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The impact of volcanic activity on microorganisms has always been a hot topic of discussion during geological history. Further studies are needed on the effects of volcanic activity on microbial growth in shale and the differences in nutrients provided by volcanic ash and other weathered rocks. This study’s results indicated that TOC contents at the bottom of the shale layer are 1.93–4.44% and 3.0% on average. The TOC contents at the top of the layer are 3.38–5.13% and 4.0% on average. It indicated that TOC contents at the bottom of the shale layer are smaller than the TOC contents at the top of the layer, suggesting that volcanic activity posed a long-term effect on biological growth. Seven different leachate concentrations were set in this experiment as follows: 1/10, 1/100, 1/500, 1/1000, 1/1500, 1/2000, and 1/2500. The results showed that the growth status of Pseudourostyla crassipes was affected by the addition of leachates with different concentrations compared to the control group. Additionally, the synthesis of chlorophyll a by Anabaena pseudoichthyoides was the most efficient with the 1/10 volcanic ash leachate. Through the analysis of major and trace elements in the solution before labeland after cultivation, the main elemental content of Ca²⁺, Mg²⁺, Na⁺, and K⁺ decreased by 3.8~87.24%, 75.96~92.70%, 86.56~95.67%, and 5.42~20.52% in the solution after microbial growth respectively. The trace elements B, Ba, Zn, and Fe decreased by 27.54~94.39%, 20~82.03%, 70.45~98.29%, and 99%. It was found that the B, Ba, Fe, and Zn elements decreased significantly. The nutrients from volcanic ash are the main factor promoting microbial growth. It can be indicated that the volcanic ash soaking solution has a higher content of nutrients when compared to the solubility of nutrients in volcanic ash compared to that of granite. A higher content of nutrients promotes microbial growth. The calculation results indicate that a volcanic eruption with a quantity of several 10¹⁰ m³ has a significant impact on microorganisms, lasting from tens of thousands to hundreds of thousands of years. Full article

Marine diatoms are essential members of both phytoplankton and phytobenthic communities, able to colonize submerged artificial and natural surfaces, contributing to benthic microbial biomass. Diatoms have developed different adaptative mechanisms to cope with various environmental stresses, including high concentrations of heavy metals. The aim of this study was to investigate the arsenic resistance of diatoms, isolated from microbial mats collected from an arsenic-rich brackish pond (Lake Mergolo della Tonnara, Italy), by evaluating (i) their ability to form biofilms in the presence of arsenite (As^III) or arsenate (As^V), and (ii) the variations in the photosynthetic pigments’ contents (i.e., chlorophyll a and c) in their biofilms. The mats were dominated by members of the genus Amphora, and isolates were affiliated with species of A. capitellata, A. coffeaeformis, and A. montana. The strains grew better in the presence of As^V than As^III, which is generally less toxic. After seven days of incubation, each strain exhibited a different ability to form biofilms on glass surfaces in the presence of arsenic (25 ppm), with A. montana strain 27 being the most effective (86%) in the presence of As^III, and A. coffeaeformis strain 26 (74%) with As^V. Photosynthetic pigment levels (chlorophyll a and c) differed in each biofilm, being poorly reduced by As^III in strain 27, and by As^V in strain 26, indicating a species-specific response to arsenic stress. Our results indicated that Amphora species thriving in this environment can form biofilms as an As-resistance mechanism, maintain their levels of photosynthetic pigments, and support the functioning of the pond ecosystem, with A. montana being favored in the presence of As^III, whereas A. coffeaeformis 26 in the presence of As^V. As producers of biofilms, these strains could be useful to develop new strategies to remediate arsenic pollution. Full article

Atmospheric correction, the removal of the atmospheric signal from a satellite image, still poses a challenge over optically complex coastal water. Here, we present the first atmospheric correction validation study performed in optically complex Norwegian fjords. We compare in situ reflectance measurements and chlorophyll-a concentrations from Western Norwegian fjords with atmospherically corrected Sentinel-3 Ocean and Land Colour Instrument observations and chlorophyll-a retrievals. Measurements were taken in Hardangerfjord, Bjørnafjord and Møkstrafjord during a bright green coccolithophore bloom in May 2022, and during a period of no apparent discoloration in April 2023. Coccolithophore blooms generally peak in the blue region (490 nm), but spectra measured in this bloom peaked in the green region (559 nm), possibly due to absorption by colored dissolved organic matter (a_CDOM(440) = 0.18 ± 0.01 m⁻¹) or due to high cell counts (up to 15 million cells/L). We tested a wide range of atmospheric correction algorithms, including ACOLITE, BAC, C2RCC, iCOR, L2gen, POLYMER and the SNAP Rayleigh correction. Surprisingly, atmospheric correction algorithms generally performed better during the bloom (average MAE = 1.25) rather than in the less scattering water in the following year (average MAE = 4.67), possibly because the high water-leaving radiances due to the high backscattering by coccolithophores outweighed the adjacency effect. However, atmospheric correction algorithms consistently underestimated water-leaving reflectance in the bloom. In non-bloom matchups, most atmospheric correction algorithms overestimated the water-leaving reflectance. POLYMER appears unsuitable for use over coccolithophore blooms but performed well in non-bloom matchups. Neither BAC, used in the official Level-2 OLCI products, nor C2RCC performed well in the bloom. Nine chlorophyll-a retrieval algorithms, including two algorithms based on neural nets, four based on red and near-infrared bands and three maximum band-ratio algorithms, were also tested. Most chlorophyll-a retrieval algorithms did not perform well in either year, although several did perform within the 70% accuracy threshold for case-2 waters. A red-edge algorithm performed best in the coccolithophore blooms, while a maximum band-ratio algorithm performed best in the following year. Full article

Cyanobacterial blooms in lakes have increased in frequency and intensity over the past two decades, negatively affecting ecological and biogeochemical processes. This study focuses on the phytoplankton composition of Lake Maggiore, with a special emphasis on cyanobacteria detection through pigment composition. While microscopy is the standard method for phytoplankton identification, pigment-based methods provide broader spatiotemporal coverage. Between May and September 2023, five measurement campaigns were conducted in Lake Maggiore, collecting bio-geochemical and bio-optical data at 27 stations. The total Chlorophyll-a (TChl a) was measured, with concentrations ranging from 1.13 to 6.9 mg/m³. Phytoplankton pigment composition was analyzed using High-Performance Liquid Chromatography (HPLC) and the CHEMTAX approach was applied for phytoplankton classification. The results were cross-validated using Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and microscopic counts. Cyanobacteria were identified based on unique pigment markers, such as carotenoids. The HPLC-derived pigment classification results aligned well with both PCA and HCA and microscopic counts verified the accuracy of the pigment-based chemotaxonomy. The study demonstrates that pigment-based classification methods, when combined with statistical analyses, offer a reliable alternative for identifying cyanobacteria and other phytoplankton groups, with potential applications in support of remote sensing algorithm development. Full article

The Albufera of Valencia, a Mediterranean coastal lagoon, has experienced a shift to hypertrophic conditions over the past 40 years due to agricultural and urban-industrial pollution. From August 2023 to early 2024, the water of the lagoon turned reddish-brown. This change has been observed in the past, but never with this intensity or duration, which typically occurs during periods of drought. In this study, carotenoid concentrations were analyzed in relation to precipitation and temperature using field and remote sensing data from February 2016 to December 2023. In November 2023, samples showed unusually high concentrations of carotenoids. The study confirmed the effectiveness of a new algorithm for estimating carotenoids using Sentinel-2 imagery to complement chlorophyll-a data. Results showed that temperature and precipitation significantly influenced carotenoid/chlorophyll-a ratio, highlighting a climatic control of phytoplankton community structure. These results highlight the importance of long-term monitoring and conservation efforts to address climate change and human impacts. This research is a first step in using optical properties of lakes as an indicator of phytoplankton dynamics under environmental stress and warns of the potential for increased occurrence or persistence of such phenomena with future climate trends. Full article

The aim of this study was to examine lettuce using different concentrations of the biostimulator N-methyl-N-methoxyamide-7-carboxybenzo(1.2.3)thiadiazole (BTHWA), a new benzothiadiazole derivative. Different concentrations of BTHWA during watering and spraying were applied to lettuce. Chlorophyll fluorescence, gas exchange, thermal images, and plant parameter data were used to study physiological process and the growth of lettuce. Chlorophyll fluorescence data showed a strong effect after the first BTHWA application to lettuce. After three applications, the plants were harvested and data were recorded. Similarly, in the second experiment, gas exchange and thermal images were recorded after the first treatment of BTHWA. Our findings showed improved chlorophyll efficiency after the first BTHWA application, and no adverse effects were recorded on the overall photochemistry at any concentration. Regarding growth parameters, spraying BTHWA reduced the fresh weight but decreased the damage index. A lower watering concentration (0.066 mg/L) applied three times did not cause any damage to plants and fresh weight, even after repeated applications. Infrared thermal images showed BTHWA application also significantly affected plant temperature. Gas exchange data revealed that sprayed plants exhibited higher transpiration rates, stomatal conductance, and photosynthetic rates when compared to watered and control plants. This study suggests that application of a low dose of BTHWA is safe to use in agriculture practices in lettuce without compromising its growth and yield. Full article

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, a_cdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating a_cdom at the wavelength 412 nm (a_cdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, R_rs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite R_rs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate a_cdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m⁻¹ from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived a_cdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of a_cdom (412) is provided for a coastal transect in the south of Vietnam. Full article

Pepper (Capsicum annuum) is a globally important vegetable, and Verticillium wilt is an important disease affecting peppers and is caused by Verticillium dahliae, which can severely reduce yields. However, the molecular mechanisms underlying the responses of pepper to infection by V. dahliae are largely unknown. We performed physiological and transcriptome analysis using resistant and susceptible pepper cultivars inoculated with V. dahliae. Compared to the susceptible cultivar MS66, the resistant cultivar MS72 retained higher chlorophyll content and lower malondialdehyde content after inoculation. At 3 days after inoculation (DAI), compared with MS66, 534 differentially expressed genes (DEGs) were identified in MS72. At 5 DAI, 2392 DEGs were identified in MS72 compared with MS66. The DEGs in MS72 were mainly enriched in the cell wall and photosynthesis-related Gene Ontology terms, as well as in pathways such as cutin, suberin, wax biosynthesis, phenylpropanoid biosynthesis, and photosynthesis. Using weighted gene co-expression network analysis, 36 hub genes involved in the resistance response were identified, including the transcription factor bHLH93 (Capana04g000815), defense-like protein 1 (MSTRG.5904), and miraculin-like (Capana10g002167). Our findings contribute to a more comprehensive understanding of the response mechanism of pepper to V. dahliae inoculation, providing new avenues for improving pepper resistance through breeding programs. Full article

Implementing nanofertilizers in cultivation to enhance food security is important and gaining great significance, as they have good properties to improve plant production, phytochemicals, and nutrient efficiency and thereby meet the demands of the increasing world population for food. This work demonstrated the impact of calcium carbonate nanoparticles (Ca-NPs) and Ca bulk at three concentrations (0, 100, and 200 mg L⁻¹) on growth, productivity, photosynthetic pigments, phytochemical content, antioxidant activity enzymes, minerals, toxicity, and genomic DNA of lettuce plants. In this regard, Ca-NPs at a concentration of 200 mg L⁻¹ reinforced the vegetative growth characteristics of lettuce plants, increasing head length by 15.7 and 19.2%, head diameter by 20.3 and 19.9%, head fresh weight by 54.4 and 52.9%, and production per hectare by 54.7 and 52.8% as compared to the control during the two growing seasons. Furthermore, the percentages of total chlorophyll (62.6 and 59.5%), carotenoids (48.4 and 56.5%), total phenolics (63.6 and 65.7%), total indoles (39.4 and 36.4%), vitamin C (39.7 and 39.6%), antioxidant activity (57.8 and 53.7%), nitrogen (70.5 and 67.5%), phosphorus (120 and 110.5%), potassium (33.0 and 33.2%), and calcium (67.14 and 63.2%) were also increased compared with the control during two consecutive growing seasons. Additionally, Ca-NPs and Ca bulk had an impact on the plants’ genomic DNA compared to the control. In addition, lettuce plants treated with Ca-NPs were proven to be nontoxic and safe for humans by using the Microtox 500 analyzer. Full article

Seagrass meadows are among the most threatened ecosystems on Earth, with losses attributed to increasing coastal populations, degraded water quality and climate change. As coastal communities work to improve water quality, there is increased concern regarding the use of herbicides within the watersheds of these sensitive ecosystems. Glyphosate is the most widely used herbicide on Earth because it is non-selective and lethal to most plants. Also, the targeted amino acid synthesis pathway of glyphosate is not carried out by vertebrates, and it is generally considered one of the safer but effective herbicides on the market. At least partially due to its cost-effectiveness compared to other techniques, including mechanical harvesting, glyphosate use in the aquatic environment has increased in coastal areas to manage aquatic weeds, maintain navigable waterways and mitigate upland flooding. This has prompted concerns regarding potential ecosystem-level impacts. To test the acute toxicity of glyphosate to seagrasses, mesocosm experiments exposed Ruppia maritima and Halodule wrightii to 1 ppm, 100 ppm and 1000 ppm of glyphosate (as glyphosate acid). No significant decrease in leaf chlorophyll a (Chl a) was identified for either species at 1 ppm versus a control; however, significant decreases were observed at higher concentrations. In all except 1000 ppm mesocosms, water column Chl a increased, with a 7-fold increase at 100 ppm. These data demonstrate that at very high glyphosate concentrations, both acute toxicity and light limitation from enhanced algal biomass may have adverse impacts on seagrasses. Despite these observations, no significant adverse impacts attributed to acute toxicity were observed at 1 ppm, which is >1000 times higher than concentrations measured in the Indian River Lagoon system. Overall, herbicide use and associated decaying biomass contribute nutrients to these systems, in contrast to the removal of nutrients when mechanical harvesting is used. Based on our data and calculations, when used at recommended application rates, contributions to eutrophication, degraded water quality and harmful algal blooms were more likely to impact seagrasses than acute toxicity of glyphosate. Full article

Ginkgo (Ginkgo biloba L.) is a widely recognized medicinal plant, often grown as an ornamental species in parks around the world. Its leaves change color from green in spring to yellow in autumn. In this study, we collected ginkgo leaves at seven developmental stages from May to November and measured chlorophylls, carotenoids, flavonoids, and antioxidant activity. The total polyphenol content showed a significant increase from May to November, rising from 15.15 ± 0.14 mg GAE g⁻¹ dw to 45.18 ± 0.42 mg GAE g⁻¹ dw. The total flavonoid content reached its peak in August at 5.87 ± 0.18 mg GAE g⁻¹ dw. In contrast, the highest concentrations of total polyphenolic acids (4.13 ± 0.16 mg CAE g⁻¹ dw) and antioxidant activity (306.95 ± 3.47 µmol TE g⁻¹) were recorded in May. We specifically focused on a less-studied group of dimeric flavonoids or biflavonoids—3′,8″-biflavones. We identified five 3′,8″-biflavones (amentoflavone, bilobetin, ginkgetin, isoginkgetin, and sciadopitysin) throughout all developmental stages. Sciadopitysin was the most abundant biflavonoid, with its concentration rising from 614.71 ± 5.49 µg g⁻¹ dw in May to 2642.82 ± 47.47 µg g⁻¹ dw in November. Alongside sciadopitysin, the content of other biflavonoids (excluding amentoflavone) generally increased over the same period. This trend is further highlighted by the total biflavonoid content, which grew from 1448.97 ± 6.63 µg g⁻¹ dw in May to 6071.67 ± 97.15 µg g⁻¹ dw in November. We observed a negative correlation between biflavonoid and chlorophyll content, which may indicate their involvement in leaf senescence. However, this hypothesis warrants further investigation. Full article

The escalating release of multi-walled carbon nanotubes (MWCNTs) into the environment has raised concerns due to their potential ecotoxicological impacts. However, their combined phytotoxicity with heavy metals such as copper (Cu) is still unclear. This study investigated the individual and combined toxic effects of MWCNTs (MWCNT, MWCNT-OH, and MWCNT-COOH) and Cu²⁺ on ryegrass (Lolium multiflorum), uniquely considering different addition orders. The results show that Cu severely inhibited the growth of ryegrass while MWCNTs exhibited a hormesis effect on ryegrass. When MWCNT and Cu were combined, the malondialdehyde (MDA) content in ryegrass showed a 32.39% increase at 20 mg/L MWCNT exposure, suggesting reduced oxidative stress. However, at the higher concentration of 1000 mg/L, it led to a significant 75.22% reduction in ryegrass biomass. MWCNT-COOH had the most pronounced effect, reducing the total chlorophyll content by 39.76% compared to unmodified MWCNT and by 10.67% compared to MWCNT-OH (500 mg/L). Additionally, pre-induced MWCNTs might alleviate the Cu in the plant by 23.08–35.38% through adsorption in the nutrient solution. Small molecule organic acids and amino acids primarily mediated the response to environmental stress in ryegrass. This research provides crucial insights into understanding the complex interactions of MWCNT and Cu²⁺ and their combined effects on plant ecosystems. Full article

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources. Full article

Background: the widespread use of antibiotics in human and veterinary medicine has contributed to the global challenge of antimicrobial resistance, posing significant environmental and public health risks. Objectives: this study aimed to examine the microbiome and resistome dynamics across a salinity gradient, analyzing water and sediment samples from the Baltic Sea coast and the Curonian Lagoon between 2017 and 2023. Methods: the composition of the water and sediment bacterial community was determined by Full-Length Amplicon Metagenomics Sequencing, while ARG detection and quantification were performed using the SmartChipTM Real-Time PCR system. Results: the observed differences in bacterial community composition between the Baltic Sea coast and the Curonian Lagoon were driven by variations in salinity and chlorophyll a (chl a) concentration. The genera associated with infectious potential were observed in higher abundances in sediment than in water samples. Over 300 genes encoding antibiotic resistance (ARGs), such as aminoglycosides, beta-lactams, and multidrug resistance genes, were identified. Of particular interest were those ARGs that have previously been detected in pathogens and those currently classified as a potential future threat. Furthermore, our findings reveal a higher abundance and a distinct profile of ARGs in sediment samples from the lagoon compared to water. Conclusions: these results suggest that transitional waters such as lagoons may serve as reservoirs for ARGs, and might be influenced by anthropogenic pressures and natural processes such as salinity fluctuation and nutrient cycling. Full article

To analyze the impact of the marine environment on the relative abundance of Illex argentinus (high and low categories) in the southwest Atlantic, this study collected logbook data from Chinese pelagic trawlers from December 2014 to June 2024, including vessel position data and oceanographic variables such as sea surface temperature, 50 m and 100 m water temperature, sea surface salinity, sea surface height, chlorophyll-a concentration, and mixed layer depth. Vessel positions were used to enhance the logbook data quality, allowing an analysis of the annual trends in the resource center of this squid at a spatial resolution of 0.1° × 0.1° and a temporal resolution of ten days. The findings showed that the resource center is primarily located around 42° S in the north and between 45° S and 47° S in the south, with a trend of northward movement during the study period. Additionally, we constructed two ensemble learning models based on decision trees—AdaBoost and PSO-RF—aiming to identify the most critical environmental factors that affect its resource abundance; we found that the optimal model was the PSO-RF model with max_depth of 5 and n_estimators of 46. The importance analysis revealed that sea surface temperature, mixed layer depth, sea surface height, sea surface salinity, and 50 m water temperature are critical environmental factors affecting this species’ resources. Given that deep learning models generally have shorter running times and higher accuracy than other models, we developed a CNN-Attention model based on the five most important input factors. This model achieved an accuracy of 73.6% in forecasting this squid for 2024, predicting that the population would first appear near the Argentine exclusive economic zone around mid-December 2023 and gradually move east and south thereafter. The predictions of the model, validated through log data, maintained over 70% accuracy during most periods at a time scale of ten days. The successful construction of the resource abundance forecasting model and its accuracy improvements can help enterprises save fuel and time costs associated with blind searches for target species. Moreover, this research contributes to improving resource utilization efficiency and reducing fishing duration, thereby aiding in lowering carbon emissions from pelagic trawling activities, offering valuable insights for the sustainable development of this species’ resources. Full article