Global climate change is altering not only long-term average conditions, but also the short-term variability of environmental drivers. However, ecological research has so far mainly focused on changes in means, and we have only limited knowledge of the effects of changing variability, or how they may depend on the mean (interactive effects). Understanding how environmental variability affects rates of population growth could be of fundamental importance to our knowledge of how eco-evolutionary processes shape important biological properties like abundance, trait distributions, community composition and species interactions, and is also essential to develop management strategies advocated to deal with climate change. Theory predicts that both positive and negative effects of increased variability on long-term population growth are possible, but the underlying mechanisms to such responses are still poorly understood for most species. This project will advance our knowledge of biological responses to climate variability, through a synergistic combination of approaches: Theoretical analyses using stochastic population and food-web models, comparative meta-analyses of observational data, and a detailed experimental study. Combined, these approaches will improve our understanding of the links from underlying life history properties to ecosystem responses to climate variability.
