Evidence map›Paper›PMID 36380474›Full record

ArticleSystematic biology2023

Modeling the Evolution of Rates of Continuous Trait Evolution.

Bruce S Martin, Gideon S Bradburd, Luke J Harmon, Marjorie G Weber

Abstract read
In one paragraph

Article in Systematic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Discriminating models of trait evolution.Evolution; international journal of organic evolution · 2026
    Article
  3. The diffused evolutionary dynamics of morphological novelty.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bruce S MartinDepartment of Plant Biology, Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI 48824, USA.ORCID 0000-0003-4412-8965
Gideon S BradburdDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0001-8009-0154
Luke J HarmonDepartment of Biological Sciences, Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID 83843, USA.ORCID 0000-0002-4985-5750
Marjorie G WeberDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.

Funding

Incorporating geography into statistical methods for analysis of population genomic DNAR35GM137919 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Gideon Bradburd · 2020 to 2026
$2.3M
NIGMS NIH HHS R35 GM137919
6 · The paper itself

Abstract

Rates of phenotypic evolution vary markedly across the tree of life, from the accelerated evolution apparent in adaptive radiations to the remarkable evolutionary stasis exhibited by so-called "living fossils." Such rate variation has important consequences for large-scale evolutionary dynamics, generating vast disparities in phenotypic diversity across space, time, and taxa. Despite this, most methods for estimating trait evolution rates assume rates vary deterministically with respect to some variable of interest or change infrequently during a clade's history. These assumptions may cause underfitting of trait evolution models and mislead hypothesis testing. Here, we develop a new trait evolution model that allows rates to vary gradually and stochastically across a clade. Further, we extend this model to accommodate generally decreasing or increasing rates over time, allowing for flexible modeling of "early/late bursts" of trait evolution. We implement a Bayesian method, termed "evolving rates" (evorates for short), to efficiently fit this model to comparative data. Through simulation, we demonstrate that evorates can reliably infer both how and in which lineages trait evolution rates varied during a clade's history. We apply this method to body size evolution in cetaceans, recovering substantial support for an overall slowdown in body size evolution over time with recent bursts among some oceanic dolphins and relative stasis among beaked whales of the genus Mesoplodon. These results unify and expand on previous research, demonstrating the empirical utility of evorates. [cetacea; macroevolution; comparative methods; phenotypic diversity; disparity; early burst; late burst].

Indexed as

Biological EvolutionCetaceaAnimalsBayes TheoremComputer SimulationPhylogeny

Identifiers

PMID36380474
PMCPMC10276627

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.