Detecting alternative attractors in ecosystem dynamics.

Area of Science:

• Ecology
• Dynamical Systems Theory
• Population Dynamics

Background:

• Ecosystems may possess alternative dynamical attractors, such as equilibria and cycles, as suggested by dynamical systems theory.
• Distinguishing alternative dynamical behaviors in natural systems is challenging due to complex interactions between biotic and abiotic factors.
• Existing research indicates some natural systems exhibit alternative states, but a robust methodology for testing distinct dynamical attractors is lacking.

Purpose of the Study:

• To develop and present a robust methodology for empirically testing whether ecosystems exhibit alternative dynamical attractors.
• To provide a tool for distinguishing between different dynamical behaviors in natural populations.

Main Methods:

• Utilized attractor reconstruction techniques to develop a novel test for alternative dynamical attractors.
• Applied the methodology to simulated, experimental, and natural time series data.

Main Results:

• Alternative dynamical behaviors are difficult to distinguish when population dynamics are driven solely by stochastic processes.
• The developed methodology readily detects alternative attractors when population dynamics involve internal system mechanisms.
• Natural populations often exhibit internally driven dynamics, making them suitable for this detection method.

Conclusions:

• The proposed approach offers a reliable method for empirically testing for alternative dynamical attractors in ecosystems.
• The ability to detect alternative attractors is dependent on the presence of internally driven dynamics within the population.
• This methodology advances our understanding of ecosystem stability and resilience by identifying distinct dynamical states.