Variation of preferred body temperatures along an altitudinal gradient: A multi-species study

Temperature affects the physiological functions of ectotherms. To maintain optimal body temperature and ensure physiological performance, these organisms can use behavioral adjustments to keep the body temperature in their specific temperature range, so-called preferred temperature (T-pref). It is therefore crucial to describe and understand how T-pref vary within and amongst populations to predict the effects of climate change of altitudinal range shifts in organisms. We aimed at determining the altitudinal variations in T-pref in three ectothermic species (the Pyrenean brook salamander - a semi-aquatic and thigmothermic amphibian - the European common lizard and the wall lizard - both heliothermic species). Using an experimental approach where T-pref were measured along a temperature gradient in laboratory conditions, we used a cross-sectional approach to compare the variation of T-pref measured in populations sampled along the altitudinal gradient in the Pyrenees. We hypothesized a complex and highly variable intra-specific response of T pref along geographical dines, with a positive relationship between T-pref and altitude (as predicted by the countergradient variation), the reverse pattern (referring to the adaptation of local optima hypothesis), or no relationship at all. Our results corroborated partially the countergradient hypothesis in the salamander (middle to high elevation part). At high altitude level, individuals may compensate for lower opportunities of favorable conditions by choosing a high temperature which maximizes their activities. However, populations from low elevation level hence better supported the adaptation of local optima hypothesis, such as both lizard species, for which T(pref )tended instead to decrease with altitude. Lizards from cold climates may be physiologically adapted to low temperature, with the ability to reach optimal functioning at lower temperature than individuals from low altitude. Our findings suggest that predicting future niche models should therefore take into account the variability of T-pref, where species might be differently affected by global warming.