Search Results (40,624)

For soil processes that are known to be temporally dynamic, such as soil respiration, methanogenesis, and nitrification–denitrification, it is challenging to capture temporal variations with field-portable greenhouse gas (GHG) analyzers to provide the most accurate estimates of season-long GHG emissions and global warming potentials (GWPs). The objective of this field study was to evaluate the effects of measurement frequency (i.e., weekly, every other week, and every third week), replication (i.e., three, four, or five), and their interaction on the consistency of season-long carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions and GWP estimates across multiple ecosystems. Results are based on direct, in-field measurements with a field-portable gas analyzer. Field research was conducted throughout the 2024 growing season in a minimally grazed pasture, tallgrass prairie, soybean under conventional and conservation management practices, and cotton under conservation management in Arkansas, USA. Season-long CO₂ emissions and GWP from the tallgrass prairie were 1.1 times (12%) greater from the weekly and every-other-week (16.9 and 17.0 Mg ha⁻¹, respectively), which did not differ, than the every-third-week (14.2 and 14.2 Mg ha⁻¹, respectively) measurement frequencies. Season-long CH₄ emissions from the minimally grazed pasture and conservation-tilled soybean system were ≥7.5 times greater with four and five replications, which did not differ, than with three replications. Global warming potential in the conservation-tilled soybean (13.9 Mg ha⁻¹) and conservation-tilled cotton (21.1 Mg ha⁻¹) systems were ≥1.1 times (13%) greater with the every-third-week than with the weekly data set. Though this study was somewhat limited due the data sub-setting approach used, even using current, state-of-the-art, field-portable GHG analyzers, an appropriate in-field measurement frequency and number of spatial replications should be considered to reliably quantify whole-field, season-long GHG emissions and GWP estimates. Full article

The carried-out microfield model research was aimed at identifying patterns in the dynamics of soil CO₂ effluxes depending on the locally occurring hydrothermal regimes of regenerated lawn ecosystems on peat–sand substrates with different peat contents. Monitoring was carried out every ten days from 21 April 2019 to 30 October 2019 and included measurements of soil and air temperature, soil moisture, and CO₂ efflux every 3 h during the day. The weather conditions of the 2019 growing season in Moscow, with air temperature close to the annual average and increased precipitation, made it possible to clarify quantitative patterns of the temperature influence on CO₂ efflux from lawn soils in case of their pronounced dynamics without real soil moisture deficit. To study relationships between CO₂ efflux and soil and air temperatures, three empirical CO₂ efflux models (Exponential, Raich–Hashimoto and Lloyd–Taylor) were used with comparative assessment of their results. The conducted investigation showed that both peat content, local hydrothermal regime, and type of vegetation cover play a significant role in efflux modulation, with the temperature factor dominating on both seasonal (72% impact) and intraday (51–94% impact) scales. The lawn substrate factor accounts for up to 10% of CO₂ efflux variability on the intraday scale. The lawn vegetation cover (with the lower and higher diversity) significantly affects the soil hydrothermal regime depending on the peat content (a higher impact with a lower peat content due to the soil pH difference). The denser vegetation reduces the soil temperature, providing better protection, and at the same time reduces soil moisture by transpiration, which provides the combined effect on the CO₂ efflux reduction (up to 1 g CO₂ m⁻² day⁻¹ reduction for the lower-pH soils). Full article

This proof-of-concept study proposes a photovoltaic transparent vacuum insulation panel (PV-TVIP) and evaluates its heat transfer and power generation characteristics with increased temperatures, and light transmission characteristics for visible light and ultraviolet wavelengths. The study was conducted with a climate-controlled chamber mimicking the common temperature range of Sapporo, Japan. The average TVIP heat flux was measured to be 65–75 W/m² with a U-value of 1.95–2.3 W/(m²∙K). Compared to earlier measurements to see the effect of seasonal atmospheric conditions to the quality of the TVIP, it was determined that the TVIP manufactured during winter conducted less heat, assumed to be caused by decreased humidity. Placing the PV between the TVIP and a glass pane increased the operating temperature by 26.06 °C and decreased power generation by 13%. Afterwards, the transparency of the TVIP and PV-TVIP were measured under a bright light therapy lamp, showing that TVIP reduced the amount of most visible light wavelengths by 50% and the PV-TVIP by 90%. UV radiation was respectively reduced by approximately 78% and 100%. The results show that while PV-TVIP shows potential as a BAPV window retrofit solution, its manufacturing requires optimized, low-humidity conditions during all phases of the manufacturing process. Full article

Reliable quantification of crop evapotranspiration (ET_c) at field resolution is a prerequisite for evidence-based irrigation scheduling in agricultural systems subject to nitrate leaching constraints. This study presents and evaluates a multi-sensor data fusion framework integrating MODIS Terra (500 m, daily) and Sentinel-2 (10–20 m, 5-day revisit) imagery to generate cloud-robust, daily ET_c maps for an 87.5 ha irrigated maize field in Nyírbátor, Hungary, during the 2020 and 2021 growing seasons. Three gap-filling strategies for missing Sentinel-2 NDVI observations were systematically compared: (i) co-regionalisation with cokriging, (ii) local time series interpolation of MODIS pixel centres using ordinary kriging, and (iii) a median time series of cotemporal MODIS pixels—a novel approach developed to suppress sub-pixel spectral contamination from roads and irrigation infrastructure. For field-mean temporal reconstruction, the median approach consistently outperformed the alternatives (adjusted R² = 0.81, NRMSE = 0.15–0.17; pixel-wise correlation 0.70–0.85), effectively filtering heterogeneous landscape artefacts. Daily crop coefficients (K_c) derived from fused NDVI time series via the FAO-56 framework yielded ET_c ranging from 0.99 mm day⁻¹ (initial stage) to 6.40 mm day⁻¹ (peak crop development). Seasonal precipitation–ET_c deficit analyses revealed contrasting patterns: near balance in 2020 versus an 85 mm mid-season deficit at critical nodes in 2021, demonstrating the potential utility of spatially explicit daily ET_c monitoring for irrigation scheduling. These deficit estimates represent irrigation demand indicators; a complete water balance would additionally require measured irrigation volumes, soil water storage changes, deep percolation, and surface runoff data. The methodology provides a proof-of-concept framework for EU Nitrates Directive compliance monitoring, relying solely on freely available satellite data. Independent ET_c validation is required before operational deployment, and transferability to other crops and regions requires validation across contrasting pedoclimatic conditions. Full article

Frequent extreme climate events pose severe threats to human health. Existing studies mainly focused on summer thermal environments, while few compared summer and winter extreme climate risks from the perspective of urban functional zones (UFZs). This study classified more precise UFZs using the machine-learning method and constructed heat and cold exposure indicators. GeoDetector was adopted to analyze driving factors and interactions of both types of exposure across UFZs. The results showed that UFZ classification achieved an overall accuracy of 81.8% and a Kappa coefficient of 0.75. High heat exposure concentrated in core public, residential, and commercial zones, while high cold exposure occurred in peripheral industrial and greenspace zones. Dual high exposure zones lay between the 3rd and 5th Ring Roads. Industrial zones positively contributed to both exposures, while commercial, public, and residential zones showed positive heat but negative cold exposure contributions, and greenspace zones presented opposite effects. Vulnerable population ratios had a strong explanatory power. Heat exposure interactions were dominated by vulnerable populations, building morphology, and landscape patterns, while cold exposure was also affected by the degree of facility agglomeration and human activities with varied mechanisms across UFZs. This study advanced single-season thermal research to multi-season exposure and zoned governance for climate-adaptive renewal. Full article

Slope stability has consistently been a critical concern in mountainous road sections, with precipitation being the most significant factor precipitating slope instability. This study aims to elucidate the mechanism of slope instability under precipitation conditions and the extent of the impact of internal disaster-causing factors. To achieve this objective, a numerical simulation analysis method combining GeoStudio2018R2 and FLAC3D7.0 software was employed to conduct a comprehensive analysis of an unstable slope in Xinjiang. Regarding research methodology, cyclic precipitation and seasonal snowmelt were considered as external influencing factors. Initially, a two-dimensional model was constructed using GeoStudio software to analyze the spatial and temporal variations in pore water pressure and moisture content within the slope, elucidating their dynamic characteristics at different temporal and spatial scales. Subsequently, a three-dimensional numerical model was established using FLAC3D software to conduct a detailed analysis of the stress–strain state of the slope under various conditions, thereby obtaining disaster parameters such as displacement and sliding velocity in different directions. Through further comparison and verification of the overall stability analysis results of the slope obtained from both software packages, it was observed that they exhibited a consistent trend. The research findings indicate that under conditions of high-intensity short-term precipitation, the safety factor of the slope decreases to the lowest level, potentially leading to shallow landslides with smaller displacement but faster sliding velocity. Conversely, seasonal snowmelt and long-term localized precipitation have a more profound impact on the internal structure of the slope, with the sliding zone potentially penetrating into the deep bedrock. Although the occurrence frequency is low, the impact range is extensive. By combining two-dimensional and three-dimensional analyses, a comprehensive assessment of the different disaster-causing factors of the slope was conducted, enhancing the accuracy of the analysis results. The research findings provide a scientific basis and reference value for the formulation of subsequent slope protection and monitoring plans. Full article

Sustainable management of hydrogeological systems that supply water and exhibit high hydrologic complexity can be studied through pragmatic numerical modeling supported by field-constrained conceptualization. This study develops a local-scale three-dimensional groundwater flow numerical model using FEFLOW for the Barranca Lebrija settlement in Aguachica town, where the Lebrija River, the Musanda floodplain lake, and groundwater system converge. The numerical model incorporates: (i) the three-dimensional distribution of geological units and lithology; (ii) water level observations from the Musanda floodplain lake; (iii) stage records from the Lebrija River; (iv) boundary conditions and flux estimates inherited from a previous regional groundwater model; and (v) hydraulic heads from two monitoring wells and five community wells. Steady-state and transient conditions were calibrated, and a sensitivity analysis was performed to identify the parameters that most strongly control surface water–groundwater exchange. The simulations reproduce seasonal groundwater level trends and demonstrate the exchange pathways among the river, floodplain lake, and groundwater system. Results indicate dual behavior: during wet periods, flooding of the Musanda floodplain lake driven by high river levels seeps into the underlying aquifer, whereas in dry periods the floodplain lake reverses its role and becomes a principal discharge boundary. This local-scale, boundary-driven approach provides a computationally tractable framework to quantify SW–GW exchange in data-scarce tropical floodplains and supports monitoring design and water-supply management. Full article

Background: The Gansu Heihe Provincial Nature Reserve harbors rich plant and animal resources, yet its coleopteran fauna has remained taxonomically and ecologically uncharacterized. To address this gap, we conducted the first systematic survey of beetle diversity across four representative transects—Youcaigou (I), Zhugou (II), Loufangya (III), and Sigou (IV)—and assessed variation in community structure using the Shannon–Wiener diversity index, Margalef richness index, Berger–Parker dominance index, Pielou evenness index, and Jaccard similarity coefficient. Results: A total of 131 species belonging to 108 genera and 22 families were identified, establishing a comprehensive baseline of beetle diversity for the reserve. Cerambycidae was the most species-rich family (27 species), while Lampyridae, Staphylinidae, and Anobiidae were each represented by only a single species, reflecting marked unevenness in family-level composition. Diversity and community structure differed substantially among transects: Transect II showed the highest Shannon–Wiener diversity index and Pielou evenness, Transect III the lowest diversity, and Transect IV the greatest dominance by a few species, while species richness declined in the order I > II > III > IV. Zoogeographic analysis revealed that widely distributed (Cosmopolitan) species predominated (83 species; 63.36%), with Palaearctic (21 species; 16.03%) and Oriental (27 species; 20.61%) elements also well represented, underscoring the reserve’s position at a key biogeographic transition zone. Within China, North China faunal elements were most prevalent (75.94%), with the North China–Northeast China distribution group alone accounting for 54.20% of species, whereas nationally widespread species comprised only 9.16%. Conclusions: This study provides the first systematic record of coleopteran diversity in the Gansu Heihe Provincial Nature Reserve, enriching the region’s biodiversity inventory and offering reference data for future insect monitoring and forest conservation. Further multi-seasonal, method-diversified surveys are needed to achieve a complete faunal inventory. Full article

Cloud-dependent irrigation platforms can support remote monitoring, but their use in precision fertigation is limited when local decisions must be made quickly and reliably. Network delay, temporary disconnection, and the use of single-point measurements may all reduce the ability of a system to respond to spatial variation in soil moisture and nutrient demand. In this work, an edge-controlled precision fertigation system was developed by combining multi-parameter soil sensing, spatial task scheduling, and a 6-DOF robotic manipulator. The ESP32 controller runs a preemptive FreeRTOS scheduler, allowing sensor acquisition, inverse-kinematics calculation, and pump actuation to be handled as separate tasks. A Kalman filter was used to smooth soil moisture measurements, and a hysteresis-based control strategy was adopted to reduce false triggering and repeated pump switching. To improve fertigation safety, a hardware–software interlock was added so that fertilizer delivery is always accompanied by water delivery. Hardware-in-the-Loop simulation and a 14-day field deployment were used to evaluate the system. The controller achieved an end-to-end latency of less than 38 ms and maintained operation during network interruptions through cached local parameters. After calibration, the robotic end-effector positioning error was reduced to ±2.4 mm. The hysteresis strategy lowered daily pump cycling by 71%. Based on prototype duty-cycle data and seasonal extrapolation, the projected seasonal water use and fertilizer demand were 44% and 38% lower, respectively, than those estimated for a uniform application. These values should be interpreted as model-based projections rather than direct season-long measurements. During 72 h of continuous operation, no Modbus faults were observed, and RTOS heap fragmentation remained stable. Overall, the results suggest that edge-based deterministic control can provide a practical route for precision fertigation where both spatial variability and intermittent connectivity must be considered. Full article

Accurate change detection in high-resolution remote sensing imagery is essential for urban planning, land-use monitoring, and disaster response. This study introduces CTA-Net, a Cross-Temporal Attention Network for binary change detection in bi-temporal optical imagery, designed to improve robustness against pseudo-changes caused by illumination variation, seasonal effects, and sensor noise. The proposed method employs a shared Siamese encoder with multi-scale Cross-Temporal Attention modules that derive spatial and channel attention from L2 feature differences, along with a lightweight confidence estimation head for per-pixel uncertainty modelling. A hybrid loss function combining confidence-weighted binary cross-entropy and focal loss is used to address class imbalance. Experiments on the LEVIR-CD dataset demonstrate that CTA-Net achieves an overall accuracy of 98.99%, an F1-score of 87.68%, an Intersection over Union of 78.06%, a Cohen’s kappa of 0.8715, and a Matthews Correlation Coefficient of 0.8721, with stable convergence and minimal overfitting. Qualitative and calibration analyses further indicate that the model produces interpretable attention maps and reliable probabilistic outputs. To evaluate cross-domain generalization, we conduct a transfer learning case study on multispectral Sentinel-2 agricultural imagery. The model is adapted to 11-channel input and fine-tuned on automatically generated change masks derived from NDVI-delta thresholding. Under this supervision protocol, CTA-Net achieves an F1-score of 95.18% and an IoU of 90.81% on a held-out test region, with balanced precision and recall. While these results demonstrate effective adaptation across sensor modality, spatial resolution, and semantic domain, the evaluation reflects agreement with the mask generation procedure rather than independently annotated ground truth. While CTA-Net shows strong performance and reasonable interpretability, its cross-domain evaluation is limited by the use of automatically generated labels. As a result, the reported transferability should be interpreted cautiously until validated on human-annotated datasets. Full article

Physalis pubescens L. is a seasonal fruit with high nutritional value but a short shelf life that limits its processing and utilization. This study integrated metagenomics and metabolomics to investigate the comparative effects of Lactiplantibacillus plantarum fermentation on volatile flavor metabolites and microbial community composition of P. pubescens by comparing initial (0 h) and post-fermentation (24 h) states. After 24 h of fermentation, 1316 volatile compounds were putatively identified by GC-MS, with 592 metabolites significantly changed and 501 upregulated and 91 downregulated. Key flavor compounds that impart citrus, floral, fruity, and rose notes including D-limonene, geraniol, D-carvone, and phenylethyl alcohol were markedly increased. Metagenomic analysis revealed that L. plantarum rapidly dominated the microbial community (relative abundance surged from <0.05% to ~72%) while effectively suppressing potential spoilage bacteria such as Escherichia coli. Functional gene annotation demonstrated significant enrichment of amino acid, carbohydrate, and fatty acid metabolism pathways, with key enzyme genes (L-lactate dehydrogenase, pyruvate oxidase, acetyl-CoA carboxylase) predominantly assigned to L. plantarum, suggesting their potential contribution to the generation of organic acids, ethanol, and esters. Spearman correlation analysis indicated that Lactobacillaceae genera were significantly positively correlated with terpenoids, phenols, alcohols, and aldehydes. This study provides the first metagenomics-metabolomics insight into the microbial and molecular mechanisms associated with flavor formation in LAB-fermented P. pubescens, offering a theoretical foundation for developing stable and controllable fermented fruit products. Full article

Deep-sea transportation is faced with complex navigation environments, long voyages, limited emergency response resources, and interacting safety risks. Existing studies have mainly focused on individual risk factors, while the correlations and coupling effects among different factors have received insufficient attention. To identify the key risk factors affecting deep-sea transportation safety, this paper proposes a novel key factor identification model based on complex network theory. Firstly, 34 risk factors affecting deep-sea transportation safety are selected from five aspects using a literature analysis method. Secondly, a weighted directed network of risk factors is constructed based on complex network theory. Then, to evaluate the node importance, six node importance evaluation indicators are established, and a node importance evaluation method is proposed by integrating the analytic hierarchy process (AHP), technique for order preference by similarity to an ideal solution (TOPSIS), and gray relational analysis (GRA). Key risk factors are then determined according to the node importance evaluation results. Finally, the effectiveness of the proposed model is verified through a case study. The results show that the top five most critical risk factors are risk of leakage, emergency speed, physical and chemical properties of the cargoes, sense of personnel safety duty, and seasonal route. The findings can provide practical support for maritime authorities, shipping companies, and safety managers in formulating targeted prevention, control, and emergency response measures for deep-sea transportation safety. Full article

Mental toughness (MT) may contribute to within-athlete rowing performance variation, yet longitudinal evidence remains sparse. This pilot study examined within-athlete associations between MT and 2K ergometer performance across a competitive season in Division II female rowers. Twelve athletes (age 20.8 ± 2.1 years) completed the mental toughness index (MTI) before four standardized 2K time trials. Performance was modeled using a linear mixed-effects model with a random intercept for the athlete. The MTI was decomposed into within- and between-athlete components, with the timepoint as a categorical covariate. Small-sample inference used CR2 cluster-robust standard errors with Satterthwaite degrees of freedom. Performance improved mid-season relative to baseline (Timepoint 3: −7.29 s; 95% CI [−13.29, −1.29]; p = 0.023). The within-athlete MTI association was small and imprecise (β = −0.48 s/point; 95% CI [−1.56, 0.59]; p = 0.311), and the between-athlete MTI was unassociated with performance (β = 0.70; p = 0.667). Stable between-athlete differences dominated over variability (ICC = 0.946; R²_m = 0.033; R²_c = 0.948). The within-athlete MTI estimate was small and imprecise; given the wide compatibility interval, both the direction and magnitude of the association remain highly uncertain, and this inconclusive finding should not be interpreted as evidence of absence. Future studies with larger samples and key covariates (e.g., training load and illness/injury) are needed to confirm these preliminary estimates. Full article

The seas around Sabah host the richest elasmobranch biodiversity in Malaysia. Currently, only 11 shark and ray species are protected under Malaysian legislation, while other species can be legally caught and sold in markets. Many of these species, including those with protected status, are captured as bycatch in commercial trawl fisheries. In Sabah, where trawling is a cornerstone of seafood production, indiscriminate fishing practices prioritize catch volume over gear selectivity. This study focuses on bycatch of Endangered, Threatened, and Protected (ETP) elasmobranchs, which represents an important ecological loss and is rarely retained for legal sale. To determine the spatiotemporal patterns of these captures, custom electronic monitoring (EM) cameras were deployed to capture time- and GPS-stamped imagery of all catch landed on fishing vessel decks. Over a 42-month period, more than 9400 individuals were recorded, of which 34% were identified as Endangered, Threatened, and Protected (ETP) species. The most common ETP shark species were Carcharhinus tjutjot, Rhizoprionodon acutus, and Sphyrna spp., while the most common ETP ray species were Telatrygon biasa, Maculabatis gerrardi/Maculabatis macrura, and Brevitrygon heterura. Spatial analysis and kernel density estimation were used to identify hotspot areas of high bycatch rates. We calculated bycatch per unit effort (BPUE) to quantify the density of ETP shark and ray bycatch across varying fishing intensities, based on the number of individuals caught per trawl towing hours in each district. Seasonal life-stage analyses indicated that neonate and immature individuals comprised a substantial proportion of the catch for several ETP species and occurred across multiple monsoon seasons, highlighting the vulnerability of early life stages to trawl fisheries. Potential mitigation measures, including spatial and temporal management strategies such as time–area closures, are recommended in areas with consistently high bycatch to reduce shark and ray bycatch and protect hotspot areas. Full article

Dog parks are widely used recreational spaces for human–dog interaction, yet there is little empirical data about how surface materials influence dogs’ behavior and welfare. This study evaluated dogs’ behavior on three surfaces commonly used in outdoor dog recreation areas. Ten dogs (N = 10) participated in ten structured play sessions in an experimental area with unrestricted access to all surfaces. The testing area consisted of a 12.2 m² playground divided into nine plots of equal size. Each plot was randomly assigned a surface material (i.e., natural grass, stabilized grass, or artificial turf) in a 3 × 3 block design. Environmental and surface temperatures were recorded in each session. Dog behavior was recorded during a pre- and post-play period and measured using a 10 s scan sampling technique. In addition, surface characteristic measures were collected throughout the study to evaluate differences in their tolerance to weather conditions and usage. Artificial turf consistently reached a higher temperature (25.2 °C; 95% CI: 24.5–25.8 °C) than natural (19.4 °C; 95% CI: 18.7–20.1 °C) and stabilized (20.0 °C; 95% CI: 19.3–20.6 °C). In this study, the artificial turf reached temperatures as high as 63.8 °C while, under the same environmental conditions, the surface temperature of both natural turfgrass treatments remained below 40 °C. During the pre-play period, dogs showed more active than passive behaviors on the stabilized surface (35.03%; 95% CI: 30.58–39.80%) compared to the natural (27.86%; 95% CI: 23.94–32.10%) and artificial turf (23.31%; 95% CI: 19.81–27.20%). During the post-play period, activity levels decreased across all surfaces, while the occurrence of passive behaviors increased and was observed more frequently on the natural turfgrass surfaces (27.30% on stabilized and 15.52% on natural) than on artificial turf (2.41%). Artificial turf was less affected by dog traffic and seasonal changes; however, its surface was harder than both natural turfgrass treatments. The addition of the stabilizing grid failed to reduce soil compaction as anticipated. Overall, dogs spent more time on both natural turfgrass surfaces than artificial turf. However, a potential confounding effect of location could have influenced dog behavior. Nonetheless, our findings show that dog owners should be cautious when using artificial turf areas when environmental temperatures are above 25 °C when the turf temperature is above the safety threshold for burn injuries. These findings highlight the importance of carefully selecting surface materials for outdoor dog spaces to ensure dogs’ safety and comfort. Full article