Global protected areas seem insufficient to safeguard half of the world's mammals from human-induced extinction.

Protected areas (PAs) are a cornerstone of global conservation and central to international plans to minimize global extinctions. During the coming century, global ecosystem destruction and fragmentation associated with increased human population and economic activity could make the long-term survival of most terrestrial vertebrates even more dependent on PAs. However, the capacity of the current global PA network to sustain species for the long term is unknown. Here, we explore this question for all nonvolant terrestrial mammals for which we found sufficient data, ∼4,000 species. We first estimate the potential population size of each such mammal species in each PA and then use three different criteria to estimate if solely the current global network of PAs might be sufficient for their long-term survival. Our analyses suggest that current PAs may fail to provide robust protection for about half the species analyzed, including most species currently listed as threatened with extinction and a third of species not currently listed as threatened. Hundreds of mammal species appear to have no viable protected populations. Underprotected species were found across all body sizes, taxonomic groups, and geographic regions. Large-bodied mammals, endemic species, and those in high-biodiversity tropical regions were particularly poorly protected by existing PAs. As new international biodiversity targets are formulated, our results suggest that the global network of PAs must be greatly expanded and most importantly that PAs must be located in diverse regions that encompass species not currently protected and must be large enough to ensure that protected species can persist for the long term.

Methodological artefacts cause counter-intuitive evolutionary conclusions in a simulation study.

In their simulation study, Garcia-Costoya et al. (2023) conclude that evolutionary constraints might aid populations facing climate change. However, we are concerned that this conclusion is largely a consequence of the simulated temperature variation being too small, and, most importantly, that uneven limitations to standing variation disadvantage unconstrained populations.

Response to von Schmalensee et al.

Von Schmalensee et al. present two concerns about our study. While the first stems from a general disagreement about our simulation methodology, the second is a useful observation of a modelling choice we made that affected simulation outcomes, but in ways that do not invalidate our original conclusions.

Environmental complexity mitigates the demographic impact of sexual selection.

Sexual selection and the evolution of costly mating strategies can negatively impact population viability and adaptive potential. While laboratory studies have documented outcomes stemming from these processes, recent observations suggest that the demographic impact of sexual selection is contingent on the environment and therefore may have been overestimated in simple laboratory settings. Here we find support for this claim. We exposed copies of beetle populations, previously evolved with or without sexual selection, to a 10-generation heatwave while maintaining half of them in a simple environment and the other half in a complex environment. Populations with an evolutionary history of sexual selection maintained larger sizes and more stable growth rates in complex (relative to simple) environments, an effect not seen in populations evolved without sexual selection. These results have implications for evolutionary forecasting and suggest that the negative demographic impact of sexually selected mating strategies might be low in natural populations.

Extinction risk predictions for the world's flowering plants to support their conservation.

More than 70% of all vascular plants lack conservation status assessments. We aimed to address this shortfall in knowledge of species extinction risk by using the World Checklist of Vascular Plants to generate the first comprehensive set of predictions for a large clade: angiosperms (flowering plants, c. 330 000 species). We used Bayesian Additive Regression Trees (BART) to predict the extinction risk of all angiosperms using predictors relating to range size, human footprint, climate, and evolutionary history and applied a novel approach to estimate uncertainty of individual species-level predictions. From our model predictions, we estimate 45.1% of angiosperm species are potentially threatened with a lower bound of 44.5% and upper bound of 45.7%. Our species-level predictions, with associated uncertainty estimates, do not replace full global, or regional Red List assessments, but can be used to prioritise predicted threatened species for full Red List assessment and fast-track predicted non-threatened species for Least Concern assessments. Our predictions and uncertainty estimates can also guide fieldwork, inform systematic conservation planning and support global plant conservation efforts and targets.

Conflicts and opportunities for commercial tree plantation expansion and biodiversity restoration across Brazil.

Substantial global restoration commitments are occurring alongside a rapid expansion in land-hungry tropical commodities, including to supply increasing demand for wood products. Future commercial tree plantations may deliver high timber yields, shrinking the footprint of production forestry, but there is an as-yet unquantified risk that plantations may expand into priority restoration areas, with marked environmental costs. Focusing on Brazil-a country of exceptional restoration importance and one of the largest tropical timber producers-we use random forest models and information on the economic, social, and spatial drivers of historic commercial tree plantation expansion to estimate and map the probability of future monoculture tree plantation expansion between 2020 and 2030. We then evaluate potential plantation-restoration conflicts and opportunities at national and biome-scales and under different future production and restoration pathways. Our simulations show that of 2.8 Mha of future plantation expansion (equivalent to plantation expansion 2010-2020), ~78,000 ha (3%) is forecast to occur in the top 1% of restoration priority areas for terrestrial vertebrates, with ~547,500 ha (20%) and ~1,300,000 ha (46%) in the top 10% and 30% of priority areas, respectively. Just ~459,000 ha (16%) of expansion is forecast within low-restoration areas (bottom 30% restoration priorities), and the first 1 Mha of plantation expansion is likely to have disproportionate impacts, with potential restoration-plantation overlap starkest in the Atlantic Forest but prominent in the Pampas and Cerrado as well. Our findings suggest that robust, coherent land-use policies must be deployed to ensure that significant trade-offs between restoration and production objectives are navigated, and that commodity expansion does not undermine the most tractable conservation gains under emerging global restoration agendas. They also highlight the potentially significant role an engaged forestry sector could play in improving biodiversity outcomes in restoration projects in Brazil, and presumably elsewhere.

Climate change vulnerability of Arctic char across Scandinavia.

Climate change is anticipated to cause species to shift their ranges upward and poleward, yet space for tracking suitable habitat conditions may be limited for range-restricted species at the highest elevations and latitudes of the globe. Consequently, range-restricted species inhabiting Arctic freshwater ecosystems, where global warming is most pronounced, face the challenge of coping with changing abiotic and biotic conditions or risk extinction. Here, we use an extensive fish community and environmental dataset for 1762 lakes sampled across Scandinavia (mid-1990s) to evaluate the climate vulnerability of Arctic char (Salvelinus alpinus), the world's most cold-adapted and northernly distributed freshwater fish. Machine learning models show that abiotic and biotic factors strongly predict the occurrence of Arctic char across the region with an overall accuracy of 89 percent. Arctic char is less likely to occur in lakes with warm summer temperatures, high dissolved organic carbon levels (i.e., browning), and presence of northern pike (Esox lucius). Importantly, climate warming impacts are moderated by habitat (i.e., lake area) and amplified by the presence of competitors and/or predators (i.e., northern pike). Climate warming projections under the RCP8.5 emission scenario indicate that 81% of extant populations are at high risk of extirpation by 2080. Highly vulnerable populations occur across their range, particularly near the southern range limit and at lower elevations, with potential refugia found in some mountainous and coastal regions. Our findings highlight that range shifts may give way to range contractions for this cold-water specialist, indicating the need for pro-active conservation and mitigation efforts to avoid the loss of Arctic freshwater biodiversity.

Modelling the probability of meeting IUCN Red List criteria to support reassessments.

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.

Climate warming and sea turtle sex ratios across the globe.

Climate warming and the feminization of populations due to temperature-dependent sex determination may threaten sea turtles with extinction. To identify sites of heightened risk, we examined sex ratio data and patterns of climate change over multiple decades for 64 nesting sites spread across the globe. Over the last 62 years the mean change in air temperature was 0.85°C per century (SD = 0.65°C, range = -0.53 to +2.5°C, n = 64 nesting sites). Temperatures increased at 40 of the 64 study sites. Female-skewed hatchling or juvenile sex ratios occurred at 57 of the 64 sites, with skews >90% female at 17 sites. We did not uncover a relationship between the extent of warming and sex ratio (r62 = -0.03, p = .802, n = 64 nesting sites). Hence, our results suggest that female-hatchling sex ratio skews are not simply a consequence of recent warming but have likely persisted at some sites for many decades. So other factors aside from recent warming must drive these variations in sex ratios across nesting sites, such as variations in nesting behaviour (e.g. nest depth), substrate (e.g. sand albedo), shading available and rainfall patterns. While overall across sites recent warming is not linked to hatchling sex ratio, at some sites there is both is a high female skew and high warming, such as Raine Island (Australia; 99% female green turtles; 1.27°C warming per century), nesting beaches in Cyprus (97.1% female green turtles; 1.68°C warming per century) and in the Dutch Caribbean (St Eustatius; 91.5% female leatherback turtles; 1.15°C warming per century). These may be among the first sites where management intervention is needed to increase male production. Continued monitoring of sand temperatures and sex ratios are recommended to help identify when high incubation temperatures threaten population viability.

Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians.

Assessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land-use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species' range size and spatial configuration of the range, biological traits, climate change, and land-use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models' uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up-to-date IUCN RL.

Uso del análisis comparativo del riesgo de extinción para priorizar la reevaluación de los anfibios en la Lista Roja de la UICN Resumen El análisis del riesgo de extinción de una especie con base en la Lista Roja (LR) de la Unión Internacional para la Conservación de la Naturaleza (UICN) es clave para guiar las políticas de conservación y reducir la pérdida de la biodiversidad. Sin embargo, este proceso demanda recursos y requiere de actualizaciones continuas, lo que se complica conforme se añaden especies nuevas a la LR. Los métodos automáticos, como los análisis comparativos usados para predecir la categoría de la especie en la LR, pueden ser una alternativa eficiente para mantener actualizados los análisis. Usamos a los anfibios como grupo de estudio para predecir cuáles especies tienen mayor probabilidad de cambiar de categoría en la LR y que, por lo tanto, se debería priorizar su reevaluación. Usamos las características biológicas de la especie, las variables ambientales e indicadores climáticos y del cambio de uso de suelo como predictores de la categoría en la LR. Elaboramos una predicción de ensamble de la categoría en la LR de la UICN para cada especie mediante la combinación de cuatro algoritmos diferentes: modelos de vínculo acumulativo, menor número de cuadros filogenéticos generalizados, bosques aleatorios y redes neurales. Con la comparación entre las categorías de la LR y la predicción de ensamble y con considerar la incertidumbre entre los algoritmos identificamos especies que deberían ser prioridad para futuras reevaluaciones con base en el desfase entre los valores predichos y los observados. Las variables de predicción más importantes entre los modelos fueron el tamaño de la distribución de la especie y su configuración espacial, las características biológicas, el cambio climático y el cambio de uso de suelo. Comparamos nuestra propuesta de índice de priorización y los cambios predichos en la LR con las reevaluaciones independientes de la LR de la UICN y descubrimos un buen desempeño tanto para la priorización como para la direccionalidad predicha de los cambios en las categorías de la LR. El modelo de ensamble de la categoría de la LR esa una herramienta prometedora para priorizar la reevaluación de las especies a la vez que considera la incertidumbre del modelo. Esta estrategia puede generalizarse para aplicarse a todos los taxones de la LR de la UICN y a los análisis regionales y nacionales. También podría mejorar la asignación de los recursos humanos y económicos limitados disponibles para mantener actualizada la LR de la UICN.

A standard approach for including climate change responses in IUCN Red List assessments.

The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.

Una estrategia estándar para incluir las respuestas al cambio climático en las evaluaciones de la Lista Roja de la UICN Resumen La Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) es una herramienta central para el monitoreo del riesgo de extinción e influye sobre las acciones y políticas para la biodiversidad. Para que esta herramienta sea efectiva, es crucial que tenga en cuenta de manera regular cada factor de extinción. El cambio climático se está convirtiendo rápidamente en un factor de extinción importante, pero considerar información sobre este factor todavía es un reto para la UICN. Se pueden usar varios métodos para predecir la declinación de una especie en el futuro, pero generalmente fallan en proporcionar estimaciones de los síntomas del peligro usados por la UICN. Diseñamos un método estandarizado para medir el impacto del cambio climático en términos del cambio en la calidad del hábitat para informar el criterio A3 sobre la reducción futura de las poblaciones. Usamos a los tetrápodos terrestres no voladores como estudio de caso para medir este impacto como la diferencia entre el nicho climático actual y futuro de las especies, definido con base en las variables bioclimáticas actuales y futuras con algoritmos de modelos alternativos, escenarios de dispersión y emisión y modelos climáticos. Nuestros modelos identificaron 171 especies (13% de las especies analizadas) para las que su categoría actual en la lista roja podría empeorar bajo el criterio A3 si no logran dispersarse más allá de su distribución actual en el futuro. Las categorías para 14 especies (1.5%) podrían empeorar si es posible la dispersión máxima. Aunque realizamos una simulación y no una evaluación formal para listas rojas, nuestros resultados sugieren que considerar los impactos del cambio climático podría reducir la clasificación incorrecta y fortalecer la coherencia y exhaustividad de las evaluaciones de la Lista Roja de la UICN.

Is the long-tailed macaque at risk of extinction?

We review the evidence that long-tailed macaques are at risk of extinction and find that papers supporting this argument present no data supporting a hypothesized decline in abundance. These papers contain numerous misrepresentations of the published literature. Long-tailed macaques thrive in human-altered habitats, are listed by the International Union for the Conservation of Nature as an invasive species of concern, and have shown the ability to increase by 7%-10% per year from low numbers, making the probability of extinction very low.

Deep time extinction of largest insular ant predators and the first fossil Neoponera (Formicidae: Ponerinae) from Miocene age Dominican amber.

BACKGROUND: Ponerine ants are almost exclusively predatory and comprise many of the largest known ant species. Within this clade, the genus Neoponera is among the most conspicuous Neotropical predators. We describe the first fossil member of this lineage: a worker preserved in Miocene-age Dominican amber from Hispaniola. RESULTS: Neoponera vejestoria sp. nov. demonstrates a clear case of local extinction-there are no known extant Neoponera species in the Greater Antilles. The species is attributable to an extant and well-defined species group in the genus, which suggests the group is older than previously estimated. Through CT scan reconstruction and linear morphometrics, we reconstruct the morphospace of extant and fossil ants to evaluate the history and evolution of predatory taxa in this island system. CONCLUSIONS: The fossil attests to a shift in insular ecological community structure since the Miocene. The largest predatory taxa have undergone extinction on the island, but their extant relatives persist throughout the Neotropics. Neoponera vejestoria sp. nov. is larger than all other predatory ant workers known from Hispaniola, extant or extinct. Our results empirically demonstrate the loss of a functional niche associated with body size, which is a trait long hypothesized to be related to extinction risk.

Scale of population synchrony confirms macroecological estimates of minimum viable range size.

Global ecosystems are facing a deepening biodiversity crisis, necessitating robust approaches to quantifying species extinction risk. The lower limit of the macroecological relationship between species range and body size has long been hypothesized as an estimate of the relationship between the minimum viable range size (MVRS) needed for species persistence and the organismal traits that affect space and resource requirements. Here, we perform the first explicit test of this assumption by confronting the MVRS predicted by the range-body size relationship with an independent estimate based on the scale of synchrony in abundance among spatially separated populations of riverine fish. We provide clear evidence of a positive relationship between the scale of synchrony and species body size, and strong support for the MVRS set by the lower limit of the range-body size macroecological relationship. This MVRS may help prioritize first evaluations for unassessed or data-deficient taxa in global conservation assessments.

Evolutionary constraints mediate extinction risk under climate change.

Mounting evidence suggests that rapid evolutionary adaptation may rescue some organisms from the impacts of climate change. However, evolutionary constraints might hinder this process, especially when different aspects of environmental change generate antagonistic selection on genetically correlated traits. Here, we use individual-based simulations to explore how genetic correlations underlying the thermal physiology of ectotherms might influence their responses to the two major components of climate change-increases in mean temperature and thermal variability. We found that genetic correlations can influence population dynamics under climate change, with declines in population size varying three-fold depending on the type of correlation present. Surprisingly, populations whose thermal performance curves were constrained by genetic correlations often declined less rapidly than unconstrained populations. Our results suggest that accurate forecasts of the impact of climate change on ectotherms will require an understanding of the genetic architecture of the traits under selection.

Explaining the primate extinction crisis: predictors of extinction risk and active threats.

Explaining why some species are disproportionately impacted by the extinction crisis is of critical importance for conservation biology as a science and for proactively protecting species that are likely to become threatened in the future. Using the most current data on threat status, population trends, and threat types for 446 primate species, we advance previous research on the determinants of extinction risk by including a wider array of phenotypic traits as predictors, filling gaps in these trait data using multiple imputation, and investigating the mechanisms that connect organismal traits to extinction risk. Our Bayesian phylogenetically controlled analyses reveal that insular species exhibit higher threat status, while those that are more omnivorous and live in larger groups have lower threat status. The same traits are not linked to risk when repeating our analyses with older IUCN data, which may suggest that the traits influencing species risk are changing as anthropogenic effects continue to transform natural landscapes. We also show that non-insular, larger-bodied, and arboreal species are more susceptible to key threats responsible for primate population declines. Collectively, these results provide new insights to the determinants of primate extinction and identify the mechanisms (i.e. threats) that link traits to extinction risk.

Heat over heritability: Increasing body size in response to global warming is not stabilized by genetic effects in Bechstein's bats.

How well populations can cope with global warming will often depend on the evolutionary potential and plasticity of their temperature-sensitive, fitness-relevant traits. In Bechstein's bats (Myotis bechsteinii), body size has increased over the last decades in response to warmer summers. If this trend continues it may threaten populations as larger females exhibit higher mortality. To assess the evolutionary potential of body size, we applied a Bayesian 'animal model' to estimate additive genetic variance, heritability and evolvability of body size, based on a 25-year pedigree of 332 wild females. Both heritability and additive genetic variance were reduced in hot summers compared to average and cold summers, while evolvability of body size was generally low. This suggests that the observed increase in body size was mostly driven by phenotypic plasticity. Thus, if warm summers continue to become more frequent, body size likely increases further and the resulting fitness loss could threaten populations.

Anthropogenic predictors of varying Holocene occurrence for Europe's large mammal fauna.

Understanding how species respond to different anthropogenic pressures is essential for conservation planning. The archaeological record has great potential to inform extinction risk assessment by providing evidence on past human-caused biodiversity loss, but identifying specific drivers of past declines from environmental archives has proved challenging. We used 17 684 Holocene zooarchaeological records for 15 European large mammal species together with data on past environmental conditions and anthropogenic activities across Europe, to assess the ability of environmental archives to determine the relative importance of different human pressures in shaping faunal distributions through time. Site occupancy probability showed differing significant relationships with environmental covariates for all species, and nine species also showed significant relationships with anthropogenic covariates (human population density, % cropland, % grazing land). Across-species differences in negative relationships with covariates provide ecological insights for understanding extinction dynamics: some mammals (red deer, aurochs, wolf, wildcat, lynx, pine marten and beech marten) were more vulnerable to past human-environmental interactions, and differing single and synergistic anthropogenic factors influenced likelihood of past occurrence across species. Our results provide new evidence for pre-industrial population fragmentation and depletion in European mammals, and demonstrate the usefulness of historical baselines for understanding species' varying long-term sensitivity to multiple threats.

Species-specific traits affect bird species' susceptibility to global change.

The current ecological crisis has risen extinction rates to similar levels of ancient mass extinctions. However, it seems to not be acting uniformly across all species but affecting species differentially. This suggests that species' susceptibility to the extinction process is mediated by specific traits. Since understanding this response mechanism at large scales will benefit conservation effort around the world, we used the IUCN global threat status and population trends of 8281 extant bird species as proxies of the extinction risk to identify the species-specific traits affecting their susceptibility to extinction within the biogeographic regions and at the global scale. Using linear mixed effect models and multinomial models, we related the global threat status and the population trends with the following traits: migratory strategy, habitat and diet specialization, body size, and generation length. According to our results and independently of the proxy used, more vulnerable species are sedentary and have larger body size, longer generation time, and higher degree of habitat specialization. These relationships apply globally and show little variation across biogeographic regions. We suggest that such concordant patterns might be caused either by a widespread occurrence of the same threats such as habitat modification or by a uniform capacity of some traits to reflect the impact of different local threats. Regardless of the cause of this pattern, our study identified the traits that affect species' response capability to the current ecological crisis. Conservation effort should focus on the species with trait values indicating the limited response capacity to overcome this crisis.

Quantifying and mapping species threat abatement opportunities to support national target setting.

The successful implementation of the Convention on Biological Diversity's post-2020 Global Biodiversity Framework will rely on effective translation of targets from global to national level and increased engagement across diverse sectors of society. Species conservation targets require policy support measures that can be applied to a diversity of taxonomic groups, that link action targets to outcome goals, and that can be applied to both global and national data sets to account for national context, which the species threat abatement and restoration (STAR) metric does. To test the flexibility of STAR, we applied the metric to vascular plants listed on national red lists of Brazil, Norway, and South Africa. The STAR metric uses data on species' extinction risk, distributions, and threats, which we obtained from national red lists to quantify the contribution that threat abatement and habitat restoration activities could make to reducing species' extinction risk. Across all 3 countries, the greatest opportunity for reducing plant species' extinction risk was from abating threats from agricultural activities, which could reduce species' extinction risk by 54% in Norway, 36% in South Africa, and 29% in Brazil. Species extinction risk could be reduced by a further 21% in South Africa by abating threats from invasive species and by 21% in Brazil by abating threats from urban expansion. Even with different approaches to red-listing among countries, the STAR metric yielded informative results that identified where the greatest conservation gains could be made for species through threat-abatement and restoration activities. Quantifiably linking local taxonomic coverage and data collection to global processes with STAR would allow national target setting to align with global targets and enable state and nonstate actors to measure and report on their potential contributions to species conservation.