Journal of Plankton Research Vol.18 no.4 pp.513-520,1996
Live sieving of freshwater zooplankton: a technique for
monitoring community size structure
Jaromir Seda and Iva Dostalkova1
Hydrobiological Institute, Czech Academy of Sciences, Na Sadkach 7 and
'Biomathematical Laboratory, Czech Academy of Sciences, Branisovska 34,
CR-370 05 Ceske Budejovice, Czech Republic
Abstract. A simple method is described for a quick determination of the size structure of zooplankton
communities. This is based on sieving of a live sample, using one or two sieves of known mesh size, and
determining the dry weight of the size fractions. Size separation by live sieving is validated statistically
on Daphnia galeata, a common planktonic cladoceran, by comparing size-sieved fractions against direct
microscopic measurements of individuals. A non-linear model was used for assessment of sieving statistics. The sieving technique facilitates the gathering of size-structured biomass data for zooplankton
for routine monitoring or long-term studies.
Introduction
There is a need for a quick but accurate technique for determining the abundance
and size structure of zooplankton samples in order to encourage quantitative
plankton studies whilst reducing the time-consuming procedures of counting and
sizing individual animals. The introduction of chlorophyll a as a measure of algal
biomass was a step forward for phytoplankton ecology not copied for the zooplankton community, although relatively quick techniques were developed to estimate individual weights of species. Convenient ways of determining the in situ
biomass of whole zooplankton communities or its constituent parts (e.g. cladocerans and copepods) were introduced in International Biological Programme
(IBP) times, using dry weight, protein nitrogen or carbon (Edmondson and Winberg, 1971; McCauley, 1984; Wetzel and Likens, 1991). Even crude techniques,
such as settled volume, can yield useful information, as for the 50 year zooplankton
time series from Lake Windermere (George and Harris, 1985).
The technique described here is based on the use of live sieving to separate individuals of different size according to how they pass through the sieve mesh. If the
technique works well, it would be useful for routine monitoring and long-term
studies to be able to quantify changes in the community size structure.
Sorting by sieving is an important procedure in benthic studies and there is some
experience on the use of different meshes for sorting the phytoplankton community (Hinga et al., 1979; Berman and Kimor, 1983), but only a few attempts are
recorded for the zooplankton community (Ejsmont-Karabin, 1978), apart from
papers on the capture characteristics of plankton nets (Smith et al., 1968; Evans
and Sell, 1985).
Sieving has been used earlier to size fraction zooplankton in the field (Hrb£cek
et al., 1978,1986; Fott et al., 1980; Magnessen, 1989) or for experimental purposes
(Korinek, 1966; McCauley and Briand, 1979; Edley and Law, 1988) but without
any check on the efficiency of the sieving procedure.
© Oxford University Press
513
J.Seda and I.Dostalkova
The aim of this paper was to describe and test the technique of live sieving, using
a common planktonic species and several mesh sizes, to assess the probabilities of
the size ranges that pass through the different meshes and how well zooplankton
size indices, based on live sieving, predict average length.
Method
Material for evaluation of the efficiency of the sieving technique
The zooplankton communities used for testing and validating the live sieving technique were collected using a 200 u.m mesh Apstein plankton net from a wide range
of lakes and reservoirs in Great Britain and the Czech Republic in order to ensure
a wide range of size structure and species diversity. Fourteen lakes and 17 reservoirs were sampled in both countries. In all cases, at least two vertical net hauls
were combined to form one sample and two samples were taken from each locality.
Both samples were usually divided into four size fractions by live sieving
through three sieves with different mesh of 1.0,0.71 and 0.42 mm. The size-defined
fractions from one sample were preserved in 4% formaldehyde, whereas the sizedefined fractions from the second sample were used for direct estimates of dry
weight biomass.
To establish the sieving statistics of a known species, Daphnia galeata was
chosen because it was present in the vast majority of samples collected. Between
150 and 200 Daphnia individuals were randomly selected from each formaldehyde-preserved zooplankton size fraction for microscopic measurement using
an eye piece micrometer. Two length measurements were taken: the body length
from the base of the tail spine to the top of head and the carapace length from the
base of the tail spine to the proximal margin of the carapace. In all, 31 sieveprocessed samples and the length of 10 308 individuals of D.galeata were measured
for assessment of the sieving characteristic of the species.
Statistical analysis
The size distributions of 10 308 measured individuals of D.galeata were analysed
for each of the sieve-processed fractions, greater and smaller than the sieve mesh.
The individual sizes were sorted into defined size classes and the proportion (i.e.
probability) of that size class which passed through or was retained on the sieve
was calculated. The relationship between daphnid size class and probability of
passage through the sieve was determined by non-linear regression analysis (Zar,
1984). We determined empirically the 'optimal' width of the size class to use in
order to obtain a smooth distribution curve. A size class width of 0.06 mm was
found to be the best and yielded as many as 32-40 size classes, depending on the
maximal size of daphnids present.
Results and discussion
The sieving characteristics for D.galeata are plotted in Figure 1 as curves of the
probability of passage (v) for different sizes of animals (L) through each size of
sieve which come from non-linear regressions (Table I) of the form:
514
Live sieving of freshwater zooplankton
1.0
( L - a,)
0.8 >
£1
= 1- e
0.6 0.4 0.2 0.0
r
i
0.4
2
i
0.6
'
i
0.8
'
i
1.0
'
i
1.2
'
i
1.4
'
i
1.6
DAPHNIA CARAPACE LENGTH
CO
•
i
1.8
2.0
(mm)
D-
o
E-
3
5
CD
o
0.0
0.4
0.6
0.8
1.0
1.2
1.4
1.6
DAPHNIA TOTAL BODY LENGTH
1.8
2.0
(mm)
Fig. 1. Distribution curves showing the probability of passing through the sieve for D.gateata of denned
size. Three sieve mesh sizes were evaluated: 0.42,0.71 and 1.00 mm.
y = 1 - e"
(1)
where a, is the intercept on the jc-axis and a2 is the slope of the regression.
Regressions are given for both kinds of lengths measured and for each of three
sieve sizes tested. Table I shows that the increasing length of the largest daphnid
retained increased with sieve size. The probability distribution curves are steeper
for carapace length than for total body length (Figure 1) which is a favourable
feature as the steeper the curve, the more precise the separation of sizes by live
sieving.
It is possible that neither body length nor carapace length is a good measure
of the size-related characteristics that determine passage through the sieve mesh
during live sieving. Carapace width is more likely to be important and this is
515
J.Seda and I.Doslalkova
Table I. The statistics of non-linear regression (y = \ - e"- ~ V2'"2) relating the probability of passage
through the sieve for D.galema (y) to Daphnia size (L) in millimetres. The shape of the resulting curves
is presented in Figure 1
Sieve
a.
SD
SD
RMS
(mm)
Range of
(mm)
L = carapace
0.42
0.71
1.00
0.826
1.260
1.435
0.002
0.011
0.004
0.049
0.118
0.096
0.0001
0.007
0.001
33.06
38.46
16.88
0-0.826
0-1.260
0-1.435
L = total body
0.42
0.71
1.00
1.114
1.717
1.980
0.003
0.010
0.007
0.075
0.224
0.151
0.0003
0.008
0.001
22.42
34.98
9.22
0-1.114
0-1.717
0-1.980
a, and a2 are parameters of the non-linear equation; RMS is residual mean square.
allometrically more related to carapace length than to total body length, especially
in a cyclomorphic species like D.galeata where total body length includes a helmet.
This may be the reason for the steeper curves of carapace length.
A nomogram (Figure 2) was constructed for predicting the most reliable sieve
size to use to separate particular sizes of D.galeata, knowing the sieving efficiency
of that size in different sieve meshes (Figure 1). We assume that there is a linear
relationship between mesh size and the regression constant a, (intercept on the
x-axis or the size of animal with zero probability passage). This linear relationship
together with equation (1) gives a predictable relationship between mesh size and
Daphnia length. Figure 2 presents the resulting nomogram of nine probability isolines (10-90% efficiencies) for a wide range of meshes and Daphnia size. For
example, to sieve Daphnia of 0.9 mm body length, or smaller, from a community
sample or culture, 90% efficiency can be obtained by using a mesh sieve of 0.6 mm.
As in Figure 1, the steepness of the isolines in Figure 2 is greater for carapace
length than for total body length. Carapace length is, therefore, a better predictor
for size separation of D.galeata.
It seemed likely that the sieving characteristics for other Daphnia species and
perhaps for the other cladocerans would be similar to those illustrated in Figure 1.
For this reason, live sieving for size was applied to samples from zooplankton communities which differed greatly in the size of dominant Daphnia species. With our
approach, we could express the size structure of a zooplankton community by
means of two simple indices: (i) as a simple proportion of large-sized cladocerans
(retained by a 710 p,m sieve) in total cladoceran or total zooplankton biomass and
(ii) as a cladoceran-size slope index. The cladoceran-size slope index is defined as
the slope of a linear regression of the cumulative proportion of cladoceran biomass
retained on three meshes (200,710 and 1000 jim) against the log,0 of the mesh size,
including that of the plankton net (see Figure 3). The slope index is always negative, ranging from -2.0 to -0.2, and the more negative the index, the smaller bodied
the zooplankton community. The slope index was a more sensitive measure than
the simple index of the proportional large-bodied biomass.
The comparison of slope indices from a range of zooplankton communities with
the average body length of the whole cladoceran component (including Bosmina
516
Live sieving of freshwater zooplankton
a
tsi
I—(
0.4
S
0.6
0.8
1.0
1.2
1.4
1.6
DAPHNIA CARAPACE LENGTH
1.8
2.0
(mm)
Q
l
r
Q
W
o
u
0.4
0.6
0.8
1.0
1.2
1.4
1.6
DAPHNIA TOTAL BODY LENGTH
1.8
2.0
(mm)
Fig. 2. Nomogram for the prediction of the most reliable sieve mesh size for size separation of D.galeata, knowing the efficiency of sieving for particular Daphnia size. Nine isolines for 10-90% efficiency
of sieving are distinguished, i.e. efficiency for Daphnia that are expected to be sieved out.
sp.) is given in Figure 4 and demonstrates a significant linear regression
(P < 0.001). As well as being a significant regression, most of 14 localities fall
within the 95% confidence limits and the slope is nearly one (Table II). The slope
index is the most robust of the community size indices because although the other
two regressions in Table II are statistically significant, they are not as sensitive
(slopes of 0.016). Figure 4 shows that the linear relationship between body length
and slope index applies to at least four species of Daphnia as well as to other
cladoceran genera.
Figure 4 provides a surprisingly good fit between directly measured length and
indirectly measured dry weight indices for 14 zooplankton communities that dif517
J.Seda and I.Dostalkova
sieve
§ 1000
sieve
§ 710 fj.m
I
0.00
2.30
log
2.85 3.00
(mesh size)
Fig. 3. Illustration of the computation of cladoceran-size slope index. There are three sieve-processed
fractions which resulted from the application of two sieves with different mesh sizes (0.71 and 1.00 mm).
A linear regression of cladoceran biomass in size fractions against the log10 of the mesh size, including
that of the plankton net, gives a calculated slope which provides a useful index for characterizing the
average body size structure of the sample.
fered widely in species composition and size structure. The figure demonstrates the
efficacy of size fractioning using a mesh size of 710 \im, as introduced by Hrbdcek
in the early 1970s, for separating large-bodied from small-bodied zooplankton.
The 710 |xm sieve is capable of separating out large-sized species like Daphnia
x,
w
o
2
Main components of
cladoceran community:
^
- 0 .5
*
p-
o
*
D. pulicarla
O D. *.!<•. ta
w
-J
. •
/ A
D. magna
/
D. cucullata and
other small cladocerans
7
/
- ry
- 1 .0
en
I
0 /^^?
/W o
w
en
®
- 1 .5
/ *
T2 -
y/
- 2 .0
(*—1
0.4
1-—-1
0.8
1
1.2
1
1
1.6
0.91
1—
2.0
AVERAGE CLADOCERAN BODY LENGTH
2.4
(mm)
Fig. 4. Comparison between two ways of expressing zooplankton size structure: (i) cladoceran-size
slope index; (ii) average body length of all cladoceran species presented in the sample. Fourteen greatly
differing zooplankton communities were compared and cladoceran species composition is illustrated
by combinations of symbols used. A linear regression line, including the 95% confidence band, is
plotted.
518
Live sieving of freshwater zooplankton
Table II. The statistics of linear regression (y = kx + q) relating the average body length of all cladocerans in a sample (y) to the three size indices based on sieving fractionation (jr). The fraction of large
cladocerans was separated on a 0.71 mm sieve
Compared size-index
k (95% CI)
x = cladoceran-size slope index 0.969 (± 0.188)
x = % of large cladocera in
total cladoceran biomass
0.016 (± 0.003)
x = % of large cladocera in
total zooplankton biomass
0.016 (± 0.004)
q
RMS
r2
P
2.42
0.024
0.91
<0.001
0.59
0.030
0.89
<0.001
0.77
0.041
0.85
•cO.001
k and q are parameters of the linear equation; RMS is the residual mean square; r2 is the coefficient
of determination.
longispina, D.pulicaria, D.pulex and D.magna with 80% efficiency. However,
there are ecological situations (such as highfishpredation pressure) when the common and ubiquitous D.galeata is not retained on the 710 |xm mesh and a smaller
mesh needs to be included in the more complex slope index.
Nevertheless, even the simpler indices based on biomass proportions of largesized cladocerans give reliable assessment of the zooplankton size structure and
the ecological situation with a dominance of large Daphnia spp. (Kerfoot and
DeMott, 1984; Pace etal., 1990; Seda and Duncan, 1994). Thus, although the earlier
applications of the sieving technique for estimating zooplankton size structure did
not include tests on how well it separated animal sizes (Baudoin and Ravera, 1972;
Hrbdcek etal., 1978,1986,1994; Magnesen, 1989), our results demonstrate not only
the usefulness of the technique, but also its reliability and accuracy, when carefully
applied.
Acknowledgements
This study was partially supported by research grant no. 6017503 from the Czech
Academy of Sciences G.A. Fund. The final version of the paper was completed
whilst J.S. was working at Royal Holloway College, University of London, with the
support of the University of London's T.G.Masaryk Fund. The authors thank Dr
A.Duncan of the Hydroacoustic Unit, Royal Holloway Institute for Environmental Research, for stimulating criticisms and language corrections.
References
Baudoin.M.F. and Ravero.O. (1972) Weight, size, and chemical composition of some freshwater zooplankters; Daphnia hyalina (Leydig). Limnol. Oceanogr., 17, 645-649.
Berman,T. and Kimor,B. (1983) A large-scale filtration apparatus for net plankton sampling. J. Plankton Res., 5,111-116.
Edley,M.T. and Law,R. (1988) Evolution of life histories and yields in experimental populations of
Daphnia magna. Biol. J. Linn. Soc, 34,309-326.
Edmondson,W.T. and Winberg.G.G. (1971) A Manual on Methods for the Assessment of Secondary
Productivity in Fresh Waters. IBP Handbook No. 17. Blackwell, Oxford, 358 pp.
Ejsmont-KarabinJ. (1978) Studies on the usefulness of different mesh-size plankton nets for thickening zooplankton. Ekol. Pol., 26,479-490.
Evans,M.S. and Sell,D.W. (1985) Mesh size and collection characteristics of 50-cm diameter conical
plankton nets. Hydrobiologia, 122,97-104.
FottJ., Pechar,L. and Praz4kova\M. (1980) Fish as a factor controlling water quality in ponds. In
BaricaJ. and Mur,L.R. (eds), Hypertrophic Ecosystems. Developments in Hydrobiology, Vol. 2,
Kluwer, Dordrecht, pp. 255-261.
519
J.Seda and I.Dostalkova
George,D.G. and Harris.G.P. (1985) The effect of climate on long-term changes in the crustacean zooplankton biomass of Lake Windermere.U.K. Nature, 316,536-539.
Hinga.K.R., Davis.P.G. and SieburthJ.McN. (1979) Enclosed chambers for the convenient reverse
flow concentration and selective filtration of particles. Limnol. Oceanogr., 24.536-540.
Hrbdcek J.. Desortova.B. and PopovskyJ. (1978) Influence of thefishstock on the phosphorus-chlorophyll ratio. Verh. Int. Ver. Limnol.,20, 1624-1628.
HrtacekJ., Albertova.O., Desortova.B., GottwaldovS.V. and PopovskyJ. (1986) Relation of the zooplankton biomass and share of large cladocerans to the concentration of total phosphorus, chlorophyll a and transparency in Hubenov and Vrchlice Reservoirs. Limnologica (Berlin), 17, 301-308.
HrbacekJ., Albertova.O., Desortova.B., Gottwaldova.V., KomarkovaJ., KopacekJ., PopovskyJ.,
SedaJ. and Vyhn«ilek,V. (1994) Overshooting phenomenon of chlorophyll-a concentrations and
yearto year variation of thefishimpact on zooplankton./Ircfr. Hydrobiol. Beih. Ergebn. Limnol. ,40,
175-184.
Kerfoot.W.C. and DeMott.W.R. (1984) Food web dynamics: dependent chains and vaulting. In
Meyers,D.G. and StricklerJ.R. (eds), Trophic Interactions Within Aquatic Ecosystems. American
Association for the Advancement of Science, New York, pp. 347-382.
Korinek,V. (1966) The production of adult females of Daphnia pulicaria Forbes in a carp pond estimated by a direct method. Verh. Int. Ver. Limnol., 16,386-391.
Magnesen.T. (1989) Vertical distribution of size-fractions in the zooplankton community in Lindaspollene, Western Norway. 1. Seasonal variations. Sarsia, 74,59-68.
McCauley.E. (1984) The estimation of the abundance and biomass of zooplankton in samples. In
DowningJ.A. and Rigler.F.H. (eds), A Manual on Methods for the Assessment of Secondary Productivity in Fresh Waters. Blackwell, London, pp. 228-265.
McCauley.E. and Briand.F. (1979) The impact of zooplankton on the dynamics of phytoplankton
species richness:fieldtest of the predation hypothesis. Limnol. Oceanogr., 1A, 243-252.
Pace.M., MacManus.G.B. and Findlay.S.E.G. (1990) Planktonic community structure determines the
fate of bacterial production in a temperate lake. Limnol. Oceanogr., 35, 795-808.
SedaJ. and Duncan.A. (1994) Lowfishpredation pressure in London reservoirs: II. Consequences to
zooplankton community structure. Hydrobiologia, 291,179-191.
Smith.P.E., Counts.R.C. and Clutter.R.I. (1968) Changes infiltrationefficiency of plankton nets due to
clogging under tow. J. Cons. Perm. Int. Explor. Mer, 32,232-248.
Wetzel.R.G. and Likens.G.E. (1991) Limnological Analyses. Springer-Verlag, New York, 391 pp.
ZarJ.H. (1984) Biostatistical Analysis. Prentice-Hall, Englewood Cliffs, NJ, 718 pp.
Received on May 15, 1995; accepted on November 16, 1995
520