A predictive model for estimating rates of primary production

A primary production model, speci"c to the subtropical North Paci"c, was developed using productivity and chlorophyll data collected at Station ALOHA (22.753N, 158.003W) and measured phytoplankton physiological parameters. The production algorithm is a mechanistic, full spectral model that provides depth-dependent photosynthesis rates. Six years of phytoplankton pigment data were analyzed to derive seasonal cycles and to parameterize chlorophyll a (Chl; monovinyl and divinyl chlorophyll a) versus depth pro"les. The Chl pro"les "t a Gaussian-type distribution with depth over a constant background concentra-tion equal to mixed-layer values.MaximumChl concentrations were always found below the surface, and the parameters displayed distinct monthly and seasonal patterns. Photosynthesis versus irradiance experiments were conducted at a number of locations and seasons in the vicinity of Station ALOHA to calculate phytoplankton physiological parameters needed for the computation of primary production rates. Relation-ships were explored between environmental conditions and the physiological and pro"le parameters in order to develop algorithms based on remotely sensed sea-surface variables and time of year. These relationships were used to model primary production rates using data collected during the Hawaii Ocean Time-series (HOT) program. The performance of the model and model parameters were tested by comparing modele