Dynamic landscapes of fear: understanding spatiotemporal risk. (October 2022)

• Record Type: Journal Article
• Authors: Palmer, Meredith S.; Gaynor, Kaitlyn M.; Becker, Justine A.; Abraham, Joel O.; Mumma, Matthew A.; Pringle, Robert M.
• Is Part Of: Trends in ecology & evolution. Volume 37:Number 10(2022)
• Page Start: 911
• Page End: 925
• Publication Date: 2022-10
• Subjects: antipredator behavior -- landscape of fear -- non-consumptive effects -- predation risk -- spatiotemporal partitioning -- trophic cascades; Ecology -- Periodicals; Evolution (Biology) -- Periodicals; 576.8
• DOI: 10.1016/j.tree.2022.06.007
• Languages: English
• ISSNs: 0169-5347

Abstract

Abstract : The landscape of fear (LOF) concept posits that prey navigate spatial heterogeneity in perceived predation risk, balancing risk mitigation against other activities necessary for survival and reproduction. These proactive behavioral responses to risk can affect individual fitness, population dynamics, species interactions, and coexistence. Yet, antipredator responses in free-ranging prey often contradict expectations, raising questions about the generality and scalability of the LOF framework and suggesting that a purely spatial, static LOF conceptualization may be inadequate. Here, we outline a 'dynamic' LOF framework that explicitly incorporates time to account for predictable spatiotemporal variation in risk–resource trade-offs. This integrated approach suggests novel predictions about predator effects on prey behaviors to refine understanding of the role predators play in ecological communities. Highlights: Ecologists use the 'landscape of fear' framework to describe spatial variation in perceived predation risk and prey response, despite mixed empirical evidence. However, risk and response are dynamic in time as well as space; we explore what drives cycles of risk and how these cycles structure antipredator decision-making in time. Temporal and spatial heterogeneities in risk interact to create spatiotemporal 'dynamic landscapes of fear', where spatial hotspots of risk vary across temporal cycles. Predictions from a dynamic fear landscape differ from those of a static, spatial landscape of fear, with consequences for forecasting prey behavior, non-consumptive effects, and behaviorally mediated trophic cascades. This framework helps resolve discrepancies between conventional fear theory and empirical data, enabling a more precise understanding of how fear structures ecological communities.