An empirical model for estimating phytoplankton productivity in estuaries
e have previously shown that primary productivity in San Francisco Bay, USA, is highly correlated with phytoplankton biomass B (chlorophyll a concentration) and an index of light avallability in the photic zone, 2, I, (photic depth times surface irradiance). To test the generality of this relation, we compiled data from San Francisco Bay and 5 other USA estuarine systems (Neuse and South Rivers, Puget Sound, Delaware Bay and Hudson River Plume), and regressed daily produclvity J' P (mg C m-2 d-') against the composite parameter B Z, I,. Regressions for each estuary were significant and typically over 80 % of the varialon in P was correlated with variations in B Z,I,. Moreover, the pooled data (n = 211) from 4 estuaries where methodologies were comparable fell along one regression line (r2= 0.82), indicating that primary productivity can be estimated in a diversity of estuarine waters from simple measures of phytoplankton biomass and hght availability. This implies that physiological variabhty (e. g. responses to variations in nutrient availabhty, temperature, sahnity, photoperiod) is a secondary control on phytoplankton production in nutrient-rich estuaries, and that one empirical function can be used to estimate seasonal variations in productivity or to map productivity along estuarine gradients of phytoplankton biomass and turbidity.
|Publication Subtype||Journal Article|
|Title||An empirical model for estimating phytoplankton productivity in estuaries|
|Series title||Marine Ecology Progress Series|
|Contributing office(s)||Toxic Substances Hydrology Program|
|Google Analytic Metrics||Metrics page|