Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/32839
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem
Author(s): Azevedo, Olivia
Parker, Thomas C
Siewert, Matthias B
Subke, Jens-Arne
Keywords: Abisko
CO2 flux
LAI
modelling
plant functional type
SOC
vegetation index
Issue Date: Jul-2021
Date Deposited: 5-Jul-2021
Citation: Azevedo O, Parker TC, Siewert MB & Subke J (2021) Predicting Soil Respiration from Plant Productivity (NDVI) in a Sub-Arctic Tundra Ecosystem. Remote Sensing, 13 (13), Art. No.: 2571. https://doi.org/10.3390/rs13132571
Abstract: 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 CO2 from this C-rich ecosystem. Monitoring soil respiration (Rs) 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 Rs 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 Rs 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.
DOI Link: 10.3390/rs13132571
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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