Search Results (13,253)

Water quality plays a central role in determining the environmental performance of pond-based tropical aquaculture systems. This study aimed to evaluate the relative environmental performance of different tropical pond-based aquaculture systems by identifying multivariate water quality patterns that allow their discrimination and comparison under commercial production conditions. Four pond-based production systems were evaluated: an aquaponic system (APS), a recirculating aquaculture system (RAS), a conventional earthen pond system (CEP), and an integrated rice–chame system (RCS). Fourteen physicochemical water quality variables were monitored throughout the production cycle under real commercial conditions using a comparative observational design. Multivariate discriminant analysis was applied to identify the variables with the highest discriminatory power and evaluate the ability of water quality patterns to correctly classify observations among production systems. The results revealed a clear multivariate separation between technologically intensive systems (APS and RAS) and less intensive and integrated systems (CEP and RCS), reflecting distinct water quality structures and environmental functioning. Variables associated with mineralization and nutrient dynamics, including electrical conductivity, dissolved solids, turbidity, phosphates, chlorides, dissolved oxygen, nitrites, and temperature, contributed most strongly to system discrimination. The discriminant functions achieved a high overall correct classification rate, demonstrating the robustness of the multivariate approach. These findings support the use of water quality variables as consistent environmental signatures for distinguishing tropical pond-based aquaculture systems, providing an operational framework for assessing their relative environmental performance. Discriminant analysis emerges as a valuable tool for system characterization and comparative evaluation, supporting environmentally informed management and optimization of chame aquaculture under tropical conditions. Although water quality represents a robust integrative indicator, it captures only one dimension of environmental performance, and additional factors such as production efficiency, energy use, and effluent characterization should be incorporated in future studies to achieve a comprehensive sustainability assessment. Full article

This article presents a performance assessment of an electrical power and cooling system powered by a parabolic dish collector and using refrigerants with low global warming potential. The study was conducted using energy and mass balances for each component and system. The simulation includes various parameters, such as solar radiation, the focal temperature of the solar collector, the ambient temperature, the power cycle pressure ratio, and the chiller’s evaporation temperature. The results show that the efficiency of the organic Rankine cycle with the refrigerant R1233zd(E) is similar to that of the refrigerants R123 and R245fa and is up to 11 and 50 times lower than with R290 and R744, respectively. The solar absorption chiller using the refrigerant R717 can achieve cooling with a supply temperature up to 5 °C lower than that of R718. The dynamic simulation results show that the energy efficiency of the proposed solar-powered generator–chiller is 14% higher than that of a standard solar-powered absorption chiller. Furthermore, the same solar-powered generator–chiller reduces the primary energy required by a conventional system by 60% (PESr = 0.60). The presented results may be useful for the design of sustainable generator–chillers for rural areas or for autonomous housing in tropical climates. Full article

The northeast monsoon prevailing over southeastern China in late seasons, generally from October to March, frequently generates water level anomalies upstream of the Taiwan Strait (TWS) that reach the coastal waters of Guangdong in South China, and, with compounding astronomical high tides, elevate coastal flood risk over the region. The risk of coastal flooding or sea inundation is further heightened when monsoon forcing co-occurs with storm surge brought by late-season tropical cyclones (TCs). This study integrates tide gauge observations from Hong Kong (HK) and its vicinity together with Delft3D Flexible Mesh simulations to diagnose a tide-modulated anomaly wave mechanism. Observations show that anomalies originating in or near TWS arrive in HK with station-dependent phasing. These water level anomalies exhibit a characteristic ~6 h periodicity west of the Taiwan Shoal, and display peaks that systematically align with the astronomical high tide. Time–frequency analysis reveals a wave period transformation from ~12 h north of Dongshandao over the coast of southeastern China to ~6 h west of the Taiwan Shoal. We test the hypothesis that wind-forced water anomalies generated in or near TWS undergo shoal-modulated nonlinear tide–wind interaction and tidal-current advection that transform their dominant period and phase-lock them to the tide, producing four anomaly peaks per day downstream and station-dependent phasing in HK. Hindcasts of the November 2024 monsoon episode reproduce the observed timing, periodicity, and spatial transition, while constituent experiments demonstrate that semi-diurnal forcing entering via the TWS is the primary driver of the ~6 h signal, with the Taiwan Shoal acting as the modulation locus. Accurate water level forecasts for the Guangdong coast, therefore, need to incorporate upstream wind forcing over the TWS and bathymetric controls around the Taiwan Shoal, with practical implications for compound flood risk during spring tides and co-occurring monsoon and/or TC events. Full article

Typhoon track prediction is an important research direction in weather forecasting. Although deep learning methods have achieved some progress in this field, challenges remain, including insufficient fusion of meteorological features, limited capability in modeling temporal and spatial evolution, and high computational cost of some models. To address these issues, this paper proposes a dual-path, multi-modal typhoon track prediction model that incorporates a gated axial Transformer to enhance the modeling of deep structural features in the meteorological environment. Numerical experimental results show that the proposed model achieves higher prediction accuracy than comparative methods in typhoon track prediction tasks across multiple time scales, demonstrating the effectiveness of the approach. Full article

Karst ecosystems play an important hydrological role in regulating regional water availability and supporting biodiversity, yet they face increasing threats from deforestation, land-use conversion, and limited scientific data to inform sustainable conservation efforts. This study aims to assess karst geodiversity, aquatic habitat diversity, and freshwater endemism in the Maybrat Karst, and to explain the linkages among these three aspects as a scientific basis for regional karst conservation. The research employed geospatial analysis and descriptive ecological analysis. Data were collected through satellite image interpretation, participatory mapping, field observations, and a comprehensive literature review. Results show that the Maybrat Karst has very high geodiversity, with ±2322.91 km² (41.49%) of the region classified as karst. All seven karst elements were identified, including 40–56 hills/km², 110 water-filled dolines, 334 springs, 178 subterranean rivers, 90 caves, and three major karst lakes. Aquatic habitat diversity is likewise very high, comprising seven habitat types across the full 100–500 m elevational range, accompanied by 17 Cherax morphotypes, indicating strong environmental differentiation. The literature review identified 18 endemic freshwater species, consisting of five Cherax species, ten rainbowfish species of the genus Melanotaenia, and three additional taxa: Pseudomugil reticulatus, Glossogobius hoesei, and Zenarchopterus ornithocephala. These findings confirm that high karst geodiversity and habitat heterogeneity make the Maybrat Karst a key aquatic endemism center, highlighting the urgent national and global imperative for comprehensive karst protection to safeguard long-term biodiversity and ecosystem sustainability. Full article

Drifting fish aggregating devices (DFADs) are central to tropical tuna purse-seine fisheries, yet their hydrodynamic performance under realistic seas has not been adequately addressed, particularly for emerging eco-friendly designs. A three-dimensional framework based on computational fluid dynamics is developed to assess the motion response and mooring loads of full-scale DFADs comprising raft buoys, biodegradable cotton rope, and iron sinkers, using four buoy layouts (Models A to D). Unsteady Reynolds-averaged Navier–Stokes (URANS) simulations are performed with a realizable k–ε closure, volume of fluid (VOF) free-surface capturing, the Euler overlay method, dynamic overset meshes, and catenary mooring coupling. Regular waves representative of operational conditions (T = 1.40 to 2.40 s, H = 0.10 to 0.40 m) are imposed via a VOF wave-forcing technique, and mesh/time-step sensitivity analyses demonstrate the accurate reproduction of the first-order wave elevation (error < 0.8%). Surge drift per cycle and heave response amplitude operators, with the relative mooring force, are evaluated as functions of the relative wavelength (λ/L_a) and wave steepness (H/λ). The results reveal that the buoy layout exerts first-order control on DFAD dynamics, whereas short, steep waves dominate motion and line loads. The intermediate end-point sinker mass achieves a favorable balance between motion suppression and mooring load control, whereas distributing a fixed total sinker mass along the rope reduces heave response and mooring force by improving the tension redistribution and overall stability. Across all sea states, Models A and D reduced motion envelopes and mooring forces, indicating their suitability as robust, low-impact configurations. The proposed framework and design recommendations provide quantitative guidance for optimizing eco-DFAD geometry and deployment strategies, supporting safer and more sustainable DFAD-based tuna fisheries. Full article

The Navel Orangeworm (Amyelois transitella Walker, 1863), a primary pest of nut crops native to North America, poses a significant potential threat to China’s agricultural biosecurity, yet its potential distribution dynamics under climate change remain unquantified. This study utilized the Biomod2 ensemble model platform to predict habitat suitability under current and future climate scenarios (SSP1-2.6 and SSP5-8.5). We evaluated the prediction accuracy of the ensemble model using calibration data, with TSS = 0.898 and AUC = 0.978, while spatially stratified cross-validation confirmed moderate spatial transferability to novel environments (median validation AUC = 0.60–0.75). The model identified thermal factors—Temperature Seasonality (Bio4) and the Mean Temperature of the Wettest Quarter (Bio8)—as the dominant drivers of distribution. While currently climatically suitable habitats are primarily confined to the tropical and subtropical regions of southern China, projections indicate a complex spatial shift driven by future warming: optimal southern habitats will undergo a net contraction due to heat stress, whereas low and moderately suitable areas will expand northward into key temperate agricultural areas. These results highlight that climate change will substantially alter the spatial topology of the pest’s climatic envelope, providing a critical scientific baseline of climatic suitability. These projections do not equate to realized invasion risk, which is further constrained by host availability, land use, irrigation, and human transport, offering a conservative framework for prioritizing early surveillance and optimizing quarantine measures. Full article

Synthetic Aperture Radar (SAR) images offer significant advantages for monitoring the dynamics of water bodies in tropical regions, mainly due to their ability to acquire data under adverse weather conditions, which frequently limit optical sensors. However, the automated classification of water bodies using SAR data still faces methodological challenges, particularly regarding the selection of the most suitable parameters and polarizations. This study proposes a multitemporal classification methodology using Sentinel-1 data to map the flood regimes of lagoon complexes in the State of Rio de Janeiro (Brazil). The approach integrates SAR image time series with the Random Forest machine learning algorithm, evaluating the performance of different polarization configurations (VV, VH, and VV–VH). The results show that the combined use of single and cross polarizations (VV–VH) achieved excellent performance, with a Kappa index of 0.83, F-score of 0.90, and overall accuracy of 0.96, demonstrating methodological robustness. The multitemporal analysis identified approximately 294 km² of permanently flooded areas, while seasonally flooded areas, associated with the seasonal variation in coastal lagoons, exhibited variations exceeding 30 km² over the time series. Full article

Nutrient inputs from human activities, such as agriculture and sewage discharge, influence algal blooms in water bodies. In Ecuador, the Daule River receives wastewater discharges. In addition, poor agricultural practices, including the unsuitable use of fertilisers in combination with soil erosion and surface runoff processes, increase the nutrient load to the river. Considering this, the objective of this study was to evaluate environmental and biological variables using statistical analysis to identify the parameters that influence algal blooms in the main stem of the Daule River. The methodology consisted of two phases: (i) data collection, including water sampling and laboratory work for the analysis of nutrients and phytoplankton, and (ii) statistical analysis, which includes univariate, bivariate, inferential and multivariate analysis (STATICO technique). The results showed that pH and dissolved oxygen were the main drivers of diatoms (Polymyxus coronalis and Aulacoseira granulate) and the charophyte Mougeotia sp. Similarly, ammonium-N was the main driver of the diatom Ulnaria ulna and the cyanobacteria Planktothrix cf. agardhii. The outcomes of this study identified the main environmental variables driving blooms of the five most abundant species, providing a basis for the development of ecological models in the context of land use and climate change. Full article

Background: Schistosoma spp. are trematodes occurring in tropical endemic areas but can be imported to non-endemic regions as causes of travel-associated infections. In this study, two pan-trematode-specific real-time PCR assays were evaluated for their diagnostic sensitivity in detecting Schistosoma spp. DNA in diagnostic human samples. Methods: Two previously described pan-trematode-specific real-time PCR assays were comparatively assessed using diagnostic samples containing DNA of either the S. haematobium complex or the S. mansoni complex, as confirmed by Schistosoma species complex-specific real-time PCR. Results: Out of a total of 655 samples containing Schistosoma spp. DNA, positive signals in at least one of the two pan-trematode real-time PCR assays were recorded for 17 (2.6%) nucleic acid extractions. Although sensitivity was in the >90% range for stool samples, only a few individual blood plasma and serum samples, and none of the Schistosoma spp. DNA-containing tissue or urine samples, tested positive by pan-trematode PCR. The lower sensitivity of pan-trematode PCR compared with Schistosoma spp.-specific PCR was semi-quantitatively confirmed by higher cycle threshold (Ct) values in the former. When comparing samples with concordant versus discordant positive results for Schistosoma spp.-specific and pan-trematode PCR, Ct values of the Schistosoma spp.-specific PCR were lower in concordantly positive samples than in discordantly positive samples. Conclusions: While the assessed pan-trematode PCR assays showed insufficient sensitivity as screening tools for blood plasma, blood serum, tissue, and urine samples from individuals with suspected schistosomiasis, they were sufficiently sensitive when applied to stool samples, in which substantial amounts of target DNA, as indicated by low Ct values in the Schistosoma species complex-specific real-time PCR assays, can be expected. For screening for Schistosoma spp. DNA in sample materials other than stool, the use of highly sensitive target-specific PCR remains necessary. Full article

Taraxacum kok-saghyz (TK), the rubber dandelion, is an emerging crop offering potential for sustainable natural rubber production independent of tropical climates. Successful domestication of TK requires a mechanistic understanding of its reproductive biology, yet floral anatomy, sporogenesis, and gametogenesis remain poorly characterized. We hypothesized that TK’s reproductive development follows the general patterns of sexually reproducing diploid Taraxacum species and other Asteraceae, distinguishable from the irregular meiosis reported in apomictic taxa. Here, using light and scanning electron microscopy across multiple developmental stages, we describe the floral and inflorescence anatomy, as well as sporogenesis and gametogenesis in TK. Anther development in TK predominantly follows the simultaneous microsporogenesis pattern, typical of eudicots, producing regular tetrahedral tetrads. Notably, we also observed occasional successive-type events resulting in dyads and tetragonal tetrads, indicating a previously unreported developmental variation within the species, culminating in mature tricellular pollen. We detail key reproductive structures, including anther wall layers, ovary mesophyll differentiation, and the presence of a micropylar obturator. The meiotic behavior and gametophyte development observed in TK are consistent with those of diploid, sexually reproducing Taraxacum species and other members of the Asteraceae, in contrast to the irregular meiosis reported in Taraxacum apomictic taxa. These newly described morphoanatomical details on reproductive aspects will inform breeding strategies and advance our understanding of pollination, fertilization, and seed development in TK. Full article

The development of stable and high-yielding fodder pearl millet genotypes with improved quality traits is crucial for enhancing livestock productivity under diverse environments. In this study, twenty-six elite genotypes, including brown midrib (bmr) lines and two check cultivars, were evaluated across four locations, which fall broadly under two agro-climatic zones of India, during the summer season of 2024 to assess their stability for yield and fodder quality traits. Significant genotypic differences and genotype × environment interactions (GEIs) were observed for all traits, indicating substantial genetic variability and environmental influence on trait expression. Additive Main Effects and Multiplicative Interaction (AMMI) and Weighted Average of Absolute Scores (WAAS) analyses identified IGPM 100 as a high-yielding and stable genotype across environments, whereas Baif Bajra 1 and IGBV 97 exhibited specific adaptation. Among quality traits, ICMbmr 2401, ICMbmr 2402, and ICMbmr 2404 recorded consistently low lignin content, confirming their potential for improving forage digestibility. Further, ICFPM 05 recorded high tillering and longer leaves, while ICMFV 2308 exhibited late flowering across locations, indicating their potential for use in developing leafy, late-flowering genotypes. The multi-trait stability index (MTSI) efficiently identified IGPM 100, ICFPM 02, ICMbmr 2404, and IGBV 9 as superior and stable genotypes across multiple traits. High selection differentials for green fodder yield and negative differentials for lignin and fibre fractions highlight the possibility of a simultaneous improvement in yield and quality traits. Overall, the integration of AMMI, WAAS, and MTSI models facilitated the identification of broadly adapted and trait-specific genotypes, which, after evaluating their combining ability, can be used for developing fodder pearl millet composites and hybrids. Full article

Hurricanes routinely damage forests across the North Atlantic Basin, yet efforts to characterize their impacts have had mixed subregional success. To elucidate these challenges, this study analyzed pre- and post-hurricane land surface phenology (LSP) for 44 moderate and strong hurricanes over 22 years using the Enhanced Vegetation Index (EVI). We statistically grouped storms based on their long-term climate attributes, then compared subregional impacts with wind speed and land cover. After accounting for wind speed, responses differed among the six subregions. The Southeast U.S. showed declines in EVI for the first winter and first year post storm, but this response was weak or absent elsewhere. The Central America region declined in the first winter but not in the subsequent growing season, while four other regions showed no increased impact with wind speed in either season. We then examined six category 4 hurricanes using a forest mask. In dry areas, drought-sensitive vegetation explained weak responses, whereas in the humid tropics, rapid refoliation or sprouting was common. These factors complicate optical remote sensing assessments. Rapid evaluations can mistake defoliation for more substantial damage, and delayed assessments can confuse EVI recovery with structural recovery. Results underscore the need for ecologically tailored monitoring approaches. Full article

The leishmaniases are a group of neglected tropical diseases caused by kinetoplastid protozoa of the genus Leishmania, transmitted by phlebotomine sandflies. In the absence of a human vaccine, current chemotherapeutic options remain suboptimal due to limited target selectivity, high cost, restricted availability in endemic low-resource regions, and escalating parasite resistance. This review highlights recent advances in rational drug design directed at the kinetoplast—a distinctive mitochondrial organelle critical for parasite viability. Different targets (e.g., kDNA, G-quadruplex, topoisomerases) and innovative approaches employing mitochondrion-targeted small molecules are discussed, as well as ligand-functionalized nanoparticle delivery systems that can transport bioactive agents to the parasite’s mitochondrial microenvironment. These strategies highlight the kinetoplast’s strong translational relevance as a selective antileishmanial target. By exploiting its unique molecular machinery, these strategies may offer improved parasite selectivity, although potential mitochondrial liabilities in host cells must be carefully evaluated. Full article

High-spatiotemporal-resolution precipitation data are essential for studies on regional hydrology, meteorology, and ecological conservation. Because the Qaidam Basin is a data-scarce region with a few ground stations and coarse-resolution remote sensing products, its utility in regional research is constrained. Therefore, high-resolution precipitation data are urgently needed. Here, longitude, latitude, the normalized difference vegetation index (NDVI), the digital elevation model (DEM), daytime and nighttime land surface temperature, slope, and aspect were selected as environmental variables. Four machine learning methods, Artificial Neural Network (ANN), Cubist, Random Forest (RF), and Support Vector Machine (SVM), were used to downscale Tropical Rainfall Measuring Mission (TRMM) precipitation data from 25 to 1 km in the Qaidam Basin and validated using ground observation stations. For annual downscaling, the accuracy ranked as Cubist > ANN > RF > SVM, and residual correction further improved performance. The Cubist model produced the best results, generating finer spatial patterns and reducing outliers in both annual and monthly products. Longitude, latitude, the DEM, and the NDVI were important contributors to the Cubist model. The resulting high-resolution dataset provides valuable support for hydrological and climate change research in the Qaidam Basin. Full article