How conservation initiatives go to scale

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Abstract

Although a major portion of the planet’s land and sea is managed to conserve biodiversity, little is known about the extent, speed and patterns of adoption of conservation initiatives. We undertook a quantitative exploration of how area-based conservation initiatives go to scale by analysing the adoption of 22 widely recognized and diverse initiatives from across the globe. We use a standardized approach to compare the potential of different initiatives to reach scale. While our study is not exhaustive, our analyses reveal consistent patterns across a variety of initiatives: adoption of most initiatives (82% of our case studies) started slowly before rapidly going to scale. Consistent with diffusion of innovation theory, most initiatives exhibit slow–fast–slow (that is, sigmoidal) dynamics driven by interactions between existing and potential adopters. However, uptake rates and saturation points vary among the initiatives and across localities. Our models suggest that the uptake of most of our case studies is limited; over half of the initiatives will be taken up by <30% of their potential adopters. We also provide a methodology for quantitatively understanding the process of scaling. Our findings inform us how initiatives scale up to widespread adoption, which will facilitate forecasts of the future level of adoption of initiatives, and benchmark their extent and speed of adoption against those of our case studies.

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Fig. 1: Location of the area-based biodiversity conservation initiatives analysed.
Fig. 2: The cumulative percentage of adopters of conservation initiatives.
Fig. 3: Slow–fast–slow models describing adoption of marine reserves by municipalities in the Philippines.
Fig. 4: Trade-off between the proportion of potential adopters predicted to adopt an initiative and the uptake rate for conservation initiatives that follow the slow–fast–slow model.

Data availability

Supplementary Table 1 lists all sources of the data used to estimate the total number of potential adopters and number of adoptions for each intervention per year. The data that support the findings of this study are available from the corresponding author on request. Correspondence and requests for materials should be addressed to M.M.

Code availability

All code for the modelling is available on GitHub (https://github.com/MikeBode/Diffusion_of_innovation_fitting).

References

  1. 1.

    Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).

  2. 2.

    Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O. & Ludwig, C. The trajectory of the Anthropocene: the great acceleration. Anthr. Rev. 2, 81–98 (2015).

  3. 3.

    Ceballos, G., Ehrlich, P. R. & Dirzo, R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proc. Natl Acad. Sci. USA 114, E6089–E6096 (2017).

  4. 4.

    Butchart, S. H. et al. Global biodiversity: indicators of recent declines. Science 328, 1164–1168 (2010).

  5. 5.

    Tittensor, D. P. et al. A mid-term analysis of progress toward international biodiversity targets. Science 346, 241–244 (2014).

  6. 6.

    Potts, S. G. et al. (eds) Summary for Policymakers of the Assessment Report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on Pollinators, Pollination and Food Production (IPBES, 2016).

  7. 7.

    Fox, H. E. et al. Explaining global patterns and trends in marine protected area (MPA) development. Mar. Policy 36, 1131–1138 (2012).

  8. 8.

    Radeloff, V. C. et al. Hot moments for biodiversity conservation. Conserv. Lett. 6, 58–65 (2013).

  9. 9.

    Mascia, M. B. & Mills, M. When conservation goes viral: the diffusion of innovative biodiversity conservation policies and practices. Conserv. Lett. 11, e12442 (2018).

  10. 10.

    Midgley, D. F. A simple mathematical theory of innovative behavior. J. Consum. Res. 3, 31–41 (1976).

  11. 11.

    Rogers, E. M. Diffusion of Innovations (Simon and Schuster, 2010).

  12. 12.

    Meskell, L., Liuzza, C., Bertacchini, E. & Saccone, D. Multilateralism and UNESCO World Heritage: decision-making, States Parties and political processes. Int. J. Herit. Stud. 21, 423–440 (2015).

  13. 13.

    Fa’asili, U. & Taua, A. Review of the Village Fisheries Management Plans of the Extension Programme in Samoa (Secretariat of the Pacific Community, 2001).

  14. 14.

    Jupiter, S. D., Cohen, P. J., Weeks, R., Tawake, A. & Govan, H. Locally-managed marine areas: multiple objectives and diverse strategies. Pac. Conserv. Biol. 20, 165–179 (2014).

  15. 15.

    Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P. & Kyriakidou, O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q. 82, 581–629 (2004).

  16. 16.

    Alcala, A. C. & Russ, G. R. No-take marine reserves and reef fisheries management in the Philippines: a new people power revolution. AMBIO 35, 245–254 (2006).

  17. 17.

    Lowry, G., White, A. & Christie, P. Scaling up to networks of marine protected areas in the Philippines: biophysical, legal, institutional, and social considerations. Coast. Manag. 37, 274–290 (2009).

  18. 18.

    Kuehne, G. et al. Predicting farmer uptake of new agricultural practices: a tool for research, extension and policy. Agric. Syst. 156, 115–125 (2017).

  19. 19.

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

  20. 20.

    Gelcich, S. et al. Alternative strategies for scaling up marine coastal biodiversity conservation in Chile. Marit. Stud. 14, 5 (2015).

  21. 21.

    Horigue, V., Aliño, P. M., White, A. T. & Pressey, R. L. Marine protected area networks in the Philippines:trends and challenges for establishment and governance. Ocean Coast. Manag. 64, 15–26 (2012).

  22. 22.

    Gelcich, S. et al. Fishers’ perceptions on the Chilean coastal TURF system after two decades: problems, benefits, and emerging needs. Bull. Mar. Sci. 93, 53–67 (2017).

  23. 23.

    Pietri, D., Christie, P., Pollnac, R. B., Diaz, R. & Sabonsolin, A. Information diffusion in two marine protected area networks in the Central Visayas Region, Philippines. Coast. Manag. 37, 331–348 (2009).

  24. 24.

    Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge Univ. Press, 1990).

  25. 25.

    Cox, M., Arnold, G. & Tomás, S. V. A review of design principles for community-based natural resource management. Ecol. Soc. 15, 38 (2010).

  26. 26.

    Cinner, J. E. et al. Bright spots among the world’s coral reefs. Nature 535, 416 (2016).

  27. 27.

    Price, D. J. Little Science, Big Science … and Beyond (Columbia Univ. Press, 1986).

  28. 28.

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

  29. 29.

    Bernhardt, E. S. et al. Synthesizing U.S. river restoration efforts. Science 5722, 636–637 (2005).

  30. 30.

    Wolfe, R. A. Organizational innovation: review, critique and suggested research directions. J. Manag. Stud. 31, 405–431 (1994).

  31. 31.

    Lahiri, S. N. Resampling Methods for Dependent Data (Springer Science & Business Media, 2013).

  32. 32.

    Burnham, K. P., Anderson, D. R. & Huyvaert, K. P. AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav. Ecol. Sociobiol. 65, 23–35 (2011).

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Acknowledgements

The Centre of Excellence for Environmental Decisions funded the workshop at the International Congress for Conservation Biology 2015 in Montpellier, France. We thank the Fiji LMMA Network for Fiji data, the CTI Atlas for Solomon Islands data and the Philippines Marine Protected Area Support Network for permission to use their MPA Database. We thank T. Blomley for permission to use his data on joint and community-based forest management, and S. Pailler for data on wildlife management areas. M.M. thanks J. Muntifering and B. Morkel for input. S.G. thanks Conicyt FB0002 and FONDECYT 1190109. R.W. thanks the Australian Research Council Centre of Excellence for Coral Reef Studies. M.M., M.B.M. and L.G. thank the Margaret A. Cargill Foundation.

Author information

M.M., M.B., M.B.M. and H.P.P. conceived the idea and led the study design. M.M., R.W., S.G., N.D., H.G., C.L.A., C.R., L.G. and R.N. collected and collated quantitative data. M.M., M.B. and M.H. conducted the analysis. All authors drafted, reviewed and edited the paper.

Correspondence to Morena Mills.

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Supplementary Information

Supplementary Information

Supplementary Figs. 1–6, Table 3 and references.

Supplementary Dataset 1.

Supplementary Tables 1, 2, 4 and 5.

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Mills, M., Bode, M., Mascia, M.B. et al. How conservation initiatives go to scale. Nat Sustain 2, 935–940 (2019) doi:10.1038/s41893-019-0384-1

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