| Autor: |
Evans, Kristen, Meli, Paula, Zamora‐Cristales, René, Schweizer, Daniella, Méndez‐Toribio, Moisés, Gómez‐Ruiz, Pilar A., Guariguata, Manuel R. |
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| Zdroj: |
Restoration Ecology; May2023, Vol. 31 Issue 4, p1-9, 9p |
| Abstrakt: |
Despite growing global attention on forest landscape restoration (FLR) as an integrated approach to enhancing environmental and human well‐being, the potential for leveraging monitoring to catalyze learning and improve management outcomes is not being fully realized. We assessed the extent to which collaborative monitoring, a process that embraces cross‐scale multilevel actors and interactions in the collection and use of information, is considered across FLR projects in Latin America by applying a diagnostic of 54 "success factors" scored from 1 (factor not in place) to 5 (factor fully in place). Responses were collected from 36 projects across 12 countries. Although respondents generally understood monitoring as crucial to FLR success, local participation scored as insufficient. Several of the lowest‐ranked success factors related to training for local people in the use of tools, forms, and technology for data collection, and to interpreting data to promote understanding of management outcomes. The most notable finding related to the paucity of networks or entities to leverage information into knowledge‐sharing and learning opportunities from the top‐down and the bottom‐up. Our results provide a preliminary indication of how to promote collaborative monitoring approaches in the context of FLR projects in Latin America. First, it requires enhanced integration among academics, local communities and governmental and nongovernmental organizations. Second, it requires a minimum level of harmonization with current policy and normative forest conservation and restoration instruments. Finally, it needs bridging organizations or individuals to share results and learning as well as dedicated resources for information infrastructures to facilitate knowledge sharing. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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