Landscape Ecology

AimHuman land-use has dramatically altered the amount, quality, and connectivity of habitat for species worldwide. Understanding how these changes affect individual species is essential for predicting the overall consequences of land-use change for biodiversity. LocationThe Caribbean island of Puerto Rico. Forest cover on the island increased from about 18 to 45% from the late 1940s to the early 2000s. MethodsUsing data on geographic distributions and functional traits for 454 tree species, we evaluated how gain of potential habitat was related to species-specific climatic associations and life-history strategies. We estimated species-specific potential habitat (climatically suitable and forested) with species distribution models and data on forest cover. We characterized each species niche breadth (the range of environmental conditions it occupies) and niche position (the environmental conditions it prefers) to compare with the conditions in reforested areas. ResultsSpecies with relatively more potential habitat in 1951 (climatically suitable and forested) also had relatively larger gains in potential habitat from 1951 to 2000. Species that tend to occupy conditions different from those common in reforested areas (i.e., more marginal habitats) gained relatively less potential habitat and species with broad environmental niches gained more potential habitat. Additionally, species with relatively acquisitive functional traits gained more suitable habitat than those with relatively conservative traits. Main conclusionsOur results show that Puerto Ricos reforestation preferentially increased habitat for species that (1) already had suitable habitat in the landscape, (2) tolerate a wide range of climatic conditions, and (3) exhibit fast, acquisitive functional strategies. These findings illustrate how land-use change in heterogeneous tropical landscapes can generate non-uniform habitat gains across species, potentially favoring generalist over specialist species and reshaping community composition.

Animal population control is widely used to mitigate conflicts between wildlife and agriculture worldwide. Structured, monitored removals are rare in South America, however, and their consequences for wildlife populations as well as their effectiveness in reducing crop damage are little understood. Using eight years of data from an experimental white-lipped peccary management program in an agricultural mosaic in the Brazilian Cerrado biome, we assess how structured, non-lethal removals affect both peccary demography and second-crop corn damage. Leslie removal models based on 6,619 captured individuals indicated that cumulative removals to approximately 85% of the initial population strongly reduced peccary abundance, with limited demographic compensation despite fluctuations in reproductive output. Corn crop damage, quantified with satellite imagery, declined over time and was correlated with peccary population size. Interannual variation in population growth and juvenile recruitment was poorly explained by climate, fire, or landscape composition. Source-sink dynamics likely play a role in maintaining healthy populations at the regional scale. Together, these results demonstrate that sustained and monitored ungulate removals can reliably reduce population size and agricultural damage, supporting coexistence between wildlife and food crop production in human-dominated tropical landscapes.

IntroductionHuman land-use intensification and the resulting habitat loss are primary drivers of insect pollinator declines. Habitat restoration offers a promising approach to counteract these declines, yet landscape-level evaluations of bee responses to restoration and management remain limited. We conducted a two-year, landscape-scale study in Wisconsin, USA, to assess how different intensities of tallgrass prairie restoration and management affect bumble bees (Bombus spp.). ObjectivesThis study aimed to determine whether (1) bumble bee abundance and diversity increase with assisted restoration, and (2) outcomes differ between low-(seeded only) and moderate-intensity (seeded and managed with prescribed fire) interventions. MethodsUsing catch-and-release surveys, we measured bumble bee abundance and diversity at 32 sites representing a gradient in restoration intervention: no intervention (unassisted recovery), low intervention, and moderate intervention. ResultsBumble bee abundance and diversity were higher at assisted restoration sites (low and moderate intervention) than at unassisted sites. Although both tended to be greater at moderate than low intervention intensities, these differences were not statistically significant. Bumble bee community composition also differed across intervention intensity, driven by shifts in dominant species (e.g., B. impatiens and B. griseocollis). Rarer taxa, including endangered and vulnerable species, occurred only at assisted restoration sites, with the largest populations at moderate intervention sites. Across all sites, bumble bee responses were strongly and positively associated with floral abundance, but not with semi-natural habitat in the surrounding landscape. ConclusionOur findings demonstrate that assisted grassland restoration can effectively increase bumble bee abundance and diversity, supporting its value as a conservation practice for pollinators. Implications for Practice: (1) Grassland restorations targeting plant communities can successfully support nontarget pollinators across a range of management intensities and landscape contexts. Adding seeds of pollinator-preferred plants could improve restorations with low floral abundance and diversity. (2) Management of existing restorations is important to maintain abundant floral resources and diverse pollinator communities. Because sites varied widely in prescribed fire use, our findings likely represent a conservative estimate of its benefits, and higher intervention intensity (e.g., repeated seeding, regular fire, mechanical or chemical shrub and invasive plants control) may further enhance outcomes for bumble bees.

Understanding behavioral differences between non-native and closely related endangered species could be important to aid conservation management. In volume 169 of Zoology, Bels et al. (2025) reported on their comparison of display-action-patterns (DAP) between native Iguana delicatissima and non-native iguanas present on islands of the Guadeloupe Archipelago in the Caribbean Lesser Antilles. Here, we address conceptual and methodological concerns about their work and reanalyze their data given our proposed corrections, primarily a literature-informed adjustment of their "species" category. We additionally utilize online videos from South American mainland I. iguana populations, from where the non-native iguanas in the Guadeloupe Archipelago originate, to better understand the different DAPs between native and non-native iguanas in the Guadeloupe Archipelago. Significant differences in DAP characteristics among "species" categories (native I. delicatissima, non-native iguanas, and hybrids) show that Bels et al. (2025) oversimplified their data analyses by merging all non-native populations into one group. This result indicates the presence of behavioral variation among subpopulations within widely hybridizing iguanid populations, which has been poorly studied. Additionally, videos from mainland populations across two major mitochondrial clades of Iguana iguana show that non-native iguanas on Guadeloupe retained DAP characteristics of those populations from which they originate. We discuss these findings in light of the proposed hypotheses put forward by Bels et al. (2025), of which two can be excluded. Overall, our reanalysis shows that studies focusing on characteristics within settings of complex hybridization in diverse species should acknowledge this complexity.

Mountain ecosystems face unprecedented pressures from anthropogenic activities and climate change, challenging the productivity of these vital habitats. In the Tien Shan mountains, understanding localized responses to these pressures is often hindered by the coarse spatiotemporal resolutions of available data. To address this, we combined high-resolution satellite imagery (1997-2021) to map land-cover dynamics in the Naryn oblast, Kyrgyzstan across a gradient of grazing intensities. We classified and quantified land-cover distribution over 24 years, investigating the roles of topography, elevation, and anthropogenic disturbances as drivers of change. Our results identify intermediate elevations, high degrees of disturbance, and the interaction between the two as the primary contributors to recent transitions in grassland, forest, and barren habitats. By integrating Landsat analysis-ready data, European Space Agency WorldCover dataset and digital elevation models at fine spatial scales, we provide valuable contemporary and historical landscape and habitat-level insights and a high-resolution framework for disentangling climate-driven shifts from land-use impacts. These findings highlight the urgency of localized management in remote, data-poor regions where rapid environmental change threatens both biodiversity and pastoral livelihoods. Our work serves as a critical baseline for characterizing the adaptability of semi-arid mountain rangelands under escalating global and regional pressures.

Reliable freshwater access drives terrestrial wildlife movements and habitat use globally. The small, rain-fed seasonal pools critical for dryland wildlife persistence are vulnerable to rising temperatures and unstable precipitation regimes projected under climate change. In southern Africa, which is expected to warm rapidly by 2100, the drying and disappearance of surface water may cause a breakdown in seasonal migrations of large, area-sensitive, and water-dependent wildlife species. Furthermore, the disappearance of ephemeral water may concentrate wildlife around remaining surface water, increasing resource competition and human-wildlife conflict. An accurate understanding of the dynamics and drivers of seasonal surface water will therefore be critical to wildlife and human health as climate change intensifies. Here, we present a framework and empirical analysis of fine-scale surface water mapping in the 520,000km2 Kavango Zambezi Transfrontier Conservation Area (KAZA), the worlds largest terrestrial conservation area. From 2019-2025, we implemented Otsu thresholding on median Automated Water Extraction Index imagery from 10m Sentinel-2 MSI, leveraging high wet season contrast between vegetation and water as a dry season positive mask. We created >35 quasi-monthly KAZA-wide Ephemeral Surface Water (ESW) rasters (mean classification accuracy 87%, compared to 50% accuracy for existing water products), and found wet season precipitation drivers of non-riparian water fill levels did not extend into the dry season. Then, using GPS data from 27 African savanna elephants (Loxodonta africana), which typically visit water every 48 hours, we compared elephant water visitation rates based on ESW to existing 30m Global Surface Water (GSW) maps. Models using ESW estimated 99% of elephant data came within a 48-hour window, compared to 42% for GSW, suggesting that ESW is a better proxy for actual wildlife water use in animal movement modeling. As aridification threatens to diminish surface water resources, we must model the drivers of wildlife movements at the scale of wildlife needs. With ESW, we provide fine scale accessible surface water data and a straightforward coding architecture for applications beyond KAZA.

Mesic resources, the late-season herbaceous vegetation found in riparian areas and wet meadows, provide disproportionately important forage and habitat across western U.S. rangelands, yet their response to climatic variability and anthropogenic influences remains poorly understood. Using a 40-year Landsat time series (1984-2024), we quantified trends in late-season productivity (NDVI) across 4.5 million hectares of the sagebrush biome and applied random forest models to distinguish between temporal and spatial predictors of mesic resource productivity. We identified a fundamental shift in how mesic resources respond to drought: from 1984 to 2004, mesic productivity was strongly correlated with drought severity (Palmer Drought Severity Index, R{superscript 2} = 0.92), but this relationship weakened substantially in the next two decades (2005-2024; R{superscript 2} = 0.28), during which time productivity increased despite persistent aridity. Temporal modeling identified rising atmospheric CO2 concentrations as the strongest predictor of this shift, consistent with enhanced plant water-use efficiency under CO2 fertilization. Spatially, large agricultural valley floodplains act as anthropogenic refugia, sustaining productive mesic resources through flood irrigation and subsequent groundwater recharge into late summer. These findings suggest that human water management and physiological shifts in vegetation are currently buffering mesic systems against meteorological drought throughout U.S. rangelands. However, this apparent buffering is spatially heterogeneous and may mask vulnerability to groundwater depletion, shifts in precipitation regimes, and woody encroachment. Sustaining these vital ecosystems will require conservation approaches that go beyond climate monitoring to include balanced management considering both agricultural and ecological water needs and constraints.

BackgroundHuman-Wildlife Conflict is emerging as one of the most critical conservation and socio-economic challenges in the Ecuadorian Andes, where both rural livelihoods and native fauna are under increasing pressure. Small-scale livestock producers in the region depend almost entirely on a limited number of cattle, meaning that the loss of even a single animal can lead to severe economic hardship. In response, antagonistic actions against wildlife are frequent, further threatening vulnerable species. At the same time, the recent proliferation of feral dogs adds a new dimension to conflict, posing risks to both livestock and native fauna. Despite the growing severity of this conflict, little is known of its drivers, spatial patterns, and socio-ecological consequences. This study seeks to fill that gap by generating insights to inform targeted conservation strategies for community-based mitigation of conflict with spectacled bears and feral dogs. MethodsTo assess the drivers and dynamics of HWC in southern Ecuador, we conducted structured interviews with livestock owners, quantifying the frequency and intensity of conflicts across multiple species and evaluating whether farm composition and management practices predict conflict patterns. ResultsOur results reveal that large carnivores cause significantly higher economic losses than smaller predators; furthermore, feral dogs have emerged as the primary source of financial damage over the past five years. Farms with a greater proportion of forest edge were associated with a higher probability of severe conflict, particularly with large carnivores. ConclusionsThese findings underscore the urgent need for proactive strategies to promote coexistence. Identifying predictive variables of conflict risk is crucial for vulnerability assessments and the design of effective mitigation policies. Controlling feral dog populations is likely to be a critical step in safeguarding both rural human livelihoods and native biodiversity in the Andean landscape.

Fuel availability and fuel dryness are consistently shown to be the primary drivers of wildfire intensity and burnt area. Here we hypothesise that differences in the timing of fuel build up and drying determine the optimal time for wildfire occurrence. We use gross primary production (GPP) as a measure of biomass production and hence fuel availability, and vapour pressure deficit (VPD) as a measure of fuel drying. We use the phase difference in the seasonal time course and magnitude of GPP and VPD to cluster regions that should therefore have distinct wildfire behaviour. We then show that each of the resultant clusters is distinctive in terms of one or more fire properties, specifically number of ignitions, burnt area, size, speed, duration, intensity, and length of the wildfire season. The emergence of distinct regimes as a function of two biophysical drivers reflects the fact that both vegetation and wildfire properties are a consequence of eco-evolutionary adaptions to environmental conditions. We then examine the degree to which human activities or vegetation properties modify these fire regimes within each of these clusters. Variability in GPP and VPD largely explains the within-cluster variation in fire properties. The type of vegetation cover has an influence on burnt area and carbon emissions in particular, while human activities are more important for fire properties such as size, rate of spread and duration largely through their influence of landscape fragmentation. Although both human activities and vegetation properties modify wildfire regimes, the ability to distinguish wildfire regimes using GPP and VPD alone emphasizes that land management, fire use and fire suppression are constrained by environmental conditions. This eco-evolutionary optimality approach to characterising wildfire regimes provides a basis for designing a simple fire model for Earth System modelling.

Sylvatic Yellow Fever (YF) is an infectious mosquito-borne disease with significant epidemiological relevance due to its widespread distribution and high lethality for human and non-human primates, particularly in tropical regions of the planet such as in Brazil. Identifying regions and periods of high environmental suitability for the occurrence of YF is essential for preventing or mitigating its burden, as it enables the efficient allocation of surveillance efforts, prevention, and implementation of control measures. Environmental modeling of YF occurrence has proven to be an effective approach toward this goal; however, its effectiveness strongly depends on the modeling framework's capabilities as well as the spatial and temporal precision of all associated data. We propose a fine-scale geospatial modeling of YF environmental suitability that is based on a generative machine-learning ensemble method built on a large set of high-resolution environmental covariates. First, we take the spatiotemporal statistical description of the environment of each of the 545 YF cases from 2019--2024 up to 30 m/monthly resolution at three buffer scales: 100 m, 500 m, and 1000 m ratios. Then, we perform a feature selection and train hundreds of One-Class Support Vector Machine submodels to form a robust ensemble model, whose predictions are projected to a 1x1 km resolution grid of Brazil under several metrics, exceeding seven million ensemble evaluations. The predictions ranked the Southern Brazil region with the highest mean suitability for YF, with a level of 0.64; Southeast comes next with 0.46, followed closely by Central-West region (0.44), North (0.39), and finally Northeast (0.28). The model exhibited high uncertainty for the North region, indicating that data collection efforts are much needed in this region. As for the environmental covariates, a feature analysis pointed out that Land use and cover accounts for the largest influence in the model output.

O_LIThe global decline of natural forests is accompanied by a rapid expansion of commercial tree plantations, which are expected to further increase to meet growing demand for wood products. However, planted forests generally support lower biodiversity than natural forests, particularly when monospecific and intensively managed. In this context, broadleaved hedgerows have been proposed as a nature-based solution to enhance biodiversity within conifer-dominated plantation landscapes. Such features may be especially beneficial for small mammals, including rodents and shrews, which are key contributors to forest ecosystem functioning. However, their effects on small mammal communities remain largely unquantified. C_LIO_LIHere, we assessed variation in small mammal communities among habitat types within a native pine plantation-dominated landscape in southwestern France. Using a multi-year, multi-season survey, we compared species richness and abundance among plantation edges, broadleaved hedgerows embedded within plantations and natural broadleaved forests. We further tested whether environmental descriptors of hedgerow sites influenced dominant species and whether seasonal and interannual demographic dynamics modified habitat-related patterns. C_LIO_LIPine plantation edges and broadleaved hedgerows supported lower small mammal species richness than natural broadleaved forests and were dominated by two habitat generalists, Apodemus sylvaticus and Crocidura russula. This pattern was driven by the near absence of the forest specialist Clethrionomys glareolus. Hedgerows did not increase species richness relative to plantations, but provided favourable habitat for A. sylvaticus, which was scarce in pine plantation, while supporting fewer C. russula. Variation in hedgerow structure and composition further influenced A. sylvaticus abundance, while seasonal and interannual rodent population dynamics modulated habitat-related differences. C_LIO_LIOur results indicate that intensively managed pine plantations act as environmental filters, excluding forest-associated small mammals. While broadleaved hedgerows benefited one species, their capacity to restore forest-specialist communities was limited without broader landscape-scale interventions. These findings highlight both the ecological benefits and constraints of edge-based habitat interventions and provide guidance for designing and evaluating biodiversity-oriented management in plantation landscapes. C_LI

The effects of the selection of livestock type (e.g., sheep or cattle) and grazing intensity on the soil seed bank of sand grasslands of conservation interest were studied. 25 grazed grassland sites classified into four grazing intensity categories were studied. The soil seed bank was analysed by seedling emergence; germinated seedlings were classified into morpho-functional, social behaviour type (SBT) and CSR strategy groups. The following hypotheses were tested: i) Diversity and density of soil seed banks are lower in sheep-grazed sites than in cattle-grazed ones. ii) The species composition, diversity, and density of the soil seed banks are more strongly affected by grazing intensity than by the livestock type. iii) Leaf traits, SBT and CSR strategy composition are highly affected both by livestock type and grazing intensity. The main effect of livestock type only affected seed bank density, while that of grazing intensity had a significant effect on most of the variables. Most of the studied variables were affected by the interaction of grazing intensity and livestock type. Total seed bank density was lower at all grazing intensity levels in sheep-grazed sites than in cattle-grazed ones, especially close to frequently visited places. We found that sheep grazing sustained a much lower total seed bank density and lower density of species of natural and semi-natural habitats regardless to the grazing intensity. Thus, livestock type must be carefully selected and high-intensity sheep grazing should be avoided in the long-run when managing sand grasslands. HighlightsO_LIThe soil seed banks of sheep and cattle grazed sand grassland were studied C_LIO_LIEffect of grazing intensity found the most important driver of seed bank diversity and density C_LIO_LIThe total soil seed bank density was higher in cattle than sheep grazed sites C_LIO_LIBoth intensity and livestock type must be considered in the grassland management planning C_LIO_LIHigh intensity sheep grazing should be avoided in sand grassland management C_LI

Spatial and spatiotemporal models are increasingly critical for understanding species distributions, tracking population change, and informing conservation decisions. As biological processes are influenced by increasing external pressures, including human disturbance or environmental change, accurate model predictions become essential for adaptive management. However, the reliability of spatial predictions depends on often-overlooked modelling choices, including the spatial resolution used to approximate underlying processes. Using long term monitoring data from a large-scale groundfish survey in the California Current ecosystem, we investigated how spatial model complexity affects the quality of ecological predictions and derived indices used for management. We fit spatial and spatiotemporal models of ocean temperature and fish biomass density for 27 commercially important species using varying levels of spatial resolution. We evaluated both in-sample and out-of-sample prediction, and effects on area-weighted biomass indices. Counter to common assumptions, increasing spatial approximation resolution did not universally improve predictions. Our case studies demonstrate that for many datasets, out-of-sample prediction quality peaked at intermediate spatial resolutions and declined at the finest scales. Through simulation testing, we found this pattern was strongest when spatial patterning had a small range and high spatial variance, and observation error was low. For most species, spatial resolution had a minimal effect on biomass trend estimates used in management, but for several commercially important rockfish species, resolution choices substantially affected both the scale and uncertainty of population indices. Our findings demonstrate that spatial model specification can substantially affect ecological inference, with direct implications for management and conservation planning. We provide practical guidance for ecologists on selecting appropriate spatial complexity through cross-validation. When out-of-sample prediction is a focus, appropriate approximation complexity should improve both parameter estimation accuracy and derived quantities.

BackgroundThe malaria transmission potential and the vulnerability of Anopheles mosquitoes to different vector control methods depend, among other factors, on the endophily, endophagy, anthropophagy and survival of each species. Local information on these bionomic parameters is generally unavailable. MethodsTo address this, we estimated species-specific values of these parameters using an augmented version of the global database of bionomics data by Massey et al. (2016). We applied inclusion and exclusion criteria to select eligible studies with relevant experimental designs that minimise bias from collection methods for parous, sac, endophagy, and endophily rates as well as for the resting duration. For the human blood index (HBI), we separated data from indoor and outdoor collections. We fitted hierarchical Bayesian models with levels based on Anopheles taxonomy to estimate these quantities. Based on the estimated bionomics, we quantified the expected vectorial capacity reduction after the introduction of a pyrethroid-pyrrole insecticide-treated net (ITN) for 57 Anopheles species. ResultsWe identified 26 eligible studies for endophagy and 61 for the parous rate, leading to a Bayesian posterior average for the Anopheles genus of 42% (95% credible interval: 18-70) and 55% (32-77) respectively. HBI values widely varied depending on the location of collection, except for some species showing strong anthropophilic behaviours. Resting duration was estimated to be 2.1 days (1.2 - 4.8) at the genus level. Few studies were available to estimate the sac and endophily rates, which prevented us from deriving precise estimates for the whole Anopheles genus. Our estimates of the vectorial capacity reduction following the introduction of a pyrrole-pyrethroid ITN ranged between 48% and 76% across species, highlighting the important differences among mosquito species in vulnerability to vector control interventions. ConclusionThis work demonstrates how data from both Anopheles species complexes and individual species can be leveraged to generate species-specific estimates of bionomic parameters, capturing the local characteristics and behaviour of malaria vectors. The dataset is readily updatable as new data become available. However, more frequent and standardised field surveys are still needed to accurately characterise local vector behaviour.

O_LIChanges in habitat structure across species distributions may contribute to the generation and maintenance of range limits, but few studies have evaluated this by directly measuring habitat availability across relevant spatial scales. C_LIO_LIHere, we test the predictions that coarse-scale and patch-level habitat availability decline towards and beyond the northern range limit of Pacific coastal dune endemic Camissoniopsis cheiranthifolia. We used aerial imagery and geographic information system (GIS) tools to measure the coarse-scale availability of coastal dune habitat in California and Oregon. The availability of finer-scale habitat patches specifically suitable for C. cheiranthifolia was measured in a 2-generation field survey of > 4,200 5m x 5m plots randomly distributed across 1100 km of coastal dune habitat transcending the species northern range limit. At each plot, we estimated the proportion of area that contained suitable habitat as well as recorded occupancy by C. cheiranthifolia. As an alternative approach to visually estimating habitat suitability, we recorded plant community composition at each plot to predict beyond-range habitat suitability using a random forest model. C_LIO_LIContrary to our predictions, we found that coastal dune habitat, measured coarsely from aerial imagery, was more abundant and continuous towards and beyond the northern range limit. At the fine scale, however, the proportion of plots with suitable habitat (patch suitability) and the proportion of habitat within plots that was suitable (patch size) declined across the range limit. Moreover, patches were more isolated from one another and, in one survey year, less temporally stable towards and beyond the range limit. Finally, occupancy by C. cheiranthifolia was less likely in smaller, more isolated, and temporally unstable patches, providing mechanistic insight to the previously observed decline in occupancy towards the range limit. C_LIO_LISynthesis: Taken together, our results suggest that fine-scale habitat patch configuration changes in ways that likely impede patch colonization, thereby reducing occupancy and limiting the species northern distribution. Thus, consideration of geographic variation in patch and landscape structure, rather than only coarse-scale habitat availability, may be essential for understanding the processes that limit species ranges. C_LI

O_LITropical dry forests are among the most threatened ecosystems globally, yet the consequences of livestock overgrazing for ant communities remain poorly documented, particularly in the Tumbesian biodiversity hotspot of southwestern Ecuador, where uncontrolled goat grazing constitutes the dominant disturbance agent. C_LIO_LIWe sampled ant communities (Formicidae) across a goat-grazing disturbance gradient in Zapotillo (Loja Province, Ecuador), establishing three disturbance levels (Dense, Semi-dense, and Open Forest) with nine 60 x 60 m plots per level (n = 27) and 486 pitfall traps. Community responses were assessed using abundance-based and presence-absence analyses of morphospecies richness, Hill-number diversity, community composition, beta diversity decomposition, and functional guild structure; vegetation structure was characterized using satellite-derived NDVI. C_LIO_LIWe recorded 47,459 individuals belonging to 22 morphospecies in six subfamilies. Morphospecies richness declined with disturbance (Dense: 19, Semi-dense: 15, Open: 12), with four specialist genera exclusive to Dense Forest. Beta diversity decomposition revealed a shift from turnover-dominated dissimilarity at moderate disturbance to nestedness-dominated dissimilarity at high disturbance, indicating progressive habitat filtering as the dominant community-restructuring process. C_LIO_LICommunity composition differed among disturbance levels (PERMANOVA: F = 4.49, R{superscript 2} = 0.272, p = 0.001) and was correlated with NDVI (r{superscript 2} = 0.341, p = 0.013). Cryptic/soil and Leaf-cutter guilds were nearly eliminated from Open forest while the Opportunist guild expanded markedly, indicating that functional homogenization precedes detectable taxonomic impoverishment. C_LIO_LIOvergrazing drives directional ant diversity loss and biotic homogenization at both taxonomic and functional levels in the Tumbesian dry forest, underscoring the conservation value of intact Dense forest. C_LI

By concentrating rodents along verges, roads can reshape rodent-mediated seed dispersal, yet empirical tests remain scarce. We conducted a two-year field experiment in Mediterranean oak woodlands in southern Portugal to test how seed dispersal varies with distance from roads across road type (paved vs. unpaved) and road-forest context (edge vs. non-edge). We tracked labeled holm oak acorns, recording dispersal distances and the number of dispersal events. The two metrics responded differently to road distance. Dispersal distances changed little with distance from roads in non-edge contexts but increased in edge road-forest contexts (2x longer at 400 m than at 10 m) and showed a year x distance-to-road interaction, with longer dispersal distances farther from roads in the second year (a poor mast year). Dispersal distances were also longer when acorns were deposited under shrubs and in areas of higher tree density, and decreased with greater natural acorn availability. In contrast, the number of dispersal events declined with distance from roads (30% more events at 10 m than at 400 m) and was higher along unpaved than paved roads (39% more events). Dispersal frequency also increased in the poor mast year and with shrub cover. No acorns crossed the road. Thus, road verges can concentrate rodent seed handling but do not increase dispersal distances near roads nor provide cross-road seed connectivity; instead, dispersal outcomes depend on edge context, road type, and microhabitat structure. Management that retains structural cover at verges and the adjacent forest edge (e.g., shrub patches and non-uniform clearing) can harness verge-associated activity to increase acorn deposition in sheltered microsites and promote regeneration farther into forest interiors in roaded landscapes.

Despite significant reductions in malaria cases across Brazil, residual transmission persists in the Legal Amazon, threatening the national goal of elimination by 2035. The Amazonian socio-ecological landscape creates a complex environment where environmental degradation and socioeconomic vulnerabilities intersect. However, the independent and combined effects of these drivers remain poorly quantified at a regional scale. We conducted a retrospective, longitudinal ecological study analyzing a comprehensive panel dataset from 2021 to 2025 across all 773 municipalities in the Brazilian Legal Amazon. We evaluated the independent effects of prior-year deforestation, extreme poverty, population density, fire activity, macroclimatic variables, and primate reservoir abundance on malaria incidence. Deforestation emerged as the dominant predictor of malaria intensity. A one-standard-deviation increase in lagged deforestation area was associated with a 48.3% increase in expected malaria cases. Socioeconomic deprivation also significantly sustained transmission, with extreme poverty increasing cases by 18.8%. Conversely, population density exhibited a strong protective effect, reducing incidence by 72.2%, reflecting the phenomenon of urban protection. While an overall temporal decline of 17.4% annually was observed, profound spatial heterogeneity persisted, with the state of Amazonas maintaining consistently high transmission without a discernible downward trend. Macroclimatic factors and primate abundance did not show statistically significant independent effects at the annual municipal scale. The persistence of malaria in the Brazilian Amazon is not merely a biomedical issue but a profound sustainable development challenge driven by the synergistic effects of land-use change and socioeconomic inequality. Deforestation and extreme poverty create a resilient reservoir of transmission risk that undermines conventional control efforts. Achieving the 2035 elimination goal demands a paradigm shift toward a One Health approach, integrating rigorous environmental protection, targeted social development, and spatially stratified public health interventions. Ultimately, the health of the Amazonian population is inextricably linked to the health of the forest itself.

Humans are profoundly reshaping the natural world. These changes are giving rise to complex and mutually risky dynamics between people and large carnivores. In protected areas across North America, bears (Ursus sp.) face rapidly rising recreation pressures that can alter their use of the landscape, either displacing them from high-quality habitats or drawing them into human-wildlife conflicts through habituation or attraction to anthropogenic resources. However, disentangling responses to recreation from other drivers can be difficult because human activity covaries with environmental and seasonal processes that also shape bear activity. We leveraged the partial closure of the popular Berg Lake Trail in Mount Robson Park, British Columbia, Canada, to investigate whether black (Ursus americanus) and grizzly bears (Ursus arctos) showed fear, attraction or neutral behavioural responses to varying recreation levels across multiple spatiotemporal scales. To understand both anticipatory responses to predictable patterns of human activity, and reactive responses to hiker events, we used detections from 43 camera traps over two years (July 2023-June 2025). We compared weekly habitat use, daily activity patterns, and direct responses to hikers (using Avoidance-Attraction Ratios; AARs) among camera sites and between open and closed sections of the trail. Our results revealed that both bear species exhibited patterns consistent with fear responses, while some black bear behaviours were also consistent with attraction responses. Both kinds of responses reflect anticipatory strategies rather than reactionary behaviours (i.e., no AAR effect). Neither species avoided recreation spatially at the weekly scale: black bears were detected more at site-weeks with greater recreation intensity, while grizzly bears were consistently detected more at sites closer to hiking trails. However, both species used daily temporal partitioning to avoid direct encounters with humans. These findings demonstrate scope for human-bear coexistence when recreation levels are managed to be moderate and predictable, and bears have sufficient space to segregate from humans during peak times. Thus, successful coexistence will hinge on co-adaptation by both bears and people. Understanding how recreation influences bear behaviour, and the spatiotemporal scale at which that occurs, is critical for guiding effective adaptive management aimed at fostering human-bear coexistence in high-traffic protected areas.

Gene flow shapes the demographic stability and evolutionary potential of tropical forest trees, yet its dynamics may differ depending on the temporal scale at which it is assessed. We combined spatial genetic structure (SGS), parentage analyses, and reproductive success metrics to investigate historical and contemporary gene dispersal in four populations of Dicorynia guianensis across French Guiana, encompassing sites differing in environment and management history. A total of 1,528 individuals were genotyped using 66 nuclear and 23 plastid microsatellite markers, enabling high-resolution inference of biparental and maternal gene dispersal. Historical mating and dispersal parameters inferred from SGS revealed marked contrasts among populations. Some populations exhibited high historical gene dispersal distances and weak spatial genetic structure, whereas others showed stronger SGS and long-term aggregative dispersal patterns. Contemporary parentage analyses further highlighted differences in seed and pollen dispersal distances, parent assignment rates, and reproductive skew. In certain populations, pronounced reproductive inequality and reduced effective connectivity were observed, while others displayed more balanced reproductive contributions. By jointly evaluating long-term dispersal legacies and present-day reproductive patterns, our study demonstrates the value of combining indirect and direct genetic approaches to assess population dynamics and conservation status in tropical forest trees. This multi-temporal perspective provides a comprehensive basis for long-term monitoring and sustainable management in heterogeneous tropical landscapes.