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Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography. Université de Montréal, Quebec, Canada.
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography.
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Number of Authors: 6
2015 (English)In: Journal of Geophysical Research - Biogeosciences, ISSN 2169-8953, E-ISSN 2169-8961, Vol. 120, no 10, 1973-1994 p.Article in journal (Refereed) Published
Abstract [en]

Permafrost-affected ecosystems are important components in the global carbon (C) cycle that, despite being vulnerable to disturbances under climate change, remain poorly understood. This study investigates ecosystem carbon storage in two contrasting continuous permafrost areas of NE and East Siberia. Detailed partitioning of soil organic carbon (SOC) and phytomass carbon (PC) is analyzed for one tundra (Kytalyk) and one taiga (Spasskaya Pad/Neleger) study area. In total, 57 individual field sites (24 and 33 in the respective areas) have been sampled for PC and SOC, including the upper permafrost. Landscape partitioning of ecosystem C storage was derived from thematic upscaling of field observations using a land cover classification from very high resolution (2x2m) satellite imagery. Nonmetric multidimensional scaling was used to explore patterns in C distribution. In both environments the ecosystem C is mostly stored in the soil (86%). At the landscape scale C stocks are primarily controlled by the presence of thermokarst depressions (alases). In the tundra landscape, site-scale variability of C is controlled by periglacial geomorphological features, while in the taiga, local differences in catenary position, soil texture, and forest successions are more important. Very high resolution remote sensing is highly beneficial to the quantification of C storage. Detailed knowledge of ecosystem C storage and ground ice distribution is needed to predict permafrost landscape vulnerability to projected climatic changes. We argue that vegetation dynamics are unlikely to offset mineralization of thawed permafrost C and that landscape-scale reworking of SOC represents the largest potential changes to C cycling.

Place, publisher, year, edition, pages
2015. Vol. 120, no 10, 1973-1994 p.
Keyword [en]
permafrost, soil organic carbon, phytomass carbon, remote sensing, tundra, taiga
National Category
Earth and Related Environmental Sciences
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-126860DOI: 10.1002/2015JG002999ISI: 000368730300007OAI: oai:DiVA.org:su-126860DiVA: diva2:906313
Available from: 2016-02-24 Created: 2016-02-16 Last updated: 2016-11-11Bibliographically approved
In thesis
1. High-resolution mapping and spatial variability of soil organic carbon storage in permafrost environments
Open this publication in new window or tab >>High-resolution mapping and spatial variability of soil organic carbon storage in permafrost environments
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Large amounts of carbon are stored in soils of the northern circumpolar permafrost region. High-resolution mapping of this soil organic carbon (SOC) is important to better understand and predict local to global scale carbon dynamics. In this thesis, studies from five different areas across the permafrost region indicate a pattern of generally higher SOC storage in Arctic tundra soils compared to forested sub-Arctic or Boreal taiga soils. However, much of the SOC stored in the top meter of tundra soils is permanently frozen, while the annually thawing active layer is deeper in taiga soils and more SOC may be available for turnover to ecosystem processes. The results show that significantly more carbon is stored in soils compared to vegetation, even in fully forested taiga ecosystems. This indicates that over longer timescales, the SOC potentially released from thawing permafrost cannot be offset by a greening of the Arctic. For all study areas, the SOC distribution is strongly influenced by the geomorphology, i.e. periglacial landforms and processes, at different spatial scales. These span from the cryoturbation of soil horizons, to the formation of palsas, peat plateaus and different generations of ice-wedges, to thermokarst creating kilometer scale macro environments. In study areas that have not been affected by Pleistocene glaciation, SOC distribution is highly influenced by the occurrence of ice-rich and relief-forming Yedoma deposits. This thesis investigates the use of thematic maps from highly resolved satellite imagery (<6.5 m resolution). These maps reveal important information on the local distribution and variability of SOC, but their creation requires advanced classification methods including an object-based approach, modern classifiers and data-fusion. The results of statistical analyses show a clear link of land cover and geomorphology with SOC storage. Peat-formation and cryoturbation are identified as two major mechanisms to accumulate SOC. As an alternative to thematic maps, this thesis demonstrates the advantages of digital soil mapping of SOC in permafrost areas using machine-learning methods, such as support vector machines, artificial neural networks and random forests. Overall, high-resolution satellite imagery and robust spatial prediction methods allow detailed maps of SOC. This thesis significantly increases the amount of soil pedons available for the individual study areas. Yet, this information is still the limiting factor to better understand the SOC distribution in permafrost environments at local and circumpolar scale. Soil pedon information for SOC quantification should at least distinguish the surface organic layer, the mineral subsoil in the active layer compared to the permafrost and further into organic rich cryoturbated and buried soil horizons.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography, Stockholm University, 2016. 54 p.
Series
Dissertations from the Department of Physical Geography, ISSN 1653-7211 ; 60
Keyword
carbon, soil organic carbon, permafrost, soil, land cover classification, digital soil mapping, machine-learning, ecosystem, mapping, landscape studies, Siberia, Arctic
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-134986 (URN)978-91-7649-529-2 (ISBN)978-91-7649-530-8 (ISBN)
Public defence
2016-12-21, DeGeersalen, Geovetenskapens hus, Svante Arrhenius väg 14, Stockholm, 13:00 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, 282700
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.

Available from: 2016-11-28 Created: 2016-10-28 Last updated: 2016-11-22Bibliographically approved
2. High-­resolution mapping of soil organic carbon storage and soil properties in Siberian periglacial terrain
Open this publication in new window or tab >>High-­resolution mapping of soil organic carbon storage and soil properties in Siberian periglacial terrain
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In the past years considerable attention has been given to soil organic carbon (SOC) stored in permafrost-affected soils in periglacial terrain. Studies have shown that these soils store around half the global SOC pool, making them a key component of the global carbon cycle. Much of the SOC presently stored in these soils has accumulated since the Pleistocene and is protected from decomposition and erosion by low temperatures close to or below the freezing point. This makes it vulnerable to remobilization under a warming climate. This thesis provides new data on SOC storage in three study areas in Siberian periglacial terrain. A high-resolution land cover classification (LCC) for each study area is used to perform detailed vertical and spatial partitioning of SOC. The results show that the vast majority (>86%) of the ecosystem carbon is stored in the top meter of soil. Low relative storage of carbon in plant phytomass indicates limited uptake potential by vegetation and emphasises the vulnerability of the SOC pool to geomorphic changes. Peat formation as well as cryoturbation are identified as the two main pedogenic processes leading to accumulation of SOC. Presence or absence of ice-rich Yedoma deposits determine soil formation and SOC storage at landscape scale. At local scale, periglacial landforms dominate SOC allocation in the tundra, while forest ecosystem dynamics and catenary position control SOC storage in the taiga. A large diversity of soil types is found in these environments and soil properties within pedons can be highly variable with depth. High-resolution satellite imagery allows upscaling of the SOC storage at unprecedented detail, but replication of soil pedons is a limiting factor for mapping of SOC in remote periglacial regions. Future research must look beyond traditional LCC approaches and investigate additional data-sources such as digital elevation models. The concept of state factors of soil formation is advocated as a framework to investigate present day and future SOC allocation in periglacial terrain.

Place, publisher, year, edition, pages
Stockholm: Stockholm University, 2015. 30 p.
Keyword
Soil organic carbon, Siberia, remote sensing, ecosystems
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-120275 (URN)
Presentation
2015-09-25, Ahlmannsalen, 13:00 (English)
Opponent
Supervisors
Available from: 2016-01-25 Created: 2015-09-04 Last updated: 2016-11-11Bibliographically approved

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