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The GEO-TREES initiative in partnership with the Forest Global Earth Observatory (ForestGEO) through support from the Bezos Earth Fund invites applications for a postdoctoral position in tree inventory and implementation for the estimation of tropical forest carbon stocks.
GEO-TREES is an ambitious global initiative – the world's first ground-based, standardized reference system to transparently and independently ensure that satellite observations accurately represent real forest carbon stocks, in all forest types and conditions, today and into the future. This unprecedented multi-network collaboration will use innovative technology, partnerships and training, broad sampling, as well as long-term commitment and fair funding for field partners to establish 100 core sites and 200 supplementary sites around the globe to measure and monitor forest biomass stocks. It will deliver these data in a powerful portal – openly accessible to the public, to the science and corporate communities, and to space agencies driving critical advances in satellite technology.
The Smithsonian Forest Global Earth Observatory (ForestGEO) is a global network of forest research plots and scientists dedicated to the study of forest function and diversity. ForestGEO conducts long-term, large-scale research on forests around the world to increase scientific understanding of forest ecosystems, guide sustainable forest management and natural-resource policies, monitor the impacts of environmental change, and build capacity in forest science. ForestGEO has joined forces with ForestPlots.net and TmFO, as well as ESA, CNRS, and other forest plot networks including RAINFOR, AfriTRON, 2ndFor, and SEOSAW to implement the GEO-TREES initiative.
High-quality, above-ground biomass reference data collected by the GEO-TREES initiative will involve three sets of co-located measurements at all core sites: forest inventory data, terrestrial laser scanning, and airborne laser scanning. These standardized measurements share a common requirement for high-quality data acquisition, transparent measurement protocols, and a long-term monitoring strategy. The integration of these three sets of measurements provides the greatest reduction in uncertainty associated with biomass measurements.
This postdoctoral position will focus on the collection and analysis of tree inventory data, and will involve field data collection, data processing, management and analysis, and the development of research papers based on the work. Importantly, the postdoc will be responsible for coordinating efforts of various field work teams to ensure consistent, accurate and comparable data acquisitions across different sites. The postdoc will also be involved in training and capacity-sharing with GEO-TREES partners and associated students.
Candidates should hold a PhD in forest ecology, geography, environmental science, surveying, or related discipline, have strong written and communication skills, and demonstrated ability to work in a team environment. Candidates should have a strong analytical background, an established record of research, and scholarly publication in forest science. Candidates with empirical, theoretical, or modeling backgrounds are encouraged to apply.
The position will be based at the ForestGEO headquarters at the Smithsonian National Museum of Natural History in Washington, DC. The fellowship will require travel for field work in a range of tropical forest countries involved in the GEO-TREES program.
The fellow will be awarded the standard Smithsonian postdoctoral salary and benefits. The appointment is for two years initially, with opportunity for extension based on successful performance. The starting date is flexible; earlier start dates are preferred.
To apply, send a single PDF file containing a cover letter including a statement of research interest, CV, contact information for three references, and three relevant publications or manuscripts to Lauren Krizel, ForestGEO Program Manager, krizell@si.edu.
For further information, contact ForestGEO Director, Stuart Davies, daviess@si.edu
