Optimisation of the Monitoring Strategy of Macroinvertebrate Communities in the River Dender, in Relation to the EU Water Framework Directive

The Dender basin in Flanders (Belgium) was used as a case study to implement the European Union (EU) Water Framework Directive. During the last 5 years, ample research on pollution loads and ecological water quality has been done on the Dender River. In addition to biological sampling of macroinvertebrates and fish, automated measurement stations were also used to investigate the spatial-temporal variability of the physical-chemical water quality. This research revealed that the pollution of the Dender River is highly variable. The high nutrient loads result in severe algae blooms during summer, leading to very complex diurnal processes. In this paper, the monitoring strategy for the assessment of the biological water quality in the Dender basin has been reviewed in relation to the EU Water Framework Directive. For this, seasonal macroinvertebrate data were collected and assessed. General trends and hidden structures in these data were analysed by means of classification trees, using different inputs (seasons, river types, and subbasins). Validation of the results was obtained by applying statistical methods. Analysis about the presence and abundance of the macroinvertebrates revealed that there is a distinct difference between the biological water quality in the Dender stem river and its tributaries. There are also seasonal differences between the macroinvertebrate communities when the Dender and its tributaries are examined separately. An optimised monitoring strategy is proposed based on these results and the EU Water Framework Directive. This includes two monitoring campaigns in summer and winter every 3 years. Furthermore, a cyclic monitoring scheme was developed to minimise sampling efforts

Distribution and ecology of the caddisflies (Trichoptera) of Flanders (Belgium)

Based on a literature survey and the identification of all available collection material, a checklist and distribution maps for the caddisflies occurring in Flanders were prepared. Of the 126 species that have been recorded, 16 are now extinct in Flanders, while the majority of the remaining species is rare and their populations are often vulnerable due to isolation. Caddisflies only occurred at high oxygen levels and relatively low conductivities and three species assemblages could be recognized. A first group of species lived in stagnant waters and those species tolerated slightly lower oxygen concentrations than species characteristic for running waters. In streams of the Campine region, which are characterized by a low pH and a low conductivity, a second group of species was found. The last group of species mainly occurred in the loamy region, where pH and conductivity are higher. Running waters in other ecoregions mainly contained ubiquist species and did not possess a characteristic species assemblage. Despite the fact that the ecological water quality in Flanders slightly increased during the last few decades, the ecological water quality of most waters is still too low for caddisflies. According to the European Union water framework directive, a good ecological water quality should be obtained in all surface waters. Additional measures to improve the water quality are necessary in order to obtain sustainable populations of the caddisfly species occurring in Flanders

Distribution and ecology of the mayflies (Ephemeroptera) of Flanders (Belgium)

A literature survey and the identification of all available collection material resulted in a checklist and distribution maps for the mayflies occurring in Flanders. In addition, the relationship between the occurrence of mayflies and water characteristics was analysed. Of the 32 species that have been recorded, six are now extinct in Flanders (three of which are potamal species), while the majority of the remaining species are rare and their populations are often strongly isolated and therefore extremely vulnerable. Waters with relatively low oxygen levels and high conductivities were characterized by the most tolerant mayfly species Cloeon dipterum and Caenis robusta. However, most other species only occurred at higher oxygen concentrations and lower conductivities and could be separated into two groups. The first group mainly occurred in waters with a high pH and were often restricted to the loamy region or to stagnant waters, while the second group occurred in waters with a lower pH and mainly occurred in the Campine region. For most mayfly species, sustainable populations can only be achieved when their current habitats are adequately protected and, in addition, measures should be taken to connect and enlarge the remaining populations

Benthic macroinvertebrates as indicators of the water quality in Bulgaria: A case-study in the Iskar river basin

AbstractMacroinvertebrates were sampled at 15 locations in the Iskar river basin in Bulgaria for the purpose of water quality assessment. Based on the chemical as well as the biological parameters, it was concluded that the water quality was still good upstream of Sofia, however, despite a huge waste water treatment plant, a strong decrease was observed when the river passed Sofia. Due to self-purification and dilution, a gradual amelioration of the water quality was observed 40 and 80km downstream of Sofia, however, water quality was still insufficient. The Irish Biotic Index (IBI), which is currently used in Bulgaria for the national monitoring of macroinvertebrates for water quality assessment, does not fulfil the requirements of the European Union Water Framework Directive (WFD). The Multimetric Macroinvertebrate Index Flanders (MMIF), on the contrary, is a WFD compliant method developed for the northern part of Belgium, which is based on (1) the total number of taxa, (2) the number of Ephemeroptera, Plecoptera and Trichoptera taxa, (3) the number of other sensitive taxa, (4) the Shannon–Wiener index and (5) the mean tolerance score. The outcome of this MMIF was strongly correlated with the outcome of the Irish Biotic Index. Therefore, it should be possible to develop a similar multimetric index for macroinvertebrates to evaluate the biological water quality in Bulgaria without much effort

Comparison of Artificial Neural Network (ANN) Model Development Methods for Prediction of Macroinvertebrate Communities in the Zwalm River Basin in Flanders, Belgium

Modelling has become an interesting tool to support decision making in water management. River ecosystem modelling methods have improved substantially during recent years. New concepts, such as artificial neural networks, fuzzy logic, evolutionary algorithms, chaos and fractals, cellular automata, etc., are being more commonly used to analyse ecosystem databases and to make predictions for river management purposes. In this context, artificial neural networks were applied to predict macroinvertebrate communities in the Zwalm River basin (Flanders, Belgium). Structural characteristics (meandering, substrate type, flow velocity) and physical and chemical variables (dissolved oxygen, pH) were used as predictive variables to predict the presence or absence of macroinvertebrate taxa in the headwaters and brooks of the Zwalm River basin. Special interest was paid to the frequency of occurrence of the taxa as well as the selection of the predictors and variables to be predicted on the prediction reliability of the developed models. Sensitivity analyses allowed us to study the impact of the predictive variables on the prediction of presence or absence of macroinvertebrate taxa and to define which variables are the most influential in determining the neural network outputs

Selection of an adequate functional diversity index for stream assessment based on biological traits of macroinvertebrates

Functional diversity (FD) is useful for the evaluation of freshwater ecosystems. The FD of macroinvertebrate families for river water quality (WQ) assessment in the Paute River Basin (PRB), Ecuador, was investigated. Macroinvertebrate samples and data about 26 physical, chemical, microbiological and hydro-geomorphological variables were available. Literature-based biological traits were allocated as scores to the macroinvertebrates data through fuzzy coding. The Generalised Additive Mixed Model (GAMM) was used to assess the performance of six FD indices using the referred 26 WQ descriptive variables. The best performing GAMM led to selecting the index based on functional dendrograms including the species community pool (wFDc) as the most suitable to characterise FD in the PRB. The sub-basins of the PRB were grouped in three classes applying Average Linkage Clustering (ALC) and using wFDc. The Random Forest (RF) algorithm was used with a global efficiency of 89% to assess the ALC clusters consistency and pre-identify the significant WQ descriptive variables, explaining most of the FD variability. The Kruskal-Wallis test was then applied to refine the outcomes of the previous analysis. Twelve WQ descriptive variables were finally identified as the best discriminant predictors for FD, including the riparian vegetation, electric conductivity, dissolved oxygen, total hardness, faecal coliforms and pH. It is believed that the implemented approach successfully assessed the stream WQ status of the PRB upon selecting a suitable macroinvertebrate FD index; as such, it could be applied to other tropical basins for WQ assessment

A comprehensive assessment of plastic remediation technologies

The global presence of plastic litter and its accumulation in the environment has become an issue of concern to the public and policymakers. This concern has triggered innovators in past decades to design and develop a multitude of remediation technologies to prevent plastic from entering the environment, or to clean up legacy litter. This study aims to (i) systematically review the current scientific literature on plastic remediation technologies, (ii) create a ‘plastic clean-up and prevention overview’ illustrating 124 remediation technologies and 29 characteristics, (iii) qualitatively analyse their key characteristics (e.g., fields of application, targeted plastic), and (iv) investigate challenges and opportunities of clean-up technologies for inland waterways (e.g., canals, rivers) and ports. We identified 61 scientific publications on plastic remediation technologies, until June 2022. Thirty-four of these studies were published within the last three years, demonstrating a growing interest. The presented overview indicates that inland waterways are, so far, the preferred field of application, with 22 technologies specifically designed for cleaning up plastics from inland waterways, and 52 additional ones with the potential to be installed in these locations. Given the importance of clean-up technologies in inland waterways, we highlighted their strengths, weaknesses, opportunities, and threats (SWOT). Our results indicate that, despite the challenges, these technologies provide essential prospects, from improving the environmental quality to raising awareness. Our study is instrumental as it illustrates an up-to-date overview and provides a comprehensive analysis of current in design phase, testing, and in use plastic remediation technologies

A Bayesian Belief Network learning tool integrates multi-scale effects of riparian buffers on stream invertebrates

Riparian forest buffers have multiple benefits for biodiversity and ecosystem services in both freshwater and terrestrial habitats but are rarely implemented in water ecosystem management, partly reflecting the lack of information on the effectiveness of this measure. In this context, social learning is valuable to inform stakeholders of the efficacy of riparian vegetation in mitigating stream degradation. We aim to develop a Bayesian belief network (BBN) model for application as a learning tool to simulate and assess the reach- and segment-scale effects of riparian vegetation properties and land use on instream invertebrates. We surveyed reach-scale riparian conditions, extracted segment-scale riparian and subcatchment land use information from geographic information system data, and collected macroinvertebrate samples from four catchments in Europe (Belgium, Norway, Romania, and Sweden). We modelled the ecological condition based on the Average Score Per Taxon (ASPT) index, a macroinvertebrate-based index widely used in European bioassessment, as a function of different riparian variables using the BBN modelling approach. The results of the model simulations provided insights into the usefulness of riparian vegetation attributes in enhancing the ecological condition, with reach-scale riparian vegetation quality associated with the strongest improvements in ecological status. Specifically, reach-scale buffer vegetation of score 3 (i.e. moderate quality) generally results in the highest probability of a good ASPT score (99–100%). In contrast, a site with a narrow width of riparian trees and a small area of trees with reach-scale buffer vegetation of score 1 (i.e. low quality) predicts a high probability of a bad ASPT score (74%). The strengths of the BBN model are the ease of interpretation, fast simulation, ability to explicitly indicate uncertainty in model outcomes, and interactivity. These merits point to the potential use of the BBN model in workshop activities to stimulate key learning processes that help inform the management of riparian zones