The University of Arizona

College of Agriculture and Life Sciences

Climate Change, Phenology, and Ecosystem Processes: What Are We Learning from the Phenocam Network?

Wednesday, February 7, 2018

Speaker:  Andrew Richardson. Northern Arizona University
 
Date: Wednesday, February 7th, 2018
 
Time: 3:00-4:00 pm
 
Location: ENR2, S107
 
ABSTRACT: Phenology has been shown to be a robust integrator of the effects of year-to-year climate variability and longer-term climate change on natural systems. At the level of organisms, phenology plays a critical role in processes related to growth, reproduction, and competition. At the level of ecosystems, phenology is important because of implications for productivity, carbon sequestration, nutrient cycling, and feedbacks to the climate system. At decadal-to-century time scales, climate change will indirectly cause additional shifts in ecosystem phenology via shifts in community composition and structure. There is a demonstrated need to better document biological responses to a changing world, and improved phenological monitoring will contribute to achieving this goal. In this talk, I will describe a collaborative research network called “PhenoCam” (http://phenocam.sr.unh.edu/). PhenoCam uses networked digital cameras – webcams – for phenological monitoring in a range of ecosystems (over 400 sites, and 1000+ site-years of archived data) across the North American continent. These sites range from coastal wetlands of the southeast to mountain highlands of the northwest, and from the hot deserts of Arizona to the cold of arctic Alaska. Images are captured every 30 minutes, are uploaded to the PhenoCam server for display in real-time, and are then processed to yield measures of vegetation greenness. I will discuss how we are using data from PhenoCam (1) to improve understanding of the environmental controls on phenology at organism-to-ecosystem scales; (2) to relate ecosystem processes (e.g. carbon and water fluxes measured via eddy covariance) to phenology; and (3) to develop predictive models and forecast future climate change impacts on phenology.
 
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