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Co-benefits of marine protected areas for nature and people

Nature Sustainability volume 6, pages 1210–1218 (2023)Cite this article

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Abstract

Conservation interventions are central strategies for achieving sustainable development goals given the inextricable dependence of humanity on nature. Current debate centres on whether interventions such as marine protected areas (MPAs) promote co-benefits or trade-offs among multiple goals such as poverty alleviation, food security and protection of marine resources. Resolving this question is hindered by a lack of quantitative impact evaluations of concurrent ecological and social co-benefits of MPAs. Here we use a statistical matching approach to examine whether MPAs are associated with co-benefits or trade-offs between reef fish abundances and measures of human well-being, including income, diet and food security in the Mesoamerican region. We find that highly protected areas (HPAs) with stringent fishing restrictions tend to support high mean abundances and stable or increasing trends in fish abundances compared with unprotected sites and ‘general use zones’ of MPAs. At the same time, indicators of income and food security were elevated in communities near MPAs, especially HPAs, compared with communities far from MPAs. Finally, proximity to MPAs and to reefs with high fish abundance were both positively associated with well-being across space. Together, these results provide quantitative evidence of co-benefits for fish and people associated with MPAs, highlighting the potential value of MPAs in achieving multiple sustainable development goals.

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Fig. 1: Conceptual diagram illustrating potential co-benefits for fisheries and local communities from MPAs.
Fig. 2: Mean abundance and trends of reef fish in open-access sites and marine protected areas (MPAs), including general use zones (GUZs) and highly protected areas (HPAs).
Fig. 3: The probability of stunting is lower near marine protected areas (MPAs), and the mean wealth index is greater near highly protected areas (HPAs) than in areas far from MPAs.
Fig. 4: Fish biomass is positively associated with the wealth index of nearby communities.

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Data availability

All data used in this study were obtained from open sources listed in Supplementary Tables 16 and 17. Ecological data are available on www.agrra.org, with some years also displayed in healthyreefs.org. Human well-being indicators are freely available from www.dhsprogram.com/data.

Code availability

The R and JAGS code used for analyses are available upon reasonable request to the corresponding author.

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Acknowledgements

We thank the many people who collected, processed, collated and made available the data underlying this study, particularly the 74 partner organizations within the Healthy Reefs Initiative (www.healthyreefs.org/partners). Primary funding for reef surveys was provided by Summit Foundation and Oak Foundation. S.W.J.C. and M.M. were supported by Summit Foundation. S.C. thanks the generous support received from Betty and Gordon Moore. A.J.N. was supported by a Smithsonian SI-CI Postdoctoral Fellowship. This is Smithsonian Marine Station contribution number 1191.

Author information

Authors and Affiliations

  1. Smithsonian Environmental Research Center, Edgewater, MD, USA

    A. Justin Nowakowski & Steven W. J. Canty

  2. Working Land and Seascapes, Smithsonian Institution, Washington, DC, USA

    A. Justin Nowakowski, Steven W. J. Canty, Jessica L. Deichmann, Thomas S. Akre & Melanie McField

  3. Conservation International, Arlington, VA, USA

    A. Justin Nowakowski & Sebastien Costedoat

  4. Smithsonian Marine Station, Fort Pierce, FL, USA

    Steven W. J. Canty & Melanie McField

  5. Global Science, WWF, Washington, DC, USA

    Nathan J. Bennett

  6. People and the Ocean Specialist Group, Commission on Environmental, Economic and Social Policy, International Union for the Conservation of Nature, Gland, Switzerland

    Nathan J. Bennett

  7. School of Public Policy and Global Affairs, University of British Columbia, Vancouver, British Columbia, Canada

    Nathan J. Bennett

  8. Barefoot Ocean, Houston, TX, USA

    Courtney E. Cox

  9. Oceans, WWF, Washington, DC, USA

    Abel Valdivia

  10. Smithsonian’s National Zoo and Conservation Biology Institute, Front Royal, VA, USA

    Jessica L. Deichmann & Thomas S. Akre

  11. Liz Claiborne and Art Ortenberg Foundation, New York, NY, USA

    Jessica L. Deichmann

  12. Department of Agricultural Economics, Sociology, and Education, Pennsylvania State University, University Park, PA, USA

    Sara E. Bonilla-Anariba

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Contributions

A.J.N., S.W.J.C. and N.B. designed the study. S.W.J.C., C.C., A.V. and M.M. contributed to field data collection on reefs. M.M. oversaw ecological data acquisition, compilation., and funding. A.J.N. collated data, conducted analyses., and led manuscript preparation. A.J.N., S.W.J.C., N.B., C.C., A.V., J.L.D., T.S.A., S.E.B.-A., S.C. and M.M. all contributed to substantive revisions and edits.

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Correspondence to A. Justin Nowakowski.

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Nature Sustainability thanks Elliott Hazen, M. Aaron MacNeil and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Maps of monitored reef sites and Demographic and Health Survey (DHS) clusters in coastal areas.

(A) To examine the effects of marine protected areas (MPAs) on fish abundance, we analysed monitoring data from reef sites (n = 87) along coastal waters of Mexico, Belize, Guatemala and Honduras in open access waters (yellow) and in general use (GUZs; green) and highly protected areas (HPAs; purple) of MPAs. Unmatched sites are shown in grey. (B) To determine whether MPAs affect indicators of human well-being, we analysed survey responses for up to 2,117 individuals from 222 matched DHS clusters along coasts of Guatemala and Honduras that were far from MPAs (>10 km; yellow) or near GUZs (≤10 km; green) or HPAs (purple). (C) To evaluate potential tradeoffs or synergies between human well-being and fish assemblages across space, we analysed fish biomass and indicators of food security and income from nearest neighbour reef sites (triangles) and DHS clusters (squares) along the Atlantic coast of Guatemala and Honduras. Map data are from sources in refs. 28,29,56.

Extended Data Fig. 2 Mean abundance and trends in open access sites and general use (GUZs) and highly protected areas (HPAs) of marine protected areas (MPAs) (n = 4,336 transects sampled at 87 sites).

To assess the effects of fishing restrictions associated with MPAs on assemblages, we used a quasi-experimental approach wherein we first matched survey sites based on site characteristics and then quantified effects of fishing restrictions (GUZs versus HPAs) while controlling for remaining variation in matching variables in Bayesian hierarchical models. Plots show estimated effects of fishing restrictions on means and trends in counts for three commercially important fish families. Error bars represent 95% Bayesian credible intervals, and letters indicate difference among groups that have statistical support – that is, 95% BCIs for contrasts exclude zero.

Extended Data Fig. 3 Interactive effects of fishing restrictions and age of marine protected areas (MPAs) on mean total fish biomass (n = 2,596 transects sampled at 61 sites).

Mean predictions (lines) and 95% credible bands (shaded areas) are from Bayesian hierarchical models fit with interaction terms for MPA age and fishing restrictions while controlling for leftover variation in matching variables. MPA age is centreed and scaled (z-score).

Extended Data Fig. 4 Interactive effects of fishing restrictions and age of marine protected areas (MPAs) on trends in total fish biomass (n = 3,102 transects sampled at 61 sites).

Mean predictions (lines) and 95% credible bands (shaded areas) are from Bayesian hierarchical models fit with interaction terms among MPA age, fishing restrictions, and year while controlling for leftover variation in matching variables. Year is centred and scaled (z-score).

Extended Data Fig. 5 Effects of size of marine protected areas (MPAs) on trends in total fish biomass (n = 3,102 transects sampled at 61 sites).

Mean predictions (lines) and 95% credible bands (shaded areas) are from Bayesian hierarchical models fit with interaction terms for MPA area and year while controlling for leftover variation in matching variables. Year is centred and scaled (z-score).

Extended Data Fig. 6 The probability of stunting (n = 1,880 individuals) is lower near marine protected areas (MPAs) than areas far from MPAs.

Plot shows model coefficients that represent the effects of MPA proximity on probability of stunting, here while controlling for wealth index. To assess the effects of MPA proximity on dimensions of human wellbeing, we used a quasi-experimental approach wherein we first matched survey clusters near and far from MPAs based on site characteristics and then quantified effects of MPA proximity while controlling for remaining variation in matching variables using Bayesian hierarchical models. Error bars represent 80% (thick) and 95% (thin) Bayesian credible intervals (BCI), and asterisks indicate mean effects with statistical support – 95% BCIs exclude zero.

Extended Data Fig. 7 Effects of proximity to general use zones (GUZ) and highly protected areas (HPA) on well-being indicators are qualitatively similar under different choices of threshold distances for defining clusters near and far from these zones of marine protected areas (MPAs).

Model coefficients are from Bayesian hierarchical models fit as in Fig. 3, while defining threshold distance as 5, 10, 15, or 20 km. Coefficients represent mean differences relative to the reference category of clusters far from MPAs. Error bars represent 95% Bayesian credible intervals. Sample sizes varied across datasets when applying different distance thresholds. For the stunting outcome, n for 5 km = 1251, 10 km = 1919, 15 km = 2611, and 20 km = 2843. For the fish diet outcome, n for 5 km = 796, 10 km = 1305, 15 km = 1801, and 20 km = 2012. For the wealth index outcome, n for 5 km = 1382, 10 km = 2117, 15 km = 2866, and 20 km = 3121.

Extended Data Fig. 8 Association between fish biomass and probability of fish consumption (A) and stunting (B) in nearby communities.

Colours indicate communities near general use zones (green) and highly protected areas (purple) of marine protected areas (MPAs) and those far from MPAs (yellow). Heavy grey line represents the mean posterior effect of fish biomass on human well-being indicators, and light grey lines are 100 random samples from the posterior distribution. For the fish diet outcome, n = 56 pairs of reef sites and survey clusters. For the stunting outcome, n = 58 pairs of reef sites and survey clusters.

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Nowakowski, A.J., Canty, S.W.J., Bennett, N.J. et al. Co-benefits of marine protected areas for nature and people. Nat Sustain 6, 1210–1218 (2023). https://doi.org/10.1038/s41893-023-01150-4

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