Passive acoustic monitoring and convolutional neural networks facilitate high-resolution and broadscale monitoring of a threatened species

Passive acoustic monitoring (PAM) detects rare/cryptic species across landscapes. We trained a convolutional neural network (PNW-Cnet) to identify marbled murrelets. PAM is used to conduct the first broad-scale marbled murrelet call phenology study. PAM and PNW-Cnet are powerful tools for marbled murrelet research and monitoring.