Integrating Genomics, Collections, and Community Science to Delimit Species Clarifies the Taxonomy of a Variable Monitor Lizard (Varanus tristis)
Date
2025
Authors
Pavón-Vázquez, C.J.
Fitch, A.J.
Doughty, P.
Donnellan, S.C.
Keogh, J.S.
Editors
Bell, R.
Advisors
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Journal article
Citation
Systematic Biology, 2025; 75(3):1-25
Statement of Responsibility
Carlos J. Pavón-Vázquez, Alison J. Fitch, Paul Doughty, Stephen C. Donnellan, J. Scott Keogh
Conference Name
Abstract
The accurate characterization of species diversity is a vital prerequisite for ecological and evolutionary research, as well as conservation. Thus, it is necessary to generate robust hypotheses of species limits based on the inference of evolutionary processes. Integrative species delimitation, the inference of species limits based on multiple sources of evidence, can provide unique insight into species diversity and the processes behind it. Here, we show how community observations can be integrated with standard molecular and phenotypic datasets under an integrative framework to identify the processes generating genetic and phenotypic variation. We implement this approach in Varanus tristis, a widespread and variable complex of Australian monitor lizards. Using genomic, phenotypic (linear and geometric morphometrics, coloration), spatial, and environmental data, we show that disparity in this complex is inconsistent with intraspecific variation and instead suggests that speciation has occurred. Based on our results, we provide an updated taxonomy for this complex and identify the processes that may have been responsible for the geographic sorting of variation. Our workflow provides a guideline for the integrative analysis of several types of data to identify the occurrence and causes of speciation. Furthermore, our study highlights the benefits and caveats associated with community science and machine learning-two tools used here-in taxonomic research.
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Dissertation Note
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OnlinePubl
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© The Author(s) 2025. Published by Oxford University Press on behalf of the Society of Systematic Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site-for further information please contact journals.permissions@oup.com.