B13F-0669
Wall-to-wall assessment of carbon stock and flux consequences of forest disturbances in the Pacific Northwest United States using remote sensing and forest inventory data
Monday, 14 December 2015
Poster Hall (Moscone South)
Huan Gu1, Christopher A Williams1, George James Collatz2, Jeffrey G Masek2, Gretchen Moisen3, Karen Schleeweis4, Bardan Ghimire1, Feng Aron Zhao5, Chengquan Huang6 and Sassan S Saatchi7, (1)Clark University, Worcester, MA, United States, (2)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (3)US Forest Service Fort Collins, Fort Collins, CO, United States, (4)Organization Not Listed, Washington, DC, United States, (5)University of Maryland College Park, Geographical Sciences, College Park, MD, United States, (6)University of Maryland, Department of Geographical Sciences, College Park, MD, United States, (7)NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Abstract:
Disturbances profoundly alter the structure and function of forests, imposing long lasting carbon legacies and strongly influencing rates of terrestrial carbon exchange with the atmosphere. Disturbance legacies vary across ecoregions, by forest types, and with disturbance severity and type. The complexity presents a significant challenge for observing and modeling carbon exchange, and hinders assessments of current and likely future states of the global carbon cycle. We demonstrate how carbon legacies vary following harvest, fire and bark beetle for forests in Pacific Norwest (PNW) United States, and how these processes influence carbon stocks and fluxes at pixel and regional scales. This study involves the use of satellite and aerial remote sensing products to characterize the frequency and severity of fire, harvest and insects over the past three decades. We use forest inventory data (FIA) to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for harvest, fire and bark beetle disturbances of varying severity across forest types and site productivity. We infer forest stand age and associated uncertainty based on maps of aboveground biomass, disturbance and forest types derived from remote sensing data, as well as carbon stock trajectories and stand productivity map derived from FIA. We then apply the group of carbon flux trajectories to the forest stand age map throughout the study area. Finally, we summarize the net carbon uptake as a consequence of disturbance and regrowth at pixel and regional scales. As such, this study represents a first demonstration of a spatially explicit assessment of carbon stock and flux responses to disturbances by linking remote sensing disturbance products, biomass maps and forest inventory data in a carbon cycle modeling framework. The methodology will be further applied across the conterminous US to provide a comprehensive forest carbon budget assessment.
