Research Briefs, Science & Technology

The underlying unity of life

Comparing animals of various sizes has historically been a challenge for biologists. From simple observation, an elephant could not be more different than a mouse. Yet, a universal underlying principle concurrently governs them both. 

Scaling laws—derived mathematical models that compare an organism’s key life traits to its body mass—present an intuitive way for scientists to study the relationships between organisms. By comparing characteristics such as metabolism, abundance, growth rate, and mortality between organisms of various sizes, biologists can gain valuable insights about the evolutionary history of life on Earth. 

In a study published last month, researchers found that previous scaling models may have been short-sighted in their conclusions, since they lacked a large enough number of organisms to observe interactions on the universal level. Ian Hatton, a professor in the Institute of Environmental Science and Technology at Universitat Autònoma de Barcelona, was the lead author of the study.

“We present relationships that show how all species, regardless of their particular traits, fall within fairly regular bounds,” Hatton wrote in an email to The McGill Tribune. “This suggests that at some level, these individual traits do not seem to matter, or that all these traits combine to have a neutral net effect on an organism’s energetics and dynamics.”

Following up on decades of scientific theory on the scaling laws that define the unity of life, Hatton began the project when he was a PhD student at McGill. 

Controversially, biologists had assumed that scaling laws between size and metabolism, a key life history trait, are defined by a function with an exponent of about three quarters. In other words, for every three-quarter increase in body mass, a given organism should undergo a proportional increase in their metabolism. 

Hatton and fellow researchers, however, found that this relationship only independently holds between major groups of animals, such as carnivores or herbivores. Across all eukaryotic life—essentially any organism that is not bacteria or archaea—the study found that the exponent is actually closer to one, meaning that when eukaryotic groups are compared, they seem to scale overall with a greater proportional relationship. 

“This [relationship] implies that different mechanisms are generating these different scaling relations within and across groups,” Hatton said. “Growth, on the other hand, exhibits similar three-quarter scaling both within and across groups, suggestive of a more basic mechanism.”

The authors of the study collected data from over 2,500 published meta-analyses. Whereas previous studies with similar questions were restricted to specific groups of animals, Hatton had the unique ability to observe patterns across life on a grand scale.

The researchers’ conclusions could drastically impact the way in which scientists approach questions of ecology and evolution in the future. 

“Once you start dealing with ecology, you are dealing with many species with widely diverse body sizes,” Andy Dobson, a co-author of the study and Professor of Ecology at Princeton University, said in an interview with the Tribune. “Since every species functions at a different rate, we use calculations to simplify these nonlinear interactions.” 

Dobson, who referred to scaling laws as the ‘spine’ on which a significant amount of ecological theory is based, sees the team’s findings as fundamental to how long-term evolutionary relationships will be understood. 

“To me, [our findings] are an affirmation of the strength of evolution,” Dobson said.  “The fact [that] we observed different slopes between different traits tells us that there are general problems [that] evolution had to solve as species evolved.” 

Looking forward, the authors hope that their newly-improved model can help make better qualitative predictions about how ecosystems and communities operate.  

“That, for me, would be the ultimate prize of 21st century science because we only have about 10 years before we run out of natural ecosystems to analyze,” Dobson said.

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