Distribution of nitrifying activity in the Seine River (France) from Paris to the estuary

The distribution of nitrification has been measured with the H¹⁴CO₃ ⁻ incorporation method in the Seine River and its estuary during summer conditions. The Seine River below Paris receives large amounts of ammonium through wastewater discharge. In the river itself, this ammonium is only slowly nitrified, while in the estuary nitrification is rapid and complete. We show that this contrasting behavior is related to the different hydrosedimentary conditions of the two systems, as nitrifying bacteria are associated with suspended particles. In the river, particles and their attached bacteria either rapidly settle or have a sestonic behavior. Because of the short residence times of the water masses, the slow growing nitrifying population has no time to develop sufficiently to nitrify the available ammonium. The estuary is characterized by strong tidal dynamics. Particles settle and are resuspended continuously with the strong current inversions of ebb and flood. As a result of these dynamics, particles and their attached nitrifying bacteria experience longer residence times in a temporary suspended state than the water masses themselves, providing to slow growing nitrifying bacteria the opportunity to develop a large population capable of nitrifying all the available ammonium.     

Improving the descendant relationship of cluster galaxies at z < 1

In this work, we study how to improve well-known techniques for detecting progenitors/descendants of galaxies, such as the NDpredict program, when applied to galaxies in clusters. The improvement of this particular method is based on the use of the red sequence of galaxies in those environments. Objects close to the red sequence in the color and magnitude diagram are more likely to belong to the cluster. This defines a probability scale which is then combined with the one generated by NDpredict. This procedure is optimized for the study of galaxies in clusters over different epochs. Our main result is that, for a sample composed of $120$ clusters, with masses greater than ${10}^{13.25}{M}_{\odot }$, selected from the IllustrisTNG simulations (namely, the TNG100 runs). In $99\%$ of the cases (i.e., $119$ systems), we obtain better performance with the red sequence method in comparison to the original NDpredict, and the average gain obtained is $28\%$ in the identification of descendants for this sample of cluster galaxies.