干旱区生态环境知识资源中心

For ectothermic species with broad geographical distributions, latitudinal/altitudinal variation in environmental temperatures (averages and extremes) is expected to shape the evolution of physiological tolerances and the acclimation capacity (i.e., degree of phenotypic plasticity) of natural populations. This can create geographical gradients of selection in which environments with greater thermal variability (e.g., seasonality) tend to favor individuals that maximize performance across a broader range of temperatures compared to more stable environments. Although thermal acclimation capacity plays a fundamental role in this context, it is unknown whether natural selection targets this trait in natural populations. Additionally, understanding whether and how selection acts on thermal physiological plasticity is also highly relevant to climate change and biological conservation. Here, we addressed such an important gap in our knowledge in the northernmost population of the four-eyed frog, Pleurodema thaul. We measured plastic responses of critical thermal limits for activity, behavioral thermal preference, and thermal sensitivity of metabolism to acclimation at 10 and 20 degrees C. We monitored survival during three separate recapture efforts and used mark-recapture integrated into an information-theoretic approach to evaluate the relationship between survivals as a function of the plasticity of thermal traits. Overall, we found no evidence that thermal acclimation in this population is being targeted by directional selection, although there might be signals of selection on individual traits. According to the most supported models, survival increased in individuals with higher tolerance to cold when cold-acclimated, probably because daily low extremes are frequent during the cooler periods of the year. Furthermore, survival increased with body size. However, in both cases, the directional selection estimates were nonsignificant, and the constraints of our experimental design prevented us from evaluating more complex models (i.e., nonlinear selection).