Ecosystem Dynamic Behavior Model (EDBM)
Sustainable Flows’ Ecosystem Dynamic Behavior Model improves yields and sustainability by revealing interactions among fish populations, ecosystem functions and fisher decision making. EDMB’s modular components are easily adapted and integrated into most fisheries management programs and the Model has already improved management strategies and optimized data collection.
GOING BEYOND CURRENT PRACTICES
Regardless of their current level of sophistication, fisheries management systems need to begin embracing complex modeling in order to address emerging challenges. Most fisheries management systems have procedures to review potential strategies before implementing them and to refine those strategies over time. However, growing technical capacity of managers and improvements in technology are providing opportunities to:
- Manage multiple fish species and their ecological interactions collectively
- Balance fishing rights with tourists, economic development, and other commercial and conservation uses
- Scale management from individual areas to larger regions or seascapes
- Integrate the impacts of climate change and invasive species
- Optimize data collection for cost savings.
EDBM’s flexibility allows its components to be adapted and integrated into a fisheries’ existing management system. Based on Management Strategy Evaluation methods, these components are organized in 5 generic phases:
- Do phase, when different EDBM configurations are tested, and different management strategies (e.g. boundaries, quotas) are analyzed for their economic and ecological impacts.
- Evaluate & learn phase, when EDBM is checked against management and fisher
ies goals and stakeholder engagement is used to ensure alignment.
- Adjust phase, when technical aspects of the model are improved, including adding new data.
- Data Collection Simulator phase runs in parallel the core phases. The Simulator analyzes sampling options, identifying the techniques, locations, frequencies and dates that meet scientific criteria and minimize costs.
Box 1: EDBM individual-based modeling techniques
EDBM recreates some of the system dynamics among fishers and their environment. Through data analysis, theories about fisher decision making and fish biology are coded as “individuals” that interact with one another in realistic ways. By altering these behavior parameters against different management strategies (e.g. fishing boundaries, catch limits), managers are able to understand how these individuals agents affect one another and ultimately yields and sustainability. For example, to test how different marine protected area boundaries impact the location, costs and yields of fishing and also fish populations, several boundaries can be modeled showing how and why fishing patterns changed. Over time, EDBM’s predictions are validated and refined while new parameters are added, thus increasing managers’ capacity to reduce risks from emerging and unforeseen environmental and economic challenges.
Box 2: EDBM’s visual component
EDBM’s visual component provides numerous graphics that simplify how the model interprets different management scenarios. Allowing stakeholders, for example, to see how fishing effort and biomass change over time under different scenarios. This helps improve stakeholder confidence in and support of management strategies. The scenario shown here suggests that fishers concentrate their efforts in the northeastern portion of the study area.