The Capacity of Australia's Protected‐Area System to Represent Threatened Species

Abstract: The acquisition or designation of new protected areas is usually based on criteria for representation of different ecosystems or land‐cover classes, and it is unclear how well‐threatened species are conserved within protected‐area networks. Here, we assessed how Australia's terrestrial protected‐area system (89 million ha, 11.6% of the continent) overlaps with the geographic distributions of threatened species and compared this overlap against a model that randomly placed protected areas across the continent and a spatially efficient model that placed protected areas across the continent to maximize threatened species’ representation within the protected‐area estate. We defined the minimum area needed to conserve each species on the basis of the species’ range size. We found that although the current configuration of protected areas met targets for representation of a given percentage of species’ ranges better than a random selection of areas, 166 (12.6%) threatened species occurred entirely outside protected areas and target levels of protection were met for only 259 (19.6%) species. Critically endangered species were among those with the least protection; 12 (21.1%) species occurred entirely outside protected areas. Reptiles and plants were the most poorly represented taxonomic groups, and amphibians the best represented. Spatial prioritization analyses revealed that an efficient protected‐area system of the same size as the current protected‐area system (11.6% of the area of Australia) could meet representation targets for 1272 (93.3%) threatened species. Moreover, the results of these prioritization analyses showed that by protecting 17.8% of Australia, all threatened species could reach target levels of representation, assuming all current protected areas are retained. Although this amount of area theoretically could be protected, existing land uses and the finite resources available for conservation mean land acquisition may not be possible or even effective for the recovery of threatened species. The optimal use of resources must balance acquisition of new protected areas, where processes that threaten native species are mitigated by the change in ownership or on‐ground management jurisdiction, and management of threatened species inside and outside the existing protected‐area system.     

Current practices in the identification of critical habitat for threatened species

The term critical habitat is used to describe the subset of habitat that is essential to the survival and recovery of species. Some countries legally require that critical habitat of listed threatened and endangered species be identified and protected. However, there is little evidence to suggest that the identification of critical habitat has had much impact on species recovery. We hypothesized that this may be due at least partly to a mismatch between the intent of critical habitat identification, which is to protect sufficient habitat for species persistence and recovery, and its practice. We used content analysis to systematically review critical habitat documents from the United States, Canada, and Australia. In particular, we identified the major trends in type of information used to identify critical habitat and in occupancy of habitat identified as critical. Information about population viability was used to identify critical habitat for only 1% of the species reviewed, and for most species, designated critical habitat did not include unoccupied habitat. Without reference to population viability, it is difficult to determine how much of a species’ occupied and unoccupied habitat will be required for persistence. We therefore conclude that the identification of critical habitat remains inconsistent with the goal of protecting sufficient habitat to support persistence and recovery of the species. Ensuring that critical habitat identification aligns more closely with its intent will improve the accuracy of the designations and may therefore help improve the benefits to species recovery when combined with adequate implementation and enforcement of legal protections.     

Use of Habitats as Surrogates of Biodiversity for Efficient Coral Reef Conservation Planning in Pacific Ocean Islands

Abstract: Marine protected areas (MPAs) have been highlighted as a means toward effective conservation of coral reefs. New strategies are required to more effectively select MPA locations and increase the pace of their implementation. Many criteria exist to design MPA networks, but generally, it is recommended that networks conserve a diversity of species selected for, among other attributes, their representativeness, rarity, or endemicity. Because knowledge of species’ spatial distribution remains scarce, efficient surrogates are urgently needed. We used five different levels of habitat maps and six spatial scales of analysis to identify under which circumstances habitat data used to design MPA networks for Wallis Island provided better representation of species than random choice alone. Protected‐area site selections were derived from a rarity–complementarity algorithm. Habitat surrogacy was tested for commercial fish species, all fish species, commercially harvested invertebrates, corals, and algae species. Efficiency of habitat surrogacy varied by species group, type of habitat map, and spatial scale of analysis. Maps with the highest habitat thematic complexity provided better surrogates than simpler maps and were more robust to changes in spatial scales. Surrogates were most efficient for commercial fishes, corals, and algae but not for commercial invertebrates. Conversely, other measurements of species‐habitat associations, such as richness congruence and composition similarities provided weak results. We provide, in part, a habitat‐mapping methodology for designation of MPAs for Pacific Ocean islands that are characterized by habitat zonations similar to Wallis. Given the increasing availability and affordability of space‐borne imagery to map habitats, our approach could appreciably facilitate and improve current approaches to coral reef conservation and enhance MPA implementation.     

Constraints of philanthropy on determining the distribution of biodiversity conservation funding

Caught between ongoing habitat destruction and funding shortfalls, conservation organizations are using systematic planning approaches to identify places that offer the highest biodiversity return per dollar invested. However, available tools do not account for the landscape of funding for conservation or quantify the constraints this landscape imposes on conservation outcomes. Using state‐level data on philanthropic giving to and investments in land conservation by a large nonprofit organization, we applied linear regression to evaluate whether the spatial distribution of conservation philanthropy better explained expenditures on conservation than maps of biodiversity priorities, which were derived from a planning process internal to the organization and return on investment (ROI) analyses based on data on species richness, land costs, and existing protected areas. Philanthropic fund raising accounted for considerably more spatial variation in conservation spending (r² = 0.64) than either of the 2 systematic conservation planning approaches (r² = 0.08–0.21). We used results of one of the ROI analyses to evaluate whether increases in flexibility to reallocate funding across space provides conservation gains. Small but plausible “tax” increments of 1–10% on states redistributed to the optimal funding allocation from the ROI analysis could result in gains in endemic species protected of 8.5–80.2%. When such increases in spatial flexibility are not possible, conservation organizations should seek to cultivate increased support for conservation in priority locations. We used lagged correlations of giving to and spending by the organization to evaluate whether investments in habitat protection stimulate future giving to conservation. The most common outcome at the state level was that conservation spending quarters correlated significantly and positively with lagged fund raising quarters. In effect, periods of high fund raising for biodiversity followed (rather than preceded) periods of high expenditure on land conservation projects, identifying one mechanism conservation organizations could explore to seed greater activity in priority locations. Our results demonstrate how limitations on the ability of conservation organizations to reallocate their funding across space can impede organizational effectiveness and elucidate ways conservation planning tools could be more useful if they quantified and incorporated these constraints.     

Range‐Wide Genetic Connectivity of the Hawaiian Monk Seal and Implications for Translocation

Abstract: The Hawaiian monk seal (Monachus schauinslandi) is one of the most critically endangered marine mammals. Less than 1200 individuals remain, and the species is declining at a rate of approximately 4% per year as a result of juvenile starvation, shark predation, and entanglement in marine debris. Some of these problems may be alleviated by translocation; however, if island breeding aggregates are effectively isolated subpopulations, moving individuals may disrupt local adaptations. In these circumstances, managers must balance the pragmatic need of increasing survival with theoretical concerns about genetic viability. To assess range‐wide population structure of the Hawaiian monk seal, we examined an unprecedented, near‐complete genetic inventory of the species (n =1897 seals, sampled over 14 years) at 18 microsatellite loci. Genetic variation was not spatially partitioned (_w=?0.03, p = 1.0), and a Bayesian clustering method provided evidence of one panmictic population (K =1). Pairwise F_ST comparisons (among 7 island aggregates over 14 annual cohorts) did not reveal temporally stable, spatial reproductive isolation. Our results coupled with long‐term tag‐resight data confirm seal movement and gene flow throughout the Hawaiian Archipelago. Thus, human‐mediated translocation of seals among locations is not likely to result in genetic incompatibilities.     

Assumption‐versus data‐based approaches to summarizing species’ ranges

For conservation decision making, species’ geographic distributions are mapped using various approaches. Some such efforts have downscaled versions of coarse‐resolution extent‐of‐occurrence maps to fine resolutions for conservation planning. We examined the quality of the extent‐of‐occurrence maps as range summaries and the utility of refining those maps into fine‐resolution distributional hypotheses. Extent‐of‐occurrence maps tend to be overly simple, omit many known and well‐documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce substantial error in estimates of species’ true areas of distribution. However, no model‐evaluation steps are taken to assess the predictive ability of these models, so model inaccuracies are not noticed. Whereas range summaries derived by these methods may be useful in coarse‐grained, global‐extent studies, their continued use in on‐the‐ground conservation applications at fine spatial resolutions is not advisable in light of reliance on assumptions, lack of real spatial resolution, and lack of testing. In contrast, data‐driven techniques that integrate primary data on biodiversity occurrence with remotely sensed data that summarize environmental dimensions (i.e., ecological niche modeling or species distribution modeling) offer data‐driven solutions based on a minimum of assumptions that can be evaluated and validated quantitatively to offer a well‐founded, widely accepted method for summarizing species’ distributional patterns for conservation applications.     

Conserving tigers in working landscapes

Tiger (Panthera tigris) conservation efforts in Asia are focused on protected areas embedded in human‐dominated landscapes. A system of protected areas is an effective conservation strategy for many endangered species if the network is large enough to support stable metapopulations. The long‐term conservation of tigers requires that the species be able to meet some of its life‐history needs beyond the boundaries of small protected areas and within the working landscape, including multiple‐use forests with logging and high human use. However, understanding of factors that promote or limit the occurrence of tigers in working landscapes is incomplete. We assessed the relative influence of protection status, prey occurrence, extent of grasslands, intensity of human use, and patch connectivity on tiger occurrence in the 5400 km² Central Terai Landscape of India, adjacent to Nepal. Two observer teams independently surveyed 1009 km of forest trails and water courses distributed across 60 166‐km² cells. In each cell, the teams recorded detection of tiger signs along evenly spaced trail segments. We used occupancy models that permitted multiscale analysis of spatially correlated data to estimate cell‐scale occupancy and segment‐scale habitat use by tigers as a function of management and environmental covariates. Prey availability and habitat quality, rather than protected‐area designation, influenced tiger occupancy. Tiger occupancy was low in some protected areas in India that were connected to extensive areas of tiger habitat in Nepal, which brings into question the efficacy of current protection and management strategies in both India and Nepal. At a finer spatial scale, tiger habitat use was high in trail segments associated with abundant prey and large grasslands, but it declined as human and livestock use increased. We speculate that riparian grasslands may provide tigers with critical refugia from human activity in the daytime and thereby promote tiger occurrence in some multiple‐use forests. Restrictions on human‐use in high‐quality tiger habitat in multiple‐use forests may complement existing protected areas and collectively promote the persistence of tiger populations in working landscapes.     

Comparing Spatially Explicit Ecological and Social Values for Natural Areas to Identify Effective Conservation Strategies

Abstract: Consideration of the social values people assign to relatively undisturbed native ecosystems is critical for the success of science‐based conservation plans. We used an interview process to identify and map social values assigned to 31 ecosystem services provided by natural areas in an agricultural landscape in southern Australia. We then modeled the spatial distribution of 12 components of ecological value commonly used in setting spatial conservation priorities. We used the analytical hierarchy process to weight these components and used multiattribute utility theory to combine them into a single spatial layer of ecological value. Social values assigned to natural areas were negatively correlated with ecological values overall, but were positively correlated with some components of ecological value. In terms of the spatial distribution of values, people valued protected areas, whereas those natural areas underrepresented in the reserve system were of higher ecological value. The habitats of threatened animal species were assigned both high ecological value and high social value. Only small areas were assigned both high ecological value and high social value in the study area, whereas large areas of high ecological value were of low social value, and vice versa. We used the assigned ecological and social values to identify different conservation strategies (e.g., information sharing, community engagement, incentive payments) that may be effective for specific areas. We suggest that consideration of both ecological and social values in selection of conservation strategies can enhance the success of science‐based conservation planning.     

Using abiotic variables to predict importance of sites for species representation

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well‐surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks.     

Linking Management Effectiveness Indicators to Observed Effects of Protected Areas on Fire Occurrence in the Amazon Rainforest

Management‐effectiveness scores are used widely by donors and implementers of conservation projects to prioritize, track, and evaluate investments in protected areas. However, there is little evidence that these scores actually reflect the capacity of protected areas to deliver conservation outcomes. We examined the relation between indicators of management effectiveness in protected areas and the effectiveness of protected areas in reducing fire occurrence in the Amazon rainforest. We used data collected with the Management Effectiveness Tracking Tool (METT) scorecard, adopted by some of the world's largest conservation organizations to track management characteristics believed to be crucial for protected‐area effectiveness. We used the occurrence of forest fires from 2000 through 2010 as a measure of the effect of protected areas on undesired land‐cover change in the Amazon basin. We used matching to compare the estimated effect of protected areas with low versus high METT scores on fire occurrence. We also estimated effects of individual protected areas on fire occurrence and explored the relation between these effects and METT scores. The relations between METT scores and effects of protected areas on fire occurrence were weak. Protected areas with higher METT scores in 2005 did not seem to have performed better than protected areas with lower METT scores at reducing fire occurrence over the last 10 years. Further research into the relations between management‐effectiveness indicators and conservation outcomes in protected areas seems necessary, and our results show that the careful application of matching methods can be a suitable method for that purpose. Vinculación de Indicadores de Efectividad de Manejo con los Efectos Observados de la Ocurrencia de Fuego en Áreas Protegidas en la Amazonia     

Ecological‐Niche Modeling and Prioritization of Conservation‐Area Networks for Mexican Herpetofauna

Abstract: One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. We used maximum‐entropy niche modeling to run distribution models for 222 amphibian and 371 reptile species (49% endemics and 27% threatened) for which we had 34,619 single geographic records. The planning region is in southeastern Mexico, is 20% of the country's area, includes 80% of the country's herpetofauna, and lacks an adequate protected‐area system. We used probabilistic data to build distribution models of herpetofauna for use in prioritizing conservation areas for three target groups (all species and threatened and endemic species). The accuracy of species‐distribution models was better for endemic and threatened species than it was for all species. Forty‐seven percent of the region has been deforested and additional conservation areas with 13.7% to 88.6% more native vegetation (76% to 96% of the areas are outside the current protected‐area system) are needed. There was overlap in 26 of the main selected areas in the conservation‐area network prioritized to preserve the target groups, and for all three target groups the proportion of vegetation types needed for their conservation was constant: 30% pine and oak forests, 22% tropical evergreen forest, 17% low deciduous forest, and 8% montane cloud forests. The fact that different groups of species require the same proportion of habitat types suggests that the pine and oak forests support the highest proportion of endemic and threatened species and should therefore be given priority over other types of vegetation for inclusion in the protected areas of southeastern Mexico.     

Permeability of Roads to Movement of Scrubland Lizards and Small Mammals

A primary objective of road ecology is to understand and predict how roads affect connectivity of wildlife populations. Road avoidance behavior can fragment populations, whereas lack of road avoidance can result in high mortality due to wildlife‐vehicle collisions. Many small animal species focus their activities to particular microhabitats within their larger habitat. We sought to assess how different types of roads affect the movement of small vertebrates and to explore whether responses to roads may be predictable on the basis of animal life history or microhabitat preferences preferences. We tracked the movements of fluorescently marked animals at 24 sites distributed among 3 road types: low‐use dirt, low‐use secondary paved, and rural 2‐lane highway. Most data we collected were on the San Diego pocket mouse (Chaetodipus fallax), cactus mouse (Peromyscus eremicus), western fence lizard (Sceloporus occidentalis), orange‐throated whiptail (Aspidoscelis hyperythra), Dulzura kangaroo rat (Dipodomys simulans) (dirt, secondary paved), and deer mouse (Peromyscus maniculatus) (highway only). San Diego pocket mice and cactus mice moved onto dirt roads but not onto a low‐use paved road of similar width or onto the highway, indicating they avoid paved road substrate. Both lizard species moved onto the dirt and secondary paved roads but avoided the rural 2‐lane rural highway, indicating they may avoid noise, vibration, or visual disturbance from a steady flow of traffic. Kangaroo rats did not avoid the dirt or secondary paved roads. Overall, dirt and secondary roads were more permeable to species that prefer to forage or bask in open areas of their habitat, rather than under the cover of rocks or shrubs. However, all study species avoided the rural 2‐lane highway. Our results suggest that microhabitat use preferences and road substrate help predict species responses to low‐use roads, but roads with heavy traffic may deter movement of a much wider range of small animal species.     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

Spatial,socio‐economic,and ecological implications of incorporating minimum size constraints in marine protected area network design

Marine protected areas (MPAs) are the cornerstone of most marine conservation strategies, but the effectiveness of each one partly depends on its size and distance to other MPAs in a network. Despite this, current recommendations on ideal MPA size and spacing vary widely, and data are lacking on how these constraints might influence the overall spatial characteristics, socio‐economic impacts, and connectivity of the resultant MPA networks. To address this problem, we tested the impact of applying different MPA size constraints in English waters. We used the Marxan spatial prioritization software to identify a network of MPAs that met conservation feature targets, whilst minimizing impacts on fisheries; modified the Marxan outputs with the MinPatch software to ensure each MPA met a minimum size; and used existing data on the dispersal distances of a range of species found in English waters to investigate the likely impacts of such spatial constraints on the region's biodiversity. Increasing MPA size had little effect on total network area or the location of priority areas, but as MPA size increased, fishing opportunity cost to stakeholders increased. In addition, as MPA size increased, the number of closely connected sets of MPAs in networks and the average distance between neighboring MPAs decreased, which consequently increased the proportion of the planning region that was isolated from all MPAs. These results suggest networks containing large MPAs would be more viable for the majority of the region's species that have small dispersal distances, but dispersal between MPA sets and spill‐over of individuals into unprotected areas would be reduced. These findings highlight the importance of testing the impact of applying different MPA size constraints because there are clear trade‐offs that result from the interaction of size, number, and distribution of MPAs in a network.     

Effectiveness of Scat‐Detection Dogs in Determining Species Presence in a Tropical Savanna Landscape

Abstract: Most protected areas are too small to sustain populations of wide‐ranging mammals; thus, identification and conservation of high‐quality habitat for those animals outside parks is often a high priority, particularly for regions where extensive land conversion is occurring. This is the case in the vicinity of Emas National Park, a small protected area in the Brazilian Cerrado. Over the last 40 years the native vegetation surrounding the park has been converted to agriculture, but the region still supports virtually all of the animals native to the area. We determined the effectiveness of scat‐detection dogs in detecting presence of five species of mammals threatened with extinction by habitat loss: maned wolf (Chrysocyon brachyurus), puma (Puma concolor), jaguar (Panthera onca), giant anteater (Myrmecophaga tridactyla), and giant armadillo (Priodontes maximus). The probability of scat detection varied among the five species and among survey quadrats of different size, but was consistent across team, season, and year. The probability of occurrence, determined from the presence of scat, in a randomly selected site within the study area ranged from 0.14 for jaguars, which occur primarily in the forested areas of the park, to 0.91 for maned wolves, the most widely distributed species in our study area. Most occurrences of giant armadillos in the park were in open grasslands, but in the agricultural matrix they tended to occur in riparian woodlands. At least one target species occurred in every survey quadrat, and giant armadillos, jaguars, and maned wolves were more likely to be present in quadrats located inside than outside the park. The effort required for detection of scats was highest for the two felids. We were able to detect the presence for each of five wide‐ranging species inside and outside the park and to assign occurrence probabilities to specific survey sites. Thus, scat dogs provide an effective survey tool for rare species even when accurate detection likelihoods are required. We believe the way we used scat‐detection dogs to determine the presence of species can be applied to the detection of other mammalian species in other ecosystems.     

Conceptual frameworks and key questions for assessing the contribution of marine protected areas to shark and ray conservation

Marine protected areas (MPAs) are key tools in addressing the global decline of sharks and rays, and marine parks and shark sanctuaries of various configurations have been established to conserve shark populations. However, assessments of their efficacy are compromised by inconsistent terminology, lack of standardized approaches to assess how MPAs contribute to shark and ray conservation, and ambiguity about how to integrate movement data in assessment processes. We devised a conceptual framework to standardize key terms (e.g., protection, contribution, potential impact, risk, threat) and used the concept of portfolio risk to identify key attributes of sharks and rays (assets), the threats they face (portfolio risk), and the specific role of MPAs in risk mitigation (insurance). Movement data can be integrated into the process by informing risk exposure and mitigation through MPAs. The framework is operationalized by posing 8 key questions that prompt practitioners to consider the assessment scope, MPA type and purpose, range of existing and potential threats, species biology and ecology, and management and operational contexts. Ultimately, MPA contributions to shark and ray conservation differ according to a complex set of human and natural factors and interactions that should be carefully considered in MPA design, implementation, and evaluation.     

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.     

A Multispecies Framework for Landscape Conservation Planning

Abstract: Rapidly changing landscapes have spurred the need for quantitative methods for conservation assessment and planning that encompass large spatial extents. We devised and tested a multispecies framework for conservation planning to complement single‐species assessments and ecosystem‐level approaches. Our framework consisted of 4 elements: sampling to effectively estimate population parameters, measuring how human activity affects landscapes at multiple scales, analyzing the relation between landscape characteristics and individual species occurrences, and evaluating and comparing the responses of multiple species to landscape modification. We applied the approach to a community of terrestrial birds across 25,000 km² with a range of intensities of human development. Human modification of land cover, road density, and other elements of the landscape, measured at multiple spatial extents, had large effects on occupancy of the 67 species studied. Forest composition within 1 km of points had a strong effect on occupancy of many species and a range of negative, intermediate, and positive associations. Road density within 1 km of points, percent evergreen forest within 300 m, and distance from patch edge were also strongly associated with occupancy for many species. We used the occupancy results to group species into 11 guilds that shared patterns of association with landscape characteristics. Our multispecies approach to conservation planning allowed us to quantify the trade‐offs of different scenarios of land‐cover change in terms of species occupancy.     

Measuring Protected‐Area Isolation and Correlations of Isolation with Land‐Use Intensity and Protection Status

Abstract: Protected areas cover over 12% of the terrestrial surface of Earth, and yet many fail to protect species and ecological processes as originally envisioned. Results of recent studies suggest that a critical reason for this failure is an increasing contrast between the protected lands and the surrounding matrix of often highly altered land cover. We measured the isolation of 114 protected areas distributed worldwide by comparing vegetation‐cover heterogeneity inside protected areas with heterogeneity outside the protected areas. We quantified heterogeneity as the contagion of greenness on the basis of NDVI (normalized difference vegetation index) values, for which a higher value of contagion indicates less heterogeneous land cover. We then measured isolation as the difference between mean contagion inside the protected area and mean contagion in 3 buffer areas of increasing distance from the protected‐area border. The isolation of protected areas was significantly positive in 110 of the 114 areas, indicating that vegetation cover was consistently more heterogeneous 10–20 km outside protected areas than inside their borders. Unlike previous researchers, we found that protected areas in which low levels of human activity are allowed were more isolated than areas in which high levels are allowed. Our method is a novel way to assess the isolation of protected areas in different environmental contexts and regions.     

Effects of Errors and Gaps in Spatial Data Sets on Assessment of Conservation Progress

Data on the location and extent of protected areas, ecosystems, and species’ distributions are essential for determining gaps in biodiversity protection and identifying future conservation priorities. However, these data sets always come with errors in the maps and associated metadata. Errors are often overlooked in conservation studies, despite their potential negative effects on the reported extent of protection of species and ecosystems. We used 3 case studies to illustrate the implications of 3 sources of errors in reporting progress toward conservation objectives: protected areas with unknown boundaries that are replaced by buffered centroids, propagation of multiple errors in spatial data, and incomplete protected‐area data sets. As of 2010, the frequency of protected areas with unknown boundaries in the World Database on Protected Areas (WDPA) caused the estimated extent of protection of 37.1% of the terrestrial Neotropical mammals to be overestimated by an average 402.8% and of 62.6% of species to be underestimated by an average 10.9%. Estimated level of protection of the world's coral reefs was 25% higher when using recent finer‐resolution data on coral reefs as opposed to globally available coarse‐resolution data. Accounting for additional data sets not yet incorporated into WDPA contributed up to 6.7% of additional protection to marine ecosystems in the Philippines. We suggest ways for data providers to reduce the errors in spatial and ancillary data and ways for data users to mitigate the effects of these errors on biodiversity assessments. Efectos de Errores y Vacíos en Conjuntos de Datos Espaciales sobre la Evaluación del Progreso de la Conservación