Recent EU-frameworks enforce the implementation of risk mitigation measures for nonpoint-source pesticide pollution in surface waters. Vegetated surface flow treatments systems (VTS) can be a way to mitigate risk of adverse effects in the aquatic ecosystems following unavoidable pollution after rainfall-related runoff events. Studies in experimental wetland cells and vegetated ditch mesocosms with common fungicides, herbicides and insecticides were performed to assess efficiency of VTS. Comprehensive monitoring of fungicide exposure after rainfall-related runoff events and reduction of pesticide concentrations within partially optimised VTS was performed from 2006-2009 at five vegetated detention ponds and two vegetated ditches in the wine growing region of the Southern Palatinate (SW-Germany). Influence of plant density, size related parameters and pesticide properties in the performance of the experimental devices, and the monitored systems were the focus of the analysis. A spatial tool for prediction of pesticide pollution of surface waters after rainfall-related runoff events was programmed in a geographic information system (GIS). A sophisticated and high resolution database on European scale was built for simulation. With the results of the experiments, the monitoring campaign and further results of the EU-Life Project ArtWET mitigation measures were implemented in a georeferenced spatial decision support system. The database for the GIS tools was built with open data. The REXTOX (ratio of exposure to toxicity) Risk Indicator, which was proposed by the OECD (Organisation for Economic Co-operation and Development), was extended, and used for modeling the risk of rainfall-related runoff exposure to pesticides, for all agricultural waterbodies on European scale. Results show good performance of VTS. The vegetated ditches and wetland cells of the experimental systems showed a very high reduction of more than 90% of pesticide concentrations and potential adverse effects. Vegetated ditches and wetland cells performed significantly better than devices without vegetation. Plant density and sorptivity of the pesticide were the variables with the highest explanatory power regarding the response variable reduction of concentrations. In the experimental vegetated ditches 65% of the reduction of peak concentrations was explained with plant density and KOC. The monitoring campaign showed that concentrations of the fungicides and potential adverse effects of the mixtures were reduced significantly within vegetated ditches (Median 56%) and detention ponds (Median 38%) systems. Regression analysis with data from the monitoring campaign identified plant density and size related properties as explanatory variables for mitigation efficiency (DP: R²=0.57, p<0.001; VD: R²=0.19, p<0.001). Results of risk model runs are the input for the second tool, simulating three risk mitigation measures. VTS as risk mitigation measures are implemented using the results for plant density and size related performance of the experimental and monitoring studies, supported by additional data from the ArtWET project. Based on the risk tool, simulations can be performed for single crops, selected regions, different pesticide compounds and rainfall events. Costs for implementation of the mitigation measures are estimated. Experiments and monitoring, with focus on the whole range of pesticides, provide novel information on VTS for pesticide pollution. The monitoring campaign also shows that fungicide pollution may affect surface waters. Tools developed for this study are easy to use and are not only a good base for further spatial analysis but are also useful as decision support of the non-scientific community. On a large scale, the tools on the one hand can help to compute external costs of pesticide use with simulation of mitigation costs on three levels, on the other hand feasible measures mitigating or remediating the effects of nonpoint-source pollution can be identified for implementation. Further study of risk of adverse effects caused by fungicide pollution and long-time performance of optimised VTS is needed.

Freshwaters are of immense importance for human well-being. Nevertheless, they are currently facing unprecedented levels of threat from habitat loss and degradation, overexploitation, invasive species and pollution. To prevent risks to aquatic ecosystems, chemical substances, like agricultural pesticides, have to pass environmental risk assessment (ERA) before entering the market. Concurrently, large-scale environmental monitoring is used for surveillance of biological and chemical conditions in freshwaters. This thesis examines statistical methods currently used in ERA. Moreover, it presents a national-scale compilation of chemical monitoring data, an analysis of drivers and dynamics of chemical pollution in streams and, provides a large-scale risk assessment by combination with results from ERA. Additionally, software tools have been developed to integrate different datasets used in ERA. The thesis starts with a brief introduction to ERA and environmental monitoring and gives an overview of the objectives of the thesis. Chapter 2 addresses experimental setups and their statistical analyses using simulations. The results show that current designs exhibit unacceptably low statistical power, that statistical methods chosen to fit the type of data provide higher power and that statistical practices in ERA need to be revised. In chapter 3 we compiled all available pesticide monitoring data from Germany. Hereby, we focused on small streams, similar to those considered in ERA and used threshold concentrations derived during ERA for a large-scale assessment of threats to freshwaters from pesticides. This compilation resulted in the most comprehensive dataset on pesticide exposure currently available for Germany. Using state-of-the-art statistical techniques, that explicitly take the limits of quantification into account, we demonstrate that 25% of small streams are at threat from pesticides. In particular neonicotinoid pesticides are responsible for these threats. These are associated with agricultural intensity and can be detected even at low levels of agricultural use. Moreover, our results indicated that current monitoring underestimates pesticide risks, because of a sampling decoupled from precipitation events. Additionally, we provide a first large-scale study of annual pesticide exposure dynamics. Chapters 4 and 5 describe software solutions to simplify and accelerate the integration of data from ERA, environmental monitoring and ecotoxicology that is indispensable for the development of landscape-level risk assessment. Overall, this thesis contributes to the emerging discipline of statistical ecotoxicology and shows that pesticides pose a large-scale threat to small streams. Environmental monitoring can provide a post-authorisation feedback to ERA. However, to protect freshwater ecosystems ERA and environmental monitoring need to be further refined and we provide software solutions to utilise existing data for this purpose.

Despite the significant presence of neuroactive substances in the environment, bioassays that allow to detect diverse groups of neuroactive mechanisms of action are not well developed and not properly integrated into environmental monitoring and chemical regulation. Therefore, there is a need to develop testing methods which are amenable for fast and high-throughput neurotoxicity testing. The overall goal of this thesis work is to develop a test method for the toxicological characterization and screening of neuroactive substances and their mixtures which could be used for prospective and diagnostic hazard assessment. In this thesis, the behavior of zebrafish embryos was explored as a promising tool to distinguish between different neuroactive mechanisms of action. Recently, new behavioral tests have been developed including photomotor response (PMR), locomotor response (LMR) and spontaneous tail coiling (STC) tests. However, the experimental parameters of these tests lack consistency in protocols such as exposure time, imaging time, age of exposure, endpoint parameter etc. To understand how experimental parameters may influence the toxicological interpretation of behavior tests, a systematic review of existing behavioral assays was conducted in Chapter 2. Results show that exposure concentration and exposure duration highly influenced the comparability between different test methods and the spontaneous tail coiling (STC) test was selected for further testing based on its relative higher sensitivity and capacity to detect neuroactive substances (Chapter 2). STC is the first observable motor activity generated by the developing neural network of the embryo which is assumed to occur as a result of the innervation of the muscle by the primary motor neurons. Therefore, STC could be a useful endpoint to detect effect on the muscle innervation and also the on the whole nervous system. Consequently, important parameters of the STC test were optimized and an automated workflow to evaluate the STC with the open access software KNIME® was developed (Chapter 3). To appropriately interpret the observed effect of a single chemical and especially mixture effects, requires the understanding of toxicokinetics and biotransformation. Most importantly, the biotransformation capacity of zebrafish embryos might be limited and this could be a challenge for assessment of chemicals such as organophosphates which require a bioactivation step to effectively inhibit the acetylcholinesterase (AChE) enzyme. Therefore, the influence of the potential limited biotransformation on the toxicity pathway of a typical organophosphate, chlorpyrifos, was investigated in Chapter 5. Chlorpyrifos could not inhibit AChE and this was attributed to possible lack of biotransformation in 24 hpf embryos (Chapter 5). Since neuroactive substances occur in the environment as mixtures, it is therefore more realistic to assess their combined effect rather than individually. Therefore, mixture toxicity was predicted using the concentration addition and independent action models. Result shows that mixtures of neuroactive substances with different mechanisms of action but similar effects can be predicted with concentration addition and independent action (Chapter 4). Apart from being able to predict the combined effect of neuroactive substances for prospective risk assessment, it is also important to assess in retrospect the combined neurotoxic effect of environmental samples since neuroactive substances are the largest group of chemicals occurring in the environment. In Chapter 6, the STC test was found to be capable of detecting neurotoxic effects of a wastewater effluent sample. Hence, the STC test is proposed as an effect based tool for monitoring environmental acute and neurotoxic effects. Overall, this thesis shows the utility and versatility of zebrafish embryo behavior testing for screening neuroactive substances and this allows to propose its use for prospective and diagnostic hazard assessment. This will enhance the move away from expensive and demanding animal testing. The information contained in this thesis is of great potential to provide precautionary solutions, not only for the exposure of humans to neuroactive chemicals but for the environment at large.

The increasing, anthropogenic demand for chemicals has created large environmental problems with repercussions for the health of the environment, especially aquatic ecosystems. As a result, the awareness of the public and decision makers on the risks from chemical pollution has increased over the past half-century, prompting a large number of studies in the field of ecological toxicology (ecotoxicology). However, the majority of ecotoxicological studies are laboratory based, and the few studies extrapolating toxicological effects in the field are limited to local and regional levels. Chemical risk assessment on large spatial scales remains largely unexplored, and therefore, the potential large-scale effects of chemicals may be overlooked. To answer ecotoxicological questions, multidisciplinary approaches that transcend classical chemical and toxicological concepts are required. For instance, the current models for toxicity predictions - which are mainly based on the prediction of toxicity for a single compound and species - can be expanded to simultaneously predict the toxicity for different species and compounds. This can be done by integrating chemical concepts such as the physicochemical properties of the compounds with evolutionary concepts such as the similarity of species. This thesis introduces new, multidisciplinary tools for chemical risk assessments, and presents for the first time a chemical risk assessment on the continental scale. After a brief introduction of the main concepts and objectives of the studies, this thesis starts by presenting a new method for assessing the physiological sensitivity of macroinvertebrate species to heavy metals (Chapter 2). To compare the sensitivity of species to different heavy metals, toxicity data were standardized to account for the different laboratory conditions. These rankings were not significantly different for different heavy metals, allowing the aggregation of physiological sensitivity into a single ranking. Furthermore, the toxicological data for macroinvertebrates were used as input data to develop and validate prediction models for heavy metal toxicity, which are currently lacking for a wide array of species (Chapter 3). Apart from the toxicity data, the phylogenetic information of species (evolutionary relationships among species) and the physicochemical parameters for heavy metals were used. The constructed models had a good explanatory power for the acute sensitivity of species to heavy metals with the majority of the explained variance attributed to phylogeny. Therefore, the integration of evolutionary concepts (relatedness and similarity of species) with the chemical parameters used in ecotoxicology improved prediction models for species lacking experimental toxicity data. The ultimate goal of the prediction models developed in this thesis is to provide accurate predictions of toxicity for a wide range of species and chemicals, which is a crucial prerequisite for conducting chemical risk assessment. The latter was conducted for the first time on the continental scale (Chapter 4), by making use of a dataset of 4,000 sites distributed throughout 27 European countries and 91 respective river basins. Organic chemicals were likely to exert acute risks for one in seven sites analyzed, while chronic risk was prominent for almost half of the sites. The calculated risks are potentially underestimated by the limited number of chemicals that are routinely analyzed in monitoring programmes, and a series of other uncertainties related with the limit of quantification, the presence of mixtures, or the potential for sublethal effects not covered by direct toxicity. Furthermore, chemical risk was related to agricultural and urban areas in the upstream catchments. The analysis of ecological data indicated chemical impacts on the ecological status of the river systems; however, it is difficult to discriminate the effects of chemical pollution from other stressors that river systems are exposed to. To test the hypothesis of multiple stressors, and investigate the relative importance of organic toxicants, a dataset for German streams is used in chapter 5. In that study, the risk from abiotic (habitat degradation, organic chemicals, and nutrients enrichment) and biotic stressors (invasive species) was investigated. The results indicated that more than one stressor influenced almost all sites. Stream size and ecoregions influenced the distribution of risks, e.g., the risks for habitat degradation, organic chemicals and invasive species increased with the stream size; whereas organic chemicals and nutrients were more likely to influence lowland streams. In order to successfully mitigate the effects of pollutants in river systems, co-occurrence of stressors has to be considered. Overall, to successfully apply integrated water management strategies, a framework involving multiple environmental stressors on large spatial scales is necessary. Furthermore, to properly address the current research needs in ecotoxicology, a multidisciplinary approach is necessary which integrates fields such as, toxicology, ecology, chemistry and evolutionary biology.

World’s ecosystems are under great pressure satisfying anthropogenic demands, with freshwaters being of central importance. The Millennium Ecosystem Assessment has identified anthropogenic land use and associated stressors as main drivers in jeopardizing stream ecosystem functions and the biodiversity supported by freshwaters. Adverse effects on the biodiversity of freshwater organisms, such as macroinvertebrates, may propagate to fundamental ecosystem functions, such as organic matter breakdown (OMB) with potentially severe consequences for ecosystem services. In order to adequately protect and preserve freshwater ecosystems, investigations regarding potential and observed as well as direct and indirect effects of anthropogenic land use and associated stressors (e.g. nutrients, pesticides or heavy metals) on ecosystem functioning and stream biodiversity are needed. While greater species diversity most likely benefits ecosystem functions, the direction and magnitude of changes in ecosystem functioning depends primarily on species functional traits. In this context, the functional diversity of stream organisms has been suggested to be a more suitable predictor of changes in ecosystem functions than taxonomic diversity. The thesis aims at investigating effects of anthropogenic land use on (i) three ecosystem functions by anthropogenic toxicants to identify effect thresholds (chapter 2), (ii) the organic matter breakdown by three land use categories to identify effects on the functional level (chapter 3) and (iii)on the stream community along an established land-use gradient to identify effects on the community level. In chapter 2, I reviewed the literature regarding pesticide and heavy metal effects on OMB, primary production and community respiration. From each reviewed study that met inclusion criteria, the toxicant concentration resulting in a reduction of at least 20% in an ecosystem function was standardized based on laboratory toxicity data. Effect thresholds were based on the relationship between ecosystem functions and standardized concentration-effect relationships. The analysis revealed that more than one third of pesticide observations indicated reductions in ecosystem functions at concentrations that are assumed being protective in regulation. However, high variation within and between studies hampered the derivation of a concentration-effect relationship and thus effect thresholds. In chapter 3, I conducted a field study to determine the microbial and invertebrate-mediated OMB by deploying fine and coarse mesh leaf bags in streams with forested, agricultural, vinicultural and urban riparian land use. Additionally, physicochemical, geographical and habitat parameters were monitored to explain potential differences in OMB among land use types and sites. Regarding results, only microbial OMB differed between land use types. The microbial OMB showed a negative relationship with pH while the invertebrate-mediated OMB was positively related to tree cover. OMB responded to stressor gradients rather than directly to land use. In chapter 4, macroinvertebrates were sampled in concert with leaf bag deployment and after species identification (i) the taxonomic diversity in terms of Simpson diversity and total taxonomic richness (TTR) and (ii) the functional diversity in terms of bio-ecological traits and Rao’s quadratic entropy was determined for each community. Additionally, a land-use gradient was established and the response of the taxonomic and functional diversity of invertebrate communities along this gradient was investigated to examine whether these two metrics of biodiversity are predictive for the rate of OMB. Neither bio-ecological traits nor the functional diversity showed a significant relationship with OMB. Although, TTR decreased with increasing anthropogenic stress and also the community structure and 26 % of bio-ecological traits were significantly related to the stress gradient, any of these shifts propagated to OMB. Our results show that the complexity of real-world situations in freshwater ecosystems impedes the effect assessment of chemicals and land use for functional endpoints, and consequently our potential to predict changes. We conclude that current safety factors used in chemical risk assessment may not be sufficient for pesticides to protect functional endpoints. Furthermore, simplifying real-world stressor gradients into few land use categories was unsuitable to predict and quantify losses in OMB. Thus, the monitoring of specific stressors may be more relevant than crude land use categories to detect effects on ecosystem functions. This may, however, limit the large scale assessment of the status of OMB. Finally, despite several functional changes in the communities the functional diversity over several trait modalities remained similar. Neither taxonomic nor functional diversity were suitable predictors of OMB. Thus, when understanding anthropogenic impacts on the linkage between biodiversity and ecosystem functioning is of main interest, focusing on diversity metrics that are clearly linked to the stressor in question (Jackson et al. 2016) or integrating taxonomic and functional metrics (Mondy et al., 2012) might enhance our predictive capacity.

The aquatic environment is exposed to multiple environmental pressures and mixtures of chemical substances, among them petroleum and petrochemicals, metals, and pesticides. Aquatic invertebrate communities are used as bioindicators to reflect long-term and integral effects. Information on the presence of species can be supplemented with information on their traits. SPEAR-type bioindicators integrate such trait information on the community level. This thesis aimed at enhancing specificity of SPEAR-type bioindicators towards particular groups of chemicals, namely to mixtures of oil sands-derived compounds, hydrocarbons, and metals. For developing a bioindicator for discontinuous contamination with oil-derived organic toxicants, a field study was conducted in the Canadian oil sands development region in Northern Alberta. The traits ‘physiological sensitivity towards organic chemicals’ and ‘generation time’ were integrated to develop the bioindicator SPEARoil, reflecting the community sensitivity towards oil sands derived contamination in relation to fluctuating hydrological conditions. According to the SPEARorganic approach, a physiological sensitivity ranking of taxa was developed for hydrocarbon contamination originating from crude oil or petroleum distillates. For this purpose, ecotoxicological information from acute laboratory tests was enriched with rapid and mesocosm test results. The developed Shydrocarbons sensitivity values can be used in SPEAR-type bioindicators. To specifically reflect metal contamination in streams via bioindicators, Australian field studies were re-evaluated with focus on the traits ‘physiological metal sensitivity’ and ‘feeding type’. Metal sensitivity values, however, explained community effects in the field only weakly. Instead, the trait ‘feeding type’ was strongly related to metal exposure. The fraction of predators in a community can, thus, serve as an indicator for metal contamination in the field. Furthermore, several metrics reflecting exposure to chemical cocktails in the environment were compared using existing pesticide datasets. Exposure metrics based on the 5% fraction of species sensitivity distributions were found to perform best, however, closely followed by Toxic Unit metrics based on the most sensitive species of a community or Daphnia magna.

Habitat loss and fragmentation due to climate and land-use change are among the biggest threats to biodiversity, as the survival of species relies on suitable habitat area and the possibility to disperse between different patches of habitat. To predict and mitigate the effects of habitat loss, a better understanding of species dispersal is needed. Graph theory provides powerful tools to model metapopulations in changing landscapes with the help of habitat networks, where nodes represent habitat patches and links indicate the possible dispersal pathways between patches. This thesis adapts tools from graph theory and optimisation to study species dispersal on habitat networks as well as the structure of habitat networks and the effects of habitat loss. In chapter 1, I will give an introduction to the thesis and the different topics presented in this thesis. Chapter 2 will then give a brief summary of tools used in the thesis. In chapter 3, I present our model on possible range shifts for a generic species. Based on a graph-based dispersal model for a generic aquatic invertebrate with a terrestrial life stage, we developed an optimisation model that models dispersal directed to predefined habitat patches and yields a minimum time until these patches are colonised with respect to the given landscape structure and species dispersal capabilities. We created a time-expanded network based on the original habitat network and solved a mixed integer program to obtain the minimum colonisation time. The results provide maximum possible range shifts, and can be used to estimate how fast newly formed habitat patches can be colonised. Although being specific for this simulation model, the general idea of deriving a surrogate can in principle be adapted to other simulation models. Next, in chapter 4, I present our model to evaluate the robustness of metapopulations. Based on a variety of habitat networks and different generic species characterised by their dispersal traits and habitat demands, we modeled the permanent loss of habitat patches and subsequent metapopulation dynamics. The results show that species with short dispersal ranges and high local-extinction risks are particularly vulnerable to the loss of habitat across all types of networks. On this basis, we then investigated how well different graph-theoretic metrics of habitat networks can serve as indicators of metapopulation robustness against habitat loss. We identified the clustering coefficient of a network as the only good proxy for metapopulation robustness across all types of species, networks, and habitat loss scenarios. Finally, in chapter 5, I utilise the results obtained in chapter 4 to identify the areas in a network that should be improved in terms of restoration to maximise the metapopulation robustness under limited resources. More specifically, we exploit our findings that a network’s clustering coefficient is a good indicator for metapopulation robustness and develop two heuristics, a Greedy algorithm and a deducted Lazy Greedy algorithm, that aim at maximising the clustering coefficient of a network. Both algorithms can be applied to any network and are not specific to habitat networks only. In chapter 6, I will summarize the main findings of this thesis, discuss their limitations and give an outlook of future research topics. Overall this thesis develops frameworks to study the behaviour of habitat networks and introduces mathematical tools to ecology and thus narrows the gap between mathematics and ecology. While all models in this thesis were developed with a focus on aquatic invertebrates, they can easily be adapted to other metapopulations.