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The Harbor Seals Strike Back After the 1989 Exxon

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The Harbor Seals Strike Back After the 1989 Exxon

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    2. 2/39 The Harbor Seals Strike Back? – After the 1989 Exxon/Valdez oil spill S. Bhotika (Ecology, UF), B. Chan (Math, Cornell), E. Heestand (EEOB, OSU), M. Madan (Stat, MUN), H. Zhang, Ph.D. (EEOB, OSU)

    3. 3/39 Outline Introduction Prince William Sound Exxon Valdez oil spill Harbor Seals Dataset Statistical Techniques Exploratory Analysis Regression Models Hierarchical Bayesian Model Discussion

    4. 4/39 Prince William Sound (PWS), Alaska Dense populations of marine mammals Sea otters, killer whales, sea lions, seals Large populations of sea birds Rich herring and salmon fisheries

    5. 5/39 Exxon/Valdez oil spill 3/24/1989 -12:04am 11 mil gallons of oil spilled into PWS 1900 km coastline contaminated Ecological impact: 250,000 seabirds 28,000 sea otters 300 harbor seals 250 bald eagles 22 orcas Billions of salmon and herring eggs

    6. 6/39 Harbor seals, Phoca vitulina richardsi Haul out onto land to rest, molt, and give birth

    7. 7/39 Harbor seals in PWS Do not appear to avoid oil at haulout sites or in the water. Do not appear to move between sites (oiled/un-oiled). Seals exposed to oil exhibit lethargic behavior and are easily approached.

    8. 8/39 Objective Assess the trends of harbor seal populations over time in PWS after the Exxon/Valdez oil spill.

    9. 9/39 Goals Estimate trends in the study area as a whole Estimate trends at individual sites Estimate the effects of covariates on seal counts

    10. 10/39 Dataset Harbor seal populations monitored at 12 haulout sites Sites visited 7 to 10 times annually (1990 – 2002) Counts conducted by aerial survey Data collected within 2 hrs of low tide Poor weather or a rapidly rising tide prohibited data collection at times (with the aid of 7-power binoculars), from a single-engine fixed-wing aircraft (Cessna185) at altitudes of 100-300m. (with the aid of 7-power binoculars), from a single-engine fixed-wing aircraft (Cessna185) at altitudes of 100-300m.

    11. 11/39 Dataset SITE: 1 to 12 YEAR: 1990 - 2002 DATE: Number of days starting Aug. 1st TIME: Time of day (in hrs) TIDEDEV: Time relative to low tide (in hrs) SEALS: Number of observed harbor seals x.UTM, y.UTM: Coordinates of the haulout sites

    12. 12/39 Statistical Techniques Exploratory data analysis General trends Spatial correlation Regression models Linear regression Poisson regression Hierarchical Bayesian model

    13. 13/39 Exploratory analysis – General trends

    14. 14/39 Exploratory analysis – General trends

    15. 15/39 Exploratory analysis – General trends

    16. 16/39 Exploratory analysis – General trends

    17. 17/39 Exploratory analysis – Spatial correlation Dataset was organized by Site and Trip Date 58 trips on which all sites were visited Cor. Matrix computed, Pearson’s value = 0.26

    18. 18/39 Exploratory analysis – Spatial correlation 6 data points available for each year Pearson’s value = 0.811 Decreasing trend of correlation over time Cannot detect any spatial correlation

    19. 19/39 Exploratory analysis – Spatial correlation Variogram is used to fit spatial correlation Omni-directional No spatial correlation is observed

    20. 20/39 Conceptual Model

    21. 21/39 An approximation

    22. 22/39 Linear regression Categorize data DATE: August, September TIDEDEV: (-8, -1], (-1, 0], (0, 1], (1, 8) TIME: [0,4), [4, 8), …, [20, 24)

    23. 23/39 Results – Linear regression YEAR, SITE, MONTH, TIDEDEV are significant R2 = 0.593, Adj. R2 = 0.581

    24. 24/39 Poisson regression

    25. 25/39 Results – Poisson regression YEAR, SITE, MONTH, TIDEDEV are significant Akaike information criterion (AIC) = 16145

    26. 26/39 Results – Poisson regression

    27. 27/39 Results – Poisson regression Applied the same regression to each site Green: pos. trend, White: neg. trend, Red: unclear

    28. 28/39 Hierarchical Bayesian (HB) Model

    29. 29/39 Remarks on the HB Model TIME was removed Quadratic form for TIDEDEV was used Reflects a concave effect Poisson regression with quadratic term was also performed with AIC = 16163 > 16145 Diffuse prior distributions were used for all parameters

    30. 30/39 Results – HB Model

    31. 31/39 Results – HB Model

    32. 32/39 Results – Poisson vs. HB

    33. 33/39 Summary of Results Similar results were obtained from Poisson regression and Hierarchical Bayesian model Significant factors: Site, Year, Date, Tidedev Harbor seal population trends in PWS: declining at sites 2, 3, 4, 6, 7, 10, 12 increasing at sites 11 not distinguishable at sites 1, 5, 8, 9 No observable spatial correlation, from either the correlation matrix or the variogram

    34. 34/39 Discussion – Overall trend Expected: seal populations declining after the oil spill and increasing and/or stabilizing over a period of time. Results: a slight decrease / undetectable Possible reasons: initial decline following spill (1989-1990) not captured in our dataset after cleanup efforts, lingering oil may affect seal health but not seal counts seal populations were already declining before the oil spill, since the 1970s

    35. 35/39 Discussion – Site specific trends Expected: seal populations declining more at oiled sites than at un-oiled sites. Results show 7 sites are declining 1 site is increasing 4 sites are indistinguishable No pattern for oiled vs. un-oiled sites Possible reasons: Water is connecting all sites (especially in PWS-enclosed body of water)

    36. 36/39 Discussion – Effects of covariates Over the study period, data were collected earlier in the year (seals may haul out less later in the year - molting period and breeding season over) Tidedev (More seals haulout closer to low tide)

    37. 37/39 Discussion – Study Limitations No seal counts prior to the spill All sites were not visited on some of the trips Sites not visited randomly (affects which sites observed at low tide) Sites visited earlier in the year over time High variability in seal observations at site over small time period Limited number of sites Limited covariates in the dataset: site area, human traffic, resources, predators

    38. 38/39 Acknowledgements Hongfei Li Kate Calder MBI / OSU Alaska Department of Fish & Game

    39. 39/39 References Ver Hoef, J. and Frost, K.J. (2003) A Bayesian hierarchical model for monitoring harbor seal changes in Prince William Sound, Alaska. Environ. And Ecol. Stat. 10, 201 – 219. Frost, K.F., Lowry, L.F., Sinclair, E., Ver Hoef, J., and McAllister, D.C. (1994) Impacts on distribution, abundance, and productivity of harbor seals. In Marine Mammals and the Exxon Valdez, T.R. Loughlin (ed.), Academic Press, Inc., San Diego. pp. 97 – 118. Garrison, W. May/June 1994. Watchable Wildlife – Harbor Seals. http://www.dfg.ca.gov/watchable/seals.html. Accessed on July 24, 2006. Kinkhart, E. and Pitcher, K. Mar 2005. Harbor Seal. Alaska Dept of Fish and Game. http://www.adfg.state.ak.us/pubs/notebook/marine/harseal.php. Accessed on July 24, 2006. NOAA/HMRAD. Oil Spill Case History 1967 – 1991. Sept 1992. http://response.restoration.noaa.gov/book_shelf/26_spilldb.pdf. Accessed on July 24, 2006. ValdezScience.com. Valdez Science: An Environmental Update. 2004. http://www.valdezscience.com. Accessed on July 24, 2006. Alaska Stock, LLC. 2006. Prince William Sound http://www.alaskastock.com/Prince_William_Sound_Photos.asp. Accessed on Aug 2, 2006.

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