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[ Livre ] West African Agriculture and Climate Change A Comprehensive Analysis: Chapter 3 Bénin

Date de soumission: 09-02-2018
Année de Publication: 2013
Document type : Livre
Discipline(s) :
Titre West African Agriculture and Climate Change A Comprehensive Analysis: Chapter 3 Bénin
Auteurs LAWIN AGNIDÉ EMMANUEL [1], JALLOH Abdulai [3], AKPONIKPE Pierre Irénikatché [2], NELSON C. Gerald [4], THOMAS S. Timothy [5],
Editeur: International Food Policy Research Institute
ISBN: 978-0-89629-204-8
DOI: 10.2499/9780896292048
Resume Climate change, as a worldwide concern, implies generally warmer temperatures as well as changes in precipitation patterns, with more extreme weather events and shifting seasons. Agriculture is especially vulnerable, and climate change will thus disproportionately affect the poor, who depend on agriculture for their livelihoods and who have a lower capacity to adapt. The population of Benin is projected to at least double (to 18 million) or possibly more than triple (to 25 million) by 2050, with increasingly densely populated urban areas. The share of agriculture in gross domestic product (GDP) is expected to stagnate or increase, indicating that nonagricultural sectors of the economy will be stagnant at best. This chapter assesses the vulnerability of the agricultural sector of Benin to climate change to provide the basis for designing informed policies to meet those challenges. The study focuses on Benin’s main foodcrops: yams, cassava, maize, and other roots and tubers. The climate models show different outcomes for precipitation levels in Benin in 2050. CNRM-CM3 and ECHAM 5 show increased precipitation, while the two other models (CSIRO Mark 3 and MIROC 3.2) show areas of precipitation decrease, mainly in the south.1 All four general circulation models (GCMs) show an increase in the normal annual maximum temperature for the whole country, ranging from slight (1°–1.5°C for MIROC 3.2) to substantial (2.5°–3.0°C for ECHAM 5). These changes in climate affect crop production simulations in varying ways. For instance, for a given GCM the modeled spatial changes in maize production generally track changes in precipitation.

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