Science of The Total Environment

Indo-Pacific humpback dolphin (Sousa chinensis) and finless porpoise (Neophocaena phocaenoides) are increasingly threatened across their native range, yet the relative influence of multiple stressors in shaping their population dynamics remains unclear. Current conservation strategies for both species are limited by incomplete data and limited assessment of affecting factors. Here, we integrated eDNA metabarcoding with Joint Species Distribution Modeling (JSDM) to assess how environmental gradients, pollution, and trophic associations interactively influence cetacean distributions in Hong Kong waters. We show that degraded water quality and intensified human activity negatively associated with cetacean occurrence, with clear species-specific responses to different stressors. S. chinensis covaried most strongly with Secchi disc depth, and presence of vessels, while N. phocaenoides was negatively associated with nitrate nitrogen and microbial pollution (sewage). The JSDM variance partitioning analysis highlighted that the occurrence of S. chinensis was primarily associated with anthropogenic disturbances (30.04%), followed by water physical properties (26.63%), whereas N. phocaenoides was more strongly associated with physical (40.9%) and anthropogenic disturbances (35.2%). By integrating eDNA and JSDM, our approach provides fine-scale diagnostics of species-specific vulnerabilities, supporting adaptive conservation strategies and guiding the realignment of protected areas to mitigate biodiversity loss in urbanized marine ecosystems. Environmental ImplicationOur study demonstrates that hazardous water pollutants, including microbial contamination, nutrient enrichment, and chemical stressors, vessel pressure, show strong, species-specific impacts on resident cetaceans in Hong Kong. By integrating eDNA metabarcoding with joint species distribution models, we provide a diagnostic framework that directly links pollutant profiles to ecological risk. These findings highlight that conventional conservation strategies overlooking pollution drivers are insufficient for marine megafauna persistence. Our approach offers an early-warning system for monitoring hazardous pollutants in coastal ecosystems and supports adaptive management strategies to mitigate biodiversity loss in urbanized seascapes.

The increasing use of microbial biopesticides in sustainable agriculture requires a deeper understanding of their potential impact on non-target pollinators. Although biocontrol agents are generally considered safer than synthetic pesticides, they may still cause subtle but ecologically relevant adverse effects on non-target organisms, especially when exposed to multiple stressors that are often overlooked in current risk assessment frameworks. Among these, nutritional stress, caused by habitat loss, fragmentation and reduced floral diversity, is becoming increasingly widespread. In this study, we investigated the lethal and sublethal effects of the bacterial biopesticide Bacillus velezensis (formerly B. amyloliquefaciens) strain QST713 at field-relevant concentrations on two key pollinators: Apis mellifera and Bombus terrestris. For the first time for a biopesticide, oral toxicity was assessed under environmental stress represented by diets with varying sugar concentrations (optimal and suboptimal) to identify potential synergistic effects on bee health. Sublethal effects were examined by studying learning performance and memory retention through a conditioning experiment under laboratory conditions. The results showed marked species-specific differences. While B. velezensis did not impact bee survival under realistic nutritional conditions, we observed a synergistic lethal effect in B. terrestris when biopesticide exposure was coupled with extreme nutritional stress (sugar deprivation). Similar species-specific differences emerged at the behavioral level: unlike A. mellifera, B. terrestris showed impaired visual learning and early long-term memory recall. Taken together, these results show that sublethal cognitive endpoints and multi-stressor contexts may reveal vulnerabilities not immediately evident through mortality-based assessments alone. Our findings also highlight the importance of including multiple pollinator species in risk assessment, as sensitivity to biopesticides might greatly vary among species.

IntroductionDrowning risk begins with water exposure, yet population-water relationships have rarely been quantified at scale using environmental measures. This study explored whether satellite-derived data was associated with subnational drowning mortality and whether associations differed by country income level. MethodsWe linked Global Burden of Disease (GBD 2021) age-standardised drowning mortality rates to satellite-derived exposures for 212 subnational regions across 12 countries (2006-2021; 3,392 region-years). Exposures were extracted via Google Earth Engine and standardised. Gamma-log generalised linear mixed models included region random intercepts and year fixed effects. Income-stratified models were estimated separately. Supplementary models assessed maritime vessel activity. ResultsNear-water population percentage was the strongest correlate of drowning (IRR 1.40; 95% CI 1.33-1.47). Permanent water coverage was protective (IRR 0.80; 0.73-0.88), as were nighttime lights (IRR 0.96; 0.95-0.97) and hot days [≥]30{degrees}C (IRR 0.95; 0.92-0.99). Mean temperature (IRR 1.17; 1.11-1.23) and precipitation (IRR 1.03; 1.01-1.04) were positively associated. Near-water effects were consistent across income strata (LIC 1.25; MIC 1.31; HIC 1.24), while other predictors showed weak or inconsistent within-strata associations. Vessel activity was modestly associated with drowning in Global Fishing Watch models (IRR 1.05; 1.01-1.09) but not in Synthetic Aperture Radar models. DiscussionSatellite-derived indicators can characterise drowning risk at scale, with population proximity to water emerging as a robust cross-context correlate. Protective associations for permanent water suggest landscape configuration may shape risk beyond proximity alone, highlighting geospatial datas value for targeting prevention where surveillance is limited.

Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low-to middle-income settings but near-null in high-income regions, while waterfront development captured very different realities across contexts. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.

As toxicology shifts towards non-animal testing, quantitative models are essential to predict adverse health effects from molecular or cellular perturbations. Quantitative Adverse Outcome Pathways (qAOPs) represent such models, building on mechanistic knowledge and quantifying the Key Event Relationships (KERs) described in AOPs. Despite the recognized need, the number of qAOPs remains limited. Bayesian-based approaches are often chosen for developing qAOP for their flexibility, but most use discretized variables, limiting their predictive power. In addition, these models are mainly built from newly generated data, underexploiting the large amount of information available. This study successfully leverages data from public literature and presents an innovative framework based on continuous variables to develop a Bayesian-based quantitative model for a central KER towards liver fibrosis. The model predicts the probability of the expression fold change for two key markers of hepatic stellate cell activation (aSMA and COL1A1), given the effects on tissue injury, using in vitro data from 9 chemicals. We propose a newly developed workflow to assist in knowledge identification, organization, and extraction from scientific literature and chemical databases. Based on in vitro data and in vivo information from the Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System) database, we estimate a biologically relevant range in COL1A1 fold change that indicates an activated state of stellate cells and high liver fibrosis odds ratios. Our study provides a case example of integrating published data and continuous variables to build a Bayesian-based model, which constitutes an essential step for predicting liver fibrosis from in vitro data.

O_LIMarine organisms, including green and brown macroalgae, exhibit a broad dependency on their microbiome which has been demonstrated in model species including Ulva compressa and Ectocarpus siliculosus with relatively simple building plans. However, it remains elusive if and how Saccharina latissima, a complex brown macroalgae with high degrees of organ and tissue differentiation, is controlled by its microbiome. C_LIO_LIWe monitored gametophyte cultures of mixed sexes, induced oogenesis and followed sporophyte development both under axenic conditions and in cultures complemented with bacterial isolates from the sugar kelp core microbiome. C_LIO_LIFemale gametophytes generally performed better in the presence of bacteria while males performed worse. Some bacterial isolates inhibit oogenesis in females entirely, whereas others have a stimulating effect. Under axenic conditions sporophytes did form, but growth, pigmentation and the establishment of an apical-basal polarization axis were severely disrupted. These defects could be resolved by complementation with many bacteria from the S. latissima core microbiome. C_LIO_LISugar kelp depends heavily on specific bacterial symbionts for growth, reproduction and development and their effect is sex-dependent in gametophytes. This work provides a platform to investigate the precise methods of cross-kingdom communication which has a large potential in the kelp production industry. C_LI

Wastewater surveillance is increasingly used for antimicrobial resistance (AMR) monitoring in urban environments, but low-resource settings often lack a piped sewerage system. Instead, coprophagous flies--flies that ingest feces--may serve as composite samplers for monitoring fecal wastes present in terrestrial environments. We evaluated whether the class 1 integron-integrase gene intI1 was associated with genetic markers of AMR and fecal source tracking markers (FST) in coprophagous flies collected from latrine entrances and food preparation areas in low-income urban Maputo, Mozambique. We quantified intI1, an enteric 16S rRNA target (for normalization), three FST markers, and 30 ARG targets using qPCR. We normalized concentrations of intI1 and each target to enteric 16S rRNA. We fit linear mixed models with a random intercept for housing compound to estimate within-fly associations between log10 relative abundance of intI1 and log10 relative abundance of each target with and without adjustment for fly taxonomic group, capture location, and standardized fly mass. We also modeled per-fly unique ARG count (i.e., number of ARG targets detected) using Poisson regression. Of 188 flies assayed, 176 passed internal controls; intI1 and enteric 16S rRNA were detected in 95% and 96% of flies, respectively. Higher relative abundance of intI1 was positively associated with ARG and FST targets, with the strongest associations observed for sulfonamide-(sul1: {beta} = 0.87; 95% CI: 0.81, 0.94; sul2: {beta} = 0.81; 95% CI: 0.73, 0.89), tetracycline- (tetA: {beta} = 0.78; 95% CI: 0.70, 0.85; tetB: {beta} = 0.69; 95% CI: 0.60, 0.79), and trimethoprim-related (dfrA17: {beta} = 0.78; 95% CI: 0.70, 0.86) genes. Associations with FST markers were weaker (i.e., human mtDNA: {beta} = 0.46; 95% CI: 0.37, 0.55; human-associated Bacteroides: {beta} = 0.34; 95% CI: 0.25, 0.43). Higher relative abundance of intI1 was also associated with a greater number of ARGs detected: each 10-fold increase in intI1 was associated with an 8% higher expected unique ARG count (aRR=1.08, 95% CI: 1.04-1.12). These findings support the need for further research across different settings exploring intI1 carried by coprophagous flies as a potential standardized screening target for AMR surveillance in unsewered terrestrial environments.

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([≤]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

With Japans rapidly aging population, demand for home healthcare is projected to increase by 62% by 2040. This study quantitatively evaluated accessibility to 24-hour home healthcare and regional disparities across all 335 secondary medical areas (SMAs) in Japan using the Enhanced Two-Step Floating Catchment Area (E2SFCA) method. We conducted a nationwide cross-sectional study analyzing approximately 430,000 population points at 500-meter mesh resolution. The E2SFCA integrated demand (age-adjusted population), supply (24-hour home care support clinics and hospitals), and transportation (road networks). Accessibility scores (ASs) and Gini coefficients were calculated for each SMA. Wards hierarchical cluster analysis classified regional types, and multiple regression based on the Penchansky and Thomas five-dimensional access framework identified factors associated with the median AS (ASM) and Gini coefficient. The median ASM was 45.71 (0.00-153.49), and the median Gini coefficient was 0.33 (0.06-0.93). Cluster analysis identified six types ranked by descending ASM, from C1 (high access, equitable; n = 48) to C6 (access desert; n = 23). C6 had a median ASM of 0.00 and Gini coefficient of 0.74, indicating virtually no access within a 30-minute catchment. Home-visit standardized claim ratios, used as external validation, declined monotonically from C1 (125.6) to C6 (17.6). For ASM, 24-hour visiting nursing stations ({beta} = +0.369) and clinic physicians ({beta} = +0.342) showed the strongest positive associations, with non-residential area negatively associated ({beta} = -0.273). For the Gini coefficient, non-residential area showed the strongest positive association ({beta} = +0.523). Taxable income per taxpayer was not significantly associated with either outcome. Non-residential area was associated with both lower accessibility and greater intra-regional inequality, suggesting that geographic constraints may limit the effectiveness of resource investment alone. Uniform nationwide implementation of policies shifting care from long-term care beds to home healthcare may not be feasible; region-specific approaches considering geographic characteristics are necessary.

Enhanced resilience conferred through sublethal stress pre-exposure may be crucial for reef building corals to cope with variable environments. The effect of stress priming on Acropora cervicornis thermotolerance was evaluated in the context of elevated temperature and ammonium enrichment, 3 and/or 6 M above ambient, respectively. Primed corals were pre-exposed to each stressor individually or in combination for eight days, while non-primed corals remained at ambient conditions. After an eight-day recovery, primed corals and a subset of non-primed corals (naive) were subjected to an acute 15-hour thermal challenge. Coral metabolism, symbiosis, and gene expression were characterized throughout the experiment. Thermal tolerance was quantified as algal symbiont, chlorophyll, and live tissue retention, along with survival probability following acute heating. Primed corals were more likely to retain symbionts and chlorophyll after heat stress and also exhibited slower tissue loss. Moreover, thermal pre-exposure reduced the risk of tissue loss or predicted mortality. Apoptotic regulation differed between primed and naive corals during the initial and secondary heat exposures. Additionally, primed corals exhibited patterns of transcriptional resilience under acute thermal stress. Altogether, results provide support for the capacity of A. cervicornis to gain resilience through pre-exposure to ecologically relevant conditions as well as insights into the molecular mechanisms underpinning this process.

The acute, subacute, and subchronic oral toxicities, as well as the combined chronic toxicity and carcinogenicity, of a nanotechnology-based formulation derived from a natural extract of Eucalyptus tereticornis leaves were investigated. This nanoformulation demonstrates anti-obesogenic and potentially anti-diabetic properties. Our study aims to conduct preclinical tests to evaluate the chemical formulation. To assess acute toxicity, rats received a single oral dose of 2000 mg/kg of the nanoformulation. In the subacute trial, mice were treated with approximately 1180 mg/kg of the nanoformulation for 28 days. In the combined chronic toxicity and carcinogenicity study, the nanoformulation was administered daily at approximately 590 mg/kg for 10 months. At the end of the experiment, hematological, biochemical, and histopathological assessments were conducted. Throughout the acute, subacute, subchronic, and chronic/carcinogenicity studies, animals showed no toxic effects from the treatment or the vehicle. No histopathological lesions, such as degeneration or cell death in the liver, kidney, or gastrointestinal tract, were observed. Treatments did not cause any clinical changes, and there were no significant differences in weight, hematological, or biochemical parameters. Therefore, the nanoformulation did not produce toxic effects in the animals.

Background Pseudomonas aeruginosa is a major cause of healthcare-associated infections in paediatric settings, where its persistence in moist environments such as hospital water and wastewater systems poses a particular risk to neonates and immunocompromised children. Aim The aim of this study was to showcase the long-term survival and transmission of P. aeruginosa in a large tertiary children's hospital in England which is crucial to develop strategies for water-safe care. Methods Environmental P. aeruginosa isolates were collected from taps, sinks, showers, and baths in augmented care areas of a 330-bed tertiary children's hospital built to NHS water-safety standards. Clinical isolates were classified as invasive (blood, cerebrospinal fluid, and bronchoalveolar lavage) or non-invasive (respiratory, urine, ear, abdominal, and rectal surveillance). Variable number tandem repeat (VNTR) profiles and metadata were extracted from PDF reports, de-identified, deduplicated, and curated using Python and R. Findings This retrospective study analysed nine-locus VNTR profiles of 457 P. aeruginosa isolates submitted to the UK Health Security Agency from a large tertiary children's hospital, identifying 56 isolate clusters (each with [≥]2 isolates), of which 19 (34%) contained at least one invasive isolate. The most persistent cluster (Cluster 1, n=20) spanned from July 2016 to September 2024, containing environmental and clinical (invasive and non-invasive) isolates. Conclusion These findings demonstrate long-term persistence of certain genotypes and temporal overlap between environmental and clinical isolates, highlighting the difficulty in detecting and eradicating P. aeruginosa in hospital water and wastewater systems and reinforcing the need for continuous rigorous water system controls.

Subsistence agriculture in sub-Saharan Africa faces persistent productivity challenges due to low soil fertility, limited inputs, and increasing climate variability. Agroforestry can offer a sustainable strategy for smallholder systems by enhancing soil quality and the presence of arbuscular mycorrhizal fungi (AMF) in crop roots. Using a canopy-based radial sampling design, we assessed the influence of Mangifera indica (mango) trees on soil properties and AMF communities in maize and cassava in southern Ethiopia. Illumina MiSeq sequencing identified 908 AMF operational taxonomic units (OTUs) from 7 families, dominated by Glomeraceae. While soil properties, including pH, total nitrogen (TN), organic carbon, and potassium, were significantly affected by the distance from mango trunks, this was not the case for AMF community composition and AMF richness and diversity. Host identity, rather than distance from the mango trees, was the primary driver of AMF community composition, with distinct and host-specific assemblages in mango, maize, and cassava roots. Soil nutrients influenced AMF diversity differently across hosts. In maize-mango systems, TN positively affected observed richness (Sobs) and Shannon diversity (N1), whereas Olsen P negatively affected N1 and Simpson diversity (N2). In cassava-mango systems, TN enhanced Sobs, and Olsen P positively influenced expected richness (Sexp). Overall, these findings demonstrate a decoupling between mango-induced soil fertility enhancement and crop AMF community composition and diversity, rather emphasizing the roles of host type and soil nutrients in structuring AMF communities. Without demonstrating direct benefits, we at least show that mango can be effectively integrated into smallholder maize and cassava production without compromising the AMF communities, while enhancing key soil fertility indicators. Maintaining adequate nitrogen levels while avoiding excessive phosphorus inputs may help sustain stable AMF communities in agroforestry systems.

ObjectivesRising temperatures are a major climate-related hazard for U.S. workers, increasing heat-related illness and a broad range of occupational injuries through indirect pathways often overlooked in economic evaluations. We examined the association between temperature and occupational injury and illness and quantified heat-attributable injuries (including illnesses) and costs in New York State. MethodsWe conducted a time-stratified case-crossover study of 591,257 workers compensation (WC) claims during the warm season (2016-2024). Daily maximum temperature was linked to injury date and county and modeled using natural cubic splines, with effect modification by industry and worker characteristics. ResultsInjury risk increased with temperature, becoming statistically significant at approximately 78{degrees}F. Relative to 65{degrees}F, injury odds increased to 1.06 (95% CI: 1.01-1.10) at 80{degrees}F, 1.12 (1.07-1.18) at 90{degrees}F, and 1.17 (1.11-1.23) at 95{degrees}F. Overall, 5.0% of claims (2,322 annually) were attributable to heat. At temperatures [≥]80{degrees}F, an estimated 1,729 excess injuries occurred annually, generating approximately $46 million in WC costs. An estimated $3.2 million to $36.1 million in medical expenditures were associated with incomplete claims, likely borne outside the WC system. ConclusionsThese findings demonstrate substantial economic costs not fully captured within WC and support workplace heat protections as a cost-containment strategy that can reduce health care spending and strengthen workforce resilience.

We present a spatially explicit, global-scale index to assess the effects of the five direct anthropogenic drivers of biodiversity loss identified by the IPBES: land use change, natural resource extraction, climate change, pollution, and invasive alien species. The Biodiversity Pressure Index (BPI) covers 30 years (1990-2020) with an annual time-step and a spatial resolution of 0.1{degrees}. We find that the coverage of drivers in available data varies and we highlight the key uncertainties that result from this. Using the best available data, we show that large parts of the terrestrial biosphere (approximately 89%, including Antarctica and Greenland) are under medium or high human pressure and that almost all areas (approximately 96%) have experienced an increase in pressure over the past three decades. The BPI shows varied spatial and temporal patterns across world regions and biomes, but many of these areas are dominated by pressures associated with rising temperatures and trade flows. Tropical and subtropical areas are subject to particularly rapidly-growing pressures, while wetlands consistently show the highest pressure levels across biomes. In revealing these and other patterns, the BPI provides a basis for improved understanding and management of biodiversity impacts in the future.

Drug overdose deaths in the United States reached record levels during the fentanyl era before recently declining. A plausible hypothesis is that a sudden drop in fentanyl purity beginning in 2023 caused the downturn in overdose mortality. We evaluated this hypothesis by replicating a published analysis with regional overdose data, using models that account for time trends and autocorrelation, and negative control indicators to test for spurious correlation. When fentanyl purity was rising, the national purity series did not track overdose increases in most regions and showed only a modest association in the West. When both purity and mortality later declined, the observed associations were also seen with unrelated macroeconomic indicators that shared the same time pattern. National fentanyl purity alone does not provide a sufficient explanation for recent overdose declines.

Canadas ambition for mineral security and its responsibilities to protect at-risk species and uphold Indigenous rights clash in the case of the Grays Bay Road and Port (GBRP) in Nunavut, an infrastructure project intended to unlock critical mineral deposits. We compiled Indigenous and Western science through a density analysis of caribou harvesting data near the proposed project site. We identified three consistently used harvesting hotspots, with the most significant hotspot lying directly in the path of the proposed GBRP project. These results indicate that the GBRP project will have significant and unmitigable negative effects on caribou conservation, food security, and Inuit harvesting rights. Prime Minister Carney claims that middle power countries must act consistently in this era of geopolitical rupture; this commitment must transfer to natural resource development reviews so that decision-making may be consistent and rooted in cross-legislation responsibilities and values, including the land claims agreements between Indigenous groups and the Government of Canada.

Road traffic accidents represent a global public safety crisis, necessitating advanced computational tools for accurate injury severity prediction and effective decision support. This study evaluates high-performing ensemble machine learning models, including AdaBoost, XGBoost, LightGBM, HistGBRT, CatBoost, Gradient Boosting, NGBoost, and Random Forest, using a comprehensive National Highway Traffic Safety Administration (NHTSA) dataset from 2018 to 2022. While all models demonstrated exceptional predictive accuracy, with HistGBRT achieving the highest overall accuracy of 92.26%, a defining achievement of this work is the perfect classification (100% precision and recall) of fatal injuries across all ensemble architectures. To bridge the gap between predictive performance and actionable intelligence, this research integrates SHapley Additive exPlanations (SHAP) to provide both global insights into dataset-wide risk factors and local, instance-specific rationales for individual crash events. The global analysis identified ethnicity, airbag deployment, and harmful event type as primary drivers of injury severity, while local force and waterfall plots revealed the precise "push and pull" of variables for specific incidents. The results offer a robust, interpretable framework for stakeholders tasked with improving traffic safety and mitigating crash-related harm.

Pacific salmon are keystone species to North Pacific freshwater, coastal, and oceanic ecosystems, but many populations have declined or become more variable in recent decades due to anthropogenic impacts and climate change. Long-term records are needed to understand past changes, identify ecosystem stressors, and guide restoration. We used sedimentary DNA (sedDNA), an emerging paleoecological approach offering broader taxonomic information than traditional methods, to reconstruct ecosystem changes across five Pacific salmon nursery lakes in British Columbia (Canada). DNA metabarcoding targeting the 18S ribosomal RNA gene V7 region was used to track shifts in eukaryotic communities including algae and invertebrates over centuries to millennia. Most lakes showed notable algal community shifts over the past two centuries, with declining green algae and rising diatom relative abundances. Chrysophytes and dinoflagellates also increased over the past century in most lakes, likely driven by stronger thermal stratification, which favored these motile and mixotrophic algae that are capable of vertical migration and flexible nutrient acquisition. We contextualized the trajectories of each core through an ordination analysis based on 98 lakes distributed across British Columbia, which identified land-use changes and longer growing seasons as potential drivers. Network analyses of the sedDNA time series revealed decreasing modularity and increasing connection across lakes, suggesting a shift in resilience mechanisms from between-module buffering by compartmentalized specialists to within-guild insurance via functional overlap among generalists. Our findings demonstrate that sedDNA provides taxonomically rich, long-term insights into aquatic ecological dynamics, which are foundational for understanding and protecting Pacific salmon nursery habitats.

Invasive insect species pose serious threats to agriculture and ecosystems, with their spread increasingly accelerated by global trade and climate change. To support prevention and mitigation efforts, it is essential to map the regions where these pests can survive and thrive. Here, we apply MaxEnt, a leading species distribution modeling framework, to estimate current (2020) and future (2040-2060) suitable habitats for five major invasive insects across the contiguous United States: brown marmorated stink bug, corn earworm, spongy moth, root weevil, and spotted lanternfly. To account for an uncertain climatic future, these projections are generated under four shared socioeconomic pathways, which reflect a range of plausible climate change scenarios. Beyond forecasting distributions, we examine several key modeling decisions, especially those often overlooked in practice. In particular, we find that background sampling strategies play a critical role in model calibration and that a hybrid sampling approach with a moderate buffer bias provides better predictive accuracy. We also show that permutation importance scores, commonly used to rank environmental variables, are highly sensitive to small changes in the background data and should be interpreted with caution. Finally, to bridge the gap between ecological modeling and applied machine learning, we provide a self-contained, math-focused background to MaxEnt aimed at practitioners outside of traditional ecological fields. Overall, this work delivers reproducible modeling workflows and critical insights into building robust, transparent, and ecologically meaningful MaxEnt models for climate-informed species distribution analysis.