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Extrapolating with density surface models Laura Mannocci Workshop on spatial models for distance sampling - Oct 2015 - Duke Case study Extrapolating cetacean densities into the unsurveyed high seas of the western North Atlantic Laura


  1. Extrapolating with density surface models Laura Mannocci Workshop on spatial models for distance sampling - Oct 2015 - Duke

  2. Case study Extrapolating cetacean densities into the unsurveyed high seas of the western North Atlantic Laura Mannocci, Jason J Roberts, David L Miller, Patrick N Halpin

  3. Case study “Here be dragons” Extrapolating cetacean densities into the unsurveyed high seas of the western North Atlantic Laura Mannocci, Jason J Roberts, David L Miller, Patrick N Halpin

  4. Acknowledgements • Observers, crews, funding agencies, and everyone responsible for conducting the surveys: • Many people who shared surveys, provided advice, and reviewed results: Suzanne Bates, Elizabeth Becker, Tim Cole, Peter Corkeron, Andrew DiMatteo, Megan Ferguson, Karin Forney, Lance Garrison, Tim Gowan, Jim Hain, Phil Hammond, Jolie Harrison, Christin Khan, Anu Kumar, Erin LaBrecque, Claire Lacey, Gwen Lockhart, Bill McLellan, Dave Miller, Richard Pace, Debi Palka, Andy Read, Vincent Ridoux, Rob Schick, Sofie Van Parijs , Gordon Waring, Amy Whitt and many others… • Our funders:

  5. INTRODUCTION Fisheries Military sonars Ship traffic http://timzimmermann.com sanctuaries.noaa.org us.whales.org

  6. INTRODUCTION Fisheries Military sonars Ship traffic http://timzimmermann.com sanctuaries.noaa.org us.whales.org To evaluate the impacts of these human activities on cetacean populations in the high seas, we need density estimates

  7. INTRODUCTION Kaschner et al. 2012 Large regions of the high seas have never been surveyed

  8. INTRODUCTION Our goal: to produce the most reliable density estimates for all cetacean species in the U.S. Navy AFTT area NAVY Atlantic Fleet Testing & Training Area

  9. INTRODUCTION Our goal: to produce the most reliable density estimates for all cetacean species in the U.S. Navy AFTT area NAVY Atlantic Fleet Testing & Training Area ? ? ? ? EEZ ? ? U.S. surveys only covered a fraction of the AFTT area  extrapolate carefully

  10. INTRODUCTION Our goal: to produce the most reliable density estimates for all cetacean species in the U.S. Navy AFTT area NAVY Atlantic Fleet Testing & Training Area ? ? ? ? EEZ ? ? U.S. surveys only covered a fraction of the AFTT area  extrapolate carefully

  11. MATERIAL AND METHODS To extrapolate carefully, we: (1) Built models with environmental covariates only

  12. MATERIAL AND METHODS Environmental covariates with a broad range of values sampled by the surveys

  13. MATERIAL AND METHODS Environmental covariates with a broad range of values sampled by the surveys Spatial covariates -Latitude, Longitude

  14. MATERIAL AND METHODS Environmental covariates with a broad range of values sampled by the surveys Spatial covariates -Latitude, Longitude Physiographic covariates -Depth -Slope -Distance to shore -Distance to isobaths

  15. MATERIAL AND METHODS This is what would happen if we use distance to shore as a covariate: Predicted density map for beaked whales Surveyed Not surveyed Aberrant predictions

  16. MATERIAL AND METHODS This is what would happen if we use distance to shore as a covariate: Predicted density map for beaked whales Surveyed Not surveyed Aberrant Dangerous extrapolation predictions beyond the covariate values sampled by surveys

  17. MATERIAL AND METHODS Environmental covariates with a broad range of values sampled by the surveys Spatial covariates -Latitude, Longitude Physiographic covariates -Depth -Slope -Distance to shore -Distance to isobaths Physical covariates -Sea surface temperature -Distance to SST fronts -Sea level anomaly

  18. MATERIAL AND METHODS Environmental covariates with a broad range of values sampled by the surveys Spatial covariates -Latitude, Longitude Physiographic covariates -Depth -Slope -Distance to shore -Distance to isobaths Physical covariates -Sea surface temperature -Distance to SST fronts -Sea level anomaly Biological covariates -Chlorophyll concentration -Primary productivity -Biomass / production of zooplankton and micronekton (SEAPODYM outputs)

  19. MATERIAL AND METHODS To extrapolate carefully, we: (1) Built models with environmental covariates only (2) Incorporated surveys from relevant ecological biomes in the North Atlantic

  20. MATERIAL AND METHODS

  21. MATERIAL AND METHODS

  22. MATERIAL AND METHODS

  23. MATERIAL AND METHODS Increase the coverage of ecological biomes encompassed by the AFTT area

  24. MATERIAL AND METHODS To extrapolate carefully, we: (1) Built models with environmental covariates only (2) Incorporated line transect surveys from relevant ecological biomes in the North Atlantic (3) Fitted parsimonious models Simplicity “Fit”

  25. MATERIAL AND METHODS Limited the degrees of freedom of smooth functions to mitigate overfitting and avoid reproducing the detailed patterns present in the data

  26. MATERIAL AND METHODS Limited the degrees of freedom of smooth functions to mitigate overfitting and avoid reproducing the detailed patterns present in the data Limited degrees of freedom

  27. MATERIAL AND METHODS Limited the degrees of freedom of smooth functions to mitigate overfitting and avoid reproducing the detailed patterns present in the data Limited degrees of freedom Overfitted

  28. MATERIAL AND METHODS Limited the degrees of freedom of smooth functions to mitigate overfitting and avoid reproducing the detailed patterns present in the data Limited degrees of freedom Overfitted Limited the number of covariates to help understand the primary environmental drivers of cetacean abundances

  29. MATERIAL AND METHODS Limited the degrees of freedom of smooth functions to mitigate overfitting and avoid reproducing the detailed patterns present in the data Limited degrees of freedom Overfitted Limited the number of covariates to help understand the primary environmental drivers of cetacean abundances  Better generalize predictions to unsurveyed areas

  30. RESULTS In total, we modeled 29 cetacean taxa Sei whale NOAA Striped dolphin NMFS

  31. RESULTS Summer Sei whale model

  32. RESULTS Surveys: EC Summer Sei whale GOM model CAR MAR

  33. RESULTS Predictors: Expl Dev 38.5% Surveys: Depth EC Summer Sei whale Sea level anomaly GOM model Sea surface temperature CAR Production of micronekton MAR

  34. RESULTS Predictors: Expl Dev 38.5% Surveys: Depth EC Summer Sei whale Sea level anomaly GOM model Sea surface temperature CAR Production of micronekton MAR Predicted densities (individuals. 100 km -2 ) Coefficient of variation

  35. RESULTS Predictors: Expl Dev 38.5% Surveys: Depth EC Summer Sei whale Sea level anomaly GOM model Sea surface temperature CAR Production of micronekton MAR SST SST Depth Depth SLA SLA Predicted densities (individuals. 100 km -2 ) Coefficient of variation

  36. RESULTS Year-round Striped dolphin model

  37. RESULTS Surveys: EC Year-round Striped dolphin GOM model CAR MAR EU

  38. RESULTS Surveys: Predictors: Expl Dev 57% EC Year-round Depth Striped dolphin GOM Production of micronekton model CAR Chlorophyll concentration MAR EU Distance to SST fronts

  39. RESULTS Surveys: Predictors: Expl Dev 57% EC Year-round Depth Striped dolphin GOM Production of micronekton model CAR Chlorophyll concentration MAR EU Distance to SST fronts Predicted densities (individuals. 100 km -2 ) Coefficient of variation

  40. RESULTS Surveys: Predictors: Expl Dev 57% EC Year-round Depth Striped dolphin GOM Production of micronekton model CAR Chlorophyll concentration MAR EU Distance to SST fronts CHL CHL CHL & CHL & DFronts DFronts Predicted densities (individuals. 100 km -2 ) Coefficient of variation

  41. CAVEATS

  42. CAVEATS Strong assumptions on the shapes of cetacean-environment relationships beyond the sampled covariate ranges Example: sei whale ? Possible underestimation of sei whale abundance in cold northern waters

  43. CAVEATS Predictions less reliable in certain areas Log CHL in June (mg.m -3 ) SST in February (°C) Polar waters with colder SST North Atlantic gyre with lower CHL in winter in summer

  44. CAVEATS Lack of data for evaluating model predictions in the high seas Qualitative assessment of predictions with presence only data from the literature:

  45. CAVEATS Lack of data for evaluating model predictions in the high seas Qualitative assessment of predictions with presence only data from the literature: Prieto et al. 2012 Clark and Gagnon 2004 Tracks of sei whales tagged in the Azores Hydrophones from the Navy SOSUS

  46. APPLICATIONS

  47. APPLICATIONS These density estimates will be entered in the Navy Acoustic Effects Model to estimate potential incidental ‘takes’ of marine mammals in the AFTT area Incidental ‘takes’

  48. PERSPECTIVES • As new survey data become available, we plan to continuously update and refine our models to provide the most accurate estimates in the AFTT area

  49. PERSPECTIVES • As new survey data become available, we plan to continuously update and refine our models to provide the most accurate estimates in the AFTT area • The incorporation of surveys from the North Atlantic gyre and polar waters would greatly improve the models

  50. Thank you for your attention!

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