Conservation Biology

Conserving migratory birds effectively requires full annual cycle strategies that identify where on-the-ground efforts can have the greatest impact. Here, we present a hemispheric spatial framework to identify priority areas for 112 migratory bird species across the Americas. Building on full annual cycle prioritizations, we defined finer-scale spatial planning units that reflect differences in migratory and congregational behaviors between shorebirds and landbirds. We compiled population data for each planning unit and focal species and applied conservation planning tools to design area-efficient portfolios of sites and landscapes that secure 10% of each species population within the Americas flyways. The resulting minimum area portfolios include 175 shorebird sites and 80 landbird landscapes optimized to meet the species-specific 10% representation targets across breeding, non-breeding, and passage seasons. We also identified a broader set of complementary solutions, ranked by an importance score, to provide decision-makers with flexible options for strategic resource allocation. This framework provides the scientific foundation for the Americas Flyways Initiative (AFI), which aims to catalyze investment in nature-based solutions and bird-friendly infrastructure to enhance the conservation of migratory birds and strengthen the resilience of the Americas flyways by 2050.

Primates are frequent targets of international conservation efforts, due to their anthropological significance and function as biodiversity conservation flagship species. Afro-Palearctic migratory birds receive considerable conservation attention in their breeding habitats, but much less in their wintering areas. Good wintering habitat conditions are, however, crucial for long-term population viability. Integrating complementary conservation efforts for these taxa may provide substantial co-benefits. Here, we evaluate the spatial, ecological, and conservation congruence between 248 Afro-Palearctic migratory bird and 213 African primate species to identify potential synergies in intercontinental conservation efforts. The wintering areas of 218 migratory bird species overlap with primate ranges. Up to 125 Afro-Palearctic migratory bird species co-occur with at least one primate species locally and highest regional cross-taxon richness occurs in forest-savanna ecotones in West Africa and eastern DRC. Agriculture and hunting threaten both taxa (88-97% of primate and 59-70% of bird species). Several conservation interventions have demonstrated effectiveness for both taxa, particularly habitat protection and hunting reduction. We propose three policy priorities: strengthening cross-taxa monitoring within existing primate research infrastructure, improving the conservation evidence base in the African context, and creating financing synergies that allow conservation investments to simultaneously benefit both taxa.

The number of species introduced outside of their historical ranges by human activity continues to rise. A subset of these species establishes, form self-sustaining populations, and some (invasive alien species) go on to cause substantial harm to biodiversity and ecosystems. Preventing new invasive alien species from establishing is the key focus of interventions, because post-establishment management is costly and often fails. However, it remains unclear how effective multilateral efforts have been in curbing the rise. Here we show that the emergence of new invasive alien species across countries is slowing, and trends are similarly negative across geographically diverse countries. Using data and modelling advances, we find a 35% reduction in the establishment of new invasive alien species over a policy-relevant 50-year time frame. The findings directly inform the assessment of progress for the invasive alien species target of the Kunming-Montreal Global Biodiversity Framework, and provide a global baseline for monitoring rates of invasive alien species establishment. Furthermore, the slowdown suggests that policy and investment over recent decades to prevent invasive alien species from entering and establishing in countries have had a positive effect.

Businesses are increasingly encouraged to disclose their nature-related dependencies, impacts, risks and opportunities. A common component of sustainability reporting is screening operational sites for ecologically sensitivity to identify locations for further evaluation and action. However, with 600+ biodiversity metrics available, selecting and interpreting appropriate metrics remains challenging for business. We developed a simple screening framework informed by the Taskforce for Nature-Related Financial Disclosures guidance, grouping eleven widely used global biodiversity metrics into four complementary [&prime]baskets[&prime], representing different aspects of biodiversity. We created hypothetical but realistic mining, onshore wind energy and agricultural companies, to assess how metric choice, buffer size, scoring approach and sensitivity thresholds influence screening outcomes. Our basket framework consistently identified similar high-priority sites across metric combinations, but site rankings varied with methodological choices. We recommend clearer guidance on metric selection and application, alongside greater transparency from business regarding assumptions, methods and limitations when screening sites for ecological sensitivity.

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.

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.

Biodiversity loss is driven by unsustainable human activities, yet the contextual conditions and underlying drivers of threats remain poorly understood. We assessed how protected areas, socioeconomic conditions, and biophysical factors explain global patterns of threat probabilities across six major threat types and four vertebrate taxa. We identified key explanatory variables and their associations with threats using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP). Socioeconomic conditions, specifically human development and income inequality, were the strongest predictors. Their associations were complex and non-linear: notably, high human development index (HDI) was associated with both higher and lower threat probabilities, depending on inequality and regional context. Second, land cover and biophysical variables, such as shrubland cover, tree cover, and elevation range, explained additional, but taxon-specific variation. Finally, protected areas showed limited ability to explain threat patterns. By linking threat probabilities to their contextual and socioecological conditions, we aim to build a better understanding of the systemic drivers of biodiversity loss.

The global market concentrates extractive pressure on lands held by Indigenous peoples, including peoples living in isolation, for whom free, prior and informed consent cannot be obtained and protection must therefore rest on territorial instruments. Halmahera, Indonesia, holds some of the worlds largest lateritic nickel reserves beneath a lowland rainforest inhabited by the Hongana Manyawa, yet the trajectory of land use and cover change across the island has not been quantified. We characterised land use and cover change over the 17,437 km2 island between 2014 and 2024 using MapBiomas time series, and projected a business-as-usual scenario to 2054 with a stochastic cellular-automata model implemented in Dinamica EGO, calibrated with weights of evidence on eight variables describing mining and logging concessions, transport infrastructure, settlements and previous clearing. Forest covered 83.0% of the island in 2014 and 82.1% in 2024; under unchanged policy it falls to 73.7% by 2054, a net loss of 162 thousand ha, or 11.2% of the 2014 baseline, at gross rates of 47,000-51,000 ha per decade. Deforestation probability is highest within 500 m of previous clearing and declines with distance from settlements, cities and mining sites, while proximity to national parks carries a negative weight of evidence. The frontier is self-propagating and spatially predictable, and legally designated territory retains forest within it. Protecting the Hongana Manyawa consequently depends on excluding extractive licensing from the interior forest ahead of the frontier rather than behind it.

Citizen science data are increasingly used to infer biodiversity change, but causal claims based on such data are credible only if sampling effort and its temporal shifts are explicitly modeled. Zhang et al. (1) used citizen science data to conclude that greater photovoltaic policy stringency, measured using the photovoltaic policy stringency index (PSI), reduced county-level bird diversity in China. We reproduced their fixed effects and instrumental variable estimates. However, the observed Shannon diversity derived from pooled citizen science records reflects both bird communities and sampling effort, which the authors' controls do not adequately capture. Accounting for observer count changed the reported statistically significant 2.10% decline in Shannon index to a nonsignificant 0.58% increase (P = 0.288) per one-standard-deviation increase in PSI, and rendered the instrumental variable estimate statistically indistinguishable from zero (P = 0.912). Yet observer count is only one of many sources of sampling bias. PSI was also associated with multiple dimensions of sampling effort, consistent with sampling effort acting as a potential mediator in the PSI-diversity chain. The sampling domain also shifted markedly from 2014 to 2023: recorded county-months increased almost 24-fold, median observer count rose from one to three, and zero-duration records declined from 57.2% to 0.17%. Without adequate adjustment, these shifts confound estimates of temporal change in observed bird diversity. Beyond its inadequate treatment of sampling effort, the original study also misinterpreted its statistical results. Although the reported R{superscript 2} values are high, they are dominated by county and year-month fixed effects, with PSI contributing a partial R{superscript 2} of only 0.048% on observed Shannon index. The PSI-photovoltaic-area correlation is also weak (r = 0.0414) and vanishes after accounting for fixed effects (P = 0.977). Furthermore, the released bird observation data contain many erroneous outliers, raising significant concerns about insufficiently rigorous data preprocessing and quality control. These results show that the released data cannot properly distinguish ecological change from sampling effort change. Robust inference from citizen science data requires checklist-level effort metadata, explicit correction for spatiotemporal sampling shifts, and close collaboration among researchers with complementary methodological and ecological expertise.

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.

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.

Evidence-based approaches are increasingly advocated and applied in conservation to provide reliable recommendations for management and policymaking. Although substantial efforts have been undertaken to generate ecological knowledge across languages and publication types, many syntheses and meta-analyses fail to include relevant literature sources; drawing into question their reliability. To assess the extent of biases resulting from ignoring grey literature and non-English publications, we reviewed and synthesised movement and migratory connectivity data for green turtles across Southeast Asia from multiple literature types and eight languages. We identified substantial losses in connectivity information, with at least half of all locations losing more than 88% of their connections, and shifts in demographic representation and sampling techniques when grey literature was excluded from the evidence base. The exclusion of non-English literature had a comparatively smaller impact. The regional connectivity network generated through this study highlights the need for holistic reviews to develop evidence bases to underpin transboundary management of migratory species. Ignoring grey literature and, potentially, regional languages in the development may lead to misallocation of limited management resources. Holistic reviews can further support the establishment of Important Areas for migratory species and inform how we meet and report on global biodiversity commitments.

Understanding how scientific effort is distributed is essential for evaluating the evidence available to guide species conservation. We assessed the temporal, thematic, methodological, and spatial organization of jaguar (Panthera onca) research across the species range. Using 1,028 bibliographic records, we applied a metadata-based scope filter, defining a primary analytical corpus of 857 articles and an inclusive sensitivity corpus of 989. We analyzed publication growth from 1946-2024, author-keyword networks, high-specificity research-domain and methodological indicators, article-based spatial concentration across nine regions, and anthropogenic context using the Human Impact Index. Publication output increased strongly and nonlinearly, with the negative-binomial generalized additive model explaining 96% of deviance. Population and abundance, human-wildlife conflict and coexistence, and movement and connectivity were the most frequent research domains, whereas camera trapping was the most frequent methodological approach. Spatial analyses included 237 georeferenced terrestrial articles. Research was strongly concentrated in the Pantanal, Mesoamerica, and Atlantic Forest, but was underrepresented relative to range area in the Andes and Choco-Darien, Amazon, and Guiana Shield. These patterns were stable to the broader scope definition. Research concentration showed no strong association with region-wide anthropogenic pressure, although studies within several extensive regions tended to occur in more human-influenced portions than the regional average. Jaguar research therefore shows substantial growth and partial alignment with applied conservation challenges but remains geographically uneven. Expanding representative research in underrepresented regions, while maintaining work in threatened landscapes, would strengthen the evidence base for range-wide conservation planning and improve coordination among countries, institutions, and regional research traditions.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

Protected areas cannot halt biodiversity loss in isolation; integrating them with surrounding human-dominated landscapes is critical. However, this integration is challenged by substantial landscape heterogeneity at their borders, hindering our understanding of cross-border changes in ecosystem service provision. We introduce a novel framework for characterizing these dynamics by analyzing ecosystem service gradients along protected area borders. For 16 protected areas in the French Alps, we assessed 12 ecosystem services using a mix of established biophysical models and novel connectivity-based models for mobile species. These were aggregated into three stakeholder-driven domains reflecting respectively rural, cultural, and urban management priorities. Automated polynomial regression analysis classified borders into five gradient types. The most common were 'Decreasing Gradients', representing a decline in ecosystem services outside the protected area, and 'Increasing Gradients', with the opposite pattern. Our analysis reveals these patterns are driven by specific landscape configurations, uncovering frequent trade-offs between the three management priorities, where, for instance, landscapes supporting rural priorities often degrade cultural and urban ones. We also identify key opportunities for synergies, by identifying areas where ecosystem services for all three priority domains increase simultaneously outside the protected area. This spatially explicit typology provides a powerful diagnostic tool for designing targeted interventions, such as prioritizing habitat restoration where ecosystem services decline or managing agricultural landscapes to mitigate conflicts across management priorities, supporting a more effective integration of protected areas into the wider landscape.

As anthropogenic threats have intensified over the past 500 years, we find ourselves in the midst of a sixth mass extinction, with continued losses of biodiversity threatening ecosystem stability. This biodiversity loss has caused species extinctions across taxa, and placed several others at high risk of functional extinction. These disturbance-driven impacts represent one of the most acute biodiversity crises facing global marine systems. Species exhibiting slow life histories characteristically have low resilience to disturbance. Here, we assess the risk of functional extinction and identify policy pathways for population recovery of the slow-living, Critically Endangered elasmobranch, the spinetail devil ray (Mobula mobular). We develop a stochastic, state-structured Integral Projection Model (IPM) parameterised with demographic data collected from fishery landings data in India, the world's largest mobulid fishery, and supplemented with data on vital rates from published literature. Using the IPM, we estimate that the population is declining at approximately 12% annually, experiencing substantial limiting pressure from fisheries overexploitation and failing to approach its biological maximum growth potential. Our results indicate that populations of M. mobular will be at high risk of functional extinction if 'business as usual' harvest scenario persists for another decade. We further show that long-term population recovery is only possible if survival increases significantly across all size classes, especially among large reproductive females, alongside a concurrent increase in fecundity. We conclude that no single policy measure is sufficient to recover population of M. mobular along the southeastern coast of India. Instead, combined protection through maximum bycatch mitigation and protection of nursery areas in no-take zones will be required for population recovery. This research demonstrates that recovery of overexploited populations often requires integrated resource management across life stages, and that the Critically Endangered M. mobular warrants urgent conservation action to avoid functional extinction.

Incorporating the complexities of climate change into conservation planning can be challenging. Climate change is projected to change the mean and variability of temperature and precipitation, and change dynamics of extreme events of many climate variables globally. These changes will all have compounding effects on ecosystems worldwide, affecting species distributions, seasonal timings, and population dynamics. However, most recent climate-informed conservation planning frameworks only focus on changes in mean conditions, leaving out ecologically important information about seasonality and extreme events. Using a case study of estuaries in the Pacific Northwest, this research seeks to answer the question "How can the effects of climate change on estuaries best be modelled and described for practical use in ecological management?" To answer this question, we used downscaled climate projection data to estimate changes in the mean and variability of temperature and precipitation. Applying extreme value theory to these projection data, we also projected changes in the magnitude of extremes in temperature and precipitation for estuaries in the region. Using descriptive statistics and open source data, our results present a novel, holistic method of understanding climate risk, including estimating extreme events, highlighting a key research gap in conservation planning. These results also highlight that trends in the mean, variability, and magnitude of climate extremes are not consistent with each other, further underscoring the importance of considering multiple dimensions of climate change together. Despite uncertainty given by climate models, the methods presented here provide a reasonable approach to plan for conservation management in the face of climate uncertainty.

Intensifying fire regimes threaten forests globally, but the risk of persistent post-fire forest loss and its potential mitigation remains poorly quantified. We analyzed millions of wildfires worldwide from 2001 to 2024 and tracked recovery in satellite-observed forest structure and ecosystem function. Post-fire persistent forest loss, indicated by modeled non-recovery to pre-fire conditions over decadal timescales, affected 57.1% of burned forest area globally since 2001, with hotspots in Pacific temperate and southern boreal forests. We then identified 'crucial fires' as events exceeding a stringent modeled-risk probability threshold for persistent structural or functional non-recovery, with fire severity strongly predicting this loss. This severity dependence revealed a management pathway, as locations with prior low-severity fire experienced lower severity in subsequent wildfires and had lower modeled probability of becoming crucial. Under a model-based counterfactual scenario, applying the estimated severity attenuation was associated with a 7.6% reduction; the top 1% of road-accessible areas accounted for 35% of this reduction. These results provide a global framework for identifying where wildfire threatens forest resistance and where targeted low-severity fire management like prescribed fire might be used to combat global forest loss.

Small-scale fisheries provide essential coastal livelihoods in developing regions, yet they often confront severe institutional voids within fragile-state contexts. Adopting a social-ecological systems framework, this study addresses three sequential objectives: characterizing the contemporary institutional and demographic status of fishery cooperatives across the five South-Central Federal Member States in comparison to their late-1980s historical peak; ranking the socio-economic, infrastructural, regulatory, and environmental impediments to cooperative efficacy; and evaluating the contributions of these cooperatives to sustainable fisheries development. This investigation analyzes how fishery cooperatives act as institutional intermediaries to bolster economic resilience within the Somali coastal economy--a sector central to the National Transformation Plan, despite persistent regulatory fragmentation. Through semi-structured qualitative interviews with key informants--analyzed via reflexive thematic analysis and chi-square testing of age-cohort structure--the study finds that illegal, unreported, and unregulated fishing and inadequate post-harvest infrastructure are the principal constraints, whereas training, education, and community collaboration constitute the primary contributions. The results characterize these cooperatives as hybrid institutions that compensate for limited central-state capacity in remote coastal settlements while serving as intermediaries for the Federal Ministry of Fisheries and Blue Economy where co-management mandates are implemented. By extending the actor-community dimension of the SES framework to include age-cohort structure, this research demonstrates that clan-based reciprocal arrangements can serve as functional substitutes for Ostroms first design principle in contexts of persistent fragility. The study recommends multi-stakeholder partnerships to advance targeted capacity-building, financial literacy, and technological integration, and suggests future research into the post-harvest and retail sectors to examine the role of women in the Somali blue economy.

Reliable population estimates are essential for wildlife management, yet monitoring schemes often do not match the administrative scale at which decisions are made. We illustrate this challenge using the Eurasian lynx in the canton of Valais, Switzerland, where official state monitoring is fragmented across three reference areas surveyed in different years. We analyzed three winters (2023-2026) of independent, canton-wide camera trap data, recording 899 independent lynx captures (27, 31 and 34 adults per winter). Lynx distribution and reproduction concentrated in the Northwest and connected to the thriving Pre-alpine populations. Density modelling for 2025/2026 estimated 37 independent lynx (95% CI: 26-52) on the whole cantonal territory, corresponding to a density of 1.09 (0.77-1.56) individuals per 100 km2. These estimates are substantially below the figures improperly extrapolated from a cross-cantonal reference area and conveyed by political authorities. Future lynx management decisions should be rooted in scientifically sound, scale-relevant information.