Conservation Science and Practice

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.

Conservation strategies for at-risk species can be aided significantly by research on topics such as ecology, life history, and threats, yet research effort is lacking for many species facing elevated extinction risk. Here we investigated whether listing under the U.S. Endangered Species Act (ESA) was associated with research effort for U.S. butterflies, and whether that effort was higher before or after ESA listing. We found that ESA-listed species had significantly more peer-reviewed publications than non-listed species after accounting for species range and taxonomic family. Further, we showed that more papers were published per year after ESA listing than before. These findings confirm that ESA-listed species benefit from greater research attention that can support data-informed conservation efforts. However, the relative scarcity of studies prior to ESA listing, as well as the lack of research for many unlisted, at-risk taxa, underscores the need for proactive, strategic research effort to inform conservation action.

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.

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.

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.

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.

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.

O_LIWhen eradication is unfeasible, invasive predator control should evaluate how removal affects ecological responses by native species. Assessments often use total invasive predator abundance to evaluate prey responses, yet intraspecific variation in diet and space use means that some subgroups cause disproportionate impacts. Identifying these problem individuals, and the spatial scales over which their impacts operate, can enable targeted spatially explicit removal to maximise impact reduction. However, despite individual-level information is often already collected during trapping operations it is seldom included when analysing predator impacts, potentially biasing the conservation outcomes expected under blanket removal. C_LIO_LIWe use a novel framework and two decades of invasive predator control data to estimate how individual variation in residency status influences the distance-dependent impacts of invasive American mink Neogale vison on water vole Arvicola amphibius occupancy across two prey surveys. We also develop a sub-model to predict mink residency status for individuals with missing age data. C_LIO_LIThe probability of capturing adult mink decreased with elevation and years of control, indicating that long-term control altered the resident population and demographic composition of mink around water vole sites. C_LIO_LIDistance-dependent negative impacts of mink varied by residency status, becoming negligible at approximately 20 km from water vole sites for resident mink and 2 km for transient. The spatial scale of mink impacts was largest during the first vole survey when resident mink were more abundant, and declined rapidly for the second survey, when mink were less abundant and spatially clustered. Our results suggest that water voles have benefited mostly from reducing resident mink rather than the total population, especially in early control phases. C_LIO_LIManagers can use our framework to develop spatially explicit and impact-based strategies, not restricted to invasive species control, to construct empirically informed management buffers around populations of conservation concern. Long-term efforts will change the landscape and invasive predator contexts, and thus we recommend iteratively updating and re-evaluating management outcome evaluations. We argue that incorporating individual heterogeneity improves our understanding of ecological mechanisms influencing management success but that the suitability of targeted strategies should be evaluated for target socioecological contexts. C_LI

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.

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.

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.

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.

Wildlife feeding during the wild turkey (Meleagris gallopavo) hunting season is legal in many states within the United States, but hunting turkeys with the aid of bait is unlawful in most states. The most common policy to prevent wildlife feeding from acting as bait is to restrict hunting within a defined radius. However, the effect of wildlife feeders on turkey harvest risk and the effectiveness of distance restrictions on mitigating that influence have not been investigated. During 2024-2025, we used GPS transmitters to track 30 adult male turkeys during the spring hunting season on private land with active feeders in Florida, USA, where hunting turkeys within a 91 m radius of a feeder was unlawful. We used Cox proportional hazard models to link risk of hunter harvest with unique feeders visited daily, number of feeders within a home range, and average morning distance and roosting distance to feeders at multiple temporal scales. Hunters harvested 53% of the tagged turkeys. Risk of hunter harvest increased with the number of unique feeders visited the previous day and after the first three days of hunting season with the number of active feeders within a home range. As distance from the most recent roost site and average morning distance to a feeder decreased, risk of hunter harvest increased. We estimated that risk of hunter harvest would be reduced by over 50% if distance restrictions were increased from 100 m to 200 m, by nearly 75% with an increase from 100 m to 300 m, and by nearly 90% with an increase from 100 m to 500 m. To completely eliminate the influence of wildlife feeders on risk of hunter harvest would require a restriction distance well beyond a 500m radius, which is impractical given that this radius would result in an area twice the average private landowner property size in the region. Thus, if wildlife feeding during the turkey hunting season is to be allowed, it will act as bait, in which case, the acceptable level of its influence as bait can be achieved with the appropriate hunting radius restriction.

ContextFire is a key driver of wildlife pattern in northern Australia, and in recent decades there has been concerted efforts to return burning practices from unmanaged wildfire to approaches more in tune with traditional approaches to fire management undertaken by First Nations people. AimsWe examined fire pattern (early and late dry season) and distance from coast in relation to mammal pattern on a Cobourg peninsula, as there was some evidence in variable patterns in fire history and mammal persistence in this landscape. MethodsIn this study we examined data collected from Garig Gunak Barlu (Cobourg) National Park, Northern Territory, between 2004 and 2017. We investigated the relationship between all native mammal abundance and species richness, and abundance for eight species, with the three environmental variables (distance from coast, preceding early dry and late dry season burning frequency), using an information theoretic model selection and averaging framework. Key resultsThere is a distinctive change in the fire and mammal pattern with respect to distance from the coast; that is, early and late dry season burning increasing moving inland from the coast, and a concomitant decrease or persistence in some key species on this fire gradient. ConclusionsOur results suggest that fire management in northern Australia still needs targeted research linked to active management to more effectively prevent declines of mammal populations. ImplicationsThe location and shape of Garig Gunak Barlu (Cobourg) National Park provide an excellent opportunity to undertake some natural experiments in strategic burning to investigate improved approaches to conservation in fire-prone landscapes.

ContextThe decline, extirpation and extinction of Australias mammal fauna is without peer. In recent decades long term monitoring has revealed tragic patterns in iconic locations such as Kakadu National Park. AimsPast studies have described universal patterns across multiple national parks in the Northern Territory, linking the declines to fire management; however, much of the data in Nitmiluk National Park do not cover the period that encompasses this decline. We examine this data separately to look for patterns with respect to fire history. MethodsWe examined standardised mammal survey data collected in Nitmiluk from 2005 to 2018, to look for correlates with year of survey, time since last burnt, and the frequency of early season and late season burns. Key resultsDespite subtle difference in methods over the years, we found there were some annual changes in the mammals, but little discernible pattern of change correlated to fire regime (which itself indicated an improvement in seasonality, and the extent of burning overall over this period). Instead, there was a distinct reduction in the survey effort. ConclusionsOur study provides further support for the pitfalls of ecological monitoring losing focus, being decoupled from management actions, and allowing ill-conceived changes in design. We recommend that future monitoring at Nitmiluk should focus on key management questions (i.e., fire), best methods for target taxa (i.e. camera traps), more regular and flexible sampling linked to a conceptual model, and integration and co-design with the local land managers, rangers and Traditional Owners. Short SummaryRe-examination of the mammal data collected in monitoring sites at Nitmiluk National Park between 2005 to 2018 indicated little pattern with fire regime over time, and instead indicated that a reduction in effort, had reduced the ability to find pattern With sparse and declining mammal population in northern Australia, future monitoring needs to be focused on key management questions.

Sky islands are high-elevation ecosystems surrounded by lowland habitats that create isolated environments with distinct climatic conditions. These factors have driven the evolution of many endemic species, separated from their larger, contiguous populations. An Individual-Based Model (IBM) was used to simulate population dynamics by modeling the behaviors and interactions of Tamiasciurus hudsonicus grahamensis (Mount Graham Red Squirrel) a subspecies of the American red squirrel (Tamiasciurus hudsonicus) that is endemic to the Pinaleno Mountains in southeastern Arizona. This approach can help predict future population trends based on historical species data leading to better conservation decisions. Using species-specific ecological preferences--including temperature, precipitation, and vegetation indices (NDVI)--an IBM was developed to simulate population dynamics and spatial distribution projections through 2100. Climate change projections, based on the best- and worst-case scenarios outlined in the 2014 National Climate Assessment, were incorporated to assess potential future population trends under changing environmental conditions. The population faces a 45-62% probability of extinction by 2100, with a significant risk of extinction within the next 50 years. A translocation experiment was conducted to evaluate the viability of relocating individuals to the Chiricahua Mountains, another sky island with a larger habitable area. However, the risk of extinction remains even higher (87-89%) due to environmental disturbances affecting both the Chiricahua and Pinaleno regions. This highlights the challenges of conservation efforts in the face of climate change and emphasizes the need for targeted management strategies to preserve this critically endangered subspecies.

The choice of appropriate methods to detect species is crucial for biodiversity monitoring. Camera trapping is currently one of the most widely used methods for characterizing mammal communities, although it requires substantial investment in equipment and personnel. In contrast, questionnaires administered to local populations provide a faster and more cost-effective alternative for assessing community composition, but may be influenced by respondent-related biases that compromise data reliability. This study evaluates the concordance between these approaches for characterizing the carnivore community in the Sierra de Segura (Jaen, southern Spain), using Cohens kappa coefficient, while also examining the individual and social factors shaping Local Ecological Knowledge (LEK). We deployed 24 camera-trap stations (144 trap nights) across a 25 km2 area to record carnivore presence. In parallel, we conducted two types of surveys with local residents (n = 103): (i) free-listing and (ii) image-based species recognition, while recording individual and social characteristics of respondents. Free-listing surveys tended to underreport species, whereas image-based surveys showed higher agreement with camera-trap data, although occasionally overestimating species presence. Higher concordance was associated with social factors indicative of closer and prolonged contact with the environment, such as permanent residence and ownership of agricultural land. Mammal communities differed between methods; however, agreement improved when respondents had higher LEK, while species-specific behavioral traits could also influence perception. Our findings demonstrate that image-based questionnaires can provide results comparable to camera trapping when respondents have strong connections to their natural surroundings. These results highlight the importance of both survey design and respondent selection in improving the accuracy of biodiversity monitoring, offering a transferable framework for integrating LEK into conservation protocols across diverse ecosystems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/720805v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@d55c34org.highwire.dtl.DTLVardef@1985c66org.highwire.dtl.DTLVardef@1da576aorg.highwire.dtl.DTLVardef@1a10ccb_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

Established invasive alien plant species require ongoing, costly management to reduce harm to agricultural and environmental values. Heterogeneous landscapes are often under threat from multiple long-established invasive plants, whose simultaneous management presents strategic and tactical challenges. Systematic monitoring of weed populations enables more strategic management by providing more detailed insights into invasion threats than the more readily available presence-only data. We leveraged six years of weed density monitoring and high-resolution environmental data to model habitat suitability for four high-priority weeds across the Australian Capital Territory. We developed habitat suitability maps for African lovegrass, Chilean needle grass, serrated tussock grass and St Johns wort. Maps were then standardised and combined to derive potential multi-species invasion hotspots at different management thresholds and explore patterns of secondary invasion threat. While some species shared environmental drivers such as elevation, each responded to distinct combinations and interactions among environmental drivers. Overall, we found approximately 71% of land had suitability for multiple weeds at various densities, but only 11% is suitable for two or more species to reach high densities. Areas suitable for most weeds often had St Johns wort as the next most suitable invader. These findings could improve management efficiency and reduce intervention challenges by focussing integrated control across species in a small number of priority areas. These findings support spatially explicit, multi-species decision-support tools for surveillance, prioritisation and strategic landscape-scale control.

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species' range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species' distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.