Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/490128

Linking micro and macroevolution in the presence of migration

Duchen, P.·Hautphenne, S.·Lehmann, L.·Salamin, N.
View original source ↗Export metadata ↓

Abstract

1. The process of speciation is of key importance in evolutionary biology because it shapes macroevolutionary patterns. This process starts at the microevolutionary level, for instance, when two subpopulations evolve towards different phenotypic optima. The speed at which these optima are reached is controlled by the degree of stabilising selection, which pushes a mean trait towards an optimum within subpopulations, and ongoing migration that pulls the mean phenotype away from that optimum. Traditionally, macro phenotypic evolution with selection has been modelled by Ornstein-Uhlenbeck (OU) processes, but these models have ignored the role of migration within species.\n\n2. Here, our goal is to reconcile the processes of micro and macroevolution by modelling migration during speciation. More precisely, we introduce an OU model where migration happens between two subpopulations within a branch of a phylogeny and this migration decreases over time as it happens during speciation. We then use this model to study the evolution of trait means along a phylogeny, as well as the way phenotypic disparity between species changes with successive epochs.\n\n3. We show that ignoring the effect of migration in sampled time-series data leads to a significant underestimation of the selective forces acting upon it. We also show that migration decreases the expected phenotypic disparity between species and we show the effect of migration in the particular case of niche filling. We further introduce a method to jointly estimate selection and migration from time-series data.\n\n4. Our model extends standard results of interactions selection-migration in a microevolutionary time frame across multiple speciation events at a macroevolutionary scale. Our results further proof that not accounting for gene flow has important consequences in inferences at both the micro and macroevolutionary scale.

Source connections

Explore related subjects

evolutionary biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Duchen, P., Hautphenne, S., Lehmann, L., Salamin, N.. 2018-12-09. Linking micro and macroevolution in the presence of migration. https://doi.org/10.1101/490128

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Ocean current models predict spatial structure for coastal biodiversity

Genomic diversity provides the raw material through which all evolutionary processes occur. Accurately describing how environmental features affect patterns of diversity shows promise in predicting the resilience of populations and entire communities to dynamic environments and novel stressors. Identifying the contribution of purely neutral responses to environmental effects can be difficult, especially across large spatial ranges with many covarying environmental features. Using an individual-based model of larvae carried by ocean currents, we predict patterns of neutral genomic diversity in a passively dispersed coastal species, suggesting large geographic regions of relative homogeneity with ancestry determined by the nearest "upstream" population with limited larval input. The genomic identity that dominates each region sharply transitions at the next such interruption, generating hierarchical structure and violating assumptions of isolation-by-distance. We call these upstream populations "lineage source regions" (LSRs), and we find strong concordance between LSR model predictions and an empirical population genomic survey of a keystone salt marsh mussel (Geukensia demissa). We quantitatively validate model performance and goodness-of-fit, updating baseline predictions of genomic diversity patterns from the classic isolation-by-distance model to this LSR framework. This spatially explicit coastal ancestry model has potential for generalization across passive dispersing species.

evolutionary biology↗
bioRxiv2026

TaxaAudit: A statistical model of consensus in phylogenetics identifies non-monophyletic taxa

Interpreting variation in genes and traits across species requires understanding their evolutionary relationships. Taxonomic hierarchies provide a practical approximation of the tree of life, with the NCBI taxonomy linking this framework directly to public sequence data. Some named groups, however, are not evolutionary clades, and recognizing these exceptions requires knowledge scattered across the phylogenetics literature. Here we introduce TaxaAudit, a statistical model that identifies taxonomic groups whose monophyly is repeatedly contradicted by published phylogenies. The model accounts for background taxonomic conflict and the ability of each study's species sampling to expose non-monophyly. Applied to 5,865 molecular phylogenies from TimeTree, TaxaAudit flagged 516 NCBI taxa at family rank and below for significant recurrent contradiction of monophyly. Excluding these taxa's monophyly requirements improved the taxonomy's agreement with independent phylogenomic reference trees and phylogenies withheld from discovery. Flagged taxa were also 3.61 times as likely as matched controls to have their monophyly challenged in publications outside the discovery set. In tree-inference experiments, excluding these monophyly constraints improved agreement with reference phylogenies relative to enforcing the unmodified taxonomy. By identifying groups whose monophyly should not be assumed, TaxaAudit lets researchers draw on published phylogenetic knowledge without reviewing the specialist literature for every taxon. This supports broader use of the NCBI taxonomy as an evolutionary framework for biological comparisons.

evolutionary biology↗
bioRxiv2026

Shared landscape, divergent genomes: Comparative population genomics of co-occurring flora in an isolated Australian mountain range

Understanding how landscape heterogeneity shapes genomic variation is key to conserving biodiversity and evolutionary potential. Yet conservation genomics is typically conducted at the single species level, limiting our ability to identify shared genomic patterns or understand how co-occurring taxa differ in their response to common environmental gradients. We assessed spatial patterns of genomic variation and their associations with geographic and environmental features among populations of nine co-existing plant species with contrasting life-histories and ecological traits across Gariwerd, a threatened biodiversity hotspot in south-eastern Australia. All species exhibited weak overall genetic structure, although the magnitude and spatial distribution of differentiation varied among species. Despite this variation, broadly consistent spatial trends were apparent, with higher genomic divergence largely concentrated in central zones and higher genomic diversity localised in southern regions of the landscape. Significant associations between genetic differentiation and geographic distance were observed in three species, while another species showed associations with environmental distance. These findings demonstrate that coexisting species can show overlapping spatial patterns in genomic variation while differing markedly in their associations with geographic and environmental variation across the same landscape. This comparative approach provides a basis for spatial prioritisation and conservation planning, while highlighting the complex eco-evolutionary processes operating across heterogeneous landscapes.

evolutionary biology↗