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Community perceptions of the impacts of desertification as related to adaptive capacity in drylands of South Punjab, Pakistan

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  • Nausheen Mazhar

    (Lahore College for Women University)

  • Safdar Ali Shirazi

    (University of the Punjab)

Abstract

Anthropogenic activities and climatic variations continue to aggravate desertification in the drylands of the world. This study is aimed to explore the perceptions of local residents in the drylands of Bahawalpur, Rahim Yar Khan and Rajanpur districts, lying in the drylands of South Punjab, regarding the impacts of desertification on humans, finances, animals and the environment of the study area. In addition, we explored possible relations between these impacts and adaptive capacity of the local population. Primary data was collected from 399 respondents in a survey conducted during Feb–July 2019 using disproportionate stratified random sampling techniques. The Rajanpur District suffered the most in terms of human and environmental impacts, while Rahim Yar Khan experienced the lowest financial and human impacts, but most severe livestock impacts due to desertification. We also found that increases in water scarcity of surface water bodies and decline in groundwater levels, along with an increase in unemployment and delayed repayment of loans, all led to reduced adaptive capacity of the respondents. These results are helpful for policy makers to plan desertification control policies, that are region specific and focus on the main impacts being faced by each district.

Suggested Citation

  • Nausheen Mazhar & Safdar Ali Shirazi, 2023. "Community perceptions of the impacts of desertification as related to adaptive capacity in drylands of South Punjab, Pakistan," Asia-Pacific Journal of Regional Science, Springer, vol. 7(2), pages 549-568, June.
    • Handle: RePEc:spr:apjors:v:7:y:2023:i:2:d:10.1007_s41685-022-00270-7
    DOI: 10.1007/s41685-022-00270-7
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    References listed on IDEAS

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    1. Xuan Wei & Lihua Zhou & Guojing Yang & Ya Wang & Yong Chen, 2020. "Assessing the Effects of Desertification Control Projects from the Farmers’ Perspective: A Case Study of Yanchi County, Northern China," IJERPH, MDPI, vol. 17(3), pages 1-15, February.
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    3. Gerald Forkuor & Ozias K L Hounkpatin & Gerhard Welp & Michael Thiel, 2017. "High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-21, January.
    4. Fan, Cheng & Xiao, Fu & Wang, Shengwei, 2014. "Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques," Applied Energy, Elsevier, vol. 127(C), pages 1-10.
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