Loading…

Modelling the sensitivity of agricultural systems to climate change and extreme climatic events

Little is known about the impacts of increased frequencies of extreme climatic events (ECEs) on agricultural landscapes, though such events may be much more detrimental than those of gradual climate change alone. Here we develop an approach for examining the sensitivity of agricultural systems to cl...

Full description

Saved in:
Bibliographic Details
Published in:Agricultural systems 2016-10, Vol.148, p.135-148
Main Authors: Harrison, Matthew T., Cullen, Brendan R., Rawnsley, Richard P.
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-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3
cites cdi_FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3
container_end_page 148
container_issue
container_start_page 135
container_title Agricultural systems
container_volume 148
creator Harrison, Matthew T.
Cullen, Brendan R.
Rawnsley, Richard P.
description Little is known about the impacts of increased frequencies of extreme climatic events (ECEs) on agricultural landscapes, though such events may be much more detrimental than those of gradual climate change alone. Here we develop an approach for examining the sensitivity of agricultural systems to climatic variability and ECEs on pasture-based dairy farms. Using a combination of spreadsheet formulae, biophysical and economic tools, we compared two approaches for generating future climate scenarios: a ‘Gradual’ approach, wherein climate projections of changes in monthly average temperature and rainfall were applied without altering the pattern of ECEs, and a ‘Variable’ approach, where monthly change projections were combined with more heatwaves, longer droughts and more extreme rainfall events to generate future scenarios with increased variability. The sensitivity of each approach was compared by modelling whole-farm system impacts on pasture and milk production, feed intake and profit under ‘Low’ and ‘High’ climate change projections based on the Representative Concentration Pathways with the highest greenhouse emissions in 2080 (RCP8.5) at three sites in southern Australia. ‘Low’ change projections had average warming of 1.6–2.0°C and rainfall 10–18% higher than the historical climate, while the ‘High’ change scenario had 2.5–3.2°C of warming and 15–30% reductions in rainfall. Both future climate scenarios applied the same average monthly change in rainfall and temperature relative to historical climates, but the relative frequency of events falling in the tails of the historical climate distribution was increased in the Variable approach. When used to simulate impacts on whole farm systems, the Variable approach translated into lower annual pasture growth and utilisation, and greater variation within and across years. Exposure to more frequent ECEs led to greater reliance on purchased feeds and lower long-term profitability, particularly in the High change scenarios. We conclude that increased climate variability associated with more frequent ECEs has impacts on agricultural systems over and above those of gradual climate change, which may have two main implications. First, climate change projections following RCP8.5 will progressively depress pasture yields and profitability of pasture-based dairy systems. Second, future modelling of climate change impacts on agricultural systems must adopt methodologies that account for the variability associated with
doi_str_mv 10.1016/j.agsy.2016.07.006
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1837294460</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0308521X16303444</els_id><sourcerecordid>1837294460</sourcerecordid><originalsourceid>FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3</originalsourceid><addsrcrecordid>eNp9kEtPwzAQhC0EEqXwBzj5yCVhbSdxInFBFS-piAtI3CzH2aSu8ii2U5F_T6r2zGlH2pnVzkfILYOYAcvut7Fu_BTzWccgY4DsjCxYLkXEeSbPyQIE5FHK2fclufJ-CwAFg3xB1PtQYdvavqFhg9Rj722wexsmOtRUN86asQ2j0y31kw_YeRoGalrb6YDUbHTfINV9RfE3OOzwtLKG4h774K_JRa1bjzenuSRfz0-fq9do_fHytnpcR0ZIGSJhdMVLwTiaLNdclAVLU53WXCdCJ1UJlTFJiUWOEnNZQl2KLCuFBpNihWDEktwd7-7c8DOiD6qz3szNdI_D6BXLheRFkmQwW_nRatzgvcNa7dz8s5sUA3WgqbbqQFMdaCqQaqY5hx6OIZxL7C065Y3F3mBlHZqgqsH-F_8D_smBDQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1837294460</pqid></control><display><type>article</type><title>Modelling the sensitivity of agricultural systems to climate change and extreme climatic events</title><source>Elsevier:Jisc Collections:Elsevier Read and Publish Agreement 2022-2024:Freedom Collection (Reading list)</source><creator>Harrison, Matthew T. ; Cullen, Brendan R. ; Rawnsley, Richard P.</creator><creatorcontrib>Harrison, Matthew T. ; Cullen, Brendan R. ; Rawnsley, Richard P.</creatorcontrib><description>Little is known about the impacts of increased frequencies of extreme climatic events (ECEs) on agricultural landscapes, though such events may be much more detrimental than those of gradual climate change alone. Here we develop an approach for examining the sensitivity of agricultural systems to climatic variability and ECEs on pasture-based dairy farms. Using a combination of spreadsheet formulae, biophysical and economic tools, we compared two approaches for generating future climate scenarios: a ‘Gradual’ approach, wherein climate projections of changes in monthly average temperature and rainfall were applied without altering the pattern of ECEs, and a ‘Variable’ approach, where monthly change projections were combined with more heatwaves, longer droughts and more extreme rainfall events to generate future scenarios with increased variability. The sensitivity of each approach was compared by modelling whole-farm system impacts on pasture and milk production, feed intake and profit under ‘Low’ and ‘High’ climate change projections based on the Representative Concentration Pathways with the highest greenhouse emissions in 2080 (RCP8.5) at three sites in southern Australia. ‘Low’ change projections had average warming of 1.6–2.0°C and rainfall 10–18% higher than the historical climate, while the ‘High’ change scenario had 2.5–3.2°C of warming and 15–30% reductions in rainfall. Both future climate scenarios applied the same average monthly change in rainfall and temperature relative to historical climates, but the relative frequency of events falling in the tails of the historical climate distribution was increased in the Variable approach. When used to simulate impacts on whole farm systems, the Variable approach translated into lower annual pasture growth and utilisation, and greater variation within and across years. Exposure to more frequent ECEs led to greater reliance on purchased feeds and lower long-term profitability, particularly in the High change scenarios. We conclude that increased climate variability associated with more frequent ECEs has impacts on agricultural systems over and above those of gradual climate change, which may have two main implications. First, climate change projections following RCP8.5 will progressively depress pasture yields and profitability of pasture-based dairy systems. Second, future modelling of climate change impacts on agricultural systems must adopt methodologies that account for the variability associated with ECEs in projected climate data, since the sensitivity of losses in production and profitability becomes greater with more frequent ECEs, even if gradual long-term changes in climate are accounted for. •Impacts of extreme climatic events (ECEs) and gradual climate change are compared.•Climate change modelling of agro-ecological systems must account for ECEs.•ECEs amplify the inter-annual variation in modelled soil water drainage and runoff.•Grassland production decreases when the severity of future drought is accounted for.•A novel approach for biophysical modelling of ECEs is documented.</description><identifier>ISSN: 0308-521X</identifier><identifier>EISSN: 1873-2267</identifier><identifier>DOI: 10.1016/j.agsy.2016.07.006</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Agriculture ; Dairy ; Drought ; Extreme climatic events ; Global circulation model ; Grazing ; Heat wave ; Livestock ; Plant stress</subject><ispartof>Agricultural systems, 2016-10, Vol.148, p.135-148</ispartof><rights>2016 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3</citedby><cites>FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3</cites><orcidid>0000-0001-7425-452X</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></links><search><creatorcontrib>Harrison, Matthew T.</creatorcontrib><creatorcontrib>Cullen, Brendan R.</creatorcontrib><creatorcontrib>Rawnsley, Richard P.</creatorcontrib><title>Modelling the sensitivity of agricultural systems to climate change and extreme climatic events</title><title>Agricultural systems</title><description>Little is known about the impacts of increased frequencies of extreme climatic events (ECEs) on agricultural landscapes, though such events may be much more detrimental than those of gradual climate change alone. Here we develop an approach for examining the sensitivity of agricultural systems to climatic variability and ECEs on pasture-based dairy farms. Using a combination of spreadsheet formulae, biophysical and economic tools, we compared two approaches for generating future climate scenarios: a ‘Gradual’ approach, wherein climate projections of changes in monthly average temperature and rainfall were applied without altering the pattern of ECEs, and a ‘Variable’ approach, where monthly change projections were combined with more heatwaves, longer droughts and more extreme rainfall events to generate future scenarios with increased variability. The sensitivity of each approach was compared by modelling whole-farm system impacts on pasture and milk production, feed intake and profit under ‘Low’ and ‘High’ climate change projections based on the Representative Concentration Pathways with the highest greenhouse emissions in 2080 (RCP8.5) at three sites in southern Australia. ‘Low’ change projections had average warming of 1.6–2.0°C and rainfall 10–18% higher than the historical climate, while the ‘High’ change scenario had 2.5–3.2°C of warming and 15–30% reductions in rainfall. Both future climate scenarios applied the same average monthly change in rainfall and temperature relative to historical climates, but the relative frequency of events falling in the tails of the historical climate distribution was increased in the Variable approach. When used to simulate impacts on whole farm systems, the Variable approach translated into lower annual pasture growth and utilisation, and greater variation within and across years. Exposure to more frequent ECEs led to greater reliance on purchased feeds and lower long-term profitability, particularly in the High change scenarios. We conclude that increased climate variability associated with more frequent ECEs has impacts on agricultural systems over and above those of gradual climate change, which may have two main implications. First, climate change projections following RCP8.5 will progressively depress pasture yields and profitability of pasture-based dairy systems. Second, future modelling of climate change impacts on agricultural systems must adopt methodologies that account for the variability associated with ECEs in projected climate data, since the sensitivity of losses in production and profitability becomes greater with more frequent ECEs, even if gradual long-term changes in climate are accounted for. •Impacts of extreme climatic events (ECEs) and gradual climate change are compared.•Climate change modelling of agro-ecological systems must account for ECEs.•ECEs amplify the inter-annual variation in modelled soil water drainage and runoff.•Grassland production decreases when the severity of future drought is accounted for.•A novel approach for biophysical modelling of ECEs is documented.</description><subject>Agriculture</subject><subject>Dairy</subject><subject>Drought</subject><subject>Extreme climatic events</subject><subject>Global circulation model</subject><subject>Grazing</subject><subject>Heat wave</subject><subject>Livestock</subject><subject>Plant stress</subject><issn>0308-521X</issn><issn>1873-2267</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9kEtPwzAQhC0EEqXwBzj5yCVhbSdxInFBFS-piAtI3CzH2aSu8ii2U5F_T6r2zGlH2pnVzkfILYOYAcvut7Fu_BTzWccgY4DsjCxYLkXEeSbPyQIE5FHK2fclufJ-CwAFg3xB1PtQYdvavqFhg9Rj722wexsmOtRUN86asQ2j0y31kw_YeRoGalrb6YDUbHTfINV9RfE3OOzwtLKG4h774K_JRa1bjzenuSRfz0-fq9do_fHytnpcR0ZIGSJhdMVLwTiaLNdclAVLU53WXCdCJ1UJlTFJiUWOEnNZQl2KLCuFBpNihWDEktwd7-7c8DOiD6qz3szNdI_D6BXLheRFkmQwW_nRatzgvcNa7dz8s5sUA3WgqbbqQFMdaCqQaqY5hx6OIZxL7C065Y3F3mBlHZqgqsH-F_8D_smBDQ</recordid><startdate>201610</startdate><enddate>201610</enddate><creator>Harrison, Matthew T.</creator><creator>Cullen, Brendan R.</creator><creator>Rawnsley, Richard P.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-7425-452X</orcidid></search><sort><creationdate>201610</creationdate><title>Modelling the sensitivity of agricultural systems to climate change and extreme climatic events</title><author>Harrison, Matthew T. ; Cullen, Brendan R. ; Rawnsley, Richard P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Agriculture</topic><topic>Dairy</topic><topic>Drought</topic><topic>Extreme climatic events</topic><topic>Global circulation model</topic><topic>Grazing</topic><topic>Heat wave</topic><topic>Livestock</topic><topic>Plant stress</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Harrison, Matthew T.</creatorcontrib><creatorcontrib>Cullen, Brendan R.</creatorcontrib><creatorcontrib>Rawnsley, Richard P.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Agricultural systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Harrison, Matthew T.</au><au>Cullen, Brendan R.</au><au>Rawnsley, Richard P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modelling the sensitivity of agricultural systems to climate change and extreme climatic events</atitle><jtitle>Agricultural systems</jtitle><date>2016-10</date><risdate>2016</risdate><volume>148</volume><spage>135</spage><epage>148</epage><pages>135-148</pages><issn>0308-521X</issn><eissn>1873-2267</eissn><abstract>Little is known about the impacts of increased frequencies of extreme climatic events (ECEs) on agricultural landscapes, though such events may be much more detrimental than those of gradual climate change alone. Here we develop an approach for examining the sensitivity of agricultural systems to climatic variability and ECEs on pasture-based dairy farms. Using a combination of spreadsheet formulae, biophysical and economic tools, we compared two approaches for generating future climate scenarios: a ‘Gradual’ approach, wherein climate projections of changes in monthly average temperature and rainfall were applied without altering the pattern of ECEs, and a ‘Variable’ approach, where monthly change projections were combined with more heatwaves, longer droughts and more extreme rainfall events to generate future scenarios with increased variability. The sensitivity of each approach was compared by modelling whole-farm system impacts on pasture and milk production, feed intake and profit under ‘Low’ and ‘High’ climate change projections based on the Representative Concentration Pathways with the highest greenhouse emissions in 2080 (RCP8.5) at three sites in southern Australia. ‘Low’ change projections had average warming of 1.6–2.0°C and rainfall 10–18% higher than the historical climate, while the ‘High’ change scenario had 2.5–3.2°C of warming and 15–30% reductions in rainfall. Both future climate scenarios applied the same average monthly change in rainfall and temperature relative to historical climates, but the relative frequency of events falling in the tails of the historical climate distribution was increased in the Variable approach. When used to simulate impacts on whole farm systems, the Variable approach translated into lower annual pasture growth and utilisation, and greater variation within and across years. Exposure to more frequent ECEs led to greater reliance on purchased feeds and lower long-term profitability, particularly in the High change scenarios. We conclude that increased climate variability associated with more frequent ECEs has impacts on agricultural systems over and above those of gradual climate change, which may have two main implications. First, climate change projections following RCP8.5 will progressively depress pasture yields and profitability of pasture-based dairy systems. Second, future modelling of climate change impacts on agricultural systems must adopt methodologies that account for the variability associated with ECEs in projected climate data, since the sensitivity of losses in production and profitability becomes greater with more frequent ECEs, even if gradual long-term changes in climate are accounted for. •Impacts of extreme climatic events (ECEs) and gradual climate change are compared.•Climate change modelling of agro-ecological systems must account for ECEs.•ECEs amplify the inter-annual variation in modelled soil water drainage and runoff.•Grassland production decreases when the severity of future drought is accounted for.•A novel approach for biophysical modelling of ECEs is documented.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.agsy.2016.07.006</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-7425-452X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0308-521X
ispartof Agricultural systems, 2016-10, Vol.148, p.135-148
issn 0308-521X
1873-2267
language eng
recordid cdi_proquest_miscellaneous_1837294460
source Elsevier:Jisc Collections:Elsevier Read and Publish Agreement 2022-2024:Freedom Collection (Reading list)
subjects Agriculture
Dairy
Drought
Extreme climatic events
Global circulation model
Grazing
Heat wave
Livestock
Plant stress
title Modelling the sensitivity of agricultural systems to climate change and extreme climatic events
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T04%3A01%3A31IST&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=Modelling%20the%20sensitivity%20of%20agricultural%20systems%20to%20climate%20change%20and%20extreme%20climatic%20events&rft.jtitle=Agricultural%20systems&rft.au=Harrison,%20Matthew%20T.&rft.date=2016-10&rft.volume=148&rft.spage=135&rft.epage=148&rft.pages=135-148&rft.issn=0308-521X&rft.eissn=1873-2267&rft_id=info:doi/10.1016/j.agsy.2016.07.006&rft_dat=%3Cproquest_cross%3E1837294460%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c377t-3cad2b312ec68a23b9155a5f2a43a4db0dcc4be98e7e87b0fb366b3a0c5ede0c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1837294460&rft_id=info:pmid/&rfr_iscdi=true