Projecting future crop productivity for global economic modeling

Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two bio...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Agricultural economics 2014-01, Vol.45 (1), p.37-50
Hauptverfasser: Müller, Christoph, Robertson, Richard D
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 50
container_issue 1
container_start_page 37
container_title Agricultural economics
container_volume 45
creator Müller, Christoph
Robertson, Richard D
description Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.
doi_str_mv 10.1111/agec.12088
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1505327831</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3186931371</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5628-5fc257374ae1918852a9bbf47765874ec31b262e00d9c9b9b3c6768201f082593</originalsourceid><addsrcrecordid>eNp9kU9LwzAYh4MoOKcXv4AFLyJ0Jmnz7-YccwpuCm7sGNIsHZ3dMpNW3bc3terBg7kEwvP78b5PADhFsIfCuVJLo3sIQ873QAcRlsaQU7wPOhBRERNE4CE48n4FIUohTjrg-snZldFVsVlGeV3VzkTa2W20dXZRh-e3otpFuXXRsrSZKiOj7cauCx2t7cKUIXUMDnJVenPyfXfB7HY4HdzFD4-j-0H_IdaEYh6TXGPCEpYqgwTinGAlsixPGaOEs9ToBGWYYgPhQmiRiSzRlFGOIcohx0QkXXDR9obJXmvjK7kuvDZlqTbG1l6G1UiCGU9QQM__oCtbu02YTqJUNHUUN4WXLRX29d6ZXG5dsVZuJxGUjUzZyJRfMgOMWvi9KM3uH1L2R8PBTyZuM4WvzMdvRrkXSYMJIueTkZzQ-c0YTkdyHPizls-VDY2u8HL2jJuPgij4Eiz5BI-IjRQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1490825629</pqid></control><display><type>article</type><title>Projecting future crop productivity for global economic modeling</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Müller, Christoph ; Robertson, Richard D</creator><creatorcontrib>Müller, Christoph ; Robertson, Richard D</creatorcontrib><description>Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.</description><identifier>ISSN: 0169-5150</identifier><identifier>EISSN: 1574-0862</identifier><identifier>DOI: 10.1111/agec.12088</identifier><language>eng</language><publisher>Malden: Elsevier Science BV</publisher><subject>Agricultural land ; Agricultural practices ; Agricultural productivity ; Carbon dioxide ; climate ; Climate change ; Climate models ; Crop modeling ; Crop production ; crops ; econometric models ; economic analysis ; Economic models ; Environmental assessment ; Environmental impact ; Environmental protection ; Global economy ; Growth models ; land productivity ; Land use ; markets ; Productivity ; Q100 ; Q190 ; space and time ; uncertainty ; Z000</subject><ispartof>Agricultural economics, 2014-01, Vol.45 (1), p.37-50</ispartof><rights>2013 International Association of Agricultural Economists</rights><rights>2014 International Association of Agricultural Economists</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5628-5fc257374ae1918852a9bbf47765874ec31b262e00d9c9b9b3c6768201f082593</citedby><cites>FETCH-LOGICAL-c5628-5fc257374ae1918852a9bbf47765874ec31b262e00d9c9b9b3c6768201f082593</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fagec.12088$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fagec.12088$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids></links><search><creatorcontrib>Müller, Christoph</creatorcontrib><creatorcontrib>Robertson, Richard D</creatorcontrib><title>Projecting future crop productivity for global economic modeling</title><title>Agricultural economics</title><addtitle>Agricultural Economics</addtitle><description>Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.</description><subject>Agricultural land</subject><subject>Agricultural practices</subject><subject>Agricultural productivity</subject><subject>Carbon dioxide</subject><subject>climate</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Crop modeling</subject><subject>Crop production</subject><subject>crops</subject><subject>econometric models</subject><subject>economic analysis</subject><subject>Economic models</subject><subject>Environmental assessment</subject><subject>Environmental impact</subject><subject>Environmental protection</subject><subject>Global economy</subject><subject>Growth models</subject><subject>land productivity</subject><subject>Land use</subject><subject>markets</subject><subject>Productivity</subject><subject>Q100</subject><subject>Q190</subject><subject>space and time</subject><subject>uncertainty</subject><subject>Z000</subject><issn>0169-5150</issn><issn>1574-0862</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kU9LwzAYh4MoOKcXv4AFLyJ0Jmnz7-YccwpuCm7sGNIsHZ3dMpNW3bc3terBg7kEwvP78b5PADhFsIfCuVJLo3sIQ873QAcRlsaQU7wPOhBRERNE4CE48n4FIUohTjrg-snZldFVsVlGeV3VzkTa2W20dXZRh-e3otpFuXXRsrSZKiOj7cauCx2t7cKUIXUMDnJVenPyfXfB7HY4HdzFD4-j-0H_IdaEYh6TXGPCEpYqgwTinGAlsixPGaOEs9ToBGWYYgPhQmiRiSzRlFGOIcohx0QkXXDR9obJXmvjK7kuvDZlqTbG1l6G1UiCGU9QQM__oCtbu02YTqJUNHUUN4WXLRX29d6ZXG5dsVZuJxGUjUzZyJRfMgOMWvi9KM3uH1L2R8PBTyZuM4WvzMdvRrkXSYMJIueTkZzQ-c0YTkdyHPizls-VDY2u8HL2jJuPgij4Eiz5BI-IjRQ</recordid><startdate>201401</startdate><enddate>201401</enddate><creator>Müller, Christoph</creator><creator>Robertson, Richard D</creator><general>Elsevier Science BV</general><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><scope>FBQ</scope><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope><scope>7U6</scope></search><sort><creationdate>201401</creationdate><title>Projecting future crop productivity for global economic modeling</title><author>Müller, Christoph ; Robertson, Richard D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5628-5fc257374ae1918852a9bbf47765874ec31b262e00d9c9b9b3c6768201f082593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Agricultural land</topic><topic>Agricultural practices</topic><topic>Agricultural productivity</topic><topic>Carbon dioxide</topic><topic>climate</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Crop modeling</topic><topic>Crop production</topic><topic>crops</topic><topic>econometric models</topic><topic>economic analysis</topic><topic>Economic models</topic><topic>Environmental assessment</topic><topic>Environmental impact</topic><topic>Environmental protection</topic><topic>Global economy</topic><topic>Growth models</topic><topic>land productivity</topic><topic>Land use</topic><topic>markets</topic><topic>Productivity</topic><topic>Q100</topic><topic>Q190</topic><topic>space and time</topic><topic>uncertainty</topic><topic>Z000</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Müller, Christoph</creatorcontrib><creatorcontrib>Robertson, Richard D</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><jtitle>Agricultural economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Müller, Christoph</au><au>Robertson, Richard D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Projecting future crop productivity for global economic modeling</atitle><jtitle>Agricultural economics</jtitle><addtitle>Agricultural Economics</addtitle><date>2014-01</date><risdate>2014</risdate><volume>45</volume><issue>1</issue><spage>37</spage><epage>50</epage><pages>37-50</pages><issn>0169-5150</issn><eissn>1574-0862</eissn><abstract>Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.</abstract><cop>Malden</cop><pub>Elsevier Science BV</pub><doi>10.1111/agec.12088</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0169-5150
ispartof Agricultural economics, 2014-01, Vol.45 (1), p.37-50
issn 0169-5150
1574-0862
language eng
recordid cdi_proquest_miscellaneous_1505327831
source Wiley Online Library Journals Frontfile Complete
subjects Agricultural land
Agricultural practices
Agricultural productivity
Carbon dioxide
climate
Climate change
Climate models
Crop modeling
Crop production
crops
econometric models
economic analysis
Economic models
Environmental assessment
Environmental impact
Environmental protection
Global economy
Growth models
land productivity
Land use
markets
Productivity
Q100
Q190
space and time
uncertainty
Z000
title Projecting future crop productivity for global economic modeling
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T03%3A17%3A05IST&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=Projecting%20future%20crop%20productivity%20for%20global%20economic%20modeling&rft.jtitle=Agricultural%20economics&rft.au=M%C3%BCller,%20Christoph&rft.date=2014-01&rft.volume=45&rft.issue=1&rft.spage=37&rft.epage=50&rft.pages=37-50&rft.issn=0169-5150&rft.eissn=1574-0862&rft_id=info:doi/10.1111/agec.12088&rft_dat=%3Cproquest_cross%3E3186931371%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1490825629&rft_id=info:pmid/&rfr_iscdi=true