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Scaling from individuals to networks in food webs
Article first published online: 7 JAN 2010
DOI: 10.1111/j.1365-2435.2009.01644.x
© 2010 The Author. Journal compilation © 2010 British Ecological Society
Additional Information
How to Cite
Stouffer, D. B. (2010), Scaling from individuals to networks in food webs. Functional Ecology, 24: 44–51. doi: 10.1111/j.1365-2435.2009.01644.x
Publication History
- Issue published online: 7 JAN 2010
- Article first published online: 7 JAN 2010
- Received 29 January 2009; accepted 6 August 2009 Handling Editor: Andrew Beckerman
- Abstract
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- Cited By
Keywords:
- food webs;
- phenomenological models;
- population-level models;
- theoretical ecology;
- network theory
Summary
1. Food webs, the set of predator–prey interactions in an ecosystem, are a prototypical complex system. Much research to date has concentrated on the use of models to identify and explain the key structural features which characterize food webs.
2. These models often fall into two general categories: (i) phenomenological models which are built upon a set of heuristic rules in order to explain some empirical observation and (ii) population-level models in which interactions between individuals result in emergent properties for the food web. Both types of models have helped to uncover how food-web structure is a product of factors such as foraging behaviour, prey selection and species’ body sizes.
3. Historically, the two types of models have followed rather different approaches to the problem. Despite the apparent differences, the overlap between the two styles of models is substantial. Examples are highlighted here.
4. By paying greater attention to both the similarities and differences between the two, we will be better able to demonstrate the ecological insights offered by phenomenological models. This will help us, for example, design experiments which could validate or refute underlying assumptions of the models. By linking models to data, scaling from individuals to networks, we will be closer to understanding the true origins of food-web structure.