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To See or Not to See: Investigating Detectability of Ganges River Dolphins Using a Combined Visual-Acoustic Survey

Overview of attention for article published in PLOS ONE, May 2014
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Title
To See or Not to See: Investigating Detectability of Ganges River Dolphins Using a Combined Visual-Acoustic Survey
Published in
PLOS ONE, May 2014
DOI 10.1371/journal.pone.0096811
Pubmed ID
Authors

Nadia I. Richman, James M. Gibbons, Samuel T. Turvey, Tomonari Akamatsu, Benazir Ahmed, Emile Mahabub, Brian D. Smith, Julia P. G. Jones

Abstract

Detection of animals during visual surveys is rarely perfect or constant, and failure to account for imperfect detectability affects the accuracy of abundance estimates. Freshwater cetaceans are among the most threatened group of mammals, and visual surveys are a commonly employed method for estimating population size despite concerns over imperfect and unquantified detectability. We used a combined visual-acoustic survey to estimate detectability of Ganges River dolphins (Platanista gangetica gangetica) in four waterways of southern Bangladesh. The combined visual-acoustic survey resulted in consistently higher detectability than a single observer-team visual survey, thereby improving power to detect trends. Visual detectability was particularly low for dolphins close to meanders where these habitat features temporarily block the view of the preceding river surface. This systematic bias in detectability during visual-only surveys may lead researchers to underestimate the importance of heavily meandering river reaches. Although the benefits of acoustic surveys are increasingly recognised for marine cetaceans, they have not been widely used for monitoring abundance of freshwater cetaceans due to perceived costs and technical skill requirements. We show that acoustic surveys are in fact a relatively cost-effective approach for surveying freshwater cetaceans, once it is acknowledged that methods that do not account for imperfect detectability are of limited value for monitoring.

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Geographical breakdown

Country Count As %
United Kingdom 3 2%
Nepal 1 <1%
Germany 1 <1%
Mexico 1 <1%
Argentina 1 <1%
Unknown 154 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 19%
Student > Ph. D. Student 30 19%
Student > Master 27 17%
Student > Bachelor 21 13%
Other 9 6%
Other 25 16%
Unknown 19 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 74 46%
Environmental Science 38 24%
Earth and Planetary Sciences 7 4%
Biochemistry, Genetics and Molecular Biology 6 4%
Engineering 5 3%
Other 10 6%
Unknown 21 13%