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.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

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).

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.

References

  1. 1.

    Transforming our World: the 2030 Agenda for Sustainable Development (United Nations, 2015).

  2. 2.

    Paris Agreement (UNFCCC, 2016).

  3. 3.

    Reid, W. V. et al. in Ecosystems and Human Well-being: Synthesis: A Report of the Millenium Ecosystem Assessment 5 (Island Press, 2005).

  4. 4.

    Gilmour, D. Forty Years of Community-Based Forestry: A Review of its Extent and Effectiveness (Food and Agriculture Organization of the United Nations, 2016).

  5. 5.

    Somanathan, E., Prabhakar, R. & Mehta, B. S. Decentralization for cost-effective conservation. Proc. Natl Acad. Sci. USA 106, 4143–4147 (2009).

    CAS  Article  Google Scholar 

  6. 6.

    Tenure Data Tool (Rights and Resources Initiative, 2017); http://rightsandresources.org/en/work-impact/tenure-data-tool/#.WY6jIq2ZORs

  7. 7.

    Hajjar, R. et al. The data not collected on community forestry. Conserv. Biol. 30, 1357–1362 (2016).

    Article  Google Scholar 

  8. 8.

    Bowler, D. E. et al. Does community forest management provide global environmental benefits and improve local welfare? Front. Ecol. Environ. 10, 29–36 (2012).

    Article  Google Scholar 

  9. 9.

    Persha, L., Agrawal, A. & Chhatre, A. Social and ecological synergy: local rulemaking, forest livelihoods, and biodiversity conservation. Science 331, 1606–1608 (2011).

    CAS  Article  Google Scholar 

  10. 10.

    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).

    CAS  Article  Google Scholar 

  11. 11.

    Edmunds, D. S. & Wollenberg, E. K. Local Forest Management: the Impacts of Devolution Policies (Earthscan, 2003).

  12. 12.

    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).

    Article  Google Scholar 

  13. 13.

    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).

    Article  Google Scholar 

  14. 14.

    Tachibana, T. & Adhikari, S. Does community-based management improve natural resource condition? Evidence from the forests in Nepal. Land Econ. 85, 107–131 (2010).

    Article  Google Scholar 

  15. 15.

    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).

    Article  Google Scholar 

  16. 16.

    Rasolofoson, R. A. et al. Impacts of community forest management on human economic well-being across Madagascar. Conserv. Lett. 10, 346–353 (2017).

    Article  Google Scholar 

  17. 17.

    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).

    Article  Google Scholar 

  18. 18.

    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).

    Article  Google Scholar 

  19. 19.

    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).

    Article  Google Scholar 

  20. 20.

    Ellis, F. & Freeman, H. A. Rural livelihoods and poverty reduction strategies in four African countries. J. Dev. Stud. 40, 1–30 (2004).

    Article  Google Scholar 

  21. 21.

    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).

    Article  Google Scholar 

  22. 22.

    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).

    CAS  Article  Google Scholar 

  23. 23.

    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).

    CAS  Article  Google Scholar 

  24. 24.

    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).

    CAS  Article  Google Scholar 

  25. 25.

    Hobley, M. Review of 30 Years of Community Forestry in Nepal (Ministry of Forests and Soil Conservation, Government of Nepal, 2013).

  26. 26.

    Ojha, H. R., Persha, L. & Chhatre, A. Community Forestry in Nepal: a Policy Innovation for Local Livelihoods (International Food Policy Research Institute, 2010).

  27. 27.

    State of Nepal’s Forests (Ministry of Forests and Soil Conservation, Government of Nepal, 2015).

  28. 28.

    Bray, D. B. et al. Mexico’s community-managed forests as a global model for sustainable landscapes. Conserv. Biol. 17, 672–677 (2003).

    Article  Google Scholar 

  29. 29.

    Hill, I. Forest Management in Nepal (World Bank, 1999).

  30. 30.

    Nepal Living Standards Survey 2010/11 (Central Bureau of Statistics, Government of Nepal, 2011).

  31. 31.

    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).

    Article  Google Scholar 

  32. 32.

    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).

    Google Scholar 

  33. 33.

    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).

    Article  Google Scholar 

  34. 34.

    Rytkönen, A. Sustainable Forest Management in Nepal: an MSFP Working Paper (Multi-Stakeholder Forestry Programme, 2016).

  35. 35.

    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).

    Article  Google Scholar 

  36. 36.

    Pouzols, F. M. et al. Global protected area expansion is compromised by projected land-use and parochialism. Nature 516, 383–386 (2014).

    Article  Google Scholar 

  37. 37.

    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).

    Article  Google Scholar 

  38. 38.

    Nepal Government Geo-portal (Ministry of Home Affairs, 2014); http://drm.moha.gov.np/?page=2

  39. 39.

    Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    CAS  Article  Google Scholar 

  40. 40.

    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).

    Article  Google Scholar 

  41. 41.

    Uddin, K. et al. Development of 2010 national land cover database for the Nepal. J. Environ. Manage. 148, 82–90 (2015).

    Article  Google Scholar 

  42. 42.

    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).

    Article  Google Scholar 

  43. 43.

    Sen, A. K. Poverty and Famines. An Essay on Entitlement and Deprivation (Oxford Univ. Press, 1981).

  44. 44.

    Green, M. & Hulme, D. From correlates and characteristics to causes: thinking about poverty from a chronic poverty perspective. World Dev. 33, 867–879 (2005).

    Article  Google Scholar 

  45. 45.

    Alkire, S. & Foster, J. Counting and multidimensional poverty measurement. J. Public Econ. 95, 476–487 (2011).

    Article  Google Scholar 

  46. 46.

    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).

    Article  Google Scholar 

  47. 47.

    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).

    Article  Google Scholar 

  48. 48.

    DFID Annual Report and Accounts 2011–2012 (Department for International Development, 2012).

  49. 49.

    Nepal Small Area Estimation of Poverty, 2011 (National Planning Commission & World Bank, 2013).

  50. 50.

    Agrawal, A. Forests, governance, and sustainability: common property theory and its contributions. Int. J. Commons 1, 111–136 (2007).

    Article  Google Scholar 

  51. 51.

    Angelsen, A. et al. Environmental income and rural livelihoods: a global-comparative analysis. World Dev. 64, S12–S28 (2014).

    Article  Google Scholar 

  52. 52.

    Edmonds, E. V. Government-initiated community resource management and local resource extraction from Nepal’s forests. J. Dev. Econ. 68, 89–115 (2002).

    Article  Google Scholar 

  53. 53.

    Stuart, E. A. Matching methods for causal inference: a review and a look forward. Stat. Sci. 25, 1–21 (2010).

    Article  Google Scholar 

  54. 54.

    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).

    Article  Google Scholar 

  55. 55.

    Global Digital Elevation Model Version 2 (Ministry of Economy, Trade and Industry & NASA, 2011).

  56. 56.

    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).

    CAS  Article  Google Scholar 

  57. 57.

    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).

    Article  Google Scholar 

  58. 58.

    Lim, S. & Basnet, H. C. International migration, workers’ remittances and permanent income hypothesis. World Dev. 96, 438–450 (2017).

    Article  Google Scholar 

  59. 59.

    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).

  60. 60.

    Global Land Cover 2000 Database (Joint Research Centre of the European Commission, 2003).

  61. 61.

    Murshed, S. M. & Gates, S. Spatial–horizontal inequality and the Maoist insurgency in Nepal. Rev. Dev. Econ. 9, 121–134 (2005).

    Article  Google Scholar 

  62. 62.

    World Database on Protected Areas (UNEP-WCMC & IUCN, 2015).

  63. 63.

    Hansen, B. B. Full matching in an observational study of coaching for the SAT. J. Am. Stat. Assoc. 99, 609–618 (2004).

    Article  Google Scholar 

  64. 64.

    R Core Development Team R: A Language Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  65. 65.

    Ho, D., Imai, K., King, G. & Stuart, E. A. MatchIt: nonparametric preprocessing for parametric causal inference. J. Stat. Softw. 42, 1–28 (2011).

    Article  Google Scholar 

  66. 66.

    Harrell, F. E. Jr. Package ‘rms’ (The Comprehensive R Archive Network, 2016).

  67. 67.

    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).

    Article  Google Scholar 

  68. 68.

    Bivand, R. et al. Package ‘spdep’ (The Comprehensive R Archive Network, 2017).

  69. 69.

    Pebesma, E. & Graeler, B. Package ‘gstat’ (The Comprehensive R Archive Network, 2017).

  70. 70.

    Blackwell, M. A selection bias approach to sensitivity analysis for causal effects. Political Anal. 22, 169–182 (2014).

    Article  Google Scholar 

  71. 71.

    Rosenbaum, P. R. Observational Studies (Springer, 2002).

Download references

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

Affiliations

Authors

Contributions

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.

Corresponding author

Correspondence to Johan A. Oldekop.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Oldekop, J.A., Sims, K.R.E., Karna, B.K. et al. Reductions in deforestation and poverty from decentralized forest management in Nepal. Nat Sustain 2, 421–428 (2019). https://doi.org/10.1038/s41893-019-0277-3

Download citation

Further reading