Estimates Of Extinction Risk Research Articles

Experimental evidence of climate change extinction risk in Neotropical montane epiphytes

Climate change is conjectured to endanger tropical species, particularly in biodiverse montane regions, but accurate estimates of extinction risk are limited by a lack of empirical data demonstrating tropical species’ sensitivity to climate. To fill this gap, studies could match high-quality distribution data with multi-year transplant experiments. Here, we conduct field surveys of epiphyte distributions on three mountains in Central America and perform reciprocal transplant experiments on one mountain across sites that varied in elevation, temperature and aridity. We find that most species are unable to survive outside of their narrow elevational distributions. Additionally, our findings suggest starkly different outcomes from temperature conditions expected by 2100 under different climate change scenarios. Under temperatures associated with low-emission scenarios, most tropical montane epiphyte species will survive, but under emission scenarios that are moderately high, 5-36% of our study species may go extinct and 10-55% of populations may be lost. Using a test of tropical species’ climate tolerances from a large field experiment, paired with detailed species distribution data across multiple mountains, our work strengthens earlier conjecture about risks of wide-spread extinctions from climate change in tropical montane ecosystems.

Modelling decisions and density dependence in monarch butterflies: A comment on Meehan and Crossley (2023)

Abstract Decisions about which processes to include in a population model can have substantial impact on estimates of population trends and extinction risk. This is particularly important for species of conservation concern, whose conservation status is decided in part on the basis of these models. In their recent paper, Meehan and Crossley (2023) Insect Conservation and Diversity, 16, 566–573 revisit a time series of overwintering monarch butterfly abundances, which previous assessments had characterised as rapidly declining and at risk of extinction. The authors, in contrast, reported no evidence for declines in the past 10 years and characterised extinction risk as low. A primary reason for the difference between these conclusions was that Meehan and Crossley used a more complex model that included a parameter for density dependence. While negative density dependence may play a role in monarch population regulation, there are a variety of unresolved issues with how and if density dependence should be included in models of monarch populations, including widely known issues with separating observation error from density dependence in noisy time series and taxon‐specific issues with fitting models to data surveyed every fourth generation and pooled at continental scales. These issues make the conclusions of Meehan and Crossley about monarch population viability much less robust than implied in their article. They do not provide convincing evidence that density dependence reduces extinction risk in monarch butterflies. Our commentary supports their general conclusion that population viability projections depend on model assumptions, but the ways in which monarch butterfly populations are regulated remains an open question.

Half of Atlantic reef-building corals at elevated risk of extinction due to climate change and other threats.

Atlantic reef-building corals and coral reefs continue to experience extensive decline due to increased stressors related to climate change, disease, pollution, and numerous anthropogenic threats. To understand the impact of ocean warming and reef loss on the estimated extinction risk of shallow water Atlantic reef-building scleractinians and milleporids, all 85 valid species were reassessed under the IUCN Red List Categories and Criteria, updating the previous Red List assessment of Atlantic corals published in 2008. For the present assessment, individual species declines were estimated based on the modeled coral cover loss (1989-2019) and projected onset of annual severe bleaching events (2020-2050) across the Atlantic. Species traits were used to scale species' relative vulnerability to the modeled cover declines and forecasted bleaching events. The updated assessments place 45.88%-54.12% of Atlantic shallow water corals at an elevated extinction risk compared to the previous assessments conducted in 2008 (15.19%-40.51%). However, coral cover loss estimates indicate an improvement in reef coverage compared to the historic time-series used for the 2008 assessments. Based on this, we infer that, although remaining dangerously high, the rate of Atlantic reef coral cover decline has surprisingly slowed in recent decades. However, based on modeled projections of sea-surface temperature that predict the onset of annual severe bleaching events within the next 30 years, we listed 26 (out of 85) species as Critically Endangered in the IUCN Red List. Each of these species had previously been listed under a lower threatened category and this result alone highlights the severe threat future bleaching events pose to coral survival and the reef ecosystems they support.

Macroecological predictors of evolutionary and plastic potential do not apply at microgeographic scales for a freshwater cladoceran under climate change.

Rapid evolutionary adaptation could reduce the negative impacts of climate change if sufficient heritability of key traits exists under future climate conditions. Plastic responses to climate change could also reduce negative impacts. Understanding which populations are likely to respond via evolution or plasticity could therefore improve estimates of extinction risk. A large body of research suggests that the evolutionary and plastic potential of a population can be predicted by the degree of spatial and temporal climatic variation it experiences. However, we know little about the scale at which these relationships apply. Here, we test if spatial and temporal variation in temperature affects genetic variation and plasticity of fitness and a key thermal tolerance trait (critical thermal maximum; CTmax) at microgeographic scales using a metapopulation of Daphnia magna in freshwater rock pools. Specifically, we ask if (a) there is a microgeographic adaptation of CTmax and fitness to differences in temperature among the pools, (b) pools with greater temporal temperature variation have more genetic variation or plasticity in CTmax or fitness, and (c) increases in temperature affect the heritability of CTmax and fitness. Although we observed genetic variation and plasticity in CTmax and fitness, and differences in fitness among pools, we did not find support for the predicted relationships between temperature variation and genetic variation or plasticity. Furthermore, the genetic variation and plasticity we observed in CTmax are unlikely sufficient to reduce the impacts of climate change. CTmax plasticity was minimal and heritability was 72% lower when D. magna developed at the higher temperatures predicted under climate change. In contrast, the heritability of fitness increased by 53% under warmer temperatures, suggesting an increase in overall evolutionary potential unrelated to CTmax under climate change. More research is needed to understand the evolutionary and plastic potential under climate change and how that potential will be altered in future climates.

30×30 for Climate: The History and Future of Climate Change–Integrated Conservation Strategies

Global agreement on 30×30 means an unprecedented last push to define how much nature will be left on the planet. At the same time that space for nature is being defined, climate change will be moving nature around. Species are now on the move to track climate change both on land and in the oceans, a process that is accelerating under dramatic new extreme events. This is an opportune time to review conservation recommendations made early in the millennium, to see how many have been taken on board over the past 20 years, and how much is left to be done to adapt to climate change as conservation pushes toward 30×30. The history of Climate Change–Integrated Conservation Strategies begins with two papers published by a group of prominent climate change biologists in 2002. The importance of including adaptation to climate change in conservation was underscored by the first estimates of extinction risk due to climate change in 2004. Subsequent literature has developed concepts such as velocity of climate change and assisted migration. Regional modeling of biodiversity change, expanding protected areas to facilitate species range movements, and managing productive landscapes to facilitate species movements are all now considered “business as usual” for conservation planning for climate change. Regional coordination of conservation efforts to ensure that species on the move are managed for climate change consistently across their range, on the other hand, is under-represented in literature and practice. Improving both theory and practice of regional coordination for climate change is an important priority for conservation now and in the future. Conservation for climate change has focused mostly on warming scenarios, but failure to act on climate change emissions reduction means that meeting Paris Agreement targets will almost certainly have to include both warming past those targets and subsequent cooling back to the target. Managing this double transition is a second critical point of emphasis for climate change biology as the world moves to 30×30.

The U.S. market for imported wildlife not listed in the CITES multilateral treaty.

The international wildlife trade presents severe conservation and environmental security risks, yet no international regulatory framework exists to monitor the trade of species not listed in the appendices of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). We explored the composition and dynamics of internationally regulated versus nonregulated trade, with a focus on importations of wild-caught terrestrial vertebrates entering the United States from 2009 to 2018. We used 10 years of species-level trade records of the numbers of live, wild-caught animals imported to the United States and data on International Union for the Conservation of Nature (IUCN) estimates of extinction risk to determine whether there were differences in the diversity, abundance, and risk to extinction among imports of CITES-listed versus unlisted species. We found 3.6 times the number of unlisted species in U.S. imports compared with CITES-listed species (1366 vs. 378 species). The CITES-listed species were more likely to face reported conservation threats relative to unlisted species (71.7%vs. 27.5%). However, 376 unlisted species faced conversation threats, 297 species had unknown population trends, and 139 species were without an evaluation by the IUCN. Unlisted species appearing for the first time in records were imported 5.5 times more often relative to CITES-listed species. Unlisted reptiles had the largest rate of entry, averaging 53 unique species appearing in imports for the first time per year. Overall trade quantities were approximately 11 times larger for imports of unlisted species relative to imports of CITES-listed species. Countries that were top exporters of CITES-listed species were mostly different from exporters of unlisted species. Because of the vulnerabilities of unlisted, traded species entering the United States and increasing global demand, we strongly recommend governments adapt their policies to monitor and report on the trade of all wildlife.

The importance of negative density dependence for rare species persistence

Determining the predictors of extinction risk is a major goal of conservation biology. Theory suggests that population characteristics such as low abundance and declining trends should equate to high extinction risk. However, rare species persist and account for nearly half of all species across global communities. Here we employ the Chicago Botanic Garden's long-term, rare species monitoring dataset to investigate population dynamics and hypothesized predictors of extinction risk of 73 populations of 43 rare species. Specifically, we ask how important negative density dependence is for rare species persistence and how well population size, population trends, life cycle duration, and clonality predict estimates of extinction risk in rare species. Extinction risk was estimated using density-dependent and density-independent population viability analyses. Based on our simulations, we found that only 33 of our populations had concerning extinction risks (>20 %). The key to these relatively low extinction risks for so many rare, listed species was negative density dependence. Population size, population trends, life cycle duration, and clonality were not good predictors of extinction risk based on our modeling efforts, though their relationships to extinction risk did agree with theoretical expectations. Our results highlight the potential importance of negative density dependence for rare species persistence and the importance of incorporating density dependence in population projection models for extinction risk assessment.

Population genomic monitoring provides insight into conservation status but no correlation with demographic estimates of extinction risk in a threatened trout.

The current extinction crisis requires effective assessment and monitoring tools. Genetic approaches are appealing given the relative ease of field sampling required to estimate genetic diversity characteristics assumed related to population size, evolutionary potential, and extinction risk, and to evaluate hybridization with non‐native species simultaneously. However, linkages between population genetic metrics of diversity from survey‐style field collections and demographic estimates of population size and extinction risk are still in need of empirical examples, especially for remotely distributed species of conservation concern where the approach might be most beneficial. We capitalized on an exceptional opportunity to evaluate congruence between genetic diversity metrics and demographic‐based estimates of abundance and extinction risk from a comprehensive Multiple Population Viability Analysis (MPVA) in a threatened fish, the Lahontan cutthroat trout (LCT). We sequenced non‐native trout reference samples and recently collected and archived tissue samples of most remaining populations of LCT (N = 60) and estimated common genetic assessment metrics, predicting minimal hybridization with non‐native trout, low diversity, and declining diversity over time. We further hypothesized genetic metrics would correlate positively with MPVA‐estimated abundance and negatively with extinction probability. We uncovered several instances of hybridization that pointed to immediate management needs. After removing hybridized individuals, cautious interpretation of low effective population sizes (2–63) suggested reduced evolutionary potential for many LCT populations. Other genetic metrics did not decline over time nor correlate with MPVA‐based estimates of harmonic mean abundance or 30‐year extinction probability. Our results demonstrate benefits of genetic monitoring for efficiently detecting hybridization and, though genetic results were disconnected from demographic assessment of conservation status, they suggest reduced evolutionary potential and likely a higher conservation risk than currently recognized for this threatened fish. We emphasize that genetic information provides essential complementary insight, in addition to demographic information, for evaluating species status.

Where traditional extinction estimates fall flat: using novel cophylogenetic methods to estimate extinction risk in platyhelminths.

Today parasites comprise a huge proportion of living biodiversity and play a major role in shaping community structure. Given their ecological significance, parasite extinctions could result in massive cascading effects across ecosystems. It is therefore crucial that we have a way of estimating their extinction risk. Attempts to do this have often relied on information about host extinction risk, without explicitly incorporating information about the parasites. However, assuming an identical risk may be misleading. Here, we apply a novel metric to estimate the cophylogenetic extinction rate, Ec, of parasites with their hosts. This metric incorporates information about the evolutionary history of parasites and hosts that can be estimated using event-based cophylogenetic methods. To explore this metric, we investigated the use of different cophylogenetic methods to inform the Ec rate, based on the analysis of polystome parasites and their anuran hosts. We show using both parsimony- and model-based approaches that different methods can have a large effect on extinction risk estimation. Further, we demonstrate that model-based approaches offer greater potential to provide insights into cophylogenetic history and extinction risk.

Reptile research shows new avenues and old challenges for extinction risk modelling.

In a new PLOS Biology paper, de Oliveira Caetano and colleagues presented an innovative method to estimate extinction risk in reptile species worldwide. The method shows a promising avenue to support Red List assessment, alongside some well-known challenges.

Cryptic extinction risk in a western Pacific lizard radiation

Cryptic ecologies, the Wallacean Shortfall of undocumented species’ geographical ranges and the Linnaean Shortfall of undescribed diversity, are all major barriers to conservation assessment. When these factors overlap with drivers of extinction risk, such as insular distributions, the number of threatened species in a region or clade may be underestimated, a situation we term ‘cryptic extinction risk’. The genus Lepidodactylus is a diverse radiation of insular and arboreal geckos that occurs across the western Pacific. Previous work on Lepidodactylus showed evidence of evolutionary displacement around continental fringes, suggesting an inherent vulnerability to extinction from factors such as competition and predation. We sought to (1) comprehensively review status and threats, (2) estimate the number of undescribed species, and (3) estimate extinction risk in data deficient and candidate species, in Lepidodactylus. From our updated IUCN Red List assessment, 60% of the 58 recognized species are threatened (n = 15) or Data Deficient (n = 21), which is higher than reported for most other lizard groups. Species from the smaller and isolated Pacific islands are of greatest conservation concern, with most either threatened or Data Deficient, and all particularly vulnerable to invasive species. We estimated 32 undescribed candidate species and linear modelling predicted that an additional 18 species, among these and the data deficient species, are threatened with extinction. Focusing efforts to resolve the taxonomy and conservation status of key taxa, especially on small islands in the Pacific, is a high priority for conserving this remarkably diverse, yet poorly understood, lizard fauna. Our data highlight how cryptic ecologies and cryptic diversity combine and lead to significant underestimation of extinction risk.

New conservation status for data-deficient endemic mammals of East Africa

Knowing the exact status of several species is unimaginable since the data available is not adequate to determine their category, they are classified as Data Deficient (DD) by the IUCN. Lack of sufficient information impedes the assessment of conservation status for DD species and could lead to missing conservation opportunities for rare mammals under multiple threats. It seems appropriate that available knowledge of each species should be recorded now because the next few decades will see even more human-induced changes. The main objective is to suggest a strategic framework and establishing categories to help overcome the uncertainty regarding the conservation status of endemic mammals of East Africa. Preliminary extinction risk categories were determined based on the IUCN Red List Criterion B particularly of criteria B1 which uses the extent of occurrence. We use quantile regression to model a relationship between the time since species discovery (50 years as a reference) and log-transformed range-size of mammal species (1–20,000 km2 area for a threatened category). Mammals that were described more than 50 years ago and have an EOO of less than 20,000 km2 are categorized under threatened status. We found a significant positive relationship between time since species discovery and geographic range size of the non-DD mammal species for all quantile levels (p < 0.05) allowed the use of time since species discovery and geographic range size to infer the proper red list category of species. Only 16 endemic mammals currently listed as Data Deficient, should continue to be listed as so (group A). The remaining species should be re-listed as threatened (17 species) and as non-threatened (25 species, groups C and D). Our finding reduced the number of DD species of mammals of East Africa from 32.04% to 8.83%. As of the investigation of the present study, 12 (70.6%) mammals suggested for threatened categories are small-sized shrews and bats. DD species introduce greater uncertainty in estimates of overall extinction risk to the endemics, and by no means are they such species that can be considered low priorities for research. DD mammals may still face high extinction risks and may be more frequently threatened than successfully evaluated mammals. These findings may hopefully contribute to a more efficient allocation of conservation funds and more efficient development of conservation plans using data available for almost all mammalian species.

Extinction risk in vascular plants and vertebrates is negatively correlated with family size

Understanding the pattern of species extinction risk is key to biodiversity conservation. Previous studies showed extinction risk correlates strongly with taxon species richness. However, there is no consistent conclusion to this hypothesis, and patterns differ among different taxonomic groups. Here, we collated lists of vascular plant and terrestrial vertebrate species information on their threatened status in Yunnan Province and performed the first systematical analysis to test the relationship between the proportion of threatened or extinct species and species richness at the family-level of the two above taxa in Yunnan Province, China. We found that extinction risk was not randomly distributed among families and the estimated extinction risk was higher among closer phylogenetic families than expected by chance. Moreover, there were significant negative correlations between extinction risk and family size in vascular plants and terrestrial vertebrates. Our results suggest that family size is a good predictor of extinction risk and extinction risk is related to evolutionary history at family-level among vascular plants and terrestrial vertebrates in Yunnan.

Initial abundance and stochasticity influence competitive outcome in communities.

Predicting competitive outcomes in communities frequently involves inferences based on deterministic population models since these provide clear criteria for exclusion (e.g. R* rule) or long-term coexistence (e.g. mutual invasibility). However, incorporating stochasticity into population- or community-level processes into models is necessary if the goal is to explain variation in natural systems, which are inherently stochastic. Similarly, in systems with demographic or environmental stochasticity, weaker competitors have the potential to exclude superior competitors, contributing to what is known as 'competitive indeterminacy'. The importance of such effects for natural communities is unknown, in part because it is difficult to demonstrate that multiple forms of stochasticity are present in these communities. Moreover, the effects of multiple forms of stochasticity on competitive outcomes are largely untested, even in theory. Here, we address these issues by examining the role of stochasticity in replicated communities of flour beetles (Tribolium sp.). To do so, we developed a set of two-species stochastic Ricker models incorporating four distinct forms of stochasticity: environmental stochasticity, demographic stochasticity, demographic heterogeneity and stochastic sex determination. By fitting models to experimental data, and simulating fit models to examine long- term behaviour, we found that both the duration of transient coexistence and the degree of competitive indeterminacy were sensitive to the forms of stochasticity included in our models. These findings suggest the current estimates of extinction risk, coexistence and time until competitive exclusion in communities may not be accurate when based on models that exclude relevant forms of stochasticity.

Comparison of three techniques for genetic estimation of effective population size in a critically endangered parrot

AbstractUnderstanding the current population size of small, spatially aggregating populations of species is essential for their conservation. Reliable estimates of the effective population size (Ne) can be used to provide an early warning for conservation managers of the risks to genetic viability of small populations. Critically endangered, migratory swift parrots Lathamus discolor exist in a single panmictic population in Australia. In their Tasmanian breeding range, they are at severe risk of predation by introduced sugar gliders, exacerbated by deforestation. We used three genetic approaches to estimate Ne using DNA samples genotyped by microsatellite markers and existing life‐history data of swift parrots. Based on all samples, we revealed small contemporary Ne estimates across methods (range: 44–140), supporting the need to urgently address threatening processes. Using the 0.5 Ne/N ratio calculated from demographic data suggests that the minimum potential contemporary population size is below 300 individual swift parrots. This is considerably lower than the published estimates derived from expert elicitation, and accords with modeled estimates of extinction risk in this species. Our study has important implications for other threatened species with unknown population sizes and demonstrates that by utilizing available genetic data, reasonable estimates of Ne can be derived.

Assessing Population Viability of Black Bears using Spatial Capture‐Recapture Models

ABSTRACTThe Central Georgia Bear Population (CGP) is the least abundant and most isolated of Georgia's 3 American black bear (Ursus americanus) populations. Beginning in 2011, changes to regulations governing harvest of the CGP resulted in an increase in female bear harvest, creating concern that future harvest could be an important influence on population viability. Hence, our objective was to assess viability of the CGP under various levels of female mortality. During 2012–2016, we used barbed‐wire hair snares to collect bear hair samples from within the range of the CGP in Georgia, USA. We used microsatellite genotyping to identify individual bears and created robust‐design, spatial detection histories for all female bears detected. We fit open population spatial capture‐recapture (SCR) models to the detection histories in a Bayesian framework. We used the Widely Applicable Information Criterion (WAIC) to rank models that varied with respect to sources of variation in detection probability, survival, and per capita recruitment, and used the model with the lowest WAIC to forecast dynamics of the CGP 50 years into the future under various levels of female mortality. We assessed the 50‐year extinction probability under a continuation of mortality levels documented during 2012–2016, and under incremental increases in female mortality above this baseline. The top model included density‐dependent per capita recruitment, annual variation in detection probability, and a trap‐level behavioral response. Abundance increased from 106 (95% CI = 86–132) females in 2012 to 136 (95% CI = 113–161) females in 2013 and remained relatively stable thereafter. Annual female survival was 0.75 (95% CI = 0.69–0.82) and did not vary among years. The per capita recruitment rate decreased over time as density increased, and was 0.49 (95% CI = 0.33–0.66) during the first time interval and 0.29 (95% CI = 0.20–0.38) during the final time interval. Annual growth rate () was 1.28 (95% CI = 1.07–1.52) between 2012 and 2013 but decreased throughout the study, ending at 1.04 (95% CI = 0.93–1.17). Forecasts indicated continuation of the female mortality levels experienced from 2012–2016 were sustainable over 50 years, with the estimated extinction risk being &lt;0.001%. Increasing annual harvest by 5 females introduced a negligible increase in the 50‐year probability of extinction, but harvesting an additional 10 females/year caused extinction risk to rise to 1.15%. We recommend that harvest regulations are structured such that mortality rates remain at current levels or do not increase by more than an annual average of 5 females above levels observed during our study. Furthermore, we recommend that managers continue to monitor the population so that harvest regulations and population models can be refined over time. © 2020 The Wildlife Society.

Generation lengths of the world's birds and their implications for extinction risk.

Birds have been comprehensively assessed on the International Union for Conservation of Nature (IUCN) Red List more times than any other taxonomic group. However, to date, generation lengths have not been systematically estimated to scale population trends when undertaking assessments, as required by the criteria of the IUCN Red List. We compiled information from major databases of published life-history and trait data for all birds and imputed missing life-history data as a function of species traits with generalized linear mixed models. Generation lengths were derived for all species, based on our modeled values of age at first breeding, maximum longevity, and annual adult survival. The resulting generation lengths varied from 1.42 to 27.87 years (median 2.99). Most species (61%) had generation lengths <3.33 years, meaning that the period of 3 generations-over which population declines are assessed under criterion A-was <10 years, which is the value used for IUCN Red List assessments of species with short generation times. For these species, our trait-informed estimates of generation length suggested that 10 years is a robust precautionary value for threat assessment. In other cases, however, for whole families, genera, or individual species, generation length had a substantial impact on their estimated extinction risk, resulting in higher extinction risk in long-lived species than in short-lived species. Although our approach effectively addressed data gaps, generation lengths for some species may have been underestimated due to a paucity of life-history data. Overall, our results will strengthen future extinction-risk assessments and augment key databases of avian life-history and trait data.

Genetically-informed population models improve climate change vulnerability assessments

Climate change will cause species extinctions that will be exacerbated by human-caused landscape changes, preventing species from tracking shifting climatic niches. Although incorporating functional connectivity into prospective population models has proven challenging, the field of landscape genetics provides underutilized tools for characterizing functional connectivity. The aim of this study was to explore how genetically-derived representations of dispersal affect assessments of environmental change impacts using a spatially-explicit population modelling approach. We illustrated the utility of this approach to test hypotheses related to the effects of dispersal representation and environmental change for the IUCN-threatened Blanding’s Turtle (Emydoidea blandingii). We integrated existing demographic and genetic datasets into a spatially-explicit metapopulation modelling framework. We ran several sets of simulations with varying dispersal representations (distance-based, landscape resistance-based with either static or changing land cover) to explore how landscape genetic estimates of connectivity impact estimates of extinction risk. Models incorporating land cover-based dispersal resulted in lower patch occupancy than simulations where dispersal was only a function of interpatch distance. Furthermore, both climate change-induced declines in habitat suitability and land use change-induced declines in connectivity reduced abundance and patch occupancy. Incorporating landscape genetics into population models revealed that choices involved in dispersal representation alter both extinction risk and path occupancy, often altering the distribution of extant patches by the end of simulations. As technological advances continue to increase access to landscape genetic datasets, we suggest that researchers carefully consider how genetic resources can be used to improve climate vulnerability assessments.

Extinction risk and conservation gaps for Aloe (Asphodelaceae) in the Horn of Africa

Identification of conservation priorities is essential for conservation planning, especially as the biodiversity crisis develops. We aimed to support conservation prioritisation by addressing knowledge gaps for the genus Aloe in the Horn of Africa. Specifically, we developed a dataset of herbarium voucher specimens and occurrence data to estimate geographic distribution of 88 species of Aloe and used this to estimate extinction risk and establish the major threats to Aloe in this region. The resulting assessments, each published on the IUCN Red List, show that 39% of the species are threatened with extinction, and the principal threats are the expansion and intensification of crop farming and livestock farming, gathering of plants, and unintentional effects of logging and wood harvesting. We review ex situ conservation in botanic gardens and seed banks, revealing gaps in coverage and urgent priorities for collection, with 25 threatened Aloe species currently unrepresented in seed banks. Protected areas in the region offer limited coverage of Aloe distributions and the most recently designated protected areas are increasingly in regions that do not overlap with Aloe distributions. However, we show with a simple optimisation approach that even a modest increase in protected area of 824 square kilometres would allow representation of all Aloe species, although further data are needed to test the area required to ensure long-term persistence (resilience) of Aloe species.

Niche syndromes reveal climate-driven extinction threat to island endemic conifers

Anthropogenic climate change is predicted to cause many extinctions worldwide1. Although species endemic to islands or archipelagos have high conservation value and are vulnerable to human impacts2,3, there has been no global analysis of climate-driven extinction risk focused on island endemics. Here, we use conifers as a model system to assess extinction risk among island endemics under climate projections for 2070. We employ the emerging technique of combining native and non-native occurrence data to model climatic conditions under which each species can sustain a population4–7 and also incorporate horticultural data to model the broader range of conditions that allow short-term survival. Our projections indicate that some species will retain suitable climatic conditions, some will experience conditions completely precluding survival and others will experience intermediate-risk conditions that lead to population decline and eventual extinction. Based on different climate change models, we report island size thresholds of 400 to 20,000 km2, below which extinction risks increase. These patterns are driven by correlations among island area and the breadth of species’ realized, fundamental and tolerance niches. Notably, realized and fundamental niche breadth are positively correlated. Our results highlight management interventions needed to protect species from climate-driven extinction across islands of different sizes. Island species are at risk as the climate changes. Island conifers are used as a model species and a combination of native and non-native occurrence data allows identification of realized, tolerable and fundamental niches; linking to island size provides an estimate of extinction risk.