Using hidden Markov models to deal with availability bias on line transect surveys

David Louis Borchers, Walter Zucchini, M.P. Heide-Jørgensen, A. Cañadas, Roland Langrock

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)
8 Downloads (Pure)

Abstract

We develop estimators for line transect surveys of animals that are stochastically unavailable for detection while within detection range. The detection process is formulated as a hidden Markov model with a binary state-dependent observation model that depends on both perpendicular and forward distances. This provides a parametric method of dealing with availability bias when estimates of availability process parameters are available even if series of availability events themselves are not. We apply the estimators to an aerial and a shipboard survey of whales, and investigate their properties by simulation. They are shown to be more general and more flexible than existing estimators based on parametric models of the availability process. We also find that methods using availability correction factors can be very biased when surveys are not close to being instantaneous, as can estimators that assume temporal independence in availability when there is temporal dependence.
Original languageEnglish
Pages (from-to)703-713
Number of pages11
JournalBiometrics
Volume69
Issue number3
Early online date12 Jul 2013
DOIs
Publication statusPublished - 2013

Keywords

  • Availability bias
  • Detection hazard
  • Hidden Markov model
  • Line transect
  • Wildlife survey

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