TY - JOUR
T1 - High-fidelity national carbon mapping for resource management and REDD+
AU - Asner, Gregory P.
AU - Mascaro, Joseph
AU - Anderson, Christopher
AU - Knapp, David E.
AU - Martin, Roberta E.
AU - Kennedy-Bowdoin, Ty
AU - van Breugel, Michiel
AU - Davies, Stuart
AU - Hall, Jefferson S.
AU - Muller-Landau, Helene C.
AU - Potvin, Catherine
AU - Sousa, Wayne
AU - Wright, Joseph
AU - Bermingham, Eldridge
N1 - Funding Information:
We thank the Carnegie Institution and Smithsonian Institution for logistical support during the airborne mapping campaign. We thank M. Colgan, A. Baccini, and SilvaCarbon for scientific input. We thank G. Alexandrov and two anonymous reviewers for their constructive comments on the manuscript. We thank the Grantham Foundation for the Protection of the Environment and William Hearst III for project financial support. Data acquisition in the BCI 50-ha plot was supported by NSF grants DEB-0640386, DEB-0425651, DEB-0346488, DEB-0129874, DEB-00753102, DEB-9909347, DEB-9615226, DEB-9615226, DEB-9405933, DEB-9221033, DEB-9100058, DEB-8906869, DEB-8605042, DEB-8206992, DEB-7922197, Center for Tropical Forest Science, MacArthur Foundation, Mellon Foundation, Celera Foundation, and numerous individuals. Data acquisition for the Agua Salud and Azuero sites was supported by HSBC Climate Partnership, Grantham Foundation for the Protection of the Environment, and an anonymous donor. Data acquisition for the Punta Galeta mangrove was supported by NSF grants BSR-9221074, DEB-9615887, DEB-0108146, DEB-0613741. The Carnegie Airborne Observatory is made possible by the Gordon and Betty Moore Foundation, Grantham Foundation for the Protection of the Environment, John D. and Catherine T. MacArthur Foundation, Avatar Alliance Foundation, W. M. Keck Foundation, the Margaret A. Cargill Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William Hearst III.
PY - 2013/7/16
Y1 - 2013/7/16
N2 - Background: High fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama - one of the first UN REDD + partner countries.Results: Integrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.Conclusions: The national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.
AB - Background: High fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama - one of the first UN REDD + partner countries.Results: Integrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.Conclusions: The national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.
KW - Biomass
KW - Carbon stock
KW - Carnegie Airborne Observatory
KW - Deforestation
KW - Forest degradation
KW - Forest inventory
KW - Light Detection and Ranging
KW - Panama
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U2 - 10.1186/1750-0680-8-7
DO - 10.1186/1750-0680-8-7
M3 - Article
C2 - 23866822
AN - SCOPUS:84880090571
SN - 1750-0680
VL - 8
JO - Carbon Balance and Management
JF - Carbon Balance and Management
IS - 1
M1 - 7
ER -