Using geospatial data to understand the relationship between tropical forest phenology and productivity

点击翻译按钮获取中文摘要

This project will investigate the relationship between leaf phenology – the timing and amount of leaf production – and primary productivity in contrasting wet and dry tropical forest habitats. Tropical forests are one of the largest and most diverse biomes on Earth. Yet, estimates of gross primary productivity (GPP) – the largest flux of the carbon cycle – are not well understood from these regions. Leaf phenology in tropical forests can be highly variable because of climatic seasonality and a diversity of species. Further, it is unclear how these dynamics affect forest productivity. Geospatial monitoring from satellites provides an unprecedented ability to track forest dynamics across sites and seasons. Merging these cutting-edge technologies with ground-based measurements will help identify site-specific processes that underlie broad-scale geospatial patterns leading to more accurate interpretation of satellite observations. This project will integrate research with education and citizen science by working with an existing outreach program, which provides outdoor, place-based, experiential environmental education to middle and high school students. A postdoctoral researcher will collaborate with middle and high school teachers to educate and train future spatial scientists, providing geospatial data for the proposed research while also meeting Next Generation Science Standards to help grow a more data-capable workforce.Leaf phenology and growing season length are thought to be primary factors controlling the terrestrial carbon cycle by setting the length of time available for photosynthesis and plant growth. Yet in the tropics there is a year-round growing season. Further, it is unclear how variation in GPP is tied to changes in leaf phenology. New satellite measurements of solar-induced fluorescence (SIF) will provide a proxy for GPP across large extents at repeated intervals. While SIF-related studies are accumulating, global and continental scale patterns have not been linked to processes occurring at the plot-scale. This project will synthesize ground-based phenology data with unmanned aerial vehicle and satellite measures of SIF to investigate the relationship between leaf phenology, climatic seasonality, and productivity. Results from this work will help disentangle the relationship between productivity and phenology in diverse tropical forests, and advance our understanding of mechanisms and site-specific differences underlying broad scale variation in satellite SIF. The methods developed in this study will have broad applicability to a wide range of environmental change and conservation applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.