Estimating uncertainty in density surface models

Details

• Journal Title:
  PeerJ
• Personal Author:
  Miller, David L. ; Becker, Elizabeth A. ; Forney, Karin A. ; Roberts, Jason J. ; Cañadas, Ana ; Schick, Robert S.
• NOAA Program & Office:
  NMFS (National Marine Fisheries Service) ; SWFSC (Southwest Fisheries Science Center)
• Description:
  Providing uncertainty estimates for predictions derived from species distribution models is essential for management but there is little guidance on potential sources of uncertainty in predictions and how best to combine these. Here we show where uncertainty can arise in density surface models (a multi-stage spatial modelling approach for distance sampling data), focussing on cetacean density modelling. We propose an extensible, modular, hybrid analytical-simulation approach to encapsulate these sources. We provide example analyses of fin whales Balaenoptera physalus in the California Current Ecosystem.
• Keywords:
  General Agricultural And Biological Sciences General Biochemistry, Genetics And Molecular Biology General Medicine General Neuroscience General Agricultural And Biological Sciences General Biochemistry, Genetics And Molecular Biology General Agricultural And Biological Sciences General Biochemistry, Genetics And Molecular Biology
• Source:
  PeerJ, 10, e13950
• DOI:
  https://doi.org/10.7717/peerj.13950
• ISSN:
  2167-8359
• Format:
  PDF
• Publisher:
  PeerJ
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/publicdomain/zero/1.0/
• Rights Information:
  CC0 Public Domain
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:1269bf858fe37f5e1f8393aa9f46efafcda80c685c7fa80df11779cf7e1dda07
• Download URL:
  https://repository.library.noaa.gov/view/noaa/50637/noaa_50637_DS1.pdf
• File Type:
  [PDF - 4.64 MB ]