Statistical code from: Passive acoustic monitoring with AI-based detection and identification reveal sooty grouse hooting patterns in western Oregon

We estimated sooty grouse hooting patterns, both daily and seasonal, using
generalized additive mixed models (GAMMs) using hooting data. The
influence of weather, topographic, and study region were examined using
these models, as were time since sunrise (daily) and day of year
(seasonal). For both daily and seasonal frameworks, we compare models that
incorporate both smooth and fixed terms using the mgcv package in Program
R using the percent of deviance explained.