Niels De Pauw

Method for biological quality assessment of watercourses in Belgium

A description is given of the method generally used in Belgium to assess the quality of running water. It involves the determination of a biotic index with scores between 0 and 10, based on samples of the aquatic macro-invertebrate community collected in situ, using a handnet.The Belgium method combines the advantages of two existing biological assessment methods worked out by Woodiwiss (1964) for the Trent River Board in the U.K., and by Tuffery & Verneaux (1968) for the Department of Fisheries and Pisciculture in France.Its major advantages are its simplicity, speed, reliability, low cost, and practical utility. Its limitations and difficulaties as well as the needs for further research are briefly discussed.The method, called the Belgian Biotic Index Method, is applicable to various types of watercourses and has recently been proposed to the Belgian Institute for Normalisation for approval as a standard method.For several years, the Belgian government has based its strategy towards surface water sanitation on water quality maps, visualizing the biotic indices obtained by the biological assessment method. As such, Belgium is advancing the recommendations for biological water quality monitoring being worked out by the Environmental and Consumer Protection Service of the Commission of the European Communities.

Fuzzy rule-based models for decision support in ecosystem management

To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed.

Applications of artificial neural networks predicting macroinvertebrates in freshwaters

To facilitate decision support in freshwater ecosystem protection and restoration management, habitat suitability models can be very valuable. Data driven methods such as artificial neural networks (ANNs) are particularly useful in this context, seen their time-efficient development and relatively high reliability. However, specialized and technical literature on neural network modelling offers a variety of model development criteria to select model architecture, training procedure, etc. This may lead to confusion among ecosystem modellers and managers regarding the optimal training and validation methodology. This paper focuses on the analysis of ANN development and application for predicting macroinvertebrate communities, a species group commonly used in freshwater assessment worldwide. This review reflects on the different aspects regarding model development and application based on a selection of 26 papers reporting the use of ANN models for the prediction of macroinvertebrates. This analysis revealed that the applied model training and validation methodologies can often be improved and moreover crucial steps in the modelling process are often poorly documented. Therefore, suggestions to improve model development, assessment and application in ecological river management are presented. In particular, data pre-processing determines to a high extent the reliability of the induced models and their predictive relevance. This also counts for the validation criteria, that need to be better tuned to the practical simulation requirements. Moreover, the use of sensitivity methods can help to extract knowledge on the habitat preference of species and allow peer-review by ecological experts. The selection of relevant input variables remains a critical challenge as well. Model coupling is a missing crucial step to link human activities, hydrology, physical habitat conditions, water quality and ecosystem status. This last aspect is probably the most valuable aspect to enable decision support in water management based on ANN models.

Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates

Abstract Predicting freshwater organisms based on machine learning is becoming more and more reliable due to the availability of appropriate datasets, advanced modelling techniques and the continuously increasing capacity of computers. A database consisting of measurements collected at 360 sampling sites in non-navigable watercourses in Flanders was applied to predict the absence/presence of benthic macroinvertebrate taxa by means of decision trees. The measured variables were a combination of physical–chemical (temperature, pH, dissolved oxygen concentration, conductivity, total organic carbon, Kjeldahl nitrogen and total phosphorus), structural (granulometric analysis of the sediment, width, depth and flow velocity of the river) and two ecotoxicological variables. The predictive power of decision trees was assessed on the basis of the number of Correctly Classified Instances (CCI). A genetic algorithm was introduced to compare the predictive power of different sets of input variables for the decision trees. The number of input variables was reduced from 15 to 2–8 variables without affecting the predictive power of the decision trees significantly. Furthermore, reducing the number of input variables allowed to ease the identification of general data trends.

Use of artificial substrates for standardized sampling of macroinvertebrates in the assessment of water quality by the Belgian Biotic Index

The paper reviews 3 years of experience in Belgium and Portugal with artificial substrates for collecting macroinvertebrates used in water quality assessment by means of the Belgian Biotic Index (B.B.I.).Artificial substrates provide a valid alternative method for sampling the macroinvertebrate fauna and the possibility of standardizing the sampling effort, whereas sampling with a handnet may be more subjective.Research has been focussed on the effect of sampler design and composition as well as conditions of exposure on the number of systematic units and the biotic index obtained.With artificial substrates correct assessments could be performed in different types of watercourses, including lowland brooks and canals as well as fast running upland rivers located in different climates.Guidelines for the development of a simple standard procedure with artificial substrates are proposed.

Comparative monitoring of diatoms, macroinvertebrates and macrophytes in the Woluwe River (Brussels, Belgium)

The river Woluwe in Brussels and Flanders (Belgium) is a small tributary of 15 km length that drains an area of 9400 ha in the Schelde river basin. The headwaters of the Woluwe are highly fragmented by diverse pond systems and are vaulted in the Brussels agglomeration. Hyporheic zones locally influence the water quality. The downstream stretch of the river receives sewage waters from households and industry. As the river Woluwe within a short distance represents a typical gradient from groundwater-fed sources in the forest towards severely polluted water, a comparative monitoring using diatoms, macroinvertebrates and macrophytes was done. The saprobic index based on diatoms, the Belgian Biotic Index (BBI) for macroinvertebrates and a macrophyte index based on the N-values of Ellenberg were used in this comparison and for estimating the correlation with the bimonthly measured chemical variables in 16 sampling stations. The diatom saprobic index and the macrophyte index were strongly correlated. Both groups showed strong correlations with phosphate, ammonium and chemical oxygen demand. The Belgian Biotic Index showed lower correlations with the nutrient variables, but was slightly better correlated to chemical oxygen demand, chloride and dissolved oxygen. None of the indices showed a correlation with nitrate. Local substrate or light conditions could interfere with the indicator system, especially for the macrophytes and occasionally for the macroinvertebrates. It was concluded that at least in this particular river system, the indices based on the primary producers were more indicative for the trophic status, whereas the BBI showed a broader relationship to the general degree of pollution. Therefore, these three indices are considered as complementary for monitoring the biological quality and the ecological status of a river system.

Analysis of macrobenthic communities in Flanders, Belgium, using a stepwise input variable selection procedure with artificial neural networks

The effect of environmental conditions on river macrobenthic communities was studied using a dataset consisting of 343 sediment samples from unnavigable watercourses in Flanders, Belgium. Artificial neural network models were used to analyse the relation among river characteristics and macrobenthic communities. The dataset included presence or absence of macroinvertebrate taxa and 12 physicochemical and hydromorphological variables for each sampling site. The abiotic variables served as input for the artificial neural networks to predict the macrobenthic community. The effects of the input variables on model performance were assessed in order to identify the most diagnostic river characteristics for macrobenthic community composition. This was done by consecutively eliminating the least important variables and, when beneficial for model performance, adding previously removed ones again. This stepwise input variable selection procedure was tested not only on a model predicting the entire macrobenthic community, but also on three models, each predicting an individual taxon. Additionally, during each step of the stepwise leave-one-out procedure, a sensitivity analysis was performed to determine the response of the predicted macroinvertebrate taxa to the input variables applied. This research illustrated that a combination of input variable selection with sensitivity analyses can contribute to the development of reliable and ecologically relevant ANN models. The river characteristics predicting presence or absence of the benthic macroinvertebrates best were the Julian day, conductivity, and dissolved oxygen content. These conditions reflect the importance of discharges of untreated wastewater that occurred during the period of investigation in nearly all Flemish rivers.

Large-scale microalgae production for nursery rearing of marine bivalves

Abstract The feasibility of large-scale bloom induction of nutritionally suited natural phytoplankton species, to feed a semi-industrial nursery of edible shellfish, built on the Belgian coast, was tested. The outdoor microalgal production unit consisted of four tanks of 100 m 2 surface each (two of 1 m depth and two of 0·5 m depth), equipped with different mixing devices. The cultures were run as chemostats in which seawater was enriched with commercial inorganic N, P, and Si fertilizers. Depending on the season, between 5–10 and 80% of the culture volume could be harvested daily, with algal densities ranging from 50 000 to 500 000 cells per ml. By manipulation of operational parameters such as detention time, nutrient levels and nutrient ratios (N:Si:P), unsuited or less suited species of algae (e.g. Chlorella and Phaeodactylum ) could be replaced by more desirable species (e.g. Skeletonema, Nitzschia, Chaetoceros ). Various biological and technological problems encountered during year round operation, including collapsing of the culture, seawater enrichment, water quality, fouling and water treatment, are commented.

Biotic index for sediment quality assessment of watercourses in Flanders, Belgium

Today, assessment of freshwater sediments in Flanders is based on the TRIAD approach in which physical-chemical, biological and ecotoxicological data are combined. No prior experience existing in Flanders with the biological assessment of the sediment quality, several biotic indices were compared on a first set of 80 samples taken in different types of lowland watercourses. This information resulted in a first selection of suitable indices consisting of a newly created Biotic Sediment Index (BSI) and the Percentage Mentum Deformities in Chironomus (Diptera, Chironomidae larvae). The starting point of the BSI was the Belgian Biotic Index (BBI) based on a combination of the taxa diversity and the presence or absence of specific indicator groups. For the refinement of the BSI, a new set of data related to the benthic macroinvertebrate communities sampled by means of a grab in more than 400 sites was collected. Community analysis by means of multivariate techniques, combining biological information with physical-chemical and ecotoxicological data was the basis for this further refinement and the scientific foundation of the original BSI. Major amendments relate to the scores assigned to the indicator groups. This refined BSI is representative for the degree of pollution, unbiased by the type of sediment and the origin of the river basin. Like the BBI, the BSI scores can vary between 10 (excellent sediment quality) and 0 (very bad sediment quality). The index values can be converted into 4 quality classes to be represented by means of a colour code.

Mass cultivation of Daphnia magna Straus on ricebran

Abstract Experiments in volumes up to 250 liter have proven that Daphinia magna can be successfully grown on (micronised) ricebran, an agro-industrial residue with little commercial value. No deficiencies were noted after more than 20 generations. A formula for the correct dosing of the ricebran, in relation to population density, is presented. Practical guidelines to run and maintain such cultures are given. In small-scale batch experiments (culture volume 8 l), population densities of 10 000 and more animals per liter were obtained within 6 weeks. Intermittent batch cultures (160 and 250 l) of D. magna could be maintained for periods of more than 5 months, solely on ricebran. A selective harvesting at regular intervals of daphnids larger than 1.4 mm resulted in about 40% higher yields than a non-selective harvest of part of the population. Average yields of 650 g wk−1m−3 and 450 g wk−1m−3, respectively, were obtained. The conversion ratio from ricebran to Daphnia biomass (wet weight) was found to be between 2 and 1 to 1, depending on the cultivation method used. Energy content of ricebran-grown daphnids was 17 000 J/g−1 dry weight. Protein content was 45 to 50% of dry material.