CONICET | Buscador de Institutos y Recursos Humanos

The changes within and between seasons in phytoplankton composition and abundance determine the carbon biomassavailable for upper levels of the food web. Temporal changes in phytoplankton community and environmental parametersin a port in Puerto Madryn, South-west Atlantic were analysed. During an annual period (2011?2012), samples of surfaceseawater were collected approximately monthly. We determined phytoplankton community structure (species composition15 and abundance) and biomass (determined by carbon content and chlorophyll a (Chl a)). Water temperature, salinity andtransparency were measured when sampling the surface water and local meteorological data were considered. The maingroups observed were diatoms (Bacillariophyta; the most abundant during the concentration peaks of Chl a), dinoflagellates(Dinophyta) and flagellates, which mainly included species of Cryptophyta and Chlorophyta. Diatoms exhibited blooms inMarch (summer?autumn) and September (spring), represented by Skeletonema costatum and Pseudo-nitzschia spp.20 respectively. Dinoflagellates contributed to the highest carbon biomass, with peaks in January (summer) and April(autumn), exemplified by Prorocentrum micans and Scrippsiella acuminata, respectively. Temporal differences in communitycomposition were related to the seasonal changes in temperature, solar irradiance, precipitation, salinity and windvelocity. The environmental conditions seem not only to determine the species composition but also cell size distribution:nanoplanktonic (≤ 20 μm) species dominated mainly during late spring, summer and early winter while microplanktonic25 species (> 20 μm) during late winter and early spring. Our results showed within-season changes and show that not onlyChl a, but also carbon content can be considered, as the former is a biased estimator of phytoplankton biomass. This studyprovides the first seasonally resolved estimation in the area of the carbon biomass available for upper levels of the food weband a necessary information for future scenarios prediction.