nicheROVER-package: (Niche) (R)egion and Niche (Over)lap Metrics for...

In nicheROVER: Niche Region and Niche Overlap Metrics for Multidimensional Ecological Niches

(Niche) (R)egion and Niche (Over)lap Metrics for Multidimensional Ecological Niches.

Description

This package uses a probabilistic method to calculate niche regions and pairwise niche overlap using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. See Swanson et al. (2014) for a detailed description and worked example below using fish stable isotope data.

Author(s)

Maintainer: Martin Lysy [e-mail]

Authors:

• Ashley D. Stasko

• Heidi K. Swanson

References

Swanson, H.K., Lysy, M., Stasko, A.D., Power, M., Johnson, J.D., and Reist, J.D. "A new probabilistic method for quantifying n-dimensional ecological niches and niche overlap." Ecology: Statistical Reports 96:2 (2015): 318-324. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1890/14-0235.1")}.

See Also

Useful links:

• https://github.com/mlysy/nicheROVER

• Report bugs at https://github.com/mlysy/nicheROVER/issues

Examples

# analysis for fish data

data(fish) # 4 fish, 3 isotopes
aggregate(fish[2:4], fish[1], mean) # isotope means per fish

# random draws from posterior distribution with default prior
nsamples <- 500
fish.par <- tapply(1:nrow(fish), fish$species,
                   function(ii) niw.post(nsamples = nsamples, X = fish[ii,2:4]))

# display p(mu | X) and p(Sigma | X) for each fish
clrs <- c("black", "red", "blue", "orange") # colors for each species
par(mar = c(4.2, 4.2, 2, 1)+.1)
niche.par.plot(fish.par, col = clrs)
legend(x = "topright", legend = names(fish.par), fill = clrs)

# 2-d projections of 10 niche regions
nsamples <- 10
fish.par <- tapply(1:nrow(fish), fish$species,
                   function(ii) niw.post(nsamples = nsamples, X = fish[ii,2:4]))

# format data for plotting function
fish.data <- tapply(1:nrow(fish), fish$species, function(ii) X = fish[ii,2:4])

niche.plot(niche.par = fish.par, niche.data = fish.data, pfrac = .05,
           iso.names = expression(delta^{15}*N, delta^{13}*C, delta^{34}*S),
           col = clrs, xlab = expression("Isotope Ratio (per mille)"))

# niche overlap plots for 95% niche region sizes

# overlap calculation.  use nsamples = nprob = 1e4 for higher accuracy.
nsamples <- 500
over.stat <- overlap(fish.par, nreps = nsamples, nprob = nsamples, alpha = .95)

# overlap plot
overlap.plot(over.stat, col = clrs, mean.cred.col = "turquoise",
             equal.axis = TRUE,
             xlab = "Overlap Probability (%) -- Niche Region Size: 95%")

nicheROVER documentation built on Oct. 13, 2023, 5:10 p.m.