Assessment of Error Rates in Acoustic Monitoring with the R package monitoR

Detecting population-scale reactions to climate change and land-use change may require monitoring many sites for many years, a process that is suited for an automated system. We developed and tested monitoR, an R package for long-term, multi-taxa acoustic monitoring programs. We tested monitoR with two northeastern songbird species: black-throated green warbler (Setophaga virens) and ovenbird (Seiurus aurocapilla). We compared detection results from monitoR in 52 10-minute surveys recorded at 10 sites in Vermont and New York, USA to a subset of songs identified by a human that were of a single song type and had visually identifiable spectrograms (e.g. a signal:noise ratio of at least 10 dB: 166 out of 439 total songs for black-throated green warbler, 502 out of 990 total songs for ovenbird). monitoR’s automated detection process uses a ‘score cutoff’, which is the minimum match needed for an unknown event to be considered a detection and results in a true positive, true negative, false positive or false n...