HomeScienceFossil Record Biases Skew Mammal Trait
SCIENCE

Fossil Record Biases Skew Mammal Trait Evolution Inferences

Simulations of land mammal preservation show biological and taxonomic filters distort trait evolution models while spatial biases do not.

WHAT YOU NEED TO KNOW
  • Simulations modeled a future fossil record of living land mammals across three preservation rates.
  • Biological and taxonomic filters strongly skewed evolutionary inferences for body mass and diet.
  • Spatial sampling filters did not significantly distort the trait evolution analyses.
  • The Galicia Supercomputing Center provided computational infrastructure for the phylogenetic analyses.

Biological and taxonomic sampling biases strongly distort reconstructions of mammal trait evolution, according to a study published Monday in Nature Communications.

A research team led by Graciela Sotelo simulated a future fossil record using living land mammals to measure how much evolutionary pattern survives incomplete preservation. Fossilization is non-uniform and depends on sedimentation rates, species ranges, body sizes, and scientific collection effort. Incomplete records frequently risk skewing analyses of deep-time biodiversity dynamics.

To evaluate these effects, the researchers filtered present-day species by sediment availability, body mass, geographic distribution, and spatial and taxonomic sampling patterns across three preservation rates. The filtered species were systematically pruned from a baseline mammal phylogenetic tree. The team then analyzed body mass and diet evolution using phylogenetic comparative methods.

The study found that biological and taxonomic filters strongly skew evolutionary inferences. Spatial filters, in contrast, do not cause significant distortion in evolutionary models.

The Galicia Supercomputing Center provided the computational resources required for the simulations. Research collaborators included scientists from Universidade de Vigo, University College London, Martin Luther University Halle-Wittenberg, Trinity College Dublin, and Axencia Galega de Innovación.

Funding for the work included grants from the European Research Council, the UK Natural Environment Research Council, the Royal Society, the Spanish Ministerio de Ciencia, Innovación y Universidades, the Agencia Estatal de Investigación, and Xunta de Galicia.

Xentir Media
Xentir Media NewsroomSource-backed AI and technology coverage, drafted by Xentir's automated editorial system under fixed human-set rules. See our editorial policy and AI usage policy.
J
Jomon · Founder & EditorFounder and editor of Xentir Media. Sets the editorial rules the newsroom system runs under, and is accountable for its corrections. About Jomon · [email protected]
The Xentir Brief
The developments worth knowing — one useful email.
Get the Brief →