AICE Speaker Series: Daniel C Reuman (University of Kansas)

Please join us for the next AICE Speaker Series with Daniel C Reuman, Professor, Ecology and Evolutionary Biology, University of Kansas.

AGENDA
3:00pm – 3:45pm: Presentation
3:45pm – 4:00pm: Q&A
4:00pm – 4:30pm: Reception

Data Science Institute, Room 105
5460 S University Ave, Chicago, IL 60615

Title: Estimating how climatic variability influences where on Earth a species is found

Abstract: A widely documented impact of climate change is its effect on the geographic ranges of species—where on Earth a species occurs—with many mobile species shifting poleward or upward in elevation. To understand the climatic determinants of species’ ranges and anticipate future changes, researchers commonly use species distribution models (SDMs) that relate environmental conditions to species observation records. However, most SDMs rely on climate normals (e.g., 30-year mean temperature or precipitation), thereby assuming that temporally averaged climate is what constrains species ranges. Demographers recognize that inter-annual variability also matters. For example, polar bears depend on spring sea ice to hunt seals. An area where spring temperature is −10 °C every year and one where temperatures alternate between years of −25 °C and years of 5 °C have the same mean temperature but very different implications for population persistence. We present methods that integrate stochastic demography with SDMs to infer how inter-annual climatic variability constrains species ranges. Applying these methods to example plants, reptiles, mammals, birds, and arthropods, we find that variability reduces estimated species distributions by an average of 22%, up to 45%. Ranges can also be sensitive to future changes in climatic variability, such as the increasing frequency of extreme events. Our results reveal large effects of variability on species distributions, and our inference tools provide a pathway to explore these effects for any species for which sufficient observation records are available.

Bio: Dan is interested in data science approaches to societal problems of a biological nature, with focus on topics in population and community ecology, biodiversity and conservation, resource management and sustainable agriculture. Dan is Professor of Ecology and Evolution and Senior Scientist at the Center for Ecological Research, University of Kansas. He was a James S McDonnell Foundation Complex Systems Scholar and a Humboldt Research Award winner. He did a PhD in math at the University of Chicago before evolving toward biological applications.