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Targeting Global Protected Area Expansion for Imperiled Biodiversity

Targeting Global Protected Area Expansion for Imperiled Biodiversity Governments have agreed to expand the global protected area network from 13% to 17% of the world’s land surface by 2020 (Aichi target 11) and to prevent the further loss of known threatened species (Aichi target 12). These targets are interdependent, as protected areas can stem biodiversity loss when strategically located and effectively managed. However, the global protected area estate is currently biased toward locations that are cheap to protect and away from important areas for biodiversity. Here we use data on the distribution of protected areas and threatened terrestrial birds, mammals, and amphibians to assess current and possible future coverage of these species under the convention. We discover that 17% of the 4,118 threatened vertebrates are not found in a single protected area and that fully 85% are not adequately covered (i.e., to a level consistent with their likely persistence). Using systematic conservation planning, we show that expanding protected areas to reach 17% coverage by protecting the cheapest land, even if ecoregionally representative, would increase the number of threatened vertebrates covered by only 6%. However, the nonlinear relationship between the cost of acquiring land and species coverage means that fivefold more threatened vertebrates could be adequately covered for only 1.5 times the cost of the cheapest solution, if cost efficiency and threatened vertebrates are both incorporated into protected area decision making. These results are robust to known errors in the vertebrate range maps. The Convention on Biological Diversity targets may stimulate major expansion of the global protected area estate. If this expansion is to secure a future for imperiled species, new protected areas must be sited more strategically than is presently the case. Citation: Venter O, Fuller RA, Segan DB, Carwardine J, Brooks T, et al. (2014) Targeting Global Protected Area Expansion for Imperiled Biodiversity. PLoS Biol 12(6): e1001891. doi:10.1371/journal.pbio.1001891 Academic Editor: Craig Moritz, Australian National University, Australia Received February 20, 2014; Accepted May 15, 2014; Published June 24, 2014 Copyright:  2014 Venter et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was funded by the Australian Research Council through the grant DP110102872 to OV. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared no competing interests exist. Abbreviations: CBD, Convention on Biological Diversity; IUCN, International Union for Conservation of Nature; ESH, Extent of Suitable Habitat; IBAs, important bird areas. * Email: oscar.venter@jcu.edu.au failing to protect the imperiled biodiversity found on more Introduction valuable land. In 2010 the 193 parties to the Convention of Biological Recognizing the failures of past protected area expansion, the Diversity (CBD) adopted a new strategic plan and set of targets to current CBD text directs that protected areas should target places tackle the continuing decline in biodiversity [1,2]. A key element of of ‘‘importance for biodiversity’’ that are ‘‘ecologically represen- this plan is Aichi target 11, which includes a commitment to tative’’ [1]. However, these locations can be expensive to protect. expand the global coverage of terrestrial protected areas from the For instance, the cost of expanding protected areas to cover all current 13% to 17% by 2020 [1]. This could drive the most rapid ‘‘important bird areas’’ (IBAs) has been estimated at US$58 billion expansion of the global protected area network in history [3], but annually (although these sums are still small compared to corresponding biodiversity benefits are far from guaranteed. This government budgets) [5]. Moreover, the majority of terrestrial is because protected areas are often preferentially established in regions have been identified as important for biodiversity by one locations that are remote or have little agricultural value [4], or more global prioritization schemes [6], which provides myriad PLOS Biology | www.plosbiology.org 1 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Protected Areas Author Summary To determine the extent of current protected areas, we Under the Convention on Biological Diversity (CBD), extracted data on International Union for Conservation of Nature governments have agreed to ambitious targets for (IUCN) category I–VI protected areas from the 2012 World expanding the global protected area network that could Database on Protected Areas [3], excluding all proposed protected drive the greatest surge in new protected areas in history. areas and those lacking ‘‘national’’ designation. For terrestrial They have also agreed to arrest the decline of known protected areas with a known areal extent but lacking polygonal threatened species. However, existing protected areas representation, we created a circular buffer of the appropriate area perform poorly for coverage of threatened species, with around its centroid. To prevent overestimation of the areal only 15% of threatened vertebrates being adequately coverage of protected areas caused by overlapping designations, represented. Moreover, we find that if future protected we merged buffered points and polygons into a single layer. Our area expansion continues in a business-as-usual fashion, final protected area layer contained 135,062 protected areas threatened species coverage will increase only marginally. covering a total of 17,026,214 km , or 12.9% of the Earth’s non- This is because low-cost priorities for meeting the CBD Antarctic land surface (Figure 1A). targets have little overlap with priorities for threatened species coverage. Here we propose a method for averting this outcome, by linking threatened species coverage to Distribution of Biodiversity protected area expansion. Our analyses clearly demon- We used distribution maps for birds [8], mammals [10], and strate that considerable increases in protected area amphibians [10]. We focused on these taxa as they are the only coverage of species could be achieved at minimal major terrestrial taxonomic groups that have been comprehen- additional cost. Exploiting this opportunity will require sively assessed for their distribution and extinction risk [10]. We directly linking the CBD targets on protected areas and excluded marine species and areas, noting that there are specific threatened species, thereby formalizing the interdepen- coverage targets for protecting the marine realm. For all three dence of these key commitments. taxonomic groups, we focused on those species that are listed by the IUCN Red List as Critically Endangered, Endangered, or Vulnerable, hereafter referred to as ‘‘threatened,’’ resulting in alternatives for meeting protected area targets in locations that are 4,118 species in total (birds = 1,135, mammals = 1,107, amphib- cheap. Given this, where should new protected areas be located to ians = 1,876; Figure 1B). We focus only on threatened species as deliver on the Aichi biodiversity targets? One option could be these are by definition the most likely species to go extinct, and based on Aichi target 12, which aims to ‘‘prevent the extinction of therefore are most important for slowing biodiversity loss and all known threatened species and improve and sustain their contributing to CBD Aichi target 12. We excluded all portions of conservation status.’’ In situ conservation of viable populations in species ranges where the species was identified as extinct, natural ecosystems has long been recognized as the fundamental introduced, or of uncertain origin. In addition to these data, we requirement for the maintenance of biodiversity [7]. Hence used data on the distribution of ecoregions as defined by the World measuring ‘‘biodiversity importance’’ in terms of protected area Wildlife Fund [12]. coverage of threatened species would help countries to simulta- neously meet these two CBD targets. Protected Area Opportunity Cost Using new data from the World Database on Protected Areas To account for the spatial variation in the cost of protected [3] and distribution maps for 4,118 globally threatened birds [8], area expansion, we used a dataset on agricultural opportunity mammals [9,10], and amphibians [10,11], as well as ecoregions cost [18], converted to 2012 US$ and with no data values filled [12], we first perform a gap analysis to determine the represen- using regularized spline interpolation with tension (Figure 1C). tation of these species in the current global protected area network. The dataset provides the estimated gross agricultural rents for We then use a systematic conservation planning framework [13] to terrestrial areas mapped at approximately the 5 km resolution. build scenarios for cost-efficiently expanding the global protected We use these data as our surrogate for the opportunity costs of area network to contribute to meeting the protected area and establishing new protected areas, as agricultural expansion is threatened species Aichi targets. Recent works have investigated the greatest single cause of habitat loss, as well as the one most strategies for achieving Aichi Target 11 by protecting IBAs [5,14] commonly associated with habitat loss driven by multiple or meeting the Global Strategy for Plant Conservation [15]. Our factors [19,20]. Agricultural opportunity costs also reflect the study is the first, to our knowledge, to use an optimization reduction in food security and tax revenue that national approach to develop scenarios for meeting the Aichi targets in a governments face when implementing protected areas. We cost-efficient manner. Incorporating cost efficiency allows the appliedafixedcostofUS$100 per km to reflect the transaction identification of options for meeting Aichi target 11 that contribute costs of acquiring new protected areas [21], although we optimally to target 12 while minimizing conflict with agricultural recognize there is likely to be considerable spatial variation in production. these costs. We did not attempt to estimate the ongoing management costs of protected areas following establishment, Methods as this metric needs to account for a number of difficult-to- measure social and socioeconomic factors [22], but a recent All spatial overlays were performed at a spatial resolution of analysis estimated that these equate to ,14% of the agricultural 500 m and then aggregated into 30 km630 km pixels to identify opportunity costs of protection [5]. candidate land for protection. By processing data at the finer resolution, we are able to account for protected areas at the subpixel level, thereby minimizing omission of small-sized Gap Analysis protected areas. This resolution of ,M degree (at the Equator) We assessed the occurrence of threatened vertebrates within falls in the midrange between scales of K degree [16] and of F protected areas using a representation target and an adequacy degree [17] typically used in such analyses. target. The representation target was achieved if any portion of PLOS Biology | www.plosbiology.org 2 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Scenarios for Protected Area Expansion To explore future scenarios for the growth of the global protected area network we used the systematic conservation planning software Marxan [24]. Marxan uses a simulated annealing algorithm to select multiple alternative sets of areas that meet prespecified conservation targets (described in the following section) while trying to minimize overall cost. All spatial data on the distribution of conservation features and conservation costs were summarized into a ‘‘planning unit’’ layer consisting of 30 km630 km square pixels comprising the world’s non-Antarctic terrestrial areas. We intersected this planning unit layer with the protected areas and agricultural opportunity layers and the geographic distribution of each of the 4,118 threatened species and ecoregions at a 500 m resolution. This allowed us to determine the agricultural opportunity cost of the unprotected portion of each planning unit and the protected and unprotected extent of each biodiversity feature within each planning unit. To explore the costs and benefits of alternate scenarios for achieving 17% protection of terrestrial areas, we developed four separate spatial scenarios using contrasting conservation targets. We accounted for the existing protected area network’s contribution to the targets in each scenario, and then added additional protected areas to ensure all targets are met. In each scenario, the aim is to minimize the costs of meeting the conservation targets. However, to avoid the global protected area target being met only through increased protection in low-cost countries, which would reduce the total cost of the target, in all scenarios we maintain the constraint that each country must meet its national protected area target. Moreover, it is at the national level that the target is being interpreted and implemented. For each scenario, we used Marxan to perform 10 runs of 1 billion iterations each, each of which represents an alternate near optimal reserve network for meeting the relevant conservation targets at the lowest overall cost. From these 10 runs, we select and report on the results from the lowest cost solution. National targets. In the first scenario, we set the conserva- tion target as each country meeting its protected area target at the lowest agricultural opportunity cost. In this scenario, we set all countries’ terrestrial protected area target to 17%, except for the 73 countries that have indicated in CBD workshops that they proposed alternative targets [25], in which case we used these targets. As countries have tended in the past to meet their targets by favoring high, far, and otherwise agriculturally low-value areas Figure 1. Key data inputs and output map from the systematic [4], we view this as our business-as-usual protected area expansion conservation planning framework. (A) Protected areas mapped scenario. We also determine the conservation benefits of protected using polygons and buffered points for nationally designated protected area target levels above the current Aichi 17% targets by setting areas [3]. (B) The number of native and extant globally threatened terrestrial and freshwater birds [8], mammals [10], and amphibians [10] national levels up to 30% of each country. per grid square. (C) The average annual agricultural opportunity cost of Ecoregional target. In this scenario, we maintain the protecting each 30 km grid square in 2012 $US [17]. (D) The distribution national-level 17% targets from scenario a but add the additional of priorities for establishing new protected areas to meet the national- constraint that countries meet their target in a way that ensures level 17% targets under Aichi target 11 at minimal cost and ignoring that each of the 821 terrestrial ecoregions receive at least 17% ecological representation (red), for covering threatened species (green), and locations selected under both scenarios (yellow). The sizes of the protection. We include this scenario as Target 11 calls for areas circles in the Venn diagrams are proportional to the area required in protected to be ‘‘ecologically representative’’ [1]. each of the three categories. Threatened species target. In this scenario, we maintain doi:10.1371/journal.pbio.1001891.g001 the national-level 17% targets from scenario a but add the additional constraint that all threatened species must be covered to the species’ distribution overlapped with the protected area the level of their adequacy targets [23]. network. To set adequacy targets we followed the method of Threatened species preference. In this scenario, we Rodrigues et al. [23] to scale the target to the species’ overall construct an efficiency frontier between the cost of meeting the geographic range size. Complete (i.e., 100%) coverage by 17% target as in a and attaining threatened species conservation protected areas was required for species with a geographic range targets as in c. The tradeoff curve is established by iteratively 2 2 of ,1,000 km . For wide-ranging species (.250,000 km ), the increasing the value given to meeting species adequacy targets, target was reduced to 10% coverage, and where geographic from no value to a value equal to that given to the 17% target range size was intermediate between these extremes, the target itself. The 17% target is always met at the national level across the was log-linearly interpolated. tradeoff frontier. PLOS Biology | www.plosbiology.org 3 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species of threatened species would increase only marginally (Figure S1C). Commission Errors in Range Maps Moreover, the majority of species that reach their adequacy targets The IUCN [10] and Birdlife International and NatureServe [8] are those with a geographic range size $250,000 km (Figure range maps used in this study comprise polygons showing S1C), as their wide distribution renders them more easily captured distribution of 4,118 globally threatened birds, mammals, and when distributing protected areas equitably across ecoregions. The amphibians. These maps may be subject to commission errors species most likely to be left unprotected are narrowly distributed [26–29], where the species is mapped as present in locations where species, which often are those in greatest need of protection it is in fact not present. As they affect range-based species [31,32]. conservation targets and lead to an overestimation of occurrence These results indicate that protected area expansion targeting in existing or prioritized areas, commission errors could influence either the cheapest land or representation of ecoregions is not an our study’s main conclusions. We performed two analyses to efficient approach for covering threatened species. Alternatively, determine the sensitivity of our primary results to commission we find that locating protected areas to ensure they meet targets errors (Text S1). First we created 100 range maps for each of the for adequate coverage of all 4,118 threatened species would cost 4,118 species of birds, mammals, and amphibians that simulated about $42.5 billion annually (Table 1), which is about 7.5 times commission error rates [25] by deleting 50% of the range of more than the cheapest option for meeting the 17% target. This narrow-ranged species (range,1,000 km ), by deleting 25% of the difference in cost is driven by low concordance between areas that range of wide-ranging species (range.250,000 km ), and by are cheap to protect and those that capture the distributions of linearly extrapolating the deletion rate for species of intermediate threatened species (Figure 1D). Land selected for threatened ranges. Second, we identified the ‘‘Extent of Suitable Habitat’’ species tends to align with tropical forest hotspots (Figure 1B), such (ESH) using high-resolution species distribution models for 1,063 as the tropical Andes and eastern Madagascar, whereas the mammals [30]. The ESH maps were used to identify locations in cheapest land to protect is remote and often in more arid zones the original maps for mammals that are likely to be commission (Figure 1D). This lack of overlap helps explain why the existing errors. We then reran our analyses using (a) the maps with protected area network, which has favored low-cost areas in each simulated commission errors and (b) the ESH maps, to quantify country [4], represents threatened species rather poorly. the effects of the simulated and mapped commission errors on our How can countries reconcile the attraction of low-cost estimated biodiversity value of meeting the 17% protected area target, and the shape of the efficiency frontier between cost and conservation with the benefits of protecting places that contribute to threatened species conservation? By varying the importance threatened vertebrate coverage. placed on meeting targets for adequate coverage of threatened species, we discover a nonlinear tradeoff between the cost of Results establishing additional protected areas and the proportion of We find that 17% of threatened vertebrates are not found in a threatened vertebrates covered by these areas (Figure 3). The single protected area and 85% are not covered to the level of our shape of the curve illustrates that large gains in the number of adequacy targets (Figure S1A). A decade ago, 20% of globally species potentially protected could be achieved for relatively small threatened terrestrial birds, mammals, and amphibians were not increases in cost. For instance, increasing by 5-fold the number of found in a single protected area and 89% were inadequately species protected relative to the low-cost, business-us-usual protected [15]. Our analysis using updated datasets indicates that scenario would increase opportunity costs to only $7.4 billion the global protected area network has made little progress since annually (1.5 times as much; Table 1). then toward securing a future for the world’s threatened We find that our primary results are robust to randomly biodiversity. simulated commission errors in the range maps. Although the We discover that if countries choose to expand their protected number of species meeting range-based coverage targets generally areas in a manner that minimizes agricultural opportunity cost, decreases once commission errors are simulated (Text S1), this meeting their national-level targets for 17% coverage would entail drop averages only 5% across the tradeoff curve (Figure S2). a once-off transaction cost of US$0.9 billion and an annual Moreover, both a visual interpretation and a quantitative measure agricultural opportunity cost of $4.9 billion (Table 1). As this of the shape of the tradeoff curve reveals that the original and option aligns with the previous pattern of protected area commission error updated curves are similarly nonlinear. More- establishment, we view it as a likely business-as-usual scenario over, using high-resolution expert-based habitat suitability models for meeting the terrestrial coverage aspect of Aichi target 11. We for 1,063 threatened mammals, we again find that commission find that this would result in only 852 (21%) threatened vertebrates errors are unlikely to alter our primary findings (Figure S3). reaching targets for adequate coverage (Figure S1B), an increase of only 249 species over existing protection (Table 1) and arguably a Discussion failure to meet Aichi target 12. Moreover, even if highly ambitious areal targets were to drive further growth of the global protected A small minority (15%) of threatened vertebrates are adequately area network beyond 2020, the costs of expansion would rise covered by existing protected areas. However, the adoption of the steeply without providing cost-effective coverage for threatened Aichi targets marks an historic opportunity for achieving species (Figure 2). conservation of the world’s biodiversity. If countries are to meet the protected area Aichi target, at least 5.8 million km of new An alternative is to ensure a representative sample of major vegetation communities is protected, as this would protect a protected areas will need to be created by 2020. Although this is a significant opportunity for biodiversity conservation, we have broader range of habitats and could lead to improved conservation outcomes. Target 11 calls for ecologically representative protected shown that protected area expansion that targets low-cost areas in area coverage. We find that if countries meet their 17% coverage each country and ignores threatened species is unlikely to protect targets in a way that distributes protection across ecoregions such species incidentally. This remains the case even if protected equally, the opportunity cost of establishing the additional areas are further expanded to cover 30% of land areas, or if they protected areas would be 4.5 times higher than the business-as- are located to cover a representative sample of Earth’s terrestrial usual scenario ($24.8 billion annually; Table 1), but that coverage ecoregions. On the other hand, we find that if protected areas are PLOS Biology | www.plosbiology.org 4 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Table 1. Costs and benefits of the current protected area network and for future protection scenarios that (a) meet country-level targets for protected area coverage; (b) meet these targets while also achieving 17% protection of each terrestrial ecoregion; (c) meet the targets from scenario a and protect a scaled fraction of the geographic ranges of threatened terrestrial birds, mammals, and amphibians; and (d) achieve the country-level targets for protected area coverage while also achieving five times the level of biodiversity protection relative to scenario a. (d) 17% Targets (a) 17% Targets (b) 17% Targets (c) Threatened Species Nationally, with Species Outcome Current Nationally Ecoregionally Adequacy Target Preference 2 { { { { Area protected (km and %)* 17,026,214, 12.9% 25,816,498, 18.2% 28,651,943, 20.2% 28,641,412, 20.2% 27,356,736, 19.4% Annual opportunity cost na 4.92+(0.88) 24.84+(1.16) 42.54+(1.16) 7.39+(1.03) (+one-off transaction cost) US$ billions Number (and %) of species 603 (15%) 852 (21%) 867 (21%) 4,118 (100%) 1,848 (45%) potentially covered by protected areas Increase in species covered na 249 (41%) 264 (44%) 3,515 (580%) 1,245 (206%) above current level *We use all non-Antarctic land areas (132,523,065 km ) as our denominator when calculating proportional protection. Protection levels exceed 17% globally because some countries have already established protected area networks that exceed this level (Greenland, for instance, has already protected 41% of its land areas). doi:10.1371/journal.pbio.1001891.t001 directed in a cost-efficient manner to protect threatened IBAs include management costs, which are estimated at ,$7 vertebrates, these species could be protected for an estimated billion annually [5]. Second, IBAs are identified for their agricultural opportunity cost of about $42.5 billion annually. We contribution to global bird conservation, without consideration also find that there is a nonlinear relationship between cost and of the cost of protecting these areas, whereas we used an species protection, indicating that options exist for increasing optimization approach to identify low-cost options for meeting threatened species protection above the business-as-usual level at conservation targets [33,34]. Third, IBAs are identified based on little additional cost. the presence of both threatened and nonthreatened species (e.g., Our estimate of the cost of reaching adequacy targets for all congregatory species), while we focused on threatened species threatened birds, mammals, and amphibians is lower than the $58 alone. billion annually estimated for protecting the world’s IBAs [5], Our analyses are subject to a number of caveats. First, we though each option comprises a similar land area. There are three considered relative cost based on gross agricultural rents, not primary reasons for this. First, the estimated costs of protecting management costs or the opportunity costs for other land uses Figure 3. Efficiency frontier between the cost of establishing additional protected areas to achieve 17% coverage and the number of species covered. The y-axis presents the proportion of Figure 2. The number of globally threatened vertebrates that each species adequacy target that is met within protected areas, reach our adequacy targets (black), and the agricultural summed across all species, and is not directly comparable to that of the opportunity cost of establishing new protected areas (red), other figures, which only count species whose protected area coverage as the proportion of global land areas protected increases meets or exceeds their target. above 17%. doi:10.1371/journal.pbio.1001891.g003 doi:10.1371/journal.pbio.1001891.g002 PLOS Biology | www.plosbiology.org 5 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species [33], nor the practicalities of establishing reserves among these meet national-level 17% targets, and ‘‘c’’ shows the protection competing land uses. Second, overlay of coarse scale maps of from the current network plus new protected areas to meet species distributions onto fine-scale protected area maps generates national-level 17% targets in a way that ensures terrestrial commission errors [26,35], though these are unlikely to qualita- ecoregions are protected to the level of 17%. Numbers in the tively change our results. Still, as commission errors mean that graphs give the number of threatened species that have their species distributions overlap less than these coarse-scale maps adequacy target fully met in each scenario. suggest, our estimate of the area needed to protect all threatened (EPS) species is a minimum [30]. Locations identified here should Figure S2 Efficiency frontier between the cost of establishing therefore be considered as broad indications of where specific additional protected areas to achieve 17% coverage and the areas for protection might be located, and our estimates of cost number of species potentially covered for the original range maps and the area requiring protection will be minima. Third, although (black circles) and the randomly reduced species range maps (red we recognize that our analyses have limited taxonomic breadth, no stars). The y-axis presents the proportion of each species adequacy other taxonomic groups (e.g., plants) have undergone compre- target that is met within protected areas, summed across all hensive assessment of both extinction risk and distribution at a species. The red stars show the average results from 100 iterations sufficiently fine scale for a comparable analysis [10]. Yet good of randomly deleting a portion of each species range; standard indications exist from the literature that protected areas identified deviations for the 100 runs average 60.82% across the tradeoff for broad taxonomic groups cover the majority of species in other, frontier and are therefore too small to graph. nontarget groups [36,37]. Finally, our species-specific targets for (EPS) protection do not account for minimum viable protected areas or connectivity and do not guarantee the long-term survival of all Figure S3 Efficiency frontier between the cost of establishing species. Moreover, many species are threatened by processes other additional protected areas to achieve 17% coverage and the than habitat loss and therefore require additional conservation number of mammal species potentially covered for original range actions both inside and outside protected areas [38]. maps (black circles) and the ESH maps (red stars). The y-axis For the global protected area network to fulfill its potential role presents the proportion of each species adequacy target that is met as the cornerstone of biodiversity conservation [39], and for within protected areas, summed across all species. governments to meet their commitments on protected areas and (EPS) species extinctions, the distribution of threatened species must Text S1 Analyses of sensitivity to range map commission errors. inform future protected area establishment. Preventing the further (DOCX) loss of all threatened species is a lofty goal and will require substantial efforts. But expanding protected areas requires Acknowledgments managing tradeoffs among societal objectives [40], and here we have shown that considerable increases in protected area coverage The data used are derived from public repositories. We thank the UNEP of species could be achieved at modest additional cost. Exploiting World Conservation Monitoring Centre and the IUCN World Commis- the nonlinearity of this tradeoff will require directly linking the sion on Protected Areas (World Database on Protected Areas); the IUCN Aichi targets on protected areas and threatened species (as well as Species Survival Commission and Red List Partnership, including BirdLife other targets, including target 5 on slowing habitat loss), thereby International, NatureServe, and Sapienza University of Rome (Red List of Threatened Species); and the World Wildlife Fund (Ecoregions) and all the formalizing the interdependence of these key commitments. people involved in developing the source data. Supporting Information Author Contributions Figure S1 The total extant geographic range size, in logarithmic The author(s) have made the following declarations about their scale, and the percent of that range in protected areas for 4,118 contributions: Conceived and designed the experiments: OV RAF DBS threatened vertebrates, with the red line detailing the range-based JC TB LJ MV SHMB HPP RJS JEMW. Performed the experiments: OV conservation targets used in the analyses. ‘‘a’’ shows the protection DBS MDM TI DOG JEMW. Analyzed the data: OV DBS JEMW. afforded by the current protected areas, ‘‘b’’ shows the protection Contributed reagents/materials/analysis tools: CR. Wrote the paper: OV from the current network plus new protected areas necessary to RAF DBS JC TB MDM TI LJ DOG HPP CR RJS MV JEMW. References 1. Convention on Biological Diversity (2011) Conference of the Parties Decision 9. Schipper J, Chanson JS, Chiozza F, Cox NA, Hoffmann M, et al. 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Geist HJ, Lambin EF (2002) Proximate causes and underlying driving forces of vertebrate geographic ranges. Biodiversity and Conservation 22: 1033–1047. tropical deforestation. Bioscience 52: 143–150. 32. Ricketts TH, Dinerstein E, Boucher T, Brooks TM, Butchart SHM, et al. (2005) 20. Achard F, Eva HD, Stibig HJ, Mayaux P, Gallego J, et al. (2002) Determination of Pinpointing and preventing imminent extinctions. Proc Natl Acad Sci U S A deforestation rates of the world’s humid tropical forests. Science 297: 999–1002. 102: 18497–18501. 21. Fuller RA, McDonald-Madden E, Wilson KA, Carwardine J, Grantham HS, et 33. Balmford A, Gaston KJ, Rodrigues ASL, James A (2000) Integrating costs of al. (2010) Replacing underperforming protected areas achieves better conser- conservation into international priority setting. Conservation Biology 14: 597– vation outcomes. Nature 466: 365–367. 22. McCreless E, Visconti P, Carwardine J, Wilcox C, Smith RJ (2013) Cheap and 34. Bode M, Wilson KA, Brooks TM, Turner WR, Mittermeier RA, et al. (2008) nasty? The potential perils of using management costs to identify global Cost-effective global conservation spending is robust to taxonomic group. Proc conservation priorities. PLoS ONE 8: e80893. Natl Acad Sci U S A 105: 6498–6501. 23. Rodrigues ASL, Akcakaya HR, Andelman SJ, Bakarr MI, Boitani L, et al. (2004) 35. Gaston KJ, Fuller RA (2008) Commonness, population depletion and Global gap analysis: priority regions for expanding the global protected-area conservation biology. Trends Ecol Evol 23: 14–19. network. Bioscience 54: 1092–1100. 36. Moore JL, Balmford A, Brooks T, Burgess ND, Hansen LA, et al. (2003) 24. Ball IR, Possingham HP (2000) Marxan (v 1.8.6): marine reserve design using Performance of sub-Saharan vertebrates as indicator groups for identifying spatially explicit anealing. User manual. Brisbane, Australia: University of priority areas for conservation. Conservation Biology 17: 207–218. Queensland. 37. Su JC, Debinski DM, Jakubauskas ME, Kindscher K (2004) Beyond species 25. Convention on Biological Diversity (2012) Protected areas: progress in the richness: community similarity as a measure of cross-taxon congruence for implementation of the programme of work and achievement of Aichi coarse-filter conservation. Conservation Biology 18: 167–173. biodiversity target 11 (UNEP/CBD/COP/11/26). 38. Ferraro PJ, Pattanayak SK (2006) Money for nothing? A call for empirical 26. Jetz W, Sekercioglu CH, Watson JEM (2008) Ecological correlates and evaluation of biodiversity conservation investments. PLoS Biol 4: 482–488. conservation implications of overestimating species geographic ranges. Conser- 39. Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405: vation Biology 22: 110–119. 243–253. 27. Hurlbert AH, Jetz W (2007) Species richness, hotspots, and the scale dependence 40. Polasky S, Nelson E, Camm J, Csuti B, Fackler P, et al. (2008) Where to put of range maps in ecology and conservation. Proc Natl Acad Sci 104: 13384– things? Spatial land management to sustain biodiversity and economic returns. 13389. Biological Conservation 141: 1505–1524. PLOS Biology | www.plosbiology.org 7 June 2014 | Volume 12 | Issue 6 | e1001891 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png PLoS Biology Public Library of Science (PLoS) Journal

Targeting Global Protected Area Expansion for Imperiled Biodiversity

PLoS Biology , Volume 12 (6) – Jun 24, 2014

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Copyright: © 2014 Venter et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was funded by the Australian Research Council through the grant DP110102872 to OV. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared no competing interests exist. Abbreviations: CBD, Convention on Biological Diversity; IUCN, International Union for Conservation of Nature; ESH, Extent of Suitable Habitat; IBAs, important bird areas
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1544-9173
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1545-7885
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10.1371/journal.pbio.1001891
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Abstract

Governments have agreed to expand the global protected area network from 13% to 17% of the world’s land surface by 2020 (Aichi target 11) and to prevent the further loss of known threatened species (Aichi target 12). These targets are interdependent, as protected areas can stem biodiversity loss when strategically located and effectively managed. However, the global protected area estate is currently biased toward locations that are cheap to protect and away from important areas for biodiversity. Here we use data on the distribution of protected areas and threatened terrestrial birds, mammals, and amphibians to assess current and possible future coverage of these species under the convention. We discover that 17% of the 4,118 threatened vertebrates are not found in a single protected area and that fully 85% are not adequately covered (i.e., to a level consistent with their likely persistence). Using systematic conservation planning, we show that expanding protected areas to reach 17% coverage by protecting the cheapest land, even if ecoregionally representative, would increase the number of threatened vertebrates covered by only 6%. However, the nonlinear relationship between the cost of acquiring land and species coverage means that fivefold more threatened vertebrates could be adequately covered for only 1.5 times the cost of the cheapest solution, if cost efficiency and threatened vertebrates are both incorporated into protected area decision making. These results are robust to known errors in the vertebrate range maps. The Convention on Biological Diversity targets may stimulate major expansion of the global protected area estate. If this expansion is to secure a future for imperiled species, new protected areas must be sited more strategically than is presently the case. Citation: Venter O, Fuller RA, Segan DB, Carwardine J, Brooks T, et al. (2014) Targeting Global Protected Area Expansion for Imperiled Biodiversity. PLoS Biol 12(6): e1001891. doi:10.1371/journal.pbio.1001891 Academic Editor: Craig Moritz, Australian National University, Australia Received February 20, 2014; Accepted May 15, 2014; Published June 24, 2014 Copyright:  2014 Venter et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This research was funded by the Australian Research Council through the grant DP110102872 to OV. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared no competing interests exist. Abbreviations: CBD, Convention on Biological Diversity; IUCN, International Union for Conservation of Nature; ESH, Extent of Suitable Habitat; IBAs, important bird areas. * Email: oscar.venter@jcu.edu.au failing to protect the imperiled biodiversity found on more Introduction valuable land. In 2010 the 193 parties to the Convention of Biological Recognizing the failures of past protected area expansion, the Diversity (CBD) adopted a new strategic plan and set of targets to current CBD text directs that protected areas should target places tackle the continuing decline in biodiversity [1,2]. A key element of of ‘‘importance for biodiversity’’ that are ‘‘ecologically represen- this plan is Aichi target 11, which includes a commitment to tative’’ [1]. However, these locations can be expensive to protect. expand the global coverage of terrestrial protected areas from the For instance, the cost of expanding protected areas to cover all current 13% to 17% by 2020 [1]. This could drive the most rapid ‘‘important bird areas’’ (IBAs) has been estimated at US$58 billion expansion of the global protected area network in history [3], but annually (although these sums are still small compared to corresponding biodiversity benefits are far from guaranteed. This government budgets) [5]. Moreover, the majority of terrestrial is because protected areas are often preferentially established in regions have been identified as important for biodiversity by one locations that are remote or have little agricultural value [4], or more global prioritization schemes [6], which provides myriad PLOS Biology | www.plosbiology.org 1 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Protected Areas Author Summary To determine the extent of current protected areas, we Under the Convention on Biological Diversity (CBD), extracted data on International Union for Conservation of Nature governments have agreed to ambitious targets for (IUCN) category I–VI protected areas from the 2012 World expanding the global protected area network that could Database on Protected Areas [3], excluding all proposed protected drive the greatest surge in new protected areas in history. areas and those lacking ‘‘national’’ designation. For terrestrial They have also agreed to arrest the decline of known protected areas with a known areal extent but lacking polygonal threatened species. However, existing protected areas representation, we created a circular buffer of the appropriate area perform poorly for coverage of threatened species, with around its centroid. To prevent overestimation of the areal only 15% of threatened vertebrates being adequately coverage of protected areas caused by overlapping designations, represented. Moreover, we find that if future protected we merged buffered points and polygons into a single layer. Our area expansion continues in a business-as-usual fashion, final protected area layer contained 135,062 protected areas threatened species coverage will increase only marginally. covering a total of 17,026,214 km , or 12.9% of the Earth’s non- This is because low-cost priorities for meeting the CBD Antarctic land surface (Figure 1A). targets have little overlap with priorities for threatened species coverage. Here we propose a method for averting this outcome, by linking threatened species coverage to Distribution of Biodiversity protected area expansion. Our analyses clearly demon- We used distribution maps for birds [8], mammals [10], and strate that considerable increases in protected area amphibians [10]. We focused on these taxa as they are the only coverage of species could be achieved at minimal major terrestrial taxonomic groups that have been comprehen- additional cost. Exploiting this opportunity will require sively assessed for their distribution and extinction risk [10]. We directly linking the CBD targets on protected areas and excluded marine species and areas, noting that there are specific threatened species, thereby formalizing the interdepen- coverage targets for protecting the marine realm. For all three dence of these key commitments. taxonomic groups, we focused on those species that are listed by the IUCN Red List as Critically Endangered, Endangered, or Vulnerable, hereafter referred to as ‘‘threatened,’’ resulting in alternatives for meeting protected area targets in locations that are 4,118 species in total (birds = 1,135, mammals = 1,107, amphib- cheap. Given this, where should new protected areas be located to ians = 1,876; Figure 1B). We focus only on threatened species as deliver on the Aichi biodiversity targets? One option could be these are by definition the most likely species to go extinct, and based on Aichi target 12, which aims to ‘‘prevent the extinction of therefore are most important for slowing biodiversity loss and all known threatened species and improve and sustain their contributing to CBD Aichi target 12. We excluded all portions of conservation status.’’ In situ conservation of viable populations in species ranges where the species was identified as extinct, natural ecosystems has long been recognized as the fundamental introduced, or of uncertain origin. In addition to these data, we requirement for the maintenance of biodiversity [7]. Hence used data on the distribution of ecoregions as defined by the World measuring ‘‘biodiversity importance’’ in terms of protected area Wildlife Fund [12]. coverage of threatened species would help countries to simulta- neously meet these two CBD targets. Protected Area Opportunity Cost Using new data from the World Database on Protected Areas To account for the spatial variation in the cost of protected [3] and distribution maps for 4,118 globally threatened birds [8], area expansion, we used a dataset on agricultural opportunity mammals [9,10], and amphibians [10,11], as well as ecoregions cost [18], converted to 2012 US$ and with no data values filled [12], we first perform a gap analysis to determine the represen- using regularized spline interpolation with tension (Figure 1C). tation of these species in the current global protected area network. The dataset provides the estimated gross agricultural rents for We then use a systematic conservation planning framework [13] to terrestrial areas mapped at approximately the 5 km resolution. build scenarios for cost-efficiently expanding the global protected We use these data as our surrogate for the opportunity costs of area network to contribute to meeting the protected area and establishing new protected areas, as agricultural expansion is threatened species Aichi targets. Recent works have investigated the greatest single cause of habitat loss, as well as the one most strategies for achieving Aichi Target 11 by protecting IBAs [5,14] commonly associated with habitat loss driven by multiple or meeting the Global Strategy for Plant Conservation [15]. Our factors [19,20]. Agricultural opportunity costs also reflect the study is the first, to our knowledge, to use an optimization reduction in food security and tax revenue that national approach to develop scenarios for meeting the Aichi targets in a governments face when implementing protected areas. We cost-efficient manner. Incorporating cost efficiency allows the appliedafixedcostofUS$100 per km to reflect the transaction identification of options for meeting Aichi target 11 that contribute costs of acquiring new protected areas [21], although we optimally to target 12 while minimizing conflict with agricultural recognize there is likely to be considerable spatial variation in production. these costs. We did not attempt to estimate the ongoing management costs of protected areas following establishment, Methods as this metric needs to account for a number of difficult-to- measure social and socioeconomic factors [22], but a recent All spatial overlays were performed at a spatial resolution of analysis estimated that these equate to ,14% of the agricultural 500 m and then aggregated into 30 km630 km pixels to identify opportunity costs of protection [5]. candidate land for protection. By processing data at the finer resolution, we are able to account for protected areas at the subpixel level, thereby minimizing omission of small-sized Gap Analysis protected areas. This resolution of ,M degree (at the Equator) We assessed the occurrence of threatened vertebrates within falls in the midrange between scales of K degree [16] and of F protected areas using a representation target and an adequacy degree [17] typically used in such analyses. target. The representation target was achieved if any portion of PLOS Biology | www.plosbiology.org 2 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Scenarios for Protected Area Expansion To explore future scenarios for the growth of the global protected area network we used the systematic conservation planning software Marxan [24]. Marxan uses a simulated annealing algorithm to select multiple alternative sets of areas that meet prespecified conservation targets (described in the following section) while trying to minimize overall cost. All spatial data on the distribution of conservation features and conservation costs were summarized into a ‘‘planning unit’’ layer consisting of 30 km630 km square pixels comprising the world’s non-Antarctic terrestrial areas. We intersected this planning unit layer with the protected areas and agricultural opportunity layers and the geographic distribution of each of the 4,118 threatened species and ecoregions at a 500 m resolution. This allowed us to determine the agricultural opportunity cost of the unprotected portion of each planning unit and the protected and unprotected extent of each biodiversity feature within each planning unit. To explore the costs and benefits of alternate scenarios for achieving 17% protection of terrestrial areas, we developed four separate spatial scenarios using contrasting conservation targets. We accounted for the existing protected area network’s contribution to the targets in each scenario, and then added additional protected areas to ensure all targets are met. In each scenario, the aim is to minimize the costs of meeting the conservation targets. However, to avoid the global protected area target being met only through increased protection in low-cost countries, which would reduce the total cost of the target, in all scenarios we maintain the constraint that each country must meet its national protected area target. Moreover, it is at the national level that the target is being interpreted and implemented. For each scenario, we used Marxan to perform 10 runs of 1 billion iterations each, each of which represents an alternate near optimal reserve network for meeting the relevant conservation targets at the lowest overall cost. From these 10 runs, we select and report on the results from the lowest cost solution. National targets. In the first scenario, we set the conserva- tion target as each country meeting its protected area target at the lowest agricultural opportunity cost. In this scenario, we set all countries’ terrestrial protected area target to 17%, except for the 73 countries that have indicated in CBD workshops that they proposed alternative targets [25], in which case we used these targets. As countries have tended in the past to meet their targets by favoring high, far, and otherwise agriculturally low-value areas Figure 1. Key data inputs and output map from the systematic [4], we view this as our business-as-usual protected area expansion conservation planning framework. (A) Protected areas mapped scenario. We also determine the conservation benefits of protected using polygons and buffered points for nationally designated protected area target levels above the current Aichi 17% targets by setting areas [3]. (B) The number of native and extant globally threatened terrestrial and freshwater birds [8], mammals [10], and amphibians [10] national levels up to 30% of each country. per grid square. (C) The average annual agricultural opportunity cost of Ecoregional target. In this scenario, we maintain the protecting each 30 km grid square in 2012 $US [17]. (D) The distribution national-level 17% targets from scenario a but add the additional of priorities for establishing new protected areas to meet the national- constraint that countries meet their target in a way that ensures level 17% targets under Aichi target 11 at minimal cost and ignoring that each of the 821 terrestrial ecoregions receive at least 17% ecological representation (red), for covering threatened species (green), and locations selected under both scenarios (yellow). The sizes of the protection. We include this scenario as Target 11 calls for areas circles in the Venn diagrams are proportional to the area required in protected to be ‘‘ecologically representative’’ [1]. each of the three categories. Threatened species target. In this scenario, we maintain doi:10.1371/journal.pbio.1001891.g001 the national-level 17% targets from scenario a but add the additional constraint that all threatened species must be covered to the species’ distribution overlapped with the protected area the level of their adequacy targets [23]. network. To set adequacy targets we followed the method of Threatened species preference. In this scenario, we Rodrigues et al. [23] to scale the target to the species’ overall construct an efficiency frontier between the cost of meeting the geographic range size. Complete (i.e., 100%) coverage by 17% target as in a and attaining threatened species conservation protected areas was required for species with a geographic range targets as in c. The tradeoff curve is established by iteratively 2 2 of ,1,000 km . For wide-ranging species (.250,000 km ), the increasing the value given to meeting species adequacy targets, target was reduced to 10% coverage, and where geographic from no value to a value equal to that given to the 17% target range size was intermediate between these extremes, the target itself. The 17% target is always met at the national level across the was log-linearly interpolated. tradeoff frontier. PLOS Biology | www.plosbiology.org 3 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species of threatened species would increase only marginally (Figure S1C). Commission Errors in Range Maps Moreover, the majority of species that reach their adequacy targets The IUCN [10] and Birdlife International and NatureServe [8] are those with a geographic range size $250,000 km (Figure range maps used in this study comprise polygons showing S1C), as their wide distribution renders them more easily captured distribution of 4,118 globally threatened birds, mammals, and when distributing protected areas equitably across ecoregions. The amphibians. These maps may be subject to commission errors species most likely to be left unprotected are narrowly distributed [26–29], where the species is mapped as present in locations where species, which often are those in greatest need of protection it is in fact not present. As they affect range-based species [31,32]. conservation targets and lead to an overestimation of occurrence These results indicate that protected area expansion targeting in existing or prioritized areas, commission errors could influence either the cheapest land or representation of ecoregions is not an our study’s main conclusions. We performed two analyses to efficient approach for covering threatened species. Alternatively, determine the sensitivity of our primary results to commission we find that locating protected areas to ensure they meet targets errors (Text S1). First we created 100 range maps for each of the for adequate coverage of all 4,118 threatened species would cost 4,118 species of birds, mammals, and amphibians that simulated about $42.5 billion annually (Table 1), which is about 7.5 times commission error rates [25] by deleting 50% of the range of more than the cheapest option for meeting the 17% target. This narrow-ranged species (range,1,000 km ), by deleting 25% of the difference in cost is driven by low concordance between areas that range of wide-ranging species (range.250,000 km ), and by are cheap to protect and those that capture the distributions of linearly extrapolating the deletion rate for species of intermediate threatened species (Figure 1D). Land selected for threatened ranges. Second, we identified the ‘‘Extent of Suitable Habitat’’ species tends to align with tropical forest hotspots (Figure 1B), such (ESH) using high-resolution species distribution models for 1,063 as the tropical Andes and eastern Madagascar, whereas the mammals [30]. The ESH maps were used to identify locations in cheapest land to protect is remote and often in more arid zones the original maps for mammals that are likely to be commission (Figure 1D). This lack of overlap helps explain why the existing errors. We then reran our analyses using (a) the maps with protected area network, which has favored low-cost areas in each simulated commission errors and (b) the ESH maps, to quantify country [4], represents threatened species rather poorly. the effects of the simulated and mapped commission errors on our How can countries reconcile the attraction of low-cost estimated biodiversity value of meeting the 17% protected area target, and the shape of the efficiency frontier between cost and conservation with the benefits of protecting places that contribute to threatened species conservation? By varying the importance threatened vertebrate coverage. placed on meeting targets for adequate coverage of threatened species, we discover a nonlinear tradeoff between the cost of Results establishing additional protected areas and the proportion of We find that 17% of threatened vertebrates are not found in a threatened vertebrates covered by these areas (Figure 3). The single protected area and 85% are not covered to the level of our shape of the curve illustrates that large gains in the number of adequacy targets (Figure S1A). A decade ago, 20% of globally species potentially protected could be achieved for relatively small threatened terrestrial birds, mammals, and amphibians were not increases in cost. For instance, increasing by 5-fold the number of found in a single protected area and 89% were inadequately species protected relative to the low-cost, business-us-usual protected [15]. Our analysis using updated datasets indicates that scenario would increase opportunity costs to only $7.4 billion the global protected area network has made little progress since annually (1.5 times as much; Table 1). then toward securing a future for the world’s threatened We find that our primary results are robust to randomly biodiversity. simulated commission errors in the range maps. Although the We discover that if countries choose to expand their protected number of species meeting range-based coverage targets generally areas in a manner that minimizes agricultural opportunity cost, decreases once commission errors are simulated (Text S1), this meeting their national-level targets for 17% coverage would entail drop averages only 5% across the tradeoff curve (Figure S2). a once-off transaction cost of US$0.9 billion and an annual Moreover, both a visual interpretation and a quantitative measure agricultural opportunity cost of $4.9 billion (Table 1). As this of the shape of the tradeoff curve reveals that the original and option aligns with the previous pattern of protected area commission error updated curves are similarly nonlinear. More- establishment, we view it as a likely business-as-usual scenario over, using high-resolution expert-based habitat suitability models for meeting the terrestrial coverage aspect of Aichi target 11. We for 1,063 threatened mammals, we again find that commission find that this would result in only 852 (21%) threatened vertebrates errors are unlikely to alter our primary findings (Figure S3). reaching targets for adequate coverage (Figure S1B), an increase of only 249 species over existing protection (Table 1) and arguably a Discussion failure to meet Aichi target 12. Moreover, even if highly ambitious areal targets were to drive further growth of the global protected A small minority (15%) of threatened vertebrates are adequately area network beyond 2020, the costs of expansion would rise covered by existing protected areas. However, the adoption of the steeply without providing cost-effective coverage for threatened Aichi targets marks an historic opportunity for achieving species (Figure 2). conservation of the world’s biodiversity. If countries are to meet the protected area Aichi target, at least 5.8 million km of new An alternative is to ensure a representative sample of major vegetation communities is protected, as this would protect a protected areas will need to be created by 2020. Although this is a significant opportunity for biodiversity conservation, we have broader range of habitats and could lead to improved conservation outcomes. Target 11 calls for ecologically representative protected shown that protected area expansion that targets low-cost areas in area coverage. We find that if countries meet their 17% coverage each country and ignores threatened species is unlikely to protect targets in a way that distributes protection across ecoregions such species incidentally. This remains the case even if protected equally, the opportunity cost of establishing the additional areas are further expanded to cover 30% of land areas, or if they protected areas would be 4.5 times higher than the business-as- are located to cover a representative sample of Earth’s terrestrial usual scenario ($24.8 billion annually; Table 1), but that coverage ecoregions. On the other hand, we find that if protected areas are PLOS Biology | www.plosbiology.org 4 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species Table 1. Costs and benefits of the current protected area network and for future protection scenarios that (a) meet country-level targets for protected area coverage; (b) meet these targets while also achieving 17% protection of each terrestrial ecoregion; (c) meet the targets from scenario a and protect a scaled fraction of the geographic ranges of threatened terrestrial birds, mammals, and amphibians; and (d) achieve the country-level targets for protected area coverage while also achieving five times the level of biodiversity protection relative to scenario a. (d) 17% Targets (a) 17% Targets (b) 17% Targets (c) Threatened Species Nationally, with Species Outcome Current Nationally Ecoregionally Adequacy Target Preference 2 { { { { Area protected (km and %)* 17,026,214, 12.9% 25,816,498, 18.2% 28,651,943, 20.2% 28,641,412, 20.2% 27,356,736, 19.4% Annual opportunity cost na 4.92+(0.88) 24.84+(1.16) 42.54+(1.16) 7.39+(1.03) (+one-off transaction cost) US$ billions Number (and %) of species 603 (15%) 852 (21%) 867 (21%) 4,118 (100%) 1,848 (45%) potentially covered by protected areas Increase in species covered na 249 (41%) 264 (44%) 3,515 (580%) 1,245 (206%) above current level *We use all non-Antarctic land areas (132,523,065 km ) as our denominator when calculating proportional protection. Protection levels exceed 17% globally because some countries have already established protected area networks that exceed this level (Greenland, for instance, has already protected 41% of its land areas). doi:10.1371/journal.pbio.1001891.t001 directed in a cost-efficient manner to protect threatened IBAs include management costs, which are estimated at ,$7 vertebrates, these species could be protected for an estimated billion annually [5]. Second, IBAs are identified for their agricultural opportunity cost of about $42.5 billion annually. We contribution to global bird conservation, without consideration also find that there is a nonlinear relationship between cost and of the cost of protecting these areas, whereas we used an species protection, indicating that options exist for increasing optimization approach to identify low-cost options for meeting threatened species protection above the business-as-usual level at conservation targets [33,34]. Third, IBAs are identified based on little additional cost. the presence of both threatened and nonthreatened species (e.g., Our estimate of the cost of reaching adequacy targets for all congregatory species), while we focused on threatened species threatened birds, mammals, and amphibians is lower than the $58 alone. billion annually estimated for protecting the world’s IBAs [5], Our analyses are subject to a number of caveats. First, we though each option comprises a similar land area. There are three considered relative cost based on gross agricultural rents, not primary reasons for this. First, the estimated costs of protecting management costs or the opportunity costs for other land uses Figure 3. Efficiency frontier between the cost of establishing additional protected areas to achieve 17% coverage and the number of species covered. The y-axis presents the proportion of Figure 2. The number of globally threatened vertebrates that each species adequacy target that is met within protected areas, reach our adequacy targets (black), and the agricultural summed across all species, and is not directly comparable to that of the opportunity cost of establishing new protected areas (red), other figures, which only count species whose protected area coverage as the proportion of global land areas protected increases meets or exceeds their target. above 17%. doi:10.1371/journal.pbio.1001891.g003 doi:10.1371/journal.pbio.1001891.g002 PLOS Biology | www.plosbiology.org 5 June 2014 | Volume 12 | Issue 6 | e1001891 Targeting Protected Areas for Threatened Species [33], nor the practicalities of establishing reserves among these meet national-level 17% targets, and ‘‘c’’ shows the protection competing land uses. Second, overlay of coarse scale maps of from the current network plus new protected areas to meet species distributions onto fine-scale protected area maps generates national-level 17% targets in a way that ensures terrestrial commission errors [26,35], though these are unlikely to qualita- ecoregions are protected to the level of 17%. Numbers in the tively change our results. Still, as commission errors mean that graphs give the number of threatened species that have their species distributions overlap less than these coarse-scale maps adequacy target fully met in each scenario. suggest, our estimate of the area needed to protect all threatened (EPS) species is a minimum [30]. Locations identified here should Figure S2 Efficiency frontier between the cost of establishing therefore be considered as broad indications of where specific additional protected areas to achieve 17% coverage and the areas for protection might be located, and our estimates of cost number of species potentially covered for the original range maps and the area requiring protection will be minima. Third, although (black circles) and the randomly reduced species range maps (red we recognize that our analyses have limited taxonomic breadth, no stars). The y-axis presents the proportion of each species adequacy other taxonomic groups (e.g., plants) have undergone compre- target that is met within protected areas, summed across all hensive assessment of both extinction risk and distribution at a species. The red stars show the average results from 100 iterations sufficiently fine scale for a comparable analysis [10]. Yet good of randomly deleting a portion of each species range; standard indications exist from the literature that protected areas identified deviations for the 100 runs average 60.82% across the tradeoff for broad taxonomic groups cover the majority of species in other, frontier and are therefore too small to graph. nontarget groups [36,37]. Finally, our species-specific targets for (EPS) protection do not account for minimum viable protected areas or connectivity and do not guarantee the long-term survival of all Figure S3 Efficiency frontier between the cost of establishing species. Moreover, many species are threatened by processes other additional protected areas to achieve 17% coverage and the than habitat loss and therefore require additional conservation number of mammal species potentially covered for original range actions both inside and outside protected areas [38]. maps (black circles) and the ESH maps (red stars). The y-axis For the global protected area network to fulfill its potential role presents the proportion of each species adequacy target that is met as the cornerstone of biodiversity conservation [39], and for within protected areas, summed across all species. governments to meet their commitments on protected areas and (EPS) species extinctions, the distribution of threatened species must Text S1 Analyses of sensitivity to range map commission errors. inform future protected area establishment. Preventing the further (DOCX) loss of all threatened species is a lofty goal and will require substantial efforts. But expanding protected areas requires Acknowledgments managing tradeoffs among societal objectives [40], and here we have shown that considerable increases in protected area coverage The data used are derived from public repositories. We thank the UNEP of species could be achieved at modest additional cost. Exploiting World Conservation Monitoring Centre and the IUCN World Commis- the nonlinearity of this tradeoff will require directly linking the sion on Protected Areas (World Database on Protected Areas); the IUCN Aichi targets on protected areas and threatened species (as well as Species Survival Commission and Red List Partnership, including BirdLife other targets, including target 5 on slowing habitat loss), thereby International, NatureServe, and Sapienza University of Rome (Red List of Threatened Species); and the World Wildlife Fund (Ecoregions) and all the formalizing the interdependence of these key commitments. people involved in developing the source data. 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