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Predator Effects In Predator-Free Space: The Remote Effects Of Predators On Prey, John L. Orrock, Lawerence M. Dill, Andrew Sih, Johnathan H. Grabowski, Scott D. Peacor, Barbara L. Peckarsky, Evan L. Preisser, James R. Vonesh, Earl E. Werner
Predator Effects In Predator-Free Space: The Remote Effects Of Predators On Prey, John L. Orrock, Lawerence M. Dill, Andrew Sih, Johnathan H. Grabowski, Scott D. Peacor, Barbara L. Peckarsky, Evan L. Preisser, James R. Vonesh, Earl E. Werner
Biological Sciences Faculty Publications
Predators can have remote effects on prey populations that are connected by migration (i.e. prey metapopulations) because predator-mediated changes in prey behavior and abundance effectively transmit the impact of predators into predator-free prey populations. Behavioral changes in prey that might give rise to remote effects are altered rates of migration or activity in the presence of predation risk (called non-consumptive effects, fear- or μ-driven effects, and risk effects). Changes in prey abundance that may result in remote effects arise from changes in prey density due to direct predation (i.e. consumptive effects, also called N-driven effects and predation effects). Remote effects …
Ecological Boundary Detection Using Bayesian Areal Wombling, Matthew C. Fitzpatrick, Evan L. Preisser, Adam Porter, Joseph Elkinton, Lance A. Waller, Bradley P. Carlin, Aaron M. Ellison
Ecological Boundary Detection Using Bayesian Areal Wombling, Matthew C. Fitzpatrick, Evan L. Preisser, Adam Porter, Joseph Elkinton, Lance A. Waller, Bradley P. Carlin, Aaron M. Ellison
Biological Sciences Faculty Publications
The study of ecological boundaries and their dynamics is of fundamental importance to much of ecology, biogeography, and evolution. Over the past two decades, boundary analysis (of which wombling is a subfield) has received considerable research attention, resulting in multiple approaches for the quantification of ecological boundaries. Nonetheless, few methods have been developed that can simultaneously (1) analyze spatially homogenized data sets (i.e., areal data in the form of polygons rather than point‐reference data); (2) account for spatial structure in these data and uncertainty associated with them; and (3) objectively assign probabilities to boundaries once detected. Here we describe the …