CedarCreek.2004.2006.boot.performances

Performances are randomly removed from the dataset,
from 1 to n-1 performances (with n = total number of performances),
a functional clustering of species is built,
and the effect of this performance remove on species clustering
is evaluated by comparing the resulting species clustering
with the species clustering obtained with all systemic performances.
The perturbation is measured by using different clustering indices.
Here, the total number of performances is 3 only,
then the interest of this process is very limited.

datasets

Cluster together the components that make up an interactive
system on the basis of their functional redundancy
for one or more collective, systemic performances.
Plot the hierarchical tree of component clusters,
the modelled and predicted performances of component assemblages,
and other results associated with a functional clustering.
Test and prioritize the significance of the different components
that make up the interactive system,
of the different assemblages of components that make up the dataset,
and of the different performances observed on the component assemblages.
The method finds application in ecology, for instance,
where the system is an ecosystem, the components are organisms or species,
and the systemic performance is the production of biomass
or the respiration of the ecosystem.
The method is extensively described in
Jaillard B, Deleporte P, Loreau M, Violle C (2018)
"A combinatorial analysis using observational data identifies species
that govern ecosystem functioning"
<doi:10.1371/journal.pone.0201135>.

Beno<c3><ae>t Jaillard

functClust

Functional Clustering of Redundant Components of a System

Philippe Deleporte

Michel Loreau

Cyrille Violle

CedarCreek.2004.2006.boot.performances function

A list of matrices, each matrix containing
 the results for a given clustering index. The indices are
 "Czekanowski_Dice", "Folkes_Mallows", "Jaccard", "Kulczynski",
 "Precision", "Rand", "Recall", "Rogers_Tanimoto", "Russel_Rao",
 "Sokal_Sneath1" and "Sokal_Sneath2" index.

Format

Evaluate by bootstrapping the robustness of species clustering
to the number of performances (annual biomass) used in the cluster analysis. — CedarCreek.2004.2006.boot.performances

Evaluate by bootstrapping the robustness of species clustering
to the number of performances (annual biomass) used in the cluster analysis.

CedarCreek.2004.2006.boot.performances: Evaluate by bootstrapping the robustness of species clustering to the number of performances (annual biomass) used in the cluster analysis.

Description

Usage

Arguments

Format

Details