Computational approaches to studying food webs, networks of who eats whom in an ecosystem.
Food webs, or networks of who eats whom in an ecosystem, provide a complex yet tractable description of ecosystem diversity and have long been a central topic in ecological research. This project aims to advance our understanding of the interplay between network structure, species traits and species interaction rules that lead to the existence of robust, species-rich ecological networks.
The project uses computational methods to model network structure and simulate energy flow through ecological networks. Wherever possible, models are parameterized using the best available empirical data. A suite of tools is under development to implement the models and analyze and visualize model outputs.
Research Team
- Rich Williams (Microsoft Research)
- Neo Martinez (Pacific Eco-informatics and Computational Ecology Lab)
- Jennifer Dunne (Santa Fe Institute)
- Ulrich Brose (Technical University, Darmstadt)
- Richard J. Williams and Drew W. Purves, The probabilistic niche model reveals substantial variation in the niche structure of empirical food webs, in Ecology, 19 September 2011
- Richard J. Williams, Biology, Methodology or Chance? The Degree Distributions of Bipartite Ecological Networks, in PLoS ONE, PLoS, 2011
- Thierry, Aaron, Petchey, Owen L., Beckerman, Andrew P., Warren, Philip H., Williams, and Richard J., The consequences of size dependent foraging for food web topology, in Oikos, vol. 120, pp. 439-502, 2011
- Jennifer A. Dunne and Richard J. Williams, Cascading extinctions and community collapse in model food webs, in Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 364, no. 1524, pp. 1711-1723, June 2009
- Tamara N. Romanuk, Yun Zhou, Ulrich Brose, Eric L. Berlow, Richard J. Williams, and Neo D. Martinez, Predicting invasion success in complex ecological networks, in Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 364, no. 1524, pp. 1743-1754, June 2009
- Richard J. Williams, Simple MaxEnt models explain food web degree distributions, in Theoretical Ecology, Springer Verlag, 9 May 2009
- Eric L. Berlow, Jennifer A. Dunne, Neo D. Martinez, Phillip B. Stark, Richard J. Williams, and Ulrich Brose, Simple prediction of interaction strengths in complex food webs, in Proceedings of the National Academy of Sciences of the USA, vol. 106, pp. 187-191, Proceedings of the National Academy of Sciences, 6 January 2009
- William J. Sutherland, Mark J. Bailey, Ian P. Bainbridge, Tom Brereton, Jaimie T. A. Dick, Joanna Drewitt, Nicholas K. Dulvy, Nicholas R. Dusic, Robert P. Freckleton, Kevin J. Gaston, Pam M. Gilder, Rhys E. Green, A. Louise Heathwaite, Sally M. Johnson, David W. Macdonald, Roger Mitchell, Daniel Osborn, Roger P. Owen, Jules Pretty, Stephanie V. Prior, Havard Prosser, Andrew S. Pullin, Paul Rose, Andrew Stott, Tom Tew, Chris D. Thomas, Des B. A. Thompson, Juliet A. Vickery, Matt Walker, Clive Walmsley, Stuart Warrington, Andrew R. Watkinson, Rich J. Williams, Rosie Woodroffe, and Harry J. Woodroof, Future novel threats and opportunities facing UK biodiversity identified by horizon scanning, in Journal of Applied Ecology, January 2008
- Richard J. Williams, Effects of network and dynamical model structure on species persistence in large model food webs, in Theoretical Ecology, January 2008
- J. A. Dunne, R.J. Williams, N.D. Martinez, R.A. Wood, and D.H. Erwin, Compilation and network analyses of Cambrian food webs, in PLoS Biology, vol. 6, January 2008
