Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy

Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland....

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Main Authors: M. Ogrič, M. Knadel, S. M. Kristiansen, Y. Peng, L. W. De Jonge, K. Adhikari, M. H. Greve
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Published: Taylor & Francis 2019
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Online Access:https://dx.doi.org/10.6084/m9.figshare.10267310
https://tandf.figshare.com/articles/Soil_organic_carbon_predictions_in_Subarctic_Greenland_by_visible_near_infrared_spectroscopy/10267310
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spelling ftdatacite:10.6084/m9.figshare.10267310 2023-05-15T16:28:27+02:00 Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy M. Ogrič M. Knadel S. M. Kristiansen Y. Peng L. W. De Jonge K. Adhikari M. H. Greve 2019 https://dx.doi.org/10.6084/m9.figshare.10267310 https://tandf.figshare.com/articles/Soil_organic_carbon_predictions_in_Subarctic_Greenland_by_visible_near_infrared_spectroscopy/10267310 unknown Taylor & Francis https://dx.doi.org/10.1080/15230430.2019.1679939 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY 59999 Environmental Sciences not elsewhere classified FOS Earth and related environmental sciences 39999 Chemical Sciences not elsewhere classified FOS Chemical sciences Ecology FOS Biological sciences Sociology FOS Sociology 69999 Biological Sciences not elsewhere classified Text article-journal Journal contribution ScholarlyArticle 2019 ftdatacite https://doi.org/10.6084/m9.figshare.10267310 https://doi.org/10.1080/15230430.2019.1679939 2021-11-05T12:55:41Z Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland. Soil samples were collected at two sites and analyzed with vis-NIRS. We used partial least square regression (PLS-R) modeling to predict SOC from vis-NIRS spectra referenced against in situ dry combustion measurements. The ability of our approach was validated in three setups: (1) calibration and validation data sets from the same location, (2) calibration and validation data sets from different locations, and (3) the same setup as in (2) with the calibration model enlarged with few samples from the opposite target area. Vis-NIRS predictions were successful in setup 1 ( R 2 = 0.95, root mean square error of prediction [RMSEP] = 1.80 percent and R 2 = 0.82, RMSEP = 0.64 percent). Predictions in setup 2 had higher errors ( R 2 = 0.90, RMSEP = 7.13 percent and R 2 = 0.78, RMSEP = 2.82 percent). In setup 3, the results were again improved ( R 2 = 0.95, RMSEP = 2.03 percent and R 2 = 0.77, RMSEP = 2.14 percent). We conclude that vis-NIRS can obtain good results predicting SOC concentrations across two subarctic ecosystems, when the calibration models are augmented with few samples from the target site. Future efforts should be made toward determination of SOC stocks to constrain soil–atmosphere carbon exchange. Text Greenland Subarctic DataCite Metadata Store (German National Library of Science and Technology) Greenland
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
39999 Chemical Sciences not elsewhere classified
FOS Chemical sciences
Ecology
FOS Biological sciences
Sociology
FOS Sociology
69999 Biological Sciences not elsewhere classified
spellingShingle 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
39999 Chemical Sciences not elsewhere classified
FOS Chemical sciences
Ecology
FOS Biological sciences
Sociology
FOS Sociology
69999 Biological Sciences not elsewhere classified
M. Ogrič
M. Knadel
S. M. Kristiansen
Y. Peng
L. W. De Jonge
K. Adhikari
M. H. Greve
Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
topic_facet 59999 Environmental Sciences not elsewhere classified
FOS Earth and related environmental sciences
39999 Chemical Sciences not elsewhere classified
FOS Chemical sciences
Ecology
FOS Biological sciences
Sociology
FOS Sociology
69999 Biological Sciences not elsewhere classified
description Release of carbon from high-latitude soils to the atmosphere may have significant effects on Earth’s climate. In this contribution, we evaluate visible–near-infrared spectroscopy (vis-NIRS) as a time- and cost-efficient tool for assessing soil organic carbon (SOC) concentrations in South Greenland. Soil samples were collected at two sites and analyzed with vis-NIRS. We used partial least square regression (PLS-R) modeling to predict SOC from vis-NIRS spectra referenced against in situ dry combustion measurements. The ability of our approach was validated in three setups: (1) calibration and validation data sets from the same location, (2) calibration and validation data sets from different locations, and (3) the same setup as in (2) with the calibration model enlarged with few samples from the opposite target area. Vis-NIRS predictions were successful in setup 1 ( R 2 = 0.95, root mean square error of prediction [RMSEP] = 1.80 percent and R 2 = 0.82, RMSEP = 0.64 percent). Predictions in setup 2 had higher errors ( R 2 = 0.90, RMSEP = 7.13 percent and R 2 = 0.78, RMSEP = 2.82 percent). In setup 3, the results were again improved ( R 2 = 0.95, RMSEP = 2.03 percent and R 2 = 0.77, RMSEP = 2.14 percent). We conclude that vis-NIRS can obtain good results predicting SOC concentrations across two subarctic ecosystems, when the calibration models are augmented with few samples from the target site. Future efforts should be made toward determination of SOC stocks to constrain soil–atmosphere carbon exchange.
format Text
author M. Ogrič
M. Knadel
S. M. Kristiansen
Y. Peng
L. W. De Jonge
K. Adhikari
M. H. Greve
author_facet M. Ogrič
M. Knadel
S. M. Kristiansen
Y. Peng
L. W. De Jonge
K. Adhikari
M. H. Greve
author_sort M. Ogrič
title Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
title_short Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
title_full Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
title_fullStr Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
title_full_unstemmed Soil organic carbon predictions in Subarctic Greenland by visible–near infrared spectroscopy
title_sort soil organic carbon predictions in subarctic greenland by visible–near infrared spectroscopy
publisher Taylor & Francis
publishDate 2019
url https://dx.doi.org/10.6084/m9.figshare.10267310
https://tandf.figshare.com/articles/Soil_organic_carbon_predictions_in_Subarctic_Greenland_by_visible_near_infrared_spectroscopy/10267310
geographic Greenland
geographic_facet Greenland
genre Greenland
Subarctic
genre_facet Greenland
Subarctic
op_relation https://dx.doi.org/10.1080/15230430.2019.1679939
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.6084/m9.figshare.10267310
https://doi.org/10.1080/15230430.2019.1679939
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