New mathematical model to characterize long-term evolutionary scenarios

Species under a taxonomic umbrella often go through adaptation or face extinction when they encounter a division in the path, and the road that is taken has been hard to track.

Now, in a recently published paper, two researchers have debated that traditionally used methods for rebuilding these paths are considered flawed.

According to Stilianos Louca, the lead author of the study and a biologist from the University of Oregon, while paleontological proof gives an understanding of how and why the biodiversity patterns had altered over geological time, fossil finds for several types of organisms are very limited to say anything.

The study was published online on April 15^th, 2020, ahead of print in the Nature journal.

Louca also observed that an alternative method is available that depends on utilizing perceptible changes in the genetic composition of an organism but the signal in such a data can be ambiguous.

Our finding casts serious doubts over literally thousands of studies that use phylogenetic trees of extant data to reconstruct the diversification history of taxa, especially for those taxa where fossils are rare, or that found correlations between environmental factors such as changing global temperatures and species extinction rates.”

Stilianos Louca, Study Lead Author and Biologist, University of Oregon

Louca is also a member of the Institute of Ecology and Evolution at the University of Oregon.

In the latest study, Louca along with Matthew W. Pennell, an evolutionary biologist at Vancouver-based University of British Columbia, also provided a way forward—that is, a mathematical model that offers alternative variables to define long-term evolutionary situations that can be precisely detected from the phylogenetic data.

I have been working with these traditional types of models for a decade now. I am one of the lead developers of a popular software package for estimating diversification rates from phylogenetic trees. And, as such, I thought I had a really good sense of how these models worked. I was wrong.”

Matthew W. Pennell, Evolutionary Biologist, University of British Columbia

In their study, the scientists observed that traditionally used techniques employ variants of a mathematical birth-death procedure to extract evolutionary data from organisms that are still living.

But such methods cannot potentially extract data about speciation as well as extinction rates, particularly for a majority of taxonomy, like bacteria, on which no fossil record is available.

In the paleontological method, the numbers of species that have disappeared and appeared in different intervals are estimated on the basis of the identified fossils and their predicted maximum and minimum ages.

The phylogenetic method extracts data from evolutionary associations between the prevalent species, utilizing predominantly genetic data, and this data is structured in phylogenetic trees called timetrees. This is typically carried out by identifying an extinction/speciation situation that most probably would create a specified phylogenetic tree.

While an impressive suite of computational methods has been developed over the past decades for extracting whatever information is left, until now we lacked a good understanding of exactly what information is left in these trees, and what information is forever lost.”

Stilianos Louca, Study Lead Author and Biologist, University of Oregon

The mathematically driven method developed by Louca and Pennell accurately clarifies the type of data that can be obtained from the extant timetrees under the common birth-death model.

The scientists also developed variables that can be identified and easily understood. These variables include all the available data about the previous diversification dynamics and how they can be assessed.

“We suggest that measuring and modeling these identifiable variables offers a more robust way to study historical diversification dynamics. Our findings also make clear that paleontological data will continue to be crucial for answering some macroevolutionary questions,” the researchers wrote in their paper.

According to Pennel, “The future depends on synthesizing information from datasets of both molecules and fossils.”

The scientists further reiterated that their findings do not annul the concept of evolution itself, they just limit the type of information that can be derived from genetic data to rebuild the path of evolution.