Precise ecological functional zoning and an understanding of its underlying drivers are fundamental for sustainable watershed management, yet traditional static zoning often fails to capture the spatial transitions and nonlinear feedbacks within social-ecological systems. This study develops an integrated framework to identify ecosystem service bundle (ESB) and quantify ecological buffer zones in the Yellow River Basin (YRB). By coupling the Self-Organizing Map (SOM) with the eXtreme Gradient Boosting-SHapley Additive exPlanations (XGBoost-SHAP) machine learning model, we analyze the nonlinear effects of socio-ecological drivers across multiple scales and project ESB dynamics toward 2030 under Shared Socioeconomic Pathway-Representative Concentration Pathway (SSP-RCP) scenarios.Our results reveal six spatial ESBs, with the SOM algorithm achieving a 93.3% efficiency improvement over K-means in handling high-resolution data. We quantitatively delineate ecological buffer zones (3.7%-9.3% of the basin), revealing a consistent northwestward migration trend driven by shifting hydro-thermal gradients. Driver effects exhibit significant scale dependence: while precipitation remains the dominant factor for water yield, socioeconomic factors like GDP increasingly govern carbon sequestration and habitat quality under future high-emission pathways. To bridge research with practice, we propose a transition from rigid boundaries to differentiated spatial governance, including cross-regional collaborative committees and adaptive planning for migrating buffer zones. This framework provides a quantitative decision-making basis for balancing ecological conservation and high-quality development in major river basins.
Understanding the mechanisms that maintain the stable provision and functionality of ecosystem services (ESs) under global change is essential for safeguarding human well-being and ecological security. However, in the environmentally fragile Qinghai-Tibet Plateau (QTP), the stability and multifunctionality of ESs remain insufficiently explored, particularly regarding their driving pathways and internal association patterns. Here, we developed a long-term dual-scale analytical framework, combining spatial analysis, machine learning-SHAP, and network analysis to reveal the formation and maintenance mechanisms of resistance of ESs (RES) and ESs multifunctionality (ESM). Key findings included: (1) ESs, RES, and ESM exhibited consistent spatial patterns at both grid and ecological function zone (EcoFunction) scales, while ESM showed a declining trend; (2) Landscape patterns were the dominant drivers of RES across scales, with relative importance reaching 29.94%. Climate impacts on ESM shifted from a positive contribution at the grid scale (26.08%) to a negative effect at the EcoFunction scale (38.41%); (3) Human activities and climate exerted the strongest direct and indirect negative effects on RES and ESM, respectively. Landscape patterns and ecological quality provided the strongest positive direct effects on RES and ESM, respectively, and served as core mediators for indirect human activities and climate influences; (4) Carbon storage and habitat quality had the strongest synergy, while their resistance coupling strength peaked at 0.69. This study further proposes differentiated management strategies to promote sustainable ES development on the QTP and advance harmonious coexistence between humans and nature.
Transitions to a new educational ecosystem result in students' academic distress, particularly at the university level. Thus, this study aimed to examine academic distress and help-seeking practices among first-year domestic and international university students in the fields of Engineering and Health Sciences. The study mainly focused on academic distress and help- seeking behavior abided by the help-seeking process model and mind sponge mechanism. A quantitative correlational research design was used. A total of 361 students were selectedusing simple random sampling. Standardized questionnaires were used to measure the variables. Descriptive statistics and Multivariate Analysis of Variance (MANOVA) were used to achieve the study objectives. The results revealed that University students had moderate levels of help-seeking behavior and academic distress. Moreover, male students had higher academic help-seeking behavior and lower academic distress than their female counterparts; whereas academic help-seeking behavior and academic distress were lower for female students. Statistically significant sex differences were also noted in academic distress. Based on the mind sponge theory, measures for the prevention of academic distress should be targeted at the optimization of help-seeking behavior with a special focus on female students who manifest a high vulnerability to academic distress. Moreover, ways such as digital-based interventions that assist in addressing a large number of students at once also merit attention.
Human activities and climate change are intensifying nitrogen loading, hypoxia, and salinity intrusion in estuarine systems, with important implications for nitrous oxide (N2O) emissions. However, the interactive effects of these co-occurring stressors on N2O production remain poorly understood. Here, we combined 15N-18O tracing and molecular analyses to investigate N2O production pathways and their microbial regulation in estuarine sediment based on a series of nitrogen-oxygen-salinity incubation treatments and field observations. Results showed that low salinity under weak hypoxia significantly increased the abundance of nirS and norB genes, indicating an enhanced potential for nitrite reduction to N2O, which in turn promoted N2O production, whereas high salinity mitigated this effect by suppressing Pseudomonas abundance. Nitrate input further stimulated denitrification, amplifying N2O production under weak hypoxia treatments. Heterotrophic denitrification was the major N2O production pathway overall, while under severe hypoxia, the contribution of nitrifier denitrification increased and could reach 65.57%. Elevated oxygen promoted complete nitrification, thereby reducing the contribution of the nitrifier nitrification and nitrifier denitrification pathways. In contrast, elevated salinity enhanced nitrifier denitrification and nitrification-coupled denitrification, associated with increased abundance of Nitrosomonas and Nitrospina. Notably, the low salinity and weak hypoxia zone emerged as a hotspot of N2O production, with a doubling of nitrogen input increasing production rates by approximately 78%. Overall, these findings demonstrate that nitrogen pollution, oxygen depletion, and salinity shifts interactively regulate N2O production in estuarine sediments, highlighting high-risk conditions for N2O emissions and providing insights for mitigating greenhouse gas emissions in human-impacted estuaries.
Typhoon disturbances profoundly reshape coastal microbial ecosystems; however, the coupled responses and co-successional dynamics of bacterial and phytoplankton communities remain poorly understood. Identifying their interactions and key drivers is essential for understanding ecosystem resilience and predicting post-disturbance algal dynamics. Using Zhanjiang Bay as a model system, we analyzed microbial succession across two typhoon events with contrasting intensities. High-throughput sequencing and environmental data were integrated with multiple machine learning models to identify the influence patterns of bacterial communities on phytoplankton diversity. SHAP analysis was applied to quantify feature contributions and detect threshold effects, and network analysis was used to characterize cross-kingdom interactions across successional stages. Microbial communities exhibited consistent directional succession under both typhoons, although Prapiroon induced stronger displacement (2.38-fold in bacteria and 2.53-fold in phytoplankton). Random Forest achieved the best predictive performance (R2 = 0.74, RMSE = 0.23). Temperature and the rare taxon Bdellovibrionota were identified as key drivers, showing clear threshold effects: phytoplankton diversity declined above 30.76 °C and increased when Bdellovibrionota exceeded 0.02%. Diversity peaked immediately after disturbance and declined during recovery, indicating a stage-dependent regulatory shift. Microbial networks followed a "collapse-reorganization-recovery" trajectory, reflecting ecosystem resilience. Our findings reveal a predictable, stage-dependent framework of microbial succession under typhoon disturbance, driven by environmental filtering and biotic interactions. The identified thresholds and microbial indicators provide a basis for recognizing critical temporal windows of elevated bloom risk, highlighting the potential of integrating microbial data with machine learning for adaptive coastal management.
Marine heatwaves are increasing in frequency and intensity, driving persistent changes in kelp forests worldwide. Along the Pacific coast of Baja California, the 2014-2016 marine heatwave produced contrasting post-disturbance states, from persistent urchin barrens to understory-dominated reefs and declining canopy kelp. Kelp forests support reef-fish assemblages that sustain key ecosystem functions, yet how these functions track habitat reorganization after extreme warming remains unclear. Because no pre-heatwave baseline exists for the region, we examined post-disturbance trajectories from 2017 onward without assuming a common starting state across subregions. We analyzed underwater visual census data from 2017 to 2024 across 12 sites spanning three biogeographic subregions (North, Middle, South) along ∼600 km of coastline. We quantified temporal changes in algae, invertebrates, and reef fishes, and assessed fish assemblages using a trait-based framework built on nine ecological traits, including body size, trophic group, growth performance, and maximum fecundity. Taxonomic and functional α-diversity were estimated as biomass-weighted Hill numbers, and β-diversity as temporal β-decay (dissimilarity over time since 2017). Species and traits driving compositional change were identified via SIMPER. Fish secondary productivity and biomass turnover (P/B) were calculated using a temperature-dependent growth model with species-specific life-history parameters and local sea surface temperature. Temporal trends were evaluated with generalized linear mixed models. Reefs followed divergent post-heatwave trajectories across subregions. Fish species richness and functional α-diversity remained stable everywhere, yet this stability masked contrasting regional dynamics in composition. In the North, assemblages showed minimal temporal change, consistent with a persistent urchin-barren configuration. In the Middle, functional β-decay increased over time, driven by shifts in trophic, growth, and body-size traits. The South showed the broadest reorganization, with significant increases in both taxonomic and functional β-decay and the strongest trait signal in maximum fecundity. Macroinvertivore biomass declined significantly in the North and showed a pronounced, though non-significant, decline in the South, with no compensatory increase in P/B among other functional groups. Our findings reveal a decoupling between biodiversity and ecosystem functioning in post-heatwave kelp-forest fish assemblages. Stable diversity metrics can conceal substantial reorganization in how assemblages produce and sustain biomass, and the biomass-dominant groups that underpin ecosystem processes are declining without compensation. Safeguarding these processes will require shifting from tracking diversity alone to directly monitoring and managing functional groups and biomass dynamics.
Clarifying the driving mechanisms of mangrove dynamics is essential for effective ecosystem management, sustaining key ecosystem services and supporting relevant Sustainable Development Goals. However, under the ongoing coupled influences of climate change and bidirectional human interventions, existing studies remain limited in integrating cross-system processes and disentangling complex relationships among multiple drivers. To address these challenges, we develop a Land-Sea Coupled Framework (LSCF) that explicitly links terrestrial and marine systems through riverine transport processes and represents key land-sea interaction processes using quantifiable variables. By integrating intelligent models and post-hoc interpretation techniques, the framework enables the identification of key drivers, as well as the characterization of their nonlinear effects and interactions. China's mangroves are used as a representative case to operationalize and demonstrate the framework. Results reveal a hierarchical structure in the driving mechanisms of mangrove dynamics. Specifically, land-use/cover change acts as the dominant driver, exhibiting increasingly nonlinear effects over time and significantly modulated by tidal range. Climatic drivers primarily function as indirect modulators, with stronger influences during contraction, whereas hydrogeomorphic features broadly shape ecosystem response patterns. Moreover, the co-occurrence of multiple climatic stressors may generate synergistic effects, thereby increasing the risk of mangrove contraction and highlighting the potential threat of compound climate extremes. Overall, the LSCF provides a transferable analytical framework for elucidating complex mechanisms of mangrove dynamics, and the resulting regional-scale insights can inform adaptive management and policy-making at local scales.
The utilization of solar energy has been integral to biological evolution, industrial revolution, and humanity's journey across the past, present, and future, shaping both natural ecosystems and technological advancements. Effectively harnessing this sustainable energy is crucial for addressing the escalating and coupled global energy-water-environment crises. This tutorial review advances an integration paradigm in which hydrogels serve as adaptable and scalable matrices enabling cost-effective solar harvesting that aligns with sustainability and economic feasibility. We first summarize the challenges inherent in existing solar technologies and extrinsic factors beyond material design that influence their sustainable development. Next, we highlight the transformative potential of integrating hydrogels into advanced solar systems through hierarchical energy utilization, multifunctional coordination, and enhanced environmental adaptability and stability. Finally, we assess the broader technological and societal implications of integrated solar harvesting systems by considering regional economic disparities, local resource availability, societal needs, and environmental impacts. By offering a pragmatic perspective on hybrid solar technologies, this tutorial review bridges academic innovation and practical application, charting pathways toward high-efficiency, cost-effective solar energy utilization, with hydrogels serving as a versatile integration platform. These advancements not only foster sustainable development but also contribute to aquatic and terrestrial ecosystem resilience while driving progress toward more resilient, eco-friendly societies.
Trait-based frameworks, notably Grime's competitor-stress-tolerant-ruderal theory, offer a powerful lens for predicting how environmental fluctuations govern community structure. Yet, classical ecological models assume environments combining extreme stress and intense disturbance are non-viable for sustained colonisation, leaving a critical bottleneck in our ability to predict how microbial systems withstand compounded operational pressures. This gap severely hinders the predictive management of engineered microbiomes critical for global waste-to-energy conversion. Here we extend the application of classic ecological frameworks by demonstrating that anaerobic digester microbiomes deploy distinct, predictable life-history strategies across a 182-day compounded gradient of biomass turnover and organic loading. High-intensity single-event disturbances drive severe volatile fatty acid accumulation (propionate reaching 2,955 mg L-1), selectively shifting the microbiome toward stress-tolerant and stress-tolerant-ruderal strategies. Traits associated with ribosome function, molecular chaperones, and enzymatic reactive oxygen species detoxification were particularly enriched under highly disturbed conditions. Conversely, intermediate regimes were associated with ruderal strategies that prioritise rapid growth over resource-uptake efficiency, dropping total chemical oxygen demand removal to 41%. Cross-system comparisons encompassing anaerobic digestion, activated sludge, and soil ecosystems, revealed both universal and context-dependent ecological traits. Survival-associated traits linked to cell maintenance and repair, protective mechanisms, and cell motility were universally associated with stress-tolerant or ruderal strategies across ecosystems, whereas nutrient transport and metabolic traits exhibited greater context dependency. These insights establish a gene-resolved framework that reconciles microbial trait selection with ecological theory, providing a roadmap to engineer microbiome resilience against process failures.
Aim: The study evaluates the effectiveness of wearable biometric devices, geofencing systems, and artificial intelligence algorithms in improving the quality of life and autonomy of individuals with Prader-Willi syndrome. It analyses the impact of digital ecosystems on reducing caregiver burden and personalizing therapy through objective data analysis. Materials and Methods: A systematic literature review was conducted in PubMed, Web of Science, and the Cochrane Library databases since 2019. Research focused on metabolic monitoring, the use of gamification and virtual reality in rehabilitation, and the implementation of smart home technologies for patients with rare genetic syndromes. Analysis indicates that data from wearable devices enables the detection of prodromal states, mitigating episodes of hyperphagia and aggression. Geofencing systems provide a safe environment for autonomous physical activity, improving cardiovascular fitness and reducing caregiver anxiety. Artificial intelligence algorithms, by personalizing the energy balance with a precision of 10 kilocalories, significantly optimize weight reduction. Conclusions: The digital support ecosystem redefines the care paradigm for Prader-Willi syndrome. Replacing human supervision with autonomous algorithmic control promotes behavioural stabilization and allows for greater patient self-determination. This process increases biological safety and significantly reduces the burden on caregivers, forming the basis of modern, individualized therapy.
Marine nitrogen fixation is a key process to support and maintain the ocean's primary production, yet our knowledge of the distribution and diversity of the diazotrophic microbes that are capable of fixing nitrogen is very limited. Here, integrating microscopic and metagenomic data, we determine the biogeography and richness of the main diazotrophic taxa across the global ocean. Analyzing 22,000 records and 15 species, we deduce a latitudinal gradient in diazotroph richness, with higher richness to the tropics driven by temperature and nutrient levels. Cyanobacteria dominate in nutrient-poor gyres, while non-cyanobacterial diazotrophs thrive in nutrient-rich zones. Across the global ocean, diazotroph richness is found to correlate positively with nitrogen fixation rates, suggesting a positive biodiversity-ecosystem function relationship. While this relationship is robust to spatial autocorrelation and confounding environmental drivers, spatial dependence in the global datasets and potential unmeasured covariates may influence local-scale inferences. The findings suggest that positive biodiversity-ecosystem functioning relationships with implications for global biogeochemical cycling exist in marine plankton.
Postharvest grain deterioration threatens global food security and economic stability, arising from complex interactions between intrinsic grain properties and environmental stressors. Despite advances in detection and control technologies, critical bottlenecks persist, including insufficient understanding of multi-factor synergies, limited scalability for smallholders, and the lack of integrated predictive management frameworks. This review systematically analyzes these gaps by constructing a novel framework centered on "Environmental drivers, biological responses, and technological interventions." It critically synthesizes deterioration mechanisms, provides a decision-oriented comparative evaluation of detection and control technologies based on performance, cost, scalability, and user scenarios, and identifies key research voids in modeling, generalizability, and climate resilience. Future breakthroughs hinge on interdisciplinary innovation, prioritizing: predictive digital twin systems integrating storage physics, biology, and quality models; intelligent responsive green materials and low-energy storage designs; and standardized data ecosystems with blockchain traceability to incentivize quality preservation. This review provides three integrated outputs: a qualitative framework linking environmental drivers, responses, and interventions; a scenario-specific decision matrix comparing technologies by performance, cost, and scalability; and a research roadmap prioritizing digital twins, green materials, and data ecosystems. The framework aims to translate mechanistic insights into practical management decisions and guide grain storage toward intelligent, resilient, and sustainable systems.
Eutrophication is widely recognized for increasing primary production, yet how changes in basal energy allocation reorganize food web architecture and stability remains insufficiently resolved. Across three eutrophic shallow lakes spanning a productivity gradient, we combined stable isotope analysis with a Bayesian mixing model (EcoDiet) to quantify the relative contributions of five basal resources to consumers. We then linked phytoplankton dominance to energy-channel diversity, trophic redundancy, and interaction-weighted modularity. Results showed that increasing phytoplankton dominance progressively concentrated basal carbon allocation into a single pelagic pathway. This shift reduced energy-channel diversity and trophic redundancy, suggesting erosion of functional buffering capacity. Conversely, phytoplankton dominance simultaneously strengthened network modularity. These results revealed a structural-functional decoupling that shifted food webs toward more pelagic-based trophic pathways and structurally modular configurations. Thus, nutrient enrichment influences ecosystem stability in multidimensional ways, altering not only productivity but also the distribution and pathways of energy through trophic networks.
The isotopic composition of atmospheric carbon dioxide (δ13Catm) provides insights into the terrestrial carbon cycle. However, long-term global δ13Catm maps with both high spatial resolution and continuous temporal coverage remain scarce. Here, we present a new global terrestrial dataset of monthly δ13Catm isoscapes from 2001 to 2020 at 0.05° spatial resolution, developed by integrating in situ observations with optimized 4D CO2 concentration fields from inversion outputs, reanalysis data, and geographic information using machine learning. Among four tested models, the Gradient Boosting Machine demonstrated the highest predictive performance under random validation (R2 = 0.80, RMSE = 0.12‰) and maintained robust performance across three spatially independent validation frameworks (R2 = 0.56-0.67, RMSE = 0.16‰-0.19‰). Key predictors were air temperature and atmospheric CO2 concentration. The resulting global terrestrial isoscapes reveal strong spatial and temporal heterogeneity. Model predictions closely align with National Oceanic and Atmospheric Administration (NOAA) marine boundary layer (MBL) observations in terms of trend magnitude, seasonal amplitude (< 0.13‰ deviation), and latitude gradient (< 0.2‰). In our study, δ13Catm seasonal amplitude varies from 0.06‰ in Southern Hemisphere mid-latitudes to 0.6‰ in Northern Hemisphere high latitudes, indicating strong hemispheric asymmetry. Moreover, over 99.8% of global terrestrial grid cells show negative trends in all seasons, with a global terrestrial average annual depletion rate of -0.030‰ ± 0.0006‰ year-1. The trend shows stronger depletion during summer and autumn, reaching its peak in August (-0.035‰ ± 0.0012‰ year-1), while spring and winter seasons remain comparatively stable. This study delivers a long-term, high-resolution global terrestrial δ13Catm isoscape dataset, offering a valuable tracer for carbon cycle research and, importantly, robust data support for large-scale investigations of carbon-water coupling in terrestrial ecosystems.
The Manila clam, Ruditapes philippinarum, is a commercially valuable non-native species that has successfully colonized European coastal ecosystems. Here, by integrating physiological experiments with a metabolic performance-based habitat suitability mapping approach, we investigate its thermal tolerance and habitat suitability in the Mediterranean Sea, with a focus on the Berre Lagoon. Using a respirometry-based thermal performance curve modelling, we quantified respiration rates across a temperature gradient and fitted a Thermal Performance Curve (TPC) selected via AICc comparison of 22 candidate models, with the Johnson and Lewin (1946) model providing best fit. The optimal temperature (Topt) was identified at 32.89°C, with a narrow thermal safety margin of 1.49°C preceding the critical thermal maximum (CTmax) of 34.38°C. Seasonal and spatial projections of Thermal Habitat Suitability (THS) for the Mediterranean populations indicate that winter remains persistently unsuitable across present and future scenarios, with minimal change over time. Conditions appear to worsen in future spring, while improving in future summer and, to a lesser extent, in future autumn. Long-term monitoring in the Berre Lagoon indicated an increase in favorable thermal conditions over time, supporting the species' persistence. These findings demonstrate the critical role of integrating physiological thresholds into ecological models to support effective management under climate change. Furthermore, they improve our capacity to predict present and future dynamics of this invasive and commercially important species, including implications for its aquaculture under accelerating Mediterranean environmental change.
Mosses are key components of terrestrial ecosystems and provide important systems for studying plant diversity, adaptation, and genome evolution. Lewinskya is a species-rich moss genus in Orthotrichaceae, but species delimitation and phylogenetic reconstruction within the genus remain difficult because diagnostic characters are often subtle or convergent. Chloroplast genomes can provide useful genomic resources and complementary evidence for comparative and systematic studies. This study aimed to generate new Lewinskya plastome resources and evaluate plastome structure, sequence variation, codon usage, and plastid-based phylogenetic relationships in the genus. Five newly sampled Lewinskya chloroplast genomes were assembled from genome-skimming data, including three circular plastome assemblies and two high-quality single-scaffold assemblies. Together with the published plastome of L. incana, the six Lewinskya plastomes ranged from 122,258 to 123,526 bp and showed conserved genome organization, gene content, GC composition, and inverted repeat boundaries. Each plastome encoded 128 genes, including 83 protein-coding genes, 37 transfer RNA genes, and eight ribosomal RNA genes. A total of 520-542 simple sequence repeats were detected per plastome, with mononucleotide repeats being dominant and most repeats located in the large single-copy region. Comparative analyses revealed no large-scale rearrangements, but several localized divergence regions were detected. Nucleotide diversity analysis identified 11 highly variable regions, including five genic regions (rps18, rpl22, infA, rpl32 and rps3) and six intergenic spacers, most of which were located in the large single-copy region. Codon usage patterns were highly similar among species and showed a preference for A/T-ending codons. Phylogenetic analyses based on 78 plastid protein-coding genes from 26 Orthotrichaceae plastomes strongly supported the sampled Lewinskya species as a clade, although some deeper relationships within the genus remained weakly resolved. The newly assembled Lewinskya plastomes expand genomic resources for Orthotrichaceae and show that chloroplast genome evolution in the sampled species is structurally conservative but contains informative localized variation. The identified repeat loci and highly variable regions provide candidate markers for future species identification and population-level studies. Plastome-scale data offer useful evidence for Lewinskya systematics, but broader taxon sampling and integration with nuclear genomic and morphological evidence will be needed to resolve difficult interspecific relationships.
The widespread use of tetracycline and its consequent aquatic pollution pose significant risks to environmental and human health. Recently, microalgae have been demonstrated as a promising, environmentally friendly and non-chemical way to reduce tetracycline levels; however, biodegradation pathways and mechanisms remain elusive. Consequently, this study systematically investigated the pathways and functional enzyme-mediated mechanisms of tetracycline biodegradation by a marine model algal species (Phaeodactylum tricornutum). The results revealed that P. tricornutum exhibits reasonable physiological adaptation and tolerance to tetracycline exposure through cellular homeostasis and the activation of energy reallocation. Simultaneously, P. tricornutum was able to biodegrade tetracycline (e.g., 88.4% of a 4 mg/L tetracycline solution). It was also proposed that this diatom degrades tetracycline via C-N bond cleavage of metallo-beta-lactamase, demethylation by cytochrome P450, deamination by cytochrome P450 and ornithine cyclodeaminase, oxygenation by flavin adenine dinucleotide (FAD)-dependent monooxygenase, reduction and ring-opening by antibiotic biosynthesis monooxygenase. This study provides multidimensional theoretical and empirical support for addressing antibiotic pollution in aquatic ecosystems.
Elevational gradients are natural laboratories for plant ecological strategies, much as altitudinal shifts in tree composition have advanced understanding of forest assembly and dynamics. Yet, functional trait-based investigations into the ecological strategies of P. massoniana plantations communities along subtropical altitudinal gradients remain remarkably scarce. This knowledge gap hinders science-based management of these forests in subtropical montane habitats. This study investigated pure P. massoniana plantations across four altitude gradients (1200-1500 m) in the subtropical mountain forest ecosystem. We quantified functional traits of different organs (leaves and roots) in P. massoniana and understory shrubs to decipher their coordinated variations with altitude. Our study revealed divergent trade-offs in the leaf economics spectrum (LES), root economics spectrum (RES), and whole-plant economics spectrum (WES) of woody plants in P. massoniana plantations along subtropical montane altitudinal gradients. P. massoniana showed a shift from acquisitive to conservative trait patterns with increasing elevation, whereas understory shrubs exhibited opposite strategies. Significant correlations emerged between leaf and root traits within the P. massoniana plantations communities. The plant economics spectrum showed significant consistency across different organs of species, and there were significant positive correlations among LES, RES, and WES. The divergent altitude-related ecological adaptation strategies observed between P. massoniana and shrubs likely reflect shrubs' heightened sensitivity to microenvironments (e.g., canopy effects) and niche complementarity, although this interpretation remains speculative and requires further research. Overall, there is a consistent resource trade-off strategy among different organs of plants in P. massoniana plantations in subtropical mountainous areas to respond to the direct or indirect effects of altitude. This study provides a theoretical basis at the functional trait level for the adaptive management of P. massoniana plantations in subtropical montane regions.
Microplastics' (MPs) capacity to sorb antibiotics in soil ecosystems poses emerging risks, yet their combined toxic effects on soil fauna remain poorly understood. Consequently, we examined the gut toxicity and antibiotic resistance genes (ARGs) of polystyrene MPs (PS-MPs) and the macrolide antibiotic roxithromycin (ROX) in Eisenia fetida. Overall, although co-exposure suppressed gut barrier gene expression (occludin and ZO-1), it did not worsen bacterial translocation (LPS and LBP) relative to single exposures, which is associated with the significant upregulation of antibacterial defense indicators (TLR and CCF), potentially enhancing bacterial clearance. Additionally, PS-MPs mediated the reduction of ROX bioaccumulation by 34.78%, which contributed to the antagonistic interactions observed across multiple indicators, including attenuated deterministic assembly of gut microbiota and ARGs under co-exposure. Beyond enriching resistant Actinobacteria (e.g., Streptomyces and Actinophytocola), ROX also enriched plastisphere-associated pathogenic taxa Escherichia and Enterococcus, as did PS-MPs. These taxa were closely implicated in gut barrier dysfunction and exhibited the strongest correlations with gut ARGs and mobile genetic elements (MGEs) profiles, particularly macrolide-lincosamide-streptogramin B (MLSB) resistance genes (mphA-01, oleC) and MGEs (intI-1(clinic), tnpA-02). Though co-exposure did not increase gut ARGs and MGEs abundance, the enrichment of gut-dominant MLSB resistance genes and MGEs extended to earthworm body tissue, notably driven by PS-MPs, while ROX increased intI-1 (clinic), the strongest contributor to overall variation. PLS-PM revealed that tissue ARGs and MGEs enrichment was associated with gut bacterial translocation driven by dysbiosis-induced activation of LPS-TLR signaling pathways, raising concerns about ARGs dissemination through earthworm-derived traditional medicine and food chains.
Increasingly, hospitals are recognizing the need to address the high mental health care needs of individuals with chronic illness, including congenital heart disease (CHD). This qualitative study explored health professionals' views on integrated mental health care in CHD. Individual, semi-structured interviews were conducted with health professionals from diverse disciplines at five CHD centers in the United States, Australia, and Switzerland. Each center had a distinct model of mental healthcare integration and a unique healthcare ecosystem. The Consolidated Framework for Implementation Research was used to guide study design and analysis. Verbatim transcriptions were analyzed thematically using MAX Qualitative Data Analysis (MAXQDA) software. Health professionals representing medicine, psychology, nursing, social work, education, and healthcare administration participated (N = 46, 58% response rate, 72% women, M = 15.5 ± 8.0 years of professional experience, interview duration: M = 47.9 ± 18.8 min). Five key themes were identified: (1) high need and demand for mental health care among individuals with CHD and their families; (2) multiple, inter-related barriers to care, including stigma and socioeconomic factors; (3) barriers to mental healthcare integration for CHD centers, including understaffing, time and fiscal constraints, and lack of clear referral pathways; (4) strategies to promote integration, including interdisciplinary teamwork and regular communication with mental health professionals embedded in cardiac care; and (5) facilitators of access to care, including routine mental health screening, multiple entry points across the medical trajectory, a preventive focus, and skills-based staff training. Results highlight the need for innovative implementation strategies to accelerate access to integrated mental healthcare for individuals with CHD across the lifespan.