Xu, J. , Morris, P. J., Liu, J. and Holden, J. (2018) PEATMAP: refining estimates of global peatland distribution based on a meta-analysis. CATENA, 160, pp. 134-140. (doi: 10.1016/j.catena.2017.09.010)
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Abstract
Peatlands play important ecological, economic and cultural roles in human well-being. Although considered sensitive to climate change and anthropogenic pressures, the spatial extent of peatlands is poorly constrained. We report the development of an improved global peatland map, PEATMAP, based on a meta-analysis of geospatial information collated from a variety of sources at global, regional and national levels. We estimate total global peatland area to be 4.23 million km2, approximately 2.84% of the world land area. Our results suggest that previous global peatland inventories are likely to underestimate peat extent in the tropics, and to overestimate it in parts of mid- and high-latitudes of the Northern Hemisphere. Global wetland and soil datasets are poorly suited to estimating peatland distribution. For instance, tropical peatland extents are overestimated by Global Lakes and Wetlands Database – Level 3 (GLWD-3) due to the lack of ground-truthing data; and underestimated by the use of histosols to represent peatlands in the Harmonized World Soil Database (HWSD) v1.2, as large areas of swamp forest peat in the humid tropics are omitted. PEATMAP and its underlying data are freely available as a potentially useful tool for scientists and policy makers with interests in peatlands or wetlands. PEATMAP's data format and file structure are intended to allow it to be readily updated when previously undocumented peatlands are found and mapped, and when regional or national land cover maps are updated and refined.
| Item Type: | Articles |
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| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Xu, Dr Jiren |
| Authors: | Xu, J., Morris, P. J., Liu, J., and Holden, J. |
| College/School: | College of Social Sciences > School of Social & Environmental Sustainability |
| Journal Name: | CATENA |
| Publisher: | Elsevier |
| ISSN: | 0341-8162 |
| ISSN (Online): | 1872-6887 |
| Published Online: | 23 September 2017 |
| Copyright Holders: | Copyright © 2017 Elsevier B.V. |
| First Published: | First published in CATENA 160: 134-140 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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