scape: Simulate phylogenetic community structure across a landscape
In willpearse/pez: Phylogenetics for the Environmental Sciences

Description Usage Arguments Details Value Author(s) References See Also Examples

scape simulates communities that are phylogenetically structured

scape(tree, scape.size = 10, g.center = 1, g.range = 1,
  g.repulse = 1, wd.all = 150, signal.center = TRUE,
  signal.range = TRUE, same.range = TRUE, repulse = TRUE,
  center.scale = 1, range.scale = 1, repulse.scale = 1,
  site.stoch.scale = 0.5, sd.center = 1, sd.range = 1, rho = NULL,
  th = 8)

`tree`	`phylo` object
`scape.size`	edge dimension of square landscape
`g.center`	strength of phylogenetic signal in species range centers
`g.range`	strength of phylogenetic signal in species range sizes
`g.repulse`	strength of phylogenetic repulsion
`wd.all`	niche width, larger values simulate broader range sizes
`signal.center`	simulate with phylosignal in range centers
`signal.range`	simulate with phylosignal in range size
`same.range`	make all range sizes equal
`repulse`	include phylogenetic repulsion in range centers
`center.scale`	adjust strength of phylogenetic attraction in range centers independent of `g.center`
`range.scale`	adjust strength of phylogenetic signal in range size independent of `g.range`
`repulse.scale`	adjust strength of phylogenetic repulsion independent of `g.repulse`
`site.stoch.scale`	adjust strength of random variation in species richness across sites
`sd.center`	sd in `rnorm` for the range centers, increase to get more variation in center values across species
`sd.range`	sd `rnorm` for the range sizes, increase to get more variation in range sizes across gradients
`rho`	Grafen branch adjustment of phylogenetic tree see `corGrafen`
`th`	probability threshold 10^-th above which species are considered present at a site

Simulates a landscape with species (i.e., tree tips) distributions dependent on a supplied phylogenetic tree. The amount and type of structure is determened by the signal parameters g.center, g.range and g.repulse. Parameters are based on an Ornstein-Uhlenbeck model of evolution with stabilizing selection. Values of g=1 indicate no stabilizing selection and correspond to the Brownian motion model of evolution; 0<g<1 represents stabilizing selection; and g>1 corresponds to disruptive selection where phylogenetic signal for the supplied tree is amplified. See corBlomberg. Communities are simulated along two gradients where the positions along those gradients, g.center and range sizes g.range, can exhibit phylogenetic signal. Phylogenetic attraction is simulated in the g.center paramter, while repulsion in g.repulse. Both can be exhibited such that closly related species are generally found with similar range centers (phylogenetic attraction) but just not at the same site (phylogenetic repulsion). The function then returns probabilities of of each species across sites and the presence and absences of species based a supplied threshold, th, which can be increased to obtain more species at sites and thus increase average site species richness.

`cc`	`comparative.comm` object with presence/absence results of simulations. The site names are the row.columns of the cells in the original grid cells that made up the data, and these co-ordinates are also given in the `env` slot of the object.
`X.joint`	full probabilities of species at sites, used to construct `cc`
`X1`	probabilities of species along gradient 1
`X2`	probabilities of species along gradient 2
`sppXs`	full probabilities of each species as an array arranged in a `scape.size`-by-`scape.size` matrix
`V.phylo`	initial phylogenetic covariance matrix from tree
`V.phylo.rho`	phylogenetic covariance matrix from tree scaled by Grafen if rho is provided
`V.center`	scaled by `g.center` phylo covariance matrix used in the simulations
`V.range`	scaled by `g.range` phylo covariance matrix used in the simulations
`V.repulse`	scaled by `g.repulse` phylo covariance matrix used in the simulations
`bspp1`	species optima for gradient 1
`bspp2`	species optima for gradient 2
`u`	the env gradients values for the two gradients
`wd`	the denominator for species ranges

M.R. Helmus, cosmetic changes by Will Pearse

Helmus M.R. & Ives A.R. (2012). Phylogenetic diversity area curves. Ecology, 93, S31-S43.

eco.scape sim.phy sim.meta

#Create balanced tree with equal branch-lengths (signal in centers)
tree <- stree(8,type="balanced")
tree$edge.length <- rep(1, nrow(tree$edge))
tree$root <- 1
kk <- scape(tree, scape.size=100, g.center=100, g.range=1, g.repulse=1, wd.all=150,
    signal.center=TRUE, signal.range=FALSE, same.range=FALSE, repulse=FALSE,center.scale = 1,
    range.scale = 1, repulse.scale = 1, site.stoch.scale = 0, sd.center=3, sd.range=1,
    rho=NULL, th=20)

#Make some plots
par(mfrow=c(1,Ntip(tree)),mar=c(.1,.1,.1,.1))
for(j in seq_along(tree$tip.label))
    image(t(1 - kk$sppXs[,,j]/max(kk$sppXs[,,j])), xlab = "",
              ylab = "",main = "",axes=FALSE, col=grey.colors(10))

par(mfrow=c(2,1))
matplot((kk$X1), type = "l", xlab="gradient",ylab = "probability",
main = "Gradient 1",col=rainbow(dim(kk$X1)[2]),lty=1)
matplot((kk$X2), type = "l", xlab="gradient",ylab = "probability",
main = "Gradient 2",col=rainbow(dim(kk$X2)[2]),lty=1)

plot(x=seq_along(sites(kk$cc)),y = rowSums(comm(kk$cc)), main = "SR",type = "l")
cor(kk$X1)