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College of Agriculture and Life Sciences
Department of Ecology and Evolutionary Biology
Xu Lab (http://xiangtaoxu.eeb.cornell.edu/ , Global Ecology and Modeling Lab) in the Department of Ecology and Evolutionary Biology is seeking a highly motivated postdoctoral researcher interested in working on (either of the) two projects related with forest ecology and terrestrial carbon cycling.
Project I: Advance monitoring and modeling temperate forest ecosystems with terrestrial laser scanning (TLS).
This project focuses on investigating forest wood ecophysiology, biomass dynamics, and carbon sequestration in natural and managed temperate forest ecosystems in upstate New York. The project will address these questions leveraging the rich and not fully tapped information from 3D forest structures acquired by TLS (BLK360 + FARO S350 from Xu lab and collaborators). The project will involve close collaborations with foresters from Cornell Cooperative Extension and staff at the Arnot Research and Teaching Forest of Cornell (https://blogs.cornell.edu/arnotforest/ ).
• Lead a research team (undergrads + grad) to collect TLS data and conduct branch trimming experiments (through collaboration with local foresters) in the Arnot Forest of Cornell and other local forest monitoring plots.
• Develop workflows to optimize data quality and improve the interpretability of TLS data; analyze individual level tree biometric data and investigate patterns and drivers of forest biomass dynamics in temperate mixed hardwood forests.
• Integrate TLS data with a state-of-the-art ecosystem model (Ecosystem Demography model v2.2) to improve our understanding of long-term carbon dynamics and sequestration potential in temperate forests.
• Communicate with collaborators in the Department of Natural Resources and the Environment, and Cornell Cooperative Extension.
Project II: Quantifying vulnerability and resilience of tropical forest biomass dynamics by integrating remote sensing data and terrestrial biosphere modeling.
This project builds on the ecosystem resilience methodology from Wu et al. (2021) Global Change Biology and integrates multiple remote sensing and ground-based data to quantify inter-annual variations in biomass dynamics (productivity and mortality) and their environmental determinants in the Amazon Forest. The project will further leverage the rich modeling experience of the lab and collaborations from NASA JPL and other institutes.
• Process and analyze various remote sensing and environmental spatial data sets across the Amazon to estimate forest productivity and mortality.
• Improve ED-2.2 model to account for the observed spatio-temporal variations.
• Explore the implications of updated biomass vulnerability and resilience to natural disturbances under global change for tropical forests.
• PhD degree from relevant disciplines (ecology, forestry, geosciences, remote sensing, engineering, computer science)
• Programming skills in R/Python/Julia/C or other equivalent languages
• (For the TLS project) Experience in ecological field work or equivalent. Ability to drive.
To apply: Applicants should submit their cover letter, CV, a 1-2 page research statement including relevant background and experiences, and a statement of contribution to diversity, equity, and inclusion , as well as the names and email or phone contacts of three professional references to: https://academicjobsonline.org/ajo/jobs/21422
Review of applications will begin immediately. Please contact Dr. Xiangtao Xu (email@example.com) with any questions.
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