Meeting Abstract

S9.2  Friday, Jan. 7  The role of evolutionary theory in predicting responses to environmental warming ANGILLETTA, M. J.*; SEARS, M. W.; Arizona State Univ., Tempe; Bryn Mawr College, Bryn Mawr

Because populations adapt to environmental changes, predicting the impacts of climate change requires a quantitative evolutionary theory. Both statistical and mechanistic models can help to predict adaptation to climate change. Statistical modeling identifies functional relationships from empirical data. These relationships can be incorporated into mechanistic models of evolutionary dynamics. Novel predictions from mechanistic models can be evaluated with new empirical data, suggesting ways to refine the theory. Although this interplay between models and data constitutes the scientific method, few researchers of thermal adaptation follow this paradigm closely. To illustrate this approach, we focus on a currently “hot” area of research: thermodynamic effects on performance. Virtually all models of thermal adaptation assume that warm-adapted and cold-adapted organisms can achieve the same fitness, yet data suggest that warm-adapted organisms outperform cold-adapted ones; in other words, individuals with higher thermal optima can achieve greater maximal performance. Statistical modeling showed that the thermodynamic effect varies among species and usually differs from that postulated by the Metabolic Theory of Ecology. Incorporating the observed thermodynamic effect into an evolutionary model leads to novel predictions: selection favors genotypes that perform best at a temperature greater than the mean body temperature. Two consequences emerge for well-adapted species in a warming environment. First, warming can cause an initial increase in fitness as the mean body temperature approaches the thermal optimum. Second, subsequent adaptation to warming would lead to greater maximal fitness. Thus, a thermodynamic effect can increase the tolerable rate of warming and reduce the probability of extinction.