Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

A strategy for the next decade to address data deficiency in neglected biodiversity

Measuring progress toward international biodiversity targets requires robust information on the conservation status of species, which the International Union for Conservation of Nature (IUCN) Red List of Threatened Species provides. However, data and capacity are lacking for most hyperdiverse groups, such as invertebrates, plants, and fungi, particularly in megadiverse or high-endemism regions. Conservation policies and biodiversity strategies aimed at halting biodiversity loss by 2020 need to be adapted to tackle these information shortfalls after 2020. We devised an 8-point strategy to close existing data gaps by reviving explorative field research on the distribution, abundance, and ecology of species; linking taxonomic research more closely with conservation; improving global biodiversity databases by making the submission of spatially explicit data mandatory for scientific publications; developing a global spatial database on threats to biodiversity to facilitate IUCN Red List assessments; automating preassessments by integrating distribution data and spatial threat data; building capacity in taxonomy, ecology, and biodiversity monitoring in countries with high species richness or endemism; creating species monitoring programs for lesser-known taxa; and developing sufficient funding mechanisms to reduce reliance on voluntary efforts. Implementing these strategies in the post-2020 biodiversity framework will help to overcome the lack of capacity and data regarding the conservation status of biodiversity. This will require a collaborative effort among scientists, policy makers, and conservation practitioners.     

Genetic diversity and IUCN Red List status

The International Union for Conservation of Nature (IUCN) Red List is an important and widely used tool for conservation assessment. The IUCN uses information about a species’ range, population size, habitat quality and fragmentation levels, and trends in abundance to assess extinction risk. Genetic diversity is not considered, although it affects extinction risk. Declining populations are more strongly affected by genetic drift and higher rates of inbreeding, which can reduce the efficiency of selection, lead to fitness declines, and hinder species’ capacities to adapt to environmental change. Given the importance of conserving genetic diversity, attempts have been made to find relationships between red-list status and genetic diversity. Yet, there is still no consensus on whether genetic diversity is captured by the current IUCN Red List categories in a way that is informative for conservation. To assess the predictive power of correlations between genetic diversity and IUCN Red List status in vertebrates, we synthesized previous work and reanalyzed data sets based on 3 types of genetic data: mitochondrial DNA, microsatellites, and whole genomes. Consistent with previous work, species with higher extinction risk status tended to have lower genetic diversity for all marker types, but these relationships were weak and varied across taxa. Regardless of marker type, genetic diversity did not accurately identify threatened species for any taxonomic group. Our results indicate that red-list status is not a useful metric for informing species-specific decisions about the protection of genetic diversity and that genetic data cannot be used to identify threat status in the absence of demographic data. Thus, there is a need to develop and assess metrics specifically designed to assess genetic diversity and inform conservation policy, including policies recently adopted by the UN's Convention on Biological Diversity Kunming-Montreal Global Biodiversity Framework.     

Trend in the Status of Breeding Bird Fauna in British Columbia, Canada, Based on the IUCN Red List Index Method

Abstract:  The World Conservation Union (IUCN) Red List Index (RLI) is used to measure global trends in the status of biodiversity. We examined how the index might be used to measure the trend in the status of indigenous breeding birds in British Columbia between 1992 and 2006. We followed the RLI method described by Butchart et al. (2004, 2007) as closely as possible . Because IUCN Red List assessments at the regional level are not available in British Columbia, we used NatureServe S (subnational) ranking data. We calculated three index trend lines. The first two of these allowed us to compare an index based on our original data to one based on data that had been retrospectively corrected; the latter produced a smooth, flat line. A third trend line, based on the corrected data but excluding species new to province since 1947, produced a gently sloping downward trend. Ongoing immigration of bird species in and out of British Columbia added to the complexity of interpreting our regional RLI-type index, especially because our S-rank data did not incorporate transboundary "rescue" effects. Because the RLI is scaled so that the maximum value is based on a state in which all species are simultaneously ranked as least concern, it may exaggerate the highest potential status of intrinsically vulnerable species. A simpler, more intuitive graphic allows reporting that is less dependent on context. We believe the RLI approach holds useful innovation for an indicator of change in biodiversity within jurisdictional boundaries.     

Declines in Common, Widespread Butterflies in a Landscape under Intense Human Use

Abstract:  Analyses of species' population losses typically show a dichotomy between strongly affected, rare, and localized species and apparently unaffected, common, and widespread species. We analyzed 16 years (1992–2007) of butterfly transect count data from The Netherlands in a reevaluation of the trends of common, widespread species. Fifty-five percent (11 of 20 species) of these species suffered severe declines in distribution and abundance. Overall, cumulative butterfly abundance declined by around 30%. Some of the species in decline used to be omnipresent in gardens and parks, and 2 of the species were previously considered agricultural pests. Based on their declines over the last 16 years, 2 of the 20 species ( Lasiommata megera and Gonepteryx rhamni ) reached endangered status in The Netherlands under the IUCN (International Union for Conservation of Nature) population-decline criterion, and 2 species ( Inachis io and Thymelicus lineola ) met vulnerable criterion. Butterflies in farmland, urban, and particularly woodland areas showed the largest decline in species abundance. The abundance of species associated with vegetation types found mainly in nature reserves (dunes, heathland, and, to a lesser extent, seminatural grassland) increased or remained stable. The decline of widespread species requires additional conservation strategies in the wider landscape.     

Quantifying the Indicator Power of an Indicator Species

Abstract:  Biodiversity indicator species are needed for classifying biotopes and sites for conservation, and a number of methods have been developed for determining indicator species for this purpose. Nevertheless, in addition to site classification, there is sometimes a need to define an indicator species that indicates the occurrence of another species. For example, when a species of interest (target species) is difficult to detect or identify, a reliable indicator species can function as a tool that saves time and money. We derived a method that provides a quantitative measure of the indicator power (IP) of an indicator species for the target species or any species assemblage. We calculated the measure of IP from a presence–absence matrix that covered several sites. The method provided a list of indicator species, the presence of which reliably indicated the presence of another species (e.g., a threatened or rare species in a given area). The IP of the species was highest when the number of shared occurrences between the indicator species and the target species was high and, simultaneously, when the indicator species and the target species occurred separately in only a few cases. The IP was also positively influenced by the number of sites with no occurrences of either the indicator or the target species. Our method can also be used to quantify different types of species occurrence indications. We refer to these types as presence–presence, presence–absence, absence–presence, and absence–absence indications. To clarify the use of the method, we examined the situation with red-listed polypores in White-backed Woodpecker (Dendrocopos leucotos) habitats in Fennoscandia and found some suitable indicator species. Our method provides a new, objective way to evaluate the IP of an indicator species.     

Attitudes toward Sustainability and Extinction

Abstract: Conservation biologists and natural resource managers are both working to maintain species, but their approaches and priorities differ. The contrast was highlighted when the World Conservation Union (IUCN) listed some commercial fish species, such as the Atlantic cod ( Gadus morhua ), in the 1996 Red List of Threatened Animals. These species qualified under IUCN's criteria because they had undergone a marked decline in abundance. Disagreements over these listings revealed fundamental differences between resource managers and conservation biologists. Resource managers aiming to maximize continuing yields using specific, explicit, and data-rich models, generally have not considered risk assessment and sometimes face the necessity for political compromises. Conservation biologists generally consider a wide diversity of species and operate in a data-poor and precautionary context with an overall aim of minimizing extinction risk. The IUCN Red List is an extreme case in point and uses simple criteria for evaluating the conservation status of all species. Under these circumstances, it can do little more than indicate a species' status in order to prompt further investigation by the appropriate body. We suggest that productive collaboration between conservation biologists and resource managers will start with an understanding of these different perspectives and will benefit from common interests in precautionary approaches, ecosystem approaches, and adaptive management studies.     

Risk-Based Viable Population Monitoring

Abstract:  We describe risk-based viable population monitoring, in which the monitoring indicator is a yearly prediction of the probability that, within a given timeframe, the population abundance will decline below a prespecified level. Common abundance-based monitoring strategies usually have low power to detect declines in threatened and endangered species and are largely reactive to declines. Comparisons of the population's estimated risk of decline over time will help determine status in a more defensible manner than current monitoring methods. Monitoring risk is a more proactive approach; critical changes in the population's status are more likely to be demonstrated before a devastating decline than with abundance-based monitoring methods. In this framework, recovery is defined not as a single evaluation of long-term viability but as maintaining low risk of decline for the next several generations. Effects of errors in risk prediction techniques are mitigated through shorter prediction intervals, setting threshold abundances near current abundance, and explicitly incorporating uncertainty in risk estimates. Viable population monitoring also intrinsically adjusts monitoring effort relative to the population's true status and exhibits considerable robustness to model misspecification. We present simulations showing that risk predictions made with a simple exponential growth model can be effective monitoring indicators for population dynamics ranging from random walk to density dependence with stable, decreasing, or increasing equilibrium. In analyses of time-series data for five species, risk-based monitoring warned of future declines and demonstrated secure status more effectively than statistical tests for trend.     

Generation lengths of the world's birds and their implications for extinction risk

Birds have been comprehensively assessed on the International Union for Conservation of Nature (IUCN) Red List more times than any other taxonomic group. However, to date, generation lengths have not been systematically estimated to scale population trends when undertaking assessments, as required by the criteria of the IUCN Red List. We compiled information from major databases of published life-history and trait data for all birds and imputed missing life-history data as a function of species traits with generalized linear mixed models. Generation lengths were derived for all species, based on our modeled values of age at first breeding, maximum longevity, and annual adult survival. The resulting generation lengths varied from 1.42 to 27.87 years (median 2.99). Most species (61%) had generation lengths <3.33 years, meaning that the period of 3 generations—over which population declines are assessed under criterion A—was <10 years, which is the value used for IUCN Red List assessments of species with short generation times. For these species, our trait-informed estimates of generation length suggested that 10 years is a robust precautionary value for threat assessment. In other cases, however, for whole families, genera, or individual species, generation length had a substantial impact on their estimated extinction risk, resulting in higher extinction risk in long-lived species than in short-lived species. Although our approach effectively addressed data gaps, generation lengths for some species may have been underestimated due to a paucity of life-history data. Overall, our results will strengthen future extinction-risk assessments and augment key databases of avian life-history and trait data.     

Current Trends in Plant and Animal Population Monitoring

Abstract:  Animal and plant population monitoring programs are critical for identifying species at risk, evaluating the effects of management or harvest, and tracking invasive and pest species. Nevertheless, monitoring activities are highly decentralized, which makes it difficult for researchers or conservation planners to get a good general picture of what real-world monitoring programs actually entail. We used a Web-based survey to collect information on population monitoring programs. The survey focused on basic questions about each program, including motivations for monitoring, types of data being collected, spatiotemporal design of the program, and reasons for choosing that design. We received responses from 311 people involved in monitoring of various species and used these responses to summarize ongoing monitoring efforts. We also used responses to determine whether monitoring strategies have changed over time and whether they differed among monitoring agencies. Most commonly, monitoring entailed collection of count data at multiple sites with the primary goal of detecting trends. But we also found that goals and strategies for monitoring appeared to be diversifying, that area-occupied and presence–absence approaches appeared to be gaining in popularity, and that several other promising approaches (monitoring to reduce parameter uncertainty, risk-based monitoring, and directly linking monitoring data to management decisions) have yet to become widely established. We suggest that improved communication between researchers studying monitoring designs and those who are charged with putting these designs into practice could further improve monitoring programs and better match sampling designs to the objectives of monitoring programs.     

Biofluorescence as a survey tool for cryptic marine species

As ecosystems come under increasing anthropogenic pressure, rare species face the highest risk of extinction. Paradoxically, data necessary to evaluate the conservation status of rare species are often lacking because of the challenges of detecting species with low abundance. One group of fishes subject to this undersampling bias are those with cryptic body patterns. Twenty‐one percent of cryptic fish species assessed for their extinction risk (International Union for Conservation of Nature [IUCN]) are data deficient. We developed a nondestructive method for surveying cryptically patterned marine fishes based on the presence of biofluorescence (underwater biofluorescence census, UBC). Blue LED torches were used to investigate how widespread biofluorescence was in cryptic reef fishes in the Coral Triangle region. The effectiveness of UBC to generate abundance data was tested on a data‐deficient pygmy seahorse species (Hippocampus bargibanti) and compared with data obtained from standard underwater visual census (UVC) surveys. We recorded 95 reef fish species displaying biofluorescence, 73 of which had not been previously described as biofluorescent. Of those fish with cryptic patterns, 87% were biofluorescent compared with 9% for noncryptic fishes. The probability of species displaying biofluorescence was 70.9 times greater for cryptic species than for noncryptic species. Almost twice the number of H. bargibanti was counted using the UBC compared with UVC. For 2 triplefin species (Ucla xenogrammus, Enneapterygius tutuilae), the abundance detected with UBC was triple that detected with UVC. The UBC method was effective at finding cryptic species that would otherwise be difficult to detect and thus will reduce interobserver variability inherent to UVC surveys. Biofluorescence is ubiquitous in cryptic fishes, making this method applicable across a wide range of species. Data collected using UBC could be used with multiple IUCN criteria to assess the extinction risk of cryptic species. Adopting this technique will enhance researchers’ ability to survey cryptic species and facilitate management and conservation of cryptic marine species.     

Assessing the extinction risk of insular,understudied marine species

Hydrothermal vents are rare deep-sea oases that house faunal assemblages with a similar density of life as coral reefs. Only approximately 600 of these hotspots are known worldwide, most only one-third of a football field in size. With advancing development of the deep-sea mining industry, there is an urgent need to protect these unique, insular ecosystems and their specialist endemic faunas. We applied the IUCN (International Union for the Conservation of Nature) Red List criteria to assess the extinction risk of vent-endemic molluscs with varying exposure to potential deep-sea mining. We assessed 31 species from three key areas under different regulatory frameworks in the Indian, West Pacific, and Southern Oceans. Three vent mollusc species were also examined as case studies of different threat contexts (protected or not from potential mining) to explore the interaction of local regulatory frameworks and IUCN Red List category assignment. We found that these assessments were robust even when there was some uncertainty in the total range of individual species, allowing assessment of species that have only recently been named and described. For vent-endemic species, regulatory changes to area-based management can have a greater impact on IUCN Red List assessment outcomes than incorporating additional data about species distributions. Our approach revealed the most useful IUCN Red List criteria for vent-endemic species: criteria B and D2. This approach, combining regulatory framework and distribution, has the potential to rapidly gauge assessment outcomes for species in insular systems worldwide.     

Effect of IUCN Red List category on public attention to mammals

Cultural data is a powerful tool to analyze public awareness of key societal issues, including the conservation of nature. I used two publicly available repositories of cultural data, Google Trends and Google Ngram, to quantify the effect of the International Union for the Conservation of Nature (IUCN) Red List conservation status on public attention toward 4539 mammal species. With Google Trends, I calculated whether Google searches for their common and scientific names have been increasing or decreasing over time. I also ran an anomaly detection analysis to investigate whether a change in red-list status directly results in an increase in Google searches. Additionally, I quantified the mentions of species’ common and scientific names in English texts with Google Ngram. Overall, Google searches for most mammal species remained at similar levels or increased since 2008. The severity of species’ IUCN Red List status was a significant predictor of increasing Google searches, although the effect size was relatively small. Red-list status seemed strongly confounded with mammal body size. Species that moved to a higher-risk category spiked significantly in Google searches directly after the new designation. The mention of species’ common names in the Google Ngram's English 2019 corpus significantly increased as the red-list category increased. These results provide valuable insight into the importance of the IUCN Red List for increasing public awareness and the usefulness of publicly available cultural data on examining the effectiveness of specific conservation efforts and thus evaluating targets for support and funding.     

Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

Patterns and biases of climate change threats in the IUCN Red List

International Union for Conservation of Nature (IUCN) Red List assessments rely on published data and expert inputs, and biases can be introduced where underlying definitions and concepts are ambiguous. Consideration of climate change threat is no exception, and recently numerous approaches to assessing the threat of climate change to species have been developed. We explored IUCN Red List assessments of amphibians and birds to determine whether species listed as threatened by climate change display distinct patterns in terms of habitat occupied and additional nonclimatic threats faced. We compared IUCN Red List data with a published data set of species’ biological and ecological traits believed to infer high vulnerability to climate change and determined whether distributions of climate change‐threatened species on the IUCN Red List concur with those of climate change‐threatened species identified with the trait‐based approach and whether species possessing these traits are more likely to have climate change listed as a threat on the IUCN Red List. Species in some ecosystems (e.g., grassland, shrubland) and subject to particular threats (e.g., invasive species) were more likely to have climate change as a listed threat. Geographical patterns of climate change‐threatened amphibians and birds on the IUCN Red List were incongruent with patterns of global species richness and patterns identified using trait‐based approaches. Certain traits were linked to increases or decreases in the likelihood of a species being threatened by climate change. Broad temperature tolerance of a species was consistently related to an increased likelihood of climate change threat, indicating counterintuitive relationships in IUCN assessments. To improve the robustness of species assessments of the vulnerability or extinction risk associated with climate change, we suggest IUCN adopt a more cohesive approach whereby specific traits highlighted by our results are considered in Red List assessments. To achieve this and to strengthen the climate change‐vulnerability assessments approach, it is necessary to identify and implement logical avenues for further research into traits that make species vulnerable to climate change (including population‐level threats).     

Quantifying Rarity, Losses, and Risks for Native Fishes of the Lower Colorado River Basin: Implications for Conservation Listing

Abstract:  We examined spatial distributions of fishes native to the lower basin of the Colorado River (25 species) at three scales to determine percent decline from historical distributions based on a regional biodiversity database. We cumulated records from 1843 to 1980 to develop a "historical distribution" for each species and used those occurrences recorded from 1981 to 1998 as "modern" records. We then contrasted historical and modern distributions to (1) quantify losses in spatial distribution; (2) determine how strongly these losses and fragmentation patterns corresponded to the perceived risk of extinction of each species, as represented by its status under the IUCN Red List of Endangered Species; and (3) update extinction risk rankings for 15 fishes endemic to the lower Colorado Basin according to the IUCN criteria. Based on presence and absence data, fish fauna of the lower Colorado Basin have suffered massive distributional losses. On average, ranges of extant species have diminished more than 45% relative to their historical distribution, and 35% of species have lost 50% or more of their occurrences. We provide nine new IUCN rankings and six updates to reflect more accurately the heightened imperilment of these species. Based on our new rankings, 7 of the 15 lower Colorado Basin endemics are critically endangered, 1 is endangered, 2 are vulnerable, and 1 is already extinct. We categorize the remaining 2 endemics as lower risk. This work demonstrates the utility of matching quantitative spatial metrics such as the scale-area slope statistic to extinction risk criteria for species whose persistence is strongly influenced by spatial distribution.     

Detecting Extinction Risk from Climate Change by IUCN Red List Criteria

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow‐acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short‐lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. Detección del Riesgo de Extinción a partir del Cambio Climático por medio del Criterio de la Lista Roja de la UICNKeith et al.     

Utility of Measuring Abundance versus Consistent Occupancy in Predicting Biodiversity Persistence

Abstract:  The primary goals of reserve selection are to represent all chosen units of biodiversity and to ensure their long-term persistence while minimizing costs. We considered two simple proxies of species persistence: a time series of point-count data to calculate abundance and a time series of presence–absence data to calculate permanence (a measure of consistent occupancy over time). Using two 10-year intervals of data from the North American Breeding Bird Survey, we compared the performance of each measure at predicting persistence 18 years later. For nonrare species, abundance and permanence predicted persistence similarly well. We performed complementarity-based reserve selections with data on species abundance and permanence (from 1970 to 1979) and then evaluated the effectiveness of the reserve networks at maintaining species populations and efficiency in land use (data from 1997 to 2006). Abundance proved a better predictor of future local persistence than permanence, which justifies the relatively larger financial and temporal costs of collecting a time series of point-count data to estimate abundance. If future extinction events were used as a measure of reserve-network effectiveness, the performance of abundance and permanence did not differ markedly. Nevertheless, when future abundance, which is a more sensitive measure of network effectiveness, was used, abundance was significantly better than permanence at selecting longer-term, high-quality, species-specific habitat but required larger reserves to do so .     

Effects of roost specialization on extinction risk in bats

Understanding causes and consequences of ecological specialization is of major concern in conservation. Specialist species are particularly vulnerable to human activities. If their food or habitats are depleted or lost, they may not be able to exploit alternative resources, and population losses may result. We examined International Union for Conservation of Nature (IUCN) Red List bat data and the number of roosts used per species (accounting for phylogenetic independence) to determine whether roost specialization is correlated with extinction risk. We found a significant correlation between the IUCN Red List category and the number of roost types used. Species that use fewer roost types had a higher risk of extinction. We found that caves and similar structures were the most widely used roost types, particularly by species under some level of risk of extinction. Many critically endangered, endangered, or vulnerable species used natural roosts exclusively, whereas less threatened species used natural and human‐made roosts. Our results suggest that roost loss, particularly in species that rely on a single roost type, may be linked to extinction risk. Our focus on a single life history trait prevented us from determining how important this variable is for extinction risk relative to other variables, but we have taken a first step toward prioritizing conservation actions. Our results also suggest that roost specialization may exacerbate population declines due to other risk factors, such as hunting pressure or habitat loss, and thus that management actions to preserve species under risk of extinction should prioritize protection of roosting sites.     

Evaluation of Biogeographic Classification Schemes for Conservation Planning: Application to New Zealand's Coastal Marine Environment

Abstract:  For many regions worldwide, multiple and often contrasting biogeographic classifications exist that are derived from a variety of taxa and techniques. This presents a challenge for managers who must choose appropriate large-scale spatial frameworks for systematic conservation planning. We demonstrate how systematically collected community data can be used to evaluate existing biogeographic classifications, identify the most appropriate metric for biogeographic patterns seen in other taxonomic groups, and develop an independent biogeographic classification scheme for systematic conservation planning. We evaluated 6 existing biogeographic classifications for New Zealand's nearshore marine environment with community-similarity metrics derived from abundance and presence–absence data for macroalgae (107 species) and mobile macroinvertebrates (44 species). The concordance between community metrics and the previous classifications was high, as indicated by a high multivariate classification success (CS) (74.3–98.3%). Subsequently, we carried out an independent classification analysis on each community metric to identify biogeographic units within a hierarchical spatial framework. The classification derived from macroalgal presence–absence data achieved the highest CS and could be used as a mesoscale classification scheme in which 11 regional groupings (i.e., bioregions) (CS = 73.8–84.8%) are nested within northern and southern biogeographic provinces (CS = 90.3–98.7%). These techniques can be used in systematic conservation planning to inform the design of representative and comprehensive networks of marine protected areas through evaluation of the current coverage of marine reserves in each bioregion. Currently, 0.22% of the territorial sea around mainland New Zealand is protected in no-take marine protected areas in which 0–1.5% of each bioregion represented.