Biological - Physical Coupling in the Gulf of Maine: Satellite and Model Studies of Phytoplankton Variability

Abstract:
Profound differences in the relative strength and seasonality of advection, tidal mixing and stratification lead to a strong spatial heterogeneity in phytoplankton dynamics in the Gulf of Maine. A quantitative understanding of the time and space scales of variability and their linkages to physical forcing is required to identify long term trends and isolate the possible effects of climate change in this economically and ecologically important continental shelf region. The Gulf of Maine is one of the more heavily studied coastal regions, however, cruises provide only non-synoptic, coarse resolution, realizations of the phytoplanktonic and hydrographic patterns and/or provide detailed but site specific quantitative rate estimates across specific boundaries / features. The relationship between regions, their interaction, and the timing and nature of their response to external forcing is poorly understood.
We are undertaking a synoptic analysis of Gulf of Maine phytoplankton variability based on integrated ocean color satellite data (SeaWiFS, OCTS and MODIS), surface temperature data (AVHRR , MODIS) and a coupled biological - physical numerical model. The goal is to quantify differences and linkages in the biological/physical coupling between and within subregions. Time series of coincident satellite data are used to quantify the dominant modes of variability and linkage on time scales from specific events (~10 days) to seasonal and interannual. The numerical circulation model used is the Princeton Ocean Model (POM). We begin with an embedded five-component (nitrate, ammonium, phosphorus, zooplankton, detritus) biological model, with the five ecosystem balance equations solved simultaneously with the POM. The project includes a retrospective analysis of archived data. The analysis is structured to provide tests of recent hypotheses regarding spring bloom development, contrasting seasonal cycles in the Gulf of Maine, patterns inferred from multi-year cruise data, linkages between regions and tests of the relative effects of local versus non-local forcing on different subsystems within the Gulf of Maine.

Introduction:
Quantification of temporal and spatial variability in biological patterns and their relationship to physical processes is a key step toward identifying long-term trends in ocean climate change and isolating local from non-local effects. Compared to the open ocean, spatial and temporal gradients in both hydrographic and biological properties of mid-latitude coastal regions are relatively large. Biological productivity is also generally higher and anthropogenic influence more concentrated. Coupling between physical forcing and biological response is most likely when their time and space scales of variability are similar (Denman and Powell 1984). Identification, and ultimately prediction of long-term trends in these coastal regions and the identification of anthropogenic influence therefore demands a rigorous quantification of both the spatial and temporal variability present, separation of local from advective effects and the ability to delineate regions and/or time periods when specific processes and relationships dominate. The Gulf of Maine represents an extremely diverse and complex coastal region with respect to oceanographic processes and biological-physical interactions.