Beyond spatial overlap: harnessing new technologies to resolve the complexities of predator–prey interactions. Issue 8 (21st February 2022)

• Record Type: Journal Article
• Authors: Suraci, Justin P.; Smith, Justine A.; Chamaillé‐Jammes, Simon; Gaynor, Kaitlyn M.; Jones, Menna; Luttbeg, Barney; Ritchie, Euan G.; Sheriff, Michael J.; Sih, Andrew
• Is Part Of: Oikos. Volume 2022:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-21
• Subjects: encounter rates -- home range overlap -- predation risk effects -- predation sequence -- predator–prey interactions -- spatial ecology; Ecology -- Periodicals; 570
• DOI: 10.1111/oik.09004
• Languages: English
• ISSNs: 0030-1299

Abstract

Abstract : Predation risk, the probability that a prey animal will be killed by a predator, is fundamental to theoretical and applied ecology. Predation risk varies with animal behavior and environmental conditions, yet attempts to understand predation risk in natural systems often ignore important ecological and environmental complexities, relying instead on proxies for actual risk such as predator–prey spatial overlap. Here we detail the ecological and environmental complexities driving disconnects between three stages of the predation sequence that are often assumed to be tightly linked: spatial overlap, encounters and prey capture. Our review highlights several major sources of variability in natural predator–prey systems that lead to the decoupling of spatial overlap estimates from actual encounter rates (e.g. temporal activity patterns, predator and prey movement capacity, resource limitations) and that affect the probability of prey capture given encounter (e.g. predator hunger levels, temporal, topographic and other environmental influences on capture success). Emerging technologies and statistical methods are facilitating a transition to a more spatiotemporally detailed, mechanistic understanding of predator–prey interactions, allowing for the concurrent examination of multiple stages of the predation sequence in mobile, free‐ranging animals. We describe crucial applications of this new understanding to fundamental and applied ecology, highlighting opportunities to better integrate ecological contingencies into dynamic predator–prey models and to harness a mechanistic understanding of predator–prey interactions to improve targeting and effectiveness of conservation interventions.