Improving population estimates by quantifying diving and surfacing patterns: A dugong example

Rie Hagihara*, Rhondda E. Jones, Alana Grech, Janet M. Lanyon, James K. Sheppard, Helene Marsh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Diving animals are available for detection from above the water when environmental conditions are favorable and the animals are near the surface. The number of animals that are unavailable for detection needs to be estimated to obtain unbiased population estimates. The current availability correction factors used in aerial surveys for the dugong (Dugong dugon) allow for variation in environmental conditions but use the average time dugongs spend near the surface (i.e., constant availability corrections). To improve availability estimates, we examined location and dive data from nine dugongs fitted with satellite telemetry units and time-depth recorders (TDRs) in eastern Australia. The effects of water depth, tidal conditions, and habitat types on dugong surfacing time were examined using generalized linear mixed models (GLMMs). We found that availability for detection differed with water depth, and depth-specific availability estimates were often lower than the constant estimates. The habitat effect was less influential, and there was no tidal effect. The number of dugongs estimated using depth-specific availabilities were higher than those obtained using constant availabilities across water depth. Hence, information on water depth can refine availability estimates and subsequent abundance estimates from dugong aerial surveys. The methodology may be applicable to other aquatic wildlife.

Original languageEnglish
Pages (from-to)348-366
Number of pages19
JournalMarine Mammal Science
Volume30
Issue number1
DOIs
Publication statusPublished - Jan 2014

Keywords

  • Abundance estimation
  • Aerial survey
  • Availability bias
  • Diving
  • Dugong
  • Generalized linear mixed model (GLMM)
  • Marine mammal
  • Population
  • Sirenia

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