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Analysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networks

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  • Regina Márcia Longo

    (Postgraduate Program in Urban Infrastructure Systems and Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil
    Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil)

  • Alessandra Leite da Silva

    (Postgraduate Program in Urban Infrastructure Systems and Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil)

  • Adélia N. Nunes

    (Department of Geography and Tourism, Centre of Studies in Geography and Spatial Planning (CEGOT), University of Coimbra (UC), 3004-530 Coimbra, Portugal)

  • Diego de Melo Conti

    (Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil)

  • Raissa Caroline Gomes

    (Postgraduate Program in Urban Infrastructure Systems and Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil)

  • Fabricio Camillo Sperandio

    (Postgraduate Program in Sustainability, Pontifical Catholic University of Campinas (PUC Campinas), Campinas 13087-571, SP, Brazil)

  • Admilson Irio Ribeiro

    (Postgraduate Program in Environmental Sciences, São Paulo State University “Júlio de Mesquita Filho” (UNESP), Sorocaba 18087-180, SP, Brazil)

Abstract

Analyzing the landscape configuration factors where they are located can ensure a more accurate spatial assessment of the supply of ecosystem services. It can also show if the benefits promoted by ecosystems depend not only on the supply of these services but also on the demand, the cultural values, and the interest of the society where they are located. The present study aims to demonstrate the provision potential of regulating ecosystem services by forest remnants in the municipality of Campinas/SP, Brazil, from the analysis and weighting of geospatial indicators, considering the assumptions of supply of and demand for these ecosystem services. The potential supply of regulating ecosystem services was evaluated through the application of an artificial neural network using landscape indicators previously surveyed for the 2319 forest remnants identified in six watersheds. The findings show that the classified remnants have a “medium” to “very high” regulating potential for the provision of ecosystem services. The use of artificial intelligence fundamentals, based on artificial neural networks, proved to be quite effective, as it enables combined analysis of various indicators, analysis of spatial patterns, and the prediction of results, which could be informative guides for environmental planning and management in urban spaces.

Suggested Citation

  • Regina Márcia Longo & Alessandra Leite da Silva & Adélia N. Nunes & Diego de Melo Conti & Raissa Caroline Gomes & Fabricio Camillo Sperandio & Admilson Irio Ribeiro, 2023. "Analysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networks," Sustainability, MDPI, vol. 15(20), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:20:p:15017-:d:1262316
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    References listed on IDEAS

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    1. González-García, Alberto & Palomo, Ignacio & González, José A. & López, César A. & Montes, Carlos, 2020. "Quantifying spatial supply-demand mismatches in ecosystem services provides insights for land-use planning," Land Use Policy, Elsevier, vol. 94(C).
    2. Huang, G. & London, J., 2012. "Mapping cumulative environmental effects, social vulnerability, and health in the San Joaquin Valley, California," American Journal of Public Health, American Public Health Association, vol. 102(5), pages 830-832.
    3. Robert Costanza, 2006. "Nature: ecosystems without commodifying them," Nature, Nature, vol. 443(7113), pages 749-749, October.
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    Cited by:

    1. Giedrius Jucevičius & Kristina Grumadaitė, 2024. "Managing Strategic Tensions in the Development of Organizational Ecosystems," Sustainability, MDPI, vol. 16(5), pages 1-18, February.
    2. Regina Márcia Longo & Alessandra Leite da Silva & Admilson Irio Ribeiro & Raissa Caroline Gomes & Fabricio Camillo Sperandio & Adélia N. Nunes, 2024. "Evaluating the Environmental Quality of Forest Remnants Using Landscape Metrics," Sustainability, MDPI, vol. 16(4), pages 1-19, February.

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