Search Results (5,436)

Tree architecture is a critical determinant of plant performance, light capture, biomechanical stability, and resource allocation. However, the multidimensional functional trait space and multiscale allometric scaling mechanisms underlying different architectural types in Malus remain poorly understood. This study investigates the multidimensional functional trait space and multiscale allometric scaling relationships among three typical architectural types (weeping, upright, and spreading) in Malus. A total of 206 germplasm accessions were analyzed by integrating nine core functional traits spanning macro-architectural, branch biomechanical, and leaf economic dimensions. Principal component analysis revealed that architectural differentiation is primarily driven by macro-architectural and branch biomechanical traits, alongside coordinated contributions from leaf economic traits. Functional diversity analysis indicated that the upright and spreading types exhibited higher functional richness, while the weeping type displayed the highest functional divergence but minimal or no functional overlap with the upright and spreading type, reflecting strong niche specialization under artificial selection. Multiscale allometric analyses demonstrated significant divergence in resource allocation strategies across hierarchical levels. At the whole-tree level, architectural types differed markedly in height–diameter and height–crown scaling relationships. At the branch level, conserved positive allometric scaling was observed, with the weeping type showing higher intercepts indicative of increased mechanical investment. At the leaf level, consistent negative allometry between petiole length and leaf area suggested optimized resource allocation for light capture. These pronounced differences suggest distinct ecological adaptation strategies: the weeping type prioritizes biomechanical compensation for pendulous branches and optimized light capture in loose canopies; the upright type emphasizes vertical light competition and mechanical compactness; the spreading type balances lateral expansion and spatial filling efficiency, reflecting differentiated resource allocation patterns shaped by artificial selection. Overall, this study reveals that tree architecture in Malus is shaped by coordinated trait interactions across multiple scales, leading to distinct ecological strategies and resource allocation patterns. These findings provide new insights into the structure–function co-evolution of woody plants and offer a theoretical framework for functional trait-assisted breeding of ornamental tree architectures. Full article

Wildfires have historically shaped Mediterranean ecosystems, fostering the adaptation of fire-resilient species such as Pinus halepensis Mill. Assessing post-fire resilience is essential to understand landscape recovery and guide forest management. This requires evaluating the speed, intensity, and trajectory of vegetation recovery relative to a defined baseline, although the influence of control point selection and baseline configuration remains unclear, despite its critical role in shaping the interpretation of recovery dynamics. This study proposes a methodological framework to assess the resilience of P. halepensis using 14-year Landsat time series following wildfire events, combined with image segmentation algorithms and Object-Based Image Analysis (GEOBIA). The analysis integrates two complementary vectors: (i) temporal evolution of NDVI and (ii) spectral probability of assignment to P. halepensis. Results indicate that NDVI suggests an average vegetation recovery time of seven years; however, spectral probability remains below 40% during this period, indicating slower tree cover recovery. Field inventories confirm that full recovery requires more than 15 years, with early stages dominated by shrublands, mainly Quercus coccifera. These findings show that NDVI alone overestimates resilience and that control selection and baseline configuration strongly influence assessments. GEOBIA enhances the ecological precision of resilience evaluation. Full article

Complex psychosis is a clinically relevant rehabilitation construct rather than a formal diagnostic category and refers to psychotic illness associated with treatment-resistant symptoms, functional impairment, and additional cognitive, psychiatric, neurodevelopmental, or physical health complexity. In this clinician-oriented narrative review, we synthesised current evidence on rehabilitation interventions for adults with complex psychosis, integrating direct evidence from specialist rehabilitation settings with indirect evidence from schizophrenia-spectrum studies when clinically informative. We searched major clinical databases, prioritised guidelines, systematic reviews, meta-analyses, and controlled studies, and organised the synthesis by functional domain and pathway relevance. Evidence was strongest for cognitive remediation, particularly when combined with broader psychiatric rehabilitation or vocational support, for family interventions in relapse prevention, and for individual placement and support in competitive employment. Social–cognitive and metacognitive interventions appear clinically valuable, although transfer to real-world functioning is more variable. Community-based rehabilitation, supported accommodation, illness self-management, and ecological adaptation strategies remain central to functional recovery when embedded within multidisciplinary pathways. Digital and virtual interventions are promising adjuncts, but their efficacy remains heterogeneous and implementation challenges include engagement, privacy, and service integration. Overall, rehabilitation in complex psychosis is most convincing when it is personalised, measurement-based, and delivered through integrated service models linking assessment, intervention selection, supported living, and recovery-oriented care. Full article

The availability of high-resolution oceanographic data is critical for evidence-based coastal environmental management and climate resilience planning, yet it remains constrained by observational gaps and the prohibitive computational cost of fine-scale hydrodynamic modeling. While downscaling techniques provide a viable pathway, current data-driven approaches often lack statistical physical associations, overlook multivariate environmental interactions, and struggle to represent complex coastal topography. To address these limitations, we present MEOFGAN—an environmentally informed downscaling framework that integrates multivariate empirical orthogonal function (MEOF) decomposition with a generative adversarial network (GAN). The model extracts physically interpretable spatial modes of coupled ocean variables, learns their cross-scale transitions through adversarial training, and systematically incorporates high-resolution bathymetry as a static environmental constraint to enhance spatial fidelity. When applied to the Bohai Sea, MEOFGAN successfully downscales sea surface temperature (SST) and sea surface height (SSH) from 1/4° to 1/12°, achieving error reductions of 30–68% compared to benchmark methods while preserving ecologically relevant structural patterns (SSIM > 0.92). The framework demonstrates strong generalization by reconstructing 500 m resolution distributions of chlorophyll-a (Chl-a), dissolved oxygen (DO), and salinity in Bohai Bay, capturing fine-scale environmental gradients during a documented algal bloom event. This work establishes a methodological framework that can be transferred as a paradigm for generating high-resolution coastal datasets. Rather than serving as a universally transferable pre-trained model, the framework requires region-specific training and application. Data generated in this manner can directly support water quality monitoring, eutrophication assessment, habitat mapping, and regionally tailored climate adaptation strategies. Full article

This study developed a comprehensive framework integrating ecosystem services (ESs), ecological adaptability, and ornamental value to guide tree species selection in historic cities constrained by soil salinization and subsurface heritage conservation. Taking Kaifeng, Henan Province, as a case study, we employed field surveys, i-Tree Eco, the Analytic Hierarchy Process, and K-means clustering to evaluate trees across protective, park, attached, and square green spaces. Results showed that carbon-related services dominated Kaifeng’s urban ES profile, with carbon storage (CS) and sequestration (CSE) value densities of 9.09 ¥·m⁻² and 0.84 ¥·m⁻²·y⁻¹, respectively. Air pollutant removal (AR) (0.21 ¥·m⁻²·y⁻¹) and P (0.009 ¥·m⁻²·y⁻¹) values remained comparatively low. Camphora officinarum Nees ex Wall delivered the highest annual ES value per tree (33.24 ¥·y⁻¹). Plaza greenery outperformed other space types in overall service provision, and deciduous broadleaf species generated greater ES value than evergreen conifers. Cluster analysis identified four functional groups: stress-tolerant pioneers, balanced adapters, high-efficiency carbon sinks, and ornamental specialists—each suited to specific green space contexts. This integrated framework offers a transferable approach for evidence-based tree selection in saline historic cities, supporting nature-based solutions in urban green space (UGS) planning. Full article

The molecular mechanisms underlying freezing recovery in vertebrates, particularly in teleost fish, remain inadequately understood. This study utilized an integrated approach combining brain transcriptomics and gut microbiota analysis to investigate the recovery process in the freeze-tolerant species Perccottus glenii following experimental freezing and thawing. Significant transcriptomic reprogramming was observed in brain tissue, with the PPAR signaling pathway strongly activated immediately upon thawing (R0), potentially facilitating lipid metabolism and neuroprotection during ischemic stress. After 4 h of recovery (R4), circadian rhythm pathways were significantly upregulated, suggesting a potential role in coordinating metabolic recovery during reperfusion. Concurrently, gut microbiota analysis revealed substantial community shifts, characterized by a marked decrease in Bacillota and an increase in Pseudomonadota during the initial recovery phase. These findings suggest that successful freezing recovery in P. glenii is associated with coordinated changes in brain and gut, highlighting potential roles of metabolic adaptation and microbial ecological dynamics under the specific freezing protocol employed. Full article

Wetland ecosystems have been a central focus of ecological research for an quite some time. Nevertheless, the degradation of wetland riparian zones has markedly accelerated due to anthropogenic activities, climate change, and habitat heterogeneity. The objective of this paper is to investigate the differences in functional traits of riparian plants under changing wetland environments on a karst plateau, as well as to elucidate the adaptive strategies of wetland plants across different habitats. This study examines the Caohai Wetland located on the Guizhou karst plateau, selecting the leaves of four dominant plant species (Phragmites australis, Onopordum acanthium, Galium odoratum, Paspalum distichum) in the Caohai Wetland lakeshore zone and analyzes the influence of soil factors on the variation of plant functional traits within the wetland riparian zone. The results reveal that: (1) significant differences exist in the functional traits of dominant plants in the riparian zones of karst plateau wetlands, with complex interrelationships among these traits; (2) the coefficients of variation for magnesium (Mg) and calcium (Ca) in the soil are notably high (79.53% and 67.21%, respectively), whereas soil oxidation-reduction potential (ORP) exhibits the lowest coefficient of variation (4.36%)—furthermore, the convergent variation in specific leaf area (SLA) and leaf dry matter content (LDMC) directly reflects the strong environmental filtering imposed by this habitat—and (3) redundancy analysis (RDA) indicates that leaf length (LL), specific leaf area (SLA), leaf area (LA), and plant carbon content (PCC) are particularly sensitive to environmental changes, while soil calcium (Ca), total nitrogen (TN), water-dispersible clay (WDR), soil organic matter (SOM), soil moisture content (SPMC), and total potassium (TK) constitute the principal soil factors influencing plant adaptive strategies in karst plateau wetlands. In conclusion, this study demonstrates that adaptation to karst wetland habitats is mediated through trade-offs in the allocation of photosynthetic products and the regulation of carbon (C), nitrogen (N), and phosphorus (P) nutrient balances under calcium-enriched and phosphorus-limited conditions, thereby reflecting the response characteristics of functional traits in karst plateau wetland plants to environmental changes. Full article

DNA methylation constitutes a primary layer of epigenetic regulation in plants, operating across three sequence contexts (CG, CHG, and CHH) through distinct enzymatic pathways. Over the past fifteen years, accumulating evidence has shown that DNA methylation varies substantially among individuals and populations of wild plants, sometimes independently of underlying genetic polymorphism. This variation can influence gene expression, transposable element activity, and phenotypic traits relevant to ecological adaptation. Population epigenetics, the study of methylation variation at the population scale, has matured from initial surveys using methylation-sensitive amplified fragment length polymorphism (MS-AFLP) into a discipline increasingly reliant on reduced-representation bisulfite sequencing (epiGBS, bsRADseq), whole-genome bisulfite sequencing (WGBS), enzymatic methyl-seq (EM-seq), and direct long-read detection by nanopore sequencing. These methodological advances are opening population epigenetics to non-model organisms across the full breadth of the plant phylogeny, from angiosperms and gymnosperms to ferns and bryophytes. We cover (i) the molecular machinery underlying plant DNA methylation, including the debated status of N6-methyladenine (6mA); (ii) empirical evidence for natural epigenetic variation in plant populations, spanning clonal, invasive, and outcrossing species; (iii) the methodological toolkit available for population-scale methylation profiling, with emphasis on approaches suitable for non-model taxa; and (iv) the ecological and evolutionary significance of population epigenetic variation, including transgenerational inheritance, stress memory, epigenetic clocks, conservation applications, and the emerging integration of epigenetics into the extended evolutionary synthesis. We identify critical knowledge gaps, particularly the near-complete absence of population-level epigenetic data for bryophytes, ferns, and lycophytes, and outline priorities for future research. Full article

Ecological resilience (ER) describes the ability of ecosystems to resist, adapt, and recover from external shocks. How to improve ER has become a crucial component of high-quality development (HQD) in the new era. Therefore, there is an urgent need to investigate the synergistic relationship between HQD and ER. In this study, taking the Yellow River Basin as an example, long-term time series data (2008–2022) were used at the provincial scale. Then we developed a logical framework to reveal the interrelationship and intrinsic mechanism between HQD and ER. Next, we explored the spatiotemporal coupling characteristics of HQD and ER using a comprehensive evaluation model and coupling coordination analysis. We found that from 2008 to 2022, the comprehensive level of HQD and ER fluctuated, and the coupling coordination degree showed significant spatial distribution characteristics. Meanwhile, from 2008 to 2022, the spatial evolution level of HQD increased in 89% of the study regions, while ER improved markedly across most regions. Furthermore, using principal component analysis (PCA), we analyzed the driving factors for HQD and ER. The analysis revealed that economic development, green innovation, livelihood improvement, and ecological adaptation play significant roles in promoting the coordinated development of HQD and ER. This research can serve as a reference and methodological guidance for achieving high-quality and sustainable development in the Yellow River Basin. Full article

Disability is frequently theorized through a polarized medical-versus-social binary that can obscure the developmental, relational, and sociocultural processes through which bodily difference becomes psychologically meaningful. This study examines how adults with congenital or early-onset physical disabilities narrate and negotiate disability in everyday life, using psychoanalytic concepts as a complementary heuristic lens within an explicitly interdisciplinary framework that integrates developmental resilience and disability theory. Thirty-five in-depth life-story interviews were conducted with seven adults (25–40 years) across approximately five sessions per participant over two months. Data was analyzed using thematic qualitative content analysis, combining systematic coding of manifest content with interpretive attention to symbolic and relational meanings, while cross-checking psychoanalytic interpretations against developmental and social-disability perspectives. Four recurring compensatory patterns were identified: (1) symbolic resignification and verbal normalization (discursive reframing and minimizing disability); (2) achievement-oriented self-positioning (performance and perfectionistic striving); (3) compensatory role assumption (caregiving/protector roles and mastery enactments); and (4) silent family dynamics (familial denial and narrative). Within the specific context of this study, these patterns appeared to function as regulatory efforts to sustain self-cohesion, agency, and belonging. However, the narratives suggest that when these strategies manifest as rigid ideals of ‘overcoming’ and hyper-competence, they may carry a significant subjective cost for participants. Compensatory behaviors are best understood as ecologically embedded regulatory processes shaped by relational resources (experienced as containing/“holding”) and by sociocultural devaluation linked to ableist norms. An integrated model is proposed in which body, self, and environment co-constitute disability across development, clarifying when compensatory strategies support creative adaptation versus defensive rigidity. Full article

Climate change has emerged as a defining global crisis, with the frequency and intensity of climate-induced disasters rising sharply and imposing disproportionate costs on developing economies and small island states. This article examines the role of climate-resilient infrastructure as a central pillar of climate-smart growth, integrating mitigation, adaptation, and long-term development objectives. It situates climate-resilient infrastructure within a planetary health setting, emphasizing the interdependence between human well-being, ecological systems, and infrastructure resilience. Climate-resilient infrastructure, not merely seen as an engineering solution but as a public good that generates significant positive externalities, reduces systemic macroeconomic risk and delivers welfare gains that exceed private financial returns. It discusses the cross-country heterogeneities in resilience outcomes, driven by differences in geographic exposure, economic capacity, institutional quality, and political economy constraints. Building on this, the study advances a welfare-based approach to infrastructure prioritization that incorporates service disruptions, distributional impacts, and fiscal risk, rather than asset values alone. It further outlines policy and financing strategies to bridge the gap between social and private returns, including public investment, concessional finance, blended instruments, and nature-based solutions. By embedding infrastructure within a planetary health lens, the paper argues that resilient systems are critical not only for safeguarding lives and livelihoods, but also for sustaining ecological stability, reducing health risks, and enabling inclusive, sustainable, and climate-smart economic growth. Full article

Geological hazards induced by large-scale and high-intensity mining activities worldwide are primary drivers of regional ecological degradation and pose significant threats to human safety and property. To construct efficient monitoring systems and enhance early warning capabilities, it is essential to clarify the formation mechanisms of various hazards and the suitability of corresponding technologies. Focusing on four typical geological hazards prevalent in mining areas (surface subsidence, ground fissures, landslides, collapses, and sinkholes), this paper characterizes their specific features and monitoring requirements. It systematically analyzes the physical principles, accuracy levels, and technical advantages and limitations of ground-based, aerial, and spaceborne monitoring, as well as multi-source remote sensing data fusion and emerging technologies (e.g., distributed optical fiber, light detection and range, microseismical monitoring, and deep learning). Utilizing case studies from an open-pit coal mine in Turkey and a loess gully mining area in China, the paper evaluates the effectiveness of methods like multi-temporal InSAR and UAV photogrammetry in identifying the evolution of these hazards. The findings indicate that the technological framework for mining area monitoring is transitioning from single-method approaches to integrated systems. However, given the complex mining environment, several bottleneck challenges remain, including single data dimensions, the limited environmental adaptability of aerospace remote sensing, insufficient stability of deep monitoring equipment, and weak anti-interference capabilities under extreme operating conditions. Consequently, this paper proposes that future innovations in geological hazard monitoring in mining areas will focus on multi-platform hierarchical collaboration, the development of multi-parameter fusion early warning criteria, and the construction of digital and visual platforms. Constructing a comprehensive monitoring system characterized by multi-scale collaboration and dynamic prediction capabilities is vital for improving safety standards in mining areas and achieving coordinated development between resource exploitation and environmental protection. The findings provide a theoretical foundation for the precise prevention and control of mining hazards, as well as for land ecological restoration. Full article

Emericellopsis species from extreme environmental conditions provide a rich source of unique and biologically active secondary metabolites. The paper exhibits a comprehensive genomic analysis including complete genome sequencing, phylogenetic reconstruction, and functional annotation of two Emericellopsis species from highly saline and alkaline coastal soil ecosystems. Comparative genomics has been applied to reveal the genetic evolution, metabolic diversity, and environmental adaptation of the Emericellopsis genus. The genomes of E. alkalina E101 and E. fimetaria p24 have been found to encode various enzymes, including carbohydrate-active enzymes such as endoxylanases, that are useful for many ecological adaptations. The genomes of E. alkalina E101 and E. fimetaria p24 feature numerous biosynthetic gene clusters (BGCs), capable of synthesizing both known and potentially novel secondary metabolites with antimicrobial activity. Some BGCs show similarity to those producing known secondary metabolites, such as leucostatin A/B, clavaric acid, ascochlorin, (-)-mellein, and apicidin, among others. However, the majority of BGCs do not display any known similarities. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of Emericellopsis fungi and may serve as a highly useful tool within biotechnological applications. Full article

Coastal ecosystems are highly dynamic and vulnerable to climate change, sea-level rise, and rapid urbanization. However, many landscape ecological risk assessments are limited by fixed scales and assumptions of spatial uniformity. This study develops a geomorphology-based framework to analyze coastal ecological risk. Using multi-source data from 1980 to 2020, the optimal analytical scale was identified as 120 m (grain) and 1000 m (extent). An integrated approach combining OPGD, XGBoost–SHAP, and restricted cubic spline (RCS) models was applied to examine risk patterns and driving mechanisms across four coastal types in Guangdong, China. The results show that the importance and interactions of driving factors vary significantly among geomorphic types, with clear nonlinear responses. Key statistical thresholds were identified, indicating ranges where risk sensitivity changes, including NDVI ≈ 0.624 in the Hilly Ria Coast, slope ≈ 2.8° in the Platform Ria Coast, elevation ≈ 14.5 m in the Barrier–Lagoon Coast, and GDP ≈ 1644.65 × 10⁶ CNY/km² in the Estuarine Delta Coast. These findings provide quantitative evidence for understanding spatial heterogeneity and the nonlinear dynamics of coastal ecological risk, and offer practical references for adaptive management. Full article

Triplophysa yarkandensis (Cypriniformes: Nemacheilidae), a rare endemic fish in the Tarim River Basin, Xinjiang, China, plays a pivotal role in maintaining the stability of plateau saline–alkaline aquatic ecosystems, yet its survival is increasingly threatened by habitat salinization. However, the multi-dimensional synergistic adaptation mechanisms linking its phenotypic variation, intestinal structure, and associated microbial communities to extreme saline–alkaline stress remain poorly understood. In this study, we innovatively integrated morphological/intestinal histological characterization, 16S rRNA gene sequencing, and microbial ecological analyses (co-occurrence networks and assembly processes) to systematically decode its adaptive strategies. Results revealed that T. yarkandensis exhibits a streamlined body shape, morphological variability, and elongated intestinal villi that may support locomotion and nutrient/ion uptake under osmotic stress. Its gut exerts a stringent selective filter, driving distinct differentiation between water and gut microbial communities—with gut-enriched core taxa (Aurantimicrobium and Aestuariivirga) and functional pathways (unsaturated fatty acid biosynthesis and ABC transporters) specialized for osmoregulation. Notably, the water microbial assembly is dominated by stochastic processes, while the gut assembly relies on host-driven deterministic selection, forming a habitat-specific adaptive pattern. These findings uncover the synergistic adaptation system of host phenotype and gut microbiota for survival in extreme saline–alkaline habitats, advancing our understanding of fish–microbe co-evolution in extreme ecosystems and providing critical theoretical support for the conservation of rare plateau fish, as well as guidance for the utilization of saline–alkaline water resources in aquaculture. Full article