Potential risk of organic micropollutants on marine phytoplankton in the greater North Sea : integration of modelling and experimental approaches

A complex chemical cocktail, with unknown composition and concentrations, is present in marine waters. Although the awareness of the vulnerability of marine ecosystems to pollution-induced changes increased, the ecotoxicological effects of chemical pollutants on marine ecosystems are poorly understood. Even in intensively monitored regions such as the North Sea, current knowledge of the ecotoxicological effects of chemicals is limited to few (priority) substances and few (model) species (discussed in chapter I). To partly address this knowledge gap, in the present work, using phytoplankton, it is assessed how marine ecosystems respond to the presence of organic chemicals. By analyzing existing data and performing laboratory experiments, ecotoxicological effects of organic chemicals to marine organisms and ecosystem functions are quantified. Specific aims of this work are: (1) to infer spatiotemporal trends of concentrations of organic chemicals; (2) to investigate the impact of primary and secondary emissions on the spatiotemporal trends of organic chemicals; (3) to examine the partitioning of organic chemicals in different environmental compartments; (4) to assess the potential ecotoxicological effect of realistic mixtures of organic chemicals along environmental gradients; and (5) to quantify the relative contribution of organic chemicals to the phytoplankton growth dynamics. Spatiotemporal trends of polychlorinated biphenyl (PCB) concentrations are inferred based on an extensive set of concentrations monitored between 1991 and 2010 in sediments of the Belgian Coastal Zone (BCZ) and the Western Scheldt estuary in chapter II. The time trends unravel two to three-fold PCB concentration decreases in the BCZ during the last 20 years. In the Western Scheldt estuary, time trends are spatially heterogeneous and not significantly decreasing. These results demonstrate that international efforts to cut down emissions of PCBs have been effective to reduce concentrations in open water ecosystems like the BCZ but had little effect in the urbanized and industrialized area of the Scheldt estuary. Most likely, estuaries are subject to secondary emissions from historical pollution. In chapter III, trends found for the BCZ (chapter II) are confirmed at larger spatiotemporal scales. In chapter III multidecadal field observations (1979–2012) in the North Sea and Celtic Sea are analyzed to infer spatiotemporal concentration trends of PCBs in mussels (Mytilus edulis) and in sediments. Decreasing interannual PCB concentrations are found in North Sea sediments and mussels. PCB concentrations in sediments show, less than PCB levels in mussels, decreasing interannual trends. In addition in chapter III, interannual changes of PCB concentrations are separated from seasonal variability. By doing so, superimposed to the generally decreasing interannual trends, seasonally variable PCB concentrations are observed. These seasonal variations are tightly coupled with seasonally variable chlorophyll a concentrations and organic carbon concentrations. Indeed, the timing of phytoplankton blooms in spring and autumn corresponds to the annual maxima of the organic carbon content and the PCB concentrations in sediments. These results demonstrate the role of seasonal phytoplankton dynamics (biological pump) in the environmental fate of PCBs at large spatiotemporal scales.The latter is a novel result since the working of the biological pump was never assessed before based on field data collected at the scale of a regional sea in multiple decades. Despite the generally decreasing spatiotemporal trends of PCBs that are found in chapter II and III, it is not clear whether current concentrations (still) pose a risk to marine ecosystems. In chapter IV, the spatiotemporal trends inferred in chapter III are used to assess the ecological risk of PCBs in North Sea and Celtic Sea sediments and mussels. To do so, PCB concentrations are compared with environmental assessment criteria (EAC). It is found that the potential ecotoxicological risk of PCBs change considerably over time and in space. Risk quotients (RQs) of PCBs in marine sediments primarily depend on the location of the monitoring site, i.e. the closer to the coast, the higher the RQ. Especially in summer, when PCB concentrations in sediments are high, PCBs present in marine coastal sediments may pose an environmental risk. By contrast, RQs in mussel depend first on the interannual changes of PCB concentrations. At present, in the Celtic Sea, RQs in mussels are below the value of 1, suggesting no potential environmental risk. In the North Sea, however, PCBS in mussels may still exceed the prescribed environmental quality criteria. Overall, the results shown in chapter IV demonstrate that the spatiotemporal variability in PCB concentrations should be considered in future environmental risk assessments. Comparing concentrations of chemicals with quality thresholds (as in chapter IV) only suggest a potential ecological risk. Therefore, in case if risk quotients exceed the value of 1, additional assessments are recommended. Considering the results obtained in chapter IV, in chapter V, additional experimental studies are performed in which a marine diatom is exposed to a realistic mixture of organic contaminants. To do so, passive samplers are used to achieve exposure to realistic mixtures of organic chemicals close to ambient concentrations. The main conclusion is that organic chemicals present in Belgian marine waters do not affect the intrinsic growth rate of Phaeodactylum tricornutum. In this context, caution is needed when extrapolating these results to field conditions. In the present research, results were obtained under laboratory controlled conditions with one single species and thus neglecting possible species interactions. Therefore, prior to extrapolating these results to other diatoms and other groups of phytoplankton species, it is suggested to assess the validity of the results in a mesocosm experiment (including multiple species and different trophic levels) or under field conditions. In addition, in chapter V, the relative contribution of organic chemicals to the growth of a marine diatom is examined. Natural drivers such as nutrients regime, light intensity and temperature explain about 85% of the observed variability in the experimental data. Although the methodology used in chapter V is a standard way to assess toxicity of chemicals, it is not realistic to use just one algal species to represent ecotoxicological effects of an entire phytoplankton community. Therefore in chapter VI, an ecosystem model is used to assess the potential adverse effects of organic contaminants on the total primary production. To do so, we model phytoplankton dynamics using four classical drivers (light and nutrient availability, temperature and zooplankton grazing) and test whether extending this model with a POP-induced phytoplankton growth limitation term improves model fit. As inclusion of monitored concentrations of PCBs and pesticides did not lead to a better model fit, it is suggested that POP-induced growth limitation of marine phytoplankton in the North Sea and the Kattegat is small compared to the limitations caused by the classical drivers. The inferred contribution of POPs to phytoplankton growth limitation is about 1% in Belgian coastal waters, but in the Kattegat POPs explain about 10% of the phytoplankton growth limitation. These results suggest that there are regional differences in the contribution of POPs to the phytoplankton growth limitation. The validity of these conclusions should be further assessed for other substances, other species and higher trophic levels

Selecting relevant predictors: impact of variable selection on model performance, uncertainty and applicability of models in environmental decision making

One of the crucial steps when developing models is the selection of appropriate variables. In this research we assessed the impact variable selection on the model performance and model applicability. Regression trees were built to understand the relationship between the ecological water quality and the physicalchemical and hydromorphological variables. Different model parameterizations and three combinations of explanatory variables were used for developing the trees. Once constructed, they were integrated with the water quality model (PEGASE) and used to simulate the future ecological water quality. These simulations were summarized per combination of explanatory variables and compared. Three key messages summarize our conclusions. First, it was confirmed that different parameterizations alter the statistical reliability of the trees produced. Secondly, it was found that statistical reliability of the models remained stable when different combinations of explanatory variables were implemented. The determination coefficient (R²) ranged from 0.68 to 0.86; Kappa statistic (K) ranged from 0.15 and 0.46; and the percentage of Correctly Classified Instances (CCI) from 33 to 59%. Thirdly, when applying the models on an independent dataset consisting of future physical-chemical water quality data, different conclusions may be taken, depending on the combination of variables used

Application of decision trees to analyze the ecological impact of invasive species in Polder lakes in Belgium

Polder lakes in Belgium are stagnant waters that were flooded by the sea in the past. Over the years, the salinity of these systems decreased. Several of these systems are colonized by invasive species (often related to fish stocking). The aim of this study was to analyze the ecological impact of invasive macroinvertebrates on native species and to assess to what extend physical-chemical variables affected the presence of invasive species. For this, decision trees were constructed, relating the abiotic lake characteristics to the presence of macroinvertebrates (both invasive and non-invasive). The major advantages of the use of single-target decision trees are the transparency of the rule sets and the possibility to use relatively small databases, since these specific systems were hardly monitored until present

Use of habitat suitability modeling in the integrated urban water system modeling of the Drava River (Varazdin, Croatia)

The development of practical tools for providing accurate ecological assessment of rivers and species conditions is necessary to preserve habitats and species, stop degradation and restore water quality. An understanding of the causal mechanisms and processes that affect the ecological water quality and shape macroinvertebrate communities at a local scale has important implications for conservation management and river restoration. This study used the integration of wastewater treatment, river water quality and ecological assessment models to study the effect of upgrading a wastewater treatment plant (WWTP) and their ecological effects for the receiving river. The WWTP and the water quality and quantity of the Drava river in Croatia were modelled in the software WEST. For the ecological modeling, the approach followed was to build habitat suitability and ecological assessment models based on classification trees. This technique allows predicting the biological water quality in terms of the occurrence of macroinvertebrates and the river status according to ecological water quality indices. The ecological models developed were satisfactory, and showed a good predictive performance and good discrimination capacity. Using the integrated ecological model for the Drava river, three scenarios were run and evaluated. The scenario assessment showed that it is necessary an integrated approach for the water management of the Drava river, which considers an upgrading of the WWTP with Nitrogen and Phosphorous removal and the treatment of other diffuse pollution and point sources (including the overflow of the WWTP). Additionally, if an increase in the minimum instream flow after the dams is considered, a higher dilution capacity and a higher self-cleaning capability could be obtained. The results proved that integrated models like the one presented here have an added value for decision support in water management. This kind of integrated approach is useful to get insight in aquatic ecosystems, for assessing investments in sanitation infrastructure of urban wastewater systems considering both, the fulfilling of legal physical chemical emission limits and the ecological state of the receiving waters

Construction of data-driven models to predict the occurrence of planktonic species in the North-Sea

Marine habitat suitability models typically predict the potential distribution of organisms based on basic abiotic variables such as salinity, oxygen concentrations, temperature fluctuations (Gogina & Zettler, 2010) or sediment class information (Degraer et al., 2008; Willems et al., 2008). Recently, Dachs & Méjanelle (2010) claimed that the modification of biota composition due to marine pollution is a factor to be taken into account in marine habitat suitability models. Although the anthropogenic pressure on the environment has been exponentially increasing during the last six decades (Dachs & Méjanelle, 2010), the global effect of human inputs on oceanic phytoplankton remains unknown (Echeveste et al., 2010). A limited number of studies have assessed the impact of anthropogenic stressors on phytoplankton in marine environments at a global level (Faust et al., 2003; Magnusson et al.,2008). In order to fill this knowledge gap, this research tries to determine to what extent pollution data can be used to predict the occurrence of the phytoplanktonic organisms compared to basic abiotic variables. Here we explored this issue by developing classification trees relating physical-chemical variables with the occurrence of the potential harmful toxic algae Odontella sinensis

Multimodel inference to quantify the relative importance of abiotic factors in the population dynamics of marine zooplankton

The effect of multiple stressors on marine ecosystems remains poorly understood and most of the knowledge available is related to phytoplankton. To partly address this knowledge gap, we tested if combining multimodel inference with generalized additive modelling could quantify the relative contribution of environmental variables on the population dynamics of a zooplankton species in the Belgian part of the North Sea. Hence, we have quantified the relative contribution of oceanographic variables (e.g. water temperature, salinity, nutrient concentrations, and chlorophyll a concentrations) and anthropogenic chemicals (i.e. polychlorinated biphenyls) to the density of Acartia clausi. We found that models with water temperature and chlorophyll a concentration explained ca. 73% of the population density of the marine copepod. Multimodel inference in combination with regression-based models are a generic way to disentangle and quantify multiple stressor-induced changes in marine ecosystems. Future-oriented simulations of copepod densities suggested increased copepod densities under predicted environmental changes

Setting priorities in river management using habitat suitability models

Worldwide river systems are under pressure from human development. River managers need to identify the most important stressors in a stream basin, to propose effective management interventions for river restoration. In the European Union, the Water Framework Directive proposes the ecological status as the management endpoint for these interventions. Many decision support tools exist that use predictive water quality models to evaluate different river management scenarios, but only a few consider a river’s ecological status in this analysis explicitly. This paper presents a novel method, which combines abiotic monitoring data and biological monitoring data, to provide information and insight on why the ecological status does not reach the good status. We use habitat suitability models as a decision support tool, which can identify the most important stressors in river systems to define management scenarios. To this end, we disassemble the ecological status into its individual building blocks, i.e., the community composition, and we use habitat suitability models to perform an ecological gap analysis. In this paper, we present our method and its underlying ecological concepts, and we illustrate its benefits by applying the method on a regional level for Flanders using a biotic index, the Multimetric Macroinvertebrate Index Flanders (MMIF). To evaluate our method, we calculated the number of correctly classified instances (CCI = 47.7%) and the root-mean-square error (RMSE = 0.18) on the MMIF class and the MMIF value. Furthermore, there is a monotonic decreasing relationship between the results of the priority classification and the ecological status expressed by the MMIF, which is strengthened by the inclusion of ecological concepts in our method (Pearson’s R2 −0.92 vs. −0.87). In addition, the results of our method are complementary to information derived from the legal targets set for abiotic variables. Thus, our proposed method can further optimize the inclusion of monitoring data for the sake of sustainable decisions in river management

Seasonal and spatial fatty acid profiling of the calanoid copepods Temora longicornis and Acartia clausi linked to environmental stressors in the North Sea

The Belgian part of the North Sea (BPNS) is subjected to multiple environmental stressors. The impact of these stressors includes the modulation of fatty acid (FA) composition of the zooplankton. This study recorded temporal and spatial patterns of the FA profiles of two dominant calanoid copepods within the BPNS: Temora longicornis (Muller, 1785) and Acartia clausi (Giesbrecht, 1889). By means of distance-based linear modelling and by applying multi model inference to generalized additive models, environmental stressors were linked to patterns of the FA profiles of these species. The FA profiles of A. clausi and T. longicornis showed distinct intraspecific, spatial and temporal differences within the BPNS. Temperature and algal food quality (marked by the ratio of silicate concentration to dissolved inorganic nitrogen concentration, SiO4/DIN) were the most important drivers of seasonal fluctuations in the DHA/EPA ratio of both species. DHA/EPA ratio can be used as marker for stress in copepods in the BPNS in order to have a quick indication of food quality changes at the basis of the food web

General health and residential proximity to the coast in Belgium : results from a cross-sectional health survey

The health risks of coastal areas have long been researched, but the potential benefits for health are only recently being explored. The present study compared the general health of Belgian citizens a) according to the EU's definition of coastal ( 50 km), and b) between eight more refined categories of residential proximity to the coast ( 250 km). Data was drawn from the Belgian Health Interview Survey (n = 60,939) and investigated using linear regression models and mediation analyses on several hypothesized mechanisms. Results indicated that populations living 50-100 km. Four commonly hypothesized mechanisms were considered but no indirect associations were found: scores for mental health, physical activity levels and social contacts were not higher at 0-5 km from the coast, and air pollution (PM ic , concentrations) was lower at 0-5 km from the coast but not statistically associated with better health. Results are controlled for typical variables such as age, sex, income, neighbourhood levels of green and freshwater blue space, etc. The spatial urban-rural-nature mosaic at the Belgian coast and alternative explanations are discussed. The positive associations between the ocean and human health observed in this study encourage policy makers to manage coastal areas sustainably to maintain associated public health benefits into the future

Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality

xxxxxWorldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standar