simdata: Simulation of Ecological Data Sets
In SSP: Simulated Sampling Procedure for Community Ecology

simdata

R Documentation

Simulation of Ecological Data Sets

Description

Simulates multiple ecological data sets using parameters estimated from a pilot study. The output can be used in downstream SSP functions for quality evaluation and sampling effort estimation.

Usage

simdata(Par, cases, N, sites)

Arguments

`Par`	A list of parameters estimated by `assempar`.
`cases`	Number of data sets to simulate.
`N`	Number of samples to simulate in each site.
`sites`	Number of sites to simulate in each data set.

Details

Presence/absence data are simulated using Bernoulli trials based on empirical frequencies of occurrence among sites (for site-level presence) and within sites (for local occurrence patterns). These matrices are then converted into abundance matrices using values drawn from Poisson or negative binomial distributions (for count data), or from log-normal distributions (for continuous data like coverage or biomass), depending on the aggregation properties estimated in the pilot data.

This process is repeated cases times, producing a list of simulated data sets that reflect the statistical properties of the original assemblage, but without incorporating environmental constraints or species co-occurrence structures.

Value

A list of simulated community data sets, to be used by datquality and sampsd.

Note

This simulation assumes that differences in composition or abundance are due to spatial aggregation, as captured by the pilot data. It does not incorporate environmental gradients or species associations. For more advanced modeling of species associations, copula-based approaches as suggested by Anderson et al. (2019) may be integrated in future versions of SSP.

References

Anderson, M. J., & Walsh, D. C. I. (2013). PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecological Monographs, 83(4), 557–574.

Anderson, M. J., de Valpine, P., Punnett, A., & Miller, A. E. (2019). A pathway for multivariate analysis of ecological communities using copulas. Ecology and Evolution, 9, 3276–3294.

Guerra-Castro, E.J., Cajas, J.C., Simões, N., Cruz-Motta, J.J., & Mascaró, M. (2021). SSP: an R package to estimate sampling effort in studies of ecological communities. Ecography 44(4), 561-573. doi: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/ecog.05284")}

McArdle, B. H., & Anderson, M. J. (2004). Variance heterogeneity, transformations, and models of species abundance: a cautionary tale. Canadian Journal of Fisheries and Aquatic Sciences, 61, 1294–1302.

Examples

## Single site simulation
data(micromollusk)
par.mic <- assempar(data = micromollusk, type = "P/A", Sest.method = "average")
sim.mic <- simdata(par.mic, cases = 3, N = 10, sites = 1)

## Multiple site simulation
data(sponges)
par.spo <- assempar(data = sponges, type = "counts", Sest.method = "average")
sim.spo <- simdata(par.spo, cases = 3, N = 10, sites = 3)

SSP documentation built on June 8, 2025, 11:41 a.m.