Diversity and Distributions

AimA comprehensive understanding of the spatial distribution of biodiversity is hindered by fragmented datasets, sampling biases, and inconsistent observation protocols. Here, we present a workflow that integrates disparate datasets to produce large scale maps of biodiversity metrics as a basis for management-relevant information tools. We use integrated species distribution modeling (iSDM) to account for sampling biases and disparate data collection techniques, taking advantage of the vast numbers of open datasets available in data aggregators like GBIF. LocationNorway (excluding Svalbard and Jan Mayen) TaxonVascular plants MethodsThe workflow consists of four main steps: data acquisition, data integration, integrated species distribution modelling (iSDM), and the production of derived outputs. Input data include structured surveys, opportunistic observations, and environmental covariates. These are standardised and integrated into a point-processed based iSDM framework to produce species richness maps, associated uncertainties, and sampling effort maps. The outputs are further processed to identify biodiversity hotspots or to summarise species-environment relationships. The workflow used vascular plant data from Norway, combining occurrence-only and presence-absence datasets with environmental covariates. Outputs were generated at a spatial resolution of 500 x 500 meters, balancing accuracy, computational feasibility and relevance for management decisions. High-performance computing resources were utilized for model fitting and predictions. A subset of available data was used to validate the species richness maps. ResultsWe produced detailed maps of species richness, uncertainties and sampling intensity across Norways heterogeneous landscape, incorporating 1218 species in our final results. The species richness patterns highlight patterns consistent with previous mapping efforts. Validation showed an increase in model accuracy when compared to models which did not use an iSDM framework. The workflow highlights limitations in the infrastructure of the currently openly accessible data, particularly the need for more structured presence-absence datasets and standardized metadata. Main conclusionsThis study underscores the potential of workflows that integrate disparate datasets for biodiversity modeling. To maximize accuracy and utility, future efforts should focus on improving data standardization, the publication and collection of more structured data, and fostering data-sharing collaborations. Advances in the workflow itself, including optimising modelling covariates and integrating more comprehensive spatio-temporal aspects, will also increase the relevance of the outputs. These advances will increase our ability to estimate species richness with a precision and accuracy that can reliably inform conservation and management decisions.

The release of tens of millions of common pheasants (Phasianus colchicus) across the UK for shooting may pose an ecological risk to native species and sensitive habitats, particularly if the birds move into protected areas (PAs) such as Special Areas of Conservation (SAC), Special Protection Areas (SPA), and Sites of Special Scientific Interest (SSSI). The extent of this ecological risk depends on the abundance of pheasants in these sensitive sites, especially if they are attracted there after the shooting season when game management efforts to retain the birds cease. We used relative pheasant abundance measures derived from British Trust for Ornithology bird atlas data from 3793 2km tetrads across four English counties (Berkshire, Cornwall, Devon, and Hertfordshire) to determine if pheasants preferentially disperse into or reside in areas with greater PA coverage. We analysed relative abundance in both the winter shooting season and the breeding season using a Bayesian occupancy-abundance model, controlling for habitat type and diversity. Our results showed a strong influence of habitat on pheasant abundance, consistent with known habitat preferences. However, we found no evidence of a relationship between relative pheasant abundance and the proportion of ecologically relevant PA coverage in a tetrad. This lack of a relationship was consistent across all four counties and across both the winter and breeding seasons. Our finding suggests that common pheasants do not preferentially disperse into or reside in protected areas compared to surrounding, unprotected land, suggesting that the ecological impacts caused by released pheasants are no more likely to occur in protected areas than in non-protected areas.

AimHuman land-use change contributes to biodiversity declines, but also creates new niches that facilitate novel biotic interactions. These interactions can reshape ecological communities and ecosystem function, yet remain poorly understood. Swiftlets and swallows in Southeast Asia present a classic example: coexistence is facilitated by fine-scale diet partitioning, with population sizes historically limited by available nesting substrates. However, several species now nest on manmade structures, particularly "nest farms" built to harvest edible swiftlet nests. We evaluated whether land-use change, especially the spread of nest farms, is leading to breakdowns in niche partitioning and increased competition among six sympatric swiftlets and swallows. LocationNorthern Borneo MethodsWe calculated geographic niche overlap using species distribution models (SDMs) with different environmental predictors, hypothesizing greater overlap when land-use variables were included. We then implemented joint species distribution models (JSDMs) to partition shared environmental responses from potential biotic interactions, predicting that competition would emerge as negative residual correlations. We used sightings from citizen-science datasets and structured surveys to evaluate the influence of climate, land-use, nest farms, morphology, and foraging behavior on species occurrences. ResultsSDMs that included land-use variables showed high niche overlap, suggesting that human activity homogenizes niches. The optimal JSDM, based on structured survey data, identified distance to nest farms as the strongest predictor of occurrence for all species, with species showing both positive and negative responses. Morphology and behavior had small effects, and residual correlations were weak, indicating limited unexplained biotic interactions. Main conclusionsHuman activity, through the creation of artificial nesting sites, broadly drives co-occurrence of swallows and swiftlets across our study region. These effects appear to operate primarily through environmental filtering rather than direct competition. Our findings reveal substantial and complex impacts of land-use change and anthropogenic nest sites on the distribution and composition of aerial insectivore communities.

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.

AO_SCPLOWBSTRACTC_SCPLOWClose-Kin Mark-Recapture (CKMR) is a statistical framework for estimating demographic parameters of wild populations. Instead of recapturing individuals, it relies on the identification of closely-related pairs such as parents and offspring, or siblings. By measuring how often such close-kin are "recaptured" among sampled animals (whether alive or dead), scientists can estimate demographic parameters such as census size, mortality rates, and connectivity. CKMR is starting to change fisheries and wildlife management by giving more reliable demographic information, even for many species that resist conventional approaches. Here we introduce the kinference R package, which provides a set of tools for finding close-kin pairs among thousands of samples each genotyped at thousands of SNPs, and for associated quality control. The CKMR context implies different requirements and assumptions to many other kinship programs. In particular, kinference accounts empirically for linkage without requiring a genome assembly, is able to estimate and control false-negative and false-positive probabilities, and can cope with null alleles. The package has been developed and used in numerous CKMR projects since 2017. This paper documents the assumptions, statistical algorithms, and intended workflow for kinference.

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.

The ongoing decline in biodiversity highlights the need for understanding the causes of population changes. This study uses 25-year, large-scale monitoring dataset to investigate the influence of climate and landscape structure on the annual population growth rates of 84 bird species across Poland. Our methodological framework involves the spatiotemporal decomposition of these environmental drivers to decouple demographic effects of long-term carrying capacities from the short-term effects of environmental perturbations. Using species-specific demographic models followed by a community-wide meta-analysis, we evaluated how individual species responses scale up to shape community-level dynamics. The results reveal significant variation in species-specific responses to individual drivers. At the community level, our findings suggest that bird populations are mainly regulated by the long-term spatial constraints rather than short-term disturbances. Persistent environmental heterogeneity had the strongest positive demographic effect on birds, followed by temperature, forest dominance over croplands, and precipitation. In contrast, rapid temporal shifts in environmental heterogeneity and precipitation anomalies negatively affected population growth, whereas urbanisation consistently exerted a negative effect across both spatiotemporal dimensions. Our results highlight the significance of protecting existing heterogeneous and ecotonal habitats, as well as the need to incorporate features that enhance habitat heterogeneity into urban development. Article impact statementPreserving heterogeneous habitats is essential for the conservation of bird populations.

Understanding the drivers of genomic health and their consequences for population viability is often overlooked but potentially important to effective conservation amidst the biodiversity crisis of the Anthropocene. Leatherback turtle (Dermochelys coriacea) populations have declined globally due to anthropogenic factors, with some populations losing over 90% of their abundance over the past 30-50 years. While conservation efforts have been successful in stabilizing some populations, others continue to decline, and the reasons for these differential trajectories remain unclear. To assess how recent demographic factors, such as population size and decline, influence population genomic health, we combined population monitoring information with medium depth whole-genome and reduced representation resequencing data from globally representative populations. We found that small-stable populations have lower genomic diversity and higher inbreeding than large declining populations, reflecting prolonged small population sizes and limited gene flow. Yet, small-stable populations also show evidence of deleterious allele purging, suggesting genetic resilience. This, combined with lack of detectable genomic erosion over the study period, provides hope for potential recovery of healthy leatherback populations provided that anthropogenic threats are effectively mitigated. However, potential time lags and possible recent increases in inbreeding among close relatives in recently declined populations warrant continued monitoring and assessment. Genomic and abundance-based metrics were less aligned following rapid population declines, emphasizing the different timescales of the evolutionary and demographic processes they reflect, respectively, and the strength in their complementary, integrative use for extinction risk assessments. This also supports that it is not too late to turn the tide for recently declined leatherback populations and that continued investment in conservation efforts and threat reductions are warranted. Collectively, our results highlight how recent and historical demography shapes current genomic health and recovery potential in leatherback turtles, aids understanding of current risks and informs future conservation and management strategies.

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

ContextAnimals balance resource acquisition with risk mitigation. These trade-offs are rarely uniform, being mediated by spatial scale, demographic traits, and environmental constraints. Understanding these divergent spatial behaviors is critical for management across human-dominated landscapes. ObjectivesWe investigated how sexual dimorphism and ontogeny interact with landscape structure to influence scale-dependent resource selection. Specifically, we sought to determine how these demographic factors mediate spatial trade-offs between optimal foraging habitats, top-down intraguild predation risk, and bottom-up severe winter weather. MethodsWe examined the spatial ecology of a solitary carnivore, the bobcat (Lynx rufus), across a heterogeneous, human-modified landscape in northern Minnesota, USA. Using spatial data derived from harvested adult and juvenile individuals, we evaluated multi-scale selection relative to land cover, structural ecotones, intraguild predator activity, and winter severity. ResultsHabitat selection was scale-dependent and partitioned demographically. Whereas bobcats universally selected for ecotones and avoided homogeneous open habitats at fine scales, responses to other features diverged by sex and age. Females actively avoided areas with high coyote activity and freezing temperatures; males exhibited high risk tolerance, apparently indifferent to coyote activity and tolerant of freezing temperatures. We identified a distinct ontogenetic spatial shift among females. Subordinate juveniles were competitively excluded from optimal natural ecotones, forcing them into riskier, anthropogenic agricultural edges. In contrast, adult females optimized foraging opportunities by selecting productive ecotones at the intersection of woody vegetation and semi-natural grasslands. ConclusionsOur findings demonstrate that habitat selection is not a static species-level trait, but instead a dynamic process resulting from the interaction between ontogeny, sex, and landscape heterogeneity. The reliance of vulnerable demographic groups on marginal or anthropogenic habitats highlights how human land-use changes can inadvertently produce ecological winners and losers within the same species. Consequently, landscape management and conservation planning for solitary carnivores must shift from broad, population-wide habitat prescriptions to strategies that explicitly accommodate the divergent spatial requirements of specific demographic cohorts.

BackgroundWintering migratory birds must balance energetic requirements, resource availability, and disturbance in increasingly human-modified landscapes. However, individual-level variability in daily movement and winter space use remains poorly understood in South Asian populations of the common crane. We investigated how seasonal dynamics, landscape composition, and individual differences structure winter movement ecology in a semi-arid agro-wetland system in western India. MethodsWe analysed high-resolution GPS telemetry data from multiple tagged cranes tracked across three consecutive winters. Daily movement distances were modelled using mixed-effects approaches to partition variance within and among individuals and among winters. Daily movement trajectories were evaluated using non-linear temporal terms. Landscape predictors, including cropland proportion, built-up area, and habitat heterogeneity, were incorporated to assess environmental drivers. Winter range distributions were estimated using autocorrelation-informed kernel density estimation within a continuous-time movement modelling framework. ResultsMost variation in daily movement occurred within individuals rather than among them, indicating strong behavioural flexibility. Interannual differences explained substantial variance, suggesting sensitivity to changing environmental conditions. Daily movement distance followed a non-linear seasonal pattern consistent with shifts in the profitability of agricultural resources over winter. Cropland proportion and landscape evenness were negatively associated with movement distance, whereas a high proportion of built-up areas increased daily movement distance, reflecting a trade-off between resource concentration and anthropogenic disturbance. Winter range distribution size varied markedly both within individuals across years and among individuals within seasons. ConclusionWinter movement and space use in common cranes are predominantly context-dependent and environmentally driven. Seasonal dynamics, agricultural landscapes, and human disturbance jointly structure movement patterns, with limited but consistent individual differences. Multi-year, individual-based telemetry provides a comprehensive understanding of winter spatial strategies in dynamic semi-arid agro-wetland systems.

BackgroundThe Andean bear (Tremarctos ornatus), South Americas only ursid, is one of the worlds most elusive large mammals, making movement data collection exceptionally rare. Addressing this gap, we present the largest telemetry dataset ever assembled, spanning 19 individuals tracked across three Ecuadorian National Parks over two decades, paired with a novel analytical approach. MethodsWe integrated Continuous-Time Movement Models (CTMM), Auto-correlated Kernel Density Estimators (AKDEs), Hidden Markov Models (HMM) and a diel niche theoretical framework to mitigate biases previously unaccounted for the species in telemetry studies. Fine-scale AKDEs and non-linear movement metrics were calculated to understand seasonal space use and movement behaviors. Speed and diffusion from CTMM and behavioral states from HMM were modelled with environmental covariates to investigate which conditions shape diel and seasonal activity. ResultsPopulation mean home range was 138.2 km2 (95% Confidence Intervals 78.7-225.5), with males (239.8 km2; 182.8-307.5), significantly exceeding females (58.5 km2; 35.5-90.3). Notably, three females exhibited ranges comparable to some males. Weekly and monthly AKDEs uncovered cyclic home range dynamics potentially driven by resource availability, with contractions around corn harvests, mortino and achupalla fruiting, and expansions during paramo transitions. Decoupling speed from diffusion rates showed region-specific behaviors: intensive patch exploitation in Llanganates, broad exploratory ranging in Cayambe-Coca, and suppressed female locomotion in Cotacachi-Cayapas. Statistical analyses identified temperature as a key diel modulator and precipitation as the seasonal driver. Foraging probability increased between 2:00-6:00, large displacements between 7:00-14:00, and nocturnal movement rose significantly under colder conditions. Across diel hypothesis frameworks, bears were classified as cathemeral rather than strictly diurnal, corroborated by camera-trap records from Colombia, Ecuador, and Peru. ConclusionsWe propose a cathemeral diel phenotype that responds to thermal fluctuations and situates Andean bears within a broader ursid context of thermoregulatory niche plasticity. This dataset reveals unprecedented resolution of regional and sex specific behaviors that will facilitate and accelerate comparative studies in rapidly changing Andean landscapes. By releasing this long-term dataset as an open resource, we provide a foundation for climate-resilient conservation strategies. More broadly, we advocate for data democratization and invite collaboration.

The small mammals in the tropical savannas of northern Australia, have undergone a degree of change in recent decades, best documented in the Northern Territory. Data is limited from northern Queensland and though the same trends are assumed, the topographic and climatic features differ substantially. In this study we examined data systematically collected from 725 sites between 1998-2012 in three bioregions representing a climatic gradient: from semi-arid to monsoon tropical savannas. We investigated via information-theoretic models and model averaging, the relationship between five mammal groupings and three landscape variables (fractional cover green, elevation and vegetation diversity) to elucidate any consistent or different patterns in the mammal fauna. Key patterns included relationships with increasing elevation (critical weight range species richness positively associated with elevation, rodent species richness negatively associated), increasing rodent and dasyurid species richness with vegetation diversity, and lower macropod and dasyurids abundance with increasing fractional cover green. These relationships underscore a need to consider mammal conservation in Queensland with more nuance than in the more topographically inert Northern Territory. Management strategies need to be more attuned to taxonomic and regional differences, to prevent perverse outcomes.

AimHome range size is a fundamental aspect of animal spatial ecology, and understanding the factors that shape it is important for conservation purposes. Several hypotheses, based on energy needs or competition, assume that home range size negatively correlates with population density. However, this pattern has been little investigated on a global scale, and it remains unclear whether it would stand at both intra- and interspecific levels. To fill this gap, we conducted a global exploration of this relationship at the level of an animal family. Location: Global. Time period: Contemporary. Major taxa studied: Wild Felidae. MethodsIndividual home range size records (n = 1022) and population density estimates (n = 1061) were retrieved from the literature for 23 felid species across the world. We first investigated the interspecific relationship by modelling the median home range size of a species as a function of its median population density. To study the intraspecific relationship, we spatially merged data points based on their spatial or temporal proximity. We then applied a mixed-effects linear model using species as a random factor. ResultsWe found that home range size was negatively associated with population density, at both interspecific (-1.323 {+/-} 0.180, p < 0.001) and intraspecific levels (-0.569 {+/-} 0.201 to - 0.537 {+/-} 0.201 depending on the merging approach, p < 0.01). Landscape features were also predictors of home range size, without confounding the effect of population density. Main conclusionsSeveral processes likely govern the relationship between home range size and population density: differences in body mass between species may drive the interspecific relationship, whereas the intraspecific pattern is probably explained by conspecific competition. Although more research is needed to quantify their relative contribution, our study highlights a worldwide ecological pattern that exists at multiple biological levels in the wild.

O_LIAgricultural intensification can support the expansion of introduced species which are highly adapted to human-modified landscapes, but the mechanisms by which this occurs are often unclear. C_LIO_LIHere we investigate the spatial ecology of a rapidly expanding introduced bumble bee (Bombus impatiens) and a native congener (B. mixtus) in agricultural landscapes of southwestern British Columbia, Canada. We used microsatellite genotyping and spatially explicit capture-recapture models to compare the foraging distance of the two species, and fitted hierarchical models to compare their abundance, behaviour (nest searching vs foraging), and lineage survival as a function of landscape composition and configuration. C_LIO_LIWe found that B. impatiens had a broader foraging range than B. mixtus, and that its colony/worker abundance were positively associated with the surrounding area of residential gardens, but decreased relative to B. mixtus abundance in response to increasing seminatural area. In contrast, B. mixtus colony abundance decreased in landscapes with a greater area of intensively managed berry crops. C_LIO_LIWe observed fewer B. impatiens queens per survey in landscapes with more low-disturbance landcover, and hypothesize space use of this species could be shaped by concentration on potential nesting habitat. Consistent with this observation, nest searching behaviour was more common for B. impatiens queens, while B. mixtus queens were primarily observed foraging, suggesting these two species derive different value from agricultural landscapes during colony establishment. C_LIO_LIFinally, we found that the rate of lineage re-capture between 2022 colonies and 2023 spring queens was nearly 10-fold higher for B. impatiens than for B. mixtus, indicating a greater capacity of the introduced species to complete its life cycle in agro-natural landscape mosaics. C_LIO_LIOur results suggest that differences in spatial ecology may contribute to the differential success of these two species in human-modified landscapes, and provide insight into the mechanisms by which land-use change shapes community composition. C_LI O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/723627v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1e72eacorg.highwire.dtl.DTLVardef@a958a0org.highwire.dtl.DTLVardef@1f970b6org.highwire.dtl.DTLVardef@156f522_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstract. Coloured diagrams of B. mixtus and B. impatiens are credited to Elaine Evans and the Xerces Society, with permission.

QuestionsEcological monitoring, repeated collection of ecological data, is essential to document how ecosystems respond to change. In grasslands, different vegetation monitoring protocols are used across disciplines, making it difficult to address multiple management objectives or research questions. We asked four questions about how three common vegetation monitoring protocols compare. (1) How do the protocols differ in how they collect data? (2) How do the protocols differ in their utility? (3) In what ways do vegetation measurements quantitatively differ across protocols? (4) What are each protocols strengths? LocationThis study was conducted on working ranches in the Southern Great Plains with vegetation consisting mainly of native forbs and grasses. MethodsWe implemented three protocols at each site: (1) the Rangeland Analysis Platform (RAP), (2) the Grassland Effectiveness Monitoring (GEM) protocol, and (3) a typical pollinator ecology survey protocol. We qualitatively compared each protocols utility and quantitatively compared cover measurements that each produced. ResultsAll three protocols displayed positive associations within cover categories, but differed in actual cover measurements. The RAP protocol, which uses remote sensing, measured the highest total vegetation cover. The GEM protocol, a line-point intercept method, had more capability to capture fine-scale cover patterns. The GEM protocol measured the most bare ground while the Pollinator protocol measured more forb coverage. ConclusionFine-scale methods like the GEM protocol are most appropriate to address objectives that require capturing small patterns that would otherwise be overlooked with methods like quadrats or remote sensing. Remote sensing is advantageous when monitoring large areas or inaccessible land, but may over-estimate cover. The Pollinator protocol is best equipped to address questions regarding flower abundance and richness. Similarities among protocols can facilitate synergy across disciplines for more effective monitoring. We emphasize the importance of denoting a clear scale and scope of monitoring objectives before selecting methods.

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.

O_LIEffective conservation of highly migratory species requires understanding genetic structure across breeding populations and access high{square}resolution markers capable of assigning individuals from mixed aggregates (e.g. bycatch or new nesting sites) to their natal origins. Genomic approaches provide unprecedented resolution but add methodological challenges; thus, it is essential to first build a genomic baseline from known breeding areas and then evaluate strategies for assigning unknown individuals. C_LIO_LITo address this, we used 2b-RAD sequencing, a genomic reduction technique useful for degraded DNA, and loggerhead turtles as a case study. This species shows philopatric breeding, while juveniles and adults form mixed aggregations in foraging grounds. C_LIO_LIOur results highlight the importance of building baselines that include all potential source populations contributing to mixed aggregations. We detected hierarchical genetic differentiation and high resolution and successfully assigned the natal origin of 124 unknown individuals from four Mediterranean foraging grounds. These grounds showed distinct source contributions, and comparisons with previous studies suggest possible temporal shifts in stock composition. C_LIO_LIWe provide a comprehensive genomic baseline for individual assignment of Altanto-Mediterranean loggerhead turtles of unknown natal origin and a general framework for identifying population-specific threats in highly migratory species. C_LI

1Effective population size (Ne) is a critical parameter for evaluating the evolutionary and persistence potential of endangered populations and for designing sustainable conservation strategies. Captive breeding and release programs are widely used across taxa to reduce risk of extinction when natural reproduction is insufficient or no longer possible, making it essential to assess their consequences. We used the case study of the landlocked Saimaa salmon (Salmo salar), one of the most critically en-dangered salmonid populations in Europe, with unique evolutionary significance due to its isolation from other populations since the last glaciation. Using long-term demographic data (1969-2024) from wild-caught founders of a captive breeding and release program, we estimated the effective population size under multiple scenarios of variance in reproductive success. Across scenarios, Ne ranged from 33 to 81 individuals, representing 32%-75% of the census size. Captive breeding practices aimed at equalizing parental contributions during fertilization and early life stages increased Ne by 12% compared to natural reproductive conditions. However, variation in survival after early developmental stages, typically beyond direct management control, remained a key determinant of Ne. Despite recent increases in the number of founders, the population remains genetically vulnerable due to historical bottlenecks. These results highlight that while captive breeding programs can partially mitigate genetic risks, their effectiveness depends critically on both controlled and uncontrolled sources of variance in reproductive success. Strengthening such programs may require combining breeding management with habitat restoration and, where appropriate, genetic rescue to ensure the long-term evolutionary potential of such unique and endangered populations.

Designing effective spatial management for chondrichthyans (sharks, skates, rays and chimaeras) requires incorporating critical areas, sites essential for population maintenance, such as reproductive and feeding areas. Yet most area-based measures have been developed without consideration of chondrichthyan habitat use. The Important Shark and Ray Area (ISRA) initiative has been pivotal in designating priority areas through a rigorous, consultative process. To complement this, our study offers researchers a testable definition for generating robust evidence to strengthen future critical area delineations and related management decisions. We define critical areas using three criteria: 1) relative frequency of use, (2) extended within-year occupancy and (3) repeated use across years. This framework enables objective comparison among candidate sites and is generalisable across different critical area types. The definition builds upon established early-life-stage habitat concepts and applies these to broader life-history functions. The utility of this framework is then demonstrated through a systematic review of contemporary peer-reviewed literature of critical chondrichthyan areas in the European Atlantic. The review highlighted 62 critical areas with Strong evidence and 41 areas of Moderate strength evidence, which informed the European Atlantic ISRA selection process. Research effort was concentrated in inshore areas, particularly around the British Isles and Portugal, with biases towards large, threatened and commercially valuable species, whilst chimaeras were notably underrepresented. Early-life stage areas were most frequently identified, whereas resting areas were rarely documented. Evidence patterns and biases are examined in the context of evolving critical area concepts to advance their development and improve the quality and breadth of future research. By outlining a testable definition, identifying key knowledge gaps, and proposing research and reporting guidelines, this work enhances the consistency, comparability, and spatial coverage of future chondrichthyan habitat research to support its application to conservation planning.