Extinction Risk Of Species Research Articles

Past and recent drivers of extinction risk in endemic New Zealand birds

AbstractLand‐cover change is a major driver of species extinction risk and the overarching loss of biodiversity. However, the impact of such change is nuanced, varying among species due to the mediation of life‐history traits and the timing of land transformation. While diverse studies have pinpointed ecological and life‐history attributes linked to the decline of bird species, the combined effects of past and recent land‐cover change often present a complex picture. In this study, we undertook a modelling approach to assess extinction risk in New Zealand's endemic birds based on life‐history traits and past (1996–2008) and recent (2008–2018) land‐cover change. Our results suggested specific variables driving extinction risk in endemic New Zealand birds. Notably, incubation length emerged as the most influential factor, trailed by past land‐cover change, body size and clutch size. This indicates that past land‐cover change in combination with large body sizes and slow life histories, characterized by low fecundity and extended incubation periods, collectively elevates the extinction risk of endemic birds in New Zealand. These results shed light on the conservation priorities for species with specific biological traits potentially exposed to the negative effects of land‐cover change.

Universal prediction of vertebrate species age at maturity

Animal age at maturity can be used as a universal and simple predictor of species extinction risk. At present, methods to estimate age at maturity are typically species-specific, limiting comparisons among species, or are infeasible due to practical constraints. To overcome this, here we develop a universal predictor of species-level age at maturity for vertebrates. We show that modelling the frequency of ‘CG’ sequences (CpG sites) in gene promoter regions yields rapid predictions of vertebrate age at maturity. Our models predict age at maturity with remarkable accuracy and generalisability, with median error rates of 30% (less than 1 year) and are robust to genome assemblies of varying quality. We generate predictions for 1912 vertebrate species for which age at maturity estimates were previously absent from public databases. The predictions can be used to help to inform management decisions for the many species for which more detailed population information is currently unavailable.

Native woody species depend on the soil microbiome to establish on burned soils, while non‐native do not

Abstract Wildfires are important natural disturbances with profound ecological impacts. However, our understanding of how to restore plant–soil microbiome interactions following wildfires remains limited, revealing a key knowledge gap in post‐wildfire ecosystem restoration. To assess the restoration of plant‐microbiome interactions in fire‐affected ecosystems, we conducted greenhouse experiments simulating wildfire effects on soil collected from Maulino Coastal Forest of central Chile, a biodiversity hotspot. We measured the plant height and photosynthesis over 90 days, and two‐year survival probability, of three common native (Aristotelia chilensis, Nothofagus glauca and N. alessandrii) and three non‐native species (Eucalyptus globulus, Pinus radiata and Genista monspessulana) planted in three soils (unburned, burned and burned soil inoculated with the native microbiome). Available nutrient concentrations (N, P and K) and activities of microbial enzymes (dehydrogenase, β‐glucosidase and urease) were also measured over 360 days. Available nutrient concentrations were consistently higher in burned and burned‐inoculated soils than in unburned soils. Enzyme activities in unburned and burned‐inoculated soils remained higher than in burned soil, indicating that the native microbiome restored microbial enzyme activities. The increase in height over 90 days was lower in burned soils compared with unburned soils for native species. However, inoculation with the native microbiome mitigated this negative effect, resulting in height increases similar to those in unburned soils. For non‐native species, burning and inoculation had negligible effects on the height increases. Similar patterns were observed for the increase in photosynthetic rate, with native species showing a reduced rate in burned soils, which was offset by microbiome inoculation, while non‐native species were unaffected by both treatments. Survival probability of native species declined in burned soil, but was the same in burned‐inoculated soil as in unburned soil. That of non‐native species was unaffected by burning or by inoculation with the native microbiome. Synthesis and applications. Native microbiomes are evidently promising tools to safeguard ecosystem functionality and mitigate species extinction risks arising from climate change and human‐induced wildfires. We advocate integrating microbiomes into future active restoration strategies for fire‐affected ecosystems.

Non-adaptedness and vulnerability to climate change threaten Plathymenia trees (Fabaceae) from the Cerrado and Atlantic Forest

Climate change is increasing species extinction risk. The ability of a species to cope with climate change can be quantified by projecting distribution models and by estimating the risk of non-adaptedness using genomic data. The Cerrado and the Atlantic Forest in Tropical South America are increasingly threatened by habitat loss and anthropogenic climate change. This work aims to evaluate the ecological and genomic vulnerability of Plathymenia taxa and its lineages, P. reticulata, a Cerrado species, and P. foliolosa, an Atlantic Forest species, to determine their current and future habitat suitability and the mismatch between current local adaptation with the expected climate changes. The species distribution models predicted a high range loss for the Plathymenia lineages. The genotype-environment association analyses showed that the Plathymenia lineages have populations adapted to different precipitation and temperature seasonality regimes. The genomic offset analyses predict a mismatch between local adaptations and future climate for the Plathymenia indicating a high risk of non-adaptedness, especially in the pessimistic scenario. Our results show an elevated extinction risk of the species due to climate change. We suggest reevaluating the extinction risk and management of the Plathymenia species separately based on their differences in vulnerability to climate change.

Distributional response of the rare and critically endangered Ilex nanchuanensis to climate change in East Asia

Abstract Global climate change, dominated by climate warming, is seriously affecting the balance of global ecosystems, but the risk of species extinction is particularly high in low-altitude mountain areas. To clarify the response of the endemic and critically endangered species Ilex nanchuanensis to climate change, this study used the MaxEnt model to simulate and predict the potential habitat of I. nanchuanensis during the Last Interglacial, Last Glacial Maximum, the current period, and two future periods (the 2050 s and 2070 s). The results showed that the hottest monthly minimum temperature is the most important climatic factor affecting the geographical distribution of I. nanchuanensis. Furthermore, I. nanchuanensis will be at risk of population shrinkage and extinction in the future, with the center of mass moving further northwest as concentrations of greenhouse gases increase, especially in the 2070 s, when its geographical distribution shrinks the most under the RCP6 scenario. Therefore, to actively respond to the impacts of climate change, protected areas should be established around the geographical distribution centers of species, and core, buffer, and experimental areas should be scientifically and rationally delineated for the conservation and cultivation of germplasm resources.

How biotic interactions structure species' responses to perturbations.

Predicting how ecological communities will respond to disturbances is notoriously challenging, especially given the variability in species' responses within the same community. Focusing solely on aggregate responses may obscure extinction risks for certain species owing to compensatory effects, emphasizing the need to understand the drivers of the response variability at the species level. Yet, these drivers remain poorly understood. Here, we reveal that despite the typical complexity of biotic interaction networks, species' responses follow a discernible pattern. Specifically, we demonstrate that the species whose population abundances are most reduced by biotic interactions-which are not always the rarest species-are those that exhibit the strongest responses to disturbances. This insight enables us to pinpoint sensitive species within communities without requiring precise information about biotic interactions. Our novel approach introduces avenues for future research aimed at identifying sensitive species and elucidating their impacts on entire communities.

Rapidly Evaluating Species at Risk Using Endemic Plants of Kosrae, Federated States of Micronesia

The International Union for Conservation of Nature (IUCN)'s Red List of Threatened Species is regarded as the primary source of global extinction risk for species. Despite this importance, the IUCN has assessed less than 20% of the world′s estimated 400,000 flowering plants due to issues like insufficient data or a lack of experts. Thousands of conservation status assessments were generated recently in response to the call to action by the revised Target 2 of the Global Strategy for Plant Conservation (GSPC), “An assessment of the conservation status of all known plant species, as far as possible, to guide conservation action.” Accelerated extinction risk assessments are needed to identify species that are most at risk of extinction, which can then be thoroughly evaluated by the Red List assessment procedure. The land area in the Pacific Islands is significantly smaller than in other parts of the world. Plant species restricted to these islands may be identified as “At Risk” due to the limited land area of these islands, despite being widespread locally. Distribution and abundance data of single-island endemic plant taxa of Kosrae, Federated States of Micronesia, are analyzed and combined with digital elevation model files from this island, ArcGIS, and herbarium data, to calculate the percentage of land area that is available within a species′ elevational occurrence, a metric we have coined the Extent of Inhabitable Elevation of Island Occurrence (EIEIO). This metric can be used as a streamlined system to rapidly identify species that need plant conservation attention and allows for a swifter response to Target 2 of the GSPC.

Cumulative human impacts on global marine fauna highlight risk to biological and functional diversity.

Anthropogenic stressors to marine ecosystems from climate change and human activities increase extinction risk of species, disrupt ecosystem integrity, and threaten important ecosystem services. Addressing these stressors requires understanding where and to what extent they are impacting marine biological and functional diversity. We model cumulative risk of human impact upon 21,159 marine animal species by combining information on species-level vulnerability and spatial exposure to a range of anthropogenic stressors. We apply this species-level assessment of human impacts to examine patterns of species-stressor interactions within taxonomic groups. We then spatially map impacts across the global ocean, identifying locations where climate-driven impacts overlap with fishing, shipping, and land-based stressors to help inform conservation needs and opportunities. Comparing species-level modeled impacts to those based on marine habitats that represent important marine ecosystems, we find that even relatively untouched habitats may still be home to species at elevated risk, and that many species-rich coastal regions may be at greater risk than indicated from habitat-based methods alone. Finally, we incorporate a trait-based metric of functional diversity to identify where impacts to functionally unique species might pose greater risk to community structure and ecosystem integrity. These complementary lenses of species, function, and habitat provide a richer understanding of threats to marine biodiversity to help inform efforts to meet conservation targets and ensure sustainability of nature's contributions to people.

POPULATION STUDY AND REASSESSMENT OF CONSERVATION STATUS OF AN ENDEMIC DIPTEROCARP, Hopea bilitonensis

Hopea bilitonensis is a rare, endemic Dipterocarp species in the Malesian Region. It has a disjunct distribution pattern, where main populations occur on the sandy soils of Bangka Belitung Islands of Indonesia and some on limestone forest in Perak, Peninsular Malaysia. Current global status of this species based on the IUCN Red List is Critically Endangered (CR) A1c+2c, B1+2c (1998) whilst in Malaysia it is assessed as CR A4c, B1ab(iii) (2010). A reassessment of the conservation status of this species is needed to provide the most current population status and its extinction risk, especially in Indonesia using the IUCN Red List Categories and Criteria version 3.1. This study was conducted to survey and assess the current populations of this species in Belitung Island where most population occurred and subsequently to recommend its current conservation status. The species is in fact still common in the island, stretching along the main roads and surrounding forests. Using the purposive sampling method, we developed a total of 16 plots of 20x20m each in 10 different locations across the Belitung Island. A total of 730 individuals were found with stem diameter at breast height ranged from 2cm to more than 30cm. For global reassessment, based on the current distribution and herbarium records, the calculated extent of occurrence (EOO) is 108,128.642km2, whilst the area of occupancy (AOO) is 84 km2. However, the species clearly has a restricted distribution and is facing high threats due to frequent timber harvesting and continuing decline of the EOO and AOO. The species extinction risk was then assessed by using five quantitative criteria of the IUCN. Therefore, we propose H. bilitonensis category is considered to be Endangered (EN) based on A2c, B2ab(i,ii,iii,iv,v) and C2a(i) criteria.

Identification of biodiversity hotspots for threatened mammal species under future climate

Climate change has led to changes in distribution, movement, and extinction risk for various wildlife species, raising concern among conservation biologists. Therefore, this study aimed to predict suitable habitats that help wildlife managers protect wildlife more effectively. To achieve our aim, we first evaluated the vulnerability of 183 terrestrial mammal species identified in Iran under climate change based on habitat, phenology and physiology, biotic interactions, and national protection status. Then, MaxEnt was used to predict the potential changes in the distribution of vulnerable species due to climate change in the next 70 years under two scenarios: SSP126 and SSP585. In the third step, a framework was employed to identify existing and future hotspots of mammal biodiversity, and the potential changes in these areas for the species were predicted in the next 70 years. The results showed that 69 terrestrial mammals were vulnerable to climate change. Subsequently, 15 species wereselected for modeling based on presence records and vulnerability to climate change. The species modeling results showed that 42 % of Iran’s habitats are currently suitable for the studied mammal species. In the future, under both climate scenarios, biodiversity hotspots for these species will be reduced, and approximately 37 % of Iran’s habitats will be suitable for the species. As a result, the current conservation network will have diminished capacity to protect the species from climate change.

Predicting the climatic suitability of non-native drought resistant trees in the face of desertification – A case study with Argania spinosa in the Iberian Peninsula

Climate change is driving a poleward shift in the optimal distributions of terrestrial organisms, including trees. Consequently, trees are expected to decrease in climatically unfavourable areas as their optimal climatic conditions shift poleward. This is the case of Mediterranean High Nature Value agroforestry systems in Iberian Peninsula, dominated by holm oaks (Quercus rotundifolia) and cork oaks (Quercus suber), which are expected to shift their future distribution northward. Failure to keep pace with climate warming poses a heightened risk of extinction for these tree species, as well as the loss of crucial ecosystem services they provide. A similar situation is found for argan trees (Argania spinosa) in the southwestern region of Morocco, where it also supports an agroforestry system. The optimum climate for these trees is also shifting northward, toward the Iberian Peninsula. As the argan tree thrives in more arid conditions with irregular precipitation, the future climatic conditions in the Iberian Peninsula may become favourable for the persistence of this tree. In light of this situation, the assisted colonization of the argan tree could potentially contribute to protecting and preserving the tree-associated ecosystem services in Iberian Peninsula. We conducted climate suitability modelling using maximum entropy approach, for both the current and future timeframes, for North of Morocco and Algeria (native range) and the whole Iberian Peninsula (non-native range). Accordingly, there appears to be a significant area with highly suitable climatic conditions (>80 %) for argan tree occurrence, covering approximately 6.7 % of the territory, over 38,000 km2. This area is projected to increase significantly in the future, covering 9–22 % of the territory, or about 55,000 and 127,000 km2. With this study, we aim to contribute to the discussion on the benefits of assisted colonization of argan trees into Iberian Peninsula, as well as potential drawbacks such as the risk of this species becoming invasive.

Predicting Conservation Status of Testudoformes under Climate Change Using Habitat Models.

Climate change promotes variations in distribution ranges, potentially leading to biodiversity loss and increased extinction risks for species. It is crucial to investigate these variations under future climate change scenarios for effective biodiversity conservation. Here, we studied the future distribution ranges of 268 Testudoformes species under climate change using habitat models, specifically species distribution models (SDMs), to assess their conservation status. Our results have indicated that over half of species are projected to experience declines in their potential distribution ranges under two scenarios. In particular, we found that three critically endangered species-Three-striped roofed turtle (Batagur dhongoka), Durango mud turtle (Kinosternon durangoense), and Colombian mud turtle (Kinosternon dunni)-displayed extraction of their distribution ranges and faced extinction under global climate change. Additionally, our analysis revealed that the potential distribution ranges of some species might increase under future climate scenarios. However, these findings must be interpreted with caution as they do not account for other significant factors such as biological invasions, population structure, land-use change, anthropogenic disturbances, and inter-organism interrelationships. Future studies should incorporate these factors to provide a more comprehensive assessment of extinction risks. Our findings suggest that climate change, in conjunction with habitat degradation and human activities, must be considered when assessing the extinction risks of Testudoformes.

Inferring the extinction risk of marine fish to inform global conservation priorities.

While extinction risk categorization is fundamental for building robust conservation planning for marine fishes, empirical data on occurrence and vulnerability to disturbances are still lacking for most marine teleost fish species, preventing the assessment of their International Union for the Conservation of Nature (IUCN) status. In this article, we predicted the IUCN status of marine fishes based on two machine learning algorithms, trained with available species occurrences, biological traits, taxonomy, and human uses. We found that extinction risk for marine fish species is higher than initially estimated by the IUCN, increasing from 2.5% to 12.7%. Species predicted as Threatened were mainly characterized by a small geographic range, a relatively large body size, and a low growth rate. Hotspots of predicted Threatened species peaked mainly in the South China Sea, the Philippine Sea, the Celebes Sea, the west coast Australia and North America. We also explored the consequences of including these predicted species' IUCN status in the prioritization of marine protected areas through conservation planning. We found a marked increase in prioritization ranks for subpolar and polar regions despite their low species richness. We suggest to integrate multifactorial ensemble learning to assess species extinction risk and offer a more complete view of endangered taxonomic groups to ultimately reach global conservation targets like the extending coverage of protected areas where species are the most vulnerable.

Benchmarking imputation methods for categorical biological data

Abstract Trait datasets are at the basis of a large share of ecology and evolutionary research, being used to infer ancestral morphologies, quantify species extinction risks, or evaluate the functional diversity of biological communities. These datasets, however, are often plagued by missing data, for instance, due to incomplete sampling, limited data and resource availability. Several imputation methods exist to predict missing values and recent studies have explored their performance for continuous traits in biological datasets. However, less is known about the accuracy of these methods for categorical traits. Here we explore the performance of different imputation methods on categorical biological traits combining phylogenetic comparative methods, machine learning and deep learning models. To this end, we develop an open‐source R package, to impute trait data while integrating a simulation framework to evaluate their performance on synthetic datasets. We run a range of simulations under different missing rates, mechanisms, biases and evolutionary models. We propose an integration between phylogenetic comparative methods and machine learning imputation, and an ensemble approach, in which selected imputation methods are combined. Our simulations show that this approach provides the most robust and accurate predictions. We applied our imputation pipeline to an incomplete trait dataset of 1015 elasmobranch species (i.e. sharks, rays and skates) and found a high imputation accuracy of the predictions based on an expert‐based assessment of the missing traits. Overall, our R package facilitates the comparison of multiple imputation methods and allows robust predictions of missing trait values. Our study highlights the benefits of coupling phylogenetic evolutionary models with machine learning inference to augment incomplete biological datasets.

Methodology for identifying the potential Alliance for Zero Extinction (AZE) tree species on a global scale

AbstractThere is a biodiversity crisis, and to prevent extinctions the most important sites to be effectively conserved must be identified. Key Biodiversity Areas (KBAs) include sites of importance for species survival. Alliance for Zero Extinction (AZE) sites, a subset of KBAs, contain ≥95% of the population of highly threatened species. Currently, only 47 tree species have been identified using the AZE criteria. The Global Tree Assessment, assessing the extinction risk of the world's tree species, has enabled trees to be incorporated into KBA and AZE sites. Here we present a methodology to utilize data from the IUCN Red List to identify potential AZE species for trees. This 10‐part methodology identified 2909 tree species as potential AZE species across the world, representing at least 5% of described tree species. As further tree species are assessments are published on the IUCN Red List, this methodology will be important for identifying potential AZE species. The methodology can be applied and adapted to any taxa on the IUCN Red List. This analysis serves as a prioritization mechanism for identifying species in urgent need of conservation action to prevent extinctions. The species identified can feed into national KBA identification efforts.

Predicting the Threat Status of Mosses Using Functional Traits.

Mosses are an early lineage of the plant kingdom, with around 13,000 species. Although an important part of biodiversity, providing crucial ecosystem services, many species are threatened with extinction. However, only circa 300 species have so far had their extinction risk evaluated globally for the IUCN Red List. Functional traits are known to help predict the extinction risk of species in other plant groups. In this study, a matrix of 15 functional traits was produced for 723 moss species from around the world to evaluate the potential of such predictability. Binary generalized linear models showed that monoicous species were more likely to be threatened than dioicous species, and the presence of a sporophyte (sexual reproduction), vegetative reproduction and an erect (straight) capsule instead of a pendent (immersed) one lowers the risk of species extinction. A longer capsule, seta and stem length, as well as broader substrate breadth, are indicative of species with a lower risk of extinction. The best-performing models fitted with few traits were able to predict extinction risks of species with good accuracy. These models applied to Data Deficient (DD) species proved how useful they may be to speed up the IUCN Red List assessment process while reducing the number of listed DD species, by selecting species most in need of a full, detailed assessment. Some traits tested in this study are a novelty in conservation research on mosses, opening new possibilities for future studies. The traits studied and the models presented here are a significant contribution to the knowledge of mosses at risk of extinction and will help to improve conservation efforts.

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

AbstractAssessing 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.

A global map of species at risk of extinction due to natural hazards

An often-overlooked question of the biodiversity crisis is how natural hazards contribute to species extinction risk. To address this issue, we explored how four natural hazards, earthquakes, hurricanes, tsunamis, and volcanoes, overlapped with the distribution ranges of amphibians, birds, mammals, and reptiles that have either narrow distributions or populations with few mature individuals. To assess which species are at risk from these natural hazards, we combined the frequency and magnitude of each natural hazard to estimate their impact. We considered species at risk if they overlapped with regions where any of the four natural hazards historically occurred (n = 3,722). Those species with at least a quarter of their range subjected to a high relative impact were considered at high risk (n = 2,001) of extinction due to natural hazards. In total, 834 reptiles, 617 amphibians, 302 birds, and 248 mammals were at high risk and they were mainly distributed on islands and in the tropics. Hurricanes (n = 983) and earthquakes (n = 868) affected most species, while tsunamis (n = 272), and volcanoes (n = 171) affected considerably fewer. The region with the highest number of species at high risk was the Pacific Ring of Fire, especially due to volcanoes, earthquakes, and tsunamis, while hurricane-related high-risk species were concentrated in the Caribbean Sea, Gulf of Mexico, and northwestern Pacific Ocean. Our study provides important information regarding the species at risk due to natural hazards and can help guide conservation attention and efforts to safeguard their survival.

Assessing Reptile Conservation Status under Global Climate Change

Global climate change drives variations in species distribution patterns and affects biodiversity, potentially increasing the risk of species extinction. Investigating the potential distribution range of species under future global climate change is crucial for biodiversity conservation and ecosystem management. In this study, we collected distributional data for 5282 reptile species to assess their conservation status based on distributional ranges using species distribution models. Our predictions indicate that the potential distribution ranges for over half of these species are projected to decrease under different scenarios. Under future scenarios with relatively low carbon emissions, the increase in the number of threatened reptiles is significantly lower, highlighting the importance of human efforts. Surprisingly, we identified some endangered species that are projected to expand their distribution ranges, underscoring the potential positive effects of climate change on some special species. Our findings emphasize the increased extinction risk faced by reptile species due to climate change and highlight the urgent need to mitigate the effects of habitat degradation and human activities on their potential distribution in the future.

Thirty years of conservation breeding: Assessing the genetic diversity of captive Livingstone's fruit bats.

Fruit bats (genus Pteropus) are typically island-endemic species important in seed dispersal and reforestation that are vulnerable to increased extinction risk. An effective method of reducing extinction risk in vulnerable species that cannot be conserved in their native habitat is establishing an ex-situ captive breeding programme. Due to anthropogenic threats and low population numbers, in the early 1990s, a captive breeding programme was established at Jersey Zoo, British Isles, for Critically Endangered Livingstone's fruit bats (Pteropus livingstonii). Here we use six polymorphic microsatellite loci to assess genetic diversity in the captive breeding population of Livingstone's fruit bats (P. livingstonii), 30 years after the programme's establishment, investigating change over generations and comparing our findings with published data from the wild population. We found no significant difference between the genetic diversity in the captive and wild populations of Livingstone's fruit bats (P. livingstonii), in both expected heterozygosity and allelic richness. The captive population has retained a comparable level of genetic diversity to that documented in the wild, and there has been no significant decline in genetic diversity over the last 30 years. We advise that a full pedigree of the paternal lineage is created to improve the management of the captive breeding programme and further reduce the possibility of inbreeding. However, it appears that the captive breeding programme is currently effective at maintaining genetic diversity at levels comparable to those seen in the wild population, which suggests reintroductions could be viable if genetic diversity remains stable in captivity.