- Title
- Vulnerable Soil Organic Carbon Density (NatureMap)
- License
- Creative Commons Attribution International(CC BY) (CCBY)
-
+ Under the CC BY license, you are free to share (copy and redistribute the material in any medium or format) and or adapt (remix, transform, and build upon the material) for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. The license terms are that you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Additionally, you may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
+ For more info see https://creativecommons.org/licenses/by/4.0/legalcode. - Description
This map shows soil organic carbon stocks that could be potentially vulnerable to human impact by 2050. We used the Predicted Soil Organic Carbon Stock dataset developed by Hengl and Wheeler (2018) as baseline and followed the Tier 1 approach on IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006, 2014 and 2019) to estimate the portion of soil organic carbon (SOC) that could be potentially vulnerable to land use change during a 30 year period both in mineral and organic soils. Organic soils were defined as those with a probability equal or higher than 5% of being classified as Histosols in the Predicted USDA Soils Orders dataset by Hengl and Nauman (2019). The remaining land surface was considered mineral soil. We used the Copernicus land cover dataset (Buchhorn et al. 2019) to associate a land cover type to each pixel in the SOC baseline. This was later cross-walked to IPCC Land Use categories (IPCC 2006) and overlapped with IPCC Climate Zones (IPCC 2006) to estimate vulnerable SOC. Pixels classified as 'forest' were further stratified by management type according Lesiv et al. (2019). Vulnerable SOC was estimated and mapped based on the stock change factors (for mineral soils) and emission factors (for organic soils) available on IPCC Guidelines.
See also:
Buchhorn, M. et al. 2019. Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2015: Globe 2020. DOI 10.5281/zenodo.3939038
Hengl, T. and Nauman T. Predicted USDA soil orders at 250 m (probabilities). https://doi.org/10.5281/zenodo.2658183 Hengl, T. and Wheeler I. (2018) Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution. https://doi.org/10.5281/zenodo.2536040
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan.
IPCC (2014) 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands, Hiraishi, T. Hiraishi, T., Krug, T., Tanabe, K., Srivastava, N., Baasansuren, J., Fukuda, M. and Troxler, T.G. (eds). Published: IPCC, Switzerland.
IPCC (2019) 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Calvo Buendia, E., Tanabe, K., Kranjc, A., Baasansuren, J., Fukuda, M., Ngarize, S., Osako, A., Pyrozhenko, Y., Shermanau, P. and Federici, S. (eds). Published: IPCC, Switzerland.
Lesiv, M. et al. (2020). Methodology for generating a global forest management layer. http://doi.org/10.5281/zenodo.3933966
Suggested Citation:
García-Rangel, S. et al. (In prep) Global distribution of natural carbon stocks potentially vulnerable to land use changes.
- Publication Date
- Jan. 27, 2022, 3:03 a.m.
- Type
- Data
- Keywords
- Category
- Climate
- Climate
- Regions
- Global
- Responsible
- theresa
- Attribution
- NatureMap
- Restrictions
- No Restrictions - Download, analyze, publish and share freely
- Language
- English
- Supplemental Information
Suggested citation
García-Rangel, S. et al. (In prep) Global distribution of natural carbon stocks potentially vulnerable to land use changes.
- Spatial Representation Type
- raster
