Real-time krill data for fisheries

Even though the majority of measures to manage the marine environment are relatively fixed or adhere to set formulas (e.g. marine protected areas, total allowable catches and quota setting), the ocean itself is highly dynamic. This can lead to disconnect between the intention of management measures and their real outcome.

Dynamic management can refine the temporal and spatial scale of managed areas, thereby balancing ecological and economic objectives. To implement dynamic management several gaps need to be filled, including developing “out-of-the-box” platforms to serve dynamic management data to users.

This project aims to develop a system to deliver acoustically derived estimates of krill density in (near) real-time from krill fishing vessels to fishery data users and managers (e.g. commercial managers, scientific researchers and/or policy managers). It is envisaged that facilitating rapid access to this data will encourage greater use and exploitation by more researchers and managers to develop new ecosystem analysis and management products.

1. Implement an open-source software toolbox to undertake unsupervised automated processing of acoustic data to krill density estimates
2. Develop metrics of data quality to inform vessels when surveying conditions are suitable in real-time
3. Build an onboard Vessel Data processing and analysis System (VDS) that connects up the processing toolbox with current day satellite communications to deliver “real-time” estimates of Antarctic krill from the fishing vessel to a terrestrial information system (specified email address, email format, metadata standard, and automated scripting to data storage)
4. Validate and verify the VDS (both software and hardware components) with historic survey data
5. Facilitate access to krill density data derived from fishing vessels and develop a road-map for how it can be made available for ecosystem management advice

The Rapidkrill project utilises a python-based tool-box (echopy) to process acoustic data, running on a small low-power computer. It is currently set up to access EK60 data onboard a vessel and send summary information to a shore-based information system.

The python-based tool-box “echopy” will be available from https://github.com/bas-acoustics/echopy