Bifurcations and multistability in empirical mutualistic networks

Area of Science:

• Ecology
• Theoretical Ecology
• Mathematical Biology

Background:

• Ecological communities face diverse species outcomes, from thriving to extinction, due to internal and external factors.
• Existing theoretical frameworks, often from random matrix theory, do not fully capture species-level dynamical heterogeneity in real-world ecosystems.
• Understanding these dynamics is crucial for effective ecological assessment and management.

Purpose of the Study:

• To develop a theoretical framework for understanding species-level dynamical heterogeneity in ecological networks.
• To investigate the impact of varying interaction strengths (competition and mutualism) on species persistence and extinction.
• To identify thresholds for multistability and different extinction scenarios in plant-pollinator networks with intragroup competition.

Main Methods:

• Utilized empirical plant-pollinator mutualistic networks with all-to-all intragroup competition.
• Modeled species abundance dynamics using a Lotka-Volterra-type equation.
• Employed a dynamical systems approach to analyze the effects of uniform competition and mutualism strengths on species persistence.

Main Results:

• Identified specific sequences of species extinctions as interaction strengths are incrementally varied.
• Determined threshold values for interaction strengths where multistability emerges.
• Demonstrated that different extinction scenarios can arise depending on initial species abundances within the ecological network.

Conclusions:

• The study elucidates interaction strength regimes that dictate species persistence and extinction patterns.
• Findings highlight the importance of initial species abundances in determining community trajectories.
• Provides a dynamical systems framework for assessing and managing ecological networks with complex interactions.