Plant range shifts: Advances, opportunities, and what we still need to know

Dr Emily V Moran1

1UC Merced, Merced, United States

Understanding how plants will shift their ranges under climate change is important for three reasons: 1) Plants form the energetic and structural basis of terrestrial ecosystems, 2) As sessile organisms, plants can only disperse as seeds and so may be limited in their range shift capacity, and 3) Because of these characteristics, plants are often the main focus of restoration efforts and assisted migration discussions.  In this talk, I will briefly discuss several past and ongoing projects relating to factors affecting the capacity for range shifts, in the context of broader research efforts.  These include the use of genetic markers to better estimate dispersal distance in non-wind-dispersed species; biotic and abiotic constraints on seedling establishment; and the role of local adaptation and evolution in response to climate change in long-lived plant species. I will then highlight several new opportunities for advancing our predictions of plant range shift responses (such as increasing modeling capacity and public data availability), as well as several knowledge gaps that need to be filled (including information on the maturation rate and seed dispersal ability of non-woody perennials and tropical species).


Emily Moran has been an assistant professor at the University of California Merced since 2014. She obtained her PhD from Duke University in 2010, and did postdoctoral research at the National Institute for Mathematical and Biological Synthesis (NIMBioS) and at ETH Zurich. Her research focuses on responses to environmental change in long-lived plants, particularly forest trees. She has investigated questions ranging from the dispersal capabilities of oaks, to local adaptation in an invasive perennial, to the role of local adaptation and evolutionary responses in conifer responses to climate change using tools ranging from field observations and experiments to genetic markers and computer modeling.

Similar Posts