Estimates of phytoplankton class‐specific and total primary production in the Mediterranean Sea from satellite ocean color observations

Abstract

[1] An approach that combines a recently developed procedure for improved estimation of surface chlorophyll a concentration (Chl surf ) from ocean color and a phytoplankton class-specific bio-optical model was used to examine primary production in the Mediterranean Sea. Specifically, this approach was applied to the 10 year time series of satellite Chl surf data from the Sea-viewing Wide Field-of-view Sensor. We estimated the primary production associated with three major phytoplankton classes (micro, nano, and picophytoplankton), which also yielded new estimates of the total primary production (P tot ). These estimates of P tot (e.g., 68 g C m À2 yr À1 for the entire Mediterranean basin) are lower by a factor of $2 and show a different seasonal cycle when compared with results from conventional approaches based on standard ocean color chlorophyll algorithm and a non-class-specific primary production model. Nanophytoplankton are found to be dominant contributors to P tot (43-50%) throughout the year and entire basin. Micro and picophytoplankton exhibit variable contributions to P tot depending on the season and ecological regime. In the most oligotrophic regime, these contributions are relatively stable all year long with picophytoplankton ($32%) playing a larger role than microphytoplankton ($22%). In the blooming regime, picophytoplankton dominate over microphytoplankton most of the year, except during the spring bloom when microphytoplankton (27-38%) are considerably more important than picophytoplankton (20-27%).

Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data

“…The analysis of the phytoplankton assemblage distribution patterns resulted from the application of our new algorithms to the Mediterranean multi-sensor reprocessed dataset (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) is consistent with the main previous knowledge, both in terms of distribution and phytoplankton ecology (Siokou-Frangou et al, 2010;Uitz et al, 2012;Estrada and Vaqué, 2014;Navarro et al, 2014). Pico-phytoplankton, with Prokaryotes as the main component, is widespread throughout the whole basin and always dominant in oligotrophic and stratified waters (see Section Results) in agreement with the observation of Siokou-Frangou et al (2010), according to which the pico component constitutes more than 50% of the total biomass in these conditions (Estrada and Vaqué, 2014).…”

“…This can represent a precious novelty, considering the lack of knowledge on the Nanoflagellate spatial distribution, improved only in the last years thanks to the more diffused usage of chemotaxonomic and molecular techniques (Latasa et al, 2010). The widespread distribution of the nano component and its high contribution to the TChla in the whole basin confirms the Uitz et al (2012) results, according to which the primary production in the Mediterranean Sea is mainly due to the nano-phytoplankton component.…”

Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data

“…Nevertheless, local physical structures generate convergences zones, which are reflected in the distinct biogeochemical properties of the two Mediterranean sub-regions, the Western and the Levantine. Thus, a notable decreasing gradient in Chla concentration is detected from the west to the east, which causes a significant longitudinal variation in primary production (Turley et al, 2000;Uitz et al, 2012). This gradient in oligotrophy is evidenced both by in situ measurements (Tanhua et al, 2013) and satellite data (D'Ortenzio and Ribera d'Alcalá, 2009).…”

“…This relevance was early recognized by Platt et al (2006), who concluded that detection of phytoplankton from remote sensing images was a major challenge in ocean optics. Therefore, over the last decade, several remote sensing algorithms have been developed to characterize the global distribution patterns of phytoplankton functional types (PFT) or size classes (PSC; e.g., Sathyendranath et al, 2004;Alvain et al, 2005Alvain et al, , 2008Ciotti and Bricaud, 2006;Raitsos et al, 2008;Aiken et al, 2009;Bracher et al, 2009;Brewin et al, 2010;Kostadinov et al, 2010;Hirata et al, 2011;Uitz et al, 2012; see recent summary in Table 2 in Table 3 in Mouw et al, 2017). A complete guide of the available approaches can be found in Mouw et al (2017).…”

Interannual variability of the Mediterranean trophic regimes from ocean color satellites

“…The DR09 results have already been used to investigate the role of the mixed layer depth (MLD) and the nitrate distribution on the Mediterranean phytoplankton phenology (Lavigne et al, 2013), while modeling studies have used the DR09 bioregionalization based on the seasonal dynamics of phytoplankton to ameliorate the primary production estimates from space (Uitz et al, 2012). Combining temporal (i.e., the trophic regimes) and spatial (i.e., the bioregions) analysis, the DR09 results thus provided a robust framework to identify the role of abiotic and biotic factors on the Mediterranean phytoplankton phenology.…”