Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem

Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exch...

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Published in:Remote Sensing
Main Authors: Olivia Azevedo, Thomas C. Parker, Matthias B. Siewert, Jens-Arne Subke
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
LAI
SOC
Q
Online Access:https://doi.org/10.3390/rs13132571
https://doaj.org/article/1be560c36c284b2b8480c7b1ece35643
id ftdoajarticles:oai:doaj.org/article:1be560c36c284b2b8480c7b1ece35643
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spelling ftdoajarticles:oai:doaj.org/article:1be560c36c284b2b8480c7b1ece35643 2023-05-15T12:59:38+02:00 Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem Olivia Azevedo Thomas C. Parker Matthias B. Siewert Jens-Arne Subke 2021-06-01T00:00:00Z https://doi.org/10.3390/rs13132571 https://doaj.org/article/1be560c36c284b2b8480c7b1ece35643 EN eng MDPI AG https://www.mdpi.com/2072-4292/13/13/2571 https://doaj.org/toc/2072-4292 doi:10.3390/rs13132571 2072-4292 https://doaj.org/article/1be560c36c284b2b8480c7b1ece35643 Remote Sensing, Vol 13, Iss 2571, p 2571 (2021) Abisko CO 2 flux LAI modelling plant functional type SOC Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13132571 2022-12-31T09:47:50Z Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO 2 from this C-rich ecosystem. Monitoring soil respiration (R s ) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of R s from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e 3.508 x , p < 0.001). Our results further suggest that NDVI and soil temperature can help predict R s if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis. Article in Journal/Newspaper Abisko Arctic Tundra Directory of Open Access Journals: DOAJ Articles Abisko ENVELOPE(18.829,18.829,68.349,68.349) Arctic Remote Sensing 13 13 2571
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Abisko
CO 2 flux
LAI
modelling
plant functional type
SOC
Science
Q
spellingShingle Abisko
CO 2 flux
LAI
modelling
plant functional type
SOC
Science
Q
Olivia Azevedo
Thomas C. Parker
Matthias B. Siewert
Jens-Arne Subke
Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
topic_facet Abisko
CO 2 flux
LAI
modelling
plant functional type
SOC
Science
Q
description Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO 2 from this C-rich ecosystem. Monitoring soil respiration (R s ) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of R s from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e 3.508 x , p < 0.001). Our results further suggest that NDVI and soil temperature can help predict R s if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis.
format Article in Journal/Newspaper
author Olivia Azevedo
Thomas C. Parker
Matthias B. Siewert
Jens-Arne Subke
author_facet Olivia Azevedo
Thomas C. Parker
Matthias B. Siewert
Jens-Arne Subke
author_sort Olivia Azevedo
title Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
title_short Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
title_full Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
title_fullStr Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
title_full_unstemmed Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
title_sort predicting soil respiration from plant productivity (ndvi) in a sub-arctic tundra ecosystem
publisher MDPI AG
publishDate 2021
url https://doi.org/10.3390/rs13132571
https://doaj.org/article/1be560c36c284b2b8480c7b1ece35643
long_lat ENVELOPE(18.829,18.829,68.349,68.349)
geographic Abisko
Arctic
geographic_facet Abisko
Arctic
genre Abisko
Arctic
Tundra
genre_facet Abisko
Arctic
Tundra
op_source Remote Sensing, Vol 13, Iss 2571, p 2571 (2021)
op_relation https://www.mdpi.com/2072-4292/13/13/2571
https://doaj.org/toc/2072-4292
doi:10.3390/rs13132571
2072-4292
https://doaj.org/article/1be560c36c284b2b8480c7b1ece35643
op_doi https://doi.org/10.3390/rs13132571
container_title Remote Sensing
container_volume 13
container_issue 13
container_start_page 2571
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