Bayesian updating to estimate extinction from sequential observation data

Colin J. Thompson*, Saritha Kodikara, Mark A. Burgman, Haydar Demirhan, Lewi Stone

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Several new approaches to estimating the probability that a species is extinct have emerged recently. Different foundational assumptions can lead to different interpretations of data and potentially to different conclusions. To explore the implications of alternative formulations, here we develop and illustrate a Bayesian Updating method for inferring extinction based on records of observations and surveys. We illustrate how it combines incidental sightings and surveys with a data set for the Alaotra Grebe, showing how estimates of extinction may be updated as new data arise, providing a means for managers to reassess priorities for survey and management dynamically.

Original languageEnglish
Pages (from-to)26-29
Number of pages4
JournalBiological Conservation
Volume229
DOIs
StatePublished - Jan 2019

Keywords

  • Bayes Factors
  • Bayes rule
  • Dynamic updating
  • Extinction
  • Observations
  • Surveys
  • Threatened species

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