Critical land change information enhances the understanding of carbon balance in the United States - Jinxun Liu; Benjamin M. Sleeter; Zhiliang Zhu; Thomas R. Loveland; Terry Sohl; Stephen M. Howard; Carl H. Key; Todd Hawbaker; Shuguang Liu; Bradley Reed; Mark A. Cochrane; Linda S. Heath; et al. (Global Change Biology, 2020)
Large‐scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine‐scale processes including land use and land cover change into a large‐scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1‐km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO 2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest - Xuexia Chen; James E. Vogelmann; Matthew Rollins; Donald Ohlen; Carl H. Key; Limin Yang; Chengquan Huang; Hua Shi (International Journal of Remote Sensing, 2011)