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The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling

Background An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (RS) data has not kept pace. Scope We identify three major challenges in interpreting RS data, and opportunities to utilize it more extensively and creati...

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Published in:Plant and soil 2017-04, Vol.413 (1/2), p.1-27
Main Authors: Phillips, Claire L., Bond-Lamberty, Ben, Desai, Ankur R., Lavoie, Martin, Risk, Dave, Tang, Jianwu, Todd-Brown, Katherine, Vargas, Rodrigo
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cited_by cdi_FETCH-LOGICAL-c546t-4eb161fcb9a902e6817c42f1862558ed1169ebe01da5aa393cbfde1e88d1e27e3
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container_issue 1/2
container_start_page 1
container_title Plant and soil
container_volume 413
creator Phillips, Claire L.
Bond-Lamberty, Ben
Desai, Ankur R.
Lavoie, Martin
Risk, Dave
Tang, Jianwu
Todd-Brown, Katherine
Vargas, Rodrigo
description Background An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (RS) data has not kept pace. Scope We identify three major challenges in interpreting RS data, and opportunities to utilize it more extensively and creatively: (1) When RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find RS > RECO. We argue this is most likely due to difficulties in calculating RECO, which provides an opportunity to utilize RS for EC quality control. (2) RS integrates belowground heterotrophic and autotrophic activity, but many models include only an explicit heterotrophic output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. (3) RS is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Downscaling EC fluxes to match the scale of RS, and improvement of RS upscaling techniques will improve resolution challenges. Conclusions RS data can bring a range of benefits to model development, particularly with larger databases and improved data sharing protocols to make RS data more robust and broadly available to the research community.
doi_str_mv 10.1007/s11104-016-3084-x
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(3) RS is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Downscaling EC fluxes to match the scale of RS, and improvement of RS upscaling techniques will improve resolution challenges. Conclusions RS data can bring a range of benefits to model development, particularly with larger databases and improved data sharing protocols to make RS data more robust and broadly available to the research community.</description><identifier>ISSN: 0032-079X</identifier><identifier>EISSN: 1573-5036</identifier><identifier>DOI: 10.1007/s11104-016-3084-x</identifier><language>eng</language><publisher>Cham: Springer</publisher><subject>Analysis ; Biomedical and Life Sciences ; Carbon cycle ; Data collection ; Datasets ; Ecology ; Life Sciences ; MARSCHNER REVIEW ; Measurement ; Plant Physiology ; Plant Sciences ; Quality control ; Respiration ; Scale models ; Soil carbon ; soil respiration ; Soil Science &amp; Conservation ; Soils</subject><ispartof>Plant and soil, 2017-04, Vol.413 (1/2), p.1-27</ispartof><rights>Springer Science+Business Media 2017</rights><rights>Springer International Publishing Switzerland 2017</rights><rights>COPYRIGHT 2017 Springer</rights><rights>Plant and Soil is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c546t-4eb161fcb9a902e6817c42f1862558ed1169ebe01da5aa393cbfde1e88d1e27e3</citedby><cites>FETCH-LOGICAL-c546t-4eb161fcb9a902e6817c42f1862558ed1169ebe01da5aa393cbfde1e88d1e27e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/44245285$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/44245285$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,885,27923,27924,58237,58470</link.rule.ids><backlink>$$Uhttps://www.osti.gov/biblio/1358494$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Phillips, Claire L.</creatorcontrib><creatorcontrib>Bond-Lamberty, Ben</creatorcontrib><creatorcontrib>Desai, Ankur R.</creatorcontrib><creatorcontrib>Lavoie, Martin</creatorcontrib><creatorcontrib>Risk, Dave</creatorcontrib><creatorcontrib>Tang, Jianwu</creatorcontrib><creatorcontrib>Todd-Brown, Katherine</creatorcontrib><creatorcontrib>Vargas, Rodrigo</creatorcontrib><creatorcontrib>Pacific Northwest National Lab. (PNNL), Richland, WA (United States)</creatorcontrib><title>The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling</title><title>Plant and soil</title><addtitle>Plant Soil</addtitle><description>Background An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (RS) data has not kept pace. Scope We identify three major challenges in interpreting RS data, and opportunities to utilize it more extensively and creatively: (1) When RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find RS &gt; RECO. We argue this is most likely due to difficulties in calculating RECO, which provides an opportunity to utilize RS for EC quality control. (2) RS integrates belowground heterotrophic and autotrophic activity, but many models include only an explicit heterotrophic output. 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(PNNL), Richland, WA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling</atitle><jtitle>Plant and soil</jtitle><stitle>Plant Soil</stitle><date>2017-04-01</date><risdate>2017</risdate><volume>413</volume><issue>1/2</issue><spage>1</spage><epage>27</epage><pages>1-27</pages><issn>0032-079X</issn><eissn>1573-5036</eissn><abstract>Background An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (RS) data has not kept pace. Scope We identify three major challenges in interpreting RS data, and opportunities to utilize it more extensively and creatively: (1) When RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find RS &gt; RECO. We argue this is most likely due to difficulties in calculating RECO, which provides an opportunity to utilize RS for EC quality control. (2) RS integrates belowground heterotrophic and autotrophic activity, but many models include only an explicit heterotrophic output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. (3) RS is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Downscaling EC fluxes to match the scale of RS, and improvement of RS upscaling techniques will improve resolution challenges. Conclusions RS data can bring a range of benefits to model development, particularly with larger databases and improved data sharing protocols to make RS data more robust and broadly available to the research community.</abstract><cop>Cham</cop><pub>Springer</pub><doi>10.1007/s11104-016-3084-x</doi><tpages>27</tpages><oa>free_for_read</oa></addata></record>
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subjects Analysis
Biomedical and Life Sciences
Carbon cycle
Data collection
Datasets
Ecology
Life Sciences
MARSCHNER REVIEW
Measurement
Plant Physiology
Plant Sciences
Quality control
Respiration
Scale models
Soil carbon
soil respiration
Soil Science & Conservation
Soils
title The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling
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