Key Biodiversity Areas (KBAs) are sites of significance for the global persistence of biodiversity. Based on the Global Standard for the Identification of Key Biodiversity Areas (KBA Standard), published in 2016, sites are currently being assessed for KBA designation in a growing number of countries across the world. For these assessments, the KBA criteria are applied to all species and ecosystems with available data. We reviewed the first comprehensive assessments of 11 countries and compared the KBA network before and after assessments. The mean (SD) number of KBAs per country increased by 69.6% (102.1), and the mean total extent of KBAs per country increased by 164.2% (150.7). More than half of the KBAs in 2024 had >50% of their area outside the 2019 KBAs, indicating a substantial increase in KBA extent (54.0% [18.8] of KBAs). The mean proportion of each KBA covered by protected or conserved areas decreased from 56.2% (20.2) to 44.5% (15.5), owing to the incorporation of unprotected sites in the KBA network. On average, 41.1% (14.0) of sites in each country (mean 44.5 [46.4] sites per country) and 47.2% (20.5) of new KBA area after the assessment were completely unprotected, indicating that many of the new sites were not recognized in national protected area networks as significant for biodiversity before the assessment. Making a comprehensive assessment of KBAs increased the combined coverage of protected and conserved area networks from 25.4% (10.6) to 32.0% (13.1) in each country and thus contributed to reducing biodiversity loss. Therefore, comprehensive assessments of KBAs led to a substantially increased number and extent of recognized sites of importance for biodiversity published in the World Database of KBAs. Where such assessments have not been made, many important areas for biodiversity may be overlooked. We therefore encourage other nations to update their KBA networks to inform efforts to meet the goals and targets of the Kunming-Montreal Global Biodiversity Framework.

The intensification and expansion of croplands are among the greatest threats to biodiversity, but the likely responses to these changes remain unknown for most species. Using data on responses of 862 bird species to changes in yields of arable crops, we extrapolate vulnerability to agriculture for the world's other terrestrial birds based on their traits and taxonomy. We estimate that 74-78% of terrestrial bird species globally suffer population declines where natural habitats are replaced by croplands, and that over half cannot persist in cropland at even the lowest current yields. Past impacts of agriculture on birds have been greatest in the tropics, particularly in coastal forest regions of Central and South America and West Africa and in southern and South-East Asia. Using these estimates to model the impacts of future scenarios of agricultural change, we find that continuing current rates of cropland expansion and yield increases (i.e. extrapolating 'business-as-usual' trends to 2050) is expected to have more negative impacts on birds (particularly in Central and South America, Eastern Europe, sub-Saharan Africa and South and East Asia) than a potential alternative of a targeted strategy of closing yield gaps while limiting cropland expansion. However, we also identify biodiverse regions of the world where closing yield gaps may have more severe impacts on birds than business-as-usual, such as the Pampas of South America and parts of the Sahel region in West Africa. The strategy of least impact for a particular area can be predicted from the response characteristics of the communities of species present there, offering opportunities to take account of regional context for designing less damaging global food production systems. ### Competing Interest Statement The authors have declared no competing interest.

Over 47,000 species on the Red List of the International Union for Conservation of Nature are assessed as being at risk of extinction, including more than 10,000 Critically Endangered (CR) species. In this Review, we focus on the status, geographical and taxonomic patterns, and threats to CR species, and the actions needed for their conservation and restoration. Just 16 countries host more than half of all CR species. Although many CR species benefit from protected areas, two-fifths require targeted species-based interventions, such as ex situ actions and conservation translocations. Further, although conservation actions are associated with improved outcomes for CR species, including reduced extinction risk, actions in place have been documented for fewer than half of these species. In addition, the assessment of conservation status is incomplete for many species and subject to taxonomic and geographical bias; as more species are assessed the number of CR species is expected to increase. To address these challenges, the conservation community has improved approaches to planning and prioritization, developed tools and metrics, and enhanced capacity to deliver conservation actions. Nevertheless, greater political ambition and substantial financial investments are needed to resource the work of governments, institutions, communities and Indigenous peoples if we are to save and recover CR species. Species classified as Critically Endangered are at greatest risk of extinction, and their preservation and recovery are crucial to meeting global biodiversity aims. This Review assesses the geographical and taxonomic distribution of Critically Endangered species, their threats, current and required conservation actions, and strategies to facilitate effective, coordinated conservation.

This is a response to a [letter](http://doi.org/10.1016/j.tree.2025.03.003) by Murray K. et al to our paper on "[:2024-ai-conhorizon]". See [:ai-should-unite-conservation] for further thoughts.

Key Biodiversity Areas (KBAs) are the largest and most complete network of significant sites for the global persistence of biodiversity. Although important sites for birds worldwide have been relatively well assessed, a key question is how effectively the global KBA network represents avian diversity. We identified bird species, orders, habitats, and geographic regions that are underrepresented by KBAs. Area of Habitat (AOH) maps for 10,517 terrestrial bird species were cropped and masked by the extent of each KBA. Almost all species had at least one part of their seasonal distribution in one or more KBAs. Twenty-nine species had no habitat overlap with KBAs, and 1900 species had <8% of their AOH overlapping KBAs. Species with KBAs identified for them (5219 trigger species) had on average 2.6% greater representation of their AOH in KBAs than species that did not. The extent of species' AOH represented by KBAs varied with region, habitat, and taxonomic group. Northern North America had the most underrepresented terrestrial bird species (up to 178 underrepresented species per 100 km2). Terrestrial bird species of tropical forests were 12.8% better represented in KBAs than expected by chance, whereas boreal and temperate forest species were less well represented than expected by chance (74.4% and 25.1%, respectively). Among avian orders, Anseriformes and Charadriiformes were underrepresented in KBAs (29.0% and 17.9%, respectively), whereas Trogoniformes and Psittaciformes were better represented (16.2% and 6.9%, respectively) than expected by chance. Bird species for potential KBA identification include marsh antwren (Formicivora paludicola) and Tabar pitta (Erythropitta splendida). These are mainly due to recent changes in species' taxonomy or their International Union for Conservation of Nature Red List category. Identifying poorly represented species and where they occur highlights shortfalls where expansion of the network could bring conservation benefits.

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

The Red List Index (RLI) is an indicator of the average extinction risk of groups of species and reflects trends in this through time. It is calculated from the number of species in each category on the IUCN Red List of Threatened Species, with trends influenced by the number moving between categories when reassessed owing to genuine improvement or deterioration in status. The global RLI is aggregated across multiple taxonomic groups and can be disaggregated to show trends for subsets of species (e.g. migratory species), or driven by particular factors (e.g. international trade). National RLIs have been generated through either repeated assessments of national extinction risk in each country or through disaggregating the global index and weighting each species by the proportion of its range in each country. The RLI has achieved wide policy uptake, including by the Convention on Biological Diversity and the United Nations Sustainable Development Goals. Future priorities include expanding its taxonomic coverage, applying the RLI to the goals and targets of the Kunming-Montreal Global Biodiversity Framework, incorporating uncertainty in the underlying Red List assessments, integrating into national RLIs the impact of a country on species' extinction risk abroad, and improving analysis of the factors driving trends.This article is part of the discussion theme issue 'Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future'.

Understanding the consequences of past conservation efforts is essential to inform the means of maintaining and restoring species. Data from the IUCN Red List for 67,217 animal species were reviewed and analyzed to determine (i) which conservation actions have been implemented for different species, (ii) which types of species have improved in status and (iii) which actions are likely to have driven the improvements. At least 51.8% (34,847) of assessed species have actions reported, mostly comprising protected areas (82.7%). Proportionately more actions were reported for tetrapods and warm-water reef-building corals, and fewer for fish, dragonflies and damselflies and crustaceans. Species at greater risk of extinction have a wider range of species-targeted actions reported compared with less threatened species, reflecting differences in documentation and conservation efforts. Six times more species have deteriorated than improved in status, as reflected in their IUCN Red List category. Almost all species that improved have conservation actions in place, and typically were previously at high risk of extinction, have smaller ranges and were less likely to be documented as threatened by hunting and habitat loss or degradation. Improvements in status were driven by a wide range of actions, especially reintroductions; for amphibians and birds, area management was also important. While conservation interventions have reduced the extinction risk of some of the most threatened species, in very few cases has full recovery been achieved. Scaling up the extent and intensity of conservation interventions, particularly landscape-scale actions that benefit broadly distributed species, is urgently needed to assist the recovery of biodiversity.

The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements, and provide comparisons to detector simulations.

Aim: To identify the broad-scale oceanic migration routes ('marine flyways') used by multiple pelagic, long-distance migratory seabirds based on a global compilation of tracking data. Location: Global. Time Period: 1989-2023. Major Taxa Studied: Seabirds (Families: Phaethontidae, Hydrobatidae, Diomedeidae, Procellariidae, Laridae and Stercorariidae). Methods: We collated a comprehensive global tracking dataset that included the migratory routes of 48 pelagic and long-distance migrating seabird species across the Atlantic, Indian, Pacific and Southern Oceans. We grouped individuals that followed similar routes, independent of species or timings of migration, using a dynamic time warping clustering approach. We visualised the routes of each cluster using a line density analysis and used knowledge of seabird spatial ecology to combine the clusters to identify the broad-scale flyways followed by most pelagic migratory seabirds tracked to-date at an ocean-basin scale. Results: Six marine flyways were identified across the world's oceans: the Atlantic Ocean Flyway, North Indian Ocean Flyway, East Indian Ocean Flyway, West Pacific Ocean Flyway, Pacific Ocean Flyway and Southern Ocean Flyway. Generally, the flyways were used bidirectionally, and individuals either followed sections of a flyway, a complete flyway, or their movements linked two or more flyways. Transhemispheric figure-of-eight routes in the Atlantic and Pacific oceans, and a circumnavigation flyway in the Southern Ocean correspond with major wind-driven ocean currents. Main Conclusions: The marine flyways identified demonstrate that pelagic seabirds have similar and repeatable migration routes across ocean-basin scales. Our study highlights the need to account for connectivity in seabird conservation and provides a framework for international cooperation.

AbstractUnderstanding the consequences of past conservation efforts is essential to inform the means of maintaining and restoring species. Data from the IUCN Red List for 67,217 comprehensively assessed animal species were reviewed and analysed to determine (i) which conservation actions have been implemented for different species, (ii) which types of species have improved in state and (iii) which actions are likely to have driven the improvements. At least 51.8% (34,847) of assessed species have actions reported, mostly comprising protected areas (82.7%), with more actions reported for both terrestrial tetrapods and warm-water reef-building corals and fewer for fish, dragonflies and damselflies and crustaceans. Species at greater risk of extinction have a wider range of species-targeted actions reported compared to less threatened species, reflecting differences in documentation and conservation efforts. Six times more species have deteriorated rather than improved in their Red List category. Almost all species that improved have conservation actions in place; species that improved in state typically were historically at high risk of extinction, have smaller ranges and lacked a range of reported threats, particularly hunting and habitat loss or degradation. All types of conservation action were associated with improvements in state, especially reintroductions and invasive species control, alongside, for amphibians and birds, area management. This suggests a range of conservation interventions have successfully conserved some species at greatest risk but have rarely recovered populations to resilient levels. Scaling up the extent and intensity of conservation interventions, particularly landscape-scale actions that benefit broadly distributed species, is urgently needed to assist the recovery of biodiversity.

Trade represents a significant threat to many wild species and is often clandestine and poorly monitored. Information on which species are most prevalent in trade and potentially threatened by it therefore remains fragmentary. We used 7 global data sets on birds in trade to identify species or groups of species at particular risk and assessed the extent to which they were congruent in terms of the species recorded in trade. We used the frequency with which species were recorded in the data sets as the basis for a trade prevalence score that was applied to all bird species globally. Literature searches and questionnaire surveys were used to develop a list of species known to be heavily traded to validate the trade prevalence score. The score was modeled to identify significant predictors of trade. Although the data sets sampled different parts of the broad trade spectrum, congruence among them was statistically strong in all comparisons. Furthermore, the frequency with which species were recorded within data sets was positively correlated with their occurrence across data sets, indicating that the trade prevalence score captured information on trade volume. The trade prevalence score discriminated well between species identified from semi-independent assessments as heavily or unsustainably traded and all other species. Globally, 45.1% of all bird species and 36.7% of globally threatened bird species had trade prevalence scores ≥1. Species listed in Appendices I or II of CITES, species with large geographical distributions, and nonpasserines tended to have high trade prevalence scores. Speciose orders with high mean trade prevalence scores included Falconiformes, Psittaciformes, Accipitriformes, Anseriformes, Bucerotiformes, and Strigiformes. Despite their low mean prevalence score, Passeriformes accounted for the highest overall number of traded species of any order but had low representation in CITES appendices. Geographical hotspots where large numbers of traded species co-occur differed among passerines (Southeast Asia and Eurasia) and nonpasserines (central South America, sub-Saharan Africa, and India). This first attempt to quantify and map the relative prevalence in trade of all bird species globally can be used to identify species and groups of species that may be at particular risk of harm from trade and can inform conservation and policy interventions to reduce its adverse impacts.

The Kunming-Montreal Global Biodiversity Framework (GBF) is the most ambitious agreement on biodiversity conservation and sustainable use to date. It calls for a whole-of-society approach aimed at halting and reversing the loss of biodiversity worldwide. To support its implementation, the Monitoring Framework of the GBF lays out how Parties to the Convention on Biological Diversity are expected to report their progress. Given the need for capacity-building and investment to operationalize the Monitoring Framework, Parties established an expert group to provide guidance on its implementation, including a gap analysis to identify the strengths and limitations of the Monitoring Framework. We present the results of the gap analysis, highlight where more work on the Monitoring Framework is needed and provide recommendations on implementing and improving it to allow effective and comprehensive tracking of progress across all elements of the GBF's Goals and Targets. We find that using required indicators (headline and binary), the Monitoring Framework fully covers 20% of the Goals' and Targets' elements and partially covers an additional 42%. Including optional (component and complementary) indicators improves full coverage to 24% and an additional 49% partial coverage. For 13% of elements, no indicators are available. While the Monitoring Framework will enable progress towards meeting the Goals and Targets of the GBF, substantial investment is still required to collect the necessary data to compute indicators, infer change, and effectively monitor progress. We highlight both immediate and long-term solutions and offer guidance on important next steps that will progressively improve the efficacy of the Monitoring Framework. ### Competing Interest Statement Multiple authors are or were employed by organisations involved in the negotiation process. That being said, all authors were acting in a non-political capacity when conducting the work on the Monitoring Framework.

Biodiversity metrics are increasingly in demand for informing government, business, and civil society decisions. However, it is not always clear to end users how these metrics differ or for what purpose they are best suited. We seek to answer these questions using a database of 573 biodiversity-related metrics, indicators, indices, and layers, which address aspects of genetic diversity, species, and ecosystems. We provide examples of indicators and their uses within the state–pressure–response–benefits framework that is widely used in conservation science. Considering complementarity across this framework, we recommend a small number of metrics considered most pertinent for use in decision-making by governments and businesses. We conclude by highlighting five future directions: increasing the importance of national metrics, ensuring wider uptake of business metrics, agreeing on a minimum set of metrics for government and business use, automating metric calculation through use of technology, and generating sustainable funding for metric production.

Artificial Intelligence (AI) is an emerging tool that could be leveraged to identify the effective conservation solutions demanded by the urgent biodiversity crisis. We present the results of our horizon scan of AI applications likely to significantly benefit biological conservation. An international panel of conservation scientists and AI experts identified 21 key ideas. These included species recognition to uncover 'dark diversity', multimodal models to improve biodiversity loss predictions, monitoring wildlife trade, and addressing human–wildlife conflict. We consider the potential negative impacts of AI adoption, such as AI colonialism and loss of essential conservation skills, and suggest how the conservation field might adapt to harness the benefits of AI while mitigating its risks.

Indigenous Peoples’ lands (IPL) cover at least 38 million km 2 (28.1%) of Earth's terrestrial surface. These lands can be important for biodiversity conservation. Around 20.7% of IPL intersect areas protected by government (PAs). Many sites of importance for biodiversity within IPL could make a substantial but hitherto unquantified contribution to global site-based conservation targets. Key Biodiversity Areas (KBAs) represent the largest global network of systematically identified sites of high importance for biodiversity. We assessed the effectiveness of IPL in slowing biodiversity loss inside and outside PAs by quantifying tree cover loss from 2000 to 2019 in KBAs at international and national levels and comparing it with losses at equivalent sites outside mapped IPL. Based on a matched sample of 1-km 2 cells in KBAs inside and outside mapped IPL, tree cover loss in KBAs outside PAs was lower inside IPL than outside IPL. By contrast, tree cover loss in KBAs inside PAs was lower outside IPL than inside IPL (although the difference was far smaller). National rates of tree cover loss in KBAs varied greatly in relation to their IPL and PA status. In one half of the 44 countries we examined individually, there was no significant difference in the rate of tree cover loss in KBAs inside and outside mapped IPL. The reasons for this intercountry variation could illuminate the importance of IPL in meeting the Convention on Biological Diversity's ambition of conserving 30% of land by 2030. Critical to this will be coordinated action by governments to strengthen and enforce Indigenous Peoples’ rights, secure their collective systems of tenure and governance, and recognize their aspirations for their lands and futures.

ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7 GeV/$c$ beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be 380$\pm$26 mbarns for the 6 GeV/$c$ setting and 379$\pm$35 mbarns for the 7 GeV/$c$ setting.

Nations have committed to reductions in the global rate of species extinctions through the Sustainable Development Goals 14 and 15, for ocean and terrestrial species, respectively. Biodiversity loss is worsening despite rapid growth in the number and extent of protected areas, both at sea and on land. Resolving this requires targeting the locations and actions that will deliver positive conservation outcomes for biodiversity. The Species Threat Abatement and Restoration (STAR) metric, developed by a consortium of experts, quantifies the contributions that abating threats and restoring habitats in specific places offer towards reducing extinction risk based on the IUCN Red List of Threatened SpeciesTM. STAR is now recommended as an appropriate metric by recent disclosure frameworks for companies to report their impacts on nature and STAR has seen widespread uptake within the private sector. However, it is currently only available for the terrestrial realm. We extend the coverage of the threat abatement component of the STAR metric (START), used to identify locations where positive interventions could make a large contribution to reducing global species extinction risk and where developments that increase threats to species should be mitigated, to the marine realm for 1646 marine species. Reducing unsustainable fishing provides the greatest opportunity to lower species extinction risk, comprising 43% of the marine START score. Three-quarters (75%) of the global marine START score falls entirely outside the boundaries of protected areas and only 2.7% falls within no-take protected areas. The STAR metric can be used both to guide protected area expansion and to target other actions, such as establishment and enforcement of fishing limits, to recover biodiversity.

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

The IUCN Red List of Threatened Species underpins much decision-making in conservation and plays a key role in monitoring the status and trends of biodiversity. However, the shortage of funds and assessor capacity slows the uptake of novel data and techniques, hampering its currency, applicability, consistency and long-term viability. To help address this, we developed sRedList, a user-friendly online platform that assists Red List assessors through a step-by-step process to estimate key parameters in a standardised and reproducible fashion. Through the platform, assessors can swiftly generate outputs including species' range maps, lists of countries of occurrence, lower and upper bounds of area of occupancy, habitat preferences, trends in area of habitat, and levels of fragmentation. sRedList is compliant with the IUCN Red List guidelines and outputs are interoperable with the Species Information Service (SIS; the IUCN Red List database) in support of global, regional and national assessments and reassessments. sRedList can also help assessors prioritise species for reassessment. sRedList was released in October 2023, with a complete documentation package (including text documentation, ‘cheatsheets’, and 15 video tutorials), and will soon be highlighted in the official Red List online training course. sRedList will help to bridge the gap between extinction risk research and Red List assessment practice, increase the taxonomic coverage and consistency of assessments, and ensure the IUCN Red List is up-to-date to best support conservation policy and practice across the world.