Dynamic energy landscapes of predators and the implications for modifying prey risk

Author:

Papastamatiou Yannis P.1ORCID,Binder Benjamin M.1ORCID,Boswell Kevin M.1,Malone Margaret A.1ORCID,Heithaus Michael R.1,Huveneers Charlie2ORCID,Mourier Johann3ORCID,Harborne Alastair R.1ORCID

Affiliation:

1. Institute of Environment, Department of Biological Sciences Florida International University North Miami Florida USA

2. Southern Shark Ecology Group, College of Science and Engineering Flinders University Bedford Park South Australia Australia

3. MARBEC, Univ Montpellier, CNRS, Ifremer, IRD Sète France

Abstract

Abstract Landscapes of fear describe a spatial representation of an animal's perceived risk of predation and the associated foraging costs, while energy landscapes describe the spatial representation of their energetic cost of moving and foraging. Fear landscapes are often dynamic and change based on predator presence and behaviour, and variation in abiotic conditions that modify risk. Energy landscapes are also dynamic and can change across diel, seasonal, and climatic timescales based on variability in temperature, snowfall, wind/current speeds, etc. Recently, it was suggested that fear and energy landscapes should be integrated. In this paradigm, the interaction between landscapes relates to prey being forced to use areas of the energy landscape they would avoid if risk were not a factor. However, dynamic energy landscapes experienced by predators must also be considered since they can affect their ability to forage, irrespective of variation in prey behaviour. We propose an additional component to the fear and dynamic energy landscape paradigm that integrates landscapes of both prey and predators, where predator foraging behaviour is modulated by changes in their energyscape. Specifically, we integrate the predator's energy landscape into foraging theory that predicts prey patch‐leaving decisions under the threat of predation. We predict that as a predator's energetic cost of foraging increases in a habitat, then the prey's foraging cost of predation and patch quitting harvest rate, will decrease. Prey may also decrease their vigilance in response to increased energetic foraging costs for predators, which will lower giving‐up densities of prey. We then provide examples in terrestrial, aerial, and marine ecosystems where we might expect to see these effects. These include birds and sharks which use updrafts that vary based on wind and current speeds, tidal state, or temperature, and terrestrial predators (e.g. wolves) whose landscapes vary seasonally with snow depth or ice cover which may influence their foraging success and even diet selection. A predator perspective is critical to considering the combination of these landscapes and their ecological consequences. Dynamic predator energy landscapes could add an additional spatiotemporal component to risk effects, which may cascade through food webs. Read the free Plain Language Summary for this article on the Journal blog.

Funder

National Science Foundation

Publisher

Wiley

Subject

Ecology, Evolution, Behavior and Systematics

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