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
Authors

Dogliotti, A.I., Lutz, V.A. and Segura, V.
Publication year 2014
DOI http://dx.doi.org/10.1016/j.rse.2013.09.021
Affiliations
  • 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

CRN3
IAI Project CRN3094
Keywords
Primary production
Model
Remote sensing
Ocean color
Argentine Sea

Highlights

•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.

Abstract

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.