From individual behavior to metapopulation dynamics: unifying the patchy population and classic metapopulation models

Area of Science:

• Ecology
• Population Dynamics
• Mathematical Biology

Background:

• Spatially structured populations exhibit diverse migration rates, ranging from frequent movements in patchy habitats to rare dispersal in classic metapopulations.
• Existing models often struggle to unify these different migration patterns within a single framework.

Purpose of the Study:

• To develop a common modeling framework for population dynamics in patchy habitats with varying migration rates.
• To create stochastic patch occupancy model (SPOM) approximations from individual-based models (IBMs).
• To apply and validate the framework using the Glanville fritillary butterfly (Melitaea cinxia).

Main Methods:

• An individual-based model (IBM) was developed using a diffusion approximation of correlated random walks for individual movements.
• Stochastic patch occupancy model (SPOM) approximations were derived from the IBM under different stochasticity assumptions (demographic, uncorrelated environmental, correlated environmental).
• The models were parameterized and tested using realistic data for the Glanville fritillary butterfly.

Main Results:

• The derived SPOMs effectively mimicked the behavior of the IBMs across different scenarios.
• SPOM parameters directly relate to individual life history and behavior, enhancing interpretability and parameter estimation.
• The unified framework successfully models populations with both high and low migration rates.

Conclusions:

• The developed modeling approach provides a unified framework for studying population dynamics in patchy habitats.
• This approach is applicable to a spectrum of population structures, from highly mobile individuals to classic metapopulations.
• The direct link between model parameters and individual traits facilitates ecological interpretation and empirical validation.