Signaling by the hormones brassinosteroid (BR) and gibberellin (GA) is critical to normal plant growth and development and is required for hypocotyl elongation in response to dark and elevated ...temperatures. Active BR signaling is essential for GA promotion of hypocotyl growth and suppresses the dwarf phenotype of GA mutants. Cross-talk between these hormones occurs downstream from the DELLAs, as GA-induced destabilization of these GA signaling repressors is not affected by BRs. Here we show that the light-regulated PIF4 (phytochrome-interacting factor 4) factor is a phosphorylation target of the BR signaling kinase BRASSINOSTEROID-INSENSITIVE 2 (BIN2), which marks this transcriptional regulator for proteasome degradation. Expression of a mutated PIF41A protein lacking a conserved BIN2 phosphorylation consensus causes a severe elongated phenotype and strongly up-regulated expression of the gene targets. However, PIF41A is not able to suppress the dwarf phenotype of the bin2-1 mutant with constitutive activation of this kinase. PIFs were shown to be required for the constitutive BR response of bes1-D and bzr1-1D mutants, these factors acting in an interdependent manner to promote cell elongation. Here, we show that bes1-D seedlings are still repressed by the inhibitor BRZ in the light and that expression of the nonphosphorylatable PIF41A protein makes this mutant fully insensitive to brassinazole (BRZ). PIF41A is preferentially stabilized at dawn, coinciding with the diurnal time of maximal growth. These results uncover a main role of BRs in antagonizing light signaling by inhibiting BIN2-mediated destabilization of the PIF4 factor. This regulation plays a prevalent role in timing hypocotyl elongation to late night, before light activation of phytochrome B (PHYB) and accumulation of DELLAs restricts PIF4 transcriptional activity.
Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping ...studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26-0.32) and linkage disequilibrium (LD, 28.8-58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine.
Large hydrological systems aggregate compositionally different waters derived from a variety of pathways. In the case of continental‐scale rivers, such aggregation occurs noticeably at confluences ...between tributaries. Here we explore how such aggregation can affect solute concentration‐discharge (C‐Q) relationships and thus obscure the message carried by these relationships in terms of weathering properties of the Critical Zone. We build up a simple model for tributary mixing to predict the behavior of C‐Q relationships during aggregation. We test a set of predictions made in the context of the largest world's river, the Amazon. In particular, we predict that the C‐Q relationships of the rivers draining heterogeneous catchments should be the most “dilutional” and should display the widest hysteresis loops. To check these predictions, we compute 10 day‐periodicity time series of Q and major solute (Si, Ca2+, Mg2+, K+, Na+, Cl‐,
SO42−) C and fluxes (F) for 13 gauging stations located throughout the Amazon basin. In agreement with the model predictions, C‐Q relationships of most solutes shift from a fairly “chemostatic” behavior (nearly constant C) at the Andean mountain front and in pure lowland areas, to more “dilutional” patterns (negative C‐Q relationship) toward the system mouth. More prominent C‐Q hysteresis loops are also observed at the most downstream stations. Altogether, this study suggests that mixing of water and solutes between different flowpaths exerts a strong control on C‐Q relationships of large‐scale hydrological systems.
Key Points
Modeling predicts that tributary mixing should affect river concentration‐discharge relationships, especially in large, heterogeneous basins
In the Amazon basin river concentration‐discharge relationships of heterogeneous basins are the least “chemostatic”
Concentration‐discharge relationships in large systems are strongly affected by mixing between waters following different pathways
Continuous monitoring of water surfaces is essential for water resource management. This study presents a nonparametric unsupervised automatic algorithm for the identification of inland water pixels ...from multispectral satellite data using multidimensional clustering and a high-performance subsampling approach for large scenes. Clustering analysis is a technique that is used to identify similar samples in a multidimensional data space. The spectral information and derived indices were used to characterize each scene pixel individually. A machine learning approach with random subsampling and generalization through a Naïve Bayes classifier was also proposed to make the application of complex algorithms to large scenes feasible. Accuracy was evaluated using an independent dataset that provides water bodies in 15 Sentinel-2 images over France acquired in different seasons and that covers a large range of water bodies and water colour types. The validation dataset covers a water surface of more than 1200 km2 (approximately 12 million pixels) including over 80,000 water bodies outlined using a semiautomatic active learning method, which were manually revised. The classification results were compared to the water pixel classification using three of the major Level 2A processors (MAJA, Sen2Cor and FMask) and two of the most common thresholding techniques: Otsu and Canny-edge. An input mask was used to remove coastal waters, clouds, shadows and snow pixels. Water pixels were identified automatically from the clustering process without the need for ancillary or pretrained data. Combinations using up to three water indices (Modified Normalized Difference Water Index-MNDWI, Normalized Difference Water Index-NDWI and Multiband Water Index-MBWI) and two reflectance bands (B8 and B12) were tested in the algorithm, and the best combination was NDWI-B12. Of all the methods, our method achieved the highest mean kappa score, 0.874, across all tested scenes, with a per-scene kappa ranging from 0.608 to 0.980, and the lowest mean standard deviation of 0.091. Standard Otsu's thresholding had the worst performance due to the lack of a bimodal histogram, and the Canny-edge variation achieved an overall kappa of 0.718 when used with the MNDWI. For water masks provided by generic processors, FMask outperformed MAJA and Sen2Cor and obtained an overall kappa of 0.764. In-depth analysis shows a quick drop in performance for all of the methods in identifying water bodies with a surface area below 0.5 ha, but the proposed approach outperformed the second best method by 34% in this size class.
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•Unsupervised multidimensional agglomerative clustering for open water identification.•High performance algorithm allows rapid processing of whole Sentinel-2 scenes.•80,000 water bodies validation dataset, summer/winter images, manually revised masks.•Higher accuracy than previous methods at a country scale with kappa value of 0.88.•New method outperforms the second best by 28% for small water bodies below 0.5 ha.
•Validation of atmospheric correction algorithms for Sentinel-2 MSI images.•Importance of sunglint correction in tropical waters is highlighted.•Chlorophyll-a models are assessed in the two optical ...water types in the system.•Locally calibrated chlorophyll-a algorithms outperformed the global algorithms.•Remote monitoring of the system with a single consistent, calibrated model.
Remote monitoring of chlorophyll-a (chla) has been widely used to evaluate the trophic state of inland and coastal waters, however, there is still much uncertainty in the algorithms applied in different optical water types. The influence of different atmospheric correction (AC) processors, which can also provide correction for sunglint and adjacency effects, on the retrieved chla is poorly understood. In this study, state-of-the-art atmospheric correction and chla algorithms are evaluated using Sentinel-2 MSI imagery in the Mundaú-Manguaba Estuarine-Lagoon System (MMELS), a productive tropical system that consists of two turbid lagoons of different optical water types (OWT). We compared the performance of six AC processors, with the addition of sunglint correction for two of them, with field measured water reflectance. There was difficulty in correcting for the atmospheric effects, especially for bands 2, 3 and 8A. Overall, C2X showed the best performance over MMELS, but with sunglint correction, ACOLITE and GRS provided the most consistent water reflectance (ρw). Sunglint correction might be essential for retrieving accurate ρw in most low-latitude water bodies. We also found that in Mundaú, the dense urban area surrounding it likely caused heavy adjacency effects in the satellite-retrieved reflectance, and thus correction for it is necessary. We also compared the performance of six chla algorithms recommended for the OWTs present in MMELS in addition to a widely applied and a global chla algorithm in retrieving this variable using both field and satellite reflectance, in this case corrected with the three best performing processors. For the in situ data, most algorithms performed well in Manguaba lagoon, while in Mundaú lagoon the semi-analytical NIR-red ratio (2SAR) algorithm was the most consistent model, and in both cases the locally calibrated algorithms outperformed the global algorithm. When retrieving chla with the satellite-derived ρw, considerably poorer results were produced, especially in Mundaú lagoon. The global algorithm was found to be especially sensitive to the atmospheric effects. We also found that the quality of AC provided by the algorithms is not a general predictor of the performance of the chla models, even when analysing individual bands separately, while the relationship between chla concentration and the ratio of bands used by most algorithms can be. Despite containing distinct water characteristics, chla can be modelled using a single algorithm, 2SAR, calibrated for MMELS as a whole, with r2 of 0.77 and nRMSE of 38.7%, and we consider that 2SAR has the potential to be a global algorithm for these OWTs, provided that it is recalibrated for a large dataset of satellite-derived BOA reflectance. We recommend that further studies explore the impacts of AC, sunglint and adjacency effects on the performance of chla algorithms, in order to delineate the most suitable combinations of AC + chla algorithms for the variable OWTs, in an effort to provide the basis for global-scale retrievals of this pigment using medium-resolution sensors such as MSI and OLI.
In 2019, the Brumadinho dam rupture released a massive amount of iron ore mining tailings into the Paraopeba River. Up to now, it remains a public health issue for the local and downstream ...populations. The present study aims to assess the behavior and fate of metal contamination following the disaster. Using new sampling strategies and up-to-date geochemistry tools, we show that the dissolved metal concentrations (< 0.22 µm cutoff filtration) remained low in the Paraopeba River. Although the tailings present high metal concentrations (Fe, Mn, Cd, and As), the high local background contents of metals and other previous anthropogenic contamination hamper tracing the sediment source based only on the geochemical signature. The Pb isotopic composition coupled with the metals enrichment factor of sediments and Suspended Particulate Matter (SPM) constitutes accurate proxies that trace the fate and dispersion of tailing particles downstream of the dam collapse. This approach shows that 1) The influence of the released tailing was restricted to the Paraopeba River and the Retiro Baixo reservoir, located upstream of the São Francisco River; 2) The tailings' contribution to particulate load ranged from 17 % to 88 % in the Paraopeba River; 3) Other regional anthropogenic activities also contribute to water and sediment contamination of the Paraopeba river.
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•Dissolved metal concentrations remained low in the Paraopeba River.•Sediments with potential of releasing large amounts of metals into river water.•Local conditions hamper tracing the sediment source based on geochemical signature.•Pb isotopic fingerprinting trace the fate and dispersion of tailing particles downstream mudflow area.•Other anthropogenic activities also contribute to water and sediments contamination.
Better understanding the fate of the atmospheric carbon (C) captured by plant photosynthesis is essential to improve natural C flux modelling. Soils are considered as the major terrestrial bioreactor ...and repository of plant C, whereas channel networks of floodplain rivers collect and transport, throughout the aquatic continuum, a significant part of plant primary production until its export through outgassing or sequestration in marine sediments. Here, we show that river meandering in forested floodplains is a crucial and widely overlooked Earth surface process promoting C fluxes from the atmosphere to the aquatic continuum, via the floodplain vegetation. Over a recent period of 35 years (1984–2019), we quantified those C fluxes in one of the most active meandering rivers on Earth, the Ucayali River, Peru, South America. We used map time series combined with above-ground forest C data to derive the amount of C that is annually captured by the growing floodplain vegetation within the active meander belt, as well as exported to the aquatic continuum by lateral channel erosion. We found that the annual building and erosion of forested floodplain areas was nearly balanced over time with 19.0±7.7×103 ha−1 yr−1 and 19.8±6.7×103 ha−1 yr−1, respectively. While growing forests within the active meander belt annually captured 0.01±0.05×106 Mg C yr−1, lateral channel erosion provided the nearly 100-fold amount of C to the river channel and its streamflow, i.e. 0.9±0.4×106 Mg C yr−1. Our findings revealed that the migration of the Ucayali River channel provided nearly 10-times more lignified C per unit area to the aquatic continuum (44.7±21.4 Mg C ha−1 yr−1) than non-meandering central Amazonian floodplains do. Together, these findings point to the importance of quantifying the overall contribution of meandering rivers to natural C fluxes worldwide.
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•River meandering in forested floodplains provides high C quantities to river waters.•The Ucayali meandering river (Peru) provides 0.9 ± 0.4 × 106 Mg C yr−1 to the Amazon.•It's nearly 10-times more per unit area than in central Amazonian wetlands.•They deliver annually by erosion 100-fold more C than they fix via photosynthesis.•Meandering rivers are overlooked agents of natural C fluxes.
To date, few empirical estimates of the IFR for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been published owing to challenges in measuring infection rates.1,2 Outside of ...closed, closely observed populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, such as antibodies. Representative seroprevalence studies provide an important opportunity to estimate the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. Despite having among the highest per-capita incidence of confirmed COVID-19 in Switzerland, Geneva's health system, with additional COVID-19 surge capacity, accommodated the influx of cases needing intensive care (peak of 80 of 110 surge capacity intensive care unit beds were in use at one time) while maintaining care quality standards.
River systems connect the terrestrial biosphere, the atmosphere and the ocean in the global carbon cycle. A recent estimate suggests that up to 3 petagrams of carbon per year could be emitted as ...carbon dioxide (CO2) from global inland waters, offsetting the carbon uptake by terrestrial ecosystems. It is generally assumed that inland waters emit carbon that has been previously fixed upstream by land plant photosynthesis, then transferred to soils, and subsequently transported downstream in run-off. But at the scale of entire drainage basins, the lateral carbon fluxes carried by small rivers upstream do not account for all of the CO2 emitted from inundated areas downstream. Three-quarters of the world's flooded land consists of temporary wetlands, but the contribution of these productive ecosystems to the inland water carbon budget has been largely overlooked. Here we show that wetlands pump large amounts of atmospheric CO2 into river waters in the floodplains of the central Amazon. Flooded forests and floating vegetation export large amounts of carbon to river waters and the dissolved CO2 can be transported dozens to hundreds of kilometres downstream before being emitted. We estimate that Amazonian wetlands export half of their gross primary production to river waters as dissolved CO2 and organic carbon, compared with only a few per cent of gross primary production exported in upland (not flooded) ecosystems. Moreover, we suggest that wetland carbon export is potentially large enough to account for at least the 0.21 petagrams of carbon emitted per year as CO2 from the central Amazon River and its floodplains. Global carbon budgets should explicitly address temporary or vegetated flooded areas, because these ecosystems combine high aerial primary production with large, fast carbon export, potentially supporting a substantial fraction of CO2 evasion from inland waters.
The protein-coding exome of a patient with a monogenic disease contains about 20,000 variants, only one or two of which are disease causing. We found that 58% of rare variants in the protein-coding ...exome of the general population are located in only 2% of the genes. Prompted by this observation, we aimed to develop a gene-level approach for predicting whether a given human protein-coding gene is likely to harbor disease-causing mutations. To this end, we derived the gene damage index (GDI): a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population. We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs. We compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing). The GDI server, data, and software are freely available to noncommercial users from lab.rockefeller.edu/casanova/GDI.
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