SYMP 22-4
Using data intensive processes to inform biodiversity conservation at multiple spatial and temporal scales

Friday, August 9, 2013: 9:40 AM
M100EF, Minneapolis Convention Center
Steve Kelling, Information Science, Cornell Lab of Ornithology, Ithaca, NY
Daniel Fink, Lab of Ornithology, Cornell University, Ithaca, NY
Marshall Iliff, Cornell Lab of Ornithology, Cornell University, Ithaca, NY
Wesley M. Hochachka, Lab of Ornithology, Cornell University, Ithaca, NY
Frank La Sorte, Cornell Lab of Ornithology, Ithaca, NY

Assessments of species occurrence and ecosystem health are typically made at local spatial scales or for certain times of year. However, the global scale of issues facing our environment --- from climate change and desertification to deforestation and agricultural expansion --- require information about biodiversity at broad geographic extents, during all seasons, and across multiple years.

Our current efforts at the Cornell Lab of Ornithology focus on creating novel, “data-driven” semiparametric models that provide an extraordinarily flexible framework for the discovery and description of dynamic patterns of species occurrence across multiple spatiotemporal scales. Using tens of millions of observational data gathered through eBird, an Internet-based network of citizen scientists who contribute checklists of bird observations, our spatiotemporal exploratory model (STEM) both quantifies spatial and temporal patterns of occurrence at local levels, while scaling up to describe continent-spanning patterns by knitting together the information contained in an ensemble of more local models. STEMs not only describe patterns of occurrence in a way that accounts for regional and temporal variation in habitat preferences of mobile animals, but additionally provide insights into the biological and physical processes that determine where species live.


STEM is rapidly transforming how ecologists view populations across their ranges and through time. We have used these models to provide precise, year-round occurrence estimates for hundreds of different bird species, revealing in unprecedented detail both local and seasonal variations in likelihood of occurrence. In this talk, we will illustrate how STEM is improving scientific understanding of bird populations and biodiversity conservation, from local to hemispheric scales. As one example, we will show how STEM reveals of migratory pathways of bird populations are highly variable species to species, and also dynamic, changing both seasonally and year-to-year. We will also describe the conservation application of STEM by the United States Bureau of Land Management and U. S. Forest Service for determining management priorities, extensions from the U.S. Department of Interior’s State of the Birds Report --- a periodic, comprehensive overview of the status of all U.S. bird species.