Meeting Abstract
Maximal whole-organism performance traits measured in the laboratory and expressed levels of performance in the field often exhibit a mismatch, complicating our understanding of the selection pressures influencing the evolution of performance traits. To better understand the evolution of optimal performance traits, we built an individual-based simulation, based on empirical morphology->performance relationships derived from an integrative, multivariate model of lizard locomotor performance over a wide range of morphospace and selective contexts, to test hypotheses about selection on locomotor performance. Starting with a population of individuals with morphological attributes determining maximal performance traits, we simulate these individuals surviving and reproducing in a complex environment, presenting each individual with successive ecological challenges requiring specific performance capabilities over their lifespan. While most challenges require sub-maximal speeds, intermittent bouts requiring increased performance capacities, such as predator escape, introduce strong, but infrequent selection for maximal performance. The phenotypes of progeny are then determined via a genetic variance-covariance (i.e. G-matrix) component, and individual fitness and subsequent phenotypic distribution over time result from combinations of trait heritability and differential selection. By comparing the results of simulations run with individuals that only perform at their maximum levels versus those that adjust this effort (and thus save energy), we can test if and under what conditions there exists a selective advantage for optimal speeds below maximum capacity. Ultimately, this model allows us to simulate the evolution of optimal movement speeds over a range of selective contexts, offering insight into the factors affecting the evolutionary relationship between optimal and maximum performance.
