Decadal basin-scale changes in diatoms, dinoflagellates, and phytoplankton color across the North Atlantic

The Continuous Plankton Recorder (CPR) survey has been used to characterize phytoplankton and zooplankton space-time dynamics in the North Sea since 1931 and in the North Atlantic since 1939. Phytoplankton biomass is assessed from these samples by visual assessment of the green color of the silk mesh, the Phytoplankton Color Index (PCI), and the total count of diatoms and dinoflagellates. Species with a frequency of occurrence greater than 1% in the samples are used as indicator species of the community. We investigated (1) long-term fluctuations of phytoplankton biomass, total diatoms, and total dinoflagellates; (2) geographical variation of patterns; (3) the relationship between phytoplankton and climate forcing in the North Atlantic CPR samples; (4) the relative contribution of diatoms and dinoflagellates to the PCI; and (5) the fluctuations of the dominant species over the period of survey to provide more information on the processes linking climate to changes in the phytoplankton community. As a result of the differences in microscopic analysis methods prior to 1958, our analyses were conducted for the period ranging from 1958 to 2002. The North Atlantic was divided into six regions identified through bathymetric criteria and separated along a North-South axis. Based on 12 monthly time series, we demonstrate increasing trends in PCI and total dinoflagellates and a decrease in total diatoms.

Structure of phytoplankton (Continuous Plankton Recorder and SeaWiFS) and impact of climate in the Northwest Atlantic Shelves

All marine organisms are affected to some extent by the movement and thermal properties of oceanic currents. However phytoplankton, because of its small size is most directly coupled to the physical environment. The intense hydrodynamic activity observed in the Northwest Atlantic Shelves Province makes this region especially intriguing from the point of view of physical-biological interactions. In the present work, remote sensed data of Sea Surface Height (SSH) anomalies, Sea-surface chlorophyll a concentrations (SeaWiFS), and Sea Surface Temperature (SST) are used to complement the Continuous Plankton Recorder (CPR) survey that continuously sampled a route between Norfolk (Virginia, USA; 39° N, 71° W) and Argentia (Newfoundland; 47° N, 54° W) over the period 1995–1998. Over this period, we examined physical structures (i.e. SST and SSH) and climatic forcing associated with space-time phytoplankton structure. Along this route, the phytoplankton structures were mainly impacted by the changes in surface flow along the Scotian Shelf rather than significantly influenced by the mesoscale features of the Gulf Stream. These changes in water mass circulation caused a drop in temperature and salinity along the Scotian Shelf that induced changes in phytoplankton and zooplankton abundance.

Remote sensing of assimilation number for marine phytoplankton

Estimating primary production at large spatial scales is key to our understanding of the global carbon cycle. Algorithms to estimate primary production are well established and have been used in many studies with success. One of the key parameters in these algorithms is the chlorophyll-normalised production rate under light saturation (referred to as the light saturation parameter or the assimilation number). It is known to depend on temperature, light history and nutrient conditions, but assigning a magnitude to it at particular space-time points is difficult. In this paper, we explore two models to estimate the assimilation number at the global scale from remotely-sensed data that combine methods to estimate the carbon-to-chlorophyll ratio and the maximum growth rate of phytoplankton. The inputs to the algorithms are the surface concentration of chlorophyll, seasurface temperature, photosynthetically-active radiation af the surface of the sea, sea surface nutrient concentration and mixed-layer depth. A large database of in situ estimates of the assimilation number is used to develop the models and provide elements of validation. The comparisons with in situ observations are promising and global maps of assimilation number are produced.