Big Sharks in the Salish Sea: combining passive acoustics with the Salish Sea model to predict Sixgill Shark (Hexanchus griseus) presence

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1 Western Washington University Western CEDAR Salish Sea Ecosystem Conference 2018 Salish Sea Ecosystem Conference (Seattle, Wash.) Apr 5th, 2:30 PM - 2:45 PM Big Sharks in the Salish Sea: combining passive acoustics with the Salish Sea model to predict Sixgill Shark (Hexanchus griseus) presence Alli Cramer Washington State Univ., United States, allison.cramer@ .wsu.edu Steve Katz Washington State Univ., United States, steve.katz@wsu.edu Kelly Andrews Northwest Fisheries Science Ctr., United States, kelly.andrews@noaa.gov Daniel H. Thornton Washington State Univ., United States, daniel.thornton@wsu.edu Follow this and additional works at: Part of the Fresh Water Studies Commons, Marine Biology Commons, Natural Resources and Conservation Commons, and the Terrestrial and Aquatic Ecology Commons Cramer, Alli; Katz, Steve; Andrews, Kelly; and Thornton, Daniel H., "Big Sharks in the Salish Sea: combining passive acoustics with the Salish Sea model to predict Sixgill Shark (Hexanchus griseus) presence" (2018). Salish Sea Ecosystem Conference This Event is brought to you for free and open access by the Conferences and Events at Western CEDAR. It has been accepted for inclusion in Salish Sea Ecosystem Conference by an authorized administrator of Western CEDAR. For more information, please contact westerncedar@wwu.edu.

2 Alli N. Cramer Dr. Steve Katz, Kelly Andrews, Dr. Daniel H. #SalishSeaSharks Photo credit: NOAA Modified through cropping and flipping by Alli Cramer

3 Photo credit: NOAA Ocean Explorer 2016 Modified through cropping by Alli Cramer.

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5 Data Properties GPS TRACKING Individual determinant Continuous in time and space WILDLIFE CAMERAS Individual indeterminate Discontinuous in time and space Photo credits (left to right): Dr. Zoe Hanley, National Parks Service Kyle Ebenhoch, Rademaker M, Meijaard E, Semiadi G, Blokland S, Neilson EW, Rode-Margono EJ (2016) First Ecological Study of the Bawean Warty Pig (Sus blouchi), One of the Rarest Pigs on Earth. PLoS ONE 11(4): e

6 Data Properties GPS TRACKING WILDLIFE CAMERAS S_ID LONG LAT YEAR MONTH DAY HOURS MINUTES SECONDS OBS_NAME Unid. Small Cetacean Blue Whale Humpback Whale Blue Whale Individual determinant Continuous in time and space Humpback Whale Humpback Whale Humpback Whale Blue Whale Blue Whale Humpback Whale Unid. Large Whale Humpback Whale Unid. Large Whale Unid. Large Whale Individual indeterminate Discontinuous in time and space Blue Whale Humpback Whale Unid. Large Whale Humpback Whale Humpback Whale Photo credits (left to right): Dr. Zoe Hanley, National Parks Service Kyle Ebenhoch, Rademaker M, Meijaard E, Semiadi G, Blokland S, Neilson EW, Rode-Margono EJ (2016) First Ecological Study of the Bawean Warty Pig (Sus blouchi), One of the Rarest Pigs on Earth. PLoS ONE 11(4): e

7 Photo credit: NOAA Ocean Explorer 2016 Modified through cropping by Alli Cramer.

8 Photo credit: NOAA Ocean Explorer 2016 Modified through cropping by Alli Cramer.

9 How does environmental variability correlate with the presence or absence of the shark? Can we predict where the shark is likely to be? Photo credit: NOAA Ocean Explorer 2016 Modified through cropping by Alli Cramer.

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11 Aerial View Side View m

12 Salish Sea Model

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16 Whale Sightings Channel Islands National Marine Sanctuary Probability of Presence Logistic Regression Present Presence Absent Water Temperature C

17 Whale Sightings Channel Islands National Marine Sanctuary Probability of Presence Logistic Regression Present Probability of Presence Presence Pseudo-Absence Absent Water Temperature C

18 Whale Sightings Channel Islands National Marine Sanctuary Probability of Presence Logistic Regression Present Probability of Presence Presence Pseudo-Absence Absent Water Temperature C

19 Present All predictors p < 0.5 Probability of Presence Absent Depth (m) Temperature C Salinity ppt Dissolved Oxygen (mg/l)

20 True Positive Rate False Positive Rate

21 Histogram of Random AUCs vs Model AUC Frequency P value < AUC values

22 Photo credit: NOAA Ocean Explorer 2016 Modified through cropping by Alli Cramer.

23 Dr. Steve Katz, Washington State University Kelly Andrews, Northwest Fisheries Science Center Dr. Daniel H. Thornton, Washington State University Dr. Tarang Khangaonkar, Pacific Northwest National Laboratory Washington State Department of Ecology Center for Institutional Research Computing at Washington State University Stephanie Labou, CEREO Washington State University Michael Frederick Meyer, Washignton State University Dr. Steve Powers, CEREO Washington State University Dr. Stephanie Hampton, CEREO Washington State University

24 Contact Check out the R Working cereo.wsu.edu/r-working-group Photo credit: NOAA Ocean Explorer 2017 screen grab.

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26 Best option for deep, long term studies

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29 Single Environmental data point Three Environmental data points

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33 Present Present Probability of Presence Probability of Presence Absent Depth (m) Temperature C Salinity ppt Absent Depth (m) Temperature C Salinity ppt All predictors p< 0.5

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35 Salish Sea Model predicted vs observed model concentrations * and estimates of model bias and RMSE.