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Reductions in deforestation and poverty from decentralized forest management in Nepal

Abstract

Since the 1980’s, decentralized forest management has been promoted as a way to enhance sustainable forest use and reduce rural poverty. Rural communities manage increasing amounts of the world’s forests, yet rigorous evidence using large-N data on whether community-based forest management (CFM) can jointly reduce both deforestation and poverty remains scarce. We estimate the impacts of CFM using a large longitudinal dataset that integrates national census-based poverty measures with high-resolution forest cover change data, and near-complete information on Nepal’s >18,000 community forests. We compare changes in forest cover and poverty from 2000–2012 for subdistricts with or without CFM arrangements, but that are otherwise similar in terms of socioeconomic and biophysical baseline measures. Our results indicate that CFM has, on average, contributed to significant net reductions in both poverty and deforestation across Nepal, and that CFM increases the likelihood of win–win outcomes. We also find that the estimated reduced deforestation impacts of community forests are lower where baseline poverty levels are high, and greater where community forests are larger and have existed longer. These results indicate that greater benefits may result from longer-term investments and larger areas committed to CFM, but that community forests established in poorer areas may require additional support to minimize tradeoffs between socioeconomic and environmental outcomes.

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Data availability

Most of the raw data used in this study are available from the Central Bureau of Statistics of Nepal and other organizations, but restrictions apply to the availability of some of the data. These data can be made available from the authors upon reasonable request, and with permission from the relevant organizations. All computer code used in this analysis is available from the authors upon reasonable request.

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Acknowledgements

We thank R. Li and S. Brines for help with travel time calculations, R. Meeks for help with data acquisition in Nepal, A. Chomentowska and D. Bhattarai for research assistance, and R. Whittingham for statistical help. We are especially grateful to the agencies and institutions that made their data available. This project was supported by the UK’s Department for International Development (grant number 203516-102), a European Union FP7 Marie Curie international outgoing fellowship (FORCONEPAL) to J.A.O. linking Newcastle University and the University of Michigan, and the Carnegie Corporation of New York ‘Andrew Carnegie Fellowship’ to K.R.E.S.

Author information

J.A.O., K.R.E.S., M.J.W. and A.A. conceived and designed the study and statistical analysis. J.A.O. compiled the dataset and performed the statistical analysis. J.A.O., K.R.E.S., B.K.K., M.J.W. and A.A. wrote the paper.

Competing interests

The authors declare no competing interests.

Correspondence to Johan A. Oldekop.

Supplementary information

  1. Supplementary Information

    Supplementary methods, Supplementary references 1–8, Supplementary Figs. 1–19, Supplementary Tables 1–14

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Fig. 1: Distribution of community forests in Nepal and mean postmatching differences in forest cover change and poverty alleviation due to CFM arrangements.
Fig. 2: Categorization and percentage mean difference in the outcome likelihood for all different joint outcomes as function of the presence or absence of CFM.
Fig. 3: Changes in predicted deforestation values and likelihood of VDCs having CFM arrangements along increases in baseline poverty (2001).