Lost in the woods: shifting habitats can lead phylogeography astray

Continuous phylogeographic inference is a popular method to estimate parameters of the dispersal process and to reconstruct the spatial location of ancestors of extant populations from samples viral of genome sequences. However, these models typically ignore that replication and population growth are tightly coupled to spatial location: populations expand in areas with abundant susceptible hosts and contract in regions with limited resources. Here, I first investigate the sampling consistency of popular summary statistics of dispersal and show that estimators of 'lineage velocities' are ill-defined. I then use simulations to investigate how local density regulation or shifting habitats perturb phylogeographic inference in continuous space and show that these can result in biassed and overconfident estimates of ancestral locations and dispersal parameters. These, sometimes dramatic, distortions depend in complicated ways on the past dynamics of habitats and underlying population dynamics and dispersal processes. Consequently, the validity of continuous phylogeographic inferences is hard to assess and confidence can be much lower than suggested by the inferred posterior distributions, in particular when involving poorly sampled locations or extrapolations far into the past.

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Publication Details

Journal
Virus Evolution
Published
2025-01-01
DOI
https://doi.org/10.1093/ve/veaf040
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
1.84
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article

Lost in the woods: shifting habitats can lead phylogeography astray

Richard A. Neher
1 citations
Virus Evolution
Species Distribution and Climate Change
1.84
article

Lost in the woods: shifting habitats can lead phylogeography astray

Richard A. Neher
article en
1 citations

Abstract

Continuous phylogeographic inference is a popular method to estimate parameters of the dispersal process and to reconstruct the spatial location of ancestors of extant populations from samples viral of genome sequences. However, these models typically ignore that replication and population growth are tightly coupled to spatial location: populations expand in areas with abundant susceptible hosts and contract in regions with limited resources. Here, I first investigate the sampling consistency of popular summary statistics of dispersal and show that estimators of 'lineage velocities' are ill-defined. I then use simulations to investigate how local density regulation or shifting habitats perturb phylogeographic inference in continuous space and show that these can result in biassed and overconfident estimates of ancestral locations and dispersal parameters. These, sometimes dramatic, distortions depend in complicated ways on the past dynamics of habitats and underlying population dynamics and dispersal processes. Consequently, the validity of continuous phylogeographic inferences is hard to assess and confidence can be much lower than suggested by the inferred posterior distributions, in particular when involving poorly sampled locations or extrapolations far into the past.

Virus EvolutionVol. 11(1)
SIB Swiss Institute of Bioinformatics (CH), University of Basel (CH)
Openalex Percentile: Top 15%
Species Distribution and Climate Change
1.84
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