Loading…
Foliar functional traits from imaging spectroscopy across biomes in eastern North America
• Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and div...
Saved in:
Published in: | The New phytologist 2020-10, Vol.228 (2), p.494-511 |
---|---|
Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843 |
---|---|
cites | cdi_FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843 |
container_end_page | 511 |
container_issue | 2 |
container_start_page | 494 |
container_title | The New phytologist |
container_volume | 228 |
creator | Wang, Zhihui Chlus, Adam Geygan, Ryan Ye, Zhiwei Zheng, Ting Singh, Aditya Couture, John J. Cavender-Bares, Jeannine Kruger, Eric L. Townsend, Philip A. |
description | • Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.
• With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.
• Model validation accuracy varied among traits (normalized root mean squared error, 9.1– 19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.
• Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity. |
doi_str_mv | 10.1111/nph.16711 |
format | article |
fullrecord | <record><control><sourceid>jstor_osti_</sourceid><recordid>TN_cdi_osti_scitechconnect_1634258</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26968104</jstor_id><sourcerecordid>26968104</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843</originalsourceid><addsrcrecordid>eNp10U9vFCEYBnBiNHZbPfgBNMRe9DAt_waYY9NYa9JUD5roiQDDdNnMwAhMzH572U7bg4lc4PB7n5D3AeANRme4nvMwb88wFxg_AxvMeNdITMVzsEGIyIYz_vMIHOe8Qwh1LScvwREljNOOiA34dRVHrxMclmCLj0GPsCTtS4ZDihP0k77z4Q7m2dmSYrZx3kNt6ytD4-PkMvQBOp2LSwHexlS28GJyyVv9CrwY9Jjd64f7BPy4-vT98rq5-fr5y-XFTWMZFbhh0ri2k0OvLRe9cKalbBAUWWEw0cy0oiWmZ5R3mDozGEO7QUhtcc80tZLRE_B-zY25eJWtL85ubQyh_lhhThlpZUUfVjSn-HtxuajJZ-vGUQcXl6wIQxJ3XUt4paf_0F1cUl3MQbGWtELIg_q4qvtdJDeoOdVlpb3CSB1KUbUUdV9Kte8eEhczuf5JPrZQwfkK_vjR7f-fpG6_XT9Gvl0ndrnE9DRBeMclRoz-BVzdn48</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2445257786</pqid></control><display><type>article</type><title>Foliar functional traits from imaging spectroscopy across biomes in eastern North America</title><source>Wiley:Jisc Collections:Wiley Read and Publish Open Access 2024-2025 (reading list)</source><source>JSTOR Archival Journals and Primary Sources Collection</source><creator>Wang, Zhihui ; Chlus, Adam ; Geygan, Ryan ; Ye, Zhiwei ; Zheng, Ting ; Singh, Aditya ; Couture, John J. ; Cavender-Bares, Jeannine ; Kruger, Eric L. ; Townsend, Philip A.</creator><creatorcontrib>Wang, Zhihui ; Chlus, Adam ; Geygan, Ryan ; Ye, Zhiwei ; Zheng, Ting ; Singh, Aditya ; Couture, John J. ; Cavender-Bares, Jeannine ; Kruger, Eric L. ; Townsend, Philip A.</creatorcontrib><description>• Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.
• With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.
• Model validation accuracy varied among traits (normalized root mean squared error, 9.1– 19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.
• Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.</description><identifier>ISSN: 0028-646X</identifier><identifier>EISSN: 1469-8137</identifier><identifier>DOI: 10.1111/nph.16711</identifier><identifier>PMID: 32463927</identifier><language>eng</language><publisher>England: Wiley</publisher><subject>Analytical methods ; Continuity (mathematics) ; Domains ; Ecosystem ; Ecosystem assessment ; Ecosystem models ; ecosystem processes ; Environment models ; foliar functional traits ; Forests ; Grasslands ; Imaging ; imaging spectroscopy ; Imaging techniques ; Leaves ; Mapping ; Model accuracy ; NEON ; North America ; Phenolic compounds ; Phenols ; Plant cover ; Plant Leaves ; Regression analysis ; Spectroscopy ; Spectrum Analysis ; trait map database ; Tropical forests ; Tundra</subject><ispartof>The New phytologist, 2020-10, Vol.228 (2), p.494-511</ispartof><rights>2020 The Authors © 2020 New Phytologist Trust</rights><rights>2020 The Authors. New Phytologist © 2020 New Phytologist Trust</rights><rights>2020 The Authors. New Phytologist © 2020 New Phytologist Trust.</rights><rights>Copyright © 2020 New Phytologist Trust</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843</citedby><cites>FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843</cites><orcidid>0000-0003-4784-4537 ; 0000-0001-5559-9151 ; 0000-0003-3375-9630 ; 0000-0003-1064-7820 ; 0000-0003-4728-6627 ; 0000-0001-6719-9956 ; 0000-0003-2463-9231 ; 0000-0001-7003-8774 ; 0000-0001-5673-7034 ; 0000000347844537 ; 0000000156737034 ; 0000000170038774 ; 0000000347286627 ; 0000000167199956 ; 0000000324639231 ; 0000000155599151 ; 0000000333759630 ; 0000000310647820</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26968104$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26968104$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,885,27922,27923,58236,58469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32463927$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1634258$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Zhihui</creatorcontrib><creatorcontrib>Chlus, Adam</creatorcontrib><creatorcontrib>Geygan, Ryan</creatorcontrib><creatorcontrib>Ye, Zhiwei</creatorcontrib><creatorcontrib>Zheng, Ting</creatorcontrib><creatorcontrib>Singh, Aditya</creatorcontrib><creatorcontrib>Couture, John J.</creatorcontrib><creatorcontrib>Cavender-Bares, Jeannine</creatorcontrib><creatorcontrib>Kruger, Eric L.</creatorcontrib><creatorcontrib>Townsend, Philip A.</creatorcontrib><title>Foliar functional traits from imaging spectroscopy across biomes in eastern North America</title><title>The New phytologist</title><addtitle>New Phytol</addtitle><description>• Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.
• With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.
• Model validation accuracy varied among traits (normalized root mean squared error, 9.1– 19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.
• Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.</description><subject>Analytical methods</subject><subject>Continuity (mathematics)</subject><subject>Domains</subject><subject>Ecosystem</subject><subject>Ecosystem assessment</subject><subject>Ecosystem models</subject><subject>ecosystem processes</subject><subject>Environment models</subject><subject>foliar functional traits</subject><subject>Forests</subject><subject>Grasslands</subject><subject>Imaging</subject><subject>imaging spectroscopy</subject><subject>Imaging techniques</subject><subject>Leaves</subject><subject>Mapping</subject><subject>Model accuracy</subject><subject>NEON</subject><subject>North America</subject><subject>Phenolic compounds</subject><subject>Phenols</subject><subject>Plant cover</subject><subject>Plant Leaves</subject><subject>Regression analysis</subject><subject>Spectroscopy</subject><subject>Spectrum Analysis</subject><subject>trait map database</subject><subject>Tropical forests</subject><subject>Tundra</subject><issn>0028-646X</issn><issn>1469-8137</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10U9vFCEYBnBiNHZbPfgBNMRe9DAt_waYY9NYa9JUD5roiQDDdNnMwAhMzH572U7bg4lc4PB7n5D3AeANRme4nvMwb88wFxg_AxvMeNdITMVzsEGIyIYz_vMIHOe8Qwh1LScvwREljNOOiA34dRVHrxMclmCLj0GPsCTtS4ZDihP0k77z4Q7m2dmSYrZx3kNt6ytD4-PkMvQBOp2LSwHexlS28GJyyVv9CrwY9Jjd64f7BPy4-vT98rq5-fr5y-XFTWMZFbhh0ri2k0OvLRe9cKalbBAUWWEw0cy0oiWmZ5R3mDozGEO7QUhtcc80tZLRE_B-zY25eJWtL85ubQyh_lhhThlpZUUfVjSn-HtxuajJZ-vGUQcXl6wIQxJ3XUt4paf_0F1cUl3MQbGWtELIg_q4qvtdJDeoOdVlpb3CSB1KUbUUdV9Kte8eEhczuf5JPrZQwfkK_vjR7f-fpG6_XT9Gvl0ndrnE9DRBeMclRoz-BVzdn48</recordid><startdate>202010</startdate><enddate>202010</enddate><creator>Wang, Zhihui</creator><creator>Chlus, Adam</creator><creator>Geygan, Ryan</creator><creator>Ye, Zhiwei</creator><creator>Zheng, Ting</creator><creator>Singh, Aditya</creator><creator>Couture, John J.</creator><creator>Cavender-Bares, Jeannine</creator><creator>Kruger, Eric L.</creator><creator>Townsend, Philip A.</creator><general>Wiley</general><general>Wiley Subscription Services, Inc</general><general>Wiley-Blackwell</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H95</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000-0003-4784-4537</orcidid><orcidid>https://orcid.org/0000-0001-5559-9151</orcidid><orcidid>https://orcid.org/0000-0003-3375-9630</orcidid><orcidid>https://orcid.org/0000-0003-1064-7820</orcidid><orcidid>https://orcid.org/0000-0003-4728-6627</orcidid><orcidid>https://orcid.org/0000-0001-6719-9956</orcidid><orcidid>https://orcid.org/0000-0003-2463-9231</orcidid><orcidid>https://orcid.org/0000-0001-7003-8774</orcidid><orcidid>https://orcid.org/0000-0001-5673-7034</orcidid><orcidid>https://orcid.org/0000000347844537</orcidid><orcidid>https://orcid.org/0000000156737034</orcidid><orcidid>https://orcid.org/0000000170038774</orcidid><orcidid>https://orcid.org/0000000347286627</orcidid><orcidid>https://orcid.org/0000000167199956</orcidid><orcidid>https://orcid.org/0000000324639231</orcidid><orcidid>https://orcid.org/0000000155599151</orcidid><orcidid>https://orcid.org/0000000333759630</orcidid><orcidid>https://orcid.org/0000000310647820</orcidid></search><sort><creationdate>202010</creationdate><title>Foliar functional traits from imaging spectroscopy across biomes in eastern North America</title><author>Wang, Zhihui ; Chlus, Adam ; Geygan, Ryan ; Ye, Zhiwei ; Zheng, Ting ; Singh, Aditya ; Couture, John J. ; Cavender-Bares, Jeannine ; Kruger, Eric L. ; Townsend, Philip A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analytical methods</topic><topic>Continuity (mathematics)</topic><topic>Domains</topic><topic>Ecosystem</topic><topic>Ecosystem assessment</topic><topic>Ecosystem models</topic><topic>ecosystem processes</topic><topic>Environment models</topic><topic>foliar functional traits</topic><topic>Forests</topic><topic>Grasslands</topic><topic>Imaging</topic><topic>imaging spectroscopy</topic><topic>Imaging techniques</topic><topic>Leaves</topic><topic>Mapping</topic><topic>Model accuracy</topic><topic>NEON</topic><topic>North America</topic><topic>Phenolic compounds</topic><topic>Phenols</topic><topic>Plant cover</topic><topic>Plant Leaves</topic><topic>Regression analysis</topic><topic>Spectroscopy</topic><topic>Spectrum Analysis</topic><topic>trait map database</topic><topic>Tropical forests</topic><topic>Tundra</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Zhihui</creatorcontrib><creatorcontrib>Chlus, Adam</creatorcontrib><creatorcontrib>Geygan, Ryan</creatorcontrib><creatorcontrib>Ye, Zhiwei</creatorcontrib><creatorcontrib>Zheng, Ting</creatorcontrib><creatorcontrib>Singh, Aditya</creatorcontrib><creatorcontrib>Couture, John J.</creatorcontrib><creatorcontrib>Cavender-Bares, Jeannine</creatorcontrib><creatorcontrib>Kruger, Eric L.</creatorcontrib><creatorcontrib>Townsend, Philip A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>OSTI.GOV</collection><jtitle>The New phytologist</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Zhihui</au><au>Chlus, Adam</au><au>Geygan, Ryan</au><au>Ye, Zhiwei</au><au>Zheng, Ting</au><au>Singh, Aditya</au><au>Couture, John J.</au><au>Cavender-Bares, Jeannine</au><au>Kruger, Eric L.</au><au>Townsend, Philip A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Foliar functional traits from imaging spectroscopy across biomes in eastern North America</atitle><jtitle>The New phytologist</jtitle><addtitle>New Phytol</addtitle><date>2020-10</date><risdate>2020</risdate><volume>228</volume><issue>2</issue><spage>494</spage><epage>511</epage><pages>494-511</pages><issn>0028-646X</issn><eissn>1469-8137</eissn><abstract>• Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.
• With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.
• Model validation accuracy varied among traits (normalized root mean squared error, 9.1– 19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.
• Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.</abstract><cop>England</cop><pub>Wiley</pub><pmid>32463927</pmid><doi>10.1111/nph.16711</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0003-4784-4537</orcidid><orcidid>https://orcid.org/0000-0001-5559-9151</orcidid><orcidid>https://orcid.org/0000-0003-3375-9630</orcidid><orcidid>https://orcid.org/0000-0003-1064-7820</orcidid><orcidid>https://orcid.org/0000-0003-4728-6627</orcidid><orcidid>https://orcid.org/0000-0001-6719-9956</orcidid><orcidid>https://orcid.org/0000-0003-2463-9231</orcidid><orcidid>https://orcid.org/0000-0001-7003-8774</orcidid><orcidid>https://orcid.org/0000-0001-5673-7034</orcidid><orcidid>https://orcid.org/0000000347844537</orcidid><orcidid>https://orcid.org/0000000156737034</orcidid><orcidid>https://orcid.org/0000000170038774</orcidid><orcidid>https://orcid.org/0000000347286627</orcidid><orcidid>https://orcid.org/0000000167199956</orcidid><orcidid>https://orcid.org/0000000324639231</orcidid><orcidid>https://orcid.org/0000000155599151</orcidid><orcidid>https://orcid.org/0000000333759630</orcidid><orcidid>https://orcid.org/0000000310647820</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0028-646X |
ispartof | The New phytologist, 2020-10, Vol.228 (2), p.494-511 |
issn | 0028-646X 1469-8137 |
language | eng |
recordid | cdi_osti_scitechconnect_1634258 |
source | Wiley:Jisc Collections:Wiley Read and Publish Open Access 2024-2025 (reading list); JSTOR Archival Journals and Primary Sources Collection |
subjects | Analytical methods Continuity (mathematics) Domains Ecosystem Ecosystem assessment Ecosystem models ecosystem processes Environment models foliar functional traits Forests Grasslands Imaging imaging spectroscopy Imaging techniques Leaves Mapping Model accuracy NEON North America Phenolic compounds Phenols Plant cover Plant Leaves Regression analysis Spectroscopy Spectrum Analysis trait map database Tropical forests Tundra |
title | Foliar functional traits from imaging spectroscopy across biomes in eastern North America |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T11%3A43%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_osti_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Foliar%20functional%20traits%20from%20imaging%20spectroscopy%20across%20biomes%20in%20eastern%20North%20America&rft.jtitle=The%20New%20phytologist&rft.au=Wang,%20Zhihui&rft.date=2020-10&rft.volume=228&rft.issue=2&rft.spage=494&rft.epage=511&rft.pages=494-511&rft.issn=0028-646X&rft.eissn=1469-8137&rft_id=info:doi/10.1111/nph.16711&rft_dat=%3Cjstor_osti_%3E26968104%3C/jstor_osti_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4371-48be598fdac67d7eb534f730c7b12a4b5752bd436913ebfbb39f78ac1d4a3c843%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2445257786&rft_id=info:pmid/32463927&rft_jstor_id=26968104&rfr_iscdi=true |