Landscape Ecology

Habitat destruction leads to a severe decline in biodiversity. Ascertaining effects of habitat loss afterwards is regularly done, whereas predicting the effects of different habitat loss scenarios on biodiversity beforehand is much preferred but as of yet rarely possible. Such predictions would help inform management decisions to prevent biodiversity loss in the first place, or at least mitigate effects if necessary, by providing handles to set priorities in making trade-offs. To this end, we developed and applied an adapted version of the information-theoretical framework of Maximum Entropy Theory in Ecology (METE) to predict species-area relationships in tropical forest landscapes undergoing habitat loss and fragmentation. Species-area relationships provide information about biodiversity and can, in undisturbed systems, be predicted using METE, based on state variables such as the total number of individuals, the total number of species, and the total area size. In disturbed systems, however, it is established that METEs predictions are off. Using an individual-based model, we explore how METEs state variables should be adjusted, based on the landscape characteristics habitat cover and degree of habitat fragmentation, to restore its accuracy of species-area relationship predictions in disturbed environments. We validate our adjusted METE predictions with empirical data. Our adjusted METE predictions demonstrate the severity of fragmentations impact on biodiversity, relative to what could be expected in a pristine, continuous environment. With this new method, we can estimate the immediate effects of habitat loss on biodiversity, as well as its long-term effects.

Ground-nesting wild bees require suitable soil conditions for their below-ground development and overwintering life stages. Understanding how soil translocation and disturbance affect individuals and the following generations of bees is important for identifying conservation measures for ground-nesting wild bees. We investigated the effects of soil translocation and disturbance on the ground-nesting solitary spring mining bee Colletes cunicularius. In a replicated controlled design, we compared the effects of soil translocation with different degrees of disturbance on the number of surviving bees and the emergence time. We found that soil translocation and disturbance reduced bee survival but did not result in complete mortality, with some individuals surviving even under severe soil disturbance. There was no evidence that soil disturbance affected the timing of spring emergence, suggesting that disturbance is unlikely to alter the timing of nest construction and, consequently, the production of the next generation. Our results indicate that translocating soil containing overwintering bees could be a promising conservation measure to compensate for habitat loss caused by land conversion.

Climate change will alter habitat suitability for plant communities in mountain ecosystems of the Western Himalaya. There will be contrasting magnitudes and spatial configurations of these changes for different plant species, and it is an important question how to translate these contrasts into effective climate-proof multi-species conservation planning. This study assessed current habitat associations and projected changes in suitable habitat for two contrasting species, Meconopsis aculeata and Rhododendron campanulatum, in Himachal Pradesh, India. Field surveys and spatially filtered occurrence records were combined with MaxEnt modelling using 10 non-collinear environmental predictors. Habitat suitability was projected to 2050 and 2070 under Shared Socioeconomic Pathways; SSP1-2.6, SSP2-4.5 and SSP5-8.5 using HadGEM3-GC31-LL. Field observations showed contrasting habitat associations, with M. aculeata occurring mainly in open alpine herbaceous communities and R. campanulatum in subalpine woody communities. Elevation was an important predictor for both species while climatic predictors contributed differently to their relative importance and response patterns. Future projections indicated reductions in suitable habitat of approximately 25% for M. aculeata and 27-28% for R. campanulatum. Habitat-change maps showed heterogeneous patterns of loss, gain and persistence rather than uniform contraction, and centroid displacement remained small (7.7-8.5 km). We performed proximity analyses to show which currently suitable areas are most close to areas of future gain, in order to support the design of climate-proof protected areas. We discuss how interspecific differences in response are relevant to multi-species conservation planning that considers the spatial relationship between current high-suitability areas and the gain, loss and redistribution of future suitable habitat.

Land use change is widely recognized as a major driver of emerging zoonotic diseases. Yet, while forest plantations are expanding worldwide, their consequences on the circulation of infectious agents in wildlife remain poorly understood. We investigated how native pine plantations and broadleaved habitats shape rodent-associated infectious hazard in the generalist wood mouse (Apodemus sylvaticus), in southwestern France. Using a multi-season survey, we screened 424 wood mice for a broad range of infectious taxa and compared infection probability and infected-host abundance among pine plantation edges, broadleaved hedgerows embedded within pine plantations and broadleaved forests. Using a combination of linear mixed model and joint species distribution modelling, we tested whether infectious hazard differed between pine plantations and broadleaved forests, whether broadleaved hedgerows shifted these patterns towards those observed in broadleaved forests, and how these habitat-related patterns varied across seasons. We detected 22 potentially infectious taxa, including nine recognized zoonotic bacteria. Season strongly influenced infectious patterns, while habitat effects were taxa and season dependent. In spring, pine plantation edges increased infection probability for Bartonella grahamii and Neoerhlichia mikurensis compared to broadleaved forest, but their strong negative effect on wood mouse abundance resulted in consistently lower infected-host abundance for most infectious taxa. Broadleaved hedgerows showed distinct and season-dependent patterns with infectious profiles resembling those of pine edges in spring, but with higher infectious hazard than both other habitats for several taxa in autumn. Our results highlight that habitat effects on infectious hazard cannot be inferred from infection probability alone. Pine plantations may reduce rodent-associated zoonotic hazard through their strong negative effect on host abundance, despite increasing infection probability for some agents. Forest diversification and restoration initiatives, such as broadleaved hedgerows here, may have unforeseen epidemiological consequences, underscoring the need to integrate disease ecology into forest management and restoration to anticipate variation in zoonotic risks, while maximizing ecological benefits.

Abstract Habitat configuration influences population connectivity and, consequently, genetic structure. River networks provide heterogeneous, hierarchically arranged environments that shift drastically from upstream to downstream. We compared congeneric species across Ephemeroptera, Plecoptera, and Trichoptera, emphasizing longitudinal replacement (upstream to downstream) and the rarely studied wet rock (hygropetric) habitats. We surveyed six rivers on the Muroto Peninsula, Japan, qualitatively sampling aquatic insects at 63 sites. Cluster analysis based on the environmental data classified surveyed sites into four clusters. We analyzed a total of 10 species from four genera that exhibit longitudinal replacement patterns within genera. Genetic analyses based on the mitochondrial cytochrome c oxidase subunit I region revealed that upstream species showed higher genetic diversity than downstream species. In contrast, species adapted to hygropetric exhibited the lowest genetic differentiation among all habitat types. A novel contribution of this study is the inclusion of hygropetric species. The surprisingly low differentiation in hygropetric species suggests high connectivity, similar to lentic species. By comparing congeneric taxa across orders within environmentally similar rivers, we reduce phylogenetic and environmental confounds, strengthening inference that habitat configuration and dispersal traits jointly shape genetic structure. These findings provide a new perspective on riverine spatial ecology and underscore the importance of microhabitat-aware comparisons for evolutionary inference.

1. As city populations expand globally, understanding how urbanization shapes ecosystem services is increasingly important. Urban agriculture plays a key role in food access, particularly in low-income areas with limited access to fresh produce. Arthropods play important roles in these systems through pollination, herbivory, pest control, and nutrient cycling. Urban development of natural areas often reduces biodiversity, including that of arthropods. Additionally, urban biodiversity frequently correlates positively with socioeconomic conditions, a pattern known as the luxury effect. 2. In this study, we examined how gradients in urbanization and socioeconomic context relate to local and landscape habitat quality, arthropod abundance, and pollination services across 21 community gardens in the Denver, CO Metro Area. To quantify ecosystem services, we employed a sentinel plant, Cucumis sativus (cucumber), and collected arthropods (insects, myriapods, arachnids, isopods), assigning them to functional groups based on their known feeding behavior. We evaluated direct and indirect pathways linking urban matrix characteristics to arthropod-mediated ecosystem services. 3. The abundance of all arthropod groups (including pollinators, herbivores, and natural enemies) declined steeply with increasing impervious surface. Neighborhood wealth was associated only with bee species richness and Shannon diversity and displayed a hump-shaped pattern that peaked at wealth levels 35-46% above the national average, then declined. Multivariate GLMs revealed that Western honeybees (Apis mellifera) were the only species driving differences in bee community composition, with their abundance positively related to neighborhood wealth. 4. We also observed pollen limitation in our cucumber plants, and as bee Shannon diversity increased, cucumber production increased. Environmental covariates alone showed no direct relationship with cucumber production, indicating that insect pollination mediated this effect. This work identifies the biophysical and social-ecological drivers of urban arthropod biodiversity and ecosystem services, revealing where crop production may be most vulnerable to decline in cities.

Plant phenology influences biotic interactions and the cycling of water, carbon, and nutrients, ultimately affecting global climate. Accurately quantifying phenological dynamics is therefore essential for ecological forecasting, yet estimates vary widely depending on data sources, smoothing approaches, and date-extraction techniques. For this reason, the selection of an appropriate processing pipeline requires benchmarking under controlled conditions. In this study, we use a Land Surface Model (LSM) to simulate ecosystem dynamics at four temperate forest sites under five lesser studied climate perturbations. The resulting synthetic dataset allows us to control for environmental conditions while comparing commonly used phenological detection methods (relative thresholds at 10%, 20% and 50%, highest rate of change, detection of inflection points in the curvature angle, detection of recovery and senescence points). Amongst tested methods, we find general agreement in responses to climate alterations, where inflection and low thresholds (10%) methods provide the closest match to the model predicted start of season, with a maximum discrepancy of 4 days. Higher thresholds (20%, 50%) are closer to the model predicted end of season, though discrepancies reach up to 10 days. High thresholds and rate-of-change methods also reliably detect the peak of season. We further show that some methods detect phenological responses missed by temperature-only type growing season, supporting the need for more realistic phenological representations in LSMs. Beyond evaluating extraction methods within a common framework, our study expands on the potential of using LSMs as sandboxes for ecological testing rather than solely predictive tools.

Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m2/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.

1. Plant populations at high elevation persist near their physiological limits, and treeline position is one of the clearest expressions of this constraint. In many mountain regions, however, this limit reflects historical land use as much as climate. Treeline shift is most often tracked as the displacement of a boundary line (1D) overlooking structural changes only visible when the ecotone is analysed as a surface (2D). 2. We reconstructed treeline ecotone dynamics at nine sites in the Italian Alps using aerial imagery from 1954 and 2017. At each site we detected the timberline and tree species line, quantified elevational displacement, and measured ecotonal surface change, relating them to climatic, land-use, and topographic predictors. 3. Both boundaries advanced upslope at all nine sites, with timberlines shifting faster (1.6 m/yr) than tree species lines (1.1 m/yr). This decoupled velocity caused the ecotonal surface to contract by ~17%. Land-use variables consistently explained more variance than climatic ones. 4. Land-use legacy and abandonment have a major role in shaping treeline dynamics. Boundary displacement reveals vegetation advance at both margins, while the surface view reveals concurrent narrowing of the habitat available for tree establishment. Both perspectives are needed to fully characterize how plant populations respond to shifting limiting factors at the treeline ecotone.

Arboreal camera trapping is an emerging remote sensing tool for building plant-frugivore interaction networks with enormous potential to provide new insights into seed dispersal as an eco-evolutionary process. Interaction data derived from camera trap videos broadly falls into two categories: visitation, indicating the presence of an animal in a tree, and intake, indicating true fruit consumption. These linked approximations of seed dispersal may or may not provide distinct sets of information, shaping our understanding of network dynamics, yet the extent to which emergent network structure depends on variable choice is unknown. To address this gap, we deployed camera traps in the canopy of 21 plant species in the Costa Rican tropical dry forest, an endangered biome with sparse community-wide plant-frugivore interaction data. Our objectives were: 1) Quantify plant-frugivore network structure in the tropical dry forest via network, group, and species-level metrics; and 2) Compare metrics between visitation and intake networks. We find strong structural patterns of low connectance, low nestedness, high modularity, and low niche overlap that differ significantly from null expectations in the same direction in both networks. The visitation network exhibited significantly greater modularity & species degree than the intake network, while the intake network exhibited significantly greater plant niche overlap than the visitation network. These findings suggest that the likelihood of consuming fruit on camera differs across species, which may have downstream consequences on other emerging metric estimations. Researchers seeking to build quantitative plant-frugivore networks should therefore consider visitation and intake variables in concert when relying on camera trap data. This work provides foundational plant-frugivore interaction data for a critically endangered biome and enhances our understanding of camera trapping as a remote sensing tool in frugivory and seed dispersal research.

Over the past two decades, significant population recoveries of tigers and leopards have driven a substantial rise in human-carnivore conflict across South Asia. Sustaining the long-term conservation of both species demands effective, adaptive conflict management. However, existing research is largely confined to isolated landscapes or protected areas, hindering the identification of spatial conflict drivers across broader, heterogeneous regions. To address this gap, this study compiled 4,457 human leopard conflict (HLC) and 2,563 human tiger conflict (HTC) records spanning 2000 to 2024 across Bangladesh, Bhutan, India, and Nepal. We evaluated conflict locations against 33 landscape, anthropogenic, climatic, topographic, and hydrological predictors across three spatial scales using binomial generalized linear regression models and three alternative background sampling methods. Model performance peaked at the largest spatial scale for both species and remained consistent across sampling strategies. HTC correlated positively with forest fragmentation and proximity to human settlements, but decreased with higher overall anthropogenic disturbance. Conversely, HLC concentrated in highly productive, high-precipitation, human-modified landscapes. These contrasting spatial patterns highlight distinct ecological responses to habitat modification and carry unique conservation implications. Ultimately, this study underscores the need to integrate carnivore abundance, wild prey densities, and socioeconomic factors to achieve a holistic understanding of conflict dynamics.

Mediterranean forests are emerging as one of the clearest hotspots of climate-change impacts, where rapid warming and increasingly severe droughts and heatwaves are pushing forest ecosystems toward their physiological and functional limits. These pressures threaten productivity, carbon dynamics, ecosystem stability, and the services forests provide. In this context, a process-based forest ecosystem model was used to assess climate-driven changes in carbon dynamics and productivity stability across Italian forests within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. 5135 plots were simulated, corresponding to ~80% of the field plots included in the second Italian National Forest Inventory (INFI). Model simulations were first evaluated against independent observations of gross primary production (GPP) from satellite-based products and forest carbon variables from the third INFI. Forest dynamics from 2015 to 2100 were simulated under three CMIP6-based emission scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) using two climate forcings (GFDL-ESM4 and UKESM1-0-LL). Future responses were assessed for GPP, aboveground biomass, growing stock volume, and carbon stocks, while variability in GPP was quantified using the coefficient of variation as an indicator of forest stability. Results show that the model reproduced the main spatial and temporal patterns of forest productivity and carbon stocks. Future projections revealed strong spatial heterogeneity and increasing divergence among scenarios after mid-century. GPP showed the earliest and strongest response to climate change, with mountain forests generally maintaining or increasing productivity and exhibiting greater stability, whereas coastal forests showed pronounced productivity declines and increasing variability, particularly under higher-emission scenarios and more extreme climate forcing. In contrast, carbon stocks generally continued to increase throughout the century, although carbon accumulation progressively slowed toward the end of the century, particularly under higher-emission scenarios.

Aim: To test whether individual movement mechanisms inferred from animal tracking data can be scaled up to explain landscape-scale patterns of population density and improve predictions of population redistribution under future environmental change. Location: Texas Gulf Coast, USA Time Period: 2009-2018 Major Taxa Studied: Whooping Crane (Grus americana) Methods: We parameterized individual-level step-selection functions using 14,898 GPS locations from 22 Whooping Cranes and propagated the resulting movement and habitat-selection mechanisms across the landscape to derive steady-state distributions of space use. We compared these movement-informed predictions with correlative species distribution models fitted to the same data. Predictions were evaluated using withheld tracking observations and fully independent population-level aerial-survey data. We then projected both approaches under sea-level-rise scenarios to assess how future habitat loss and fragmentation alter crane space use. Results: Movement mechanisms derived from individual-level tracking data captured the mechanistic dependence of population density on habitat quality and spatial configuration. When projected across the landscape, these mechanisms reproduced fully independently observed density patterns and outperformed conventional species distribution models. Because predictions arose from movement mechanisms rather than occurrence-environment correlations, movement-informed models also captured the effects of habitat reconfiguration under sea-level rise. They projected pronounced population redistribution and an expansion of core space-use areas of up to 80% which conventional models missed. Main Conclusions: Individual movement mechanisms derived from biologging data can scale up to explain current population structure and predict future redistribution under environmental change. By mechanistically accounting for how habitat configuration constrains accessibility, movement-informed models reveal severe impacts of fragmentation that are missed by conventional distribution models. Rapidly expanding biologging datasets therefore offer a scalable basis for connecting individual behavior to macroecological patterns and improving biodiversity forecasts in changing landscapes.

Diurnal ectotherms in hot and dry ecosystems face an acquisition trade-off between maximizing collective energy intake and minimizing individual exposure time. We employed optimal foraging and thermoregulation models to examine the surface foraging and thermoregulatory strategies of Pogonomyrmex barbatus foragers in response to habitat warming in a tropical deciduous forest. Foraging activity was evaluated using field-based thermal performance curves (fTPCs) for individual foraging speed and collective foraging success. Thermoregulation was assessed through indices of thermal unsuitability, as well as thermoregulatory effectiveness and exploitation. Our results show that afternoon conditions were significantly hotter and drier than those in the morning. Furthermore, the decoupling of fTPCs was dynamic; while the optimal temperature (Topt) for individual foraging speed remained stable at 44 degrees C, the Topt for collective foraging success shifted from 35 degrees C in the morning to 41 degrees C in the afternoon. This shift in foraging strategy, driven by stressful afternoon conditions, was reflected in a transition of the thermoregulatory strategy. Specifically, the probability of foraging activity decreased as thermal unsuitability increased, with a lower baseline in the afternoon. The thermoregulatory exploitation dropped from 94% in the morning to 63% in the afternoon. Based on thermoregulatory effectiveness, foragers transitioned from an active thermoregulatory strategy in the morning to a thermoconformist strategy in the afternoon while foraging on the surface. So, the observed colonies optimized the balance between individual foraging speed and collective foraging success through a thermoregulatory strategy that was primarily spatial in the morning and strictly temporal in the afternoon. A comparison with historical data from the same site reveals a 40% contraction in the total daily foraging window since 2013.

Tick-borne disease risk reflects the combined influence of vector abundance, pathogen prevalence, human exposure, and seasonal activity, yet these components are rarely integrated at the county level. We developed species-specific ecological risk scores for three medically important tick species (Acari: Ixodidae): Amblyomma americanum (L.), Dermacentor variabilis (Say), and Ixodes scapularis Say, across all 102 Illinois counties using data from 2019 to 2022. County-level predicted tick abundance and pathogen prevalence were scaled and combined using equal weights to generate primary vector-level risk scores. Robustness to the equal-weight assumption was evaluated by systematically varying the relative weights assigned to abundance and pathogen prevalence, while a separate sensitivity analysis incorporated reported tick-bite incidence where available. Associations with human disease were evaluated using negative binomial regression of tick-borne disease case counts on the corresponding risk scores, with county population included as an offset. Monthly phenology indicators were constructed by integrating human disease cases, reported tick bites, and sampled tick abundance and were evaluated in relation to temperature and precipitation. Seasonal risk was estimated by combining county-level vector risk with species-specific monthly phenology, generating monthly risk surfaces that were deployed through an interactive R Shiny application. Higher risk scores were significantly associated with greater disease case rates for each tick species. County rankings were highly stable under moderate changes in abundance and prevalence weighting. Seasonal activity differed among species, with A. americanum and D. variabilis showing concentrated warm-season risk and I. scapularis exhibiting a broader seasonal profile. These county-level seasonal risk maps identify where and when relative tick-borne disease risk is elevated in Illinois, supporting targeted prevention, surveillance, and clinical awareness.

Information on Western bongo (Tragelaphus eurycerus eurycerus) across its range remains scarce and fragmented, leaving the status of populations poorly understood, limiting effective conservation planning. We conducted three camera-trap surveys across Semuliki National Park, Uganda, between October 2019 and August 2020 (90 camera locations; 11,640 camera days), during which we detected the only currently known population of Western bongo in East Africa. We assessed the status of this population using data from the final survey (March-August 2020), when bongos were detected, applying an individual identification system adapted from Eastern bongo (Tragelaphus eurycerus isaaci) and spatially explicit capture-recapture (SECR) modelling to estimate density and abundance. To reflect known aspects of bongo ecology, we incorporated sex and habitat covariates derived from remotely sensed data as predictors of density. Bongos were detected on 17 occasions, and we identified 18 individuals (11 females and 7 males), of which seven immature individuals (5 females and 2 males). The top-ranking SECR model included the tasseled cap greenness index and sex as predictors of density. The model estimated a population size of 56.49 individuals (SE = 7.69; 95% CI = 41.43-71.56), with an estimated density of 0.58 individuals km-2 (SE = 0.171; 95% CI = 0.32-1.09) within Semuliki National Park. These results provide the first quantitative baseline for this population and suggest the presence of an established breeding population, highlighting the need for structured monitoring to support its long-term conservation.

BACKGROUND: The Argentine ant (Linepithema humile) is among the world's worst invasive species. In the Donana Biological Reserve (Spain), it is associated with human structures that provide the mild, moist conditions it needs within the hot, dry scrubland. We evaluated a habitat-modification treatment, predicting that removing this suitable habitat would eradicate the invader locally. Over an 18-year period, we monitored ant communities at a treated and an untreated site, at different distances from the human structures, before and after treatment, and analysed how temperature and worker numbers affected encounters at baits between the Argentine ant and native ants. RESULTS: Distance to the human structures shaped ant communities at both sites, but only the treated site changed after treatment. There, the Argentine ant decreased close to the human structure and almost disappeared farther from it, whereas the endemic Cataglyphis tartessica and C. floricola recovered, especially close to the structure. At baits, the outcome of encounters depended mainly on how temperature changes favoured each species relative to its maximum activity temperature: Cataglyphis spp. displaced the Argentine ant in the morning, as temperature increased, and the Argentine ant recovered the baits in the late afternoon. Numerical advantage favoured only the Argentine ant. CONCLUSION: Habitat modification reduced the Argentine ant and allowed endemic ants to recover, but did not eradicate the invader, which persisted at low abundance 13 years after treatment. In protected areas, habitat management should be combined with eradication, monitoring and prevention of spread.

Climate affects biological processes and organisms. It is extensively recorded, and its effects are frequently studied. Climatic variables are recorded as time series of measurements, but these are often summarized as long-term averages, throwing away biologically relevant information. Subsequent analyses can therefore miss important climate effects or suffer from low predictive power. Here, we propose a new method, StatClim, inferring the most informative climatic summary from the data. Instead of taking a fixed arbitrary summary of a time series, StatClim automatically estimates the beginning and width of a climatic window and simultaneously calculates data aggregation, which best predicts a response variable. We implemented the proposed approach as a Bayesian hierarchical model in Stan. We illustrated the potential of StatClim on published data on mast seeding of Fagus sylvatica. StatClim correctly identified known climatic windows relevant for this tree species, but also uncovered that mast seeding is triggered by high temperatures within these windows. We demonstrated flexibility of the model to account for complex data structures, we ran power analysis showing the ability of the model to identify climatic effects even with modest datasets, and we evaluated its false positive rate, which is lower than 0.01. We discuss the advantages and limitations of StatClim. Compared to existing alternatives, it is suitable for hypothesis testing and offers important advances, such as estimation of the type of aggregation. In combination with existing methods, StatClim will facilitate data-driven use of climatic and microclimatic data and therefore discovering so far unknown climatic effects on biological processes and ecosystem functioning.

Aim Regional climate-change refugia - areas where abiotic conditions related to hydrology and topography sustain unique plant communities despite an otherwise unsuitable regional macroclimate - have been essential for maintaining biodiversity through past climatic transitions. At fine spatial scales, regional refugia can also contain microrefugia, where canopy structure and topography strongly buffer understory microclimate. We tested whether such microrefugia structure understory plant communities within a regional climate-change refugium, where sheltered, groundwater-fed canyons have sustained a biogeographically distinctive flora since the Last Glacial Maximum. Location Temperate forest in the North American Great Plains, Nebraska, USA. Methods In a 20.2-ha forest inventory plot spanning a sharp topographic gradient, we quantified diversity, composition, and distributions and of understory woody and herbaceous plants across seven functional groups along fine-scale topographic, light, and soil moisture gradients. Results Woody species density and richness were significantly higher within sheltered microrefugia in canyon bottoms and on forested slopes and strongly decreased with increasing canopy openness, whereas C4 grass richness was highest along the exposed, high-light forest-prairie ecotone, reflecting divergent functional group responses to microclimate buffering. Soil moisture structured richness across functional groups: woody plant and C3 grass richness peaked at moisture extremes, sedge richness at intermediate moisture variability, and C4 grass richness declined with increasing moisture variability. Both woody and herbaceous understory plants showed strong variation in composition with topography; in particular, woody seedlings and graminoids exhibited strong species turnover with increasing elevation. Main Conclusions These results demonstrate that topographically driven microrefugia support disproportionate understory biodiversity and suggest that protecting both regional refugia and finer-scale microrefugia will be critical for conserving plant communities, including species documented exclusively in microrefugia, as macroclimate continues to change.

Urban protected areas (PAs) have become important habitats for wildlife in rapidly expanding human-dominated landscapes. These PAs may provide refuge and continuously abundant resources, which may enable some adaptable carnivores to persist and attain high abundances. However, little is known about the population ecology and interactions between carnivores sharing such spatially restricted and disturbed urban habitats. We evaluated the densities and spatio-temporal interactions of leopards (Panthera pardus) and striped hyenas (Hyaena hyaena) in Jhalana-Amagarh Conservation Reserve, a protected area (PA) embedded within the metropolis of Jaipur, India. During May-July 2025, we deployed 30 paired camera-traps and used spatially explicit capture-recapture models to estimate density and individual activity centres. We further quantified their diel activity and temporal overlap using kernel density estimation. Leopard density was estimated at 7.03 {+/-} 1.31 individuals/10 km sq and striped hyena density at 4.06 {+/-} 0.96 individuals/10 km sq, with activity centres of both species occurring in close proximity and frequently towards the reserve periphery. Both species were predominantly nocturnal and showed high temporal overlap ({Delta}4 = 0.801, CI=0.73-0.86). Our results report exceptionally high leopard and striped hyena densities in an urban PA and exemplify the importance of small PAs within rapidly expanding cities, stressing the need for finer-scale studies more broadly to understand the mechanisms shaping interactions between the two species. However, such systems require careful management of food subsidies, habitat quality and connectivity along with long-term monitoring of population viability, disease dynamics and human-wildlife conflict.