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 Data typeData setYearsDescription EffortJapanese large mesh drift net1973-1992Based on albacore catches Japanese squid drift net1978-1992Based on squid catch and squid CPUE Korean squid drift net1979-1992Based on squid catch and Japanese squid CPUE Taiwanese squid drift net1972-1992Based on squid catch and Japanese squid CPUE Hawaiian shallow level 11991-2001Swordfish sets close to the Hawaiian islands BycatchJapanese large mesh drift net1991Observer data Japanese squid drift net1990Observer data Korean squid drift net1990Observer data Taiwanese squid drift net1990Observer data Hawaiian shallow level 11992-2003Total bycatch proportioned into shallow and deep SurvivalTern Island1992-2002From mark-recapture data

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 Population FFSKureMidwayP & HLisianskyLaysan 0.949600.993290.866390.846170.993190.81379

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 Adult survival0.95 Eggs per chick0.5 Egg survival0.65 Fledgling to adult survival0.74 No skipping No lags Did not include non breeders In counts