A New Global Peatland Map Expected for 2020

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Global peatlands play a crucial ecological and economic role and have a substantial cultural share in human history. Covering approximately 3% of the global land area, peatlands store twice as much carbon than all terrestrial biomass. However, about 10% of all peatlands are drained and hence a significant carbon source – being responsible for 5% of all anthropogenic carbon dioxide emissions [1]. Furthermore, drainage of peatlands results in soil degradation, high risks regarding fires, land subsidence as well as water pollution [2]. Even though the sensitivity to anthropogenic pressures and a changing climate is recognised, the global extent of peatlands is poorly understood, and the demand for rapid availability of spatially explicit and high-resolution data on status and extent of global peatlands is acuter than ever, especially under consideration of the Paris Agreement entering into force in 2020.

Although often included in global wetland databases, the recognition of peatlands in climatic contexts enhanced the integration of these into stand-alone earth system (ESM) as well as global climate (GCM) models. Using grid-based land-surfaces, GCMs, as well as ESMs, require defined locations as well as fractional covers of peatlands on model grids. Since this has so far been challenging, especially in remote areas with the occurrence of predators or diseases, peatlands were frequently overlooked in databases [3]. However, so far three approaches have been made to map the complete global peatland distribution, each having had its innovative success-story but also challenges. The first map by Yu and colleagues in 2010 [4] was an estimated binary map rather than a gridded product and did not include true and accurate coverage and distribution details for many regions. Another approach [5,6] used soil maps in correlation with global wetland maps, based on remote sensing data such as the Global Inundation Extent from Multi-Satellites (GIEMS) initiative [7], the Surface Water Microwave Product Series (SWAMPS) [8] as well as MODIS data from the Global Lake and Wetlands Database (GLWD-3) [9]. Especially the latter one often led to an over-estimation of tropical peatland extents due to the lack of accurate ground-truthing for areas outside Canada, Scandinavia or Western Siberia [4]. Furthermore, hydromorphic soils are frequently not separated into mineral and organic categories for soil mapping. The most recent global peatland inventory PEATMAP [10] is based on a meta-analysis of high temporal and spatial data regarding peatlands. Nonetheless, this did not result in the provision of a complete map, despite being more accurate due to the eradication of over- as well as underestimations regarding peatland extent and peat layer thickness, especially in the tropics as well as mid- and high-latitudes of the Northern Hemisphere.

Figure 1: Areas of agreement and disagreement between PEATMAP and HWSD v1.2 (panels a and b), and between PEATMAP and GLWD-3 (c and d) for Europe (a and c) and Southeast Asia (b and d). In panels (a) and (b), black to red shading scale indicates percentage cover of histosols according to HWSD v1.2 in those pixels that contain peat according to PEATMAP (i.e., percentage by which PEATMAP overestimates HWSD histosol cover); white to green shading scale indicates percentage cover of histosols according to HWSD v1.2 in those pixels not identified as peat by PEATMAP (i.e., percentage by which HWSD histosol cover overestimates PEATMAP). White indicates pixels not identified as peatlands by either PEATMAP or HWSD v1.2. In panels (c) and (d), red indicates pixels identified as peatlands by both PEATMAP and GLWD-3; black indicates pixels that are only identified as peatlands by PEATMAP and not by GLWD-3; green indicates pixels that are only identified as peatlands by GLWD-3 and not by PEATMAP; white indicates pixels not identified as peatlands by either PEATMAP or GLWD-3. [10]

Figure 1: Areas of agreement and disagreement between PEATMAP and HWSD v1.2 (panels a and b), and between PEATMAP and GLWD-3 (c and d) for Europe (a and c) and Southeast Asia (b and d). In panels (a) and (b), black to red shading scale indicates percentage cover of histosols according to HWSD v1.2 in those pixels that contain peat according to PEATMAP (i.e., percentage by which PEATMAP overestimates HWSD histosol cover); white to green shading scale indicates percentage cover of histosols according to HWSD v1.2 in those pixels not identified as peat by PEATMAP (i.e., percentage by which HWSD histosol cover overestimates PEATMAP). White indicates pixels not identified as peatlands by either PEATMAP or HWSD v1.2. In panels (c) and (d), red indicates pixels identified as peatlands by both PEATMAP and GLWD-3; black indicates pixels that are only identified as peatlands by PEATMAP and not by GLWD-3; green indicates pixels that are only identified as peatlands by GLWD-3 and not by PEATMAP; white indicates pixels not identified as peatlands by either PEATMAP or GLWD-3. [10]

There is thus an urgent need for innovation in peatland mapping, respectively a better and more integrative use of novel remote sensing methods and technologies. Despite the technological progress made in mapping and monitoring the terrestrial carbon cycle using remote sensing, the spatially accurate quantification of soil carbon budgets remains underdeveloped due to the lack of temporal as well as spatial variations in vegetation physiology and phenology in many models. These difficulties regarding technical issues with vegetation – signal interferences complicated quality control methods and thus the reliability of the peatland maps produced so far [11]. However, recent advances in remote sensing techniques, such as solar-induced chlorophyll fluorescence, sensor capabilities (including the upcoming BIOMASS and FLEX missions) as well as a rapidly increasing data pool from legacy observations offers novel opportunities to assess terrestrial carbon cycle processes. This allows developing a new approach of peatland mapping where also information regarding pedology as well as palaeoecology are taken into consideration. A new global high-resolution peatland map, combining these aspects, is expected for 2020 by a collaborative action under the leadership of the Department of Peatland Studies and Palaeoecology and the Greifswald Mire Centre, both from the University of Greifswald, Germany. The Mire Centre already coordinates the International Mire Conservation Group’s (ICGM) global peatland database which is the largest continuous data pool for distribution and status of peatlands all over the globe, based on digital peatland, soil and other proxy data per country and region. The team from Greifswald links a variety of networks, methodologies as well as databases, combining ecological and remote sensing data with legacy soil maps for successful ground-truthing [12]. This meets the requirements to produce a high-resolution map of peatlands, being one of the most challenging land-types for accurate, high-resolution mapping [13], based on aggregated data from local and national peat information.

Figure 2: Example for data integration from the valleys southeast of Lake Kyoga. a) Blue dots: peat point data (National Survey for Energy Peat, 2004); b) Topographical Wetness Index (AfSIS): high TWI in red & darker blue; c) Orange: drawn peatland polygons [12]

Figure 2: Example for data integration from the valleys southeast of Lake Kyoga. a) Blue dots: peat point data (National Survey for Energy Peat, 2004); b) Topographical Wetness Index (AfSIS): high TWI in red & darker blue; c) Orange: drawn peatland polygons [12]

This new global peatland map will combine the results from lessons-learned with recent technological and methodological advancements in GIS and remote sensing. The team’s organisation as an international network of specialists within the field, especially with local authorities and scientists from remote areas makes this new mapping approach an auspicious and exciting project to tackle this overdue issue.

Figure 3: Eriophorum spp. on a raised bog complex in central Scotland. Photo by Claudia Windeck.

Figure 3: Eriophorum spp. on a raised bog complex in central Scotland. Photo by Claudia Windeck.

References:

[1] Victoria, R., Banwart, S., Black, H., Ingram, J., Joosten, H., Milne, E., … & Baskin, Y. (2012). The benefits of soil carbon. Foresight chapter in UNEP Yearbook, 2012, 19-33.

[2] Joosten, H., Tapio-Biström, M. L., & Tol, S. (2012). Peatlands: guidance for climate change mitigation through conservation, rehabilitation and sustainable use. Food and Agriculture Organization of the United Nations.

[3] Krankina, O. N., Pflugmacher, D., Friedl, M., Cohen, W. B., Nelson, P., & Baccini, A. (2008). Meeting the challenge of mapping peatlands with remotely sensed data. Biogeosciences, 5(6), 1809-1820.

[4] Yu, Z. C. (2012). Northern peatland carbon stocks and dynamics: a review. Biogeosciences, 9(10), 4071-4085.

[5] Köchy, M., Hiederer, R., & Freibauer, A. (2015). Global distribution of soil organic carbon–Part 1: Masses and frequency distributions of SOC stocks for the tropics, permafrost regions, wetlands, and the world. Soil, 1(1), 351-365.

[6] Köchy, M., Don, A., van der Molen, M. K., & Freibauer, A. (2015). Global distribution of soil organic carbon–part 2: certainty of changes related to land use and climate. Soil, 1(1), 367-380.

[7] Papa, F., Prigent, C., Aires, F., Jimenez, C., Rossow, W. B., & Matthews, E. (2010). Interannual variability of surface water extent at the global scale, 1993–2004. Journal of Geophysical Research: Atmospheres, 115(D12).

[8] Schroeder, R., McDonald, K. C., Chapman, B. D., Jensen, K., Podest, E., Tessler, Z. D., … & Zimmermann, R. (2015). Development and evaluation of a multi-year fractional surface water data set derived from active/passive microwave remote sensing data. Remote Sensing, 7(12), 16688-16732.

[9] Lehner, B., & Döll, P. (2004). Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology, 296(1-4), 1-22.

[10] Xu, J., Morris, P. J., Liu, J., & Holden, J. (2018). PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. Catena, 160, 134-140.

[11] Zhao, Y., Yu, Z., Tang, Y., Li, H., Yang, B., Li, F., … & Zhou, A. (2014). Peatland initiation and carbon accumulation in China over the last 50,000 years. Earth-Science Reviews, 128, 139-146.

[12] Barthelmes, A., Barthelmes, K. D., Dommain, R., Margalef, O., & Joosten, H. (2014, May). Towards a global high resolution peatland map in 2020. In EGU General Assembly Conference Abstracts (Vol. 16, p. 2239).

[13] Wu, Y., Chan, J. R., & Verseghy, D. L. (2017). A map of global peatland distribution created using machine learning for use in terrestrial ecosystem and earth system models.

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