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Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review

Author

Listed:
  • Neelesh Yadav

    (Bioinformatics Center, Forest Research Institute, Dehradun 248006, Uttarakhand, India)

  • Shrey Rakholia

    (Bioinformatics Center, Forest Research Institute, Dehradun 248006, Uttarakhand, India)

  • Reuven Yosef

    (Eilat Campus, Ben Gurion University of the Negev, P.O. Box 272, Eilat 881020, Israel)

Abstract

In this study, tree-selection/plantation decision support systems (DSSs) were reviewed and evaluated against essential objectives in the available literature. We verified whether existing DSSs leverage multiple data sources and available online resources such as web interfaces. We compared the existing DSSs, and in this study mainly focused on five main objectives that DSSs can consider in tree selection, including (a) climate resilience, (b) infrastructure/space optimization, (c) agroforestry, (d) ecosystem services, and (e) urban sustainability. The climate resilience of tree species and urban sustainability are relatively rarely taken into account in existing systems, which can be integrated holistically in future DSS tools. Based on this review, deep neural networks (DNNs) are recommended to achieve trade-offs between complex objectives such as maximizing ecosystem services, the climate resilience of tree species, agroforestry conservation, and other benefits.

Suggested Citation

  • Neelesh Yadav & Shrey Rakholia & Reuven Yosef, 2024. "Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review," Land, MDPI, vol. 13(2), pages 1-12, February.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:2:p:230-:d:1337764
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    References listed on IDEAS

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    1. Peng Zhang & Huize Ren & Xiaobin Dong & Xuechao Wang & Mengxue Liu & Ying Zhang & Yufang Zhang & Jiuming Huang & Shuheng Dong & Ruiming Xiao, 2023. "Understanding and Applications of Tensors in Ecosystem Services: A Case Study of the Manas River Basin," Land, MDPI, vol. 12(2), pages 1-23, February.
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