MOVING SPECIES: MODELLING SPATIAL AND TEMPORAL RESPONSES TO ENVIRONMENTAL CHANGE

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The world around us is changing rapidly. Natural habitats are shrinking in size and increasing in isolation, the climate is warming, and extreme weather events are becoming more frequent. Many of these changes have negative impacts on biodiversity—the plants and animals with which we share the planet. Recent research has documented how species have responded to recent changes in climate. For example, species are shifting their distributions to higher elevations and latitudes where temperatures are cooler, and plants are flowering earlier in the year as the growing season lengthens and spring moves forward. However, we still lack robust models for predicting species’ future responses and the impacts of biodiversity change on the ecosystem processes critical for sustaining life on Earth, such as nutrient cycling, water purification and, at larger spatial scales, climate regulation. This proposal attempts to address this challenge. First, I will synthesise global databases on plant distributions and phenology (the timing of periodic life history events) to examine the variation in species’ response to recent anthropogenic climate warming. I will then attempt to model this variation taking into account species differences as well as the interactions between species to generate a unified framework that brings together both responses in space and time. Second, I will explore the links between the structure of communities and their ecological function. There is growing evidence that more diverse communities tend to be more productive and more stable through time. However, it is not just the total number of species that is important, but also their complementarity to one another. Phylogeny—the evolutionary tree-of-life—provides one measure of species similarity as theory predicts that more closely related species will be more ecologically similar, and thus may provide a better index of species complementarity. Here, I will use information on the plant tree-of-life to characterise the relationship between productivity and the phylogenetic structure of forest tree communities across North America. I will then use algorithms that reconstruct species distributions from climate data to predict the likely composition of future forest communities using climate projections. By describing the likely structure of future communities, this work allows us to speculate on possible changes in ecosystem functioning under climate change. My aim is to improve our ability to predict not only species’ futures, but also the functional properties of future ecosystems.