Calling Phenology of Two Frog Species in South Korean Rice Paddies Using Automated Call Detection

Amphibian breeding phenology provides key insights into species' sensitivity to climatic and anthropogenic drivers. We used passive acoustic monitoring (PAM) with automated call detection to examine the calling activity of <i>Dryophytes japonicus</i> and <i>Pelophylax nigromaculatus</i> in South Korean rice paddies across five breeding seasons (2018-2022). Both species exhibited distinct seasonal patterns: <i>D. japonicus</i> showed a synchronous and concentrated calling peak in mid-June (GAM deviance explained = 34%), whereas <i>P. nigromaculatus</i> initiated calling earlier and maintained a longer, less synchronized calling period extending into July (GAM deviance explained = 19%). Zero-inflated negative binomial models demonstrated that temperature was the strongest predictor of calling activity in both species, though responses to humidity and wind differed. <i>D. japonicus</i> maintained high calling rate under warm conditions, with only modest suppression at high humidity, whereas <i>P. nigromaculatus</i> was strongly inhibited by combined warm and humid conditions. These results establish a detailed information on the calling phenology of <i>D. japonicus</i> and <i>P. nigromaculatus</i> in East Asian agroecosystems highlight species-specific sensitivities to local weather variables. Our findings demonstrate that automated acoustic monitoring offers an efficient way to document ecological responses to weather variability and may serve as a long-term tool to track phenological shifts under climate change. Future advances in sound analysis, including the integration of deep-learning algorithms and cross-species detection frameworks, could further improve automated biodiversity monitoring in complex agricultural landscapes.