simulate_static(): static metacommunities from the Gaussian response of Dray
& Legendre (2008), also used by Peres-Neto et al. (2012), as a baseline without
population dynamics. Data can be Poisson counts, binomial presences or the
expected values.
With several gradients, for example environment and space, the expected
abundance is the product of the responses.simulate_logistic() and logistic_gradients(): presences and absences from
logistic responses to two gradients, with the seven scenarios of Appendix C of
Peres-Neto et al. (2012).phylo_vector() and trait_partition(): phylogenetic gradient analysis of Peres-Neto et al.
(2012), tested against the original code in Octave.
The test between a trait and the environment stays in ade4::fourthcorner().picante::match.phylo.comm(), drop with a warning the
species found in only one of them. Repeated names are an error.trait_partition(): semipartial correlations of each predictor, with their tests,
following Appendix A of Peres-Neto et al. (2012).plot_node_test(): results of node_test() on the tree, as in Figure 3 of Leibold
et al. (2010), as a phylogram or a fan. plot_trait_partition(): fractions of
trait_partition().daphniids: data of Leibold et al. (2010), rebuilt from the public survey.node_contrasts() now keeps nodes that join two tips, as the article does.
cherries = FALSE gives the original code.node_test(): semipartial replaces partial_r2, following the article, and
there are p_adjusted (false discovery rate), biogeographic events, the joint
permutation of the article (p_joint), 9999 permutations by default and cores.pcc_test() and phylo_eigenvectors(): phylogenetic community composition of
Peres-Neto & Kembel (2015), with site and species permutations.phylo_beta_test() and phylo_beta(): phylogenetic beta-diversity framework of
the same article, a distance-based redundancy analysis of the mean phylogenetic
distance between communities.node_test() and node_contrasts(): regression of clades on the environment,
node by node, from Leibold et al. (2010), with site and species permutations.simulate_metacommunity() and mc_dynamics(): stochastic extirpation of
populations (extirpation), used by Thompson et al. (2020) in their
competition-colonisation scenario.First version: the model of Thompson et al. (2020) with phylogenetic traits and competition, spatially implicit and grid landscapes, torus permutations and time-varying environments. Code from the pcps-sim project.
Rule-based assembly (assemble_community()): limiting similarity (GAUSE
algorithm of Colwell & Winkler 1984), habitat filtering and neutral assembly,
as in Kraft et al. (2007).
traits_ou(): traits under an Ornstein-Uhlenbeck process with one or several
optima (multi-peak OU; Brownian motion when alpha = 0), with
paint_regimes() to assign regimes to clades.
New vignettes: vignette("phylogenetic-structure"), on how dispersal, niche
conservatism and competition shape phylogenetic community structure, and
vignette("evaluating-methods"), on type I error and power with simulations.
vignette("evaluating-methods") shows tree shape as a factor of the design,
with trees from treeshapesim (in Suggests).