Mut-networks-EcoEvo-under-stochasticity

The code and data presented in this repository constitute the core framework for simulating the study titled “Environmental stochasticity modulates trait matching, indirect effects, and resilience in adaptive mutualistic networks.” The archive Data_result.zip includes the data underlying the main results of the paper (corresponding to Figs. 2–4).The archive Mut-networks-EcoEvo-under-stochasticity.zip contains the MATLAB programs used to generate simulation data for exploring the parameter space of environmental stochasticity, with temporal autocorrelation serving as the primary example. Code Description (Mut-networks-EcoEvo-under-stochasticity.zip) LG_PM.m: MATLAB code describing population dynamics (differential equation Eqn. 1). trait_evolution.m: MATLAB code for calculating species trait updates based on the coevolutionary model (Eqn. 2). environment_change.m: MATLAB code describing environmental change (Eqn. 3). trait_match.m: MATLAB code for computing trait matching. update_interaction.m: MATLAB code for updating interspecific interactions. get_jacmat.m: MATLAB code for obtaining the Jacobian matrix. get_between_trait_distance.m: MATLAB code for calculating between-species trait distances. get_envir_distance.m: MATLAB code for calculating species-environment distances. get_indirect_effect.m: MATLAB code for calculating the indirect effects of ecological interactions. Model_Core.m: The main MATLAB program for generating simulation data to explore the parameter space of environmental stochasticity (using temporal autocorrelation as the primary example). MutNet_tot.xls: Empirical mutualistic networks used to parameterize the adjacency matrices in this study. These data were obtained from the Web of Life database (www.web-of-life.es).