Reliability of Manual Counting for Thermal Census of Bats Within Human‐Made Structures

Abstract

Traditional methods for censusing wild bat populations are often prone to bias and can be impractical for complex roosts within human‐made structures. Thermal infrared cameras have increasingly provided a remote sensing solution, but resulting bat counts from thermal video are typically generated by human observers for which reliability remains poorly understood. Because these manual counts serve both as population estimates and as benchmarks for validating novel computer vision censusing methods, assessing their potential biases is essential. This study evaluated the inter‐observer consistency of manual bat counts from thermal videos across three Mexican free‐tailed bat ( Tadarida brasiliensis ) roosts in human‐made structures. We outlined methods for collecting thermal footage, training human counters ( n = 4), and assessing count consistency. We assessed interrater agreement and reliability through Bland–Altman plots, supplemented by intraclass correlation coefficients (ICC). One counter exhibited consistent undercounting, significantly reducing agreement ( p < 0.001) and reliability ( p = 0.001). Correlation heatmap analysis indicated that high abundances of insects, birds, and other non‐bat flying objects increased count variability within the study group ( p < 0.001). These findings demonstrate the importance of applying standardized statistical assessments of observer consistency before using manual counts as census estimates. Ensuring reliability is particularly critical as observer‐based thermal counts increasingly serve as validation datasets for computer vision approaches to bat censusing.