干旱区生态环境知识资源中心

Knowledge of the thermal ecology of a species can improve model predictions for temperature-induced population collapse, which in light of climate change is increasingly important for species with limited distributions. Here, we use a multi-faceted approach to quantify and integrate the thermal ecology, properties of the thermal habitat, and past and present distribution of the diurnal, xeric-adapted, and active-foraging Namibian lizard Pedioplanis husabensis (Sauria: Lacertidae) to model its local extinction risk under future climate change scenarios. We asked whether climatic conditions in various regions of its range are already so extreme that local extirpations of P. husabensis have already occurred, or whether this micro-endemic species is adapted to these extreme conditions and uses behavior to mitigate the environmental challenges. To address this, we collected thermoregulation and climate data at a micro-scale level and combined it with micro-and macroclimate data across the species’ range to model extinction risk. We found that P. husabensis inhabits a thermally harsh environment, but also has high thermal preference. In cooler parts of its range, individuals are capable of leaving thermally favorable conditions-based on the species’ thermal preference-unused during the day, probably to maintain low metabolic rates. Furthermore, during the summer, we observed that individuals regulate at body temperatures below the species’ high thermal preference to avoid body temperatures approaching the critical thermal maximum. We find that populations of this species are currently persisting even at the hottest localities within the species’ geographic distribution. We found no evidence of range shifts since the 1960s despite a documented increase in air temperatures. Nevertheless, P. husabensis only has a small safety margin between the upper limit of its thermal preference and the critical thermal maximum and might undergo range reductions in the near future under even the most moderate climate change scenarios.