Conservation Biology

To prevent species extinctions, targeted action must focus on areas of threatened biodiversity facing intense human pressures. This objective is even more important in the run-up to 2030, the target date to conserve 30% of lands and waters globally. Conservation Imperatives (unprotected terrestrial sites that harbour rare, range-restricted, and threatened species) are critical to preventing imminent species losses. To prioritize among the 16,825 Conservation Imperatives Sites spanning 1.64 million km2, we ranked each site using a prioritization framework based on four criteria: number of threatened species per site; irreplaceability of the site; the proportion of an ecoregions remaining habitat contained in the site; and conversion pressure. Our approach prioritizes 1,667 sites representing 501,426 km2, or 0.37% of Earths terrestrial surface, most in need of urgent protection, with 87.34% of these sites occurring in 20 countries and in 250 ecoregions. This prioritization directly addresses the concern that protected areas must be targeted to protect endangered species, habitats and populations: 33.46% of the prioritized Conservation Imperatives Sites scored higher in irreplaceability than 90% of existing protected areas. Additionally, 51.53% are within 2.5 km2 of an existing protected area, making extending protection or restoring connectivity more feasible. Targeting conservation actions, especially in this small set of countries and ecoregions identified here, would contribute "high quality" areas for biodiversity as part of reaching the 30% coverage target by 2030.

Effective biodiversity conservation requires tools that can identify priority areas under growing human pressures. Building on the concept of global biodiversity hotspots, we present a transparent and repeatable approach to mapping conservation priorities using data for 33,604 species of terrestrial vertebrates from the IUCN Red List. This framework expands the taxonomic scope of previous efforts and integrates updated information on key human-driven threats to biodiversity. We identify that around 13% of Earths terrestrial surface qualifies as vertebrate conservation hotspots, often shaped by distinct combinations of species groups and threats. These results highlight the need for tailored, context-specific conservation strategies. By providing a robust method to guide spatial prioritization, our work supports more effective implementation of conservation targets in a rapidly changing world.

The 36 global biodiversity hotspots harbor a disproportionate share of the worlds endemic species, making their conservation critical for planetary health. Traditionally hotspots were defined as ecoregions with [≥]1,500 endemic vascular plant species and >70% natural habitat loss; this relied heavily on expert judgment, with subjective assessments of endemism and habitat loss applied. Challenges in defining endemism, quantifying habitat loss, and the global unevenness in available vascular plant data have hindered hotspot identification over the past decades. Here, we built a global dataset of 150,487 rare vascular plants, identified from 88.1% of the worlds known vascular species, and recognize hotspots based on their richness using three complementary conservation targets and algorithms. We then quantified natural habitat loss and habitat fragmentation using high-resolution remote sensing data and assessed the diversity and distribution of terrestrial vertebrates within these newly identified hotspots. Our data-driven method recovered all the 36 established global biodiversity hotspots, revised 17, and identified 11 new hotspots spanning diverse ecosystems across six continents. These 47 hotspots cover 26.63% of global land area, yet contain 83.8% of rare vascular plants, 92.4% of mammals, 96.1% of birds, 87.8% of reptiles, and 95.0% of amphibians. Collectively, they encompass >89% of terrestrial vertebrates classified as IUCN threatened species. Only 10 hotspots have undergone [≥]70% habitat loss, and the lack of a consistent relationship with habitat fragmentation suggests that this criterion is not globally applicable. Effectively protecting [~]27% of Earths land could theoretically safeguard >89.8% of threatened terrestrial species and >67% of threatened terrestrial species hotspot area, assuming effective protection of the identified biodiversity hotspots. Targeted conservation efforts within these global biodiversity hotspots can meet the established biodiversity targets of the Kunming-Montreal Global Biodiversity Framework as well as post-2030 biodiversity targets. Most importantly, our framework enables conservation scientists to iteratively identify and update global biodiversity hotspots in step with growing global biodiversity data.

BackgroundA structural governance failure sits at the intersection of international biodiversity law and the digital genomics revolution. The Convention on Biological Diversity (CBD) and the Nagoya Protocol on Access and Benefit-Sharing (ABS) were designed to ensure that countries of biological origin share equitably in commercial benefits from their genetic resources. Critically, these instruments apply exclusively to non-human genetic resources: plants, animals, fungi, and microbiota. Human genetic resources are deliberately excluded from the CBD and Nagoya ABS framework and are governed separately through bioethics instruments, including the World Health Organization (WHO) framework and the Declaration of Helsinki. This study focuses on non-human digital sequence information (DSI), nucleotide and protein sequence data derived from non-human organisms deposited in open-access databases, which underpins industries generating over USD 1.56 trillion in annual revenue. Africa, hosting approximately 25% of global terrestrial species and nine of the worlds 36 biodiversity hotspots, provides a disproportionate share of the genetic resources from which non-human DSI is derived, yet receives negligible monetary returns because digitisation severs the traceability chain that ABS governance requires. Human genomic data is presented here solely as a secondary indicator of Africas broader infrastructure; it does not constitute the legal basis for Africas modelled allocation share under the Cali Fund. ObjectivesThis study systematically characterises (i) Africas non-human biodiversity endowment as the basis for Cali Fund claims; (ii) ABS governance readiness across 54 African Union (AU) member states; (iii) the commercial trajectories of non-human DSI-dependent industries and projected Cali Fund benefit-sharing flows; and (iv) Africas human genomic representation as a secondary infrastructure indicator, explicitly distinguished from the non-human DSI benefit-sharing argument. MethodsA structured evidence synthesis was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 reporting elements, where applicable to a secondary data analysis design. Literature was searched across PubMed, Scopus, Web of Science, Google Scholar, and official repositories of the CBD, Food and Agriculture Organization of the United Nations (FAO), International Union for Conservation of Nature (IUCN), and United Nations Environment Programme (UNEP). The search was restricted to January 2022 - April 2026 to capture post-Kunming-Montreal Global Biodiversity Framework (KMGBF) literature. A total of 412 records were identified before screening; 34 peer-reviewed articles and 19 institutional documents met all inclusion criteria. Quantitative Cali Fund scenario modelling used the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) and KPMG (2024) non-human DSI sector revenue baseline (CBD/WGDSI/2/2/Add.2). The 12.5% net profit margin is a cross-sector proxy from that study; actual margins vary by sector. Africas modelled allocation share (20-25%) is the authors analytical construct based on Africas non-human species richness and hotspot share; it is not an internationally agreed formula. ResultsAfricas non-human biodiversity endowment is exceptional: 25% of terrestrial species, nine of 36 biodiversity hotspots, and the worlds second-largest tropical forest system. Non-human DSI from African genetic resources is a critical input to industries generating USD 1.56 trillion annually, yet Africa contributes a marginal and unmeasured fraction of International Nucleotide Sequence Database Collaboration (INSDC) sequences. As a secondary indicator, 94.48% of genome-wide association study (GWAS) participants as of 2024 were of European ancestry (Corpas et al., 2025); this human genomic data is presented for contextual illustration only and is not the basis for Africas Cali Fund modelled allocation share. Zero African Union member states have enacted legislation explicitly covering non-human DSI in their ABS framework. Africas modelled allocation share ranges from USD 312 million (Scenario A, 20% weight) to USD 5.83 billion (Scenario C, 25% weight) annually. ConclusionsAfrica is among the most biologically rich continents on Earth for non-human life, yet structurally excluded from the benefit-sharing framework the CBD intended to create. The Cali Fund represents the first mechanism capable of correcting this at scale. Realising Africas modelled allocation share requires urgent legislative reform, institutional capacity investment, sequencing infrastructure development, and a coordinated African position at COP17 scheduled in Yerevan, October 2026.

Effective conservation planning increasingly relies on species distribution models (SDMs) to guide where actions deliver the greatest biodiversity benefits through spatial conservation prioritization. However, SDMs are inherently uncertain, and this uncertainty propagates through prioritization processes, affecting the identification of priority areas and influencing conservation decisions. Here, we evaluate whether correcting SDM overprediction reduces uncertainty propagation into spatial conservation prioritization. Using two large European datasets of vertebrates and invertebrates, we compared unconstrained SDMs with models corrected for overprediction through a Bayesian integration of occurrences, expert range maps, and habitat suitability. We found that overprediction correction reduced spatial and performance uncertainty, with uncertainty strongly structured by model and algorithm choice and amplified when overprediction was not corrected. Although no single modelling adjustment fully eliminates uncertainty propagation from SDMs into prioritization, we demonstrate that overprediction correction consistently reduces it across datasets, taxa, and modelling approaches, highlighting its importance for robust conservation planning.

Native vegetation protection is a key strategy for delivering both biodiversity and climate benefits, and protected areas have been widely adopted to keep tropical biomes standing. Yet deforestation is driven by interrelated environmental and social factors, and the effectiveness of protected areas varies considerably across space. Here, we evaluated the impact of 802 protected and conserved areas in the Brazilian Amazon on preventing vegetation loss and avoiding carbon emissions over the past 40 years using statistical matching to address the location bias of protection. We found that protected areas were effective throughout the study period, reducing the probability of deforestation per km2 by an average of 0.5 percentage points per year. While the Amazon biome lost 14% of its native vegetation between 1986 and 2024, protected areas prevented the deforestation of 290,436 km2, nine times their actual internal loss. They also stored 45,336 Mt of carbon in 2016 (61% of the Amazon stock) and prevented the emission of 7,300 Mt of CO2 by 2024. Deforestation inside the areas and remoteness reduced their impact, while areas that were initially more preserved were more effective. Area size and age had no influence over impact once we analyzed the amount of avoided deforestation per size and age. Impact also varied across Brazilian states, highlighting the role of regional context. All three protection categories (conservation units, indigenous lands, and quilombola territories) showed a positive mean impact, indicating that each, in aggregate, contributes to reducing deforestation. These findings provide robust evidence of the substantial role of Amazonian protected areas in habitat conservation and climate mitigation, while underscoring that this contribution remains undervalued. We advocate for strategically expanding protection to areas of greatest potential impact, and for securing adequate funding to ensure protected areas can fulfill that potential.

AimBiodiversity-rich regions often lack the scientific infrastructure needed to document and curate their own biodiversity, creating inequalities in access to taxonomic reference material. We investigated how biological, institutional, and geopolitical factors shape the retention, extraction, and appropriation of reptile holotypes, the name-bearing specimens upon which species descriptions are based. LocationGlobal. TaxonReptiles. MethodsWe compiled a historical dataset of reptile holotype origins and destinations spanning 1758-2024 to reconstruct long-term patterns of retention and international specimen flows. We then quantified species-level holotype retention, holotype flows between country pairs, and country-level patterns of retention, appropriation, and network centrality for the period 1990-2024, and used generalised linear mixed models to assess the biological, institutional, and geopolitical determinants of these contemporary circulation processes. ResultsAlthough nearly 90% of reptile species described originated in the Global South, less than a quarter of their holotypes remain housed there. Historically, exported holotypes consistently outnumbered retained holotypes on a decadal basis until the early twenty-first century. Retention was promoted by local scientific capacity, institutional infrastructure, collector involvement in species descriptions, and environmental governance. In contrast, extraction was concentrated in highly endemic regions with limited scientific infrastructure and was associated with taxonomic revisions, socioeconomic interest, and disparities in political stability and colonial history. Appropriation of foreign holotypes was greatest in countries with high research investment, strong environmental governance, and historical geopolitical influence. Main conclusionsGlobal patterns of holotype circulation reflect a persistent geography of scientific inequality. The distribution of taxonomic reference material emerges from the interaction of retention, extraction, and appropriation processes, linking local biodiversity discovery to uneven global scientific capacity. Reducing these inequalities will require investments in taxonomic expertise, institutional infrastructure, and governance frameworks that promote more equitable stewardship of biodiversity knowledge and its material foundations.

Accelerating environmental change in the Antarctic and Southern Ocean (ASO) necessitates robust extinction risk assessments to inform conservation priorities and track progress towards global biodiversity targets. Nevertheless, no systematic, region-wide baseline of extinction risk currently exists for tracking ASO biodiversity responses to ongoing change, a significant barrier to global biodiversity monitoring. Here, we present the first comprehensive synthesis of extinction risk knowledge spanning plants, animals, and fungi across the ASO, examining biases in current assessments, the distribution of Threatened species and their associated threats. In the absence of a complete regional species checklist, species were compiled from >6,800,000 occurrences and existing checklists, yielding 5,403 assessments representing 2,806 species using a data-inclusive workflow that increased available assessments by over three-fold. Assessments are heavily biased towards vertebrates (56% assessed), while invertebrates, despite their ecological prevalence, are markedly underrepresented (4% assessed). Among vertebrates, mammals have the highest proportion of Threatened species (35%), while ASO birds are disproportionately Threatened (27%) compared to the global average (12%) with the greatest threat for ASO species being Biological Resource Use. Despite more Threatened species in the sub-Antarctic islands and the Antarctic Peninsula, relative to assessment effort, these regions had fewer Threatened species than expected, indicating these areas may function as refugia. These pronounced assessment biases highlight the need for more balanced, representative, and data-inclusive extinction risk assessments to be able to effectively detect conservation status change. This work represents an important step in ensuring ASO representation in global biodiversity monitoring frameworks strengthening the capacity of these frameworks to detect, attribute, and respond to future biodiversity changes.

There is an urgent need to gather data on harvest rates of waterbirds in Europe to assess the sustainability of hunting. Estimates of total waterbird harvest in the United Kingdom (UK) and the relative harvest of different huntable species come from two separate surveys, the Value of Shooting (PACEC 2014) and National Gamebag Census (NGC, Aebischer 2019), and these have been recently used to explore the likelihood of unsustainable harvests of wild waterbirds by UK hunters (Ellis and Cameron 2022; Madden et al., 2025). The reliability of these sustainability estimates depends on how representative the original surveys are of hunter behaviour and success. There are also 1-3 million released game-farm mallard (Anas platyrhynchos) that takes up considerable and unquantified proportions of the UK waterbird harvest. Here we explore uncertainties in the UK winter harvest of wild waterfowl by comparing estimates from the NGC dataset with those from the Crown Estate coastal hunting clubs, and a novel approach using analysis of social-media images (2019/20 to 2023/24). We explore the difference in species-specific harvest with and without the uncertainties in the number of released mallard and the total number of duck harvested in the UK. Waterbird harvest estimates differ markedly depending on the input dataset and whether released mallard are included in the analysis. Confidence intervals of each estimate are inflated by uncertainties in the number of released game-farm mallard contributing to, and the size of that national bag. Estimates extrapolated from social media suggest the national harvest of several species may be considerably larger than the corresponding NGC estimates (e.g. Teal *2.07 and gadwall *11.2), while mallard harvests away from formal shoots represented by NGC are significantly lower (*0.71). Excluding released mallard reduces the statistical estimate of total wild duck harvest by 56-63%, which would have biologically significant effects if realised.

Italy, one of Europe's most biodiverse countries, is expected to undergo landscape-wide nature recovery thanks to the EU Nature Restoration Regulation. National red lists represent critical instruments for informing conservation strategies at finer geographic resolutions and prioritizing taxa of national importance; yet the taxonomic completeness of Italian red lists remains unquantified in relation to national biodiversity. Equally, no systematic evaluation has been conducted on the representation of threatened and endemic Italian taxa within European and international conservation directives and treaties. We present the first comprehensive review of threat status and policy inclusion of Italian biodiversity, encompassing animals, plants, fungi, lichens, and algae. We cross-referenced national species checklists with Italian, European, Mediterranean, and global IUCN red lists, alongside policy annexes from the Birds and Habitats Directives, the Bern and Barcelona Conventions, and CITES. Our dataset comprised 76,845 taxa, of which 8,389 are endemic; yet red list assessments exist for only 10% of this total (7,349 taxa, including 1,700 endemics). Conservation policy coverage is even more restrictive: only 1,346 taxa are listed under at least one legislative instrument, with only half of these classified as threatened. This constitutes a compounding double bottleneck with most of the Italian biodiversity remaining both unassessed and unprotected and systematically biasing conservation policy toward an unrepresentative fraction of national biodiversity. We recommend accelerated national assessments and urgent establishment of a national biodiversity priority list founded on transparent prioritization protocols. This would complement ecosystem-based interventions mandated by the Nature Restoration Regulation while correcting for vertebrate-centred biases.

Controlling invasive species is a global conservation priority but is typically resource-limited, necessitating strategies to optimize control. Spatial prioritization methods can improve the efficiency of invader control by quantifying the benefits, costs, and risks of alternative intervention strategies. Yet prioritization designs are sensitive to the distinction between protecting native populations that are currently sympatric with invaders versus safeguarding presently allopatric native populations by preventing invader expansion. Gaining a better understanding of this distinction stands to improve our ability to prioritize the management of invaders whose distributions--and thus impacts on native species--are dynamic. We asked how prioritization designs addressing current versus future invader threats affected tradeoffs among focal species protection, biodiversity conservation, disturbance risk, and overlap with existing conservation infrastructure. As a case study, we spatially prioritized population control of invasive barred owls (Strix varia) in the northwestern US. We found that distinguishing between current versus future threats posed by barred owls to the native spotted owl (S. occidentalis) strongly mediated whether invader control stood to benefit native at-risk animal communities. Furthermore, this distinction also affected the degree to which population control would overlap with fire risk and federally protected forests, both of which plausibly affect the viability and success of conservation action. These results thus illustrate that deciding to prioritize the control of invaders based on their current versus future impacts on native species can dramatically affect the distribution and characteristics of high-priority areas for management. Our findings also directly inform control of barred owls in the northwestern US: we found that prioritizing future threats to spotted owls could protect at-risk amphibian communities from novel barred owl predation, but that high fire risk and minimal protected forest may complicate implementation. Thus, in both our system and more broadly, spatial prioritization methods are an important tool for quantitative, reproducible, and successful invader control.

Governments, civil society organizations and businesses often lack the biodiversity data they need for decision-making and adaptive management, impacting their planning, reporting and performance. We explored the biodiversity data needs of such actors in Colombia, Ghana and Switzerland to identify factors affecting data availability and use. Responses to questionnaire surveys showed that the data types with the biggest gaps between user needs and access were progress on conservation or sustainability actions, species populations, habitat state and ecological risk. The most frequent data blockages related to inadequate resources and organizational capacity. Obstacles significantly associated with a lack of primary data included an absence of organizational biodiversity goals and monitoring systems. Problems accessing habitat quality and species abundance data were associated with data collection methods being unknown or unavailable. Businesses were more likely than other groups to need data on threats, perhaps reflecting the increasing importance of environmental risk to the corporate sector. Businesses are less likely to collect primary data or use secondary data and are significantly more likely to be unclear on what biodiversity indicators to use. Non-business organizations are significantly more likely to be unable to access data because of a lack of funding for data collection, analysis, and use. Our results highlight the need for stakeholders across sectors to work together to find common solutions to build and invest in monitoring capacity that unblocks the flow of biodiversity data.

iNaturalist has rapidly grown to become one of the largest contributors of global biodiversity data, being widely used in academic research, to support and inform applied conservation, and to help develop policy indicators for decision makers. However, the availability of iNaturalist data varies based on the digital platform it is accessed from. Here, we assess whether the pathway used to access iNaturalist data from three commonly available biodiversity data sources: iNaturalist, the Global Biodiversity Information Facility (GBIF) and ESRIs ArcGIS Online, alters occurrence record availability and downstream analyses for ecological inference. First, we investigate iNaturalist data availability on ArcGIS Online and find that the reduced field metadata for record location and obscuration information can lead to biased assumptions in the spatial ranges of sensitive species. Second, when assessing iNaturalist records available through GBIF, we find that restrictive Creative Commons observation licenses prevent an average of 26.1% of iNaturalist Research Grade records from being exported to GBIF, and this can lead to differences in environmental niche analysis when compared to datasets including all available research grade records. Understanding differences in platform licensing when integrating across biodiversity data repositories is another consideration for researchers and practitioners when conducting biodiversity assessments. Our results show that the pathway through which iNaturalist data are accessed can function as a methodological filter, potentially altering spatial coverage, the climatic conditions represented by occurrence datasets, and downstream ecological analysis.

The Natura 2000 network for protected areas is one of Europes main tool to address the loss of Biodiversity. Voluntary commitments of all 27 Member States aim for an extension to 30% of the European land and sea area by 2030. Despite the substantial efforts towards improving declining species and habitats across the continent and the limited success in measured improvements of biodiversity trends in the protected areas, the potential issue of fragmentation and configuration of the documented Natura 2000 sites has not been analysed in depth. This study presents an analysis of the full Natura 2000 data set of terrestrial and marine protected areas in Europe, to which extent documented sites are split up into smaller fragments, how their spatial configuration and shape might mitigate or invite edge effects, and which edge effects might be expected based on the surrounding land cover and land use matrix. Our results show a substantial fragmentation of the network, with four times more individual patches than recorded sites, and 75% of these patches being smaller than 1 km2. Across four size categories between smaller than 1 km2 and larger than 100 km2, about a quarter of patches show a spatial configuration that is likely to cause substantial edge effects due to a suboptimal ratio between area and perimeter. At the same time, many of the smallest patches are surrounded by a large share of sealed surfaces and agricultural areas within a 500m radius. Considering fragmentation and edge effects in future reporting, monitoring and planning of additional designations and restoration activities could close an important gap in understanding causes for continuing declines of Europes biodiversity and highlight pathways to mitigate them.

Despite substantial global commitments to expand protected-area networks, the strategic allocation of limited resources remains challenging. Spatial conservation planning helps identify priority regions that maximise conservation benefits per unit area. Yet, they also tend to neglect two fundamental aspects of conservation: climate-driven range shifts and the representation of environmentally distinct populations within species. Here, we propose a continental-scale conservation planning framework that explicitly accounts for both processes through novel routines implemented in the conservation planning software CAPTAIN. We apply this framework to European crop wild relatives (CWR), for which niche coverage is a focal priority, as it underpins their potential to support agricultural adaptation to future environmental stressors through breeding programs. Comparative analyses on a subset of 186 CWR associated with five focal crops show that accounting for range shifts and niche coverage leads to substantially different conservation priorities from those obtained with a baseline model based on current distributions only. These additions reduced the number of non-protected species by 64%, increased the average protected distribution range by 43%, increased mean niche coverage from 75.8% to 84.5% and reduced the number of species with less than half of their niche protected from 35 to 10. Applied to a more comprehensive checklist of 1,140 European CWRs, the final framework identifies continental-scale priority areas representing 93.5% of these taxa and includes 94.4% of its critically endangered species. Our results highlight the importance of incorporating both temporal dynamics and within-species environmental representation when designing conservation strategies under climate change. RepositoryThe repository will be made publicly accessible after publication at doi: https://10.5281/zenodo.19855597

1.AimThe Species Threat Abatement and Restoration (STAR) metric was developed to support setting and measuring progress towards science-based targets for species conservation, in alignment with the Kunming-Montreal Global Biodiversity Framework. The STAR metric quantifies the potential reduction in species global extinction risk achievable through actions to abate threats (START) and restore habitat (STARR). The STAR metric is used across multiple sectors to assess contributions to nature-positive species outcomes and implement action for biodiversity. Here we present a substantially enhanced global estimate of START for terrestrial vertebrates. Developed in response to user demand, this work integrates advancements in methodology and data quality, increased spatial resolution, and addition of reptile species. LocationGlobal Time PeriodCurrent Major taxa studiedTerrestrial vertebrates MethodsSTART was estimated at 1km2 resolution for 9,100 species of threatened and Near Threatened birds, mammals, amphibians and reptiles, using IUCN Red List assessments (version 2025-1) and area of habitat (AOH) maps generated using an advanced data-driven methodology and satellite-derived land-cover data. AOH maps were validated using a two-stage protocol using species observation data. ResultsThe six countries with the highest estimated START scores, and therefore the largest individual potential to reduce global extinction risk via tackling threats nationally were Brazil, Madagascar, Indonesia, Mexico, Ecuador and Colombia (each contributing over 5% of global estimated START). The threat with the greatest individual potential to reduce extinction risk was annual and perennial non-timber crops (21.2% of global START). Main conclusionsTargeted actions to tackle a few high-impact threats in a few discrete locations, and cumulative effort across multiple areas with lower individual potential, are both required to meaningfully reduce species extinction risk through threat abatement. This global scale estimation of START enables consistent scoping of conservation opportunity over large areas and provides the critical initial data to support planning and action.

Identifying what makes species vulnerable to extinction requires accounting for complex biological and environmental interactions. Due to their high predictive accuracy, machine learning methods have been widely used for these assessments; however, relying on black-box models offers limited interpretability. Here, using a comprehensive dataset of anthropogenic, ecological, morphological, demographic, and biogeographical variables from 9,053 species (81% of birds worldwide), we applied Inductive Logic Programming (ILP), an explainable artificial intelligence framework, to generate explicit and quantitative IF-THEN rules with confidence scores for bird extinction risk. Our approach revealed that extinction vulnerability follows a hierarchical structure, shaped by interactions among range size, morphological traits, and human pressures. The framework recovered well-established knowledge, while also revealing previously undescribed extinction patterns. For example, consistent with prior evidence, species with geographic ranges below [~]13,500 km{superscript 2} were identified as higher risk (88% confidence). Nevertheless, this threshold shifted to [~]3,270 km{superscript 2} when human impacts were removed, revealing quantitatively how anthropogenic activities expand the pool of vulnerable species beyond those at risk due to biological and biogeographical traits alone. Beyond established patterns, species with tail length >304 mm were identified as higher risk (82% confidence), a pattern not previously documented. ILP models achieved 91% overall accuracy, slightly lower than Random Forest (93%), but notably better than Neural Networks (83%). These results show that ILP can offer high accuracy results with full interpretability, also providing quantitative transition thresholds that clarify the structural architecture of extinction risk, and translate complex ecological interactions into actionable tools for conservation.

Large-scale annual releases of pheasants Phasianus colchicus and their subsequent management for recreational shooting create various ecological impacts in the UK. While effects at release sites are fairly well understood, dispersing birds may influence areas farther away. If they enter ecologically important but sensitive protected areas (PAs), any negative impacts could be especially harmful. Using tracking data, from 766 birds across 10 sites, we estimated survival and dispersal of released pheasants and applied these patterns to gamebird release records near English PAs to gauge intrusion risk. Of 2,885 registered release sites, just over half lay within 2 km of a PA. A large number of shoots release relatively few birds while a small number release many birds. Thus, numbers expected to enter a particular PA likely depend both on the size of releases and proximity to the PA. We estimate that, at a national level, a maximum of between 525,000 and 784,000 pheasants might be found within PAs very soon after release, representing around 1.7% of all the pheasants released annually. This number declines over the months after release until in February, we estimate that there are between 131,000 and 196,000 pheasants (0.4% of the total release) might be found within PAs. The critical metric by which ecological damage might occur is their density within PAs. Mean densities soon after release averaged 12.0 birds/ha in PAs within 250 m of release sites. This density declined markedly both in time (as birds died) and space (as they moved further from the pen as potential areas increased). By November, densities in PAs 500-1000m from release sites peaked at 0.5 birds/ha, falling to 0.16 birds/ha in February. These estimated densities are around two orders of magnitude lower than those known to cause strong, lasting impacts within release pens. The results are subject to assumptions about movement behaviour, game management and bias in registration. Despite these constraints, considerable local variation exists, with a minority of high-volume release sites very near PAs posing the greatest potential ecological risk.

Aim: To forecast near-future arrivals of non-native terrestrial and freshwater vertebrates at the regional level. Location: Global (geopolitical regions worldwide, including countries and main administrative divisions). Methods: We compiled first regional record data and assembled functional and macroecological variables for 1,931 non-native vertebrate species. For each region, we identified recently arrived non-native species using retrospective windows of thirty and twenty years ending in 2015 (1986-2015; 1996-2015). We then fitted region-specific random-forest models classifying recently arrived species versus those not yet arrived using as predictors: (i) harmonised species traits (e.g., habitat, diet, body size and native-range attributes) and (ii) spread history, capturing time since first record elsewhere. Predictive performance was evaluated using leave-one-out cross-validation, comparing full models with trait-only and spread-only variants. We also assessed relationships between predictive accuracy, predictor importance, and the geographic positioning and trade connectedness of regions. Finally, we predicted region-specific probabilities of arrival for species not yet recorded. Results: Forecasting accuracy was consistently high across regions and taxa, with AUC values above 0.9 in more than half of the focal regions. Full models substantially outperformed models using either predictor set alone, and spread-history-only models typically exceeded trait-only models. Relative importance of spread-history predictors declined with geographic distance to the focal region, whereas predictability was lower in highly trade-connected regions. Predicted near-future high-risk arrivals were dominated by birds and freshwater fishes and showed strong regional structuring. A small set of species ranked highly across many regions (e.g., birds: Phasianus colchicus, Acridotheres tristis, Amandava amandava, Colinus virginianus, Corvus splendens and Lonchura malacca; fishes: Coregonus peled and Oreochromis mossambicus; mammal: Oryctolagus cuniculus), suggesting substantial unrealised spread potential. Main conclusions: Near-future regional arrivals of non-native vertebrates are predictable from spread history and species traits. This enables scalable, updateable regional watchlists to support prevention, early detection and horizon scanning.

Connectivity is critical to sustaining endangered carnivores in speciose yet fragmented landscapes such as in the global south. Corridors to mitigate fragmentation are designed based on charismatic species or habitat-based approaches, but their multispecies effectiveness for maintaining functional connectivity remains poorly tested. We combined landscape genetic analyses across five sympatric carnivores - Panthera tigris, Panthera pardus, Prionailurus viverrinus, Felis chaus, and Melursus ursinus, to evaluate how landscape features shape functional connectivity in a globally important felid landscape. We then assessed the efficiency of existing tiger corridors and single-species surrogates for maintaining multispecies functional connectivity. Species exhibited contrasting responses to landscape variables, producing distinct resistance surfaces and connectivity corridors. Spatial similarity of connectivity between species pairs was highly variable (r = 0.14-0.93), but no single species effectively captured connectivity patterns of the broader carnivore community (maximum mean overlap of <0.7 across species). Moreover, genetically optimized corridors were at least 70% more efficient in capturing connectivity compared to existing tiger corridors, demonstrating mismatches between structural and functional connectivity. Our results highlight limitations of surrogate-based corridor planning and demonstrate that integrating multispecies functional connectivity can substantially improve conservation planning in human-dominated landscapes.