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
Abstract Parasite species frequently co‐occur more or less than expected by chance. These nonrandom co‐occurrence patterns can be driven by pre‐ or postinfection priority effects: parasites are more or less likely to attempt infection in a host already infected by another parasite species or may have higher or lower establishment and survival in hosts already infected by another parasite species. How these two types of priority effects differentially affect parasite distributions at the host population level remains unexplored. Using a probabilistic state transition diagram parameterized with field data and analyzed with two simulation methods, I show that the two types of priority effects lead to contrasting outcomes at the host population level. As preinfection priority effects transition from facilitation to inhibition, uninfected hosts decrease by up to 39%, and hosts infected by both parasites decrease by up to 84%, with concomitant increases in single infections by either parasite species. In contrast, as postinfection priority effects transition from facilitation to inhibition, the proportion of uninfected hosts remains unchanged, but the proportion of hosts infected by both parasites decreases by up to 89%, with increases in hosts singly infected by the first‐arriving parasite. Interactions between parasites at the within‐host level and the specific nature of those interactions alter infection patterns at the host population level.
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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