Temporal variation of genetic diversity and differentiation of albacore, Thunnus alalunga, in the Mediterranean Sea

This study is on albacore (Thunnus alalunga, Bonnaterre 1788), an epi- and mesopelagic oceanic tuna species cosmopolitan in the tropical and temperate waters of all oceans including the Mediterranean Sea, extending in a broad band between 40°N and 40°S. What it’s known about albacore population structure is based on different studies that used fisheries data, RFLP, mtDNA control region and nuDNA markers, blood lectins analysis, individual tags and microsatellite. At the moment, for T. alalunga six management units are recognized: the North Pacific, South Pacific, Indian, North Atlantic, South Atlantic and Mediterranean stocks. In this study I have done a temporal and spatial comparison of genetic variability between different Mediterranean populations of Thunnus alalunga matching an historical dataset ca. from 1920s composed of 43 individuals divided in 3 populations (NADR, SPAIN and CMED) with a modern dataset composed of 254 individuals and 7 populations (BAL, CYP, LIG, TYR, TUR, ADR, ALB). The investigation was possible using a panel of 94 nuclear SNPs, built specifically for the target species at the University of Basque Country UPV/EHU. First analysis done was the Hardy-Weinberg, then the number of clusters (K) was determined using STRUCTURE and to assess the genetic variability, allele frequencies, the average number of alleles per locus, expected (He) and observed (Ho) heterozygosis, and the index of polymorphism (P) was used the software Genetix. Historical and modern samples gives different results, showing a clear loss of genetic diversity over time leading to a single cluster in modern albacore instead of the two found in historical samples. What this study reveals is very important for conservation concerns, and additional research endeavours are needed.

Gyrokinetic modelling of plasma transport and investigation on test particle dynamics

Turbulent plasmas inside tokamaks are modeled and studied using guiding center theory, applied to charged test particles, in a Hamiltonian framework. The equations of motion for the guiding center dynamics, under the conditions of a constant and uniform magnetic field and turbulent electrostatic field are derived by averaging over the fast gyroangle, for the first and second order in the guiding center potential, using invertible changes of coordinates such as Lie transforms. The equations of motion are then made dimensionless, exploiting temporal and spatial periodicities of the model chosen for the electrostatic potential. They are implemented numerically in Python. Fast Fourier Transform and its inverse are used. Improvements to the original Python scripts are made, notably the introduction of a power-law curve fitting to account for anomalous diffusion, the possibility to integrate the equations in two steps to save computational time by removing trapped trajectories, and the implementation of multicolored stroboscopic plots to distinguish between trapped and untrapped guiding centers. The post-processing of the results is made in MATLAB. The values and ranges of the parameters chosen for the simulations are selected based on numerous simulations used as feedback tools. In particular, a recurring value for the threshold to detect trapped trajectories is evidenced. Effects of the Larmor radius, the amplitude of the guiding center potential and the intensity of its second order term are studied by analyzing their diffusive regimes, their stroboscopic plots and the shape of guiding center potentials. The main result is the identification of cases anomalous diffusion depending on the values of the parameters (mostly the Larmor radius). The transitions between diffusive regimes are identified. The presence of highways for the super-diffusive trajectories are unveiled. The influence of the charge on these transitions from diffusive to ballistic behaviors is analyzed.

Dynamics of inorganic carbon and carbonate saturation in the Gulf of Cádiz (SW Spain)

The study of inorganic carbon chemistry of the coastal ocean is conducted in the Gulf of Cádiz (GoC). Here we describe observations obtained during 4 sampling cruises in March, June, September and November 2015. The primary data set consists of state-of-the-art measurements of the keystone parameters of the marine CO2 system: Total Alkalinity (TA), pH, dissolved inorganic carbon (DIC). We have then calculated aragonite and calcite saturation state. The distribution of inorganic carbon system parameters in the north eastern shelf of the Gulf of Cádiz showed temporal and spatial variability. River input, mixing, primary production, respiration and remineralization were factors that controlled such distributions. Data related to carbonate saturation of calcite and aragonite reveal the occurrence of a supersaturated water; in any case, both species increased with distance and decreased with depth. The carbon system parameters present a different behaviour close to the coast to offshore ad at deeper water. In this area six water masses are clearly identified by their different chemical properties: Surface Atlantic Water, North Atlantic Central Water (NACW) and Mediterranean Water (MOW). Moreover, with this work the measurement of calcium in seawater is optimize, allowing a better quantification for future work of the saturation state of CaCO3.

Local and nonlocal integro-differential reaction-diffusion models for protein dynamics in Alzheimer's disease

In this work, integro-differential reaction-diffusion models are presented for the description of the temporal and spatial evolution of the concentrations of Abeta and tau proteins involved in Alzheimer's disease. Initially, a local model is analysed: this is obtained by coupling with an interaction term two heterodimer models, modified by adding diffusion and Holling functional terms of the second type. We then move on to the presentation of three nonlocal models, which differ according to the type of the growth (exponential, logistic or Gompertzian) considered for healthy proteins. In these models integral terms are introduced to consider the interaction between proteins that are located at different spatial points possibly far apart. For each of the models introduced, the determination of equilibrium points with their stability and a study of the clearance inequalities are carried out. In addition, since the integrals introduced imply a spatial nonlocality in the models exhibited, some general features of nonlocal models are presented. Afterwards, with the aim of developing simulations, it is decided to transfer the nonlocal models to a brain graph called connectome. Therefore, after setting out the construction of such a graph, we move on to the description of Laplacian and convolution operations on a graph. Taking advantage of all these elements, we finally move on to the translation of the continuous models described above into discrete models on the connectome. To conclude, the results of some simulations concerning the discrete models just derived are presented.