Landscape Ecology

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.

Cities are characterized by elevated temperatures, increased pollution, and high-density human populations which often are accompanied by changes in available resources, like food. These shifts have the potential to drive phenotypic divergence in urban wildlife. Functional morphological traits, like body size, can mediate interactions between wildlife and habitat and are closely tied to life history and fitness. While examples of functional morphological variation associated with urbanization are increasing, variation in such traits as a response to urbanization remains unexplored for most taxa. Here, we investigated morphological divergence between urban and rural populations of house mice (Mus musculus domesticus). House mice are globally distributed in diverse habitats and are a model system with a wealth of phenotypic data, making them useful for the study of the impacts of urbanization on morphology. Using a paired replicate design, we sampled urban and rural populations in three distinct metropolitan regions in the eastern United States. We found that body size was smaller in urban populations. Using 3D geometric morphometrics, we also analyzed variation in cranial shape across habitats. Differences in cranial shape were largely allometric, that is, driven by differences in body size. However, we also uncovered evidence of cranial shape variation between habitats not explained by size. In contrast, we did not find evidence for habitat-driven differences in cranial capacity independent of size. Overall, our results suggest a key role for body size in mediating morphological responses to urbanization and highlight the potential of house mice as a globally-distributed model for urbanization.

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

Nature-Based Solutions are increasingly promoted to address current urban challenges. While their potential effects on vector-borne disease risks have been documented, data on Aedes albopictus, a known arbovirus vector, remain limited in France. A previous study showed that urban vegetation moderately increases the abundance of adult mosquitoes of this species, but the monitoring period lasted only six months. Using ovitraps, we monitored Ae. albopictus egg density dynamics over multiple years (2022 to 2024) and analysed its environmental predictors in various urban environments. We included lagged meteorological variables, land cover metrics, and the cumulated egg densities recorded in the previous weeks as environmental predictors. Both parametric (GLMM) and non-parametric (Random Forest) models were fitted to weekly egg counts per trap. Our findings highlight that (i) egg density dynamics were related to how vegetation classes structured the landscape, (ii) growing degree days and cumulated number of eggs recorded in specific lagged time windows were the main contributors to egg density, and (iii) the non-parametric and parametric models performed similarly in terms of prediction accuracy.

Romania represents one of the few European Union member states in which all four Old World vulture species historically maintained breeding populations: the Griffon Vulture (Gyps fulvus), Cinereous Vulture (Aegypius monachus), Egyptian Vulture (Neophron percnopterus) and Bearded Vulture (Gypaetus barbatus). Until the 2026 reintroduction efforts initiated by Foundation Conservation Carpathia and Rewilding Romania, Romania remained the last EU country whose former vulture guild had not been targeted for active recovery. Despite this exceptional significance in a European conservation context, no comprehensive synthesis of the historical and contemporary distribution of these species in Romania has been undertaken. We conducted a comprehensive review to gather all available vulture occurrence data and present a fully georeferenced database of 1,170 occurrence records spanning 1818-2025. We systematically searched museum collections, historical ornithological literature, modern field surveys and citizen-science platforms. The database documents substantial breeding populations across the Carpathian arc and Dobrogea until the early twentieth century, followed by near-total breeding collapse between the 1920s and 1960s driven by persecution, secondary poisoning and agrarian transformation. In total, 149 confirmed or probable breeding records have been documented for the four species combined, with the most recent confirmed breeding records dating to 1929 (Gyps fulvus), 1929 (Gypaetus barbatus), 1942 (Aegypius monachus) and 1966 (Neophron percnopterus). Non-breeding occurrences increase markedly after 2010, consistent with dispersal from expanding Balkan source populations. The F[a]g[a]ra {square} and Retezat Mountains emerge as the historically most important breeding strongholds for all four species. Our dataset constitutes the most detailed historical baseline currently available for vulture conservation in Romania and is intended to identify key historical sites with high potential for future reintroduction and recovery. Our results show that Romania historically supported the full guild of European obligate scavengers, and that its collapse occurred within barely four decades (1920s-1960s). The dataset highlights the value of reconstructing historical baselines in regions where functional extinction preceded the onset of modern monitoring, and provides an empirical foundation for reassembling a keystone scavenger guild at a continental scale.

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

Statewide tracking of urban tree canopy change is essential for evaluating progress toward policy targets, but detecting real change requires both high-resolution mapping and rigorous uncertainty estimation. We produced a four-year canopy cover time series for all California census-designated places using 60-cm NAIP aerial imagery and a U-Net deep learning model trained with semi-automated LiDAR-derived labels and manually annotated tiles. Canopy cover and change were estimated using stratified, error-adjusted area estimation, enabling comparisons across years. Statewide canopy cover showed a modest negative trend from 2016 to 2022 (Sens slope: -0.60% per year), but confidence intervals included zero across all groups and climate zones, indicating that trends were not statistically distinguishable from no change. Urban canopy cover was consistently lower than non-urban canopy by approximately six percentage points, and canopy cover was highest in the Northern California Coast and lowest in the Southwest Desert. Residential parcels accounted for 55-56% of canopy within incorporated urban areas across all years, indicating that statewide canopy increase goals will require engagement with private landowners. Error adjustment substantially altered canopy estimates relative to raw pixel-count totals, with direct implications for AB 2251 canopy tracking where baselines and targets drawn from unadjusted maps may not reflect true canopy extent. This open-source workflow is transferable to future NAIP acquisition years and other U.S. states, providing a scalable framework for long-term urban forest monitoring.

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

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

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

Habitat fragmentation disrupts metapopulation dynamics by altering environmental conditions and constraining demographic processes critical for persistence and recruitment. In the dry Afromontane forests of northern Ethiopia, we investigated how natural and anthropogenic drivers affect seedlings, saplings, and mature tree dynamics of Olea europaea subsp. cuspidata across 34 patches. We used dynamic occurrence models to quantify effects of patch area, altitude, browsing, and disturbance. Our results indicate that high disturbance reduces seedling occurrence probability lower disturbance sites has seedling in 30% of survey plots, high disturbance would bring this down to 10% (median = -1.322, 95% CI: -2.703 to -0.283). Disturbance makes seedling less likely to persist, while large patch size help seedling persists (median = -0.93, 9 5 % CrI -1.87 - -0.02). For mature individuals, disturbance was the only significant predictor of occurrence probability, suggesting greater resistance to environmental and spatial variability compared to earlier life stages. These findings emphasize that while mature trees display resilience, the successful regeneration of Olea europaea is constrained by disturbance, but current level of browsing is not a threat. Management strategies for conservation should prioritise reducing disturbance through community engagement and forest stewardship to enhance regeneration potential and ensure long-term population viability.

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

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.

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.

Infectious disease time series often show signs of epidemic transitions, such as the peaks and troughs of the time series. In these time series, key system parameters can lead to catastrophic changes in the dynamical system behaviour (often called critical transitions). Modellers have increasingly shown that early warning signals can anticipate these transitions, both critical and non-critical, in infectious disease time series. Existing methods, however, generally focus on univariate time series data, or ignore spatiotemporal patterns that may be present as a disease spreads through a population. Recent ecological literature developments expand existing temporal and spatial methods to consider the covariance matrix of multiple, related time series. However, many of these proposed signals still make an assumption of stationary time series/system equilibrium. Whilst often true in ecological modelling, disease systems are seldom at equilibrium. In this paper, we propose the usage of the eigendecomposition of the non-stationary covariance matrix as a more suitable early warning signal for epidemiological data. We first analyse the expected trends in the eigenvalues and eigenbasis of the covariance matrix on approach to a transition. Next we apply these methods to a spatially-structured susceptible-infectious-recovered model to explore how the eigenbasis may provide extra information to modellers. Finally, we test these methods on SARS-CoV-2 case data during the 2020-2021 pandemic period in England.

Urban pollinator gardens can provide refugia and support diverse populations of native bees amid threats from habitat destruction, pesticides, and potential ecological pressures from the introduced honey bee (Apis mellifera (Linnaeus, 1748)). The University of California, Berkeley, maintained a native bee garden at the Oxford Tract research facility to study the biodiversity, phenology, and foraging habits of urban bees from 2003 to 2009. That garden was decommissioned, and a new garden was re-established in 2019. Using diversity observations from the early 2000s garden and non-lethal sampling techniques, we characterized plant-pollinator interactions between flowers and urban bees in the newer bee garden with a bipartite interaction network. Across 12 flower species, we observed two non-native pollinators, the honey bee (A. mellifera) and the alfalfa leafcutter (Megachile rotundata (Fabricius, 1793)), along with at least ten native bee species across three families (Apidae, Halictidae, Megachilidae). We found that, despite the garden being created for native bees, honey bees accounted for 84% of all pollination interactions. The most abundant native bees were sweat bees (Family: Halictidae). Generalist interactions dominated the network, as both honey and sweat bees foraged on most available flowers. Honey bees showed a significant positive correlation with floral abundance, visiting flowers with the highest number of inflorescences, whereas native bees did not show this preference. These results indicate that native bee garden stewardship could benefit from greater floral diversity, while avoiding the dominance of any single species with high floral abundance, thereby reducing the likelihood of direct competition with honey bees.

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

Changing climates are reshaping animal populations, but our understanding of how demographic trends are shaped by individual responses to local environmental conditions is often limited to long-term studies with restricted spatial scales. Increasing evidence suggests that climatic extremes exert differential selection pressures across environments, often leading to nonstationary biological responses among populations. Participatory science (i.e. citizen science) observations can detect this variation at large geographic scales, but analyses of these data often lack insight into the individual-level responses that are required to explain the origins of such variation. Here we present a new research framework that uses long-term data to validate, then inform analyses of participatory science data to measure reproductive responses to environmental variation across large geographic scales. We use this approach to investigate how reproduction in a montane-adapted songbird, the mountain chickadee (Poecile gambeli), varies across elevations and latitudes in response to extreme scarcity and extreme accumulation of snow throughout the Sierra Nevada Mountains in North America. Chickadee reproduction in lower and higher elevation populations was often differentially impacted by drought and deluge snowfall extremes, but these relationships varied across latitudes. Reproductive performance in the northern Sierra Nevada was negatively affected by snow deluge conditions at high elevations, whereas snow drought conditions reduced reproductive output at low elevations. These relationships changed in the central Sierras where drought conditions negatively impacted both elevations, but deluge conditions improved reproductive performance at both low and high elevations. Reproduction in the southern Sierra Nevada was less affected by spring snow levels, likely due to the lower snow accumulation and earlier snowmelt in this region. These results emphasize the power of long-term studies to inform and interpret participatory science data in order to better understand how animal responses to environmental extremes vary across large geographic scales.

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

Recovery debt (RD) quantifies the interim deficit of biodiversity and function during the recovery process after disturbance. Unlike typical recovery indices derived from data on experimental-control comparisons, RD further considers the target (reference) biodiversity level, modelling the rate at which it is approached over time. However, the application of the RD approach to active restoration has not been explicitly implemented to date. Here, we extend the RD framework to evaluate active ecological restoration in agricultural systems, defining the onset of recovery as the shift from intensive to wildlife-friendly management. We applied this approach to assess short-term pollinator recovery in 14 olive groves across a gradient of farming intensification and landscape complexity in southern Spain. Restoration actions included adopting low-intensity ground cover management and actively restoring field margins. At one, three, and five years post-restoration, we assessed community responses by quantifying bee abundance, species richness, plant-bee network properties, and flower visitation rates. Reference systems were defined by olive groves in complex landscapes with low-intensity herb cover management and organic farming practices. Following restoration, the RD of bee abundance decreased from 71% to 55%. We found no significant effects of pre-intervention agricultural management on RD. Instead, across sites, the reduction of the RD (i.e., recovery) of bee abundance, richness, network connectance and flower visitation rate was strongly mediated by the availability of high-quality semi-natural areas in the surrounding landscape and by the ecological contrast created by restoration interventions at both the farm and floral patch levels. RD for other network metrics showed no significant pattern of variation. Our study demonstrates that wildlife-friendly management and targeted habitat restoration can rapidly reduce recovery debt for bee abundance and function in permanent agroecosystems. However, the recovery of more complex interaction-network properties likely requires longer timescales.