ecospace (version 1.4.2)

ecospace-package: ecospace: Simulating Community Assembly and Ecological Diversification Using Ecospace Frameworks

Description

ecospace is an R package that implements stochastic simulations of community assembly (ecological diversification) using customizable ecospace frameworks (functional trait spaces). Simulations model the 'neutral', 'redundancy', 'partitioning', and 'expansion' models of Bush and Novack-Gottshall (2012) and Novack-Gottshall (2016a,b). It provides a wrapper to calculate common ecological disparity and functional ecology statistical dynamics as a function of species richness. Functions are written so they will work in a parallel-computing environment.

Details

The package also contains a sample data set, functional traits for Late Ordovician (Type Cincinnatian) fossil species from the Kope and Waynesville formations, from Novack-Gottshall (2016b).

References

Bush, A. and P.M. Novack-Gottshall. 2012. Modelling the ecological-functional diversification of marine Metazoa on geological time scales. Biology Letters 8: 151-155.

Novack-Gottshall, P.M. 2016a. General models of ecological diversification. I. Conceptual synthesis. Paleobiology 42: 185-208.

Novack-Gottshall, P.M. 2016b. General models of ecological diversification. II. Simulations and empirical applications. Paleobiology 42: 209-239.

See Also

The 'calc_metrics' function relies extensively on the functional diversity package FD-package, and hence lists this package as a depends, so it is loaded simultaneously.

Examples

# NOT RUN {
# Get package version, citation, updates, and vignette
packageVersion("ecospace")
citation("ecospace")
news(package = "ecospace")
vignette("ecospace")

# Create an ecospace framework (functional-trait space) with 15 characters
#    (functional traits) of mixed types
nchar <- 15
ecospace <- create_ecospace(nchar = nchar, char.state = rep(3, nchar),
  char.type = rep(c("factor", "ord.fac", "ord.num"), nchar / 3))

# Use to assemble a stochastic "neutral" sample of 20 species (from
#    initial seeding by 5 species)
x <- neutral(Sseed = 5, Smax = 20, ecospace = ecospace)
head(x, 10)

# Calculate ecological disparity (functional diversity) dynamics as a
#    function of species richness
# Statistic 'V' [total variance] not calculated because there are factors
#    in the sample
metrics <- calc_metrics(samples = x, Smax = 20, Model = "Neutral", Param = "NA")
metrics

# Plot statistical dynamics as function of species richness
op <- par()
par(mfrow = c(2,4), mar = c(4, 4, 1, .3))
attach(metrics)
plot(S, H, type = "l", cex = .5)
plot(S, D, type = "l", cex = .5)
plot(S, M, type = "l", cex = .5)
plot(S, V, type = "l", cex = .5)
plot(S, FRic, type = "l", cex = .5)
plot(S, FEve, type = "l", cex = .5)
plot(S, FDiv, type = "l", cex = .5)
plot(S, FDis, type = "l", cex = .5)

par(op)

# }