High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA
The inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks—a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2021-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/abe4f4 |
| _version_ | 1827870358044147712 |
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| author | L Ma G Hurtt H Tang R Lamb E Campbell R Dubayah M Guy W Huang A Lister J Lu J O’Neil-Dunne A Rudee Q Shen C Silva |
| author_facet | L Ma G Hurtt H Tang R Lamb E Campbell R Dubayah M Guy W Huang A Lister J Lu J O’Neil-Dunne A Rudee Q Shen C Silva |
| author_sort | L Ma |
| collection | DOAJ |
| description | The inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks—a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling approach previously developed for the state of Maryland to 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain, which includes Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In this study, we employ an updated version of the Ecosystem Demography (ED) model, an improved lidar initialization strategy, and an expanded calibration/validation approach. High resolution (90 m) wall-to-wall maps of present aboveground carbon, aboveground carbon sequestration potential, aboveground carbon sequestration potential gap (CSPG), and time to reach sequestration potential were produced over the RGGI domain where airborne lidar data were available, including 100% of eight states, 62% of Maine, 12% of New Jersey, and 0.65% of New York. For the eight states with complete data, an area of 228 552 km ^2 , the contemporary forest aboveground carbon stock is estimated to be 1134 Tg C, and the forest aboveground CSPG is estimated to be larger at >1770 Tg C. Importantly, these estimates of the potential for added aboveground carbon sequestration in forests are spatially resolved, are further partitioned between continued growth of existing trees and new afforested/reforested areas, and include time estimates for realization. They are also assessed for sensitivity to potential changes in vegetation productivity and disturbance rate in response to climate change. The results from this study are intended as input into regional, state, and local planning efforts that consider future climate mitigation in forests along with other land-use considerations. |
| first_indexed | 2024-03-12T15:55:40Z |
| format | Article |
| id | doaj.art-5cf1da04abee46859b486fc36e9d4aa7 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:55:40Z |
| publishDate | 2021-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-5cf1da04abee46859b486fc36e9d4aa72023-08-09T14:54:42ZengIOP PublishingEnvironmental Research Letters1748-93262021-01-0116404501410.1088/1748-9326/abe4f4High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USAL Ma0https://orcid.org/0000-0002-3959-4155G Hurtt1https://orcid.org/0000-0001-7278-202XH Tang2https://orcid.org/0000-0001-7935-5848R Lamb3https://orcid.org/0000-0001-6237-4778E Campbell4R Dubayah5M Guy6W Huang7https://orcid.org/0000-0001-9608-1690A Lister8https://orcid.org/0000-0002-0412-7039J Lu9https://orcid.org/0000-0001-6326-6330J O’Neil-Dunne10A Rudee11Q Shen12C Silva13Department of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaMaryland Department of Natural Resources , Annapolis, MD 21401, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of America; School of Resource and Environmental Sciences, Wuhan University , Wuhan, Hubei Province 430079, People’s Republic of ChinaNorthern Research Station, Forest Inventory and Analysis National Inventory & Monitoring Applications Center (NIMAC), U. S. Forest Service , York, PA 17402, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaRubenstein School of Natural Resources and the Environment, University of Vermont , Burlington, VT 05405, United States of AmericaWorld Resources Institute , Washington, DC 20002, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaDepartment of Geographical Sciences, University of Maryland , College Park, MD 20742, United States of AmericaThe inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks—a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling approach previously developed for the state of Maryland to 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain, which includes Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In this study, we employ an updated version of the Ecosystem Demography (ED) model, an improved lidar initialization strategy, and an expanded calibration/validation approach. High resolution (90 m) wall-to-wall maps of present aboveground carbon, aboveground carbon sequestration potential, aboveground carbon sequestration potential gap (CSPG), and time to reach sequestration potential were produced over the RGGI domain where airborne lidar data were available, including 100% of eight states, 62% of Maine, 12% of New Jersey, and 0.65% of New York. For the eight states with complete data, an area of 228 552 km ^2 , the contemporary forest aboveground carbon stock is estimated to be 1134 Tg C, and the forest aboveground CSPG is estimated to be larger at >1770 Tg C. Importantly, these estimates of the potential for added aboveground carbon sequestration in forests are spatially resolved, are further partitioned between continued growth of existing trees and new afforested/reforested areas, and include time estimates for realization. They are also assessed for sensitivity to potential changes in vegetation productivity and disturbance rate in response to climate change. The results from this study are intended as input into regional, state, and local planning efforts that consider future climate mitigation in forests along with other land-use considerations.https://doi.org/10.1088/1748-9326/abe4f4forestcarbon sequestrationclimate mitigationlidarecosystem modelling |
| spellingShingle | L Ma G Hurtt H Tang R Lamb E Campbell R Dubayah M Guy W Huang A Lister J Lu J O’Neil-Dunne A Rudee Q Shen C Silva High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA Environmental Research Letters forest carbon sequestration climate mitigation lidar ecosystem modelling |
| title | High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA |
| title_full | High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA |
| title_fullStr | High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA |
| title_full_unstemmed | High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA |
| title_short | High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA |
| title_sort | high resolution forest carbon modelling for climate mitigation planning over the rggi region usa |
| topic | forest carbon sequestration climate mitigation lidar ecosystem modelling |
| url | https://doi.org/10.1088/1748-9326/abe4f4 |
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