AD-AIOI 13S ARMY EN6INEER WATERWAYS EXPERIMENT STATION VICKSBURG-ETC FIG 6/6ESTIMATING PYTOPLANKTON BIOMASS AND PRODUCTIVITY.U )
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Jeffrey J. IanikIneancAgemtWilliam D.!TaylorIneaeyAgemtVictor W. Lambou No. WES-78-12
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Aouatic plantsB iomas sPhytoplanktonPrimary, productivity
2&. AWWAACT (Candis di m~et atb It ncewy acd Identlfy by block nuusbet)-Estimates of phytoplankton biomass and rates of production can provide a
manager with some insight into questions concerning trophic state, waterquality, and aesthetics. Methods for estimation of phytoplankton biomass in-clude a gravimetric approach, microscopic enumeration, and chlorophyll a analy-sis. Strengths alid weaknesses of these and other methods are presented.Productivity estimation techniques are discussed including oxygen measurement,carbon dioxide measurements, carbon 14 measurements, and the chlorophyllmethod. Again, strengths and weaknesses are presented. -,ORIIII EIIOOIOVSSUSLT Unclassified
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Preface
The study reported herein was sponsored by the Office, Chief ofEngineers, U. S. Army, under the Environmental and Water Quality Opera-
tional Studies (EWQOS) Program, Task IB.l, Improved Description ofReservoir Ecological and Water Quality Processes. The EWQOS Program has
been assigned to the U. S. Army Engineer Waterways Experiment Station
(WES), Vicksburg, Miss., under the purview of the Environmental
Laboratory (EL).
The investigation was conducted under Interagency Agreement No.
WES-78-12 between the WES and the U. S. Environmental Protection Agency
(EPA), Las Vegas, Nev., and the University of Nevada, Las Vegas, Nev.
The authors of this report were Messrs. J. J. Janik, W. D. Taylor, and
V. W. Lambou.
The study was conducted under the general WES supervision of
Dr. Kent Thornton and Mr. Joseph Norton; Dr. Jerome L. Mahloch, Program
Manager, EWQOS; Dr. Rex L. Eley, Chief, Ecosystems Research and Simula-
tion Divison; and Dr. John Harrison, Chief, EL.
The Commanders and Directors of the WES during the study and the Ipreparation of this report were COL John L. Cannon, CE, and COL Nelson P.
Conover, CE. The Technical Director was Mr. F. R. Brown.
1T
I -,
JV
Contents
Page
Preface .. ......................... ......
Introduction. ......................... ... 3
Phytoplankton Biomass Techniques. .................. 3
Microscopic Methods for Measuring Biomass .. ............. 4
Numerical abundance .. ..................... 4Cell volume (biovolume) .. ................... 5Cell surface area .. ....................... 5Plasma volume .. ......................... 6
Chemical and Physical Methods for Measuring Biomass. .......... 6
Dry weight. ........................... 6Ash-free dry weight .. ..................... 6
Chlorophyll a Analysis. ........................ 7
Carbon. ....................... ..... 7Phosphorus. ........................... 7Nitrogen. ....................... .... 8
Phytoplankton Productivity Techniques .. ............... 9
Oxygen measurements .. .. .. .. .. .. .. .. .. .. 10Carbon dioxide measurements. .... ............. 11Carbon-14 measurements .... ................ 12Chlorophyll method ..... .................. 12
Algae-Related Conversion Formulas. .... ............. 13
References ..... ......................... 14
Table 1
2
ESTIMATING PHYTOPLANKTON BIOMASS AND PRODUCTIVITY
Introduction
1. Biomass and productivity measurements provide important infor-
mation on phytoplankton abundance and growth. Phytoplankton biomass is
the amount of algal material present, whereas productivity is the rate
at which algal cell material is produced. These data give the reservoir
manager a measure of the biological status of the primary producers.
Phytoplankton in many lake systems limit the quantitative and qualita-
tive aspects of the higher trophic levels; therefore, knowledge of phyto-
plankton activities is fundamental to understanding and managing a water
body for specific uses. Management questions concerning lake trophic
state, water quality, fisheries, and aesthetics can be addressed from
these data. Many models, predicting the consequences of nutrients, tur-
bidity, toxicants, and hydrological modifications, require accurate mea-
surements of phytoplankton biomass and productivity. The purpose of
this report is to describe and compare methods for estimating phyto-
plankton biomass and productivity.
Phytoplankton Biomass Techniques
2. Biomass may be defined as the living matter of the various
groups of organisms present in an ecological sector at the time of obser-
vation. The phytoplankton biomass (standing crop) is the quantity of
autotrophic planktonic organisms present in a water body (Steemann-
Nielson 1963).
*3. Various microscopic, chemical, and biochemical techniques are
used to measure the quantity of phytoplankton biomass. The following
quantitative measurements can be made using microscopic techniques: nu-
merical abundance, cell volume, cell surface area, and plasma volume.
4. Common chemical and biochemical procedures for measuring bio-
mass include the following parameters: dry weight, ash-free dry weight,
3
carbon, phosphorus, nitrogen, and chlorophyll a. In the absence of
specific analyses, it is possible to estimate particular components
indirectly from available data by the use of conversion formulas
(Table 1).
5. Direct microscopic examination provides the most useful kind
of information (Fogg 1965) and has three basic advantages over other
methods. The first is that the algae are observed each time a count is
made so that any changes in appearance, size, shape, or aggregation of
cells can be recorded. The second is that dead and living cells may be
differentiated. The third is that exact information on algal species
composition and size distribution is obtainable.
6. Nonmicroscopic determinations of phytoplankton biomass may be
impaired by the presence of detrital material, particulate organic
matter, zooplankton, and bacteria, but are less time consuming than
microscopic counting methods.
Microscopic Methods for Measuring Biomass
Numerical abundance
7. The use of numerical abundance (cells/ml) is of limited value
as a measurement of biomass. This is attributable to the variation in
cell size within individuals of a species and between different species
of phytoplankton. Cell counts do not express these differences since
equal numerical value is assigned to each algal cell regardless of size.
Paasche (1960) reported that cell numbers tend to be biased towards the
smaller, usually more numerous species in the community. Munawar et al.
(1974) reported that cell numbers can neither give information about
phytoplankton biomass nor can they be correlated with primary production,
particularly where algal populations are variable in size; however, cell
numbers have been correlated with chlorophyll a. Taylor et al. (1979)
found a rank correlation (r s ) between cell numbers and chlorophyll a for
44 eastern and southeastern U. S. lakes to be 0.72 (P < 0.01). Munawar
et al. (1974) also reported a significant correlation between cell abun-
dance and chlorophyll a (r = 0.59, P < 0.01).
4
Cell volume (biovolume)
8. Determination of cell volume (pm3 per individual or colony)provides a measure of the phytoplankton biomass (mg fresh weight/m3)
assuming that the specific weight of algae is approximately unity. This
measurement of standing crop is widely accepted in quantitative surveys
(Rodhe et al. 1958, Nauwerck 1963, Munawar and Nauwerck 1971). The
appropriate dimensions of at least 25 randomly selected cells are mea-
sured, and the volume of each of the measured cells is calculated, from
which the mean cell volume is derived (Smayda 1978). The mean cell
volume should not be calculated from the average linear dimensions of
the individual cells. Cell volumes are usually reported in pm 3/1 or
Pm /m 3 . Simple geometric formulae may be used to compute the cell
volumes, although some phytoplankton cells may have to be subdivided into
several shapes because of their complex geometric configurations. Cell
volumes are computed by simply integrating the volumes calculated for
each form. Standard volumes from published sources should be used with
great care in these calculations since differences in cell dimensions
vary considerably from one lake to another and even seasonally from the
same lake.
9. Results of phytoplankton surveys expressed in terms of biovol-
umes may tend to overemphasize the importance of the larger forms as pro-
ducers (Paasche 1960). The small nannoplankton generally assimilate
much more carbon per unit of biomass than do the larger forms (Findenegg
1965).
10. Cell volumes generally provide good correlations with other
biomass and productivity parameters. Munawar et al. (1974) reported
that cell volume was better correlated to chlorophyll a and photosynthe-
sis rates than to cell surface area and numerical abundance. Taylor
et al. (1979), however, reported better Spearman rank correlations
(P < 0.01) with cell numbers and chlorophyll a than with biovolumes and
chlorophyll a (rs = 0.72 and 0.66, respectively).
Cell surface area
11. Cell surface area (pm2) provides a better method of estimating
standing crop than does numerical abundance; however, it is not as widely
5
used or as quantitative as cell volume (Munawar et al. 1974). Cell sur-
face area is important since it represents the assimilative area for
nutrients. The area computation is similar to the method used in com-
puting cell volumes.
Plasma volume312. The measurement of plasma volume (pm ) has been suggested as
a more accurate method than cell volume to estimate standing crop
(Paasche 1960). Plasma volume is restricted to the cytoplasm in which
the chloroplasts are embedded, thus excluding the vacuoles. This method
has limited acceptance in phytoplankton surveys because of the difficulty
in quantifying the volume of the cytoplasm in algal cells (Smayda 1965).
Chemical and Physical Methods for Measuring Biomass
Dry weight
13. Dry weight is determined by drying a sample until a constant
weight is obtained (Weber 1973). Results are usually reported in Pg/l.
This method provides a rapid estimate of biomass, but errors occur be-
cause delicate algal cells may be disrupted on the filter surface with
a subsequent loss of cell material, and algal cells retain a variable
amount of residual water after the drying process. Most investigators
dry their samples at 105'C; other drying temperatures have been used,
but the conversion or comparison of these results is difficult.
Ash-free dry weight
14. Ash-free dry weight is calculated by subtracting the ash con-
tent from the dry weight. Results are usually reported in pg/l.
15. This method is preferable to dry weight as a measure of algal
biomass when comparisons involving mixed assemblages of species are made.
This is due to the variable ash content in planktonic algae, e.g., 50
percent ash in diatoms and 5-20 percent ash in green algae (Nalewajko
1966). Carbon content is often employed as a basis for production rates
of phytoplankton populations and is normally in the range of 53 + 5% of
the ash-free dry weight (Lund and Tailing 1957). Additional conversion
formulas are given in Table 1.
6
Chlorophyll a Analysis
16. Chlorophyll a is the predominant chlorophyll pigment in plank-
tonic algae and assumes considerable importance in productivity studies
and standing crop estimates. The speed and the simplicity of chloro-
phyll a analysis are the two main reasons that this method is the most
popular for estimating standing crop (Strickland 1960). Results are
usually reported in g/l. The analysis is far less time consuming than
are the microscopic "counting" methods. It does not, however, furnish
information on algal species and size composition. This method of
estimating biomass is also faced with certain problems: pigment extrac-
tion is not always complete; chlorophyll content varies with the age and
light or shade adaptation of the population; relative pigment composi-
tion of various phytoplankton groups is not always constant; and degrada-
tion products may be included with active chlorophyll by ordinary extrac-
tion processes.
17. Chlorophyll a data are valuable for the rapid comparison of
productivity in different bodies of water and are especially informative
when used in conjunction with other biomass parameters (Fruh et al.
1966).
Carbon
18. The quantity of carbon present in algal cells provides a
satisfactory method for measuring standing crop. The relative amount of
carbon present in algal cells on an ash-free organic matter basis is
fairly constant. Ryther (1954) has calculated the amount to be 45-55
percent in marine forms. The values for freshwater forms are similar.
Table I presents additional relationships.
Phosphorus
19. Phosphorus (P) in the form of cellular phosphorus or as total
water phosphorus has been used to estimate phytoplankton standing crop.
The quantity of cellular phosphorus is quite variable; the amount ab-
sorbed by growing phytoplankton and the phosphorus content of result-
ing cells depends on the phosphorus content of the surrounding medium.
Another problem is that plants have the ability to store the phosphorus
7
in excess of normal requirements (Mackereth 1953), a process termed
luxury uptake. Thus, the final phosphorus content of an algal cell
depends upon the growth history of the plant and the growth medium.
Standing crop estimates from P are gross approximations. The relation-
ship of cell carbon to cell phosphorus is (Strickland 1960):
Cell Carbon (mg) = Cell Phosphorus (mg) x 49(+15)
20. Various authors have developed regression equations for pre-
dicting chlorophyll a concentrations as a function of phosphorus (Carlson
1977; Dillon and Rigler 1974; Jones and Bachmann 1976). Kalff and
Knoechel (1978) presented a regression equation that provides a mechanism
for estimating mean summer biomass from mean summer total phosphorus lake
data according to the following relationship:
Biomass (pg/m 3 ) = 1.206 log phosphorus (mg/m3 ) + 1.635
where r = 0.84, n = 28,and p < 0.001. Additional conversions from phos-
phorus to biomass via chlorophyll a and carbon are given in Table 1.
Nitrogen
21. This element, like phosphorus, can vary according to the
amount present in the medium from which the plants are grown and can
provide only an approximate estimation of standing crop. Strickland
(1960) determined the following relationships for marine phytoplankton:
Cell carbon (mg) = cell nitrogen (mg) x 6(+2)
and
Chlorophyll a (mg) = cell nitrogen (mg)7 (+3)
8
Phytoplankton Productivity Techniques
22. Primary productivity is the rate at which energy is stored by
photosynthetic and chemosynthetic activity of producer organisms (algae)
in the form of organic substances that can be used as fuod materials
(Odum 1971). Respiration, on the other hand, is the use of organic
substances by organisms to provide the energy they need for their life
processes. Several component categories have been identified and found
to be useful in understanding energy flows in aquatic systems.
23. The basic equation used to describe photosynthesis and aerobic
respiration is
energy inputphotosynthesis
6C02 + 6H20 C6H1206 + 602
energy outputrespiration
Carbon dioxide is the primary carbon source taken from the environment
and incorporated into cell mass through the use of solar energy. One ofthe byproducts of this reaction is 02, which is released into surround-
ing environment and used to satisfy respiratory demands of the organism
itself. Aerobic respiration utilizes stored food and 02 and produces2
~CO 2 and water. Consequently, both photosynthesis and respiration can be
measured by observing the increase of 02 in the aquatic environment
diurnally (or under conditions where light is present) and the decrease
in 02 nocturnally (or under conditions where light is not present).
These processes can also be measured by observing the decrease in CO2 in
the aquatic environment diurnally and the increase of CO2 nocturnally.
24. If the general equation for production/respiration proceeds
exactly as given, the C02 /02 budget should exhibit a ratio of one. There
are other processes occurring in aquatic systems that alter the CO2 bud-
get(anaerobic respiration will release CO2 without consuming 02).
25. Gross primary productivity is defined as the total rate of
9
photosynthesis, including the organic matter used in respiration during
the measurement period. It is also known as "total photosynthesis" or
"total assimilation" (Odum 1971). Net primary productivity is the stor-
age rate of organic matter in plant tissues in excess of the respiratory
utilization by the plants during the period of measurement. It is also
known as "apparent photosynthesis" or "net assimilation" (Odum 1971).
Net community productivity is the storage rate of organic matter not
used by autotrophs and heterotrophs (i.e., net primary production minus
heterotrophic consumption) during the period under consideration.
26. There are four general methods to measure phytoplankton pri-
mary productivity. These involve the measurement of (1) changes in the
02 content of water, (2) changes in the CO2 content of water, (3) incor-
poration of carbon-14 tracers into the organic matter of phytoplankton,
or (4) chlorophyll. In general, the values for gross production will
depend on how production is measured. According to Rich and Wetzel
(1978),
Oxygen not reduced to water because of anaerobic respirationwill appear as net production but not as respiration and gross
photosynthesis by the oxygen method will underestimate theflow of energy through the ecosystems. Carbon methods willcorrectly estimate gross carbon uptake but will underestimatean accumulation of reducing power on non-carbon substrates
by anaerobic metabolism and overestimate the flow of energythrough the system.
Sources for error in the use of the carbon method include respiratory
losses of CO2 and the secretion of soluble organic products of photo-
synthesis. The carbon method is far more sensitive and better suited
for use in oligotrophic waters than the 02 method. Fogg (1965), however,
recommends the 02 method in eutrophic waters.
Oxygen measurements
27. This technique provides estimates of net and gross productiv-
ity as well as respiration. Samples of phytoplankton can be incubated
in situ in clear and dark bottles and changes in their 02 content can
be measured over time. Another approach is to measure changes in 02
concentration diurnally and nocturnally in the aquatic environment.
Initial concentrations of dissolved 02 (C1 ) can be expected to be reduced
10
to a lower value (C2 ) by respiration under conditions where light is not
present and to be increased to a higher concentration (C3 ) by photosyn-
thesis under conditions where light is present. The following measure-
ments can be calculated with the technique:
a. Respiratory activity = (C1 - C2 ).
b. Net primary production = (C3 - C).
c. Gross primary production (C3 - C2) = (C3 - C1) + (C1 - C2).
Results can be expressed as the amount of carbon fixed (as a result of
photsynthesis) per unit volume of water per hour or day.
28. There are advantages and disadvantages to measuring 02 changes
in bottles as opposed to measuring those actually occurring in the envi-
ronment. Any method that encloses water samples in bottles involves a
drastic alteration in the environment: (1) the normal turbulence of
the water is reduced to such low levels that important components of the
community settle out and collect on the glass surface of the bottle
where supplies of CO2 and other nutrients are likely to be transported
to the site at reduced rates; buoyant forms float to the surface;
(2) motile members of the community are likely to swim either toward or
away from the light (depending on its intensity), and when they reach
the wall of the bottle, they may become attached there or may perish;
and (3) the large increase in solid surface presented by the walls of
the bottle enhances the growth of bacteria and fungi, generating an
unnatural biomass of these components and an equally unnatural respira-
tion rate as computed from the dark bottle data. Bunt (1965) found that
respiration was not the same for all species of phytoplankton in both
light and dark bottles. Differences in daytime and nighttime respiration
of autotrophs and heterotrophs could affect the accuracy of estimates of
productivity obtained by measuring 02 concentration changes in the
aquatic environment. If the exchange of 02 with the atmosphere is
significant, it should be corrected for in determining productivity by
measuring changes in 02 concentrations in the aquatic environment.
Carbon dioxide measurements
29. As with the 02 method, changes in CO2 can be measured in clear
and dark bottles incubated in situ, or diurnal and nocturnal changes can
11
be measured in the aquatic environment. Both production and respiration
can be estimated from these changes.
30. In aquatic systems the pH of water is a function of the dis-
solved CO2 content and changes in pH are usually measured and then con-
verted to CO2. A calibration curve for the water in a particular system
must be prepared because the pH and CO2 content are not linearly related
and the degree of pH change per unit of CO2 change depends upon the buf-
fering capacity of the water. Thus, one unit of CO2 removed by photosyn-
thesis will bring about a pH increase in soft water from a mountain
stream greater than that in well-buffered sea water (Odum 1971). De-
tailed instructions for calibration curves are given by Beyers et al.
(1963). Most of the discussion relative to the use of 02 measurements
is also pertinent to the use of CO2 measurements.
Carbon-14 measurements
31. With this technique the incorporation of carbon-14 tracer
into the organic matter of phytoplankton during photosynthesis is used
to measure primary production. There is uncertainty as to whether the
radiocarbon method measures net or gross photosynthesis, or a rate be-
tween the two (Steemann-Nielsen 1963 and Yentsch 1963). Ryther (1954)
has shown that it measures a quantity closer to the net photosynthetic
rate.
Chlorophyll method
32. Chlorophyll has been described previously as a measure of
biomass; however, it can also be used to measure productivity. The use
of this method is not as widespread as the other methods. Many of the
problems mentioned in the biomass techniques section also affect the
measurement of productivity. An additional problem is that algae species
tend to be sun or shade adapted according to the light intensity that
the algae experience. Shade-adapted plants tend to have a higher concen-
tration of chlorophyll than do sun-adapted plants.
33. This method requires the measurements of the assimiliation
ratio (the rate of production per gram of chlorophyll, as grams 02 per
hour per gram chlorophyll), the chlorophyll concentration, and surface
light radiation. Ryther and Yentsch (1957) found that marine
12
phytoplankton at light saturation have a reasonably constant assimila-
tion ratio of 3.7 grams of carbon assimilated per hour per gram of chlo-
rophyll. Calculated production rates based on this ratio and on
chlorophyll-light measurements were very similar to those obtained by
the light- and dark-bottle oxygen method.
Algae-Related Conversion Formulas
34. Conversion formulas used to calculate particular biological
and chemical components from available data are listed in Table 1. The
table gives the formula, limitations and qualifications, and a reference
for each conversion listed. These conversion formulas should be used
with utmost caution because of variability in the relative chemical com-
position of biological samples. The variability is dependent upon a
number of biological, historical, and environmental conditions. Only
rough estimates can be expected for many factors; however, if the uncer-
tainties of the factors are fully realized and the inherent errors are
appreciated, useful information may be obtained and used.
13
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15
Ii
Steemann-Nielson, E. 1963. Productivity, definition and measurement.In: The Sea, Vol 2. M. H. Hill (ed.). Interscience, New York.pp. 129-164.
Strathman, R. E. 1967. Estimating the organic carbon content of phyto-plankton from cell volume or plasma volume. Limnol. Oceanogr. 12(3):411-418.
Strickland, J. D. H. 1960. Measuring the production of marine phyto-plankton. Bulletin No. 122. Fish Res. Board of Canada, Queens Printer,
Ottawa, Canada.
Taylor, W. D., L. R. Williams, S. C. Hern, and V. W. Lambou. 11979Phytoplankton Water Quality Relationship in U. S. Lakes. Part VII.Comparison of some new and old indices and measurements of trophicstate. EPA-600/3-79-079. U. S. Environmental Protection Agency,Las Vegas, Nevada.
Verduin, J., L. R. Williams, and V. W. Lambou. 1976. Components con-tributing to light extinction in natural waters: Method for isolation.U. S. Environmental Protection Agency. National Eutrophication SurveyWorking Paper No. 369.
Weber, C. I. (ed.). 1973. Biological field and laboratory methods formeasuring the quality of surface waters and effluents. EPA-670/4-73-001. National Environmental Research Center Office of Research andDevelopment, U. S. Environmental Protection Agency, Cincinnati, Ohio.
Williams, L. R., V. W. Lambou, S. C. Hern, and R. W. Thomas. 1978.Relationships of productivity and problem conditions to ambient nutri-ents: National Eutrophication Survey findings for 418 eastern lakes.
EPA-600/3-78-002. U. S. Environmental Protection Agency, Las Vegas,Nevada.
Wright, J. C. 1959. Limnology of Canyon Ferry Reservoir. II. Phyto-plankton standing crop and primary production. Limnol. Oceanogr.4(3):235-245.
Yentsch, C. S. 1963. Primary production. Oceanogr. Mar. Biol. Ann.
Rev. 1:157-175.
16
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In accordance with letter from DAEN-RDC, DAEN-ASI dated
22 July 1977, Subject: Facsimile Catalog Cards forLaboratory Technical Publications, a facsimile catalogcard in Lihrary of Congress MARC format is reproduced
below.
Janik, Jeffrey J.
Estimating phytoplankton biomass and productivityfinal report / by Jeffrey J. Janik, William D. Taylor
(Department of Biological Sciences, University of
4Nevada, Las Vegas) Victor W. Lambou (Environmental
Monitoring and Support Laboratory, U.S. EnvironmentalProtection Agency, Las Vegas, Nev.). -- Vicksburg,
Miss. : U.S. Army Engineer Waterways Experiment Station
Springfield, Va. : available from NTIS, [1981].
16, 7 P. ; 27 cm. -- (Miscellaneous paper / U.S.Army Engineer Waterways Experiment Station E-81-2)
Cover title."June 1981.'"Prepared for Office, Chief of Engineers, U.S. Army
under Interagency Agreement No. WES-78-12, EWQOS Task
IB.I."
"Monitored by Environmental Laboratory, U.S. ArmyEngineer Waterways Experiment Station, Vicksburg,
Miss."At head of title: Environmental and Water Quality
Janik, Jeffrey J.
Estimating phytoplankton biomass and productivity ... 1981.(Card 2)
Operational Studies.
Bibliography: p. 14-16.
1. Aquatic plants. 2. Phytoplankton. 3. Primary
productivity (Biology). 1. Taylor, William D.
II. Lambou, Victor W. III. University of Nevada.
Department of Biological Sciences. IV. United States.
Environmental Protection Agency. Environmental Monitoring
and Support Laboratory. V. United States. Army. Corps
of Engineers. Office of the Chief of Engineers. VI. U.S.
Army Engineer Waterways Experiment Station. Environmental
Laboratory. VII. Environmental and Water Quality
Operational Studies. VIII. Title IX. Series: Miscellaneous
paper (U.S. Army Engineer Waterways Experiment Station)
E-81-2.TA7.W34m no. E-81-2
oo
AD-AlOl 413 ARMY ENGINEER WATERWAYS EXPERIMENT STATION VICKSBURG--ETC F/6 6/6
ESTI MATING PHYTOPLANKTON B ZOMASS AND PRODUCTIVITY U)
JUN al J J JAN IK, W D TAYLOR, V W LAMBOU
UNCLASSIFIED WES/MP/E81-2
SUPPLEMENTAR"
4
INFORMATION
DEPARTMENT OF THE ARMYWATERWAYS EXPERIMENT STATION. CORPS OF ENGINEERS
P. 0. BOX 631VICKSBURG. MISSISSIPPI 39180
IN REPLY pgm T, WESEV 21 October 1981
Errata Sheet
No. I
ENVIRONMENTAL & WATER QUALITY OPERATIONAL STUDIES
ESTIMATING PHYTOPLANKTON BIOMASS AND PRODUCTIVITY
Miscellaneous Paper E-81-2
June 1981
1. Page 5, paragraph 10: Change lines 3 and 4 of this paragraph to read
that cell volume was better correlated to chlorophyll a and photosyntheticrates than to cell surface area and numerical abundance. Taylor
2. Page 8, paragraph 20: Change line 5 of this paragraph to read
for estimating mean summer biomass (wet weight) from mean summer total
phosphorus lake
3. Page 8, paragraph 20: Change the centered unnumbered equation in thisparagraph to read
Log biomass (mg 10 3/m 3) = 1.206 log phosphorus (mg/m3 ) + 1.635
4. Pages 14, 15, and 16: Replace these with the inclosed corrected pages.
5. Table 1, Sheets 2, 4, 5, and 7: Replace these with the inclosed correctedsheets
* I
References
Antia, N. J., C. D. McAllister, T. R. Parsons, K. Stephens, and 1. D. H.
Strickland. 1963. Further measurements of primary production using alarge volume plastic sphere. Limnol. Oceanogr. 8:166-183.
Beyers, R. J., J. Latimer, H. T. Odum, R. B. Parker, and N. E. Arm-strong. 1963. Directions for determinations of changes in carbondioxide concentration from changes in pH. Publ. Inst. Mar. Sci. Univ.Texas. 9:454-489.
Bunt, J. 1965. Measurements of photosynthesis and respiration in amarine diatom with the mass spectrometer and with carbon-14. Nature207:1373-1375.
Carlson, R. E. 1977. A trophic state index for lakes. Limnol.Oceanogr. 22(2):361-369.
Dillon, D. J. and F. H. Rigler. 1974. The phosphorus chlorophyllrelationship in lakes. Limnol. Oceanogr. 19:767-773.
Findenegg, I. 1965. Relationship between standing crop and primaryproductivity. In: Primary Productivity in Aquatic Environments. C. R.Goldman (ed.). Mem. Ist. Ital. Idrobiol. 18 Suppl., University ofCalifornia Press, Berkeley. pp. 273-289.
Fogg, G. E. 1965. Algal cultures and phytoplankton ecology. Universityof Wisconsin Press, Madison, Wisconsin.
Fruh, E. G., H. M. Stewart, G. F. Lee, and G. A. Rohlich. 1966.Measures of eutrophication and trends. J. Wat. Pollut. Control Fed.38(8): 1237-1258.
Jones, J. R. and R. W. Bachmann. 1976. Prediction of phosphorus andchlorophyll levels in lakes. J. Water Pollut. Control Fed. 48(9):2176-2182.
Kalff, J. and R. Knoechel. 1978. Phytoplankton and their dynamics inoligotrophic and eutrophic lakes. Ann. Rev. Ecol. Syst. 9:475-495.
Lambou, V. W., L. R. Williams, S. C. Hern, R. W. Thomas, and J. D.Bliss. 1976. Prediction of phytoplankton productivity in lakes. In:Proceedings of the Conference on Environmental Modeling and Simulation,EPA 600-9/76-016. pp. 696-700.
Lund, J. W. G. 1964. Primary production and periodicity of phyto-
plankton Verb. Int. Vet. Limnol. 15:37-56.
Lund, 3. W. G. and J. F. Talling. 1957. Botanical limnological methodswith special reference to the algae. Bot. Rev. 23:489-583.
Mackereth, F. J. 1953. Phosphorus utilization by Asterionella formosaHass. J. Exp. Bot. 4:296-313.
Mullin, M. M., P. R. Sloan, and R. W. Eppley. 1966. Relationshipbetween carbon content, cell volume, and area in phytoplankton. Limnol.Oce nogr. 11(2):307-311.
14
. ../. ,
Munawar, M. and A. Nauwerck. 1971. The composition and horizontaldistribution of phytoplankton in Lake Ontario during the year 1970. In:Proc. 14th Conf. Great Lakes Res., Int. Assoc. Great Lakes Res.pp. 69-78.
Munawar, M., P. Stadelmann, and I. F. Munawar. 1974. Phytoplanktonbiomass, species composition and primary production at a nearshore andmidlake station of Lake Ontario during IFYGL. Proc. 17th Conf. GreatLake Res. Internat. Assoc. Great Lakes Res. pp. 629-652.
Nalewajko, C. 1966. Dry weight, ash and volume data for some fresh-water planktonic algae. J. Fish Res. Bd. Canada. 23(8):1285-1288.
Nauwerck, A. 1963. The relationships between zooplankton and phyto-plankton in Lake Erken. Symb. Bot. Uppsal. 17(5):1-163.
Odum, E. P. 1971. Fundamentals of Ecology. Third Edition. W. B.Saunders Company, Philadelphia.
Paasche, E. 1960. On the relationship between primary production and
standing stock of phytoplankton. J. Cons. Int. Explor. Mer. 26:33-48.
Rich, P. H. and R. G. Wetzel. 1978. Detritus in the lake ecosystem.The Amer. Natur. 112(982):57-71.
Rodhe, W., R. A. Vollenweider, and A. Nauwerck. 1958. The primary pro-duction and standing crop of phytoplankton. In: Perspectives in MarineBiology. A. A. Buzzati - Traverso (ed.). University of CaliforniaPress, Berkeley. pp. 299-322.
Ryther, J. 1954. The ratio of photosynthesis to respiration in marineplankton algae and its effect upon the measurement of productivity.Deep-Sea Res. 2:134-139.
Ryther, J. H. and C. S. Yentsch. 1957. The estimation of phytoplanktonproduction in the ocean for chlorophyll and light data. Limnol.Oceanogr. 2:281-286.
Smayda, T. J. 1965. A quantitative analysis of the phytoplankton ofthe Gulf of Panama II: On the relationship between C assimilation and14diatom standing crop. Inter-American Tropical Tuna Commission Bulletin.9(7):467-531.
Smayda, T. J. 1978. From phytoplankters to biomass. In: PhytoplanktonManual. A. Sournia (ed.). United Nations Educational, Scientific andCultural Organization, Paris. pp. 273-279.
Soeder, C. J., J. F. Talling, and I. Baak. 1969. Dry weight and ashcontent. In: A Manual on Methods of Measuring Primary Production inAquatic Environments. I.B.P. Handbook No. 12. Blackwell ScientificPublications, Oxford and Edinburgh. pp. 18-21.
Spangler, F. L. 1969. Chlorophyll and carotenoid distribution andphytoplankton ecology in Keystone Reservoir, Tulsa, Oklahoma. Ph.D.dissertation. Oklahoma State University.
15
Steemann-Nielson, E. 1963. Productivity, definition and measurement.In: The Sea, Vol 2. M. H. Hill (ed.). Interscience, New York.pp. 129-164.
Strathmann, R. E. 1967. Estimating the organic carbon content of phyto-plankton from cell volume or plasma volume. Limnol. Oceanogr. 12(3):411-418.
Strickland, .. I). H. 1960. Measuring the production of marine phyto-plankton. Bulletin No. 122. Fish Res. Board of Canada, Queens Printer,Ottawa, Canada.
Taylor, W. D., L. R. Williams, S. C. Hero, and V. W. Lambou. 1979.Phytoplankton Water Quality Relationship in U. S. Lakes. Part VII.Comparison of some new and old indices and measurements of trophicstate. EPA-600/3-79-079. U. S. Environmental Protection Agency,Las Vegas, Nevada.
Verduin, J., L. R. Williams, and V. W. Lambou. 1976. Components con-tributing to light extinction in natural waters: Method for isolation.U. S. Environmental Protection Agency. National Eutrophication SurveyWorking Paper No. 369.
Weber, C. 1. (ed.). 1973. Biological field and laboratory methods formeasuring the quality of surface waters and effluents. EPA-670/4-73-001. National Environmental Research Center Office of Research andDevelopment, U. S. Environmental Protection Agency, Cincinnati, Ohio.
Williams, L. R., V. W. Lambou, S. C. Hem, and R. W. Thomas. 1978.Relationships of productivity and problem conditions to ambient nutri-ents: National Eutrophication Survey findings for 418 eastern lakes.EPA-600/3-78-002. U. S. Environmental Protection Agency, Las Vegas,Nevada.
Wright, J. C. 1959. Limnology of Canyon Ferry Reservoir. II. Phyto-plankton standing crop and primary production. Limnol. Oceanogr.4(3):235-245.
Yentsch, C. S. 1963. Primary production. Oceanogr. Mar. Biol. Ann.Rev. 1:157-175.
16
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D-R19i 4 3 ESTIMTING PHYTOPLNKTON BIOMSS ND PRODUCTIITY(U)ARMY ENGINEER IRTERWdAYS EXPERIMENT STATION YICKSBURG HS71
ENIRONMENTAL LAB J J JANIK ET AL. JUN 81
I UNCLASSIFIED WES/MPIE-8i-2 F/G 616 NL
I1LIL Ia.-
NWI 111112.
MICROCOPY RESOLUTION TEST CHARTNATIONAL BUREAU OF STANDARDS- 1963-A
SUPPL EMENTAR#
INFRMATIONK
.. . y W.. . . . . . . . .. . .. . . . . . . . . . . . .
DEPARTMENT OF THE ARMYWATERWAYS EXPERIMENT STATION. CORPS OF ENGINEERS
~P.O. BOX 631
VICKSBURG, Mississippi 3016
WEEV 1 1 March 1985
* N Errata Sheet
No. 2
* ENVIRONMENTAL & WATER QUALITY OPERATIONAL STUDIES
ESTI14ATING PHYTOPLANKTON BIOMASS AND PRODUCTIVITY
Miscellaneous Paper E-81-2
June 1981
* Table 1, Sheets 1-7: Replace with inclosed corrected sheets.
HYDRAULIC$ GEOTECHNICAL STRUCTURES ENVIRONMENTAL COASTAL ENGINEERINGLABORATORY LABORATORY LABORATORY LABORATORY RESEARCH CENTER
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