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A forest loss report card for the world’s protected areas

Abstract

Protected areas are a key tool in the conservation of global biodiversity and carbon stores. We conducted a global test of the degree to which more than 18,000 terrestrial protected areas (totalling 5,293,217 km2) reduce deforestation in relation to unprotected areas. We also derived indices that quantify how well countries’ forests are protected, both in terms of forested area protected and effectiveness of protected areas at reducing deforestation, in relation to vertebrate species richness, aboveground forest carbon biomass and background deforestation rates. Overall, protected areas did not eliminate deforestation, but reduced deforestation rates by 41%. Protected area deforestation rates were lowest in small reserves with low background deforestation rates. Critically, we found that after adjusting for effectiveness, only 6.5%—rather than 15.7%—of the world’s forests are protected, well below the Aichi Convention on Biological Diversity’s 2020 Target of 17%. We propose that global targets for protected areas should include quantitative goals for effectiveness in addition to spatial extent.

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Fig. 1: Locations of the 18,171 PAs in our main analysis and global deforestation rates.
Fig. 2: Deforestation rate distributions.
Fig. 3: Forest loss in and around PAs.
Fig. 4: Effects of control area deforestation rate and PA area on PA deforestation rates.
Fig. 5: Forest biodiversity threat index.
Fig. 6: Annual deforestation rate and total aboveground forest carbon versus adjusted forested area protected.

Data availability

All data used are publicly available. Sources for the data are given in the Methods section.

Code availability

Analysis code is available at https://github.com/wolfch2/PA_matching.

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Authors and Affiliations

Authors

Contributions

C.W. and M.G.B. conceived the project. C.W. conducted the data analysis and wrote the first draft with input from T.L., W.J.R., D.A.Z.-C. and M.G.B. All authors edited the manuscript.

Corresponding author

Correspondence to Christopher Wolf.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Ecology & Evolution thanks Jonas Geldmann and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Extended Data Fig. 1 The distribution of IUCN categories for the 18,171 PAs in our primary spatial analysis.

Protected area categories are: Ia – ‘Strict Nature Reserve,’ Ib – ‘Wilderness Area,’ II – ‘National Park,’ III – ‘Natural Monument or Feature,’ IV – ‘Habitat/Species Management Area,’ V – ‘Protected Landscape/ Seascape,’ VI – ‘Protected area with sustainable use of natural resources.’ The protected areas were split into ‘Strict’ (categories I-IV), ‘Nonstrict’ (categories V-VI), and ‘Unknown’ (any other category).

Extended Data Fig. 2 Net annual forest loss rate within protected areas and in matched control areas.

In contrast to the forest loss results, net loss is not a true percentage since loss and gain are binary while cover is continuous (see SI Methods for details). Results are grouped by geographic region and PA category (IUCN category I-IV: ‘Strict,’ V-VI: ‘Nonstrict’). Points correspond to median (across PAs) percentage forest loss. Error bar end points are the 1st and 3rd quartiles for this variable. Forest loss within protected areas has generally been less than in nearby unprotected areas.

Extended Data Fig. 3 Change in the annual forest loss rate associated with the creation of PAs.

The change variable is the deforestation rate after minus before creation of a PA. Results are grouped by geographic region and PA category (IUCN category I-IV: ‘Strict,’ V-VI: ‘Nonstrict’). Points correspond to means, and error bars show standard errors.

Extended Data Fig. 4 Predictors of deforestation rates within protected areas.

Each row shows a different predictor variable, and the columns show coefficient estimates, standard errors, and FDR-adjusted p-values. Because a spatially varying coefficient model was used, estimates, etc. can all vary geographically. Travel time to nearest densely-populated area was also included as a predictor, but it was found to be non-significant, with no evidence of spatial variability. Only coefficients with associated p-value less than 0.05 are mapped.

Extended Data Fig. 5 Threatened and non-threatened forest vertebrate species richness.

We considered these spatial variables as predictors of deforestation within protected areas to explore relationships between PA effectiveness (with respect to limiting deforestation) and biodiversity.

Extended Data Fig. 6 Sensitivity analysis exploring the effect of stricter matching criteria.

Medians (center points) and 1st and 3rd quartiles (ranges) are shown. The first row is for our primary matching dataset (see Fig. 3) based on five classes per continuous matching covariate while the second row shows results based on 10 classes per covariate (only 9 were used for travel time – see Supplementary Methods). Overall, the use of stricter matching criteria did not appear to considerably alter our results.

Extended Data Fig. 7 Predictors of deforestation rates within protected areas for dataset using stricter matching criteria.

Travel time to nearest densely-populated area (p=0.20) was not spatially varying and is not shown in order to parallel our main results (Extended Data Fig. 4). Additionally, population density, PA age, and strict protection were all found to be constant spatially for this restricted dataset. Only coefficients with associated p-value less than 0.05 are mapped.

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Wolf, C., Levi, T., Ripple, W.J. et al. A forest loss report card for the world’s protected areas. Nat Ecol Evol 5, 520–529 (2021). https://doi.org/10.1038/s41559-021-01389-0

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