The Evidence for New Species Across the Tree of Life: Morphology Still Rules the Largest Kingdoms
DOI:
https://doi.org/10.18061/bssb.v4i1.10466Keywords:
biodiversity, cryptic species, species delimitation, taxonomyAbstract
Over the past ~20 years, several forces have converged to potentially create a seismic shift in how new species are described. These forces include: (1) pleas for DNA-based taxonomy, (2) large-scale genomic datasets for species delimitation, (3) new statistical methods for molecular species delimitation, (4) the discovery of hundreds of cryptic species hiding within morphology-based species, (5) the possibility that most morphologically distinct species are already described, and (6) the putative decline of morphology-based taxonomy. But has a major shift towards molecular-based taxonomy actually happened? Here, we examined newly described species from 9 major groups across the Tree of Life and the evidence used to delimit them. We found five major results. First, in the largest groups, most new species were still described based on morphological data alone, including arthropods, mollusks, and plants (groups collectively including ~90% of all known species). Second, in other groups, most new species were described based on both molecular and morphological evidence, including chordates, fungi, bacteria, and archaeans. Third, species described based only on molecular data remain rare. Fourth, within animals, the majority of species descriptions that incorporated molecular data included only mitochondrial sequences. Fifth, molecular data were typically used to build a tree and generate genetic distances, rather than being used for statistical delimitation methods. Our results suggest that many new developments in species delimitation are underutilized by taxonomists (e.g. genomics), likely because these developments do not offer the fastest way to describe new species before they become extinct. Our results also suggest that many morphologically distinct species (and cryptic species) remain to be described.
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Copyright (c) 2025 Adam J. Ziegler, Xin Li, John Wiens

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