| partitionR {comstab} | R Documentation |
Partitioning of the temporal CV of ecological communities
Description
PartitionR() is a function used to partition the temporal coefficient of variation of a community
into the variability of the average species and three stabilizing effects: the dominance, asynchrony and averaging effects
(see Details).
Usage
partitionR(z, ny = 1)
Arguments
z |
A |
ny |
Only species appearing more than |
Details
The analytic framework is described in details in Segrestin et al. (2024). In short, the partitioning relies on the following equation:
CV_{com} = CV_e \Delta \Psi \omega
where CV_{com} is the community coefficient of variation (reciprocal of community stability),
CV_e is the expected community CV when controlling for the dominance structure and species temporal synchrony,
\Delta is the dominance effect, \Psi is the asynchrony effect, and \omega is the averaging effect.
Value
Returns an object of class 'comstab'.
An object of class 'comstab' is a list containing the following components:
-
'CVs'a named vector of calculated coefficient of variations.CVeis the CV of an average species,CVtildeis the mean of species CVs weighted by their relative abundances,CVais the expected community CV if the community was stabilized by species asynchrony only, andCVcis the observed community CV. -
'Stabilization'a named vector of the stabilizing effects.tauis the total stabilization,Deltais the dominance effect,Psiis the asynchrony effect, andomegais the averaging effect. -
'Relative'a named vector of the relative contributions of each stabilizing effect to the total stabilization.Delta_cont,Psi_cont, andomega_contare the relative contribution of respectively, the dominance, asynchrony, and averaging effects to the total stabilization. Returns a vector of NAs if any Stabilizing effect is higher than 1.
Author(s)
Jules Segrestin, jsegrestin@gmail.com
References
Segrestin et al. (2024) A unified framework for partitioning the drivers of stability of ecological communities. Global Ecology and Biogeography, 33(5), e13828. https://doi.org/10.1111/geb.13828
Examples
require(stats)
# Simulates a custom community time series using 'comTS()':
z <- comTS(nsp = 10, ny = 30, even = 0.6, mvs = 1.5, sync = "0")
# Runs the partitioning of the community coefficient of variation:
partitionR(z)