A key requirement for implementing ecosystem-based management is to obtain timely information on significant fluctuations in the ecosystem (Botsford et al. 1997). However, obtaining all necessary information about physical and biological changes at appropriate temporal and spatial scales is a daunting task. Intuitively, one might assume that physical data are more important for the interpretation of ecosystem changes than biological data, but analyses of time series data suggest otherwise: physical data are more erratic and often confusing over the short term compared to biological data, which tend to fluctuate less on annual time scales (Hare & Mantua 2000). Even so, biological time-series may also be confusing when coexisting marine species respond differently to ecosystem variability. For example, while warming temperatures in the Gulf of Alaska following the 1976 to 1977 regime shift favored an increase in gadoids and flatfish, a variety of forage fish and pandalid shrimp species virtually disappeared (Anderson & Piatt 1999). Zooplankton communities in the Gulf of Alaska also demonstrated similar patterns of response (Francis et al. 1998). At the basin scale, favorable conditions for salmon in Alaska following the regime shift were matched inversely by poor conditions in the California Current (Francis et al. 1998). In marine birds, subtropical species increased, while subarctic ones decreased during a warming phase in the southern California Bight. Clearly, no single index can tell the whole story accurately. Multi-species, multi-region, and multi-trophic level approaches are needed to quantify fluctuations in marine ecosystem processes and in the distribution and abundance of its inhabitants, to determine critical parameter thresholds and to use this information in management and marine conservation.