Targeting Global Protected Area Expansion for Imperiled Biodiversity Oscar Venter Richard A. Fuller Daniel B. Segan Josie Carwardine Thomas Brooks Stuart H. M. Butchart Moreno Di Marco Takuya Iwamura Liana Joseph Damien O'Grady Hugh P. Possingham Carlo Rondinini Robert J. Smith Michelle Venter James E. M. Watson

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 Targeting Global Protected Area Expansion for Imperiled Biodiversity 2014 PLoS Biology 10.1371/journal.pbio.1001891 venter2014-targeting-global-protected-area-expansion-biodiversity venter2014-targeting-global-protected-area-expansion-biodiversity.txt, the project's staged copy 7d59a036b42fbce20fe270128112b9db8af9ac04 cc-by conservation-science

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 204 spans located by searching the stored text for the quote's exact words, allowing any whitespace between them where global protected-area expansion should occur to meet area and threatened-species targets cost-efficiently how can countries expand terrestrial protected areas while balancing agricultural opportunity cost, ecological representation, and coverage of threatened vertebrates the first optimization-based global scenarios jointly targeting Aichi protected-area coverage and threatened-species adequacy at minimum agricultural opportunity cost method low spatial concordance and a nonlinear cost tradeoff between cheap protected-area expansion and threatened-species coverage computational-modelcomputational-model Preference for remote or low-value land leaves imperiled biodiversity on valuable land unprotected.residual protected-area placement Optimization locates added protected areas that meet targets while minimizing agricultural conflict.systematic conservation planning Processing at 500 metres retains subpixel protected areas before aggregation to planning units.fine-resolution overlay Buffered nonpolygon records are merged with polygons to avoid double-counting overlapping designations.protected-area layer correction Gross agricultural rents represent the foregone production cost of new protected areas.opportunity-cost proxy Coverage requirements decrease log-linearly as species range size increases.range-scaled adequacy Marxan searches alternative planning-unit sets that meet targets at low cost.simulated annealing Every country must meet its own target, preventing global savings through concentration in low-cost countries.national target constraint Increasing the value assigned to species adequacy traces cost against biodiversity coverage.efficiency-frontier weighting Random range deletion and suitable-habitat maps test sensitivity of results to false mapped presence.commission-error simulation Low overlap between cheap land and threatened-species ranges makes comprehensive species targeting more expensive.spatial mismatch Modest added cost can capture a disproportionately large increment in threatened-species coverage.nonlinear tradeoff exploitation Only birds, mammals, and amphibians had sufficiently comprehensive distribution and extinction-risk assessments. Agricultural rent is a surrogate rather than a complete measure of protected-area opportunity cost. The fixed transaction cost ignores likely spatial variation. Ongoing protected-area management costs were not estimated. Coarse species-range maps can contain commission errors that overestimate occurrence. The sensitivity simulation deletes fixed fractions of estimated ranges rather than observing true occurrence. Cost estimates exclude management cost, other land-use opportunity costs, and practical reserve-establishment constraints. Coarse species ranges over fine protected-area maps make the required area and cost estimates minima. Priority locations are broad indications, not specific reserve boundaries. Taxonomic breadth is limited because other groups lack comparable global assessments. Species targets do not account for minimum viable protected areas or connectivity. Meeting habitat-coverage targets does not guarantee long-term survival. Species threatened by processes other than habitat loss require additional actions inside and outside protected areas. protected areasprotected areas Aichi target 11Aichi target 11 agricultural valueagricultural value imperiled biodiversityimperiled biodiversity biodiversity importancebiodiversity importance Aichi target 12Aichi target 12 distribution of threatened speciesdistribution of threatened species future establishment of protected areasfuture establishment of protected areas species conservationspecies conservation gap analysisgap analysis systematic conservation planning frameworksystematic conservation planning framework World Database on Protected AreasWorld Database on Protected Areas protected area networkprotected area network spatial resolution of 500 mspatial resolution of 500 m 30 km×30 km pixels30 km×30 km pixels category I–VI protected areascategory I–VI protected areas protected area layerprotected area layer Critically EndangeredCritically Endangered EndangeredEndangered VulnerableVulnerable threatenedthreatened agricultural opportunity costagricultural opportunity cost gross agricultural rentsgross agricultural rents habitat losshabitat loss agricultural expansionagricultural expansion representation targetrepresentation target adequacy targetadequacy target geographic range sizegeographic range size MarxanMarxan simulated annealing algorithmsimulated annealing algorithm planning unitplanning unit conservation featuresconservation features conservation costsconservation costs national protected area targetnational protected area target business-as-usual protected area expansion scenariobusiness-as-usual protected area expansion scenario ecologically representativeecologically representative terrestrial ecoregionsterrestrial ecoregions threatened speciesthreatened species efficiency frontierefficiency frontier tradeoff curvetradeoff curve commission errorscommission errors overestimation of occurrenceoverestimation of occurrence simulated commission errorssimulated commission errors Extent of Suitable HabitatExtent of Suitable Habitat global protected area networkglobal protected area network agricultural opportunity cost of $4.9 billionagricultural opportunity cost of $4.9 billion threatened vertebratesthreatened vertebrates wide-ranging specieswide-ranging species narrowly distributed speciesnarrowly distributed species cheapest landcheapest land land selected for threatened speciesland selected for threatened species low concordancelow concordance difference in costdifference in cost nonlinear tradeoffnonlinear tradeoff large gains in the number of species potentially protectedlarge gains in the number of species potentially protected relatively small increases in costrelatively small increases in cost range mapsrange maps high-resolution expert-based habitat suitability modelshigh-resolution expert-based habitat suitability models cost-efficient mannercost-efficient manner minimum viable protected areasminimum viable protected areas connectivityconnectivity additional conservation actionsadditional conservation actions cornerstone of biodiversity conservationcornerstone of biodiversity conservation societal objectivessocietal objectives interdependence of these key commitmentsinterdependence of these key commitments distribution of threatened species → future establishment of protected areasThreatened-species distributions should inform new protected-area locations. protected areas → species conservationArea expansion can contribute to species conservation only when species distributions guide siting. Aichi target 11 → Aichi target 12Threatened-species coverage can help countries meet both international targets simultaneously. Critically Endangered, Endangered, or Vulnerable → threatenedThe three IUCN Red List statuses are collectively referred to as threatened. agricultural opportunity cost → gross agricultural rentsGross agricultural rents serve as a surrogate for the opportunity cost of protection. geographic range size → adequacy targetRange size determines the fraction of a species distribution that must be protected. national protected area target → global cost minimizationNational constraints prevent all added protection from being concentrated in cheap countries. terrestrial ecoregions → ecologically representativeEqual ecoregion coverage implements the policy requirement for ecological representation. commission errors → primary conclusionsCommission errors could influence the main conclusions but sensitivity analyses indicate little qualitative change. cheapest land → threatened speciesCheap protected-area expansion represents threatened species poorly because cheap land and species ranges rarely overlap. nonlinear tradeoff → cost-efficient species protectionThe frontier exposes options for large species gains at modest additional cost. large gains in the number of species potentially protected → relatively small increases in costLarge gains in species coverage can be obtained for relatively small cost increases. commission errors → primary resultsBoth simulated deletion and suitable-habitat models leave the main results robust. priority locations → specific protected areasMapped priorities are broad indications rather than final reserve boundaries. species-specific targets → long-term survivalCoverage targets do not guarantee long-term species survival. protected areas → additional conservation actionsNon-habitat threats require measures inside and outside protected areas. protected areas target → threatened species targetThe commitments should be formally linked to exploit the cost-coverage tradeoff. coverage - representation sense: any protected overlap with a species distribution coverage - adequacy sense: a range-size-scaled fraction of distribution protected cost - agricultural-opportunity sense: forgone gross agricultural rent threatened - IUCN sense: Critically Endangered, Endangered, or Vulnerable efficiency - frontier sense: species-target attainment gained per added protection cost business as usual - residual-siting sense: national area targets met on lowest-cost land commission error - range-map sense: predicted presence where a species is absent priority location - broad-indication sense: regional guidance rather than a reserve boundary extends → global protected-area gap analysesnote: The study adds an optimization framework and joint cost/species scenarios. contrasts-with → low-cost area-only protected-area expansionnote: Species-targeted locations are compared with cheap, often arid and remote locations. supports → joint implementation of Aichi targets 11 and 12note: Linking targets exploits the nonlinear cost-species tradeoff. qualifies → range-map-based priority locationsnote: The locations are broad indications and estimated area and cost are minima. recommends → threatened-species-informed protected-area establishmentnote: The conclusion states that species distributions must inform expansion. supports → cost-efficient threatened-species targetingnote: The nonlinear frontier permits large biodiversity gains at relatively small added cost. agricultural expansion —causes→ habitat lossthe relation itself is separately evidenced · strength of the relation: 0.95 · note: Strong flat causal statement. · the relation stated: Agricultural expansion is stated to be the greatest single cause of habitat loss.agricultural expansionhabitat loss commission errors —causes→ overestimation of occurrencethe relation itself is separately evidenced · strength of the relation: 0.95 · note: Strong flat causal statement. · the relation stated: False mapped presence leads to overestimated occurrence in protected and priority areas.commission errorsoverestimation of occurrence low concordance —causes→ difference in costthe relation itself is separately evidenced · strength of the relation: 0.95 · note: Strong flat causal statement. · the relation stated: The cost difference is explicitly driven by spatial discordance.low concordancedifference in cost cheapest land —contrasted-with→ land selected for threatened speciesthe relation itself is separately evidenced · strength of the relation: 0.95 · note: Explicit whereas contrast. · the relation stated: The cheapest remote and arid land is contrasted with tropical forest hotspots selected for threatened species.cheapest landland selected for threatened species wide-ranging species —contrasted-with→ narrowly distributed speciesthe relation itself is separately evidenced · strength of the relation: 0.95 · note: Explicit cross-group contrast. · the relation stated: Wide-ranging species readily meet ecoregional targets whereas narrow species are left unprotected. Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span writes 'species ... with a geographic range size ≥250,000 km 2' and 'their wide distribution', not 'wide-ranging species'.wide-ranging speciesnarrowly distributed species Seventeen percent of threatened vertebrates occur in no protected area and eighty-five percent fall short of adequacy targets. Updated data show little global progress relative to the corresponding assessment a decade earlier. Business-as-usual national expansion would cost US$0.9 billion once and US$4.9 billion annually. That cheapest expansion would bring only 852 threatened vertebrates to adequate coverage, 249 more than current protection. Expanding area targets beyond seventeen percent would sharply raise costs without cost-effective threatened-species coverage. Equal ecoregional representation costs 4.5 times the business-as-usual scenario while only marginally improving threatened-species coverage. Narrowly distributed species remain the most likely to be unprotected under ecoregional representation. Meeting adequacy targets for all 4,118 threatened vertebrates would cost about US$42.5 billion annually, 7.5 times the cheapest area-only option. Low concordance between cheap land and threatened-species distributions drives the cost difference. The tradeoff between protected-area cost and threatened-vertebrate coverage is nonlinear. A fivefold gain in species protected over business as usual would raise annual opportunity cost only to US$7.4 billion. Simulated commission errors reduce species meeting targets by only five percent on average and do not change the nonlinear frontier. Only fifteen percent of threatened vertebrates are adequately covered by the existing network. At least 5.8 million square kilometres of new protected areas were required for the Aichi area target. Targeting low-cost areas, even at thirty-percent land coverage or with ecoregional representation, does not incidentally protect threatened species well. Cost-efficient targeting of threatened vertebrates can substantially improve species coverage at modest additional cost. species listed as Critically Endangered, Endangered, or Vulnerable on the IUCN Red Listthreatened a target achieved when any part of a species distribution overlaps the protected-area networkrepresentation target range-scaled protected-area coverage, from full coverage for narrow ranges to ten percent for very wide rangesadequacy target estimated gross agricultural rent used as the cost surrogate for new protectionagricultural opportunity cost a thirty-by-thirty-kilometre square pixel used by the optimizationplanning unit country-level coverage targets met at the lowest agricultural opportunity costbusiness-as-usual protected area expansion scenario mapped presences at locations where a species is actually absentcommission errors the tradeoff curve between the cost of seventeen-percent coverage and threatened-species target attainmentefficiency frontier 193 parties — parties adopting the Convention on Biological Diversity strategic plan 13% to 17% by 2020 — planned increase in global terrestrial protected-area coverage 4,118 globally threatened — birds, mammals, and amphibians mapped in the analysis 500 m — spatial resolution used for overlays 30 km×30 km pixels — aggregation and planning-unit resolution 135,062 protected areas — features in the final protected-area layer 17,026,214 km² — total area of the final protected-area layer 12.9% — share of non-Antarctic land in the final layer 1,135 — threatened bird species 1,107 — threatened mammal species 1,876 — threatened amphibian species US$100 per km² — fixed transaction cost assigned to new protected areas ∼14% — estimated protected-area management cost relative to agricultural opportunity cost <1,000 km² — range threshold receiving complete protected-area coverage target 100% — adequacy coverage target for narrow-ranged species >250,000 km² — wide-ranging species threshold 10% coverage — adequacy target for wide-ranging species 10 runs of 1 billion iterations each — Marxan search effort per scenario 821 terrestrial ecoregions — ecoregions constrained to receive target protection 17% — minimum protection assigned to each terrestrial ecoregion 100 range maps — commission-error simulations for each threatened species 1,063 mammals — taxa with high-resolution suitable-habitat sensitivity maps 17% — threatened vertebrates absent from all protected areas 85% — threatened vertebrates below adequacy targets US$0.9 billion — one-time transaction cost of business-as-usual expansion $4.9 billion — annual agricultural opportunity cost of business-as-usual expansion 852 (21%) — threatened vertebrates adequately covered in business as usual 249 species — increment adequately covered over the existing network 4.5 times higher — ecoregional scenario cost multiplier $24.8 billion annually — ecoregional scenario opportunity cost $42.5 billion annually — annual cost of all-species adequacy 7.5 times — all-species scenario multiplier over the cheapest option $7.4 billion annually — cost of a fivefold species-coverage increase 1.5 times as much — fivefold-improvement cost relative to business as usual 5% — average target-attainment drop under simulated commission errors 15% — threatened vertebrates adequately covered by existing areas 5.8 million km² — new protected area required to meet the Aichi target protected area coverageprotected area coverage distribution of threatened speciesdistribution of threatened species agricultural opportunity costagricultural opportunity cost geographic range sizegeographic range size conservation targetsconservation targets conservation costsconservation costs national protected area targetnational protected area target species adequacy targetsspecies adequacy targets commission error ratescommission error rates management costsmanagement costs connectivityconnectivity

Targeting Global Protected Area Expansion for Imperiled Biodiversity

Abstract

Meeting international targets for expanding protected areas could simultaneously contribute to species conservation, but only if the distribution of threatened species informs the future establishment of protected areas.

Introduction

In 2010 the 193 parties to the Convention of Biological Diversity (CBD) adopted a new strategic plan and set of targets to tackle the continuing decline in biodiversity [1] , [2] . A key element of this plan is Aichi target 11, which includes a commitment to expand the global coverage of terrestrial protected areas from the current 13% to 17% by 2020 [1] . This could drive the most rapid expansion of the global protected area network in history [3] , but corresponding biodiversity benefits are far from guaranteed. This is because protected areas are often preferentially established in locations that are remote or have little agricultural value [4] , failing to protect the imperiled biodiversity found on more valuable land.

Recognizing the failures of past protected area expansion, the current CBD text directs that protected areas should target places of “importance for biodiversity” that are “ecologically representative” [1] . However, these locations can be expensive to protect. For instance, the cost of expanding protected areas to cover all “important bird areas” (IBAs) has been estimated at US$58 billion annually (although these sums are still small compared to government budgets) [5] . Moreover, the majority of terrestrial regions have been identified as important for biodiversity by one or more global prioritization schemes [6] , which provides myriad alternatives for meeting protected area targets in locations that are cheap. Given this, where should new protected areas be located to deliver on the Aichi biodiversity targets? One option could be based on Aichi target 12, which aims to “prevent the extinction of all known threatened species and improve and sustain their conservation status.” In situ conservation of viable populations in natural ecosystems has long been recognized as the fundamental requirement for the maintenance of biodiversity [7] . Hence measuring “biodiversity importance” in terms of protected area coverage of threatened species would help countries to simultaneously meet these two CBD targets.

Using new data from the World Database on Protected Areas [3] and distribution maps for 4,118 globally threatened birds [8] , mammals [9] , [10] , and amphibians [10] , [11] , as well as ecoregions [12] , we first perform a gap analysis to determine the representation of these species in the current global protected area network. We then use a systematic conservation planning framework [13] to build scenarios for cost-efficiently expanding the global protected area network to contribute to meeting the protected area and threatened species Aichi targets. Recent works have investigated strategies for achieving Aichi Target 11 by protecting IBAs [5] , [14] or meeting the Global Strategy for Plant Conservation [15] . Our study is the first, to our knowledge, to use an optimization approach to develop scenarios for meeting the Aichi targets in a cost-efficient manner. Incorporating cost efficiency allows the identification of options for meeting Aichi target 11 that contribute optimally to target 12 while minimizing conflict with agricultural production.

Methods

All spatial overlays were performed at a spatial resolution of 500 m and then aggregated into 30 km×30 km pixels to identify 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 protected areas. This resolution of ∼⅓ degree (at the Equator) falls in the midrange between scales of ½ degree [16] and of ⅛ degree [17] typically used in such analyses.

Protected Areas

To determine the extent of current protected areas, we extracted data on International Union for Conservation of Nature (IUCN) category I–VI protected areas from the 2012 World Database on Protected Areas [3] , excluding all proposed protected areas and those lacking “national” designation. For terrestrial protected areas with a known areal extent but lacking polygonal representation, we created a circular buffer of the appropriate area around its centroid. To prevent overestimation of the areal coverage of protected areas caused by overlapping designations, we merged buffered points and polygons into a single layer. Our final protected area layer contained 135,062 protected areas covering a total of 17,026,214 km 2 , or 12.9% of the Earth's non-Antarctic land surface ( Figure 1A ).

Key data inputs and output map from the systematic conservation planning framework. (A) Protected areas mapped using polygons and buffered points for nationally designated protected areas [3] . (B) The number of native and extant globally threatened terrestrial and freshwater birds [8] , mammals [10] , and amphibians [10] per grid square. (C) The average annual agricultural opportunity cost of protecting each 30 km grid square in 2012 $US [17] . (D) The distribution of priorities for establishing new protected areas to meet the national-level 17% targets under Aichi target 11 at minimal cost and ignoring ecological representation (red), for covering threatened species (green), and locations selected under both scenarios (yellow). The sizes of the circles in the Venn diagrams are proportional to the area required in each of the three categories.

Distribution of Biodiversity

We used distribution maps for birds [8] , mammals [10] , and amphibians [10] . We focused on these taxa as they are the only major terrestrial taxonomic groups that have been comprehensively assessed for their distribution and extinction risk [10] . We excluded marine species and areas, noting that there are specific coverage targets for protecting the marine realm. For all three 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 4,118 species in total (birds = 1,135, mammals = 1,107, amphibians = 1,876; Figure 1B ). We focus only on threatened species as these are by definition the most likely species to go extinct, and therefore are most important for slowing biodiversity loss and contributing to CBD Aichi target 12. We excluded all portions of species ranges where the species was identified as extinct, introduced, or of uncertain origin. In addition to these data, we used data on the distribution of ecoregions as defined by the World Wildlife Fund [12] .

Protected Area Opportunity Cost

To account for the spatial variation in the cost of protected area expansion, we used a dataset on agricultural opportunity cost [18] , converted to 2012 US$ and with no data values filled using regularized spline interpolation with tension ( Figure 1C ). The dataset provides the estimated gross agricultural rents for terrestrial areas mapped at approximately the 5 km resolution. We use these data as our surrogate for the opportunity costs of establishing new protected areas, as agricultural expansion is the greatest single cause of habitat loss, as well as the one most commonly associated with habitat loss driven by multiple factors [19] , [20] . Agricultural opportunity costs also reflect the reduction in food security and tax revenue that national governments face when implementing protected areas. We applied a fixed cost of US$100 per km 2 to reflect the transaction costs of acquiring new protected areas [21] , although we recognize there is likely to be considerable spatial variation in these costs. We did not attempt to estimate the ongoing management costs of protected areas following establishment, as this metric needs to account for a number of difficult-to-measure social and socioeconomic factors [22] , but a recent analysis estimated that these equate to ∼14% of the agricultural opportunity costs of protection [5] .

Gap Analysis

We assessed the occurrence of threatened vertebrates within protected areas using a representation target and an adequacy target. The representation target was achieved if any portion of the species' distribution overlapped with the protected area network. To set adequacy targets we followed the method of Rodrigues et al. [23] to scale the target to the species' overall geographic range size. Complete (i.e., 100%) coverage by protected areas was required for species with a geographic range of <1,000 km 2 . For wide-ranging species (>250,000 km 2 ), the target was reduced to 10% coverage, and where geographic range size was intermediate between these extremes, the target was log-linearly interpolated.

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 km×30 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 conservation 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 [4] , we view this as our business-as-usual protected area expansion scenario. We also determine the conservation benefits of protected area target levels above the current Aichi 17% targets by setting national levels up to 30% of each country.

Ecoregional target

In this scenario, we maintain the national-level 17% targets from scenario a but add the additional constraint that countries meet their target in a way that ensures that each of the 821 terrestrial ecoregions receive at least 17% protection. We include this scenario as Target 11 calls for areas protected to be “ecologically representative” [1] .

Threatened species target

In this scenario, we maintain the national-level 17% targets from scenario a but add the additional constraint that all threatened species must be covered to the level of their adequacy targets [23] .

Threatened species preference

In this scenario, we construct an efficiency frontier between the cost of meeting the 17% target as in a and attaining threatened species conservation targets as in c. The tradeoff curve is established by iteratively increasing the value given to meeting species adequacy targets, from no value to a value equal to that given to the 17% target itself. The 17% target is always met at the national level across the tradeoff frontier.

Commission Errors in Range Maps

The IUCN [10] and Birdlife International and NatureServe [8] range maps used in this study comprise polygons showing distribution of 4,118 globally threatened birds, mammals, and amphibians. These maps may be subject to commission errors [26] – [29] , where the species is mapped as present in locations where it is in fact not present. As they affect range-based species conservation targets and lead to an overestimation of occurrence in existing or prioritized areas, commission errors could influence our study's main conclusions. We performed two analyses to determine the sensitivity of our primary results to commission errors ( Text S1 ). First we created 100 range maps for each of the 4,118 species of birds, mammals, and amphibians that simulated commission error rates [25] by deleting 50% of the range of narrow-ranged species (range<1,000 km 2 ), by deleting 25% of the range of wide-ranging species (range>250,000 km 2 ), and by linearly extrapolating the deletion rate for species of intermediate ranges. Second, we identified the “Extent of Suitable Habitat” (ESH) using high-resolution species distribution models for 1,063 mammals [30] . The ESH maps were used to identify locations in the original maps for mammals that are likely to be commission errors. We then reran our analyses using (a) the maps with simulated commission errors and (b) the ESH maps, to quantify the effects of the simulated and mapped commission errors on our estimated biodiversity value of meeting the 17% protected area target, and the shape of the efficiency frontier between cost and threatened vertebrate coverage.

Results

We find that 17% of threatened vertebrates are not found in a single protected area and 85% are not covered to the level of our adequacy targets ( Figure S1A ). A decade ago, 20% of globally threatened terrestrial birds, mammals, and amphibians were not found in a single protected area and 89% were inadequately protected [15] . Our analysis using updated datasets indicates that the global protected area network has made little progress since then toward securing a future for the world's threatened biodiversity.

We discover that if countries choose to expand their protected areas in a manner that minimizes agricultural opportunity cost, meeting their national-level targets for 17% coverage would entail a once-off transaction cost of US$0.9 billion and an annual agricultural opportunity cost of $4.9 billion ( Table 1 ). As this option aligns with the previous pattern of protected area establishment, we view it as a likely business-as-usual scenario for meeting the terrestrial coverage aspect of Aichi target 11. We find that this would result in only 852 (21%) threatened vertebrates reaching targets for adequate coverage ( Figure S1B ), an increase of only 249 species over existing protection ( Table 1 ) and arguably a failure to meet Aichi target 12. Moreover, even if highly ambitious areal targets were to drive further growth of the global protected area network beyond 2020, the costs of expansion would rise steeply without providing cost-effective coverage for threatened species ( Figure 2 ).

The number of globally threatened vertebrates that reach our adequacy targets (black), and the agricultural opportunity cost of establishing new protected areas (red), as the proportion of global land areas protected increases above 17%.

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.

An alternative is to ensure a representative sample of major vegetation communities is protected, as this would protect a broader range of habitats and could lead to improved conservation outcomes. Target 11 calls for ecologically representative protected area coverage. We find that if countries meet their 17% coverage targets in a way that distributes protection across ecoregions equally, the opportunity cost of establishing the additional protected areas would be 4.5 times higher than the business-as-usual scenario ($24.8 billion annually; Table 1 ), but that coverage of threatened species would increase only marginally ( Figure S1C ). Moreover, the majority of species that reach their adequacy targets are those with a geographic range size ≥250,000 km 2 ( Figure S1C ), as their wide distribution renders them more easily captured when distributing protected areas equitably across ecoregions. The species most likely to be left unprotected are narrowly distributed species, which often are those in greatest need of protection [31] , [32] .

These results indicate that protected area expansion targeting either the cheapest land or representation of ecoregions is not an efficient approach for covering threatened species. Alternatively, we find that locating protected areas to ensure they meet targets for adequate coverage of all 4,118 threatened species would cost about $42.5 billion annually ( Table 1 ), which is about 7.5 times more than the cheapest option for meeting the 17% target. This difference in cost is driven by low concordance between areas that are cheap to protect and those that capture the distributions of threatened species ( Figure 1D ). Land selected for threatened species tends to align with tropical forest hotspots ( Figure 1B ), such as the tropical Andes and eastern Madagascar, whereas the cheapest land to protect is remote and often in more arid zones ( Figure 1D ). This lack of overlap helps explain why the existing protected area network, which has favored low-cost areas in each country [4] , represents threatened species rather poorly.

How can countries reconcile the attraction of low-cost conservation with the benefits of protecting places that contribute to threatened species conservation? By varying the importance placed on meeting targets for adequate coverage of threatened species, we discover a nonlinear tradeoff between the cost of establishing additional protected areas and the proportion of threatened vertebrates covered by these areas ( Figure 3 ). The shape of the curve illustrates that large gains in the number of species potentially protected could be achieved for relatively small increases in cost. For instance, increasing by 5-fold the number of species protected relative to the low-cost, business-us-usual scenario would increase opportunity costs to only $7.4 billion annually (1.5 times as much; Table 1 ).

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 each species adequacy target that is met within protected areas, summed across all species, and is not directly comparable to that of the other figures, which only count species whose protected area coverage meets or exceeds their target.

We find that our primary results are robust to randomly simulated commission errors in the range maps. Although the number of species meeting range-based coverage targets generally decreases once commission errors are simulated ( Text S1 ), this drop averages only 5% across the tradeoff curve ( Figure S2 ). Moreover, both a visual interpretation and a quantitative measure of the shape of the tradeoff curve reveals that the original and commission error updated curves are similarly nonlinear. Moreover, using high-resolution expert-based habitat suitability models for 1,063 threatened mammals, we again find that commission errors are unlikely to alter our primary findings ( Figure S3 ).

Discussion

A small minority (15%) of threatened vertebrates are adequately covered by existing protected areas. However, the adoption of the Aichi targets marks an historic opportunity for achieving conservation of the world's biodiversity. If countries are to meet the protected area Aichi target, at least 5.8 million km 2 of new protected areas will need to be created by 2020. Although this is a significant opportunity for biodiversity conservation, we have shown that protected area expansion that targets low-cost areas in each country and ignores threatened species is unlikely to protect such species incidentally. This remains the case even if protected areas are further expanded to cover 30% of land areas, or if they are located to cover a representative sample of Earth's terrestrial ecoregions. On the other hand, we find that if protected areas are directed in a cost-efficient manner to protect threatened vertebrates, these species could be protected for an estimated agricultural opportunity cost of about $42.5 billion annually. We also find that there is a nonlinear relationship between cost and species protection, indicating that options exist for increasing threatened species protection above the business-as-usual level at little additional cost.

Our estimate of the cost of reaching adequacy targets for all threatened birds, mammals, and amphibians is lower than the $58 billion annually estimated for protecting the world's IBAs [5] , though each option comprises a similar land area. There are three primary reasons for this. First, the estimated costs of protecting IBAs include management costs, which are estimated at ∼$7 billion annually [5] . Second, IBAs are identified for their contribution to global bird conservation, without consideration of the cost of protecting these areas, whereas we used an optimization approach to identify low-cost options for meeting conservation targets [33] , [34] . Third, IBAs are identified based on the presence of both threatened and nonthreatened species (e.g., congregatory species), while we focused on threatened species alone.

Our analyses are subject to a number of caveats. First, we considered relative cost based on gross agricultural rents, not management costs or the opportunity costs for other land uses [33] , nor the practicalities of establishing reserves among these competing land uses. Second, overlay of coarse scale maps of species distributions onto fine-scale protected area maps generates commission errors [26] , [35] , though these are unlikely to qualitatively change our results. Still, as commission errors mean that species distributions overlap less than these coarse-scale maps suggest, our estimate of the area needed to protect all threatened species is a minimum [30] . Locations identified here should therefore be considered as broad indications of where specific areas for protection might be located, and our estimates of cost and the area requiring protection will be minima. Third, although we recognize that our analyses have limited taxonomic breadth, no other taxonomic groups (e.g., plants) have undergone comprehensive assessment of both extinction risk and distribution at a sufficiently fine scale for a comparable analysis [10] . Yet good indications exist from the literature that protected areas identified for broad taxonomic groups cover the majority of species in other, nontarget groups [36] , [37] . Finally, our species-specific targets for protection do not account for minimum viable protected areas or connectivity and do not guarantee the long-term survival of all species. Moreover, many species are threatened by processes other than habitat loss and therefore require additional conservation actions both inside and outside protected areas [38] .

For the global protected area network to fulfill its potential role as the cornerstone of biodiversity conservation [39] , and for governments to meet their commitments on protected areas and species extinctions, the distribution of threatened species must inform future protected area establishment. Preventing the further loss of all threatened species is a lofty goal and will require substantial efforts. But expanding protected areas requires managing tradeoffs among societal objectives [40] , and here we have shown that considerable increases in protected area coverage of species could be achieved at modest additional cost. Exploiting the nonlinearity of this tradeoff will require directly linking the Aichi targets on protected areas and threatened species (as well as other targets, including target 5 on slowing habitat loss), thereby formalizing the interdependence of these key commitments.

Supporting Information

The total extant geographic range size, in logarithmic scale, and the percent of that range in protected areas for 4,118 threatened vertebrates, with the red line detailing the range-based conservation targets used in the analyses. “a” shows the protection afforded by the current protected areas, “b” shows the protection from the current network plus new protected areas necessary to meet national-level 17% targets, and “c” shows the protection from the current network plus new protected areas to meet national-level 17% targets in a way that ensures terrestrial ecoregions are protected to the level of 17%. Numbers in the graphs give the number of threatened species that have their adequacy target fully met in each scenario.

(EPS)

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Efficiency frontier between the cost of establishing additional protected areas to achieve 17% coverage and the number of species potentially covered for the original range maps (black circles) and the randomly reduced species range maps (red stars). The y -axis presents the proportion of each species adequacy target that is met within protected areas, summed across all species. The red stars show the average results from 100 iterations of randomly deleting a portion of each species range; standard deviations for the 100 runs average ±0.82% across the tradeoff frontier and are therefore too small to graph.

(EPS)

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Efficiency frontier between the cost of establishing additional protected areas to achieve 17% coverage and the number of mammal species potentially covered for original range maps (black circles) and the ESH maps (red stars). The y -axis presents the proportion of each species adequacy target that is met within protected areas, summed across all species.

(EPS)

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Analyses of sensitivity to range map commission errors.

(DOCX)

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