Use of satellite data for modelling food availability and survival of marine fish larvae

A modelling scheme is described which uses satellite retrieved sea-surface temperature and chlorophyll-a to derive monthly zooplankton biomass estimates in the eastern North Atlantic; this forms part of a bio-physical model of inter-annual variations in the growth and survival of larvae and post-larvae of mackerel (Scomber scombrus). The temperature and chlorophyll data are incorporated first to model copepod (Calanus) egg production rates. Egg production is then converted to available food using distribution data from the Continuous Plankton Recorder (CPR) Survey, observed population biomass per unit daily egg production and the proportion of the larval mackerel diet comprising Calanus. Results are validated in comparison with field observations of zooplankton biomass. The principal benefit of the modelling scheme is the ability to use the combination of broad scale coverage and fine scale temporal and spatial variability of satellite data as driving forces in the model; weaknesses are the simplicity of the egg production model and the broad-scale generalizations assumed in the raising factors to convert egg production to biomass.

The global distribution of phytoplankton size spectrum and size classes from their light-absorption spectra derived from satellite data

The absorption spectra of phytoplankton in the visible domain hold implicit information on the phytoplankton community structure. Here we use this information to retrieve quantitative information on phytoplankton size structure by developing a novel method to compute the exponent of an assumed power-law for their particle-size spectrum. This quantity, in combination with total chlorophyll-a concentration, can be used to estimate the fractional concentration of chlorophyll in any arbitrarily-defined size class of phytoplankton. We further define and derive expressions for two distinct measures of cell size of mixed. populations, namely, the average spherical diameter of a bio-optically equivalent homogeneous population of cells of equal size, and the average equivalent spherical diameter of a population of cells that follow a power-law particle-size distribution. The method relies on measurements of two quantities of a phytoplankton sample: the concentration of chlorophyll-a, which is an operational index of phytoplankton biomass, and the total absorption coefficient of phytoplankton in the red peak of visible spectrum at 676 nm. A sensitivity analysis confirms that the relative errors in the estimates of the exponent of particle size spectra are reasonably low. The exponents of phytoplankton size spectra, estimated for a large set of in situ data from a variety of oceanic environments (similar to 2400 samples), are within a reasonable range; and the estimated fractions of chlorophyll in pico-, nano- and micro-phytoplankton are generally consistent with those obtained by an independent, indirect method based on diagnostic pigments determined using high-performance liquid chromatography. The estimates of cell size for in situ samples dominated by different phytoplankton types (diatoms, prymnesiophytes, Prochlorococcus, other cyanobacteria and green algae) yield nominal sizes consistent with the taxonomic classification. To estimate the same quantities from satellite-derived ocean-colour data, we combine our method with algorithms for obtaining inherent optical properties from remote sensing. The spatial distribution of the size-spectrum exponent and the chlorophyll fractions of pico-, nano- and micro-phytoplankton estimated from satellite remote sensing are in agreement with the current understanding of the biogeography of phytoplankton functional types in the global oceans. This study contributes to our understanding of the distribution and time evolution of phytoplankton size structure in the global oceans.