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Nordic Society Oikos

Trophic Uncertainty vs Parsimony in Food Web ResearchAuthor(s): Debal DebSource: Oikos, Vol. 78, No. 1 (Feb., 1997), pp. 191-194Published by: Blackwell Publishing on behalf of Nordic Society OikosStable URL: http://www.jstor.org/stable/3545816 .

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FORUMFORUMFORUMFORUM is intended for new ideas or new ways of interpreting existing information. Itprovides a chance for suggesting hypotheses and for challenging current thinking onecological issues. A lighter prose, designed to attract readers, will be permitted. Formalresearch reports, albeit short, will not be accepted, and all contributions should be concisewith a relatively short list of references. A summary is not required.

Trophicuncertaintyvsparsimonyinfood webresearchDebal Deb, WWF-India, Eastern Region, Tata Centre 5th floor, 43 ChowringheeRd, Calcutta 700 071, India.

Gut content analysis (GCA) is the most widely acceptedmethodfor generalisingabout a species' food habits. GCA is valuable ifthe purposeof the studyis to determine he frequencyor strengthof interactions between species, or to establish new food links.However, determiningall food links throughGCA is impossiblefor large speciose webs. Furthermore,GCA may not reveal thetrue nature of linkage dynamics due to environmental andphysiological stochasticity. It is therefore parsimoniousto as-sume that linkages betweenspecies recorded n the literature willbe found in all food webs, if the same prey and predatorspeciesoccur in those systems.To reveal newlinkages, fresh GCA is desirable,but impracticablefor large speciose webs containing many rare and endangeredspecies, in which case it may be replacedby severalnon-dissectivemethods.High-resolutiondata for tropical webs could be gener-ated throughobservations made by trained indigenous peoples.

Gut content analysis (GCA) is performed to find outwhat an animal has eaten, and the finding is subse-quently generalized: what has been found in a speci-men's stomach would represent the diet items of thespecies. This kind of inductive generalization is a pow-erful tool in biology. However, inferring from GCAmay not always reveal the true nature of interactiondynamics (Stoner and Zimmerman 1988). For example,the variety and density of prey, access to the fooditems, predator hunger and gustatory preferences mayaffect the inferences drawn from the typological GCA.Not only are the trophic links always in a state of flux(Lane 1985), but the directionality of the links alsovaries according to developmental stages of organisms(Warren 1989, Deb 1995). Thus, the gut contents oftoday's samples are likely to differ from those of an-other time; similar samples from different communitiesmay also yield different GCA results, due to theirdifferent species compositions and abundances, andalso perhaps due to different environmental influences.

Considering these and other limitations of GCA,many researchers have adopted several alternativemethods, but their explanations as to why GCA wasnot conducted (Stoner and Zimmerman 1988, Havens1991, Polis 1991, Deb 1995) often appear to reveal thatpeer review of such works demanded those explana-

tions. This, combined with the fact that different non-dissective methods have been employed by food webresearchers only in recent years (e.g. Havens et al.1996), seems to indicate that GCA has been held bymany authorities to be the most reliable method.Schoenly and Cohen (1991), for example, insist thatGCA is indispensable for establishing food linkages,and ought to be conducted afresh for every new de-scription of a food web, in order to ascertain thetrophic links actually existing in the system during eachperiod of observation.

Trophic indeterminatenessPrecision of inferencesregardingthe structureof a foodweb crucially depends on the resolution of data. Todescribe an entire web requires identifying all taxa inthe system, which appears too ambitious to accomplish.The checklist of species in a moderately sized commu-nity tends to lengthen with time and effort spent onidentifying them (Cohen et al. 1993, Havens et al.1996). As a corollary, the diet spectrum of any onespecies is likely to increase indefinitely with efforts todiscover them (Polis 1991). One might call this "trophicindeterminateness",which seems to be corroborated bya growing body of evidence.Polis (1991) derived his "species-effort curve" fromhis study of desert arthropods, and aquatic systemshave also yielded similar results. For example, thewater flea Daphnia, known to be purely herbivorous,were reported by Gilbert and coworkers (Burns andGilbert 1986, Gilbert and MacIsaac 1989) to kill andconsume small rotifers such as Keratella in the processof filtering algae. Calanoid copepods, known as pelagicherbivores, are now reported also to eat small bra-chionid rotifers (Warren and Lawton 1987). Until re-cently, phagotrophic uptake of bacteria by phyto-flagellates (Tranvik et al. 1989) was also unknown.Aquatic micro-organisms await intensive studies to re-veal further details of feeding behaviour. Terrestrialexamples include such common mammalian herbivores

OIKOS 78:1 (1997) 191

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as sheep and red deer who occasionally consumelive birds - to meet mineral deficiency in food (Bazely1989), and the Arabian wolf (Canis lupus arabs) in theSarawat mountain range who thrive mainly on fish andbirds, as reported in the March 1995 issue of BBCWildlife reports (p. 11). Thus, the number of potentialfood items of an animal may be larger than what isbelieved to be its actual diet spectrum. By contrast, apotential food organism may not be eaten by thepredator, if the prey has anti-predator adaptations: forexample, Keratella slacki, Brachionus calyciflorus, andPolyarthra spp. most effectively evade predation fromthe predatory rotifer Asplanchna(Kerfoot and Sih 1987,Gilbert and Kirk 1988).In spite of this expanded knowledge of feeding biolo-gies, the presence or absence of the trophic links maynot always be detectable by random gut examinationsdue to stochastic environmental and physiological rea-sons. Predator hunger, for instance, regulates theplanktonic clearance rates of both usually-resistant andsusceptible prey (Stemberger 1985). Furthermore, afresh GCA may reveal that a particularresource type isabsent from the gut of an animal, but that may notindicate the "absence of a link. Rather, it simply meansthat the predator did not eat the prey type during theperiod equal to the gut passage time", when it wasexamined (Havens 1991). Such spatio-temporal uncer-tainty about the constancy of dietary links may debili-tate the very objective of GCA.Schoener (1989) opined that the decision to drawpotential links must be either "vetted by experiments ...or by extensive comparative observations, both hard tocome by and unlikely to be obtained for most foodwebs in even the far future, however desirable" (p.1586). Schoenly and Cohen (1991), however, not onlydemand such experiments and repeated observations beperformed, but would also like to see the ideal studentto report the fluctuations of population densities, aswell as seasonal changes of selected abiotic environmen-tal parameters that might give clues to the flux ofdietary links. Thus, they suggest that trophic linkagesbe deduced from all empirical data in every particularcase, instead of inducingthem from a few cases. Thisstand is characteristic of extreme empiricism,and leavesno scope for generalization. One may also argue thatSchoenly and Cohen's recommendation implies thatfirst we describe a phenomenon (here, presence/absenceof trophic link), and then seek a suitable cause (e.g.environmental parameters) by reference to which wecan explain the phenomenon under that description - aprocedure that corrupts the scientific method.

Application of Occam's razorIn contrast with their own recommendation, Schoenlyand Cohen (1991) themselves relied on the published

data of food habits of the species comprising theirtime-specific webs, constructed "by assuming that afeeding link from prey A to predator B was present ifand only if such a link was present in the cumulativeweb and species A and B occurred together at the timeof observation". A cumulative web is a web whichincorporates all known trophic links between pairs ofspecies across time (links during summer, winter, dayand night, for example). Thus A is assumed to belinked always to B, regardlessof how often A eats B, orwhether this link is stronger or weaker than other suchlinks in the community. This parsimony of assumptionthat the links between pairs of (onto)species observed inthe past will be observed in the future and in similarsystems involves application of Occam's razor, which isessential for all rational enquiry (Lindh 1993). Basedessentially on this argument, most recent food webstudies are literature-dependent,and yet show improvedgeneralisations about web statistics (e.g. Martinez 1991,1992, Havens 1992, 1993, Deb 1995). The essentialimprovement in these studies has been due to finerresolution of known data rather than using new dietaryinformation.

One problem with cumulative webs is that if ontoge-netic diet shifts occurred, the simultaneous presence ofA and B in their webs would not necessarily signify afeeding relation between them (Schoenly and Cohen1991). Thus, if B is eaten by the juvenile, but notthe adult of species A, the calculation of food linksbetween them whenever A and B co-occur wouldsimply overestimate the number of actual links incumulative webs. This overestimation could be avoidedif the relevant life-history stages of organisms are de-scribed separately as distinct web elements in the cumu-lative webs (Havens 1992, Deb 1995). I would liketo call such elements ontospecies (Deb 1995). Thus,species A may be resolved into ontospecies X (theyoung of species A) and Y (adult A), such that B(in the above example) is linked with X, but not withY.

Estimating overestimation limitsConstructing cumulative webs implies that the organ-ismsgn the web under study use (or, will use) all trophicbiologies they are known to use. As a result, thenumber of food links (L) tends to be overestimated(Pimm et al. 1991). Here the methodological problem iswhether the overestimation of L approximates the to-pologically maximum number of feasible links (Lmax)amongst all ontospecies, in which case the whole exer-cise of cumulative web analysis is bound to yield spuri-ous results. Lmax is defined as

Lmax= S(S- 1)- si(si-1) 2 = si(S- si)/2,OIKOS 78:1 (1997)92

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where si is the number of species on the ith trophiclevel, and S = E si. To test if L calculated from cumula-tive webs might approximate Lmax,I analysed my owndata on two freshwater ponds from southern Bengal,and simulated 11 500 randomized webs on computer,using the same pool of ontospecies (Deb 1995). Alltrophic links between the ontospecies were inferredfrom the literature. The result (Fig. 1) shows that thetwo estimates move increasingly apart from each otheras S increases, and the lower limit of the Lmaxrange isabove the upper limit of the range of L. This indicatesthat the method of literature-dependencedoes not over-estimate linkages to such extent as to exhaust thepossibility of counti

SupplementingGInformation about tlinks between speciemation for constructhe study concernswith the frequency1991), and (b) a simtor and prey speciWhen a new speciewhen the food habitGCA seems to bewith the other (ont

1000

L 500

Fig. 1. The relationshi11500 randomized nenon-randominkagesis co-incident or at 1