Components Of Aquatic Ecosystems Research Articles

Comparing Sediment Bacterial Communities of Volcanic Lakes and Surrounding Rivers in Inner Mongolia Autonomous Region, Northeastern China.

Volcanic lakes originate from a volcanic crater or caldera, and were a crucial component of aquatic ecosystems. Sediment bacteria play an important role in the nutrient cycling of aquatic ecosystems; however, their patterns distribution in volcanic lakes and the surrounding river habitats are unknown. In this study, we compare the sediment bacterial communities and their co-occurrence networks between these two habitats in the Inner Mongolia Autonomous Region, Northeastern China (the Arxan UNESCO Global Geopark), using 16S rRNA gene amplicon sequencing. The results revealed that there were significant variations in the physicochemical parameters of the sediment between these two habitats. The bacterial α-diversity, β-diversity, and community composition of the sediment also significantly differed between these two habitats. Network analysis showed that the co-occurrence patterns and keystone taxa in the sediment differed between these two habitats. The sediment bacterial communities in the river habitats were more stable than those in the lake habitats in the face of environmental change. Canonical correspondence analysis demonstrated that both physical (pH and MC) and nutrition-related factors (TN, TP, LOI, and TOC) were the most important environmental factors shaping the variations of bacterial community composition (BCC) in the sediment between these two habitats. This work could greatly improve our understanding of the sediment BCC of the sediment from aquatic ecosystems in the UNESCO Global Geopark.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using “extended Local Similarity Analysis” and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

Seasonal toxicity of urban road dust in runoff process-studies in Poland

Urban road dust (URD) is one of the most important non-point sources of pollution in agglomerations. The aim of this study was to assess the seasonal toxic effects of URD runoff in two regions of Poland. The concentrations of elements in URD and leachate were studied. The impact of pollutants in URD runoff on water organisms was evaluated using Daphtoxkit F and Rotoxkit F (LC50). The acute toxicity tests for crustaceans and rotifers were selected as the response of these taxa reflects the impact on zooplankton, a key component of aquatic ecosystem and the basis of most food webs. The concentrations of elements were found to vary depending on the site, although URD samples collected in Katowice agglomeration (Upper Silesia) had higher values of elements (Mn, Cu, Zn, As) compared to Wrocław (Lower Silesia). The concentrations of Mn, Zn, As, Cr, and Mg in water-soluble fraction of URD were higher in summer and winter in the Upper Silesia region due to rainwater runoff resulting from traffic, industries, post-industrial waste, and the presence of old heating systems. When comparing the content of elements in the water-soluble fraction between seasons, Zn, As, Cr, and Al concentrations were slightly higher in winter. The highest mortality of Daphnia magna and Brachiouns calyciflorus was observed in URD from both agglomerations in winter. However, the mortality is likely due to the concentration of elements or/and the coexistence of an unknown compound or a synergistic effect of the studied elements. This study highlights the alarming seasonal sources of elements in URD runoff, which will directly enter the food chain and affect the entire ecosystem, and human health.

CoSFISH: a comprehensive reference database of COI and 18S rRNA barcodes for fish.

Fish, being a crucial component of aquatic ecosystems, holds significant importance from both economic and ecological perspectives. However, the identification of fish at the species level remains challenging, and there is a lack of a taxonomically complete and comprehensive reference sequence database for fish. Therefore, we developed CoSFISH, an online fish database. Currently, the database contains 21 535 cytochrome oxidase I sequences and 1074 18S rRNA sequences of 21 589 species, belonging to 8 classes and 90 orders. We additionally incorporate online analysis tools to aid users in comparing, aligning and analyzing sequences, as well as designing primers. Users can upload their own data for analysis, in addition to using the data stored in the database directly. CoSFISH offers an extensive fish database and incorporates online analysis tools, making it a valuable resource for the study of fish diversity, phylogenetics and biological evolution. Database URL: http://210.22.121.250:8888/CoSFISH/home/indexPage.

Isolation of freshwater protozoan from Gomti river, Lucknow

Freshwater protozoa are integral components of aquatic ecosystems, playing crucial roles in nutrient cycling, energy flow and microbial community dynamics. Protozoa also plays vital role in food chain. The environmental condition in which protozoa can live and multiply, there is always an optimum range for each group. In this study total 7 sites were selected for water samples collection from different regions of Lucknow. During this study, total 16 species of protozoa are observed like Amoeba, Paramecium, Vorticella etc. The identification is made on the basis of the body shape, size, type of locomotion, and structure of macro and micro nucleus. With the help of recent study, we highlighted the taxonomic diversity of freshwater protozoa, including ciliates, flagellates, amoebae and sporozoans in Gomti River, Lucknow.

Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to follow and understand these changes. Advances in imaging technology have enabled novel possibilities to study plankton populations, but the manual classification of images is time consuming and expert-based, making such an approach unsuitable for large-scale application and urging for automatic solutions for the analysis, especially recognizing the plankton species from images. Despite the extensive research done on automatic plankton recognition, the latest cutting-edge methods have not been widely adopted for operational use. In this paper, a comprehensive survey on existing solutions for automatic plankton recognition is presented. First, we identify the most notable challenges that make the development of plankton recognition systems difficult and restrict the deployment of these systems for operational use. Then, we provide a detailed description of solutions found in plankton recognition literature. Finally, we propose a workflow to identify the specific challenges in new datasets and the recommended approaches to address them. Many important challenges remain unsolved including the following: (1) the domain shift between the datasets hindering the development of an imaging instrument independent plankton recognition system, (2) the difficulty to identify and process the images of previously unseen classes and non-plankton particles, and (3) the uncertainty in expert annotations that affects the training of the machine learning models. To build harmonized instrument and location agnostic methods for operational purposes these challenges should be addressed in future research.

Seasonal Variation, Diversity, and Composition of Planktons in the Ganga River

Plankton are important components of aquatic ecosystems because they contribute to primary production, which sustains fisheries and other ecosystem functions. The study was carried out over a one-year period at three Ganga River sites: Haridwar (Bhadrabad) site A1, Bijnor (Balawali) site A2, and Muzaffarnagar (Bairaj Ganga bridge) site. Bacillariphyceae made almost 65% of the phytoplankton at location A1 14% Chlorophyceae and 14% Cynophyceae. The zooplankton consisted of Protozoa (80%) and Cladocera (20%), with Ulvophyceae accounting for 7%. At location A2, the phytoplankton composition was Bacillariphyceae (79%) and Chlorophyceae (7%). ˃ Cynophyceae (7%). Ulvophyceae (7%), and zooplankton were Protozoa (80%), Rotifera (20%). At location A3, the phytoplankton mix shifted to Bacillariphyceae (70%). ˃ Chlorophyceae (18%) ˃ Cynophyceae (12%) and Protozoa (60%) Rotifera accounts for 40%. The Simpson diversity index (D) value for phytoplankton is 0.58, whereas for zooplankton, the value is 0.53. The mean plankton density at locations A1, A2, and A3 was 2059, 2959, and 3304 individuals per liter, respectively. Only dissolved oxygen in physicochemical characteristics correlated positively with plankton density; all other metrics correlated negatively.

Synergistic digestibility effect by planktonic natural food and habitat renders high digestion efficiency in agastric aquatic consumers

A digestibility enhancing effect of natural food on stomachless fish model (Cyprinus carpio) was verified by fluorogenic substrate assays of enzymatic activities in experimental pond carp gut flush and planktonic food over a full vegetative season. Then compared with size-matched conspecific grown artificially (tank carp) and an advanced omnivore species possessing true stomach (tilapia, Oreochromis niloticus). Results suggested activities of digestive enzymes (except amylolytic) were significantly higher in pond carp (p ≤ 0.05) than in the size-matched tank carp. Even compared to tilapia, pond carp appeared superior (p < 0.05; proteolytic or chitinolytic activities) or comparable (p > 0.05; phosphatase or cellulolytic activities). Amylolytic, chitinolytic, and phosphatases activities in pond carp gut significantly increased (p ≤ 0.01) over season. Several orders-of-magnitude higher enzymatic activities were detected in planktonic natural food than expressed in carp gut. Amino acid markers in planktonic food revealed a higher share of zooplankton (microcrustaceans), but not phytoplankton, synchronized with higher activities of complex polysaccharide-splitting enzymes (cellulolytic and chitinolytic) in fish gut. Periods of clear water phase low in chlorophyll-a and nutrients, but high in certain zooplankton (preferably cladocerans), may create a synergistic digestibility effect in pond carp. We conclude aquatic ecosystem components (natural food, water, microbiota) enhance fishes' hydrolyzing capabilities of C/N/P macromolecules and even their complex polymers such as cellulose, chitin, and maybe phytate (to be validated), to the extent that being stomachless is not an issue. Aquatic nutritional ecologists may consider that laboratory-based understandings of digestibility may underestimate digestion efficiency of free-ranging fish in ponds or lakes.

Impact of Nuclear Pollution on the Population and Diversity of Plankton

Plankton, as a crucial component of aquatic ecosystems, plays a key role in maintaining ecological balance with its population and diversity. However, with the increase in human activities, the emission of nuclear waste, and the frequency of nuclear accidents, the issue of nuclear pollution has become increasingly severe, posing a significant threat to the living environment of plankton. The primary sources of nuclear pollution are the discharge of nuclear waste and leaks from nuclear power plant accidents. These radioactive substances dissolve in water and emit radiation, causing severe damage to the aquatic ecosystem. Plankton, such as algae and protozoa, due to their characteristics, are more susceptible to radiation. The impact of nuclear pollution on the population and diversity of plankton is evident. To protect the balance of aquatic ecosystems, it's necessary to strengthen the management and regulation of nuclear pollution, reduce the discharge of nuclear waste, and lower the risk of nuclear accidents. Also, for water bodies already affected by nuclear pollution, effective purification measures should be taken to restore the health of the aquatic ecosystem.

Deep-Learning-Based Automatic Extraction of Aquatic Vegetation from Sentinel-2 Images—A Case Study of Lake Honghu

Aquatic vegetation is an important component of aquatic ecosystems; therefore, the classification and mapping of aquatic vegetation is an important aspect of lake management. Currently, the decision tree (DT) classification method based on spectral indices has been widely used in the extraction of aquatic vegetation data, but the disadvantage of this method is that it is difficult to fix the threshold value, which, in turn, affects the automatic classification effect. In this study, Sentinel-2 MSI data were used to produce a sample set (about 930 samples) of aquatic vegetation in four inland lakes (Lake Taihu, Lake Caohai, Lake Honghu, and Lake Dongtinghu) using the visual interpretation method, including emergent, floating-leaved, and submerged vegetation. Based on this sample set, a DL model (Res-U-Net) was used to train an automatic aquatic vegetation extraction model. The DL model achieved a higher overall accuracy, relevant error, and kappa coefficient (90%, 8.18%, and 0.86, respectively) compared to the DT method (79%, 23.07%, and 0.77) and random forest (78%,10.62% and 0.77) when utilizing visual interpretation results as the ground truth. When utilizing measured point data as the ground truth, the DL model exhibited accuracies of 59%, 78%, and 91% for submerged, floating-leaved, and emergent vegetation, respectively. In addition, the model still maintains good recognition in the presence of clouds with the influence of water bloom. When applying the model to Lake Honghu from January 2017 to October 2023, the obtained temporal variation patterns in the aquatic vegetation were consistent with other studies. The study in this paper shows that the proposed DL model has good application potential for extracting aquatic vegetation data.

Estimating the Colored Dissolved Organic Matter in the Negro River, Amazon Basin, with In Situ Remote Sensing Data

Dissolved organic matter (DOM) is a crucial component of continental aquatic ecosystems. It plays a vital role in the carbon cycle by serving as a significant source and reservoir of carbon in water. DOM provides energy and nutrients to organisms, affecting primary productivity, organic composition, and the food chain. This study presents empirical bio-optical models for estimating the absorption of colored dissolved organic matter (aCDOM) in the Negro River using in situ remote sensing reflectance (Rrs) data. Physical–chemical data (TSS, DOC, and POC) and optical data (aCDOM and Rrs) were collected from the Negro River, its tributaries, and lakes and empirical relationships between aCDOM at 440 nm, single band, and the ratio bands of Rrs were assessed. The analysis of spectral slope shows no statistically significant correlations with DOC concentration or aCDOM absorption coefficient. However, strong relationships were observed between DOC and aCDOM (R2 = 0.72), aCDOM and Rrs at 650 nm (R2 &gt; 0.80 and RMSE &lt; 1.75 m−1), as well as aCDOM and the green/red band ratio (R2 &gt; 0.80 and RMSE &lt; 2.30 m−1). aCDOM displayed large spatial and temporal variations, varying from 1.9 up to 20.1 m−1, with higher values in rivers of the upper course of the Negro basin and lower values in rivers with total solids suspended &gt; 10 mg·L−1. Environmental factors that influence the production of dissolved organic matter include soil type, dense forest cover, high precipitation, and low erosion rates. This study demonstrated that aCDOM can serve as an indicator of DOC, and Rrs can serve as an indicator of aCDOM in the Negro basin. Our findings offer a starting point for future research on the optical properties of Amazonian black-water rivers.

Analysis of diversity and function of epiphytic bacterial communities associated with macrophytes using a metagenomic approach

Epiphytic bacteria constitute a vital component of aquatic ecosystems, pivotal in regulating elemental cycling. Despite their significance, the diversity and functions of epiphytic bacterial communities adhering to various submerged macrophytes remain largely unexplored. In this study, we employed a metagenomic approach to investigate the diversity and function of epiphytic bacterial communities associated with six submerged macrophytes: Ceratophyllum demersum, Hydrilla verticillata, Myriophyllum verticillatum, Potamogeton lucens, Stuckenia pectinata, and Najas marina. The results revealed that the predominant epiphytic bacterial species for each plant type included Pseudomonas spp., Microbacterium spp., and Stenotrophomonas rhizophila. Multiple comparisons and linear discriminant analysis effect size indicated a significant divergence in the community composition of epiphytic bacteria among the six submerged macrophytes, with 0.3–1% of species uniquely identified. Epiphytic bacterial richness associated with S. pectinata significantly differed from that of both C. demersum and H. verticillata, although no significant differences were observed in diversity and evenness. Functionally, notable variations were observed in the relative abundances of genes associated with carbon, nitrogen, and phosphorus cycling within epiphytic bacterial communities on the submerged macrophyte hosts. Among these communities, H. verticillata exhibited enrichment in genes related to the 3-hydroxypropionate bicycle and nitrogen assimilation, translocation, and denitrification. Conversely, M. verticillatum showcased enrichment in genes linked to the reductive citric acid cycle (Arnon-Buchanan cycle), reductive pentose phosphate cycle (Calvin cycle), polyphosphate degradation, and organic nitrogen metabolism. In summary, our findings offer valuable insights into the diversity and function of epiphytic bacteria on submerged macrophyte leaves, shedding light on their roles in lake ecosystems.

Freshwater fish diversity and IUCN Red List status of glacial-fed (Bheri) and spring-fed (Babai) rivers in the wake of inter-basin water transfer

Freshwater fish are crucial components of aquatic ecosystems that are affected by a range of anthropogenic activities. Freshwater bodies in Nepal are under different threats affecting biodiversity. Inter-basin water transfer (IBWT) involving damming and diversion of water from one river basin to another is considered a major threat to aquatic biodiversity. Impact assessment of such projects include generation of baseline information on different biotic and abiotic variables. The aim of this study was to generate baseline information on fish diversity from the glacial-fed (Bheri) and the spring-fed (Babai) rivers and their selected tributaries from western Nepal in the wake of the first proposed inter-basin water transfer from the former to the latter. A total of 10 sampling sites, five each from Bheri and Babai River systems, were chosen strategically. Electrofishing was conducted encompassing different seasons in 2018 following the standard method. A total of 32 species with catch per unit effort (CPUE) of 47±24 from Bheri and 42 species with CPUE of 63±52 from Babai River were recorded. Cyprinidae, followed by Nemacheilidae, were the most dominant families in both river systems, and Barilius vagra and Schistura beavani were the most dominant species in both. Species richness and abundance showed a significant difference between rivers, and differences in fish assemblages reflects differences in ecological regimes. Failure to observe migratory species such as Anguilla bengalensis suggests that migratory routes may already have been affected. Of the total 52 species recorded, eight are in the threatened categories of the IUCN Red List and need active conservation measures. The findings provide a reference to assess the impacts of water transfers on fish assemblages in these river systems.

Evaluation of Water Quality of the Surface Water Bodies in Gorakhpur City

Growing population, intensive agriculture, climate change, water pollution and depleting natural water resources are the main factors of water scarcity in India. More than 80 percent of sewage water generated by human activities is discharged into rivers and oceans without any control, resulting in environmental pollution and greatly affecting human health. Eighty percent of diseases and 50 percent of child deaths worldwide are related to polluted water. Water plays an important role for living beings and humans. Therefore, regular water quality monitoring is considered a top priority for all countries in the world. Water quality monitoring not only helps countries assess and predict pollution, but also provides information for planning the sustainable use of water resources. Rivers are an important component of both urban and rural aquatic ecosystems, and rapidly increasing pollution in rivers seriously threatens the safety of these ecosystems. The degradation of surface water quality due to increasing pollution and climate change has become a serious concern worldwide. Such degradation threatens the use of water resources, especially drinking water supplies, and economic development.

Water quality and the presence of metals in crustaceans (Sartoriana spinigera) and mollusks (Pila globosa) close to an urban waste landfill in Kodda at Gazipur

Degradation of water and sediment quality along with other aquatic ecosystem components, due to urban waste is a significant concern that demands attention. Despite of the multifaceted use of the Konabari area within the Gazipur City Corporation of Bangladesh, limited studies have assessed the health of the floodplain ecosystem adjacent to urban waste landfills in Kodda. This research focuses on evaluating water quality parameters and the presence of metals and metalloids in water, sediment, and biota (invertebrates) in the lowland floodplain near the Kodda municipal landfill in Gazipur district. In December 2022, thirteen composite samples, including water, sediment, crustaceans (Sartoriana spinigera), and mollusks (Pila globosa), were collected from the designated sampling site. Surface and sub-surface (0–15 cm depth) water were collected using a water sampler for water quality analysis, and the presence of heavy metal and metalloid content of the water, sediment, crabs, and mollusks were analyzed using an atomic absorption spectrometer. The results indicated dissolved oxygen concentrations ranging from 0.30 to 5.81 mg/l (mean 3.1±2.37 mg/l). Certain locations directly affected by waste discharge exhibited alarmingly low dissolved oxygen levels (~0.71 mg/l), coupled with elevated temperatures and phosphate (PO43−) content (2–7.4 mg/l). The scarcity of heavy metal concentrations (&lt;0.0677 mg/l) in water may be attributed to the constant flow of water preventing metal accumulation in the flowing water. However, sediment analysis revealed significantly higher concentrations (mean±Sd) of Fe (15240±1211 mg/kg), Mn (1122±180 mg/kg), Cu (44±5.5 mg/kg), Cr (28±3.2 mg/kg), Ni (39±2.4 mg/kg), As (3.7±0.89 mg/kg), and Zn (72±3.95 mg/kg) compared to other studies in various locations. Crustacean (Crab) samples showed concentrations of Cr, As, Pb, Cd, Zn, and Cu exceeding recommended permissible limits. Pila globosa emerged as an effective ecological bioindicator of aquatic pollution, with concentrations of Cr, Mn, Ni, Cu, Zn, and Pd exceeding recommended limits. Despite eco-environmental indices suggesting low to moderate contamination, the heavy metals and metalloids study indicated degradation of ecosystem health triggered by urban waste discharge. Consequently, the study recommends proper waste treatment in landfills and their transformation from open dumps to scientifically managed controlled waste landfills. Ann. Bangaldesh Agric. 27(2):175-189

Monitoring Spatio-Temporal Variations of Ponds in Typical Rural Area in the Huai River Basin of China

Ponds constitute a pivotal component of aquatic ecosystems. The aquatic ecosystem of the Huai River Basin (HRB) in China was once damaged by severe pollution, and numerous ponds in the basin have not been secured. In this paper, Shenqiu County, a typical county in HRB with many ponds, is selected. Based on high-resolution images with ALOS in 2010, GF-2 in 2016, and GF-1 in 2022, we employed discriminant analysis (DA), classification and regression tree, support vector machine, and random forest to extract the ponds based on object-oriented and further analyzed the spatial-temporal variations of the ponds in this county. The results of the DA in these three years exhibited a higher kappa coefficient (&gt;0.7), and overall accuracy (&gt;75%), signifying superior performance when compared to the other three methods. There were 4625, 5315, and 4748 ponds in 2010, 2016, and 2022, with a total area of 12.87, 11.99, and 9.37 km2, respectively. The number of ponds had a trend of rising in the initial period (2010–2016) and falling later (2016–2022), while the total area revealed a continuous decline. Meanwhile, these ponds showed a clustering phenomenon with three main clustering areas, and the scope of the clustering areas also changed to a certain extent from 2010 to 2022. Our study offers valuable methodological support for the ecological monitoring and management of water environments in regions characterized by a dense concentration of ponds. The crucial data related to ponds in this study will help inform both environmental and social development initiatives within the area.

Spatial distribution and population density of submerged aquatic vegetation in Shatt Al-Arab River

Submerged aquatic vegetation (SAV) is an integral component of aquatic ecosystems and provides essential habitats and ecosystem services. This study investigated the distribution and abundance of SAV in the Shatt Al-Arab River, located in Southern Iraq, and examined its relationship with changing environmental factors. Monthly surveys were conducted at three stations from October 2015 to September 2016 to assess the percentage cover of vegetation, biomass, and the physicochemical properties of water and sediment. Three SAV species belonging to the Potamogetonaceae family have been recorded. Canonical correspondence analysis showed a negative relationship between Potamogeton perfoliatus and depth/reactive phosphorus. The abundance of plants in this area was significantly lower than that reported in previous studies. Species richness and abundance were analyzed at all stations during the same period using biodiversity indices. The analysis revealed differences in species richness between the stations. This decline in abundance was likely due to increased salinity, nutrients, and anthropogenic pressures. This study demonstrates the impact of environmental changes on ecologically important SAV and emphasizes the necessity of implementing conservation and management strategies.

Species richness pattern of aquatic vascular macrophytes along elevation gradients in Nepal Himalayas

Abstract. Siwakoti EA, Nepali B, Mandal TN, Baniya CB. 2023. Species richness pattern of aquatic vascular macrophytes along elevation gradients in Nepal Himalayas. Biodiversitas 24: 5179-5190. Aquatic vascular macrophytes constitute an important component of aquatic ecosystems. This study aims to determine the species richness pattern of aquatic vascular macrophytes along elevation gradients (100-4900 m asl) in the Nepal Himalayas. We used available published literature on elevational ranges of aquatic vascular macrophytes in Nepal to interpolate the species elevational ranges, thereby providing species richness estimates for 100 m elevational bands. A total of 113 species of aquatic vascular macrophytes belonging to 66 genera under 35 families were recorded from Nepal. Among these macrophytes, dicots were represented by 21 families, monocots with 10 families and pteridophytes with 4 families. Regarding the geographical divisions, the total number of aquatic vascular macrophytes recorded was 76 from the east, 90 from the central and 67 from the west, conclusively central Nepal showed the maximum number of macrophytes. The highest species richness was contributed by Hydrocharitaceae followed by Potamogetonaceae, Plantaginaceae, Lentibulariaceae and Nymphaeaceae. So far, the functional types of macrophytes are concerned, free-floating species were 15, submerged species were 36, floating-leaved species were 18 and emergent species were 44 along elevation gradients in the three geographical divisions in Nepal. The Generalized Linear Model (GLM) was applied to find out the relation between the species richness of aquatic vascular macrophytes with elevation. It showed a statistically significant monotonic declining pattern with increasing elevation. The occurrence of this model was further verified by aquatic vascular macrophyte richness at every 200 m elevation which converged with the general pattern. The study conducted along one of the world’s longest bioclimatic elevational gradients led to support the monotonic declining pattern of aquatic vascular macrophytes richness indicating the difference in richness pattern among aquatic and terrestrial ecosystems. It also emphasizes the importance of conserving aquatic ecosystems with their vegetation.

Effects of antidepressant exposure on aquatic communities assessed by a combination of morphological identification, functional measurements, environmental DNA metabarcoding and bioassays

The antidepressant fluoxetine is frequently detected in aquatic ecosystems, yet the effects on aquatic communities and ecosystems are still largely unknown. Therefore the aim of this study is to assess the effects of the long-term application of fluoxetine on key components of aquatic ecosystems including macroinvertebrate-, zooplankton-, phytoplankton- and microbial communities and organic matter decomposition by using traditional and non-traditional assessment methods. For this, we exposed 18 outdoor mesocosms (water volume of 1530 L and 10 cm of sediment) to five different concentrations of fluoxetine (0.2, 2, 20 and 200 μg/L) for eight weeks, followed by an eight-week recovery period. We quantified population and community effects by morphological identification, environmental DNA metabarcoding, in vitro and in vivo bioassays and measured organic matter decomposition as a measure of ecosystem functioning. We found effects of fluoxetine on bacterial, algal, zooplankton and macroinvertebrate communities and decomposition rates, mainly for the highest (200 μg/L) treatment. Treatment-related decreases in abundances were found for damselfly larvae (NOEC of 0.2 μg/L) and Sphaeriidae bivalves (NOEC of 20 μg/L), whereas Asellus aquaticus increased in abundance (NOEC <0.2 μg/L). Fluoxetine decreased photosynthetic activity and primary production of the suspended algae community. eDNA assessment provided additional insights by revealing that the algae belonging to the class Cryptophyceae and certain cyanobacteria taxa were the most negatively responding taxa to fluoxetine. Our results, together with results of others, suggest that fluoxetine can alter community structure and ecosystem functioning and that some impacts of fluoxetine on certain taxa can already be observed at environmentally realistic concentrations.

Using a Bayesian Network Model to Predict Risk of Pesticides on Aquatic Community Endpoints in a Rice Field-A Southern European Case Study.

Bayesian network (BN) models are increasingly used as tools to support probabilistic environmental risk assessments (ERAs), because they can better account for uncertainty compared with the simpler approaches commonly used in traditional ERA. We used BNs as metamodels to link various sources of information in a probabilistic framework, to predict the risk of pesticides to aquatic communities under given scenarios. The research focused on rice fields surrounding the Albufera Natural Park (Valencia, Spain), and considered three selected pesticides: acetamiprid (an insecticide), 2-methyl-4-chlorophenoxyacetic acid (MCPA; a herbicide), and azoxystrobin (a fungicide). The developed BN linked the inputs and outputs of two pesticide models: a process-based exposure model (Rice Water Quality [RICEWQ]), and a probabilistic effects model (Predicts the Ecological Risk of Pesticides [PERPEST]) using case-based reasoning with data from microcosm and mesocosm experiments. The model characterized risk at three levels in a hierarchy: biological endpoints (e.g., molluscs, zooplankton, insects, etc.), endpoint groups (plants, invertebrates, vertebrates, and community processes), and community. The pesticide risk to a biological endpoint was characterized as the probability of an effect for a given pesticide concentration interval. The risk to an endpoint group was calculated as the joint probability of effect on any of the endpoints in the group. Likewise, community-level risk was calculated as the joint probability of any of the endpoint groups being affected. This approach enabled comparison of risk to endpoint groups across different pesticide types. For example, in a scenario for the year 2050, the predicted risk of the insecticide to the community (40% probability of effect) was dominated by the risk to invertebrates (36% risk). In contrast, herbicide-related risk to the community (63%) resulted from risk to both plants (35%) and invertebrates (38%); the latter might represent (in the present study) indirect effects of toxicity through the food chain. This novel approach combines the quantification of spatial variability of exposure with probabilistic risk prediction for different components of aquatic ecosystems. Environ Toxicol Chem 2024;43:182-196. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.