Intraspecific priority effects in response to egg hatching delay in a pond-breeding salamander.

As reproduction phenologies shift with climate change, populations can experience intraspecific priority effects, wherein early hatching cohorts experience an advantage over late-hatching cohorts, resulting in altered demography. Our study objective was to identify how variation in egg hatching phenology alters intraspecific interactions in small-mouthed salamanders, Ambystoma texanum. We addressed two research questions: (Q1) How are demographic responses altered by variation in the temporal duration of hatching between cohorts, and (Q2) How does the seasonality of hatching delays affect demographic responses? We manipulated hatching phenologies of A. texanum eggs and reared larvae in outdoor mesocosms to metamorphosis. For Q1, hatching delay exhibited non-linear relationships with survival and body size, with the greatest asynchrony in cohort additions resulting in the highest mortality and largest body sizes. For Q2, hatching delay effects were stronger (i.e., survival was lower and body sizes larger) when they occurred later in the season, potentially due to temperature differences that larvae experienced. Overall, our results demonstrate that changes in intraspecific interactions due to phenological shifts can be context-dependent, depending on the strength (i.e., temporal duration) and seasonality of such processes. Identifying context-dependencies of phenological shifts will be critical for predicting changes in organismal demographics with climatic shifts.

Improving denitrification estimation by joint inclusion of suspended particles and chlorophyll a in aquaculture ponds.

The denitrification process in aquaculture systems plays a crucial role in nitrogen (N) cycle and N budget estimation. Reliable models are needed to rapidly quantify denitrification rates and assess nitrogen losses. This study conducted a comparative analysis of denitrification rates in fish, crabs, and natural ponds in the Taihu region from March to November 2021, covering a complete aquaculture cycle. The results revealed that aquaculture ponds exhibited higher denitrification rates compared to natural ponds. Key variables influencing denitrification rates were Nitrate nitrogen (NO3--N), Suspended particles (SPS), and chlorophyll a (Chla). There was a significant positive correlation between SPS concentration and denitrification rates. However, we observed that the denitrification rate initially rose with increasing Chla concentration, followed by a subsequent decline. To develop parsimonious models for denitrification rates in aquaculture ponds, we constructed five different statistical models to predict denitrification rates, among which the improved quadratic polynomial regression model (SQPR) that incorporated the three key parameters accounted for 80.7% of the variability in denitrification rates. Additionally, a remote sensing model (RSM) utilizing SPS and Chla explained 43.8% of the variability. The RSM model is particularly valuable for rapid estimation in large regions where remote sensing data are the only available source. This study enhances the understanding of denitrification processes in aquaculture systems, introduces a new model for estimating denitrification in aquaculture ponds, and offers valuable insights for environmental management.

Acclimatization of a sequencing batch vertical oxidation pond with simulated agricultural wastewater using duckweed as vegetation: analysis of efficiency, Biomass, and Soil properties.

Vertical oxidation pond operated in sequencing batch mode (HRT: 1.25 day) with duckweed as the vegetation was used to acclimatize with simulated agricultural wastewater. The maximum removal rate of urea [371 g/(m3.d)] and COD [222.4 g/(m3.d)] were observed at moderate concentrations of urea (500 mg/L), N-P-K (60 mg/L), and pesticide (20 mg/L). Inhibition and toxicity posed by higher concentrations, decreased the removals of urea (83% to 61%), COD (81% to 51%), and TDS (76% to 50%) at the end of the acclimatization. Steady removal (> 99%) of PO43--P was observed during acclimatization. Effluent pH increased due to the generation of NH4+-N (maximum 370 ± 5 mg/L) from the assimilation of urea. Oxidation of ammonia led to the maximum generation of NO2--N and NO3--N of 10 mg/L and 9 mg/L, respectively. Particles less than 300 µm increased, and both specific gravity (from 2.62 to 2.42) and maximum dry density (from 1.73 to 1.30 g/cm3) of the base soil decreased with an increase in urea, N-P-K, and pesticide. Reactor biomass increased (1.42 to 1.90 g/L) up to initial concentrations of urea (500 mg/L), N-P-K (60 mg/L), and pesticide (20 mg/L), then decreased (1.68 g/L) with an increase in concentration.

Diminished storage capacity of ponds caused by sedimentation weakens their nitrogen removal efficiency.

Though their small size, ponds play a disproportionately crucial role in eliminating nitrogen (N) transporting to downstream freshwaters. As significant water infrastructures, ponds are non-sustainable due to loss of storage capacity resulting from sedimentation. However, the effects of pond sedimentation on N removal is widely neglected in landscape N processing. The NUFER (Nutrient flows in Food chains, Environment and Resources use) model was employed to estimate N runoff from 1960 to 2018. We reconstructed the dynamic of number and storing capacity of about 14 million ponds due to construction and sedimentation from 1960 to 2018, projecting these trends into the year 2060. Our approach incorporated first-order kinetic reactions, including water residence time (HRT), to estimate N removal of ponds, utilizing data 6 monitoring ponds and 81 ponds from literature studies. Our analysis reveals a fourteen-fold increase in N runoff over the past six decades, rising from 0.8 Mt N in 1960 to 11.4 Mt N in 2018. Due to the initial rapid expansion of ponds, N removal by ponds increased from 6.4 % in 1960 to 13.6 % in 1990. Sedimentation is prevalent in ponds, particularly in small ponds with a sedimentation accumulation rate of 2.96 cm yr-1. Pond sedimentation, which reduces HRT, resulted in a decrease in pond N removal percentage to 11.2 % in 2018 and a projected 7.4 % by the year 2060, assuming similar sediment accumulation rates persist in the future. Overall, our findings underscore the non-negligible role of ponds as landscape nodes in N cycling. Urgent mitigation measures are needed to extend the lifetime of existing ponds and sustain their critical role in water quality management.

Control of cyanobacterial growth with potassium; implications for bloom control in nuclear storage ponds.

Microbial blooms have been reported in the First Generation Magnox Storage Pond at the Sellafield Nuclear Facility. The pond is kept alkaline with NaOH to minimise fuel rod corrosion, however alkali-tolerant microbial blooms dominated by the cyanobacterium Pseudanabaena catenata are able to thrive in this hostile environment. This study assessed the impact of alternative alkali-dosing regimens (KOH versus NaOH treatment) on biomass accumulation, using a P. catenata dominated mixed culture, which is representative of the pond environment. Optical density was reduced by 40-67 % with KOH treatment over the 3-month chemostat experiment. Microbial community analysis and proteomics demonstrated that the KOH-dependent inhibition of cell growth was mostly specific to P. catenata. The addition of KOH to nuclear storage ponds may therefore help control growth of this pioneer photosynthetic organism due to its sensitivity to potassium, while maintaining the high pH needed to inhibit the corrosion of stored nuclear fuel.

Viromic and Metagenomic Analyses of Commercial Spirulina Fermentations Reveal Remarkable Microbial Diversity.

Commercially produced cyanobacteria preparations sold under the name spirulina are widely consumed, due to their traditional use as a nutrient-rich foodstuff and subsequent marketing as a superfood. Despite their popularity, the microbial composition of ponds used to cultivate these bacteria is understudied. A total of 19 pond samples were obtained from small-scale spirulina farms and subjected to metagenome and/or virome sequencing, and the results were analysed. A remarkable level of prokaryotic and viral diversity was found to be present in the ponds, with Limnospira sp. and Arthrospira sp. sometimes being notably scarce. A detailed breakdown of prokaryotic and viral components of 15 samples is presented. Twenty putative Limnospira sp.-infecting bacteriophage contigs were identified, though no correlation between the performance of these cultures and the presence of phages was found. The high diversity of these samples prevented the identification of clear trends in sample performance over time, between ponds or when comparing successful and failed fermentations.

Food web collapse and regime shift following goldfish introduction in permanent ponds.

In a global context of invasive alien species (IAS), native predators are often eradicated by functionally different IAS, which may induce complex cascading consequences on ecosystem functioning because of the key role predators play in structuring communities and stabilizing food webs. In permanent ponds, the most abundant freshwater systems on Earth, global human-mediated introductions of alien omnivores such as the pet trade goldfish are driving broad-scale patterns of native predators' exclusion, but cascading consequences on food web structure and functioning are critically understudied. We compared food webs of naturally fishless ponds versus ponds where dominant native predators (newts) had been extirpated by invasive goldfish within the last decade. Integrating community-wide isotopic, taxonomic and functional traits approaches, our study reveals that pond food webs collapsed in both vertical and horizontal dimensions following goldfish introduction and the associated exclusion of native predators. Consumer taxonomic diversity was drastically reduced, essentially deprived of amphibians as well as predatory and mobile macroinvertebrates to the profit of burrowing, lower trophic level consumers (detritivores). Changes in community structure and function underlined a regime shift from a macrophyte-dominated system mainly characterized by benthic primary production (periphyton), to a macrophyte-depleted state of ponds hosting communities mainly associated with phytoplankton primary production and detritus accumulation, with higher tolerance to eutrophication and low dissolved oxygen concentration. Results underline major impacts of widely introduced omnivores such as the goldfish on the functioning of pond ecosystems with potentially dramatic consequences on the key ecosystem services they deliver, such as global biodiversity support or water quality improvement. They also shed light on the key role of submerged aquatic vegetation in supporting diverse communities and complex food webs in shallow lentic systems and call for urgent consideration of threats posed by IAS on ponds' ecosystems by managers and policymakers.

Trophic effects of Bti-based mosquito control on two top predators in floodplain pond mesocosms.

Chironomid (Diptera: Chironomidae) larvae play a key role in aquatic food webs as prey for predators like amphibian and dragonfly larvae. This trophic link may be disrupted by anthropogenic stressors such as Bacillus thuringiensis var. israelensis (Bti), a biocide widely used in mosquito control. In a companion study, we recorded a 41% reduction of non-target larval chironomids abundance in outdoor floodplain pond mesocosms (FPMs) treated with Bti. Therefore, we examined the diet of two top predators in the FPMs, larvae of the palmate newt (Salamandridae: Lissotriton helveticus) and dragonfly (Aeshnidae: predominantly Anax imperator), using bulk stable isotope analyses of carbon and nitrogen. Additionally, we determined neutral lipid fatty acids in newt larvae to assess diet-related effects on their physiological condition. We did not find any effects of Bti on the diet proportions of newt larvae and no significant effects on the fatty acid content. We observed a trend in Aeshnidae larvae from Bti-FPMs consuming a higher proportion of large prey (Aeshnidae, newt, damselfly larvae; ~42%), and similar parts of smaller prey (chironomid, mayfly, Libellulidae, and zooplankton), compared to controls. Our findings may suggest bottom-up effects of Bti on aquatic predators but should be further evaluated, for instance, by using compound-specific stable isotope analyses of fatty acids or metabarcoding approaches.

Pilot-scale microalgae cultivation and wastewater treatment using high-rate ponds: a meta-analysis.

Microalgae cultivation in wastewater has been widely researched under laboratory conditions as per its potential to couple treatment with biomass production. Currently, only a limited number of published articles consider outdoor and long-term microalgae-bacteria cultivations in real wastewater environmental systems. The scope of this work is to describe microalgal cultivation steps towards high-rate algal pond (HRAP) scalability and identify key parameters that play a major role for biomass productivity under outdoor conditions and long-term cultivations. Reviewed pilot-scale HRAP literature is analysed using multivariate analysis to highlight key productivity parameters within environmental and operational factors. Wastewater treatment analysis indicated that HRAP can effectively remove 90% of NH4+, 70% of COD, and 50% of PO43-. Mean reference values of 210 W m-2 for irradiation, 18 °C for temperature, pH of 8.2, and HRT of 7.7 are derived from pilot-scale cultivations. Microalgae biomass productivity at a large scale is governed by solar radiation and NH4+ concentration, which are more important than retention time variations within investigated studies. Hence, selecting the correct type of location and a minimum of 70 mg L-1 of NH4+ in wastewater will have the greatest effect in microalgae productivity. A high nutrient wastewater content increases final biomass concentrations but not necessarily biomass productivity. Pilot-scale growth rates (~ 0.54 day-1) are half those observed in lab experiments, indicating a scaling-up bottleneck. Microalgae cultivation in wastewater enables a circular bioeconomy framework by unlocking microalgal biomass for the delivery of an array of products.

Microplastic pollution and ecological risk assessment of a pond ecosystem.

Microplastic (MP) pollution has been observed in various ecosystems as a result of the rapid increase in plastic production over the past half-century. Nevertheless, the extent of MP pollution in different ecosystems, particularly in freshwater ecosystems, has not been well-studied, and there are limited investigations on this particular topic, specifically in Türkiye. Here, we quantify the occurrence and distribution of MPs in surface water samples collected from Topçu Pond (Türkiye) for the first time. Water samples were collected at five stations and filtered (30 L for each station) through stacked stainless steel sieves (5 mm, 328 µm, and 61 µm mesh size) with a diameter of 30 cm. The abundance, size, color, shape, and type of collected debris samples were analyzed after the wet peroxide oxidation process. MP particles were observed in all samples at an average abundance of 2.4 MPs/L. The most abundant MP size class and type were 0-999 µm and fiber respectively. On the other hand, prevalent colors were black and colorless in general. According to the Raman analysis results, the identified MP derivatives were polypropylene (40%), polyamide (30%), ethylene acrylic acid (20%), and polyvinylchloride (10%). Moreover, the pollution load index (PLI) index was used to determine the pollution status. PLI values were determined as 1.91 at station S1, 1.73 at station S2, 1.31 at station S3, 1 at station S4 and 1.24 at station S5. The PLI value determined for the overall pond was 1.4. The results of this research show that MP pollution is present in Topçu Pond and contributes to the expanding literature on MP pollution in pond ecosystems.

Duplex Real-Time Fluorescent Quantitative PCR Assays for the Detection of Toxigenic Microcystis Genotypes Based on SNP/InDel Variation in mcy Gene Cluster.

In this study, the toxigenic characteristics of 14 strains of Microcystis were analyzed, and single nucleotide polymorphism (SNP) and insertion/deletion (InDel) loci in microcystin synthetase (mcy) gene clusters were screened. Based on SNP and InDel loci associated with the toxigenic characteristics, primers and TaqMan or Cycling fluorescent probes were designed to develop duplex real-time fluorescent quantitative PCR (FQ-PCR) assays. After evaluating specificity and sensitivity, these assays were applied to detect the toxigenic Microcystis genotypes in a shrimp pond where Microcystis blooms occurred. The results showed a total of 2155 SNP loci and 66 InDel loci were obtained, of which 12 SNP loci and 5 InDel loci were associated with the toxigenic characteristics. Three duplex real-time FQ-PCR assays were developed, each of which could quantify two genotypes of toxigenic Microcystis. These FQ-PCR assays were highly specific, and two Cycling assays were more sensitive than TaqMan assay. In the shrimp pond, six genotypes of toxigenic Microcystis were detected using the developed FQ-PCR assays, indicating that above genotyping assays have the potential for quantitative analysis of the toxigenic Microcystis genotypes in natural water.

Microbiomes on microplastics versus natural microcarriers: Stability and transformation during aquatic travel from aquaculture ponds to adjacent stream.

Microplastics (MPs) with different physical-chemical properties are considered as vectors for the propagation of microbes in aquatic environments. It remains unclear how plastic types impact on the plastisphere and whether different MPs spread microbes more rapidly than natural materials in microbes across distinct water bodies as proposed previously. We used in-situ incubation to investigate the microbes attached on MPs of polyethylene (PE), polypropylene (PP), and polyvinyl chloride (PVC), versus that on two natural microcarriers (quartz sands and bamboo) during the travel from aquaculture ponds with impacted by fish farming to adjacent freshwater stream. The results showed that the microbial communities on the carriers were shaped not only by environmental conditions, which were primary determinants but also by carrier types. All the tested plastics did not carry more microbes than the natural carriers during the journey. The biofilm community composition on PVC is distinct from that on PE and PP MPs and natural carriers. The plastisphere of PE and PP kept microbial proportions as natural materials did but PVC retained less than nature materials. Bamboo carried more potential pathogens than plastic polymers and quartz. The results indicated that the communities of plastisphere is polymer-type dependent, and, compared with the natural materials, MPs did not show enhanced propagation of microbes, including pathogens, cross distinct environments.

Assessing controls on sedimentation rates and sediment organic carbon accretion in beaver ponds.

Beaver dams trap sediment, promote channel-floodplain connectivity, modify biogeochemical cycling and organic carbon (OC) storage, and influence geomorphic form. Beaver-related sediment accumulation has been investigated at longer timescales (e.g., > 1000 years) and shorter timescales (< 10 years), but we lack information on sedimentation and sediment-associated OC accretion rates over multiple decades in relatively persistent beaver ponds (10-100 years old). We coupled field surveys of 45 beaver ponds with historical aerial imagery and radiometric dating with 7Be, 210Pb, and 14C to calculate sedimentation rates, mean sediment depth, and sediment OC content at two study sites in the southern Rocky Mountains, USA. Sedimentation rates in beaver ponds (median = 5.7 cm yr-1, mean = 11.6 cm yr-1) decreased with pond age. Incised, single threaded reaches had greater variability in mean sediment depth compared to less incised reaches. In less incised reaches, mean sediment depth and beaver dam height increased with pond age, indicating more stable dams and depositional environments. Sediment OC content within beaver ponds (median = 0.8 %, mean = 1.7 %) increased with finer sediment grain size distributions. Sediment OC accretion rates in ponds ranged between 0.13 and 23 Mg C ha -1 per year. We used Monte Carlo simulations to estimate it would take ∼100 years or more of uninhibited beaver activity for deposition to laterally reconnect adjacent terraces in the incised study reaches, a common objective within many stream restoration projects. Our findings show that beaver ponds in complex, multi-threaded reaches better retain fine sediment over longer timescales, highlighting the need to incorporate geomorphic context when considering whether beaver can help restore incised river channels and floodplain connectivity, retain fine sediment, and store OC on the landscape.

Cyanobacteria respond to trophic status in shallow aquatic ecosystems.

Small and shallow water bodies are particularly sensitive to adverse conditions connected with anthropogenic eutrophication. As model systems, ponds are a good object for ecological research and monitoring of global environmental changes. We examined cyanobacteria along with other groups of algae versus zooplankton and abiotic characteristics of water in 51 aquatic ecosystems exposed to anthropogenic pressure (from natural forest to highly disturbed field ponds) with 3 distinct trophic groups: meso-, eu- and hypertrophic. This study aimed to define how different levels of trophy affect pond-specific cyanobacteria assemblages and to identify species responding to particular trophic states. We demonstrated that trophic type determined the occurrence of certain cyanobacteria species. From among 78 identified taxa, shade- and turbid mixed adapted were the most numerous. Eutrophic ponds had the highest cyanobacteria species and diversity and abundance of zooplankon. Dominating species such as Chroococcus minimus, Anagnostidinema amphibium, Phormidium granulatum or Komvophoron minutum preferred mesotrophic, while e.g. Jaaginema subtilissimum, Limnolyngbya circumcreta, Limnothrix vacuolifera or Romeria leopolienis eutrophic waters and these were not grazed by filtrators. Only 3 species (Aphanizomenon flos-aquae, Dolichospermum circinale, Planktothrix agardhii) were associated with hypertrophic ponds. Therefore, we assume that cyanobacteria taxa have a high indicative potential to distinguish between trophic type of ponds. Reynolds Functional Groups also exhibit responses to changes in water quality. It was partucularly evident in the case of cyanobacteria representatives of codon M which was attributed to eutrophic ponds. Advancing our understanding about trophic preferences of cyanobacteria is crucial, especially in the era of global warming and the persistent issue of water eutrophication, when problems with harmful cyanobacterial blooms are intensifying. The research findings have ecological significance and management implications, highlighting the often-overlooked importance of pond ecosystems in maintaining overall water quality.

Using machine learning models to estimate Escherichia coli concentration in an irrigation pond from water quality and drone-based RGB imagery data.

The rapid and efficient quantification of Escherichia coli concentrations is crucial for monitoring water quality. Remote sensing techniques and machine learning algorithms have been used to detect E. coli in water and estimate its concentrations. The application of these approaches, however, is challenged by limited sample availability and unbalanced water quality datasets. In this study, we estimated the E. coli concentration in an irrigation pond in Maryland, USA, during the summer season using demosaiced natural color (red, green, and blue: RGB) imagery in the visible and infrared spectral ranges, and a set of 14 water quality parameters. We did this by deploying four machine learning models - Random Forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), and K-nearest Neighbor (KNN) - under three data utilization scenarios: water quality parameters only, combined water quality and small unmanned aircraft system (sUAS)-based RGB data, and RGB data only. To select the training and test datasets, we applied two data-splitting methods: ordinary and quantile data splitting. These methods provided a constant splitting ratio in each decile of the E. coli concentration distribution. Quantile data splitting resulted in better model performance metrics and smaller differences between the metrics for both the training and testing datasets. When trained with quantile data splitting after hyperparameter optimization, models RF, GBM, and XGB had R2 values above 0.847 for the training dataset and above 0.689 for the test dataset. The combination of water quality and RGB imagery data resulted in a higher R2 value (>0.896) for the test dataset. Shapley additive explanations (SHAP) of the relative importance of variables revealed that the visible blue spectrum intensity and water temperature were the most influential parameters in the RF model. Demosaiced RGB imagery served as a useful predictor of E. coli concentration in the studied irrigation pond.

Identification and Composition of Cyanobacteria in Ecuadorian Shrimp Farming Ponds-Possible Risk to Human Health.

Toxic cyanobacterial blooms in various water bodies have been given much attention nowadays as they release hazardous substances in the surrounding areas. These toxic planktonic cyanobacteria in shrimp ponds greatly affect the survival of shrimps. Ecuador is the second highest shrimp producing country in the Americas after Brazil; and the shrimp-based economy is under threat due to toxic cyanobacterial blooms in Ecuador shrimp ponds. This study investigated the abundance of different cyanobacteria in the shrimp ponds at the Chone and Jama rivers (in Manabi province) at Ecuadorian pacific coast, focusing on different environmental factors, such as temperature, pH, salinity, and light. Temperature and pH were identified as key factors in influencing the abundance of cyanobacteria, with a significant positive correlation between Raphidiopsis raciborskii and pH. The highest and lowest abundance of cyanobacteria found during the dry season in the shrimp ponds near the Chone and Jama rivers were > 3 × 106 and 1 × 106 Cell.m-3, respectively. The Shannon-Wiener Diversity Index fluctuated between 0.41-1.15 and 0.31-1.15 for shrimp ponds of Chone and Jama rivers, respectively. This variation was linked to changes in salinity and the presence of harmful algal blooms, highlighting the importance of continuous monitoring. Additionally, the study areas showed eutrophic conditions with low diversity, underlining the need for additional spatiotemporal studies and expanded research in both rivers, to better understand these complex phenomena. The findings underscore the importance of continuous monitoring and expanded research in cyanobacteria ecology, with implications for public health and aquatic resource management.

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditional fish farming methods incur enormous economic costs owing to labor-intensive schedule monitoring and care, illnesses, and sudden fish deaths. Another ongoing issue is automated fish species recommendation based on water quality. On the one hand, the effective monitoring of abrupt changes in water quality may minimize the daily operating costs and boost fish productivity, while an accurate automatic fish recommender may aid the farmer in selecting profitable fish species for farming. In this paper, we present AquaBot, an IoT-based system that can automatically collect, monitor, and evaluate the water quality and recommend appropriate fish to farm depending on the values of various water quality indicators. A mobile robot has been designed to collect parameter values such as the pH, temperature, and turbidity from all around the pond. To facilitate monitoring, we have developed web and mobile interfaces. For the analysis and recommendation of suitable fish based on water quality, we have trained and tested several ML algorithms, such as the proposed custom ensemble model, random forest (RF), support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), logistic regression (LR), bagging, boosting, and stacking, on a real-time pond water dataset. The dataset has been preprocessed with feature scaling and dataset balancing. We have evaluated the algorithms based on several performance metrics. In our experiment, our proposed ensemble model has delivered the best result, with 94% accuracy, 94% precision, 94% recall, a 94% F1-score, 93% MCC, and the best AUC score for multi-class classification. Finally, we have deployed the best-performing model in a web interface to provide cultivators with recommendations for suitable fish farming. Our proposed system is projected to not only boost production and save money but also reduce the time and intensity of the producer's manual labor.

Gemmobacter denitrificans sp. nov., a denitrifying bacterium, isolated from pond water for Litopenaeus vannamei.

A novel Gram-stain-negative strain, designated JM10B15T, was isolated from pond water for Litopenaeus vannamei collected from Jiangmen City, Guangdong province, south PR China. Cells of the strain were aerobic, rod-shaped, and motile by lateral flagella. JM10B15T could grow at 15-40 °C, pH 6.0-9.5, and in 0-3.0 % NaCl, with optimal growth at 25-35 °C, pH 7.5-8.5, and in 0 % NaCl, respectively. Furthermore, this strain grew well on Reasoner's 2A agar but not on nutrient broth agar or Luria-Bertani agar. JM10B15T was a denitrifying bacterium capable of removing nitrites and nitrates, and three key functional genes, nasA, nirS, and nosZ, were identified in its genome. The results of phylogenetic analyses based on the 16S rRNA gene and genome sequences indicated that JM10B15T belonged to the genus Gemmobacter. JM10B15T showed the highest 16S rRNA sequence similarity to Gemmobacter lutimaris YJ-T1-11T (98.8 %), followed by Gemmobacter aquatilis IFAM 1031T (98.6 %) and Gemmobacter serpentinus HB-1T (98.1 %). The average nucleotide identity and digital DNA-DNA hybridization values between JM10B15T and the other type strains of genus Gemmobacter were 78.1-82.1 % and 18.4-22.1 %, respectively. The major fatty acids of strain JM10B15T were summed feature 8 (C18 : 1 ω6c and/or C18 : 1 ω7c) and C18 : 1 ω7c 11-methyl. In addition, the major respiratory quinone of this novel strain was Q-10, and the predominant polar lipids were phosphatidylglycerol, phosphatidylethanolamine, four unidentified phospholipids, three unidentified lipids, and an unidentified aminophospholipid. Results of analyses of the phylogenetic, genomic, physiological, and biochemical characteristics indicated that JM10B15T represents a novel species of the genus Gemmobacter, for which the name Gemmobacter denitrificans sp. nov. is proposed. The type strain is JM10B15T (=GDMCC 1.4148T=KCTC 8140T).

Global biochemical profiling of fast-growing Antarctic bacteria isolated from meltwater ponds by high-throughput FTIR spectroscopy.

Fourier transform infrared (FTIR) spectroscopy is a biophysical technique used for non-destructive biochemical profiling of biological samples. It can provide comprehensive information about the total cellular biochemical profile of microbial cells. In this study, FTIR spectroscopy was used to perform biochemical characterization of twenty-nine bacterial strains isolated from the Antarctic meltwater ponds. The bacteria were grown on two forms of brain heart infusion (BHI) medium: agar at six different temperatures (4, 10, 18, 25, 30, and 37°C) and on broth at 18°C. Multivariate data analysis approaches such as principal component analysis (PCA) and correlation analysis were used to study the difference in biochemical profiles induced by the cultivation conditions. The observed results indicated a strong correlation between FTIR spectra and the phylogenetic relationships among the studied bacteria. The most accurate taxonomy-aligned clustering was achieved with bacteria cultivated on agar. Cultivation on two forms of BHI medium provided biochemically different bacterial biomass. The impact of temperature on the total cellular biochemical profile of the studied bacteria was species-specific, however, similarly for all bacteria, lipid spectral region was the least affected while polysaccharide region was the most affected by different temperatures. The biggest temperature-triggered changes of the cell chemistry were detected for bacteria with a wide temperature tolerance such Pseudomonas lundensis strains and Acinetobacter lwoffii BIM B-1558.

Nitrogen Removal Performance and Microbial Community Structure of IMTA Ponds (Apostistius japonicus-Penaeus japonicus-Ulva).

Denitrification and anaerobic ammonium oxidation (anammox) are key processes for nitrogen removal in aquaculture, reducing the accumulated nitrogen nutrients to nitrogen gas or nitrous oxide gas. Complete removal of nitrogen from aquaculture systems is an important measure to solve environmental pollution. In order to evaluate the nitrogen removal potential of marine aquaculture ponds, this study investigated the denitrification and anammox rates, the flux of nitrous oxide (N2O) at the water-air interface, the sediment microbial community structure, and the gene expression associated with the nitrogen removal process in integrated multi-trophic aquaculture (IMTA) ponds (Apostistius japonicus-Penaeus japonicus-Ulva) with different culture periods. The results showed that the denitrification and anammox rates in sediments increased with the increase of cultivation periods and depth, and there was no significant difference in nitrous oxide gas flux at the water-air interface between different cultivation periods (p > 0.05). At the genus and phylum levels, the abundance of microorganisms related to nitrogen removal reactions in sediments changed significantly with the increase of cultivation period and depth, and was most significantly affected by the concentration of particulate organic nitrogen (PON) in sediments. The expression of denitrification gene (narG, nirS, nosZ) in surface sediments was significantly higher than that in deep sediments (p < 0.05), and was negatively correlated with denitrification rate. All samples had a certain anammox capacity, but no known anammox bacteria were found in the microbial diversity detection, and the expression of gene (hzsB) related to the anammox process was extremely low, which may indicate the existence of an unknown anammox bacterium. The data of this study showed that the IMTA culture pond had a certain potential for nitrogen removal, and whether it could make a contribution to reducing the pollution of culture wastewater still needed additional practice and evaluation, and also provided a theoretical basis for the nitrogen removal research of coastal mariculture ponds.