Sha, Zongyao; Bai, Yongfei; Li, Ruren; Lan, Hai; Zhang, Xueliang; Li, Jonathon; Liu, Xuefeng; Xie, Yichun (2021): The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.926334
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Abstract:
It is well agreed that massive emissions of greenhouse gases (GHGs), particularly that from carbon dioxide (CO2), have been driving and will continue to drive global climate changes, one of which is global warming. Traditional measures by cutting carbon emissions are not enough; we need to find ways to sink more carbon from the atmosphere. Land management practices (LMPs) have massive effect on carbon sequestration from vegetation. Optimal land management practices (OLMPs) refer to LMPs that are capable of a higher, if not the highest, target carbon sequestration level given the current climatic and non-climatic conditions. Carbon sequestration potential, which is termed as carbon gap, is the difference in carbon sequestration with- and without- OLMPs.
This dataset presents the carbon gap computed on the basis of implementing the OLMPs identified within a 20km local neighborhood under the same conditions in terms of landforms, vegetation biomes and soil profiles. We show that globally an extra of 13.73 PgC per year could be sequestered if OLMPs are implemented.
This datasets include an image file Carbongap_2km.tif, the averaged global carbon gap flux for the years 2001-2018, and a number of statistical sheets related to the carbon gap.
Related to:
Sha, Zongyao; Bai, Yongfei; Li, Ruren; Lan, Hai; Zhang, Xueliang; Li, Jonathon; Liu, Xuefeng; Chang, S; Xie, Yichun (2022): The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management. Communications Earth & Environment, 3(1), https://doi.org/10.1038/s43247-021-00333-1
Further details:
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | File content | Content | Sha, Zongyao | |||
| 2 | Binary Object | Binary | Sha, Zongyao |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
22 data points