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Farmers’ perceptions and role of institutional arrangements in climate change adaptation: Insights from rainfed Pakistan

  • Rainfed farmers are among the most vulnerable farming communities to climate change in Pakistan because of the heavy reliance of crop farming on rain and of farmers’ livelihoods on crop farming. The best and most timely responses against climate change are suitable adaptation measures. Accurately perceiving the risks associated with climate change is an essential factor for planning and then implementing adaptations. Using farm household-level data of 400 rainfed farmers collected through a well-designed and field-tested questionnaire, this study examines the association between various adaptation stages (climate risk perceptions, adaptation planning, and implementation of adaptation) and their determinants using a multivariate probit (MVP) model. The findings indicate that farmers’ perceptions of climatic changes are in line with historical climatic data. Climate risk management (CRM) trainings and digital agriculture extension and communication (DAEC) services (indicators of formal institutional arrangements) show a highlyRainfed farmers are among the most vulnerable farming communities to climate change in Pakistan because of the heavy reliance of crop farming on rain and of farmers’ livelihoods on crop farming. The best and most timely responses against climate change are suitable adaptation measures. Accurately perceiving the risks associated with climate change is an essential factor for planning and then implementing adaptations. Using farm household-level data of 400 rainfed farmers collected through a well-designed and field-tested questionnaire, this study examines the association between various adaptation stages (climate risk perceptions, adaptation planning, and implementation of adaptation) and their determinants using a multivariate probit (MVP) model. The findings indicate that farmers’ perceptions of climatic changes are in line with historical climatic data. Climate risk management (CRM) trainings and digital agriculture extension and communication (DAEC) services (indicators of formal institutional arrangements) show a highly significant impact on all adaptation stages. Input market distance, farmer cooperative meetings (an indicator of informal institutional arrangement), off-farm income, education, and number of male family members are among the other key determinants. A highly significant association between various adaptation stages indicates that accurate climate risk perceptions lead to planning and implementation of adaptations. When risk perceptions are underestimated or lacking, then adaptations do not occur. The results further indicate that the timely availability of reliable information on advanced agricultural inputs, weather parameters, crop farming advisory services, and market information could help rainfed farmers devise sound adaptations to minimize risks associated with climate change. The study recommends the provision of CRM trainings and DAEC services to provide a better understanding and promote sound adaptation planning through the adaptive capacity enhancement of rainfed farming communities for sustainable production and livelihood security.show moreshow less

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Metadaten
Author:Nasir Mahmood, Muhammad Arshad, Yasir Mehmood, Muhammad Faisal Shahzad, Harald KächeleGND
URN:urn:nbn:de:kobv:eb1-opus-7375
DOI:https://doi.org/10.1016/j.crm.2021.100288
ISSN:2212-0963
Parent Title (English):Climate Risk Management
Publisher:Elsevier
Document Type:Article
Language:English
Year of Completion:2021
Date of first Publication:2021/02/20
Publishing Institution:Hochschule für nachhaltige Entwicklung Eberswalde
Release Date:2023/10/09
Tag:Adaptation planning; Climate risk management trainings; Digital advisory services; Pakistan; Rainfed; Risk perceptions
Volume:32
Article Number:100288
Institutions / Departments:Fachbereich Landschaftsnutzung und Naturschutz
open_access (DINI-Set):open_access
University Bibliography:University Bibliography
Zweitveröffentlichung
Peer-Review / Referiert
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
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