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.
피인용 0
초록·키워드
The yellow-legged hornet(Vespa velutina nigrithorax) has emerged as a critical invasive predator threatening apicultural ecosystems across East Asia and Europe. Understanding how meteorological conditions drive hornet activity patterns and how climate change will amplify invasion risks is essential for developing effective management strategies. This study conducted comprehensive field observations and trap monitoring from 2018 to 2024 in South Korea to develop season-specific regression models based on correlations between meteorological variables and hornet abundance. Solar radiation exhibited the strongest correlation with hornet activity(r= 0.745), followed by precipitation (r= -0.714) and temperature (r= 0.669). Season-specific regression models integrating temperature, precipitation, and solar radiation indices achieved exceptional predictive power, with R² values ranging from 0.711 in spring to 0.908 in autumn, and validation accuracies of 78-85% using independent 2023-2024 data. Application of validated models to IPCC SSP 5-8.5 climate projections revealed complex seasonal restructuring, with spring and autumn activity increasing by 31% and 29% respectively by 2100, while summer activity declined 24% due to extreme heat stress. Spatial distribution modeling predicted that severe-risk areas will expand to 65% of South Korea by the century’s end, with northward range expansion rates of 50-70 km per decade. Apis mellifera apiaries exhibited 5.4-fold greater vulnerability to climate-driven hornet increases than Apis cerana, reflecting the profound consequences of coevolutionary history. These findings demonstrate that current management strategies focused on spring and summer control are inadequate for addressing projected autumn population explosions, necessitating a transition to proactive, forecast-based integrated pest management systems.
본문·목차
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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