Food for thought Why compare marine ecosystems?

Effective marine ecosystem-based management (EBM) requires understanding the key processes and relationships controlling the aspects of biodiversity, productivity, and resilience to perturbations. Unfortunately, the scales, complexity, and non-linear dynamics that characterize marine ecosystems often confound managing for these properties. Nevertheless, scientifically derived decisionsupport tools (DSTs) are needed to account for impacts resulting from a variety of simultaneous human activities. Three possible methodologies for revealing mechanisms necessary to develop DSTs for EBM are: (i) controlled experimentation, (ii) iterative programmes of observation and modelling (“learning by doing”), and (iii) comparative ecosystem analysis. We have seen that controlled experiments are limited in capturing the complexity necessary to develop models of marine ecosystem dynamics with sufficient realism at appropriate scales. Iterative programmes of observation, model building, and assessment are useful for specific ecosystem issues but rarely lead to generally transferable products. Comparative ecosystem analyses may be the most effective, building on the first two by inferring ecosystem processes based on comparisons and contrasts of ecosystem response to human-induced factors. We propose a hierarchical system of ecosystem comparisons to include within-ecosystem comparisons (utilizing temporal and spatial changes in relation to human activities), within-ecosystem-type comparisons (e.g. coral reefs, temperate continental shelves, upwelling areas), and cross-ecosystem-type comparisons (e.g. coral reefs vs. boreal, terrestrial vs. marine ecosystems). Such a hierarchical comparative approach should lead to better understanding of the processes controlling biodiversity, productivity, and the resilience of marine ecosystems. In turn, better understanding of these processes will lead to the development of increasingly general laws, hypotheses, functional forms, governing equations, and broad interpretations of ecosystem responses to human activities, ultimately improving DSTs in support of EBM.