Search Results (846)

Tea (Camellia sinensis) cultivation is a major global industry that faces sustainability challenges due to soil degradation and greenhouse gas (GHG) emissions from intensive management. Biochar—charcoal designed and used as a soil amendment—has emerged as a potential tool to improve soil health, enhance carbon sequestration, and mitigate GHG fluxes in agroecosystems. However, field-scale evidence of its effects on GHG dynamics in woody crops like tea remains limited, particularly regarding methane (CH₄). Here, we present, to our knowledge, the first field assessment of biochar impacts on CO₂, CH₄, and H₂O vapour fluxes in a subtropical tea agroforestry system with and without shade trees in northeastern Bangladesh. Using a closed dynamic chamber and real-time gas analysis, we found that biochar application (at 7.5 t·ha⁻¹) significantly enhanced average soil methane (CH₄) uptake by 84%, while soil respiration (CO₂ efflux) rose modestly (+18%) and water-vapour fluxes showed a marginal increase. Canopy conditions modulated these effects: biochar strongly enhanced CH₄ uptake under both shaded and open canopies, whereas biochar effects on water-vapour flux were detectable only when biochar was combined with a shade-tree canopy. Structural equation modelling suggests that CH₄ flux was primarily governed by biochar-induced changes in soil pH, moisture, nutrient status, and temperature, while CO₂ and H₂O fluxes were shaped by organic matter availability, temperature, and phosphorus dynamics. These findings demonstrate that biochar can promote CH₄ uptake and alter soil carbon–water interactions during the dry season in tea plantation systems and support operational biochar use in combination with shade-tree agroforestry. Full article

Root exudates represent a critical belowground carbon flux; however, direct field-based quantification of these rates on intact mangrove roots remains limited due to methodological challenges. Here, we present, to our knowledge, the first in situ evaluation of root exudation rates in a subtropical Bruguiera gymnorhiza forest in Japan, employing a modified cuvette method specifically designed for field measurements on intact root systems. The net root exudation rates measured in artificial seawater at depths of 0–60 cm ranged from 0.01 to 0.97 mg C g⁻¹ h⁻¹, with a mean of 0.22 mg C g⁻¹ h⁻¹. Although this mean rate was comparable to values reported for tropical terrestrial forests, the spatiotemporal variation exhibited variable site-specific patterns. At the midstream site, exudation rates were closely coupled with fine root biomass under nitrogen-limited conditions and peaked during summer. In contrast, the upstream site exhibited unusually high exudation rates during winter, even in deep soil layers. Furthermore, contrary to patterns typically observed in terrestrial forests, exudation rates showed positive correlations with root C:N ratios and proton efflux. These findings suggest that root exudation in mangroves is regulated by complex interactions among site-specific hydrological regimes and stress-adaptation mechanisms, particularly salinity tolerance and nutrient acquisition, rather than by simple growth trade-offs. When integrated over a depth of 0–60 cm, the estimated annual root exudate carbon flux was approximately 0.4 kg C m⁻² yr⁻¹. This likely represents a conservative lower-bound estimate because fine root systems extend well below this depth in mangrove forests. Our results strongly suggest that root exudates constitute an important, previously under-recognized component of the “missing carbon” in mangrove ecosystems and underscore the need to explicitly incorporate this flux into blue carbon models to more accurately evaluate mangrove carbon sequestration capacity. Full article

The effect of afforestation in infertile mountainous areas is closely related to the soil ecological environment. Soil enzyme activities and the structure and functions of microbial communities are core indicators reflecting soil quality. Clarifying the response patterns of the two to Cyclobalanopsis gilva afforestation in infertile mountainous areas can provide a key scientific basis for targeted improvement of the cultivation efficiency of C. gilva plantations under different site conditions in the eastern subtropical region of China. In this study, 7-year-old C. gilva young forests in infertile mountainous areas and control woodland areas were selected in Shouchang Forest Farm, Jiande, Zhejiang Province, located in the subtropical region of China. Soil enzyme activities and microbial biomass in different soil layers, as well as metagenomes of rhizosphere and bulk soils, were determined to explore the effects and internal correlations of site conditions on soil enzyme activities and microbial community characteristics of C. gilva forests. The results showed that the activities of urease and catalase, as well as the content of microbial biomass nitrogen in the surface soil of infertile mountainous areas, were significantly lower than those in control woodland areas. The shared dominant phyla in the two types of sites included Proteobacteria and Acidobacteria, and the shared dominant genera included Bradyrhizobium. In addition, the relative abundances of three unclassified populations of Proteobacteria and functional genes related to cofactor and vitamin metabolism in the rhizosphere soil of infertile mountainous areas were significantly higher than those in control woodland areas. Meanwhile, the dominant microbial phyla in the rhizosphere soil of infertile mountainous areas had a closer correlation with soil enzyme activities and microbial biomass. This study clarified the ecological strategy of C. gilva young forests adapting to infertile mountainous areas: by increasing the relative abundances of functional genes related to cofactor and vitamin metabolism in rhizosphere microorganisms, promoting the enrichment of microorganisms associated with soil nitrogen cycling, and enhancing the correlations between dominant microbial phyla and soil enzyme activities and microbial biomass, the nitrogen resource limitation on soil microbial activity in infertile mountainous areas is balanced. This finding provides direct guidance for optimizing the afforestation and management techniques of C. gilva in infertile mountainous areas and has important practical value for promoting forest ecological restoration. Full article

Soil organic matter (SOM) is a key indicator for evaluating soil fertility and ecological functions, and hyperspectral technology provides an effective means for its rapid and non-destructive estimation. However, in practical soil systems, the spectral response of SOM is often highly covariant with mineral composition, moisture conditions, and soil structural characteristics. Under small-sample conditions, hyperspectral SOM modeling results are usually highly sensitive to spectral preprocessing methods, sample perturbations, and model architecture and parameter configurations, leading to fluctuations in predictive performance across independent runs and thereby limiting model stability and practical applicability. To address these issues, this study proposes a multi-strategy collaborative deep learning modeling framework for small-sample conditions (SE-EDCNN-DA-LWGPSO). Under unified data partitioning and evaluation settings, the framework integrates spectral preprocessing, data augmentation based on sensor perturbation simulation, multi-scale dilated convolution feature extraction, an SE channel attention mechanism, and a linearly weighted generalized particle swarm optimization algorithm. Subtropical red soil samples from Guangxi were used as the study object. Samples were partitioned using the SPXY method, and multiple independent repeated experiments were conducted to evaluate the predictive performance and training consistency of the model under fixed validation conditions. The results indicate that the combination of Savitzky–Golay filtering and first-derivative transformation (SG–1DR) exhibits superior overall stability among various preprocessing schemes. In model structure comparison and ablation analysis, as dilated convolution, data augmentation, and channel attention mechanisms were progressively introduced, the fluctuations of prediction errors on the validation set gradually converged, and the performance dispersion among different independent runs was significantly reduced. Under ten independent repeated experiments, the final model achieved R² = 0.938 ± 0.010, RMSE = 2.256 ± 0.176 g·kg⁻¹, and RPD = 4.050 ± 0.305 on the validation set, demonstrating that the proposed framework has good modeling consistency and numerical stability under small-sample conditions. Full article

Early age cracking induced by cement hydration heat in a 37.6 m-wide PK-section concrete box girder was investigated through full-scale field testing and numerical simulation. Material properties, temperature, and strain were measured, and the obtained thermal and mechanical parameters were used to simulate temperature and stress distributions during cantilever casting. Results show that direct casting on the foundation cap led to extensive vertical cracking in diaphragms, where tensile stresses exceeded concrete strength, corresponding to a cracking index of approximately 1.8, with thermal-to-shrinkage stress ratios up to 3:1 in critical regions. Under cantilever construction conditions, significant transverse stress occurred only at the diaphragm bottom, reaching a cracking index of about 1.6, with a thermal-to-shrinkage ratio of 2:1. Reducing casting temperature lowered thermal stress by 0.1 MPa/°C, while adding 0.9 kg/m³ polypropylene fibers increased early-age tensile strength by 15%. Optimized mix design or the inclusion of mineral admixtures such as silica fume further reduced shrinkage. The combined application of these measures effectively mitigated early-age cracking risk, providing practical guidance for the construction of wide-box girders in subtropical climates. Full article

Cupressus duclouxiana is an ecologically and economically important conifer endemic to southwestern China (e.g., central Yunnan and southern Sichuan), yet its potential distribution under future climate change remains insufficiently understood. In this study, we employed an ensemble species distribution modeling framework implemented in biomod2 to predict the current and future suitable habitats of C. duclouxiana across China. A total of 154 occurrence records and 17 key environmental variables were used to construct ensemble models integrating twelve algorithms. The ensemble model showed high predictive performance (TSS = 0.99, Kappa = 0.98). Temperature-related variables dominated habitat suitability, with the minimum temperature of the coldest month identified as the primary limiting factor, accounting for 44.1%. Under current climatic conditions, suitable habitats are mainly concentrated in southwestern China, particularly in Sichuan, Yunnan, and Xizang (Tibet). Future projections under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5) consistently indicate habitat expansion by the late 21st century, accompanied by pronounced northward and northwestward range shifts. The largest expansion is projected under the SSP3-7.0 scenario, highlighting the sensitivity of C. duclouxiana to intermediate warming trajectories. Overall, climate warming is expected to increase habitat availability while reshaping the spatial distribution of C. duclouxiana across China. These findings provide scientific support for climate-adaptive afforestation planning and conservation management, and offer broader insights into the responses of subtropical coniferous species to future climate change. Full article

Understanding the influence of tree species and their intrinsic traits on biochar yield and carbon retention is essential for optimizing the conversion of biomass to biochar in carbon-negative systems. While it is well-established that pyrolysis temperature and broad feedstock categories significantly affect biochar properties, the extent of species-level variation within woody biomass under standardized pyrolysis conditions remains insufficiently quantified. Here, we synthesized biochar from seven common subtropical tree species at 600 °C under oxygen-limited smoldering conditions and quantified three key indices: biochar yield (Y), carbon recovery efficiency (ηC), and carbon enrichment factor (EC). We further examined the relationships of these indices with feedstock characteristics (initial carbon content, wood density) and functional group identity (conifer vs. broadleaf). Analysis of variance revealed significant interspecific differences in ηC but weaker effects on Y, indicating that species identity primarily governs carbon retention rather than total mass yield. Broadleaf species (Liquidambar formosana, Castanea mollissima) exhibited consistently higher ηC and EC than conifers (Pinus massoniana, P. elliottii), reflecting higher lignin content and wood density that favor aromatic char formation. Principal component and cluster analyses clearly separated coniferous and broadleaf taxa, accounting for over 80% of total variance in carbon-related traits. Regression models showed that feedstock carbon content, biochar carbon content, and wood density together explained 15.5% of the variance in ηC, with feedstock carbon content exerting a significant negative effect, whereas wood density correlated positively with carbon retention. These findings demonstrate that tree species and their functional traits jointly determine carbon fixation efficiency during smoldering. High initial carbon content alone does not guarantee enhanced carbon recovery; instead, wood density and lignin-derived structural stability dominate retention outcomes. Our results underscore the need for trait-based feedstock selection to improve biochar quality and carbon sequestration potential, and provide a mechanistic framework linking species identity, functional traits, and carbon stabilization in biochar production. Full article

Lateral Organ Boundaries Domain (LBD) proteins are plant-specific transcription factors characterized by a typical N-terminal LOB domain and are critical for plant growth, development, and stress response. Currently, LBD genes have been investigated in various plant species, but they have yet to be identified in Neolamarckia cadamba, known as a ‘miracle tree’ for its fast growth and acknowledged for its potential medicinal value in tropical and subtropical areas of Asia. In this study, a total of 65 NcLBD members were identified in N. cadamba by whole-genome bioinformatics analysis. Phylogenetic analysis revealed their classification into two clades with seven distinct groups, and their uneven distribution across 18 chromosomes, along with 6 tandem repeats and 58 segmental duplications. Furthermore, enrichment analysis of transcription factor binding motifs within NcLBD promoters identified the MYB-related and WRKY families exhibited the most significant enrichment in the NcLBD promoter. Protein interaction network analysis revealed potential interactions among NcLBD proteins, as well as their interactions with various transcription factors. RNA-seq and qRT-PCR analyses of NcLBDs transcript levels showed distinct expression patterns both across various tissues and under different hormone and abiotic stress conditions. Specifically, NcLBD3, NcLBD37, and NcLBD47 were highly expressed in vascular cells and induced by abiotic stress, including cold, drought, and salt, suggesting their significant role in the processes. In summary, our genome-wide analysis comprehensively identified and characterized LBD gene family in N. cadamba, laying a solid foundation for further elucidating the biological functions of NcLBD genes. Full article

To enhance the climate adaptability and diagnostic precision of university sustainability frameworks, this study presents a critical advancement to the PICSOU (Performance Indicators for Core Sustainability Objectives of Universities) framework’s Indoor Environmental Quality (IEQ) module. The research employs a comparative approach across two distinct climate zones: the campus of Chengdu Jincheng College in a humid subtropical climate (CDJCC; Köppen Cwa) with natural ventilation, and the campus of Tallinn University of Technology in a temperate climate (TalTech; Köppen Dfb) with mechanical ventilation. A key innovation at CDJCC was the deployment of a novel, integrated sensor that combines a Frequency-Modulated Continuous Wave (FMCW) radar module for real-time occupancy detection with standard IEQ sensor suite (CO₂, PM_2.5, temperature, humidity), enabling unprecedented analysis of occupant-IEQ dynamics. At TalTech, comprehensive IEQ monitoring was conducted using standard sensors. Results demonstrated that mechanical ventilation (TalTech) effectively decouples indoor conditions from external fluctuations. In contrast, natural ventilation (CDJCC) exhibits strong seasonal coupling, reflected by a Seasonal Ventilation Efficacy Coefficient (${\lambda }_{\mathit{season}}$), indicating that seasonal differences in effective ventilation are present but vary by indoor space type under occupied conditions. Consistent with this stronger indoor–outdoor linkage, PM_2.5 infiltration was also pronounced in naturally ventilated spaces, as evidenced by a high infiltration factor ($I/O$ ratio) that remained consistently elevated. This work conclusively validates a conditional, climate-resilient workflow for PICSOU’s IEQ category, integrating these empirical coefficients to transform its IEQ assessment into a dynamic and actionable tool for optimizing campus sustainability strategies globally. Full article

Regional precipitation patterns are influenced by a combination of global climatic drivers and local environmental conditions. This study takes Henan Province, located in the middle and lower reaches of the Yellow River, as a case study. Using wavelet analysis, cross-wavelet transform (XWT), and wavelet coherence (WTC), we investigated the periodic relationships between summer (July) precipitation in Henan Province during 1983–2022 and four key factors: El Niño–Southern Oscillation (ENSO), East Asian Summer Monsoon (EASM), Western Pacific Subtropical High (WPSH), and Normalized Difference Vegetation Index (NDVI). The results indicate that (1) Precipitation shares a common periodic signal at approximately 3–6 years with all influencing factors, and additionally exhibits low-frequency co-variability at the 18–20-year timescale with ENSO, EASM, and WPSH; (2) ENSO, EASM, and WPSH are identified as the primary drivers of precipitation variability in the middle and lower reaches of the Yellow River; (3) In recent years, anomalous summer precipitation in this region has been closely linked to the periodic activities of ENSO, EASM, and WPSH. Full article

Agricultural nonpoint source pollution is emerging as one of the increasingly serious environmental concerns all over the world. This study conducted field experiments in Zengcheng District, Guangzhou City, from 2019 to 2023 to explore the mechanisms by which different crop types, fertilization modes, and meteorological conditions affect the loss of nitrogen and phosphorus in agricultural nonpoint source pollution. In rice and corn, the CK and PK treatment groups showed significant fitting advantages, such as the R² of rice-CK reaching 0.309. MAE was 0.395, and the R² of corn-PK was as high as 0.415. For compound fertilization groups such as NPK and OF, the model fitting ability decreased, such as the R² of rice-NPK dropping to 0.193 and the R² of corn-OF being only 0.168. In addition, the overall performance of the model was limited in the modeling of total phosphorus. A relatively good fit was achieved in corn (such as NPK group R² = 0.272) and in vegetables and citrus. R² was mostly below 0.25. The results indicated that fertilization management, crop types, and meteorological conditions affected nitrogen and phosphorus losses in agricultural runoff. Cornfields under conventional nitrogen, phosphorus, and potassium fertilizer (NPK) and conventional nitrogen and potassium fertilizer treatment without phosphorus fertilizer (NK) treatments exhibited the highest nitrogen losses, while citrus fields showed elevated phosphorus concentrations under NPK and PK treatments. Organic fertilizer treatments led to moderate nutrient losses but greater variability. Organic fertilizer treatments resulted in moderate nutrient losses but showed greater interannual variability. Meteorological drivers differed among crop types. Nitrogen enrichment was mainly associated with high temperature and precipitation, whereas phosphorus loss was primarily triggered by short-term extreme weather events. Linear regression models performed well under simple fertilization scenarios but struggled with complex nutrient dynamics. Crop-specific traits such as flooding in rice fields, irrigation in corn, and canopy coverage in citrus significantly influenced nutrient migration. The findings of this study highlight that nutrient losses are jointly regulated by crop systems, fertilization practices, and meteorological variability, particularly under extreme weather conditions. These findings underscore the necessity of crop-specific and climate-adaptive nutrient management strategies to reduce agricultural nonpoint source pollution. By integrating long-term field observations with machine learning–based analysis, this study provides scientific evidence to support sustainable fertilizer management, protection of water resources, and environmentally responsible agricultural development in subtropical regions. The proposed approaches contribute to sustainable land and water resource utilization and climate-resilient agricultural systems, aligning with the goals of sustainable development in rapidly urbanizing river basins. Full article

Ecological stoichiometry provides a useful lens for linking nutrient status to ecosystem functioning, but cross-compartment (green leaves, surface litter, and topsoil) evidence for subtropical secondary forests is still limited. In particular, it remains unclear how forest type regulates coupled carbon (C), nitrogen (N), and phosphorus (P) patterns in leaves, litter, and soils on P-retentive Acrisols and how these patterns can be used to infer nutrient limitations. We measured C, N, and P concentrations and stoichiometric ratios in leaves, surface litter, and topsoil (0–10 cm) from 38 plots representing four dominant forest types (shrub, coniferous, mixed coniferous–broadleaf, and broadleaf) in subtropical public welfare forests of eastern China. We compared elemental concentrations and ratios among forest types and compartments and examined cross-compartment associations. Forest-type differences in stoichiometric patterns were most pronounced for leaf and soil concentrations/ratios, whereas litter metrics were comparatively conservative. Coniferous stands had the highest leaf C concentration and the highest litter C:N and C:P ratios, together with relatively low soil N and P concentrations. Broadleaf stands had the highest soil C and N concentrations and the highest litter and soil N:P, suggesting a tendency toward P limitation under comparatively N-rich conditions. Shrub and mixed forests were intermediate, with shrubs exhibiting the lowest litter N:P. Leaf N:P averaged 7.5 in coniferous stands and 12.5–14.9 in mixed and broadleaf stands. Coherent correlations of C:P from leaves to litter and soils and a negative relationship between leaf N:P and soil C:N suggested coordinated stoichiometric linkages along the leaf–litter–soil continuum. Overall, the results show that forest type organizes plot-scale C:N:P coupling on Acrisols and that leaf–litter–soil stoichiometry can be used as a practical framework for identifying whether N- versus P-related constraints are more likely to dominate different subtropical forest types and for informing nutrient-aware restoration and management. Full article

Under the background of global climate change, frequent drought events have significantly impacted plant–insect interaction. This study focuses on Ficus microcarpa, an important landscaping and urban greening tree species in tropical and subtropical regions, and its primary herbivorous pest, Perina nuda, by applying the age-stage, two-sex life table theory to systematically evaluate the effects on the life history traits and population dynamics of P. nuda reared on F. microcarpa subjected to different levels of drought stress. The results demonstrated that reared on drought-stressed F. microcarpa significantly altered multiple life history traits of P. nuda. All drought treatments significantly shortened the larval development period. Under both light and severe drought conditions, adult lifespan was prolonged, the total pre-oviposition period was reduced, fecundity per female increased, and generation time (T) was shortened. However, significant increases in pupal weight, intrinsic rate of increase (r), and finite rate of increase (λ) were observed only under light drought stress. The population prediction results indicate that both light and severe drought stress lead to obviously higher population growth rates and larger population sizes at 200 days compared to the control group. These findings suggest that the population fitness of P. nuda is enhanced under light and severe drought stress, potentially increasing the probability of pest outbreaks. This study provides an important theoretical basis and practical advice on forecasting population dynamics and implementing integrated management strategies for P. nuda in the context of climate change. Full article

Quinoa, in addition to its nutritional benefits, is adaptable to, and tolerant of, high-altitude and Mediterranean environmental conditions. However, its largely cross-compatible free-living ancestor, pitseed goosefoot, possesses expansive adaptive variation as its ecotypes are found on arid or well-drained soils throughout temperate and subtropical North America. In this context, the objective of this study was to characterize F7:10 lines from quinoa × pitseed goosefoot hybrids to identify promising lines with desirable agronomic traits and adaptation to hyper-arid production environments. The agro-morphological characterization of 14 interspecific experimental lines plus wild parents (5), checks (3, including one derived from a much earlier wide cross), and an F2 population was performed for 25 quantitative and 26 qualitative descriptors, along with calculation of the selection index. Among the morphological variables, the average number of primary branches per plant (NPB) was six (CV = 78%), the average plant height (PH) was 143.5 cm (CV = 40%), and the average panicle diameter (PDI) was 17.9 cm (CV = 62%). With regard to the yield component variables, the average harvest index (HI) was 39% (CV = 36%), the average weight of 1000 grains (W1000G) was 2.59 g (CV = 42%), and the average yield per hectare (HYP) was 4.68 t ha⁻¹ (CV = 65%). Regarding the correlations between variables, it was observed that all phenological phases showed positive correlations with plant height (PH) and negative correlations with yield components, specifically with DG, DT, HI, and W1000G. The highest-yielding lines were GR10 (8.16 t ha⁻¹), GR07 (7.53 t ha⁻¹), GR11 (7.27 t ha⁻¹), and GR01 (7.02 t ha⁻¹). Multivariate and cluster analyses identified four groups of lines, with groups II and IV standing out for their desirable agronomic traits. However, based on the selection index, lines RL08, RL07, ER06, GR03, and GR11 were identified as the most promising. In terms of quality, 18 out of the 23 lines were classified as sweet (<0.11% saponin) and 5 as bitter (>0.11 saponin). In conclusion, the selection index identified pitseed goosefoot cross-derived quinoa lines having superior yield potential, short plant height, large grain size, early maturity, and low saponin content. Full article

Moringa oleifera, widely recognized as the horseradish tree or drumstick tree, is classified within the Moringaceae family, which comprises 13 species predominantly distributed across tropical and subtropical regions. The plant possesses a variety of therapeutic, nutritional, and beneficial health properties, including its potential to enhance the immune system. The present work provides extensive bibliographic research addressing the chemical composition of Moringa oleifera and its immunomodulatory properties with a focus on the cellular and molecular mechanisms involved in the regulation of immune function, which is crucial in unchecked cell proliferation and metastasis. The chemical composition of Moringa oleifera, including kaempferol, chlorogenic acid, quercetin, and niazimicin, varies between different biological parts of the plant (seeds, leaves, roots, and stems). The presence of these various chemical compounds contributes to the plant’s effect on the immune response via different pathways. Several studies indicate that Moringa oleifera mitigates inflammation by suppressing key pro-inflammatory mediators, such as TNF-α, IL-1β, inducible nitric oxide synthase (iNOS), prostaglandin E2 (PGE-2), and cyclooxygenase-2 (COX-2), while simultaneously enhancing anti-inflammatory mediators through activation of PPAR-γ. Furthermore, the immunomodulatory properties and possible application in health promotion and disease prevention, especially in cancer therapy, are discussed. Studies indicate that Moringa oleifera can modulate the tumor microenvironment (TME) by reducing Treg polarization, enhancing NK cell cytotoxicity, and prompting the proliferation and clonal expansion of CD8⁺ and CD4⁺ T lymphocytes. Together, Moringa oleifera could be considered for the treatment of conditions related to immune dysregulation, such as cancer. Full article