TY - JOUR T1 - Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model A1 - Baskerville, Edward B. A1 - Dobson, Andy P. A1 - Bedford, Trevor A1 - Allesina, Stefano A1 - Anderson, T. Michael A1 - Pascual, Mercedes Y1 - 2011/12/29 N2 - Author Summary The relationships among organisms in an ecosystem can be described by a food web, a network representing who eats whom. Food web organization has important consequences for how populations change over time, how one species extinction can cause others, and how robustly ecosystems respond to disturbances. We present a computational method to analyze how species are organized into groups based on their interactions. We apply this method to the plant and mammal food web from the Serengeti savanna ecosystem in Tanzania, a pristine ecosystem increasingly threatened by human impacts. This web is unusually detailed, with plants identified down to individual species and corresponding habitats. Our analysis, which differs from the compartmental studies typically done in food webs, reveals that functionally distinct groups of carnivores, herbivores, and plants make up the Serengeti web, and that plant groups reflect distinct habitat types. Furthermore, since herbivore groups feed across multiple plant groups, and carnivore groups feed across multiple herbivore groups, energy represents a wider range of habitats as it flows up the web. This pattern may partly explain how the ecosystem remains in balance. Additionally, our method can be easily applied to other kinds of networks and modified to find other patterns. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 12 UR - https://doi.org/10.1371/journal.pcbi.1002321 SP - e1002321 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002321 ER -