인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
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 morphological variation in <i>Schizothorax oconnori</i>, <i>Schizothorax waltoni</i>, and their natural hybrids was examined using conventional and image-based analysis approaches. In total, 38 specimens of <i>S. oconnori</i>, 35 of <i>S. waltoni</i>, and 37 natural hybrids were collected from the Shigatse to the Lhasa section of the Yarlung Zangbo River during June and July 2021. A total of 21 morphometric, 4 meristic, and 27 truss variables were employed for the classification of <i>S. oconnori</i>, <i>S. waltoni</i>, and natural hybrids. Principal component analysis (PCA) and factor analysis (FA), as well as discriminant function analysis (DFA) and cluster analysis (CA), were conducted to identify differences based on traditional and truss measurements. Four principal components explained 75.92% of the variation among the morphometric characters, while five principal components accounted for 79.69% of the variation among the truss distances. FA results showed that factor 1 was associated with head shape, and factor 2 was associated with fins based on morphometric characters. Among the truss characters, factor 1 was related to head shape, and factor 2 was related to chest shape. In DFA, morphometric measurements achieved higher accuracy (100%) compared to truss distances (94.55%). The head morphology of hybrids exhibited intermediate traits between <i>S. oconnori</i> and <i>S. waltoni</i>. Both morphometry-based and truss-based clustering indicated that the morphology of natural hybrids leaned toward <i>S. oconnori</i>. In conclusion, the combination of morphometric and truss analysis is beneficial for classifying <i>S. oconnori</i>, <i>S. waltoni</i>, and their natural hybrids. The presence of natural hybrids could be considered an evolutionary response to the differentiation of nutritional and spatial niches in the middle Yarlung Zangbo River.
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.