COS 27-5 - Effects of predation-risk and predator hunting mode on prey stoichiometry: A meta-analysis

Tuesday, August 13, 2019: 9:20 AM
L005/009, Kentucky International Convention Center
Shelby Rinehart, Ecology, Evolution, and Behavior, The Hebrew University of Jerusalem, Jerusalem, Israel and Dror Hawlena, Ecology, Evolution and Behavior, The Hebrew University of Jerusalem, Jerusalem, Israel
Background/Question/Methods

The general stress paradigm (GSP) provides a predictive framework that links predator effects to ecosystem function using prey induced physiological defenses (i.e., physiological stress responses). Across many taxa, physiological stress responses are initiated by a rapid increase of stress hormones or proteins that trigger a suite of physiological effects including increased cardiovascular activity, blood pressure, and respiration. Elevated cardiovascular activity diverts energy and nutrients from secondary production to the induction of key defense phenotypes. These physiological responses are expected to increase prey demand for C—upregulating gluconeogenesis (i.e., the breakdown of N-rich proteins into C-rich glucose) and resulting in prey with higher body C:N. However, recent work suggests that there is variation in the effects of physiological responses on prey nutrient stoichiometry, and factors such as predator hunting mode influence the effects of predators on prey nutrient composition. Here, we conducted a meta-analysis testing how predation-risk influences prey physiology and how prey physiological responses are impacted by predator functional traits. We analyzed data from publications reporting the effects of predation-risk on the 1) nutrient content, (ii) nutrient ratios, and (iii) the macronutrient composition of prey bodies.

Results/Conclusions

As predicted by the GSP, prey physiological stress responses increased the C:N and C:P ratios of prey bodies. However, the mechanism underlaying this effect is unclear- as studies measuring only prey body C reported decreases in prey C content under predation-risk. Prey under predation-risk also reduced the concentration of fats, carbohydrates, and proteins in their body tissues. Interestingly, the magnitude of a prey’s physiological stress response to predation depended critically on the hunting mode of their predator. For instance, prey encountering sit-and-wait predators had greater reductions in body fat and carbohydrate content than prey encountering active predators. Active predators should induce weaker responses in prey because their cues satiate the environment, making it difficult for prey to reliably predict levels of predation-risk. Overall, our findings suggest that prey physiological stress responses to predation-risk have predictable effects on the nutrient stoichiometry of prey body tissues, with the magnitude of this response being mediated by predator hunting mode. Understanding how prey physiological stress responses affect prey nutrient stoichiometry is critical, as it provides a means for ecologists to predict the ultimate consequences of predator-prey interactions on ecosystem function.