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.

O_LIChanges in habitat structure across species distributions may contribute to the generation and maintenance of range limits, but few studies have evaluated this by directly measuring habitat availability across relevant spatial scales. C_LIO_LIHere, we test the predictions that coarse-scale and patch-level habitat availability decline towards and beyond the northern range limit of Pacific coastal dune endemic Camissoniopsis cheiranthifolia. We used aerial imagery and geographic information system (GIS) tools to measure the coarse-scale availability of coastal dune habitat in California and Oregon. The availability of finer-scale habitat patches specifically suitable for C. cheiranthifolia was measured in a 2-generation field survey of > 4,200 5m x 5m plots randomly distributed across 1100 km of coastal dune habitat transcending the species northern range limit. At each plot, we estimated the proportion of area that contained suitable habitat as well as recorded occupancy by C. cheiranthifolia. As an alternative approach to visually estimating habitat suitability, we recorded plant community composition at each plot to predict beyond-range habitat suitability using a random forest model. C_LIO_LIContrary to our predictions, we found that coastal dune habitat, measured coarsely from aerial imagery, was more abundant and continuous towards and beyond the northern range limit. At the fine scale, however, the proportion of plots with suitable habitat (patch suitability) and the proportion of habitat within plots that was suitable (patch size) declined across the range limit. Moreover, patches were more isolated from one another and, in one survey year, less temporally stable towards and beyond the range limit. Finally, occupancy by C. cheiranthifolia was less likely in smaller, more isolated, and temporally unstable patches, providing mechanistic insight to the previously observed decline in occupancy towards the range limit. C_LIO_LISynthesis: Taken together, our results suggest that fine-scale habitat patch configuration changes in ways that likely impede patch colonization, thereby reducing occupancy and limiting the species northern distribution. Thus, consideration of geographic variation in patch and landscape structure, rather than only coarse-scale habitat availability, may be essential for understanding the processes that limit species ranges. C_LI

Natural history collections underpin our understanding of species distributions, yet some historical records remain embedded in modern avifaunal checklists despite limited documentation and no independent verification. One such case concerns the Dusky Parrot Pionus fuscus in Colombia: although reported from specimens collected by Melbourne A. Carriker Jr. in 1942 in the Serrania de Perija, the species has not been observed in the country for nearly eight decades yet continues to be included in national checklists and conservation assessments. We reassessed the validity of this record by applying a multi-evidence framework integrating historic archival reconstruction, specimen-based morphological comparisons, climatic niche analyses, biogeographic limit assessment and contemporary survey-effort data. Historical documentation and morphological evidence based on high-resolution specimen images and associated curatorial records demonstrate that the Carriker specimens correspond to Pionus chalcopterus, not P. fuscus. Climatic niche analyses reveal minimal environmental overlap between P. chalcopterus and P. fuscus, and place the Perija locality within the climatic niche of P. chalcopterus, while regional biogeography and extensive modern birdwatching coverage provide no support for the occurrence of P. fuscus in Perija. Together, these concordant lines of evidence demonstrate that P. fuscus does not occur in Colombia. Our findings support its removal from national bird lists and conservation assessments and highlight how integrated, multi-evidence reassessments of historical records strengthen ornithological baselines, improve biogeographic inference and ensure that conservation priorities rest on verifiable evidence.

AimUnderstanding whether invasive species retain or shift their ecological niches has traditionally relied on scalar overlap metrics that quantify the magnitude of niche change, but not its structure. Here, we test whether biological invasions involve a reorganisation of the environmental axes along which native and invasive ranges are differentiated, and whether the dominant axes of this reorganisation are consistently associated with invasion pathway type (intercontinental vs. within-continent). LocationGlobal (North America, Europe, Africa, Asia, Australasia). Time periodContemporary (environmental variables representing long-term averages, 1980-2021). Major taxa studiedFreshwater crayfish (Decapoda: Astacidea): Procambarus clarkii, Faxonius limosus, Pacifastacus leniusculus, Faxonius virilis, Faxonius rusticus. MethodsWe analysed native and invasive occurrences for five globally important crayfish invaders using [~]400 hydrologically resolved environmental variables from the Global Crayfish Database of Geospatial Traits. Classification models were used to quantify environmental differentiation between native and invasive ranges, and feature contributions were aggregated by environmental domain (climate, topography, soil, land cover). Patterns were evaluated across intercontinental and within-continent invasion pathways and assessed for robustness using cross-validation, permutation tests, sample-size sensitivity, and comparisons with classical niche overlap metrics. ResultsNative and invasive occurrences were consistently distinguishable across all species (accuracy 96.5-99.9%). A pathway-dependent pattern emerged: intercontinental invaders were primarily differentiated along climatic dimensions (58-76% of model importance), whereas within-continent invaders showed a more balanced contribution of climatic and topographic variables ([~]42% each), including strong signals from river network position. This contrast was stable across cross-validation folds (SD < 1.6%), and supported by permutation tests (P = 0.001). Classical niche overlap metrics (Schoeners D = 0.30-0.62) did not capture this qualitative distinction. Main conclusionsBiological invasions involve not only changes in niche position but a reorganisation of the environmental axes that distinguish species distributions. Our results suggest that the dominant axes of this reorganisation differ systematically with invasion pathway, reflecting whether species encounter novel climatic regimes or primarily shift within existing climatic space along topographic and network-position gradients. By resolving which environmental dimensions underpin native-invasive differentiation, this approach provides a complementary perspective to scalar overlap metrics and a basis for more mechanistic interpretations of invasion processes.

Alpine ecosystems are among the most climate sensitive on Earth, yet logistical challenges and detection biases often impede robust assessment of alpine dependent species. We investigated habitat associations and density patterns of the Sierra Nevada subspecies of the Gray-crowned Rosy-Finch (Leucosticte tephrocotis dawsoni), an alpine obligate and regional endemic, over five breeding seasons from 2018 to 2022 using hierarchical distance sampling and mark-recapture distance sampling to explicitly account for imperfect detection and spatial heterogeneity. Density estimates tracked annual snowpack variation, ranging from 4.77 individuals/km{superscript 2} in a low snow year to 12.08 individuals/km{superscript 2} in a high snow year. Abundance was highest near persistent snow patches that provide foraging habitat and near cliffs that provide nesting substrate, and declined sharply above approximately 10% woody cover, with densities approaching zero beyond approximately 25%, indicating a steep ecological threshold. In contrast, the proportion of surveyed blocks with detections remained relatively stable across years. Together, these patterns indicate a three timescale co-limitation framework in which breeding habitat is shaped by static features (cliffs), dynamic annual drivers (snowpack), and longer-term directional change (woody encroachment). By linking population density to climate sensitive habitat features, this study provides a high-resolution abundance-based baseline for long term monitoring and offers a framework for evaluating climate vulnerability in alpine and other resource-limited systems. Open Research StatementData necessary to replicate the analyses and results presented in this manuscript will be archived in the Dryad Digital Repository upon acceptance, with no embargo on the material. The R code associated with this manuscript is not novel. All analyses use publicly available packages and functions without modification, including mrds (v2.3.0), unmarked (v1.2.5), tidyverse (v2.0.0), MuMIn (v1.47.5), and standard ggplot2 visualization tools. All code is properly cited within the manuscript and publicly available through CRAN. Complete analysis scripts will be archived in Dryad alongside the data upon acceptance to facilitate full reproducibility of results.

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.

Species distribution models (SDMs) are widely used to support risk assessment for invasive non-native plant species (INNPS), but their performance is constrained by the coverage of occurrence data. Combining occurrences from citizen science (CS) platforms with data from structured state agency (StAg) monitoring provides unique advantages, yet they are rarely integrated. Here, we systematically compare how CS, StAg, and combined (COM) occurrence data influence the inferred environmental niches, predictive performance, and spatial applicability of SDMs for three widespread INNPS (A. altissima, H. mantegazzianum, I. glandulifera) in central Germany. We quantified niche overlap between datasets using PCA and Schoeners D and applied a hierarchical SDM utilizing boosted regression trees, while the Area of Applicability (AOA) was assessed to identify monitoring gaps. CS data were strongly biased toward lower-elevation, urbanized environments, whereas StAg data captured higher-elevation, remote habitats, particularly along watercourses. Niche overlap reflected both invasion stage and habitat preferences: A. altissima, a species that is spreading, showed the lowest overlap. H. mantegazzianum, associated with linear habitats like watercourses and infrastructure, exhibited intermediate overlap, while I. glandulifera, a widespread species, displayed the highest overlap. Overall, combined models achieved the highest predictive performance (AUC: 0.85, TSS: 0.58), reduced uncertainty along environmental gradients and produced more ecologically plausible suitability patterns. AOA analysis revealed high applicability ([&ge;]59%) across data sources and species, with COM models consistently reducing extrapolation uncertainty. Our findings highlight that integrating CS and StAg data reduces spatial biases and enhances SDM robustness, which is vital to improve INNPS risk assessments and management. HighlightsO_LICitizen science and state agency data capture distinct environmental spaces. C_LIO_LIOverlap between data sources is related to invasion stage and habitat preference. C_LIO_LICombined data improves invasive species niche representation and model accuracy. C_LIO_LIAOA analysis reveals monitoring gaps, especially in remote and high-elevation areas. C_LI

Northern gannets (Morus bassanus) have been regarded as a seabird success story, due to population increases throughout the 20th and 21st century contrasting with global seabird declines. However, in 2022 gannets experienced a severe outbreak of High Pathogenicity Avian Influenza (HPAI) across their global distribution, leading to an urgent need to reassess their population status. This study presents breeding gannet census numbers for 2023/24 from all colonies across the North-East Atlantic metapopulation (Great Britain, Ireland, the Channel Islands, Iceland, Norway, the Faroe Islands, France, Germany, Russia). Gannet numbers decreased by 17% across the North-East Atlantic metapopulation between the 2013/14 and 2023/24 census from 414,598 to 345,854 apparently occupied sites (AOS), a global decrease of at least 13%. The bulk of the reduction in AOS was driven by the largest colonies (>10,000 AOS) each losing tens of thousands of AOS. These figures likely underestimate the impact of the HPAI outbreak worldwide, since most colonies will have increased between the last census in 2013/14 and the 2022 HPAI outbreak, and the Canadian breeding population was last counted pre-HPAI outbreak. Scotland still holds the largest proportion of both the North-East Atlantic metapopulation (59%), and the world population (46%), while Great Britain, Ireland and the Channel Islands together hold 83% of the North-East Atlantic metapopulation and 64% of the world population. This study not only presents an updated population census for gannets in the North-East Atlantic but illustrates the large-scale impacts of a disease outbreak on a seabird species across its global range and highlights the importance of more regular census efforts to better quantify the demographic consequences of such events.

Semi-aquatic mammals lie at the intersection of several key conservation issues such as wetland deterioration or species invasions, and monitoring their distribution in space and time is essential to inform conservation strategies. However, gathering information about their presence is challenging due to their elusive lifestyle and generally low abundance. The Eurasian otter (Lutra lutra), a near-threatened and strictly protected species in Europe, is currently recolonizing part of its historical range. Its high conservation interest, combined with a dynamic more commonly associated with range-expanding or invasive species, makes it a particularly compelling case study. Otter monitoring has traditionally relied on scat surveys, but recent environmental DNA (eDNA) and camera-trapping initiatives have emerged offering promising complementary tools. Yet, these approaches have rarely been formally compared, either to one another or across regions. Here, we compared the efficiency of spraint surveys, camera traps, and eDNA for detecting otters, and assessed how their performance varied among four catchments in southern France where the species is known to be present. All three methods provided otter detections with varying efficiency. Scat surveys were the most effective method, with an average detection probability of 0.71 and no strong variability between catchments. Although camera-traps had the lowest detection rate, they provided detections at two of the four sites where no spraint was found, highlighting the complementarity of these two approaches. Detection rates varied greatly between individual cameras rather than between catchments, underscoring sensitivity to camera-placement. eDNA showed important variability between catchments, with detection probabilities differing by roughly sixfold across regions. All in all, our results highlight differences in efficiency between methods and across environmental conditions, and show the value of combining approaches for future monitoring programs.

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.

Accurate home range knowledge is essential for conserving species that are highly dependent on certain types of habitats. The critically endangered European mink (Mustela lutreola) is a wetland specialist whose movements are constrained by riparian and wetland habitats. In dendritic landscapes, conventional home range estimators such as Minimum Convex Polygons tend to include unsuitable habitats in estimated home ranges. Using VHF telemetry data from 16 individual-years tracked in France between 1996-1999 and 2020-2022, we compared four methods: Kernel Density Estimator (KDE), an adaptative sphere-of-influence local convex hull (a-LoCoH), a newly developed Ecological Home Range method (EHR), and a Generalized Additive Model (GAM) approach integrating hydrographic covariates. Our objective is to determine which method best accounts for the European minks specialization in wetlands, considering the spatial distribution of locations. Evaluation with wetland-specific metrics showed KDE consistently overestimated range extent and included unsuitable habitats, and a-LoCoH yielded mixed results, but these indicated that the method was not effective in excluding unused habitats. It was EHR and GAM methods that aligned more closely with ecological constraints. We therefore recommend GAM because it matches our objective and has the capacity to integrate additional environmental variables. Using the GAM, male home ranges averaged 3,074 ha--26 times larger than female ranges (116 ha)-- and were significantly larger in river than marsh landscapes. These are the largest ranges reported for the species. Large spatial requirements heighten vulnerability to road fatality and predation, both significant threats for remaining French populations. Our findings highlight the need for conservation strategies that integrate precise, habitat-based range estimates. The GAM method offers a robust, adaptable framework for managing European mink and other semi-aquatic species in complex landscapes.

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.

AimAnalysis of species distributions often rests on the assumption of environmental equilibrium. That is, the distribution of a species (as documented by observation records) captures the full range of environmental conditions under which that species can maintain viable populations. Despite the centrality of this assumption to a variety of biogeographic questions, it is rarely empirically tested. This is particularly critical for recently introduced invasive species that are characterized by rapid expansion in their introduced range, often coupled with a niche shift relative to their native distribution. Defining equilibrium under these dynamic conditions is difficult. We developed the concept of environmental stasis as a more tractable proxy for equilibrium. In the context of species invasions, we define stasis as a prolonged period without an increase in the environmental conditions occupied by a species. LocationNorth America Time Period1614 to 2020. Major Taxa StudiedInvasive plants MethodsWe applied the metric of climatic stasis to a suite of 258 invasive plant species in North America. We categorized their invasion trajectories into three classes (linear, two- and three-phase) based on theoretical expectations and then assessed how many had demonstrated environmental (climatic) stasis over a period of at least thirty years. ResultsMore than 80% of the species were best fit by two- or three-phase models, indicating a declining rate of expansion. Climatic stasis was only documented for 44% of the species. In contrast, 85% of the species were in climatic stasis in their native ranges. The time to reach stasis ranged from 30 to 145 years (mean 90), and species at stasis in their invaded range occupied 97% of the climatic space they occupied in their native range. Main ConclusionsThis assessment provides valuable insight into the unrealized threat posed by the majority of invasive plants that have not yet reached stasis, as well as identifying which species can be most appropriately evaluated by methods that depend on the equilibrium assumption. Our work also demonstrates the useful perspective provided by the environmental stasis concept, which enables empirical quantification of one of the key aspects of equilibrium.

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 relatedness in sharks is challenging due to uncertainty in distributions, low population densities and difficulties in sampling across life stages. In Fiji, bull sharks (Carcharhinus leucas), with an effective population size estimate of [~]258, aggregate at the Shark Reef Marine Reserve (SRMR), but gravid females disperse at the end of the year to give birth in adjacent rivers. Questions remain regarding reproductive connectivity, female returns across years, and kinship structure. Using population genomics on 296 bull sharks across age classes (neonates, young-of-the-year, juveniles, and adults) collected over a decade at the SRMR and in three adjacent rivers, we assessed familial connections. Direct genetic links, including first- and second-degree relationships, connected SRMR adults with young age classes in the Navua and Rewa rivers, providing evidence of reproductive connectivity. Within rivers, genetic similarities across cohorts revealed reproductive philopatry. Remarkably, several individuals sampled years apart were assigned to the same sire-dam pairs, indicating repeated pairings across breeding seasons. However, the few related links detected between the SRMR and the rivers may reflect incomplete sampling. Altogether, bull shark reproduction in Fiji seems influenced by reproductive philopatry and repeated pairings, suggesting added complexity in their reproductive behaviour.

Community science data are increasingly recognized as important resources for biodiversity research, in part because of the spatial and temporal resolution that they afford. While these data are useful for applications such as describing occurrence patterns, tracking movement of migratory animals, and recording phenological events, they can also be probed for "second-order" purposes, such as documenting species interactions. Here, I present a dataset of more than 35,000 annotated interactions between monarch butterfly (Danaus plexippus) larvae and their associated host plants from the community science platform iNaturalist. I document more than 70 unique species of milkweed hosts (Apocynaceae: Asclepiadoideae) used by monarch larvae, including a number of previously undocumented interactions. Monarchs show strong seasonal turnover in the species of host plants used across the migratory cycle, highlighting the importance of early season hosts like Asclepias viridis and A. asperula in eastern North America and A. californica and A. cordifolia in the west. I also demonstrate that non-native horticultural milkweed species have increased the spatial extent of monarch breeding during winter (November - February) by more than 60%, a pattern previously suggested from observational data but not formally quantified until now. To my knowledge, this represents the largest analysis to date of species interactions using unstructured community science data and highlights the value of platforms like iNaturalist for conducting fundamental research in ecology and conservation.

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.

Understanding how climate shapes intraspecific genetic turnover is critical for predicting biodiversity responses to global change, yet such analyses remain limited for systems where natural adaptation and human-mediated dispersal jointly structure diversity. Here, we investigate the spatio-temporal dynamics of genetic composition in the western honey bee (Apis mellifera) across Anatolia and Thrace, a major historical refugium harboring five subspecies. Using a dataset of 672 individuals genotyped at 30 microsatellite loci, we characterize population structure and model ancestry compositions as a function of environmental and geographic variables. We integrate Gradient Forests and Generalized Dissimilarity Modelling to identify key climatic drivers of intra-specific turnover and project future changes under multiple CMIP6 climate scenarios. We detect five major ancestral groups with widespread admixture structured by both spatial processes and environmental gradients. While geographic distance explains a substantial proportion of variation, climatic variables account for a large fraction of ancestry turnover. Spatial projections reveal distinct ecological regions corresponding to subspecies distributions, with high turnover zones aligned with major geographic and ecological barriers. Climate projections indicate substantial restructuring of ancestry compositions over the 21st century. Most ancestral groups show declines in persistence and resilience, whereas lineages associated with warmer and drier conditions expand under future scenarios. Regions of high uniqueness and refugia contract, while areas experiencing rapid turnover and novel ancestry compositions increase. Existing Genetic Conservation Areas provide incomplete representation of diversity and are projected to lose effectiveness under future climates. Our results demonstrate that climate change is likely to disrupt spatial genetic structure, promote admixture, and threaten persistence and resilience of honey bee populations. By modeling ancestry composition as a multidimensional proxy for genetic variation, for the first time to our knowledge, this study provides a scalable framework for forecasting intraspecific biodiversity dynamics and informing conservation and management strategies under global change.