Oceanic Primary Production: Estimation by Remote Sensing at Local and Regional Scales

TLDR

Satellites are the sole means to study marine primary production at ocean‑basin scales, and chlorophyll maps from remote sensing are used to develop algorithms for estimating primary production, a challenge in applied plant physiology. The study proposes an algorithm that merges a spectral‑angular submarine light model with a spectral photosynthesis response model, and calls for fieldwork to gather data that will optimize satellite‑based biological oceanography. The algorithm integrates a spectral‑angular submarine light model with a spectral photosynthesis response model and, for large‑scale application, relies on a dynamic biogeography of physiological rate parameters and water‑column structure.

Abstract

Satellites provide the only avenue by which marine primary production can be studied at ocean-basin scales. With maps of chlorophyll distribution derived from remotely sensed data on ocean color as input, deduction of a suitable algorithm for primary production is a problem in applied plant physiology. An algorithm is proposed that combines a spectral and angular model of submarine light with a model of the spectral response of algal photosynthesis. To apply the algorithm at large horizontal scale, a dynamic biogeography is needed for the physiological rate parameters and the biological structure of the water column. Fieldwork to obtain this type of data should be undertaken so that the use of satellite data in modern biological oceanography may be optimized.