I investigate how climate shapes the geographic distributions of genes, species, and ecosystems, and how this understanding can inform biodiversity conservation in the face of climate change. I primarily study plants using big data. My current projects, a sample of which are listed below, involve synthesizing large datasets on species occurrences, plant functional traits, climate, population genetics, phylogenetics, and species endangerment to answer questions related to conservation biogeography. See my CV for past work and publications.
Incomplete range filling. Understanding the processes that limit species ranges is critcical to forecasting the biotic impacts of global environmental change. I’m developing a framework for using climatic niche modeling to test hypotheses about plant distributions and dispersal limitation, such as whether prevailing wind patterns are linked to incomplete range filling in North American trees.
Biogeography of the California Flora. The ecology and evolution of plant communities takes place in twisted manifold at the intersection of multidimensional geographic and environmental spaces. As part of the California Plant Phylodiversity Project I’m using a new CCH dataset to explore macroecological patterns in the geographic ranges and climatic niches of 5000+ California plant species. Coauthors: CPPP
Global weirding. Where will anthropogenic climate change deliver a future climate similar to extreme historic years, and where will it deliver “global weirding” – a breakdown of historic correlations among variables, in which future years represent climates with no historic analog? We apply a novel index of multivariate global weirding to late 20th-century trends to map the nature of changes in the covariance structure of climate regimes. Coauthor: Andrew Crane-Droesch
Functional biogeography of fire. Today’s maps of wildfire regimes are based on top-down geophysical parameters and historic fire records. What can we learn from constructing a bottom-up alternative based on fire-related functional traits of the local vegetation communities? Coauthor: Jens Stevens
Recent climate exposure of vegetation assemblages. Recent climate trends show that the rate and nature of contemporary climate change is very spatially heterogeneous. We use niche models, interannual typicality, and climate velocity statistics to assess three orthogonal dimensions of cliamate exposure in ecosystems across the western US. Coauthors: Healy Hamilton and Stephanie Auer
Bay Area fire weather. Devastating wildfires in the hills near Berkeley are historically associated with Diablo Winds driven by unusual weather conditions. We are exploring the use of machine learning algorithms like self organizing maps to model trends in these synoptic weather patterns. Coauthors: David Ackerly, Bill Collins, and Max Moritz