The influence of spatial processes on fish community structure: using a metacommunity framework for freshwater bioassessment.

The use of biological indicators in a bioassessment approach is important for inferences of anthropogenic stress in routine monitoring programs. One of the primary assumptions of bioassessment is that biological indicators observed at specific sampling sites will allow for inferences of local environmental quality; however, this assumption requires a reliable understanding of dispersal processes, which is particularly relevant in river systems due to their dendritic network. Inter-stream dispersal between different points of the river network could bias bioassessment, especially for highly mobile organisms like fish. Here, we examine standard biological metrics used in routine biomonitoring to determine how spatial variables, including dispersal, influence inferences between fish populations and environmental gradients. Using redundancy analysis (RDA) and variation partitioning, we tested the relative influence of both environmental and spatial variables on fish community structure and related community metrics. Fish were collected from 99 sampling sites distributed across 44 rivers and streams of the Great Morava River Basin, Serbia. Electroconductivity, the percentage of agricultural areas, dissolved oxygen, ammonia, and nitrate-nitrogen were found to be significant environmental variables, while ten spatial predictors from broad- to small-scales were found to influence fish community structure and community metrics. Our results suggest that contemporary dispersal among streams influences fish community composition, but that trait-based metrics are less sensitive than basic measures of diversity to spatial processes. Our results highlight the need for spatially independent sampling, as well as the need to consider dispersal-based processes in routine biomonitoring.

The Influence of Contracaecum larvae (Nematoda, Anisakidae) Parasitism on the Population of Prussian carp (Carassius gibelio) in Lake Sakadas, Croatia.

Contracaecum larvae are geographically widely distributed, utilizing many animal species as hosts; and fish represent an important paratenic host in their life cycle. Their presence in Prussian carp (Carassius gibelio) was studied in Lake Sakadas (Croatia) in 2017 and 2018. Two gill nets of different sizes submerged during a 12-h period were used to collect the fish. Contracaecum larvae were recorded in the stomach, slightly coiled or elongated on the intestine serosa or encapsulated in a gut wall of 20 individuals. The effect of Contracaecum sp. on the health of their host was determined by estimating the effect of the parasites' presence, number, and biomass on fish length, weight, and the Fulton's condition factor (CF). Infected fish showed negative (b < 3; p < 0.05) and uninfected fish positive allometric growth (b > 3; p < 0.05). Fish weight and CF in infected individuals were significantly low in comparison to the uninfected ones (Mann−Whitney U test: U = 1078.00, U = 423.50, respectively; p < 0.004). These results emphasize the importance of evaluating parasitic nematode presence in economically important fish species. Even more, if this endoparasite has a detectable negative impact on a resilient species such as the Prussian carp, it is important to monitor its occurrence in other fish species.

Implications of local niche- and dispersal-based factors that may influence chironomid assemblages in bioassessment.

Local environmental factors and dispersal-based processes can both influence the structure of metacommunities in freshwater ecosystems. Describing these patterns is especially important for biomonitoring approaches that are based on inferences made from benthic macroinvertebrate assemblages. Here, we examine the metacommunity structure of chironomid assemblages collected from 28 sampling stations along the Southern Morava River, Serbia. We examined the extent of dispersal-based processes along a temporal scale. We obtained 8 models for the different sampling seasons that determined the spatial variables that best explained variability in chironomid assemblages. Spatial processes were found to be a significant predictor of variation for chironomids during the late winter/spring (March and May) and autumn (October and November), concordant with the known phenology of common taxa. Species sorting and mass effects were found to be significant processes that structured the chironomid metacommunity. In addition, biological interactions, inferred from fish biomass, and habitat traits, demonstrated by macrophyte and riparian vegetation, were found to influence species sorting. A high variability of chironomid metacommunity structure across sampling seasons suggests that monitoring programs that include macroinvertebrates in bioassessment should avoid months with pronounced spatial processes, and consequently maximize a correlation between community structure and local environmental factors.

Potentially toxic elements in invasive fish species Prussian carp (Carassius gibelio) from different freshwater ecosystems and human exposure assessment.

Concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, Sn, and Zn were detected in the muscle and gills of Prussian carp from three different freshwater ecosystems: isolated ponds and the South Morava River in Serbia, and Kopacko Lake in complex wetland ecosystem of the Kopacki Rit Nature Reserve in Croatia. The main goals of the present research were to assess the concentrations of potentially toxic elements (PTEs) in the muscle and gills of Prussian carp (Carassius gibelio), to examine whether abiotic factors from three different freshwater ecosystems affect the accumulation of PTEs in fish tissues, and to estimate the human health risk resulting from fish consumption. There were only six concentrations of PTEs in the gill tissue (Cr, Hg, Mn, Pb, Sn, and Zn) that were not significantly different among the different freshwater ecosystems. In the muscles, the differences were much less visible. Kopacko Lake distinguished with the highest values of metal pollution index (MPI) for muscles (0.24) and isolated ponds with the highest values of MPI for gills (0.8). The redundancy analysis (RDA) showed that concentrations of Al, Mn, Zn, Cu, and Fe in the gill tissue were significantly correlated with the environmental variables. In contrast, the RDA based on element concentrations in the fish muscles indicated no significant relationship with the environment. Isolated ponds, with no inflow of freshwater, stand out as the most polluted, followed by Kopacko Lake with occasional floods. Flowing freshwater ecosystem South Morava River can be single out as at least polluted with PTEs. The target hazard quotients (THQ) and hazard index (HI) suggested there were no significant noncarcinogenic health risks. The target carcinogenic risk factor (TR) for As and Pb confirmed there were no cancer risks related to human fish consumption. Since the elevated concentrations of toxic Cd and As in Prussian carp were estimated, an early warning should be assumed, especially for fishing activities in these areas.

The application of Uniform Manifold Approximation and Projection (UMAP) for unconstrained ordination and classification of biological indicators in aquatic ecology.

The analysis of community structure in studies of freshwater ecology often requires the application of dimensionality reduction to process multivariate data. A high number of dimensions (number of taxa/environmental parameters × number of samples), nonlinear relationships, outliers, and high variability usually hinder the visualization and interpretation of multivariate datasets. Here, we proposed a new statistical design using Uniform Manifold Approximation and Projection (UMAP), and community partitioning using Louvain algorithms, to ordinate and classify the structure of aquatic biota in two-dimensional space. We present this approach with a demonstration of five previously published datasets for diatoms, macrophytes, chironomids (larval and subfossil), and fish. Principal Component Analysis (PCA) and Ward's clustering were also used to assess the comparability of the UMAP approach compared to traditional approaches for ordination and classification. The ordination of sampling sites in 2-dimensional space showed a much denser, and easier to interpret, grouping using the UMAP approach in comparison to PCA. The classification of community structure using the Louvain algorithm in UMAP ordinal space showed a high classification strength for data with a high number of dimensions than the cluster patterns obtained with the use of a Ward's algorithm in PCA. Environmental gradients, presented via heat maps, were overlayed with the ordination patterns of aquatic communities, confirming that the ordinations obtained by UMAP were ecologically meaningful. This is the first study that has applied a UMAP approach with classification using Louvain algorithms on ecological datasets. We show that the performance of local and global structures, as well as the number of clusters determined by the algorithm, make this approach more powerful than traditional approaches.

In Situ Effects of a Microplastic Mixture on the Community Structure of Benthic Macroinvertebrates in a Freshwater Pond.

Benthic communities contain some of the most threatened organisms in aquatic habitats due to different anthropogenic pressures. The high abundance of microplastics in sediments will continue to increase in the future, further increasing the probability of interactions between macroinvertebrates and microplastics. In the present study, a benthic community in a relatively pristine shallow pond was exposed either to an environmentally relevant high concentration of a microplastic mixture of 80 g m-2 in the sediment, or a control sediment, without the addition of microplastics. The mixture of microplastics contained irregularly shaped polyethylene, polyvinyl chloride, and polyamide in a ratio of 50:25:25%, respectively. The in situ experiment lasted for 100 d. The total number of taxa that colonized the microcosms was 22 (17 in the control and 18 in the microplastic treatment), and the colonization was not affected by the treatment. The most dominant group within the macroinvertebrate community was the dipteran family Chironomidae, in both the control and the microplastic treatment. No significant differences in the abundance and biomass at a community level were recorded between the groups by permutational multivariate analysis of variance (F = 0.993, p = 0.456 and F = 0.344, p = 0.797, respectively). The mixture of microplastics did not influence the abundance or biomass of the functional feeding groups (F = 1.810, p = 0.137 and F = 0.377, p = 0.736, respectively). The species richness, species abundance, species biomass, Shannon's diversity index, and Simpson's index of diversity showed no statistically significant differences between the control and treatment groups. Czekanowski's quantitative similarity index indicated that 84% of the community remained unaffected after microplastic exposure. Environ Toxicol Chem 2022;41:888-895. © 2021 SETAC.

Searching for lichen indicator species: the application of self-organizing maps in air quality assessment-a case study from Balkan area (Serbia).

The subject of this paper is the possibility of using self-organizing map (SOM) in the biomonitoring studies. We used lichens as biomonitors to indicate different degrees of air quality. This research included all of 88 lichen species that was collected at 75 investigated points. These lichen species showed the different responses to air pollution. The air quality was assessed by IAP (index of atmospheric pollution) values. The IAP values were calculated for all of investigated points on the territory of four natural and one urban ecosystem. Calculated IAP values were in range of 10 to 75. On the basis of the lichen data and IAP values, we have employed SOM analysis that distinguished three clusters (A, B, and C). It presented lichen indicator species for each cluster: 16 species for cluster A, 18 species for cluster B, and two species for cluster C. This paper presents a useful method to find indicator species.

Application of deep learning in aquatic bioassessment: Towards automated identification of non-biting midges.

Morphological species identification is often a difficult, expensive, and time-consuming process which hinders the ability for reliable biomonitoring of aquatic ecosystems. An alternative approach is to automate the whole process, accelerating the identification process. Here, we demonstrate an automatic machine-based identification approach for non-biting midges (Diptera: Chironomidae) using Convolutional Neural Networks (CNNs) as a means of increasing taxonomic resolution of biomonitoring data at a minimal cost. Chironomidae were used to build the automatic identifier, as a family of insects that are abundant and ecologically important, yet difficult and time-consuming to accurately identify. The approach was tested with 10 morphologically very similar species from the same genus or subfamilies, comprising 1846 specimens from the South Morava river basin, Serbia. Three CNN models were built utilizing either species, genus, or subfamily data. After training the artificial neural network, images that the network had not seen during the training phase achieved an accuracy of 99.5% for species-level identification, while at the genus and subfamily level all images were correctly assigned (100% accuracy). Gradient-weighted Class Activation Mapping (Grad-CAM) visualized the mentum, ventromental plates, mandibles, submentum, and postoccipital margin to be morphologically important features for CNN classification. Thus, the CNN approach was a highly accurate solution for chironomid identification of aquatic macroinvertebrates opening a new avenue for implementation of artificial intelligence and deep learning methodology in the biomonitoring world. This approach also provides a means to overcome the gap in bioassessment for developing countries where widespread use techniques for routine monitoring are currently limited.

An environmentally relevant concentration of titanium dioxide (TiO2) nanoparticles induces morphological changes in the mouthparts of Chironomus tentans.

The present study was carried out in order to assess the influence of environmentally relevant concentrations of TiO2 nanoparticles (E171 human food grade) toxicity on the freshwater midge Chironomus tentans. Tested concentrations were 125, 250, 500, 1000, 2000 and 4000 mg of E171 TiO2 per 1 kg of sediment, for the experiment aiming at life trait toxicity observation; and 2.5, 25 and 250 mg of E171 TiO2 per 1 kg of sediment for the experiment aiming at mouthpart deformity observation. The experimental design was constructed for the sediment dwelling chironomid larvae according to OECD guidelines. For the first time, a geometric morphometric approach was used to assess the deformities in chironomid larvae as sublethal implications of nanoparticle exposure. The present study showed a concentration-response relationship between the TiO2 concentration in the substrate and the TiO2 intake. The mortality and emergence ratio was affected at concentrations >1000 mg/kg. Geometric Morphometrics revealed the tendency of the mentum teeth to narrow and elongate and the mandibles to widen, as well as the loss of the first inner tooth, with a TiO2 concentration rise. The variability of morphological changes observed in the mouthparts indicates that C. tentans could be used as a bioindicator in nano-TiO2 monitoring.

The response of chironomid taxonomy- and functional trait-based metrics to fish farm effluent pollution in lotic systems.

The lotic habitats affected by trout farm waste are colonized with a particular invertebrate community of which chironomids are the most abundant group. However, there is little information available regarding how chironomid community structures respond to this type of pollution at the highest taxonomic resolution. Eight fish farms, together with their lotic systems as recipients, were used to test the variability of the chironomid community and its surrogates (taxonomic and functional metrics) across spatially arranged sampling sites to form a gradual decrease in the trout farm influence. The self organizing map (SOM) classified six different types of chironomid communities which were characteristic for both the control and affected habitats. The species indicator analyses listed 32 taxa as positive indicators of water pollution. The SOM and Kruskal-Wallis test revealed that the pattern of chironomid community structure obtained was mainly driven by six environmental parameters (Altitude, conductivity, distance from the outlet, hardness, HN4-N, NO3-N). Categorical principal components analysis (CATPCA) derived three models for each type of biotic metric, in which for diversity-, taxonomy- and functional feeding group-based metrics, the first two dimensions explained 55.2%, 58.3% and 55.4%, of the total variance respectively for 315 sampling sites. According to this analysis, the total number of taxa (S), abundance and the Shannon-Wiener index (H') (as a diversity metric), as well as the proportion of Tanypodinae (as taxonomic group) and grazers/scraper (GRA) and gatherer collector (GAT)(as FFG metrics), were related to the outlet distance gradient, thus showing great potential to be used in the multimetric approach in bioassessment.

The best data design for applying the taxonomic distinctness index in lotic systems: A case study of the Southern Morava River basin.

The taxonomic distinctness (Δ+) index has been recognized as a robust measure to assess human impacts on marine biodiversity. However, its applicability in freshwater ecosystems has still not been confirmed. We aimed to propose the most suitable data design for calculating the Δ+ index for application in assessing anthropogenically caused degradation in lotic environments. We calculated the values of Δ+ based on different taxa groups and taxa resolutions, in order to examine its utility as a potential metric in bioassessment programs. We found that the exclusion of non-insect taxa and selected insect orders significantly increased the index sensitivity. Thus, we believe that an appropriate data design for Δ+ calculation based on macroinvertebrate assemblages is the main prerequisite for the effective estimation of degradation in lotic environments. In addition, we argue that a decrease in taxonomic resolution up to genus level is completely acceptable, as it results in only minor information loss. Bearing this in mind would significantly facilitate its application in rapid bioassessment programs. Despite the observed correlation, the utility of Δ+ as a potential bioassessment metric is rather limited, since its fails to detect fine differences in environmental stress, and instead only roughly distinguishes between two basic classes of degradation level, unimpacted and impacted.

The potential of chironomid larvae-based metrics in the bioassessment of non-wadeable rivers.

The chironomid community in non-wadeable lotic systems was tested as a source of information in the construction of biological metrics which could be used into the bioassessment protocols of large rivers. In order to achieve this, we simultaneously patterned the chironomid community structure and environmental factors along the catchment of the Danube and Sava River. The Self organizing map (SOM) recognized and visualized three different structural types of chironomid community for different environmental properties, described by means of 7 significant abiotic factors (a multi-stressor gradient). Indicator species analysis revealed that the chironomid taxa most responsible for structural changes significantly varied in their abundance and frequency along the established environmental gradients. Out of 40 biological metrics based on the chironomid community, the multilayer perceptron (MLP), an supervised type of artificial neural network, derived 5 models in which the abundance of Paratrichocladius rufiventis, Orthocladiinae, Cricotopus spp., Cricotopus triannulatus agg. and Cricotopus/Orthocladius ratio achieved a significant relationship (the r Pearson's linear correlation coefficient>0.7) with the multi stressor environment. The sensitivity analysis "partial derivatives" (PaD) method showed that all 5 biological metrics within the multi-stressor gradient were mostly influenced by dissolved organic carbon (DOC). Despite short and monotonous environmental gradients and the absence of reference conditions, the chironomid community structure and biological metrics predictably changed along the multistress range, showing a great potential for the bioassessment of large rivers.

The utility of two marine community indices to assess the environmental degradation of lotic systems using fish communities.

Multimetric approaches are commonly used to evaluate the ecological status of aquatic ecosystems. However, it has been recommended that the sensitivity of existing methods be improved through the investigation of the potential of new metrics to detect environmental disturbances. In this study we tested the effectiveness of two community indices (Taxonomic distinctness index (TDI) and Abundance biomass comparison (ABC) method), primarily proposed for marine ecosystems, to identify sites with different levels of environmental degradation in lotic systems using fish community data. Fish samples were collected over the period 2003-2011 at 131 sampling stations. To generate water and habitat quality classes, a self-organizing map (SOM) based on environmental data was applied. Gradients over the SOM map were investigated for the values of the TDI and ABC indices. The results of this study reveal that the values of both the TDI and ABC indices are highly correlated with water and habitat quality gradients. However, despite the observed correlation, the utility of TDI as a potential metric in bioassessment programs is rather limited, due to its lack of discriminatory power. In contrast, the ABC method could be proposed as a novel metric, but can only be applied in type-specific multimetric approaches.

Commercial fish species of inland waters: a model for sustainability assessment and management.

The permanent increase in the exploitation of commercial fish species has led to the need for developing practical and effective tools for the sustainability assessment and management of the target fish populations. The aim of this study was to formulate an ESHIPPOfishing model which would provide a reliable assessment of commercial fish population sustainability and indicate the conservation priorities. The existing ESHIPPO model was modified by introducing a new Index of local sustainability of fish populations (ILSFP) which enables the selection of "keystone populations" and "keystone habitats/ecosystems" within the basin being investigated. We employed a self-organizing map (SOM) in order to visualize the spatial distribution of the keystone populations and keystone habitats/ecosystems for each fish species. Based on the ILSFP values, environmental specialization (ES) of a fish species and local environmental factors (HIPPO factors), the model estimates the degree of sustainability (DS) of commercial fish populations in the freshwater ecosystems of the western Balkan Peninsula. The results indicate a low degree of sustainability for the majority of commercial fish species of the Middle Danube Basin, especially Acipenser ruthenus and Hucho hucho. The ESHIPPOfishing model presents a cost effective conservation approach, formulated to be applicable to any kind of river basin. The application of the ESHIPPOfishing model provides a comprehensive insight into the viability of target fish populations, which would not only further improve the selection of conservation priorities, but also facilitate the management of aquatic ecosystems.