Effect of Light and Temperature Cycles and Climate Change on Adaptation in Lizards

点击翻译按钮获取中文摘要

Barry Sinervo IOS 1022031 Effect of Light and Temperature Cycles and Climate Change on Adaptation in LizardsRecent climate changes in maximum daily temperatures during spring and summer in many parts of the world appear to be driving local population extinctions of many lizard species. Field studies of key reproductive parameters such as breeding time will be conducted on the side-blotched lizard, a species with detailed information on genetics of lay date in nature. Breeding time is expected to change rapidly under the observed 2°C shift in maximum daily spring temperatures observed during the past two decades in California. The researchers expect to find strong natural selection on breeding time. In laboratory experiments, the researchers will study climate-warming effects on "plastic changes" in breeding time to determine physiological limits of acclimation to climate warming. For example, climate warming is expected to induce earlier breeding but this plastic shift in lay date, due to milder winters, may paradoxically generate strong selection for later lay dates because the optimal period for summer juvenile growth has not changed. Finally, a theoretical model that has been used to accurately predict worldwide extinctions of lizards will be used to predict locations of ongoing population extinctions of side-blotch lizards across the US and Mexico. The predictions will be verified with ground-truth surveys and measurements of microclimate. This study will supply critical information on how species adapt to rapid climate change and if adaptation is not possible, it will estimate extinction likelihood. Lizard species are a valuable model because of well-developed methods for studying natural selection, genetics and thermal physiology. Understanding climate effects on ecology of single species (e.g., demography, reproduction) is a first step in understanding climate impacts on ecosystem functioning. These issues are vital for predicting climate impacts on any ecosystem functioning, human agricultural systems included.