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Abundance Estimation of Long‐Diving Animals Using Line Transect Methods
Author(s) -
Okamura Hiroshi,
Minamikawa Shingo,
Skaug Hans J.,
Kishiro Toshiya
Publication year - 2012
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2011.01689.x
Subject(s) - transect , abundance estimation , distance sampling , abundance (ecology) , sampling (signal processing) , statistics , environmental science , estimation , aerial survey , fishery , ecology , computer science , biology , mathematics , geography , remote sensing , engineering , systems engineering , filter (signal processing) , computer vision
Summary Line transect sampling is one of the most widely used methods for estimating the size of wild animal populations. An assumption in standard line transect sampling is that all the animals on the trackline are detected without fail. This assumption tends to be violated for marine mammals with surfacing/diving behaviors. The detection probability on the trackline is estimated using duplicate sightings from double‐platform line transect methods. The double‐platform methods, however, are insufficient to estimate the abundance of long‐diving animals because these animals can be completely missed while the observers pass. We developed a more flexible hazard probability model that incorporates information on surfacing/diving patterns obtained from telemetry data. The model is based on a stochastic point process and is statistically tractable. A simulation study showed that the new model provides near‐unbiased abundance estimates, whereas the traditional hazard rate and hazard probability models produce considerably biased estimates. As an illustration, we applied the model to data on the Baird’s beaked whale ( Berardius bairdii ) in the western North Pacific.