Countergradient variation in locomotor performance of two sympatric Polynesian skinks (Emoia impar, Emoia cyanura).

PHYSIOLOGICAL AND BIOCHEMICAL ZOOLOGY(2014)

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摘要
Physiological function in ectotherms is tightly linked to body temperature. As a result, the thermal sensitivity of physiological function may evolve to optimize fitness across different thermal environments. One hypothesis for the evolution of thermal sensitivity, coadaptation, predicts that optimal temperatures for performance should evolve to match the temperatures that an organism experiences in nature. Another hypothesis, countergradient variation, posits that genetic variation can compensate for decreased performance in cool environments, leading to physiological phenotypes that do not track environmental temperatures. On Mo"orea, French Polynesia, thermal ecology and physiology were studied in two morphologically similar skinks that differ in habitat use. Previous studies show that Emoia impar tends to inhabit closed-canopy and interior habitats that are cooler compared to those inhabited by Emoia cyanura, but these differences had not been quantified on Mo"orea. The goal of this study was to determine whether this pattern of habitat partitioning exists on Mo"orea and relates to interspecific differences in thermal physiology and to evaluate whether the evolution of thermal sensitivity supports coadaptation or countergradient variation. I found that E. impar inhabits closed-canopy habitats with cooler substrates and with higher altitudes compared to habitats of E. cyanura. Although the two species do not differ significantly in critical thermal minimum, E. impar has a significantly lower preferred body temperature and critical thermal maximum than does E. cyanura. Despite a preference for cooler habitats and temperatures, E. impar has a warmer optimal temperature for sprint speed and sprints faster than E. cyanura at all temperatures, which supports the countergradient model of thermal adaptation. These results are robust to three different curve-fitting functions and support the view that generalist/specialist trade-offs do not universally constrain the evolution of performance curves.
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