Climate Change Impacts on Global Ecology

Air temperature is a key metric for estimating impacts on terrestrial ecological communities, which experience variations in temperature in space and over days and years. Emerging studies have identified increasing trends in spatial and temporal autocorrelation in both data from observations and select Earth System Model (ESM) simulations. The homogenizing effect of increasing autocorrelation reduces the incidence of protective refugia and increases the duration of unfavorable conditions, which have nonlinear effects on organisms and communities. An opportunity exists at the intersection of climate science and ecology to quantitatively integrate knowledge about future ecological response. Additionally, a comprehensive analysis has not yet studied autocorrelation trends and uncertainty under multiple emissions scenarios with multiple models and initial conditions, or at the local scale in downscaled simulations. Here, we quantify spatial and temporal autocorrelation in a comprehensive analysis of observations and simulations. We develop ecologically informed indices for temperature impacts informed by the best tools from ecology, data science, and climate science.