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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ftdatacite:10.6084/m9.figshare.10267310.v1 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.v1 https://tandf.figshare.com/articles/Soil_organic_carbon_predictions_in_Subarctic_Greenland_by_visible_near_infrared_spectroscopy/10267310/1 unknown Taylor & Francis https://dx.doi.org/10.1080/15230430.2019.1679939 https://dx.doi.org/10.6084/m9.figshare.10267310 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.v1 https://doi.org/10.1080/15230430.2019.1679939 https://doi.org/10.6084/m9.figshare.10267310 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 |
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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.v1 https://tandf.figshare.com/articles/Soil_organic_carbon_predictions_in_Subarctic_Greenland_by_visible_near_infrared_spectroscopy/10267310/1 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Subarctic |
genre_facet |
Greenland Subarctic |
op_relation |
https://dx.doi.org/10.1080/15230430.2019.1679939 https://dx.doi.org/10.6084/m9.figshare.10267310 |
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.v1 https://doi.org/10.1080/15230430.2019.1679939 https://doi.org/10.6084/m9.figshare.10267310 |
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