Idenfitying and Understanding North American Carbon Cycle Perturbations from Natural and Anthropogenic Disturbances

Abstract

Carbon dioxide accumulating in our atmosphere is one of the most important environmental threats of our time. Humans and changing climate, separately or in concert, have affected global vegetation, biogeochemical cycles, biophysical processes, and primary production. Recent studies have found temporary carbon stores in North American vegetation due to land-cover land-use change, but have yet to characterize regional mechanisms across the continent. This research implemented multi-resolution remote sensing data, coupled with ecosystem simulations, to determine the importance of fine-scale disturbance in our understanding of dynamics that drove and/or perturbed carbon sequestration in North America from 1982 through 2005.

The research involved three components: 1) identified large regions with natural and anthropogenic vegetation disturbances; 2) determined causes of disturbances with high-spatial resolution data and mapped associative fine-scale land cover dynamics; and 3) used prior empirical observations in simulations to quantify mechanisms that altered carbon pathways.

Investigation of normalized difference vegetation index data from the NOAA series of Advanced Very High Resolution Radiometers found regions in North America that experienced marked increases in photosynthetic capacity at various times from 1982 to 2005. Inspection of anomalies with multi-resolution data from Landsat, IKONOS, aerial photography, and ancillary data revealed a wide range of causes: climatic influences; severe drought and subsequent recovery; irrigated agriculture expansion; insect outbreaks followed by logging and subsequent regeneration; and forest fires with subsequent regeneration.

Fine-scale land cover change dynamics were included in Carnegie-Ames-Stanford approach simulations to enhance replication of carbon cycle processes found in empirical observations. Integration of multi-resolution remote sensing data, with carbon ecosystem process modeling, improved regional understanding and accounting of dynamic fine-scale spatial-temporal North American ecosystem carbon balance by a total of ~10 − 250 teragrams of carbon. Coarse resolution simulations could fail to identify important local scale drivers which impact regional carbon balance.