A Taxonomist’s Guide to the Genealogical Divergence Index

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ID: 332451
2026
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Abstract
Abstract Speciation proceeds independently across lineages, generating varying levels of genetic divergence that are difficult to translate into discrete species boundaries. Widely used empirical heuristics such as genetic distance thresholds, DNA barcoding gaps, and measures of gene tree exclusivity provide practical tools for species delimitation, but their reliance on arbitrary cutoffs can strongly bias the number of delimited species. Here, we evaluate a coalescent-based alternative, the genealogical divergence index (gdi), which uses Bayesian estimates of divergence times, population sizes, and migration rates to explicitly quantify genealogical independence along the speciation continuum. We explore the utility of gdi by applying it to genomic data from 76 species and 113 populations of North American lizards. We test whether gdi reliably distinguishes populations from recognized species, if a biologically meaningful tipping point exists, and how empirical patterns align with commonly used species delimitation thresholds. We show that while gdi captures key features of the population-species continuum, it inconsistently separates populations from species. At the recommended species-level threshold of gdi = 0.7, the predicted probability of species status is approximately 0.5 in our test data. Among the population parameters examined, unscaled divergence (measured in substitutions per site) is the strongest predictor of species status, followed by migration rate. By conducting a quantitative review of the literature, we show that the pattern of continuous gdi variation across populations and species holds true in a more diverse set of taxa. Our results highlight the importance of considering gdi as part of a multi-evidence and reference-based framework for species delimitation, rather than a binary decision metric.
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Authors Adam D. Leaché, Sonal Singhal, Matthew K. Fujita, Hayden R. Davis, Julio A. Lemos‐Espinal, Andrew Gottscho, Jonathan Q. Richmond, Christopher Blair, Paschalia Kapli, Ziheng Yang
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Journal systematic biology
Year 2026
DOI
10.1093/sysbio/syag077
URL
https://doi.org/10.1093/sysbio/syag077
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