Rectal colonization by resistant bacteria increases the risk of infection by the colonizing strain in critically ill patients with cirrhosis.

BACKGROUND & AIMS: It remains unclear whether rectal colonization with multidrug-resistant organisms (MDROs) is prevalent and predisposes to infections by the same pathogens in patients with cirrhosis. METHODS: Two series of critically ill patients were evaluated. In the Barcelona cohort, 486 consecutive patients were prospectively evaluated, 129 with and 357 without cirrhosis (2015-2016). Rectal swabs were performed at admission and weekly thereafter (until intensive care unit [ICU] discharge) to detect MDRO colonization. Risk factors for colonization and infection by MDROs were evaluated. A retrospective cohort from Frankfurt (421 patients with cirrhosis; 2010-2018) was investigated to evaluate MDRO rectal colonization in another epidemiological scenario. RESULTS: In the Barcelona cohort, 159 patients were colonized by MDROs (32.7%), 102 (64.2%) at admission and 57 (35.8%) during follow-up. Patients with cirrhosis showed higher rates of rectal colonization at admission than those without cirrhosis (28.7% vs. 18.2%, p = 0.01) but similar colonization rates during ICU stay. Extended-spectrum beta-lactamase-Enterobacterales were the most frequent MDROs isolated in both groups. Colonization by MDROs independently increased the risk of infection by MDROs at admission and during follow-up. Risk of new infection by the colonizing strain was also significantly increased in patients with (hazard ratio [HR] 7.41) and without (HR 5.65) cirrhosis. Rectal colonization by MDROs was also highly prevalent in Frankfurt (n = 198; 47%; 131 at admission [66.2%] and 67 [33.8%] during follow-up), with vancomycin-resistant enterococci being the most frequent colonizing organism. Rectal colonization by MDROs was also associated with an increased risk of infection by MDROs in this cohort. Infections occurring in MDR carriers were mainly caused by the colonizing strain. CONCLUSION: Rectal colonization by MDROs is extremely frequent in critically ill patients with cirrhosis. Colonization increases the risk of infection by the colonizing resistant strain. LAY SUMMARY: Rectal colonization by multidrug-resistant organisms (MDROs) is a prevalent problem in patients with cirrhosis requiring critical care. The pattern of colonizing bacteria is heterogeneous with relevant differences between centers. Colonization by MDROs is associated with increased risk of infection by the colonizing bacteria in the short term. This finding suggests that colonization data could be used to guide empirical antibiotic therapy and de-escalation policies in patients with cirrhosis.

Surgical ciliated cyst after a mandibular surgery: a particular case report and review of the literature.

BACKGROUND: Surgical ciliated cyst is a rare clinicopathological lesion that appears in patients who undergo maxillofacial surgery. In this report we present a particular mandibular case and we discuss the etiopathogenesis and clinicopathological features of this pathology after reviewing the current literature, as well as the origin of its respiratory epithelial profile. CASE PRESENTATION: The patient is a 67-year-old male with an irregular radiolucency in a previously tooth extracted area of the mandible. The histopathological study revealed a cystic lesion with a connective wall with chronic inflammation, partially lined by a ciliated pseudostratified epithelium. PAS and CK19 stains showed the respiratory characteristics of this epithelium and confirmed the final diagnosis of mandibular surgical ciliated cyst. CONCLUSIONS: Surgical ciliated cyst is an uncommon entity associated with maxillofacial surgical procedures with bone and nasal cartilage grafts. In our case, treatment with growth factors present in platelet-rich plasma could explain the respiratory changes observed in the cystic epithelial lining."

Stream microbial communities and ecosystem functioning show complex responses to multiple stressors in wastewater.

Multiple anthropogenic drivers are changing ecosystems globally, with a disproportionate and intensifying impact on freshwater habitats. A major impact of urbanization are inputs from wastewater treatment plants (WWTPs). Initially designed to reduce eutrophication and improve water quality, WWTPs increasingly release a multitude of micropollutants (MPs; i.e., synthetic chemicals) and microbes (including antibiotic-resistant bacteria) to receiving environments. This pollution may have pervasive impacts on biodiversity and ecosystem services. Viewed through multiple lenses of macroecological and ecotoxicological theory, we combined field, flume, and laboratory experiments to determine the effects of wastewater (WW) on microbial communities and organic-matter processing using a standardized decomposition assay. First, we conducted a mensurative experiment sampling 60 locations above and below WWTP discharges in 20 Swiss streams. Microbial respiration and decomposition rates were positively influenced by WW inputs via warming and nutrient enrichment, but with a notable exception: WW decreased the activation energy of decomposition, indicating a "slowing" of this fundamental ecosystem process in response to temperature. Second, next-generation sequencing indicated that microbial community structure below WWTPs was altered, with significant compositional turnover, reduced richness, and evidence of negative MP influences. Third, a series of flume experiments confirmed that although diluted WW generally has positive influences on microbial-mediated processes, the negative effects of MPs are "masked" by nutrient enrichment. Finally, transplant experiments suggested that WW-borne microbes enhance decomposition rates. Taken together, our results affirm the multiple stressor paradigm by showing that different aspects of WW (warming, nutrients, microbes, and MPs) jointly influence ecosystem functioning in complex ways. Increased respiration rates below WWTPs potentially generate ecosystem "disservices" via greater carbon evasion from streams and rivers. However, toxic MP effects may fundamentally alter ecological scaling relationships, indicating the need for a rapprochement between ecotoxicological and macroecological perspectives.

Interactive effects of foundation species on ecosystem functioning and stability in response to disturbance.

A major challenge in ecology is to understand determinants of ecosystem functioning and stability in the face of disturbance. Some important species can strongly shape community structure and ecosystem functioning, but their impacts and interactions on ecosystem-level responses to disturbance are less well known. Shallow ponds provide a model system in which to study the effects of such species because some taxa mitigate transitions between alternative ecosystem states caused by eutrophication. We performed pond experiments to test how two foundation species (a macrophyte and a mussel) affected the biomass of planktonic primary producers and its stability in response to nutrient additions. Individually, each species reduced phytoplankton biomass and tended to increase rates of recovery from disturbance, but together the species reversed these effects, particularly with larger nutrient additions. This reversal was mediated by high cyanobacterial dominance of the community and a resulting loss of trait evenness. Effects of the foundation species on primary producer biomass were associated with effects on other ecosystem properties, including turbidity and dissolved oxygen. Our work highlights the important role of foundation species and their interactive effects in determining responses of ecosystem functioning to disturbance.

The predictability of a lake phytoplankton community, over time-scales of hours to years.

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics.

Density constrains cascading consequences of warming and nitrogen from invertebrate growth to litter decomposition.

Smaller invertebrate body mass is claimed to be a universal response to climate warming. It has been suggested that body mass could also predict consumer influences on ecosystem processes in a warmer world because generalized rules describe relationships between body mass, temperature, and metabolism. However, the utility of this suggestion remains tenuous because the nutritional and physiological constraints underlying relationships between body mass and consumer-driven processes are highly variable in realistic settings. Here we test, using a generalist invertebrate detritivore, fungi, and leaf litter, the limitations imposed by nutrition on growth and decomposition in response to global change. Strong competition for fungal food resources limited invertebrate growth and reduced body mass plasticity in response to warming and nitrogen pollution scenarios. When competition was relaxed by experimentally reducing invertebrate density, consumption of fungi promoted rapid invertebrate growth and enhanced invertebrate sensitivity to the global change scenarios, especially warming and nitrogen pollution together. Accordingly, fungi promoted invertebrate body mass plasticity and mediated consumer effects on decomposition causing the relative influence of warming and nitrogen pollution to vary across trophic levels. An important implication is that managing nitrogen pollution may alter which trophic level is most sensitive to warming.

Genotypic trait variation modifies effects of climate warming and nitrogen deposition on litter mass loss and microbial respiration.

Intraspecific variation in genotypically determined traits can influence ecosystem processes. Therefore, the impact of climate change on ecosystems may depend, in part, on the distribution of plant genotypes. Here we experimentally assess effects of climate warming and excess nitrogen supply on litter decomposition using 12 genotypes of a cosmopolitan foundation species collected across a 2100 km latitudinal gradient and grown in a common garden. Genotypically determined litter-chemistry traits varied substantially within and among geographic regions, which strongly affected decomposition and the magnitude of warming effects, as warming accelerated litter mass loss of high-nutrient, but not low-nutrient, genotypes. Although increased nitrogen supply alone had no effect on decomposition, it strongly accelerated litter mass loss of all genotypes when combined with warming. Rates of microbial respiration associated with the leaf litter showed nearly identical responses as litter mass loss. These results highlight the importance of interactive effects of environmental factors and suggest that loss or gain of genetic variation associated with key phenotypic traits can buffer, or exacerbate, the impact of global change on ecosystem process rates in the future.

[Incremental innovation in healthcare in Spain during the COVID-19 pandemic]. / La innovación incremental en salud en España durante la pandemia de la COVID-19.

OBJECTIVE: It is important to understand the impact of the COVID-19 pandemic on incremental innovation and its protection through industrial property rights, in order to acquiring valuable insights to develop effective public policies and corporate strategies. The objective was to analyze incremental innovations in response to the pandemic that have been protected by industrial property rights, and to examine whether the COVID-19 pandemic had a positive or negative effect on incremental innovation, promoting or inhibiting it. METHODS: Utility models in the health patent class have been used as indicators (01.01.20 to 31.12.21), since the information they provide and their characteristics (requirements of applications and publication) allowed us to obtain preliminary conclusions in the short term. Their frequency of application during the pandemic months was analyzed and compared with an equivalent period immediately before (01.01.18 to 31.12.19). RESULTS: The analysis showed that there had been greater activity in healthcare innovation by all agents (individuals, companies and the public sector). In the pandemic period of 2020-2021, 754 utility models were requested, representing a nearly 40% increase compared to the equivalent period of 2018-2019, of which 284 were identified as pandemic-related innovations, with 59.7% of rights holders being individuals, 36.4% being companies, and only 3.9% being public entities. CONCLUSIONS: In general, incremental innovations require less investment and shorter technology maturation times, which had made it possible to respond, in some cases successfully, to situations of initial shortages of many medical devices, such as ventilators and protective equipment.

OBJETIVO: Es importante comprender cómo la pandemia de COVID-19 ha afectado a la innovación incremental y su protección mediante derechos de propiedad industrial, con el fin de obtener información valiosa para desarrollar políticas públicas y estrategias empresariales. El objetivo de este estudio fue analizar las innovaciones incrementales como respuesta a la pandemia que han sido protegidas por derechos de propiedad industrial, y examinar si la pandemia de la COVID-19 había tenido un efecto positivo o negativo en la innovación incremental, fomentándola o inhibiéndola. METODOS: Se emplearon como indicadores los modelos de utilidad de la clase de patentes del ámbito salud en el periodo entre el 1 de enero de 2020 y el 31 de diciembre de 2021, puesto que la información que proporcionan y sus características (requisitos de solicitud y publicación) permitían extraer algunas conclusiones incipientes en el corto plazo. Se analizó su frecuencia de solicitud durante los meses de pandemia y se comparó con un periodo temporal equivalente inmediatamente anterior (1 de enero de 2018 a 31 de diciembre de 2019). RESULTADOS: El análisis mostró que hubo una mayor actividad de innovación sanitaria por parte de todos los agentes (particulares, empresas y sector público). En el período de la pandemia de 2020-2021, se solicitaron 754 modelos de utilidad, lo que representó un aumento de casi el 40% en comparación con el período equivalente de 2018-2019, de los cuales se identificaron 284 como innovaciones relacionadas con la pandemia, con el 59,7% de los titulares de los derechos siendo personas individuales, el 36,4% siendo empresas y solo el 3,9% siendo entidades públicas. CONCLUSIONES: En general, las innovaciones incrementales requieren menor inversión y plazos de maduración de la tecnología más cortos, lo que permitía responder, en algunos casos exitosamente, a las situaciones de desabastecimiento inicial de muchos productos sanitarios, como respiradores y equipos de protección.

Judgments of learning in bilinguals: Does studying in a L2 hinder learning monitoring?

Nowadays, use of a second language (L2) has taken a central role in daily activities. There are numerous contexts in which people have to process information, acquire new knowledge, or make decisions via a second language. For example, in academia and higher education, English is commonly used as the language of instruction and communication even though English might not be students' native or first language (L1) and they might not be proficient in it. Such students may face different challenges when studying and learning in L2 relative to contexts in which they study and learn in their L1, and this may affect their metamemory strategies. However, little is yet known about whether metamemory processes undergo significant changes when learning is carried out in L2. The aim of the present study was to investigate the possible consequences on learning derived from studying materials in L2 and, more specifically, to explore whether the interplay between monitoring and control (metamemory processes) changes as a function of the language involved. In three experiments, we explored whether font type (Experiment 1), concreteness (Experiment 2), and relatedness (Experiment 3) affected judgments of learning (JOLs) and memory performance in both L1 and L2. JOLs are considered the result of metacognitive strategies involved in the monitoring of learning and have been reported to vary with the difficulty of the material. The results of this study showed that people were able to monitor their learning in both L1 and L2, even though they judged L2 learning as more difficult than L1. Interestingly, self-perceived difficulty did not hinder learning, and people recognized L2 materials as well or better than L1 materials. We suggest that this might be an example of a desirable difficulty for memory.

[Factors associated with the duration of SARS-CoV-2 infection in healthcare professionals at a second-level public hospital in the Community of Madrid (Spain) during the sixth wave.] / Factores asociados a la duración de la infección por SARS-CoV-2 en profesionales sanitarios de un hospital público de segundo nivel de la Comunidad de Madrid durante la sexta ola.

OBJECTIVE: The incidence of COVID-19 infections among health professionals during the sixth wave has suffered an exponential increase, mainly due to the rapid community transmission caused by the Omicron variant. The main objective of the study was to evaluate the time to negativization in COVID-positive health professionals during the sixth wave, according to the PDIA result; and secondarily, to evaluate the possible influence of other factors (previous infection, vaccination, sex, age, job position) on the time to get negative status. METHODS: A descriptive, longitudinal, observational and retrospective study was carried out at Infanta Sofía University Hospital (Madrid, Spain). Made from the registry of the Occupational Risk Prevention Service of suspected or confirmed cases of SARS-COV-2 infection in health professionals, during the period between November 1, 2021 and February 28, 2022. Bivariate comparisons were made using Mann Whitney, Kruskal Wallis or Chi-square test (or exact test) according to variables. Subsequently, logistic regression (explanatory model) was performed. RESULTS: The cumulative incidence of SARS-COV-2 infection in health professionals was 23.07%. The mean time to become negative was 9.94 days. Only the history of previous SARS-COV-2 infection had a statistically significant influence on the time to negativization of PDIA. The variables vaccination, sex and age had no effect on the time to negativization of PDIA. CONCLUSIONS: Professionals with a history of COVID-19 infection present lower times of negativization than those who had not have the disease. The results of our study confirm the immune escape of the vaccine against COVID-19, since more than 95% of those infected had received a complete vaccination schedule.

OBJETIVO: La incidencia de contagios por COVID-19 entre profesionales sanitarios durante la sexta ola, ha sufrido un incremento exponencial motivado principalmente por la rápida trasmisión comunitaria ocasionada por la variante Ómicron. El objetivo principal del estudio fue evaluar el tiempo de negativización en los profesionales sanitarios COVID positivos durante la sexta ola, según resultado de PDIA; y, de forma secundaria, evaluar la posible influencia de otros factores (infección previa, vacunación, sexo, edad, puesto de trabajo) en el tiempo de negativización. METODOS: Se realizó un estudio descriptivo, longitudinal, observacional y retrospectivo en el Hospital Universitario Infanta Sofía (Madrid), a partir del registro del Servicio de Prevención de Riesgos Laborales de casos sospechosos o confirmados de infección por SARS-COV-2 en profesionales sanitarios, durante el periodo comprendido entre el 1 de noviembre de 2021 y el 28 de febrero de 2022. Se hicieron comparaciones bivariadas mediante Mann Whitney, Kruskal Wallis o test de Chi-cuadrado (o test exacto) según variables. Posteriormente se realizó regresión logística (modelo explicativo). RESULTADOS: La incidencia acumulada de infección por SARS-COV-2 en profesionales sanitarios fue del 23,07%. El tiempo medio en negativizar fue de 9,94 días. Únicamente el antecedente de infección previa por SARS-COV-2 influyó de forma estadísticamente significativa en el tiempo de negativización de PDIA. Las variables vacunación, sexo y edad no tuvieron efecto en el tiempo de negativización de PDIA. CONCLUSIONES: Los profesionales con antecedente de infección por COVID-19 presentan tiempos inferiores de negativización que aquellos que no han pasado la enfermedad. Los resultados de nuestro estudio constatan el escape inmunológico de la vacuna frente al COVID-19, pues más del 95% de los infectados habían recibido una pauta de vacunación completa.

Deep Learning Classification of Lake Zooplankton.

Plankton are effective indicators of environmental change and ecosystem health in freshwater habitats, but collection of plankton data using manual microscopic methods is extremely labor-intensive and expensive. Automated plankton imaging offers a promising way forward to monitor plankton communities with high frequency and accuracy in real-time. Yet, manual annotation of millions of images proposes a serious challenge to taxonomists. Deep learning classifiers have been successfully applied in various fields and provided encouraging results when used to categorize marine plankton images. Here, we present a set of deep learning models developed for the identification of lake plankton, and study several strategies to obtain optimal performances, which lead to operational prescriptions for users. To this aim, we annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera. Our best models were based on transfer learning and ensembling, which classified plankton images with 98% accuracy and 93% F1 score. When tested on freely available plankton datasets produced by other automated imaging tools (ZooScan, Imaging FlowCytobot, and ISIIS), our models performed better than previously used models. Our annotated data, code and classification models are freely available online.

Underwater dual-magnification imaging for automated lake plankton monitoring.

The Dual Scripps Plankton Camera (DSPC) is a new approach for automated in-situ monitoring of phyto- and zooplankton communities based on a dual magnification dark-field imaging microscope. Here, we present the DSPC and its associated image processing while evaluating its capabilities in i) detecting and characterizing plankton species of different size and taxonomic categories and ii) measuring their abundance in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scaled with measurements derived by microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland) delivered images of plankton individuals, colonies, and heterospecific aggregates at hourly timescales without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior. The DSPC was able to track the dynamics of taxa, mostly at the genus level, in the size range between ∼10 µm to ∼ 1 cm, covering many components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances. The most significant disagreements between traditional methods and the DSPC resided in the measurements of zooplankton community properties. Our data suggest that the DSPC is better equipped to study the dynamics and demography of heterogeneously distributed organisms such as zooplankton, because high temporal resolution and continuous sampling offer more information and less variability in taxa detection and quantification than traditional sampling. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and diel fluctuations with a temporal frequency and morphological resolution that was never observed by traditional methods. Access to high frequency, reproducible and real-time data of a large spectrum of the planktonic ecosystem expands our understanding of both applied and fundamental plankton ecology. We conclude the DSPC is robust for both research and water quality monitoring and suitable for stable long-term deployments.

Light limitation increases multidimensional trait evenness in phytoplankton populations.

Individual-level variation arising from responses to environmental gradients influences population and community dynamics. How such responses empirically relate to the mechanisms that govern species coexistence is, however, poorly understood. Previous results from l ake phytoplankton communities suggested that the evenness of organismal traits in multiple dimensions increases with resource limitation, possibly due to resource partitioning at the individual level. Here we experimentally tested the emergence of this pattern by growing two phytoplankton species (Pseudokirchneriella subcapitata and Microcystis aeruginosa) under a gradient of light intensity, in monoculture and jointly. Under low light (resource) conditions, the populations diversified into a wide range of phenotypes, which were evenly distributed in multidimensional trait space (defined by four pigment-related trait dimensions), consistent with the observed field pattern. Our interpretation is that under conditions of light limitation, individual phytoplankton cells alter photosynthetic traits to reduce overlap in light acquisition, acquiring unexploited resources and thereby likely maximising individual success. Our results provide prime experimental evidence that resource limitation increases the evenness of conspecific and heterospecific microbial phenotypes along trait axes, advancing our understanding of trait-based coexistence.

Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering.

Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single cell and colony level improves our ability to understand dynamics in natural communities. Automated high-frequency monitoring of these communities is presently limited by the absence of repeatable, rapid protocols to analyse SFCM datasets, where images of individual particles are not available. Here we demonstrate a repeatable, semi-automated method to (1) rapidly clean SFCM data from a phytoplankton community by removing signals that do not belong to live phytoplankton cells, (2) classify individual cells into trait clusters that correspond to functional groups, and (3) quantify the biovolumes of individual cells, the total biovolume of the whole community and the total biovolumes of the major functional groups. Our method involves the development of training datasets using lab cultures, the use of an unsupervised clustering algorithm to identify trait clusters, and machine learning tools (random forests) to (1) evaluate variable importance, (2) classify data points, and (3) estimate biovolumes of individual cells. We provide example datasets and R code for our analytical approach that can be adapted for analysis of datasets from other flow cytometers or scanning flow cytometers.

Pesticides drive risk of micropollutants in wastewater-impacted streams during low flow conditions.

Micropollutants enter surface waters through various pathways, of which wastewater treatment plants (WWTPs) are a major source. The large diversity of micropollutants and their many modes of toxic action pose a challenge for assessing environmental risks. In this study, we investigated the potential impact of WWTPs on receiving ecosystems by describing concentration patterns of micropollutants, predicting acute risks for aquatic organisms and validating these results with macroinvertebrate biomonitoring data. Grab samples were taken upstream, downstream and at the effluent of 24 Swiss WWTPs during low flow conditions across independent catchments with different land uses. Using liquid chromatography high resolution tandem mass spectrometry, a comprehensive target screening of almost 400 organic substances, focusing mainly on pesticides and pharmaceuticals, was conducted at two time points, and complemented with the analysis of a priority mixture of 57 substances over eight time points. Acute toxic pressure was predicted using the risk assessment approach of the multi-substance potentially affected fraction, first applying concentration addition for substances with the same toxic mode of action and subsequently response addition for the calculation of the risk of the total mixture. This toxic pressure was compared to macroinvertebrate sensitivity to pesticides (SPEAR index) upstream and downstream of the WWTPs. The concentrations were, as expected, especially for pharmaceuticals and other household chemicals higher downstream than upstream, with the detection frequency of plant protection products upstream correlating with the fraction of arable land in the catchments. While the concentration sums downstream were clearly dominated by pharmaceuticals or other household chemicals, the acute toxic pressure was mainly driven by pesticides, often caused by the episodic occurrence of these compounds even during low flow conditions. In general, five single substances explained much of the total risk, with diclofenac, diazinon and clothianidin as the main drivers. Despite the low predicted acute risk of 0%-2.1% for affected species, a significant positive correlation with macroinvertebrate sensitivity to pesticides was observed. However, more effect data for pharmaceuticals and a better quantification of episodic pesticide pollution events are needed for a more comprehensive risk assessment.

Fish population genetic structure shaped by hydroelectric power plants in the upper Rhine catchment.

The Rhine catchment in Switzerland has been transformed by a chain of hydroelectric power stations. We addressed the impact of fragmentation on the genetic structure of fish populations by focusing on the European chub (Squalius cephalus). This fish species is not stocked and copes well with altered habitats, enabling an assessment of the effects of fragmentation per se. Using microsatellites, we genotyped 2133 chub from 47 sites within the catchment fragmented by 37 hydroelectric power stations, two weirs and the Rhine Falls. The shallow genetic population structure reflected drainage topology and was affected significantly by barriers to migration. The effect of power stations equipped with fishpasses on genetic differentiation was detectable, albeit weaker than that of man-made barriers without fishpasses. The Rhine Falls as the only long-standing natural obstacle (formed 14 000 to 17 000 years ago) also had a strong effect. Man-made barriers also exacerbated the upstream decrease in allelic diversity in the catchment, particularly when lacking fishpasses. Thus, existing fishpasses do have the desired effect of mitigating fragmentation, but barriers still reduce population connectivity in a fish that traverses fishpasses better than many other species. Less mobile species are likely to be affected more severely.

Environmental context and magnitude of disturbance influence trait-mediated community responses to wastewater in streams.

Human land uses and population growth represent major global threats to biodiversity and ecosystem services. Understanding how biological communities respond to multiple drivers of human-induced environmental change is fundamental for conserving ecosystems and remediating degraded habitats. Here, we used a replicated 'real-world experiment' to study the responses of invertebrate communities to wastewater perturbations across a land-use intensity gradient in 12 Swiss streams. We used different taxonomy and trait-based community descriptors to establish the most sensitive indicators detecting impacts and to help elucidate potential causal mechanisms of change. First, we predicted that streams in catchments adversely impacted by human land-uses would be less impaired by wastewater inputs because their invertebrate communities should be dominated by pollution-tolerant taxa ('environmental context'). Second, we predicted that the negative effects of wastewater on stream invertebrate communities should be larger in streams that receive proportionally more wastewater ('magnitude of disturbance'). In support of the 'environmental context' hypothesis, we found that change in the Saprobic Index (a trait-based indicator of tolerance to organic pollution) was associated with upstream community composition; communities in catchments with intensive agricultural land uses (e.g., arable cropping and pasture) were generally more resistant to eutrophication associated with wastewater inputs. We also found support for the 'magnitude of disturbance' hypothesis. The SPEAR Index (a trait-based indicator of sensitivity to pesticides) was more sensitive to the relative input of effluent, suggesting that toxic influences of wastewater scale with dilution. Whilst freshwater pollution continues to be a major environmental problem, our findings highlight that the same anthropogenic pressure (i.e., inputs of wastewater) may induce different ecological responses depending on the environmental context and community metrics used. Thus, remediation strategies aiming to improve stream ecological status (e.g., rehabilitating degraded reaches) need to consider upstream anthropogenic influences and the most appropriate indicators of restoration success.