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.     

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.     

Incorporating Climate and Ocean Change into Extinction Risk Assessments for 82 Coral Species

Many marine invertebrate species facing potential extinction have uncertain taxonomies and poorly known demographic and ecological traits. Uncertainties are compounded when potential extinction drivers are climate and ocean changes whose effects on even widespread and abundant species are only partially understood. The U.S. Endangered Species Act mandates conservation management decisions founded on the extinction risk to species based on the best available science at the time of consideration—requiring prompt action rather than awaiting better information. We developed an expert‐opinion threat‐based approach that entails a structured voting system to assess extinction risk from climate and ocean changes and other threats to 82 coral species for which population status and threat response information was limited. Such methods are urgently needed because constrained budgets and manpower will continue to hinder the availability of desired data for many potentially vulnerable marine species. Significant species‐specific information gaps and uncertainties precluded quantitative assessments of habitat loss or population declines and necessitated increased reliance on demographic characteristics and threat vulnerabilities at genus or family levels. Adapting some methods (e.g., a structured voting system) used during other assessments and developing some new approaches (e.g., integrated assessment of threats and demographic characteristics), we rated the importance of threats contributing to coral extinction risk and assessed those threats against population status and trend information to evaluate each species’ extinction risk over the 21st century. This qualitative assessment resulted in a ranking with an uncertainty range for each species according to their estimated likelihood of extinction. We offer guidance on approaches for future biological extinction risk assessments, especially in cases of data‐limited species likely to be affected by global‐scale threats. Incorporación del Cambio Climático y Oceánico en Estudios de Riesgo de Extinción para 82 Especies de Coral     

Quantification of Extinction Risk: IUCN's System for Classifying Threatened Species

Abstract: The International Union for Conservation of Nature (IUCN) Red List of Threatened Species was increasingly used during the 1980s to assess the conservation status of species for policy and planning purposes. This use stimulated the development of a new set of quantitative criteria for listing species in the categories of threat: critically endangered, endangered, and vulnerable. These criteria, which were intended to be applicable to all species except microorganisms, were part of a broader system for classifying threatened species and were fully implemented by IUCN in 2000. The system and the criteria have been widely used by conservation practitioners and scientists and now underpin one indicator being used to assess the Convention on Biological Diversity 2010 biodiversity target. We describe the process and the technical background to the IUCN Red List system. The criteria refer to fundamental biological processes underlying population decline and extinction. But given major differences between species, the threatening processes affecting them, and the paucity of knowledge relating to most species, the IUCN system had to be both broad and flexible to be applicable to the majority of described species. The system was designed to measure the symptoms of extinction risk, and uses 5 independent criteria relating to aspects of population loss and decline of range size. A species is assigned to a threat category if it meets the quantitative threshold for at least one criterion. The criteria and the accompanying rules and guidelines used by IUCN are intended to increase the consistency, transparency, and validity of its categorization system, but it necessitates some compromises that affect the applicability of the system and the species lists that result. In particular, choices were made over the assessment of uncertainty, poorly known species, depleted species, population decline, restricted ranges, and rarity; all of these affect the way red lists should be viewed and used. Processes related to priority setting and the development of national red lists need to take account of some assumptions in the formulation of the criteria.     

Trait‐based prediction of extinction risk of small‐bodied freshwater fishes

Small body size is generally correlated with r‐selected life‐history traits, including early maturation, short‐generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small‐bodied freshwater fishes from 4 temperate river basins: Murray‐Darling, Australia; Danube, Europe; Mississippi‐Missouri, North America; and the Rio Grande, North America. Twenty‐three ecological and life‐history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed‐effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size—among small‐bodied species—was the most influential trait correlated with threatened species listings. The k‐folds cross‐validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small‐bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11,000 unclassified freshwater fishes, especially those under threat from proposed dam construction in the world's most biodiverse river basins.     

Toward quantification of the impact of 21st‐century deforestation on the extinction risk of terrestrial vertebrates

Conservation actions need to be prioritized, often taking into account species’ extinction risk. The International Union for Conservation of Nature (IUCN) Red List provides an accepted, objective framework for the assessment of extinction risk. Assessments based on data collected in the field are the best option, but the field data to base these on are often limited. Information collected through remote sensing can be used in place of field data to inform assessments. Forests are perhaps the best‐studied land‐cover type for use of remote‐sensing data. Using an open‐access 30‐m resolution map of tree cover and its change between 2000 and 2012, we assessed the extent of forest cover and loss within the distributions of 11,186 forest‐dependent amphibians, birds, and mammals worldwide. For 16 species, forest loss resulted in an elevated extinction risk under red‐list criterion A, owing to inferred rapid population declines. This number increased to 23 when data‐deficient species (i.e., those with insufficient information for evaluation) were included. Under red‐list criterion B2, 484 species (855 when data‐deficient species were included) were considered at elevated extinction risk, owing to restricted areas of occupancy resulting from little forest cover remaining within their ranges. The proportion of species of conservation concern would increase by 32.8% for amphibians, 15.1% for birds, and 24.7% for mammals if our suggested uplistings are accepted. Central America, the Northern Andes, Madagascar, the Eastern Arc forests in Africa, and the islands of Southeast Asia are hotspots for these species. Our results illustrate the utility of satellite imagery for global extinction‐risk assessment and measurement of progress toward international environmental agreement targets.     

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.     

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.     

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.     

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.     

A GIS-Based Comparison of the Mexican National and IUCN Methods for Determining Extinction Risk

Abstract:  The national systems used in the evaluation of extinction risk are often touted as more readily applied and somehow more regionally appropriate than the system of the International Union for Conservation of Nature (IUCN). We compared risk assessments of the Mexican national system (method for evaluation of risk of extinction of wild species [MER]) with the IUCN system for the 16 Polianthes taxa (Agavaceae), a genus of plants with marked variation in distribution sizes. We used a novel combination of herbarium data, geographic information systems (GIS), and species distribution models to provide rapid, repeatable estimates of extinction risk. Our GIS method showed that the MER and the IUCN system use similar data. Our comparison illustrates how the IUCN method can be applied even when all desirable data are not available, and that the MER offers no special regional advantage with respect to the IUCN regional system. Instead, our results coincided, with both systems identifying 14 taxa of conservation concern and the remaining two taxa of low risk, largely because both systems use similar information. An obstacle for the application of the MER is that there are no standards for quantifying the criteria of habitat condition and intrinsic biological vulnerability. If these impossible-to-quantify criteria are left out, what are left are geographical distribution and the impact of human activity, essentially the considerations we were able to assess for the IUCN method. Our method has the advantage of making the IUCN criteria easy to apply, and because each step can be standardized between studies, it ensures greater comparability of extinction risk estimates among taxa.     

Regional IUCN Red Listing: the Process as Applied to Birds in the United Kingdom

Abstract:  The World Conservation Union (IUCN) has developed guidelines that enable the assessment of extinction risk at a regional scale. We used these guidelines to assess the extinction risk of birds in the United Kingdom for comparison with an existing assessment of conservation status. Sixty-four species were categorized as regionally threatened, of which 12 were critically endangered. The categorizations of the 223 species assessed agreed broadly with those from the existing U.K. system, which considers more than extinction risk, thus giving a more complete assessment of conservation status. There was, however, a tendency for the IUCN process to give higher risk status to edge-of-range species (some of which are relatively recent colonists considered of comparatively low conservation concern) and low status to those that have declined substantially but remain common (such as many farmland birds, the focus of considerable conservation effort in the United Kingdom). The final red list depended heavily on the subjective decisions made during the assessment process. An alternative interpretation of the guidelines could have resulted in as many as 19 or as few as 6 species being listed as critically endangered. We recommend the revision of the IUCN guidelines to reduce this subjectivity, in particular with respect to the effect of extralimital populations on the likelihood of regional extinction, and hence the potential for variation in the manner of application between regional red-list assessors. Preventing extinction does not have to be the principal driving force behind conservation action at a regional scale if the continuance of a species is safeguarded in other regions.     

Evidence for the Role of Infectious Disease in Species Extinction and Endangerment

Abstract:  Infectious disease is listed among the top five causes of global species extinctions. However, the majority of available data supporting this contention is largely anecdotal. We used the IUCN Red List of Threatened and Endangered Species and literature indexed in the ISI Web of Science to assess the role of infectious disease in global species loss. Infectious disease was listed as a contributing factor in <4% of species extinctions known to have occurred since 1500 (833 plants and animals) and as contributing to a species' status as critically endangered in <8% of cases (2852 critically endangered plants and animals). Although infectious diseases appear to play a minor role in global species loss, our findings underscore two important limitations in the available evidence: uncertainty surrounding the threats to species survival and a temporal bias in the data. Several initiatives could help overcome these obstacles, including rigorous scientific tests to determine which infectious diseases present a significant threat at the species level, recognition of the limitations associated with the lack of baseline data for the role of infectious disease in species extinctions, combining data with theory to discern the circumstances under which infectious disease is most likely to serve as an agent of extinction, and improving surveillance programs for the detection of infectious disease. An evidence-based understanding of the role of infectious disease in species extinction and endangerment will help prioritize conservation initiatives and protect global biodiversity.     

Geographic range size and extinction risk assessment in nomadic species

Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to‐and‐fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid‐zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning.     

Toward reassessing data‐deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data‐deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data‐deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data‐deficient assessments. To develop this, we reviewed 2879 data‐deficient assessments in 6 animal groups and identified 8 main justifications for assigning data‐deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data‐deficient species slipping unnoticed toward extinction.     

Developing Classification Criteria under the U.S. Endangered Species Act: Bowhead Whales as a Case Study

Abstract: Under the U.S. Endangered Species Act, a species is classified as endangered, threatened, or recovered based on the extent to which its survival is affected by one or more of five subjective factors. A key criticism of the act is that it makes no reference to quantitative or even qualitative parameters of what constitutes "danger of extinction." Without objective standards to guide decisionmakers, classification decisions fall prey to political and social influences. We recommend the development of species-specific, status-determining criteria as a means to rationalize and expedite the listing process and reclassification decisions, independent of the requirement for delisting criteria in recovery plans. Such criteria should (1) clearly define levels of vulnerability, (2) identify gaps in information on life-history parameters, and (3) address uncertainty in existing data. As a case study, we developed preliminary criteria for bowhead whales (    Balaena mysticetus ). Thresholds for endangered and threatened status were based on World Conservation Union ( IUCN) Red List criteria and population viability analyses. Our analysis indicates that particular attention must be focused on population structure within the species to appropriately classify the degree to which one or more components of a species are vulnerable to extinction. A similar approach could be used in the classification of other species. According to our application of the IUCN criteria and those developed for similar species by Gerber and DeMaster (1999) , the Bering Sea population of bowhead whales should be delisted, whereas the other four populations of bowheads should continue to be considered endangered.     

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).     

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Albatross populations in peril: a population trajectory for black-browed albatrosses at south Georgia.

Simulation modeling was used to reconstruct Black-browed Albatross (Diomedea melanophris) population trends. Close approximations to observed data were accomplished by annually varying survival rates, reproductive success, and probabilities of returning to breed given success in previous years. The temporal shift in annual values coincided with the start of longline fishing at South Georgia and potential changes in krill abundance. We used 23 years of demographic data from long-term studies of a breeding colony of this species at Bird Island, South Georgia, to validate our model. When we used annual parameter estimates for survival, reproductive success, and probabilities of returning to breed given success in previous years, our model trajectory closely followed the observed changes in breeding population size over time. Population growth rate was below replacement (lambda < 1) in most years and was most sensitive to changes in adult survival. This supports the recent IUCN uplisting of this species from "Vulnerable" to "Endangered." Comparison of pre-1988 and post-1988 demography (before and after the inception of a longline fishery in the breeding area) reveals a decrease in lambda from 0.963 to 0.910. A life table response experiment (LTRE) showed that this decline in lambda was caused mostly by declines in survival of adults. If 1988-1998 demographic rates are maintained, the model predicts a 98% chance of a population of fewer than 25 pairs within 78 years. For this population to recover to a status under which it could be "delisted," a 10% increase in survival of all age classes would be needed.