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Proximate and Underlying Deforestation Causes in a Tropical Basin through Specialized Consultation and Spatial Logistic Regression Modeling

Author

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  • Wenseslao Plata-Rocha

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autonoma de Sinaloa, Culiacan 80013, Mexico)

  • Sergio Alberto Monjardin-Armenta

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autonoma de Sinaloa, Culiacan 80013, Mexico)

  • Carlos Eduardo Pacheco-Angulo

    (Facultad de Ciencias Forestales y Ambientales, Universidad de los Andes, Merida 5110, Venezuela)

  • Jesus Gabriel Rangel-Peraza

    (Division de Estudios de Posgrado e Investigacion, Tecnologico Nacional de Mexico—Instituto Tecnologico de Culiacan, Culiacan 80220, Mexico)

  • Cuauhtemoc Franco-Ochoa

    (Facultad de Ciencias de la Tierra y el Espacio, Universidad Autonoma de Sinaloa, Culiacan 80013, Mexico)

  • Zuriel Dathan Mora-Felix

    (Division de Estudios de Posgrado e Investigacion, Tecnologico Nacional de Mexico—Instituto Tecnologico de Culiacan, Culiacan 80220, Mexico)

Abstract

The present study focuses on identifying and describing the possible proximate and underlying causes of deforestation and its factors using the combination of two techniques: (1) specialized consultation and (2) spatial logistic regression modeling. These techniques were implemented to characterize the deforestation process qualitatively and quantitatively, and then to graphically represent the deforestation process from a temporal and spatial point of view. The study area is the North Pacific Basin, Mexico, from 2002 to 2014. The map difference technique was used to obtain deforestation using the land-use and vegetation maps. A survey was carried out to identify the possible proximate and underlying causes of deforestation, with the aid of 44 specialized government officials, researchers, and people who live in the surrounding deforested areas. The results indicated total deforestation of 3938.77 km 2 in the study area. The most important proximate deforestation causes were agricultural expansion (53.42%), infrastructure extension (20.21%), and wood extraction (16.17%), and the most important underlying causes were demographic factors (34.85%), economics factors (29.26%), and policy and institutional factors (22.59%). Based on the spatial logistic regression model, the factors with the highest statistical significance were forestry productivity, the slope, the altitude, the distance from population centers with fewer than 2500 inhabitants, the distance from farming areas, and the distance from natural protected areas.

Suggested Citation

  • Wenseslao Plata-Rocha & Sergio Alberto Monjardin-Armenta & Carlos Eduardo Pacheco-Angulo & Jesus Gabriel Rangel-Peraza & Cuauhtemoc Franco-Ochoa & Zuriel Dathan Mora-Felix, 2021. "Proximate and Underlying Deforestation Causes in a Tropical Basin through Specialized Consultation and Spatial Logistic Regression Modeling," Land, MDPI, vol. 10(2), pages 1-18, February.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:2:p:186-:d:497583
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    References listed on IDEAS

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    1. María Alejandra Quintero-Morales & Wenseslao Plata-Rocha & Sergio Alberto Monjardín-Armenta & Vicente Olimón-Andalón & Edith Hilario Torres-Montoya, 2021. "Geospatial Simulation Model of Sustainable Mangrove Development Scenarios for the Years 2030 and 2050 in Marismas Nacionales, Mexico," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    2. Saif Ullah & Yixiong Wu & Azeem Iqbal Khan, 2023. "Evaluating the Socioeconomic Factors on Deforestation in Northern Pakistan: A Study on Existing Economic Incentive Tools for Reducing Deforestation," Sustainability, MDPI, vol. 15(7), pages 1-22, March.

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