Skip to contents

comdynamite

Process-based metacommunity simulations in R, with phylogenetic structure.

comdynamite implements the model of Thompson et al. (2020): density-independent growth set by the match between each species’ environmental optimum and the local environment, Beverton–Holt competition, Poisson demographic stochasticity, and dispersal among sites. On top of the original model it offers:

  • phylogenetic structure: optima, niche breadths and maximum growth rates with phylogenetic signal (Pagel’s lambda), traits under single- or multi-optimum Ornstein-Uhlenbeck processes, and competition that is stronger between close relatives;
  • spatially implicit or explicit landscapes: uniform dispersal among exchangeable sites, or a grid (optionally a torus) with an exponential dispersal kernel and a spatially autocorrelated environment;
  • restricted null models for grids: site permutations of a torus that keep its spatial structure;
  • an environment that can change over time, and abundances recorded at chosen steps;
  • rule-based assembly without population dynamics, as in Kraft et al. (2007): limiting similarity (the GAUSE algorithm of Colwell & Winkler 1984), habitat filtering and neutral assembly, on one or several traits.

Installation 

remotes::install_github("diogoprov/comdynamite")

Example 

library(comdynamite)
set.seed(1)
tr <- treeshapesim::sim_tree_shape(40)
sim <- simulate_metacommunity(
  landscape  = landscape_implicit(50),
  traits     = species_traits(tr, lambda = 1),
  alpha      = competition_matrix(tr, type = "phylo"),
  dispersal  = 0.01,
  n_steps    = 1000
)
sim$abundance  # sites x species

See vignette("comdynamite") for species sorting vs. mass effects, grids and time-varying environments, vignette("phylogenetic-structure") for an ecological question worked through simulations, and vignette("evaluating-methods") for the evaluation of a statistical method. The website has the articles and the function reference.

  • mcomsimr, by Patrick Thompson, is the original R implementation of the model of Thompson et al. (2020). comdynamite was written independently from the published equations. It differs in its conventions (sigma is the standard deviation of the Gaussian response, so it equals sqrt(2) times the niche breadth of Thompson et al.; alpha[j, k] is the effect of species k on species j) and adds phylogenetic traits and competition, grid landscapes on a torus with their restricted permutations, and abundances recorded over time.

  • gen3sis (Hagen et al.

    1. is a general engine for eco-evolutionary simulations on landscapes that change over geological time. Speciation, extinction, dispersal and trait evolution are simulated, so the phylogeny is an outcome of the simulation, and the ecological rules are functions that the user writes. In comdynamite the phylogeny is an input: the tree is fixed, traits are placed on it with a chosen phylogenetic signal, and a fixed population model runs over ecological time (no speciation). This is what simulation studies of methods need, because tree shape and phylogenetic signal can be set independently and replicates can be paired by tree across scenarios. The two can be combined: a phylogeny produced by gen3sis can be used as the regional pool of a comdynamite simulation.

  • treeshapesim simulates trees with separately controlled imbalance and branching times, to use as regional pools in comdynamite. Tree shape can then be a factor in the design of a simulation study:

    tr <- treeshapesim::sim_tree_shape(40, beta = -1, c = -0.5)
sim <- simulate_metacommunity(landscape_implicit(20), species_traits(tr, lambda = 1),
                              competition_matrix(tr, type = "phylo"),
                              dispersal = 0.01, n_steps = 1000)

Citation

Provete, D. B. (2026). comdynamite: Process-based metacommunity simulations with phylogenetic structure. R package. https://doi.org/10.5281/zenodo.23993533

This DOI always points to the latest version; each release also has its own DOI on Zenodo. In R, citation("comdynamite") gives the entry with the installed version.

References

Thompson, P. L., Guzman, L. M., De Meester, L., Horváth, Z., Ptacnik, R., Vanschoenwinkel, B., Viana, D. S., & Chase, J. M. (2020). A process-based metacommunity framework linking local and regional scale community ecology. Ecology Letters, 23, 1314–1329. https://doi.org/10.1111/ele.13568

Hagen, O., Flück, B., Fopp, F., Cabral, J. S., Hartig, F., Pontarp, M., Rangel, T. F., & Pellissier, L. (2021). gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth’s biodiversity. PLoS Biology, 19, e3001340. https://doi.org/10.1371/journal.pbio.3001340

Colwell, R. K., & Winkler, D. W. (1984). A null model for null models in biogeography. In D. R. Strong, D. Simberloff, L. G. Abele, & A. B. Thistle (Eds.), Ecological Communities: Conceptual Issues and the Evidence (pp. 344–359). Princeton University Press. https://doi.org/10.1515/9781400857081.344

Kraft, N. J. B., Cornwell, W. K., Webb, C. O., & Ackerly, D. D. (2007). Trait evolution, community assembly, and the phylogenetic structure of ecological communities. The American Naturalist, 170, 271–283. https://doi.org/10.1086/519400