Data from: 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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Data Archiving and Networked Services (DANS)
2019
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Online Access: | https://doi.org/10.5061/dryad.8382j4r |
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fttriple:oai:gotriple.eu:50|dedup_wf_001::c0104cbd559bea3f42dff72862029193 2023-05-15T14:53:43+02:00 Data from: 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 Postanogova, Olga Räsänen, Aleksi Kotze, D. Johan Laurila, Tuomas Juutinen, Sari Kondratyev, Vladimir Aurela, Mika 2019-01-01 https://doi.org/10.5061/dryad.8382j4r undefined unknown Data Archiving and Networked Services (DANS) http://dx.doi.org/10.5061/dryad.8382j4r https://dx.doi.org/10.5061/dryad.8382j4r lic_creative-commons oai:easy.dans.knaw.nl:easy-dataset:104002 10.5061/dryad.8382j4r oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:104002 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f re3data_____::r3d100000044 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 Life sciences medicine and health care moss Eriophorum Satellite image Spatial extrapolation Permafrost Vascular plant spatial variation NDVI Remote sensing Sphagnum Land cover type Salix Betula nana LAI topography vegetation Ecosystem carbon exchange Carex soil temperature reflectance Soil Arctic Siberia Tiksi envir geo Dataset https://vocabularies.coar-repositories.org/resource_types/c_ddb1/ 2019 fttriple https://doi.org/10.5061/dryad.8382j4r https://doi.org/10.5061/DRYAD.8382J4R 2023-01-22T16:51:09Z 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 25 ◦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 ... Dataset Arctic Betula nana Climate change Eriophorum permafrost Tiksi Tundra Siberia Unknown Arctic Tiksi ENVELOPE(128.867,128.867,71.633,71.633) |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
unknown |
topic |
Life sciences medicine and health care moss Eriophorum Satellite image Spatial extrapolation Permafrost Vascular plant spatial variation NDVI Remote sensing Sphagnum Land cover type Salix Betula nana LAI topography vegetation Ecosystem carbon exchange Carex soil temperature reflectance Soil Arctic Siberia Tiksi envir geo |
spellingShingle |
Life sciences medicine and health care moss Eriophorum Satellite image Spatial extrapolation Permafrost Vascular plant spatial variation NDVI Remote sensing Sphagnum Land cover type Salix Betula nana LAI topography vegetation Ecosystem carbon exchange Carex soil temperature reflectance Soil Arctic Siberia Tiksi envir geo Mikola, Juha Virtanen, Tarmo Linkosalmi, Maiju Vähä, Emmi Nyman, Johanna Postanogova, Olga Räsänen, Aleksi Kotze, D. Johan Laurila, Tuomas Juutinen, Sari Kondratyev, Vladimir Aurela, Mika Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
topic_facet |
Life sciences medicine and health care moss Eriophorum Satellite image Spatial extrapolation Permafrost Vascular plant spatial variation NDVI Remote sensing Sphagnum Land cover type Salix Betula nana LAI topography vegetation Ecosystem carbon exchange Carex soil temperature reflectance Soil Arctic Siberia Tiksi envir geo |
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 25 ◦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 ... |
format |
Dataset |
author |
Mikola, Juha Virtanen, Tarmo Linkosalmi, Maiju Vähä, Emmi Nyman, Johanna Postanogova, Olga Räsänen, Aleksi Kotze, D. Johan Laurila, Tuomas Juutinen, Sari Kondratyev, Vladimir Aurela, Mika |
author_facet |
Mikola, Juha Virtanen, Tarmo Linkosalmi, Maiju Vähä, Emmi Nyman, Johanna Postanogova, Olga Räsänen, Aleksi Kotze, D. Johan Laurila, Tuomas Juutinen, Sari Kondratyev, Vladimir Aurela, Mika |
author_sort |
Mikola, Juha |
title |
Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
title_short |
Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
title_full |
Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
title_fullStr |
Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
title_full_unstemmed |
Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data |
title_sort |
data from: spatial variation and linkages of soil and vegetation in the siberian arctic tundra – coupling field observations with remote sensing data |
publisher |
Data Archiving and Networked Services (DANS) |
publishDate |
2019 |
url |
https://doi.org/10.5061/dryad.8382j4r |
long_lat |
ENVELOPE(128.867,128.867,71.633,71.633) |
geographic |
Arctic Tiksi |
geographic_facet |
Arctic Tiksi |
genre |
Arctic Betula nana Climate change Eriophorum permafrost Tiksi Tundra Siberia |
genre_facet |
Arctic Betula nana Climate change Eriophorum permafrost Tiksi Tundra Siberia |
op_source |
oai:easy.dans.knaw.nl:easy-dataset:104002 10.5061/dryad.8382j4r oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:104002 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f re3data_____::r3d100000044 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 |
op_relation |
http://dx.doi.org/10.5061/dryad.8382j4r https://dx.doi.org/10.5061/dryad.8382j4r |
op_rights |
lic_creative-commons |
op_doi |
https://doi.org/10.5061/dryad.8382j4r https://doi.org/10.5061/DRYAD.8382J4R |
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1766325308659597312 |