Characterizing flood impact on Swiss floodplains using inter-annual time series of satellite imagery

Pressure on the biodiversity of ecosystems along many rivers is growing continuously due to the increasing number of hydropower facilities regulating downstream flow and sediment regimes. Despite a thorough understanding of the shortterm processes and interactions at this hydro-biosphere interface, long-term analyses of the impacts on floodplain dynamics are lacking. We used inter-annual Landsat 4, 5, 7 and 8 time series to analyze the effects of hydrological events on floodplain vegetation in four mountainous floodplains in the Swiss Alps. Using a spectral mixture analysis approach, we demonstrate that the floodplain vegetation dynamics of mountainous rivers can be recovered at a spatial resolution of 30 meters. Our results suggest that interactions between floods and floodplain vegetation are complex and not exclusively related to flood magnitude. Of the four reaches analyzed, only data gathered along the submountainous reach with a quasi-natural flow regime show a clear link between remotely sensed vegetation indices and floods. In addition, our 29-year time series shows a continuous upward trend in vegetation indices along the floodplains, strongest in the reaches affected by hydropower facilities. The approach presented in this study can be easily replicated in other mountain ranges by providing available flow data to verify the impact of hydropower on floodplain vegetation dynamics

Ensemble Properties of Comets in the Sloan Digital Sky Survey

We present the ensemble properties of 31 comets (27 resolved and 4 unresolved) observed by the Sloan Digital Sky Survey (SDSS). This sample of comets represents about 1 comet per 10 million SDSS photometric objects. Five-band (u,g,r,i,z) photometry is used to determine the comets' colors, sizes, surface brightness profiles, and rates of dust production in terms of the Af{\rho} formalism. We find that the cumulative luminosity function for the Jupiter Family Comets in our sample is well fit by a power law of the form N(< H) \propto 10(0.49\pm0.05)H for H < 18, with evidence of a much shallower fit N(< H) \propto 10(0.19\pm0.03)H for the faint (14.5 < H < 18) comets. The resolved comets show an extremely narrow distribution of colors (0.57 \pm 0.05 in g - r for example), which are statistically indistinguishable from that of the Jupiter Trojans. Further, there is no evidence of correlation between color and physical, dynamical, or observational parameters for the observed comets.Comment: 19 pages, 8 tables, 11 figures, to appear in Icaru

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants with Treatment Resistance in Schizophrenia

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85490 participants (48635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P =.001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P =.04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Remotely sensed impact of flow alteration on Swiss floodplains

Floodplains, though covering a very small fraction of the land, offer key ecosystem services to our society. Floodplains play an active role in the maintenance of river water quality, in the protection of floods, in supporting a unique biodiversity and in many other ecosystem services. In Switzerland, pristine floodplains have lost 90% of their occupied area since 1850. This work was undertaken within the framework of NRP-70, with the aim of reconciling the increase in hydropower production with support for natural biodiversity, which seems to lead to a difficult compromise in the current situation. Airborne and spaceborne remote sensing offer unique capabilities to observe and monitor river systems and floodplains through various technologies. The current dissertation presents the use of remote sensing for observations and monitoring of floodplains and their dynamics, specifically to observe the impact of water flow alteration on the riparian ecosystems. Three complementary aspects of Swiss floodplains are considered throughout the dissertation. The work carried out in the frame of this dissertation is focused mainly on a few sections of a restricted number of river reaches. A robust methodology for riverine habitat dynamics quantification is developed, based on land cover classification produced on high-resolution imagery. Standard and infrared cameras were used to acquire images over five consecutive seasons along three river reaches. The quantification method provides recommendations for monitoring floodplains in Switzerland using unmanned aerial systems. A second method was developed to observe the resource allocation strategies of riparian vegetation at the individual level based on imaging spectroscopy. This method allowed the comparison of the distribution of strategies located along different reaches. Four imaging spectroscopy datasets acquired during two consecutive years, as well as leaf samples from two field campaigns, were used to extract plant traits from alluvial willows. Individuals located along river reaches affected by water flow alteration show a shift towards more competitive strategies. A third method was developed to observe trends in riparian vegetation over the last decades using inter-annual satellite acquisitions. The channel extent was semi-automatically detected using spectral mixture analysis. Acquisitions from Landsat missions 4, 5, 7, and 8 covering the years 1988 to 2016 over four reaches were used to extract trends and correlations with discharge data from hydrometric stations. Correlations between floods and changes in vegetation indices were found only in the case of the natural, sub-mountainous river, while no correlation was found in the case of the two reaches affected by hydropower infrastructure and the mountainous reach. The description of vegetation development through resource allocation strate-gies offers a new point of view on the consequence of water flow alteration and fitswith usual observation, namely the oft-observed channel narrowing. The resultssuggest that the processes shaping the plant characteristics of riparian vegetationoperate over a relatively long period of time. In the different works undertaken, Ialso showed that the specificity of the riverine land cover allows for a robust description of the river landscape, such as the spatio-temporal relationships between water,gravel and vegetation cover. This thesis contributes to the discussion of impact ofwater flow alteration on riparian ecosystems and the possibility of management fora close future. The interactions between the flow regime, the sediment regime, riparian vegetation and other components of the floodplains are still lacking someunderstanding, but recent research is on the way to produce the required recommendations to implement environmental flows. Though river science is advancingfrom day to day, the most critical constraints to protect floodplains in Switzerlandremain on the political level

Characterizing flood impact on Swiss floodplains using interannual time series of satellite imagery

Pressure on the biodiversity of ecosystems along many rivers is growing continuously due to the increasing number of hydropower facilities regulating downstream flow and sediment regimes. Despite a thorough understanding of the shortterm processes and interactions at this hydro-biosphere interface, long-term analyses of the impacts on floodplain dynamics are lacking. We used inter-annual Landsat 4, 5, 7 and 8 time series to analyze the effects of hydrological events on floodplain vegetation in four mountainous floodplains in the Swiss Alps. Using a spectral mixture analysis approach, we demonstrate that the floodplain vegetation dynamics of mountainous rivers can be recovered at a spatial resolution of 30 meters. Our results suggest that interactions between floods and floodplain vegetation are complex and not exclusively related to flood magnitude. Of the four reaches analyzed, only data gathered along the submountainous reach with a quasi-natural flow regime show a clear link between remotely sensed vegetation indices and floods. In addition, our 29-year time series shows a continuous upward trend in vegetation indices along the floodplains, strongest in the reaches affected by hydropower facilities. The approach presented in this study can be easily replicated in other mountain ranges by providing available flow data to verify the impact of hydropower on floodplain vegetation dynamics

Remotely sensing variation in ecological strategies and plant traits of willows in perialpine floodplains

Natural floodplains are characterized by a complex habitat mosaic. However, damming, water storage, and hydropower production affect many floodplains by altering their natural habitat diversity. Field sampling data and imaging spectroscopy are used in combination with statistical models to assess resource allocation strategies of willow stands in perialpine floodplains. Three contrasting floodplain reaches located along two rivers in Switzerland serve as test beds: The Sarine River is partitioned into an upstream and downstream segment under the influence of a dam and a hydropower plant, while the Sense River represents an undisturbed, natural floodplain. Airborne imaging spectrometer data allow mapping of spatially distributed Competitor/Stress tolerator/Ruderal (CSR) strategies using a partial least square modeling approach. Using cross validation, we demonstrate that a statistical modeling approach can reveal variations in CSR scores based on the StrateFy model. Such intraspecific variation of CSR scores cannot be captured by a strategy categorization based solely on the species. Results reveal that willows shifted toward more competition and less stress tolerance along hydrologically altered reaches compared to the willows strategy along the natural control. Moreover, the overall distribution of strategies indicates that stress factors (i.e., limiting growth factors), rather than disturbance (i.e., events leading to partial or total destruction), shape the plant traits of alluvial willow trees. Detailed assessments of resource allocation strategies contribute to a more complete understanding of the continuous and reciprocal shaping between flow regimes, landforms, and alluvial vegetation