High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. (6th April 2021)
- Record Type:
- Journal Article
- Title:
- High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. (6th April 2021)
- Main Title:
- High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA
- Authors:
- Ma, L
Hurtt, G
Tang, H
Lamb, R
Campbell, E
Dubayah, R
Guy, M
Huang, W
Lister, A
Lu, J
O'Neil-Dunne, J
Rudee, A
Shen, Q
Silva, C - Abstract:
- Abstract: 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 furtherAbstract: 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. … (more)
- Is Part Of:
- Environmental research letters. Volume 16:Number 4(2021)
- Journal:
- Environmental research letters
- Issue:
- Volume 16:Number 4(2021)
- Issue Display:
- Volume 16, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 16
- Issue:
- 4
- Issue Sort Value:
- 2021-0016-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04-06
- Subjects:
- forest -- carbon sequestration -- climate mitigation -- lidar -- ecosystem modelling
Environmental sciences -- Periodicals
Human ecology -- Research -- Periodicals
Environmental health -- Periodicals
333.7 - Journal URLs:
- http://iopscience.iop.org/1748-9326 ↗
http://www.iop.org/EJ/toc/1748-9326 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1748-9326/abe4f4 ↗
- Languages:
- English
- ISSNs:
- 1748-9326
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3791.592955
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