Evolution 2016: Evolution of the Thermal Niche in Anolis

IMG_4609Studies of adaptive radiation often focus on two main axes of divergence: the structural niche (e.g., where a species lives) and resource niche (e.g., what a species eats). In his SSE Symposium talk titled “The physiology of adaptive radiation,” Alex Gunderson explained the importance of a third, under-appreciated axis of species diversification: the thermal niche. Gunderson and colleagues tested whether different approaches to estimate the rates of evolution of the thermal niche lead to different conclusions, and whether thermal traits evolve at similar rates to classic ecomorphological traits like body size and limb length.

Scientists generally use three main approaches to quantify the thermal niche and estimate rates of thermal niche evolution: ecological niche modeling (ENM), organismal body temperatures, and physiological data (tolerance/sensitivity to different temperatures). Different studies use different approaches, but few use all three. Each of these metrics addresses a different scale of thermal biology, from broad environmental variables (ENM) to individual organisms (physiology). Gunderson and colleagues therefore predicted that estimated rates of evolution would vary based on the metrics used, and they used data from a number of Anolis species to test this prediction.

Specifically, the authors predicted that: a) ecological niche modeling approaches would estimate greater rates of thermal niche evolution, because environmental factors like temperature and precipitation used in ENM are very broad metrics, and are not necessarily directly correlated with individual thermal niche; b) organismal temperature data would estimate intermediate rates of thermal niche evolution, while it is a measure of individual thermal niche, it is also quite plastic; c) physiological measures would estimate the most conservative/low  rates of evolution, because measures of thermal maxima and minima most accurately reflect the possible tolerance and sensitivity of individuals to thermal environments. They found that physiological data does indeed produce the most conservative estimates of thermal trait evolution, but their predictions about the performance of ENM and body temperature differed. Estimates of thermal niche evolution were highest when using body temperature data, and were intermediate when based on ENM. The fact that body temperature-based estimates of evolution rates were higher than ENM-based estimates suggests that researchers are generally underestimating error in body temperature measurements in the field.

After evaluating the results of these three different approaches in relation to thermal niche evolution, the researchers then compared rates of evolution of thermal traits to those of classical ecomorphological traits. When they used ENM, thermal traits seemed to evolve much more rapidly than morphological traits. In contrast, when they used physiological data, they found the opposite. Clearly, different metrics of climatic niche lead to different conclusions about evolutionary patterns. Gunderson therefore recommends incorporating aspects of multiple ecological and physiological scales when studying divergence of the thermal niche.

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