Conservation Science and Practice

Native vegetation protection is a key strategy for delivering both biodiversity and climate benefits, and protected areas have been widely adopted to keep tropical biomes standing. Yet deforestation is driven by interrelated environmental and social factors, and the effectiveness of protected areas varies considerably across space. Here, we evaluated the impact of 802 protected and conserved areas in the Brazilian Amazon on preventing vegetation loss and avoiding carbon emissions over the past 40 years using statistical matching to address the location bias of protection. We found that protected areas were effective throughout the study period, reducing the probability of deforestation per km2 by an average of 0.5 percentage points per year. While the Amazon biome lost 14% of its native vegetation between 1986 and 2024, protected areas prevented the deforestation of 290,436 km2, nine times their actual internal loss. They also stored 45,336 Mt of carbon in 2016 (61% of the Amazon stock) and prevented the emission of 7,300 Mt of CO2 by 2024. Deforestation inside the areas and remoteness reduced their impact, while areas that were initially more preserved were more effective. Area size and age had no influence over impact once we analyzed the amount of avoided deforestation per size and age. Impact also varied across Brazilian states, highlighting the role of regional context. All three protection categories (conservation units, indigenous lands, and quilombola territories) showed a positive mean impact, indicating that each, in aggregate, contributes to reducing deforestation. These findings provide robust evidence of the substantial role of Amazonian protected areas in habitat conservation and climate mitigation, while underscoring that this contribution remains undervalued. We advocate for strategically expanding protection to areas of greatest potential impact, and for securing adequate funding to ensure protected areas can fulfill that potential.

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

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.

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.

Aims: Species' distributions are determined by the interplay between ecological niche and dispersal ability, constrained by biogeographical barriers. Bald-headed uakaris (Cacajao spp.) are highly specialized primates often associated with seasonally flooded forests. In this study, we used ecological niche models to assess changes in habitat suitability and geographic distribution of uakari species under future scenarios. Location: Western Amazonia. Methods: We integrated ecological niche models, current deforestation data, and dispersal ability to estimate habitat suitability under two Shared Socioeconomic Pathway (SSP) scenarios: intermediate (SSP2-4.5) and very high (SSP5-8.5) greenhouse gas (GHG) emissions. Results: Our models project shifts in suitable conditions for all species. Three of the five species are projected to experience substantial reductions ([&ge;]62%) in suitable habitat conditions within their current ranges by 2050 under both future scenarios. Across the western Amazonia, up to 219,189 km2 and 211,276 km2 of land are projected to be unsuitable within the uakari ranges under the intermediate and very high emissions scenarios, respectively. This is particularly relevant for C. calvus, C. rubicundus, and C. ucayalii. At the species level, the uakaris may lose between 343 km2 and 84,531 km2 of their ranges in the intermediate scenario and 858 km2 and 76,216 km2 in the very high scenario. Shifts in suitability due to climate change are expected to vary from 6 to 191 km in the intermediate scenario and from 5 to 168 km in the very high scenario. Furthermore, the uakaris may lose between 0.5% and 8% of their current ranges due to deforestation in all scenarios. Main conclusions: Our findings reveal a high sensitivity of the uakaris to climate change impacts. It is projected that all species may experience contractions in the suitable areas and spatial suitability within their ranges by 2050, underscoring climate change as a relevant threat to these taxa.

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.

Nepal's rangelands provide multiple benefits, including support for pastoral livelihoods and alpine biodiversity, regulation of water and soil nutrients, and sequestering carbon. Climate change and anthropogenic pressures are altering these rangelands, leading to vegetation and biodiversity change. However, national-scale assessments of rangeland change are limited in Nepal. This study quantified rangeland changes at multiple spatial scales and assessed the climatic and non-climatic drivers of rangeland change. About 80.7% of Nepal's high-altitude rangeland (> 2,000m) outside protected areas showed no significant change. Among areas exhibiting significant annual maximum NDVI trends, 383,281 ha (18.6%) showed positive and 14,702 ha (0.7%) showed negative trends, corresponding the ratio of increase in vegetation greenness and decline in vegetation greenness to 26:1. Climate predicted positive trends covered 627,184 ha (30.5%), whereas residual trends caused by non-climatic drivers covered 94,656 ha (4.6%). Climate induced negative trends covered 47,609 ha (2.3%) while residual trends were observed in 6,260 ha (0.3%). Negative trend pixels were concentrated mainly within the 3,000 to 5,000 m elevation band, with Karnali Province recording the highest proportional climate predicted decline in vegetation greenness (3.4%). At the municipality scale, rangeland change showed no significant relationship with grazing pressure derived from gridded livestock data, suggesting that grazing pressure alone did not explain the non-climatic vegetation signal. These spatially explicit, nationally consistent results identify where rangeland change is occurring and help distinguish climatic and non-climatic drivers of rangeland vegetation change, providing evidence to support targeted rangeland management under Nepal's federal governance structure.

Camera trap networks such as Snapshot Safari have generated millions of labelled wildlife images across Africa, enabling the training of deep learning models for automated species classification. However, deploying models trained in one African region to another remains poorly understood. To the best of our knowledge, this study presents the first systematic evaluation of geographic domain shift within the African continent for wildlife camera trap species classification, using the Machine Learning sub-field of Artificial Intelligence. We use three model architectures, each interacting with Snapshot Serengeti in a different way: BEiTV2is fine-tuned on Serengeti images as a supervised baseline; DINOv2 with FAISS uses Serengeti images as a retrieval index without any weight updates; and BioCLIP is a true zero-shot foundation model that receives no Serengeti training data at all. All three are then evaluated on two Southern African test sets, Snapshot Kgalagadi and Snapshot Kruger, as well as on locally collected wildlife photographs from Botswana. We conduct eight experiments covering in-domain baselines, cross-dataset transfer, data scaling, MegaDetector preprocessing, grayscale vs. colour image conditions, and per-species transfer analysis. This work provides the first empirical characterisation of intra-African domain shift across both supervised and zero-shot architectures, and offers practical guidance for conservation AI practitioners who need to deploy models across the diverse ecosystems of Southern Africa without collecting new labelled data.

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.

Italy, one of Europe's most biodiverse countries, is expected to undergo landscape-wide nature recovery thanks to the EU Nature Restoration Regulation. National red lists represent critical instruments for informing conservation strategies at finer geographic resolutions and prioritizing taxa of national importance; yet the taxonomic completeness of Italian red lists remains unquantified in relation to national biodiversity. Equally, no systematic evaluation has been conducted on the representation of threatened and endemic Italian taxa within European and international conservation directives and treaties. We present the first comprehensive review of threat status and policy inclusion of Italian biodiversity, encompassing animals, plants, fungi, lichens, and algae. We cross-referenced national species checklists with Italian, European, Mediterranean, and global IUCN red lists, alongside policy annexes from the Birds and Habitats Directives, the Bern and Barcelona Conventions, and CITES. Our dataset comprised 76,845 taxa, of which 8,389 are endemic; yet red list assessments exist for only 10% of this total (7,349 taxa, including 1,700 endemics). Conservation policy coverage is even more restrictive: only 1,346 taxa are listed under at least one legislative instrument, with only half of these classified as threatened. This constitutes a compounding double bottleneck with most of the Italian biodiversity remaining both unassessed and unprotected and systematically biasing conservation policy toward an unrepresentative fraction of national biodiversity. We recommend accelerated national assessments and urgent establishment of a national biodiversity priority list founded on transparent prioritization protocols. This would complement ecosystem-based interventions mandated by the Nature Restoration Regulation while correcting for vertebrate-centred biases.

The biodiversity crisis is exacerbated by persistent gaps in taxonomic, geographic, and conservation knowledge. This study provides a comprehensive assessment of Linnean, Wallacean, and conservation shortfalls in Rivulidae (Cyprinodontiformes), one of the most diverse families of Neotropical freshwater fishes. To this end, an extensive dataset was compiled, comprising 494 valid species, 51 synonyms, 3,419 occurrence records, and information on life cycle, distribution, and conservation status. The Linnean shortfall remains open: after 1975, the rate of species description increased sharply, and estimates indicate that 103 species remain undescribed (95% CI: 53-212). The year of species description was influenced by detectability and accessibility factors, with larger species, more widely distributed species, and species occurring in more densely populated areas being described earlier. The Wallacean shortfall was broad and spatially uneven: only 5.34% of the region was considered adequately sampled. The conservation shortfall was also substantial: 179 species are threatened with extinction, 69 species remain Not Evaluated, and 62 are Data Deficient. The mean time between taxonomic description and first IUCN extinction-risk assessment was 25.7 years. Moreover, 59.9% of species have no records within protected areas, including 69.3% of threatened species. These findings synthesize an urgent challenge: biodiversity knowledge and conservation shortfalls must be overcome simultaneously to protect species that are still being discovered, remain poorly documented spatially, and are restricted to habitats under intense anthropogenic pressure. The conservation of Rivulidae cannot wait for complete knowledge; action amid uncertainty is necessary to prevent both known and unknown species from disappearing.

AimBiodiversity-rich regions often lack the scientific infrastructure needed to document and curate their own biodiversity, creating inequalities in access to taxonomic reference material. We investigated how biological, institutional, and geopolitical factors shape the retention, extraction, and appropriation of reptile holotypes, the name-bearing specimens upon which species descriptions are based. LocationGlobal. TaxonReptiles. MethodsWe compiled a historical dataset of reptile holotype origins and destinations spanning 1758-2024 to reconstruct long-term patterns of retention and international specimen flows. We then quantified species-level holotype retention, holotype flows between country pairs, and country-level patterns of retention, appropriation, and network centrality for the period 1990-2024, and used generalised linear mixed models to assess the biological, institutional, and geopolitical determinants of these contemporary circulation processes. ResultsAlthough nearly 90% of reptile species described originated in the Global South, less than a quarter of their holotypes remain housed there. Historically, exported holotypes consistently outnumbered retained holotypes on a decadal basis until the early twenty-first century. Retention was promoted by local scientific capacity, institutional infrastructure, collector involvement in species descriptions, and environmental governance. In contrast, extraction was concentrated in highly endemic regions with limited scientific infrastructure and was associated with taxonomic revisions, socioeconomic interest, and disparities in political stability and colonial history. Appropriation of foreign holotypes was greatest in countries with high research investment, strong environmental governance, and historical geopolitical influence. Main conclusionsGlobal patterns of holotype circulation reflect a persistent geography of scientific inequality. The distribution of taxonomic reference material emerges from the interaction of retention, extraction, and appropriation processes, linking local biodiversity discovery to uneven global scientific capacity. Reducing these inequalities will require investments in taxonomic expertise, institutional infrastructure, and governance frameworks that promote more equitable stewardship of biodiversity knowledge and its material foundations.

O_LIMonitoring and limiting the spread of invasive species on islands requires efficient detection and population estimation methods. However, elusive species can be difficult to monitor using traditional methods, making autonomous approaches such as camera trapping and acoustic monitoring increasingly valuable. C_LIO_LIOn the island of Okinawa, Japan, the small Indian mongoose ( Urva auropunctata) threatens many native species since its introduction in 1910. Listed among the worlds worst invasive species, effective monitoring of U. auropunctata in Okinawa is critical. The Okinawa Environmental Observation Network (OKEON) uses camera traps to detect U. auropunctata, but success depends on precise placement. Though OKEON also includes a high-resolution acoustic monitoring programme, no audio classification model currently exists for U. auropunctata. Developing such a model could improve substantially our capacity to detect and manage the species. C_LIO_LIUsing sparse U. auropunctata vocalisations collected from camera trap videos, we built a lightweight Convolutional Neural Network distilled from a more complex model for classifying contact calls and alarm calls of U. auropunctata. Our distilled model performed similarly to the full model at detecting vocalisations from training data, but was considerably faster. C_LIO_LIWe applied the distilled classifier to [~]486 hrs of audio collected over eight years from southern Okinawa, where we successfully detected U. auropunctata a handful of times in each year of recording. In spite of strong model performance on test data, our model did not transfer well to unseen data, perhaps owing to the rarity of U. auropunctata calls and consequent small training dataset size, limiting its utility for ecological monitoring. C_LIO_LIPractical implication. The use of sparse audio data from camera trap videos to train an acoustic classifier had limited utility to detect the rarely vocalising U. auropunctata from passive acoustic monitoring data. We provide several recommendations for enhancing classifier performance to provide robust actionable insights into the distribution and spread of U. auropunctata, and aid targeted conservation efforts for Okinawas threatened biodiversity. C_LI

The rariphotic zone, typically spanning depths of approximately 130 to 300 meters, represents a key transition between light-dependent coral reef ecosystems and the aphotic deep sea. Despite its potential ecological importance, including its proposed role as a refuge for species exposed to climate-driven stress, rariphotic ecosystems remain poorly understood. In this study, we conducted a systematic review and synthesis of the scientific literature on these habitats from 1970 to 2025. Following the PRISMA 2020 protocol, we analyzed 185 studies to characterize the historical development of research, identify geographic and methodological biases, and assess shifts in research priorities over five decades.Our results show a marked increase in research effort over the last decade, driven in part by advances in underwater technologies such as Remotely Operated Vehicles (ROVs), Human Occupied Vehicles (HOVs), and Baited Remote Underwater Video Station (BRUVS). However, this growth remains uneven, with persistent biases toward benthic rather than pelagic studies and a strong concentration of research in geographically accessible regions. Multivariate analyses of research novelty indicate that technological innovation and the formal recognition of the rariphotic zone in 2018 corresponded with major structural shifts in literature. Although the rariphotic zone is now increasingly recognized as an ecologically distinct component of the reef continuum, it remains underrepresented in ecological theory and conservation frameworks. Future research should move beyond descriptive taxonomic mapping toward integrative, data-driven functional ecology, with particular emphasis on long-term monitoring and depth-stratified connectivity.

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.

Although a strand of scholarship on pandemic prevention flourished in the wake of the COVID-19 pandemic, a theoretically informed empirical analysis of global governance entrepreneurs and practitioner perspectives is lacking. This gap is salient given the need to consider the nuances, political realities, and feasibility of real-world governance practice, particularly with the recent adoption of the Pandemic Agreement under the World Health Organisation. In this paper, nexus governance and regime complex theory guides an analysis of recommendations for potential real-world governance responses for pandemic prevention from wildlife trade for human consumption elicited from global governance entrepreneurs and practitioners through semi-structured interviews and document analysis. Recommendations on future governance practice largely focused on strengthening coordination across various policy sectors to improve use of existing institutional arrangements, with particular emphasis on better integration of the biodiversity conservation policy sector within global pandemic prevention governance, as well as reform of the World Organisation for Animal Health and the Convention on International Trade in Endangered Species of Fauna and Flora. With governance deficits for prevention of pandemics emerging from the wildlife trade left by the now largely concluded Pandemic Agreement, a renewed research agenda on shared governance pathways becomes paramount.

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.

1. Ruby-throated hummingbirds (Archilochus colubris) exhibit flower preferences and readily visit human subsidies like feeders. However, foraging behavior and plant-animal interactions may vary across spatial, temporal, and landscape gradients. Despite the popularity and ubiquity of Ruby-throated Hummingbirds in the eastern U.S., there has never been a quantitative assessment of their flower preferences or feeder use across broad scales. 2. We investigated how feeder visitation, flower visitation, and flower trait preferences vary by latitude, season, and land use in the northeastern United States using over 6 million occurrence records of Ruby-throated Hummingbirds and flowering plants, >2,100 annotated hummingbird-flower interactions, and >2,700 feeder visit occurrences. 3. We found that hummingbird feeder use declined over the year, increased with latitude, and was higher in developed landscapes. Flower visitation increased over the year across all latitudes, with higher visitation in developed landscapes. Finally, we found that native plant use diverged between landscapes, such that the probability of visiting a native flower increased over time in non-developed land uses but declined over time in developed ones, demonstrating that hummingbirds track the advancement of native floral phenology and use non-native, cultivated flowers as a human subsidy due to either availability or preferences. 4. Our preference and network models revealed that while hummingbird-plant network structure was similar across landscapes, the composition of important taxa shifted from native, wild species like Monarda and Impatiens to non-native, cultivated species like Salvia. 5. Using trait-based models of flower visitation, we found that hummingbirds preferred native, tubular, and red/orange flowers fitting the hummingbird pollination syndrome despite visiting >260 different plant species. Red and orange flowers were preferred across all seasons, suggesting color may be a reliable signal of nectar availability across species and contexts. Native and tubular flowers were strongly preferred during the breeding season; however, preferences relaxed during spring and fall migration. 6. These findings reveal the consistent preferences of Ruby-throated Hummingbirds for native, tubular, and red/orange flowers, and underscore how spatial and temporal factors reshape foraging behavior and trait preferences. Our results also highlight the value of community-collected data in characterizing plant-pollinator interactions across broad spatial and temporal scales.

Mass mortality events (MMEs) create sudden pulses of carrion that can alter how vertebrate scavengers use carcass resources, including the frequency, duration, and timing of species-carcass contacts. These changes could have implications for pathogen transmission at the scavenger-carcass interface. We aimed to develop and apply a reproducible analytical framework for using camera-trap data to quantify transmission-relevant vertebrate activity at carcass sites under differing carrion biomass scenarios. We studied experimental carcass plots (single carcass ~43 kg; 'mass mortality' plots [10 carcasses, >350 kg total]; 6 of each) in Australia's alpine ecosystem. The framework integrated descriptive summaries (bipartite network analysis, Kaplan-Meier curves) and marked temporal point-process models to characterise structural and temporal dimensions of species-carcass activity. Mass mortality plots had greater overall visitation duration, occurring as sustained activity (50% of visitation event volume by day 17), compared with intense then rapidly declining activity at single carcasses (50% by day 8). Mass mortality plots also had higher predicted daily arrival probability and contact hours across most species, indicating an extended window for pathogen transmission. This framework provides empirically derived contact parameters for MME-related disease spread models using camera-trap data to identify potential transmission pathways at the scavenger-carcass interface.

ContextThe movement of vertebrate hosts across urbanized landscapes can play a key role in the transmission of direct-contact diseases. Understanding how wildlife hosts move in urban landscapes, and how transmission is affected by their landscape-constrained and disease-altered movements, is imperative for better predicting the spread of disease. ObjectiveWe assess how the movement of red foxes (Vulpes vulpes) according to landcover type, and their infection status, affect the spread of mange (caused by Sarcoptes scabiei) in an urbanized landscape. MethodsWe developed a mange transmission model (MTM) using an agent-based model to compare two movement behaviours of foxes in Scarborough (Ontario, Canada): random and landcover-based. We further assessed the effects of movement on disease transmission by considering the foxs infection status and comparing a range of movement probability scenarios. We quantified the number of effective contact events and the effective reproduction number (Re) according to each scenario. ResultsWe found that both landcover-dependent movement and infection status influenced the spread of mange within fox populations. The number of effective contact events and effective reproduction number Re was greatest when landscape heterogeneity was included in the model and foxes moved through paths of least resistance to movement, and when susceptible and infected foxes had an equal probability of leaving a fragmented habitat patch. ConclusionsOur findings suggest that mange spread may be accelerated along movement corridors in fragmented, heterogenous landscapes. As urban areas expand and remnant habitat within these is further lost and animals are relegated to fewer movement pathways, disease transmission may increase.