Search Results (5,296)

Mangrove replantation is widely implemented as a rehabilitation-oriented response to coastal degradation, yet many replanted stands remain poorly assessed after plantation. This study provides a preliminary dry-season post-plantation habitat characterization of an eight-year-old replanted Rhizophora mucronata stand at Sungai Ujung River, South Sulawesi, Indonesia. Its novelty lies in integrating vegetation structure, surface-active brachyuran taxonomic units, selected surface-water variables, and sediment texture within a single replanted stand where no baseline or long-term monitoring data were available. The final descriptive dataset included seven plots across three transects. Surface-active brachyurans and water-quality variables were recorded across five valid sampling occasions: three spring-tide and two neap-tide occasions. Because tidal period was a sampling-occasion-level condition and temporal replication was limited, spring–neap patterns were interpreted descriptively. Eight surface-active brachyuran taxonomic units comprising 676 individuals were recorded, dominated by Metopograpsus latifrons. Crab abundance, Shannon diversity, and water-quality profiles varied among occasions and plots. All 113 living mangrove individuals were R. mucronata, with established trees, visible seedlings, and scarce poles. Sediment texture ranged from sand-dominated to clay-rich substrates. These findings provide a structured reference point for future monitoring, but do not demonstrate replantation success, recovery trajectory, or functional recovery. Full article

Saline water irrigation is a potential strategy to address agricultural water scarcity, but its effects on soil respiration and carbon balance are not well understood. To clarify these effects and promote the safe utilization of saline water resources, this study investigated five irrigation water salinity levels EC_iw: 1.3, 3.4, 7.1, 10.6, and 14.1 dS·m⁻¹ (i.e., 1, 2, 4, 6, 8 PSU; 1000, 2000, 4000, 6000, 8000 mg·L⁻¹) in a winter wheat–summer maize rotation during 2024–2025. The results indicated that saline water irrigation caused salt accumulation during the wheat season, whereas salt leaching occurred during the maize season. When EC_iw ≤ 3.4 dS·m⁻¹, no notable decreases were observed in dry matter accumulation, water productivity, and carbon emission efficiency for both crops. In contrast, when EC_iw > 3.4 dS·m⁻¹, the crop yields and net carbon input of the crop rotation system were suppressed to a considerable extent. Furthermore, under saline water irrigation, the average soil respiration rate decreased by 4.1–25.2% during the wheat growing season, while that for maize decreased by 7.4–30.7%. Soil respiration in wheat was negatively correlated with soil salinity and pH, and positively correlated with soil moisture (p < 0.01). In maize, soil respiration was negatively correlated with salinity (p < 0.01), and positively correlated with soil moisture (p < 0.05) and temperature (p < 0.01). The entropy-weighted TOPSIS model identified 3.4 dS·m⁻¹ as the appropriate irrigation salinity threshold for maintaining yield and carbon sink function in this rotation system. Full article

Cassava is a crop of major socioeconomic and cultural importance in Colombia. One of the main challenges is production seasonality, driven by climatic conditions that constrain planting and harvesting periods. Currently, cultivated varieties exhibit a substantial reduction in root dry matter content (DMC) following the onset of the rains. This study evaluated the agronomic performance of genotype SM2828-28 under semi-commercial field conditions in the departments of Cesar, Bolívar, and Magdalena in the Colombian Caribbean region. This genotype exhibited greater stability and productivity, outperforming commercial checks. The genotype also showed high and stable DMC. Root quality and starch functional properties were also assessed. Starch from SM2828-28 exhibited numerically lower setback values and a relatively consistent rheological profile across harvest ages, indicating greater gel stability during cooling—an attribute desirable for industrial applications requiring consistent textural properties. The genetic progress achieved for key industrial traits highlights the potential of SM2828-28 for extended-harvest systems aimed at reducing seasonality in raw material supply for the cassava starch industry. These results suggest that genetic factors contribute to the stability of DMC under extended-harvest conditions and support the inclusion of this trait as a target in cassava breeding programs. Full article

Soil salinization is a major abiotic constraint on tomato production worldwide. To evaluate adult-stage tomato performance under contrasting saline and non-saline conditions, 23 tomato accessions (13 large-fruited and 10 cherry types) were evaluated at two solar-greenhouse locations in Hebei Province, China: a non-saline site in Shijiazhuang and a saline–alkali site in Huanghua, Cangzhou. Eleven growth, biomass, yield, and quality traits were assessed, and salt tolerance coefficients (STCs) were calculated to characterize relative trait performance between the two sites. Accessions were also genotyped using a PARMS marker linked to SlHAK20. Biomass accumulation was generally lower at the saline site, with above-ground and root dry weights showing the largest relative differences between the two sites, whereas plant height differed comparatively little. Total soluble solids (TSS) were higher at the saline site in most accessions, with the largest relative difference (91.7%) observed in large-fruited accession 305. Correlation analysis revealed strong positive associations between fresh and dry weights of both shoot and root tissues (p < 0.0001). Large-fruited accession 305 and cherry accession 436 showed comparatively favorable biomass retention and relatively small morphological differences between the two sites and therefore represent candidate accessions for further evaluation. The observed SlHAK20-linked marker genotypes were not consistently aligned with phenotypic performance among accessions, indicating that the predictive value of this marker requires further validation. These findings should be interpreted cautiously because salinity was confounded with location, the experiment was conducted during a single growing season, and the marker analysis was not validated in an independent population. This study provides a preliminary comparative evaluation approach and candidate accessions for further investigation and breeding of tomatoes adapted to saline environments. Full article

River-connected lakes are characterized by complex hydrological regimes, where hydrodynamic conditions serve as key physical drivers of aquatic ecosystem evolution and eutrophication. However, traditional water-balance methods struggle to accurately quantify water exchange under strong seasonal water-level fluctuations and the backwater effect of the Yangtze River, resulting in significant gaps in understanding lake hydrodynamic features and their seasonal eutrophication response patterns. Taking Dongting Lake as an example, this study employed a two-dimensional hydrodynamic model coupled with the advection–dispersion equation of a conservative tracer to simulate the spatiotemporal patterns of flow velocity and water turnover time during the dry season, rising-water season, wet season, and receding-water season using observed hydrological data from 2017 to 2025. Field sampling data and structural equation modeling were further used to identify the pathways through which hydrodynamic conditions affect lake trophic status. Flow velocity and water turnover time exhibited significant spatiotemporal heterogeneity: water turnover time was generally within 10 d in main flood channels but exceeded 60 d in stagnant floodplain areas and local topographic depressions. Seasonally, it was shortest in the wet season due to enhanced hydrological connectivity, yet longest in the dry season because of weakened hydraulic connection. The effects of hydrodynamics on trophic status were strongly season-dependent: during the rising-water season, hydrodynamics inhibited nutrient accumulation through dilution and flushing; during the wet season, strong runoff promoted external nutrient input; and during the dry season, hydrodynamics mainly affected trophic status by modifying physical habitat conditions for algal growth. These findings reveal the hydrological and hydrodynamic mechanisms regulating eutrophication in typical river-connected lakes, providing direct scientific support for hydrological regulation optimization, zonal eutrophication prevention and control, and water environmental carrying capacity assessment in Dongting Lake and similar systems, enabling lake managers to formulate differentiated pollution control strategies based on the hydrodynamic–trophic status response relationships across different hydrological seasons. Full article

Solar-assisted underground thermal energy storage (UTES) can reduce the seasonal mismatch between summer solar availability and winter heat demand. However, regional planning requires renewable charging resources and subsurface thermal performance to be evaluated jointly. This study developed a lithology-resolved GIS–laboratory framework for preliminary borehole thermal energy storage screening in the Euganean Hills, northeastern Italy. Thermal conductivity and volumetric heat capacity were characterized for 23 local specimens under dry and water-saturated conditions. Conductivity was measured parallel and perpendicular to the dominant rock fabric. Additional basalt measurements and clay/silt reference values were used where local sampling was insufficient. Normalized thermal effusivity was combined multiplicatively with normalized seasonal solar radiation to define a dimensionless Ground Thermal–Solar Suitability (GTSS) index. Property uncertainty was propagated using 10,000 non-parametric bootstrap realizations. Saturated conductivity generally exceeded 3.0 $\mathrm{W}{\mathrm{m}}^{-1}{\mathrm{K}}^{-1}$ in compact carbonate formations. From the conservative dry/perpendicular to the favorable saturated/parallel scenario, lithology-level GTSS increased by 2.6–9.4%. Approximately 30.1% of mapped cells increased by one suitability class and 0.5% by two classes. Relative 95% GTSS interval widths ranged from 2.5–16.9% in the conservative scenario and 1.1–13.5% in the favorable scenario. Maiolica and Scaglia Rossa provided the strongest combination of thermal performance and spatial continuity. At Turri, field-equivalent conductivity was 5.10 $\mathrm{W}{\mathrm{m}}^{-1}{\mathrm{K}}^{-1}$, or 2.50–3.45 times the laboratory-weighted estimates. This difference confirms that field-scale fracture, groundwater, and borehole effects lie outside the laboratory calibration domain. GTSS therefore supports uncertainty-aware regional prioritization, not site-specific performance prediction. Full article

Urban-forest monitoring increasingly requires intelligent sensor-driven systems capable of characterizing short-term tree responses while operating efficiently within Internet of Things (IoT) and edge-computing environments. This study proposes a fusion-based artificial intelligence framework that integrates Quantization-Aware Training (QAT)-optimized PointNet++ models with machine-learning regression to predict a short-term dendrometer-derived stem-diameter response expressed in biomass-equivalent units. The framework combines 1024-point LiDAR tree representations, geometric measurements, and environmental sensor data through three components: QAT-optimized PointNet++ models for 34-species classification and trunk–crown part segmentation, frozen model-based prediction and geometric feature extraction, and MLP and XGBoost regression models for prediction of the short-term target. The dataset contained 2694 trees from five regions of South Korea, with the target derived from dendrometer-based stem-diameter measurements recorded over a 14-day interval between 8 September 2022 and 22 September 2022. Importantly, this short-term signal reflects both structural and reversible water-status-related stem dynamics and is therefore not interpreted as direct dry-biomass accumulation or carbon sequestration. The QAT-optimized models retained 92.52% segmentation accuracy (82.67% mIoU) and 80.46% species-classification accuracy, while the regression model reached R² = 0.9663 and RMSE = 0.4437 kg for the defined biomass-equivalent target. Quantization reduced the saved model size of both encoders by approximately 10.5× (21 MB → 2 MB) and accelerated CPU inference by up to 4.1×. These efficiency measurements were obtained on an ×86 desktop CPU and therefore characterize computational compression benefits rather than completed deployment or field validation on a low-power embedded device. These results demonstrate the computational feasibility of combining compressed point-cloud perception with multimodal prediction of short-term dendrometer-derived stem dynamics. Validation over seasonal and multi-year periods using independent biomass-reference measurements would be required before extending the framework to long-term biomass accumulation or carbon-sequestration assessment. Full article

Slopes excavated in coal-measure strata are prone to rainfall-induced landslides because water-induced disturbances progressively degrade rock-mass shear strength. This study investigated six coal-measure lithologies from the unloading zone of the Fushun West Open-Pit Mine using triaxial compression tests after separate wetting–drying and continuous-immersion treatments. Condition-dependent cohesion, c, and internal friction angle, φ, were fitted with exponential functions and incorporated into the Mohr–Coulomb criterion. For scenario analysis, the retention ratios measured in the two separate treatment series were applied sequentially in a separable empirical parameterization. This no-interaction approximation was used to update coal-measure strength inputs in representative slope models. Cohesion and φ decreased exponentially within the tested ranges, with in-sample R² values greater than 0.85, and cohesion was generally more sensitive. Continuous immersion produced rapid early softening, whereas wetting–drying cycles produced cumulative deterioration. Limit-equilibrium and finite-element calculations showed lower safety factors and more concentrated deformation under more severe parameter-reduction scenarios. Model-specific cumulative-displacement reference values of 52.36–213.82 mm were paired with Fs levels of approximately 1.15, 1.05, and 1.00 and compared qualitatively with historical monitoring curves. The findings provide a reference for rainy-season slope-stability prediction and staged warning in open-pit coal mines. Full article

The source regions of the Yangtze and Yellow Rivers on the Tibetan Plateau provide vital water resources for downstream ecosystems and populations, yet their runoff responses to climate warming remain insufficiently understood. Based on daily runoff data from six hydrological stations in the Yellow and the Yangtze River basins during 1980–2023, this study investigates the evolution and relatively stronger statistical climatic association of runoff in the source regions of the Yangtze and Yellow Rivers. The results indicate that annual runoff exhibited an overall increasing trend, primarily driven by a significant increase in non-flood-season runoff, while flood-season runoff increased insignificantly; Low runoff indices increased significantly at most stations, reflecting enhanced low-flow conditions and increased dry-season water availability, whereas high runoff indices showed no significant trends; wavelet analysis identified dominant periodicities of approximately 13.5 and 4.8 years. Furthermore, it indicates that precipitation remains the relatively stronger partial statistical climatic association for flood-season runoff throughout the study period, with its statistical association continuously strengthening. However, under climate warming, the influence of temperature on runoff is also gradually intensifying. The preceding cold season has exhibited an increased statistical contribution of temperatures, although concurrent warm-season precipitation maintains a stable statistical contribution. These findings carry significant implications for sustainable water resource management and climate adaptation in the Asian Water Tower, underscoring the necessity to incorporate changing climatic associations into long-term hydrological planning to safeguard downstream water security and ecosystem services. Full article

In seasonally arid systems, where water is a key limiting resource, unseasonal precipitation events may promote landscape greening. Because herbivores track spatial variation in fresh plant growth, dry-season precipitation could be an important catalyst of out-of-season foraging opportunities in seasonal arid environments. The eastern escarpment of California’s Sierra Nevada Mountains in the western United States features an intense ecoclimatic gradient from the Owens Valley’s cold desert to the High Sierra’s alpine tundra, in which patterns of temperature and precipitation vary seasonally and elevationally, and along which critically endangered Sierra Nevada bighorn sheep (“Sierra bighorn”) migrate seasonally. Immediately preceding the unusually warm 2021–2022 winter, the eastern Sierra experienced an historic autumn precipitation event, presenting an opportunity to investigate how unseasonal weather events shape patterns of plant green-up, and whether these conditions stand to impact herbivore space use. Here, we report on landscape greenness, indexed using the green chromatic coordinate, measured from 26,222 images collected by an in situ array of 20 time-lapse cameras deployed across the desert–alpine gradient of the eastern Sierra, over 5 years centered on the 2021–2022 fall-winter season. We compare greenness trends between time windows following rainfall and random timepoints to identify how unseasonal precipitation impacts plant greening using hierarchical linear models with a continuous first-order autocorrelation structure. Greenness trends were significantly more positive after rain than at random timepoints for low-elevation perennial grasses (p < 0.001), indicating that these plants readily uptake moisture regardless of the season. We additionally compare in situ greenness measurements with NDVI derived from satellite instrumentation to examine whether fine-scale patterns of green-up following unseasonal rains are detectable from space. Although in situ camera greenness and satellite NDVI were positively correlated, unseasonal species-specific greening was not detectable at the comparatively coarse scale of satellite analysis. Finally, we use GPS collar data from a population of Sierra bighorn to explore whether migratory behaviors could be associated with unseasonal landscape greening. Together, this work reveals that dry-season precipitation coupled with cold-season warm spells can lead to unseasonal landscape greenness and suggests that this process may facilitate herbivore access to high-quality forage during a normally barren time of year. Full article

This study investigates the length–weight relationship, growth patterns, and population structure of Prochilodus nigricans in a tropical river environment, providing biometric information relevant to ecological studies, fisheries assessment, and conservation planning. A total of 139 individuals were sampled across rainy and dry seasons, and biometric variables (BD—Body Depth, TL—Total Length, SL—Standard Length, TW—Total Weight, and GW—Gonad Weight) were compared using descriptive statistics and regression analyses. Significant differences in biometric parameters were observed between seasons and sexes. Among the sampled individuals, body depth, standard length, total length, and total weight were significantly higher during the rainy season for both sexes; however, these differences should be interpreted with caution because different gill-net mesh sizes were used between hydrological periods. Gonad weight and gonadosomatic index (GSI) differed significantly between males and females in both seasons. A significant overall effect of season was detected for gonad weight, although pairwise seasonal differences were observed only in males, whereas no significant seasonal effect was detected for GSI. Length–weight relationships indicated isometric growth in both sexes. These results provide baseline biometric information useful for future ecological studies and complementary fisheries assessments of P. nigricans in the Tocantins–Araguaia Basin. Full article

Warming is making drought and heat co-occur more often, intensifying compound stress on cropland in northern China’s drylands, where water scarcity makes further irrigation expansion untenable. On the Guanzhong Plain, a major grain-producing region, it remains unclear which irrigation conditions buffer cropland carbon–water productivity—the carbon assimilated per unit of water consumed—against such events. Using growing-season (March–October) remote sensing for 2016–2024, we identified the 2022 compound drought–heat event pixel by pixel and classified cropland as stable rainfed, transitional/mixed, or stable high-coverage irrigation from the pre-event (2016–2020) irrigated-area fraction and its persistence. In 2022, 88.9% of cropland experienced at least one compound dry–hot day, with dry–hot overlap 2.4 times the independence expectation. After balancing climate, terrain, soil, spatial position, and subpixel cropland fraction, stable high-coverage irrigation held no advantage in event-year resistance, post-event recovery, or overall resilience. Carbon assimilation remained above its pre-event level while carbon–water productivity fell, so the event cost water-use efficiency rather than carbon. Event-period root-zone soil-moisture change ranked first, and irrigated-area fraction last, among twelve random-forest predictors of resistance. We flagged 6722.3 km² of cropland for water-use audits and 2418.1 km² for supplemental irrigation; limited water should be allocated by realized moisture status, exposure, and resilience, not by irrigability. Full article

Accurate monitoring of surface water quality remains challenging due to pronounced spatial heterogeneity and limited ground observations. Satellite remote sensing offers scalable solutions, yet the extent to which environmental drivers enhance predictive performance, particularly in complex river–lake systems, remains insufficiently understood. This study develops a parallel comparative river–lake modeling framework to estimate permanganate index (CODmn), total phosphorus (TP), and total nitrogen (TN) by integrating satellite spectral data with climatic and land-use variables. Four model configurations were evaluated: spectral predictors alone (M₁), spectral predictors combined with climate variables (M₂), spectral predictors combined with land-use information (M₃), and full integration of all predictors (M₄). LightGBM models were optimized using Bayesian hyperparameter tuning (Optuna) and trained over rivers (January 2021–July 2025) and lakes (January 2021–December 2024) datasets in the Dongliao Basin, China. Spectral predictors alone (M₁) provided robust performance for CODmn ($R^2$ = 0.78), with marginal improvement when land-use variables were included (M₂) in rivers ($R^2$ = 0.80). In contrast, nutrient predictions showed stronger dependence on environmental covariates. TN predictions improved substantially with land-use inputs ($M3$) (R² = 0.75 in rivers and 0.63 in lakes with M₂), with further gains with full integration ($M4$) in lakes (${\mathrm{R}}^2$ = 0.66). TP predictions exhibited marked improvements with land-use variables in rivers (R² = 0.76) and with full integration in lakes ($R^2$ = 0.72). Model interpretability analysis using SHAP revealed that spectral features dominate CODmn estimation, while climatic and watershed characteristics exert greater influence on TN variability. Seasonal analysis indicated that hydrological drivers dominate during wet seasons, while land-use effects and internal biogeochemical processes become more important in dry seasons. The proposed framework advances predictive accuracy and process understanding, supporting more effective monitoring and management of water quality in complex river–lake systems. Full article

To elucidate the recharge relationships and hydrological processes among different water bodies in the Qinghai Lake Basin, precipitation, river water, groundwater, and lake water samples were collected from April to November 2024. The hydrogen and oxygen stable isotope compositions (δ²H and δ¹⁸O) were determined to characterize their spatiotemporal variations, and the MixSIAR model was applied to quantitatively evaluate the recharge contributions among different water bodies. The results show significant differences in stable isotope compositions among the various water bodies. Overall, lake water exhibited the most enriched isotopic signatures, whereas groundwater was the most depleted and isotopically stable, while precipitation displayed the largest variability. Precipitation isotopes exhibited pronounced seasonal effects. River water showed a depletion–enrichment–depletion pattern, reflecting the important recharge contributions from wet season precipitation and frozen-soil meltwater. Groundwater exhibited relatively weak seasonal variations and a distinct smoothing effect. In contrast, the isotopic composition of lake water was jointly controlled by evaporative fractionation and multiple recharge sources, with the highest enrichment occurring in spring and gradual depletion during wet season and dry season. Spatially, significant isotopic differences were observed among rivers. Groundwater was relatively enriched in the western part of the basin and depleted in the eastern part, whereas lake water exhibited an opposite pattern, characterized by enrichment in the east and depletion in the west. The Local Meteoric Water Line (LMWL) of the Qinghai Lake Basin was defined as δ²H = 8.07δ¹⁸O + 37.48 (R² = 0.96). Both the slope and intercept were higher than those of the Global Meteoric Water Line (GMWL), indicating that locally recycled evaporated moisture played an important role in regional precipitation formation. The river water line showed characteristics similar to those of the groundwater line, suggesting strong hydraulic connectivity between river water and groundwater. In contrast, the lake water line deviated markedly from the meteoric water line, indicating significant evaporative fractionation of lake water. The MixSIAR results indicate that the contributions of river water, groundwater, and precipitation to lake water were 37.5%, 33.9%, and 28.6%, respectively. These findings reveal the complex hydrological connections and transformation processes among multiple water bodies in the Qinghai Lake Basin and provide a scientific basis for water resource management and ecological environmental protection in inland basins of the Qinghai–Tibet Plateau. Full article

Straw biochar has the potential to improve rice productivity and mitigate greenhouse gas emissions. However, its synergistic regulatory effects on yield performance and methane (CH₄) emissions in double-cropping rice systems, especially under the intermediate climate warming scenario, remain poorly understood. A two-year field experiment was carried out from 2022 to 2023 with four treatments: ambient temperature with direct straw incorporation (CKS), ambient temperature with straw biochar incorporation (CKB), warming with direct straw incorporation (WS), and warming with straw biochar incorporation (WB). Rice yield and yield components, CH₄ emission characteristics, soil physicochemical properties, and functional microbial abundance were systematically determined. The results showed that for early rice, compared with CKS, CKB maintained a stable yield, while WS had a significantly reduced yield of 7.01% (p < 0.05); compared with WS, WB had an increased yield of 4.65% (p > 0.05), which was mainly attributed to the increases in grain weight, dry matter accumulation from heading to maturity, and leaf SPAD value after heading. For late rice, compared with CKS, CKB had no significant difference in yield, while WS had a decreased yield of 8.47% (p < 0.05); compared with WS, WB had a significantly increased yield of 6.47% (p < 0.05), mainly due to the increases in spikelets per panicle, dry matter accumulation at tillering, as well as the number of secondary branches and spikelets on secondary branches. For CH₄ emissions, compared with CKS, CKB significantly reduced CH₄ emissions and yield-scaled CH₄ emissions by 48.67% (p < 0.05) and 47.75% (p < 0.05) in early rice, and by 35.22% (p < 0.05) and 37.22% (p < 0.05) in late rice, respectively. Compared with WS, WB significantly reduced CH₄ emissions and yield-scaled CH₄ emissions by 57.81% (p < 0.05) and 59.61% (p < 0.05) in early rice, and by 42.55% (p < 0.05) and 46.09% (p < 0.05) in late rice, respectively. Correlation analysis revealed that CKB and WB reduced CH₄ emissions by decreasing soil $\mathrm{N}{\mathrm{H}}_4^{+}\text{-}\mathrm{N}$, DOC, and methanogen abundance in early rice, and by lowering DOC and methanogen abundance in late rice. In summary, straw biochar incorporation can significantly reduce CH₄ emissions from double-cropping rice paddies under ambient temperature. Under the intermediate climate warming scenario, this practice can partially mitigate yield losses (significant in the late-rice season) and simultaneously lower CH₄ emissions. It is an efficient agricultural management strategy adapted to climate warming, providing a key scientific basis and feasible technical pathways for sustainable production in double-cropping rice regions of South China. Full article