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Mark Maunder (IATTC) Carlos Alvarez-Flores (Okeanos - Oceanides) Simon Hoyle (SPC)

A general covariate based approach for modeling the population dynamics of protected species: application to black footed albatross ( Phoebastria nigripes ). Mark Maunder (IATTC) Carlos Alvarez-Flores (Okeanos - Oceanides) Simon Hoyle (SPC). Photo Credit. Outline. General approach Data used

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Mark Maunder (IATTC) Carlos Alvarez-Flores (Okeanos - Oceanides) Simon Hoyle (SPC)

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  1. A general covariate based approach for modeling the population dynamics of protected species: application to black footed albatross (Phoebastria nigripes) Mark Maunder (IATTC) Carlos Alvarez-Flores (Okeanos - Oceanides) Simon Hoyle (SPC) Photo Credit

  2. Outline • General approach • Data used • Results • Discussion

  3. Spatial issue • Multiple sub-populations • All caught in same fisheries • Little information on which population a caught bird is from • Populations effected by different non-fishery mortality

  4. General approach • Population dynamics model • Integrated analysis • Fit to multiple data types • Survival a function of covariates • Fishing impacts • Non-fishery related impacts • Bycatch data aggregated from multiple populations

  5. Basic dynamics • Multiple populations • No exchange among populations • Skipping breeding • Share parameters among populations

  6. Basic dynamics

  7. Covariates

  8. Bycatch data p indexes population

  9. Index of abundance q = 1

  10. Survivorship prior

  11. Reproduction Where Erate is the maximum eggs per individual at low population size (=1) Emax is the maximum number of eggs produced by the entire population when the number of breeders is very large

  12. Reproduction

  13. Initial conditions • Simulate the population for 100 years to get equilibrium • Scaling this to get initial numbers

  14. Data Used

  15. Count Data Used

  16. FFS sub-population count data

  17. Parameters estimated • Initial abundance scalar for each population • Coefficient for each fishing effort series • Recruitment carrying capacity for each population • Survival for each population • Coefficient for Midway and Laysan survival covariates

  18. FFS sub-populations • Assume all FFS have same survival • Estimate Initial abundance scalar for each population • Estimate recruitment carrying capacity for each population

  19. Fits to data Thick lines - no covariates of additional mortality Thin lines - covariates of additional mortality were included to Midway and Laysan populations Solid lines – no fishing effort Dashed lines - with fishing effort

  20. With and without additional covariates

  21. Fits to the data when separating FFS into it’s sub-populations

  22. FFS data fit from sub-populations (dashed line) and pooled data (solid line)

  23. Base survival estimates

  24. Fishery impact

  25. Revisions • Model sub-populations? • Fisheries to include • Drift net • Hawaiian longline deep/shallow • High seas longline • Other fisheries • Data • Counts • Fishing effort • Bycatch • Survival priors • Survival covariates • What parameters to estimate

  26. Questions • Should the catch-rates in fisheries differ among populations (e.g. fisheries closer to population) • How to model sample data about origin of captures?

  27. The End

  28. Revisions • Model sub-populations? • Fisheries to include • Drift net • Hawaiian longline deep/shallow • High seas longline • Other fisheries • Data • Counts • Fishing effort • Bycatch • Survival priors • Survival covariates • What parameters to estimate

  29. revisions • Are counts pairs or numbers • Update counts to include all data • Correct catch data • Decide what fisheries to include • Covariate for an additional mortality factor from 1953 to 1982 for Midway and Laysan • Other covariates • How to constrain Rmax in FFS sub pops • Model FFS sub populations or not (do birds move between them?) • Juvenile survival rate from Sophie • Need to check the initial conditions and recruitment • Check sex structure in model

  30. revisions • Age of breeding??? Possibly age 7-8 from Lebreton’s recruitment model, Goodmans work suggests age 6-8 • Which survival parameters to use • Hypothesis testing for including covariates • After 1979 tern island increased habitat and is probably inter-atoll movement, also whale-skate disappeared • Whale-skate bands turned up on tern island • Egg loss in 1989 due to washover, tern island and others • What are swordfish ratios to tuna in non Japanese fleets • Widowing would increase effect of biomass • Is the island location relative to fishing effort important? • Changes in regulations will impact the correlations • Closure of Hawaiian longline moved effort to California, where mitigation regulations are weaker

  31. revisions • Use fledgling counts • Counts are the year of fledging? • Breeding success rates, i.e. egg survival • Breeding success at laysan island may be biased low cause hard to find chicks, however also has lower hatching survival • Check which survival estimates to use • There are some effort data for driftnets • Probably able to split hawaii longline bycatch estimates into deep shallow and time/space paul has done this • Boggs did analysis on age of birds in bycatch • Midway killing large number of birds in 50s and 60s

  32. Other survival covariates • Covariate for an additional mortality factor from 1953 to 1982 for Midway and Laysan

  33. Summary • Method shows promise • Need to update data • Need to include additional fisheries • Results are very preliminary • Fisheries appear to have substantial impact • Initial results indicate that populations are increasing in recent years

  34. Tern Island No skipping No lags Did not include non breeders In counts

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