2,6-Dichlorobenzamide (BAM) is a major groundwater micropollutant posing problems for drinking water treatment plants (DWTPs) that depend on groundwater intake. <em>Aminobacter</em> sp. MSH1 uses BAM as the sole source of carbon, nitrogen, and energy and is considered a prime biocatalyst for groundwater bioremediation in DWTPs. Its use in bioremediation requires knowledge of its BAM-catabolic pathway, which is currently restricted to the amidase BbdA converting BAM into 2,6-dichlorobenzoic acid (2,6-DCBA) and the monooxygenase BbdD transforming 2,6-DCBA into 2,6-dichloro-3-hydroxybenzoic acid. Here, we show that the 2,6-DCBA catabolic pathway is unique and differs substantially from catabolism of other chlorobenzoates. BbdD catalyzes a second hydroxylation, forming 2,6-dichloro-3,5-dihydroxybenzoic acid. Subsequently, glutathione-dependent dehalogenases (BbdI and BbdE) catalyze the thiolytic removal of the first chlorine. The remaining chlorine is then removed hydrolytically by a dehalogenase of the <em>α</em>/<em>β</em> hydrolase superfamily (BbdC). BbdC is the first enzyme in that superfamily associated with dehalogenation of chlorinated aromatics and appears to represent a new subtype within the <em>α</em>/<em>β</em> hydrolase dehalogenases. The activity of BbdC yields a unique trihydroxylated aromatic intermediate for ring cleavage that is performed by an extradiol dioxygenase (BbdF) producing 2,4,6-trioxoheptanedioic acid, which is likely converted to Krebs cycle intermediates by BbdG.

<em>Aim:</em> Species distribution models (SDMs) are widely used to study geographic distributions of taxa in response to natural and anthropogenic environmental conditions. For a community, common approaches include fitting individual SDMs (iSDMs) to all taxa or directly modelling community properties such as richness. However, the parameters of iSDMs are difficult to identify for rare taxa, and community properties do not reveal taxon‐specific responses. Individual models can be combined into a hierarchical multispecies distribution model (mSDM) that constrains taxon‐specific parameters according to overarching community parameters, or a joint model (jSDM) in which interdependencies between taxa are jointly inferred. We compare how individual, hierarchical multispecies and joint SDMs differ in quality of fit, explanatory power and predictive performance, and analyse how these properties depend on the prevalence of taxa.<br /><em>Taxa:</em> Presence–absence observations of 245 benthic macroinvertebrate taxa identified at a mixed taxonomic resolution.<br /><em>Location:</em> Four hundred and ninety‐two sites in rivers throughout Switzerland.<br /><em>Methods:</em> Individual, hierarchical and joint hierarchical generalized linear models (GLM) were developed for all taxa. Parameters were estimated using maximum likelihood estimation or Bayesian inference with Hamiltonian Markov chain Monte Carlo simulations. Predictive performance was assessed with cross‐validation. In addition, the predicted family and species richness of the models was compared with a GLM for richness.<br /> Results: Individual models show a slightly higher quality of fit largely due to overfitting for rare taxa. The mSDM achieves a similar quality of fit and explanatory power, mitigates overfitting for rare taxa and considerably improves predictive performance over the whole community. The joint models further improve the quality of fit, but decrease predictive performance and increase predictive uncertainty.<br /><em>Main conclusions:</em> We show that even a relatively simple mSDM combines many of the analytical capabilities of iSDMs and improves predictive performance. Increasingly complex mSDMs and jSDMs provide additional analytical possibilities, but depending on the data and research questions, different levels of complexity may be appropriate.

Temporary streams constitute a significant proportion of rivers globally and are common in wet, cool, temperate regions. These heterogeneous ecosystems harbour high biodiversity associated with the dynamic turnover of taxa. Despite flow permanence being widely recognised as an important environmental control, few studies have characterised biotic responses to long‐term hydrological variability in temporary streams. We examined taxonomic and functional macroinvertebrate communities of perennial and nonperennial river reaches over a 26‐year period. Flow permanence resulted in spatial variation in taxonomic and functional macroinvertebrate communities. Nonperennial river reaches, which were characterised by dynamic habitat provision (lotic, lentic, and dry states) over the study period, supported more heterogeneous communities than perennial river reaches. Hydrological variables, in particular wetted width, water depth, and zero‐flow states, were instrumental in structuring taxonomic and functional communities, although the importance of substrate conditions increased in autumn. Hydrological conditions resulted in separation of perennial and nonperennial taxonomic communities regardless of season, whereas functional communities differed only in spring. Our results emphasise that understanding of community responses to hydrological variability is enhanced by analyses that concurrently explore taxonomic and functional responses to long‐term intraannual and interannual hydrological variability. Moreover, functional responses represent a robust method to test ecological responses to hydrological drivers. Further research that builds on our work is needed to inform the protection of both perennial and nonperennial streams as they adapt to ongoing environmental change.

The <em>leaky pipeline</em> phenomenon refers to the disproportionate decline of female scientists at higher academic career levels and is a major problem in the natural sciences. Identifying the underlying causes is challenging, and thus solving the problem remains difficult. To better understand the reasons for the leaky pipeline, we assess the perceptions and impacts of gender bias and imbalance—two major drivers of the leakage—at different academic career levels with an anonymous survey in geoscience academia (<em>n</em>=1220). The survey results show that both genders view male geoscientists as substantially more gender‐biased than female scientists. Moreover, female geoscientists are more than twice as likely to experience negative gender bias at their workplaces and scientific organizations compared to male geoscientists. There are also pronounced gender differences regarding (i) the relevance of role models, (ii) family‐friendly working conditions and (iii) the approval of gender quotas for academic positions. Given the male dominance in senior career levels, our results emphasize that those feeling less impacted by the negative consequences of gender bias and imbalance are the ones in position to tackle the problem. We thus call for actions to better address gender biases and to ensure a balanced gender representation at decision‐making levels to ultimately retain more women in geoscience academia.

Sensor drift is commonly observed across engineering disciplines, particularly in harsh media such as wastewater. In this study, a novel stabilizing controller for nitrification of high strength ammonia solutions is designed based on online signal derivatives. The controller uses the derivative of a drifting nitrite signal to determine if nitrite-oxidizing bacteria (NOB) are substrate limited or substrate inhibited. To ensure a meaningful interpretation of the derivative signal, the process is excited in a cyclic manner by repeatedly exposing the NOB to substrate-limited and substrate-inhibited conditions. The resulting control system successfully prevented nitrite accumulations for a period of 72 days in a laboratory-scale reactor. Slow disturbances in the form of feed composition changes and temperature changes were successfully handled by the controller while short-term temperature disturbances are shown to pose a challenge to the current version of this controller. Most importantly, we demonstrate that drift-tolerant control for the purpose of process stabilization can be achieved without sensor redundancy by combining deliberate input excitation, qualitative trend analysis, and coarse process knowledge.

Ice-covered periods might significantly contribute to lake emissions at ice-melt, yet a comprehensive understanding of under-ice carbon dioxide (CO₂) dynamics is still lacking. This study investigated the processes driving spatiotemporal patterns of under-ice CO₂ in large Lake Onego. In March 2015 and 2016, under-ice CO₂, dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) distributions were measured along a river to an open-lake transect. CO₂ decreased from 120/129 μmol L⁻¹ in the river to 51/98 μmol L⁻¹ in the bay, and 34/36 μmol L⁻¹ in the open lake, while DOC decreased from 1.18/1.55 mmol L⁻¹ in the river to 0.67/1.04 mmol L⁻¹ in the bay in 2015 and 2016, respectively. These decreases in concentrations with increasing distance from the river mouth indicate that river discharge modulates spatial patterns of under-ice CO₂. The variability between the 2 years was mainly driven by river discharge and ice transparency affecting the extent of under-ice convection. Higher discharge during winter 2016 resulted in higher CO₂ concentrations in the bay. By contrast, intensive under-ice convection led to lower, more homogeneously distributed CO₂ in 2015. In conclusion, the river-to-bay transition zone is characterized by strong CO₂ variability and is therefore an important zone to consider when assessing the CO₂ budget of large lakes.

We investigated radiatively driven under-ice convection in Lake Onego (Russia) during 3 consecutive late winters. In ice-covered lakes, where the temperature of water is below the temperature of maximum density, radiatively driven heating in the upper water column induces unstable density distributions leading to gravitational convection. In this work, we quantified the key parameters to characterise the radiatively driven under-ice convection: (1) the effective buoyancy flux, <em>B_*</em> (driver), and its vertical distribution; (2) the convective mixed-layer thickness, <em>h</em>_{<em>C</em><em>M</em><em>L</em>} (depth scale); and (3) the convective velocity,<em>w_*</em>(kinematic scale). We compared analytical <em>w_*</em> scaling estimates to in situ observations from high-resolution acoustic Doppler current profilers. The results show a robust correlation between <em>w_*</em> and the direct observations, except during the onset and decay of the solar radiation. Our results highlight the importance of accurately defining the upper limit of <em>h</em>_CML in highly turbid water and the need for spectrally resolving solar radiation measurements and their attenuation for accurate <em>B_*</em> estimates. Uncertainties in the different parameters were also investigated. We finally examined the implications of under-ice convection for the growth rate of nonmotile phytoplankton and provide a simple heuristic model as a function of easily measurable parameters.

Identifying objectives is essential for decision making, but individuals have difficulties stating their important objectives. In public and environmental decisions, the diverse views of stakeholders should be included, but eliciting a broad set of objectives is challenging. We (1) study the effectiveness of individual brainstorming for eliciting objectives in a real-world setting; (2) test three interventions to support individuals in generating objectives; (3) investigate which and how many stakeholders are necessary to generate a comprehensive set of objectives; and (4) develop a feasible elicitation procedure for practice. In an experimental test, 71 stakeholders participated in five decisions about regional wastewater infrastructure planning in Switzerland. Three interventions were tested with an online survey procedure: (i) providing category cues, (ii) a perspective-taking task, and (iii) providing a predefined master list of objectives. In simple brainstorming, participants stated few objectives (<em>M</em> = 3.3) associated with 2.9 different categories on average. Participants consistently missed objectives they later considered important. Providing a master list was the only intervention that substantially increased the number and breadth of objectives (<em>M</em> = 12 objectives in <em>M</em> = 5.3 categories). With the help of our survey, participants generated between 30 and 38 distinct objectives for each decision case. Between five and nine participants were sufficient to generate these; more participants did not contribute new objectives. Most decision makers need help generating their objectives; combining simple brainstorming with a master list is a straightforward improvement that does not require a facilitator. An online process is promising for involving a large group of stakeholders.

Ensemble modelling was used to assess the robustness of projected impacts of pumped‐storage (PS) operation and climate change on reservoir ice cover. To this end, three one‐dimensional and a two‐dimensional laterally averaged hydrodynamic model were set up. For the latter, the strength of the impacts with increasing distance from the dam was also investigated. Climate change effects were simulated by forcing the models with 150 years of synthetic meteorological time series created with a weather generator based on available air temperature scenarios for Switzerland. Future climate by the end of the 21^st century was projected to shorten the ice‐covered period by ~2 months and decrease ice thicknesses by ~13 cm. Under current climate conditions, the ice cover would already be affected by extended PS operation. For example, the average probability of ice coverage on a specific day was projected to decrease by ~13% for current climate and could further be reduced from ~45% to ~10% for future climate. Overall, the results of all models were consistent. Although the number of winters without ice cover was projected to increase for all one‐dimensional models, studying individual segments of the two‐dimensional model showed that the impact was pronounced for segments close to the PS intake/outlet. In summary, the reservoir's ice cover is expected to partially vanish with higher probability of open water conditions closer to the PS intake/outlet.

Eutrophication of shallow lakes often triggers a series of cascading ecological effects. Among these are shifts in the zooplankton community structure due to phytoplankton changes, or shifts in the fish community reducing size-selective feeding of planktivorous fish. In such conditions, larger zooplankton (e.g. <em>Daphnia</em>) can have a selective advantage. Re-oligotrophication can reverse such food-web interactions. Europe’s largest wetland system (the Danube Delta) went through a period of eutrophication and is now slowly recovering again. However, changes in the <em>Daphnia</em> populations triggered by eutrophication in this system have remained unstudied. We used different sampling strategies to screen 24 lakes (which differ in their ecological state) for the presence of <em>Daphnia</em> as well as for biotic and abiotic parameters potentially explaining <em>Daphnia</em> abundance<em>. Daphnia</em> densities were surprisingly low. We found <em>D. magna</em> ephippia in the sediment, but no <em>D. magna</em> in the water column. Microsatellite analyses on pelagic <em>Daphnia</em> populations confirmed the presence of the <em>D. longispina</em> complex and provided evidence for significant hybridisation events. FluoroProbe data showed that <em>Daphnia</em> was mainly present in lakes with a higher phytoplankton production. Our study provides insights into the spatial and temporal distribution of <em>Daphnia</em> in a very dynamic wetland system.

Repeated and independent emergence of trait divergence that matches habitat differences is a sign of parallel evolution by natural selection. Yet, the molecular underpinnings that are targeted by adaptive evolution often remain elusive. We investigate this question by combining genome-wide analyses of copy number variants (CNVs), single nucleotide polymorphisms (SNPs), and gene expression across four pairs of lake and river populations of the three-spined stickleback (<em>Gasterosteus aculeatus</em>). We tested whether CNVs that span entire genes and SNPs occurring in putative <em>cis</em>-regulatory regions contribute to gene expression differences between sticklebacks from lake and river origins. We found 135 gene CNVs that showed a significant positive association between gene copy number and gene expression, suggesting that CNVs result in dosage effects that can fuel phenotypic variation and serve as substrates for habitat-specific selection. Copy number differentiation between lake and river sticklebacks also contributed to expression differences of two immune-related genes in immune tissues, <em>cathepsin A</em> and <em>GIMAP7</em>. In addition, we identified SNPs in <em>cis</em>-regulatory regions (eSNPs) associated with the expression of 1865 genes, including one eSNP upstream of a carboxypeptidase gene where both the SNP alleles differentiated and the gene was differentially expressed between lake and river populations. Our study highlights two types of mutations as important sources of genetic variation involved in the evolution of gene expression and in potentially facilitating repeated adaptation to novel environments.<br />

Zwei Studien der Eawag und des Oekotoxzentrums zeigen erneut, dass Gewässer in landwirtschaftlich genutzten Einzugsgebieten stark mit Pflanzenschutzmitteln belastet sind. Die Konzentrationen einzelner Stoffe stellen über Monate hinweg ein Risiko für chronische Schäden dar und liegen längere Zeit über Werten, ab denen für Pflanzen und Tiere im Wasser ein akut toxisches Risiko besteht. Untersuchungen der Artenvielfalt in den Bächen und Biotests bestätigen die Gefahr, welche von diesen Stoffgemischen ausgeht.

Nitrification of wastewater requires control for the purposes of efficiency and of stability. However, first, the highly complex microbial community in wastewater treatment plants and very different compositions of wastewaters impede a complete understanding of nitrification. Second, the determination of the states of the process is seldom exact because sensors are subject to a high level of wear and tear. Consequently, instrumentation, control, and automation (ICA) of nitrification processes are a challenge. I hypothesize that soft-sensors - based on the signals of robust, physical sensors - and specially designed control loops, which do not need redundant information to correct for drift, can reduce the maintenance needs for the control of nitrification. Consequently, the econonomical application range for ICA of nitrification processes can be extended.<br /> A large part of this thesis is dedicated to the stabilisation of urine nitrification as a pretreatment for nutrient recovery. To this end, an online nitrite detection and an according control of the process are required. Furthermore, the thesis comprises an ammonia aeration controller, which is based on pH signals, to be used in municipal wastewater. The four chapters of the thesis focus on the following topics.<br /> The first chapter investigates calibration experiments for in-line UV-Vis sensors. Such sensors can serve as soft-sensors for numerous substances. With differently designed experiments, data for the calibration of UV-Vis based nitrite models in high strength wastewater was recorded. Online experiments executed in-situ allow calibrating similarly exact models like experiments which are conducted by spiking additional nitrite. The good performance of the models being based on online experiments is explained by the correlation of other light-absorbing substances in the process with nitrite.<br /> The second chapter evaluates the potential of a stoichiometry-based soft-sensor for nitrite. The stoichiometry of nitrification theoretically allows distinguishing the ammonia and the nitrite oxidation rates by means of the derivatives of the dissolved oxygen and of the pH signal and in turn detecting nitrite accumulations. We show that under relatively ideal conditions the dynamics in the ratio of the two derivatives show similarities with the dynamics in the nitrite concentration. Factors that deteriorate this information quality are identified.<br /> The third part of this thesis investigates how drifting sensor signals can be used as an input for a feedback controller without relying on redundant information to correct this drift. The controller shall prevent uncontrolled nitrite accumulation in a urine nitrification system. To this end, the controller does not use the absolute value of the nitrite signal, but its 1^st and 2^nd derivative as inputs. By controlled accumulation and degradation of nitrite, the controller can keep the derivatives continuously informative. The switch from substrate inhibition to substrate limitation of the nitrite oxidising bacteria can be identified by means of the inflection point in the signal. The developed controller is tested successfully on a lab-scale reactor.<br /> The fourth chapter of this thesis describes an ammonia based aeration controller. These controllers usually require maintenance intensive instrumentation. Therefore a new ammonia soft sensor for continuously operated municipal wastewater treatment plants is developed. It relies on the 1^st derivative of a pH difference measured over the aerated zone. This soft sensor is successfully tested in a controller deployed on various municipal wastewater treatment plants. The controller was designed to increase its robustness towards drift in the pH signals.

We compared taxon composition of the <em>Daphnia longispina</em> hybrid community, as reconstructed from dormant eggs (retrieved from sediment samples) and the pelagic population (retrieved from formaldehyde-preserved zooplankton samples), from the same lake and of the same time period. As microsatellite markers do not work on largely fragmented DNA, such as of formaldehyde-preserved samples, both types of samples (dormant eggs and pelagic <em>Daphnia</em>) were screened with single-nucleotide polymorphism (SNP) markers. Here, we designed a genotyping panel of short SNP-bearing amplicons and, to facilitate screening, we developed a multiplex genotyping protocol. The results of this comparison confirmed differences between dormant and pelagic samples. Specifically, <em>D. galeata</em> was overrepresented in the sedimentary egg bank in comparison to the pelagic population, indicating that this taxon is more involved in sexual reproduction than other taxa. In addition to being successfully applied on formaldehyde-preserved samples, SNP-genotyping was more efficient than microsatellites on sedimentary eggs, and was more sensitive for hybrid detection. In conclusion, the SNP-based genotyping panel presented here enables to study the genetic structure of past populations from common formaldehyde-preserved collections. It is also promising for genotyping old dormant eggs, which can extend the temporal range of <em>Daphnia</em> community reconstructions.<br />

Titanium dioxide nanoparticles (TiO₂ NPs) are widely incorporated in various consumer products such as cosmetics and food. Despite known human exposure, the potential risks of TiO₂ NPs during pregnancy are not fully understood, but several studies in mice elucidated toxic effects on fetal development. It has also been shown that modifying NPs with positive or negative surface charge alters cellular uptake and abolishes fetotoxicity of silicon dioxide (SiO₂) NPs in mice.<br /> Here, we investigated accumulation and translocation of positively charged TiO₂-NH₂ and negatively charged TiO₂-COOH NPs at the placental barrier, to clarify whether surface charge provides a means to control TiO₂ NP distribution at the placental barrier. To ensure outcome relevant for humans, the recently developed <em>in vitro</em> human placental co-culture model and the gold standard amongst placental translocation models – the <em>ex vivo</em> perfusion of human term placental tissue - were employed during this study. Sector field-ICP-MS analysis of maternal and fetal supernatants as well as placental cells/tissues revealed a substantial accumulation of both TiO₂ NP types while no considerable placental translocation was apparent in both models. Characterization of agglomeration behavior demonstrated a strong and fast agglomeration of TiO₂-NH₂ and TiO₂-COOH NPs in the different culture media.<br /> Overall, our results indicate that surface charge is not a key factor to steer placental uptake and transfer of TiO₂. Moreover, the negligible placental transfer but high accumulation of TiO₂ NPs in placental tissue suggests that potential effects on fetal health may occur indirectly, which calls for further studies elucidating the impact of TiO₂ NPs on placental tissue functionality and signaling.

Governments in countries across the world increasingly adopt the “green growth” discourse to underline their ambition for the greening of their economies. The central tenet of this narrative is the economic opportunities rather than challenges arising from the pursuit of environmental sustainability. Our paper synthesises insights from 113 recent scientific articles, dealing with both environmental issues and economic growth, as well as innovation. Our ambition is exploratory in attempting to take stock of heterogeneous contributions across the spectrum of social science. The articles have been reviewed with a focus on six themes, derived from current discussions in economic geography and transition studies: skills, technology, physical resources, markets, institutions and policies. Four major implications emerge from the review. First, green growth requires competences that allow for handling complex, non-routine situations – in both the private and the public sector. Second, technological progress should be directed towards greener technologies, to avoid investments funds being channelled to brown technologies for short-term returns. Third, our knowledge of the opportunities for achieving green growth must base upon a joint assessment of market failures, structural system failures and transformational system failures. Finally, greater attention should be devoted to the geography of green growth processes at different scales.

Achieving effective, sustainable environmental governance requires a better understanding of the causes and consequences of the complex patterns of interdependencies connecting people and ecosystems within and across scales. Network approaches for conceptualizing and analysing these interdependencies offer one promising solution. Here, we present two advances we argue are needed to further this area of research: (i) a typology of causal assumptions explicating the causal aims of any given network-centric study of social–ecological interdependencies; (ii) unifying research design considerations that facilitate conceptualizing exactly what is interdependent, through what types of relationships and in relation to what kinds of environmental problems. The latter builds on the appreciation that many environmental problems draw from a set of core challenges that re-occur across contexts. We demonstrate how these advances combine into a comparative heuristic that facilitates leveraging case-specific findings of social–ecological interdependencies to generalizable, yet context-sensitive, theories based on explicit assumptions of causal relationships.

<em>Background</em>: Mental disorders, particularly depression and post-traumatic stress disorder, are common long-term psychological outcomes in emergency contexts arising from conflicts, natural disasters, and other challenging environmental conditions. In emergencies, people suffer not only from the lack of external resources such as drinking water and food but also from poor mental health. Mental disorders can substantially impair daily activities in vulnerable individuals. However, water, sanitation, and hygiene (WASH) behaviors are daily activities that require effort, time, and strong internal motivation. Therefore, questions arise: whether there is a relationship between mental health and safe water behaviors, and if so, whether the motivational drivers of these behaviors are affected by mental health.<br /><em>Methods</em>: Our cross-sectional study conducted face-to-face interviews with 638 households in rural Malawi. We used a quantitative questionnaire based on the risks, attitudes, norms, abilities, and self-regulation (RANAS) approach to measure motivational psychosocial factors. Mental health was assessed using the validated Chichewa version of the Self-Reporting Questionnaire (SRQ-20). Results. Almost a third of the respondents reported poor mental health. We found significant negative association between mental health and self-reported safe water collection (<em>p</em> = .01, <em>r</em> = −.104) but not between safe water transportation and storage behavior. The moderation analysis revealed significant interaction effects of mental health with some psychosocial factors and therefore on WASH behaviors. Poor mental health changed the influence of three psychosocial factors—perceived others’ behavior, commitment, and remembering—on safe drinking water collection behavior. The influence on water transportation and storage behavior of the perceived severity of contracting a disease, the belief that transporting and storing water requires substantial effort, and others’ approval depended on the mental health condition of the respondent.<br /><em>Conclusions</em>: These results imply that populations with a significant proportion of individuals with poor mental health will benefit from interventions to mitigate mental health before or parallel to behavioral change interventions for WASH. Specific population-level interventions have been shown to have a positive effect on mental well-being, and they have been successfully applied at scale. This research is especially relevant in emergency contexts, as it indicates that mental health measures before any WASH interventions will make them more effective.

The concept of “advocacy coalitions” is the bedrock of the Advocacy Coalition Framework (ACF), one of the most established and successful approaches for understanding policy processes across the globe. This article revisits and sharpens the conceptual definition of advocacy coalitions. We summarize the lessons from its theoretical emphases under the ACF and specify its five attributes (policy actors, shared beliefs, coordination, resources, and stability). Through this specification, we identify the ideal coalition type and several coalition subtypes. We then clarify and make a distinction between how we think about coalitions as a concept and how we approach coalitions empirically. This article sharpens the lens for describing and explaining coalitions toward better observations, theorizing, and measurements. It ends with next steps for further deepening and broadening knowledge about advocacy coalitions.

An in vitro model of the fish intestine is of interest for research and application in diverse fields such as fish physiology, aquaculture and chemical risk assessment. The recently developed epithelial barrier model of the fish intestine relies on the RTgutGC cell line from rainbow trout (<em>Oncorhynchus mykiss</em>), cultured in inserts on permeable membranes. Our aim was to extend the current system by introducing intestinal fibroblasts as supportive layer in order to reconstruct the epithelial–mesenchymal interface as found in vivo. We therefore initiated and characterized the first fibroblast cell line from the intestine of rainbow trout, which has been termed RTgutF. Co-culture studies of RTgutGC and RTgutF were performed on commercially available electric cell substrate for impedance sensing (ECIS) and on newly developed ultrathin, highly porous alumina membranes to imitate the cellular interaction with the basement membrane. Cellular events were examined with non-invasive impedance spectroscopy to distinguish between barrier tightness and cell density in the ECIS system and to determine transepithelial electrical resistance for cells cultured on the alumina membranes. We highlight the relevance of the piscine intestinal fibroblasts for an advanced intestinal barrier model, particularly on ultrathin alumina membranes. These membranes enable rapid crosstalk of cells cultured on opposite sides, which led to increased barrier tightening in the fish cell line-based epithelial–mesenchymal model.<br />

More than 60% of the spionid polychaetes recorded in South Africa to date have type localities from outside the region. One of these is <em>Rhynchospio glutaea</em> (Ehlers, 1897), originally described from Argentina, which was suggested to have arrived in Table Bay via shipping. Recently specimens conforming to the description of <em>R. glutaea</em> were collected on the south coast of South Africa from within the effluent outflow pipes from an on-shore abalone farm. The species, here named <em>Rhynchospio mzansi</em> n. sp., belongs to the <em>Rhynchospio glutaea</em> complex, and has tridentate hooded hooks that usually start on chaetiger 15–18 and up to four pairs of dorsal anal cirri. Four molecular markers confirm that the South African material is a previously undescribed species that is the most basal of the other species within the <em>R. glutaea</em> complex and genetically closest to <em>R. glutaea</em> and <em>R. arenincola</em> Hartmann, 1936, from the west coast of North America<em>.</em> This is the first species in this genus described for South Africa.

We present the laboratory results of immersion freezing efficiencies of cellulose particles at supercooled temperature (<em>T</em>) conditions. Three types of chemically homogeneous cellulose samples are used as surrogates that represent supermicron and submicron ice-nucleating plant structural polymers. These samples include microcrystalline cellulose (MCC), fibrous cellulose (FC) and nanocrystalline cellulose (NCC). Our immersion freezing dataset includes data from various ice nucleation measurement techniques available at 17 different institutions, including nine dry dispersion and 11 aqueous suspension techniques. With a total of 20 methods, we performed systematic accuracy and precision analysis of measurements from all 20 measurement techniques by evaluating <em>T</em>-binned (1 ^∘C) data over a wide <em>T</em> range (−36 ^∘C &lt;<em>T</em>&lt;−4 ^∘C). Specifically, we intercompared the geometric surface area-based ice nucleation active surface site (INAS) density data derived from our measurements as a function of <em>T</em>, <em>n</em>_s,geo(<em>T</em>). Additionally, we also compared the <em>n</em>_s,geo(<em>T</em>) values and the freezing spectral slope parameter (Δlog(<em>n</em>s,geo)/Δ<em>T</em>) from our measurements to previous literature results. Results show all three cellulose materials are reasonably ice active. The freezing efficiencies of NCC samples agree reasonably well, whereas the diversity for the other two samples spans ≈ 10 ^∘C. Despite given uncertainties within each instrument technique, the overall trend of the <em>n</em>_s,geo(<em>T</em>) spectrum traced by the <em>T</em>-binned average of measurements suggests that predominantly supermicron-sized cellulose particles (MCC and FC) generally act as more efficient ice-nucleating particles (INPs) than NCC with about 1 order of magnitude higher <em>n</em>_s,geo(<em>T</em>).

Despite being preventable, foodborne diseases remain a global health challenge. Poor food hygiene practices such as improper handling of kitchen utensils are among the major causes of diarrhea transmission. A formative study was conducted in Malawi to inform an intervention design to promote complementary food hygiene practices. An assessment of contextual and psychosocial factors for behavior change was conducted using Risk, Attitude, Norms, Ability, and Self-regulation model. We conducted 323 household surveys with caregivers of children aged 6 to 24 months. Analysis of variance was used to estimate difference between doers and non-doers of three targeted behaviors: washing utensils with soap, keeping utensils on a raised place, and handwashing with soap. Analysis of variance analyses revealed that literacy level, ownership of animals, and presence of handwashing facility and dish racks were contextual factors predicting storage of utensils on an elevated place and handwashing frequencies. Psychosocial factors, such as time spent to wash utensils with soap, distance to the handwashing facility, and cost for soap, had an influence on washing utensils and handwashing practices. Perceived vulnerability determined effective handwashing and storage of utensils. Perceived social norms and ability estimates were favorable for the three targeted behaviors. Promotion of already existing targeted beneficial behaviors should be encouraged among caregivers. Risk perceptions on storage of utensils and handwashing practices should be increased with motivational exercises such as paint games. Caregivers’ technical know-how of local dish rack and tippy tap construction is essential.<br />

Purifying and functionalising multi-walled carbon nanotubes (MWCNTs) are important processes for providing property modifications, improving handling and enhancing reactivity. The removal of impurities allows avoiding synthesis process interferences and the formation of by-products. During the process it is possible to change the MWCNT properties, e.g. providing enhanced hydrophilicity and better chemical reactivity. In this work, a two-step procedure of MWCNT functionalisation with non-oxidative and oxidative agents is presented. Firstly, hydrochloric acid was used to remove catalyst impurities, which remain after the synthesis process. Secondly, nitric acid was employed to oxidise the MWCNT surfaces and incorporate carboxylic groups onto the surface.

Aquatic oligochaetes are important bioindicators of sediment quality in watercourses and lakes, but their morphological identification to the species level is challenging and sometimes impossible. The use of DNA barcoding and metabarcoding could greatly facilitate the identifications of specimens and improve ecological diagnoses based on oligochaete communities. The aim of this study was to test how well metabarcoding approaches based on high throughout sequencing (HTS) could perform in assessing oligochaete species diversity and the biological quality of sediments. We analysed oligochaete communities at several sites in Swiss rivers, comparing morphological data to metabarcoding of mixed specimen, sieved sediment and total sediment samples. We amplified the cytochrome <em>c</em> oxidase (COI) marker using universal primers and/or specific primers to metazoans. Our results showed that metabarcoding analysis of mixed specimens allowed a more representative assessment of the biodiversity than the metabarcoding of sieved or total sediments. Although community structures obtained with the morphological and metabarcoding analyses were different in term of presence/absence of species and species abundances, the ecological diagnoses based on these two approaches largely agreed.

<em>Motivation.</em> Our surface water is impacted by a wide variety of contaminants released through human activities. One contaminant group of concern is micropollutants, which can have eco-toxicological effects in trace concentrations. Micropollutants, for example, include plant protection products and biocides, which are specifically designed to harm organisms. An important input pathway of micropollutants to surface water can be untreated sewer overflows (combined sewer overflows and stormwater outlets). However, the understanding of factors influencing the occurrence and levels of micropollutants is limited and challenged by: i) high spatial differences among sites, ii) a large number of discharge sites and iii) high temporal fluctuating discharge events.<br /><br /><em>Research objective.</em> This thesis intends to enhance our understanding of micropollutants in sewer overflows. It aims to investigate efficient methods to prioritize sewer overflow sites, which can be potentially harmful for receiving waters. The presented work focuses on the development of model prediction and efficient monitoring approaches and includes the following: i) a Swiss-wide model to assess how many discharge sites may be critical (Chapter 2), ii) fundamentals to develop passive sampling as an alternative monitoring method for short duration sewer overflows (Chapter 3 and 4) and iii) an extended monitoring study covering 20 combined sewer overflows (CSOs) to explore spatial differences among sites (Chapter 5). The main findings of this thesis are presented in the following.<br /><br /><em>Model-based screening.</em> A dynamic substance flow modeling approach was applied to 2,500 Swiss municipalities, considering micropollutant accumulation and wash-off on urban surfaces. The approach is based on the simplification, that there is one CSO and one stormwater outlet per municipality. The model allows for an estimation of the micropollutant concentration fluctuations in sewer overflows in 10-min resolution. The results show the importance of untreated discharges from sewer overflows as emission into receiving waters. The load contribution to sewer overflows of micropollutants in stormwater (e.g. plant protection products and biocides) is estimated to be considerably higher than of micropollutants in municipal wastewater (e.g. pharmaceuticals and other household chemicals). In addition, the results indicate that up to 83% of all urban catchments have sewer overflows that need to rely on upstream dilution in order to not exceed substance-specific environmental quality standards (EQS). Thus, this nationwide screening approach clearly highlights the need for a more detailed assessment of micropollutants in sewer overflows, and especially, the need for more measured data to allow the development of validated micropollutant prediction models.<br /><br /><em>Measuring.</em> Difficulties of monitoring sewer overflows with traditional methods are i) high concentration fluctuations with unknown event durations which require a high temporal sampling resolution, ii) many discharge sites and iii) placement, operation, and maintenance of equipment. Hence, passive samplers for polar organic micropollutants are analyzed systematically as a viable alternative to monitor short duration sewer overflows. The main advantage of passive samplers is the continuous accumulation of contaminants from the water phase, with no need for external energy sources nor for immense water sample storage volume. In a first step, the impact of fluctuating concentrations on deviations from true time-weighted average (TWA) concentrations was studied. The results highlight that the deviations induced by fluctuating concentrations are similar or smaller than uncertainties arising from chemical analysis and environmental factors. Understanding the uptake mechanism of micropollutants is one of the most important issues that needs to be resolved to reduce uncertainties in passive sampling data. The uptake experiments in sewer conditions for short duration events (&lt;36h) indicate that the mass transfer is either dominated by the sorbent, or, by a multi-step mechanism. Therefore, a new semi-empirical mixed rate control model is proposed, which can be directly used for future studies under similar conditions. A field validation (3 locations, 10 events) shows that TWA concentration estimates measured by passive samplers are within a factor of 0.4 to 3.1 compared to composite water samples. Hence, the use of upper limit TWA concentration estimates is recommended for compliance checking with EQS. The findings clearly show that passive samplers are suitable to estimate TWA concentration ranges in sewer overflows and, thus facilitate identification of potentially critical discharge sites.<br /><br /><em>Occurrence of micropollutants. </em>Unique monitoring data from 20 CSO sites was collected with passive samplers. In total 13 polar organic micropollutants were analysed in 95 events (2-7 events per site). The results highlight indicator micropollutants, which were often found in the monitored CSOs and could be used in future monitoring studies: diclofenac, benzotriazole, carbamazepine, diazinon, diuron, carbendazim, mecoprop, metolachlor and terbutryn. Further, our results reveal that the spatial differences among CSO sites are bigger than the inter-event differences within a site for all studied micropollutants. Nevertheless, no significant correlation with land use data could be identified. The results, therefore, suggest that additional factors, most likely the contaminant usage pattern, have a considerable influence on the observed spatial differences. Both municipal wastewater and stormwater contributed to concentrations above the EQS in CSOs (not in the receiving water). In addition, the monitoring with passive samplers indicates that at least 13 out of 20 CSOs show concentrations above EQS in CSOs, and would rely on dilution by receiving waters to not exceed EQS.<br /><br /><em>Outlook.</em> Overall, the thesis shows the relevance of sewer overflows as a source of micropollutants entering receiving water bodies. The findings can serve as a basis for the development of a systematic and stepwise approach to efficiently identify critical sites. The development of such an approach would require joint efforts by eco-toxicologists, analytical chemists, regulators and wastewater engineers. This approach could be based on a simplified modeling approach as a first indicator, followed by passive sampling to assess micropollutant levels. To enable the widespread application of passive samplers in monitoring programs, regulators’ and operators’ confidence in passive sampling needs to be strengthened with more field validation studies and common guidelines.

Research and policy processes in many fields, such as sustainability and health, are increasingly relying on transdisciplinary cooperation among a multitude of governmental, nongovernmental, and private actors from local to global levels. In the absence of hierarchical chains of command, multistakeholder governance may accommodate conflicting or diverse interests and facilitate collective action, but its effectiveness depends on its capacity to integrate systems, transformation, and target knowledge. Approaches to foster such governance are nascent and quickly evolving, and methodological standards to facilitate comparison and learning from best practice are needed. However, there is currently no evaluation approach that (i) comprehensively assesses the capacity for knowledge integration in multistakeholder governance, (ii) draws on the best available knowledge that is being developed in various fields, and (iii) combines a systematic and transferable methodological design with pragmatic feasibility.<br /><br /> We brought together 20 experts from institutions in nine countries, all working on evaluation approaches for collaborative science–policy initiatives. In a synthesis process that included a 2-day workshop and follow-up work among a core group of participants, we developed a tool for evaluating knowledge integration capacity in multistakeholder governance (EVOLvINC). Its 23 indicators incorporate previously defined criteria and components of transdisciplinary evaluations into a single, comprehensive framework that operationalizes the capacity for integrating systems, target, and transformation knowledge during an initiative’s (a) design and planning processes at the policy formulation stage, (b) organization and working processes at the implementation stage, and (c) sharing and learning processes at the evaluation stage of the policy cycle. EVOLvINC is (i) implemented through a questionnaire, (ii) builds on established indicators where possible, (iii) offers a consistent and transparent semiquantitative scoring and aggregation algorithm, and (iv) uses spider diagrams for visualizing results. The tool builds on experience and expertise from both the northern and southern hemispheres and was empirically validated with seven science–policy initiatives in six African and Asian countries.<br /><br /> As a generalized framework, EVOLvINC thus enables a structured reflection on the capacity of multistakeholder governance processes to foster knowledge integration. Its emphasis on dialog and exploration allows adaptation to contextual specificities, highlights relative strengths and weaknesses, and suggests avenues for shaping multistakeholder governance toward mutual learning, capacity building, and strengthened networks. The validation suggests that the adaptive capacity of multistakeholder governance could be best enhanced by considering systems characteristics at the policy formulation stage and fostering adaptive and generic learning at the evaluation stage of the policy cycle.

Floodplain ecosystems are some of the most biodiverse ecosystems on earth. This level of biodiversity is sustained by a great diversity of habitats and ecological niches, resulting from the interaction between the natural flow and sediment regimes. However, the ecological integrity of floodplains is rapidly deteriorating worldwide because of human activities. Flow regulation for hydropower production is one of the main drivers of ecological degradation in freshwaters and in floodplains in particular. Dams, impoundments and diversions result in a simplification of the natural flow regime, which becomes less variable, this in turn drives a simplification of the riverscape and a decrease in its biodiversity and ecological functioning. The general aim of this thesis is to investigate how communities of aquatic macroinvertebrates are shaped by hydrology in an alluvial floodplain in order to refine our understanding of hydrology – biodiversity linkages in complex ecosystems. To achieve this aim, I conducted an extensive field survey and an innovative field experiment on the Maggia River floodplain, in southern Switzerland. First, I investigated how different flooding regimes and recent flooding history lead to different community structures amongst floodplain habitats. I found that frequent flooding favored rheophilic species over more lentic groups, and limited strong competitive interactions to occur by maintaining low periphyton standing crops. Then, I developed a novel experimental setup, where 24 ponds were excavated out of two gravel bars in the floodplain, and monitored macroinvertebrate metacommunity assembly over 45 days. I showed that the interaction between the local environment and the degree of connectivity to the regional species pool can lead to different assembly trajectories through time. The findings of the experiment were then broadly compared to the temporal changes in metacommunity organization observed in the natural habitats. There, I found that local environmental conditions and the degree of landscape connectivity greatly affected metacommunity structure. Most importantly, I showed that metacommunity organization changed in time during post-disturbance metacommunity assembly, and that the temporal shifts between the main structuring processes differed with the dispersal ability of species. Finally, I used stable isotope analyses to calculate the food chain length within macroinvertebrate communities, and assessed how it responded to gradients of habitat size, productivity and disturbance regime. There, I showed that flooding reduced food chain length, because predators were feeding at lower trophic levels in frequently disturbed habitats. Overall, this study shows that maintaining flow variability and spatial heterogeneity in flood disturbance is key to sustaining floodplain aquatic biodiversity. My research also contributes to the field of metacommunity ecology by showing that metacommunity organization is highly variable in time and especially during assembly after disturbance.

The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources – e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis – keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.

Ubiquitous sensing will create many opportunities and threats for urban water management, which are only poorly understood today. To identify the most relevant trends, we conducted a horizon scan regarding how ubiquitous sensing will shape the future of urban drainage and wastewater management. Our survey of the international urban water community received an active response from both the academics and the professionals from the water industry. The analysis of the responses demonstrates that emerging topics for urban water will often involve experts from different communities, including aquatic ecologists, urban water system engineers and managers, as well as information and communications technology professionals and computer scientists. Activities in topics that are identified as novel will either require (i) cross-disciplinary training, such as importing new developments from the IT sector, or (ii) research in new areas for urban water specialists, for example, to help solve open questions in aquatic ecology. These results are, therefore, a call for interdisciplinary research beyond our own discipline. They also demonstrate that the water management community is not yet prepared for the <em>digital transformation</em>, where we will experience a data demand, i.e. a “pull” of urban water data into external services. The results suggest that a lot remains to be done to harvest the upcoming opportunities. Horizon scanning should be repeated on a routine basis, under the umbrella of an experienced polling organization.

Principal component analysis (PCA) is by far the most widespread tool for unsupervised learning with high-dimensional data sets. It is popularly studied for exploratory data analysis and online process monitoring. Unfortunately, fine-tuning PCA models and particularly the number of components remains a challenging task. Today, this selection is often based on a combination of guiding principles, experience, and process understanding. Unlike the case of regression, where cross-validation of the prediction error is a widespread and trusted approach for model selection, there are no tools for PCA model selection enjoying this level of acceptance. In this work, we address this challenge and evaluate the utility of the cross-validated ignorance score with both simulated and experimental data sets. Application of this model selection criterion is based on the interpretation of PCA as a density model, as in probabilistic principal component analysis. With simulation-based benchmarking, it is shown to be (a) the overall best performing criterion, (b) the preferred criterion at high noise levels, and (c) very robust to changes in noise level. Tests on experimental data sets suggest that the ignorance score is sensitive to deviations from the PCA model structure, which suggests the criterion is also useful to detect of model-reality mismatch.

Studies worldwide have demonstrated through <em>in vitro</em> bioassays and chemical analysis that endocrine-disrupting chemicals (EDCs) can accumulate in river sediments. However, remobilization of sediment-bound EDCs due to bioturbation or re-suspension during flood events remains poorly understood. The aim of this study was to evaluate the bioavailability of EDCs, more specifically estrogenic compounds (EC), from sediment under turbulent conditions using a passive sampling approach. Sediment was sampled along the Luppe River, Germany, previously described as a "hotspot" for ECs. The concentration of target ECs and estrogenic activity were investigated using chemical analysis (LC MS/MS) in addition to a novel screening tool (planar Yeast Estrogen Screen; p-YES) that utilizes high performance thin-layer chromatography plates in combination with an <em>in vitro</em> bioassay (YES). Estrone (50%, E1) and nonylphenol (35%, NP) accounted for the majority of estrogenic activity reported of up to 20 ± 2.4 μg E2 equivalents per kg dry weight in the Luppe sediments. Two types of passive samplers (polar organic chemical integrative sampler (POCIS) and Chemcatcher) were used to investigate the bioavailability of ECs from suspended sediment under laboratory conditions. NP, E1, E2 and ethynylestradiol (EE2) were remobilized from Luppe sediment when subjected to turbulent conditions, such as in a flood event, and were readily bioavailable at ecotoxicologically relevant concentrations (NP 18 μg/L, E1 14 ng/L, E2 0.2 ng/L, EE2 0.5 ng/L).

Microbial biofilms in gravity-driven membrane (GDM) filtration systems can efficiently degrade the cyanotoxin microcystin (MC), but it is unclear if this function depends on the presence of MC-producing cyanobacteria in the source water habitat. We assessed the removal of MC from added <em>Microcystis aeruginosa</em> biomass in GDMs fed with water from a lake with regular blooms of toxic cyanobacteria (ExpL) or from a stream without such background (ExpS). While initial MC removal was exclusively due to abiotic processes, significantly higher biological MC removal was observed in ExpL. By contrast, there was no difference in MC degradation capacity between lake and stream bacteria in separately conducted liquid enrichments on pure MC. Co-occurrence network analysis revealed a pronounced modularity of the biofilm communities, with a clear hierarchic distinction according to feed water origin and treatment type. Genotypes in the network modules associated with ExpS had significantly more links to each other, indicating that these biofilms had assembled from a more coherent source community. In turn, signals for stochastic community assembly were stronger in ExpL biofilms. We propose that the less “tightly knit” ExpL biofilm assemblages allowed for the better establishment of facultatively MC degrading bacteria, and thus for higher overall functional efficiency.<br />

Basic understanding of formation of aerobic granular sludge (AGS) has mainly been derived from lab-scale systems with simple influents containing only highly diffusible volatile fatty acids (VFA) as organic substrate. This study compares start-up of AGS systems fed by different synthetic and municipal wastewaters (WW), characterised by increasing complexity in terms of non-diffusible organic substrate. Four AGS reactors were started with the same inoculum activated sludge and operated for one year. The development of AGS, settling characteristics, nutrient and substrate removal performance as well as microbial community composition were monitored. Our results indicate that the higher the content of diffusible organic substrate in the WW, the faster the formation of AGS. The presence of non-diffusible organic substrate in the influent WW led to the formation of small granules and to the presence of 20–40% (% of total suspended solids) of flocs in the AGS. When AGS was fed with complex influent WW, the classical phosphorus and glycogen accumulating organisms (PAO, GAO) were outcompeted by their fermentative equivalents. Substrate and nutrient removal was observed in all reactors, despite the difference in physical and settling properties of the AGS, but the levels of P and N removal depended on the influent carbon composition. Mechanistically, our results indicate that increased levels of non-diffusible organic substrate in the influent lower the potential for microbial growth deep inside the granules. Additionally, non-diffusible organic substrates give a competitive advantage to the main opponents of AGS formation – ordinary heterotrophic organisms (OHO). Both of these mechanisms are suspected to limit AGS formation. The presented study has relevant implications for both practice and research. Start-up duration of AGS systems treating high complexity WW were one order of magnitude higher than a typical lab-scale system treating VFA-rich synthetic WW, and biomass as flocs persisted as a significant fraction. Finally, the complex synthetic influent WW – composed of VFA, soluble fermentable and particulate substrate - tested here seems to be a more adequate surrogate of real municipal WW for laboratory studies than 100%-VFA WW.

Inaccurate description of uncertainty in the error models can cause biases in parameter estimation. When the parameters of the deterministic model and the error model are inferred jointly from the observations, the posterior converges to regions that reflect the processes in both high and low flows. If the nature of errors in low and high flows is different to the extent that the same error description cannot be used for both, biases in inference are introduced. In such cases, the parameter posterior will adjust to the region of the hydrograph with longer proportionate presence in the calibration time series. In this paper we demonstrate that the autoregressive order 1 (AR1) description of errors can lead to sub-optimally performing predictive models if the calibration period has substantial sections of inadequately modelled flows. Inference is performed within the Bayesian framework. We show this for a synthetic example as well as a case study. We also see that the predictive uncertainty bands that we get using the AR1 description can be overconfident and also admit negative values. To mitigate this, we analyze an alternative to additive error models. We use a distribution with a non-negative support, gamma in this study, reflecting the uncertainty in the system response at every time step. The gamma distribution is conditioned on the deterministic model output, which determines its mode and standard deviation. We capture autocorrelation in time using copulas. Given that copulas can capture dependence between different marginals, we use different specifications of the marginal distribution for high and low flows. The results show that 1) biases in parameter estimation can be reduced if a representative error description is attained using the flexibility of a copula-based likelihood. 2) The non-negative support allows to make more realistic uncertainty intervals for low flows. 3) However, the autocorrelation parameter in copulas severely interacts with the model and heteroscedasticity parameters. 4) While the formulation, in principle, should be of added value for parameter inference, in case of less informative priors, the flexibility of this description can produce non-robust inference.

Out of the &gt;107 million chemicals already registered with the Chemical Abstracts Services, less than 0.5% are being regulated, and even fewer are evaluated for their safety. Consequently, a new paradigm in risk assessment is urgently needed. It should encompass faster and less costly methods and reduce the number of animals needed for testing. One proposal is to combine computational modeling with small-scale bioassay methods. This chapter describes the methods that link in vitro bioassays using fish cells with physiologically based toxicokinetic (PBTK) modeling in order to predict the acute toxicity, bioaccumulation, and impact of chemicals on fish growth. The main focus is on PBTK modeling; thus all the model equations and parameters available for eight fish species as well as suggestions for possible software implementation will be provided. The PBTK model described here can account for respiratory and dietary uptake routes and for chemical biotransformation processes.

Awareness concerning sustainable groundwater consumption under the context of land use and climate change is gaining traction, raising the bar for adequate understanding of the complexities of natural and anthropogenic processes and how they affect groundwater quality. The heterogeneous characteristics of aquifers have hampered comprehensive source, transport and contaminant identification. As questions remain about the behavior and prediction of well-known groundwater contaminants, new concerns around emerging contaminants are on the increase. This review highlights some of the key contaminants that originate from anthropogenic activities, organized based on land use categories namely agricultural, urban and industrial. It further highlights the extensive overlap, in terms of both provenance as well as contaminant type, between the different land use sectors. A selection of case studies from literature that describe the continued concern of established contaminants, as well as new and emerging compounds, are presented to illustrate the many qualitative threats to global groundwater resources. In some cases, the risk of groundwater contamination lacks adequate gravity, while in others the underlying physical and societal processes are not fully understood and activities may commence without adequately considering potential impacts. In the agricultural context, the historic and current application of fertilizers and plant protectants, use of veterinary pharmaceuticals and hormones, strives to safeguard the growing food demands. In the context of a sprawling urban environment, waste, human pharmaceuticals, and urban pesticide outputs are increasing, with adequate runoff and sanitation infrastructure often lagging. Finally, industrial activities are associated with accidental leaks and spills, while the large-scale storage of industrial byproducts has led to legacy contaminants such as those stemming from raw mineral extraction. With this review paper, we aim to underscore the need for transdisciplinary research, along with transboundary communication, using sound science and adaptive policy and management practice in order to procure sustainable groundwater quality.

The persistence of ecological systems in changing environments requires energy, materials, and information. Although the importance of information to ecological function has been widely recognized, the fundamental principles of ecological science as commonly expressed do not reflect this central role of information processing. We articulate five fundamental principles of ecology that integrate information with energy and material constraints across scales of organization in living systems. We show how these principles outline new theoretical and empirical research challenges, and offer one novel attempt to incorporate them in a theoretical model. To provide adequate background for the principles, we review major concepts and identify common themes and key differences in information theories spanning physics, biology and semiotics. We structured our review around a series of questions about the role information may play in ecological systems: (i) what is information? (ii) how is information related to uncertainty? (iii) what is information processing? (iv) does information processing link ecological systems across scales? We highlight two aspects of information that capture its dual roles: <em>syntactic information</em> defining the processes that encode, filter and process information stored in biological structure and <em>semiotic information</em> associated with structures and their context. We argue that the principles of information in living systems promote a unified approach to understanding living systems in terms of first principles of biology and physics, and promote much needed theoretical and empirical advances in ecological research to unify understanding across disciplines and scales.<br />

Sensor maintenance is time-consuming and is a bottleneck for monitoring on-site wastewater treatment systems. Hence, we compare maintained and unmaintained sensors to monitor the biological performance of a small-scale sequencing batch reactor (SBR). The sensor types are ion-selective pH, optical dissolved oxygen (DO), and oxidation-reduction potential (ORP) with platinum electrode. We created soft sensors using engineered features: ammonium valley for pH, oxidation ramp for DO, and nitrite ramp for the ORP. Four soft sensors based on unmaintained pH sensors correctly identified the completion of the ammonium oxidation (89–91 out of 107 cycles), about as many times as soft sensors based on a maintained pH sensor (91 out of 107 cycles). In contrast, the DO soft sensor using data from a maintained sensor showed slightly better (89 out of 96 cycles) detection performance than that using data from two unmaintained sensors (77, respectively 82 out of 96 correct). Furthermore, the DO soft sensor using maintained data is much less sensitive to the optimisation of cut-off frequency and slope tolerance than the soft sensor using unmaintained data. The nitrite ramp provided no useful information on the state of nitrite oxidation, so no comparison of maintained and unmaintained ORP sensors was possible in this case. We identified two hurdles when designing soft sensors for unmaintained sensors: i) Sensors’ type- and design-specific deterioration affects performance. ii) Feature engineering for soft sensors is sensor type specific, and the outcome is strongly influenced by operational parameters such as the aeration rate. In summary, the results with the provided soft sensors show that frequent sensor maintenance is not necessarily needed to monitor the performance of SBRs. Without sensor maintenance monitoring smalls-scale SBRs becomes practicable, which could improve the reliability of unstaffed on-site treatment systems substantially.

The heritable endosymbiont <em>Spiroplasma</em> infects many insects and has repeatedly evolved the ability to protect its hosts against different parasites. Defenses do not come for free to the host, and theory predicts that more costly symbionts need to provide stronger benefits to persist in host populations. We investigated the costs and benefits of <em>Spiroplasma</em> infections in pea aphids (<em>Acyrthosiphon pisum</em>), testing 12 bacterial strains from three different clades. Virtually all strains decreased aphid lifespan and reproduction, but only two had a (weak) protective effect against the parasitoid <em>Aphidius ervi</em>, an important natural enemy of pea aphids. <em>Spiroplasma</em>‐induced fitness costs were variable, with strains from the most slowly evolving clade reaching higher titers and curtailing aphid lifespan more strongly than other strains. Some <em>Spiroplasma</em> strains shared their host with a second endosymbiont, <em>Regiella insecticola</em>. Although the result of an unfortunate handling error, these co‐infections proved instructive, because they showed that the cost of infection with <em>Spiroplasma</em> may be attenuated in the presence of <em>Regiella</em>. These results suggest that mechanisms other than protection against <em>A. ervi</em> maintain pea aphid infections with diverse strains of <em>Spiroplasma</em>, and that studying them in isolation will not provide a complete picture of their effects on host fitness.

Many parasites alter their host's phenotype in a manner that enhances their own fitness beyond the benefits they would gain from normal exploitation. Such host manipulation is rarely consistent with the host's best interests resulting in suboptimal and often fatal behavior from the host's perspective. In this case, hosts should evolve resistance to host manipulation. The cestode <em>Schistocephalus solidus</em> manipulates the behavior of its first intermediate copepod host to reduce its predation susceptibility and avoid fatal premature predation before the parasite is ready for transmission to its subsequent host. Thereafter, <em>S. solidus</em> increases host activity to facilitate transmission. If successful, this host manipulation is necessarily fatal for the host. I selected the copepod <em>Macrocyclops albidus</em>, a first intermediate host of <em>S. solidus,</em> for resistance or susceptibility to host manipulation to investigate their evolvability. Selection on the host indeed increased host manipulation in susceptible and reduced host manipulation in resistant selection lines. Interestingly, this seemed to be at least partly due to changes in the baseline levels of the modified trait (activity) rather than actual changes in resistance or susceptibility to host manipulation. Hence, hosts seem restricted in how rapidly and efficiently they can evolve resistance to host manipulation.

Resource recovery from faecal sludge can take many forms, including as a fuel, soil amendment, building material, protein, animal fodder, and water for irrigation. Resource recovery as a solid fuel has been found to have high market potential in Sub-Saharan Africa. Laboratory- and pilot-scale research on faecal sludge solid fuel production exists, but it is unclear which technology option is most suitable in which conditions. This review offers an overview and critical analysis of the current state of technologies that can produce a dried or carbonized solid fuel, including drying, pelletizing, hydrothermal carbonization, and slow-pyrolysis. Carbonization alters fuel properties, and in faecal sludge, it concentrates the ash content and decreases the calorific value. Overall, a non-carbonized faecal sludge fuel is recommended, unless a carbonized product is specifically required by the combustion technology or end user. Carbonized and non-carbonized fuels have distinct characteristics, and deciding whether to char or not to char is a key judgement in determining the optimal solid fuel technology option. Based on the existing evidence, this review provides a decision-making structure for selecting the optimal technology to produce a faecal sludge solid fuel and identifies the top research needs prior to full-scale implementation.

This thesis investigates meta-ecosystem processes in streams. It specifically considers decomposition, a key ecosystem function, and how it is governed by terrestrial and aquatic landscapes and communities. Using a combination of field surveys, laboratory and field experiments, and statistical modeling, this thesis shows that the local distribution of freshwater biodiversity results from a combination of deterministic and stochastic processes, while the amount and identity of terrestrial subsidies entering streams at the reach scale is controlled by human land use decisions. Finally, this thesis scales mechanisms operating at the between-individual level up to the landscape level to provide estimates of ecosystem functioning in entire stream catchments.

Species interactions lie at the heart of many theories of macroevolution, from adaptive radiation to the Red Queen. Although some theories describe the imprint that interactions will have over long time scales, we are still missing a comprehensive understanding of the effects of interactions on macroevolution. Current research shows strong evidence for the impact of interactions on macroevolutionary patterns of trait evolution and diversification, yet many macroevolutionary studies have only a tenuous relationship to ecological studies of interactions over shorter time scales. We review current research in this area, highlighting approaches that explicitly model species interactions and connect them to broad‐scale macroevolutionary patterns. We also suggest that progress has been made by taking an integrative interdisciplinary look at individual clades. We focus on African cichlids as a case study of how this approach can be fruitful. Overall, while the evidence for species interactions shaping macroevolution is strong, further work using integrative and model‐based approaches is needed to spur progress towards understanding the complex dynamics that structure communities over time and space.<br />

Parasites can shape the structure and function of ecosystems by influencing both the density and traits of their hosts. Such changes in ecosystems are particularly likely when the host is a predator that mediates the dynamics of trophic cascades. Here, we experimentally tested how parasite load of a small predatory fish, the threespine stickleback, can affect the occurrence and strength of trophic cascades and ecosystem functioning. In a factorial mesocosm experiment, we manipulated the density of stickleback (low vs. high), and the level of parasite load (natural vs. reduced). In addition, we used two stickleback populations from different lineages: an eastern European lineage with a more pelagic phenotype (Lake Constance) and a western European lineage with a more benthic phenotype (Lake Geneva). We found that stickleback caused trophic cascades in the pelagic but not the benthic food chain. Evidence for pelagic trophic cascades was stronger in treatments where parasite load of stickleback was reduced with an antihelmintic medication, and where fish originated from Lake Constance (i.e., the more pelagic lineage). A structural equation model revealed that differences in stickleback lineage and parasite load were most likely to impact trophic cascades via changes in the composition, rather than overall biomass, of zooplankton communities. Overall, our results provide experimental evidence that parasites of predators can influence the cascading effects of fish on lower trophic levels with consequences on ecosystem functioning.

The historic emissions of polar micropollutants in a natural drinking water source were investigated by non-target screening with high-resolution mass spectrometry and open cheminformatics tools. The study area consisted of a riverbank filtration transect fed by the river Lek, a branch of the lower Rhine, and exhibiting up to 60-year travel time. More than 18,000 profiles were detected. Hierarchical clustering revealed that 43% of the 15 most populated clusters were characterised by intensity trends with maxima in the 1990s, reflecting intensified human activities, wastewater treatment plant upgrades and regulation in the Rhine riparian countries. Tentative structure annotation was performed using automated <em>in silico</em> fragmentation. Candidate structures retrieved from ChemSpider were scored based on the fit of the <em>in silico</em> fragments to the experimental tandem mass spectra, similarity to openly accessible accurate mass spectra, associated metadata and presence in a suspect list. 67 unique structures (72 over both ionisation modes) were tentatively identified, 25 of which were confirmed and included contaminants so far unknown to occur in bank filtrate or in natural waters at all, such as tetramethylsulfamide. This study demonstrates that many classes of hydrophilic organics enter riverbank filtration systems, persisting and migrating for decades if biogeochemical conditions are stable.

An important goal in toxicology is the development of new ways to increase the speed, accuracy and applicability of chemical hazard and risk assessment approaches. A promising route for this is the integration of <em>in vitro</em> assays with biological pathway information. Here we examine how the Adverse Outcome Pathway (AOP) framework can be used to develop pathway based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from <em>in vitro</em> to <em>in vivo</em>, and to extrapolate across species. Finally, we identified best practices for modeling, model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of a quantitative AOP models and ultimately their use in regulatory applications.

This study reports the use of the recently developed EASZY assay that uses transgenic cyp19a1b-GFP zebrafish (<em>Danio rerio</em>) embryos to assess <em>in vivo</em> estrogenic activity of 33 surface (SW) and waste water (WW) samples collected across Europe that were previously well-characterized for estrogen hormones and <em>in vitro</em> estrogenic activity. We showed that 18 out of the 33 SW and WW samples induced estrogenic responses in the EASZY assay leading to a significant and concentration-dependent up-regulation of the ER-regulated <em>cyp19a1b</em> gene expression in the developing brain. The <em>in vivo</em> 17β-estradiol-equivalents (EEQs) were highly correlated with, both, the chemical analytical risk quotient (RQ) based on steroidal estrogen concentrations and EEQs reported from five different <em>in vitro </em> reporter gene assays. Regression analyses between the vitro and <em>in vivo</em> effect concentrations allowed us to determine an optimal cut-off value for each <em>in vitro </em> assay, above which <em>in vivo</em> responses were observed. These <em>in vitro</em> assay-specific effect-based trigger values (EBTs), ranging from 0.28 to 0.58 ng EEQ/L define the sensitivity and specificity of the individual <em>in vitro </em> assays for predicting a risk associated with substances acting through the same mode of action in water samples. Altogether, this study demonstrates the toxicological relevance of <em>in vitro</em>-based assessment of estrogenic activity and recommends the use of such <em>in vitro/in vivo</em> comparative approach to refine and validate EBTs for mechanism-based bioassays.

The outbreak of the Ebola virus disease (EVD) from 2014 to 2016 is over. However, several outbreaks of contagious diseases have already arisen and will recur. This paper aims to evaluate the effectiveness of EVD prevention promotions in the Gambia and to assess the psychosocial factors that steer three behaviors: handwashing with soap, calling the Ebola Hotline, and not touching a person who might be suffering from EVD. In 2015, data were gathered from 498 primary care providers. The questionnaire was based on psychosocial factors from the risks, attitudes, norms, abilities, and self-regulation (RANAS) model. Three promotional activities were significantly associated with psychosocial factors of handwashing and, thus, with increased handwashing behavior: the home visit, posters, and info sheets. Norm factors, especially the perception of what other people do, had a great impact on handwashing with soap and on calling the Ebola Hotline. The perceived certainty that a behavior will prevent a disease was a predictor for all three protection behaviors. Commitment to the behavior emerged as especially relevant for the intention to call the Ebola Hotline and for not touching a person who might be suffering from EVD. Health behavior change programs should rely on evidence to target the right psychosocial factors and to maximize their effects on prevention behaviors, especially in emergency contexts.