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Protected areas have a mixed impact on waterbirds, but management helps

Nature volume 605, pages 103–107 (2022)Cite this article

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Abstract

International policy is focused on increasing the proportion of the Earth’s surface that is protected for nature1,2. Although studies show that protected areas prevent habitat loss3,4,5,6, there is a lack of evidence for their effect on species’ populations: existing studies are at local scale or use simple designs that lack appropriate controls7,8,9,10,11,12,13. Here we explore how 1,506 protected areas have affected the trajectories of 27,055 waterbird populations across the globe using a robust before–after control–intervention study design, which compares protected and unprotected populations in the years before and after protection. We show that the simpler study designs typically used to assess protected area effectiveness (before–after or control–intervention) incorrectly estimate effects for 37–50% of populations—for instance misclassifying positively impacted populations as negatively impacted, and vice versa. Using our robust study design, we find that protected areas have a mixed impact on waterbirds, with a strong signal that areas managed for waterbirds or their habitat are more likely to benefit populations, and a weak signal that larger areas are more beneficial than smaller ones. Calls to conserve 30% of the Earth’s surface by 2030 are gathering pace14, but we show that protection alone does not guarantee good biodiversity outcomes. As countries gather to agree the new Global Biodiversity Framework, targets must focus on creating and supporting well-managed protected and conserved areas that measurably benefit populations.

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Fig. 1: Map of study sites.
Fig. 2: Changes in estimates of protected area impact under different study designs.
Fig. 3: Estimates of protected area impact under a BACI study design.
Fig. 4: Predictors of protected area impact.

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Data availability

The waterbird count data used in this study are collated and managed by Wetlands International and the National Audubon Society, and are available on request (http://iwc.wetlands.org/index.php/ and http://netapp.audubon.org/cbcobservation/, respectively). We requested all data from both providers for the years 1900–2018, for all waterbird families (see Supplementary Information 2), and for sites in all available countries (though data from Russia was excluded as permissions were not given). All the data that pertain to explanatory variables are freely available, as specified in Extended Data Tables 2, 3.

Code availability

The code used to produce all analysis and figures are archived on Zenodo at https://doi.org/10.5281/zenodo.5794511. Code are also available on GitHub at https://github.com/hannahwauchope/PAImpact; this is the recommended mode of access as it will contain any updates or clarifications.

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Acknowledgements

We thank the coordinators, thousands of volunteer counters, and funders of the International Waterbird Census. This data collection effort is funded by the Ministry of the Environment of Japan, Environment Canada, AEWA Secretariat, EU LIFE+ NGO Operational Grant, MAVA Foundation, Swiss Federal Office for Environment and Nature, French Ministry of Environment and Sustainable Development, UK Department of Food and Rural Affairs, Norwegian Nature Directorate, Dutch Ministry of Economics, Agriculture and Innovation, DOB Ecology and Wetlands International members. CBC Data is provided by National Audubon Society and through the generous efforts of Bird Studies Canada and countless volunteers across the western hemisphere. H.S.W. was funded by a Cambridge–Australia Poynton Scholarship, Cambridge Department of Zoology J. S. Gardiner Studentship and Cambridge Philosophical Society Grant. H.S.W. and B.I.S. are funded by the Royal Commission for the Exhibition of 1851. W.J.S. was funded by Arcadia, The David and Claudia Harding Foundation and MAVA. J.P.G.J. was supported by a visiting fellowship to Fitzwilliam College Cambridge. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). Finally, the authors would like to acknowledge the use of the University of Exeter High-Performance Computing (HPC) facility in carrying out this work.

Author information

Author notes

  1. Taej Mundkur

    Present address: Wetlands International, Ede, The Netherlands

Authors and Affiliations

  1. Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, UK

    Hannah S. Wauchope, Jonas Geldmann, Benno I. Simmons & William J. Sutherland

  2. Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall Campus, Penryn, UK

    Hannah S. Wauchope & Benno I. Simmons

  3. School of Natural Sciences, College of Engineering and Environmental Science, Bangor University, Bangor, UK

    Julia P. G. Jones

  4. Center for Macroecology, Evolution and Climate, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark

    Jonas Geldmann & Richard A. Fuller

  5. School of Biological Sciences, University of Queensland, Brisbane, Queensland, Australia

    Tatsuya Amano

  6. Centre for Biodiversity and Conservation Science, University of Queensland, Brisbane, Queensland, Australia

    Tatsuya Amano

  7. Wetlands International LAC Argentina Office, Buenos Aires, Argentina

    Daniel E. Blanco

  8. Cornell Lab of Ornithology, Ithaca, NY, US

    Alison Johnston

  9. Centre for Research into Ecological and Environmental Modelling, University of St Andrews, St Andrews, UK

    Alison Johnston

  10. Wetlands International, Ede, The Netherlands

    Tom Langendoen & Szabolcs Nagy

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Contributions

H.S.W., J.P.G.J., J.G., B.I.S., T.A., R.A.F., A.J. and W.J.S. conceived the study. D.E.B., T.L., T.M. and S.N. provided waterbird count data, which H.S.W. and T.A. collated. H.S.W. performed analysis, produced figures and wrote the text with advice from all authors, especially J.P.G.J., J.G., B.I.S., T.A., A.J. and W.J.S. All authors contributed to the review of the manuscript before submission for publication and approved the final version.

Corresponding authors

Correspondence to Hannah S. Wauchope or Taej Mundkur.

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Extended data figures and tables

Extended Data Fig. 1 Changes in estimates of protected area impact under different study designs, for all analyses.

Proportion of Before-After (BA) or Control-Intervention (CI) populations that changed outcome when analysed under a BACI framework, by each analysis (n = 21; 20 full parameter, plus one focal analysis). Shown for all populations (a), then the proportion of positive (b), no (c) or negative impact populations (d) that changed in outcome. Each point is an analysis, with boxplots showing distribution (box bounded by 25th and 75th percentiles, centre shows 50th percentile, whiskers extend to 1.5*IQR above 75th percentile, for maxima, or below 25th percentile, for minima). Large points show focal analysis estimates.

Extended Data Fig. 2 Estimates of protected area impact under a BACI study design, for all analyses.

Percentage of populations that have been positively, negatively or not impacted by protected areas, by each analysis (n = 21; 20 full parameter analyses, plus one focal analysis). Each point is an analysis, with boxplots showing distribution (box bounded by 25th and 75th percentiles, centre shows 50th percentile, whiskers extend to 1.5*IQR above 75th percentile, for maxima, or below 25th percentile, for minima). Large points show estimates from focal analysis. Panels show estimates under BACI (a), Before-After (b) or Control-Intervention (c) frameworks.

Extended Data Fig. 3 Estimates of protected area impact under a BA study design.

Proportion of populations (n = 6263) showing various responses to protection, per site (a; n = 860) and species (b; n = 66), when response to protection is calculated in a BA framework. Each species/site is one bar, with the proportion of their populations in each category shown on the y axis. Bar width is scaled to the number of populations of that species/site in the dataset, log scaled in the case of species, with a wider bar meaning the species/site has more populations. Each colour represents a different way a population can respond to protection, and an example of each is shown at the bottom. This figure is based on our focal analysis; Extended Data Fig. 2b shows the proportion of populations within each broad outcome category across all full parameter analyses.

Extended Data Fig. 4 Estimates of protected area impact under a CI study design.

Proportion of populations (n = 3783) showing various responses to protection, per site (a; n = 698) and per species (b; n = 32), when response to protection is calculated in a CI framework. Each species/site is one bar, with the proportion of their populations in each category shown on the y axis. Bar width is scaled to the number of populations of that species/site in the dataset, log scaled in the case of species, with a wider bar meaning the species/site has more populations. Each colour represents a different way a population can respond to protection, and an example of each is shown at the bottom. This figure is based on our focal analysis; Extended Data Fig. 2c shows the proportion of populations within each broad outcome category across all full parameter analyses.

Extended Data Fig. 5 Predictors of protected area impact, with odds ratios and confidence intervals.

Odds ratios for covariates predicting protected area (PA) effectiveness under a BACI framework. Estimated using cumulative link mixed models, points show model estimates, tails show 95% confidence intervals, and significance is indicated by bold colours (P < 0.05). Dashed line given at an odds ratio of one (ratios above one indicate a positive relationship, and below one a negative relationship). Y axis shows all analyses (20 full parameter analyses, plus one focal analysis, with the focal analysis given in the first row). Colours show covariate grouping. Orders are measured relative to Anseriformes, and Anthromes relative to Urban. Note that we expect continuous variables (PA Area, Body Size, Governance) to have smaller coefficients as they express odds ratios per unit increment.

Extended Data Fig. 6 Schematic demonstrating matching procedure.

Example of the matching procedure for one species, using a toy dataset of 6 protected sites (A to F) and 3 unprotected sites (X, Y and Z), with three dummy example covariates, climate (cloud), land use (wheat) and human population (person). See methods, ‘Matching’ for a more detailed step by step walk through of this process.

Extended Data Table 1 Parameter estimates and sample sizes across analyses
Full size table
Extended Data Table 2 Covariates used to perform site matching
Full size table
Extended Data Table 3 Covariates used to assess what factors affect protected area impact
Full size table

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Wauchope, H.S., Jones, J.P.G., Geldmann, J. et al. Protected areas have a mixed impact on waterbirds, but management helps. Nature 605, 103–107 (2022). https://doi.org/10.1038/s41586-022-04617-0

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