Landscape Ecology

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.

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.

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.

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.

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.

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.

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.

Residential greenness has been associated with reduced heat-related illness, yet the specific role of greenspace morphology at the neighborhood scale remains insufficiently understood. This study quantified the relationship between heat-related illness and multiple dimensions of greenspace morphology using an eight year (2016-2023) unbalanced panel dataset comprising 19,021 block group year observations across 2,427 census block groups in Arizona, USA. One meter high resolution National Agricultural Imagery Program aerial imagery was classified to calculate greenspace percentage, number of greenspaces, average size, shape complexity, connectedness, and distantness, at the block group level. We applied conditional spatial autoregressive models with a negative binomial distribution to estimate associations between each morphology metric and yearly heat-related illness counts, adjusting for sociodemographic and geographic covariates. We found higher greenspace percentage, aggregation, shape complexity, connectedness, and density were consistently associated with lower heat-related illness risk. A one standard deviation increases in shape complexity corresponded to a 12.4% decrease in expected heat-related illness counts (IRR=0.876, 95% CI: 0.834-0.921). Similarly, increases in greenspace percentage (14.6% decrease; IRR=0.855, 95% CI: 0.827-0.885), number of greenspace patches (3.7% decrease; IRR=0.963, 95% CI: 0.937-0.990), average size (4.5% decrease; IRR=0.955, 95% CI: 0.923-0.989), and connectedness (5.5% decrease; IRR=0.945, 95% CI: 0.918-0.972) were all protective. In contrast, larger inter greenspace distances were associated with increased heat-related illness risk (6.1% increase; IRR=1.061, 95% CI: 1.033-1.091). Our findings highlight the critical importance of multiple dimensions of greenspace morphology in mitigating heat-related health risks. These results suggest that heat reduction planning with greening initiatives should consider not only the amount of greenspace but also its spatial configuration to maximize cooling and result in health benefits.

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.

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.

AO_SCPLOWBSTRACTC_SCPLOWMountain gradients facilitate our understanding of species range limits, competition dynamics, stress-resilience trade-offs, and determinants of vegetation zone boundaries. Forest compositional models often use altitude as the main predictor, a proxy for temperature that is defensible where floristic transitions are gradual and climate relationships are linear. However, mountains with distinct assemblages, representing tropical gradients or areas with complex biogeographic history, require a modeling framework that reflects non-linear dynamics or interactions between environmental factors, including outlier events (rather than mean conditions). Our study system encompasses both tropical and temperate forests along a broad ([~]3000 m) altitudinal gradient, positioned within a narrow latitudinal band (< 1{degrees}) and composed of mature, continuous forest in the Bhutan Himalaya. To represent the breadth of climatic conditions experienced over a trees lifetime, we used a Bayesian modeling paradigm and integrated multi-generational field knowledge to develop a priori hypotheses and informed priors, with consideration of monsoon seasonality and possible ecophysiological thresholds. Our approach followed three stages (the Pattern, the Mechanism, the Test). Specifically, we interpolated microclimate data and derived custom metrics based on thermodynamics, propagating uncertainty into subsequent models to test whether climate posteriors outperformed altitude in explaining growth form partitioning. For spatial patterns, we identified six distinct vegetation zones (encompassing 145 species from 57 families), with a mid-gradient peak in richness at the tropical-temperate transition zone, and convergence of deciduousness at either end of the gradient. For individual growth forms, abundance was tied to different ecological mechanisms, explained by adaptations to climatic stressors and competition trade-offs. For instance, evergreen broad-leaved dominance was linked to ephemeral cloud immersion, whereas tropical deciduous species were affiliated with higher vapor pressure deficit at lower altitudes. Most importantly, compositional (between-group) models showed that the interaction between frost events and fog probability (air saturation prior to the dry season) governed growth form partitioning more than any single factor; temperate deciduous species, confined to a narrow altitudinal band, exemplified this finding. Our methodological approach is transferable to other data-sparse mountain systems, and our results highlight the vulnerability of unique habitat types and montane endemics under climate change scenarios that alter the fog-frost dynamics. Second abstract in DzongkhaTo see the second abstract in Dzongkha, the official language of Bhutan, please visit our Zenodo site: https://doi.org/10.5281/zenodo.19081441.

A majority of stream restoration efforts in central Europe focus on streams that are less than five meters wide. Restoration aims to increase structural complexity, thereby enhancing habitat heterogeneity, promoting biodiversity, and reestablishing aquatic-terrestrial linkages that can drive responses in adjacent terrestrial communities. However, the effects of small stream restoration on terrestrial biodiversity remain poorly understood because research focuses mainly on large rivers. Here, we investigated the effects of restoration on the structural complexity of the stream channel as well as the terrestrial habitat and plant diversity on a local and landscape scale across 55 small streams in an agricultural landscape. We compared restored stream sections with non-restored ones that were similar to the conditions before restoration. We also assessed how restored sections changed over time since restoration. Restored stream sections showed a higher stream structural complexity and habitat diversity, both of which are targets of active restoration measures. Restoration also increased riparian plant diversity, both directly and indirectly through structural complexity and habitat diversity. Although time since restoration did not influence structural complexity, it drove successional changes in plant communities that became increasingly associated with wetland habitat conditions. Our results demonstrate that small stream restoration effectively increases floodplain habitat and plant diversity in agricultural landscapes, primarily by enhancing water availability in the floodplain. Restoration actions on small streams support biodiversity if they improve stream channel complexity, connect the stream with its floodplain, and create floodplain habitats.

Rift Valley fever (RVF) is a mosquito-borne disease that can cause severe illness and death in both humans and livestock. Since 2016, Uganda has experienced recurrent but localized RVF outbreaks concentrated in the countrys southwestern region. The ecological drivers of this emergence remain unclear, as outbreaks have occurred throughout the year and show little association with meteorological patterns. We evaluated whether crop cultivation, particularly banana cultivation, is associated with RVF outbreak occurrence after controlling for likely confounders. We conducted a longitudinal study of human-inhabited 5 x 5 km grid cells across southwestern Uganda from 2016-2024. Annual Sentinel-2 satellite imagery composites were used to classify land cover into banana, coffee, ground crops, and non-crop categories, and the proportion of each land type was calculated for every grid-cell year. Because land cover proportions are compositional, isometric log-ratio transformations were used to estimate the independent effects of each land type. Confounding was addressed through propensity weighting, and crop substitution effects were estimated using g-computation. Banana land cover was the only land type consistently associated with increased RVF outbreak likelihood. In grid-cell years with low baseline banana cover, a 10-percentage point substitution from other land classes into banana was associated with a 1.64-fold increase in the odds of an RVF outbreak (95% CI: 1.17-2.29). In a simplified banana-only model, each 10-percentage point increase in banana cover was associated with a 1.21-fold increase in outbreak odds (95% CI: 1.02-1.43). Holding banana cover constant, substitutions among coffee, ground crop, and non-crop land showed weak or null associations. These findings suggest that banana cultivation may be an important ecological feature influencing RVF transmission dynamics and outbreak risk in southwestern Uganda. Author SummaryRift Valley fever (RVF) is a mosquito-borne disease that affects both humans and livestock and has caused repeated outbreaks in southwestern Uganda since 2016. While rainfall and flooding are often linked to RVF outbreaks elsewhere, Ugandas recent outbreaks have occurred across seasons and are not well explained by weather patterns alone. We investigated whether agricultural land use could help explain where outbreaks occur. Using satellite imagery from 2016-2024, we measured the amount of banana cultivation, coffee cultivation, ground crops, and non-crop land across southwestern Uganda and evaluated their association with RVF outbreak occurrence. We found that areas with greater banana cultivation were consistently more likely to experience RVF outbreaks, even after accounting for environmental and demographic factors. In contrast, coffee, ground crops, and non-crop land showed little evidence of an independent association with outbreak risk. These findings suggest that banana cultivation may create ecological conditions that favor RVF transmission. Rather than indicating that bananas themselves cause disease, the results point to banana-growing landscapes as potential environments where interactions among mosquitoes, livestock, and humans may increase transmission opportunities. Understanding these local ecological drivers could help improve surveillance, risk assessment, and prevention strategies for RVF in Uganda and other endemic regions.

Various hypotheses have been proposed to explain why some species persist or even flourish in urban areas. Yet, despite its central role in determining when and where animals encounter resources, disturbance, and risk, movement behaviour remains an overlooked mechanism of urban success. In urban areas, human activities are strongly periodic, i.e. predictable in space and time. This may favour species able to adjust their behaviour to predictable cycles of resources and risks in space and time. Here, we tested this hypothesis and tracked movement behaviour along an urbanisation gradient in three mammal species with different urban success: red fox (Vulpes vulpes), an urban dweller; raccoon (Procyon lotor), an invasive urban dweller; and wild boar (Sus scrofa), an urban utiliser. We analysed periodicity in movement behaviour and investigated whether increasing urbanisation is associated with periodic reorganisation of activity timing, space use, and further analysed alterations in habitat selection along the urbanisation gradient. Our results show that foxes aligned their movement behaviour with human activity, having stronger day-night contrasts and more repeatable space use than their rural counterparts. Urban raccoons showed a contrasting strategy; they were more active during the day, without changes in their movement routines under increasing urbanisation, suggesting a flexible strategy that explains their urban success. In contrast, wild boars reduced routine movement behaviours with increasing urbanisation, consistent with their occurrence in less predictable suburban environments and avoidance of city centres. In summary, our results suggest that movement behaviour may be a key mechanism enabling animals to persist in cities, revealing distinct behavioural strategies for coping with urban environments.

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.

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.

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.

Abstract To identify countries with potential weaknesses in respiratory public health protection, we characterised shared hotspot patterns across three major respiratory infectious diseases and assessed whether the resulting shared hotspot scores were associated with worse COVID-19 outcomes. A Bayesian multivariate shared-component spatiotemporal model was fitted to data from 204 countries over 1990-2023 using Global Burden of Disease 2023 estimates to derive a shared hotspot score for each country. Generalized estimating equation negative binomial models were then used to examine associations between the shared hotspot score and COVID-19 incidence and mortality over 2020-2023. The shared hotspot score showed substantial cross-country heterogeneity, with the highest values concentrated in sub-Saharan Africa, South Asia, and Southeast Asia. Tuberculosis showed the strongest contribution to the shared spatial component (lambda = 1.657, 95% highest density interval: 0.883-2.506). Higher shared hotspot scores were significantly associated with both higher COVID-19 incidence (incidence rate ratio = 1.6783, 95% confidence interval: 1.4564-1.9340; p = 8.308 x 10^-13) and mortality (incidence rate ratio = 1.7436, 95% confidence interval: 1.5061-2.0186; p = 9.912 x 10^-14). Countries with persistently high co-occurrence of common respiratory infectious diseases also experienced worse COVID-19 outcomes, suggesting that the shared hotspot score may inform preparedness-oriented surveillance and resource allocation for future large-scale respiratory epidemics or pandemics.

This study investigates changes in habitat connectivity and meta-ecosystem resilience between 1817 and 2022 along a 150 km section of a large European river (Danube) and its adjacent floodplains. The analysis was based on a time series of functional habitat networks (graphs) constructed from historical records and remote sensing data, integrating habitat suitability and dispersal modes of functional organism groups. The results indicate that overall habitat availability declined by about 50% since 1817, leading to the near-complete loss of functional connectivity among dynamic habitats by 1910. Less dynamic habitats persisted or expanded but became functionally less connected. Connectivity-based habitat classification further revealed four distinct functional connectivity clusters and the near-complete loss of an originally dominant, dynamic, and highly connected habitat type. Furthermore, the results indicated a fundamental loss of meta-ecosystem resilience. This development was reflected by increased spatial modularity among functionally similar habitats and by reduced layer dissimilarity and structural robustness in multilayer networks representing the spatial habitat structure and functional habitat connectivity across different functional organism groups.

Tropical dryland ecosystems are highly biodiverse and fragmented and are experiencing significant anthropogenic and climatic changes. With increasing extremes in temperature and precipitation, coupled with significant alteration, these ecosystems are at greater risk of increased exposure and vulnerability to climatic change; however, little work has quantified the climatic shifts occurring within these ecosystems globally. Here, we aim to fill this gap by using the ERA-5 reanalysis and CHIRPS precipitation data to quantify changes in essential climatic variables in tropical drylands since 2000. Overall, we find that regional pressures differ, with tropical dry forests, savannas, and shrublands becoming hotter and drier in the Neotropics and parts of the Afrotropics and Australasia. By contrast, the tropical dry forests in the Indomalayan, Oceania, and Nearctic are experiencing hotter and wetter conditions. Globally, though, these ecosystems are experiencing more change than the global average, suggesting they may be approaching tipping points in their resilience, ultimately shrinking the area where they can survive.