A diagnostic for collaborative monitoring in forest landscape restoration
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Title |
A diagnostic for collaborative monitoring in forest landscape restoration
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Creator |
Guariguata, M.R.
Evans, K. |
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Subject |
ecological restoration
forest rehabilitation landscape |
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Description |
Monitoring is crucial to meet the goals of the major global forest landscape restoration (FLR) initiatives that are underway. If members of the global FLR community are going to learn from one another, a multi‐scalar, multi‐site monitoring approach is needed to generate information that can provide the basis for social learning and adaptive management, both of which are essential processes for FLR. This requires reframing and expanding the perspective of monitoring so that compliance monitoring is just one component of a multidimensional approach where collaborative monitoring and compliance‐oriented monitoring are complementary. However, FLR planners and implementers often lack experience in applying collaborative approaches in multi‐stakeholder settings, and there are few tools that show how to implement FLR or to engage in collaborative monitoring in FLR. Through a literature review, we identified the factors that contribute to successful collaborative monitoring in FLR and synthesized them into a diagnostic that was vetted by 20 global experts. The result is a checklist of 42 core success factors to be assessed at local, subnational, and national levels at different stages in the planning and implementation of FLR. The tool has practical application by providing guidance on best practices: specifically, how to start collaborative monitoring, and more generally, how to plan, prepare for, and evaluate FLR activities. This diagnostic complements other diagnostics, such as those used to identify FLR sites, as it can identify preexisting strengths and weaknesses in new initiatives, or pinpoint problems with ongoing implementation. The diagnostic explicitly addresses issues of scale, including multiple sites, governance levels, and changes over time.
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Date |
2020-07
2021-03-08T08:17:45Z 2021-03-08T08:17:45Z |
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Type |
Journal Article
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Identifier |
Guariguata, M.R., Evans, K. 2020. A diagnostic for collaborative monitoring in forest landscape restoration. Restoration Ecology, 28 (4): 742-749. https://doi.org/10.1111/rec.13076
1061-2971 1526-100X https://hdl.handle.net/10568/112082 https://www.cifor.org/library/7457 https://doi.org/10.1111/rec.13076 |
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Language |
en
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Rights |
CC-BY-NC-4.0
Open Access |
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Publisher |
Wiley
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