Dr. Stephanie Pau

Dr. Stephanie Pau
Stem Field
Geography
Title of Research
The phenology and productivity of tropical forests using thermal imaging
Description of Research Area

The vulnerability of tropical forests to climate change is globally significant because these habitats are hyper-diverse, and store and cycle large amounts of carbon. Forest canopy temperatures depart considerably from air temperatures, sometimes by as much as air temperatures are projected to increase by the end of this century; yet canopy temperatures are rarely considered in climate change analyses. Preliminary results from near-continuous thermal imaging and eddy covariance estimates from a tropical forest in Panama show that canopy temperatures reached a maximum of ~34 °C, and exceeded maximum air temperatures by as much as 7 °C. Gross primary productivity (GPP) – which represents the gross rate of carbon fixed by the forest during photosynthesis – was highest at a canopy temperature of ~31 °C, above which declines in GPP occurred. Although future warming is projected to be greater in high latitude regions, these results show that tropical forest productivity is highly sensitive to small changes in temperature.

This postdoctoral researcher would continue work on understanding the thermal environment of the tropical forest canopy in Panama. New directions for future work could address: 1) how water stress affects canopy temperatures and resulting GPP, 2) the different sensitivities of diverse species in the canopy and how leaf-level processes scale up to the whole canopy, 3) how phenological patterns and seasonal changes in leaf development and demography constrain GPP, and/or 4) integration and scaling with satellite remote sensing data. This is a collaborative project with researchers from Oregon State University and Princeton University, and there will be opportunities to network with a diverse group of scholars.

Special Research & Career Skills

This position would include training in skills such as thermal imaging and near-surface remote sensing techniques as well as statistical modeling in R. Career skills and professional development would include training in writing and oral presentations, networking, grant-writing, work-life balance, and job application components such as applying, interviewing, and negotiating.