figures 29, 30, and 31 were purposely
II
0
0
22°-
MUNSEL LAKE
Sat.
PRIMARY PRODUCTION)
C..)
LIGHT:
16°
Sat.
o
ASSIMILATION NUMBER
A N ITR OG EN
20° -(AT DEPTH OF MAXIMUM
8
TEMPERATURE
-
LIGHT SATURATION
0
..
Sat.. Sat. Sot. Sat, Sat. Sat. Sat.
Sat.
Sat.
Sot
-------------- ..4
Cl)
-
-
L
8°-
L
I)C
zIJ
III.
L511
4°.
0
.
..
2
E
3
uI.. ..
IJ.
.
0-
£-
FEJ M' A
A
M
Tj
1971
j 'A'S'
'
0
'N '0
1972
Figure 29. Comparison of phytoplankton assimilation numbers, light, temperature, and nitrogen at the depth
of maximum primary production during the study period in Munsel Lake, Oregon. Horizontal
dashed lines set off three season combinations: (1) winter, late spring, (2) early summer, fall,
and (3) late summer.
'C
I,I
MUNSEL LAKE
(AT DEPTH OF MAXIMUM PRIMARY PRODUCTION)
/
I
- -
K
Iv-
TEMPER4 fl/RE (°C)
Figure 30. Possible relationship between phytoplankton assimilation
numbers and temperature at the depth of maximum primary production in Munsel Lake, Oregon.
0
MUNSEL LAKE
c)
(AT DEPTH OF MAXIMUM PRIMARY PRODUCTION)
WINTER
LATE SPRING
/
\ EQDUCTIONA
6
SUMMf
FALL
L-L::
D -0
\ ASSM. NO.
6
i:i
\
-
\
.4
4.
A'3
/
2.L,,' I3.\
/
1\.
...
\...
\.
.....
.1/
II
I
0
I
2
'
'.\t
I
4
PH YTOPL ANK TON BIOMA 55 (Mg. C/i/.a
I
6
8
m3)
Figure 31. Theoretical relationships between phytoplankton biomass,
production, and growth rate compared with phytoplankton
biomass, production, and assimilation numbers measured at the depth of maximum primary production during
the study period in Munsel Lake, Oregon.
selected from depth profiles of the parameters graphed in those fig-
ures. The basis for the selection was that all data had to be from the
depth of maximum primary production. At the depth of maximum
primary production light is considered to be at saturation, if there is
demonstrated photoinhibition at shallower depths (Figure 25, also see
Phytoplankton Primary Production and Chlorophyll
Estimates).
Table 5 gives the sampling date codes used in Figures 29 through 35.
Water temperatures (Figure 11), chiorophyllabiomasses (Figure 25),
and nitrogen concentrations (Figure 21) are nearly orthograde between
the surface and a depth of 6 m on each date considered in Figure 29.
The depth of maximum primary production in Munsel Lake varied
from the surface to 3 m during the study period.
Table 5. Conversion of sampling date codes to sampling dates.
Sampling Dates
Feb. 13-15, 1971
Mar. 20-22, 1971
Apr. 17-19, 1971
May 16-18, 1971
Jun. 9-12, 1971
Jun. 26-29, 1971
Jul. 13-16, 1971
Jul. 31 Aug. 3, 1971
Aug. 18-21, 1971
Sep. 4-7, 1971
Oct. 2-5, 1971
Nov. 6-9, 1971
Jan. 2-5, 1972
Devils
Sampling Date Codes
Mercer
Siltcoos
Munsel
-
1
1
1
2
2
2
3
3
-
3
4
4
-
4
5
5
5
5
6
7
8
9
6
7
8
9
6
7
8
9
10
10
11
11
12
13
12
13
6
7
8
9
10
11
12
13
10
11
12
13
Figure 29 suggests a positive relationship between temperature
and phytoplankton assimilation numbers at the depth of maximum
primary production. Light can be considered as a relatively constant
environmental factor and the nutrient data is inconclusive since
nitrogen could still be fairly available in other forms (NH4+N and
dissolved organic
N, i.e. , urea) dependent upon excretory products
and nutrient regeneration rates.
When phytoplankton assimilation numbers are plotted against
temperature, both measurements taken at the depth of maximum
primary production (Figure 30), one may examine more closely a
possible causal relationship. A temperature coefficient, or Q10,
is the ratio of the rate of an activity at a given time to its rate at a
temperature 100 C lower. This temperature coefficient can be used
to determine whether rate increases in cellular reactions may be due
to the effect of temperature or to some other factor. Warburg (as
cited by Giese, 1968) measured Q101s for photosynthetic reactions at
high light intensities. These
c'5
ranged from 1. 6 to 4.3 over a
temperature range of 4°C to 30° C. Fogg (1966) reports Q101s of
from 2 to 4 for various planktonic and non-planktonic algae grown at
light saturation. The calculated Q101s in the present study, using
the slope of the curve in Figure 30, were 2.71 for the range 7°C to
17°C and 2.69 for the range 12°C to 22° C. Both of these calculated
Q101s are well within the range described by Warburg and Fogg (1966)
for thermochemical reactions.
The phytoplankton as similation number having the sampling date
code 9 in Figure 30, however, could not possibly be due directly to
the effect of a temperature increase. The
for the 0.7°C tern-
perature difference between the phytoplankton assimilation numbers
having sampling date codes 8 and 9 was 955.9, well outside the range
of Q101s recorded for changes in photosynthetic growth rates at high
light intensities. There must be an explanation other than temperature increase for the phytoplankton assimilation number measured
on that date.
Figure 31 considers the possibility of additional dens itydependent functions occurring in Munsel Lake at the depth of maximum
primary production. Two productivity periods are considered:
(1) winter, late spring, and (2) summer, fall. There appears to be a
distinct decreasing trend in phytoplankton assimilation numbers as
phytoplankton biomasses increase during the summer and fall period.
This relation applies only to those measurements taken at the depth
of maximum primary production. Any relations between phytoplankton
biomasses and phytoplankton production are less clearly indicated.
There is a small degree of evidence to suggest that the data in Figure
31 are varying in the manner theorized in Figure 2 for a single eco-
system, if that ecosystem had two different but fairly constant periods
of productivity.
Figure 32 examines possible oscillations in the productivity and
predator-prey relations of Munsel Lake as reflected by its phytoplankton and zooplankton biomasses. Three periods of productivity
are considered here: (1) winter, late spring
and (3) late summer.
(2) early summer, fall,
it is interesting to note that a comparison of
the dates of the biomass estimates in Figure 32 with the dates of the
temperatures recorded in Figtire 29 will reveal that the same date
codes are present within each seasonal period in each figure.
Phyto-
plankton and zooplankton biomasses periodically increased (or
decreased) accordingly with periodic changes in temperature at the
depth of maximum primary production. There is a fair degree of
evidence to suggest that thedata in Figure 32 are oscillating in two
axes in the manner theorized in Figure 3 for a single ecosystem, if
that ecosystem had three different but fairly constant periods of productivity.
After analysis of the data plotted in Figures 29 through 32 and in
view of what is known and/or suspected about the trophic processes of
phytoplankton, a tentative conclusion can be reached that temperature
may have been a dominant environmental factor governing changes in
measured phytoplankton relative growth rates and ecosystem produc-
tivity in Munsel Lake. During the period studied, no calculations
were performed for surface area : volume ratios of the lake's
indigenous algal species. However, microscopic examination of the
MUNSEL LAKE 1970-71-72
SUMMER 1970
4'
\
I
c? c'
/
>1ATE SUMMER
-.4
/EARLY SUMMER, FALL
/
/
WINTER, LATE SPRING
4
tO
20
40
60
80
00
200
400
ZOOPL4NKTON B/OM.4SS (Mean Mg. Dry WI. n7)
Figure 32. Seasonal progression of phytoplankton and zooplankton biomasses during the study period in Munsel Lake, Oregon.
Dashed lines hypothesize the possible seasonal predatorprey relationships and the direction of increasing productivity within the lake system.
water revealed that on nearly every sampling date the algal species
composition was mostly that of nannoplankton.
Actual nutrient availability may have remained relatively constant throughout the sampling period, with the exception of sampling
date code 9. This could conceivably occur if nutrient regeneration
was occurring in the shoals and in the limnetic zone at a rate equal to
or faster than the nutrient loss occurring by sedimentation of algae
out of the trophogenic zone and into the hypolimnion. As temperatures
increased, so would regeneration rates. The shoal area (0-5 m deep)
is comparatively largein Munsel Lake, about 31% of the lake's total
surface area (Oakley, l962b).
Hutchinson and Bowen (1950), in a radiochemical study of a
small lake having comparable morphometric characteristics with
Munsel. Lake, found, that littoral vegetation and littoral sediments are
a major nutrient storage area and a source for phosphorus entering
the epilimnion of small lakes during the spring and summer.
Bacterial nutrient regeneration in the littoral zone increases in sum-
mer as water temperatures increase and may reach a peak shortly
after the main growth of littoral macrophytes has come to an end. The
process may result in a continuously accelerated nutrient input spread
horizontally into the epilimnion as water temperatures increase.
Nitrogen sources in lakes can be divided into two categories:
(1) newly available nitrogen (NO3-N and N2-N) and (2) regenerated
nitrogen (NH4+N and dissolved organic nitrogen - N). Newly avail-
able nitrogen in the photic zone of a lake can occur either as a result
of inputs from precipitation and terrestrial runoff, nitrogen fixation
within the lake, or from the overturn of the hypolimnion. Regenerated nitrogen occurs primarily through the decomposition of organic
nitrogen by bacteria and through the excretory products of zooplankton.
A majority of the total available nitrogen in Munsel Lake may have
resulted from short-term regeneration as was shown by Dugdale and
Goe ring (1967). With the use of '5N labeled compounds they found
that over 60% of the nitrogen uptake of phytoplankton in northern
temperate oceans was due to recent regeneration of nitrogen, pri-
manly ammonia. The percentage rose to over 90% in tropical oceanic
regions. Nitrogen regeneration was almost certainly occurring in the
littoral zone of Munsel Lake and its storage and recycling may have
proceeded in a manner much like that described for phosphorus
The sharply increased phytoplankton assimilation number on
sampling date 9 (Figures 29, 30, 31) might possibly be due to the
regeneration rates of nitrogen and phosphorus reaching a peak,
exceeding nutrient sedimentation rates, and resulting in a net increase
of nutrients in the trophogenic zone. Another possible explanation is
that zooplankton biomasses were also at a peak on this date, having
doubled over an 18 day period (Figure 32). This might have resulted
in a sharp increase in excretory ammonia, stimulating phytoplankton
relative growth rates.
The preceding trophic analysis cannot be accepted as definite
proof that temperature was a dominant environmental factor governing changes in phytoplankton relative growth rates in Munsel Lake.
The sole purpose of the exercise was to illustrate how an analysis of
the trophic processes of phytoplankton might proceed if the effects of
various controlling and limiting factors could be satisfactorily
separated and measured. Unfortunately, too little is known about the
interactions of controlling and limiting factors in natural ecosystems,
particularly with reference to phytoplankton communities.
It is known that in situ nutrient additions can result in increased
phytoplankton as similation numbers (Gloos chenko and Curl, 1971); but
the effect that temperature may- have on phytoplankton assimilation
numbers is less certain. The process of photosynthesis is dependent
upon two sets of phytosynthetic reactions, both of which must occur.
The first set of reactions is light dependent (the light reaction) and the
second set of reactions is light independent (the dark reaction). When
light is at saturation and nutrients are constant, photosynthetic rates
may become governed by the dark reaction which is temperature
dependent up to about 300 C, when certain enzymes become deactivated
(Raven and Curtis, 1970). Under these conditions, phytoplankton
relative growth rates may parallel temperature changes, that is, if
no adaptation to temperature or to light is occurring. But adaptation
both to tempe rature and to light does occur in natural phytoplankton
populations, making it extremely difficult to interpret phytoplankton
relative growth rates. The hypothetical relationships depicted in Fig-
ure 1 may aid us in conceptualizing the trophic processes of phytoplankton, but may not necessarily help us to thoroughly understand
their dynamics.
No attempt was made to analyze any trophic processes of phyto-
plankton that may be operating in Devils, Siltcoos, and Mercer lakes
(Figures 33, 34, 35). In these three lakes no correlations were evident between variations in temperature and nutrients, considered
individually, and assimilation numbers measured at the depth of
maximum primary production. Oscillations in the productivity of
these lakes could not be described on the basis of density-dependent
functions.
Application. Study objective number four is to determine if
standard limnological techniques can be used to provide the informa-
tion necessary for a trophic classification of lakes on the basis of
density-dependent functions. Previous investigators have demonstrated that there is no general correlation between a lake's trophic
status and measured relative growth rates of its phytoplankton cornmunities; but there does appear to be a general relationship between
lake trophy and existing biomasses of living material.
Figure 36 compares the mean annual phytoplankton and
91
DEVILS LAKE 1970-71-72
SUMMER 1970
8
4
2
10
80 100
40
60
20
ZOOI°L 4 N/( TON 8/OMA 55 (Mean Mg. Dry WI.
200
m1
Figure 33. Seasonal progression of phytoplankton and zooplankton biomasses during the study period in Devils Lake, Oregon.
400
92
-
SJLTCOOS LAKE 1970-71-72
A SUMMER 1970
I
o0tI
w
II!
4
2
4
6
8
10
20
40
60 80 100
200
400 600
m31
Figure 34. Seasonal progression of phytoplankton and zooplankton biomasses during the study period in Siltcoos Lake, Oregon.
ZOOPL4NKTOIV 5/041455 (Mean Mg. Ory WI.
93
MERCER LAKE 1970-71-72
SUMMER 1970
8
4
2
20
10
40
60
80
100
200
ZOQPLANKTON B/OM4SS (Mean Mg. Dry Wt. m)
Figure
35.
Seasonal progression of phytoplankton and zooplankton biomasses during the study period in Mercer Lake, Oregon.
400
C.k
*7
to
8
.__-
I
6
I
0
JUN 71 -JAN 72
2
DEVILS
0
A
SILTCOOS
'10
1970-71-72
MERCER
0
MUNSEL
0
400
200
80 100
60
40
ZOOPL4N/(TON BIOMASS (Mean Annual Mg Dry WI. m3)
20
Figure 36. Theoretical relationships between phytoplankton biomass and
biomass of zooplankton within particular lake systems
(dashed lines) and between lake systems (solid line) compared with mean annual phytoplankton and zooplankton
biomasses measured for the four study lakes. Arrow
hypothesizes direction of increasing productivity between
lake systems.
95
zooplankton biomasses measured in the four study lakes during two
time periods. The time interval June 1971 through January 1972 has
exactly coincident sampling dates for all four of the study lakes. A
comparison of Figure 36 with Figures 27 and 28 shows that there is a
general increase in mean annual phytoplankton and zooplankton bio-
masses as mean summer primary production estimates increase.
The relationship is less clear for Devils and Siltcoos lakes, Siltcoos
Lake having the highest summer primary production estimates while
Devils Lake has the highest zooplankton biomasses.
Density-dependent functions make the assumption that in a series
of ecosystems having different basic capacities to produce phyto-
plankton, those systems having the highest phytoplankton production
capacity should be able to sustain higher phytoplankton densities at
higher zooplankton densities; and a positive correlation should exist
between phytoplankton biomass and zooplankton biomass. These
relationships are shown in Figure 3 and described by Brocksen, Davis,
and Warren (1970). The trend in Figure 36 appears to follow these
relationships and the four study lakes can be classified by trophy on
the basis of density-dependent functions.
However, it also appears that a major weakness of this lake
classification scheme is that as ecosystems approach eutrophy, zooplankton biomasses become less dependent upon phytoplankton bio-
masses. Devils Lake sustains about twice the zooplankton biomasses
present in Siltcoos Lake, while its phytoplankton production capacity
may actually be less than that of Siltcoos Lake (Figures 28, 36).
There are at least two possible interpretations of this phenomenon.
The first is concerned with zooplankton nutrition.
Phytoplankton are not the only prey of zooplankton. Bacteria
and detritus can also be important in the nutrition of these filter-
feeders. In fact, in eutrophic ecosystems, bacteria and detritus may
be an even more important source of food than phytoplankton for
zooplankton nutrition. A study of the dependence of herbivorous zooplankton upon the phytoplankton in an eutrophic lake in Sweden showed
that phytoplankton were of secondary importance to bacteria and
detritus as a direct source of food for the zooplankton (Nauwerck,
1963).
In both Devils and Siltcoos lakes the zooplankton may be highly
dependent upon bacteria and detritus. If this is so, and if Devils Lake
sustains higher bacterial and detrital biomasses than Siltcoos Lake,
then Devils Lake could possibly sustain higher zooplankton biomasses
with a lower phytoplankton production capacity.
Both Devils and Siltcoos lakes are fai1y eutrophic ecosystems
and their mean phytoplankton bioma$s estimates may not be very indic-
ative of the total food available to their zooplankton. The logarithmic
scales of Figures 32 through 35 exaggerate changes in the ordinate
values with respect to those plotted on the abscissa. In reality,
97
phytoplankton biomasses were changing very little with large changes
in zooplankton biomasses. Had bacterial and detrital biomass estimates been available, it would have been preferable to plot zooplank-
ton biomasses against the sum of phytoplankton, bacterial, and
detrital biomasses. Lake classification on the basis of dens itydependent functions could then possibly be more discriminating
between eutrophic ecosystems.
The second interpretation of the relatively high zooplankton bio-
masses measured in Devils Lake is concerned with a higher trophic
level, fish populations. No attempt was made to study the fish populations of Devils and Siltcoos lakes but it is possible that high standing
stocks of fish in Siltcoos Lake are controlling the zooplankton bio-
masses there to a greater extent than in Devils Lake. This conclusion, however, would be premature without additional data on the
bacterial, detrital, and fish biomasses of both study lakes.
Density-dependent functions can provide a graphic conceptualiza-
tion of biomass relations, if enough data are available, and through
these functions we may be able to better understand the biological
reasons why lakes of low, intermediate, and high productivity may
sustain low, intermediate, and high biomasses of both predators and
prey, including species of interest such as fish.
A General Discussion
Preceding sections of this thesis have discussed lake classification and the estimation of ecosystem productivity by descriptive
techniques, limnetic primary production estimates, and densitydependent functions. The purpose of a general discussion will be to
evaluate and summarize the relative merits and deficiencies of each
of these methods in the estimation of lake trophy and the rate of cul-
tural eutrophication.
A distinction should first be made between the processes of
normal eutrophication and cultural eutrophication. Each of the gen-
eral techniques listed above can be used to estimate the present status
of a lake in its normal evolution from oligotrophy through eutrophy,
but it is only by detecting accelerations in the rates or intensities of
existing biological processes that we can determine when cultural
eutrophication is taking place (Hooper, 1969). The detection of
accelerations can only occur when productivity estimates are repeated
over a period of time. It is therefore important that techniques for
classifying lakes and estimating the present state of their productivity
are also applicable for measuring cultural eutrophication.
The early descriptive lake classification techniques have
limited significance for the estimation of lake productivity, Lake
classification by region and origin, by thermal stratification, and by
general morphology (basin shape) are three such lake classification
schemes.
Other techniques, owing their origin to the descriptive philosophy
of lake classification, have become variously useful as relative
indices of ecosystem productivity. Water hardness or total alkalinity,
total dissolved solids, and specific conductance can be useful relative
indices in regional studies, but it is difficult to fix absolute scales for
lake trophy on the basis of these chemical indices when lakes are
surveyed over a wide geographical area. Water transparency data,
whether measured with a photometer or a Secchi disc, can be somewhat difficult to interpret because they do not always discriminate
between various types of suspended matter. Changes in lake trans-
parency may not necessarily be due to an increase of plankton
organisms. Morphometric indices such as mean depth and shoreline
development are useful indices of normal eutrophication but are of
little consequence as indices of rapid cultural eutrophication.
Nutrient levels have long been used as relative indices of lake
productivity and with one exception there appears to be general con-
fusion as to their relative significance. That single exception seems
to be the element phosphorus. For over 50 years limnologists have
known that phosphorus is a major factor in lake eutrophication.
Hutchinson (1957) believed that phosphorus is the single micronutrient
most likely to be deficient and therefore limiting to algal growth in
100
lakes. I would like to summarize the discussions of Bartsch,
Vallentyne, Edmondson, and Shapiro in a recent symposium sponsored
by the American Society of Limnology and Oceanography (Likens,
1972a).
Theirirnplicit conclusions were that cultural eutrophication
can be halted by advanced waste treatment practices and that the most
important nutrients to be removed through waste treatment are phos-
phorus, nitrogen, and carbon, in that order.
For these reasons I believe that total phosphorus concentrations
are perhaps the most significant single chemical index to be used in
the estimation of a lake's potential productivity. As lakes become
more eutrophic, nitrogen may begin to play a comparable role with
phosphorus as a limiting nutrient in determining ecosystem productivity. This view on the comparative roles of nitrogen and phosphorus
is held by Thomas (as cited by Hutchinson, 1967) and it again supports
the thesis that phosphorus is the single most important element to be
used in the estimation of a lake's trophy.
Dis solved orthophosphate concentrations appear repeatedly in
limnological literature but they are extremely difficult to interpret in
terms of lake classification and the estimation of ecosystem productivity because they are not necessarily indicative of the nutrient availability of phosphorus or of any other micronutrient. Inorganic phosphorus undergoes rapid exchange within lake basins through bacterial
regeneration (Hutchinson and Bowen, 1950). In addition, it can be
101
stored in excess in aquatic autotrophs (Hutchinson, 1957, 1967),
possibly to be utilized at a later time when it is less available or when
some other limiting nutrient such as nitrogen becomes more available.
Total phosphorus is perhaps thesingle chemical index most
indicative of general nutrient levels in lakes. As more information
becomes available it may someday be possible to propose an absolute
trophic scale based on total phosphorus and several other selected
micronutrients, just as has been done for limnetic primary production
estimates.
Limnetic primary production estimation is a technique which has
been adaptable to a great many ecosystems. The Rodhe (1969) scale
may be fairly sensitive to cultural eutrophication but, used as an
absolute trophic scale, it can be difficult to interpret under certain
conditions. Using this scale, two types of lakes are imperfectly
classified according to popular conceptions of lake trophy and ecosys-
tern productivity: those lakes that are very shallow and those that are
fairly deep. Very shallow lakes frequently support large biomasses of
macrophytic plants and periphyton, two autotrophic producers that are
not included in limnetic primary production estimates (Likens, 1972b).
The primary production estimates of relatively deep lakes can be dif-
ficult to interpret on an absolute trophic scale if the estimates are
fairly high. High primary production estimates imply advanced
stages of eutrophy, a status which we may not always be able to accept
102
intuitively for certain lakes having moderate to extreme mean depths.
A further inadequacy of primary estimates is that they do not
always reflect consumer activities. It is here that lake classification
and the estimation of ecosystem productivity on the basis of densitydependent functions may have some merit. Given enough data it may
be possible to perform graphic analyses of food relations at different
enrichment levels and to predict changes likely to occur as a cons equence of cultural eutrophication of an ecosystem of interest. Through
density-dependent studies of bacterial, detr ital, phytoplankton, and
zooplankton biomasses it may eventually be possible to predict bio-
logical changes likely to occur in a given ecosystem with a given level
of cultural eutrophication.
Such studies might be most useful in the interpretation of slow
changes in an ecosystem resulting from relatively mild eutrophication.
It is fully realized that to provide the information necessary for an
analysis of this type would require considerable effort and financial
resources. Yet there may be cases in which such effort is warranted
because of the value of a particular resource for an intended use.
103
SUMMARY AND CONCLUSIONS
(1)
On the Rodhe (1969) trophic scale, which classifies lakes on the
basis of their mean limnetic primary production estimates,
Devils, Siltcoos, Mercer, and Munsel lakes would all be classified as naturally eutrophic with Mercer and Munsel lakes bordering on the lower range of natural eutrophy. Descriptive
techniques and biomass estimates appeared also to have significant lake classification value because they provided these same
relative conclusions for the four study lakes. The fixing of abso-
lute trophic scales is a difficult assignments whether lakes are
clas sified by descriptive techniques, limnetic primary production
estimates, or biomass data.
(2)
No correlations can currently be demonstrated between measured
mean phytoplankton relative growth rates (P/B measurements of
phytoplankton communities) and a lake's trophic status. Correla-
tions may theoretically exist between the relative growth rates of
a single "type" phytoplankton population and lake trophy. How-
ever, any such correlations cannot currently be demonstrated
between lake systems having widely differing trophic status and
differing species composition because of the two following
endogenous factors which can mask the relative significance of
any phytoplankton relative growth measurements:
104
(a)
differing surface area volume ratios for various algal
species often found naturally associated with oligotrophic
mesotrophic, and eutrophic ecosystems; i.e.
causes differ-
erit endogenous species efficiencies for nutrient uptake.
(b)
possible partial cell division synchrony occurring in phytoplankton populations in any single ecosystem making it
extremely important to know whether relative growth meas-
urements were performed on juvenile or senile populations;
i. e., can cause a bias in relative weight of chlorophyll a
algal dry weight and production biomass (as weight of
chlorophyll a or algal dry weight) ratios.
(3)
Within a single ecosystem, measured phytoplankton relative
growth rates may have some relative significance for estimating
changes in ecosystem productivity if species composition and
algal cell surface area volume ratios do not vary widely during
the period of measurement. Possible cell division synchrony
may remain an unknown factor but, even so, it may be possible
to attempt certain tentative interpretations of the trophic dynamics
of phytoplankton, based on suspected density relations between
measured phytoplankton relative growth rates and the integration
of light, temperature, and nutrient availability.
105
(4)
Temperature may have been a dominant environmental factor
governing changes in phytoplankton relative growth rates and
ecosystem productivity in Munsel Lake. Relative changes in
ecosystem productivity in this lake during 1971 may be most
directly correlated with temperature changes. However, nutrient
availability must be considered the dominant environmental factor
governing the status of each of the study lakes on a scale of
oligotrophy through eutrophy.
(5)
It is possible, through the use of standard limnological techniques
to classify lakes by trophy on the basis of density-dependent functions. However, lake classification by trophy should not be
attempted on the basis of mean phytoplankton community relative
growth rates. Mean annual or summer phytoplankton and zooplankton biomasses will correlate fairly well with ecosystem
trophy, for oligotrophic through mesotrophic ecosystems.
Eutrophic lakes are less easily classified on the basis of densitydependent functions when just phytoplankton and zooplankton bio-
masses are considered. Lake classification by predator and prey
biomasses is a very old idea and cannot be considered as a contribution of the concept of density-dependent functions. Instead,
density-dependent functions provide a point of view and a conceptualizat ion through which we may further our understanding of
106
the biological reasons why lakes of low, intermediate, and high
productivity may sustain low, intermediate, and high mean bio-
masses of both predators and prey.
(6)
There can be no single universally satisfactory method of classifying lakes and estimating relative trophy in natural ecosystems.
This may stem from the fact that there is no universally acceptable definition of what constitutes a lakes trophy. Descriptive
classification techniques, limnetic primary production estimates,
and biomass estimates all measure essentially different qualities
and all have been used as objective measurements of present
trophic status. Repetition of these objective measurements may
suggest that a change in trophic status has occurred. However,
the interpretation of these changes or accelerations of rates or
intensities of biological processes has been, and most likely will
continue to be, a very difficult and highly subjective undertaking.
(7)
Through density-dependent studies of bacterial, detrital, phyto-
plankton, and zooplankton biomasses, it may eventually be possible to predict biological changes likely to occur in a given
ecosystem with a given level of cultural eutrophication.
(8)
To perform a comparative regional study of lake productivity
perhaps the simplest effective techniques are to use mean
107
summer total dissolved solids and mean depth, in that order of
importance, as relative indices of lake productivity. For serious
comparative productivity studies of widely scattered lakes, per-
haps the most suitable technique is the calculation of mean
summer limnetic primary production. The complexity of this
approach limits its application to rather sophisticated limnological
sampling. Very often, however, useful comparative productivity
estimates may be gained through the calculation of mean summer
phytoplankton and/or zooplankton biomasses, a slightly simpler
task.
(9)
Total phosphorus is perhaps the single chemical index most
indicative of the general nutrient level of a lake. However, sufficient data has not yet been accumulated to postulate an absolute
trophic scale based on concentrations of this micronutrient.
(10) No new methods can be suggested through which investigators may
quickly and accurately assess lake productivity. Almost all presently used techniques are complicated time-consuming, and
inconclusive.
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