Estimation of primary production in the southern Argentine continental shelf and shelf-break regions using field and remote sensing data

Published in Remote Sensing of Environment, v. 140:497-508

Dogliotti, A.I., Lutz, V.A. and Segura, V.

Publication year 2014
  • Instituto de Astronomía y Física del Espacio (IAFE), CONICET-UBA, Pabellón IAFE-Ciudad Universitaria, C.C. 67-Suc. 28, C1428ZAA Ciudad Autónoma de Buenos Aires, Argentina
  • Instituto Franco&ndashArgentino para el Estudio del Clima y sus Impactos (UMI IFAECI/CNRS-CONICET-UBA), Ciudad Universitaria Pabellón II Piso 2, C1428EHA Ciudad Autónoma de Buenos Aires, Argentina
  • Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP), Paseo Victoria Ocampo No. 1, B7602HSA Mar del Plata, Argentina
  • Instituto de Investigaciones Marinas y Costeras, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina


IAI Program


IAI Project CRN3094


•Five models to estimate primary production in the Argentine Sea were tested.

•A non-spectral and uniform biomass profile model (BIOM) provided the best estimates.

•Good performance was found when applied to MODIS data and field P-I parameters.

•Errors in MODIS Chla, Kd(PAR), and PAR products were 40%, 20% and 50%, respectively.


The Argentine continental shelf and shelf-break regions comprise a large and rich biological area of the ocean. However, field estimations of primary production are scarce, making remote sensing of ocean color a valuable tool to provide synoptic maps of primary production in this ecologically relevant region. Field studies performed during spring 2005, and summer and winter 2006 showed a high spatial and seasonal variability in the daily integrated water column primary production, chlorophyll-a and biomass-normalized photosynthetic parameters. Using field measurements, five different and relatively simple (non-spectral and vertically homogeneous biomass) models were tested: three chlorophyll-, one carbon- and one absorption-based model. The chlorophyll-based &lsquoBIOM&rsquo model developed by Platt and Sathyendranath (Science, 241:1613&ndash1620, 1988) provided the closest estimates to the field values, and was selected as the local algorithm. Its performance was assessed using simultaneous satellite-derived products and field photosynthetic parameters as input. Close values compared to the field estimates were obtained using BIOM (Absolute Percent Difference error, APD ~ 10%), even though satellite-derived products used as input to the model (i.e. chlorophyll-a concentration, diffuse attenuation coefficient in the photosynthetically active radiation range &mdash PAR-, and PAR irradiance) showed relative high errors (APD ~ 40%, 20% and 50%, respectively). Provided that an efficient way to assign the physiological parameters in a pixel-by-pixel basis is found, this model seems to be the best to produce primary production maps from remote sensing of ocean color in the southern Argentine shelf and shelf-break regions.