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Group formation stabilizes predator–prey dynamics


Theoretical ecology is largely founded on the principle of mass action, in which uncoordinated populations of predators and prey move in a random and well-mixed fashion across a featureless landscape. The conceptual core of this body of theory is the functional response, predicting the rate of prey consumption by individual predators as a function of predator and/or prey densities1,2,3,4,5. This assumption is seriously violated in many ecosystems in which predators and/or prey form social groups. Here we develop a new set of group-dependent functional responses to consider the ecological implications of sociality and apply the model to the Serengeti ecosystem. All of the prey species typically captured by Serengeti lions (Panthera leo) are gregarious, exhibiting nonlinear relationships between prey-group density and population density. The observed patterns of group formation profoundly reduce food intake rates below the levels expected under random mixing, having as strong an impact on intake rates as the seasonal migratory behaviour of the herbivores. A dynamical system model parameterized for the Serengeti ecosystem (using wildebeest (Connochaetes taurinus) as a well-studied example) shows that grouping strongly stabilizes interactions between lions and wildebeest. Our results suggest that social groups rather than individuals are the basic building blocks around which predator–prey interactions should be modelled and that group formation may provide the underlying stability of many ecosystems.

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Figure 1: Group density in relation to population density for Serengeti lions and their predominant eight prey species.
Figure 2: Predicted effects of group formation by Serengeti lions and/or their prey on the functional response of individual lions.
Figure 3: Locally stable parameter combinations ( ε versus d ) for lion–wildebeest models.
Figure 4: Time-series data for Serengeti wildebeest and lions.


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We thank the many individuals who have assisted with Serengeti population monitoring over the decades. J.M.F. thanks the Visitor’s Programme of the Centre for Population Biology, Imperial College London, for logistic support during the preparation of this work. This work was supported by Discovery Grants to J.M.F. and A.R.E.S. from the Natural Sciences and Engineering Research Council of Canada, and by NSF Grants for Long-Term Research in Environmental Biology and Biocomplexity to C.P.

Author Contributions Field data used for this paper came from long-term collaborative studies by J.M.F., C.P. and A.R.E.S., with statistical analysis of the data by J.M.F. and A.M. Models were developed and analysed by J.M.F. All four authors participated in discussion of the results at a workshop and contributed to manuscript preparation.

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Correspondence to John M. Fryxell.

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Supplementary Information

The file contains Supplementary Table 1 (listing the parameters for curves shown in Fig. 1), Supplementary Figure 1 (showing seasonal variation in wildebeest group density and number of wildebeest groups encountered during censuses), and Supplementary Equations (listing equations for population equilibria and community matrix coefficients used for local stability analysis). (PDF 216 kb)

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Fryxell, J., Mosser, A., Sinclair, A. et al. Group formation stabilizes predator–prey dynamics. Nature 449, 1041–1043 (2007).

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