A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)

Detalhes bibliográficos
Autor(a) principal: Amani-Male,O.
Data de Publicação: 2024
Outros Autores: Feizabadi,Y., Norouzi,G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100333
Resumo: Abstract The study strives to analyze the potential variations of farmers' income under climate change by using Ricardian approach. The case study was Mazandaran province of Iran and three autumn crops, i.e. wheat, barley and canola were considered as the investigated crops. The Long Ashton Research Station Weather Generator (LARS-WG) model was selected to downscale the climate data. Three climate variables were downscaled for the years 2020-2080 under three climate scenarios: optimistic (RCP2.6), medium (RCP4.5), and pessimistic (RCP8.5). The Ricardian approach was also employed to predict the economics of climate change. Accordingly, the mean monthly temperature of the province is projected to have an upward trend under all climate scenarios, however, the rainfall pattern would be varied. The results of economic impacts of climate change also approved that the net income of investigated crops would be different trends under climate change scenarios. Accordingly, the variations of air temperature and rainfall would lead that the net income increases for wheat and barley, while it decreases for canola.
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spelling A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)climate changeagriculturenet incomeRicardian approachAbstract The study strives to analyze the potential variations of farmers' income under climate change by using Ricardian approach. The case study was Mazandaran province of Iran and three autumn crops, i.e. wheat, barley and canola were considered as the investigated crops. The Long Ashton Research Station Weather Generator (LARS-WG) model was selected to downscale the climate data. Three climate variables were downscaled for the years 2020-2080 under three climate scenarios: optimistic (RCP2.6), medium (RCP4.5), and pessimistic (RCP8.5). The Ricardian approach was also employed to predict the economics of climate change. Accordingly, the mean monthly temperature of the province is projected to have an upward trend under all climate scenarios, however, the rainfall pattern would be varied. The results of economic impacts of climate change also approved that the net income of investigated crops would be different trends under climate change scenarios. Accordingly, the variations of air temperature and rainfall would lead that the net income increases for wheat and barley, while it decreases for canola.Instituto Internacional de Ecologia2024-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100333Brazilian Journal of Biology v.84 2024reponame:Brazilian Journal of Biologyinstname:Instituto Internacional de Ecologia (IIE)instacron:IIE10.1590/1519-6984.261997info:eu-repo/semantics/openAccessAmani-Male,O.Feizabadi,Y.Norouzi,G.eng2022-08-10T00:00:00Zoai:scielo:S1519-69842024000100333Revistahttps://www.scielo.br/j/bjb/https://old.scielo.br/oai/scielo-oai.phpbjb@bjb.com.br||bjb@bjb.com.br1678-43751519-6984opendoar:2022-08-10T00:00Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)false
dc.title.none.fl_str_mv A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
title A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
spellingShingle A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
Amani-Male,O.
climate change
agriculture
net income
Ricardian approach
title_short A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
title_full A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
title_fullStr A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
title_full_unstemmed A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
title_sort A model-based evaluation of farmers' income variability under climate change (case study: autumn crops in Iran)
author Amani-Male,O.
author_facet Amani-Male,O.
Feizabadi,Y.
Norouzi,G.
author_role author
author2 Feizabadi,Y.
Norouzi,G.
author2_role author
author
dc.contributor.author.fl_str_mv Amani-Male,O.
Feizabadi,Y.
Norouzi,G.
dc.subject.por.fl_str_mv climate change
agriculture
net income
Ricardian approach
topic climate change
agriculture
net income
Ricardian approach
description Abstract The study strives to analyze the potential variations of farmers' income under climate change by using Ricardian approach. The case study was Mazandaran province of Iran and three autumn crops, i.e. wheat, barley and canola were considered as the investigated crops. The Long Ashton Research Station Weather Generator (LARS-WG) model was selected to downscale the climate data. Three climate variables were downscaled for the years 2020-2080 under three climate scenarios: optimistic (RCP2.6), medium (RCP4.5), and pessimistic (RCP8.5). The Ricardian approach was also employed to predict the economics of climate change. Accordingly, the mean monthly temperature of the province is projected to have an upward trend under all climate scenarios, however, the rainfall pattern would be varied. The results of economic impacts of climate change also approved that the net income of investigated crops would be different trends under climate change scenarios. Accordingly, the variations of air temperature and rainfall would lead that the net income increases for wheat and barley, while it decreases for canola.
publishDate 2024
dc.date.none.fl_str_mv 2024-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100333
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1519-69842024000100333
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1519-6984.261997
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto Internacional de Ecologia
publisher.none.fl_str_mv Instituto Internacional de Ecologia
dc.source.none.fl_str_mv Brazilian Journal of Biology v.84 2024
reponame:Brazilian Journal of Biology
instname:Instituto Internacional de Ecologia (IIE)
instacron:IIE
instname_str Instituto Internacional de Ecologia (IIE)
instacron_str IIE
institution IIE
reponame_str Brazilian Journal of Biology
collection Brazilian Journal of Biology
repository.name.fl_str_mv Brazilian Journal of Biology - Instituto Internacional de Ecologia (IIE)
repository.mail.fl_str_mv bjb@bjb.com.br||bjb@bjb.com.br
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