Dissolved Oxygen Concentration Research Articles

Using Machine Learning Models for Short-Term Prediction of Dissolved Oxygen in a Microtidal Estuary

This paper presents a comprehensive approach to predicting short-term (for the upcoming 2 weeks) changes in estuarine dissolved oxygen concentrations via machine learning models that integrate historical water sampling, historical and upcoming 2-week meteorological data, and river discharge and discharge metrics. Dissolved oxygen is a critical indicator of ecosystem health, and this approach is implemented for the Neuse River Estuary, North Carolina, U.S.A., which has a long history of hypoxia-related habitat degradation. Through meticulous data preprocessing and feature selection, this research evaluates the predictions of dissolved oxygen concentrations by comparing a recurrent neural network with four other models, including a Multilayer Perceptron, Long Short-Term Memory, Gradient Boosting, and AutoKeras, through sensitivity experiments. The input predictors to our prediction models include water temperature, turbidity, chlorophyll-a, aggregated river discharge, and aggregated wind based on eight directions. By emphasizing the most impactful predictors, we streamlined the model-building processes and built a hindcast system from 2015 to 2019. We found that the recurrent neural network model was most effective in predicting the dissolved oxygen concentrations, with an R2 value of 0.99 at multiple stations. Different from our machine learning hindcast models that used observed upcoming meteorological and discharge data, an actual forecast system would use forecasted meteorological and discharge data. Therefore, an actual operational forecast may have lower accuracy than the hindcast, as determined by the accuracy of the predicted meteorological and discharge data. Nevertheless, our studies enhance our understanding of the factors influencing dissolved oxygen variability and set the basis for the implementation of a predictive tool for environmental monitoring and management. We also emphasized the importance of building station-specific models to improve the prediction results.

Metatranscriptomic Analysis Reveals Synergistic Activities of Comammox and Anammox Bacteria in Full-Scale Attached Growth Nitrogen Removal System.

Leveraging comammox Nitrospira and anammox bacteria for shortcut nitrogen removal can drastically lower the carbon footprint of wastewater treatment facilities by decreasing aeration energy, carbon, alkalinity, and tank volume requirements while also potentially reducing nitrous oxide emissions. However, their co-occurrence as dominant nitrifying bacteria is rarely reported in full-scale wastewater treatment. As a result, there is a poor understanding of how operational parameters, in particular, dissolved oxygen, impact their activity and synergistic behavior. Here, we report the impact of dissolved oxygen concentration (DO = 2, 4, 6 mg/L) on the microbial community's transcriptomic expression in a full-scale integrated fixed film activated sludge (IFAS) municipal wastewater treatment facility where nitrogen removal is predominantly performed by comammox Nitrospira and anammox bacterial populations. 16S rRNA transcript compositions revealed anammox bacteria and Nitrospira were significantly more active in IFAS biofilms compared to suspended sludge biomass. In IFAS biofilms, anammox bacteria significantly increased hzo expression at lower dissolved oxygen concentrations and this increase was highly correlated with the amoA expression levels of comammox bacteria. Interestingly, the genes involved in nitrite oxidation by comammox bacteria were significantly more upregulated, relative to the genes involved in ammonia oxidation with decreasing dissolved oxygen concentrations. Ultimately, our findings suggest that comammox Nitrospira supplies anammox bacteria with nitrite via ammonia oxidation and that this synergistic behavior is dependent on dissolved oxygen concentrations.

Robust inverse control strategy for dissolved oxygen concentration based on disturbance boundary estimation

Robust inverse control strategy for dissolved oxygen concentration based on disturbance boundary estimation

Increasing dissolved oxygen concentration of irrigation water is beneficial to nitrogen uptake of cotton under mulched drip irrigation

ContextEnhancing crop nitrogen absorption is crucial for improving nitrogen fertilizer utilization efficiency. Soil oxygen conditions play a vital role in influencing crop nutrient uptake. However, the impact of dissolved oxygen concentration in irrigation water on cotton’s nitrogen absorption remains unknow under mulched drip irrigation conditions. RESEARCH QUESTION: This study aimed to investigate whether the dissolved oxygen concentration in irrigation water affects cotton’s nitrogen uptake. METHODS: Urea was utilized as the nitrogen fertilizer, and 5 dissolved oxygen concentration of irrigation water were set in the experiment by adding sodium percarbonate (CK: 3.9 mg L−1, CO1: 9.2 mg L−1, CO2: 13.3 mg L−1, CO3: 17.3 mg L−1, CO4: 25.5 mg L−1). RESULTS: The results showed that increasing the dissolved oxygen concentration in irrigation water could increase the soil urease activity and bacterial operational taxonomic units (OTU), which may be beneficial to the urea decomposition and nitrogen cycling function. Towards the end of the cotton growth period, oxygenation irrigation led to an increase in nitrate nitrogen and ammonium nitrogen content in the soil. The average nitrate nitrogen content in the 0–60 cm soil layer of CO1, CO2, CO3 and CO4 increased by 12.4 %, 14.7 %, 15.9 % and 17.3 % respectively compared with CK. Similarly, the average ammonium nitrogen content of CO1, CO2, CO3 and CO4 in the 0–40 cm soil layer increased by 8.9 %, 11.7 %, 12.0 % and 11.6 % respectively compared with CK. Increasing the dissolved oxygen concentration in irrigation water resulted in elevated dry matter accumulation in cotton. The total dry matter of CO1, CO2, CO3 and CO4 increased by 9.5 %, 12.6 %, 14.6 % and 16.8 % respectively compared with CK. Additionally, the nitrogen concentration in each cotton organ also exhibited an increase. The total nitrogen accumulation of CO1, CO2, CO3 and CO4 increased by 26.1 %, 36.2 %, 48.2 % and 53.1 % respectively compared with CK. Furthermore, increasing the dissolved oxygen concentration in irrigation water also facilitated nitrogen migration to cotton bolls (boll shell + seed + fiber). The cotton boll nitrogen accumulation of CO1, CO2, CO3 and CO4 increased by 1.8 %, 3.4 %, 4.2 % and 4.2 % (absolute value) compared with CK (reached significant level). Finally, the lint yield and fiber quality parameters (micronaire, fiber elongation, fiber breaking strength) exhibited further improvement with the increase in dissolved oxygen concentration in irrigation water. CONCLUSIONS: Increasing the dissolved oxygen concentration in irrigation water promotes nitrogen absorption in cotton, facilitates nitrogen accumulation in cotton bolls, and enhances nitrogen fertilizer utilization efficiency. Moreover, it positively impacts cotton lint yield and fiber quality.

Impact of Temperature on the Growth Performance, Survival Rate, Osmoregulation, Dissolved Oxygen and Physiological Changes of Freshwater Tilapia (Oreochromis mossambicus)

For many aquatic species, any changes in water temperature affect their survival. This study was performed to investigate the effect of rising temperature on the growth parameters, protein content, dissolved oxygen content, moisture content osmoregulation, and physiological activity of freshwater Tilapia (Oreochromis mossambicus). The experiments were set in plastic fish tanks, the experimental tank placed in direct sunlight and the control tank in shade, and measuring temperature and pH daily, with proper aeration and feed was provided. The study found that increasing water temperature led to higher mortality rates and low survivability percentages in fish, with a higher growth rate in the experimental group with a pH range of 5.7 to 8.2. High dissolved oxygen levels were recorded during the experimental period, with a mean difference of 26.56 compared to the control group, possibly causing restless movement in fish. The study revealed that the alkalinity of water decreases with increasing temperature. The study found that increased salinity led to a significant increase in growth performance, indicating an increase in metabolic rate, and a decrease in alkaline nature. The difference between the mean protein value in the experimental and control groups is 0.896mg/ml. Thermal limitations may negatively impact O. mossambicus physiological responses, impacting aquaculture production due to predicted global climate change-induced water temperature changes.

Research on Enhancing Copper-Ammonia-Thiosulfate Eco-Friendly Gold Leaching by Magnetization of Lixiviant Solution and Their Kinetic Mechanism

In thiosulfate leaching of gold, the copper-ammonia complex serves as an oxidant and catalyst. This study examined the impact of magnetizing the copper-ammonia thiosulphate lixiviant solution on gold leaching from refractory oxidized ores. Magnetization reduced surface tension, improved wettability and infiltration, and enhanced the diffusion of leaching agents. It also increased dissolved oxygen content and boosted the catalytic efficiency of copper-ammonia complexes. These changes led to more efficient gold extraction, with column leaching showing a 4.74% improvement in extraction rates compared to non-magnetized methods and a 3.67% improvement over cyanide processes. These findings suggest that magnetized copper-ammonia thiosulphate lixiviant is a promising, environmentally friendly alternative to cyanide for refractory oxidized gold ores.

Research on Enhancing Copper-Ammonia-Thiosulfate Eco-Friendly Gold Leaching by Magnetization of Lixiviant Solution and Their Kinetic Mechanism

In thiosulfate leaching of gold, the copper-ammonia complex serves as an oxidant and catalyst. This study examined the impact of magnetizing the copper-ammonia thiosulphate lixiviant solution on gold leaching from refractory oxidized ores. Magnetization reduced surface tension, improved wettability and infiltration, and enhanced the diffusion of leaching agents. It also increased dissolved oxygen content and boosted the catalytic efficiency of copper-ammonia complexes. These changes led to more efficient gold extraction, with column leaching showing a 4.74% improvement in extraction rates compared to non-magnetized methods and a 3.67% improvement over cyanide processes. These findings suggest that magnetized copper-ammonia thiosulphate lixiviant is a promising, environmentally friendly alternative to cyanide for refractory oxidized gold ores.

Invertebrate trophic structure on marine ferromanganese and phosphorite hardgrounds

AbstractThe Southern California Borderland hosts a variety of geologic and oceanographic features that allow for diverse habitats to occur in a restricted region with a strong oxygen minimum zone (OMZ) and hard substrates. These include ferromanganese (FeMn) crusts and phosphorites targeted for deep‐seabed mining in other regions. Baseline studies regarding hardground macro‐ (> 0.3 mm) and megafaunal (> 2 cm) invertebrates are lacking, although they contribute to understanding nutrient cycling and resilience of deep‐sea communities to ocean deoxygenation, fishing, or mineral extraction. With the goal of understanding how substrate type, depth, and dissolved oxygen concentration influence invertebrate trophic structure, we surveyed δ13C and δ15N values of invertebrates on hard substrates on the Southern California Borderland margin along a depth gradient (120–2400 m) through the OMZ at inshore (< 100 km from shore) and offshore (100–250 km from shore) sites, using generalized additive models and community‐level metrics. Macrofaunal isotopic values correlate with substrate type, exhibiting higher trophic diversity on FeMn crusts and specialized communities on phosphorites. Megafaunal isotopic values correlate with proximity to shore; animals offshore seem to depend more on phytoplanktonic production than animals inshore. In general, δ15N increased with decreasing dissolved oxygen and increasing depth, possibly due to remineralization processes within the OMZ and with depth. We discuss how feeding modes and community composition might influence the observed patterns. This study elucidates the importance of the environmental context in shaping invertebrate trophic structure on continental margins and provides baseline knowledge that may be useful in regions where these minerals are targeted for extraction.

Application of a Gallic Acid–Based Oxygen Scavenger Label for the Preservation of L‐Ascorbic Acid in Orange Juice

ABSTRACTCitrus juices are rich sources of antioxidants, including vitamin C, but are prone to oxidation during storage. We investigated the application of gallic acid (GA), an environmentally friendly reducing agent, as active packaging to mitigate this issue. Orange juice was packaged in airtight glass containers both with and without GA‐based oxygen scavenger (GA‐OS) label and stored at 20°C and 4°C. During the storage, we monitored oxygen levels in the headspace and dissolved oxygen concentration in the orange juice, vitamin C content and browning. In the presence of GA‐OS, oxygen levels in the headspace were reduced by half in under 1 h at 21°C and within 2 h at 4°C. Dissolved oxygen concentration decreased 50% after 8 h at 21°C and after 1.2 days at 4°C. In the absence of GA‐OS, vitamin C degraded completely within 30 days at 21°C and 45 days at 4°C. In contrast, GA‐OS nearly fully preserved vitamin C for 105 days at both temperatures. Browning, quantified by delta E, escalated in GA‐OS‐absent samples to 16.79 ± 0.16 at 21°C to 12.19 ± 0.10 at 4°C, whereas GA‐OS samples exhibited no significant browning. Our results underscore GA‐OS's efficacy in preserving the quality of liquid foodstuffs, exemplified by orange juice, suggesting its broad range applicability as active packaging.

Oxygen corrosion of reboiler tube served in production of dilution steam from heat exchanger of petrochemical refinery

This paper reports the oxygen corrosion of heat exchanger tubes serviced in dilute steam generation system. The floating head heat exchanger employed in a petrochemical industry underwent remnant corrosion failures particularly at lower passes of tube bundle. Initially remote field eddy current inspection technique was employed for tube bundle conditional assessment and further, root cause of degradation of tube had been analyzed. Comprehensive experimental techniques including visual examination, tube chemistry analysis, external tube surface morphological analysis, elemental mapping, scanning electron microscopy, light microscopy and x-ray diffraction studies were employed. The tube surface at the degraded position with its cross sectional examination was rigorously evaluated as well. Moreover, actual steam parameters such as pH, conductivity and iron & chloride concentration have been monitored in the petrochemical facility. The detailed analysis concluded that dissolved oxygen in boiler feed water (BFW) was the root cause for corrosion failure. Several other foreign elements were detected and source of each element was discussed in the context of actual heat exchanger operating conditions. Simulated conditions of BFW service have electrochemically been evaluated in two different dissolved oxygen concentrations at 7.5 ppm and 12.7 ppm, respectively. Even small increase of dissolved oxygen in BFW could lead to promotion of oxygen reduction reaction. Theoretically SA179 tubes operated at pH of 9.75 could lead to formation of bicarbonate and it could protect the tube in absence of dissolved oxygen as evaluated by Molecular Dynamics simulation. However, according to obtained results, tube has been degraded due to presence of dissolved oxygen in BFW. Various contributing factors such as external paint/coat removal, absence of de-aerator system in BFW treatment and improper corrosion inhibitor programme were discussed. Several practical countermeasures have been suggested to mitigate oxygen corrosion failure in petrochemical refineries.

Physics-informed and data-driven modeling of an industrial wastewater treatment plant with actual validation

Data-driven modeling is essential in chemical engineering, especially in complex systems like wastewater treatment plants. Recurrent neural networks are effective for modeling parameters in wastewater treatment process such as dissolved oxygen concentration and chemical oxygen demand due to their nonlinear adaptability. However, traditional models face challenges such as the requirement for larger datasets and more frequent sampling, noisy measurements, and overfitting. To address this, physics-informed neural networks integrate physical knowledge for improved performance. In our study, we apply both approaches to a wastewater treatment plant, enhancing prediction performance. Our results demonstrate that physics-informed models perform successfully in offline and online validation, especially when standard methods fail. They maintain effectiveness without frequent updates. Yet, integrating physics-informed knowledge can introduce noise when standard methods suffice. This result points out the need for careful consideration of model choice in different scenarios.

Estimated dissolved oxygen in a river located in the south of Rio Grande do Sul

The present study aimed to estimate the dissolved oxygen concentrations in the Piratini River Watershed (in Brazilian Portuguese: BHRP), located in the northwest region of the State of Rio Grande do Sul. DO is a crucial parameter in assessing water quality, as it is essential for the maintenance of aquatic ecosystems. To estimate this, global linear regression models were applied, statistical tools capable of evaluating the effect that one or more variables exert on another. The analyzed data come from collections carried out by Environmental Protection Foundation (FEPAM) between the years 2005 and 2013, period that, due to the rigorous protocol followed and sampling periodicity, revealed a robust and consistent data set. For the selection of parameters, we sought those that had the smallest sampling failures in the historical data series, namely: Thermotolerant Coliforms, Total Phosphorus, Ammoniacal Nitrogen and Total Nitrogen, Turbidity, Total Solids and Hydrogenionic Potential. After applying the linear regressions, the best global models generated were able to explain 91.90% of the variations in dissolved oxygen in the BHRP, once all the analyzed parameters were incorporated, consolidating the applicability of the method. It is also conclude that, with the exception of Total Phosphorus, all training periods are within the limits tolerated by legislation.

A global four‐dimensional gridded dataset of ocean dissolved oxygen concentration retrieval from Argo profiles

AbstractLack of a long‐term time series of dataset with a high spatiotemporal resolution at a global scale poses a great challenge to clarify the characteristics of DOC in space and depth, and its trend in time. Thus, there is an urgent need for the development of a global DOC gridded dataset in space, time and depth. The Biogeochemical Argo (BGC‐Argo) provides an important data source for obtaining global DOC, but is limited by irregular spatial sampling locations. Besides, BGC‐Argo has shorter time series coverage and fewer profiles compared to Core‐Argo. Thus, this manuscript aims at reconstructing the DOC profiles based on the Core‐Argo and BGC‐Argo profiles and then developing a spatial, temporal and depth‐specific gridded DOC dataset, named G4D‐DOC. Validation results demonstrate that G4D‐DOC has a good overall consistency with WOA18 and GLODAPv2 datasets, particularly at depths of 10 dbar and 1000 dbar, where it surpasses consistency at other standard depths. In addition, compared to WOA18, G4D‐DOC has achieved a breakthrough in a temporal resolution from a climatological monthly to monthly, and compared to GLODAPv2, G4D‐DOC has achieved a breakthrough in space from irregular discrete locations to regular grids. Further, G4D‐DOC can be widely used to conduct the characteristics of DOC in space and depth and its trends at global and regional scales. The metadata of G4D‐DOC is as follows: four dimensions mean two dimensions in space (longitude and latitude), one in time and one in depth; data format is standard Hierarchical Data Format Version 4 (HDF4) with a spatial resolution of 1 degree and temporal resolutions of annual, seasonal and monthly intervals at 26 standard layers above 2000 dbar in depth; the spatial coverage is global and the time period is from 2005 to 2022.

Evaluation of influence of dissolved oxygen on corrosion behaviors of FeCrW model alloys in 360 °C water

The dissolved oxygen in a coolant can affect the oxidation properties of structural materials. A desirable oxide phase formation is achieved by manipulating the oxygen level in the coolant, which can mitigate structural material degradation in nuclear power plants. Therefore, the role of dissolved oxygen in the corrosion of structural materials in aqueous environments needs to be understood. In this study, a short-term corrosion test (up to 300 h) of Ferritic/Martensitic steels (F/M steels; FeCrW model alloys), namely, Fe12Cr1W, Fe9Cr1W, and Fe9Cr, in stagnant water at 360 °C was performed in a pressurized autoclave with the dissolved oxygen concentration controlled to 1 ppm or a very low level (<1 ppm). The results of the corrosion tests showed that an increase in the oxygen level in the water elevated the corrosion potential, allowing the phase transition of iron oxide from magnetite (Fe3O4) to hematite (Fe2O3), whereas there was no significant correlation between the concentrations of the alloying elements Cr and W and the oxide growth rate. In addition, hematite was found to mitigate further oxide growth. Finally, a mechanism for the growth of the initial oxide layer was proposed based on the experimental results.

Integrated mRNA-seq and miRNA-seq analysis reveals the miRNAs participating in the response and metabolic remodeling processes of Trachinotus blochii to different reoxygenation modes after hypoxia

Hypoxia has become a common phenomenon in aquatic environments. Golden pompano (Trachinotus blochii) are sensitive to fluctuations in dissolved oxygen concentration and are seriously affected by hypoxic stress. When facing hypoxia in aquaculture areas, it may be effective to alleviate the adverse effects of low oxygen by increasing dissolved oxygen through physical and chemical means. However, it is not known whether different reoxygenation rates have different physiological consequences. In this study, we utilized RNA-seq and miRNA-seq to investigate the effects of various hypoxia and reoxygenation treatments: normoxia, hypoxia, rapid reoxygenation (RRG; dissolved oxygen [DO] recovery within 10 mins), and gradual reoxygenation (GRG; DO recovery within 3 h). Under hypoxic conditions, the miR-130b-5p∼IDH3 pair was involved in the regulation of the TCA cycle and activation of HIF-1α expression in response to insufficient oxygen levels. Additionally, in RRG, under the regulation of the miR-132–5p∼PGAM, miR-8485∼LIPA, and miR-212–5p∼GAPDHS pairs, the energy supply came to increase relative to hypoxia. In GRG, the miR-130b-5p∼IDH3 pair regulated metabolism, which returned to the normal level. These findings provide new data for clarifying the metabolic regulatory pathways of golden pompano during hypoxia and reoxygenation processes.

A high-precision interpretable framework for marine dissolved oxygen concentration inversion

A high-precision interpretable framework for marine dissolved oxygen concentration inversion

Treatment of Wastewaters with Different Ammonium Concentrations in a Sequencing Batch Reactor by Nitritation and Denitritation Processes

In the treatment of industrial and municipal wastewaters, biological nitrification and denitrification processes have been widely applied methods. However, in recent years, experimental studies have been carried out on nitritation and denitritation processes in order to reduce the cost of wastewater treatment. In this study, the removal of synthetic wastewaters containing ammonium at various concentrations through nitritation and denitritation processes was investigated in a sequence batch reactor (SBR). The SBR was operated at a low dissolved oxygen concentration of 0.7±0.2 mg/L, while the initial pH level and temperature were kept constant at 7.5 and 25 ℃, respectively, which were below the defined optimal level for nitritation. For the initial concentrations of 100, 150, and 200 mg NH4-N/L, 91, 142, and 180 mg NOx-N were produced, respectively with the specific nitritation rates of 0.69, 0.95, and 0.81 mg NH4-N/mg MLVSS.hour. Considering the operating conditions of nitritation, approximately NO2-N/NOx-N ratio of 80% could be considered as successful with the combined effect of DO limitation and NH3 inhibition on the nitrite oxidizing bacteria. During the first days of nitritation and denitritation processes, change of nitrogen concentrations was negligible because the adaptation of organisms to the oxic and anoxic conditions. After completing nitritation stage, denitritation was carried out by using methanol as an electron donor for the initial concentrations of 91, 142, and 180 mg/L of NOx-N in 96, 120 and 264 hours of reaction times, respectively.

Forecasting fish mortality from water and air quality data using deep learning models.

High rate of aquatic mortality incidents recorded in Taiwan and worldwide is creating an urgent demand for more accurate fish mortality prediction. Present study innovatively integrated air and water quality data to measure water quality degradation, and utilized deep learning methods to predict accidental fish mortality from the data. Keras library was used to build multilayer perceptron and long short-term memory models for training purposes, and the models' accuracies in fish mortality prediction were compared with that of the naïve Bayesian classifier. Environmental data from the 5 days before a fish mortality event proved to be the most important data for effective model training. Multilayer perceptron model reached an accuracy of 93.4%, with a loss function of 0.01, when meteorological and water quality data were jointly considered. It was found that meteorological conditions were not the sole contributors to fish mortality. Predicted fish mortality rate of 4.7% closely corresponded to the true number of fish mortality events during the study period, that is, four. A significant surge in fish mortality, from 20% to 50%, was noted when the river pollution index increased from 5.36 to 6.5. Moreover, the probability of fish mortality increased when the concentration of dissolved oxygen dropped below 2mg/L. To mitigate fish mortality, ammonia nitrogen concentrations should be capped at 5mg/L. Dissolved oxygen concentration was found to be the paramount factor influencing fish mortality, followed by the river pollution index and meteorological data. Results of the present study are expected to aid progress toward achieving the Sustainable Development Goals and to increase the profitability of water resources.

Hypothalamic transcriptome response to simulated diel earthen pond hypoxia cycles in channel catfish (Ictalurus punctatus).

Commercial culture of channel catfish (Ictalurus punctatus) occurs in earthen ponds that are characterized by diel swings in dissolved oxygen concentration that can fall to severe levels of hypoxia, which can suppress appetite and lead to suboptimal growth. Given the significance of the hypothalamus in regulating these processes in other fishes, an investigation into the hypothalamus transcriptome was conducted to identify specific genes and expression patterns responding to hypoxia. Channel catfish in normoxic water were compared with catfish subjected to 12 h of hypoxia (20% oxygen saturation; 1.8 mg O2/L; 27°C) followed by 12 h of recovery in normoxia to mimic 24 h in a catfish aquaculture pond. Fish were sampled at 0-, 6-, 12-, 18-, and 24-h timepoints, with the 6- and 12-h samplings occurring during hypoxia. A total of 190 genes were differentially expressed during the experiment, with most occurring during hypoxia and returning to baseline values within 6 h of normoxia. Differentially expressed genes were sorted by function into Gene Ontology biological processes and revealed that most were categorized as "response to hypoxia," "sprouting angiogenesis," and "cellular response to xenobiotic stimulus." The patterns of gene expression reported here suggest that transcriptome responses to hypoxia are broad and quickly reversibly with the onset of normoxia. Although no genes commonly reported to modulate appetite were found to be differentially expressed in this experiment, several candidates were identified for future studies investigating the interplay between hypoxia and appetite in channel catfish, including adm, igfbp1a, igfbp7, and stc2b.NEW & NOTEWORTHY Channel catfish are an economically important species that experience diel episodic periods of hypoxia that can reduce appetite. This is the first study to investigate their transcriptome from the hypothalamus in a simulated 24-h span in a commercial catfish pond, with 12 h of hypoxia and 12 h of normoxia. The research revealed functional groups of genes relating to hypoxia, angiogenesis, and glycolysis as well as individual target genes possibly involved in appetite regulation.

Salinity decreases methane concentrations in Chinese lakes

Lakes are important sources of methane (CH4), and understanding the influence of environmental factors on CH4 concentration in lake water is crucial for accurately assessing CH4 emission from lakes. In this study, we investigated CH4 concentration in two connected Tibetan Plateau lakes, Lake Keluke (an open freshwater lake) and Lake Tuosu (a closed saline lake), through in-situ continuous measurements taken in different months from 2021 to 2023. The results show substantial spatial and seasonal variations in CH4 concentrations in the two lakes, while the CH4 concentrations in Lake Keluke are consistently higher than those in Lake Tuosu for each month. Despite sharing similar environmental conditions due to connected (e.g. pH, water temperature, dissolved oxygen content, and total organic carbon content), the critical difference between the two lakes is their salinity. This implies that salinity is the critical factor contributing to the decrease in CH4 concentrations in Lake Tuosu, possibly due to the changes in microbial species between freshwater and brackish/saline lakes. Additionally, to further validate the effect of salinity on CH4 concentrations in lake water, we compared the CH4 concentrations of 33 lakes (including 5 saline lakes and 28 freshwater lakes) from the Tibetan Plateau, Chinese Loess Plateau, and Yangtze Plain, and found that saline lakes consistently exhibit lower CH4 concentrations (avg. 0.08 μmol/L), while freshwater lakes generally display higher CH4 concentrations (avg. 1.25 μmol/L) with considerable fluctuations. Consequently, freshwater and saline lakes exhibit distinct CH4 emissions, which could be used for more accurate estimation of global CH4 emission from lakes.