How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Loss-on-ignition (LOI) is the most widely used measure of organic matter in lake sediments, a variable related to both climate and land-use change. The main drawback for conventional measurement methods is the processing time and hence high labor costs associated with high-resolution analyses. On th...

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Published in:Journal of Paleolimnology
Main Authors: Ancin Murguzur, Francisco Javier, Brown, Antony, Clarke, Charlotte, Sjøgren, Per Johan E, Svendsen, John-Inge, Alsos, Inger Greve
Format: Article in Journal/Newspaper
Language:English
Published: Springer 2020
Subjects:
Online Access:https://hdl.handle.net/10037/20725
https://doi.org/10.1007/s10933-020-00121-5
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spelling ftunivtroemsoe:oai:munin.uit.no:10037/20725 2023-05-15T14:28:02+02:00 How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes? Ancin Murguzur, Francisco Javier Brown, Antony Clarke, Charlotte Sjøgren, Per Johan E Svendsen, John-Inge Alsos, Inger Greve 2020-05-19 https://hdl.handle.net/10037/20725 https://doi.org/10.1007/s10933-020-00121-5 eng eng Springer Journal of Paleolimnology Norges forskningsråd: 250963/F20 Norges forskningsråd: 250963 Norges forskningsråd: 255415 info:eu-repo/grantAgreement/RCN/FRIMEDBIO/213692/Norway/Ancient DNA of NW Europe reveals responses to climate change// info:eu-repo/grantAgreement/RCN/KLIMAFORSK/255415/Norway/Climate History along the Arctic Seaboard of Eurasia/CHASE/ info:eu-repo/grantAgreement/RCN/FRIMEDBIO/250963/Norway/ECOGEN - Ecosystem change and species persistence over time: a genome-based approach/ECOGEN/ Ancin Murguzur, Brown AG, Clarke, Sjøgren, Svendsen, Alsos. How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?. Journal of Paleolimnology. 2020;64(2):59-69 FRIDAID 1820434 doi:10.1007/s10933-020-00121-5 0921-2728 1573-0417 https://hdl.handle.net/10037/20725 openAccess Copyright 2020 The Author(s) VDP::Mathematics and natural science: 400 VDP::Matematikk og Naturvitenskap: 400 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2020 ftunivtroemsoe https://doi.org/10.1007/s10933-020-00121-5 2021-06-25T17:57:56Z Loss-on-ignition (LOI) is the most widely used measure of organic matter in lake sediments, a variable related to both climate and land-use change. The main drawback for conventional measurement methods is the processing time and hence high labor costs associated with high-resolution analyses. On the other hand, broad-based near infrared reflectance spectroscopy (NIRS) is a time and cost efficient method to measure organic carbon and organic matter content in lacustrine sediments once predictive methods are developed. NIRS-based predictive models are most robust when applied to sediments with properties that are already included in the calibration dataset. To test the potential for a broad applicability of NIRS models in samples foreign to the calibration model using linear corrections, sediment cores from six lakes (537 samples, LOI range 1.03–85%) were used as reference samples to develop a predictive model. The applicability of the model was assessed by sequentially removing one lake from the reference dataset, developing a new model and then validating it against the removed lake. Results indicated that NIRS has a high predictive power (RMSEP < 4.79) for LOI with the need for intercept and slope correction for new cores measured by NIRS. For studies involving many samples, NIRS is a cost and time-efficient method to estimate LOI on a range of lake sediments with only linear bias adjustments for different records. Article in Journal/Newspaper Arctic University of Tromsø: Munin Open Research Archive Journal of Paleolimnology 64 2 59 69
institution Open Polar
collection University of Tromsø: Munin Open Research Archive
op_collection_id ftunivtroemsoe
language English
topic VDP::Mathematics and natural science: 400
VDP::Matematikk og Naturvitenskap: 400
spellingShingle VDP::Mathematics and natural science: 400
VDP::Matematikk og Naturvitenskap: 400
Ancin Murguzur, Francisco Javier
Brown, Antony
Clarke, Charlotte
Sjøgren, Per Johan E
Svendsen, John-Inge
Alsos, Inger Greve
How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
topic_facet VDP::Mathematics and natural science: 400
VDP::Matematikk og Naturvitenskap: 400
description Loss-on-ignition (LOI) is the most widely used measure of organic matter in lake sediments, a variable related to both climate and land-use change. The main drawback for conventional measurement methods is the processing time and hence high labor costs associated with high-resolution analyses. On the other hand, broad-based near infrared reflectance spectroscopy (NIRS) is a time and cost efficient method to measure organic carbon and organic matter content in lacustrine sediments once predictive methods are developed. NIRS-based predictive models are most robust when applied to sediments with properties that are already included in the calibration dataset. To test the potential for a broad applicability of NIRS models in samples foreign to the calibration model using linear corrections, sediment cores from six lakes (537 samples, LOI range 1.03–85%) were used as reference samples to develop a predictive model. The applicability of the model was assessed by sequentially removing one lake from the reference dataset, developing a new model and then validating it against the removed lake. Results indicated that NIRS has a high predictive power (RMSEP < 4.79) for LOI with the need for intercept and slope correction for new cores measured by NIRS. For studies involving many samples, NIRS is a cost and time-efficient method to estimate LOI on a range of lake sediments with only linear bias adjustments for different records.
format Article in Journal/Newspaper
author Ancin Murguzur, Francisco Javier
Brown, Antony
Clarke, Charlotte
Sjøgren, Per Johan E
Svendsen, John-Inge
Alsos, Inger Greve
author_facet Ancin Murguzur, Francisco Javier
Brown, Antony
Clarke, Charlotte
Sjøgren, Per Johan E
Svendsen, John-Inge
Alsos, Inger Greve
author_sort Ancin Murguzur, Francisco Javier
title How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
title_short How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
title_full How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
title_fullStr How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
title_full_unstemmed How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?
title_sort how well can near infrared reflectance spectroscopy (nirs) measure sediment organic matter in multiple lakes?
publisher Springer
publishDate 2020
url https://hdl.handle.net/10037/20725
https://doi.org/10.1007/s10933-020-00121-5
genre Arctic
genre_facet Arctic
op_relation Journal of Paleolimnology
Norges forskningsråd: 250963/F20
Norges forskningsråd: 250963
Norges forskningsråd: 255415
info:eu-repo/grantAgreement/RCN/FRIMEDBIO/213692/Norway/Ancient DNA of NW Europe reveals responses to climate change//
info:eu-repo/grantAgreement/RCN/KLIMAFORSK/255415/Norway/Climate History along the Arctic Seaboard of Eurasia/CHASE/
info:eu-repo/grantAgreement/RCN/FRIMEDBIO/250963/Norway/ECOGEN - Ecosystem change and species persistence over time: a genome-based approach/ECOGEN/
Ancin Murguzur, Brown AG, Clarke, Sjøgren, Svendsen, Alsos. How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?. Journal of Paleolimnology. 2020;64(2):59-69
FRIDAID 1820434
doi:10.1007/s10933-020-00121-5
0921-2728
1573-0417
https://hdl.handle.net/10037/20725
op_rights openAccess
Copyright 2020 The Author(s)
op_doi https://doi.org/10.1007/s10933-020-00121-5
container_title Journal of Paleolimnology
container_volume 64
container_issue 2
container_start_page 59
op_container_end_page 69
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