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 Aim To use a long‐term collection of bulk plankton samples to test the capacity of DNA metabarcoding to characterize the spatial and seasonal patterns found within a range of zooplankton communities, and investigate links with concurrent abiotic data collected as part of Australia's Integrated Marine Observing System (IMOS) programme. Location Samples were sourced seasonally for 3 years from nine Pan‐Australian marine sites (n = 90). Methods Here, we apply a multi‐assay metabarcoding approach to environmental DNA extracted from bulk plankton samples. Six assays (targeting 16SrRNA and COI genes) were used to target, amplify and sequence the zooplankton diversity found within each sample. The data generated from each assay were filtered and clustered into OTUs prior to analysis. Abiotic IMOS data collected contemporaneously enabled us to explore the physical and chemical drivers of community composition. Results From over 25 million sequences, we identified in excess of 500 distinct taxa and detected clear spatial differences. We found that site and sea surface temperature are the most consistent predictors of differences between zooplankton communities. We detected endangered and invasive species such as the bryozoan Membranipora membranacea and the mollusc Maoricolpus roseus , and seasonal occurrences of species such as humpback whales ( Megaptera novaeangliae ). We also estimated the number of samples required to detect any significant seasonal changes. For OTU richness, this was found to be assay dependent and for OTU assemblage, a minimum of nine samples per season would be required. Main Conclusion Our results demonstrate the ability of DNA to capture and map zooplankton community changes in response to seasonal and spatial stressors and provide vital evidence to environmental stakeholders. We confirm that a metabarcoding method offers a practical opportunity for an ecosystem‐wide approach to long‐term biomonitoring and understanding marine biomes where morphological analysis is not feasible.
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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