Is observed variability in the long-term results of the Continuous Plankton Recorder survey a response to climate change?

In the more than 50 years that the Continuous Plankton Recorder (CPR) survey has operated on a regular monthly basis in the north-east Atlantic and North Sea, large changes have been witnessed in the planktonic ecosystem. These changes have taken the form of long-term trends in abundance for certain species or stepwise changes for others, and in many cases are correlated with a mode of climatic variability in the North Atlantic, either: (1) the North Atlantic Oscillation (NAO), a basin-scale atmospheric alteration of the pressure field between the Azores high pressure cell and the Icelandic Low; or (2) the Gulf Stream Index (GSI), which measures the latitudinal position of the north wall of the Gulf Stream. Recent work has shown that the changes in the GSI are coupled with the NAO and Pacific Southern Oscillation with a 2 year lag. The plankton variability is also possibly linked to changes observed in the distribution and flux of water masses in the surface, intermediate and deep waters of the North Atlantic. For example, in the last two decades, the extent and location of the formation of North Atlantic Deep Water, Labrador Sea Intermediate Water and Norwegian Sea intermediate and upper-layer water has altered considerably. This paper discusses the extent to which observed changes in plankton abundance and distribution may be linked to this basin-scale variability in hydrodynamics. The results are also placed within the context of global climate warming and the possible effects of the observed melting of Arctic permafrost and sea ice on the subpolar North Atlantic.

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.

How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.