Compartments1 in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups2. Theoretically, compartments increase the stability in networks1,2,3,4,5, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches6,7,8,9 or insufficient methodological rigour8,10,11. Here we show that a method for detecting compartments from the social networking science12,13,14 identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results12,13,14. A graphical presentation14 reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs15,16,17.
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We thank M. Huxham and D. Raffaelli for providing data on the Ythan Estuary food web; N. Martinez and J. Dunne for providing data on the Little Rock Lake food webs; L. Abarca-Arenas for providing data on the 45-taxa Chesapeake Bay food web; C. Darnell for enhancing the diagram; and C. Goddard and J. Liu for comments and suggestions. This work was supported by the Great Lakes Fishery Commission (A.E.K., D.M.M.), the National Institute of Child Health and Human Development (K.A.F.) and the National Science Foundation (K.A.F.). Opinions reflect those of the authors and do not necessarily reflect those of the granting agency.
The authors declare that they have no competing financial interests.
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