分类学(生物学)
基因组学
生物多样性
数据科学
物种描述
生物
人工智能
计算机科学
进化生物学
生态学
基因组
生物化学
基因
作者
Kevin Karbstein,Lara M. Kösters,Ladislav Hodač,Martin Hofmann,Elvira Hörandl,Salvatore Tomasello,Natascha D. Wagner,Brent C. Emerson,Dirk C. Albach,Stefan Scheu,Sven Bradler,Jan de Vries,Iker Irisarri,Li He,Pamela S. Soltis,Patrick Mäder,Jana Wäldchen
标识
DOI:10.1016/j.tree.2023.11.002
摘要
Although species are central units for biological research, recent findings in genomics are raising awareness that what we call species can be ill-founded entities due to solely morphology-based, regional species descriptions. This particularly applies to groups characterized by intricate evolutionary processes such as hybridization, polyploidy, or asexuality. Here, challenges of current integrative taxonomy (genetics/genomics + morphology + ecology, etc.) become apparent: different favored species concepts, lack of universal characters/markers, missing appropriate analytical tools for intricate evolutionary processes, and highly subjective ranking and fusion of datasets. Now, integrative taxonomy combined with artificial intelligence under a unified species concept can enable automated feature learning and data integration, and thus reduce subjectivity in species delimitation. This approach will likely accelerate revising and unraveling eukaryotic biodiversity.
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