Splitting Historical Blue Whale Catches using Spatial GAMs Cole Monnahan 1/16/2012 Mizroch et al. 1984.

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Presentation transcript:

Splitting Historical Blue Whale Catches using Spatial GAMs Cole Monnahan 1/16/2012 Mizroch et al. 1984

Background/Motivation North Pacific Blue whales (B. musculus) were exploited commercially from Endangered, but no assessment due in part to conflated catches Themes: 2 Stocks: the eastern (ENP) and western (WNP) based on morphological¹ and acoustic² analyses Uncertainty: date, location, statistical, ecological ¹ Gilpatrick & Perryman 2008, ² Stafford et al. 2001

Ecology WNP ENP

Land Stations

Catches Before 1950

Floating Factories Photo: A. Berzin

Catches After 1950

Catches from

Acoustic Data Locations Goal: Infer stock identity of catches (using the acoustic data) Acoustic Hydrophones

1995/1996 NP 1995/1996 NP 1999/2001 GoA 1996/1997 Eastern Tropical Pacific (ETP) Acoustic Data Dates

Acoustic Spectrograms Image from: Stafford 2003, Two types of blue whale calls recorded in the Gulf of Alaska

Acoustic Data

Western population only in western Aleutians Eastern population only in ETP

Models A priori predictors: Lat/Long and Month cover the spatial and temporal stock movements Generalized Additive Models (GAM) Over-dispersion is expected, so a beta-binomial distribution is used Jackknifing bootstrapping to quantify statistical uncertainty of predictions

Binomial vs. Beta-Binomial

Over-dispersed Binomial

GAM Models AIC supports beta-binomial and GAM GAMLSS [Rigby & Stasinopoulos 2002] in R Separate models for ENP and WNP of form: The model predicts: the probability of observing a call at a given location/month in an hour.

Residuals for ENP Models

Eastern Model Surface

Western Model Surface

Final Model Ecological Assumptions: 1.Populations call at the same rates 2.Relative population sizes stable over decades 3.Movement patterns stable over many decades 4.AB song distribution reflects all demographic groups The final probability of catch being ENP is then:

Ecological Uncertainty Deviations from α=1 lead to unexplained uncertainty Vary α to explore sensitivity to assumptions

Probability of Eastern (α=1)

Statistical Uncertainty: Jackknifing

Jackknifed Errors: May

Probability of Eastern (α=1)

Results: Best Estimate

Results: Min ENP

Results: Max ENP

Final Results

Conclusions 1.This approach splits the catches and tries to accurately quantify the uncertainty 2.With more data, the ecological assumptions could be tested. But sensitivity analyses are best option. 3.It allows assessment of ENP (chapter 2!)…and maybe WNP in the future

Acknowledgements Trevor Branch: Advice and funding International Whaling Commission (IWC): Provided annual catch and individual database. Kate Stafford (UW Applied Physics Lab): Raw acoustic data on call types (+ advice). Yulia Ivashchenko (NMML): Providing Soviet catch data Andre Punt (UW SAFS): Suggesting the beta-binomial GAM And of course….

Questions? Comments? Advice?