1 / 29

Output of LL1 CPUE analysis

This appendix presents detailed analysis of CPUE Index in historical series models with varying data resolutions and weighting factors. The study explores impacts of different area weightings and models on CPUE trends, depicted through Q-Q plots and monitoring data.

harolds
Download Presentation

Output of LL1 CPUE analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Output of LL1 CPUE analysis CCSBT/ESC/1009/22 Appendix Tomoyuki Itoh and Norio Takahashi NRIFSF, Fisheries Research Agency Suggested seeing colour version in the Power Point file.

  2. Fig. 1a. CPUE index (different historical series)Base and Reduced model did not included BET and YFT CPUEs in the GLM models.

  3. Fig. 1b. CPUE index (Different GLM model; No area weighting)

  4. Fig. 1c. CPUE index (Different GLM model; Constant Square)

  5. Fig. 1d. CPUE index (Different GLM model; Variable Square)

  6. Fig. 1e. CPUE index (Different GLM models; W0.8 area weighting)

  7. Fig. 1f. CPUE index (Different GLM models; W0.5 area weighting)

  8. Fig. 1g. CPUE index (Different area weighting; Base)

  9. Fig. 1h. CPUE index (Different area weighting; Reduced base)

  10. Fig. 2. Sum of area index for variable square by year (Area index is by year, month, Area and Latitude 5 degree.)

  11. Fig. 3a. CPUE index monitoring (different data resolution )5x5 month data vs shot-by-shot data

  12. Fig. 3b. CPUE index monitoring (Different area weighting; Base; Using shot-by-shot data)

  13. Fig. 4. CPUE index monitoring (adding vessel ID)Using shot-by-shot data for vessel ID.

  14. Fig. 5a. CPUE index monitoring (Subtract factor from Base model; No area weighting)

  15. Fig. 5b. CPUE index monitoring (Subtract factor from Base model; Constant Square area weighting)

  16. Fig. 5c. CPUE index monitoring (Subtract factor from Base model; Variable Square area weighting)

  17. Fig. 5d. CPUE index monitoring (Subtract factor from Base model; W0.8 area weighting)

  18. Fig. 5e. CPUE index monitoring (Subtract factor from Base model; W0.5 area weighting)

  19. Fig. 6a Q-Q plot of GLM standardization (Base)

  20. Fig. 6b. Q-Q plot of GLM standardization (Run-03)

  21. Fig. 6c. Q-Q plot of GLM standardization (Run-06)

  22. Fig. 6d. Q-Q plot of GLM standardization (Reduced Base)

  23. Fig. 6e. Q-Q plot of GLM standardization (Base – Year*Area)

  24. Fig. 6f. Q-Q plot of GLM standardization (Base – Year*Latitude)

  25. Fig. 6g. Q-Q plot of GLM standardization (Base – Month*Area)

  26. Fig. 6h. Q-Q plot of GLM standardization (Base – Yellowfin tuna CPUE)

  27. Fig. 6i. Q-Q plot of GLM standardization (Base – Bigeye tuna CPUE)

  28. Fig. 6j. b10 Q-Q plot of GLM standardization (Shot-by-shot data)

  29. Fig. 6k. Q-Q plot of GLM standardization (Base+vessel ID; Useing shot-by-shot data

More Related