Loading…

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to...

Full description

Saved in:
Bibliographic Details
Published in:International journal of biometeorology 2018-05, Vol.62 (5), p.823-832
Main Authors: Battisti, R., Sentelhas, P. C., Boote, K. J.
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-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3
cites cdi_FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3
container_end_page 832
container_issue 5
container_start_page 823
container_title International journal of biometeorology
container_volume 62
creator Battisti, R.
Sentelhas, P. C.
Boote, K. J.
description Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (− 30, − 15, 0, + 15, and + 30%), and solar radiation (− 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha −1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from − 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .
doi_str_mv 10.1007/s00484-017-1483-1
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1970874651</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1970874651</sourcerecordid><originalsourceid>FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3</originalsourceid><addsrcrecordid>eNp1kMFu3CAURVGVqjOZ9gOyiZCydgoYA14mUdJWitRF2jXC-NEwsvEM4JGmq3x6mE4SZdMVeuLc93QPQmeUXFJC5NdECFe8IlRWlKu6oh_QkvKaVZQ1_AQtCWGkkpSpBTpNaU1KRgn5CS1YS1uhiFiipwcIyWe_83mPTehxhO3sI4wQMp4c9uMmTrt_YzrMbpojTtO-AxOwjdMGJz_Og8l-CnicehhSYSK2gx9NBmwfTfgDOOW595CwD_hhmvMjxICvo_nrh8_oozNDgi8v7wr9vrv9dfO9uv_57cfN1X1la8ly1TlWO9ZAKcMdt9S1rWKW94wLB4pa0smutrJWvbC96mljm04IKIQRnSWmXqGL497SZztDynpdqoRyUtNWEiW5aGih6JEq1VKK4PQmliJxrynRB-f66FwX5_rgXB8y5y-b526E_i3xKrkA7Aik8lVsxHen_7v1GZlZj5g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1970874651</pqid></control><display><type>article</type><title>Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil</title><source>Springer Link</source><creator>Battisti, R. ; Sentelhas, P. C. ; Boote, K. J.</creator><creatorcontrib>Battisti, R. ; Sentelhas, P. C. ; Boote, K. J.</creatorcontrib><description>Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (− 30, − 15, 0, + 15, and + 30%), and solar radiation (− 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha −1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from − 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .</description><identifier>ISSN: 0020-7128</identifier><identifier>EISSN: 1432-1254</identifier><identifier>DOI: 10.1007/s00484-017-1483-1</identifier><identifier>PMID: 29196806</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Agricultural production ; Air temperature ; Animal Physiology ; Biological and Medical Physics ; Biophysics ; Brazil ; Carbon dioxide ; Carbon Dioxide - analysis ; Climate Change ; Climate models ; Climate studies ; Computer Simulation ; Crop growth ; Crops ; Crops, Agricultural - growth &amp; development ; Crops, Agricultural - metabolism ; Earth and Environmental Science ; Energy balance ; Energy balance of soil ; Environment ; Environmental Health ; Glycine max - growth &amp; development ; Glycine max - metabolism ; Infiltration ; Meteorology ; Models, Theoretical ; Moisture content ; Original Paper ; Photosynthesis ; Plant growth ; Plant Physiology ; Plant Transpiration ; Rain ; Rainfall ; Reduction ; Runoff ; Sensitivity analysis ; Soil dynamics ; Soil temperature ; Soil water ; Solar radiation ; Soybeans ; Sunlight ; Temperature ; Temperature effects ; Temperature requirements ; Temperature rise ; Water availability ; Water infiltration</subject><ispartof>International journal of biometeorology, 2018-05, Vol.62 (5), p.823-832</ispartof><rights>ISB 2017</rights><rights>International Journal of Biometeorology is a copyright of Springer, (2017). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3</citedby><cites>FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3</cites><orcidid>0000-0001-5768-4501</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29196806$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Battisti, R.</creatorcontrib><creatorcontrib>Sentelhas, P. C.</creatorcontrib><creatorcontrib>Boote, K. J.</creatorcontrib><title>Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil</title><title>International journal of biometeorology</title><addtitle>Int J Biometeorol</addtitle><addtitle>Int J Biometeorol</addtitle><description>Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (− 30, − 15, 0, + 15, and + 30%), and solar radiation (− 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha −1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from − 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .</description><subject>Agricultural production</subject><subject>Air temperature</subject><subject>Animal Physiology</subject><subject>Biological and Medical Physics</subject><subject>Biophysics</subject><subject>Brazil</subject><subject>Carbon dioxide</subject><subject>Carbon Dioxide - analysis</subject><subject>Climate Change</subject><subject>Climate models</subject><subject>Climate studies</subject><subject>Computer Simulation</subject><subject>Crop growth</subject><subject>Crops</subject><subject>Crops, Agricultural - growth &amp; development</subject><subject>Crops, Agricultural - metabolism</subject><subject>Earth and Environmental Science</subject><subject>Energy balance</subject><subject>Energy balance of soil</subject><subject>Environment</subject><subject>Environmental Health</subject><subject>Glycine max - growth &amp; development</subject><subject>Glycine max - metabolism</subject><subject>Infiltration</subject><subject>Meteorology</subject><subject>Models, Theoretical</subject><subject>Moisture content</subject><subject>Original Paper</subject><subject>Photosynthesis</subject><subject>Plant growth</subject><subject>Plant Physiology</subject><subject>Plant Transpiration</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Reduction</subject><subject>Runoff</subject><subject>Sensitivity analysis</subject><subject>Soil dynamics</subject><subject>Soil temperature</subject><subject>Soil water</subject><subject>Solar radiation</subject><subject>Soybeans</subject><subject>Sunlight</subject><subject>Temperature</subject><subject>Temperature effects</subject><subject>Temperature requirements</subject><subject>Temperature rise</subject><subject>Water availability</subject><subject>Water infiltration</subject><issn>0020-7128</issn><issn>1432-1254</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kMFu3CAURVGVqjOZ9gOyiZCydgoYA14mUdJWitRF2jXC-NEwsvEM4JGmq3x6mE4SZdMVeuLc93QPQmeUXFJC5NdECFe8IlRWlKu6oh_QkvKaVZQ1_AQtCWGkkpSpBTpNaU1KRgn5CS1YS1uhiFiipwcIyWe_83mPTehxhO3sI4wQMp4c9uMmTrt_YzrMbpojTtO-AxOwjdMGJz_Og8l-CnicehhSYSK2gx9NBmwfTfgDOOW595CwD_hhmvMjxICvo_nrh8_oozNDgi8v7wr9vrv9dfO9uv_57cfN1X1la8ly1TlWO9ZAKcMdt9S1rWKW94wLB4pa0smutrJWvbC96mljm04IKIQRnSWmXqGL497SZztDynpdqoRyUtNWEiW5aGih6JEq1VKK4PQmliJxrynRB-f66FwX5_rgXB8y5y-b526E_i3xKrkA7Aik8lVsxHen_7v1GZlZj5g</recordid><startdate>20180501</startdate><enddate>20180501</enddate><creator>Battisti, R.</creator><creator>Sentelhas, P. C.</creator><creator>Boote, K. J.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</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>3V.</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88F</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KL.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M1Q</scope><scope>M2P</scope><scope>M7P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-5768-4501</orcidid></search><sort><creationdate>20180501</creationdate><title>Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil</title><author>Battisti, R. ; Sentelhas, P. C. ; Boote, K. J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Agricultural production</topic><topic>Air temperature</topic><topic>Animal Physiology</topic><topic>Biological and Medical Physics</topic><topic>Biophysics</topic><topic>Brazil</topic><topic>Carbon dioxide</topic><topic>Carbon Dioxide - analysis</topic><topic>Climate Change</topic><topic>Climate models</topic><topic>Climate studies</topic><topic>Computer Simulation</topic><topic>Crop growth</topic><topic>Crops</topic><topic>Crops, Agricultural - growth &amp; development</topic><topic>Crops, Agricultural - metabolism</topic><topic>Earth and Environmental Science</topic><topic>Energy balance</topic><topic>Energy balance of soil</topic><topic>Environment</topic><topic>Environmental Health</topic><topic>Glycine max - growth &amp; development</topic><topic>Glycine max - metabolism</topic><topic>Infiltration</topic><topic>Meteorology</topic><topic>Models, Theoretical</topic><topic>Moisture content</topic><topic>Original Paper</topic><topic>Photosynthesis</topic><topic>Plant growth</topic><topic>Plant Physiology</topic><topic>Plant Transpiration</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Reduction</topic><topic>Runoff</topic><topic>Sensitivity analysis</topic><topic>Soil dynamics</topic><topic>Soil temperature</topic><topic>Soil water</topic><topic>Solar radiation</topic><topic>Soybeans</topic><topic>Sunlight</topic><topic>Temperature</topic><topic>Temperature effects</topic><topic>Temperature requirements</topic><topic>Temperature rise</topic><topic>Water availability</topic><topic>Water infiltration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Battisti, R.</creatorcontrib><creatorcontrib>Sentelhas, P. C.</creatorcontrib><creatorcontrib>Boote, K. J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Health &amp; Medical Complete (ProQuest Database)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Biological Science Collection</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Military Database</collection><collection>ProQuest Science Journals</collection><collection>ProQuest Biological Science Journals</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><jtitle>International journal of biometeorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Battisti, R.</au><au>Sentelhas, P. C.</au><au>Boote, K. J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil</atitle><jtitle>International journal of biometeorology</jtitle><stitle>Int J Biometeorol</stitle><addtitle>Int J Biometeorol</addtitle><date>2018-05-01</date><risdate>2018</risdate><volume>62</volume><issue>5</issue><spage>823</spage><epage>832</epage><pages>823-832</pages><issn>0020-7128</issn><eissn>1432-1254</eissn><abstract>Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (− 30, − 15, 0, + 15, and + 30%), and solar radiation (− 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha −1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from − 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>29196806</pmid><doi>10.1007/s00484-017-1483-1</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-5768-4501</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0020-7128
ispartof International journal of biometeorology, 2018-05, Vol.62 (5), p.823-832
issn 0020-7128
1432-1254
language eng
recordid cdi_proquest_journals_1970874651
source Springer Link
subjects Agricultural production
Air temperature
Animal Physiology
Biological and Medical Physics
Biophysics
Brazil
Carbon dioxide
Carbon Dioxide - analysis
Climate Change
Climate models
Climate studies
Computer Simulation
Crop growth
Crops
Crops, Agricultural - growth & development
Crops, Agricultural - metabolism
Earth and Environmental Science
Energy balance
Energy balance of soil
Environment
Environmental Health
Glycine max - growth & development
Glycine max - metabolism
Infiltration
Meteorology
Models, Theoretical
Moisture content
Original Paper
Photosynthesis
Plant growth
Plant Physiology
Plant Transpiration
Rain
Rainfall
Reduction
Runoff
Sensitivity analysis
Soil dynamics
Soil temperature
Soil water
Solar radiation
Soybeans
Sunlight
Temperature
Temperature effects
Temperature requirements
Temperature rise
Water availability
Water infiltration
title Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T13%3A58%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Sensitivity%20and%20requirement%20of%20improvements%20of%20four%20soybean%20crop%20simulation%20models%20for%20climate%20change%20studies%20in%20Southern%20Brazil&rft.jtitle=International%20journal%20of%20biometeorology&rft.au=Battisti,%20R.&rft.date=2018-05-01&rft.volume=62&rft.issue=5&rft.spage=823&rft.epage=832&rft.pages=823-832&rft.issn=0020-7128&rft.eissn=1432-1254&rft_id=info:doi/10.1007/s00484-017-1483-1&rft_dat=%3Cproquest_cross%3E1970874651%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c372t-bf23f25e1284f4c1f9982c4d246fe81c0b7b3c738d6cd8d15c5b66ec4da6bc0a3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1970874651&rft_id=info:pmid/29196806&rfr_iscdi=true