Literature DB >> 24640545

Enhancing species distribution modeling by characterizing predator-prey interactions.

Anne M Trainor, Oswald J Schmitz, Jacob S Ivan, Tanya M Shenk.   

Abstract

Niche theory is a well-established concept integrating a diverse array of environmental variables and multispecies interactions used to describe species geographic distribution. It is now customary to employ species distribution models (SDMs) that use environmental variables in conjunction with species location information to characterize species' niches and map their geographic ranges. The challenge remains, however, to account for the biotic interactions of species with other community members on which they depend. We show here how to connect species spatial distribution and their dependence with other species by modeling spatially explicit predator-prey interactions, which we call a trophic interaction distribution model (TIDM). To develop the principles, we capitalized on data from Canada lynx (Lynx canadensis) reintroduced into Colorado. Spatial location information for lynx obtained from telemetry was used in conjunction with environmental data to construct an SDM. The spatial locations of lynx-snowshoe hare encounters obtained from snow-tracking in conjunction with environmental data were used to construct a TIDM. The environmental conditions associated with lynx locations and lynx-hare encounters identified through both SDM and TIDM revealed an initial transient phase in habitat use that settled into a steady state. Nevertheless, despite the potential for the SDM to broadly encompass all lynx hunting and nonhunting spatial locations, the spatial extents of the SDM and TIDM differed; about 40% of important lynx-snowshoe hare locations identified in the TIDM were not identified in the lynx-only SDM. Our results encourage greater effort to quantify spatial locations of trophic interactions among species in a community and the associated environmental conditions when attempting to construct models aimed at projecting current and future species geographic distributions.

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Year:  2014        PMID: 24640545     DOI: 10.1890/13-0336.1

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


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