Abstract
Passive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false indications of presence are still an important limitation and a crucial factor for acceptance of these techniques in wildlife surveys. Here we present the Assemblage of Focal Species Recognizers—AFSR, a novel approach for decreasing false positives and increasing models’ precision in multispecies contexts. AFSR focusses on decreasing false positives by excluding unreliable sound file segments that are prone to misidentification. We used MatlabHTK, a hidden Markov models interface for bioacoustics analyses, for illustrating AFSR technique by comparing two approaches, 1) a multispecies recognizer where all species are identified simultaneously, and 2) an assemblage of focal species recognizers (AFSR), where several recognizers that each prioritise a single focal species are then summarised into a single output, according to a set of rules designed to exclude unreliable segments. Both approaches (the multispecies recognizer and AFSR) used the same sound files training dataset, but different processing workflow. We applied these recognisers to PAM recordings from a remote island colony with five seabird species and compared their outputs with manual species identifications. False positives and precision improved for all the five species when using AFSR, achieving remarkable 0% false positives and 100% precision for three of five seabird species, and < 6% false positives, and >90% precision for the other two species. AFSR’ output was also used to generate daily calling activity patterns for each species. Instead of attempting to withdraw useful information from every fragment in a sound recording, AFSR prioritises more trustworthy information from sections with better quality data. AFSR can be applied to automated species identification from multispecies PAM recordings worldwide.
Highlights
Recent technical advances in sound-recording technologies and analyses have considerably enlarged the potential application of bioacoustics in conservation studies
Since the analysis of performance here are based on the time length assigned to each category, the false positives are given in proportion of time
Passive acoustic monitoring (PAM) recordings made in the natural settings can register complex soundscapes containing sound passages susceptible to generate misidentification
Summary
Recent technical advances in sound-recording technologies and analyses have considerably enlarged the potential application of bioacoustics in conservation studies. The integration of PAM recording with automated identification is a considerable advance that can be applied in biodiversity assessments in diverse environmental conditions and ecosystems These methods show great potential for wildlife monitoring, limitations and uncertainties remain that discourage incorporation of these analyses into management programs. High number of false positives can be problematic when acoustic sampling is the only method used to generate indications of presence for species focus of conservation actions. This is the case for many seabird species in remote offshores islands. Grey-faced petrels are the first species to vocalize at the colony after dusk (from ~19:20 hrs), shortly followed by Common diving petrels, Fluttering shearwaters, and White-faced storm petrels (all vocalizing from around ~19:30 hrs; Fig 4).
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