Collaborative Research: RAPID: Airborne LIDAR and Hyperspectral observations to support characterization of litter pool distributions in partnership with NSF DeAD project

Battelle Memorial Institute, Richland OH

Investigators

Abstract

Drylands cover more of the Earth’s surface than any other biome and nearly half of the United States. They are characterized by low rainfall amounts, yet high variability in rainfall. This makes drylands unique from wetter locations, yet research is lacking that helps us understand how rainfall variability impacts ecosystem services such as removal of carbon from the atmosphere and the ability of landscapes to store water during drought. In this project researchers will leverage high rainfall variability at the Santa Rita Experimental Site to explore the production and decomposition of plant litter, which influences ecosystem services. Researchers will collect high resolution airborne images and surface elevation data to explore spatial and temporal patterns in plant litter. This funding will enable a multi-year investigation of variability by filling a gap in annual remote sensing data collection. The data will be made available to the public by the National Ecological Observatory Network (NEON) to enable a variety of research related to understanding the ecosystem outcomes of high rainfall variability. Researchers recognize that dryland litter decay differs from that of mesic systems in part due to higher heterogeneity and temporal variability in litter inputs, litter distribution, and environmental conditions across time and space. The unvegetated interspaces characteristic of drylands allow litter transport by wind and water until restricted by surface features (e.g., plant bases, rocks). Environmental conditions (e.g., moisture, temperature, solar radiation) differ greatly among the microsites where litter accumulates, strongly affecting decomposition rates. Accordingly, quantifying decomposition across drylands is a microbial-to-macroscale problem of integrating fine-scale process controls across spatial-temporal heterogeneity in environmental conditions. Researchers will integrating fieldwork, modeling, and remote sensing approaches across a hierarchical range of scales to capture the distribution of litter across a range of environmental conditions. The project will fund a survey by the NEON Airborne Observation Platform at the Santa Rita Experimental Site that will provide an annual record of imaging spectroscopy and lidar data, enabling landscape-scale multi-temporal analysis of ecosystem dynamics. 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.