A comparison of primary production models in an Antarctic mesoscale area

• Main Authors: García Muñoz, Cristina, López Urrutia, Ángel, Lubián, Luis M., García, Carlos M., Hernández León, Santiago, Sangrà, Pablo
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Unidad de Investigación Marina de Tecnalia 2012
• Subjects: Antarctic; Carr; South Shetland Islands; Southern Ocean; Antarc*; Sea ice
• Online Access: http://hdl.handle.net/10261/101275

XVII Simposio Ibérico de Estudios de Biología Marina In the last decades remote sensing models to estimate ocean primary production (PP) have been developed in order to monitor large areas of the global ocean (i.e. Eppley et al ., 1985; Behrenfeld and Falkowsky 1997; Marra et al ., 2003; Behrenfeld et al ., 2005; Westberry et al ., 2008) as well as specific sites like the Southern Ocean (Dierssen et al ., 2000; Arrigo et al ., 2008). Several papers have focused on the comparison of the results obtained by these models (Campbell et al ., 2002; Carr et al ., 2006) and controversial results, in relation to the algorithms used, have been presented, especially for the Southern Ocean (Campbell et al ., 2002; Carr et al . 2006; Shang et al . 2010). This region is a well known High Nutrient Low Chlorophyll area (HNLC), and it is generally assumed to be controlled by the supply of micronutrients (especially iron) and light that are needed for photosynthesis by primary producers. This type of bottom-up control suggests that the ecosystem will be sensitive to changes in physical forcing that influence the light and nutrient environment experienced by phytoplankton (e.g. upwelling, mixed layer depth, sea ice) (Rintoul et al ., 2012). Three kind of remote-sensing models and one based in the Metabolic Theory of Ecology (MTE) were applied to real data obtained during Coupling cruise (January 2010) in a mesoscale area of the Southern Ocean around the South Shetland Islands (SSI). The results obtained were compared and discussed to discern why they differ. The previous knowledge of the study area has allowed us to implement improvements in the selected models to achieve realistic results of PP based on the limitation by light, mixed layer depth and nutrient concentration. Peer Reviewed