title: Understanding and predicting effects of modified interactions through a qualitative analysis of community structure.
abstract: Models of ecological communities are traditionally based on relationships between pairs of species, where the strengths of per capita interactions are fixed and independent of population abundance. A growing body of literature, however; describes interactions whose strength is modified by the density of either a third species or by one of the species involved in a pairwise interaction. These modified interactions have been treated as indirect effects, and the terminology addressing them is diverse and overlapping. In this paper we develop a general analytical framework based on a qualitative analysis of community structure to account for the consequence of modified interactions in complex ecological communities. Modified interactions are found to create both direct and indirect effects between species. The sign of a direct effect can change in some instances depending on the magnitude of a key variable or parameter, which leads to a threshold change in system structure and dynamics. By considering alternative structures of a community, we extend our ability to model perturbations that move the system far from a previous equilibrium. Using specific examples, we reinterpret existing results, develop hypotheses to guide experiments or management interventions, and explore the role of modified interactions and positive feedback in creating and maintaining alternative stable states. Through a qualitative analysis of community structure, system feedback is demonstrated as being key in understanding and predicting the dynamics of complex ecological communities.
authors.affiliation: CSIRO Marine and Atmospheric Research GPO Box 1538, Hobart, Tasmania 7001, Australia. JEFFREY.DAMBACHER@CSIRO.AU
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Dambacher
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Ramos-Jiliberto
mesh_terms: D000818:Animals; D005075:Biological Evolution; D018533:Biomass; D017753:Ecosystem; D020387:Food Chain; D006801:Humans; D008433:Mathematics; D008954:Models, Biological; D011156:Population Density; D036301:Qualitative Research