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

Research output: Contribution to journalArticlepeer-review

Abstract

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 Dryophytes japonicus and Pelophylax nigromaculatus in South Korean rice paddies across five breeding seasons (2018–2022). Both species exhibited distinct seasonal patterns: D. japonicus showed a synchronous and concentrated calling peak in mid-June (GAM deviance explained = 34%), whereas P. nigromaculatus 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. D. japonicus maintained high calling rate under warm conditions, with only modest suppression at high humidity, whereas P. nigromaculatus was strongly inhibited by combined warm and humid conditions. These results establish a detailed information on the calling phenology of D. japonicus and P. nigromaculatus 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.

Original languageEnglish
Article number3141
JournalAnimals
Volume15
Issue number21
DOIs
StatePublished - Nov 2025

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • automated call detection
  • Dryophytes japonicus
  • frog calling phenology
  • passive acoustic monitoring
  • Pelophylax nigromaculatus
  • rice paddies
  • weather effects

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