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Dissecting the paradox of stasis in evolutionary biology

illustration of magnifying glass and evolutionary tree

Linking microevolutionary theory with evolutionary change observed across millions of years (macroevolution) remains a challenge for evolutionary biology.

Natural populations often experience strong directional selection and harbour substantial additive genetic variance in most quantitative traits. Accordingly, on short timescales, populations typically show rapid evolutionary responses – just as predicted by theory. Yet, over long timescales the very same quantitative traits often evolve exceedingly slowly: periods of low or no net evolution over millions of years – morphological stasis – is a dominating feature of life on earth according to current interpretations of the fossil record. 

Why do we observe so little evolution on long timescales when we observe so much evolution on shorter timescales?

This “paradox of stasis” remains a fundamental challenge that needs to be solved if we are to obtain a cohesive understanding of phenotypic evolution across timescales.

Researchers studying phenotypic evolution at opposite ends of the timescale continuum have largely adapted different perspectives and tools in their work, hampering the progress towards resolving the paradox of stasis. The ROCKS-PARADOX project will remedy this by merging theory and data across paleontology and evolutionary biology. 

plot of evolutionary data
Evolutionary dynamics on timescales in-between micro- and macroevolution. (A) Evolutionary biology is currently focused on observable change across a few generations (microevolution) and among-species comparative data (macroevolution). Our understanding of trait dynamics during the time interval  in-between micro- and macroevolution (the “Evolutionary black box”) needs to improve to understand how observations on short and long timescales relate to each other. (B) Morphological divergence (N = 70,432) in size traits during the “Evolutionary black box” (log scale, standardized by the dimensionality of the trait, k) calculated from 331 fossil time-series of morphological change within single lineages.

The ambitious and overarching goal of the ROCKS-PARADOX project is to dissect the paradox of stasis by providing a fundamental and deeper understanding of the patterns of evolutionary trait dynamics across long and short timescales, and the processes that govern them.

How will we reach these ambitious goals?

A large database of morphological time series – explicit measures of traits across time within a lineage – spanning generational to million-year timescales will be analyzed using a newly developed statistical modeling framework. The goal is to explore evolutionary dynamics on timescales in-between micro- and macroevolution, a time-scale that is understudied in an evolutionary context.

We will also capitalize on the clonal nature of bryozoans and obtain estimates of key quantitative genetic parameters from samples of fossil and recent bryozoan specimens using machine-learning algorithms. We will estimate temporal broad-sense genetic variances (and covariances) from several independent lineages spanning a few thousands to a few million years and investigate the effects of evolvability and genetic constraints on morphological evolution. 

scanning electron microscope images of bryozoans
Examples of candidate species that might be analyzed using machine-learning approaches to estimate temporal broad-sense genetic variance-covariance matrices. (A) Crepidacantha crinispina; (B) Steginoporella magnifica; (C) Arachnopusia unicornis; (D) Aimulosia marsupium; (E) Antarctothoa tongima; (F) Valdemunitella valdemunita. 


Published Feb. 4, 2022 6:51 PM
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