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Analysis of the Vulnerability of Agriculture to Climate and Anthropogenic Impacts in the Beni Mellal-Khénifra Region, Morocco

Author

Listed:
  • Fatine Eddoughri

    (Laboratory of Water, Biodiversity and Climate Change, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco)

  • Fatima Zohra Lkammarte

    (Laboratory of Water, Biodiversity and Climate Change, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco)

  • Moussa El Jarroudi

    (Department of Environmental Sciences and Management, SPHERES Research Unit, University of Liège, 6700 Arlon, Belgium)

  • Rachid Lahlali

    (Phytopathology Unit, Department of Plant Protection, Ecole Nationale d’Agriculture de Meknès, Meknès 50001, Morocco)

  • Ahmed Karmaoui

    (Bioactives (Health and Environmental, Epigenetics Team), University Moulay Ismail, Meknès 50050, Morocco
    Faculty of Sciences and Techniques, University Moulay Ismail, Errachidia 52000, Morocco
    Moroccan Center for Culture and Sciences, Zagora 47900, Morocco)

  • Mohammed Yacoubi Khebiza

    (Laboratory of Water, Biodiversity and Climate Change, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco)

  • Mohammed Messouli

    (Laboratory of Water, Biodiversity and Climate Change, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco)

Abstract

Climate change (CC) is a significant concern for many climate-sensitive socio-economic sectors, such as agriculture and food production. The current study aimed at analyzing the current vulnerability of the Moroccan agricultural sector to CC and anthropogenic impact and identifying the relevant vulnerability factors in the Beni Mellal-Khénifra region. In this regard, a multidisciplinary approach was used to assess the vulnerability. To do this, an index based on five components was designed, including climate, plant production, animal production, geography, and anthropogenic aspects. The numerical model has benefited from data retrieved from three recognized indices such as Normalized Difference Vegetation Index (NDVI), Standardized Precipitation Index (SPI), and Vegetation Condition Index (VCI), and from the reported data of the agricultural, environmental, and socio-economic governmental departments. The results showed that there was a significant vulnerability of all the five components to CC. Particularly, the province of Azilal was the most vulnerable, followed by Khénifra, Fquih Ben Salah, and Beni Mellal, while Khouribga was the least vulnerable. These components might help to determine the mechanisms and priority sectors, the most vulnerable to CC and anthropogenic effects, to take urgent measures. These may guide decision makers to carry out effective actions, namely, the amounts to be spent to mitigate this vulnerability. It will also make it possible to know where, when, and how the adaptation should take place.

Suggested Citation

  • Fatine Eddoughri & Fatima Zohra Lkammarte & Moussa El Jarroudi & Rachid Lahlali & Ahmed Karmaoui & Mohammed Yacoubi Khebiza & Mohammed Messouli, 2022. "Analysis of the Vulnerability of Agriculture to Climate and Anthropogenic Impacts in the Beni Mellal-Khénifra Region, Morocco," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13166-:d:941682
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    References listed on IDEAS

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    4. Nassima Amiri & Rachid Lahlali & Said Amiri & Moussa EL Jarroudi & Mohammed Yacoubi Khebiza & Mohammed Messouli, 2021. "Development of an Integrated Model to Assess the Impact of Agricultural Practices and Land Use on Agricultural Production in Morocco under Climate Stress over the Next Twenty Years," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    5. World Bank, 2018. "World Development Report 2018 [Rapport sur le développement dans le monde 2018]," World Bank Publications - Books, The World Bank Group, number 28340.
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    1. Lukas Folkens & Daniel Bachmann & Petra Schneider, 2023. "Driving Forces and Socio-Economic Impacts of Low-Flow Events in Central Europe: A Literature Review Using DPSIR Criteria," Sustainability, MDPI, vol. 15(13), pages 1-24, July.
    2. László Huzsvai & Csaba Juhász & Loujaine Seddik & Györgyi Kovács & József Zsembeli, 2024. "The Future Probability of Winter Wheat and Maize Yield Failure in Hungary Based on Long-Term Temporal Patterns," Sustainability, MDPI, vol. 16(10), pages 1-17, May.

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