frbiol$505

Freshwater Biology (1996) 35, 343–347

OPINION

A reply to Sarnelle (1996) and some further commentson Harris’s (1994) opinions

G R A H A M P. H A R R I SCSIRO Institute of Natural Resources and Environment, PO Box 225, Dickson, ACT 2602, and Co-operative Research Centrefor Freshwater Ecology, University of Canberra, Kirinari Street, Bruce, ACT 2617, Australia

Sarnelle (1996) has taken me to task for erring in my grazing rates and susceptibility to predation. It is clearthat large Daphnia are the ‘keystone’ organisms inOpinion paper (Harris, 1994) in this journal and,

furthermore, for promulgating misconceptions in my lakes and that consistent, empirical patterns from food-chain manipulations are revealed when the results ofanalysis of ecosystem behaviour. I welcome this oppor-

tunity to reply because the points Sarnelle raises are such experiments are summarized in terms of the abund-ance of these organisms.of some importance for the interpretation of ‘bio-

manipulation’ or food-web manipulation experiments I have highlighted this phrase deliberately becauseit lies at the core of the debate. No one can doubt thatand consequently for our understanding of aquatic

ecosystems. This is a debate of substance and relevance large Daphnia can have a large grazing impact whenpresent in sufficient numbers. Expressing the impactto both science and management. There are many

areas of agreement between us but some significant of food-web manipulations by selecting cases wherethe abundance of Daphnia is high or low and plottingdifferences in interpretation of data.

Sarnelle is correct in stating that food-web research the results against phosphorus loads (Sarnelle, 1992,1993; Mazumder, 1994) produces clear phytoplanktonhas now yielded useful, synthetic analyses. Good

science is being done in the tradition of limnology responses. Even though Mazumder (1994) is entitled‘Patterns of algal biomass in dominant odd- vs. even-and its contribution to ecology in general (Harris,

1985). Indeed, it is precisely because there are now link lake ecosystems’, it was the abundance of Daphniawhich was used to infer the state of the food chain.a large number of reported food-web manipulation

experiments that we can begin to put all these results Sarnelle (1992) also used the abundance of Daphnia asa surrogate for higher level interactions. The link fromtogether and assess the patterns of response by aquatic

ecosystems (DeMelo, France & McQueen, 1992). Some Daphnia to phytoplankton is clear—algal biomass islower when Daphnia are present and abundant—themore such compilations have appeared since Harris

(1994) was written; for example, Mazumder (1994) and links from Daphnia to higher trophic levels and otherecosystem components are less clear and more com-Reynolds (1994). Food-web manipulation experiments

seek to influence phytoplankton biomass in lakes by plex. Manipulating ‘keystone species’ or significantsystem ‘bioengineers’ in Lawton’s terminologyaltering higher level trophic interactions. In particular,

by reducing planktivory and, hence, increasing herbi- (Lawton & Jones, 1993; Jones, Lawton & Shachak,1994; Jones & Lawton, 1995) does have a significantvory the aim is to reduce phytoplankton biomass and

mitigate the effects of eutrophication. Food chains effect on system function. These species not only havea major impact on their prey but also have a significantwith an odd number of levels (one, three, five) should

be ‘green’, while those with even numbers (two, four) impact on resource availability, often in subtle andindirect ways (Elser et al., 1988; Sterner, 1990; Sterner,should have reduced abundances of phytoplankton.

Large cladoceran grazers (such as species of Daphnia) Elser & Hessen, 1992).Food-chain theory (predator-dependent theory:are key organisms because of their high growth and

© 1996 Blackwell Science Ltd 343

344 G.P. Harris

Hairston, Smith & Slobodkin, 1960; Fretwell, 1977; point. Food-chain theory is not a sufficient explanationof the observations. When presented as VollenweiderOksanen et al., 1981; and some grazing models: De

Angelis, 1992) predicts no increase in algal biomass would have, Mazumder’s (1994) data show an increaseof three orders of magnitude in log10Chl in the presence(as chlorophyll) as total phosphorus (TP) rises.

Zooplankton biomass should increase with TP loading of Daphnia across a log10TP concentration gradient of1–995 µg l–1 with only a slightly lower slope thanwhile chlorophyll is held constant by grazing.

Mazumder (1994) noted that the predictions of the the corresponding plot for lakes lacking the grazer(0.85 6 0.05 v 0.97 6 0.02). The regression line pointsfood-web manipulation theory did not entirely hold

because there is still a significant positive response of to a significant increase in chlorophyll with TP overthis range in the presence of the dominant grazingchlorophyll to TP loadings even in the presence of

significant Daphnia populations. Hansson (1992) ‘bioengineers’. Phytoplankton biomass does increasewith enrichment even in the presence of large clado-obtained the same result. Increased resource availabil-

ity produces higher algal biomass even in the presence ceran grazers and large phytoplankton are more com-mon in eutrophic waters (Watson, McCauley &of Daphnia. Mazumder concluded ‘It is possible that

a significant increase of Chl to TP in the dominant Downing, 1992).So why should the chlorophyll increase even ifeven link ecosystems [i.e. with Daphnia present] results

from the accumulation of ungrazeable large algae with grazers are present? Clearly not all of the algal biomassis ‘mopped up’ by the grazers as food-chain manipula-increasing nutrient availability...’

Sarnelle (1996) is correct in taking me to task for tions and models would predict. De Angelis (1992)has extensively reviewed the development of mathem-asserting that ‘top-down manipulation will be ineffec-

tual in eutrophic systems’. Both Sarnelle’s (1992) paper atical models of the processes of phytoplanktongrowth, nutrient regeneration, grazing and sedimenta-(which I missed) and Mazumder’s (1994) analyses of

many data sets do reveal that grazing is significant in tion. The release of phytoplankton growth from graz-ing was originally described by Rosenzweig (1971) andeutrophic waters. However, the conclusion that ‘top-

down’ effects increase with enrichment is not, as yet, called the ‘paradox of enrichment’ because enrichmentleads to instability. One of the reasons why algaebased on sufficient data. Merely quoting the data from

eutrophic waters (Sarnelle, 1996) hides a much more bloom, even in the presence of grazers like Daphnia,is the mismatch in growth rates between algae andgeneral pattern of behaviour. Mazumder’s data reveal

some unexpected non-linearities in the grazing cladocerans (Reynolds, 1984, 1994; Harris, 1986). Thezooplankton ‘track’ the availability of resources. Theresponse with trophic state. At present we can only

speculate as to why this might be so. (In fact the mismatch in time and space scales between phyto-plankton and zooplankton population responses hasnumber of Mazumder’s (1994) data points for highly

eutrophic waters is rather low (n 5 18) and the ‘flat’ long been documented (e.g. Harris, 1980). Modelsof the ‘paradox of enrichment’ show that once theresponse of chlorophyll to TP at high TP in the

presence of Daphnia (which supports the hypothesis maximum growth rates of the phytoplankton exceedthe maximum grazing rates of the zooplankton, chaoticof strong grazing in eutrophic waters) depends on

three points which deviate markedly from the overall blooms of algae begin to occur. As eutrophicationproceeds, sufficient nutrient builds up in the waterrelationship.)

Sarnelle (1996) also takes me to task for using the so that larger phytoplankton may bloom which arecontrolled less effectively by the grazers (see thedevelopment of blooms of ungrazeable algae as an

explanation of ‘why Vollenweider’s models work at discussion in Reynolds, 1994). At this point the systembegins to oscillate wildly with blooms and crashes ofall’. Sarnelle asserts that the increase of chlorophyll

with increased TP is ‘small’ in the absence of planktiv- phytoplankton and large oscillations in the popula-tions of zooplankton. Reynolds speaks of a ‘lurching,orous fish (i.e. Daphnia present). I do not regard an

increase in chlorophyll of three orders of magnitude cyclical pattern of bottom-up production and exploitat-ive responses’.(Fig. 2 in Mazumder, 1994) as ‘small’! Certainly the

evidence does seem to point to a significant grazing Reynolds (1994) also points out that for successful‘biomanipulation’ to occur the water body shall noteffect in eutrophic waters despite the paucity of some

of the data. However, I was making a more general be dominated by ‘Oscillatoria or any bloom-forming

© 1996 Blackwell Science Ltd, Freshwater Biology, 35, 343–347

A reply to Sarnelle (1996) 345

blue-green alga.’ Reynolds notes that larger phyto- sufficient explanation and that on many occasionsevents did not turn out as expected. Time scales areplankton (larger in one, two or three dimensions)

not only break the tracking cycle because they are important—both of experiment and response—andother ecosystem components are involved. Pelagicunavailable to filter-feeding zooplankton but also

because they slow down the rate of feeding. The food chains are imbedded in larger ecosystemcontext.development of blooms of larger phytoplankton

depends on a number of factors including nutrient When viewed as a human intervention in inter-actions between some components of a complex sys-fluxes, hydrodynamics and successional state (Reyn-

olds, 1984; Harris, 1986). tem, food-chain manipulation should (and does)produce surprises on occasion (Reynolds, 1994). SurelyBlooms of blue-green algae (cyanobacteria) are

poorly grazed. The presence of blooms of colonial N- this is to be expected. The system-level interactionsbetween pelagic food chains and other componentsfixing cyanobacteria may be indicative of N limitation

as well as P limitation. Recent Canadian work has such as sediments and macrophytes are complex.Reynolds (1994) discusses the important interactiondemonstrated that there is a degree of constancy in

the whole basin cycling of N and P in lakes. Findlay between cladoceran grazers and macrophyte beds.Others (Blindow et al., 1993) have noted that lakes mayet al. (1994) and Hendzel, Hecky & Findlay (1994)

manipulated the N : P loading ratios of an experi- alternate between turbid, phytoplankton-dominatedand clear, macrophyte-dominated states over longmental lake in the Canadian Experimental Lakes Area

(ELA) over a number of years and examined the time periods. Complex interactions between nutrients,turbidity, light, zooplankton and fish are certainlysystem response. What happened was that as the N : P

ratio of the external loadings was reduced, N-fixing involved (Reynolds, 1994).‘Bottom-up’ predictions of the algal response tocyanobacteria flourished and compensated for the

reduced N load. Successful ‘biomanipulation’ is there- eutrophication are based on the biomass response ofone or two hundred phytoplankton species lumpedfore contingent on events and elemental cycling in a

number of ‘currencies’ and nutrient fluxes from into a small number of functional groups (Duarteet al., 1995). Predictions based on resource-dependentexternal loads as well as internal regeneration from

grazing and sediment exchange. ‘Surprises’ in food- theories are modified by food-chain interactions. ‘Top-down’ food chain manipulations depend entirely onchain manipulations may therefore occur when out-

comes from events in other ‘currencies’ cut across the functional population response of a very fewspecies of large cladocerans. Why should we expect athe expected sequence of events. Little wonder the

outcomes are complex. system response contingent on the performance of oneor a very few ‘keystone’ species to be as robust asThe burning question, however, is does manipula-

tion of higher levels in the food chain (planktivorous that dependent on the responses of large functionalgroups—particularly when we know that the ‘key-and piscivorous fish) always lead to increased abund-

ance of Daphnia and control of algal blooms? That is, stone’ organism is also influenced by other systemcomponents over long time scales? Immigration ofshort of actually manipulating the Daphnia population

directly (by sieving or adding individuals), can we species and subsequent population growth are notcertainties in ponds and lakes (Talling, 1950). Observa-rely on indirect means to produce the required effect?

Does Daphnia necessarily come to dominate the grazer tions confirm this.Science and management have different goals (Car-community after zooplanktivorous fish are eliminated

in sufficient time to control the outbreaks of algal penter & Kitchell, 1992) and we should not attemptto force the marriage. Good science (which is whatblooms? Sarnelle (1996) admits to a caveat here. Never-

theless, Sarnelle asserts that this is likely ‘given enough we are discussing here), and a sophisticated under-standing of complex interactions in aquatic eco-time’ and that, even in lakes with low initial popula-

tions, significant Daphnia populations must ‘eventually systems, does not necessarily translate into robustmanagement techniques (Cullen, 1990; Harris, 1994).develop’. Do the data confirm these assertions? I think

the answer is no. Compilations of observed v expected Papers such as those of Mazumder (1994) move usforward from ‘stories about special cases’ towards aresults (DeMelo et al., 1992; Mazumder, 1994; Reyn-

olds, 1994) show that food-chain theory is not a more general, synthetic understanding of food-chain

© 1996 Blackwell Science Ltd, Freshwater Biology, 35, 343–347

346 G.P. Harris

(1988) Zooplankton mediated transitions between Nmanipulations. Nevertheless knowledge is still incom-and P limited algal growth. Limnology andplete, more good science is to be encouraged, ‘sur-Oceanography, 33, 1–14.prises’ still occur and papers such as Reynolds (1994)

Findlay D.L., Hecky R.E., Hendzel L.L., Stainton M.P.warn us of the dangers of hubris.& Regehr G.W. (1994) Relationship between N2One brief postscript. I now believe that Harris (1994)fixation and heterocyst abundance and its relevance

has a rather too pessimistic view of the functioning ofto the nitrogen budget of lake 227. Canadian Journal

ecosystems, and that aquatic ecosystems, whilst highly of Fisheries and Aquatic Science, 51, 2254–2266.variable in space and time, are sufficiently close to the Fretwell S.D. (1977) The regulation of plant communities‘edge of chaos’ that repeatable system properties like by food chains exploiting them. Perspectives in Biologythose in Mazumder (1994) do frequently emerge and Medicine, 20, 168–185.(Cohen & Stewart, 1994; Ellner & Turchin, 1995). A Hairston N.G., F.E. Smith and L.B. Slobodkin (1960)

Community structure, population control andhierarchy of scales of interaction (Harris, 1980, 1986)competition. American Naturalist, 94, 421–425.leads to an intrinsically dynamic system behaviour

Hansson L.A. (1992) The role of food chain compositionwhich is predictable in probabilistic terms. A predict-and nutrient availability in shaping algal biomassable system of self-organizing components may there-development. Ecology, 73, 241–247.fore arise from an unpredictable environment (Perry,

Harris G.P. (1980) Temporal and spatial scales in1995). Systems ecology and biogeochemistry is there-phytoplankton ecology. Mechanisms, methods, models

fore an ecology of meta-rules and emergent featuresand management. Canadian Journal of Fisheries and

arising from a model of ecological pandemonium Aquatic Science, 37, 877–900.(Dennett, 1993). Harris G.P. (1985) The answer lies in the nesting

behaviour. Freshwater Biology, 15, 261–266.Harris G.P. (1986) Phytoplankton Ecology. Chapman &References

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