Nearly 12% of the world’s terrestrial surface is now classified as some form of protected area (PA) [1]. Indeed, the designation and maintenance of PAs are considered key global strategies to address the growing extinction crisis [1]. The unprotected world has been so transformed by human activity that it can now be characterized more readily by a set of human biomes than by the classic biogeographic regions [2]. Therefore, affording an area protection, a long-standing and current centrepiece of conservation strategy [3], appears to be an effective means of conserving its biodiversity features. Conservation scientists have rightly been concerned, however, that simple assumptions of positive ecological performance may be misleading [4]–[9]. Studies have recognized that effective PA management is key to biodiversity protection [7], and demonstrated that PA designation achieves good conservation return on investment at a relatively low cost [10]. Evidence exists, however, that in many cases PA systems are inefficiently planned to maximize benefits to biodiversity often owing to their spatial location [4], [6], and worrying declines in biodiversity even within PAs in particular regions have been identified [5], [8].

Much interest has focused on determining PA effectiveness in terms of preventing landscape cover changes (e.g. [11]–[13]), but these assessments serve only as a proxy for PA performance, as the measures used cannot necessarily capture the implications of land use change for biodiversity features. Where the latter are investigated, outcomes are typically available for specific areas, such as the tropics [8], or particular taxa, such as birds [14] or mammals [5]. Given that negative pressures on biodiversity and evidence for population declines are global in extent [15], [16], the overall significance of terrestrial PAs for maintaining biodiversity values thus remains unclear. Protected area policy demonstrating their efficacy should ideally be evidence-based, that is, informed by rigorously established objective scientific evidence, as should be the case for conservation policy generally [17]. However, such evidence is not as well developed as it should be [18], despite urgent calls for so doing both in the scientific [18], [19] and policy [3] arenas.

Protected area ecological performance would best be assessed by determining for every established PA what the overall biodiversity status is compared with what would have happened in the absence of protection. Plainly such a comparison cannot readily be achieved. One experimentally tractable alternative is the assessment of biodiversity before and after land cover change, but such studies are extremely rare (although see [20] for a notable exception). The scarcity of data to enable comparisons before/after PA establishment almost invariably necessitates comparisons of each PA with some other area that is unprotected, but similar in all but this designation. As a consequence, assessments of PA performance are typically restricted to small spatial scales and particular taxa (e.g. [14], [21]), but there is no clear indication of the generality of their often-contrasting outcomes [18], [21], [22]. The biodiversity response when comparing a PA with some other area that is unprotected can vary widely, with different studies finding both higher and/or lower biodiversity values across areas [8], [20]–[22]. Results from such studies suggest that PA ecological performance is context-specific and can be influenced by several local factors [8], [18], [22]. As a consequence, the generality of PA efficacy in maintaining biodiversity across regions remains unclear.

Here we use local scale studies comparing biodiversity between PAs and surrounding alternative land use areas to test if PAs contain higher biodiversity values than surrounding areas, using a meta-analysis. Specifically, our aim is to assess the ecological performance of terrestrial PAs, compared with areas in close proximity that are not protected, thus outside PAs, using three key biodiversity attributes: the abundances of individual species (hereafter ‘species abundances’), assemblage abundances (summed across species) and assemblage species richness. These are key measures of biodiversity [23]. We also use an information theoretic approach with candidate explanatory variables to explore reasons for the variation in effect size. We then consider sources of bias in interpreting results, and highlight the benefits and shortcomings of our approach in determining PA efficacy.

The mean effect size using the random effects model, which provides an indication of the general trend across all 861 comparisons, was 0.444 (95% confidence intervals 0.324–0.564; Table 1). Substantial variation was present in the direction and size of effects in response variables for different pairwise comparisons (I²>87.9%; Q-statistic significant at <0.01; Table 1). However, when fitting the random effects model, PAs had higher species abundances (Figure 2A; N = 330), assemblage abundances (Figure 2A; N = 297) and assemblage species richness (Figure 2A; N = 234) than land use areas outside PAs (see Table 1).

Effect sizes for PAs with no IUCN category designation were lower than those with a designation, but remained positive and overlapped with the overall effect size and so we included them here (Table 1). Studies that reported across clusters of PAs rather than individual PAs remained positive and were thus included in the overall assessment of effect size (Table 1). When resampling effect sizes to account for pseudoreplication, they remained positive and overlapped with the overall effect size for both inside-outside PAs and inside PA only comparisons, but were less positive for species responses (Table S2). The variance of these resampled effect sizes also increased, but we note that effect size precision increases with additional data (Figure S3 in File S1). Thus, the present results overall can be considered robust to pseudoreplication.

Although variable, the mean effect sizes confirm that on average PAs contain significantly higher numbers of species and more individuals for mammals, birds, herptiles and arthropods, but the effect is non-significant for plants (Figure 2B; Table 1). Small mammals showed a smaller effect size for species abundance (<1 kg; N = 25; 0.042; CI: −0.236–0.320) than did large mammals (>1 kg; N = 114; 0.372; CI: 0.131–0.613). These results suggest that while most species benefit from PA establishment, a suite of them, typically plants, fare better outside PAs in typically anthropogenically transformed habitat.

Protected area efficacy by continent generally showed positive effect sizes, apart from South America (strongly negative and only just non-significant) and Australia (also non-significant; Figure 2C). We note that sample sizes for Europe and Australia are low.

Improved biodiversity outcomes with an increase in IUCN management category would seem an obvious a priori outcome, but such a simple relationship was not clear (Figure 2D). IUCN Category 2 PAs, and to a lesser extent Category 1 PAs, had a high positive effect size. However, although the sample sizes are low, so did IUCN Category 5 PAs that allow much extractive use within their borders. PAs with no IUCN designation, and those of categories 4 and 6 had no significant effect and few data are available on Category 3 PAs.

Species listed as Least Concern, Near Threatened, Vulnerable or Endangered by the IUCN generally had greater abundances inside than outside PAs (Figure 3; Table 1). A small sample size of only six observations from one species (Gorilla gorilla) that is Critically Endangered was non-significant. However, at least for species abundance, few data on those species of greatest conservation concern, as measured by their Red List status, are available (Figure 3). Indeed, published studies comparing the abundances of highly threatened species both inside and outside PAs are rare, and many such species do not occur in PAs [18], [41].

The overall effect size from pairwise comparisons inside PAs only (0.172; 95% confidence intervals: 0.083–0.261) was lower than that of the inside and outside comparisons only (their 95% confidence intervals did not overlap). When fitting the random effects model, pristine areas in PAs only, did not have significantly higher species abundances (−0.086; CI: −0.235–0.063; n = 295), but did have significantly higher assemblage abundances (0.165; CI: 0.044–0.286; n = 152) and significantly higher assemblage species richness (0.529; CI: 0.364–0.694; n = 176) than anthropogenically disturbed areas.

The variation explained by the fitted explanatory models was low, with the meta-analytical and socio-economic models each accounting for about 5% and 7%, respectively, of the variation in effect size (Table S3). By contrast, the PA-model accounted for 25% of the variation (Table S3). For all candidate explanatory variables there were multiple competing best-fit models (Table S4). Distance among comparison sites explained only c. 1% of the variation in effect size for studies included in our meta-analysis (Table S5). Indeed, despite being significant the relationship between effect size and the greatest distance between comparison sites was weak (Pearson’s r = 0.146; p<0.001) as was the relationship with distance to PA boundary (r = 0.085; p<0.05).

An initial assessment of global PA efficacy should be to determine if differences exist in biodiversity between PAs and unprotected land in a direction demonstrating higher biodiversity values in the former. Most of the studies included here did indeed find higher species abundances, assemblage abundance, and species richness inside PAs compared to areas outside them. This pattern holds across taxonomic groups (although non-significant for plants) and continents (although non-significant for South America and Australia).

What mechanisms underlie the non-significant effects for plants and for South America and Australia are not entirely obvious. Clearly, habitat change has major effects on plants, with many studies documenting replacement of particular species and changes in habitat structure [2], [24], [42], [43]. Likewise there has been a growing focus on the scarcity of large old trees [44]. The plant studies analysed here included 53 pairwise comparisons of species richness, 41 of assemblage abundance and 12 of species abundances. All of the 12 species abundance studies were concerned with trees. This balance of investigations to date may account for the lack of an effect, and may rather reflect the globally emerging fingerprint for biodiversity loss under global change, where community turnover, but not necessarily species richness change is observed [43]. In the case of Australia, the small sample size may be driving the absence of an effect size. Alternatively, most data from Australia (84%; 16/19) came from only one study that documented the recovery of small mammal populations after their isolation from invasive predators [45], and so it is not clear to what extent this outcome reflects general patterns on the continent. For South America the situation is also difficult to explain. The taxon with the most data for South America was the mammals (53%; 81/152), many of them large (>1 kg; 54%; N = 44), and their increase outside PAs contributes to the non-significant outcome. One explanation may be hunting pressure. Carrilo et al. [46] found that increasing hunting pressure inside a PA diminished large mammal populations in Costa Rica. In contrast to our general finding, Negroes et al. [47] found that private forest reserves in Brazil were responsible for conserving medium to large-sized vertebrates, more so than PAs. While primary forest is globally irreplaceable for conserving biodiversity [24], land use areas under low extraction, or regenerating forests, seem to contribute to a degree to an integrated landscape level conservation strategy, which may be particularly true in South America [48]. Furthermore, in a comparable meta-analysis, Gibson et al. [24] found that primary forests in South America retain more biodiversity than transformed forests, but since they did not focus on PAs exclusively, they had a larger sample size (N = 909). This finding emphasises that greater sample sizes could increase a positive effect size signal between transformed and more natural areas, a finding that our data corroborate (Figure S3 in File S1).

Despite effect sizes generally being positive, PA efficacy clearly varies considerably amongst PAs, species and local contexts, as demonstrated here and in region-specific studies [5], [8], [17], [21]. Determining the mechanisms driving the pattern of higher species abundances, assemblage abundance, and species richness inside compared to outside PAs remains challenging. Using GLMs we sought to explore a range of proximate factors that might explain this variation. We included explanatory variables such as spatial structure, socio-economic conditions, and structural attributes of PAs, which have been shown elsewhere to have effects on biodiversity values [4], [6], [49]–[55]. These assessments provided some insight, but did not account for much of the variation in effect sizes found here. Since comparisons inside and outside PAs in our database were mainly made at the local scale, the geographic context explained little of the observed effect size variation. In consequence, the extent of site matching, which may play a role in increasing estimates of PA efficacy outcomes in some cases [56], may be less important in our database comparing biodiversity features themselves, rather than proxies such as deforestation (but see [56]). Socio-economic factors influence conservation outcomes in some regions [50]–[52], but here also fared relatively poorly at explaining variation. Likewise structural variables such as PA size and location explained little of the variation. Some of these variables are important drivers of biodiversity variation generally, such as area and latitudinal position (mostly via energy availability) [57], [58], [59]. However, they have much less of an influence per se on differences in diversity inside and outside PAs. Such an outcome suggests that PA efficacy itself is invariate, at least with regard to these variables. In other words the largest effect is of the PAs themselves, as we found here. Our meta-analysis of studies which compare pristine and transformed areas within PAs themselves bears out this suggestion. The pristine areas typically have higher biodiversity values than the transformed areas. Moreover, the effect size here is weaker than the effect size found when comparisons are between sites inside and outside PAs. Together with evidence that pristine forests retain biodiversity features to a greater degree than transformed areas [24], these outcomes suggest that PAs must offset negative anthropogenic influences to a greater degree than no PA designation.

Nonetheless, additional variation may be attributable to other factors such as characteristics of the organisms themselves. For mammals at least, we were able to show that larger species in particular are reduced outside PAs, in keeping with other evidence that smaller mammals are typically better able to tolerate conditions outside PAs [8], [21], [53], [60]. Others have also highlighted the contrasting responses in biodiversity documented by assessments among PAs, but comparing different taxonomic groups [8], [21]. Interspecific variability in population responses to landscape change is well-known (e.g. [61]), and some taxa obviously fare better in transformed landscapes, even within PAs. Whether this is the case for species that have a high threat status is more difficult to discern given that information for such species is so scarce [41]. Unfortunately, the scope of our data did not enable us to pursue in more detail possible factors underlying effect size variation among continents and other taxa, largely because of the risk of misleading subgroup effects [25], [27]. A range of factors could explain the variation we found given substantial life history differences among these taxa (e.g. dispersal distances, life span, migration propensity, tolerance of disturbance [62]–[64]), and considerable differences in the evolutionary history of species on continents [59], [65].

Similarly, the relationship between the designated management status of a PA and effective conservation of its biodiversity features also seems to be unclear. This outcome provides further evidence for calls that the IUCN PA management categories should be reassessed to reflect biodiversity outcomes rather than management objectives (see [66]). Thus, challenges for conservation science include determining which mechanisms drive positive PA efficacy, under which conditions PAs fail species with differential responses to threats, and concomitantly, IUCN threat designations, and how management categories and biodiversity outcomes can best be aligned.

In addition to these proximate mechanisms that might influence effect size, several ultimate mechanisms may also be important. These include (i) the observation that PAs are non-randomly placed, typically biased towards areas of inaccessibility, which in itself would reduce threatening anthropogenic processes [54]; (ii) the persistence of existing differences in abundance and richness between the areas at the time of PA designations, as a result of the choice of location [18]; (iii) that lower levels of threatening processes, such as habitat alteration or exploitation, have prevailed inside PAs than elsewhere; (iv) that active management of PAs has maintained or increased abundance and richness relative to outside PAs [18]; and/or (v) leakage effects, where threatening processes are displaced from PAs to surrounding areas [55].

Given that data on biodiversity condition before and after establishment of PAs is so rare, studies have understandably had to focus on some comparison of PAs to other areas that may embody likely outcomes if the area had not received PA designation. However, the effect size as calculated here can inherently not explicitly consider the counterfactual (the biodiversity outcome that would have occurred if there had been no PA designation, see [18], [56], [67]). Site matching approaches attempt to address this bias arising when observable biophysical and socioeconomic factors may affect biodiversity in addition to PA designation [56], [67]. While these studies may detect a weaker signal for the influence of PA designation itself, they still typically focus on proxies of biodiversity to determine performance outcomes, such as deforestation offsets. Although the irreplaceability of primary forests for biodiversity has been established [24], measures of deforestation cannot characterize changes in species richness and abundance itself. As a consequence, the vast majority of published studies on biodiversity have taken a broader view of the counterfactual, and made what for the investigators seemed a priori sensible comparisons between PAs and other areas that they held to embody likely outcomes if the former had not received designation. However, due to the way the original studies were designed, the dataset developed here cannot be analysed with site matching approaches. Thus some concern might remain that the observed effects have been influenced by any one or many of the mechanisms above. Nonetheless, the ultimate mechanisms that drive patterns of higher biodiversity retention within PAs are clearly far from universal, and their geographic distribution and intensity is poorly known [18], [67]. Therefore, a comprehensive assessment of PA effectiveness can benefit from assessments that consider the net outcomes of both observed effects (as is the case here) in addition to those approaches that can better quantify assessments of effects of bias (i.e. site matching approaches [56] or experimental designs [20]).

In conclusion, despite the ultimate mechanisms underlying our findings not being firmly established, and much variation in effect sizes across regions and among taxa remaining unexplained, a signal is clear: PAs have positive biodiversity values compared with alternative land uses. In consequence, our results, together with emerging qualitative evidence [9], suggest that in general PA establishment itself may confer a net benefit to biodiversity. Thus, our approach provides a quantitative demonstration of the value of PAs as an effective strategy for conserving biodiversity. In other words, studies undertaken at a local scale to date clearly indicate that an ecological foundation exists from which the economic, political and social benefits of PAs are being realized [68]. This outcome provides evidence in support of the value of the Aichi Biodiversity Target 11 of the Convention on Biological Diversity’s (CBD) new Strategic Plan for Biodiversity [69], the nationally agreed goals to fulfil signatory countries commitments under the CBD [69]. Target 11 calls for the expansion and effective management of PAs. The outcomes of our analyses show why this Target is worth achieving.