ccm: Community Composition Modeling

In labdsv: Ordination and Multivariate Analysis for Ecology

Community Composition Modeling

Description

Compares the composition of modeled communities to real data using Bray-Curtis similarity

Usage

ccm(model,data)

Arguments

model	fitted data from a predictive model
data	actual data from the modeled communities

Details

The algorithm sweeps through the fitted values and data one sample unit at time calculating the similarity to the simulated community to the real community. The calculation is similarity, not dissimilarity, and results in a vector of length equal to the number of sample units.

The diverse matrix has the diversity of the data in the first column, and the diversity of the simulated or fitted data in the second column.

Value

A list object with two components:

sim	a vector of similarities of modeled communities to actual data
diverse	Shannon-Weaver diversity values for modeled and real data

Author(s)

David W. Roberts [e-mail]

Examples

data(bryceveg) 
bryceveg <- dropspc(bryceveg,4)
bryce.bc <- dsvdis(bryceveg,'bray')
bryce.nmds <- nmds(bryce.bc)
## Not run: bryce.preds <- predict(bryce.nmds,bryceveg)
## Not run: bryce.ccm <- ccm(bryceveg,bryce.preds$fitted)
## Not run: summary(bryce.ccm$sim)
## Not run: boxplot(bryce.ccm$diverse)

labdsv documentation built on April 10, 2023, 5:08 p.m.