Grazer control and nutrient limitation of phytoplankton biomass in two Australian reservoirs

Freshwater Biology (1997) 38, 49–65

Grazer control and nutrient limitation ofphytoplankton biomass in two Australian reservoirs

V L A D I M I R M A T V E E V * A N D L I L I A N M A T V E E VAMurray-Darling Freshwater Research Centre and CRC for Freshwater Ecology, PO Box 921, Albury 2640, Australia*Author to whom correspondence should be sent at present address: CSIRO Land and Water, c/o Water Resources Centre, 1345Ipswich Road, Rocklea, Queensland 4106, Australia

S U M M A R Y

1. Grazer and nutrient controls of phytoplankton biomass were tested on tworeservoirs of different productivity to assess the potential for zooplankton grazing toaffect chlorophyll/phosphorus regression models under Australian conditions.Experiments with zooplankton and nutrients manipulated in enclosures, laboratoryfeeding trials, and the analysis of in-lake plankton time series were performed.2. Enclosures with water from the more productive Lake Hume (chlorophylla 5 3–17.5 µg l–1), revealed significant zooplankton effects on chlorophyll a in 3/6,phosphorus limitation in 4/6 and nitrogen limitation in 1/6 of experimentsconducted throughout the year. Enclosures with water from the less productiveLake Dartmouth (chlorophyll a 5 0.8–3.5 µg l–1), revealed significant zooplanktoneffects in 5/6, phosphorus limitation in 5/6 and nitrogen limitation in 2/6 ofexperiments.3. While Lake Hume enclosure manipulations of the biomass of cladocerans(Daphnia and Diaphanosoma) and large copepods (Boeckella) had negative effects,small copepods (Mesocyclops and Calamoecia) could have positive effects onchlorophyll a.4. In Lake Hume, total phytoplankton biovolume was negatively correlated withcladoceran biomass, positively with copepod biomass and was uncorrelated withtotal crustacean biomass. In Lake Dartmouth, total phytoplankton biovolume wasnegatively correlated with cladoceran biomass, copepod biomass and totalcrustacean biomass.5. In both reservoirs, temporal variation in the biomass of Daphnia carinata alonecould explain more than 50% of the observed variance in total phytoplanktonbiovolume.6. During a period of low phytoplankton biovolume in Lake Hume in spring–summer 1993–94, a conservative estimate of cladoceran community grazing reacheda maximum of 0.80 day–1, suggesting that Cladocera made an importantcontribution to the development of the observed clear-water phase.7. Enclosure experiments predicted significant grazing when the Cladocera/Phytoplankton biomass ratio was greater than 0.1; this threshold was consistentlyexceeded during clear water phase in Lake Hume.8. Crustacean length had a significant effect on individual grazing rates in bottleexperiments, with large Daphnia having highest rates. In both reservoirs, meancrustacean length was negatively correlated with phytoplankton biovolume. Theobserved upper limit of its variation was nearly twice as high compared to otherworld lakes.

© 1997 Blackwell Science Ltd 49

50 V. Matveev and L. Matveeva

Introduction

The relationships between inputs of phosphorus (P) ation seemed to contradict the findings of Quiros(1990) so we decided to re-test the role of grazingand chlorophyll (Chl) a, or total P and Chl a haveunder conditions prevailing in another region of thebeen used for the prediction of lake trophic state andSouthern Hemisphere—South-Eastern Australia.for lake restoration measures (review by Reynolds,

Different indices have been suggested for assessing1992). However, because of logarithmic scale andgrazing effects at the level of whole lakes. Lamperthigh residual variance, these relationships predict(1988) used total zooplankton biomass to predictsignificant decline in algal abundance only when P-declines of phytoplankton in lakes due to grazing. Hereduction is strong: Chl a can vary as much as twosuggested a threshold of 1.5 g m–2 of zooplanktonorders of magnitude for a given constant P-value forbiomass to be sufficient to cause a clear-water phase.inter-lake comparisons (Smith, 1982; Mazumder, 1994;Pace (1984) suggested that zooplankton compositionBaigun & Marinone, 1995), or one order of magnitudeand mean body size, but not the absolute biomass,for intra-lake comparisons (Ferris & Tyler, 1985).influences P–Chl a relationships in lakes. ZooplanktonZooplankton grazing may determine a considerablebody length was found to be a good predictor of thepart of this residual variance in Chl a (Carpenter,intensity of grazing and variance in phytoplanktonKitchell & Hodgson, 1985; Carpenter et al., 1995). Inter-biomass in twenty-five North American lakes as welllake comparisons revealed that when grazers are notas in whole-lake experiments (Carpenter et al., 1991,under intensive fish pressure, Chl a increases with1996). The ratios of biomass of zooplankton to phyto-total P at a much slower rate than when they areplankton (McCauly & Kalf, 1981; Gulati, 1990; Jeppesen(Hansson, 1992; Sarnelle, 1992; Mazumder, 1994).et al., 1990), or Cladocera to phytoplankton (SchriverWhile the P–Chl a regression itself can be consideredet al., 1995) have also been used as indices of grazing,the basis for the nutrient-reducing strategy in lakeincreasing in whole-lake biomanipulation experimentsrestoration, the assumption that its residual variancewhere grazing was enhanced by the reduction ofis affected by grazers is important for biomanipulation:planktivorous fish. Zooplankton community grazinga strategy of reducing algal biomass through therates were also estimated for different lakes andmanipulation of fish communities and enhancedcompared with phytoplankton growth (Sterner, 1989;zooplankton grazing (Shapiro & Wright, 1984).Reynolds, 1994).Studies of the role of zooplankton grazing for P–Chl

In the present study, we obtained and analyseda relationships in lakes of the Southern Hemisphere arethe aforesaid indices for two reservoirs of differentless numerous than in the Northern Hemisphere.productivity and performed enclosure experiments inHowever, for ninety-seven Argentine lakes and reser-which zooplankton and nutrients were manipulated.voirs, Quiros (1990) found that mean zooplankton sizeThe following questions were asked: (i) is grazingwas a significant predictor of residual variance in thea significant factor for phytoplankton dynamics inTP–Chl a relationship, suggesting that grazing wasAustralian reservoirs? (ii) is there temporal variationimportant there too. In spite of this, there have beenin the relative roles of grazing vs. nutrient limitationclaims that neither TP-Chl a models of the Northernfor algal biomass? (iii) what is the evidence of theHemisphere (White, 1983; Baigun & Marinone, 1995)potential for biomanipulation in Australian reservoirsnor the concept of biomanipulation/top-down controlcompared to other regions of the world?(Boon et al., 1994) are likely to be applicable to regions

of the Southern Hemisphere. In particular, Boon et al.(1994) expressed a view that in Australian inland Methodswaters, grazing on phytoplankton is unlikely to be

Description of reservoirsenhanced by biomanipulation because efficientCladocera grazers are rare, while zooplankton usually Two large reservoirs in South-Eastern Australia haveconsists of less efficient calanoids and rotifers. They been studied: Lake Hume (Murray River system, Newalso speculated that cyanobacteria may have detri- South Wales) and Lake Dartmouth (Mitta Mitta Rivermental effects on local zooplankton, restraining system, Victoria). At its full capacity, Lake Hume

(147°029E, 36°059S) has a surface area of 202.5 km2, agrazers’ growth. Their argument about biomanipul-

© 1997 Blackwell Science Ltd, Freshwater Biology, 38, 49–65

Grazing in Australian reservoirs 51

maximum depth of 41.4 m, and its water surface is at biomass according to equations given in Bottrell et al.(1976) for taxonomically similar species.an altitude of 192 m above sea level. The catchment

of the lake is mainly farmland with patches of eucalypt Phytoplankton was collected at one middle-lakestation with a 10-m hose (25 mm inside diameter). Aforests. The depth of the euphotic zone (1% of surface

irradiance) is usually between 4 and 7.5 m. Mean weight was attached to the end of the hose to ensurestrictly vertical submergence. On taking a sample, theeuphotic zone concentrations of Chl a in the lacustrine

area of the reservoir vary from 3.0–17.5 µg l–1, total P content of the hose was emptied into a bucket and,after a thorough mixing, 100 ml of water were pre-from 20 to 50 µg l–1 and total N from 220 to 600 µg

l–1. It is a monomictic lake with water temperatures served with acid Lugol’s solution. In the laboratory,phytoplankton of this sample was concentrated inin winter above 9°C and with a distinct stratification

of the water column in summer. graduated cylinders for at least 10 days, and thencounted in subsamples in a 0.05 ml graduated cellAt its full capacity, Lake Dartmouth (147°309E,

36°309S) has a surface area of 63 km2, a maximum under a compound microscope. Phase contrast wasused for counting diatoms with thin, poorly visibledepth of 170 m, and its water surface is at an altitude

of 486 m above sea level. The catchment is mainly walls (Rhizosolenia and Attheya). In total, 400–1000 cellsof phytoplankton were counted in each sample. Celleucalypt forests. The depth of the euphotic zone is

usually between 9 and 12 m. Mean euphotic zone Chl biovolumes were estimated by approximations tosimilar geometric solids.a concentrations in the lacustrine area of the reservoir

vary from 0.8–3.5 µg l–1, total P from less than 10–30 µg l–1 and total N from 120 to 320 µg l–1. The watercolumn in Lake Dartmouth is also stratified in summer, Time series analysiswhile winter temperatures of the upper 30 m areuniform with the seasonal lowest of 9°C. We did not To analyse plankton time series in the lakes, we first

calculated cross-correlations for unsmoothed data tomeasure the temperature below this.determine the time lag in the effect of a given zooplank-ton characteristic on phytoplankton biomass. In all

Plankton sampling and enumerationcases, maximal correlations were found at zero timelags. As sampling intervals were probably too longSamples of both zooplankton and phytoplankton were

taken every 1–3 weeks from September 1993 to for precise time lag identification, zero time lags mighthave meant that delays in responses of phytoplanktonDecember 1994 at two reference middle-lake stations

located in the lacustrine zone of the reservoirs. could take any values less than a sampling interval.For simplicity we assumed that the relationships wereZooplankton was collected by making two 20–0 m

vertical hauls at each station using an Apstein-type contemporaneous and subsequent regression analysiswas performed for zero time lags. Residuals of regres-quantitative plankton net (mesh size 80 µm, 11.5 cm

inside-mouth diameter, speed 1 m s–1). Such a net is sions were tested for autocorrelations. Some relation-ships had autocorrelated residuals, which could be anexpected to have an efficiency of 44% (Shapiro &

Wright, 1984), so a correction factor of 2.3 3 was used indication of spurious serial dependencies. To avoidthem, we split each time series yielding autocorrelatedfor estimates of crustacean abundances. Animals were

preserved with 70% ethanol and stained with Lugol’s residuals into two time series composed of only oddor only even observations. This increased samplingsolution. Four samples collected on a given date were

pooled in the laboratory. Several subsamples were intervals and removed autocorrelations in residuals inmost cases. If such rarefied time series withtaken from the pooled sample and animals were

counted under a dissecting microscope in a 55.6 cm3 independent residuals still produced a significant cor-relation, it was considered as valid evidence of aBogorov chamber until the total number of animals

of a given species reached 50–100 individuals. relationship. However, if in a correlation based onrarefied series the residuals were still autocorrelated,Body lengths of at least twenty animals of each

major size class within each species (1–5 classes) were it was excluded from further analysis. SYSTAT packagewas used for all statistical computations (Wilkinson,measured several times throughout the year. Then

they were used for calculating individual weights and 1990).



Indices of community grazing where light and temperature conditions were main-tained close to the conditions of the epilimnion. The

Total biomass of crustacean zooplankton, the biomass irradiance was set to about 3% of the near-surface,of Cladocera and Copepoda, mean crustacean length underwater irradiance, which has been shown in(MCL) and the Cladocera/Phytoplankton biomass laboratory experiments to provide high growth ratesratio were calculated for each sampling date on both of local strains of Aulacoseira (Melosira) granulatalakes. MCL was a biomass-weighted average: (D. Green, personal communication). After 4 days

of incubation, biomass of zooplankton species wereMCL 5 Σ (Li 3 Bi)/Σ Bi,determined in enclosures. Three litres of water from

where Li 5 mean body length of i-th species of each container were filtered through 80-µm mesh netzooplankton, Bi 5 biomass of i-th species. for that purpose. No preservatives were added to

We used Cladocera rather than total zooplankton in ensure separate counting of live and dead animalsthe numerator of the ratio because in the present study and assessment of the mortality level. As numbers ofCopepoda proved to be an inconsistent predictor of corpses were always scarce, it was assumed that thevariance in algal biomass. As cladoceran biomass was mortality of zooplankton was negligible throughoutexpressed in µg dry weight l–1 for calculations of the the experiments. Other aspects of these experiments,ratio, algal biovolume was converted to the same units the methods of zooplankton manipulations, nutrientusing a coefficient of 0.44 pg µm–3 (Reynolds, 1984). additions, etc., have been described in detail earlier

(Matveev et al., 1994a). As in previous experiments of asimilar design (Lehman & Sandgren, 1985), enclosuresExperiments with manipulated density of zooplanktonwere not replicated with respect to levels of zooplank-and nutrient additionston biomass or types of nutrient additions.

Chl a samples were prepared as previously (MatveevThese experiments were designed to test the relativeimportance of grazer vs. nutrient controls for phyto- et al., 1994a), but a different method of analysis was

used (ISO, 1991) without acidification to correct forplankton biomass in lakes. In each experiment, agradient of zooplankton biomass is created by diluting phaeophytins.or concentrating animals in enclosures with lake water.After a period of incubation, assessment of phyto- Statistics of experimentsplankton response is made. A resulting significant

For statistical analysis of the effects on phytoplanktonnegative correlation between the biomass of zooplank-

biomass in enclosure experiments, Chl a concentrationton and phytoplankton is considered evidence of

was regressed on total zooplankton biomass. Lineargrazer control. The addition of nutrients to some

regressions and product-moment coefficients of cor-enclosures tests the relative extent of nutrient limita-

relation were calculated. Significant regressionstion of phytoplankton. The general idea of this design

(P , 0.05) were considered evidence of zooplanktonwas first proposed by Lehman & Sandgren (1985),

effects. Confidence limits of 99% were constructedhowever, we modified it for the conditions of Aus-

for the regression line. Phytoplankton biomass wastralian reservoirs where diatoms constitute a signific-

considered nutrient-limited if nutrient-enriched con-ant proportion of total phytoplankton. At first sight,

tainers displayed Chl a concentrations above the 99%large enclosures suspended in a lake seem to have the

confidence limits for unenriched containers. To deter-advantage of preserving natural conditions. However,

mine the role of individual grazers, Chl a was alsothe resulting inevitable stagnation of the water inside

considered a variable dependent on the biomass ofthem can cause considerable sinking losses of phyto-

each zooplankton species in the experiments andplankton, especially diatoms (Reynolds, 1984). This

stepwise forward multiple regression analysis wasresults in the distortion of the original community

applied (Sokal & Rohlf, 1981).structure. To circumvent the problem, we reduced thesize of enclosures to 4 l to make them transportable

Grazing rates and Cladocera community grazingand allow for regular overturns and mixing of theircontent (Matveev, Matveeva & Jones, 1994a). Experi- Grazing rates of crustaceans (Daphnia carinata, Boeckella

triarticulata, Diaphanosoma unguiculatum, Ceriodaphniamental containers were delivered to the laboratory



sp. and Moina micrura) were measured on different predominance of diatoms (Aulacoseira granulata, A.sp.,Attheya), while minima with diatoms, cyanobacteria,dates. Lake phytoplankton was offered as food after

a 10-m column of water was collected from the pelagial greens and small flagellates (Fig. 1b).The crustacean community, which accounted for thewith a hose and separated from zooplankton by

filtering through 350-µm mesh net. Experiments were bulk of zooplankton biomass in Lake Hume, wascomposed of Diaphanosoma unguiculatum Gurney,conducted and analysed according to Matveev et al.

(1994a), however, in the present study the duration of Daphnia carinata King, D. lumholtzi Sars, Ceriodaphniasp., Moina micrura Kurz, Bosmina meridionalis Sars,experiments was 8–9 h and bottles with grazers were

overturned and shaken every hour to minimize sedi- Calamoecia ampulla (Searle), Boeckella triarticulata(Thomson) and Mesocyclops notius Kiefer. Zooplanktonmentation of diatoms. The significance of declines in

mean cell concentrations after incubation with grazers biomass peaked during spring–summer when thelargest cladocerans increased in numbers (Diaphano-was estimated using t-test (Matveev et al., 1994a).

Cladoceran community grazing in Lake Hume was soma and D. carinata) and in autumn when the cope-pods were most abundant (Mesocyclops, Boeckella andestimated according to the formula:Calamoecia). The Cladoceran peak coincided with clear-

CG 5 Σ(Gi/Wi)Bi, water phase, while copepods peaked during the high-est phytoplankton abundance (Fig. 1c, d vs. a).where CG 5 cladoceran community grazing rate

In Lake Dartmouth, total phytoplankton biovolume(day–1, proportion of volume cleared in 24 h), Gi 5

remained nearly constant from 1993 until mid-Augustmean grazing rate of an i-th cladoceran, averaged over1994. It started increasing at the end of August andall food items consumed (Table 3) and converted intoreached a peak in October 1994 with a predominance ofl animal–1 day–1, Wi 5 individual dry weight (g) of andiatoms (Rhizosolenia, Cyclotella, Synedra, Asterionella)i-th cladoceran determined allometrically from body(Fig. 2a, b). This was preceded by a decline in totallength (Bottrell et al., 1976), Bi 5 biomass of an i-thbiomass of crustaceans. When crustaceans had highcladoceran (g l–1) observed in the lake on a givenbiomass (mainly due to Daphnia) from October 1993date. We did not include copepods in estimates ofto April 1994 and in December 1994, phytoplanktoncommunity grazing because, at least for some of them,was depressed (Fig. 2,c, d vs. a). Zooplankton biomassthere were indications that their stimulatory effectsin Lake Dartmouth was also dominated by crusta-on algal growth could have exceeded their suppressiveceans. The following species reached countable num-effects. For CG, we used weight-specific rather thanbers: Diaphanosoma unguiculatum Gurney, Daphniaper capita grazing rates, which probably resulted incarinata King, D. lumholtzi Sars, Ceriodaphnia sp., Bos-some underestimation of grazing because of the usemina meridionalis Sars, Calamoecia ampulla (Searle),of relatively large animals in feeding trials. Thus, ourBoeckella triarticulata (Thomson) and Mesocyclopsmethod was conservative with respect to a restrictedthermocyclopoides australiensis (Sars) Kiefer.number of potential grazers included and because of

the use of weight-specific rates.

Correlations between time series

Results Total crustacean biomass was not correlated in timewith phytoplankton biovolume in Lake Hume. TheSeasonal changes in the planktonbiomass of Cladocera was significantly negativelycorrelated with corresponding time series for phyto-In Lake Hume, total biovolume of phytoplankton

peaked in September 1993 (the austral spring) and plankton biovolume. Copepods showed suggestivepositive relationship with phytoplankton biovolumelate February–June 1994 (autumn–winter) (Fig. 1a). In

October–January 1993–94 (spring–summer) a clear- (Fig. 3a, b, c). In Lake Dartmouth, both total crustaceanbiomass, Cladocera and Copepoda biomass were signi-water phase was observed when total phytoplankton

biovolume declined by an order of magnitude com- ficantly negatively correlated with phytoplanktonbiovolume. (Fig. 3d, e, f). Mean crustacean length waspared to the previous peak. A long gradual decline

also took place at the end of 1994 (Fig. 1a). The maxima significantly negatively correlated with phytoplanktonbiovolume in both lakes (Fig. 4). This was primarilyof phytoplankton biovolume were associated with the



Fig. 1 Plankton dynamics in LakeHume in 1993–1994. All curves arebased on 3-point moving averages.(a) Total phytoplankton biovolume.(b) Relative biovolumes of majorgroups of phytoplankton:cya 5 cyanobacteria; dia 5 diatoms;gre 5 green algae; fla 5 smallflagellates. (c) Total crustacean biomass.Dotted horizontal line indicates aminimal threshold level of1.5 g dr. wt m–2 for the biomass ofzooplankton grazers necessary to causeclear-water phase (Lampert, 1988).(d) Relative crustacean biomass:Me 5 Mesocyclops; Bo 5 Boeckella;Da 5 Daphnia; Ca 5 Calamoecia;Di 5 Diaphanosoma. (e) Biomass ratio ofCladocera/Phytoplankton. Dottedhorizontal line indicates minimal ratio(0.1) for significant effects ofzooplankton grazing on phytoplanktonpredicted by enclosure experiments(present study, Fig. 8, abscissa). Notethat the intersections of the observedcurve with the value 0.1 also isolate theperiod of predominance of largeCladocera in zooplankton [verticaldotted lines, (d)], spring-summer peakbiomass of crustaceans in 1993–94 [(c)]and clear-water phase inphytoplankton [(a)].

due to large Daphnia. Its biomass per se was signific- estimates for the effects of relatively mild changes inthe biomass of grazers on Chl a in lake water.antly negatively correlated with phytoplankton bio-

volume, explaining more than 50% of the observedLake Hume. In the austral spring (October 1993), thevariance in phytoplankton biovolume (Fig. 4).manipulation of crustacean biomass in enclosures pro-duced a highly significant negative correlation of thegrazers biomass with Chl a. Nutrient additions had noExperiments with manipulated zooplankton andeffect on Chl a (Fig. 5). At that time, lake phytoplanktonnutrient additionswas dominated by small diatoms, such as Aulacoseira

Manipulated zooplankton biomass varied, on the aver- sp. and Cyclotella. Multiple regression analysis sug-age, by a factor of 5 in each enclosure experiment. It gested that Diaphanosoma and Boeckella were the majorvaried seasonally by a factor of 10 in Lake Hume and grazers (Table 1).

In early summer (December 1993), crustacean bio-33 in Lake Dartmouth. So our experiments provided



Fig. 2 Plankton dynamics in LakeDartmouth in 1993–94. All curves arebased on 3-point moving averages.(a) Total phytoplankton biovolume.(b) Relative biovolumes of majorgroups of phytoplankton:cya 5 cyanobacteria;chry 5 chrysophytes; dia 5 diatoms;gre 5 greens; fla 5 small flagellates.(c) Total crustacean biomass.(d) Relative crustacean biomass:Me 5 Mesocyclops; Ca 5 Calamoecia;Da 5 Daphnia; Di 5 Diaphanosoma.(e) Biomass ratio of Cladocera/Phytoplankton. Dotted horizontal lineindicates minimal ratio (0.1) forsignificant effects of zooplanktongrazing on phytoplankton predicted byenclosure experiments (present study,Fig. 8, abscissa).

mass was again strongly correlated with Chl a in abundant. While total biomass of crustaceans had nosignificant effect on Chl a in February 1994 (Fig. 5),enclosures, while P or P 1 N additions significantly

increased Chl a (Fig. 5). N alone had no significant manipulated density of Mesocyclops was correlatedwith Chl a, explaining 74% of the variance in a positiveeffect. Phytoplankton was dominated by small colon-

ies of Microcystis, cryptomonads, small Aulacoseira sp. linear regression (Table 1) or 86% if a second orderpolynomial fitting was used (Fig. 6). In the latter case,and Sphaerocystis, while multiple regression analysis

suggested Daphnia and Boeckella as principle grazers even if nonlinear interaction of the grazer with itsresource is assumed, for the most of the range ofin the enclosures (Table 1).

In late summer (February 1994), no significant effect Mesocyclops biomass the relationship was still positive.In mid-autumn (April 1994), both grazing and P-of grazing was detected, while P-limitation was very

pronounced when large diatoms were predominant limitation had significant effects on Chl a, while Nadditions did not (Fig. 5). Multiple regression analysis(Aulacoseira granulata and Attheya) and small copepod

grazers such as Calamoecia and Mesocyclops were most suggested that Calamoecia and Daphnia were important



Fig. 3 Correlations between time seriesof crustacean biomass andphytoplankton biovolume in LakesHume and Dartmouth.Lake Hume. (a) Phytoplanktonbiovolume vs. total crustacean biomass(r2 5 0.003, P . 0.10, NS).(b) Phytoplankton biovolume vs.Cladocera biomass: independentresiduals in even time series for whichthe level of significance of theregression, P , 0.01; total r2 5 0.30.(c) Phytoplankton biovolume vs.Copepoda biomass: independentresiduals in even time series for whichP , 0.10; total r2 5 0.23.Lake Dartmouth. (d) Phytoplanktonbiovolume vs. total crustacean biomass:independent residuals in both odd andeven time series for which P , 0.02;total r2 5 0.37. (e) Phytoplanktonbiovolume vs. Cladocera biomass:independant residuals in both odd andeven time series, for which P , 0.05;total r2 5 0.31. (f) Phytoplanktonbiovolume vs. Copepoda biomass:independant residuals in odd timeseries for which P , 0.01; totalr2 5 0.25. Unsmoothed data. For detailssee Methods.

grazers of phytoplankton which, at that time, was a Microcystis, large Staurastrum and Peridinium as wellas cryptomonads, while the principle grazer was indi-mixture of large and small algae (A. granulata, Attheya,

small Aulocoseira sp. and cryptomonads) (Table 1). cated to be Daphnia (Table 2).In early summer (December 1993), grazers’ effectIn early winter (June 1994), neither nutrients nor

grazing seemed to be important, while later (August was significant, as were the effects of N and P whenthey were added separately, but not together (Fig. 7).1994), P or P 1 N had significant effects on Chl a

(Fig. 5). Multiple regression analysis showed significant nega-tive effect of Calamoecia, when phytoplankton con-sisted of Microcystis, Dinobryon and cryptomonads

Lake Dartmouth(Table 2).

In late summer (February 1994), the effect of grazersIn spring (October 1993), the effect of grazing washighly significant, P or N 1 P-additions were signific- was significant, while nutrient additions did not affect

Chl a (Fig. 7). Although total effect of crustaceanant, while N had no effect (Fig. 7). At that time,phytoplankton was dominated by small colonies of community was negative, individual populations had



Fig. 4 Phytoplankton biovolume inLakes Hume and Dartmouth as afunction of mean crustacean length andDaphnia biomass. The regressions onmean crustacean length for both lakeshad independent residuals in odd andeven time series. They were significantat P , 0.001 in Lake Hume andP , 0.05 in Lake Dartmouth. Theregressions on Daphnia biomass hadindependent residuals in odd and eventime series and were significant atP , 0.001 in both reservoirs.Unsmoothed data. For details seeMethods.

contrasting effects on Chl a: Diaphanosoma biomass In late winter (August 1994), the effect of crustaceanbiomass was insignificant, while P- or P 1 N-additionswas negatively correlated while Calamoecia biomasshad a significant effect on Chl a (Fig. 7). Duringpositively correlated with Chl a (Table 2). At that time,this time small copepods were dominant zooplanktonphytoplankton consisted of cryptomonads, Dinobryon,while Staurastrum, Cyclotella, Synedra and crypto-Rhizosolenia, Synedra and Staurastrum.monads were dominant phytoplankton.In mid-autumn (April 1994), Daphnia was likely to

In summary, 3/6 of enclosure experiments suggestedbe the most important grazer responsible for a stronggrazing and 4/6 nutrient limitation of phytoplanktonand significant negative correlation of crustacean bio-in the water of Lake Hume. P-additions had pro-mass with Chl a in Lake Dartmouth. At that time,nounced effects in 4/6 and N-additions in 1/6 ofboth P- and N- additions had significant effects onexperiments. Enclosure experiments with the water ofChl a, and phytoplankton was dominated byLake Dartmouth, suggested significant grazing incryptomonads, Synedra and Staurastrum (Fig. 7,5/6 cases and nutrient limitation of phytoplanktonTable 2).in 5/6 cases. P-additions had pronounced effects inIn winter (June 1994), grazing was again significant5/6 experiments and N-additions in 2/6.as well as P- or P 1 N-additions (Fig. 7). The biomass

of small copepods (Calamoecia and Mesocyclops) wasCladocera/phytoplankton biomass rationegatively correlated with Chl a, when phytoplankton

consisted mainly of Staurastrum, cryptomonads, Rhizo- Enclosure experiments allowed us to define the condi-tions for significant grazing. The proportion of vari-solenia, Dinobryon and Mallomonas (Table 2).



Fig. 5 Results of enclosure experimentswith water from Lake Hume. Final Chla concentration vs. manipulatedcrustacean biomass. Oct 93: r2 5 0.83,P , 0.001; Dec 93: r2 5 0.93, P , 0.001;Feb 94: r2 5 0.32, NS; Apr 94: r2 5 0.73,P , 0.01; June 94: r2 5 0.26, NS;Aug 94: r2 5 0.12, NS.

ance in Chl a explained by manipulated biomass of ratio in the summer of 1993–94 was due to an increasein Cladocera biomass in Lake Hume. When largecrustaceans in enclosures (r2) was plotted vs. the

Cladocera/Phytoplankton biomass ratio (Fig. 8). As cladocerans were abundant in Lake Dartmouth inOctober 1993–April 1994, the ratio was also above 0.1can be seen, there was a strong and significant relation-

ship (r2 5 0.82, P , 0.001). Horizontal dashed line ‘a’, and phytoplankton biomass was very low (Fig. 2e vs.a). In May–August 1994, cladoceran biomass in Lakeseparating data-points for experiments with significant

grazing (above the line) from those where grazing Dartmouth declined, causing a decline in the Clado-cera/Phytoplankton ratio below 0.1. Such conditionswas insignificant (below the line), corresponds to a

Cladocera/Phytoplankton ratio of the order of 0.1 have eventually resulted in a rise in total phytoplank-ton biovolume in September.(Fig. 8). The dynamics of the ratio in Lake Hume

(Fig. 1e) showed, that when its value was above thethreshold of 0.1 (horizontal dotted line) in 1993–94,

Grazing rates of individual grazersclear-water phase was observed (Fig. 1a), providing agood prediction of phytoplankton dynamics in the Of all crustaceans tested, the largest, D. carinata,

(2.8 mm long in our trials) had highest grazing rateslake from our enclosure experiments. The rise of the



Table 1 Dominant species of plankton in Lake Hume experiments with final predictors of multiple forward stepwise regressionanalysis for Chl a (dependent variable) vs. zooplankton biomass (independent variables)

Total cellDate of Dominant biovolume Dominant Predictors and signexperiment phytoplankton (mm3 l–1) zooplankton of impact R2 P

25.10.93 Aulacoseira sp. 0.44 Diaphanosoma Diaphanosoma(–) 0.90 0.001Cyclotella Calamoecia Boeckella(–)

Boeckella

13.12.93 Microcystis 0.18 Daphnia Daphnia(–) 0.97 0.000Cryptomonads Calamoecia Boeckella(–)Aulacoseira sp. BoeckellaSphaerocystis

14.02.94 Aulacoseira 1.35 Calamoecia Mesocyclops(1) 0.74 0.003granulata Attheya MesocyclopsAulacoseira sp. DiaphanosomaCryptomonads

25.04.94 Attheya Aulacoseira 2.11 Calamoecia Calamoecia(–) 0.79 0.01granulata Boeckella Daphnia(–)Aulacoseira sp. MesocyclopsCryptomonads Ceriodaphnia

Daphnia

20.06.94 Aulacoseira 3.02 Boeckella No effects – NSgranulata Attheya CalamoeciaCryptomonads Mesocyclops

22.08.94 Aulacoseira 1.49 Boeckella No effects – NSgranulata CalamoeciaAulacoseira sp. Diaphanosoma

on natural phytoplankton. It consumed all food itemspresent in Lake Hume water at the time of theexperiment with a mean value of 5.15 ml animal–1 h–1

(Table 3). The next largest, Boeckella (1.67 mm) andDiaphanosoma (1.00 mm), also consumed nearly allitems present at mean rates of 1.45 and 0.64 mlanimal–1 h–1, respectively. Smaller crustaceans, such asMoina (0.85 mm) and Ceriodaphnia sp. (0.60 mm), hadmean grazing rates of 1.07 and 0.97 ml animal–1 h–1,respectively. The effect of increasing crustacean lengthon grazing rate was highly significant (one-wayANOVA, F3,20 5 33.9, P , 0.001). Colonies of cyanob-acteria (Microcystis , 50 µm) were grazed at rateswithin 99% confidence limits of the mean rate for allother food items in Daphnia and within 90% limits inBoeckella, suggesting the lack of strong selectivityagainst the cyanobacteria. Grazing on Microcystis infeeding trials was consistent with the results of LakeHume enclosure experiment in December 1993 and ofLake Dartmouth experiment in October 1993: total Chl

Fig. 6 Chlorophyll a concentration as a function of a was significantly negatively affected by manipulatedmanipulated biomass of Mesocyclops: enclosure experiment densities of Daphnia and Boeckella when Microcystiswith Lake Hume water conducted in February 1994. predominated (Tables 1,2, Figs. 5, 7).



Fig. 7 Results of enclosure experimentswith water from Lake Dartmouth. FinalChl a concentration vs. manipulatedcrustacean biomass. Oct 93: r2 5 0.91,P , 0.001; Dec 93: r2 5 0.62, P , 0.02;Feb 94: r2 5 0.64, P , 0.01; Apr 94:r2 5 0.92, P , 0.001; June 94: r2 5 0.69,P , 0.02; Aug 94: r2 5 0.07, NS.

Community grazing in Lake Hume 0.27–0.47 day–1, suggesting that Cladocera were againsignificant contributors to the decline of total phyto-

For periods when the Cladocera/Phytoplankton bio-plankton.

mass ratio exceeded 0.1 in Lake Hume (Fig. 1e), whichwas observed during the lowest algal biovolume(clear-water phases, Fig. 1a) the estimated community Discussiongrazing of Cladocera varied between 0.19 and0.80 day–1. The assumption of sufficiency of the The two reservoirs studied differed in morphology

and productivity. However, our 4-year observations500 ml l–1 day–1 level for continued control of algae bygrazers (Reynolds, 1994) suggests that cladocerans (V. Matveev & L. Matveeva, unpublished work) sug-

gests that the generic composition of both zooplanktonalone could be responsible for maintaining the clear-water phase in Lake Hume from 4 November to 8 and phytoplankton varies little between Lakes Hume

and Dartmouth. The planktonic communities differDecember 1993. During that period their grazingvaried between 0.53 and 0.80 day–1. In October– mainly in total biomass, the relative abundance of

species and biomass dynamics. Our spring–summerDecember 1994, grazing estimates varied from



Table 2 Dominant species of plankton in Lake Dartmouth experiments with final predictors of multiple forward stepwiseregression analysis for Chl a (dependent variable) vs. zooplankton biomasses (independent variables)

Total cellDate of Dominant biovolume Dominant Predictors and signexperiment phytoplankton (mm3 l–1) zooplankton of impact R2 P

31.10.93 Microcystis 0.22 Daphnia Daphnia(–) 0.97 0.000Staurastrum CalamoeciaPeridiniumCryptomonads

20.12.93 Microcystis 0.26 Calamoecia Calamoecia(–) 0.50 0.03Dinobryon DaphniaCryptomonads

28.02.94 Cryptomonads 0.18 Diaphanosoma Diaphanosoma(–) 0.86 0.003Dinobryon Daphnia Calamoecia(1)Rhizosolenia Synedra CalamoeciaStaurastrum

18.04.94 Cryptomonads 0.19 Diaphanosoma Daphnia(–) 0.89 0.000Synedra CalamoeciaStaurastrum Daphnia

Mesocyclops

13.06.94 Staurastrum 0.25 Calamoecia Calamoecia(–) 0.88 0.006Cryptomonads Daphnia Mesocyclops(–)Rhizosolenia MesocyclopsDinobryonMallomonas

15.08.94 Staurastrum 0.22 Calamoecia No effects – NSCyclotella Synedra MesocyclopsCryptomonads

Table 3 Grazing rates of Lake Hume zooplankton (ml animal–1 h–1) measured on mixtures of lake phytoplankton

Daphnia Boeckella Diaphanosoma Ceriodaphnia Moina

Sphaerocystis – – NS 0.63** 1.07*Quadrigula – – – NS NSMicrasterias – – – NS NSClosteriopsis 2.64** 0.55* – NS NSTrachelomonas – – – – –Aulacoseira sp. 4.66*** 0.76** – – NSA.granulata 5.15** 1.37** – NS NSRhizosolenia 6.89*** 2.21*** – 1.30*** NSAttheya 5.45*** 2.48*** – NS NSSynedra 6.27*** 1.59*** – – –Cyclotella 4.55** 0.85* 0.37* NS NSRhodomonas 5.81** 2.13** 0.54* – –Cryptomonas 5.90** 1.42* 1.02* – –Microcystis sp. 4.20*** 1.12** – – –

Mean 5.15 1.45 0.64 0.97 1.07

*P , 0.05, **P , 0.01, ***P , 0.001. NS 5 no significant effect (P . 0.05),– 5 food item not present in lake phytoplankton

observations on other reservoirs of South-Eastern Aus- Thus, these two reservoirs are quite typical for South-Eastern Australia.tralia, covering a gradient of oligotrophic to eutrophic

waters, indicate that plankton composition is similar This study suggests that zooplankton grazing inAustralian reservoirs may be sufficient to affect theto the composition of Lakes Hume and Dartmouth.



In our feeding trials, crustacean size had a significanteffect on grazing rate, while in enclosure experiments,the negative effect on Chl a was often associatedwith the largest crustaceans: Daphnia, Boeckella andDiaphanosoma. This supports previous findings inlaboratory and inter-lake studies that grazing rateincreases with body size (Burns, 1969; Knoechel &Holtby, 1986). At a larger scale, in both unproductiveLake Dartmouth and productive Lake Hume, meancrustacean length was negatively correlated with totalphytoplankton biovolume in support of the view thatzooplankton grazer size is a good predictor of variationin phytoplankton biomass (Pace, 1984; Carpenter et al.,1991, 1996). A peculiar feature of both Australianreservoirs studied was a much higher upper limit ofvariation in mean crustacean length compared to other

Fig. 8 Proportion of variance in Chl a explained by crustacean lakes of the world: more than 2 mm in Lake Humebiomass in enclosure experiments as a function of the and Lake Dartmouth vs. 1.01–1.27 mm in other lakesCladocera/Phytoplankton biomass ratio. Horizontal dashed

(Carpenter et al., 1996). This was largely due to theline ‘a’ corresponds to the minimal significant (P , 0.05) effectof crustacean biomass on Chl a. Note that the projection of this presence in zooplankton of Daphnia carinata, the bio-line from intersection with regression onto abscissa indicates mass of which per se could explain more than 50% ofthe ratio of 0.1 used in Figs 1e and 2e. All data-points for variation in phytoplankton biovolume.experiments with insignificant effects of crustacean biomass on

The potential for biomanipulation, that is reductionChl a are below line ‘a’. Dashed lines along regression 5 99%of algal biomass in lakes by enhancing grazing throughconfidence limits.

fish manipulations, was suggested to depend on crus-tacean body length (Carpenter et al., 1996). As ourresidual variance in Chl–TP regressions as described

for other regions of the world (Quiros, 1990; Sarnelle, findings suggest that the observed grazing effectswere sufficient to make the crustacean length model1992; Mazumder, 1994; Carpenter et al., 1995). At the

scale of our enclosure experiments, conducted with applicable to the conditions of the two reservoirsstudied, we hypothesize that Australian water bodiesthe water of two lakes of contrasting productivity, the

seasonal frequency of significant grazing was nearly containing large daphnids have a higher potentialfor biomanipulation than other lakes in the world.the same as that of P-limitation: 3/6 vs. 4/6 in Lake

Hume and 5/6 vs. 5/6 in Lake Dartmouth. P-limitation However, this hypothesis may be limited to the situ-ations where total grazing impacts are not confoundedwas apparently prevalent over N-limitation. At the

scale of whole lakes, the importance of grazing was by ungrazability of phytoplankton, or not overriddenby positive food web interactions such as stimulationsuggested by negative correlations with phytoplank-

ton biovolume in time series of the biomass of Clado- of phytoplankton by fish (Matveev, Matveeva & Jones,1994b), by invertebrate predators (Matveeva &cera (Lake Hume) or Cladocera and Copepoda (Lake

Dartmouth). Moreover, the Cladocera/Phytoplankton Matveev, 1995) or by copepods (Cruz-Pizarro &Carillo, 1991; Lyche et al., 1996).biomass ratio was strongly positively correlated with

explained variance of Chl a as a function of zooplank- Total biomass of zooplankton was not a significantpredictor when regressed on phytoplankton bio-ton biomass, in agreement with another experimental

study (Epp, 1996). The threshold of the ratio for volume in time series comparisons for Lake Hume. Itwas also unsuitable for explaining the clear-watereffective grazing of 0.1, derived from our relationship,

predicted well the period of clear-water phase in phase in this reservoir: two seasonal peaks exceededthe suggested threshold of 1.5 g m–2 of zooplanktonproductive Lake Hume in 1993–94. Even a conservative

estimate of Cladocera community grazing made for biomass necessary to cause clear-water phase(Lampert, 1988), but only one coincided with lowthis period suggested an impact sufficiently high to

maintain the observed clear-water phase. phytoplankton (when Cladocera were abundant).



When Copepoda dominated the zooplankton in win- components of the zooplankton. Cladocera (includingter, also far in excess of 1.5 g m–2, phytoplankton large Daphnia) not only occurred in both reservoirsbiovolume was at its maximum. This might have perennially, but could dominate the community bio-been partly due to the suggested capability of small mass continuously for up to 8 months (Lake Dart-calanoids (Cruz-Pizarro & Carrillo, 1991) and cyclo- mouth). Perennial occurrence of D. carinata waspoids (Lyche et al., 1996) to stimulate the growth of reported for Lake Alexandrina, South Australialake phytoplankton. Indeed, we found positive effects (Geddes, 1984), a large, natural water body differingof both Mesocyclops and Calamoecia on Chl a in some from Lakes Hume and Dartmouth by its physio-enclosure experiments and a suggestive positive cor- chemical conditions. In Australia, D. carinata is wide-relation of copepod biomass with phytoplankton bio- spread geographically and occurs in a variety ofvolume in Lake Hume. habitats (Benzie, 1988).

In our enclosure experiments with Lake Hume Neither do our data confirm the suggestion thatwater, we observed significant limitation by grazing, the capacity of Australian zooplankton for top-downnutrients or both during different periods. Thus, our control of algae and cyanobacteria is minor enough toresults support the contention that the relative influ- disregard the use of biomanipulation as a managementence of grazing and nutrient limitation on phytoplank- tool (Boon et al., 1994). While the success of biomanip-ton varies seasonally in productive lakes (Sommer ulation may depend on mechanisms other than top-et al., 1986; Bartell et al., 1988; Vanni & Tempte, 1990). down control (Matveev et al., 1994a, b), cyanobacteriaInterestingly, such seasonal changes were also were not selected against in our experiments. Althoughobserved in Lake Dartmouth with its low productivity. the abundance and diversity of cyanobacteria in LakesAlthough the results of enclosure experiments may

Hume and Dartmouth during the study period didnot be conclusive at the scale of whole lakes, our

not allow us to test the ability of zooplankton toobservations at this scale (lake time series) suggested

control or prevent cyanobacterial blooms, Microcystisthat at least grazing impact varied in time.

colonies present in our feeding and enclosure experi-Enclosure experiments also suggested that in the

ments were significantly suppressed by grazers. Asless productive Lake Dartmouth, grazing impact on

Australian zooplankton do differ taxonomically fromChl a was more important than in the more productiveother continents, conclusions about grazer–cyanobact-Lake Hume: the frequencies for significant grazingerial interactions based on northern hemispherewere 5/6 vs. 3/6, respectively. Although this findingstudies should be transferred to this region only withseems to be in line with the hypothesis of McQueen,considerable caution: there are studies showing thatPost & Mills (1986) that grazers’ impact is likely to besouthern hemisphere Cladocera (Matveev & Balseiro,higher in oligotrophic waters, our data do not cover1990) and Copepoda (Burns & Xu, 1990) can benefita sufficient range of lakes’ trophic states for compre-from feeding on cyanobacteria at a population level.hensive testing of this hypothesis. Elser & GoldmanTherefore in Australia, further research is needed for(1991) compared zooplankton effects on phytoplank-reliable predictions of the ability of zooplankton toton in three lakes of contrasting trophic status (Chl a:suppress cyanobacteria. Clearly the suppressive effectsless than 0.5 µg l–1, 1–5 µg l–1 and more than 100 µgon the planktonic algae may be considerable, at leastl–1) using enclosure techniques similar to ours. Theyat certain times.found negligible responses of phytoplankton to

zooplankton in two lakes at both extremes of produc-tivity, but a strong response in a lake with Chl a equalto 1–5 µg l–1. High frequency of significant grazing in AcknowledgmentsLake Dartmouth, which has similar Chl a concentra-

This study was funded by the Land and Watertion, coincides with this observation.Resources Research and Development Corporation.The observations of this study do not corroborateWe thank S. Carpenter, who drew our attention tothe view that the grazing niche in the plankton ofcrustacean length model, C. Townsend and twoAustralian freshwaters is filled by calanoid copepodsanonymous referees for valuable comments on theand rotifers (Boon et al., 1994). In both reservoirs

studied, Cladocera and Cyclopoida were essential manuscript.



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Grazer control and nutrient limitation of phytoplankton biomass in two Australian reservoirs