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Aim: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert- based informa-tion is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert- based in-formation with detailed empirical evidence. Here, we compared expert- based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individu-als from 49 mammal species.Location: Worldwide.Time period: 1998–2021.Major taxa studied: Forty- nine terrestrial mammal species.Methods: Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habi-tat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS- based habitat suitability measures were in agree-ment with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types.Results: IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively.Main conclusions: We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species in-cluded in this study, it is appropriate to use IUCN habitat suitability data in macro-ecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data. expert opinion, GPS, habitat suitability, habitat type, habitat use, IUCN, mammals, movement, selection ratio, telemetry

Summary Global biodiversity is increasingly threatened by anthropogenic environmental change. While there is mounting evidence that habitat loss is a key threat to biodiversity, global assessments typically ignore additional threats from habitat fragmentation. Here, we present a species-area model that integrates habitat size and connectivity, considering species habitat preference and dispersal capacity, patch size, inter-patch distances, and landscape matrix permeability. We applied the model to predict threats from habitat loss and fragmentation to non-volant mammal diversity across the world’s ecoregions. We predict that, on average, 10 mammal species are committed to extinction due to habitat loss and fragmentation (range 0–86). On average, 9% of loss is due to fragmentation (range 0%–90%). Considering both habitat loss and fragmentation, our model can be used for large-scale explorative assessments to inform and evaluate strategies for minimizing biodiversity loss and for optimizing habitat conservation and restoration.

As a source of emerging infectious diseases, wildlife assemblages (and related spatial patterns) must be quantitatively assessed to help identify high‐risk locations. Previous assessments have largely focussed on the distributions of individual species; however, transmission dynamics are expected to depend on assemblage composition. Moreover, disease–diversity relationships have mainly been studied in the context of species loss, but assemblage composition and disease risk (e.g. infection prevalence in wildlife assemblages) can change without extinction. Based on the predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk through the calculation of the community‐level basic reproductive ratio R0, an index of invasion potential, persistence, and maximum prevalence of a pathogen in a wildlife assemblage. For density‐dependent diseases, we found that, in addition to tropical areas which are commonly viewed as infectious disease hotspots, northern temperate latitudes included high‐risk areas. We also forecasted the effects of climate change and habitat loss from 2015 to 2035. Over this period, many local assemblages showed no net loss of species richness, but the assemblage composition (i.e. the mix of species and their abundances) changed considerably. Simultaneously, most areas experienced a decreased risk of density‐dependent diseases but an increased risk of frequency‐dependent diseases. We further explored the factors driving these changes in disease risk. Our results suggest that biodiversity and changes therein jointly influence disease risk. Understanding these changes and their drivers and ultimately identifying emerging infectious disease hotspots can help health officials prioritize resource distribution., Emerging infectious diseases are serious global threats. Most of these diseases originate from wildlife, particularly mammals, which face an ongoing biodiversity crisis. Using predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk by calculating community‐level R0. High values in temperate European, Asian, and North American locations point to risks beyond the tropics. Forecasted effects of climate change and habitat loss from 2015 to 2035 suggested many mammal assemblages will change considerably in their composition, even without local extinctions. Simultaneously, most areas were predicted to have decreased density‐dependent disease risk but increased frequency‐dependent disease risk.

Although there is mounting evidence that habitat loss is a key driver of biodiversity loss, global assessments typically ignore the additional effects of habitat fragmentation. Here, we assessed the combined effect of habitat loss and fragmentation on non-volant mammal species richness in 804 of the world’s terrestrial ecoregions. To that end we used a species-area model that integrates differences in both habitat suitability and habitat connectivity, accounting for species habitat preference, patch size, inter-patch distances, landscape matrix permeability and species’ dispersal capacity. On average across the ecoregions, 10 mammal species are committed to extinction due to habitat loss and fragmentation combined, up to a maximum of 86. On average, 9% of the estimated species loss is caused by fragmentation, yet this can be up to 90%. Our results imply that comprehensive strategies for meeting international biodiversity targets require not only combatting habitat loss, but also measures to reduce fragmentation.

Schipper, Aafke M. et al., Scenario‐based biodiversity modelling is a powerful approach to evaluate how possible future socio‐economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio‐economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc‐seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area‐weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (−0.02) than the regional rivalry and fossil‐fuelled development scenarios (−0.06 and −0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub‐Saharan Africa. In some scenario‐region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but also focus on reducing or mitigating the impacts of other pressures

Land use and hunting are 2 major pressures on biodiversity in the tropics. Yet, their combined impacts have not been systematically quantified at a large scale. We estimated the effects of both pressures on the distributions of 1884 tropical mammal species by integrating species’ range maps, detailed land-use maps (1992 and 2015), species-specific habitat preference data, and a hunting pressure model. We further identified areas where the combined impacts were greatest (hotspots) and least (coolspots) to determine priority areas for mitigation or prevention of the pressures. Land use was the main driver of reduced distribution of all mammal species considered. Yet, hunting pressure caused additional reductions in large-bodied species’ distributions. Together, land use and hunting reduced distributions of species by 41% (SD 30) on average (year 2015). Overlap between impacts was only 2% on average. Land use contributed more to the loss of distribution (39% on average) than hunting (4% on average). However, hunting reduced the distribution of large mammals by 29% on average; hence, large mammals lost a disproportional amount of area due to the combination of both pressures. Gran Chaco, the Atlantic Forest, and Thailand had high levels of impact across the species (hotspots of area loss). In contrast, the Amazon and Congo Basins, the Guianas, and Borneo had relatively low levels of impact (coolspots of area loss). Overall, hunting pressure and human land use increased from 1992 to 2015 and corresponding losses in distribution increased from 38% to 41% on average across the species. To effectively protect tropical mammals, conservation policies should address both pressures simultaneously because their effects are highly complementary. Our spatially detailed and species-specific results may support future national and global conservation agendas, including the design of post-2020 protected area targets and strategies., El uso de suelo y la caza son dos de las principales presiones ejercidas sobre la biodiversidad de los tropicos. Aun as ´ ´ı, los impactos combinados que generan no han sido cuantificados sistem´aticamente a gran escala. Estimamos los efectos de ambas presiones sobre la distribucion de 1,884 especies de mam ´ ´ıferos tropicales al integrar mapas de distribucion de las especies, mapas detallados del uso de suelo (de 1992 y 2015), datos de ´ preferencia de h´abitat espec´ıficos por especie y un modelo de presion de caza. Identificamos adem ´ ´as las ´areas en donde los impactos combinados eran mayores (puntos calientes) y menores (puntos fr´ıos) para determinar las ´areas prioritarias para la mitigacion o prevenci ´ on de dichas presiones. El uso de suelo fue el principal conductor ´ de la reduccion de la distribuci ´ on para todas las especies de mam ´ ´ıferos que consideramos. Sin embargo, la presion por caza caus ´ o reducciones adicionales en la distribuci ´ on de especies de gran tama ´ no. Juntas, el uso ˜ de suelo y la caza redujeron la distribucion de las especies en un 41% (DS 30) en promedio (a ´ no 2015). El ˜ solapamiento entre los impactos fue, en promedio, solo del 2%. El uso de suelo contribuy ´ o m´ ´as a la perdida ´ de la distribucion (39%, en promedio) que la caza (4%, en promedio). A pesar de esto, en promedio la caza ´ redujo la distribucion de los mam ´ ´ıferos de gran tamano en un 29%; por lo tanto, los grandes mam ˜ ´ıferos perdieron una cantidad desproporcionada de ´area debido a la combinacion de ambas presiones. El Gran Chaco, el Bosque ´ Atl´antico y Tailandia tuvieron niveles altos de impacto en todas las especies (puntos calientes de perdida de ´ ´area). Como contraste, las cuencas del Amazonas y el Congo, las Guayanas y Borneo tuvieron niveles relativamente bajos de impacto (puntos fr´ıos de perdida de ´ ´area). En general, las presiones por caza y uso de suelo incrementaron desde 1992 a 2015 y las correspondientes perdidas de distribuci ´ on incrementaron de un 38% a un 41% en promedio ´ para todas las especies. Para proteger de forma efectiva a los mam´ıferos tropicales, las pol´ıticas de conservacion´ deber´ıan considerar a ambas presiones de manera simult´anea, pues sus efectos son altamente complementarios. Nuestros resultados espacialmente detallados y espec´ıficos para cada especie pueden respaldar las futuras agendas de conservacion nacionales e internacionales, incluyendo el dise ´ no de las estrategias y los objetivos de las ˜ ´areas protegidas para despues de 2020.

Ecological risks (ERs) of pollutants are typically assessed using species sensitivity distributions (SSDs), based on effect concentrations obtained from bioassays with unknown representativeness for field conditions. Alternatively, monitoring data relating breeding success in bird populations to egg concentrations may be used. In this study, we developed a procedure to derive SSDs for birds based on field data of egg concentrations and reproductive success. As an example, we derived field-based SSDs for p,p′-DDE and polychlorinated biphenyls (PCBs) exposure to birds. These SSDs were used to calculate ERs for these two chemicals in the American Great Lakes and the Arctic. First, we obtained field data of p,p′-DDE and PCBs egg concentrations and reproductive success from the literature. Second, these field data were used to fit exposure-response curves along the upper boundary (right margin) of the response’s distribution (95th quantile), also called quantile regression analysis. The upper boundary is used to account for heterogeneity in reproductive success induced by other external factors. Third, the species-specific EC10/50s obtained from the field-based exposure-response curves were used to derive SSDs per chemical. Finally, the SSDs were combined with specific exposure data for both compounds in the two areas to calculate the ER. We found that the ERs of combined exposure to these two chemicals were a factor of 5–35 higher in the Great Lakes compared to Arctic regions. Uncertainty in the species-specific exposure-response curves and related SSDs was mainly caused by the limited number of field exposure-response data for bird species. With sufficient monitoring data, our method can be used to quantify field-based ecological risks for other chemicals, species groups, and regions of interest.

Size spectra are important indicators of biomass distribution, for fundamental understanding as well as for application in management. While many size spectra models have been developed, it is unclear how response to stress varies across models and in comparison to data. In the present study, we therefor collected papers on empirical size spectra in stressed aquatic ecosystems and compared the results to theoretical models’ predictions from literature. A general decrease of the slope, as suggested by most of the studied models, is supported by the data found. The investigated empirical studies revealed a strong trend for the slope: 40 out of 57 studies reported a decrease with stress. Deviations from the linear model increased in 10 out of 20 cases and the intercept became larger in 25 out of 43 cases. The data concerning specific impact drivers is generally consistent and supportive of current expert opinions. Our results support that an integration of deviation from the linear model and intercept in the size spectra models could provide better coupling between modeling and field surveys for some stressors.

Conservation planning and biodiversity assessments need quantitative targets to optimize planning options and assess the adequacy of current species protection. However, targets aiming at persistence require population-specific data, which limit their use in favor of fixed and nonspecific targets, likely leading to unequal distribution of conservation efforts among species. We devised a method to derive equitable population targets; that is, quantitative targets of population size that ensure equal probabilities of persistence across a set of species and that can be easily inferred from species-specific traits. In our method, we used models of population dynamics across a range of life-history traits related to species' body mass to estimate minimum viable population targets. We applied our method to a range of body masses of mammals, from 2 g to 3825 kg. The minimum viable population targets decreased asymptotically with increasing body mass and were on the same order of magnitude as minimum viable population estimates from species- and context-specific studies. Our approach provides a compromise between pragmatic, nonspecific population targets and detailed context-specific estimates of population viability for which only limited data are available. It enables a first estimation of species-specific population targets based on a readily available trait and thus allows setting equitable targets for population persistence in large-scale and multispecies conservation assessments and planning.

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Biodiversity and ecosystem service losses driven by land-use change are expected to intensify as a growing and more affluent lobal population requires more agricultural and forestry products, and teleconnections in the global economy lead to increasingremote environmental responsibility. By combining global biophysical and economic models, we show that, between theyears 2000 and 2011, overall population and economic growth resulted in increasing total impacts on bird diversity and carbonsequestration globally, despite a reduction of land-use impacts per unit of gross domestic product (GDP). The exceptions wereNorth America and Western Europe, where there was a reduction of forestry and agriculture impacts on nature accentuated bythe 2007–2008 financial crisis. Biodiversity losses occurred predominantly in Central and Southern America, Africa and Asiawith international trade an important and growing driver. In 2011, 33% of Central and Southern America and 26% of Africa’sbiodiversity impacts were driven by consumption in other world regions. Overall, cattle farming is the major driver of biodiversityloss, but oil seed production showed the largest increases in biodiversity impacts. Forestry activities exerted the highestimpact on carbon sequestration, and also showed the largest increase in the 2000–2011 period. Our results suggest that toaddress the biodiversity crisis, governments should take an equitable approach recognizing remote responsibility, and promotea shift of economic development towards activities with low biodiversity impacts.

Environmental pollution is an important driver of biodiversity loss. Yet, to date, the effects of chemical exposure on wildlife populations have been quantified for only a few species, mainly due to a lack of appropriate laboratory data to quantify chemical impacts on vital rates. In this study, we developed a method to quantify the effects of toxicant exposure on wildlife population persistence based on field monitoring data. We established field-based vital-rate-response functions for toxicants, using quantile regression to correct for the influences of confounding factors on the vital rates observed, and combined the response curves with population viability modelling. We then applied the method to quantify the impact of DDE on three bird species: the White-tailed Eagle, Bald Eagle, and Osprey. Population viability was expressed via five population extinction vulnerability metrics: population growth rate (r1 ), critical patch size (CPS), minimum viable population size (MVP), probability of population extirpation (PE), and median time to population extirpation (MTE). We found that past DDE exposure concentrations increased population extirpation vulnerabilities of all three bird species. For example, at DDE concentrations of 25 mg/kg wet mass of egg (the maximum historic exposure concentration reported in literature for the Osprey), r1 became small (White-tailed Eagle and Osprey) or close to zero (Bald Eagle), the CPS increased up to almost the size of Connecticut (White-tailed Eagle and Osprey) or West Virginia (Bald Eagle), the MVP increased up to approximately 90 (White-tailed Eagle and Osprey) or 180 breeding pairs (Bald Eagle), the PE increased up to almost certain extirpation (Bald Eagle) or only slightly elevated levels (White-tailed Eagle and Osprey) and the MTE became within decades (Bald Eagle) or remained longer than a millennium (White-tailed Eagle and Osprey). Our study provides a method to derive species-specific field-based response curves of toxicant exposure, which can be used to assess population extinction vulnerabilities and obtain critical levels of toxicant exposure based on maximum permissible effect levels. This may help conservation managers to better design appropriate habitat restoration and population recovery measures, such as reducing toxicant levels, increasing the area of suitable habitat or reintroducing individuals.

A large number of diversity metrics are available to study and monitor biodiversity, and their responses to biodiversity changes are not necessarily coherent with each other. The choice of biodiversity metrics may thus strongly affect our interpretation of biodiversity change and, hence, prioritization of resources for conservation. Therefore it is crucial to understand which metrics respond to certain changes, are the most sensitive to change, show consistent responses across different communities, detect early signals of species decline, and are insensitive to demographic stochasticity. Here we generated synthetic communities and simulated changes in their composition according to 9 scenarios of biodiversity change to investigate the behaviour of 12 biodiversity metrics. Metrics showed diverse abilities to detect changes under different scenarios. Sørensen similarity index, arithmetic and geometric mean abundance, and species and functional richness were the most sensitive to community changes. Sørensen similarity index, species richness and geometric abundance showed consistent responses across all simulated communities and scenarios. Sørensen similarity index and geometric mean abundance were able to detect early signals of species decline. Geometric mean abundance, and functional evenness under certain scenarios, had the greatest ability to distinguish directional trends from stochastic changes, but Sørensen similarity index and geometric mean abundance were the only indices to show consistent signals under all replicates and scenarios. Classic abundance-weighted heterogeneity indices (e.g. Shannon index) were insensitive to certain changes or showed misleading responses, and are therefore unsuitable for comparison of biological communities. We therefore suggest that separate metrics of species composition, richness, and abundance should be reported instead of (or in addition to) composite metrics like the Shannon index., We thank R D Gregory and another anonymous reviewer for providing constructive comments on earlier versions of the manuscript. This article is based upon work from COST Action ES1101 “Harmonising Global Biodiversity Modelling” (Harmbio), supported by COST (European Cooperation in Science and Technology)

Methods to quantify the vulnerability of species to extinction are typically limited by the availability of species-specific input data pertaining to life-history characteristics and population dynamics. This lack of data hampers global biodiversity assessments and conservation planning. Here, we developed a new framework that systematically quantifies extinction risk based on allometric relationships between various wildlife demographic parameters and body size. These allometric relationships have a solid theoretical and ecological foundation. Extinction risk indicators included are (1) the probability of extinction, (2) the mean time to extinction, and (3) the critical patch size. We applied our framework to assess the global extinction vulnerability of terrestrial carnivorous and non-carnivorous birds and mammals. Irrespective of the indicator used, large-bodied species were found to be more vulnerable to extinction than their smaller counterparts. The patterns with body size were confirmed for all species groups by a comparison with IUCN data on the proportion of extant threatened species: the models correctly predicted a multimodal distribution with body size for carnivorous birds and a monotonic distribution for mammals and non-carnivorous birds. Carnivorous mammals were found to have higher extinction risks than non-carnivores, while birds were more prone to extinction than mammals. These results are explained by the allometric relationships, predicting the vulnerable species groups to have lower intrinsic population growth rates, smaller population sizes, lower carrying capacities, or larger dispersal distances, which, in turn, increase the importance of losses due to environmental stochastic effects and dispersal activities. Our study is the first to integrate population viability analysis and allometry into a novel, process-based framework that is able to quantify extinction risk of a large number of species without requiring data-intensive, species-specific information. The framework facilitates the estimation of extinction vulnerabilities of data-deficient species. It may be applied to forecast extinction vulnerability in response to a changing environment, by incorporating quantitative relationships between wildlife demographic parameters and environmental drivers like habitat alteration, climate change, or hunting.

Wildlife management to reduce the impact of wildlife on their habitat can be done in several ways, among which removing animals (by either culling or translocation) is most often used. There are however alternative ways to control wildlife densities, such as opening or closing water points. The effects of these alternatives are poorly studied. In this paper, we focus on manipulating large herbivores through the closure of water points (WPs). Removal of artificial WPs has been suggested to change the distribution of African elephants, which occur in high densities in national parks in Southern Africa and are thought to have a destructive effect on the vegetation. Here, we modeled the long-term effects of different scenarios of WP closure on the spatial distribution of elephants, and consequential effects on the vegetation and other herbivores in Kruger National Park, South Africa. Using a dynamic ecosystem model, SAVANNA, scenarios were evaluated that varied in (1) availability of artificial WPs, (2) levels of natural water, and (3) elephant densities. Our modeling results showed that elephants can indirectly negatively affect the distributions of mesomixed feeders, mesobrowsers and some mesograzers under wet conditions. The closure of artificial WPs hardly had any effect during these natural wet conditions. Only under dry conditions the spatial distribution of both elephant bulls and cows changed when the availability of artificial water was severely reduced in the model. These changes in spatial distribution triggered changes in the spatial availability of woody biomass over the simulation period of 80 years and this led to changes in the rest of the herbivore community, resulting in increased densities of all herbivores, except for giraffe and steenbok, in areas close to rivers. The spatial distributions of elephant bulls and cows showed to be less affected by the closure of WPs than most of the other herbivore species. Our study contributes to ecologically informed decisions in wildlife management. The results from this modeling exercise imply that long-term effects of this intervention strategy should always be investigated at an ecosystem scale.

Context: Increasing the amount of green infrastructure, defined as small-scale natural landscape elements, has been named as a climate adaptation measure for biodiversity. While green infrastructure strengthened ecological networks in some studies, it is not known whether this effect also holds under climate change, and how it compares to other landscape adaptation options. Objectives: We assessed landscape adaptation options under scenarios of climate change for a dispersal-limited and climate-sensitive species: great crested newt, Triturus cristatus. Methods: A spatially-explicit modelling framework was used to simulate newt metapopulation dynamics in a case study area in the Netherlands, under alternative spatial configurations of 500 ha to-be-restored habitat. The framework incorporated weather-related effects on newt recruitment, following current and changing climate conditions. Results: Mild climate change resulted in slightly higher metapopulation viability, while more severe climate change (i.e. more frequent mild winters and summer droughts) had detrimental effects on metapopulation viability. The modelling framework revealed interactions between climate and landscape configuration on newt viability. Restoration of ponds and terrestrial habitat may reduce the negative effects of climate change, but only when certain spatial requirements (habitat density, connectivity) as well as abiotic requirements (high ground water level) are met. Conclusions: Landscape scenarios where habitat was added in the form of green infrastructure were not able to meet these multiple conditions, as was the case for a scenario that enlarged core areas. The approach allowed a deduction of landscape design rules that incorporated both spatial and abiotic requirements resulting in more effective climate adaptation options.

To prioritize conservation efforts, it is important to know which plant species are most vulnerable to extinction. Intrinsic extinction vulnerabilities depend on demographic parameters, but for many species these demographic parameters are lacking. Body size has been successfully used as proxy of such parameters to estimate extinction vulnerability of birds and mammals. For plants, not all necessary demographic parameters have been related to size yet. Here, we derived allometric relationships with maximum plant height for the intrinsic population growth rate and the carrying capacity. Furthermore, for the first time, we derived a relationship between the variance in population growth rate due to environmental stochasticity and plant height. These relationships were used to relate extinction vulnerability to maximum plant height. Extinction vulnerability was found to be most sensitive to fluctuations in the population growth rate due to environmental stochasticity. Large plant species were less susceptible to environmental stochasticity, resulting in a lower vulnerability to extinction than small plant species. This negative relationship between plant size and extinction vulnerabilities is in contrast to previous results for mammals and birds. These results increase our theoretical understanding of the relationship between plant functional traits and extinction vulnerabilities and may aid in assessments of data deficient species. The uncertainty in the allometric relationships is, however, too large to quantify true extinction vulnerabilities. Further investigation in the relationship between demographic parameters and plant traits other than height is needed to further enhance our understanding of plant species extinction vulnerabilities.

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., Article impact statement: Automatic screening to prioritize species reassessments optimizes the use of resources and keeps the IUCN Red List up to date.