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International audience; Although next-generation sequencing (NGS) has drastically improved diagnosis for patients with rare diseases (RDs), access to knowledge of effective treatments is still sparse and often unclear. The large number of RDs (>7,000 estimated) and their genetic heterogeneity make the identification of existing treatments difficult for clinicians. To facilitate treatment visibility, Solve-RD has promoted the development of the Treatabolome DB, a database to facilitate the identification of putative treatments linked to the causative gene or genetic variant/s.A relational database maps genetic variants, or genes, to treatments according to the information collected through systematic literature reviews (SLRs) produced by disease experts. To date, 8 SLRs have been completed on congenital myasthenic syndromes, laminopathies, muscular channelopathies, mitochondrial disorders (Leigh syndromes), hereditary peripheral neuropathies, genetic forms of Parkinson's disease, and metabolic myopathies. Currently, the Treatabolome consists of a dataset of more than 180 different treatments addressing more than 1000 unique variants and 77 genes, that can be interrogated through a web portal by clinicians and researchers. Gene and variant associated treatments can be programmatically queried with the API. The RD-Connect GPAP already incorporates a connection with the Treatabolome by benefitting from the open API of the platform.

This work documents the ICON‐Earth System Model (ICON‐ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non‐hydrostatic) framework with its unstructured, icosahedral grid concept. The ICON‐A atmosphere uses a nonhydrostatic dynamical core and the ocean model ICON‐O builds on the same ICON infrastructure, but applies the Boussinesq and hydrostatic approximation and includes a sea‐ice model. The ICON‐Land module provides a new framework for the modeling of land processes and the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are represented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin‐up of a base‐line version at a resolution typical for models participating in the Coupled Model Intercomparison Project (CMIP). The performance of ICON‐ESM is assessed by means of a set of standard CMIP6 simulations. Achievements are well‐balanced top‐of‐atmosphere radiation, stable key climate quantities in the control simulation, and a good representation of the historical surface temperature evolution. The model has overall biases, which are comparable to those of other CMIP models, but ICON‐ESM performs less well than its predecessor, the Max Planck Institute Earth System Model. Problematic biases are diagnosed in ICON‐ESM in the vertical cloud distribution and the mean zonal wind field. In the ocean, sub‐surface temperature and salinity biases are of concern as is a too strong seasonal cycle of the sea‐ice cover in both hemispheres. ICON‐ESM V1.0 serves as a basis for further developments that will take advantage of ICON‐specific properties such as spatially varying resolution, and configurations at very high resolution., Plain Language Summary: ICON‐ESM is a completely new coupled climate and earth system model that applies novel design principles and numerical techniques. The atmosphere model applies a non‐hydrostatic dynamical core, both atmosphere and ocean models apply unstructured meshes, and the model is adapted for high‐performance computing systems. This article describes how the component models for atmosphere, land, and ocean are coupled together and how we achieve a stable climate by setting certain tuning parameters and performing sensitivity experiments. We evaluate the performance of our new model by running a set of experiments under pre‐industrial and historical climate conditions as well as a set of idealized greenhouse‐gas‐increase experiments. These experiments were designed by the Coupled Model Intercomparison Project (CMIP) and allow us to compare the results to those from other CMIP models and the predecessor of our model, the Max Planck Institute for Meteorology Earth System Model. While we diagnose overall satisfactory performance, we find that ICON‐ESM features somewhat larger biases in several quantities compared to its predecessor at comparable grid resolution. We emphasize that the present configuration serves as a basis from where future development steps will open up new perspectives in earth system modeling., Key Points: This work documents ICON‐ESM 1.0, the first version of a coupled model based on the ICON framework. Performance of ICON‐ESM is assessed by means of CMIP6 Diagnosis, Evaluation, and Characterization of Klima experiments at standard CMIP‐type resolution. ICON‐ESM reproduces the observed temperature evolution. Biases in clouds, winds, sea‐ice, and ocean properties are larger than in MPI‐ESM., European Union H2020 ESM2025, European Union H2020 COMFORT, European Union H2020ESiWACE2, Deutsche Forschungsgemeinschaft TRR181, Deutsche Forschungsgemeinschaft EXC 2037, European Union H2020, Deutscher Wetterdienst, Bundesministerium fuer Bildung und Forschung, http://esgf-data.dkrz.de/search/cmip6-dkrz/, https://mpimet.mpg.de/en/science/modeling-with-icon/code-availability, http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=RUBY-0_ICON-_ESM_V1.0_Model

International audience

International audience

Isotopic measurements showed that N2O production during drought is unexpectedly dominated by denitrification of organic nitrogen., Nitrous oxide is a powerful greenhouse gas whose atmospheric growth rate has accelerated over the past decade. Most anthropogenic N2O emissions result from soil N fertilization, which is converted to N2O via oxic nitrification and anoxic denitrification pathways. Drought-affected soils are expected to be well oxygenated; however, using high-resolution isotopic measurements, we found that denitrifying pathways dominated N2O emissions during a severe drought applied to managed grassland. This was due to a reversible, drought-induced enrichment in nitrogen-bearing organic matter on soil microaggregates and suggested a strong role for chemo- or codenitrification. Throughout rewetting, denitrification dominated emissions, despite high variability in fluxes. Total N2O flux and denitrification contribution were significantly higher during rewetting than for control plots at the same soil moisture range. The observed feedbacks between precipitation changes induced by climate change and N2O emission pathways are sufficient to account for the accelerating N2O growth rate observed over the past decade.

The stable isotope compositions of soil water (δ2H and δ18O) carry important information about the prevailing soil hydrological conditions and for constraining ecosystem water budgets. However, they are highly dynamic, especially during and after precipitation events. In this study, we present an application of a method based on gas-permeable tubing and isotope-specific infrared laser absorption spectroscopy for in situ determination of soil water δ2H and δ18O. We conducted a laboratory experiment where a sand column was initially saturated, exposed to evaporation for a period of 290 days, and finally rewatered. Soil water vapor δ2H and δ18O were measured daily at each of eight available depths. Soil liquid water δ2H and δ18O were inferred from those of the vapor considering thermodynamic equilibrium between liquid and vapor phases in the soil. The experimental setup allowed for following the evolution of soil water δ2H and δ18O profiles with a daily temporal resolution. As the soil dried, we could also show for the first time the increasing influence of the isotopically depleted ambient water vapor on the isotopically enriched liquid water close to the soil surface (i.e., atmospheric invasion). Rewatering at the end of the experiment led to instantaneous resetting of the stable isotope profiles, which could be closely followed with the new method. From simple soil δ2H and δ18O gradients calculations, we showed that the gathered data allowed one to determinate the depth of the evaporation front (EF) and how it receded into the soil over time. It was inferred that after 290 days under the prevailing experimental conditions, the EF had moved down to an approximate depth of −0.06 m. Finally, data were used to calculate the slopes of the evaporation lines and test the formulation for kinetic isotope effects. A very good agreement was found between measured and simulated values (Nash and Sutcliffe efficiency, NSE = 0.92) during the first half of the experiment, i.e., until the EF reached a depth of −0.04 m. From this point, calculated kinetic effects associated with the transport of isotopologues in the soil surface air layer above the EF provided slopes lower than observed. Finally, values of kinetic isotope effects that provided the best model-to-data fit (NSE > 0.9) were obtained from inverse modeling, highlighting uncertainties associated with the determinations of isotope kinetic fractionation and soil relative humidity at the EF.

Plants like winter wheat are known for their insufficient N uptake between sowing and the following growing season. Especially after N-rich crops like oilseed rape or field bean, nitrogen retention of the available soil N can be poor, and the risk of contamination of the hydrosphere with nitrate (NO3-) and the atmosphere with nitrous oxide (N2O) is high. Therefore, novel strategies are needed to preserve these unused N resources for subsequent agricultural production. High organic carbon soil amendments (HCA) like wheat straw promote microbial N immobilization by stimulating microbes to take up N from soil. In order to test the suitability of different HCA for immobilization of excess N, we conducted a laboratory incubation experiment with soil columns, each containing 8 kg of sandy loam of an agricultural Ap horizon. We created a scenario with high soil mineral N content by adding 150 kg NH4+-N ha-1 to soil that received either wheat straw, spruce sawdust or lignin at a rate of 4.5 t C ha-1, or no HCA as control. Wheat straw turned out to be suitable for fast immobilization of excess N in the form of microbial biomass N (up to 42 kg N ha-1), followed by sawdust. However, under the experimental conditions this effect weakened over a few weeks, finally ranging between 8 and 15 kg N ha-1 immobilized in microbial biomass in the spruce sawdust and wheat straw treatment, respectively. Pure lignin did not stimulate microbial N immobilization. We also revealed that N immobilization by the remaining straw and sawdust HCA material in the soil had a greater importance for storage of excess N (on average 24 kg N ha-1) than microbial N immobilization over the 4 months. N fertilization and HCA influenced the abundance of ammonia oxidizing bacteria and archaea as the key players for nitrification, as well as the abundance of denitrifiers. Soil with spruce sawdust emitted more N2O compared to soil with wheat straw, which in relation released more CO2, resulting in a comparable overall global warming potential. However, this was counterbalanced by advantages like N immobilization and mitigation of potential NO3- losses.

Rewetting of soil might contribute considerably to the annual production of nitrous oxide (N2O) in ecosystems subjected to long dry periods. Therefore, it is crucial to elucidate the most important factors responsible for large pulses of N2O with rewetting. In this study, we carried out a series of rewetting experiments with soil samples collected from upland and riparian forest, grassland and arable land. We analysed the dynamics of ammonium (NH4+), nitrite (NO2−), nitrate (NO3−) and dissolved organic matter (DOM) of air‐dried soil samples after rewetting. We also analysed the effects of sterilization of soil samples by γ‐irradiation on N2O production with rewetting. Furthermore, we explored the effects of rewetting and sterilization on the isotopic composition of N2O in the different soil samples. The grassland soil produced the largest amount of N2O (64.1 μg N kg−1) in 1 hour on rewetting, followed by upland forest soil, whereas it was least for soils from riparian forest and arable land. Gamma irradiation, however, decreased soil N2O production from forest soil samples by 30–90% after rewetting, but increased N2O production in grassland and arable land soils three‐fold and two‐fold, respectively. Correlation analysis revealed that NO2− concentration in the soil samples at the time of rewetting was the most relevant factor that explained soil N2O production after rewetting. Furthermore, the addition of NO2− before rewetting increased N2O production during rewetting more than with additions of NO3− and NH4+ in all soil samples. The 15N site preference values of N2O produced after rewetting were close to 0‰, indicating a denitrification‐related production process according to the classical view. However, additional abiotic processes responsible for soil N2O production during rewetting cannot be excluded.