Beyond spatial overlap: harnessing new technologies to resolve the complexities of predator–prey interactions

• Published in: Oikos Vol. 2022; no. 8
• Main 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
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.08.2022; Nordic Ecological Society
• Subjects: Activity patterns; Animal behavior; applied ecology; Behaviour; Decoupling; Ecology; encounter rates; Environmental conditions; Environmental risk; Environmental Sciences; home range overlap; Hunger; Interspecific relationships; Life Sciences; New technology; Predation; predation risk effects; predation sequence; Predator prey relations; Predator-prey interactions; Predator-prey simulation; Predators; Prey; prey species; Probability theory; Risk; Risk taking; Sequencing; spatial ecology; Statistical analysis; Statistical methods; topography; predation sequence; encounter rates; predator-prey interactions; predation risk effects; spatial ecology; home range overlap
• DOI: 10.1111/oik.09004
• ISSN: 0030-1299

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.