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ade4 (version 1.5-2)

macroloire: Assemblages of Macroinvertebrates in the Loire River (France)

Description

A total of 38 sites were surveyed along 800 km of the Loire River yielding 40 species of Trichoptera and Coleoptera sampled from riffle habitats. The river was divided into three regions according to geology: granitic highlands (Region#1), limestone lowlands (Region#2) and granitic lowlands (Region#3). This data set has been collected for analyzing changes in macroinvertebrate assemblages along the course of a large river. Four criterias are given here: variation in 1/ species composition and relative abundance, 2/ taxonomic composition, 3/ Body Sizes, 4/ Feeding habits.

Usage

data(macroloire)

Arguments

encoding

latin1

source

Ivol, J.M., Guinand, B., Richoux, P. and Tachet, H. (1997) Longitudinal changes in Trichoptera and Coleoptera assemblages and environmental conditions in the Loire River (France). Archiv f�r Hydrobiologie, 138, 525--557. Pavoine S. and Dol�dec S. (2005) The apportionment of quadratic entropy: a useful alternative for partitioning diversity in ecological data. Environmental and Ecological Statistics, 12, 125--138.

Examples

Run this code
data(macroloire)
    apqe.Equi <- apqe(macroloire$fau, , macroloire$morphoregions)
    apqe.Equi
    #test.Equi <- randtest.apqe(apqe.Equi, method = "aggregated", 99)
    #plot(test.Equi)

    m.phy <- taxo2phylog(macroloire$taxo)
    apqe.Tax <- apqe(macroloire$fau, m.phy$Wdist, macroloire$morphoregions)
    apqe.Tax
    #test.Tax <- randtest.apqe(apqe.Tax, method = "aggregated", 99)
    #plot(test.Tax)

    dSize <- sqrt(dist.prop(macroloire$traits[ ,1:4], method = 2))
    apqe.Size <- apqe(macroloire$fau, dSize, macroloire$morphoregions)
    apqe.Size
    #test.Size <- randtest.apqe(apqe.Size, method = "aggregated", 99)
    #plot(test.Size)

    dFeed <- sqrt(dist.prop(macroloire$traits[ ,-(1:4)], method = 2))
    apqe.Feed <- apqe(macroloire$fau, dFeed, macroloire$morphoregions)
    apqe.Feed
    #test.Feed <- randtest.apqe(apqe.Feed, method = "aggregated", 99)
    #plot(test.Size)

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