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Integrating continental-scale citizen-science, environmental, and physiological data to identify the drivers of species migration

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posted on 2014-07-16, 16:16 authored by Sarah SuppSarah Supp, Tina Cormier, Frank LaSorte, Marisa Lim, Gil Bohrer, Don Powers, Susan Wethington, Scott Goetz, Catherine Graham

This poster was presented at the Gordon Research Seminar and Conference, "Unifying Ecology Across Scales", 19-25 July 2014. 

Many species undertake annual long-distance migration, a behavior that comprises an important form of seasonal variation in community composition, species diversity, and ecosystem function in many temperate landscapes. Long-distance movement of species is energetically costly, and individuals must be able to access resources and habitat to promote survival during migration, and to arrive at breeding grounds in good enough condition to successfully reproduce and fledge offspring. Species may migrate in response to static cues (e.g. day length) or to dynamic cues (environment, weather). Understanding the drivers of long-distance movement is critical to predicting how species will respond climate change. A physiological understanding of species will help researchers predict whether the species response (e.g. a shift in migration timing) will mitigate potentially positive or negative effects of shifting climate patterns on individual survival and population viability. Hummingbirds are ideal for evaluating the impacts of climate change on long-distance migration and physiology. They inhabit a broad range of ecosystems, physiologically respond quickly to environmental shifts, and are directly tied to changes in environment through their mutualistic relationship with flowering plants. Here, we use citizen-science observation data reported to eBird (2004-2013) for 5 North American hummingbird species to a) describe migration timing and routes, b) compare inter-annual variability in migration and environmental parameters, c) model which static and dynamic cues are associated with migration parameters, and d) use the model results and physiological constraints to predict hummingbird response under 3 climate change scenarios. We predict that species may be able to shift migration routes to quickly respond to climate change, but may be unable to physiologically cope with an increase in extreme weather events that push individuals toward their energetic constraints on survival.

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