Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Impact of Tanzania’s Wildlife Management Areas on household wealth

Nature Sustainability volume 3, pages 226–233 (2020)Cite this article

Subjects

Abstract

Large-scale area-based conservation measures affect millions of people globally. Understanding their social impacts is necessary to improve effectiveness and minimize negative consequences. However, quantifying the impacts of conservation measures that affect large geographic areas and diverse peoples is expensive and methodologically challenging, particularly because such evaluations should capture locally defined conceptions of well-being while permitting policy-relevant comparisons. Here, we measure the impact of Tanzania’s Wildlife Management Areas (WMAs), a national community-based conservation and poverty reduction initiative. We use a novel, cost-effective impact evaluation method based on participatory wealth ranking and Bayesian multilevel modelling. We find that from 2007 to 2015 the impacts of WMAs on wealth were small and variable, with no clear evidence of widespread poverty reduction. Accompanying qualitative data suggest that apparently positive effects in one WMA cannot be directly attributed to WMA activities. Our results suggest that current WMA policy needs to be revisited if it is to promote positive local development.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Changes in household wealth from 2007 to 2014–2015.
Fig. 2: Mean differences-in-differences between trends in household wealth from 2007 to 2014–2015 associated with each of the six WMAs.
Fig. 3: Differences in wealth and WMA impacts associated with household characteristics.

Similar content being viewed by others

Data availability

The datasets analysed during the current study are available in the UK Data Service ReShare repository, https://doi.org/10.5255/UKDA-SN-852960, and are fully described in a data descriptor paper29.

Code availability

Computer code used in this analysis is available from the authors upon reasonable request.

References

  1. Watson, J. E. M., Dudley, N., Segan, D. B. & Hockings, M. The performance and potential of protected areas. Nature 515, 67–73 (2014).

    Article  CAS  Google Scholar 

  2. Roe, D., Elliott, J., Sandbrook, C. & Walpole, M. Biodiversity Conservation and Poverty Alleviation: Exploring the Evidence for a Link (John Wiley & Sons, 2012).

  3. Martin, A. Just Conservation: Biodiversity, Wellbeing and Sustainability (Taylor & Francis, 2017).

  4. Pullin, A. S. et al. Human well-being impacts of terrestrial protected areas. Environ. Evid. 2, 19 (2013).

    Article  Google Scholar 

  5. den Braber, B., Evans, K. L. & Oldekop, J. A. Impact of protected areas on poverty, extreme poverty, and inequality in nepal. Conserv. Lett. 33, e12576 (2018).

    Article  Google Scholar 

  6. Jones, N., McGinlay, J. & Dimitrakopoulos, P. G. Improving social impact assessment of protected areas: a review of the literature and directions for future research. Environ. Impact Assess. Rev. 64, 1–7 (2017).

    Article  Google Scholar 

  7. Oldekop, J. A., Holmes, G., Harris, W. E. & Evans, K. L. A global assessment of the social and conservation outcomes of protected areas. Conserv. Biol. 30, 133–141 (2016).

    Article  CAS  Google Scholar 

  8. Schleicher, J. The environmental and social impacts of protected areas and conservation concessions in South America. Curr. Opin. Environ. Sustain. 32, 1–8 (2018).

    Article  Google Scholar 

  9. Naidoo, R. et al. Evaluating the impacts of protected areas on human well-being across the developing world. Sci. Adv. 5, eaav3006 (2019).

    Article  CAS  Google Scholar 

  10. Oldekop, J. A., Sims, K. R. E., Karna, B. K., Whittingham, M. J. & Agrawal, A. Reductions in deforestation and poverty from decentralized forest management in Nepal. Nat. Sustain. 2, 421–428 (2019).

    Article  Google Scholar 

  11. Ferraro, P. J. & Pressey, R. L. Measuring the difference made by conservation initiatives: protected areas and their environmental and social impacts. Philos. Trans. R. Soc. Lond. B 370, 20140270 (2015).

    Article  Google Scholar 

  12. Baylis, K. et al. Mainstreaming impact evaluation in nature conservation. Conserv. Lett. 9, 58–64 (2016).

    Article  Google Scholar 

  13. Woodhouse, E. et al. Guiding principles for evaluating the impacts of conservation interventions on human well-being. Philos. Trans. R. Soc. Lond. B 370, 20150103 (2015).

    Article  Google Scholar 

  14. Agarwala, M. et al. Assessing the relationship between human well-being and ecosystem services: a review of frameworks. Conserv. Soc. 12, 437–449 (2014).

    Article  Google Scholar 

  15. Palmer Fry, B. et al. Monitoring local well-being in environmental interventions: a consideration of practical trade-offs. Oryx 51, 68–76 (2017).

    Article  Google Scholar 

  16. Howland, O., Noe, C. & Brockington, D. The multiple meanings of prosperity and poverty: a cross-site comparison from Tanzania. J. Peasant Stud. https://doi.org/10.1080/03066150.2019.1658080 (2019).

  17. Woodhouse, E. & McCabe, J. T. Well-being and conservation: diversity and change in visions of a good life among the Maasai of northern Tanzania. Ecol. Soc. 23, 43 (2018).

    Article  Google Scholar 

  18. Ferraro, P. J., Hanauer, M. M. & Sims, K. R. E. Conditions associated with protected area success in conservation and poverty reduction. Proc. Natl Acad. Sci. USA 108, 13913–13918 (2011).

    Article  CAS  Google Scholar 

  19. Pfaff, A., Robalino, J., Sanchez-Azofeifa, G. A., Andam, K. S. & Ferraro, P. J. Park location affects forest protection: land characteristics cause differences in park impacts across Costa Rica. B. E. J. Econom. Anal. Policy 9, (2009).

  20. Ferraro, P. J. & Miranda, J. J. Heterogeneous treatment effects and mechanisms in information-based environmental policies: evidence from a large-scale field experiment. Res. Energy Econ. 35, 356–379 (2013).

    Article  Google Scholar 

  21. 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 

  22. Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models (Cambridge Univ. Press, 2006).

  23. Sills, E. O. et al. Building the evidence base for REDD+: study design and methods for evaluating the impacts of conservation interventions on local well-being. Glob. Environ. Change 43, 148–160 (2017).

    Article  Google Scholar 

  24. 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).

    Article  CAS  Google Scholar 

  25. Ho, D. E., Imai, K., King, G. & Stuart, E. A. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Polit. Anal. 15, 199–236 (2007).

    Article  Google Scholar 

  26. Arriagada, R. A., Sills, E. O., Pattanayak, S. K. & Ferraro, P. J. Combining qualitative and quantitative methods to evaluate participation in Costa Rica’s program of payments for environmental services. J. Sustain. For. 28, 343–367 (2009).

    Article  Google Scholar 

  27. Margoluis, R., Stem, C., Salafsky, N. & Brown, M. Design alternatives for evaluating the impact of conservation projects. N. Dir. Eval. 2009, 85–96 (2009).

    Article  Google Scholar 

  28. Tanzania’s Wildlife Management Areas: A 2012 Status Report (WWF, 2014).

  29. Bluwstein, J. et al. A quasi-experimental study of impacts of Tanzania’s wildlife management areas on rural livelihoods and wealth. Sci. Data 5, 180087 (2018).

    Article  Google Scholar 

  30. Noe, C. & Kangalawe, R. Y. M. Wildlife protection, community participation in conservation, and (dis) empowerment in southern Tanzania. Conserv. Soc. 13, 244 (2015).

    Article  Google Scholar 

  31. Bluwstein, J. & Lund, J. F. Territoriality by conservation in the Selous–Niassa corridor in Tanzania. World Dev. 101, 453–465 (2018).

    Article  Google Scholar 

  32. Wright, C. V. Turbulent terrains: the contradictions and politics of decentralised conservation. Conserv. Soc. 15, 157 (2017).

    Article  Google Scholar 

  33. Moyo, F., Ijumba, J. & Lund, J. F. Failure by design? Revisiting Tanzania’s flagship Wildlife Management Area Burunge. Conserv. Soc. 14, 232 (2016).

    Article  Google Scholar 

  34. Benjaminsen, T. A., Goldman, M. J., Minwary, M. Y. & Maganga, F. P. Wildlife management in Tanzania: state control, rent seeking and community resistance. Dev. Change 44, 1087–1109 (2013).

    Article  Google Scholar 

  35. Igoe, J. & Croucher, B. Conservation, commerce, and communities: the story of community-based wildlife management areas in Tanzania’s northern tourist circuit. Conserv. Soc. 5, 534–561 (2007).

    Google Scholar 

  36. Brockington, D., Howland, O., Loiske, V.-M., Mnzava, M. & Noe, C. Economic growth, rural assets and prosperity: exploring the implications of a 20-year record of asset growth in Tanzania. J. Mod. Afr. Stud. 56, 217–243 (2018).

    Article  Google Scholar 

  37. Tanzania Mainland Poverty Assessment (World Bank, 2015).

  38. Kangalawe, R. Y. M. & Noe, C. Biodiversity conservation and poverty alleviation in Namtumbo district, Tanzania. Agric. Ecosyst. Environ. 162, 90–100 (2012).

    Article  Google Scholar 

  39. Noe, C. Contesting Village Land: Uranium and Sport Hunting in Mbarang’andu Wildlife Management Area, Tanzania (The Land Deal Politics Initiative, 2013).

  40. Homewood, K. et al. The Economic and Social Viability of Tanzanian Wildlife Management Areas (Copenhagen Centre for Development Research, 2015).

  41. Bluwstein, J. Creating ecotourism territories: environmentalities in Tanzania’s community-based conservation. Geoforum 83, 101–113 (2017).

    Article  Google Scholar 

  42. Bluwstein, J., Moyo, F. & Kicheleri, R. P. Austere conservation: understanding conflicts over resource governance in Tanzanian wildlife management areas. Conserv. Soc. 14, 218 (2016).

    Article  Google Scholar 

  43. Homewood, K. et al. Realising the Promise of Tanzania’s Wildlife Management Areas (ESPA, 2017).

  44. Williams, A. Community Natural Resources Management in Tanzania (Africa Biodiversity Collaborative Group, 2017).

  45. Butchart, S. H. M. et al. Shortfalls and solutions for meeting national and global conservation area targets. Conserv. Lett. 8, 329–337 (2015).

    Article  Google Scholar 

  46. de Lange, E., Woodhouse, E. & Milner-Gulland, E. J. Approaches used to evaluate the social impacts of protected areas. Conserv. Lett. 9, 327–333 (2016).

    Article  Google Scholar 

  47. Lund, J. F., Shackleton, S. & Luckert, M. in Measuring Livelihoods and Environmental Dependence: Methods for Research and Fieldwork (eds Angelsen, A. et al.) 175–189 (Earthscan, 2011).

  48. Scoones, I. Investigating difference: applications of wealth ranking and household survey approaches among farming households in southern Zimbabwe. Dev. Change 26, 67–88 (1995).

    Article  Google Scholar 

  49. Agresti, A. Categorical Data Analysis (Wiley, 2002).

  50. Mkukuta: Tanzania’s National Strategy for Growth and Reduction of Poverty (United Republic of Tanzania, 2005).

  51. Bluwstein, J. et al. Between dependence and deprivation: the interlocking nature of land alienation in Tanzania. J. Agrar. Change 18, 806–830 (2018).

    Article  Google Scholar 

  52. Naidoo, R. et al. Complementary benefits of tourism and hunting to communal conservancies in Namibia. Conserv. Biol. 30, 628–638 (2016).

    Article  Google Scholar 

  53. Naidoo, R. et al. Effect of diversity of large wildlife species on financial benefits to local communities in northwest Namibia. Environ. Resour. Econ. 48, 321–335 (2011).

    Article  Google Scholar 

  54. Lindsey, P. A. et al. Benefits of wildlife-based land uses on private lands in Namibia and limitations affecting their development. Oryx 47, 41–53 (2013).

    Article  Google Scholar 

  55. Goldman, M. Partitioned nature, privileged knowledge: community-based conservation in Tanzania. Dev. Change 34, 833–862 (2003).

    Article  Google Scholar 

  56. Nelson, F. Emerging or Illusory? Community Wildlife Management in Tanzania (IIED, 2007).

  57. Galvin, K., Beeton, T. & Luizza, M. African community-based conservation: a systematic review of social and ecological outcomes. Ecol. Soc. 23, 39 (2018).

    Article  Google Scholar 

  58. Sulle, E., Lekaita, E. & Nelson, F. From Promise to Performance? Wildlife Management Areas in Northern Tanzania (Tanzania Natural Resource Forum and Maliasili Initiatives, 2011).

  59. 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  CAS  Google Scholar 

  60. Salerno, J., Mulder, M. B., Grote, M. N., Ghiselli, M. & Packer, C. Household livelihoods and conflict with wildlife in community-based conservation areas across northern Tanzania. Oryx 50, 702–712 (2016).

    Article  Google Scholar 

  61. Homewood, K., Nielsen, M. & Keane, A. Women, wellbeing and Wildlife Management Areas in Tanzania. J. Peasant Stud. (in press).

  62. Zafra-Calvo, N., Lobo, J. M., Prada, C., Nielsen, M. R. & Burgess, N. D. Predictors of elephant poaching in a wildlife crime hotspot: the Ruvuma landscape of southern Tanzania and northern Mozambique. J. Nat. Conserv. 41, 79–87 (2018).

    Article  Google Scholar 

  63. Angrist, J. D. & Pischke, J.-S. Mostly Harmless Econometrics: An Empiricist’s Companion (Princeton Univ. Press, 2008).

  64. Homewood, K., Kristjanson, P., & Trench, P. C. (eds) Staying Maasai?: Livelihoods, Conservation and Development in East African Rangelands (Springer-Verlag, 2009).

  65. White, H. Theory-based impact evaluation: principles and practice. J. Dev. Eff. 1, 271–284 (2009).

    Article  Google Scholar 

  66. Jagger, P., Luckert, M. K., Banana, A. & Bahati, J. Asking questions to understand rural livelihoods: comparing disaggregated vs. aggregated approaches to household livelihood questionnaires. World Dev. 40, 1810–1823 (2012).

    Article  Google Scholar 

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

  68. Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).

    Article  Google Scholar 

  69. Gelman, A. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper). Bayesian Anal. 1, 515–534 (2006).

    Article  Google Scholar 

  70. Gelman, A. Scaling regression inputs by dividing by two standard deviations. Stat. Med. 27, 2865–2873 (2008).

    Article  Google Scholar 

Download references

Acknowledgements

This research was carried out as part of the project Poverty and Ecosystem Impacts of Tanzania’s Wildlife Management Areas (PIMA), NE/L00139X/1, funded with support from the Ecosystem Services for Poverty Alleviation (ESPA) programme. The ESPA programme was funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC) and the Natural Environment Research Council (NERC). A.K. also acknowledges support from the Understanding the Impacts of the Current El Niño programme of NERC and Department for International Development (DfID) (grant reference no. NE/P004725/1). We thank the Government of Tanzania for their permission to carry out fieldwork associated with this research project and the Tanzanian communities who participated in the research.

Author information

Authors and Affiliations

  1. School of GeoSciences, University of Edinburgh, Edinburgh, UK

    Aidan Keane

  2. Department of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark

    Jens Friis Lund, Jevgeniy Bluwstein & Martin Reinhardt Nielsen

  3. Department of Geosciences, University of Fribourg, Fribourg, Switzerland

    Jevgeniy Bluwstein

  4. UN Environment Programme World Conservation Monitoring Centre, Cambridge, UK

    Neil D. Burgess

  5. Centre for Macroecology, Evolution and Climate, University of Copenhagen, Copenhagen, Denmark

    Neil D. Burgess

  6. Department of Anthropology, University College London, London, UK

    Katherine Homewood

Authors
  1. Aidan Keane
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jens Friis Lund
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jevgeniy Bluwstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Neil D. Burgess
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martin Reinhardt Nielsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Katherine Homewood
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the conceptualization of the project and the development of the survey and sampling procedures. J.B. led data collection in the field. A.K. analysed the data. A.K. led the writing of the manuscript, with all authors contributing sections of text, comments and review.

Corresponding author

Correspondence to Aidan Keane.

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, Tables 1–3 and Figs. 1–6.

Supplementary Data 1

The full set of criteria decided by and used in village-level focus group wealth-ranking exercises.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Keane, A., Lund, J.F., Bluwstein, J. et al. Impact of Tanzania’s Wildlife Management Areas on household wealth. Nat Sustain 3, 226–233 (2020). https://doi.org/10.1038/s41893-019-0458-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41893-019-0458-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Anthropocene