Modeling Population Growth under Climate Stressors Using Age-Structured Matrix Models

Abstract

Climate resilience, a focus of many recent studies, has been examined from ecological, physiological, and evolutionary perspectives. However, sampling biases towards adults, males, and certain species have made establishing the link between environmental change and population-level change problematic. Here we used data from four laboratory studies, in which we administered pre- and post-natal stressors, such as suboptimal incubation temperature, heat stress, and food restriction, to zebra finches and quantified hatching success, post-hatch survival, and reproductive success, to parameterize age-structured population dynamics models with the goal of estimating the effect of the stressors on relative population growth rates. Using the same model structure, we tested the hypothesis that early life stages influence population growth rate more than later life stages. Our models suggested that stressful events during embryonic development, such as suboptimal incubation temperatures and reduced gas exchange for the embryos, have a greater total impact on population growth than post-hatch stressors, such as heat stress and food restriction. However, among life history traits, differences in hatching success and sex ratio of offspring in response to stressors changed population growth rates more than differences in any other demographic rate estimates. These results suggest that when predicting population resilience against climate change, it is critical to account for effects of climate change on all life stages, including early stages of life, and to incorporate individuals’ physiology and stress tolerance that likely influence future stress responses, reproduction, and survival.