Data from: Modelling misclassification in multi-species acoustic data when estimating occupancy and relative activity

Wilson J Wright, Kathryn M Irvine, Emily S Almberg & Andrea R Litt
1. Surveying wildlife communities provides data for informing conservation and management decisions that affect multiple species. Autonomous recording units (ARUs) can efficiently gather community data for a variety of taxa, but generally require software algorithms to classify each recorded call to a species. Species classification errors are possible during this process and result in both false negative and false positive detections. Available approaches for analysing ARU data do not model the species classification probabilities, meaning...
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