Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil...

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Published in:Biogeosciences
Main Authors: Mikola, Juha, Virtanen, Tarmo, Linkosalmi, Maiju, Vähä, Emmi, Nyman, Johanna, Postagonova, Olga, Räsänen, Aleksi, Kotze, Johan, Laurila, Tuomas, Juutinen, Sari, Kondatyev, Vladimir, Aurela, Mika
Format: Article in Journal/Newspaper
Language:English
Published: European Geosciences Union (EGU) 2018
Subjects:
Online Access:http://hdl.handle.net/11250/2588534
https://doi.org/10.5194/bg-15-2781-2018
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description Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 ∘C in bare soil and lichen tundra, and varied from 5 to 9 ∘C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models. publishedVersion © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License.
format Article in Journal/Newspaper
author Mikola, Juha
Virtanen, Tarmo
Linkosalmi, Maiju
Vähä, Emmi
Nyman, Johanna
Postagonova, Olga
Räsänen, Aleksi
Kotze, Johan
Laurila, Tuomas
Juutinen, Sari
Kondatyev, Vladimir
Aurela, Mika
spellingShingle Mikola, Juha
Virtanen, Tarmo
Linkosalmi, Maiju
Vähä, Emmi
Nyman, Johanna
Postagonova, Olga
Räsänen, Aleksi
Kotze, Johan
Laurila, Tuomas
Juutinen, Sari
Kondatyev, Vladimir
Aurela, Mika
Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
author_facet Mikola, Juha
Virtanen, Tarmo
Linkosalmi, Maiju
Vähä, Emmi
Nyman, Johanna
Postagonova, Olga
Räsänen, Aleksi
Kotze, Johan
Laurila, Tuomas
Juutinen, Sari
Kondatyev, Vladimir
Aurela, Mika
author_sort Mikola, Juha
title Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
title_short Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
title_full Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
title_fullStr Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
title_full_unstemmed Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
title_sort spatial variation and linkages of soil and vegetation in the siberian arctic tundra – coupling field observations with remote sensing data
publisher European Geosciences Union (EGU)
publishDate 2018
url http://hdl.handle.net/11250/2588534
https://doi.org/10.5194/bg-15-2781-2018
long_lat ENVELOPE(128.867,128.867,71.633,71.633)
geographic Arctic
Tiksi
geographic_facet Arctic
Tiksi
genre Arctic
Climate change
permafrost
Tiksi
Tundra
genre_facet Arctic
Climate change
permafrost
Tiksi
Tundra
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Biogeosciences
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op_relation Biogeosciences. 2018, 15 (9), 2781-2801.
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2588534 2023-05-15T14:59:27+02:00 Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data Mikola, Juha Virtanen, Tarmo Linkosalmi, Maiju Vähä, Emmi Nyman, Johanna Postagonova, Olga Räsänen, Aleksi Kotze, Johan Laurila, Tuomas Juutinen, Sari Kondatyev, Vladimir Aurela, Mika 2018 http://hdl.handle.net/11250/2588534 https://doi.org/10.5194/bg-15-2781-2018 eng eng European Geosciences Union (EGU) Biogeosciences. 2018, 15 (9), 2781-2801. urn:issn:1726-4170 http://hdl.handle.net/11250/2588534 https://doi.org/10.5194/bg-15-2781-2018 cristin:1588337 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no CC-BY 2781-2801 15 Biogeosciences 9 Journal article Peer reviewed 2018 ftntnutrondheimi https://doi.org/10.5194/bg-15-2781-2018 2019-09-17T06:54:45Z Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 ∘C in bare soil and lichen tundra, and varied from 5 to 9 ∘C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models. publishedVersion © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Article in Journal/Newspaper Arctic Climate change permafrost Tiksi Tundra NTNU Open Archive (Norwegian University of Science and Technology) Arctic Tiksi ENVELOPE(128.867,128.867,71.633,71.633) Biogeosciences 15 9 2781 2801