Connecting ecological and physical time-series:the potential role of changing seasonality

There are many ecological time-series available to the marine scientific community and it is essential that the patterns they exhibit be investigated and understood. To achieve this it is usually necessary to connect such series to others, e.g. fish abundance to sea-surface temperature, wind stress or food availability. Regression models are popular for analysing such information and can be useful in separating and assessing the relative influences of various effects on a given series. However, in such contexts, serial correlation will often render the statistics derived from such models difficult to interpret-and we feel that this fact is generally under-rated. From the literature available, there is ample evidence of scientific mechanisms between pairs of time-series being supported mainly by the value of statistics such as correlation coefficients. Unfortunately, however, where data are observational, not derived from designed experiments and serially correlated, such statistical tests can be of limited use in deducing scientific mechanisms. Surprisingly, the classical technique of decomposing time-series into separate long-term trend, seasonal, cyclic and noise components is rarely attempted (cf. Broekhuizen & McKenzie 1995), and, even when information is available at high temporal resolutions, annual averages are often used as summaries (e.g. Fromentin & Planque 1996, Hirst & Batten 1998). This obliterates any interesting seasonal structure in the time-series which may be useful in aiding ultimate scientific interpretation. The purpose of this comment is to promulgate the idea that seasonal structure, omnipresent in environmental data (e.g. Beare et al. 1998), might actually be helpful in explaining mechanism between pairs, or even groups, of time-series where changes in the seasonal structure occur simultaneousiy. The point is illustrated with a dramatic example involving the North Atlantic Oscillation (NAO) index, which is strongly related to the meteorology of the whole North Atlantic region (Hurrel 1995, 1996) and the abundance of Stage 5 and 6 Calanus finrnarchicus in the northern North Sea where a change in seasonal structure occurred in 2 series in the same year (1967). Other profound changes in the ecology of the North Atlantic and North Sea have also been noted in that period. In the north-west Atlantic on the Georges Bank, for example, the haddock population crashed in 1967 (see Hayes & Buxton 1992) but at the same time exploded to the south and east in the North Sea, together with stocks of cod and whiting during a well-documented period known as the 'gadoid outburst'. Also at that time, herring catches fell in the seas around Britain and were replaced by mackerel, which became the new focus of the pelagic fisheries of the northern European nations (Gunderson 1993). Here, we analyse the NAO and the abundance of Stage 5 and 6 Calanus finrnarchicus in the north-western quadrant (57" to 61°N, 4"W to 0') of the North Sea (Fig. 1). We use the NAO index of Jones et al. (1997) which was constructed using mean-sea-level-pressure data from Reykjavik and Gibraltar and is freely available at the following website: http://www.cru. uea.ac. uk. Jones' NAO data are available as monthly aggregated values and extend from July 1821 to the near present. NAO indices are usually interpreted by examining the long-term trend associated with the winter months. The exclusive use of only this part of the year is justified on the basis of its higher signal to noise ratio. The presence of a long-term trend in the winter NAO, however, indicates that there is a changing seasonal structure within this index. The time-series data for Stage 5 and 6 C. finmarchicus are Continuous Plankton Recorder data (Warner & Hays 1994). Both the NAO index (1958 to 1996) and Calanus finrnarchicus data (1958 to 1996) were analysed using standard time-series decomposition techniques (e.g. Broekhuizen & McKenzie 1995) which separate the