Spatial impacts on gene flow may hinder linking phylogeographic data to macroevolutionary patterns

Biogeography relies on estimates of phylogeny and gene flow to test hypotheses. Established theory posits: (i) gene flow varies non-randomly with respect to geography and (ii) gene flow can mislead phylogenetic inference. These findings, often viewed in isolation, together suggest that spatial impacts on gene flow could bias biogeographic inference. For example, whenever a 'peripheral' population is isolated and inferred as sister to a 'core' clade of adjacent populations that exchange migrants, it might reflect elevated gene flow of 'core' populations rather than macroevolutionary processes (e.g. direction of colonization). Given this ubiquitous but often unacknowledged biogeographic setting, it remains unknown how spatial influences on gene flow impact metrics used to assess biogeographic hypotheses (e.g. branch length or monophyly). We simulate gene flow that varies non-randomly regarding geography and found that relatively low levels of gene flow lead to monophyly of adjacent populations, with longer branches for peripheral populations, regardless of true divergence history. We highlight an empirical example wherein antbirds (Thamnophilidae) are young in Amazonia, but older at Amazonia's periphery. Although it is unclear if the simulated bias applies to antbirds, our results suggest a distinguishability problem for any nodes stemming from radiations in geographically heterogeneous environments.

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Publication Details

Journal
Proceedings of the Royal Society B Biological Sciences
Published
2026-04-22
DOI
https://doi.org/10.1098/rspb.2025.2825
Primary Topic
Genetic diversity and population structure
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatial impacts on gene flow may hinder linking phylogeographic data to macroevolutionary patterns

Ethan F. Gyllenhaal, Lukas J. Musher
Proceedings of the Royal Society B Biological Sciences
Genetic diversity and population structure
article

Spatial impacts on gene flow may hinder linking phylogeographic data to macroevolutionary patterns

Ethan F. Gyllenhaal, Lukas J. Musher
article en

Abstract

Biogeography relies on estimates of phylogeny and gene flow to test hypotheses. Established theory posits: (i) gene flow varies non-randomly with respect to geography and (ii) gene flow can mislead phylogenetic inference. These findings, often viewed in isolation, together suggest that spatial impacts on gene flow could bias biogeographic inference. For example, whenever a 'peripheral' population is isolated and inferred as sister to a 'core' clade of adjacent populations that exchange migrants, it might reflect elevated gene flow of 'core' populations rather than macroevolutionary processes (e.g. direction of colonization). Given this ubiquitous but often unacknowledged biogeographic setting, it remains unknown how spatial influences on gene flow impact metrics used to assess biogeographic hypotheses (e.g. branch length or monophyly). We simulate gene flow that varies non-randomly regarding geography and found that relatively low levels of gene flow lead to monophyly of adjacent populations, with longer branches for peripheral populations, regardless of true divergence history. We highlight an empirical example wherein antbirds (Thamnophilidae) are young in Amazonia, but older at Amazonia's periphery. Although it is unclear if the simulated bias applies to antbirds, our results suggest a distinguishability problem for any nodes stemming from radiations in geographically heterogeneous environments.

Proceedings of the Royal Society B Biological SciencesVol. 293(2069)
Texas Tech University (US), Cornell University (US), Drexel University (US)
Division of Biological Infrastructure
Reduced inequalities
Openalex Percentile: Top 7%
Genetic diversity and population structure
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Spatial impacts on gene flow may hinder linking phylogeographic data to macroevolutionary patterns — Ethan F. Gyllenhaal, Lukas J. Musher · Proceedings of the Royal Society B Biological Sciences (2026) | TGRS Research Map | TGRS