Politics of National Red List Classifications: Challenging the Reclassification of Araucaria araucana

Previous studies show that conservation actions have prevented extinctions, recovered populations, and reduced declining trends in global biodiversity. However, all studies to date have substantially underestimated the difference conservation action makes because they failed to account fully for what would have happened in the absence thereof. We undertook a scenario-based thought experiment to better quantify the effect conservation actions have had on the extinction risk of the world's 235 recognized ungulate species. We did so by comparing species' observed conservation status in 2008 with their estimated status under counterfactual scenarios in which conservation efforts ceased in 1996. We estimated that without conservation at least 148 species would have deteriorated by one International Union for Conservation of Nature (IUCN) Red List category, including 6 species that now would be listed as extinct or extinct in the wild. The overall decline in the conservation status of ungulates would have been nearly 8 times worse than observed. This trend would have been greater still if not for conservation on private lands. While some species have benefited from highly targeted interventions, such as reintroduction, most benefited collaterally from conservation such as habitat protection. We found that the difference conservation action makes to the conservation status of the world's ungulate species is likely to be higher than previously estimated. Increased, and sustained, investment could help achieve further improvements.

Stopping declines in biodiversity is critically important, but it is only a first step toward achieving more ambitious conservation goals. The absence of an objective and practical definition of species recovery that is applicable across taxonomic groups leads to inconsistent targets in recovery plans and frustrates reporting and maximization of conservation impact. We devised a framework for comprehensively assessing species recovery and conservation success. We propose a definition of a fully recovered species that emphasizes viability, ecological functionality, and representation; and use counterfactual approaches to quantify degree of recovery. This allowed us to calculate a set of 4 conservation metrics that demonstrate impacts of conservation efforts to date (conservation legacy); identify dependence of a species on conservation actions (conservation dependence); quantify expected gains resulting from conservation action in the medium term (conservation gain); and specify requirements to achieve maximum plausible recovery over the long term (recovery potential). These metrics can incentivize the establishment and achievement of ambitious conservation targets. We illustrate their use by applying the framework to a vertebrate, an invertebrate, and a woody and an herbaceous plant. Our approach is a preliminary framework for an International Union for Conservation of Nature (IUCN) Green List of Species, which was mandated by a resolution of IUCN members in 2012. Although there are several challenges in applying our proposed framework to a wide range of species, we believe its further development, implementation, and integration with the IUCN Red List of Threatened Species will help catalyze a positive and ambitious vision for conservation that will drive sustained conservation action.

Abstractxxxxxx.

In the face of biodiversity loss worldwide, it is paramount to quantify species' extinction risk to guide conservation efforts. The International Union for the Conservation of Nature (IUCN)'s Red List is considered the global standard for evaluating extinction risks. IUCN criteria also inform national extinction risk assessments. Bayesian models, including the state‐of‐the‐art JARA (‘Just Another Red List Assessment’) tool, deliver probabilistic statements about species falling into extinction risk categories, thereby enabling characterisation and communication of uncertainty in extinction risk assessments. We coupled the state‐of‐the‐art VAST (‘Vector Autoregressive Spatio‐Temporal’) modelling tool and JARA, for better informed Red List assessments of marine fishes. In this framework, VAST is fitted to scientific survey catch rate data to provide indices to JARA whose uncertainty is propagated to JARA outcomes suggesting extinction risk categories (under the population reduction criterion). In addition, VAST delivers a valuable habitat assessment to better understand what may be driving extinction risk in the study region. Here, we demonstrate the coupled VAST‐JARA modelling framework by applying it to five contrasting North Sea species, with or without a quantitative stock assessment and with different conservation statuses according to the latest global Red List assessments. The North Sea application coupled with previous assessments and studies suggest that, among the three elasmobranchs, starry ray is in most need of urgent research (and conservation actions where appropriate), followed by spurdog, while lesser‐spotted dogfish is increasing in biomass. Moreover, both the VAST‐JARA modelling framework and previous research indicate that, while European plaice is not of conservation concern, cod has likely met the IUCN criteria for being listed as Endangered recently. Synthesis and applications. The predictions of the VAST‐JARA modelling framework for North Sea species, including JARA output and VAST habitat assessment, constitute valuable supporting information to make interpretations based on Red List guidelines, which will help decision‐makers in their next North Sea Red List assessment. We foresee applications of the modelling framework to assist Red List assessments of numerous marine fishes worldwide. Our modelling framework has many potential advantageous uses, including informing resource management about climate change impacts on species' extinction risks.

Comparative lists of species’ extinction risk are increasingly being used to prioritise conservation resources. Extinction risk is most rigorously assessed using quantitative data on species’ population trajectories, but in the absence of such data, assessments often rely on qualitative estimates based on expert opinion of species abundances, distributions and threats. For example, one-third of coral species are classified as threatened and another third as near threatened on the IUCN Red List, despite a lack of data at the population level for the vast majority of species. Since many taxa show a strong correlation between species traits and extinction risk, an alternate approach is to identify traits associated with extinction in other groups and apply them to the taxon of interest. Here, we examine whether life-history traits associated with stress tolerance, fecundity and habitat specialisation are correlated with Red List conservation status in reef corals. We found no relationship between conservation status and life-history traits, suggesting that either traits identified as important predictors of extinction risk in other taxa are not important in corals, or that conservation status does not accurately reflect species’ relative extinction risk. Therefore, using global-scale extinction risk assessments to inform conservation of coral reefs presents a high risk of ‘silent extinctions’ of undescribed species. We argue that the conservation status for the vast majority of coral species should be ‘data deficient’ and is likely to remain so for the foreseeable future, and that the status and trends of coral populations can only be reliably assessed at relatively small scales.

Biodiversity indices often combine data from different species when used in monitoring programs. Heuristic properties can suggest preferred indices, but we lack objective ways to discriminate between indices with similar heuristics. Biodiversity indices can be evaluated by determining how well they reflect management objectives that a monitoring program aims to support. For example, the Convention on Biological Diversity requires reporting about extinction rates, so simple indices that reflect extinction risk would be valuable. We developed 3 biodiversity indices that are based on simple models of population viability that relate extinction risk to abundance. We based the first index on the geometric mean abundance of species and the second on a more general power mean. In a third index, we integrated the geometric mean abundance and trend. These indices require the same data as previous indices, but they also relate directly to extinction risk. Field data for butterflies and woodland plants and experimental studies of protozoan communities show that the indices correlate with local extinction rates. Applying the index based on the geometric mean to global data on changes in avian abundance suggested that the average extinction probability of birds has increased approximately 1% from 1970 to 2009.Conectando Índices para el Monitoreo de la Biodiversidad con la Teoría de Riesgo de ExtinciónResumenLos índices de biodiversidad combinan frecuentemente los datos de diferentes especies cuando se usan en los programas de monitoreo. Las propiedades heurísticas pueden sugerir índices preferidos, pero carecemos de medios objetivos para discriminar a los índices con propiedades heurísticas similares. Los índices de biodiversidad pueden evaluarse al determinar qué tan bien reflejan los objetivos de manejo que un programa de monitoreo busca apoyar. Por ejemplo, la Convención sobre la Diversidad Biológica requiere reportar las tasas de extinción, así que los índices que reflejan el riesgo de extinción serían valiosos. Desarrollamos 3 índices de biodiversidad que se basan en modelos sencillos de viabilidad de población y que relacionan el riesgo de extinción con la abundancia. Basamos el primer índice en la media geométrica de la abundancia de especies, y el segundo en una media de poder más general. En el tercer índice integramos la media geométrica y la tendencia. Estos índices requieren los mismos datos que índices previos, pero también se relacionan directamente con el riesgo de extinción. La información de campo sobre mariposas y plantas de bosque, y los estudios experimentales de comunidades protozoarias, muestran que los índices se correlacionan con las tasas locales de extinción. Al aplicar el índice basado en la media geométrica sobre los datos globales de los cambios en la abundancia de aves, sugirió que la probabilidad de extinción promedio de aves ha incrementado aproximadamente 1% desde 1970 hasta 2009.Palabras ClaveÍndice de biodiversidad, media geométrica, medida de la biodiversidad, riesgo de extinción

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

Groupers are highly susceptible to human‐induced impacts, making them one of the most threatened fish families globally. Extinction risk assessments are important in endangered threatened species management, however the most comprehensive—the International Union for Conservation of Nature (IUCN) Red List—cannot classify approximately one‐third of grouper species due to data deficiency. We used an ordinal analytical approach to model relationships between species‐level traits and extinction risk categories. We found that larger species and those with shallower maximum depths and smaller geographic ranges had higher extinction risk. Using our best fitting model, we classified data deficient grouper species into IUCN's extinction risk categories based on traits. Most of these species were predicted to be of least concern. However, 12% were predicted to be endangered or vulnerable, suggesting that they may be of conservation interest. Importantly, we provide a quantitative method for overcoming data gaps that can be applied to conservation of other species.

Understanding the conservation status of species is important for prioritizing the allocation of resources to redress or reduce biodiversity loss. Regional organizations that manage threats to the marine biodiversity of the Caribbean and Gulf of Mexico seek to delineate conservation priorities. This process can be usefully informed by extinction risk assessments conducted under the International Union for Conservation of Nature (IUCN) Red List criteria: a widely used, objective method to communicate species‐specific conservation needs. Prior to the recent Red List initiatives summarized in this study, the conservation status was known for just one‐quarter of the 1360 Greater Caribbean marine bony shorefishes. During 10 Red List workshops, experts applied data on species' distributions, populations, habitats, and threats in order to assign an extinction risk category to nearly 1000 shorefishes that range in the Greater Caribbean. As conservation is mostly implemented at national and local levels, two more workshops assessed the Gulf of Mexico populations of 940 shorefishes using the regional Red List guidelines. About 5% of these shorefishes are globally or regionally threatened, including 6% of Greater Caribbean endemics and 26% of Gulf endemics. About 9% of the species are Data Deficient. Species‐richness analyses show that the highest numbers of threatened species endemic to the Greater Caribbean are found in Belize, Panama, and the Cayman Islands. The most pervasive threats to the threatened and Near Threatened species are overexploitation, habitat degradation, and predation by the invasive lionfish. Half of the threatened species are experiencing multiple threats that are likely to amplify extinction risk. Recommended actions, in addition to conducting diversity surveys in lesser explored areas, include improving fishery management, reducing habitat degradation, and controlling lionfish populations.

The current rapid loss of biodiversity globally calls for improved tools to predict conservation status. Conservation status varies among taxa and is influenced by intrinsic species’ traits and extrinsic factors. Among these predictors, the most consistently recognized and widely available is geographic range area. However, ranges of equal area can have diverse spatial configurations that reflect variation in threatening processes and species’ characteristics (e.g. dispersal ability), and can affect local and regional population dynamics. The aim of this study is to assess if and how the spatial configuration of a species’ range relates to its conservation status. We obtained range maps and two descriptors of conservation status: extinction risk and population trend, from the IUCN for 11 052 species of amphibians, non‐marine birds and terrestrial mammals distributed across the World. We characterized spatial configuration using descriptors of shape and fragmentation (fragment number and size heterogeneity) and used regression analysis to evaluate their role in explaining current extinction risk and population trend. The most important predictor of conservation status was range area, but our analyses also identified shape and fragmentation as valuable predictors. We detected complex relationships, revealed by multiple interaction terms, e.g. more circular shapes were negatively correlated with population trend, and heterogeneity was positively correlated with extinction risk for small range areas but negatively for bigger ranges. Considering descriptors of spatial configuration beyond size improves our understanding of conservation status among vertebrates. The metrics we propose are relatively easy to define (although values can be sensitive to data quality), and unlike other correlates of status, like species’ traits, are readily available for many species (all of those with range maps). We argue that considering spatial configuration predictors is a straightforward way to improve our capacity to predict conservation status and thus, can be useful to promote more effective conservation.

Recently 64 species in Korea have been ranked as rare and endangered taxa by the Ministry of Environment using two categories, I and II. The original threat categories produced by the Ministry of Environment were developed to provide a standard for specifying animals and plants in danger of extinction and has been influential sources of information used in species conservation in Korea. However, the criteria by Ministry of Environment were applied to the whole taxa only by regional boundaries, especially in South Korea, rather than international context, and it also lacked an explicit framework that was necessary to ensure repeatability among taxa because of the absence of quantitative criteria to measure the likelihood of extinction. The World Conservation Union (IUCN) has developed quantitative criteria for assessing the conservation status of species. The threatened species categories, the 2000 IUCN Red List, proposed by SSC (Species Survival Commission) of IUCN have become widely recognized internationally. Details of threatened Korean plants, identified by applying the IUCN threat categories and definitions, were listed and analyzed. The number of species identified as threatened was only 34 out of 64 taxa (48.4%), while the rest of taxa were rejected from the original lists. Many of the species (51.6%, 33 taxa) excluded from the original list proposed by Ministry of Environment do not qualify as Critically Endangered, Endangered or Vulnerable because these taxa were widely distributed either in Japan or in China/far eastern Russia and there is no evidence of substantial decline in these countries. An evaluation of taxa in Korea has been carried out only based on subjective views and qualitative data, rather than quantitative scientific data, such as rates of decline, distribution range size, population size, and risk of extinction. Therefore, the national lists undermine the credibility of threatened species lists and invite misuse, which have been raised by other cases, qualitative estimate of risk, political influence, uneven taxonomic or geographical coverage. The increasing emphasis on international responsibilities means that global scale is becoming more significant. The current listings by Environment of Ministry of Korea should be challenged, and the government should seek to facilitate the resolution of disagreements. Especially the list should be flexible enough to handle uncertainty and also incorporates detailed, quantitative data. It is suggested that the highest priorities for the Red List should be given to endemic species in Korea first. After setting up the list of endemic species to Korea, quantitative data on population size and structure, distributional range, rated of decline, and habitat fragmentation should be collected as one of long term projects for the Red list categories. Transparency and accountability are the most important key factors. Also, species assessors are named and data sources referenced are required for the future objective evaluations on Korean plant taxa.

The influence of uncertainty on conservation assessments: Australian frogs as a case study

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

Aim To determine whether life‐history characters that affect population persistence (e.g. habit and life span) and those that influence reproductive success (e.g. sexual system and fruit type) are non‐randomly correlated with extinction risk (i.e. threat category) in the Australian flora (c. 19,000 species, of which c. 14% is threatened). To identify patterns that present useful conservation directions. To understand patterns of extinction risk in the Australian flora at a broad scale.Location Continental Australia.Methods A country‐wide exploration of four life‐history characters in the Australian flora (n = 18,822 species) was undertaken using reference texts, expert opinion, herbarium records and field work. For each character and threat‐category combination, a G‐test (using a log‐linear model) was performed to test the null hypothesis that the two factors were independent in their effects on count. A generalized linear model (GLM) with a logit link and binomial error distribution was constructed with the proportion of taxa in each extinction risk category as the response variable and the habit, sex and fruit‐type characters as explanatory terms. In a separate approach, we investigated patterns across the threat categories of non‐endangered extant, endangered, and extinct using a multinomial model. We examined whether or not species‐poor genera were more likely to contain threatened or extinct species than species‐rich genera. A GLM with a binomial error distribution and logit link function was constructed to obtain a weighted regression on the proportion of species listed as extinct or endangered within a genus versus the log of the size of the genus. We also used a supertree analysis and character tracing to investigate the role of phylogeny on extinction risk.Results We found that the Australian flora is primarily composed of bisexual shrubs with dry‐dehiscent fruits. Dioecious breeding systems (separate female and male flowers on separate plants) in many floras are the predominant unisexual system, but in Australia there are unexpectedly high levels of monoecy (separate female and male flowers on the same plant). Within the extinct data set of 31 species we detected a significant departure from that expected for habit but not for life span, sexual system or fruit type. There are significantly fewer trees on the extinct list than expected. This may reflect the greater resilience of trees than of other growth habits to extinction processes as well as the observation time‐frame. Within the endangered data set of 450 species we found significant differences in the representation of the observed characters from that expected within sex systems and fruit types. We show that, depending on the life form, unisexual breeding systems can be significantly and positively associated with endangered species compared with non‐threatened species. For example, there are more monoecious species than expected by chance among the tree species listed as endangered but fewer among the herbaceous life forms. Threat category was found to be non‐randomly clustered in some clades.Main conclusions Life‐history characters in certain combinations are predictive of extinction risk. Phylogeny is also an important component of extinction risk. We suggest that specific life‐history characters could be used for conservation planning and as an early warning sign for detecting vulnerability in lists of species.

AimThe current assessment of extinction risk in reef corals by the International Union for Conservation of Nature (IUCN) has been criticized, because coral life‐history traits associated with resilience are not reflected in the conservation status. We aimed to carry out a quantitative assessment of the link between reef coral traits and species extinction risk informed by extinctions of reef corals observed in the fossil record.LocationGlobal.Time periodPlio‐Pleistocene and present day.Major taxa studiedScleractinian reef corals.MethodsWe used morphological traits, phylogenetic information and evidence of extinction during the Plio‐Pleistocene to predict the extinction risk of contemporary reef corals. Our model was trained using 138 Caribbean fossil coral species and an automatic machine learning algorithm. We then used this model to predict the extinction risk of 674 modern coral species.ResultsModel validation confirmed 77% accuracy in predicting extinction risk of fossil corals. Extinction risk predicted by our model showed a near‐random (57%) match with the IUCN conservation status. Our model also suggested that corals in the Least Concern or Near Threatened categories might be at higher risk of extinction than currently believed.Main conclusionsMorphological traits of fossil corals linked to their extinction risk in the Plio‐Pleistocene Caribbean Sea are known to reflect the vulnerability of extant corals. However, the results from our fossil‐calibrated model do not match the IUCN assessment of reef corals, with increased overall extinction risk. This does not necessarily indicate near‐future extinction risk, because fossil extinctions are spread over thousands of years. However, we show the applicability of using fossil data to inform the extinction risk of modern corals and recommend that future assessments of extinction risk of reef corals should consider incorporating the relationship between morphological traits and resilience, calibrated by fossil data, to maximize the utility of the extinction risk assessment.