Water Nutrient Research Articles

Pelatihan Sistem Hidroponik Menggunakan Sampah Plastik untuk Meningkatkan Ekonomi dan Ketahanan Pangan

Tanjungrejo is located in the Sukun, Malang City, East Java. Some of the jobs of the people on Tanjung Putra Yudha 2 Street, Sukun, Malang City are scavengers and pedicab drivers. Since late 2019 there has been a COVID-19 pandemic caused by the SARS CoV-2 virus, which has caused more than 2.33 million deaths worldwide. The COVID-19 pandemic has caused family food availability to be insufficient and reduced family food, this also affects the economy in the form of a decrease in income but has a high enough expenditure every month to meet family food needs. Hydroponics is a technology used on critical land so that it can remain productive. Hydroponic systems can be used on plants that have the properties to utilize nutrients in water, examples of suitable vegetables include mustard greens, spinach, and kale. The hydroponic system can provide economic benefits from the harvest that can be sold or fulfill daily needs. This training was conducted in several stages, including pretest assessment, introduction to the hydroponic system, preparation of tools and materials, workmanship, mentoring, and evaluation in the form of a post-test. The results of the questionnaire filling were analyzed using the one group pretest-posttest method and obtained an average score of 30.7 pretest and 96.7 posttest. This shows that the training significantly increased participants' knowledge regarding the benefits of hydroponic systems.

Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed

Excess nutrients in surface water and groundwater can lead to water quality deterioration in available water resources. Thus, the classification of nutrient concentrations in water resources has gained significant attention during recent decades. Machine learning (ML) algorithms are considered an efficient tool to describe nutrient loss from agricultural land to surface water and groundwater. Previous studies have applied regression and classification ML algorithms to predict nutrient concentrations in surface water and/or groundwater, or to categorize an output variable using a limited number of input variables. However, there have been no studies that examined the application of different ML classification algorithms in agricultural settings to classify various output variables using a wide range of input variables. In this study, twenty-four ML classification algorithms were implemented on a dataset from three locations within the Upper Parkhill watershed, an agricultural watershed in southern Ontario, Canada. Nutrient concentrations in surface water were classified using geochemical and physical water parameters of surface water and groundwater (e.g., pH), climate and field conditions as the input variables. The performance of these algorithms was evaluated using four evaluation metrics (e.g., classification accuracy) to identify the optimal algorithm for classifying the output variables. Ensemble bagged trees was found to be the optimal ML algorithm for classifying nitrate concentration in surface water (accuracy of 90.9%), while the weighted KNN was the most appropriate algorithm for categorizing the total phosphorus concentration (accuracy of 87%). The ensemble subspace discriminant algorithm gave the highest overall classification accuracy for the concentration of soluble reactive phosphorus and total dissolved phosphorus in surface water with an accuracy of 79.2% and 77.9%, respectively. This study exemplifies that ML algorithms can be used to signify exceedance of recommended concentrations of nutrients in surface waters in agricultural watersheds. Results are useful for decision makers to develop nutrient management strategies.

Coupling of submerged macrophytes and epiphytic biofilms reduced methane emissions from wetlands: Evidenced by an antibiotic inhibition experiment

Wetlands are the largest natural methane source, but how submerged macrophytes affect methane emission remains controversial. In this study, the impacts of submerged macrophytes on methane fluxes, water purification, and epiphytic microbial community dynamics were investigated in simulated wetlands (with and without Hydrilla verticillata) treated with norfloxacin (NOR) for 24 days. Mean methane fluxes were significantly lower in treatments with Hydrilla verticillata (56.84–90.94 mg/m2/h) than bulks (65.96–113.21 mg/m2/h) (p < 0.05) during the experiment regardless of NOR. The relative conductivity (REC) values, H2O2, and malondialdehyde (MDA) contents increased in plant leaves, while water nutrients removal rates decreased with increasing NOR concentration at the same sampling time. The partial least squares path model analysis revealed that plant physiological indices and water nutrients positively affected methane fluxes (0.72 and 0.49, p < 0.001). According to illumina sequencing results of 16S rRNA and pmoA genes, α-proteobacteria (type II) and γ-proteobacteria (type I) were the dominant methanotroph classes in all epiphytic biofilms. The ratio of type I/type II methanotrophs and pmoA gene abundance in epiphytic biofilm was considerably lower in treatment with 16 mg/L NOR than without it (p < 0.05). pmoA gene abundance was negatively correlated with methane fluxes (p < 0.05). Additionally, the assembly of epiphytic bacterial community was mainly governed by deterministic processes, while stochastic dispersal limitation was the primary assembly process in the epiphytic methanotrophic community under NOR stress. The deterministic process gained more importance with time both in bacterial and methanotrophic community assembly. Network analysis revealed that relationships among bacteria in epiphytic biofilms weakened with time but associations among methanotrophic members were enhanced under NOR stress over time. It could be concluded that submerged macrophytes-epiphytic biofilms symbiotic system exhibited potential prospects to reduce methane emissions from wetlands under reasonable management.

Molecularly Imprinted Polymers for the Selective Recognition of Microcystins: An African Perspective

AbstractMicrocystins (MCs) are found in aquatic settings and have detrimental effects on both human and animal health. Their occurrence is influenced by the deposition of nutrients in water and further increased by high temperatures which favor the proliferation of harmful algal blooms (HABs). Climatic conditions in Africa favor the growth of HABs. Therefore, determination of MC contamination of African water sources is of paramount importance. The use of molecularly imprinted polymers (MIPs) for the adsorption of MCs has recently gained increasing interest in the selective and rapid determination of MCs in water. MIPs are ideal adsorbents for this purpose because of their versatility and environmental friendliness and thus have potential to replace conventional adsorbents such as activated carbon and silica composites. This review summarizes the occurrence of MCs in Africa as well as the detection and determination methods used for analysis. Secondly, common methods for the synthesis of MIPs are compared and their application and efficacy towards determination of MCs in water is investigated, with focus on the African continent. An assessment of current challenges and proposed solutions is also presented.

Cyanobacterial water blooms as an environmental hazard to waters

The article describes and analyzes the problem of cyanotoxin contamination of water bodies in Ukraine and other countries of the world. Eutrophication of water bodies, which is caused by human activity, climate change lead to uncontrolled development of cyanobacteria, and thus to ecological danger in hydrosphere objects. Anthropogenic eutrophication (increasing the content of nutrients in water due to their introduction into water bodies during pollution of water bodies by flood and municipal runoff, fish farming use of water bodies), temperature rise, increase in carbon dioxide content in the atmosphere, as a result of the transformation of introduced organic matter in water, contribute to increasing the dominance of cyanobacteria in water ecosystems. Bloomforming cyanobacteria produce various neurotoxins, hepatotoxins, and dermatotoxins that can be fatal to birds and mammals (including waterfowl, cattle, and dogs) and threaten the use of water bodies for public water supply, recreation, irrigation, and fishing. Among the toxins of blue-green algae, nodularin, saxitoxin, microcystin, domoic acid, guanitoxin, anatoxins and others were found. Exceeding the critical mass of algae and their metabolites activates the selfdecomposition process. This leads to the removal of oxygen from the water, and instead the release of methane, hydrogen sulfide, ammonia, and other toxic substances. The result of this is not only the death of fish. Cyanobacteria are capable of natural genetic transformation — genetic change of the cell as a result of direct absorption and inclusion of exogenous DNA from its environment. A sufficiently effective solution to the issue of controlling the activity of cyanobacteria is the use of humic preparations. it was established that humic substances (humic acids, fulvic acids) in certain concentrations negatively affect the growth, development and activity of cyanobacteria. Humic substances, as a component of organic matter and a reserve of organic carbon in its global cycle, have a negative effect on hydrobionts by increasing their concentration in water bodies. However, humic substances are able to regulate the activity of phytoplankton. The introduction of humic substances at a concentration of 2-5 mg/l of reservoir water significantly affects the activity of phytoplankton (suppresses phytoplankton vegetation, reduces the slime formation of cyanobacteria, and, from the beginning, inactivates the synthesis of cyanotoxins). This effect is provided by the alkaline pH of humates, high content of iron and copper.

Assessment of Water Quality Variations and Trophic State of the Joumine Reservoir (Tunisia) by Multivariate Analysis

North Tunisia’s Joumine reservoir provides water for drinking and agriculture irrigation purposes. Therefore, its water quality is crucial, especially with the recurrence of dry years in a global climate change context. This study aims to evaluate its environmental parameters, phytoplankton community structure, and trophic status. The data were newly analyzed using multivariate statistical methods and redundancy analysis (RDA) with the Trophic State Index (TSI) and Trophic State Index deviation (TSID). Monthly sampling occurred from May 2021 to June 2022 at eight stations. Water samples were collected to assess physical-chemical parameters and Chlorophyll-a, as well as to identify phytoplankton species. Three seasonal clusters of summer, autumn, and spring were identified. Water nutrient variations primarily resulted from point and non-point source contamination, along with natural processes. Carlson’s Trophic State Index (CTSI) indicates a eutrophic status for the Joumine reservoir. TSID indicated there was no algal turbidity in the reservoir. The study identified 25 phytoplankton taxa, with Chlorophyceae exhibiting high densities and diversities. RDA revealed that NO3−, NH4+, DO, pH, water flow, and water temperature were the most important environmental factors controlling phytoplankton structure in the Joumine reservoir. The outcomes of this study may provide helpful information to improve the management of the Joumine reservoir.

Silicon composition and stoichiometric ratios with other nutrients in the lower Minjiang River, Southeast China.

Over the past decades, rivers have delivered imbalanced nutrient loads to coastal marine ecosystems due to human activities, which leads to serious regional or global eutrophication problems. The Minjiang River is heavily influenced by human activities. To understand the changing characteristics of nutrient transport ratios in the Minjiang River waters, we measured the seasonal variations of carbon, nitrogen, phosphorus and silicon nutrients in the lower surface waters of the Minjiang River between July 2019 and July 2020. The results showed that the annual average contents of dissolved silicon (DSi), lithogenic silicon (LSi) and biogenic silicon (BSi) in the surface waters of the lower Minjiang River were 5.30, 4.58 and 2.37 mg·L-1, respectively. There were large seasonal differences among these parameters, with higher content of DSi than LSi and BSi in summer, higher content of DSi than BSi and LSi in autumn and higher content of LSi than DSi and BSi in winter. The proportions of DSi in total silicon tended to decrease gradually from land to sea, while the proportion of BSi was on the contrary. In term of stoichiometric ratios, the Minjiang River mostly presented carbon or phosphorus limitation and was unlimited by silicon or nitrogen. About 1.03×1010 mol DSi and 0.46 ×1010 mol BSi were delivered via the Minjiang River to the ocean yearly, showing a decreasing trend year by year. Based on the data in recent years, the nutrient loads of carbon, nitrogen, and phosphorus transported by Minjiang River showed an increasing trend. The imbalanced nutrient loads may lead to changes in the structure and function of the river, estuary, and offshore ecosystems. The study of nutrient stoichiometric ratios can provide a theoretical basis for solving the problems in structural balance of nutrients and eutrophication in Minjiang River estuary and adjacent marine waters.

Novel insight into ammonium, phosphate, and iron(II) dynamics in the sediment porewater of a constructed wetland under artificial aeration through the diffusive equilibrium in thin films technique

The analysis of porewater concentrations in constructed wetland sediments could help to understand biogeochemical processes, the sources and sinks of nutrients, and their effect on overlying water quality. In this study, we measured high-resolution porewater concentration profiles of ammonium (NH4+-N), nitrate (NO3N), phosphate (PO43--P), and ferrous iron (Fe(II)) in-situ in the Laratinga constructed wetland in Mount Barker (South Australia) using diffusive equilibration in thin films (DET) techniques. Measurements were taken under light and dark conditions, and non-aerated and aerated conditions to determine the effect on sediment porewater nutrient concentrations. Baseline surface water nutrient concentrations (NH4+-N > 36 mg L-1, PO43--P > 0.43 mg L-1) greatly exceeded water quality guideline criteria. Aeration of the water column alleviated night-time hypoxic conditions (i.e. dissolved oxygen increased from a minimum of 0.7 mg L-1 to a minimum of 4 mg L-1), and increased the redox potential in the sediment. Significant differences were present for NH4+-N, PO43--P, and Fe(II) concentrations with depth in the sediment. Ammonium concentrations in the sediment reduced under aerated conditions, presumably due to enhanced nitrification. However it was observed that PO43--P and Fe(II) concentrations increased significantly with aeration, especially under dark conditions, and were strongly correlated (R2>0.8). This was not what was hypothesised and points to complex interactions between Fe and P in the sediment. Nitrate concentrations in the sediment were below the detection limit (<0.9 mg L-1) which suggests limited nitrification-denitrification is occurring. Overall the results suggest that DET techniques are useful tools for quantifying porewater concentrations of nutrients in constructed wetlands under various environmental conditions.

Characterisation of a low methane emission rice cultivar suitable for cultivation in high latitude light and temperature conditions

Rice cultivation on paddy soil is commonly associated with emissions of methane, a greenhouse gas, but rice varieties may differ in their actual level of emissions. This study analysed methane emissions associated with 22 distinct rice genotypes, using gas chromatography, and identified the cultivar Heijing 5 from northern China as a potential low-methane rice variety. To confirm this and to examine whether Heijing 5 can perform similarly at higher latitudes, Heijing 5 was cultivated in field trials in China (lat. 32° N) and Sweden (lat. 59° N) where (i) methane emissions were measured, (ii) methanogen abundance in the rhizosphere was determined using quantitative PCR, and (iii) the concentrations of nutrients in water and of heavy metals in rice grain and paddy soil were analysed. The results demonstrated that the low-methane rice cultivar Heijing 5 can successfully complete an entire growth period at high-latitude locations such as central Sweden. Massively parallel sequencing of mRNAs identified candidate genes involved in day length and cold acclimatisation. Cultivation of Heijing 5 in central Sweden was also associated with relatively low heavy metal accumulation in rice grains and lowered nutrient losses to neighbouring water bodies.

SEDIMENT TRANSPORT ESTIMATION FROM HYDROLOGICAL AND AUTOREGRESSIVE MODELS

Hydrologic modeling allows the simulation of runoff and sediment processes, which are applied in integrated watershed management, soil and water nutrients, among others. However, these models require considerable amounts of input data. Sediment data is often lacking in quantity and quality, which leads to uncertainty in hydrological models. The objective of the present study was to propose a methodological alternative based on sediment time series in the Santa Cruz de Aquismón sub-basin, San Luis Potosí, Mexico, by means of autoregressive integrated moving average models (ARIMA) and the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated with measured flows from the National Surface Water Data Bank (BANDAS) of station 26 241 (Ballesmi). Model calibration and validation performance was assessed with Nash-Sutcliffe Coefficient (NSE), percent bias (PBIAS), and the root mean squared error (RMSE). The SWAT model fit was rated as very good. The hydrologic model results were compared to the daily sediment estimates from three months in 1985 (June, September, and November) obtained from ARIMA models. The mean absolute percent error (MAPE) was 0.571, 0.168, and 0.029, respectively. The results indicated that the use of the ARIMA model for sediment estimation is useful when there are short time series with limited information, since it allows the completion of missing data series or short-term estimates.

Local environmental variables outperform spatial and land use pattern in the maintenance and assembly of phytoplankton communities in the wetland cluster

Phytoplankton is a crucial primary producer in wetland ecosystems and is highly sensitive to changes in water quality. It has long been considered one of the most important biological indicators for monitoring water pollution. However, our understanding of the various aspects of phytoplankton communities assembly and the factors driving them remains limited. In this study, we conducted collection and analysis of phytoplankton samples from a temperate wetland cluster encompassing both lake and marsh types under the backdrop of industrial pollution from the petroleum industry. Our aim was to investigate the influence of spatial factors, land use patterns, and local environmental variables on the taxonomic and functional structure of the phytoplankton community, utilizing structural equation modeling (SEM) and variation partitioning. Our results revealed that environmental filtering exerts a greater relative impact on shaping the taxonomic composition of phytoplankton compared to mass effects. Human activities, such as industrial and agricultural production, can lead to landscape modifications that increase water nutrient levels and consequently influence the community composition. Taxonomic beta diversity is determined by both mass effects and environmental filtering. In contrast, functional beta diversity responds more to local environmental gradients, while the land use pattern was not important for facets of beta diversity in the wetland cluster. These results validate the concordance and complementarity between functional and taxonomy-based biome structures, highlighting the significance of integrating multiple ecological drivers. The results of this study contribute to a deeper understanding of wetland community assembly and the processes of biogeography, and are of crucial significance for the biological monitoring and management of freshwater ecosystem environmental pollution.

Exploring the Drivers of Spatiotemporal Patterns in Fish Community in a Non-Fed Aquaculture Reservoir

Non-fed aquaculture is an important contributor to low environmental impact protein production. However, knowledge of spatiotemporal patterns of the fish community in non-fed fishery systems remains limited, despite their ecological importance for sustainable aquaculture and fisheries. To elucidate the status of the fisheries and their critical drivers in non-fed fishery systems, hydroacoustic surveys were conducted seasonally in Hongchaojiang Reservoir in two seasons (spring and autumn) of two consecutive years: 2018 and 2019. Results showed that the average fish density in Hongchaojiang Reservoir was 121.6 ind./1000 m3. Fish communities varied significantly between geographical locations and seasons. On the temporal scale, fish densities in October were higher than those in April. On the spatial scale, fish densities were higher in the upstream (S1 and S3) than those in the midstream (S2, S4, S5, S6), while the density of S7, S8 and S9 in the downstream was the lowest. Trophic level index, zooplankton, chlorophyll-a, and phytoplankton play vital roles in fish distributional patterns, while the target strength, which reflects fish body size, was highly associated with water temperature, dissolved oxygen, total organic carbon, and phytoplankton. These results suggest that the spatiotemporal distribution of the fish community in Hongchaojiang Reservoir was jointly influenced by biotic and abiotic variables of water bodies, and highlight the importance of water nutrient levels and food availability in shaping fish distribution in the non-fed aquaculture system. This study should improve our understanding of ecological patterns and dominant drivers in fish stocks and provide information for successful sustainable management in non-fed purification fisheries.

EFFECT OF TOMATO PLANT DENSITY ON AQUAPONIC SYSTEM PRODUCTION

The need to increase food production and match the food security demands under climate change impacts generate the force for developing aquaponic system. An aquaponic system was established at the Central Laboratory for Agricultural Climate (CLAC), Egypt, to investigate the effect of tomato plant density (2, 4 and 6 plants / m2) on tomato and fish production as well as the quality of rare water. Nutrient film technique (3 m length) used to produce tomato integrated with aquaculture of tilapia fish. Vegetative growth characteristics and yield parameters of Tomato as well as tilapia yield parameters plus the nutrient contents of rare water were recorded. The revealed results indicated that increasing the tomato plant density from 2 up to 6 plants / m2 led to a decrease in the No. of leaves, total leaves area and plant height of tomato. The early and total yield of tomato per plant significantly increased by decreasing the plant density from 6 to 4 and 2 plants /m2. On the contrary, the highest total yield per m2 was given by tomato density 6 plants. Tilapia average weight of (g), tilapia total yield (Kg/m3), average daily gain (ADG) and specific growth rate % (SGR) results increased significantly by increasing the plant density of tomato from 2 and 4 up to 6 plants / m2. Increasing the tomato plant density led to decrease significantly NO3, P, K, Ca and Mg (ppm) values of fish rare water content during the season period due to increasing the removal of nutrients for tomato sake. The accumulation of nutrients in rare fish water increased by increasing the growth of fish tilapia. The highest results of NO3, P, K, Ca and Mg were recorded by tomato plant density 2 plants /m2 while 6 plants /m2 had the lowest nutrient contents. For sustainable food production, the study recommended the plant density of tomato 6 plants /m2. 18 tomato plants in 3 m NFT system length (6 plants/m2) integrated with 150 tilapia fish in 1 m3.

Effect of cage culture on sedimentary heavy metal and water nutrient pollution: Case study in Sansha Bay, China

The aquaculture area in China's coastal waters has increased rapidly from 6000 km2 in 1990 to 22,000 km2 in 2020. Despite extensive research regarding the effect of coastal aquaculture on water and sediment pollution, evaluating the quantitative relationship between aquaculture and pollutants remains challenging. Sansha Bay, the world's largest cage aquaculture base for Pseudosciaena crocea, is a typical enclosed bay used for investigating aquaculture pollution. A cage culture database is established from 2000 to 2020 in Sansha Bay. Meanwhile, 236 sediment samples from 3 sediment cores and 67 water samples from 4 transects are obtained from the bay for experiments. The main indicators are five nutrients (NO3−, SiO32−, PO43−, NH4+, and NO2−) in the water samples, the grain size, the heavy metal (Zn, Cu, Pb, Cr, Cd, and As) content, and the 210Pb radioactivity in sediment samples. Based on data obtained and a new calculation method, the annual increment in Zn, Cu, As, Cd, Pb, and Cr contents in the cultured zone is shown to increase by 2137 %, 1881 %, 506 %, 300 %, 202 %, and 118 % in 2000–2018, respectively, as compared with the levels in a noncultured zone. The activities of the cage culture increased NO3− by 9 %, PO43− by 30 %, NH4+ by 115 %, and NO2− by 232 %, compared with natural conservative mixing processes, such as the mixing of SiO32−, in 2020. A novel quantitative approach with broad applicability is proposed to evaluate the magnitude of anthropogenically induced environmental contamination. The effectiveness of the proposed technique is demonstrated through a case study conducted in Sansha Bay, China.

Non-Point Sources (Septic Tanks) of Surface Water Nutrient Pollution: A Review and a Study of Taylor Creek, Okeechobee County, Florida

This study investigated the impact of high-density septic systems (aka Onsite Sewerage and Disposal Systems, OSTDS) along the canals located in the communities of the lower Taylor Creek area on water quality at the northern periphery of Lake Okeechobee. Using sucralose as an anthropogenic tracer, we investigated the septic derived non-point sourcing of nutrients which feed harmful algal (cyanobacterial) blooms (HABs) in Lake Okeechobee and adjacent waters. &#x0D; &#x0D; The subdivisions investigated were Treasure Island (TI) and Taylor Creek Isles (TCI) located to the east and west of Taylor Creek. TI homes are all on septic tanks whereas TCI is serviced by a municipal vacuum sewerage system.&#x0D; &#x0D; TI canals had 5.3 times the mean concentration of sucralose relative to TCI canals. On a yearly basis, the Treasure Island sites away from Taylor Creek had 2.25 times the total phosphorus and 1.20 times the total nitrogen compared to the Taylor Creek isles sites. An extensive literature review of non-point pollution is included.

Accumulation and transport of nutrient and pollutant elements in riparian soils, sediments, and river waters across the Thames River Watershed, Connecticut, USA

Understanding drivers of nutrient and pollutant elements (NPEs) in soils, sediments, and river water is important for protecting water resources and aquatic ecosystems. The objectives of this study were to quantify accumulation and transport of NPEs (P, As, Cd, Cu, Ni, Pb, and Zn) in riparian soils, sediments, river water, and watershed-scale exports within seven post-industrial subwatersheds of the Thames River, Connecticut, USA. Suspended sediments and river water samples were collected from February 2019 to January 2020. Arsenic concentrations in soil (6 to 18 mg kg−1) and sediments (8 to 85 mg kg−1) generally exceeded state and federal EPA quality targets but not river water. Elevated Pb ‘hot spots’ occurred in some riparian soils (>2000 mg kg−1) and sediments (>200 mg kg−1), but the other NPEs concentrations were below toxic thresholds. Riparian soil concentrations and watershed land cover were generally weak predictors for NPE concentrations in bottom sediments, suspended sediments, and river water. DOC, Mn, and Fe concentrations were important predictors for area-normalized dissolved and sediment-bound export of NPEs across the seven watersheds. Dissolved export was greater than sediment export for Mn, P, As, Cd, Cu, and Ni but not for Fe, Pb, and Zn. Watersheds with higher farmland had higher P river water concentrations, but the larger, more urbanized watershed had the highest total and area-normalized P export. An estuarine sediment core that captures sediment from the whole watershed and spans pre-industrial conditions through present shows that export of most NPEs has decreased since its peak, but all remain above baseline throughout the Thames River watershed. Future constraints on surface soil-river exchange and erosion inputs are needed to investigate rates of NPE sourcing to the watersheds.

Coastal nutrient enrichments facilitated reproductive output in exotic mangrove species over two decades

Litterfall may facilitate the outperformance of exotic species by inducing better resource acquisition and reproductive performance. However, the drivers that determine litterfall patterns in exotic and native species have remained insufficiently investigated due to the lack of long-term observations. Here, we employed empirical dynamic modeling on a two-decade-long litterfall observation (1999–2019) in a subtropical mangrove forest in Shenzhen, China, to evaluate the relative importance of environmental drivers on different species. We found that mangrove leaf litterfall in both exotic and native species was strongly altered by temperature, and the causal relationship was stronger in the dominant exotic species Sonneratia apetala compared to native species. However, the main driver of reproductive output differed largely between exotic and native species; temperature was the main cause of native reproduction, whereas coastal nutrients drove the reproductive output of exotic species. Our study highlighted that high nutrient availability in Shenzhen Bay in the past decade allowed the exotic species S. apetala to gain better reproductive output than native species. We imply that enriched nutrients in coastal water likely contributed to exotic dominance in China’s coastal mangrove forest.

Content and dynamics of nutrients in the surface water of shallow Lake Mulehe in Kisoro District, South–western Uganda

The purpose of this study was to investigate the content and dynamics of nutrients in the shallow (max. 6 m) Lake Mulehe. We collected 54 water samples from nine sampling stations between the wet season (March–May 2020 and dry season (June–August 2020). Nutrients; ammonia–nitrogen (NH4–N), nitrate–nitrogen (NO3–N), nitrite–nitrogen (NO2–N), total nitrogen (TN), total phosphorus (TP) and soluble reactive phosphorus (SRP) were investigated in accordance with APHA 2017 standard procedures. Besides, physical parameters: Temperature, pH, turbidity, electrical conductivity and dissolved oxygen were measured in situ. The water quality index (WQI) was used to determine the water quality of Lake Muhele using drinking water quality standards developed by the Uganda National Bureau of Standards and the World Health Organization. Results indicated that nutrients (TN, NO3–N, TP, NH4-N, NO2–N and SRP) did not differ substantially between study stations (p > 0.05) but did reveal significant differences (p < 0.05) across study months. Besides, nutrient levels differed significantly between seasons (p < 0.05) except for SRP and NH4–N. The WQI values varied from 36.0 to 74.5, with a mean of 58.69. The recorded overall WQI value places Lake Mulehe’s water quality into the ‘poor’ category in terms of worthiness for human consumption. The study, therefore, recommends continuous pollution monitoring and enforcement of local regulations to reduce pollution in the lake as a result of anthropogenic activities.

In-situ catalytic bio-oil production from hydrothermal liquefaction of Cu-impregnated water hyacinth: Screening of reaction parameters

The rapid growth of water hyacinth (WH) is a major concern worldwide as it adversely affects the aquatic world's life by lowering the oxygen level or depleting the water's nutrients. In this study, the hydrothermal liquefaction of WH was performed by impregnating it with Cu and Co to enhance bio-oil production. It has been found that the Cu-impregnated-WH exhibited a high bio-oil yield in comparison to Co-impregnated-WH. The influence of reaction parameters e.g., reaction residence time, temperature, and the biomass-to-water ratio were also screened to achieve the maximum liquefaction. Further, the water-to-biomass ratio significantly tailored the bio-oil yields. It has been found that 0.2M-Cu-impregnated-WH with a 1:9 biomass-to-water ratio and 270 °C/30 min were the best-optimized conditions for the highest total bio-oil yield (41 wt%) and conversion (83%). The isolated optimum bio-oils were characterized by the GC-MS analysis to ascertain the composition of compounds that attributed to the maximum area% of N-containing and phenolics compounds. The maximum amount of both types of bio-oils was found to be high from the liquefaction of Cu-impregnated WH compared to non-catalytic. Moreover, the char was characterized by XRD, FT-IR, and TEM analysis, which confirmed the breaking of linkages of WH, and the presence of Cu in the form of CuO. The findings of the study clearly signify the potential of WH for sustainable energy production and the char obtained can be used for various other applications.

Types and Distribution of Macroinvertebrates Stressed by Heavy Metals in Mangrove Forests

Heavy metals can decrease the number of species in nature. This research aims to determine the relationship between the type of macroinvertebrates stressed by heavy metals in the Wonorejo Mangrove Area, Surabaya, East Java. This type of research is observational. The determination of stations was done using the purposive random sampling method. Tests for Pb and Cd content were carried out using the AAS method. Nutrient content testing was carried out using the AAS and Kjeldahl methods. Data analysis was presented descriptively, and multivariate analysis was done using Principal Component Analysis (PCA). Based on the present research, it can be concluded that there are variations in the type and distribution of macroinvertebrates stressed by heavy metals in the mangrove area of Surabaya. Station 1 is dominated by Ocypode ryderi, Station 2 by Assiminea sp., Station 3 by Scylla paramamosain, and Station 4 by Cerithidea sp. with the high presence of metals (Cd, Pb), and soil and water nutrients (Org-C, N) at Stations 1, 3, and 4. The Station 2 has only Pb. Assiminea sp. (Phylum Mollusca) can be the best candidate for metal bioindicators because it appears in all locations where soil and water have been contaminated with Pb and Cd metals without affecting their life.