Ecological Applications

Accelerating global urbanization necessitates a better understanding of how to manage cities that promote biodiversity. However, we currently lack multi-year, multi-city studies, which limits a generalizable understanding of how both within and between city differences impact the spatial and temporal dynamics of urban biodiversity. Here, we tested hypotheses about the drivers of butterfly diversity within and across urban parks by applying Bayesian occupancy models to five years of iNaturalist community science data from 2,550 parks in 22 major U.S. cities. We found that cities with bigger parks supported more species per park, including more disturbance- and edge-avoidant species. This was driven by a positive effect of park size on butterfly species colonization rates. We also found that attributes of habitat quality (plant diversity within parks and tree cover surrounding parks) contributed to butterfly species occupancy. Park connectivity increased species persistence, but the overall effects on butterfly species occupancy varied across cities. Finally, we found that the total area of tree cover throughout a city, rather than the size or connectivity of individual parks, was the primary determinant of city-wide diversity: Increasing total tree canopy cover from below-average (~6%) to above-average (~22%) increased city-wide species richness by ~10%. These findings highlight the need for cities to maintain large parks while also increasing city-wide tree cover to support biodiversity across local to regional scales. By integrating high-resolution community science data across the continental U.S., this study provides mechanistic insight into how cross-scale processes shape urban biodiversity dynamics and identifies generalizable recommendations for improving urban conservation management.

Urban green spaces are increasingly recognised as important refuges for biodiversity, yet their ecological value depends strongly on design and management. Here, we investigate how fine-scale structural and microhabitat components shape urban ant assemblages, using ants as indicators of broader arthropod responses to urbanisation. Ant communities were sampled in twelve urban green spaces in Cordoba (southern Spain) over a ten-year period (2004 to 2013) using pitfall traps, alongside detailed characterisation of vegetation structure and ground-layer microhabitats. In total, 38 species and 25,578 individuals were recorded. Microhabitat variables explained 58% of the variation in species occurrence. Community differences among microhabitats were driven primarily by nestedness, with dense herbaceous cover acting as a core habitat and edge-related components contributing disproportionately to beta diversity. Tree abundance showed a unimodal relationship with species richness, with maximum diversity at intermediate densities, while shrub and lawn cover had weak or inconsistent effects. Fine-scale elements such as leaf litter, stones, woody debris, and small bare-ground patches strongly influenced species occurrence by providing thermal refugia, nesting substrates, and foraging opportunities. The invasive Argentine ant (Linepithema humile) exhibited strong but spatially restricted dominance and species-specific negative effects on native ants, emphasising the role of habitat context in mediating invasion impacts. Our results demonstrate that urban biodiversity is maximised by enhancing fine-scale habitat heterogeneity rather than increasing green cover alone. We highlight practical design principles for urban green infrastructure that prioritise structural diversity and ground-layer complexity to support resilient arthropod communities.

Frugivorous insect larvae are dependent on fruiting plants for development, leading to complex host-parasite interactions that may be influenced by many factors at various scales. We compared the relative effects of factors at the individual, neighborhood, and landscape scales in forest patches. Our results suggest that in areas like upstate New York, where agricultural land uses are dominant, individual scale factors are the most influential. Specifically, parasitism increased with host fruit crop size, but was not associated with host species richness or proximity to forest edge. Notably, the most parasitized hosts were non-native species, including Frangula alnus Mill. (Glossy Buckthorn), indicating a potential role of invasive species to shape host-parasite interactions in our system. Our results underscore the importance of host-specific traits in structuring parasitism patterns and suggest management could consider both the ecological context of host traits and the influence of invasive species at multiple scales.

O_LIWhen eradication is unfeasible, invasive predator control should evaluate how removal affects ecological responses by native species. Assessments often use total invasive predator abundance to evaluate prey responses, yet intraspecific variation in diet and space use means that some subgroups cause disproportionate impacts. Identifying these problem individuals, and the spatial scales over which their impacts operate, can enable targeted spatially explicit removal to maximise impact reduction. However, despite individual-level information is often already collected during trapping operations it is seldom included when analysing predator impacts, potentially biasing the conservation outcomes expected under blanket removal. C_LIO_LIWe use a novel framework and two decades of invasive predator control data to estimate how individual variation in residency status influences the distance-dependent impacts of invasive American mink Neogale vison on water vole Arvicola amphibius occupancy across two prey surveys. We also develop a sub-model to predict mink residency status for individuals with missing age data. C_LIO_LIThe probability of capturing adult mink decreased with elevation and years of control, indicating that long-term control altered the resident population and demographic composition of mink around water vole sites. C_LIO_LIDistance-dependent negative impacts of mink varied by residency status, becoming negligible at approximately 20 km from water vole sites for resident mink and 2 km for transient. The spatial scale of mink impacts was largest during the first vole survey when resident mink were more abundant, and declined rapidly for the second survey, when mink were less abundant and spatially clustered. Our results suggest that water voles have benefited mostly from reducing resident mink rather than the total population, especially in early control phases. C_LIO_LIManagers can use our framework to develop spatially explicit and impact-based strategies, not restricted to invasive species control, to construct empirically informed management buffers around populations of conservation concern. Long-term efforts will change the landscape and invasive predator contexts, and thus we recommend iteratively updating and re-evaluating management outcome evaluations. We argue that incorporating individual heterogeneity improves our understanding of ecological mechanisms influencing management success but that the suitability of targeted strategies should be evaluated for target socioecological contexts. C_LI

Understanding the relationships between soil macrofauna and decomposition is crucial for predicting how land-use change impacts ecosystem function in fragmented systems. This is because soil macrofauna affect decomposition and also respond to the changes in abiotic conditions across habitat gradients. This study investigates edge effects on the macrofauna contributions to decomposition across forest-field ecotones. We used bait lamina assay to quantify aboveground and belowground feeding activity of soil macrofauna in Autumn 2025 in three deciduous forest-old field ecotones and one coniferous forest-old field ecotone, in Southwestern Ontario, Canada. Vegetation diversity and composition, LAI and soil characteristics (i.e., soil organic matter, pH, temperature and moisture) were measured at each plot along the ecotone. Pitfall trap data collected in Summer 2025 at the same sites were used to characterize macrofauna communities. We used generalized linear mixed effects models to estimate the effect of distance to edge, site, and depth into the soil on bait lamina consumption and soil macrofauna, with transect nested within site as random effects. Consumption activity increased with distance into the forest from the field, with the edge representing an intermediate; and, decreased with increasing depth into the soil. In contrast, soil macrofauna abundance, especially isopods, decrease with distance into the forest from the field. These trends varied significantly across sites, so that consumption activity and abundance sometimes remained constant across the ecotone (i.e., site x distance interaction). The results demonstrate that macrofaunal contributions to bait consumption varied along the ecotone, shaped by interacting environmental gradients and shifts in community composition unique to each site.

Species distribution models (SDMs) increasingly inform conservation and biosecurity decisions in freshwater systems, where the reliability of its uncertainty estimates matters as much as its point predictions. Ensemble SDMs derive prediction intervals from across-replicate variance, but this variance captures systematic error only when replicates disagree about it, an assumption that fails when training data are contaminated with low-accuracy records, the norm in citizen-science datasets. Whether this failure is spatially uniform or concentrates in identifiable parts of a range is unknown. Using a panel of European freshwater crayfish spanning native headwater-associated species and invasive lowland colonizers, we show that contamination-induced calibration failure is strongly spatially structured: it concentrates at stream-network headwaters, the topological tops of the network, where upstream-aggregated predictors are structurally undefined, and scales with contamination severity, replicated across four species and both dominant ensemble protocols (replicate and consensus). The failure is driven by upward prediction bias, not by intervals failing to widen: contaminated ensembles overpredict suitability in headwaters, and because the bias is shared across ensemble members, the intervals do not flag it. This is a conservation-relevant blind spot, because headwaters are both refugia for threatened native crayfish and front lines for invasion; an SDM that silently overpredicts suitability there misdirects survey and management effort toward the segments where its predictions are least trustworthy. Standard leave-one-basin-out conformal calibration, the recommended panel-wide remedy, repairs marginal coverage but leaves headwaters undercovered, because a single calibration threshold is dominated by the abundant non-headwater segments. A group-conditional (Mondrian) variant, calibrating the two populations separately, restores reliable coverage in both at no extra cost and reallocates width where it is needed. We recommend network-position-stratified calibration as a default for ensemble SDMs in dendritic freshwater systems.

Context. The relationship between biodiversity and zoonotic disease risk is a central topic in community ecology, yet empirical evidence in Europe remains scarce and often contradictory compared to North American studies. Addressing this gap is fundamental to better anticipate zoonotic disease dynamics. Objectives. We investigated the transmission dynamics of West Nile virus (WNV) in Veneto (Italy), a major European hotspot. Because this vector-borne pathogen is primarily transmitted by Culex mosquitoes and maintained by several avian hosts, we analysed how multiple facets of both avian and mosquito biodiversity influence its transmission. Methods. Using Generalized Additive Models (GAMs) trained on longitudinal entomological and ornithological surveillance data, we modelled the probability of WNV presence in mosquito pools as a function of host and vector community structure. To isolate the effects of biodiversity, we explicitly controlled for climatic and landscape covariates. Results. In agricultural landscapes, we found that higher avian diversity leads to higher viral presence, driven by the dominance of highly competent synanthropic hosts. Conversely, a dilution effect emerges across the broader regional landscape where areas of higher ecological integrity allow for more complex and functionally diverse avian communities. Furthermore, we identified significant vector-mediated regulation, where high abundances of mammophilic vectors effectively suppress viral prevalence through larval competition. Conclusions. Our findings suggest that the dilution effect is a property of intact ecosystems which can be lost, or even locally reversed, in anthropogenically altered environments. Because such habitat degradation fundamentally alters zoonotic transmission dynamics, landscape planning must prioritize ecological restoration. Ultimately, embedding these practices into One Health strategies represents a proactive approach to mitigating disease emergence.

The exchange of energy and organisms across habitat boundaries links aquatic and terrestrial ecosystems and sustains ecosystem functioning. Although disturbance may disrupt these linkages, the mechanisms at play remain poorly understood. Here, we investigated the extent to which flow intermittency may disrupt riparian-aquatic ecosystem linkages by altering consumer communities in the recipient ecosystem or by altering resource quality in the donor ecosystem. We ran an experiment in an intermittent river network in California, focusing on a critical forest-to-river subsidy (organic matter in the form of leaf litter), its transformation, and its reciprocal benefit (aquatic insect production). Using three riparian species (willow, cottonwood, and oak) at sites spanning a gradient of flow permanence, we quantified intraspecific plasticity in leaf traits (specific leaf area, nitrogen and phosphorus concentrations, and {delta}13C), measured decomposition rates, and estimated the secondary production of aquatic shredders (Plecoptera). Across all leaf species, decomposition rates were 16-36% lower at intermittent than perennial sites, an effect largely driven by intraspecific leaf trait plasticity rather than changes in consumer abundance. At high flow intermittency, willow experienced water stress (enriched {delta}13C) and reduced specific leaf area, while cottonwood showed primarily stoichiometric responses (reduced leaf nitrogen and phosphorus). Despite these divergent strategies, all species produced lower-quality litter at intermittent sites. Variance partitioning confirmed that initial litter quality uniquely explained 51.5% of variation in decomposition rates, more than double the contribution of invertebrate community metrics; and structural equation modeling revealed that both leaf traits and stonefly (Plecoptera) secondary production significantly predicted decomposition rates, with leaf traits exerting the stronger effect. Notably, stonefly secondary production was 37-98% lower at intermittent sites across leaf species. Because these insects later emerge as terrestrial adults, they provide a significant energy flux to riparian predators, and, thus, impoverished litter quality suppresses the reciprocal transfer of energy back to terrestrial food webs. As drought intensifies globally, the decoupling of terrestrial-aquatic linkages may begin in the riparian canopy.

1. Sandy beaches along urbanized coasts are increasingly managed through beach nourishment and hard infrastructure, yet these interventions often constrain natural dune-building processes. Along the Belgian coast, where much of the beach-dune interface is bordered by dikes, promenades and intensive recreation, strandline vegetation may provide an overlooked mechanism for retaining sand and initiating embryo dune development. 2. We assessed the potential for four pioneer dune plant species (Cakile maritima, Calamagrostis arenaria, Elymus farctus and Salsola kali) to establish, develop vegetation cover and contribute to sand accumulation along the Belgian coast. Using field surveys from 2017-2023, LiDAR-derived beach elevation and annual sediment dynamics, we modelled species occurrence and abundance/cover in low-disturbance reference zones and projected these relationships across the wider coastline. 3. Occurrence models identified where abiotic conditions allow plants to establish and persist until the late growing season, whereas zero-inflated abundance/cover models estimated expected vegetation development across environmental gradients. Predicted occurrence was widespread for several species, suggesting that the abiotic gradients modelled here are not the primary constraints on potential establishment across large parts of the coast. In contrast, expected abundance/cover showed stronger species-specific responses, particularly to sand accretion, indicating that sediment dynamics mainly affect post-establishment vegetation development rather than occurrence alone. 4. Independent field measurements of embryo dunes showed positive relationships between vegetation cover and local sand accumulation for all four species. When scaled using spatial predictions of potential abundance/cover, pioneer vegetation could retain substantial volumes of sand, with Cakile maritima contributing the largest share, followed by Salsola kali, Elymus farctus and Calamagrostis arenaria. Estimated volumes depended on assumptions about whether vegetation occurs as dispersed units or aggregated patches. 5. Synthesis and applications. Our results show that, even along a heavily urbanized and nourished coastline, abiotic conditions can support strandline vegetation and embryo dune initiation where disturbance is reduced. Management actions such as limiting trampling, adapting beach cleaning and protecting strandline vegetation could enhance the retention of nourished sand and support nature-based coastal defense. Rather than replacing engineered interventions, strandline vegetation may increase the efficiency with which available sediment is retained within the beach-dune system.

Connectivity is critical to sustaining endangered carnivores in speciose yet fragmented landscapes such as in the global south. Corridors to mitigate fragmentation are designed based on charismatic species or habitat-based approaches, but their multispecies effectiveness for maintaining functional connectivity remains poorly tested. We combined landscape genetic analyses across five sympatric carnivores - Panthera tigris, Panthera pardus, Prionailurus viverrinus, Felis chaus, and Melursus ursinus, to evaluate how landscape features shape functional connectivity in a globally important felid landscape. We then assessed the efficiency of existing tiger corridors and single-species surrogates for maintaining multispecies functional connectivity. Species exhibited contrasting responses to landscape variables, producing distinct resistance surfaces and connectivity corridors. Spatial similarity of connectivity between species pairs was highly variable (r = 0.14-0.93), but no single species effectively captured connectivity patterns of the broader carnivore community (maximum mean overlap of <0.7 across species). Moreover, genetically optimized corridors were at least 70% more efficient in capturing connectivity compared to existing tiger corridors, demonstrating mismatches between structural and functional connectivity. Our results highlight limitations of surrogate-based corridor planning and demonstrate that integrating multispecies functional connectivity can substantially improve conservation planning in human-dominated landscapes.

Protected areas cannot halt biodiversity loss in isolation; integrating them with surrounding human-dominated landscapes is critical. However, this integration is challenged by substantial landscape heterogeneity at their borders, hindering our understanding of cross-border changes in ecosystem service provision. We introduce a novel framework for characterizing these dynamics by analyzing ecosystem service gradients along protected area borders. For 16 protected areas in the French Alps, we assessed 12 ecosystem services using a mix of established biophysical models and novel connectivity-based models for mobile species. These were aggregated into three stakeholder-driven domains reflecting respectively rural, cultural, and urban management priorities. Automated polynomial regression analysis classified borders into five gradient types. The most common were 'Decreasing Gradients', representing a decline in ecosystem services outside the protected area, and 'Increasing Gradients', with the opposite pattern. Our analysis reveals these patterns are driven by specific landscape configurations, uncovering frequent trade-offs between the three management priorities, where, for instance, landscapes supporting rural priorities often degrade cultural and urban ones. We also identify key opportunities for synergies, by identifying areas where ecosystem services for all three priority domains increase simultaneously outside the protected area. This spatially explicit typology provides a powerful diagnostic tool for designing targeted interventions, such as prioritizing habitat restoration where ecosystem services decline or managing agricultural landscapes to mitigate conflicts across management priorities, supporting a more effective integration of protected areas into the wider landscape.

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species' range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species' distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

Aim: To forecast near-future arrivals of non-native terrestrial and freshwater vertebrates at the regional level. Location: Global (geopolitical regions worldwide, including countries and main administrative divisions). Methods: We compiled first regional record data and assembled functional and macroecological variables for 1,931 non-native vertebrate species. For each region, we identified recently arrived non-native species using retrospective windows of thirty and twenty years ending in 2015 (1986-2015; 1996-2015). We then fitted region-specific random-forest models classifying recently arrived species versus those not yet arrived using as predictors: (i) harmonised species traits (e.g., habitat, diet, body size and native-range attributes) and (ii) spread history, capturing time since first record elsewhere. Predictive performance was evaluated using leave-one-out cross-validation, comparing full models with trait-only and spread-only variants. We also assessed relationships between predictive accuracy, predictor importance, and the geographic positioning and trade connectedness of regions. Finally, we predicted region-specific probabilities of arrival for species not yet recorded. Results: Forecasting accuracy was consistently high across regions and taxa, with AUC values above 0.9 in more than half of the focal regions. Full models substantially outperformed models using either predictor set alone, and spread-history-only models typically exceeded trait-only models. Relative importance of spread-history predictors declined with geographic distance to the focal region, whereas predictability was lower in highly trade-connected regions. Predicted near-future high-risk arrivals were dominated by birds and freshwater fishes and showed strong regional structuring. A small set of species ranked highly across many regions (e.g., birds: Phasianus colchicus, Acridotheres tristis, Amandava amandava, Colinus virginianus, Corvus splendens and Lonchura malacca; fishes: Coregonus peled and Oreochromis mossambicus; mammal: Oryctolagus cuniculus), suggesting substantial unrealised spread potential. Main conclusions: Near-future regional arrivals of non-native vertebrates are predictable from spread history and species traits. This enables scalable, updateable regional watchlists to support prevention, early detection and horizon scanning.

Quagga mussels (Dreissena rostriformis bugensis) are ecosystem engineers that can alter nutrient cycling, benthic-pelagic coupling, and food-web structure in deep lakes. Although their invasion trajectories are well documented in the Laurentian Great Lakes in North America, depth-specific population dynamics remain poorly resolved in recently invaded European perialpine lakes. We analyzed five annual lake-wide surveys (2021-2025) from 54 stations spanning 2.4-253 m depth in Lake Constance to quantify changes in quagga mussel density, biomass, and shell-length distribution. Contrary to expectations of lake-wide exponential growth, shallow-water populations (< 20 m) showed no significant increase during the study period and appear to have reached carrying capacity before monitoring began. In contrast, densities increased monotonically at intermediate depths (40-125 m), indicating ongoing expansion into deeper strata. Mean shell length declined with depth, and size distributions in shallow waters shifted toward larger individuals, consistent with a transition from active recruitment to somatic growth of established mussels. Compared with the Laurentian Great Lakes, Lake Constance already has substantially higher shallow-water biomass, whereas deeper invasion trajectories are broadly similar. These results show that quagga mussel invasion in deep European lakes can combine rapid littoral saturation with slower profundal expansion, complicating direct transfer of predictions from the Great Lakes. Continued depth-stratified monitoring will be essential for anticipating future ecosystem effects in perialpine lakes.

The global coral reef crisis has prompted restoration initiatives worldwide. Targeting the coral larval stage is among the most scalable approaches as recruitment operates over large spatial scales. It thus represents one of the best levers for coral population recovery. Active coral larval seeding has shown considerable success, and passive substrate engineering has emerged as a promising complementary strategy. Coral settlement modules featuring helix recesses have increased settlement and survival by up to 80-fold on small experimental units, but whether these results translate to tools deployable at the scale of thousands of units, remains yet an open question. Here, we transferred structural features from successful experimental coral settlement designs into production-ready concrete modules to (i) evaluate coral recruitment on five designs at four reef sites differing in flow regime and coral cover over one year; (ii) compare production-scale performance against experimental clay modules and natural reef substrate; and (iii) identify key parameters for large-scale production. The helix recess geometry of coral settlement modules outperformed the featureless control design approximately 20-fold and exceeded natural reef recruitment at least 3- to 32-fold. The helix features were successfully transferred from experimental clay to production-scale concrete modules, yielding comparable settlement densities when standardized to crevice length, which proved to be the biologically relevant unit of available habitat. Production feasibility was demonstrated by producing 690 modules for deployment on a hybrid reef on the west side of Oahu, Hawaii. The passive coral larval recruitment approach presented here could substantially improve the logistical and economic feasibility of large-scale coral reef restoration. This approach requires neither coral larval rearing, handling, nor coral fragmenting, and is compatible with active larval seeding where genetic diversity or larvae supply are limiting factors. The coral settlement modules can be cast in standardized concrete molds at precast facilities. Modules have demonstrated consistent coral recruitment enhancement across reef environments with contrasting flow and coral cover. Deploying mixed arrays of helix-recess structures with designs offering multi-level complexity and three-dimensional rugosity maximizes outcomes for coral, fish, and invertebrate communities simultaneously. Site selection is the most critical deployment decision and should consider larval supply, hydrodynamics, and substrate stability which drive recruitment outcomes more than design choice alone. The modules offer a range of application potential, ranging from integration into existing coastal infrastructure over stand-alone reef restoration approaches, to substrate-consolidating interconnected arrangements.

The guano of insectivorous bats holds ecological information that can be assessed non-invasively to characterize the gut microbiome and diet, alongside environmental microbes and pathogens of conservation concern. Despite this potential, how guano communities change during decomposition remains understudied, particularly inside anthropic roosts rather than caves. In this study, guano from little brown bat (Myotis lucifugus) colonies was sampled monthly across the summer maternity season from three sites across two locations in Connecticut, USA, at fresh deposition and at 4, 8, and 12 weeks following deposition. Resolving these cross-kingdom signals required five workflows: short-read 16S and ITS2 amplicon sequencing (Illumina) for bacterial and fungal profiling, long-read CO1 metabarcoding (Oxford Nanopore) for arthropod diet in fresh samples, long-read shotgun metagenomics for viral identification in aged samples, and targeted qPCR for organisms of bat, human, and forest-health concern. Fresh guano generated a consistent bacterial signal across sites, whereas fresh fungal communities differed by site. Responses to decomposition depended on roost setting: exterior sites lost fungal diversity and shifted toward environmental aerobes over time, while the interior roost retained the fresh sample profile. Dietary composition varied temporally, was dominated by Diptera, and included the invasive emerald ash borer (Agrilus planipennis). Pseudogymnoascus destructans, the causal agent of white-nose syndrome, occurred in fresh and aged samples at all three sites but persisted for 12 weeks only at the interior roost, where antifungal bacterial taxa were depleted. Long-read shotgun metagenomics of aged guano recovered roughly 100 viral species, predominantly bacteriophages, alongside non-bacteriophage mastadenoviruses associated with humans, bats, and other mammals. These results show that anthropic structures influence the trajectory of guano microbiome succession, and that maternity colony guano enables non-invasive assessment of environmental pathogens, bat diet, and bacterial and fungal communities.

Waterbirds serve as important indicators of both aquatic and terrestrial ecosystem health, making effective monitoring essential for tracking population health and identifying potential causes of decline. Drones have provided opportunities to overcome historic waterbird monitoring challenges, but the expertise and time required for manual image analysis creates a major bottleneck. Recent advances in deep learning-based object detection have enabled rapid, automatic detection of features in complex ecological imagery, though applications have largely been limited to single-species colonies, and practitioners lack quantitative comparisons of annotation time and accuracy across different levels of automation. We systematically compared four waterbird monitoring approaches using identical survey areas from Chester Island, a mixed-species colony in Matagorda Bay, Texas, in 2025: (1) traditional ground-based counts, (2) manual drone imagery-based counts, (3) computer-assisted counts using pre-annotations from an object detector with manual human verification (Human+ML), and (4) fully automated counts using object detector annotations (ML-only). We trained a YOLOv10 object detection model on manually annotated imagery of Chester Island in 2021 and applied it to the 2025 imagery. Manual drone annotation detected 6,530 birds in 40.5 hr and served as the primary reference standard. Human+ML detected 5,826 birds (89% of manual) in 7.7 hr, an 81% reduction in annotation time. ML-only detected 5,679 birds (87% of manual) in approximately 46 min, a 98% reduction. Ground counts recorded 5,868 birds (90% of manual). Detection generalized well across species while classification depended heavily on training data and morphological distinctiveness. The Human+ML workflow emerged as a practical middle ground, providing practitioners with empirical data to evaluate partial versus full automation strategies based on monitoring objectives.

Agroecosystems are dynamic ecosystems, constituted by patches of vegetation and agricultural use, where biodiversity is shaped by spatial and temporal variability. While most studies have focused on spatial composition and configuration, the role of temporal variability remains poorly understood. Yet, temporal dynamics can strongly modify species composition, abundance, and persistence in ecological communities. Temporal variability is particularly relevant in agroecosystems with rainfed agriculture where environmental conditions shift dramatically between rainy and dry seasons. In this paper, we assess the role of temporal variability on biodiversity maintenance in an agricultural matrix using a metacommunity model that simulates an agricultural landscape under rainfed conditions, that is, with abrupt seasonal changes in the agricultural patches. This model couples a local community network dynamic with a migration dynamic and is based on empirically documented features of rainfed agricultural matrices. Our results show that temporal variability provides new opportunities for species to recover from low densities. However, the effect of temporal variability is not straightforward. It depends on the initial and final conditions, the migration and mortality rates and the intensity of temporal variability. Overall, our findings highlight the need to further investigate temporal variability to better understand its role in shaping biodiversity in agricultural landscapes.

ContextArtificial light at night (ALAN) has profound impacts on individual organisms and entire communities. Still, humans tend to underestimate the true biological (spatial) footprint of ALAN, in part because of our limited sensitivity to light compared to other organisms. ObjectivesWe sought to demonstrate how far ALAN can reach into dark spaces at levels that can impact organismal behavior and physiology using a fundamental physical law, the inverse square law. MethodsWe created a spatially explicit model of light spread on real landscapes, parameterized using increasingly available landscape-scale vegetation data to account for attenuation through forests and blocking by topographic relief. ResultsLighting types common in rural areas can produce biologically important effects more than 1 kilometer from the source, and effects of large lights might stretch 3 kilometers or more. The footprint of a light is determined by the complex and multidimensional interaction between characteristics of the light itself and the environment. For example, attenuation through a dense forest might decrease the footprint of a light more than 90% compared to the same light on a grassland. In complex environments, even small changes in light placement and characteristics can lead to large changes in the biological footprint of the light. ConclusionsDesigners and land stewards must account for lighting type, brightness, directionality, and reflected light to create ecologically responsible lighting. Vertical vegetation and topography strongly influence the propagation of biologically detrimental light, and environmental context is vital when planning and installing lights to minimize the biological impacts.

In order to feed a growing global population without silencing nature, conceiving agricultural management strategies reconciling yield and conservation goals is key. Using numerical simulations of a metacommunity model, we explore the possibilities for compromise offered by spatial management strategies of farmed areas. Each strategy is characterized by its farming intensity, the proportion of farmed lands and their spatial aggregation. We show that achieving equitable yield-biodiversity compromise is difficult. While conciliatory strategies offering top yield and biodiversity are typically not possible, accepting slightly lower yields (ie, "Pretty Good Yield strategies") allows to recover substantial biodiversity. Such reconciliation possibilities are limited for species with small dispersal. Yield increases mainly through farmland expansion, whereas farming intensity strongly influences biodiversity, increasing it at low intensity before decreasing with further intensification. Finally, we demonstrate that reconciliation is easier if agricultural production relies on biodiversity through ecosystem services.