Hopp til hovedteksten
Admar logo
Print friendly version


”Adaptive management of living marine resources by integrating different data sources and key ecological processes (ADMAR): A joint effort by IMR and CEES”

The Norwegian Ocean Resource Act (Havressursloven) of 2009 is a formal implementation of the Ecosystem Approach to Fisheries. This requires explicit management action towards data rich stocks, as well as for data poor stocks, including those of minor commercial importance.

The overall goal of this project is to enhance knowledge of ecosystem functioning and to derive a framework for operational adaptive management. To meet this goal, progress needs to be made in two directions: Firstly, there is a need for developing models with high levels of realism. Different data sources (survey data, fisheries statistics, life history traits, multi species considerations etc.), including their error structures, need to be integrated to derive key parameters and time-series. Further development of stock assessment models, including identifying and quantifying uncertainties, is paramount. Secondly, better biological models must be developed, which incorporate food-web interactions and provide a basic understanding of ecosystem functioning. In order to model multi-species dynamics parsimoniously, size-based models will be developed. These models, which realistically describe the essential ecological processes, may be particularly useful in data-poor situations.

Using both approaches, the project will seek to derive Harvest Control Rules (HCR) for exploited stocks. This allows us to study the outcome of different harvesting scenarios, under varying amounts of information, and see how a reduction in information affects the most robust HCR, in an operational setting. The project will also consider different ecological scenarios, where species interactions continuously change within and among species over the course of harvesting and environmental changes. These operational models form the basis for deriving a modeling framework, which provides scientifically sound advice conditioned on the level and quality of the available information.