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.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $8.67 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
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.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Transforming our World: the 2030 Agenda for Sustainable Development (United Nations, 2015).
Paris Agreement (UNFCCC, 2016).
Reid, W. V. et al. in Ecosystems and Human Well-being: Synthesis: A Report of the Millenium Ecosystem Assessment 5 (Island Press, 2005).
Gilmour, D. Forty Years of Community-Based Forestry: A Review of its Extent and Effectiveness (Food and Agriculture Organization of the United Nations, 2016).
Somanathan, E., Prabhakar, R. & Mehta, B. S. Decentralization for cost-effective conservation. Proc. Natl Acad. Sci. USA 106, 4143–4147 (2009).
Tenure Data Tool (Rights and Resources Initiative, 2017); http://rightsandresources.org/en/work-impact/tenure-data-tool/#.WY6jIq2ZORs
Hajjar, R. et al. The data not collected on community forestry. Conserv. Biol. 30, 1357–1362 (2016).
Bowler, D. E. et al. Does community forest management provide global environmental benefits and improve local welfare? Front. Ecol. Environ. 10, 29–36 (2012).
Persha, L., Agrawal, A. & Chhatre, A. Social and ecological synergy: local rulemaking, forest livelihoods, and biodiversity conservation. Science 331, 1606–1608 (2011).
Chhatre, A. & Agrawal, A. Trade-offs and synergies between carbon storage and livelihood benefits from forest commons. Proc. Natl Acad. Sci. USA 106, 17667–17670 (2009).
Edmunds, D. S. & Wollenberg, E. K. Local Forest Management: the Impacts of Devolution Policies (Earthscan, 2003).
Rasolofoson, R. A., Ferraro, P. J., Jenkins, C. N. & Jones, J. P. G. Effectiveness of community forest management at reducing deforestation in Madagascar. Biol. Conserv. 184, 271–277 (2015).
Wright, G. D., Andersson, K. P., Gibson, C. C. & Evans, T. P. Decentralization can help reduce deforestation when user groups engage with local government. Proc. Natl Acad. Sci. USA 52, 14958–14963 (2016).
Tachibana, T. & Adhikari, S. Does community-based management improve natural resource condition? Evidence from the forests in Nepal. Land Econ. 85, 107–131 (2010).
Pailler, S., Naidoo, R., Burgess, N. D., Freeman, O. E. & Fisher, B. Impacts of community-based natural resource management on wealth, food security and child health in Tanzania. PLoS ONE 10, e0133252 (2015).
Rasolofoson, R. A. et al. Impacts of community forest management on human economic well-being across Madagascar. Conserv. Lett. 10, 346–353 (2017).
Jumbe, C. B. L. & Angelsen, A. Do the poor benefit from devolution policies? Evidence from Malawi’s forest co-management program. Land Econ. 84, 562–581 (2006).
Rahut, D. B., Ali, A. & Behera, B. Household participation and effects of community forest management on income and poverty levels: empirical evidence from Bhutan. Forest Policy Econ. 61, 20–29 (2015).
Geist, H. J. & Lambin, E. F. Proximate causes and underlying driving forces of tropical deforestation: tropical forests are disappearing as the result of many pressures, both local and regional, acting in various combinations in different geographical locations. BioScience 52, 143–150 (2002).
Ellis, F. & Freeman, H. A. Rural livelihoods and poverty reduction strategies in four African countries. J. Dev. Stud. 40, 1–30 (2004).
Ho, D. E., Imai, K., King, G. & Stuart, E. A. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Anal. 15, 199–236 (2007).
Andam, K. S., Ferraro, P. J., Pfaff, A., Sanchez-Azofeifa, G. A. & Robalino, J. A. Measuring the effectiveness of protected area networks in reducing deforestation. Proc. Natl Acad. Sci. USA 105, 16089–16094 (2008).
Andam, K. S., Ferraro, P. J., Sims, K. R. E., Healy, A. & Holland, M. B. Protected areas reduced poverty in Costa Rica and Thailand. Proc. Natl Acad. Sci. USA 107, 9996–10001 (2010).
Blackman, A., Corral, L., Lima, E. S. & Asner, G. P. Titling indigenous communities protects forests in the Peruvian Amazon. Proc. Natl Acad. Sci. USA 114, 4123–4128 (2017).
Hobley, M. Review of 30 Years of Community Forestry in Nepal (Ministry of Forests and Soil Conservation, Government of Nepal, 2013).
Ojha, H. R., Persha, L. & Chhatre, A. Community Forestry in Nepal: a Policy Innovation for Local Livelihoods (International Food Policy Research Institute, 2010).
State of Nepal’s Forests (Ministry of Forests and Soil Conservation, Government of Nepal, 2015).
Bray, D. B. et al. Mexico’s community-managed forests as a global model for sustainable landscapes. Conserv. Biol. 17, 672–677 (2003).
Hill, I. Forest Management in Nepal (World Bank, 1999).
Nepal Living Standards Survey 2010/11 (Central Bureau of Statistics, Government of Nepal, 2011).
Pandit, B. H., Albano, A. & Kumar, C. Community-based forest enterprises in Nepal: an analysis of their role in increasing income benefits to the poor. Small Scale For. 8, 447–462 (2009).
Malla, Y. B., Neupane, H. R. & Branney, P. J. Why aren’t poor people benefiting from community forestry? J. Forest Livelihood 3, 78–93 (2003).
Sims, K. R. E. & Alix-Garcia, J. M. Parks versus PES: evaluating direct and incentive-based land conservation in Mexico. J. Environ. Econ. Manage. 86, 8–28 (2017).
Rytkönen, A. Sustainable Forest Management in Nepal: an MSFP Working Paper (Multi-Stakeholder Forestry Programme, 2016).
Ojha, H. R. Beyond the ‘local community’: the evolution of multi-scale politics in Nepal’s community forestry regimes. Int. Forest. Rev. 16, 339–353 (2014).
Pouzols, F. M. et al. Global protected area expansion is compromised by projected land-use and parochialism. Nature 516, 383–386 (2014).
Oldekop, J. A., Sims, K. R. E., Whittingham, M. J. & Agrawal, A. An upside to globalization: international migration drives reforestation in Nepal. Glob. Environ. Change 52, 66–74 (2018).
Nepal Government Geo-portal (Ministry of Home Affairs, 2014); http://drm.moha.gov.np/?page=2
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Goerg, G. M. The Lambert way to Gaussianize heavy-tailed data with the inverse of Tukey’s h transformation as a special case. Sci. World J. 2015, 909231 (2015).
Uddin, K. et al. Development of 2010 national land cover database for the Nepal. J. Environ. Manage. 148, 82–90 (2015).
Uddin, K., Abdul Matin, M. & Maharjan, S. Assessment of land cover change and its impact on changes in soil erosion risk in Nepal. Sustainability 10, 4715 (2018).
Sen, A. K. Poverty and Famines. An Essay on Entitlement and Deprivation (Oxford Univ. Press, 1981).
Green, M. & Hulme, D. From correlates and characteristics to causes: thinking about poverty from a chronic poverty perspective. World Dev. 33, 867–879 (2005).
Alkire, S. & Foster, J. Counting and multidimensional poverty measurement. J. Public Econ. 95, 476–487 (2011).
Alkire, S. & Santos, M. E. Measuring acute poverty in the developing world: robustness and scope of the multidimensional poverty index. World Dev. 59, 251–274 (2014).
Bartram, J. et al. Global monitoring of water supply and sanitation: history, methods and future challenges. Int. J. Environ. Res. Public Health 11, 8137–8165 (2014).
DFID Annual Report and Accounts 2011–2012 (Department for International Development, 2012).
Nepal Small Area Estimation of Poverty, 2011 (National Planning Commission & World Bank, 2013).
Agrawal, A. Forests, governance, and sustainability: common property theory and its contributions. Int. J. Commons 1, 111–136 (2007).
Angelsen, A. et al. Environmental income and rural livelihoods: a global-comparative analysis. World Dev. 64, S12–S28 (2014).
Edmonds, E. V. Government-initiated community resource management and local resource extraction from Nepal’s forests. J. Dev. Econ. 68, 89–115 (2002).
Stuart, E. A. Matching methods for causal inference: a review and a look forward. Stat. Sci. 25, 1–21 (2010).
Meyfroidt, P. & Lambin, E. F. Prospects and options for an end to deforestation and global restoration of forests. Annu. Rev. Environ. Resour. 36, 343–371 (2012).
Global Digital Elevation Model Version 2 (Ministry of Economy, Trade and Industry & NASA, 2011).
Nelson, A. & Chomitz, K. M. Effectiveness of strict vs. multiple use protected areas in reducing tropical forest fires: a global analysis using matching methods. PLoS ONE 6, e22722 (2011).
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).
Lim, S. & Basnet, H. C. International migration, workers’ remittances and permanent income hypothesis. World Dev. 96, 438–450 (2017).
Nelson, A. Estimated Travel Time to the Nearest City of 50,000 or More People in the Year 2000 (Joint Research Center of the European Commission, 2008).
Global Land Cover 2000 Database (Joint Research Centre of the European Commission, 2003).
Murshed, S. M. & Gates, S. Spatial–horizontal inequality and the Maoist insurgency in Nepal. Rev. Dev. Econ. 9, 121–134 (2005).
World Database on Protected Areas (UNEP-WCMC & IUCN, 2015).
Hansen, B. B. Full matching in an observational study of coaching for the SAT. J. Am. Stat. Assoc. 99, 609–618 (2004).
R Core Development Team R: A Language Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).
Ho, D., Imai, K., King, G. & Stuart, E. A. MatchIt: nonparametric preprocessing for parametric causal inference. J. Stat. Softw. 42, 1–28 (2011).
Harrell, F. E. Jr. Package ‘rms’ (The Comprehensive R Archive Network, 2016).
Karna, B. K., Shivakoti, G. P. & Webb, E. L. Resilience of community forestry under conditions of armed conflict in Nepal. Environ. Conserv. 37, 201–209 (2010).
Bivand, R. et al. Package ‘spdep’ (The Comprehensive R Archive Network, 2017).
Pebesma, E. & Graeler, B. Package ‘gstat’ (The Comprehensive R Archive Network, 2017).
Blackwell, M. A selection bias approach to sensitivity analysis for causal effects. Political Anal. 22, 169–182 (2014).
Rosenbaum, P. R. Observational Studies (Springer, 2002).
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.
Supplementary methods, Supplementary references 1–8, Supplementary Figs. 1–19, Supplementary Tables 1–14