How to understand biodiversity in natural ecosystems and their complex dynamic behavior? Jiliang Hu, an independent postdoctoral researcher at MIT, and his supervisor, Jeff Gore, have found a way to solve ecological problems with physics research ideas. Through experiments and model verification, they proved that only two parameters are required to predict the dynamic phase and phase transition presented in the ecological community. Recently, the results of this research were published in the journal Science.
The first author of the paper, Hu Jingliang, an independent postdoctoral researcher at the Massachusetts Institute of Technology, source MIT
In the paper, titled “Emergent phases of ecological diversity and dynamics mapped in microcosms,” Hu and Jeff Gore instead of the scientific logic of traditional biologists constantly asking questions about the details of the mechanisms behind phenomena, instead devotes themselves to “describing chaotic and random ecosystems with a concise and beautiful framework.” Combining theory and microbial community experiments, they proved that only two coarse-grained parameters of “species number” and “average interspecific interaction intensity” need to be known to predict the kinetic phases and phase transitions emerging in ecological communities.
“Thermodynamics describes the behavior of a large number of gas molecules and requires only a few emergent state variables, such as temperature and pressure, without knowing the coordinates and velocity of each molecule.” Along these lines, Jeff Gore et al. found similar coarse-grained descriptions in ecological networks. For the first time, the method proposes a relatively uniform framework for complex ecosystems – it no longer relies on any biological detail, like a concise formula with universal applicability that can be used to describe any ecological community from the rainforest to the small intestinal flora.
Predicting complex ecosystems on just two variables is a groundbreaking and innovative experiment. Hu Zhiliang said that after the paper was submitted, there were more than 50 pages of review comments returned, but the three reviewers gave high evaluations, “I have the bottom in my heart, and I feel that the significance of my work has been recognized.”
The paper also received positive reviews after its publication, with physicist Fernanda Pinheiro describing the work as “a beautiful piece of work.”
The relationship between biodiversity and community stability has been debated in the field of ecology, and the main reason for this controversy is the complex dynamics exhibited by natural ecosystems, which may be caused both by random shocks of the environment and by the eigenproperties of ecological networks (complex interspecies interaction networks).
In this regard, on the one hand, some early theorists proposed that the increase in the complexity of ecological networks will inevitably lead to their instability; On the other hand, scientists have also demonstrated that ecosystems can maintain species diversity over time.
The work of Hu and others proposes an effective framework that brings together the two most well-known theories of theoretical ecology.
“Our experimental system effectively controls ambient noise, proving the conclusion of theoretical predictions: only two coarse-grained parameters – the number of species and the intensity of interspecies interactions – can effectively describe the dynamic behavior of complex ecosystems.” Hu said the predictions and theoretical frameworks they presented in the study are robust to biological detail, so the phase maps of biodiversity and community dynamics they propose “could be widely applicable in more ecosystems.”
He also said that future work should try to explore whether the proposed kinetic phase map is universally applicable to complex ecological communities composed of various life forms at various space-time scales.
“This work may be of interest to scientists in different fields.” First, the stability and diversity of microbial communities are critical to the function and health of different microbiomes, such as the intestinal flora and the soil flora. Hu Jingliang said that several types of ecodynamic models they use have been widely used in the study of many other ecosystems, so the ecodynamic phase diagram proposed here may also be universal for other ecological communities.
“We propose a theoretical framework inspired by statistical physics that extracts small amounts of coarse-grained control variables from high-dimensional ecological networks, and this approach could be generalized to the study of other complex systems.” Hu said.
It is understood that Hu Jiliang received his bachelor’s degree from Qian Xuesen class at Tsinghua University, received his doctorate under the supervision of Professor Jeff Gore of the Department of Physics of MIT, and is currently an independent postdoctoral researcher at MIT Physics of Living System. (Source: China Science Daily Zhao Guangli)
Related Paper Information:https://doi.org/10.1126/science.abm7841