Environmental Health Perspectives

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.

Background Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combustion-derived pollutants linked to cardiovascular disease. Prior NHANES analyses have evaluated these chemicals individually, failing to capture the correlated co-exposure structures that characterize real-world environmental burden, thereby underscoring the need for application. In this study, we applied an unsupervised machine learning pipeline to urinary biomarker data to identify multi-chemical exposure clusters and quantify their differential cardiovascular risk profiles in a nationally representative US sample. Methods We analyzed 2,979 participants from NHANES between 2017-2018, representing an estimated 36.8 million US adults after complex survey weighting. Twenty-five urinary biomarkers (6 PAH, 19 VOC metabolites) were log-transformed, imputed using Multivariate Imputation by Chained Equations (MICE), and standardized. Uniform Manifold Approximation and Projection (UMAP) was used for dimensionality reduction, followed by Gaussian Mixture Model (GMM) clustering. Survey-weighted prevalence estimates with 95% confidence intervals (CIs) were calculated for hypertension and high total cholesterol within each cluster. Weighted multivariable logistic regression was used to estimate odds ratios (OR) for hypertension, adjusting for age, sex, race/ethnicity, and income. Results Four exposure clusters were identified with a mean assignment probability of 0.948. The High combustion cluster (n=370; estimated 5.1 million US adults) exhibited the highest multi-chemical burden and a weighted hypertension prevalence of 39.3% (95% CI 37.2-41.4%), compared to 28.7% (95% CI 21.9-35.5%) in the Low exposure reference group. After demographic adjustment, High combustion cluster membership was independently associated with 38.4% higher odds of prevalent hypertension (OR 1.38). The prediction model achieved a cross-validated area under the receiver operating characteristic curve (AUC) of 0.849 (SD 0.017). Non-Hispanic Black participants constituted approximately 40% of the High combustion cluster, exceeding their representation in lower-risk clusters. Conclusions Multi-chemical exposome profiling identifies four cardiovascularly distinct subpopulations in the US adult population. Membership in the High combustion exposure cluster was associated with higher odds of prevalent hypertension and disproportionately affected Non-Hispanic Black participants. These findings support the use of multichemical approaches over single-pollutant analyses and highlight the relevance of environmental exposure patterns for making policy and targeted cardiovascular risk stratification.

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.

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.

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.

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.

Neem-derived biopesticides are increasingly applied in agriculture and have been tested in aquaculture research, yet their effects on non-target aquatic invertebrates remain insufficiently characterized. We evaluated the effect of neem extract on the brine shrimp Artemia franciscana using an integrated ecotoxicological approach combining phenotypic, transcriptomic, and histological analyses. Juvenile A. franciscana exhibited dose-dependent mortality and sublethal abnormalities, with a 24 h median lethal concentration of 292.48 mg/L (95% confidence interval, 257.75- 331.89) for mortality and a median effective concentration of 146.36 mg/L (95% confidence interval, 113.04- 189.50) for the combined endpoint "abnormal + dead". In adults, males showed greater mortality than females after extended exposure. High-throughput RNA sequencing revealed broad treatment-associated differences in transcript abundance, with juveniles displaying downregulation of detoxification enzymes and chitin biosynthesis genes, alongside enrichment of immune- and cuticle-related gene ontologies. Adults showed transcriptional signatures of stress, including upregulation of heat shock proteins and cytoskeletal components, and suppression of genes involved in energy metabolism. Chitin precursor enzymes were selectively downregulated in males, and altered carbohydrate metabolism was observed in females. Histological analyses revealed structural deterioration of the brood sac cuticle and reduced ovarian area in treated females, consistent with transcriptomic evidence of impaired exoskeletal and reproductive processes. Overall, neem exposure was associated with phenotypic, histological, and transcriptomic changes in A. franciscana. These results support the use of combined transcriptomic and histopathological endpoints to characterize responses to plant-derived biopesticides in aquatic arthropods.

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.

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.

The Million Veteran Program (MVP) represents the largest and one of the most diverse single cohorts associated with longitudinal Electronic Health Record data (EHR) data. We profiled a subset of samples from MVP using the Illumina Infinium MethylationEPIC Beadchip (EPIC array) to generate one of the largest single cohort methylation dataset to-date. Methylation profiles were analyzed for 45,460 total individuals, with the most populous ancestries composed of 27,455 Europeans, 11,798 African Americans, and 4,859 Admixed Americans. We detail the strict quality control standards implemented to ensure the most robust method of methylation profiling of the MVP cohort. This dataset was then applied to evaluate the effects of smoking exposure on DNA methylation in MVP participants. Ancestry-stratified epigenome-wide association studies (EWAS) of smoking status (ever/never) were performed using over 750,000 probes with certifiable signal. Our multi-ancestry meta-analysis demonstrates replicability with existing EWAS and identifies 3,207 novel probe-smoking associations unlocked via the depth and breadth of data in this cohort.

Browning and eutrophication strongly influence aquatic ecosystems by altering nutrient dynamics, light availability, and food web structure. To investigate their combined effects on aquatic communities, we conducted a nine-week mesocosm experiment in a clear-water north-temperate lake, crossing dissolved organic carbon (DOC) and total phosphorus plus total nitrogen (TP+TN) enrichment treatments. Multi-trophic plankton communities (bacterioplankton, phytoplankton, and zooplankton) were monitored over time using environmental DNA (eDNA) marker gene amplicon sequencing. Beta-diversity analyses highlighted temporal and treatment-driven community restructuring, while PERMANOVA and Principal Response Curve analyses identified the treatments and taxa driving these changes. Our results show that elevated DOC favoured taxa associated with the microbial loop, while nutrient enrichment and lower DOC promoted the green pathway. Threshold responses across trophic levels were observed at 5-7 mg L-{superscript 1} DOC and 30-70 g L-{superscript 1} TP, marking the levels at which compositional shifts propagated through the food web. Overall, this study demonstrated how aquatic communities respond dynamically to browning and nutrient enrichment, offering insight into the mechanisms shaping multi-trophic interactions under a multiple stressor scenario. HighlightsO_LIBrowning and nutrient pulses drove coordinated shifts across bacterioplankton, phytoplankton, and zooplankton. C_LIO_LITemporal community succession and treatment effects were captured through beta-diversity and multivariate ordination analyses. C_LIO_LIThreshold responses propagated through the food web at 5-7 mg L-{superscript 1} DOC and 30-70 {micro}g L-{superscript 1} TP. C_LI Scientific Significance Statement TopicThis study provides insights into the interactive effects of browning and eutrophication on community composition shifts in freshwater ecosystems. Using a mesocosm experiment, we identified thresholds for dissolved organic carbon and total phosphorus + nitrogen concentrations that drove compositional changes across bacterial, phytoplankton, and zooplankton communities, as determined by environmental DNA amplicon sequencing data. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/719940v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@5f11dborg.highwire.dtl.DTLVardef@18d4f6aorg.highwire.dtl.DTLVardef@58cb68org.highwire.dtl.DTLVardef@1924a42_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

Traditionally, studies have explored the impacts of individual water chemistry parameters on the persistence of Mycobacterium spp. and Legionella spp. in isolation with the underlying assumption that these associations are likely monotonic in nature. Yet chemical and microbiological changes are complex, and associations are likely highly combinatorial. In this study, we use interpretable machine learning models to disentangle the integrative and nonlinear associations between water chemistry and occurrence/abundance of Mycobacterium spp. and Legionella spp. Seasonal data from source water, point-of-entry and distribution systems of eight full-scale drinking water systems demonstrated that shifts in overall water chemistry were associated with the changes in microbial abundance during treatment and distribution. Machine learning models indicated moderate predictive ability of integrated water chemistry towards Legionella spp. abundance and towards the occurrence of both Legionella spp. and Mycobacterium spp., whereas predictive performance for Mycobacterium spp. abundance was limited. The association between nitrate and Legionella spp. abundance was disinfectant regimes dependent, while dissolved organic carbon exhibited a concentration dependent response type (i.e., positive and negative association). In chloraminated systems, Legionella spp. abundance was positively associated with ammonia and nitrate, highlighting the critical role of nitrification. Here, it appears that pH likely influences the initial colonization of Legionella spp. while ammonia governs its abundance in drinking water. Overall, this study demonstrates that integrated water chemistry and parameter-specific nonlinear effects collectively explain persistence of Mycobacterium spp. and Legionella spp. in drinking water systems.

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.

Background: Opioid-related mortality in Texas has escalated dramatically, increasingly driven by illicitly manufactured fentanyl. To address local surges in mortality, the Galveston County Health District deployed the Galveston County Opioid Defense Effort (GCODE) in July 2023, leveraging digitally integrated surveillance data from emergency medical services (EMS) and the Medical Examiner to provide targeted naloxone distribution in identified overdose hot spots. Methods: Using a segmented interrupted time series (ITS) design and Poisson regression with robust standard errors, we evaluated the population-level impact of GCODE on opioid-involved mortality through the end of 2025. Data were sourced from the Galveston Area Ambulance Authority (GAAA) and vital statistics (ICD-10 codes). We assessed mortality trajectory changes, the observed fatality ratio among EMS-detected opioid events (the Survival Gap), and demographic and geographic covariates. Results: The Poisson ITS model included 519 weekly observations (N = 14,827 tract-weeks across 101 census tracts). Pre-intervention, opioid mortality increased by 0.16% weekly (IRR = 1.0016; 95% CI: 1.000-1.003; p = 0.011). Following GCODE deployment, the mortality trajectory reversed to a sustained 0.55% weekly decrease (IRR = 0.9945; 95% CI: 0.990-0.999; p = 0.021). The observed fatality ratio among EMS-detected events declined from 7.59% (preintervention mean; SD = 0.111) to 1.71% (post-intervention; SD = 0.042; Chi^2 = 19.824; p = 0.0001). Opioid decedents were significantly younger than the general mortality population (OR = 0.945 per year of age; p < 0.001), and were descriptively more likely to lack documented race/ethnicity data (41.23% vs. 8.27% Unknown; p < 0.001), limiting equity analysis. Conclusions: The findings are consistent with GCODE having meaningfully reduced opioid mortality by substantially lowering event-level lethality. These results suggest that targeted, digitally coordinated harm reduction can decouple overdose incidence from fatal outcomes, with implications for harm reduction program design in structurally constrained environments.

Diet is an important ecological modulator of the oral microbiome, yet population-level evidence on a broader spectrum of food components remains limited. This cross-sectional study investigated associations among dietary intake, oral rinse microbiome, and oral disease conditions in a nationally representative sample of United States adults from the National Health and Nutrition Examination Survey. A total of 3,254 participants with oral rinse microbiome sequencing data were included, with oral conditions classified as oral health, caries-only, periodontitis-only, or co-existing disease. Dietary intake was assessed using 24-hour dietary recalls and summarized as dietary indices and energy-adjusted food components. Associations between diet and the oral microbiome were evaluated using community-level analyses, regression models, mediation analyses, and unsupervised clustering, while accounting for oral conditions. This study found that dietary intake, as a combined variable set, explained 3.6% of the variance in oral rinse microbial community structure; this was comparable to oral disease status or smoking and larger than sociodemographic factors. Healthier dietary profiles, including higher health-associated dietary index scores and greater vegetable and fruit intake, were associated with taxa commonly linked to oral health (e.g., Neisseria, Cardiobacterium and Lautropia). In contrast, added sugars, alcoholic drinks, cured meat, potatoes, dairy products, and higher dietary inflammatory index scores showed opposite association patterns. Mediation analyses suggested that coordinated microbial groups may partly link dietary exposures with oral disease outcomes, particularly for vegetables and added sugars. Additionally, three population-level dietary patterns were identified, among which the plant-rich pattern was associated with more favorable oral health and microbial profiles enriched in nitrate-reducing commensals, including Neisseria and Haemophilus. Overall, dietary intake was associated with oral microbiota composition and oral health conditions, supporting ecological influences of dietary components beyond sugar on oral bacteria and dental diseases. Longitudinal studies are needed to clarify the direction and causality of these relationships.

Non-pharmaceutical interventions (NPIs) have been important for controlling SARS-CoV-2 transmission, particularly before and during initial vaccine rollout. During the pandemic, the US Centers for Disease Control and Prevention issued isolation and masking guidance in case of COVID-19-like illness, a positive SARS-CoV-2 test, or known exposure to SARS-CoV-2. However, the impact of this guidance on mitigating transmission in office workplaces is unclear. We used a network-based mathematical model to estimate the impact of this guidance on SARS-CoV-2 transmission among office workers and their communities. The model represented social contacts in the home, office, and community. We used data from the CorporateMix study to parametrize social contacts among office workers and calibrated the model to represent the COVID-19 epidemic in Georgia, USA from January 2021 through August 2022. In the reference scenario (58% adherence to guidance among office workers and the broader population), workplace transmission accounted for a small fraction of total infections. Reducing adherence among office workers to 0% increased workplace transmissions by 27.1% and increasing adherence to 75% reduced workplace transmission by 7.0%. Increasing adherence to 75% among office workers had minimal impact on symptomatic cases and deaths; increasing it among the broader population was more effective in reducing office worker cases and deaths. In our model, moderate adherence to recommended NPIs in workplaces was effective in reducing transmission, but increasing adherence had limited benefit given workplaces that have low contact intensity and hybrid work arrangements. These results underscore the public health benefits of community-wide adoption of recommended NPIs.

Biodiversity is expected to enhance the stability of ecological communities under environmental stress, but the relative roles of functional, interspecific, and intraspecific diversity remain poorly resolved, particularly under multiple concurrent stressors. We tested how these diversity dimensions shaped the growth and recovery of marine Synechococcus communities in a microcosm experiment manipulating strain composition across four strain-richness levels and two interspecific diversity levels under control, atrazine, warming, and combined atrazine-plus-warming treatments. Functional diversity was quantified from flow-cytometric trait data and analyzed as initial functional diversity during the stress phase and assembled functional diversity during recovery. Contrary to our expectations, higher initial functional diversity was associated with lower community growth during stress, while higher assembled functional diversity was generally associated with weaker recovery. However, these relationships depended on stressor identity and interspecific diversity: in two-species communities, the negative effects of functional diversity were reduced, and under combined stress, higher assembled functional diversity was associated with improved recovery. In contrast, intraspecific diversity consistently enhanced community growth and recovery, while interspecific diversity primarily promoted functional recovery. Together, our results show that functional, interspecific, and intraspecific diversity can influence stress responses through distinct pathways.

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.

Coastal marine ecosystems are increasingly threatened by multiple stressors such as ocean acidification and deoxygenation, but how these co-occurring stressors interact is often poorly understood. This is especially true for tropical coral reefs where deoxygenation is an emerging yet understudied threat. Using hypoxia response curves combined with rigorous pH control, we show that acidification alters hypoxia sensitivity and oxyregulation of reef-building corals in a species-specific manner: three species exhibited increased sensitivity to various degrees, while the fourth showed enhanced tolerance. Consequently, acidification pushes critical hypoxia thresholds into oxygen regimes already prevalent on reefs today, potentially driving shifts in community composition and accelerating risks to reef resilience as these stressors intensify in the future. Our findings challenge assumptions of uniform coral vulnerability under multi-faceted climate change, emphasizing the need for trait-based approaches and to account for stressor interactions in predictive models to better anticipate coral reef futures under rapid climate change.