Silicon isotopes: linking soil Si availability and plant Si strategies

<p>One of the most puzzling properties of silicon (Si) is its differential absorption by plants. Depending on the plant species, water and soil Si availability, environmental factors such as grazing and temperature, plant Si contents can vary from 0.1 % to 10 %<sup></sup>(on a dry weight basis). Advances in genomics improved our understanding of biochemical and molecular mechanisms underlying plant Si uptake providing a framework to explain the variability of Si in plants and its distribution. Yet complex Si roles in plant strategies, its dependence on environmental factors and in mediating interactions with their environments and other organisms remain misunderstood. How is plant Si uptake affected by soil Si availability and how is Si distribution between tissue types controlled? It is hard for us to answer those questions even if Si plant traits are an indicator of the soil Si status. For example, a few studies showed that Si content and phytolith distribution are mainly controlled by Si availability. In this study, a pot experiment was conducted in a greenhouse where wheat (Triticum turgidum L.) was grown on three different soils: an aric podzol, an andosol and a calcosol. These soils are contrasted in term of clay size distribution, SiO<sub>2</sub> concentrations and organic matter content and are presumed to reflect French soils variability in term of Si dynamics. Here, we focus on how plant Si patterns, both Si content and Si isotopes, are linked to soil Si availability leading to new insights to the mechanisms underlying the different Si uptake and translocation strategies. This work is supported by the BIOSiSOL project (ANR-14-CE01-0002).</p>

Study of the Nuclear Structure of some Neutron Rich Si Isotopes Using Shell Model with Skyrme Interaction

The nuclear structure of 28-40Si isotopes toward neutron dripline has been investigated in framework of shell model with Skyrme-Hrtree-Fock method using certain Skyrme parameterizations. Moreover, investigations of static properties such as nuclear densities for proton, neutron, mass, and, charge densities with their corresponding rms radii, neutron skin thicknesses, binding energies, separation energies, shell gap, and pairing gap have been performed using the most recent Skyrme parameterization. The calculated results have been compared with available experimental data to identify which of these parameterizations introduced equivalent results with the experimental data. For all dynamic properties, sdpf shell model space has been used to generate one body transition density matrix element with SDPFK two body effective interaction. The calculations also reproduced the low and higher-laying 2+ energy level scheme, and reduced transition probability B(E2) for even Si-isotopes.

The evolution of stable silicon isotopes in a coastal carbonate aquifer, Rottnest Island, Western Australia

Dissolved silicon (DSi) is a key nutrient in the oceans, but there are few data available regarding Si isotopes in coastal aquifers. Here we investigate the Si isotopic composition of 12 fresh and 17 saline groundwater samples from Rottnest Island, Western Australia, which forms part of the world’s most extensive aeolianite deposit (the Tamala Limestone Formation). Two bedrock samples were also collected from Rottnest Island for Si isotope analysis. The δ30Si values of groundwaters ranged from −0.39 to +3.60 ‰ with an (average: +1.59 ‰) and the rock samples were −0.76 and −0.13 ‰. Due to the relatively low concentrations of DSi (64 to 196 μM) and clay-forming cations in fresh groundwaters, the correlation between δ30Si values and DSi concentrations (ρ = 0.59, p = 0.02) may be explained by Si adsorption onto Fe-Al (oxy)hydroxides present in the aquifer. An increase in groundwater δ30Si in association with the occurrence of water-rock interactions may explain the spatial pattern in δ30Si across the aquifer, and is consistent with the correlation between δ30Si and tritium activities when considering all groundwaters (ρ = −0.68, p = 0.0002). In the deeper aquifer, the inverse correlation between DSi and Cl concentrations (ρ = −0.79, p = 0.04) for the more saline groundwaters is attributed to groundwater mixing with local seawater that is depleted in DSi (