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Ecological Sensitivity of the Mata Allo Sub-Watershed, South Sulawesi: A Spatial Analysis Using Principal Component Analysis

Author

Listed:
  • Syamsu Rijal

    (Laboratory of Forest Planning and Information System, Forestry Faculty, Hasanuddin University, Makassar 90245, Indonesia)

  • Samsuri

    (Forestry Faculty, Universitas Sumatera Utara, Medan 20155, Indonesia)

  • Heni Masruroh

    (Geography Department, Faculty of Social Science, Universitas Negeri Malang, Malang 65145, Indonesia)

  • Munajat Nursaputra

    (Laboratory of Forest Planning and Information System, Forestry Faculty, Hasanuddin University, Makassar 90245, Indonesia)

  • Chairil A

    (Laboratory of Forest Planning and Information System, Forestry Faculty, Hasanuddin University, Makassar 90245, Indonesia)

  • Nur Zamzam Putri Ardi

    (Laboratory of Forest Planning and Information System, Forestry Faculty, Hasanuddin University, Makassar 90245, Indonesia)

Abstract

Watersheds are critical ecosystems that provide essential services, but they face increasing threats from deforestation, land use changes, and climate variability. The Mata Allo Sub-Watershed, which is characterized by steep topography and high rainfall, is particularly vulnerable to erosion, landslides, and habitat loss, necessitating robust conservation strategies. This study used principal component analysis (PCA) to assess ecological sensitivity, focusing on slope, rainfall, vegetation density, and land cover. The PCA results identified land cover as the most influential positive factor in F1 (loading value: 0.588), increasing sensitivity due to human-induced land use changes, while rainfall contributed most negatively (−0.638) by potentially mitigating extreme ecological risks. These contrasting roles underscore the complexity of interactions shaping watershed sensitivity. Slope strongly influenced F2 (−0.795), explaining 26.48% of the variance and highlighting the critical role of steep slopes in exacerbating erosion risks. Vegetation density in F3 (−0.679) and rainfall in F4 (−0.724) played significant roles in stabilizing soil and mitigating ecological risks, emphasizing their importance in reducing watershed sensitivity. The “Extremely Sensitive” class covers 48.79% of the watershed, primarily in areas with steep slopes and sparse vegetation, while “High Sensitivity” areas occupy 34.93%. Projections for 2032 suggest a reduction in “Extremely Sensitive” zones to 41.00%, reflecting improvements from targeted management interventions. These findings provide a foundation for promoting sustainable watershed management, enhancing climate resilience, and supporting biodiversity conservation efforts in vulnerable regions.

Suggested Citation

  • Syamsu Rijal & Samsuri & Heni Masruroh & Munajat Nursaputra & Chairil A & Nur Zamzam Putri Ardi, 2025. "Ecological Sensitivity of the Mata Allo Sub-Watershed, South Sulawesi: A Spatial Analysis Using Principal Component Analysis," Sustainability, MDPI, vol. 17(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:2:p:447-:d:1562911
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    References listed on IDEAS

    as
    1. María Isabel DELGADO & Fernanda Julia GASPARI & Eduardo Emilio KRUSE, 2015. "Land use changes and sediment yield on a hilly watershed in Central-East Argentina," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 10(3), pages 189-197.
    2. Boubaker Khallef & Rabah Zennir, 2023. "Forest cover change detection using Normalized Difference Vegetation Index in the Oued Bouhamdane watershed, Algeria - A case study," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 69(6), pages 254-265.
    3. Nareth Nut & Machito Mihara & Jaehak Jeong & Bunthan Ngo & Gilbert Sigua & P.V. Vara Prasad & Manny R. Reyes, 2021. "Land Use and Land Cover Changes and Its Impact on Soil Erosion in Stung Sangkae Catchment of Cambodia," Sustainability, MDPI, vol. 13(16), pages 1-25, August.
    4. Ana Ascenso & Bruno Augusto & Sílvia Coelho & Isilda Menezes & Alexandra Monteiro & Sandra Rafael & Joana Ferreira & Carla Gama & Peter Roebeling & Ana Isabel Miranda, 2024. "Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities," Sustainability, MDPI, vol. 16(17), pages 1-21, August.
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