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Cited by 358

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Forest commons and local enforcement

Open access
Chhatre, Ashwini, Agrawal, Arun·2008·Proceedings of the National Academy of Sciences

Abstract

This article examines the relationship between local enforcement and forests used as commons. It uses a unique multicountry dataset, created over the past 15 years by the International Forestry Resources and Institutions Research Program. Drawing on original enforcement and forest commons data from 9 countries, we find that higher levels of local enforcement have a strong and positive but complex relationship to the probability of forest regeneration. This relationship holds even when the influence of a number of other factors such as user group size, subsistence, and commercial importance of forests, size of forest, and collective action for forest improvement activities is taken into account. Although several of the above factors have a statistically significant relationship to changes in the condition of forest commons, differences in levels of local enforcement strongly moderate their link with forest commons outcomes. The research, using data from diverse political, social, and ecological contexts, shows both the importance of enforcement to forest commons and some of the limits of forest governance through commons arrangements.

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Metadata

Authors
Chhatre, A., & Agrawal, A.
Venue
Proceedings of the National Academy of Sciences
Published
2008-09-09
Volume
105
Issue
36
Pages
13286-13291
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2033148381
Cited by
358
References
26
FWCI
18.21
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Forest commons and local enforcement. https://app.cochat.ai/papers/10.1073/pnas.0803399105
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Chhatre, A., & Agrawal, A. (2008). Forest commons and local enforcement. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0803399105

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.