Exploring the population impacts of climate change effects on the mean, variance and autocorrelation of temperature using thermal performance curves.

KimCuddington

University of Waterloo

"Exploring the population impacts of climate change effects on the mean, variance and autocorrelation of temperature using thermal performance curves."

Climate change is altering the mean, variance and autocorrelation of temperature. However, linear approaches to incorporating these temperature impacts in simple population models do not provide realistic predictions regarding climate change impacts. For example, simple degree days approaches or using a linear function of temperature to alter the density-independent population growth rate will not account for the sometimes catastrophic decrease in performance with high temperatures. We use an extremely simple population model coupled to nonlinear thermal performance curves to explore the simultaneous impact of changes to temperature mean, variance and autocorrelation. The realized density-independent population growth rate is given by three types of thermal performance curves that correspond to published data. We find relatively small impacts on established population dynamics when realistic changes in temperature sequences are used, suggesting that many populations may be quite robust to temperature-driven climate change impacts in the near term. The most extreme right-skewed performance curves are most likely to result in species extinctions, even though these curves have higher optimal temperatures.
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