Caching in or falling back at the Sevilleta

TL;DR

This study models how caching rodents in arid environments optimize foraging strategies considering resource scarcity, body size, and seasonal uncertainty, revealing size-dependent differences in cache use and risk management.

Contribution

It introduces a stochastic dynamic programming model to analyze foraging behavior in desert rodents, highlighting size-related thresholds in cache benefits and risk responses.

Findings

Resource scarcity increases dependence on fallback foods.

A body size threshold of 50 g influences cache use and fitness benefits.

Larger rodents with bigger caches are less affected by seasonal uncertainties.

Abstract

Foraging in uncertain environments requires balancing the risks associated with finding alternative resources against potential gains. In aridland environments characterized by extreme variation in the amount and seasonal timing of primary production, consumer communities must weigh the risks associated with foraging for preferred seeds that can be cached against fallback foods of low nutritional quality (e.g., leaves) that must be consumed immediately. Here we explore the influence of resource-scarcity, body size, and seasonal uncertainty on the expected foraging behaviors of caching rodents in the northern Chihuahaun Desert by integrating these elements with a Stochastic Dynamic Program (SDP) to determine fitness-maximizing foraging strategies. We demonstrate that resource-limited environments promote dependence on fallback foods, reducing the likelihood of starvation while increasing future risk exposure. Our results point to a qualitative difference in the use of fallback foods and the fitness benefits of caching at the threshold body size of 50 g. Above this threshold the fitness benefits are greater for consumers with smaller caches, affirming empirical observations of cache use among rodents in such dynamic environments. This suggests that larger-bodied consumers with larger caches may be less sensitive to the future uncertainties in monsoonal onset predicted by global climate scenarios.