A taxonomy of multiple stable states in complex ecological communities

Area of Science:

• Ecology
• Theoretical Ecology
• Complex Systems

Background:

• Natural systems comprise interconnected units, making their dynamics and fragility difficult to predict.
• Regime shifts, or abrupt transitions from healthy to degraded ecosystem states, are a key fragility scenario.
• Alternative stable states explain regime shifts in simple models, but upscaling to complex systems is debated.

Purpose of the Study:

• To investigate how multistability (the existence of multiple stable states) scales with system complexity in ecological communities.
• To identify generic multistability regimes in species-rich models with random interactions.
• To characterize the distinct fingerprints of each regime regarding state number, species richness, and perturbation response.

Main Methods:

• Modeling species-rich communities and archetypical complex biological systems.
• Assuming random interactions within these complex systems.
• Analyzing the emergence of different multistability regimes based on interaction schemes.

Main Results:

• Four distinct multistability regimes generically emerge in models of species-rich communities.
• Each regime is consistently associated with specific interaction schemes.
• Distinct 'fingerprints' characterize each regime, including the number of states, species richness, and response to perturbations.

Conclusions:

• Multistability in complex ecological communities is not monolithic but occurs in distinct, predictable regimes.
• Understanding these regimes clarifies the conditions and types of alternative stable states in nature.
• This work advances the predictability of ecosystem functioning and fragility in complex natural systems.