- Objectives
- Improve the yellowfin and bigeye indices of relative abundance from longline data
- Determine methods to identify targeting in longline fisheries
- Develop spatio-temporal models for creating indices of relative abundance from longline data
- Develop appropriate longline length composition data for the index of abundance and for the catch
- Background
- Indices of relative abundance derived for longline CPUE data are the most important piece of information in the bigeye and yellowfin stock assessments
- Only the Japanese data are currently used to create these indices
- The characteristics, tactics, and spatial distribution of the fishery have been changing over time
- The same length composition data is used for the index and for the catch, but these could differ
- New methods, such as spatio-temporal modelling, have been developed and should be used in the creation of the indices
- Relevance for management
- The indices have direct impact on the stock assessment and any improvements in the indices will directly improve the management advice for bigeye and yellowfin
- Duration
- 18 months, starting June 2018
- Workplan and status
- June-Dec 2018: Evaluate the data available in the IATTC database and implement the spatio-temporal models
- Jan-Feb 2019: Hold a one-week workshop to discuss approaches to resolve issues in using the longline CPUE data
- May-June 2019: Hold a two-week working group to analyze the data (not funded)
- External collaborators
- NRIFSF, Japan
- Invited speakers
- Deliverables
- Workshop report
- Working group report (not funded)
- Indices of relative abundance
- Project report to SAC
- Updated date: 01 Apr 2021
- Progress summary for the reporting period
- Preparations for the workshop included:
- Provision of operational-level longline data for main distant-water longline fleets
- Visits by Japanese (Dr. Keisuke Satoh) and Korean (Dr. Sung-Il Lee) scientists to work with the staff on analyses
- Visit by external expert (Dr. Simon Hoyle, supported by ISSF).
- A workshop was held on February 2019: 23 participants, including 7 invited speakers
- The work continued after the workshop and the context of the project H.1.1
- Challenges and key lessons learnt
- The operational data essential for improving the assessment are not permanently available to the staff.
- Matching size-composition and operational data proved difficult, and is not yet completed, the indices were obtained by modelling data aggregated into a 1° latitude by 1° longitude
- The additional workshop needed to finalize the work (Project H.1.e) is not currently funded.
- Materials for the workshop
- Presentation at SAC-10
- Comments
- The work related to this project continued in Project H.1.e
