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Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ageing refers to the loss of organismal functionality with age, a process that is characterised by decreased reproduction and survival probability. In natural populations, it is expected that environmental conditions influence an individual's ageing trajectory. Understanding the role of environmental heterogeneity on ageing variation could provide critical insights into population resilience and species distribution but remains overlooked. Telomeres, the end cap of chromosomes, are a promising integrative physiological marker of an individual's health and a possible proxy to aid the understanding of variation in ageing trajectories. Here, we review the existing information on telomere length and its dynamics in wild populations distributed across spatial scales. Despite a relative scarcity of information, there is evidence for divergence in telomere length between populations facing contrasting environments. Nonetheless, a higher spatial resolution and temporal replication are needed to fully understand the role that environmental conditions play on telomere length variation. Since most of the existing studies are correlational, future field and laboratory experiments are required. For the first time, we demonstrate the use of population telomere data to predict species habitat suitability through species distribution models (SDMs). This represents a promising new research area in the study of ageing pattern variation in wild populations. Furthermore, the inclusion of telomere data in future physiological SDMs may improve our understanding of species distribution and population resilience. However, the use of telomeres within this context could be limited if no previous knowledge on the relevance of telomeres as markers of health and survival at the species level is available. Finally, we suggest some key practical and theoretical considerations that, ideally, future studies combining biogeographic and telomere data should pay attention. [ABSTRACT FROM AUTHOR]

Zoogeographical regions, or zooregions, are areas of the Earth defined by species pools that reflect ecological, historical and evolutionary processes acting over millions of years. Consequently, researchers have assumed that zooregions are robust and unlikely to change on a human timescale. However, the increasing number of human‐mediated introductions and extinctions can challenge this assumption. By delineating zooregions with a network‐based algorithm, here we show that introductions and extinctions are altering the zooregions we know today. Introductions are homogenising the Eurasian and African mammal zooregions and also triggering less intuitive effects in birds and amphibians, such as dividing and redefining zooregions representing the Old and New World. Furthermore, these Old and New World amphibian zooregions are no longer detected when considering introductions plus extinctions of the most threatened species. Our findings highlight the profound and far‐reaching impact of human activity and call for identifying and protecting the uniqueness of biotic assemblages. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The contraction of a species' distribution range, which results from the extirpation of local populations, generally precedes its extinction. Therefore, understanding drivers of range contraction is important for conservation and management. Although there are many processes that can potentially lead to local extirpation and range contraction, three main null models have been proposed: demographic, contagion, and refuge. The first two models postulate that the probability of local extirpation for a given area depends on its relative position within the range; but these models generate distinct spatial predictions because they assume either a ubiquitous (demographic) or a clinal (contagion) distribution of threats. The third model (refuge) postulates that extirpations are determined by the intensity of human impacts, leading to heterogeneous spatial predictions potentially compatible with those made by the other two null models. A few previous studies have explored the generality of some of these null models, but we present here the first comprehensive evaluation of all three models. Using descriptive indices and regression analyses we contrast the predictions made by each of the null models using empirical spatial data describing range contraction in 386 terrestrial vertebrates (mammals, birds, amphibians, and reptiles) distributed across the World. Observed contraction patterns do not consistently conform to the predictions of any of the three models, suggesting that these may not be adequate null models to evaluate range contraction dynamics among terrestrial vertebrates. Instead, our results support alternative null models that account for both relative position and intensity of human impacts. These new models provide a better multifactorial baseline to describe range contraction patterns in vertebrates. This general baseline can be used to explore how additional factors influence contraction, and ultimately extinction for particular areas or species as well as to predict future changes in light of current and new threats. [ABSTRACT FROM AUTHOR]

Shared socioeconomic pathways are a key tool in predicting biodiversity scenarios and in the subsequent design of environmental policies. Here, we discuss how recent policy changes to global trade routes, agriculture, and energy production in response to the war in Ukraine are impacting socioeconomic scenarios used to set and assess biodiversity targets. We also discuss how the disruption to the global geopolitical landscape provides a window of opportunity for policy reform and the radical societal paradigm shift that is needed to tackle the global biodiversity crisis. We call for the re‐evaluation of biodiversity targets with newly developed scenarios that reflect the changes made to production and consumption patterns. We also recommend establishing national biodiversity working groups to screen proposed policies for their potential risks to the drivers of biodiversity change, since policy decisions made in response to the war that seemingly are far removed from the environment can have lasting impacts on nature. [ABSTRACT FROM AUTHOR]

1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species' traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species' traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14-99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases. [ABSTRACT FROM AUTHOR]