Species delimitation 4.0: integrative taxonomy meets artificial intelligence

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.

Bibliographic Details

Main Authors:	Karbstein, Kevin, Kösters, Lara, Hodač, Ladislav, Hofmann, Martin, Hörandl, Elvira, Tomasello, Salvatore, Wagner, Natascha D., Emerson, Brent C., Albach , Dirk C., Scheu, Stefan, Bradler, Sven, de Vries, Jan, Irisarri, Iker, Li, He, Pamela Soltis, Mäder, Patrick, Wäldchen, Jana
Other Authors:	Federal Ministry of Education and Research (Germany)
Format:	artículo biblioteca
Language:	English
Published:	Elsevier BV 2024-06-06
Subjects:	Integrative taxon-omics, machine learning, reticulate evolution, species delimitation, taxonomically complex groups, Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss, taxonomy, artificial intelligence,
Online Access:	http://hdl.handle.net/10261/359747
Tags:	Add Tag No Tags, Be the first to tag this record!