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NST (version 3.1.10)

Normalized Stochasticity Ratio

Description

To estimate ecological stochasticity in community assembly. Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. The new index, normalized stochasticity ratio (NST), is to estimate ecological stochasticity, i.e. relative importance of stochastic processes, in community assembly. With functions in this package, NST can be calculated based on different similarity metrics and/or different null model algorithms, as well as some previous indexes, e.g. previous Stochasticity Ratio (ST), Standard Effect Size (SES), modified Raup-Crick metrics (RC). Functions for permutational test and bootstrapping analysis are also included. Previous ST is published by Zhou et al (2014) . NST is modified from ST by considering two alternative situations and normalizing the index to range from 0 to 1 (Ning et al 2019) . A modified version, MST, is a special case of NST, used in some recent or upcoming publications, e.g. Liang et al (2020) . SES is calculated as described in Kraft et al (2011) . RC is calculated as reported by Chase et al (2011) and Stegen et al (2013) . Version 3 added NST based on phylogenetic beta diversity, used by Ning et al (2020) .

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install.packages('NST')

Monthly Downloads

505

Version

3.1.10

License

GPL-2

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Maintainer

Daliang Ning

Last Published

June 5th, 2022

Functions in NST (3.1.10)

NST-package

Normalized Stochasticity Ratio
beta.obs.rand

Test data B observed and null beta diversity
beta.g

Various taxonomic beta diversity indexes
dist.3col

Transform distance matrix to 3-column matrix
cNST

Normalized Stochasticity Ratio based on customized metrics and null results
match.name

Check and ensure the consistency of IDs in different objects.
ab.assign

Randomly draw individuals into species according to specified probabilities
nst.boot

Bootstrapping test for ST and NST
beta.limit

Upper limit of different beta diversity (dissimilarity) indexes
nst.panova

Permutational multivariate ANOVA test for ST and NST
bmntd.big

beta mean nearest taxon distance (betaMNTD) from big data
null.models

Options of null model algorithms
tNST

Taxonomic Normalized Stochasticity Ratio (tNST)
tda

Test dataset A
pNST

Normalized Stochasticity Ratio based on phylogenetic beta diversity
taxo.null

Null models of taxonomic beta diversity