Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data

Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data

Abstract The diversity of biological and ecological characteristics of organisms, and the underlying genetic patterns and processes of speciation, makes the development of universally applicable genetic species delimitation methods challenging. Many approaches, like those incorporating the multispec...

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Bibliographic Details
Main Authors: Shahan Derkarabetian, James Starrett, Marshal Hedin
Format: Article
Language:English
Published: BMC 2022-02-01
Series:Frontiers in Zoology
Subjects:
Integrative taxonomy
Multispecies coalescent
RADSeq
Short-range endemism
Southern Appalachians
Supervised machine learning
Online Access:https://doi.org/10.1186/s12983-022-00453-0

Internet

https://doi.org/10.1186/s12983-022-00453-0

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