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Predictions from harbor porpoise habitat association models are confirmed by long-term passive acoustic monitoring
Brookes, K.L.; Bailey, H.; Thompson, P.M. (2013). Predictions from harbor porpoise habitat association models are confirmed by long-term passive acoustic monitoring. J. Acoust. Soc. Am. 134(3): 2523-2533. http://dx.doi.org/10.1121/1.4816577
In: The Journal of the Acoustical Society of America. American Institute of Physics: New York. ISSN 0001-4966; e-ISSN 1520-8524, more
Peer reviewed article  

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Keyword
    Marine/Coastal
Author keywords
    acoustic applications, bioacoustics, environmental monitoring (geophysics), underwater sound, zoology

Authors  Top 
  • Brookes, K.L.
  • Bailey, H.
  • Thompson, P.M.

Abstract
    Survey based habitat association models provide good spatial coverage, but only a snapshot in time of a species' occurrence in a particular area. A habitat association model for harbor porpoises was created using data from five visual surveys of the Moray Firth, Scotland. Its predictions were tested over broader temporal scales using data from static passive acoustic loggers, deployed in two consecutive years. Predictions of relative abundance (individuals per kilometer of survey transect) were obtained for each 4?km?×?4?km grid cell, and compared with the median number of hours per day that porpoises were acoustically detected in those cells. There was a significant, but weak, correlation between predicted relative abundance and acoustic estimates of occurrence, but this was stronger when predictions with high standard errors were omitted. When grid cells were grouped into those with low, medium, and high predicted relative abundance, there were similarly significant differences in acoustic detections, indicating that porpoises were acoustically detected more often in cells where the habitat model predicted higher numbers. The integration of acoustic and visual data added value to the interpretation of results from each, allowing validation of patterns in relative abundance recorded during snapshot visual surveys over longer time scales.

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