Ecography

Reliable models of species niches and distributions depend on accurately matching occurrences to environments via spatial and temporal coordinates. For fossil occurrences, time-averaging and age uncertainty can create mismatches between fossils and their associated environments, distorting inferred niches and distributions. Using a virtual ecology approach, we assessed how temporal uncertainty ({+/-}200 years to the full late Quaternary) influences niche and distribution estimates for four virtual species centered on three periods: Holocene (6,000 y.b.p), deglacial (13,500 y.b.p.), and Last Glacial Maximum (18,000 k.y.b.p.). We compared uncertain estimates, derived by matching occurrences with environmental layers drawn from different times within each uncertainty window, against true niches and distributions. We found that during environmentally stable intervals, niches and distributions were robust to temporal uncertainty until it reached {+/-}2500 years. Higher environmental variability reduced accuracy, with the greatest mismatch occurring during the deglacial. These results demonstrate both the promise and limitations of paleodistribution reconstruction.

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.

Theory suggests that different components of environmental fluctuations, from daily and seasonal cycles to multidecadal trends, can have distinct and even opposing effects on species abundances and community dynamics, depending on their specific adaptations. But empirical research that deconstructs the influence of these different cycles on communities is lacking. Here, we used long-term biological monitoring data together with flow records of rivers across New Zealand to (i) investigate the role of fast, slow, and seasonal river-flow fluctuations in structuring macroinvertebrate communities; and (ii) to assess whether life-history and mobility traits mediate the response. Using joint species distribution models, we found striking differences in taxon and community responses to the different components of river flow variation. Responses to slow fluctuations were generally stronger and better predicted by traits, while responses to seasonal fluctuations were highly heterogeneous. Fast increases in flow, typical of flooding events, had pervasive negative effects on species abundances, but the severity of impact partly depended on mobility traits. Our results suggest that different ecological mechanisms underpin the response to distinct environmental fluctuations, highlighting the value of jointly considering multiple temporal scales of variation and species functional traits to understand and predict how communities reorganise under fluctuating environmental regimes.

Urbanization and human-induced environmental changes create unique and unprecedented thermal landscapes, yet the extent to which species respond to these changes remains poorly understood. One major challenge in studying these responses is the spatial mismatch between the small scale at which organisms experience their environment and the broader scale at which climate data are typically collected. We use Infrared Thermography (IRT) to quantify the fine scale microclimate in urban and rural habitats used by two tropical agamid lizards, Calotes versicolor and Psammophilus dorsalis. By combining field-based body temperatures and lab-based measures of thermal limits (CTmax, CTmin)and preferences (Tpref), we assess how the thermal heterogeneity of these fine mosaics of microhabitats influence the degree of thermoregulation (k) of these species. We find that thermal responses to urbanization are shaped by species-specific thermal traits and patterns of microhabitat use. Between the species, urban individuals did not differ markedly in habitat thermal heterogeneity, substrate temperature used or degree of thermoconformity. However, within species, P. dorsalis experiences warmer and more heterogeneous conditions in rural habitats, whereas C. versicolor experiences similar thermal conditions across habitats. Calotes versicolor also exhibits broader thermal tolerance and preferred temperature ranges than P. dorsalis. Collectively, our results suggest that P. dorsalis may be more susceptible to the thermal constraints imposed by human-modified landscapes. Overall, we demonstrate the critical need to account for microclimatic conditions and species-specific thermal traits when determining how animals respond to changes in the thermal environment expected from climate change.

Paleobiologists commonly use genera as a proxy for species in biodiversity studies. However, a lingering concern is that patterns among genera might not always faithfully reflect patterns among species. To date, the concern has focused chiefly on measured patterns of richness over time and on implied origination and extinction rates. However, similar issues might arise for studies of morphological disparity. Moreover, there potentially are additional implications of disparity patterns among species versus those among genera concerning the range of observable anatomical characters and whether disparity within genera is comparable to disparity among genera. If clades have some relatively slowly changing characters that workers have used to denote different genera, then we would expect to see congeneric species to cluster in morphospace; however, if such characters are rare, then within-genus disparity might approach among-genus disparity. Here, we use genus-level and species-level disparity patterns among acanthoceratid ammonoids from the Late Cretaceous. In particular, we examine whether these different level imply different evolutionary dynamics over a major ecological event (Ocean Anoxic Event 2) and how disparity within genera (i.e., among congeneric species) compares to disparity among genera. We find genus-level disparity somewhat inflates early acanthoceratid disparity but implies similar patterns over the OAE2. We also find that within-genus disparity is slightly lower than among-genus, but not hugely so. The combined results suggest that acanthoceratoid shell anatomy does not really show "genus" level characters, even if congeneric species do tend to be more similar to each other than to species in other genera. Thus, this might provide more of a warning for other types of studies using anatomical data (e.g., phylogenetic studies) than for disparity studies. Non-technical SummaryMany paleobiologists use genera to examine scientific questions. This leads to questions over whether this broader approach misses important species-level patterns. This study uses acanthoceratid ammonoids from the Late Cretaceous to examine disparity patterns at both the genus-level and the species-level. We specifically examine the disparity at both levels of this group over a time of high stress for this group, Ocean Anoxic Event 2 (OAE2). Our results show that genus-level disparity slightly exaggerates early acanthoceratid disparity but lowers to a similar pattern to the species-level disparity during OAE2. Within-genus disparity is shown to be slightly lower than among-genus, but not enough to be startling. Together, these results indicate that while some species within the same genus tend to be more alike to each other than those in other genera, there isnt a set of true "genus" level characters. This outcome leads to a warning against using anatomical data in phylogenetic studies, but less so for disparity studies.

O_LIUnderstanding functional community structure and the niche-based mechanisms that enable coexistence among sympatric species is essential for explaining how biodiversity is maintained in natural systems, and for anticipating how ecological communities will respond to ongoing environmental change. Stable isotope analysis provides a process-oriented perspective on resource use by integrating information across time and space, thereby allowing reconstruction of realised isotopic niches that reflect multiple dimensions of ecological differentiation. C_LIO_LIWe applied this framework to a community of ungulates in the Central-Eastern Italian Alps, including red deer (Cervus elaphus), roe deer (Capreolus capreolus), and Alpine chamois (Rupicapra rupicapra). Using stable isotope ratios in summer-grown hair segments ({delta}13C, {delta}15N, {delta}34S, {delta}18O, {delta}2H), we quantified species-specific n-dimensional niche hypervolumes within a Bayesian framework and estimated niche regions, overlap probabilities, univariate differentiation and multivariate structure. C_LIO_LIDespite broad dietary overlap typically observed among these ungulates, we found clear isotopic niche segregation, with mean pairwise overlap consistently remaining below 40%. Three dimensions emerged as primary drivers of differentiation: water sourcing ({delta}18O), diet quality ({delta}15N), and habitat openness ({delta}13C). Specifically, chamois appeared to derive more water from plants in their diet rather than from drinking, and to consume a higher-quality diet compared to Cervids. Red deer relied more heavily on forested habitats for resource use compared to roe deer and chamois, and additional isotopic differences between red deer and roe deer may stem from fine-scale abiotic conditions like microclimate and topography. We found no isotopic evidence for differential niche breadth among the three ungulate species. C_LIO_LITogether, these patterns highlight functional differentiation across multiple ecological axes, offering mechanistic insight into how these ungulates segregate realised niche space despite substantial potential for resource overlap. This multi-element isotope perspective underscores the value of integrative, process-based approaches for understanding current coexistence as well as improving predictions of how mammal communities may reorganise under accelerating environmental change. C_LI

Enhanced AbstractO_ST_ABSBackgroundC_ST_ABSThere is overwhelming evidence that global change is having widespread, detrimental impacts on biodiversity. Population declines and local disappearances have been recorded with increasing frequency across all taxa, resulting in a steady rise in the number of threatened species. However, the number of documented extinctions remains counterintuitively low ([~] 1000 species across all kingdoms) compared to the sense of emergency pervading the scientific community. In isolation, that figure might fuel scepticism about the biodiversity crisis, but when put into context, it reveals that current extinction rates might be comparable to those that occurred during past mass extinction events estimated from the fossil record ([&ge;] 75% extinctions within < 2 million years). Although this is an important clue supporting the claim that we might now be witnessing a new ( sixth) mass extinction, it falls short of definitive proof. The claim bears such high importance that it requires exceptionally solid foundations. However, our main aim was not to ascertain whether current extinction rates qualify as a new mass extinction event in progress. Instead, we examined the intersection of potential future loss scenarios and species discovery rates to address the fundamental question of whether and when we will be able to confirm a mass extinction is under way. AdvancesOur extrapolations suggest that the timing for a mass extinction to materialise (2,604-34,808 years from now at 75% diversity loss) is consistent with past mass extinctions (e.g., 12,000-108,000 years estimated for the Permian-Triassic extinction to unfold) under modern extinction rates (loss of 0.004%-0.053% of global species richness per year). We identify the minimum necessary conditions in which we could confirm a mass extinction under the full range of assumptions related to total species diversity (ranging from < 1.8 million to 163.2 million animal species) and discovery rates (e.g., [~] 13,110 new animal species described per year as of 2026, with the number growing by [~]77 species per year), and the associated timeframe required. We show that there are many realistic future scenarios where we would fail to detect a mass extinction in progress. OutlookBased on available evidence, the rate of global biodiversity loss might already be consistent with the standard definition of a mass extinction. But even if true, current extinction rate estimates (20-8343 times background rates) would not necessarily imply a mass extinction is currently unfolding, because this claim can only be verified a posteriori. Our projections instead indicate that there is a high risk of not recognising a mass extinction as it unfolds -- 49% across all parametrisations we explored. Furthermore, the temporal scale required for a mass extinction to materialise is orders of magnitude longer than relevant policy and legislative horizons, a mismatch that might appear to absolve todays society of responsibility. In reality, the opposite is true -- underestimating the likelihood of already being on a trajectory toward a mass extinction could have catastrophic consequences for future generations and historical accountability. Future generations will be forced to confront a world they perceive as normal, unaware of how much better off humanity could have been.

Spatial and spatiotemporal models are increasingly critical for understanding species distributions, tracking population change, and informing conservation decisions. As biological processes are influenced by increasing external pressures, including human disturbance or environmental change, accurate model predictions become essential for adaptive management. However, the reliability of spatial predictions depends on often-overlooked modelling choices, including the spatial resolution used to approximate underlying processes. Using long term monitoring data from a large-scale groundfish survey in the California Current ecosystem, we investigated how spatial model complexity affects the quality of ecological predictions and derived indices used for management. We fit spatial and spatiotemporal models of ocean temperature and fish biomass density for 27 commercially important species using varying levels of spatial resolution. We evaluated both in-sample and out-of-sample prediction, and effects on area-weighted biomass indices. Counter to common assumptions, increasing spatial approximation resolution did not universally improve predictions. Our case studies demonstrate that for many datasets, out-of-sample prediction quality peaked at intermediate spatial resolutions and declined at the finest scales. Through simulation testing, we found this pattern was strongest when spatial patterning had a small range and high spatial variance, and observation error was low. For most species, spatial resolution had a minimal effect on biomass trend estimates used in management, but for several commercially important rockfish species, resolution choices substantially affected both the scale and uncertainty of population indices. Our findings demonstrate that spatial model specification can substantially affect ecological inference, with direct implications for management and conservation planning. We provide practical guidance for ecologists on selecting appropriate spatial complexity through cross-validation. When out-of-sample prediction is a focus, appropriate approximation complexity should improve both parameter estimation accuracy and derived quantities.

Fuel availability and fuel dryness are consistently shown to be the primary drivers of wildfire intensity and burnt area. Here we hypothesise that differences in the timing of fuel build up and drying determine the optimal time for wildfire occurrence. We use gross primary production (GPP) as a measure of biomass production and hence fuel availability, and vapour pressure deficit (VPD) as a measure of fuel drying. We use the phase difference in the seasonal time course and magnitude of GPP and VPD to cluster regions that should therefore have distinct wildfire behaviour. We then show that each of the resultant clusters is distinctive in terms of one or more fire properties, specifically number of ignitions, burnt area, size, speed, duration, intensity, and length of the wildfire season. The emergence of distinct regimes as a function of two biophysical drivers reflects the fact that both vegetation and wildfire properties are a consequence of eco-evolutionary adaptions to environmental conditions. We then examine the degree to which human activities or vegetation properties modify these fire regimes within each of these clusters. Variability in GPP and VPD largely explains the within-cluster variation in fire properties. The type of vegetation cover has an influence on burnt area and carbon emissions in particular, while human activities are more important for fire properties such as size, rate of spread and duration largely through their influence of landscape fragmentation. Although both human activities and vegetation properties modify wildfire regimes, the ability to distinguish wildfire regimes using GPP and VPD alone emphasizes that land management, fire use and fire suppression are constrained by environmental conditions. This eco-evolutionary optimality approach to characterising wildfire regimes provides a basis for designing a simple fire model for Earth System modelling.

Mediterranean Basin, one of the most important hot spots for reptiles, is also expected to experience significant impacts with climate change, posing a severe risk for the herpetofauna of the region. This study uses the snake-eyed lizard Ophisops elegans as a model organism to investigate the potential impacts of past and future climate change on reptile distributions in the region. An ecological niche model (ENM) was developed with the Maxent algorithm, with location points from GBIF and bioclimatic variables from the CHELSA dataset, then projected onto past LGM ([~]21 kya) and future (2071-2100 SSP3-7.0 and SSP5-8.5) scenarios. Results show that the present-day distribution of O. elegans is primarily driven by temperature seasonality and precipitation, indicating a preference for coastal Mediterranean climates with dry summers. The LGM projection suggests a fragmented and contracted range, confined to coastal refugia around the Mediterranean and Caspian Seas. Future projections for 2071-2100 show consistent and alarming contraction of suitable habitats under both SSP scenarios. In conclusion these findings indicate that O. elegans is vulnerable to significant habitat loss under projected climate change. This severe impact on a wide-spread species implies that the herpetofauna of the Mediterranean Basin may face a significant threat in future.

AimHuman land-use has dramatically altered the amount, quality, and connectivity of habitat for species worldwide. Understanding how these changes affect individual species is essential for predicting the overall consequences of land-use change for biodiversity. LocationThe Caribbean island of Puerto Rico. Forest cover on the island increased from about 18 to 45% from the late 1940s to the early 2000s. MethodsUsing data on geographic distributions and functional traits for 454 tree species, we evaluated how gain of potential habitat was related to species-specific climatic associations and life-history strategies. We estimated species-specific potential habitat (climatically suitable and forested) with species distribution models and data on forest cover. We characterized each species niche breadth (the range of environmental conditions it occupies) and niche position (the environmental conditions it prefers) to compare with the conditions in reforested areas. ResultsSpecies with relatively more potential habitat in 1951 (climatically suitable and forested) also had relatively larger gains in potential habitat from 1951 to 2000. Species that tend to occupy conditions different from those common in reforested areas (i.e., more marginal habitats) gained relatively less potential habitat and species with broad environmental niches gained more potential habitat. Additionally, species with relatively acquisitive functional traits gained more suitable habitat than those with relatively conservative traits. Main conclusionsOur results show that Puerto Ricos reforestation preferentially increased habitat for species that (1) already had suitable habitat in the landscape, (2) tolerate a wide range of climatic conditions, and (3) exhibit fast, acquisitive functional strategies. These findings illustrate how land-use change in heterogeneous tropical landscapes can generate non-uniform habitat gains across species, potentially favoring generalist over specialist species and reshaping community composition.

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

Climate change can affect salmon and steelhead (Oncorhynchus spp.) throughout their anadromous life cycles, yet there have been no assessments of which Canadian populations face the greatest exposure. We developed a framework to quantify relative climate change exposure of salmon and steelhead populations based on the spatial and temporal distribution of different life stages. Exposure was calculated from climate model projections for freshwater and marine climate variables considering unique impact thresholds for each population and life stage. We applied this framework to 60 Conservation Units of Pacific salmon and steelhead in the Fraser River basin, British Columbia. Lake-type sockeye had the highest exposure, driven by elevated stream temperatures during adult freshwater migration and spawning stages and relatively low thermal tolerance of marine stages. Chinook salmon were the next most exposed, while coho, pink, and chum salmon had relatively low exposure. Uniquely, steelhead exposure was driven by high stream temperatures during incubation. Our framework is broadly applicable, and our findings provide critical input for climate change vulnerability assessments and forward-looking resilience planning for Pacific salmon.

Recent progress in mathematical kinship modelling has allowed one to predict the probable numbers of kin for a typical population member. In the models, kin may be structured by age and sex, both in static or time-variant demographies. Knowing the probable numbers of kin in different stages - such as parity, health status, or geographic location - however, remains an open challenge in Kinship Demography. Knowing how population structure delimits kin to distinct stages is an advance - for instance, the probability of having one sister at home and one sister away has different social implications from the probability of having two sisters. We present a novel analytical framework, grounded in branching process theory, that provides kin-number distributions jointly structured by age and stage. Using recursive compositions of probability generating functions (PGFs), we derive the joint age, stage, and age x stage kin-number distributions. All marginal distributions over either dimension naturally emerge. Simple extensions of the PGF approach additionally yield: the joint distribution of an individuals own stage and their kins stage; the probable numbers of kin deaths, both in total and by generation number; and the probabilities of being kinless and/or orphaned. We demonstrate the framework through novel results in an application using UK parity-specific fertility and mortality data. HighlightsO_LIA new method calculates probability generating functions for the number of kin structured by age and stage C_LIO_LIThe model allows predicting the probable numbers of kin organised by age and stage C_LIO_LIRecursive nesting of probability generating functions in branching processes is used C_LIO_LIAn application is presented highlighting the novel results C_LI

Global biodiversity is declining at an unprecedented rate due to rapid environmental change and increasing human pressures. Ongoing urban expansion fragments natural systems, while urban design increasingly seeks to mitigate these impacts through the integration of blue-green infrastructure. Effective biodiversity monitoring is therefore essential to evaluate ecological conditions within these novel socio-ecological systems. Although urban biodiversity monitoring is challenged by its high landscape heterogeneity, dense human populations provide opportunities for large-scale data collection through public participation in citizen science. Using data from 25 City Nature Challenge (CNC) projects across the United Kingdom (2020-2025), we assessed the effects of the four-day bioblitz on species inventories, participation in biological recording, and spatial patterns of recording effort. CNC events doubled public participation in iNaturalist recording relative to baseline activity, leading to the documentation of numerous previously unrecorded species through increased observer effort and broader use of urban blue-green spaces. These results show that CNC events enhance urban biodiversity datasets by increasing the number of observers and reducing spatial and observer biases, providing a cost-effective tool for enriching urban biodiversity data. In addition to generating ecological data, CNC events could have public health benefits through increased exposure to urban blue-green spaces.

Species tolerating the same environmental conditions can potentially colonize and thrive in the same habitats and eco-regions. Are any pair of those species equally probable to co-occur in the same community? Can we quantify the propensity of two species to co-occur together? Here, we focus on a simple but largely overlooked community-level pattern: the co-occurrence-occupancy curve, which relates the tendency of species to co-occur with others to their total occupancy across sites. We first define this empirical curve and then derive its expected shape under a random null model that assumes site equivalence and species independence. Building on these results, we introduce the Species Association Index (SAI), an occupancy-standardized measure that quantifies the tendency of a species to associate with others independently of its overall frequency of occurrence. The SAI enables meaningful comparisons among species with contrasting occupancies and provides a transparent benchmark against which departures from neutrality can be assessed. We illustrate the approach using two contrasting systems--tropical rain forest trees on Barro Colorado Island and organisms from Mediterranean rocky shores--highlighting both the generality of the co-occurrence-occupancy framework and its limitations.

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.

Mesic resources, the late-season herbaceous vegetation found in riparian areas and wet meadows, provide disproportionately important forage and habitat across western U.S. rangelands, yet their response to climatic variability and anthropogenic influences remains poorly understood. Using a 40-year Landsat time series (1984-2024), we quantified trends in late-season productivity (NDVI) across 4.5 million hectares of the sagebrush biome and applied random forest models to distinguish between temporal and spatial predictors of mesic resource productivity. We identified a fundamental shift in how mesic resources respond to drought: from 1984 to 2004, mesic productivity was strongly correlated with drought severity (Palmer Drought Severity Index, R{superscript 2} = 0.92), but this relationship weakened substantially in the next two decades (2005-2024; R{superscript 2} = 0.28), during which time productivity increased despite persistent aridity. Temporal modeling identified rising atmospheric CO2 concentrations as the strongest predictor of this shift, consistent with enhanced plant water-use efficiency under CO2 fertilization. Spatially, large agricultural valley floodplains act as anthropogenic refugia, sustaining productive mesic resources through flood irrigation and subsequent groundwater recharge into late summer. These findings suggest that human water management and physiological shifts in vegetation are currently buffering mesic systems against meteorological drought throughout U.S. rangelands. However, this apparent buffering is spatially heterogeneous and may mask vulnerability to groundwater depletion, shifts in precipitation regimes, and woody encroachment. Sustaining these vital ecosystems will require conservation approaches that go beyond climate monitoring to include balanced management considering both agricultural and ecological water needs and constraints.

In an era of severe global biodiversity threats, understanding the link between species traits and their endangerment helps uncover causes of risk and infer threats to understudied species. Most animals have complex life cycles with distinct stages that may face stage-specific threats. Current conservation frameworks rely heavily on adult traits, potentially misjudging extinction risk. Using Chinese anurans as a model, we integrated functional traits from both adult and tadpole stages to examine their association with extinction risk. We found that body size positively correlates with risk in both stages. Microhabitat use related with extinction risk in tadpoles but shows no significant link in adults. Adult relative tympanum diameter and head length also correlate with extinction risk. These results indicate that species vulnerability is shaped by multi-stage traits, with both shared and stage-specific threats. Conservation based solely on adult traits may fail to accurately assess species threats. We call for integrating a whole-life-history perspective into biodiversity assessment and conservation to more effectively address the global biodiversity crisis.

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.