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Environmental Management

, Volume 63, Issue 1, pp 110–123 | Cite as

Farmer Perceptions of Climate Change, Observed Trends and Adaptation of Agriculture in Pakistan

  • Muhammad AbidEmail author
  • Jürgen Scheffran
  • Uwe A. Schneider
  • Ehsan Elahi
Article

Abstract

Farmers’ willingness and ability to adapt agricultural systems depend on their knowledge about changes in climate and perceived risks of extreme events. Using cross-sectional data of 450 farmers collected from three agro-ecological zones of Punjab, Pakistan, this study investigates farmer perceptions of climate change and their agreement with observed climatic trends. In addition, this study explores the correlation between different adaptation stages (perceptions, intentions, and adaptation) and their key drivers using a Multivariate Probit Model. This study also explores the adaptation measures adopted by farmers. The results of the study show that the perceptions of increasing mean temperature match well with locally recorded data. However, a discrepancy is found in some cases between farmer perceptions of rainfall changes and local climate records. Moreover, education, experience, land tenure, land holdings, extension, cooperation, access to weather forecasting, and marketing information are the factors influencing the three adaptation stages. A strong association is found among the three adaptation stages. Particularly, the study confirms the hypothesis that accurate perceptions lead to stronger adaptation intentions compared to underestimated or no perceptions. Further, farmers prefer basic adaptation measures including changing crop varieties, input use and planting dates over advanced measures, such as planting shade trees, soil conservation, and crop diversification. The study recommends providing farmers, especially small landholders and tenants, easy access to information, institutional services and training on the use of advanced measures to reduce negative impacts of climate change at the farm level.

Keywords

Climate change Accuracy of perceptions Adaptation intentions Farm level adaptation Pakistan 

Notes

Acknowledgements

This study has been part of a Ph.D. research project at Universität Hamburg, Germany at the School of Integrated Climate System Sciences (SICSS). We gratefully acknowledge the funding sources for this research: Higher Education Commission (HEC), Pakistan; Deutscher Akademischer Austauschdienst (DAAD); Kompetenzzentrum Nachhaltige Universität (KNU); School of integrated Climate System Sciences (SICSS); and the Research Group Climate Change and Security (CLISEC) in the Excellence Cluster “Integrated Climate System Analysis and Prediction” (CliSAP) supported by Deutsche Forschungsgemeinschaft (DFG). We thankfully acknowledge the Pakistan Meteorology Department (PMD) for providing climate data for the analysis. Further, we are thankful to the local agricultural extension departments, farmers, and enumerators for their time and cooperation in the process of successful data collection during March and April 2014. Moreover, we are very thankful to the editors and anonymous reviewers for their insightful comments and suggestions to improve the manuscript.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Muhammad Abid
    • 1
    • 2
    Email author
  • Jürgen Scheffran
    • 2
  • Uwe A. Schneider
    • 3
  • Ehsan Elahi
    • 4
  1. 1.Centre for Climate Research and Development (CCRD)COMSATS University IslamabadIslamabadPakistan
  2. 2.Research Group Climate Change and Security (CLISEC), Institute of Geography, Center for Earth System Research and Sustainability (CEN)University of HamburgHamburgGermany
  3. 3.Research Unit Sustainability and Global Change, Center for Earth System Research and Sustainability (CEN)University of HamburgHamburgGermany
  4. 4.School of BusinessNanjing University of Information Science and TechnologyNanjing ShiChina

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