Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

Validating graph-based connectivity models with independent presence–absence and genetic data sets

Habitat connectivity is a key objective of current conservation policies and is commonly modeled by landscape graphs (i.e., sets of habitat patches [nodes] connected by potential dispersal paths [links]). These graphs are often built based on expert opinion or species distribution models (SDMs) and therefore lack empirical validation from data more closely reflecting functional connectivity. Accordingly, we tested whether landscape graphs reflect how habitat connectivity influences gene flow, which is one of the main ecoevolutionary processes. To that purpose, we modeled the habitat network of a forest bird (plumbeous warbler [Setophaga plumbea]) on Guadeloupe with graphs based on expert opinion, Jacobs’ specialization indices, and an SDM. We used genetic data (712 birds from 27 populations) to compute local genetic indices and pairwise genetic distances. Finally, we assessed the relationships between genetic distances or indices and cost distances or connectivity metrics with maximum-likelihood population-effects distance models and Spearman correlations between metrics. Overall, the landscape graphs reliably reflected the influence of connectivity on population genetic structure; validation R² was up to 0.30 and correlation coefficients were up to 0.71. Yet, the relationship among graph ecological relevance, data requirements, and construction and analysis methods was not straightforward because the graph based on the most complex construction method (species distribution modeling) sometimes had less ecological relevance than the others. Cross-validation methods and sensitivity analyzes allowed us to make the advantages and limitations of each construction method spatially explicit. We confirmed the relevance of landscape graphs for conservation modeling but recommend a case-specific consideration of the cost-effectiveness of their construction methods. We hope the replication of independent validation approaches across species and landscapes will strengthen the ecological relevance of connectivity models.     

Using environmental and geographic data to optimize ex situ collections and preserve evolutionary potential

Maintenance of biodiversity through seed banks and botanical gardens, where the wealth of species’ genetic variation may be preserved ex situ, is a major goal of conservation. However, challenges can persist in optimizing ex situ collections if trade-offs exist among cost, effort, and conserving species evolutionary potential, particularly when genetic data are not available. We evaluated the genetic consequences of population preservation informed by geographic (isolation by distance [IBD]) and environmental (isolation by environment [IBE]) distance for ex situ collections for which population provenance is available. We used 19 genetic and genomic data sets from 15 plant species to assess the proportion of population genetic differentiation explained by geographic and environmental factors and to simulate ex situ collections prioritizing source populations based on pairwise geographic distance, environmental distance, or both. Specifically, we tested the impact prioritizing sampling based on these distances may have on the capture of neutral, functional, or putatively adaptive genetic diversity and differentiation. Individually, IBD and IBE explained limited population genetic differences across all 3 genetic marker classes (IBD, 10–16%; IBE, 1–5.5%). Together, they explained a substantial proportion of population genetic differences for functional (45%) and adaptive (71%) variation. Simulated ex situ collections revealed that inclusion of IBD, IBE, or both increased allelic diversity and genetic differentiation captured among populations, particularly for loci that may be important for adaptation. Thus, prioritizing population collections based on environmental and geographic distance data can optimize genetic variation captured ex situ. For the vast majority of plant species for which there is no genetic information, these data are invaluable to conservation because they can guide preservation of genetic variation needed to maintain evolutionary potential within collections.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Comparing spatial conservation prioritization methods with site- versus spatial dependency-based connectivity

Larval dispersal is an important component of marine reserve networks. Two conceptually different approaches to incorporate dispersal connectivity into spatial planning of these networks exist, and it is an open question as to when either is most appropriate. Candidate reserve sites can be selected individually based on local properties of connectivity or on a spatial dependency-based approach of selecting clusters of strongly connected habitat patches. The first acts on individual sites, whereas the second acts on linked pairs of sites. We used a combination of larval dispersal simulations representing different seascapes and case studies of biophysical larval dispersal models in the Coral Triangle region and the province of Southeast Sulawesi, Indonesia, to compare the performance of these 2 methods in the spatial planning software Marxan. We explored the reserve design performance implications of different dispersal distances and patterns based on the equilibrium settlement of larvae in protected and unprotected areas. We further assessed different assumptions about metapopulation contributions from unprotected areas, including the case of 100% depletion and more moderate scenarios. The spatial dependency method was suitable when dispersal was limited, a high proportion of the area of interest was substantially degraded, or the target amount of habitat protected was low. Conversely, when subpopulations were well connected, the 100% depletion was relaxed, or more habitat was protected, protecting individual sites with high scores in metrics of connectivity was a better strategy. Spatial dependency methods generally produced more spatially clustered solutions with more benefits inside than outside reserves compared with site-based methods. Therefore, spatial dependency methods potentially provide better results for ecological persistence objectives over enhancing fisheries objectives, and vice versa. Different spatial prioritization methods of using connectivity are appropriate for different contexts, depending on dispersal characteristics, unprotected area contributions, habitat protection targets, and specific management objectives. Comparación entre los métodos de priorización de la conservación espacial con sitio y la conectividad espacial basada en la dependencia     

Use of environmental DNA in assessment of fish functional and phylogenetic diversity

Assessing the impact of global changes and protection effectiveness is a key step in monitoring marine fishes. Most traditional census methods are demanding or destructive. Nondisturbing and nonlethal approaches based on video and environmental DNA are alternatives to underwater visual census or fishing. However, their ability to detect multiple biodiversity factors beyond traditional taxonomic diversity is still unknown. For bony fishes and elasmobranchs, we compared the performance of eDNA metabarcoding and long-term remote video to assess species’ phylogenetic and functional diversity. We used 10 eDNA samples from 30 L of water each and 25 hr of underwater videos over 4 days on Malpelo Island (pacific coast of Colombia), a remote marine protected area. Metabarcoding of eDNA detected 66% more molecular operational taxonomic units (MOTUs) than species on video. We found 66 and 43 functional entities with a single eDNA marker and videos, respectively, and higher functional richness for eDNA than videos. Despite gaps in genetic reference databases, eDNA also detected a higher fish phylogenetic diversity than videos; accumulation curves showed how 1 eDNA transect detected as much phylogenetic diversity as 25 hr of video. Environmental DNA metabarcoding can be used to affordably, efficiently, and accurately census biodiversity factors in marine systems. Although taxonomic assignments are still limited by species coverage in genetic reference databases, use of MOTUs highlights the potential of eDNA metabarcoding once reference databases have expanded.     

A review of selection‐based tests of abiotic surrogates for species representation

Because conservation planners typically lack data on where species occur, environmental surrogates—including geophysical settings and climate types—have been used to prioritize sites within a planning area. We reviewed 622 evaluations of the effectiveness of abiotic surrogates in representing species in 19 study areas. Sites selected using abiotic surrogates represented more species than an equal number of randomly selected sites in 43% of tests (55% for plants) and on average improved on random selection of sites by about 8% (21% for plants). Environmental diversity (ED) (42% median improvement on random selection) and biotically informed clusters showed promising results and merit additional testing. We suggest 4 ways to improve performance of abiotic surrogates. First, analysts should consider a broad spectrum of candidate variables to define surrogates, including rarely used variables related to geographic separation, distance from coast, hydrology, and within‐site abiotic diversity. Second, abiotic surrogates should be defined at fine thematic resolution. Third, sites (the landscape units prioritized within a planning area) should be small enough to ensure that surrogates reflect species’ environments and to produce prioritizations that match the spatial resolution of conservation decisions. Fourth, if species inventories are available for some planning units, planners should define surrogates based on the abiotic variables that most influence species turnover in the planning area. Although species inventories increase the cost of using abiotic surrogates, a modest number of inventories could provide the data needed to select variables and evaluate surrogates. Additional tests of nonclimate abiotic surrogates are needed to evaluate the utility of conserving nature's stage as a strategy for conservation planning in the face of climate change.     

Multispecies genetic objectives in spatial conservation planning

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear‐cut guidance on how genetic features can be incorporated into conservation‐planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation‐priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected‐area networks that appropriately preserve community‐level evolutionary patterns.     

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial–environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial–environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.     

Application of next-generation sequencing technologies to conservation of wood-inhabiting fungi

Next-generation sequencing (NGS) has significantly increased knowledge of microbial communities and their distribution. However, it is still not common to apply NGS technology to microbial conservation. We sought to use NGS technologies to evaluate conservation strategies for wood-inhabiting fungi. Evaluating a deadwood experiment 3 years after it was established, we specifically examined which tree species combinations promoted the highest richness of wood-inhabiting fungi. Deadwood enrichment was an effective strategy and logs of 6 tree species, either those with the highest wood-inhabiting fungal α and γ diversity or those with the highest β diversity, maintained >1,000 operational taxonomic units (OTUs) spread over a wide range of taxonomic groups. In comparison, a conservation strategy based only on the results of sporocarp surveys yielded 591 OTUs. This result highlights the need to use NGS approaches to inform microbial conservation strategies. We also determined that 5 tree species with the highest saproxylic beetle γ diversity simultaneously conserved wood-inhabiting fungi. Apart from deadwood volume, we suggest data on deadwood quality and species also be included as indicators, especially for wood-inhabiting fungal diversity, and incorporated quickly in forest assessment and monitoring systems in Central Europe.     

Protected area characteristics that help waterbirds respond to climate warming

Protected area networks help species respond to climate warming. However, the contribution of a site's environmental and conservation-relevant characteristics to these responses is not well understood. We investigated how composition of nonbreeding waterbird communities (97 species) in the European Union Natura 2000 (N2K) network (3018 sites) changed in response to increases in temperature over 25 years in 26 European countries. We measured community reshuffling based on abundance time series collected under the International Waterbird Census relative to N2K sites’ conservation targets, funding, designation period, and management plan status. Waterbird community composition in sites explicitly designated to protect them and with management plans changed more quickly in response to climate warming than in other N2K sites. Temporal community changes were not affected by the designation period despite greater exposure to temperature increase inside late-designated N2K sites. Sites funded under the LIFE program had lower climate-driven community changes than sites that did not received LIFE funding. Our findings imply that efficient conservation policy that helps waterbird communities respond to climate warming is associated with sites specifically managed for waterbirds.     

Six Common Mistakes in Conservation Priority Setting

A vast number of prioritization schemes have been developed to help conservation navigate tough decisions about the allocation of finite resources. However, the application of quantitative approaches to setting priorities in conservation frequently includes mistakes that can undermine their authors’ intention to be more rigorous and scientific in the way priorities are established and resources allocated. Drawing on well‐established principles of decision science, we highlight 6 mistakes commonly associated with setting priorities for conservation: not acknowledging conservation plans are prioritizations; trying to solve an ill‐defined problem; not prioritizing actions; arbitrariness; hidden value judgments; and not acknowledging risk of failure. We explain these mistakes and offer a path to help conservation planners avoid making the same mistakes in future prioritizations. Seis Errores Comunes en la Definición de Prioridades de Conservación     

Using environmental heterogeneity to plan for sea‐level rise

Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present‐day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low‐lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies.     

Dynamics in the global protected-area estate since 2004

Nations of the world have committed to a number of goals and targets to address global environmental challenges. Protected areas have for centuries been a key strategy in conservation and play a major role in addressing current challenges. The most important tool used to track progress on protected-area commitments is the World Database on Protected Areas (WDPA). Periodic assessments of the world's protected-area estate show steady growth over the last 2 decades. However, the current method, which uses the latest version of the WDPA, does not show the true dynamic nature of protected areas over time and does not provide information on sites removed from the WDPA. In reality, this method can only show growth or remain stable. We used GIS tools in an approach to assess protected-area change over time based on 12 temporally distinct versions of the WDPA that quantify area added and removed from the WDPA annually from 2004 to 2016. Both the narrative of continual growth of protected area and the counter-narrative of protected area removal were overly simplistic. The former because growth was almost entirely in the marine realm and the latter because some areas removed were reprotected in later years. On average 2.5 million km² was added to the WDPA annually and 1.1 million km² was removed. Reasons for the inclusion and removal of protected areas in the WDPA database were in part due to data-quality issues but also to on-the-ground changes. To meet the 17% protected-area component of Aichi Biodiversity Target 11 by 2020, which stood at 14.7% in 2016, either the rate of protected-area removal must decrease or the rate of protected-area designation and addition to the WDPA must increase.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

Conservation and social outcomes of private protected areas

Government administered protected areas (PAs) have dominated conservation strategies, discourse, and research, yet private actors are increasingly managing land for conservation. Little is known about the social and environmental outcomes of these privately protected areas (PPAs). We searched the global literature in English on PPAs and their environmental and social outcomes and identified 412 articles suitable for inclusion. Research on PPAs was geographically skewed; more studies occurred in the United States. Environmental outcomes of PPAs were mostly positive (89%), but social outcomes of PPAs were reported less (12% of all studies), and these outcomes were more mixed (65% positive). Private protected areas increased the number or extent of ecosystems, ecoregions, or species covered by PAs (representativeness) and PA network connectivity and effectively reduced deforestation and restored degraded lands. Few PPA owners reported negative social outcomes, experienced improved social capital, increased property value, or a reduction in taxes. Local communities benefited from increased employment, training, and community-wide development (e.g., building of schools), but they reported reduced social capital and no significant difference to household income. The causal mechanisms through which PPAs influence social and environmental outcomes remain unclear, as does how political, economic, and social contexts shape these mechanisms. Future research should widen the geographical scope and diversify the types of PPAs studied and focus on determining the casual mechanisms through which PPA outcomes occur in different contexts. We propose an assessment framework that could be adopted to facilitate this process.     

Climate suitability as a predictor of conservation translocation failure

The continuing decline and loss of biodiversity has caused an increase in the use of interventionist conservation tools, such as translocation. However, many translocation attempts fail to establish viable populations, with poor release site selection often flagged as an inhibitor of success. We used species distribution models (SDMs) to predict the climate suitability of 102 release sites for amphibians, reptiles, and terrestrial insects and compared suitability predictions between successful and failed attempts. We then quantified the importance of climate suitability relative to 5 other variables frequently considered in the literature as important determinants of translocation success: number of release years, number of individuals released, life stage released, origin of the source population, and position of the release site relative to the species’ range. Probability of translocation success increased as predicted climate suitability increased and this effect was the strongest among the variables we considered, accounting for 48.3% of the variation in translocation outcome. These findings should encourage greater consideration of climate suitability when selecting release sites for conservation translocations and we advocate the use of SDMs as an effective way to do this.     

Evaluating the conservation impact of Antarctica's protected areas

Antarctic specially protected areas (ASPAs) are a key regulatory mechanism for protecting Antarctic environmental values. Previous evaluations of the effectiveness of the ASPA system focused on its representativeness and design characteristics, presenting a compelling rationale for its systematic revision. Upgrading the system could increase the representation of values within ASPAs, but representation alone does not guarantee the avoided loss or improvement of those values. Identifying factors that influence the effectiveness of ASPAs would inform the design and management of an ASPA system with the greatest capacity to deliver its intended conservation outcomes. To facilitate evaluations of ASPA effectiveness, we devised a research and policy agenda that includes articulating a theory of change for what outcomes ASPAs generate and how; building evaluation principles into ASPA design and designation processes; employing complementary approaches to evaluate multiple dimensions of effectiveness; and extending evaluation findings to identify and exploit drivers of positive conservation impact. Implementing these approaches will enhance the efficacy of ASPAs as a management tool, potentially leading to improved outcomes for Antarctic natural values in an era of rapid global change. Evaluación del impacto de conservación de las áreas protegidas de la Antártida     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Effects of law enforcement and community outreach on mammal diversity in a biodiversity hotspot

Management activities such as law enforcement and community outreach are thought to affect conservation outcomes in protected areas, but their importance relative to intrinsic environmental characteristics of the parks and extrinsic human pressures surrounding the parks have not been explored. Furthermore, it is not clear which is more related to conservation outcomes—the management itself or local people's perceptions of the management. We measured objective (reports by park staff) and subjective (reports by local people) levels of community outreach and law enforcement based on responses to 374 questionnaires. We estimated mammal abundance and diversity of 6 protected areas based on data from 115 camera traps in Xishuangbanna, southwest China, a biodiversity hotspot with high hunting and land-conversion pressures. We then examined correlations among them and found that local people's perception of law enforcement was positively related to the local abundance of 2 large, hunted species, wild boar (Sus scrofa) (β = 15.22) and muntjac (Muntiacus vaginalis) (β = 14.82), but not related to the abundance of smaller mammals or to objective levels of enforcement. The subjective frequency of outreach by park staff to local communities (β = 3.42) and park size (β = 3.28) were significantly and positively related to mammal species richness, whereas elevation, human population density, and subjective frequency of law enforcement were not. We could not conclude that community outreach and law enforcement were directly causing increased mammal abundance and diversity. Nevertheless, the patterns we detected are some of the first empirical evidence consistent with the idea that biodiversity in protected areas may be more positively and strongly related to local perceptions of the intensity of park management than to either intrinsic (e.g., elevation, park size) or extrinsic (e.g., human population density) environmental factors.