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Spatial Analysis of Environmentally Sensitive Areas to Soil Degradation Using MEDALUS Model and GIS in Amazonas (Peru): An Alternative for Ecological Restoration

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  • Gerson Meza Mori

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru)

  • Cristóbal Torres Guzmán

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru)

  • Manuel Oliva-Cruz

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru)

  • Rolando Salas López

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru)

  • Gladys Marlo

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru)

  • Elgar Barboza

    (Instituto de Investigación para el Desarrollo Sustentable de Ceja de Selva (INDES-CES), National University Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas 01001, Peru
    Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Av. La Molina 1981, Lima 15024, Peru)

Abstract

Land degradation is a permanent global threat that requires an interdisciplinary approach to addressing solutions in a given territory. This study, therefore, analyses environmentally sensitive areas to land degradation using the Mediterranean Desertification and Land Use (MEDALUS) and Geographic Information System (GIS) method through a multi-criteria approach in the district of Florida (Peru). For the method, we considered the main quality indicators such as: Climate Quality Index (CQI), Soil Quality Index (SQI), Vegetation Quality Index (VQI), and Management Quality Index (MQI). There were also identified groups of parameters for each of the quality indicators analyzed. The results showed that 2.96% of the study area is classified as critical; 48.85% of the surface is classified as fragile; 15.48% of the areas are potentially endangered, and 30.46% are not threatened by degradation processes. Furthermore, SQI, VQI, and MQI induced degradation processes in the area. Based on the results, five restoration proposals were made in the study area: (i) organic manure production, (ii) cultivated and improved pastures and livestock improvement, (iii) native forest restoration, (iv) construction of reservoirs in the top hills and (v) uses of new technologies. The findings and proposals can be a basic support and further improved by decision-makers when implemented in situ to mitigate degradation for a sustainable use of the territory.

Suggested Citation

  • Gerson Meza Mori & Cristóbal Torres Guzmán & Manuel Oliva-Cruz & Rolando Salas López & Gladys Marlo & Elgar Barboza, 2022. "Spatial Analysis of Environmentally Sensitive Areas to Soil Degradation Using MEDALUS Model and GIS in Amazonas (Peru): An Alternative for Ecological Restoration," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14866-:d:969133
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    References listed on IDEAS

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    1. Saskia Keesstra & Gerben Mol & Jan De Leeuw & Joop Okx & Co Molenaar & Margot De Cleen & Saskia Visser, 2018. "Soil-Related Sustainable Development Goals: Four Concepts to Make Land Degradation Neutrality and Restoration Work," Land, MDPI, vol. 7(4), pages 1-20, November.
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    Cited by:

    1. Theilon Henrique de Jesus Macêdo & Cristiano Tagliaferre & Bismarc Lopes da Silva & Alessandro de Paula & Odair Lacerda Lemos & Felizardo Adenilson Rocha & Rosilene Gomes de Souza Pinheiro & Ana Carol, 2023. "Assessment of Land Desertification in the Brazilian East Atlantic Region Using the Medalus Model and Google Earth Engine," Land, MDPI, vol. 13(1), pages 1-16, December.
    2. Letizia Pace & Vito Imbrenda & Maria Lanfredi & Pavel Cudlín & Tiziana Simoniello & Luca Salvati & Rosa Coluzzi, 2023. "Delineating the Intrinsic, Long-Term Path of Land Degradation: A Spatially Explicit Transition Matrix for Italy, 1960–2010," IJERPH, MDPI, vol. 20(3), pages 1-18, January.

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