[MARMAM] New Publication: Handling dolphin detections from C-PODs, with the development of acoustic parameters for verification and the exploration of species identification possibilities.

James Robbins jamesrichardrobbins at googlemail.com
Fri Jan 1 08:28:32 PST 2016


Dear colleagues,
My co-authors and I are pleased to announce the following publication:

James R. Robbins, Anja Brandecker, Michelle Cronin, Mark Jessopp,
Rob McAllen & Ross Culloch (2015): *Handling dolphin detections from
C-PODs, with the development of acoustic parameters for verification and
the exploration of species identification possibilities*. Bioacoustics,
DOI: 10.1080/09524622.2015.1125789

Abstract:
C-PODs are static passive acoustic monitoring devices used to detect
odontocete vocalizations in the range of 20–160 kHz. However, falsely
classified detections may be an issue, particularly with broadband species
(i.e. many dolphin species) due to anthropogenic and other noise occurring
at the same frequency. While porpoise detections are verified using
species-specific acoustic parameters, the equivalent does not currently
exist for verifying dolphin detections. Development of such parameters
would increase the accuracy of dolphin detections and eliminate the need
for additional monitoring techniques or devices, reducing the cost of
monitoring programmes. Herein, we present parameters based on acoustic
characteristics of bottlenose (*n* = 29), common (*n* = 19) and
Risso’s (*n* = 99)
dolphin click trains, sighted within 1 km of C-PODs during land-based
surveys, for in-software verification. Overlap of click train parameters
among dolphin species prevented robust species identification; therefore,
parameters were devised for these dolphin species collectively using
frequency, inter-click interval and click train duration. A data set of
4898 Detection Positive Hours was visually verified using these parameters.
The temporal and spatial patterns in the visually verified data were
similar to land-based observations, suggesting the parameters operate at an
acceptable accuracy. However, 68% of high-, moderate- and low-quality KERNO
detections were false-positive. Our results suggest that the accuracy of
classifiers and quality class weightings are site-specific, and we
highlight the importance of data exploration to make the most appropriate
software choices based on the aims of a study.

This paper is available online:
http://dx.doi.org/10.1080/09524622.2015.1125789

If there are any questions, queries or you would like to request a PDF
copy, please contact the corresponding author at :
jamesrichardrobbins at googlemail.com

Kind regards, and wishing you a happy new year.
James Robbins
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