pMEM (version 0.1-1)

geoMite: Borcard's Oribatid Mite Data Set - Geographic Information System Version -

Description

Oribatid mite community data in a peat bog surrounding Lac Geai, QC, Canada

Usage

data(geoMite)

Format

A list with five sf data frames:

core

A data frame with 70 rows (peat cores) containing point geometries and 46 fields containing values of environmental variables at the locations of the cores as well as the number of individuals of one of 35 Oribatid species observed in the cores (see details).

water

A data frame with three rows containing polygon geometries and a single field: a factor variable named "Type" and specifying whether the polygon represents open water (value == "Water") or flooded areas (value == "Flooded") at the time of sampling.

substrate

A data frame with 13 rows containing polygon geometries and seven fields. The first field is a factor that specifies one of six substrate classes (see details) and the remaining six fields are binary variables for each of these six substrate classes that take the value 1 when the polygon is of the class being represented by the that variable and otherwise take the value 0.

shrub

A data frame with four rows containing polygon geometries and a single field: an ordered variable named "Type" and specifying whether the polygon represents areas with no shrub (value == "None"), a few shrubs (value == "Few"), or many shrubs (value == "Many").

topo

A data frame with four rows containing polygon geometries and a single field: a factor variable named "Type" and specifying the type of peat micro-topography. There are two such types: "Blanket" (flat area) and "Hummock" (raised bumps).

Author

Daniel Borcard, <[e-mail]> and Pierre Legendre <[e-mail]>

Details

Fields of the point geometry (geoMite$core) are:

SubsDens

Substrate density (g/L).

WatrCont

Water content of the peat (g/L)

Substrate-prefixed

Six binary variables describing the substrate(s) from which the peat core samples were collected. Further details are given below.

Shrub

A three-level ordered factor describing the presence and abundance of shrubs (mainly Ericaceae ) on the peat surface.

Topo

A two-level factor describing the microtopography of the peat mat.

Flooded

A binary variable specifying whether the area in which the core was sampled was flooded at the time of sampling.

Species-prefixed

Counts of one of 35 Oribatid species identified purely on the basis of their morphology.

The types of substrates are described as follows:

Sphagn1

Sphagnum magellanicum (with a majority of S. rubellum).

Sphagn2

Sphagnum rubellum.

Sphagn3

Sphagnum nemoreum (with a minority of S. angustifolium).

Sphagn4

Sphagnum rubellum and S. magellanicum in equal parts.

Litter

Ligneous litter.

Barepeat

Bare peat.

These types are not mutually exclusive categories: cores were sometimes taken at the boundary between two or more substrate types and thus belong to many of these categories.

As stated earlier, identification of the Oribatid species was carried out solely on the basis of their morphology as little is known on the ecology of these small animals.

Geometries in geoMite$water, geoMite$substrate, geoMite$shrub, and geoMite$topo were generated by outlining images from Fig. 1 in Borcard et al. (1994) using a square grid with a resolution of about 10 mm. Because of the inaccuracy to the available printed document the actual resolution is probably inferior (i.e., 10 cm in both the x and y direction).

Orientation: the X coordinates corresponds to distances going from the edge of the water to the edge of the forest. The Y coordinates correspond the distances along the lake's shore.

References

Borcard, D. and Legendre, P. 1994. Environmental Control and Spatial Structure in Ecological Communities: An Example Using Oribatid Mites (Acari, Oribatei). Environ. Ecol. Stat. 1(1): 37-61 tools:::Rd_expr_doi("10.1007/BF00714196")

Borcard, D., Legendre, P., and Drapeau, P. 1992. Partialling out the spatial component of ecological variation. Ecology, 73, 1045-1055. tools:::Rd_expr_doi("10.2307/1940179")

Borcard, D.; Legendre, P.; and Gillet, F. 2018. Numerical Ecology with R (2nd Edition) Sprigner, Cham, Switzerland. tools:::Rd_expr_doi("10.1007/978-3-319-71404-2")

See Also

Data set oribatid from package ade4, which is another version of this data set.

Examples

data(geoMite)

attach(geoMite)

## Color definitions:
col <- list()
col[["substrate"]] <- c(Sphagn1 = "#00ff00", Sphagn2 = "#fffb00",
                        Sphagn3 = "#774b00", Sphagn4 = "#ff8400",
                        Litter = "#ee00ff", Barepeat = "#ff0004")
col[["water"]] <- c(Water = "#008cff", Flooded = "#ffffff00",
                    core = "#000000ff")
col[["shrub"]] <- c(None = "#dfdfdf", Few = "#a7a7a7", Many = "#5c5c5c")
col[["topo"]] <- c(Blanket = "#74cd00", Hummock = "#bc9d00")

## Graphical paramters:
p <- par(no.readonly = TRUE)
par(mar=c(0,0,1,0), mfrow=c(1L,4L))

## Substrate:
plot(st_geometry(substrate), col=col[["substrate"]][substrate$Type],
     main="Substrate")
plot(st_geometry(water[1L,]), col=col[["water"]][water[1L,]$Type], add=TRUE)
plot(st_geometry(water[-1L,]), col=col[["water"]][water[-1L,]$Type], lty=3L,
     add=TRUE)
plot(st_geometry(core), pch = 21L, bg = "black", add=TRUE)

## Shrubs:
plot(st_geometry(shrub), col = col[["shrub"]][shrub$Type], main="Shrubs")
plot(st_geometry(water[1L,]), col=col[["water"]][water[1L,]$Type], add=TRUE)
plot(st_geometry(water[-1L,]), col=col[["water"]][water[-1L,]$Type], lty=3L,
     add=TRUE)
plot(st_geometry(core), pch = 21L, bg = "black", add=TRUE)

## Topograghy:
plot(st_geometry(topo), col = col[["topo"]][topo$Type], main="Topography")
plot(st_geometry(water[1L,]), col=col[["water"]][water[1L,]$Type], add=TRUE)
plot(st_geometry(water[-1L,]), col=col[["water"]][water[-1L,]$Type], lty=3L,
     add=TRUE)
plot(st_geometry(core), pch = 21L, bg = "black", add=TRUE)

## Legends:
plot(NA, xlim=c(0,1), ylim=c(0,1), axes = FALSE)
legend(x=0, y=0.9, pch=22L, pt.cex = 2.5, pt.bg=col[["substrate"]],
       box.lwd = 0, legend=names(col[["substrate"]]), title="Substrate")
legend(x=-0.025, y=0.6, pch=c(22L,NA,21L), pt.cex = c(2.5,NA,1),
       pt.bg=col[["water"]], box.lwd = 0, lty = c(0L,3L,NA),
       legend=c("Open water","Flooded area","Peat core"))
legend(x=0, y=0.4, pch=22L, pt.cex = 2.5, pt.bg=col[["shrub"]], box.lwd = 0,
       legend=names(col[["shrub"]]), title="Shrubs")
legend(x=0, y=0.2, pch=22L, pt.cex = 2.5, pt.bg=col[["topo"]], box.lwd = 0,
       legend=names(col[["topo"]]), title="Topography")

### Display the species counts

## Get the species names:
unlist(
  lapply(
    strsplit(colnames(core),".",fixed=TRUE),
    function(x) if(x[1L] == "Species") x[2L] else NULL
  )
) -> spnms

## See the maximum counts for all the species
apply(st_drop_geometry(core[,paste("Species",spnms,sep=".")]),2L,max)

## Species selection to display:
sel <- c("Brachysp","Hoplcfpa","Oppinova","Limncfci","Limncfru")

## Range of counts to display:
rng <- log1p(c(0,1000))

colmap <- grey(seq(1,0,length.out=256L))

## Update the graphical parameters for this example
par(mar=c(0,0,2,0), mfrow=c(1L,length(sel) + 1L))

## Display each species in the selection over the substrate map
for(sp in sel) {
  plot(st_geometry(substrate), col=col[["substrate"]][substrate$Type],
       main=sp)
  plot(st_geometry(core), pch=21L, add = TRUE, cex=1.5,
       bg=colmap[1 + 255*log1p(core[[paste("Species",sp,sep=".")]])/rng[2L]])
}

## Display the colour chart for the species counts:
par(mar=c(2,7,3,1))
image(z=matrix(seq(0,log1p(1000),length.out=256L),1L,256L), col=colmap,
      xaxt="n", yaxt="n", y=seq(0,log1p(1000),length.out=256L), xlab="",
      cex.lab = 1.5,
      ylab=expression(paste("Counts by species (",ind~core^{-1},")")))
axis(2L, at=log1p(c(0,1,3,10,30,100,300,1000)), cex.axis = 1.5,
     label=c(0,1,3,10,30,100,300,1000))

## Restore graphical parameters:
par(p)