[[science.abm7841_sm.pdf]] > With only a little information, researchers can predict the circumstances under which an ecosystem will be stable or unstable. > MIT researchers studied ecosystems of up to 48 species of bacteria and discovered how the communities shift from stable to unstable states. > The behavior of these ecosystems can be predicted based on just two pieces of information: > > 1. the number of species in the community and > 2. how strongly they interact with each other. > They defined three states of ecological communities, and calculated the conditions necessary for them to move from one state to another. > Phase 1: Initially, each community existed in a phase called “stable full existence,” in which all species coexist without interfering with each other. > Phase 2: As either the number of species or interactions between them were increased, the communities entered a second phase, known as “stable partial coexistence.” In this phase, populations remain stable, but some species became extinct. The overall community remained in a stable state, meaning that the population returns to a state of equilibrium after some species go extinct. > Phase 3: Finally, as the number of species or strength of interactions increased even further, the communities entered a third phase, which featured more dramatic fluctuations in population. The ecosystems became unstable, meaning that the populations persistently fluctuate over time. > While some extinctions occurred, these ecosystems tended to have a larger overall fraction of surviving species. > “While we cannot access all biological mechanisms and parameters in a complex ecosystem, we demonstrate that its diversity and dynamics may be emergent phenomena that can be predicted from just a few aggregate properties of the ecological community: ==species pool size and statistics of interspecies interactions==,” Hu says. > In both models, increasing the number of species and the strength of their interactions, whether direct or mediated through an abiotic factor, will typically lead to extinctions before it leads to loss of stability. This results in a phase of partial coexistence preceding a phase of instability, no matter whether species diversity and extinctions are necessary (as in the random LV model) or not (as in the pH-based model) for the mechanism that drives fluctuations. We propose that this ordering,which is robust in many-species models but need not be in few-species models, can be an indicator of emergent collective behavior. - Paper: https://www.science.org/doi/10.1126/science.abm7841 - News: https://news.mit.edu/2022/ecosystems-instability-models-1006