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.
macroloire is a list of 5 components.
is a data frame containing the abundance of each species in each station.
is a data frame describes two traits : the maximal sizes and feeding habits for each species. Each trait is divided into categories. The maximal size achieved by the species is divided into four length categories: <= 5mm ; >5-10mm ; >10-20mm ; >20-40mm. Feeding habits comprise seven categories: engulfers, shredders, scrapers, deposit-feeders, active filter-feeders, passive filter-feeders and piercers, in this order. The affinity of each species to each trait category is quantified using a fuzzy coding approach. A score is assigned to each species for describing its affinity for a given trait category from "0" which indicates no affinity to "3" which indicates high affinity. These affinities are further transformed into percentage per trait per species.
is a data frame with species and 3 factors: Genus, Family and Order. It is a data frame of class "taxo": the variables are factors giving nested classifications.
is a data frame giving for each station, its name (variable "SamplingSite"), its distance from the source (km, variable "Distance"), its altitude (m, variable "Altitude"), its position regarding the dams [1: before the first dam; 2: after the first dam; 3: after the second dam] (variable "Dam"), its position in one of the three regions defined according to geology: granitic highlands, limestone lowlands and granitic lowlands (variable "Morphoregion"), presence of confluence (variable "Confluence")
is a data frame containing the latin names of the species.
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 for Hydrobiologie, 138, 525–557.
Pavoine S. and Doledec S. (2005) The apportionment of quadratic entropy: a useful alternative for partitioning diversity in ecological data. Environmental and Ecological Statistics, 12, 125–138.
data(macroloire) apqe.Equi <- apqe(macroloire$fau, , macroloire$morphoregions) apqe.Equi #test.Equi <- randtest.apqe(apqe.Equi, method = "aggregated", 99) #plot(test.Equi) ## Not run: 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) ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.