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
This study investigates the role of winter meteorological indices in predicting Apis mellifera colony losses under various climate change scenarios. This predictive model focuses on environmental temperature variability, emphasizing extreme fluctuations and persistent cold spells, which significantly contribute to overwintering mortality. The findings indicate that rising average temperatures and an increase in high-temperature days have the most profound impact on A. mellifera overwintering mortality. Additionally, an expanded daily temperature range, especially in southern and inland regions, further complicates the bees' ability to regulate their temperature, leading to additional energy expenditures that weaken colony resilience. Furthermore, the projected decrease in low-temperature days by 2100, particularly in southern coastal and central inland areas, presents a challenge for bees, as reduced exposure to cold disrupts their ability to transition into the overwintering phase, leaving colonies unprepared for winter. Moreover, the increase in autumn rainfall days threatens bees by limiting their foraging days and hindering their ability to stockpile resources for winter. This study developed meteorological index-based predictive models to simulate A. mellifera winter mortality rate across the country and applied these models to evaluate the potential impacts of future climate change scenarios on A. mellifera overwintering mortality. The findings emphasize the need for region-specific weather-based forecasting models, as climate impacts on A. mellifera survival vary across different geographic areas. The development of such predictive tools can inform strategic management decisions to mitigate the effects of climate change on pollinator populations and maintain the critical ecosystem services.
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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