인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The "dear enemy effect," wherein territorial animals exhibit reduced aggression toward familiar neighbors compared to strangers, is a widespread strategy to minimize energy expenditure on territory defense. However, whether and how this behavioral capacity varies across with differing vocal complexity remains poorly unclear. We investigated neighbor-stranger discrimination (NSD) in two sympatric tit species that exhibit a stark contrast in song repertoire complexity: coal tits (<i>Periparus ater</i>) and green-backed tits (<i>Parus monticolus</i>). Acoustic analysis revealed that coal tits possessed a large population-level song-type diversity (19 distinct song types) and, crucially, a significantly larger individual syllable repertoire size compared to green-backed tits (5 song types). Playback experiments showed that coal tits exhibited a robust "dear enemy" effect, responding to strangers with significantly closer approach distance and higher flight frequencies near the nest. In contrast, green-backed tits showed uniformly low and undifferentiated responses toward both playbacks of familiar neighbors and strangers, indicating a lack of discrimination. This interspecific divergence was underpinned differences in individual repertoire size and population-level acoustic diversity, with green-backed tits exhibiting higher vocal similarity among individuals. These results demonstrate that the capacity for fine-scale NSD is not universal and suggest that constrained vocal systems-characterized by minimal individual repertoires and high acoustic similarity among individuals-may limit the potential for vocal individual recognition, thereby favoring alternative territorial strategies.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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