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Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks
Environmental Science Division, Argonne National Laboratory, 9700 South Cass Avenue, IL, Argonne, United States; Computational Biology and Biophysics, Sandia National Laboratories, CA, Livermore, United States.
Department of Physical Geography and Quaternary Geology, Stockholm University, Stockholm, Sweden.
Department of Geology and Environmental Science, University of Pittsburgh, PA, Pittsburgh, United States.
State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
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2021 (English)In: Science Advances, E-ISSN 2375-2548, Vol. 7, no 9, article id eaaz5236Article in journal (Refereed) Published
Abstract [en]

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

Place, publisher, year, edition, pages
American Association for the Advancement of Science (AAAS) , 2021. Vol. 7, no 9, article id eaaz5236
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Climate Science Physical Geography
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URN: urn:nbn:se:umu:diva-181742DOI: 10.1126/sciadv.aaz5236ISI: 000622481300001PubMedID: 33627437Scopus ID: 2-s2.0-85102095316OAI: oai:DiVA.org:umu-181742DiVA, id: diva2:1539237
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EU, Horizon 2020, 851181Available from: 2021-03-23 Created: 2021-03-23 Last updated: 2025-02-01Bibliographically approved

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Siewert, Matthias

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