A spatial integrated population model applied to black-footed albatross Simon Hoyle Mark Maunder

Background Black-footed albatross Phoebastria nigripes Breed on north-western Hawaiian islands –Genetically distinct population on Torishima island About breeding pairs in Hawaiian population Conservation status –Endangered (IUCN) –Petition (US ESA)

Project PFRP – integrated modelling for protected species Current status –2 models Hoyle & Maunder Maunder, Alvarez-Flores & Hoyle

Model structure Spatial effects at 2 levels –Sub-populations on islands and island groups Kure, Midway, Pearl & Hermes Reef, Lisianski, Laysan, French Frigate Shoals (FFS) FFS also broken down into Disappearing, East, Little Gin, Gin, Round, Trig, Tern, and Whale-Skate islands –Spatial and temporal overlap of birds and fishing effort Bycatch from pooled population Birds interact with fishing vessels Bird distribution depends on age and stage Integrated analysis –Fitting to multiple data types

Data types by model

Nest and fledgling counts Collated in Cousins and Cooper 2001 Timing of counts –Year = fledge year –Nests = counts of nests or pairs, Dec – Jan –Fledglings = counts of chicks or fledglings, May – July

Nest and fledgling counts - uncertainty CV Direct counts of breeding pairs5% Based on sample counts & transects10% Extrapolations of total bird counts20% Estimated from chicks counted later, or doubt expressed 30% Uncertainty reportedAs given

Trends vary by island

Breeding success rates

Survival rates – correlated with fishing effort

Return rates

Breeding season range

Summer range

Albatross distribution 1

Albatross distribution 2

Fishing effort Effort typeMAHHM Hawaiian longline – shallow and deepYY Californian longline – shallowNY Alaskan groundfish longline – BSAI and GOANY Non-US longline – shallow and deepNY Large mesh driftnet (Japan)YY Squid driftnet (Japan, Korea, Taiwan)YY

HA and CA longline effort

Driftnet effort

Non-US longline effort

Bycatch estimates

Fishing selectivity Catch at age –Recapture of tagged birds (C&C 2000) –Ageing of Canadian longline bycatch Above strongly suggest higher juvenile selectivity Potential extra sources –Timing of Hawaiian longline fishery captures –Samples from driftnet fisheries at Burke Museum, U Washington (60+) –Samples from Hawaii LL fishery

Population model (HM) Multi-state age-based model Recruitment Dynamics Initial conditions Likelihoods

Important population processes Spatial and temporal relationships of fishing effort and bird distribution Selectivity (catchability of different life stages) Skipping breeding & breeding success by island Density dependence Movement between islands? –Recruitment –As adults

Migration Seems important for dynamics at the local scale –Whale-Skate island disappears –After a number of years, Trig island pop increases(?) –Tern island grows too fast? Impractical to estimate, and may not be significant between island groups –No linkage with Torishima

Model structure 5 stages –juvenile –immature –successful breeder –unsuccessful breeder –non-breeder Population structured by colony, time, stage, & age Dynamics in 2 stages: N’(t)=N(t)survival N(t+1)=N’(t)transition

Dynamics

Distribution of birds and effort Effort in each fishery by grid varies through time Bird distribution varies by season, stage, and year Spatial and temporal effects in Hawaiian catch rates Distribution can be inferred from telemetry, Hawaiian bycatch

Mortality

Stage transitions (breeding) Attempt breeding (i.e. NB or SB/UB) Successful breeding (i.e. SB or UB)

Density dependence Not currently in model Likely to act on probability of successful breeding, age at first breeding, & probability of attempting to breed

Initial conditions Initial recruitment per colony Rzero c Projected across age classes at time t start given natural mortality and transition rates

Expected values and Likelihoods For fitting to –Bycatch –Counts (nests and fledglings) –Tagging data –Breeding success

Bycatch (lognormal LL) Counts (lognormal LL)

Observed survival Transition rates use a similar approach – adding up estimated transitions Likelihood –Multivariate normal fit to Hessian Tagging data

Breeding success (binomial likelihood) Expected value

Estimated parameters Currently only –Rzero c –  c (colony effect on p(breed successfully) –q f (catchability by fishery) All other parameters currently fixed

Results Fit to –Count data –Mark-recapture survival Return rate –Bycatch estimates –Breeding success Total bycatch Population trajectories

Survival and return rate

Return rate

Bycatch estimates

Breeding success

Count data

Total bycatch

Conclusion Modelling in progress –Algorithm working –Preparing new distribution data Important question for managers is overall population trend Interesting to examine what processes may explain differing population trends by island –Breeding success –Recruitment/migration rates –Differential fishing mortality

The end

To Do Initial conditions – check and fix Density dependence