Diversity and Distributions

AimSpecies distribution models (SDMs) are an important tool for predicting species occurrences in geographic space and for understanding the drivers of these occurrences. An effect of environmental variable selection on SDM outcomes has been noted, but how the treatment of variables influences models, including model performance and predicted range area, remains largely unclear. For example, although landcover variables included in SDMs in the form of proportions, or relative cover, recent findings suggest that for species associated with uncommon habitats the simple presence or absence of a landcover feature is most informative. Here we investigate the generality of this hypothesis and determine which representation of environmental features produces the best-performing models and how this affects range area estimates. Finally, we document how outcomes are modulated by spatial grain size, which is known to influence model performance and estimated range area. LocationNorth America MethodsWe fit species distribution models (via Random Forest) for 57 water bird species using proportional and binary estimates of water cover in a grid cell using occurrence data from the eBird citizen science initiative. We evaluated four different thresholds of feature prevalence (land cover representations) within the cell (1%, 10%, 20% or 50%) and fit models across both breeding and non-breeding seasons and multiple grain sizes (1, 5, 10, and 50 km cell lengths). ResultsModel performance was not significantly affected by the type of land cover representation. However, when the models were fitted using binary variables, the model-assessed importance of water bodies significantly decreased, especially at coarse grain sizes. In this binary variable-case, models relied more on other land cover variables, and over-or under-predicted the species range by 5-30%. In some cases, differences up to 70% in predicted species ranges were observed. Main conclusionsMethods for summarizing landcover features are often an afterthought in species distribution modelling. Inaccurate range areas resulting from treatment of landcover features as binary or proportional could lead to the prioritization of conservation efforts in areas where the species do not occur or cause the importance of crucial habitats to be missed. Importantly, our results suggest that at finer grain sizes, binary variables might be more useful for accurately measuring species distributions. For studies using relatively coarse grain sizes, we recommend fitting models with proportional land cover variables.

AimDetecting and describing temporal changes in biological communities is fundamental to biodiversity research and applied ecology. Species richness remains a widespread metric in long-term monitoring, yet it obscures underlying processes since changes in species richness are often only the result of turnover, homogenisation and/or shifts in relative abundances. Furthermore, biodiversity trends and their drivers can vary across spatial scales, demanding spatially explicit approaches. This study aims at unravelling how changes in community structure shape trends in richness across spatial scales, offering a more mechanistic view on biodiversity trend detection. LocationEurope Time period1975 - 2023 Major taxa studiedBirds MethodsWe first assessed trends in breeding bird richness on local (site-level) and national scale for 25 European countries or sub-divisions using linear models. Next, we applied the multi-scale Measures of Biodiversity (MoB) framework in a temporal context to decompose changes in species richness into contributions from individual density, species-abundance distribution, and con-specific spatial aggregation. We then quantify how these components drive species richness from local plots to national extents. Analyses were further conducted separately for farmland and forest guilds, as well as across ecoregions. ResultsThree general patterns emerged beyond variation among countries and functional guilds: Aggregation dominates local richness dynamics, evenness governs broad-scale trends, and density plays an intermediate role. Findings of distinct local and national trends in bird richness agree with previous findings, albeit we find more heterogeneous average trends among countries on local scales. Distinct trends and components patterns vary among ecoregions within countries, highlighting the need for sub-national analyses. Main conclusionsThis scale-explicit, component-based approach reveals how changes in community structure shape trends in species richness from local to national scales. Such mechanistic insights of biodiversity change might enable more precisely targeted conservation strategies and identification of external drivers.

AimSpatial autocorrelation (SAC), also known as aggregation, is a notable property of species distributions and diversity; it reflects species niche and dispersal, has conservation significance, and affects ecological models. Yet, we know little about spatial and temporal patterns of SAC in empirical data. Here, we assess SAC in both observed species distributions and species richness, quantifying its magnitude and prevalence over large extents and across spatial resolutions. We also assess its dynamics over the past 50 years. LocationCzechia, Europe, New York State, Japan Time period1972 - 2017 Major taxa studiedBirds MethodsWe analyzed four temporally replicated gridded bird atlases, each aggregated to multiple grain sizes. To measure SAC in species distributions, we used the Join count statistic (JC) and its deviation from the expectation under a random distribution. We assessed temporal changes in JC and their relationship with changes in occupancy, given their close association. We used Morans I to measure SAC in species richness. ResultsBoth species distributions and diversity were positively autocorrelated across all regions, periods, and grains, and the magnitude of autocorrelation mostly decreased with increasing grain. We found that the temporal change of JC varied across species and regions, with zero average trends in Morans I, JC, and occupancy. However, when JC and occupancy were considered jointly, we found systematic temporal shifts: contracting species became more aggregated (compact) while expanding species became more fragmented (disjoint). Main conclusionsStronger SAC at finer grains suggests greater predictability of diversity and distributions at these scales. Despite zero average change in occupancy or SAC, their coupled shifts highlight the importance of considering both jointly. We found long-distance dispersal (rather than advancing edge) and vulnerability of isolated populations to extinction as the major drivers of range dynamics in temperate birds.

Conservation strategies and biodiversity assessments have long prioritized taxonomic metrics such as species richness and endemism, often neglecting intraspecific genetic diversity, a key driver of population adaptability and long-term resilience. Here, we present a scalable framework for quantifying and mapping multi-species genetic diversity using publicly available DNA sequence data. By calculating nucleotide diversity ({pi}) across taxa and aggregating values spatially, we define the Genetic Diversity Index (GDI): a site-level metric capturing geographic patterns of intraspecific genetic variation. Using simulations under different scenarios, we assessed the robustness of the GDI and implemented three corrective measures to address sampling bias and the additive effects of species richness. We queried over 25 million accessions from public databases representing 9,409 European vascular plant species and applied this approach to [~]630,000 georeferenced sequences across 1,860 species. Our results reveal distinct genetic diversity hotspots in the Anatolian Peninsula, Southern Iberia, and Eastern Alps regions corresponding to historical glacial refugia and ecological transition zones. GDI values were largely uncorrelated with species richness or phylogenetic diversity, confirming that the index captures a unique and independent dimension of biodiversity. Our indices performed extremely well and showed that fewer than 1% of studied sites exhibited a significant effect of sampling bias, validating the methods reliability under uneven data coverage. By integrating genetic diversity into spatial biodiversity analyses, the GDI detects large-scale patterns of evolutionary significance and fills a critical methodological gap, providing a reproducible tool to support conservation prioritization and policy at regional and global scales. SignificanceGenetic diversity is a fundamental component of biodiversity and critical to species resilience, yet it remains absent from most biodiversity assessments. We present a scalable framework for evaluating multi-species genetic diversity across landscapes, introducing three complementary Genetic Diversity Indices (GDI) designed for different scenarios in biodiversity assessment and conservation planning. Applying this approach to European vascular plants, we reveal that genetic diversity patterns are largely decoupled from taxonomic and phylogenetic diversity, highlighting a fundamental yet overlooked dimension of biodiversity. Our framework charts a clear path for global assessments of genetic diversity in vascular plants and beyond. Incorporating GDI into conservation strategies is critical to complement traditional metrics and better safeguard evolutionary potential of biodiversity in a rapidly changing world.

AimPeripheral regions of the Alps are often overlooked in molecular studies, yet they may play a major role in shaping the current distribution of species and genetic lineages. LocationEurope TaxonAngiosperms (Primulaceae: Primula) MethodsBy focusing on the bears ear (Primula auricula) complex as model species, we used genetic inferences for population genetic structure and performed genetic reconstructions, species delimitations and divergence time estimates in order to get a detailed view of its molecular evolution and current genetic structuring across the Alps sensu lato. ResultsThe Lombardian Alps and the southern eastern Alps are genetically distinct in the vicinity of the Adige valley. The northern and western Alps and their peripheries constitute a third clade and are separated by the siliceous central Alps. Within the latter, an additional cluster made of singular populations from the Devoluy and Vercors regions is retrieved, likely reflecting a strong founder effect rather than an ancient divergence. Main conclusionsThe biogeographic history P. auricula sensu lato pinpoints the importance of the peripheral regions in a phylogeographic context. Populations from northern peripheral regions exhibit long-lasting isolation and in situ survival during glaciations, followed by recolonization into the central Alpine massif.

ContextGenetic diversity is essential for the persistence and future adaptation of species. However, human-driven habitat fragmentation results in population isolation, often leading to rapid loss of genetic diversity and adaptive capacity. Genetic management of focal taxa may be overlooked in many threatened species conservation programs. The Endangered southeastern Australian mallee emu-wren Stipiturus mallee is a species that may benefit from genetic management. Its current range encompasses patchily distributed sub-populations, prone to bottlenecks and genetic drift. Thus, the reintroduction to areas from which the species has been locally extirpated requires careful selection of founders to maximise genetic diversity. AimsWe analyse reduced-representation genomic data from seven sampling areas across the global meta-population to design a translocation strategy that maximises heterozygosity and retention of mallee emu-wren allelic diversity. MethodsWe estimated genetic structure, genetic diversity within, and differentiation between subpopulations, thus testing previous inference based on 12 length-variable loci of low population differentiation with 10,840 genome-wide SNP loci. We also estimated effective population sizes to identify populations in need of genetic augmentation, Finally, we used metapop2 simulations to estimate the relative contributions of each population to global genetic diversity of the species and to estimate the source and number of founders that would maximise heterozygosity and allelic richness in a hypothetical newly established population. Key resultsWe found weak genetic structure across all sampling areas, supporting previous conclusions that the global mallee emu-wren population should be considered a single genetic unit for management purposes. Low but significant Weir and Cockerham pairwise FST among locations indicated differentiation between sampling areas, suggesting that contemporary gene flow is restricted. Effective population sizes for the two regions supporting the largest numbers of mallee emu-wrens were below the threshold associated with reduced adaptive potential. ConclusionsThe genetic health and adaptive potential of sampled mallee emu-wren sub-populations are at risk. Implications The global mallee emu-wren meta-population would likely benefit from genetic augmentation, including reciprocal gene flow between extant sub-populations. To maximise genetic diversity in newly established populations, managers should prioritise gene-pool mixing with founders sourced from all sampled areas.

Many range-restricted taxa are currently experiencing population declines yet lack fundamental information regarding distribution and population size. Establishing baseline estimates for both these key biological parameters is however critical for directing conservation planning for at-risk range-restricted species. The International Union for the Conservation of Nature (IUCN) Red List uses three range metrics that define species distributions and inform extinction risk assessments: extent of occurrence (EOO), area of occupancy (AOO) and area of habitat (AOH). However, calculating all three metrics using standard IUCN approaches relies on a geographically representative sample of locations, which for rare species is often spatially biased. Here, we apply model-based interpolation using Species Distribution Models (SDMs), correlating occurrences with remote-sensing covariates, to calculate IUCN range metrics, protected area coverage and a global population estimate for the Critically Endangered Philippine Eagle (Pithecophaga jefferyi). Our final range wide continuous SDM had high predictive accuracy (Continuous Boyce Index = 0.927) and when converted to a binary model estimated an AOH = 23,185 km2, a maximum EOO = 605,759 km2, a minimum EOO = 272,272 km2, with an AOO = 53,867 km2. Based on inferred habitat from the AOH metric, we estimate a global population of 318 breeding pairs (range: 258-362 pairs), or 636 mature individuals, across the Philippine Eagle global range. Protected areas covered 34 % of AOH, 15 % less than the target representation, with the continuous model identifying key habitat as priority conservation areas. We demonstrate that even when occurrences are geographically biased, robust habitat models can be built that enable quantification of baseline IUCN range metrics, protected area coverage, and a population size estimate. In the absence of adequate location data for many rare and threatened taxa, our method is a promising spatial modelling tool with widespread applications, in particular for island endemics facing high extinction risk.

A number of "shortcuts" for assessing biodiversity and prioritizing conservation action have been proposed, one of which is to focus on a subset of the most common species. I critically evaluated the claim that common species better explain patterns of species richness than rare species, using bird data from the same spatial extent at two markedly different spatial resolutions and a third dataset for a larger spatial extent. I did find situations where common species convey more information about species richness patterns than rare species, such as in sequential correlations of species sets with total species richness. However, "hotspots" of species richness tended to be most associated with species occurring with intermediate frequency, rather than the most common (or most rare) species. Furthermore, differences in the degree and sequence of rarity across the three datasets meant that conclusions drawn from species in one dataset did not necessarily hold in the others. Overall, therefore, I found little evidence that common species alone could provide a satisfactory shortcut to understanding biodiversity, particularly given that rare species are often facing the greatest risk of extirpation or extinction. Drawing upon citizen scientists to aid in monitoring and ensuring that unusual or unique ecosystem types and configurations are surveyed may be invaluable in obtaining the thorough understanding of biodiversity needed for successful conservation outcomes.

AimSpecies distribution modelling can be used to reveal if the ecology of a species varies across its range, to investigate if range expansions entailed niche shifts, and to help assess ecological differentiation: the answers to such questions are vital for effective conservation. The leopard (Panthera pardus spp.) is a generalist species composed of one African and eight Asian subspecies, reflecting dispersal from an ancestral African range. This study uses species distribution models to compare the niches of leopard subspecies, to investigate if they conserved their niches when moving into new territories or adapted to local conditions and shifted niche. LocationAfrica and Eurasia MethodsWe assembled a database of P. pardus spp. presences. We then associated them with bioclimatic variables to identify which are relevant in predicting the distribution of the leopard. We then constructed a species distribution model and compared the distribution predicted from models based on presences from all subspecies versus the ones built only using African leopards. Finally, we used multivariate analysis to visualise the niche occupied by each subspecies in the climate space, and to compare niche overlaps to assess ecological differentiation. ResultsNiche comparisons and model predictions suggest a general lack of niche separation between all subspecies. Most Asian subspecies have overlapping niches and occupy subsets of the niche of the African leopard. Nevertheless, we found the Persian leopard Panthera pardus saxicolor to have the most distinct niche, giving some evidence for niche expansion in more Northern Asian subspecies. Main conclusionsThese results suggest little ecological differentiation among leopard subspecies and a lack of adaptation to novel climates after dispersal from Africa. This finding complements recent genetic studies in implying that the taxonomy of Asian leopards may not reflect biological differentiation, an issue that is important to resolve due to its relevance for the conservation of the species.

AIMSpecies invasions are a major driver of global biodiversity loss, but only a minority of invasions are successful. Evidence suggests that invasive success is linked to life-history traits. Yet, data on invasive success and species traits remain fragmented across multiple sources. Here we present the Invasive Traits of Freshwater Fish (ITOFF) database, an interdisciplinary framework that integrates multiple datasets to elucidate the role of life-history traits in shaping invasive success. ITOFF allows seamless access to invasive species data and fosters collaborative actions through knowledge sharing. ITOFF is supported by an innovative web-application that makes complex relationships between invasive and native species accessible to a broad audience. The scientific contribution of ITOFF is illustrated by examining the role of life-history traits and phylogeny in invasion success. LOCATIONGlobal. METHODSGeneralized linear models were used to test the contribution of generation time, trophic level, longevity, and temperature range to invasive success. Through divisive cluster analysis we investigate the role of multiple traits in determining invasive success. Finally, we construct phylogenetic trees to investigate the role of evolutionary history in the invasion process. RESULTSITOFF unifies data for 1917 freshwater fish species representative of invasive species, those species they endanger, and species impacted by invasives but not considered endangered. Invasive species are generally characterized by greater temperature ranges, but are indistinguishable from impacted, endangered, and critically endangered species for the remaining life-history traits. Further, we show that invasive species are generally not distinct from impacted or endangered species when considering multiple traits or phylogeny. MAIN CONCLUSIONSITOFF provides an accessible platform for the improved forecasting of species invasions. ITOFF data shows that classical predictions of life-history traits determining invasive success do not hold amongst freshwater fish species. Forecasting of invasive species must therefore shift towards a wholistic approach encompassing the species and the environment.

Prioritizing regions for conservation is essential for effectively allocating limited conservation resources. One of the most common approaches to prioritization is identifying regions with the highest biodiversity, or hotspots, typically using global range map data. Range maps are readily available at large scales for an array of taxa, but are also known to differ from local-scale survey data in the same regions. We examined how prioritizations may differ between range map and survey data using the North American Breeding Bird survey (BBS) and BirdLife International range maps as a case study. Hotspot prioritizations were generated for species richness and the richness of rare species at two scales.\n\nTotal species richness patterns differed substantially between data types with at most a 41% overlap in identified hotspots. Some regions had few or no hotspots for one data type and a significant number for the other. Hotspots for rare species were more similar across the data types with 44% overlap at the larger scale. Future efforts to prioritize areas for conservation should consider differences between local-scale survey data and range maps, match data to the scale of interest, and develop methods to better downscale range map-based prioritizations to the scale of conservation decisions.

O_LIMany conservation interventions prove ineffective because they lack a rigorous evidence-base. Multifactorial drivers and data limitations often hinder anticipatory planning and are difficult to tackle with standard methods. Predictive modelling approaches that integrate diverse data sources with biological hypotheses can bridge this gap by clarifying the drivers of decline and evaluating management options under uncertainty. C_LIO_LI We developed a Bayesian integrated population model (IPM) applicable to lekking species, combining incomplete data from different life stages and seasons while accounting for observation error. IPMs are widely recognised for reducing bias relative to single-data-stream analyses, yet their application in conservation planning remains limited. C_LIO_LIWe applied the model to the threatened Western Capercaillie population in Scotland, which has been declining since at least the 1980s despite decades of conservation efforts, a typical case requiring urgent, evidence-based management. By fitting the model to 30 years of biased and incomplete monitoring data, we investigated associations between demographic processes and their potential drivers, including weather variables, fence collision mortality and a proxy of predation pressure. We used model predictions to evaluate the joint effectiveness of proposed management actions aimed at improving vital rates, including fence management and diversionary feeding. C_LIO_LIData integration improved population estimate precision by 17-49% relative to standalone national survey estimates, confirming that the decline continued from 1990-2023. Reproductive rate was related to the pattern of April warming, negatively affected by pre-breeding precipitation and positively by vole abundance, the latter consistent with the alternative prey hypothesis. Model predictions indicated that combining diversionary feeding with fence removal produced the most favourable conservation outcomes, but growth remained limited and uncertainty included possible continued decline. C_LIO_LI5. This modelling approach forms a key component of Scotlands Capercaillie Emergency Plan 2025-2030, guiding management by assessing population-level responses and predicting conservation intervention outcomes. In future, the model could support formal adaptive management through iterative evaluation of interventions as new data become available. Beyond this case study, our integrated approach offers a transferable framework for managing multifactorial declines in other threatened species under uncertainty. C_LI

AimDespite the increasing interest in developing new bioregionalizations and assessing the most widely accepted biogeographic frameworks, no study to date has sought to systematically define a system of small bioregions nested within larger ones that better reflect the distribution and patterns of biodiversity. Here, we examine how an algorithmic, data-driven model of diversity patterns can lead to an ecologically interpretable hierarchy of bioregions. LocationAustralia. Time periodPresent. Major taxa studiedTerrestrial vertebrates and vascular plants. MethodsWe compiled information on the biophysical characteristics and species occupancy of Australias geographic conservation units (bioregions). Then, using cluster analysis to identify groupings of bioregions representing optimal discrete-species areas, we evaluated what a hierarchical bioregionalization system would look like when based empirically on the within-and between-site diversity patterns across taxa. Within an information-analytical framework, we then assessed the degree to which the World Wildlife Funds (WWF) biomes and ecoregions and our suite of discrete-species areas are spatially associated and compared those results among bioregionalization scenarios. ResultsInformation on biodiversity patterns captured was moderate for WWFs biomes (50- 58% for birds beta, and plants alpha and beta diversity, of optimal discrete areas, respectively) and ecoregions (additional 4-25%). Our plants and vertebrate optimal areas retained more information on alpha and beta diversity across taxa, with the two algorithmically derived biogeographic scenarios sharing 86.5% of their within- and between-site diversity information. Notably, discrete-species areas for beta diversity were parsimonious with respect to those for alpha diversity. Main conclusionsNested systems of bioregions must systematically account for the variation of species diversity across taxa if biodiversity research and conservation action are to be most effective across multiple spatial or temporal planning scales. By demonstrating an algorithmic rather than subjective method for defining bioregionalizations using species-diversity concordances, which reliably reflects the distributional patterns of multiple taxa, this work offers a valuable new tool for systematic conservation planning.

Biogeography has a critical influence on how ecological communities respond to threats and how effective conservation interventions are designed. For example, the resilience of ecological communities is linked to environmental and climatic features, and the nature of threats impacting ecosystems also varies geographically. Understanding community-level threat responses may be most accurate at fine spatial scales, however collecting detailed ecological data at such a high resolution would be prohibitively resource intensive. In this study, we aim to find the spatial scale that could best capture variation in community-level threat responses whilst keeping data collection requirements feasible. Using a database of biodiversity records with extensive global coverage, we modelled species richness and total abundance (the responses) across land-use types (reflecting threats), considering three different spatial scales: biomes, biogeographical realms, and regional biomes (the interaction between realm and biome). We then modelled data from three highly sampled biomes separately to ask how responses to threat differ between regional biomes and taxonomic group. We found strong support for regional biomes in explaining variation in species richness and total abundance compared to biomes or realms alone. Our biome case studies demonstrate that there is a high variation in magnitude and direction of threat responses across both regional biomes and taxonomic group, but all groups in tropical forest showed a consistently negative response, whilst many taxon-regional biome groups showed no clear response to threat in temperate forest and tropical grassland. Our results suggest that the taxon-regional biome unit has potential as a reasonable spatial and ecological scale for understanding how ecological communities respond to threats and designing effective conservation interventions to bend the curve on biodiversity loss.

Assessing the extinction risk of species through the IUCN Red List is key to guiding conservation policies and reducing biodiversity loss. This process is resource-demanding, however, and requires a continuous update which becomes increasingly difficult as new species are added to the IUCN Red List. The use of automatic methods, such as comparative analyses to predict species extinction risk, can be an efficient alternative to maintaining up to date assessments. Using amphibians as a study group, we predict which species were more likely to change status, in order to suggest species that should be prioritized for reassessment. We used species traits, environmental variables, and proxies of climate and land-use change as predictors of the IUCN Red List category of species. We produced an ensemble prediction of IUCN Red List categories by combining four different model algorithms: Cumulative Link Models (CLM), phylogenetic Generalized Least Squares (PGLS), Random Forests (RF), Neural Networks (NN). By comparing IUCN Red List categories with the ensemble prediction, and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessments due to high prediction versus observation mismatch. We found that CLM and RF performed better than PGLS and NN, but there was not a clear best algorithm. The most important predicting variables across models were species range size, climate change, and landuse change. We propose ensemble modelling of extinction risk as a promising tool for prioritizing species for reassessment while accounting for inherent models uncertainty.

Dispersal patterns dictate genetic population structure, and ultimately population resilience, through maintaining critical ecological processes and genetic diversity. Direct observation of dispersal events is not often possible, but genetic methods offer an alternative method of indirectly measuring dispersal. Here, we use 7 652 genome-wide single-nucleotide polymorphisms (SNPs) to evaluate genetic population structure and infer dispersal capabilities of the Western Grasswren (Amytornis textilis textilis; WGW) in Western Australia (n = 118), utilising a sister species, the Thick-billed Grasswren (Amytornis modestus; TBGW) as a comparison dataset (n = 80). We found genetic divergence and low genetic diversity between two populations (Hamelin and Peron) in the WGW, despite evidence of long dispersal distances within populations by females. In addition, the two WGW populations were found to be more genetically divergent than two described subspecies of TBGW, despite the WGW occurring over a smaller spatial scale. By comparing these two grasswren species, our data suggest a narrow strip of land may be acting as a geographic barrier in the WGW, limiting dispersal between a peninsula population to the mainland. We investigate if morphology aligns with genetic divergence, with some estimates of divergence between WGW populations greater than those between subspecies of TBGW. However, confidence intervals were large, preventing definitive conclusions. Our results support the hypothesis that peninsula populations of small, ground-dwelling birds are genetically isolated from adjacent mainland populations. Furthermore, there is evidence to suggest that the limited gene flow is asymmetrical, with directional dispersal occurring from the bounded peninsula population to the mainland. Our study also highlights how substantial genetic divergence does not necessarily coincide with phenotypic differences.

AimsSpecies distributions result from both biotic and abiotic interactions across large spatial scales. The interplay of these interactions as climate changes quickly has been understudied, particularly in herbivorous insects. Here, we investigate the relative impacts these influences on the putative northern range expansion of the giant swallowtail butterfly in North America. LocationNorth America. Time period1959-2018. Major taxa studiedEastern Giant swallowtail, Papilio cresphontes (Lepidoptera: Papilionidae); common hop tree, Ptelea trifoliata; common prickly ash, Zanthoxylum americanum; southern prickly ash, Zanthoxylum clava-herculis (Saphidales: Rutaceae). MethodsWe used data from museum collections and citizen science repositories to generate species distribution models. Distribution models were built for each species over two time periods (T1 = 1959-1999; T2 = 2000-2018). ResultsModels for P. cresphontes and associated host plants had high predictive accuracy on spatially-explicit test data (AUC 0.810-0.996). Occurrence data align with model outputs, providing strong evidence for a northward range expansion in the last 19 years (T2) by P. cresphontes. Host plants have shifted in more complex ways, and result in a change in suitable habitat for P. cresphontes in its historic range. P. cresphontes has a northern range which now closely aligns with its most northern host plant - continued expansion northward is unlikely, and historic northern range limits were likely determined by abiotic, not biotic, factors. Main conclusionsBiotic and abiotic factors have driven the rapid northern range expansion in the giant swallowtail butterfly across North America in the last 20 years. A number of bioclimatic variables are correlated with this expansion, notably an increase in mean annual temperature and minimum winter temperature. We predict a slowing of northward range expansion in the next 20-50 years as butterflies are now limited by the range of host plants, rather than abiotic factors.

PREMISEUnderstanding the habitat requirements of imperiled flora is critical for informing ex situ conservation practices, designing effective reintroduction strategies, and understanding how climate change will impact such species, especially in montane regions with high levels of environmental heterogeneity. In southern Appalachia, USA, the Mountain Sweet Pitcher Plant (Sarracenia rubra ssp. jonesii) and Mountain Purple Pitcher Plant (Sarracenia purpurea var. montana) inhabit overlapping ranges. These taxa rarely co-occur in the same mountain bogs but frequently hybridize at sites where they do co-occur. METHODSWe assessed patterns of climatic niche differentiation in these imperiled taxa to explore whether they naturally co-occur or may have been brought into secondary contact through human translocations. In addition, we constructed ecological niche models to evaluate the comparative availability of suitable habitat for each taxon under present and future climates. RESULTSWe 1) find evidence that the two taxa inhabit distinct niches, and 2) predict that current populations of Sarracenia rubra ssp. jonesii will experience climates markedly different from those it currently inhabits in the future, while 3) suitable habitat for S. purpurea var. montana will remain comparatively stable and may expand in its current range. CONCLUSIONSDespite high spatial overlap, these two related taxa exhibit divergent climatic niches, resulting in highly different management needs and conservation approaches. We raise concerns about the future of mountain bog plant assemblages, and the rare species they include, under climate change.

AimTo assess if and how species range size relates to range structure, if the observed geographic range properties can be retrieved from predicted maps based on species distribution modeling, and whether range properties are predictable from biogeophysical factors. LocationEurope Time periodCurrent Major taxa studied813 vascular plant species endemic to Europe MethodsWe quantified the size and spatial structure of species geographic ranges and compared ranges currently occupied with those predicted by species distribution models (SDMs). SDMs were constructed using complete occurrence data from the Atlas Florae Europaeae and climatic, soil and topographic predictors. We used landscape metrics to characterize range size, range division and patch shape structure, and analysed the phylogenetic, geographic and ecological drivers of species range size and structure using phylogenetic generalized least squares (pGLS). ResultsRange structure metrics were mostly decoupled from species range size. We found large differences in range metrics between observed and predicted ranges, in particular for species with intermediate observed range size and occupied area, and species with low and high observed patch size distribution, geographic range filling, patch shape complexity and geographic range fractality. Elevation heterogeneity, proximity to continental coasts, Southerly or Easterly geographic range positions and narrow ecological niche breadth constrained species observed range size and range structure to different extents. The strength and direction of the relationships differed between observed and predicted ranges. Main conclusionsSeveral range structure metrics, in addition to range size, are needed to adequately describe and understand species ranges. Species range structure can be well explained by geophysical factors and species niche width, albeit not consistently for observed and predicted ranges. As range structure can have important ecological and evolutionary consequences, we highlight the need to develop better predictive models of range structure than provided by current SDMs, and we identify the kinds of species for which this is most necessary.

Conserving biodiversity under a changing climate is a complex challenge that requires comprehensive conservation planning approaches accounting for both current biodiversity patterns and the diverse ecological and environmental changes that species and ecosystems are likely to encounter over time. Systematic conservation planning (SCP) offers a strategic framework to meet this challenge by prioritizing areas that promote species persistence and ecological resilience. Traditionally, SCP focuses on conserving adequate amounts of species distributions to ensure their long-term persistence. More recently, partitioning species distributions into bioclimatic components has emerged to explicitly represent niche variability, enhancing adaptive capacity by preserving local adaptations and genetic diversity across environmental gradients. Despite this conceptual progress, empirical comparisons of species-level and bioclimatic component prioritization remain scarce. This study aimed to compare species-level and bioclimatic component prioritization by assessing their trade-offs and effectiveness in supporting species persistence and ecological resilience. Specifically, we aimed to (i) assess the surrogacy between species-level and bioclimatic component prioritizations, (ii) examine their spatial overlap and divergence, and (iii) quantify and compare environmental heterogeneity within priority areas identified by each approach. We found that species-level and bioclimatic component prioritizations act as reasonable surrogates for one another overall, but species-level prioritization tended to underrepresent the least-covered bioclimatic components, with failures to capture certain components in the top-ranked areas. Spatial overlap between the two approaches was generally high, though it declined with more restrictive thresholds and under future conditions. Additionally, bioclimatic component prioritizations consistently captured higher within-group multivariate dispersion in environmental heterogeneity in selected areas. Our findings highlight that bioclimatic component prioritization captures greater environmental heterogeneity and complements species-based approaches by better representing niche diversity. Integrating both strategies may offer a more robust path toward climate-resilient conservation planning that accounts for ecological requirements and environmental variation.