As temperature increases, predator attack rate is more important to survival than a smaller window of prey vulnerability

Abstract

Climate change can have strong effects on species interactions and community structure. Temperature-dependent effects on predator-prey interactions are a major mechanism through which these effects occur. To understand the net effects of predator attack rates and dynamic windows of prey vulnerability, we examined the impacts of temperature on the interaction of a caterpillar (Arctia virginalis) and its ant predator (Formica lasioides). We conducted field experiments to examine attack rates on caterpillars relative to temperature, ant abundance, and body size, and laboratory experiments to determine the effects of temperature on caterpillar growth. We modeled temperature-dependent survival based on the integrated effects of temperature-dependent growth and temperature- and size-dependent predation. Attack rates on caterpillars increased with warming and ant recruitment, but decreased with caterpillar size. Caterpillar growth rates increased with temperature, narrowing the window of vulnerability. The model predicted that net caterpillar survival would decrease with temperature, suggesting that A. virginalis populations could be depressed with future climate warming. Theoretical work suggests that the net outcome of predator-prey interactions with increasing temperature depends on the respective responses of interacting species in terms of velocity across space, whereas the present study suggests the importance of effects of temperature on prey window of vulnerability, or "velocity" across time.

Temperature dependency of predation: Increased killing rates and prey mass consumption by predators with warming

“…Our results for how killing rates and prey mass consumption respond to increases in temperature are in agreement with previous work showing enhanced feeding rates by ectothermic consumers with rising temperatures, (Dangles et al., 2013; Dreisig, 1981; Lemoine et al., 2014; Mas‐Martí et al., 2015; Pepi, Grof‐Tisza, Holyoak, & Karban, 2018; Sanchez‐Salazar et al., 1987; Seifert et al., 2014). As temperature increases, ectotherms increase their feeding rates to meet their increased metabolic demands (Dell, Pawar, & Savage, 2014; Rall et al., 2010; Vucic‐Pestic, Ehnes, Rall, & Brose, 2011).…”

Prey–predator phenological mismatch under climate change

“…Mostly, modifications of such trophic interactions because of phenological asynchronies are expected to be specific to each interaction systems depending on several considerations. Firstly, as previously presented, it will be specific to individual species' responses to the modification of different abiotic parameters [66], but also to the phenological sensitivity of all species involved to common abiotic parameters and to their ability to shift in the same direction or not. Indeed, interacting species that do not rely on the same environmental cues to trigger phenological events may be more harshly impacted by climate-change, as for example photoperiod changes over the year will remain stable but not temperature changes.…”

Precipitation-dependent source–sink dynamics in a spatially-structured population of an outbreaking caterpillar

“…While the incorporation of local, patch-level factors is increasing, few studies have explicitly modeled how changes in weather patterns influenced the spatial and temporal dynamics of spatially-structured populations (but see Pardikes et al 2015;Tack et al 2015;Kahilainen et al 2018). Yet changes in precipitation and temperature can either directly (Huey and Kingsolver 1989;Karban et al 2015) or indirectly influence local and regional processes through loss of habitat (Johnson 2004) or changes in bottom-up (Boughton 1999) and top-down (Pepi et al 2018) forces driving patch-quality. One explanation for the paucity of studies incorporating climatic variables is that early metapopulation models pooled occupancy data over multiple years to account for stochastic environmental fluctuations as opposed to explicitly quantifying their effects (Hanski et al 1996;Moilanen 1999).…”