Geography

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Author: search.filters.author.Lamb, Rachel

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    Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling
    (Wiley, 2023-04-04) Ma, Lei; Hurtt, George; Tang, Hao; Lamb, Rachel; Lister, Andrew; Chini, Louise; Dubayah, Ralph; Armston, John; Campbell, Elliott; Duncanson, Laura; Healey, Sean; O'Neil-Dunne, Jarlath; Ott, Lesley; Poulter, Benjamin; Shen, Quan
    Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.
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    Peer-Reviewed Offset Protocol for U.S. Forest Projects 1.0
    (2022-04-29) Albee, Madeleine; Hoffman Delett, Camille; Panday, Frances Marie; Lamb, Rachel; Hurtt, George
    The protocol was developed for submission into Second Nature's Peer Review Offset Network by the Campus Forest Carbon Project. As of October 2022, the protocol is still under review. This offset protocol is a modified version of a previously adopted protocol created by the California Environmental Protection Agency Air Resources Board as a Compliance Offset Protocol for U.S. Forest Projects. The Campus Forest Carbon Project modified this protocol using NASA Carbon Monitoring System science to integrate a high-resolution remote sensing and modeling based quantification methodology into the voluntary carbon offset market for forest projects. Accompanying the protocol is a background and development document that outlines the specific changes to the protocol and the context surrounding its development.