Organismal Biology in the Age of Ecosystem-Based Management

摘要

Ecosystem-based management rests upon a scientific foundation involving greater structural complexity and larger spatial and temporal scales of predictive models. Increases in complexity and scale impose constraints upon the extent to which complexityat the level of an organism (life history, behavior, and physiology) can be modeled. Although the earliest ecosystem models, notably Ecopath and its successors, eliminated much organismal detail and instead adopted a biomass dynamic approach, newer models such as Atlantis and multispecies virtual population analysis retain greater detail at the organismal level. However, effective ecosystem-based management will require appreciation of the limitations of complex models and reliance upon parallel insights on key processes gained through empirical research that are not captured by models. These insights should be used to evaluate differences between model predictions and management outcomes, modify models where possible, and adjust management measures suggested by models otherwise. Important empirical research at the organismal level includes effects of habitat, contaminants, and physical and chemical properties of water on organismal traits. It is then important to understand reciprocal effects of those changes on the ecosystem (e.g., temperature-driven changes in growth that alter trophic interactions). Intrapopula-tion variability in life history traits, behavior, and physiology can increase resilience to ecosystem change, and those benefits and processes that erode that variability need to be understood. Ultimately, the continued evolution toward ecosystem-based science and management should strive for a balance between reality and tractability in underlying models and incorporate empirical research in addition to model outputs to best shape management measures.