Post-doctoral position linking hyperspectral-lidar data to tropical forest structure and dynamics
This postdoc will use high resolution hyperspectral-lidar remote sensing to inform the PPA forest dynamics model (Strigul et al. 2008, Ecological Monographs; Bohlman and Pacala 2012, Journal of Ecology) in species-rich tropical systems. We seek to understand how tree structural and physiological attributes that can be quantified by the image data relate to growth, mortality and allometry, which are key model inputs. Our goal is to identify groups of trees and species that have both similar dynamic rates and structural properties and distinct image characteristics. The post-doctoral researcher will analyze and synthesize image data and field data, such as individual tree growth rates and species structural and physiological traits, in the context of the PPA forest model. This research provides a unique opportunity to connect cutting-edge remote sensing technology/analysis with the development of a cutting-edge model of tropical forest dynamics. The ultimate goal of the project is to extend understanding and predictive capability from intensive study sites to wide swaths of tropical forest that are only accessible by airborne remote sensing systems. The position will be based at the University of Florida and focused on field sites in Panama. The University of Florida provides a strong academic community for tropical and ecological research. The position requires background and skills in remote sensing, background in ecology, forestry and/or plant physiology, strong quantitative skills, demonstrated ability to publish and to assist in grant writing, and good ability to work collaboratively. Familiarity with forest models is a plus. Please send a cover letter describing your research interests and skills and how they relate to this position, along with a CV and the names/contact information of 3 references, to: Stephanie Bohlman, School of Forest Resources and Conservation, University of Florida, [email protected].
