Modeling Global Macroclimatic Constraints on Ectotherm Energy Budgets

Abstract

We describe a mechanistic individual-based model of how global macroclimatic constraints affect the energy budgets of ectothermic animals. The model uses macroclimatic and biophysical characters of the habitat and organism and tenets of heat transfer theory to calculate hourly temperature availabilities over a year. Data on the temperature dependence of activity rate, metabolism, food consumption and food processing capacity are used to estimate the net rate of resource assimilation which is then integrated over time. We detail and explore the significance of assumptions used in these calculations. We present a new test of this model in which we show that the predicted energy budget sizes for 11 populations of the lizard Sceloporus undulalus are in close agreement with observed results from previous field studies. This demonstrates that model tests are feasible and the results are reasonable. Further, since the model represents an upper bound to the size of the energy budget, observed residual deviations form explicit predictions about the effects of environmental constraints on the bioenergetics of the study lizards within each site that may be tested by future field and laboratory studies. Three major new improvements to our modeling are discussed. We present a means to estimate microclimate thermal heterogeneity more realistically and include its effects on field rates of individual activity and food consumption. Second, we describe an improved model of digestive function involving batch processing of consumed food. Third, we show how optimality methods (specifically the methods of stochastic dynamic programming) may be included to model the fitness consequences of energy allocation decisions subject to food consumption and processing constraints which are predicted from the microclimate and physiological modeling Individual-based models that incorporate macroclimatic constraints on individual resource acquisition, assimilation and allocation can provide insights into theoretical investigations about the evolution of life histories in variable environments as well as provide explicit predictions about individual, population and community level responses to global climate change.