They discover how ecosystems become unstable

Ecosystems are very complex systems in which even relatively small changes can lead to large-scale consequences. However, simply knowing two variables can help us predict the health of an ecosystem. These, according to scientists at the Massachusetts Institute of Technology, are the number of species and the strength of their interactions.

MIT researchers, who specialize in examining interspecific interactions between microbes in controlled laboratory experiments, set out to calculate what conditions were needed for communities to transition from one state to another during three stages of different development.

This approach produced a “phase diagram”, which resembles the diagrams used by physicists to plot the conditions necessary for water to change from solid to liquid and then to gas.

“The amazing and wonderful thing about a phase diagram is that it summarizes a lot of information in a very simple way. We can draw a limit that predicts the loss of stability and the appearance of fluctuations in a population”, explains Jeff Gore, professor of physics at MIT who led the project, whose results have just been published in a study.

“In order to see phase transitions in the lab, you really need to have experimental communities where you can turn the knobs yourself and make quantitative measurements of what’s going on,” he adds.

Population behaviors

Gore and his colleagues previously demonstrated how competitive and cooperative behaviors affect populations, which helped them identify warning signs of population collapse in larger ecosystems. In the process, Gore decided to test some of the predictions theoretical physicists have made about the dynamics of large, complex ecosystems.

“One of these predictions was that ecosystems go through phases of varying stability depending on the number of species in the community and the degree of interaction between species. In this framework, the type of interaction (predatory, competitive or cooperative) doesn’t matter. Only the strength of the interaction counts,” the scientists explain.

To test this prediction, Gore and his colleagues created bacterial communities of up to 48 species. In each, the researchers controlled the number of species by forming different communities with different sets of species.

They then enhanced species interactions by increasing the amount of food available, allowing populations to increase while causing environmental changes such as increased acidification. The tests confirmed the prediction that, initially, each community would exist in a phase of “complete and stable existence”, in which all species would co-exist with little or no interference.

Achieving ecosystem stability

However, when the number of species or their interactions have increased, communities have entered a second phase called “stable partial coexistence”, in which populations remain stable while some species disappear. “The community in general remained in a stable state, which means that the population returns to a state of equilibrium after the extinction of certain species,” explain the scientists.

Once the number of species or the strength of their interactions increased further, communities entered a third phase, which was marked by increased instability with much more dramatic population fluctuations. However, even when some species became extinct, these ecosystems still had a higher total number of species that survived.

From this data, we were able to draw a phase diagram that describes how ecosystems change based on just two factors: the number of species and the strength of interactions between them.

“It’s analogous to how physicists can describe changes in the behavior of water as a function of just two conditions: temperature and pressure. Detailed knowledge of the exact speed and position of each water molecule is not necessary,” they add.

This understanding of ecosystems is important because accurate predictions about them can now be made based on a few known facts.

“If we cannot access all the mechanisms and biological parameters of a complex ecosystem, we show that its diversity and its dynamics can be emergent phenomena predictable from a few aggregated properties of the ecological community: size of the groups of species and species interaction statistics. says Jiliang Hu, an MIT graduate student who played a key role in the project.

an important tool

A phase diagram like this, adds Gore, can help ecologists make predictions about what might happen in natural ecosystems like forests, even with little information available, because all they will need to know is the number of resident species and what they interact so closely with. .

“We can make predictions or statements about what the community is going to do, even in the absence of detailed knowledge of what is happening,” says Gore. “We don’t even know which species help or hurt which other species. These predictions are based solely on the statistical distribution of interactions within this complex community.”

Additional work at MIT is currently examining the flow of new species between isolated populations, such as those similar to island ecosystems, that affect the dynamics of those populations. This could help shed light on how islands can maintain species diversity even in the face of extinction.

By Daniel T. Cross. Articles in English

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