ABSTRACT
This study evaluates the ship of opportunity (Ferrybox) concept for both sustained monitoring of UK shelf sea waters and numerical model validation. Release of phosphate from the wreck of a chemical tanker (MV Ece) in the western English Channel (49.73 degrees N, 3.25 degrees W) in March 2006 is used to demonstrate the importance of sustained observations in decision support systems and policy development. The Ferrybox system continuously collects sea surface (5m) data from a suite of autonomous electronic sensors installed on a passenger ferry operating year-round between Portsmouth (UK) and Bilbao (Spain). The detection of anomalously high concentrations of phosphate (1.54mmolm(-3), four times the usual level) and onset of phytoplankton growth close to the wreck site in March 2006 was placed in the context of multiple years of measurements (phosphate, nitrate, silicate and chlorophyll) collected from the Ferrybox system (2003-2006) and the long-term time series station E1 (50.03 degrees N, 4.65 degrees W, 1930-1987) in the English Channel. With regard to decision support, release of phosphate from the tanker is unlikely to pose a threat as phytoplankton growth at the end of winter is not unusual in this region and dissolved inorganic nitrogen rather than phosphate (DIN:DIP=10-18) is likely to ultimately limit algal growth in spring 2006. With regard to policy development, the Oslo and Paris (OSPAR) commissions recommendation of sampling every three years in "non-problem areas" is likely to provide statistically inadequate data, given the interannual and decadal variability identified in the Ferrybox and E1 data: the Ferrybox data show that oceanic winter nutrient concentrations varied by 35-50% between 2003/2004 and 2005/2006 due to deeper mixing of water off-shelf in early 2005/2006 and comparisons between the Ferrybox and E1 years show that the western English Channel is currently experiencing a low in phosphate concentrations similar to those in the 1960s. The importance of Ferrybox data in evaluating the reliability of predictive operational models needed in decision support is also demonstrated, by highlighting both strengths and weaknesses in a state-of-the-art ecosystem model designed for UK shelf waters.
