Algal biomass and macroinvertebrate dynamics in intermittent braided rivers: new perspectives from instream pools

Perennial streams and rivers are now largely subjected to fragmentation and lentification processes due to flow reduction, which creates a number of lateral habitats with different degrees of hydrological connectivity. These habitats have environmental conditions and biotic interactions that can be far divergent than those of main channel habitats. However, they remain largely unexplored, especially in temperate regions. We here focused on studying algal dynamics and their interactions with aquatic invertebrates across mesohabitats (i.e., main channel, secondary channel, pools) in streambeds under both normal and low flow conditions. We selected four watercourses in the Po Plain (northern Italy), where we detected the main dynamics and drivers of algal and invertebrate communities by applying mixed effect modelling. A clear algal growth trend was detected in summer, and was similar for all mesohabitats, but with temporal decoupling and doubled values in pools. Mesohabitat and time were central factors in driving benthic algae dynamics that, in turn, negatively affected aquatic invertebrates. Hydrology and algae seemed to have a mutually reinforcing effect on macroinvertebrates by reducing almost all the investigated metrics. By considering future projections on further regime shifts in lotic systems, loss of biodiversity driven by algal blooms could become a major concern, and also for potential cascade impacts on other biotic compartments of river networks

Physical habitat modeling for river macroinvertebrate communities

Habitat models rarely consider macroinvertebrate communities as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the whole community. This research aimed at providing an approach to model the habitat of the macroinvertebrate communities. The study was carried out in three rivers, located in Italy and characterized by a braiding morphology, gravel riverbeds, and low flows during the summer period. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the mesohabitat scale. Using different datasets gathered from field data collection and 2D hydrodynamic simulations, the model was calibrated in the Trebbia River (2019 field campaign) and validated in the Trebbia, Taro, and Enza rivers (2020 field campaign). The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R2 coefficient (R2cv) of the training dataset was 0.71, whereas the R2 coefficient (R2test) for the validation dataset was 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and river morphological modifications. Lastly, the proposed approach allowed to extend the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to ecological flows design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent

Communities in high definition : Spatial and environmental factors shape the micro-distribution of aquatic invertebrates

According to metacommunity theories, the structure of natural communities is the result of both environmental filtering and spatial processes, with their relative importance depending on factors including local habitat characteristics, functional features of organisms, and the spatial scale considered. However, few studies have explored environmental and spatial processes in riverine systems at local scales, explicitly incorporating spatial coordinates into multi-taxa distribution models. To address this gap, we conducted a small-scale study to discriminate between abiotic and biotic factors affecting the distribution of aquatic macroinvertebrates, applying metacommunity concepts. We studied a mountain section in each of three perennial streams within the Po River Basin (northern Italy). We sampled macroinvertebrates both in summer and winter, using specific in situ 50-point random sampling grids. Environmental factors, including benthic organic matter (BOM), flow velocity, water depth, and substrate were recorded together with spatial coordinates for each sampling point. The relationships between community metrics (taxon richness, abundance, biomass, biomass-abundance ratio, and functional feeding groups) and explanatory variables (environmental and spatial) were assessed using generalised additive models. The influence of the explanatory variables on community structure was analysed with joint species distribution models. Environmental variables-primarily BOM-were the main drivers affecting community metrics, whereas the effects of spatial variables varied among metrics, streams, and seasons. During summer, community structure was strongly affected by BOM and spatial position within the riverbed, the latter probably being a proxy for mass effects mediated by biotic and stochastic processes. In contrast, community structure was mainly shaped by hydraulic variables in winter. Using macroinvertebrate communities as a model group, our results demonstrate that metacommunity concepts can explain small-scale variability in community structure. We found that both environmental filtering and biotic processes shape local communities, with the strength of these drivers depending on the season. These insights provide baseline knowledge that informs our understanding of ecological responses to environmental variability in contexts including restoration ecology, habitat suitability modelling, and biomonitoring.Peer reviewe

Exploring the potential of metabarcoding to disentangle macroinvertebrate community dynamics in intermittent streams

Taxonomic sufficiency represents the level of taxonomic detail needed to detect ecological patterns to a level that match the requirement of a study. Most bioassessments apply the taxonomic sufficiency concept and assign specimens to the family or genus level given time constraints and the difficulty to correctly identify species. This holds particularly true for stream invertebrates because small and morphologically similar larvae are hard to distinguish. Low taxonomic resolution may hinder detecting true community dynamics, which thus leads to incorrect inferences about community assembly processes. DNA metabarcoding is a new, affordable and cost-effective tool for the identification of multiple species from bulk samples of organisms. As it provides high taxonomic resolution, it can be used to compare results obtained from different identification levels. Measuring the effect of taxonomic resolution on the detection of community dynamics is especially interesting in extreme ecosystems like intermittent streams to test if species at intermittent sites are subsets of those from perennial sources or if independently recruiting taxa exist. Here we aimed to compare the performance of morphological identification and metabarcoding to detect macroinvertebrate community dynamics in the Trebbia River (Italy). Macroinvertebrates were collected from four perennial and two intermittent sites two months after flow resumption and before the next dry phase. The identification level ranged from family to haplotype. Metabarcoding and morphological identifications found similar alpha diversity patterns when looking at family and mixed taxonomic levels. Increasing taxonomic resolution with metabarcoding revealed a strong partitioning of beta diversity in nestedness and turnover components. At flow resumption, beta diversity at intermittent sites was dominated by nestedness when family-level information was employed, while turnover was evidenced as the most important component when using Operational Taxonomic Units (OTUs) or haplotypes. The increased taxonomic resolution with metabarcoding allowed us to detect species adapted to deal with intermittency, like the chironomid Cricotopus bicinctus and the ephemeropteran Cloeon dipterum. Our study thus shows that family and mixed taxonomic level are not sufficient to detect all aspects of macroinvertebrate community dynamics. High taxonomic resolution is especially important for intermittent streams where accurate information about species-specific habitat preference is needed to interpret diversity patterns induced by drying and the nestedness/ turnover components of beta diversity are of interest to understand community assembly processes

LFR safety approach and main ELFR safety analysis results

This paper summarizes the approach to safety for the LFR systems, developed on the basis of the recommendations of the Generation IV International Forum (GIF) Risk and Safety Working Group (RSWG) and taking into account the fundamental safety objectives and the Defence-in-Depth approach, as described by IAEA Safety Guides, as well as the Safety quantitative objectives reported in the European Utilities Requirements (EUR). LEADER project activities are focused on the resolution of the key issues as they emerged from the 6th FP ELSY project attempting to reach a new industrial size European Lead-cooled Fast Reactor (ELFR) configuration. Apart from the safety approach, the main results of the ELFR safety transient analysis, where the most important design basis condition (DBC) and design extension condition (DEC) transient initiators were re-analyzed using the system codes RELAP5 (ENEA), TRACE-FRED (PSI), SIM-LFR (KIT) and SIMMER (CIRTEN), are summarized

Ventilatory associated barotrauma in COVID-19 patients: A multicenter observational case control study (COVI-MIX-study)

Background: The risk of barotrauma associated with different types of ventilatory support is unclear in COVID-19 patients. The primary aim of this study was to evaluate the effect of the different respiratory support strategies on barotrauma occurrence; we also sought to determine the frequency of barotrauma and the clinical characteristics of the patients who experienced this complication. Methods: This multicentre retrospective case-control study from 1 March 2020 to 28 February 2021 included COVID-19 patients who experienced barotrauma during hospital stay. They were matched with controls in a 1:1 ratio for the same admission period in the same ward of treatment. Univariable and multivariable logistic regression (OR) were performed to explore which factors were associated with barotrauma and in-hospital death. Results: We included 200 cases and 200 controls. Invasive mechanical ventilation was used in 39.3% of patients in the barotrauma group, and in 20.1% of controls (p<0.001). Receiving non-invasive ventilation (C-PAP/PSV) instead of conventional oxygen therapy (COT) increased the risk of barotrauma (OR 5.04, 95% CI 2.30 - 11.08, p<0.001), similarly for invasive mechanical ventilation (OR 6.24, 95% CI 2.86-13.60, p<0.001). High Flow Nasal Oxygen (HFNO), compared with COT, did not significantly increase the risk of barotrauma. Barotrauma frequency occurred in 1.00% [95% CI 0.88-1.16] of patients; these were older (p=0.022) and more frequently immunosuppressed (p=0.013). Barotrauma was shown to be an independent risk for death (OR 5.32, 95% CI 2.82-10.03, p<0.001). Conclusions: C-PAP/PSV compared with COT or HFNO increased the risk of barotrauma; otherwise HFNO did not. Barotrauma was recorded in 1.00% of patients, affecting mainly patients with more severe COVID-19 disease. Barotrauma was independently associated with mortality. Trial registration: this case-control study was prospectively registered in clinicaltrial.gov as NCT04897152 (on 21 May 2021)

Prior specification in one-factor mixed models applied to community ecology data

In community ecology studies the goal is to evaluate the effect of environmental covariates on a response variable while investigating the nature unobserved heterogeneity. We focus on onefactor mixed models in a Bayesian setting and introduce an intuitive Penalized Complexity (PC) prior to balance the variance components of the model. We start with the simple one-way anova and discuss extension to spatially structured residuals, following a Matern exponential covariance

PC priors for residual correlation parameters in one-factor mixed models

Lack of independence in the residuals from linear regression motivates the use of random effect models in many applied fields. We start from the one-way anova model and extend it to a general class of one-factor Bayesian mixed models, discussing several correlation structures for the within group residuals. All the considered group models are parametrized in terms of a single correlation (hyper-)parameter, controlling the shrinkage towards the case of independent residuals (iid). We derive a penalized complexity (PC) prior for the correlation parameter of a generic group model. This prior has desirable properties from a practical point of view: (i) it ensures appropriate shrinkage to the iid case; (ii) it depends on a scaling parameter whose choice only requires a prior guess on the proportion of total variance explained by the grouping factor; (iii) it is defined on a distance scale common to all group models, thus the scaling parameter can be chosen in the same manner regardless the adopted group model. We show the benefit of using these PC priors in a case study in community ecology where different group models are compared