Total Phosphorus Research Articles

Evaluation of substrates for optimizing vermicomposting products

The high global market value of fresh mushrooms implies high importance of spent mushroom substrate (SMS) as a by-product that poses environmental challenges, if not properly treated. Reported studies demonstrate the positive effects of SMS on earthworm growth and reproduction, particularly when combined with other substrates such as cow dung (CD). This study utilized SMS and CD as substrates in varying ratios. A total of 375 young non-clitellated Eisenia fetida were randomly assigned to plastic containers, ensuring similar average individual worm weight, and maintained at 50% to 60% moisture. Weekly observations were made on earthworm average weight, cocoon production, and hatchling count. The growth and reproduction of earthworms differed significantly among treatments, with Treatment 3 (T3) (50:50 SMS and CD) showing the highest growth and Treatment 5 (T5) (0:100 SMS and CD) the lowest. Changes in pH, EC, total Kjeldahl nitrogen (TKN), total organic carbon (TOC), C/N ratio, and total available phosphorus (TAP) were observed over the experimental period, indicating dynamic nutrient dynamics within the substrates. The exchangeable potassium decreased with increasing proportions of CD, while the exchangeable sodium content showed variation across treatments. The observed variations can be attributed to differences in initial substrate composition and microbial activity during vermicomposting.

The efficacy of integrated vermifiltration technology for treatment of food analysis laboratory wastewater

The macrophyte-assisted vermifiltration (MAVF) technology was applied for treatment of food analysis laboratory wastewater at Industrial Technology Institute (ITI), Sri Lanka for the first time. Three laboratory-scale sub-surface vertical flow units were established:1) without earthworms and plants (Control unit), 2) with earthworms (Eisenia fetida) (vermi-filtration unit (VF unit), 3) with both earthworms and macrophytes (Canna indica) (MAVF unit). Wastewater was fed batch-wise with a feeding rate of 10 mL/min and seven days hydraulic retention time (HRT) for eight consecutive batches. Physiochemical parameters, Chemical Oxygen Demand (COD), Total Phosphorus (TP), Total Nitrogen (TN), pH, of the influent and effluent of all three units were analyzed to investigate the treatment efficiencies. One-Way ANOVA was performed to evaluate the significant differences in treatment efficiencies. The mean COD removal efficiencies of the control unit, VF unit, and MAVF unit were 60.2 % ± 10.7, 71.6± 8.07 %, and 72.0 % ± 8.86, respectively. Average TN removal efficiencies of the control unit, VF unit, and MAVF unit were 8.05 % ± 5.75, 10.9±6.4 %, and 24.9 % ±12.84, respectively. Average TP removal efficiencies were 35.84 % ± 17.5, 35.84 % ± 17.5 %, and 40.0 % ±16.76, respectively. The COD removal displayed promising results, whereas the means for enhancing TP and TN removal should be further studied. The findings of this study sensitizes the testing laboratories to go green by adopting in-house cost effective laboratory wastewater treatment systems.

Environmental determinants of aerobic methane oxidation in a tropical river network

Aerobic methane oxidation (MOX) significantly reduces methane (CH4) emissions from inland water bodies and is, therefore, an important determinant of global CH4 budget. Yet, the magnitude and controls of MOX rates in rivers – a quantitatively significant natural source of atmospheric CH4 – are poorly constrained. Here, we conducted a series of incubation experiments to understand the magnitude and environmental controls of MOX rates in tropical fluvial systems. We observed a large variability in MOX rate (0.03 - 3.45 μmol l-1d-1) shaped by a suit of environmental variables. Accordingly, we developed an empirical model for MOX that incorporate key environmental drivers, including temperature, CH4, total phosphorus, and dissolved oxygen (O2) concentrations, based on the results of our incubation experiments. We show that temperature dependency of MOX (activation energy: 0.66 ± 0.18 eV) is lower than that of sediment methanogenesis (0.71 ± 0.21 eV) in the studied tropical fluvial network. Furthermore, we observed a non-linear relationship between O2 concentration and MOX, with the highest MOX rate occuring ∼135 μmol O2l-1, above or below this “optimal O2” concentration, MOX rate shows a gradual decline. Together, our results suggest that the relatively lower temperature response of MOX compared to methanogenesis along with the projected decrease of O2 concentration due to organic pollution may cause elevated CH4 emission from tropical southeast Asian rivers. Since estimation of CH4 oxidation is often neglected in routine CH4 monitoring programs, the model developed here may help to integrate MOX rate into process-based models for fluvial CH4 budget.

Long-term responses of internal environment dynamics in a freshwater lake to variations in external nutrient inputs: A model simulation approach

Lake restoration usually focuses on reducing external nutrient sources. However, when sediments contain nutrients accumulated over multiple years, internal nutrient release can delay restoration progress. In lake restoration and management, it is important to understand the dynamic relationship between nutrient concentrations in a lake and internal and external nutrient sources. In this study, we quantified external nutrient inputs through measurements and compared them with internal sediment release from simulation using the PCLake+ model. Additionally, we evaluated alterations in the internal nutrient release, lake nutrient concentrations, and algae biomass (chlorophyll-a) within the lake following varying degrees of reduction in external nutrient loads. The results demonstrate that the PCLake+ effectively simulated the lake's nutrient concentration and algae biomass. Based on the PCLake+ estimates, internal nutrient loads accounted for 51 % of the total nitrogen (N) and 80 % of the total phosphorus (P) loadings in Lake Erhai in 2019. In 2020, the total contributions were 43 % for TN and 72 % for TP. We simulated four scenarios where external nutrient inputs were reduced to 25 %, 50 %, 75 %, and 99.99 % of their original levels. The 40-year simulation showed that the lake's ecological system initially exhibited a fast internal response but reached equilibrium after eight years. P concentrations took longer to reach equilibrium compared to N concentrations, probably due to the stronger binding characteristics of P. To meet the water quality target in the future, it is necessary to reduce external N and P inputs into Lake Erhai by at least 23 % and 15 %, respectively, under current conditions. Although reducing external nutrient loads can indirectly lower internal nutrient loads, water management should address both external and internal loads simultaneously, as internal release cannot be effectively reduced by external reductions alone. Additionally, the lake's internal release may continue for several years, even with reductions in external inputs.

Comprehensive evaluation of product characteristics and energy consumption in hydrothermal carbonization of food waste anaerobic digestate: A perspective on phosphorus recovery and fuel properties

Food waste digestate (FWD) is rich in organic matter and phosphorus(P) elements, making it a potential source for energy and P recovery. Hydrothermal carbonization (HTC) addresses FWD's dehydration and stability issues, improving hydrochar's fuel properties and P recovery in hydrothermal liquid. Experiments with various additives reveals 1M HCl's effectiveness, increasing P recovery by 88.31 % at 120 °C, decreasing hydrochar ash content by 21.42 %, and raising heating value by 45.01 %. Principal component analysis highlights the viability of acid treatment for P leaching and hydrochar enhancement, with pH as a crucial factor. HTC substantially reduces energy consumption by 57.42 % compared to direct drying. Hydrochar without additives shows potential as slow-release P fertilizers, with a 28.8 % increase in total phosphorus at 240 °C, where 99.4 % of P exists as apatite inorganic. Soil tests reveal differences with formic acid method in P availability, showing varying correlations with different P forms. This research offers insights for FWD resource utilization.

Performances of a novel BAF with ferromanganese oxide modified biochar (FMBC) as the carriers for treating antibiotics, nitrogen and phosphorus in aquaculture wastewater.

In this paper, a biological aerated filter (BAF) based on ferromanganese oxide-biochar (FMBC) was constructed to investigated the removal performance and mechanism for conventional pollutants and four kinds of antibiotic, in contrast of conventional zeolite loaded BAF (BAF-A) and bamboo biochar filled BAF (BAF-B). Results showed that the average removal efficiency of total nitrogen (TN), total phosphorus (TP) and antibiotics in a FMBC-BAF (named by BAF-C) were 52.97 ± 2.27%, 51.58 ± 1.92% and 70.36 ± 1.00% ~ 81.65 ± 0.99% respectively in running period (39-100 d), which were significantly higher than those of BAF-A and BAF-B. In the BAF-C, the expression of denitrification enzyme activities and the secretion of extracellular polymeric substance (EPS) especially polyprotein (PN) were effectively stimulated, as well as accelerated electron transfer activity (ETSA) and lower electrochemical impedance spectroscopy (EIS) were acquired. After 100 days of operation, the abundance of nitrogen, phosphorus and antibiotic removal functional bacteria like Sphingorhabdus (4.52%), Bradyrhizobium (1.98%), Hyphomicrobium (2.49%), Ferruginibacter (7.80%), unclassified_f_Blastoca tellaceae (1.84%), norank_f_JG30-KF-CM45 (6.82%), norank_f_norank_o_SBR1031 (2.43%), Nitrospira (2.58%) norank_f_Caldilineaceae (1.53%) and Micropruina (1.11%) were enriched. Mechanism hypothesis of enhanced performances of nutrients and antibiotics removal pointed that: The phosphorus was removed by adsorption and precipitation, antibiotics removal was mainly achieved through the combined action of adsorption and biodegradation, while nitrogen removal was realized by biologic nitrification and denitrification in a FMBC-BAF for aquaculture wastewater treatment.

Dual impacts of hydrology and damming on eutrophication: Comparison of two Ramsar wetlands in the middle Yangtze floodplain

Dam construction for social-economic benefits has raised substantial biological and ecological concerns. However, contrasting findings have been reported regarding the role of hydrological modification in floodplain lake ecosystems. Here, we evaluated the influence of hydrology and dam construction on the eutrophication of floodplain lakes over the last 200 years by studying Zn/Al (an indicator of industrial activities), nutrient influxes (total phosphorus, TP), cyanobacteria production (canthaxanthin) and aquatic invertebrate dynamics (chironomids) in 210Pb dated sediment cores from two Ramsar Wetlands of International Importance in the middle Yangtze floodplain, one dammed (Wanghu) and the other freely connected (Poyang) with the Yangtze River. The results show that Wanghu Lake transitioned to a macrophyte-dominated clear water state (as indicated by the increases in pigment derived ultraviolet radiation index and dominance of macrophyte-related chironomid taxa) after local dam construction when anthropogenic nutrient loadings were relatively low. With increases in nutrient loadings, phytoplankton increased in both lakes, but water clarity declined and macrophyte-related chironomids decreased only in the lake which was locally dammed. Our study reveals that local damming facilitates the response of floodplain lake ecosystems to eutrophication and decouples it from the effects of hydrological variability. This study highlights the potential influence of hydrology and damming on the eutrophication of floodplain lakes by influencing water clarity and macrophyte coverage, implying that evaluating the role of local dam construction on ecosystem states should be based on knowledge of nutrient conditions in floodplain lakes.

Pre-training enhanced spatio-temporal graph neural network for predicting influent water quality and flow rate of wastewater treatment plant: Improvement of forecast accuracy and analysis of related factors

Efficient management of wastewater treatment plants (WWTPs) necessitates accurate forecasting of influent water quality parameters (WQPs) and flow rate (Q) to reduce energy consumption and mitigate carbon emissions. The time series of WQPs and Q are highly non-linear and influenced by various factors such as temperature (T) and precipitation (Precip). Conventional models often struggle to account for long-term temporal patterns and overlook the complex interactions of parameters within the data, leading to inaccuracies in detecting WQPs and Q. This work introduced the Pre-training enhanced Spatio-Temporal Graph Neural Network (PT-STGNN), a novel methodology for accurately forecasting of influent COD, ammonia nitrogen (NH3-N), total phosphorus (TP), total nitrogen (TN), pH and Q in WWTPs. PT-STGNN utilizes influent data of the WWTP, air quality data and meteorological data from the service area as inputs to enhance prediction accuracy. The model employs unsupervised Transformer blocks for pre-training, with efficient masking strategies to effectively capture long-term historical patterns and contextual information, thereby significantly boosting forecasting accuracy. Furthermore, PT-STGNN integrates a unique graph structure learning mechanism to identify dependencies between parameters, further improving the model's forecasting accuracy and interpretability. Compared with the state-of-the-art models, PT-STGNN demonstrated superior predictive performance, particularly for a longer-term prediction (i.e., 12 h), with MAE, RMSE and MAPE at 12-h prediction horizon of 2.737 ± 0.040, 4.209 ± 0.060 and 13.648 ± 0.151 %, respectively, for the algebraic mean of each parameter. From the results of graph structure learning, it is observed that there are strong dependencies between NH3-N and TN, TP and Q, as well as Precip, etc. This study innovatively applies STGNN, not only offering a novel approach for predicting influent WQPs and Q in WWTPs, but also advances our understanding of the interrelationships among various parameters, significantly enhancing the model's interpretability.

Construction and Application of the Phaeozem Health Evaluation System in Liaoning Province, China

Soil degradation has led to a continuous decline in the quality of phaeozem, which is seriously threatening the foundation of national food security. Therefore, precisely evaluating the health status of phaeozem resources and their spatial and temporal variations are crucial for ensuring the effective implementation of soil degradation prevention and control strategies. In this study, soil data from 140 sites were collected, and eight physical and chemical indices (sand content, silt content, pedon thickness, organic matter, total potassium, total nitrogen, total phosphorus, and pH) were utilized to assess the soil health status of phaeozem in Liaoning Province. The results showed the following: (1) The minimum data set is aligned with previous research findings and effectively mirrors the soil’s health condition. (2) The substantial coefficients of variation observed for pedon thickness, sand content, and silt content across regions suggest notable differences, likely influenced by climatic variations, parent material differences, and anthropogenic activities. (3) The study area’s average soil pH of 6.39 indicates an overall acidic nature, potentially attributed to intense soil weathering and suboptimal fertilization practices. (4) The soil health index (SHI) ranged from 0.33 to 0.91, with an average of 0.62, which indicates that the majority of the phaeozem in Liaoning Province are in a sub-healthy state (SHI < 0.6 = unhealthy, SHI 0.6–0.8 = sub-healthy, SHI ≥ 0.8 = healthy). These sub-healthy areas are primarily located in hills, mountains, and the Liaohe Plain, and are significantly impacted by rainfall and wind erosion. Meanwhile, unhealthy areas are concentrated in the south and center of the province, characterized by fragile ecological environments and challenging agricultural conditions.

Effects of Deep Tillage on Wheat Regarding Soil Fertility and Rhizosphere Microbial Community.

Wheat production is intrinsically linked to global food security. However, wheat cultivation is constrained by the progressive degradation of soil conditions resulting from the continuous application of fertilizers. This study aimed to examine the effects of deep tillage on rhizosphere soil microbial communities and their potential role in improving soil quality, given that the specific mechanisms driving these observed benefits remain unclear. Soil fertility in this research was evaluated through the analysis of various soil parameters, including total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium, among others. The high-throughput sequencing technique was utilized to examine the rhizosphere microbial community associated with deep tillage wheat. The findings indicated that deep tillage cultivation of wheat led to reduced fertility levels in the 0-20 cm soil layer in comparison with non-deep tillage cultivation. A sequencing analysis indicated that Acidobacteria and Proteobacteria are the dominant bacterial phyla, with Proteobacteria being significantly more abundant in the deep tillage group. The dominant fungal phyla identified were Ascomycota, Mortierellomycota, and Basidiomycota. Among bacterial genera, Arthrobacter, Bacillus, and Nocardioides were predominant, with Arthrobacter showing a significantly higher presence in the deep tillage group. The predominant fungal genera included Mortierella, Alternaria, Schizothecium, and Cladosporium. Deep tillage cultivation has the potential to enhance soil quality and boost crop productivity through the modulation of soil microbial community structure.

A deep learning-based model for estimating pollution fluxes from rivers into the sea and its optimization

Pollution fluxes from rivers into the sea are currently the main source of pollutants in nearshore areas. Based on the source-sink process of the basin-estuary-coastal waters system, the pollution fluxes into the sea and their spatiotemporal heterogeneity were estimated. A deep learning-based model was established to simplify the estimation of pollution fluxes into the sea, with socio-economic drivers and meteorological data as input variables. A method for estimating the contribution rate of pollution fluxes from different spatial gradient was proposed. In this study, we found that (1) the pollution fluxes into the sea of total nitrogen (TN) and total phosphorus (TP) from the Bohai Sea Rim Basin (BSRB) in 1980, 1990, 2000, 2010, and 2020 were 25.38 × 104, 26.12 × 104, 27.27 × 104, 29.82 × 104, 25.31 × 104 and 1.32 × 104, 2.14 × 104, 2.09 × 104, 1.87 × 104, 1.68 × 104 tons, respectively. (2) The proportion of rural life and livestock to the TN was the highest, accounting for 39.18 % and 21.19 %, respectively. The proportion of livestock to the TP was the highest, accounting for 39.20 %, followed by rural life, accounting for 24.72 %. The results indicated that the pollution fluxes in the BSRB were related to human economic activities and relevant environmental protection measures. (3) The deep learning-based model established to estimate runoff pollution fluxes into the sea had the accuracy of over 90 %. (4) As for contribution rate, in terms of the elevation, the range of 0–100 m had the highest proportion, accounting for 39.65 %. The range of 50–100 km from the coastline had the highest proportion, accounting for 18.11 %. In terms of the district, coastal area has the highest proportion, accounting for 38.00 %. This study revealed the changing trends and driving mechanisms of pollution fluxes into the sea over the past 40 years and established a simplified deep learning-based model for estimating pollution fluxes into the sea. Then, we identified regions with high pollution contribution rate. The results can provide scientific references for the adaptive management of the nearshore areas based on the ecosystem.

Relationships between environmental variables and fish functional groups in impounded reaches of the Upper Mississippi and Yangtze Rivers

Large rivers throughout the world have been transformed by anthropogenic stressors that are known to influence the structure and composition of fish assemblages. Management of large rivers requires balancing socio-economic and political considerations with biodiversity conservation efforts. By exchanging best management practices between rivers, management efforts can be improved. However, data limitations have largely prevented comparative analyses among fish assemblages in large rivers, potentially limiting the effectiveness of shared management strategies. To improve understanding of the similarities and differences between the Upper Mississippi and Yangtze Rivers, we (1) compared environmental variables and functional traits of fish assemblages between the two systems, (2) identified traits responsible for distinguishing functional groups from one another, and (3) investigated relationships between similar functional groups of fishes and environmental variables to establish expectations for how fish assemblages in large rivers might respond to anthropogenic stressors. Regional species pools in the Upper Mississippi and Upper Yangtze Rivers were characterized by a similar composition of functional traits; the majority of species were omnivorous, had affinities for gravel or sand substrates, and produced sinking eggs. Few species were pelagic, planktivorous, or herbivorous. Functional groups in both rivers were primarily distinguished according to species' trophic habits and substrate preferences, with secondary contributions from species’ water column positions and life history characteristics. Pelagic planktivores and small-bodied guarders with an affinity for structural habitat complexity tended to increase downriver in both systems, in direct association with total phosphorus concentrations, agricultural land use, and temperature. In contrast, proportions of lithophilic species with affinities for gravel or cobble substrates were highest in segments located furthest upriver. By highlighting the sensitivity of different groups of fishes to anthropogenic stressors, we provide insights into the functional ecology of fishes inhabiting the Mississippi and Yangtze Rivers.

Interpretable prediction, classification and regulation of water quality: A case study of Poyang Lake, China

Effective identification and regulation of water quality impact factors is essential for water resource management and environmental protection. However, the complex coupling of water quality systems poses a significant challenge to this task. This study proposes coherent model for water quality prediction, classification and regulation based on interpretable machine learning. The decomposition-reconstruction module is used to transform non-stationary water quality series into stationary series while effectively reducing the feature dimensions. Spatiotemporal multi-source data is introduced by using the Maximum Information Coefficient (MIC) for feature selection. The Temporal Convolutional Network (TCN) is used to extract the temporal features of different variables, followed by the introduction of External Attention mechanism (EA) to construct the relationship between these features. Finally, the target water quality sequence is simulated using Gated Recurrent Unit (GRU). The proposed model was applied to Poyang Lake in China to predict six water quality indicators: ammonia nitrogen (NH3-N), dissolved oxygen (DO), pH, total nitrogen (TN), total phosphorus (TP), water temperature (WT). The water quality was then classified based on the prediction results using the XGBoost algorithm. The findings indicate that the proposed model's Nash-Sutcliff Efficiency (NSE) value ranges from 0.88 to 0.99, surpassing that of the benchmark model, and demonstrates strong interval prediction performance. The results highlight the superior performance of the XGBoost algorithm (with an accuracy of 0.89) in addressing water quality classification issues, particularly in cases of category imbalance. Subsequently, interpretability analysis using the SHapley Additive exPlanation (SHAP) method revealed that the model is capable of learning relationships between different variables and there exists a possibility of learning the physical laws. Ultimately, this study proposes a water quality regulation mechanism that improves TN and DO levels by stepwise changing the magnitude of water temperature, which significantly improves in the case of data limitations. In conclusion, this study presents an overall framework for integrating water quality prediction, classification and improvement for the first time, forming a complete set of water quality early warning and improvement management strategies. This framework provides new ideas and ways for lake water quality management.

Characteristics of Water Environment and Its Influencing Factors in Zhari Namco Basin, Xizang

Zhari Namco is situated in the alpine grassland belt of northwestern Xizang with a fragile ecological environment. As the third-largest lake in Xizang, there has been a long-term lack of research data concerning its basin water environment. In an effort to elucidate the surface water environment characteristics of the basin and the factors influencing them, an extensive investigation was conducted from August 2021 to June 2022, encompassing periods of high flow, low flow, and base flow. Further, the study also involved comprehensive assessments of the water chemistry characteristics and spatial-temporal variation in lake sampling sites of the basin that were not significant by using mathematical statistics, hydrochemical analysis, correlation analysis, and principal component analysis. The findings revealed the following： ① The water in the Zhari Namco Basin exhibited an alkaline nature, with dominant ionic compositions in the lake comprising Na+, SO42-, and Cl-, whereas the rivers were primarily characterized by Ca2+, HCO3-, and SO42-. ② The main pollutants exceeding established standards included sulfates, arsenic, chlorides, and total phosphorus. The study identified significant spatiotemporal variations in water quality. Temporally, the exceedance of sulfates, arsenic, and total phosphorus was most pronounced during high-flow periods, followed by that during low-flow and base flow periods, with chloride levels showing less temporal variation. Spatially, river water quality surpassed that of the lakes, with arsenic, total phosphorus, TDS, sulfate, chloride, K+, and Na+ concentrations in lakes 1 to 2 orders of magnitude higher than those in rivers. Water qualities exceeding the established standard were primarily found in the lake, with less spatial variations within the lake itself. ③ Hydrochemical processes within the basin were found to be primarily influenced by natural phenomena, including evaporation-concentration and rock weathering. Various elements entered the lakes via surface runoff, where they continuously accumulated under the influence of evaporation-concentration processes, ultimately leading to exceedances. ④ Temporal variations in water quality were primarily attributed to increased elemental loss and intensified evaporation during high-flow periods. The spatial discrepancies in water quality were predominantly a consequence of the differing hydrodynamic conditions between flowing water bodies and enclosed water bodies.

Interaction between microalgae and phycosphere bacteria in a binary cultivation system-based dairy farm wastewater treatment

The combination of microalgal culture and wastewater treatment is an emerging topic. This study investigated the use of different microalgae to treat different types of dairy farm wastewater. The results showed that the removal of ammonia nitrogen and total phosphorus by mixed microalgae was over 99% and 80%, respectively. The highest production of protein in biomass and extracellular polymeric substances was observed in high-concentration wastewater. In the phycosphere, the abundance of Proteobacteria and Cyanobacteria increased, while that of Bacteroidota decreased. Phycosphere bacteria were strongly correlated with microalgal growth and the composition of extracellular polymeric substances, especially with bound extracellular polymeric substances relative to soluble extracellular polymeric substances. Genes associated with photosynthesis and respiration in phycosphere bacteria were upregulated, contributing to the material exchange capacity in the microalgal-bacterial systems. The interaction between microalgae and phycosphere bacteria thus represents the core of the binary cultivation system-based wastewater treatment and requires further investigation.

Microalgal production and nutrient recovery under mixotrophic mode using cheese whey permeate

Mixotrophic microalgal solutions are efficient nutrient recovery methods, with potential to prolong the cultivation seasons in temperate climates. To improve operation sustainability, the study used landfill leachate for nitrogen source and whey permeate for phosphorus and organic carbon. A non-axenic polyculture, dominated by green algae, was cultivated in mixotrophic mode on glucose or whey permeate compared to a photoautotrophic control in outdoor pilot-scaled raceway ponds during Nordic spring and autumn. The whey permeate treatment had the highest algal growth rate and productivity (0.48 d−1, 183.8 mg L−1 d−1), nutrient removal (total nitrogen: 21.71 mg L−1 d−1, total phosphorus: 3.05 mg L−1 d−1) and recovery rate (carbon: 85.19 mg L−1 d−1, nitrogen: 17.01 mg L−1 d−1, phosphorus: 2.58 mg L−1 d−1). When grown in whey permeate, algal cultures demonstrated consistent productivity and biochemical composition in high (spring) and low light conditions (autumn), suggesting the feasibility of year-round production in Nordic conditions.

Impact of Intercropping Five Medicinal Plants on Soil Nutrients, Enzyme Activity, and Microbial Community Structure in Camellia oleifera Plantations.

Intercropping medicinal plants plays an important role in agroforestry that can improve the physical, chemical, and biological fertility of soil. However, the influence of intercropping medicinal plants on the Camellia oleifera soil properties and bacterial communities remains elusive. In this study, five intercropping treatment groups were set as follows: Curcuma zedoaria/C. oleifera (EZ), Curcuma longa/C. oleifera (JH), Clinacanthus nutans/C. oleifera (YDC), Fructus Galangae/C. oleifera (HDK), and Ficus simplicissima/C. oleifera (WZMT). The soil chemical properties, enzyme activities, and bacterial communities were measured and analyzed to evaluate the effects of different intercropping systems. The results indicated that, compared to the C. oleifera monoculture group, YDC and EZ showed noticeable impacts on the soil chemical properties with a significant increase in total nitrogen (TN), nitrate nitrogen (NN), available nitrogen (AN), available phosphorus (AP), and available potassium (AK). Among them, the content of TN and AK in the rhizosphere soil of Camellia oleifera in the YDC intercropping system was the highest, which was 7.82 g/kg and 21.94 mg/kg higher than CK. Similarly, in the EZ intercropping system, the content of NN and OM in the rhizosphere soil of Camellia oleifera was the highest, which was higher than that of CK at 722.33 mg/kg and 2.36 g/kg, respectively. Curcuma longa/C. oleifera (JH) and Clinacanthus nutans/C. oleifera (YDC) had the most effect on soil enzyme activities. Furthermore, YDC extensively increased the activities of hydrogen peroxide and acid phosphatase enzymes; the increase was 2.27 mg/g and 3.21 mg/g, respectively. While JH obviously increased the urease activity, the diversity of bacterial populations in the rhizosphere soil of the intercropping plants decreased, especially the Shannon index of YDC and HDK. Compared with the monoculture group, the bacterial community abundance and structure of JH and YDC were quite different. The relative abundance of Actinobacteriota and Firmicutes was increased in YDC, and that of Acidobacteriota and Myxococcota was increased in JH. According to the redundancy analysis (RDA), pH, total potassium, and soil catalase activity were identified as the main factors influencing the microbial community structure of the intercropping systems. In conclusion, intercropping with JH and YDC increased the relative abundance of the dominant bacterial communities, improved the microbial community structure, and enhanced the soil nutrients and enzyme activities. Therefore, in the future, these two medicinal plants can be used for intercropping with C. oleifera.

Variation in foliar inorganic phosphorus concentrations in perennial ryegrass (Lolium perenne L.)

ABSTRACT Breeding ryegrass for reduced inorganic phosphorus (Pi) concentrations in leaf vacuoles could lower pasture P fertiliser requirements with economic and environmental benefits. We investigated foliar Pi% accumulation characteristics of a range of ryegrass cultivars and ecotypes in glasshouse experiments, and ryegrass cultivars from two field trials. Pi in ryegrass was also compared with Pi in cocksfoot, tall fescue, prairie grass and Phalaris in a glasshouse experiment. Pi expressed as a percentage of leaf total phosphorus was higher (average 82.5%) in the older ryegrass cultivars – Ruanui, and Nui and the New Zealand hill country ecotypes (85%) than in more recently bred cultivars like Aberdart and One50 (74.7%). In the other grass species, foliar Pi% was lowest in prairie grass, intermediate in tall fescue with the highest values in cocksfoot, Phalaris and ryegrass. The results suggest that including a lower Pi concentration in future ryegrass breeding programmes might improve ryegrass P use efficiency without compromising growth rates.

Spectral Characteristics of Dissolved Organic Matter in Sediments from Yuanhe River Basin

Dissolved organic matter （DOM） plays an important role in indicating the pollution of the water environment, and sediment is the main source of endogenous pollution of the water environment. Research on the spectral characteristics of DOM in sediments was important for the interpretation of water environment pollution. In this study, UV-visible absorption spectroscopy and three-dimensional fluorescence spectroscopy combined with the parallel factor analysis （PARAFAC） were used to analyze the fluorescent components, sources, and influencing factors of DOM in sediments from the Yuanhe River Basin. The results showed that the average of ω（TN）, ω（TP）, and ω（OM） in sediments from the Yuanhe River Basin were 0.52, 0.66, and 21.22 g·kg-1, respectively. The concentrations of total nitrogen and total phosphorus increased along the flow direction. In addition, the sediment DOM from the Yuanhe River Basin mainly originated from terrestrial sources. The chromophoric DOM concentration and aromaticity of DOM from the downstream reaches were significantly higher than those from the upstream and midstream reaches. Based on PARAFAC, four fluorescent components of DOM in sediments from the Yuanhe River Basin were identified, including three humus-like components （C1, C3, and C4） and one protein-like component （C2）. The sediment DOM was dominated by humus-like materials. Moreover, the fluorescent intensity of the fluorescent components was higher in the downstream reaches. Redundancy analysis revealed that the physicochemical properties of sediments in the mainstream and downstream reaches played a more significant role in the spectral properties of DOM. Phosphorus pollution and the terrestrial humus-like substance of sediment DOM were homologous. These results indicated that the spectral properties of DOM were the indicator of water environmental pollution in the region with strong anthropogenic influence.

Temporal-Spatial Fluctuations of a Phytoplankton Community and Their Association with Environmental Variables Based on Classification and Regression Tree in a Shallow Temperate Mountain River.

The effects of environmental factors on phytoplankton are not simply positive or negative but complex and dependent on the combination of their concentrations in a fluctuating environment. Traditional statistical methods may miss some of the complex interactions between the environment and phytoplankton. In this study, the temporal-spatial fluctuations of phytoplankton diversity and abundance were investigated in a shallow temperate mountain river. The machine learning method classification and regression tree (CART) was used to explore the effects of environmental variables on the phytoplankton community. The results showed that both phytoplankton species diversity and abundance varied fiercely due to environmental fluctuation. Microcystis aeruginosa, Amphiprora sp., Anabaena oscillarioides, and Gymnodinium sp. were the dominant species. The CART analysis indicated that dissolved oxygen, oxidation-reduction potential, total nitrogen (TN), total phosphorus (TP), and water temperature (WT) explained 36.00%, 13.81%, 11.35%, 9.96%, and 8.80%, respectively, of phytoplankton diversity variance. Phytoplankton abundance was mainly affected by TN, WT, and TP, with variance explanations of 39.40%, 15.70%, and 14.09%, respectively. Most environmental factors had a complex influence on phytoplankton diversity and abundance: their effects were positive under some conditions but negative under other combinations. The results and methodology in this study are important in quantitatively understanding and exploring aquatic ecosystems.