Towards the construction of a validated numerical system to study the mesoscale dynamics of the North East Atlantic (2003-2006)

Máster en Oceanografía

Influence of the combined disposal of sewage and brine on meiofauna

[EN] Confluence of anthropogenic influences is common in coastal areas (e.g., disposal of different pollutants like industrial and domestic sewage, brine, etc.). In this study we assessed whether the combined disposal of domestic sewage and brine altered patterns in the abundance and assemblage structure of subtidal meiofauna inhabiting sandy seabeds. Samples were collected in May 2008 and January 2009 at varying distances (0, 15, and 30 m) from the discharge point. Meiofaunal abundances were consistently larger at 0 m (1663.05 ± 1076.86 ind 10 cm?2, mean ± standard error) than at 15 m (471.21 ± 307.97 ind 10 cm?2) and 30 m (316.50 ± 256.85 ind 10 cm?2) from the discharge outfall. This pattern was particularly accentuated for nematodes. Proximity to the discharge point also altered patterns in meiofaunal assemblage structure, though temporal shifts in the sedimentary composition also contributed to explain differences in the meiofaunal assemblage structure. As a result, meiofauna may be a reliable tool for monitoring studies of the combined disposal of sewage and brine as long as potential confounding factors (here temporal changes in grain size composition) are considered.

Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.