A phenology of fear: Investigating scale and seasonality in predator–prey games between wolves and white‐tailed deer

Abstract

Predators and prey engage in games where each player must counter the moves of the other, and these games include multiple phases operating at different spatiotemporal scales. Recent work has highlighted potential issues related to scale‐sensitive inferences in predator–prey interactions, and there is growing appreciation that these may exhibit pronounced but predictable dynamics. Motivated by previous assertions about effects arising from foraging games between white‐tailed deer and canid predators (coyotes and wolves), we used a large and year‐round network of trail cameras to characterize deer and predator foraging games, with a particular focus on clarifying its temporal scale and seasonal variation. Linear features were strongly associated with predator detection rates, suggesting these play a central role in canid foraging tactics by expediting movement. Consistent with expectations for prey contending with highly mobile predators, deer responses were more sensitive to proximal risk metrics at finer spatiotemporal scales, suggesting that coarser but more commonly used scales of analysis may miss useful insights into prey risk‐response. Time allocation appears to be a key tactic for deer risk management and was more strongly moderated by factors associated with forage or evasion heterogeneity (forest cover, snow and plant phenology) than factors associated with the likelihood of predator encounter (linear features). Trade‐offs between food and safety appeared to vary as much seasonally as spatially, with snow and vegetation phenology giving rise to a “phenology of fear.” Deer appear free to counter predators during milder times of year, but a combination of poor foraging state, reduced forage availability, greater movements costs, and reproductive state dampen responsiveness during winter. Pronounced intra‐annual variation in predator–prey interactions may be common in seasonal environments.

Fear, concealment, and time of day interactively predict group size of a common ungulate

“…In addition, coyotes, which emerged as the dominant carnivore in Indiana only after extirpation of larger carnivores (Lyon, 1934), are well adapted for urbanization and can persist in urban areas near roads and buildings (Ellington & Gehrt, 2019; Appendix S5). Other studies have also documented risk‐aversive behavior of deer in response to both natural predators (Clare et al, 2023; Crawford et al, 2019) and anthropogenic activity such as hunting (Sullivan et al, 2018) and development (Maurer et al, 2022). In our study system, anthropogenic development and spatiotemporal pulses of coyote use intensity seemed to interactively heighten fear of multiple mortality sources to which deer responded by forming larger groups.…”

Coping with unpredictable environments: fine-tune foraging microhabitat use in relation to prey availability in an alpine species

“…Foraging microhabitat selection has been largely investigated as a function of habitat characteristics and availability (Tsiakiris et al 2009 ; Belotti et al 2013 ; Eierman et al 2014 ; Spear et al 2020 ; Barras et al 2020 ; Korniluk et al 2021 ). Although it is generally assumed that a forager distribution occurs at the highest prey densities to maximise their intake rate (Holling 1959 ; Stephens and Krebs 1986; Zwarts and Wanink 1993 ; Wallace et al 2015 ; Roder et al 2020 ), there is evidence showing that the overlap between species occurrences and the distribution of key resources may be imperfect due to different constraints including habitat complexity (i.e., detectability; Martinez et al 2010 ; Müller et al 2012 ; Benoit-Bird et al 2013 ; Liu et al 2019 ), presence of predators (e.g., Brown 1988 ; Heithaus et al 2002 ; Clare et al 2023 ), density-dependent effects (Piersma 2012; DeRoy et al 2020 ), as well as limitation associated with the sampling methodology (e.g., Hunsicker et al 2011 ; Kuhn et al 2015 ). In this regard, when both prey and microhabitat availability have been assessed, they have been often evaluated separately over different spatial or temporal extents (Guillemette et al 1992 ; Johnson and Sherry 2001; Barbaro et al 2008 ; Moreno-Rueda et al 2018 ; Scridel et al 2022 ), leading to a potential mismatch between the observation of predators and environmental data such as prey-predator distribution (Hunsicker et al 2011 ; Kuhn et al 2015 ).…”

Applied ecology of fear: A meta‐analysis on the potential of facilitating human‐wildlife coexistence through nonlethal tools

“…Experience of prey interacting with predators may also shape the strength with which prey respond to different cues (Berger et al., 2001). Moreover, even if prey sense a cue, this does not always lead to an anti‐predator response since prey continuously face a trade‐off between anti‐predator behaviour and other essential behaviours such as the need for foraging when an individual is in a poor health condition (Clare et al., 2023; Gaynor et al., 2019).…”