Abstract
Abstract. The seasonal and year-to-year variability of the phytoplankton size class (PSC) spatial distribution has been examined in the Mediterranean Sea by using the entire time series of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) space observations (1998–2010). Daily maps of PSCs have been determined using an empirical model based on a synoptic relationship between surface chlorophyll a and diagnostic pigments referred to different taxonomic groups. The analysis of micro-, nano- and pico-phytoplankton satellite time series (1998–2010) describes, quantitatively, the algal assemblage structure over the basin and reveals that the main contribution to chlorophyll a in most of the Mediterranean Sea comes from the pico-phytoplankton component, especially in nutrient-poor environments. Regions with different and peculiar features are the Northwestern Mediterranean Sea, the Alborán Sea and several coastal areas, such as the North Adriatic Sea. In these areas, local interactions between physical and biological components modulate the composition of the three phytoplankton size classes. It results that, during the spring bloom season, micro-phytoplankton dominates in areas of intense vertical winter mixing and deep/intermediate water formation, while in coastal areas micro-phytoplankton dominates in all seasons because of the nutrient supply from the terrestrial inputs. In the Alborán Sea, where the Atlantic inflow modulates the nutrient availability, any predominance of one class over the other two has been observed. The nano-phytoplankton component instead remains widespread over the entire basin along the year, and its contribution to chlorophyll a is of the order of 30–40 %. The largest inter-annual signal occurs in the Northwestern Mediterranean Sea, driven by the year-to-year variation in intensity and extension of the spring bloom, followed by the Alborán Sea, in which the inter-annual variability is strongly modulated by the Atlantic inflow. In absence of sufficient in situ data of community composition, the satellite-based analysis demonstrated that pico-, nano- and micro-phytoplankton classes often coexist. The predominance of one group over the other ones is strongly dependent on the physical and biological processes occurring at the mesoscale. These processes directly influence the nutrient and light availability, which are the principal forcing for the algae growth.
Highlights
Phytoplankton represents an important element for the survival and comprehension of the marine ecosystem
For the first time, we estimate the contribution of micro, nano- and pico-phytoplankton to the total chlorophyll a over the Mediterranean Sea by applying an abundance-based model (Brewin et al, 2011b, referred to as BR) to the entire time series of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission
Considering that each region can be characterized by a specific pigment content, we hypothesized that the different pigment ratios can represent one of the possible reasons that can justify the observed deviation of the model from the in situ phytoplankton size class (PSC) classification
Summary
Phytoplankton represents an important element for the survival and comprehension of the marine ecosystem. Several satellite models have been developed in recent years to classify the algal cells on the basis of optical variable measured from space These are usually divided into two main classes: direct models, which exploit the optical properties directly captured by the sensor; and indirect models, as those based on the strong relationship between the chlorophyll a concentration and the functional groups or taxa and PSCs (Moisan et al, 2012). The objective of this work is dual: (i) to understand how well a simple empirical model solely based on chlorophyll a data, as per Brewin et al (2011b) hereafter referred to as BR, can describe the phytoplankton biomass distribution in the Mediterranean Sea; and (ii) to study the spatio-temporal variability of the three phytoplankton size classes (micro-, nano- and pico-phytoplankton) in this basin, by applying the selected model to the ocean colour products.
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