aqp (version 1.8-6)

sp3: Soil Profile Data Example 3

Description

Soil samples from 10 soil profiles, taken from the Sierra Foothill Region of California.

Usage

data(sp3)

Details

These data were collected to support research funded by the Kearney Foundation of Soil Science.

References

http://casoilresource.lawr.ucdavis.edu/

Examples

## this example investigates the concept of a "median profile"

# required packages
library(ape)
data(sp3)

# generate a RGB version of soil colors
# and convert to HSV for aggregation
sp3$h <- NA ; sp3$s <- NA ; sp3$v <- NA
sp3.rgb <- with(sp3, munsell2rgb(hue, value, chroma, return_triplets=TRUE))
sp3[, c('h','s','v')] <- t(with(sp3.rgb, rgb2hsv(r, g, b, maxColorValue=1)))

# promote to SoilProfileCollection
depths(sp3) <- id ~ top + bottom

# aggregate across entire collection
a <- slab(sp3, fm= ~ clay + cec + ph + h + s + v, slab.structure=10)

# check
str(a)

# convert back to wide format
library(reshape)
a.wide.q25 <- cast(a, top + bottom ~ variable, value=c('p.q25'))
a.wide.q50 <- cast(a, top + bottom ~ variable, value=c('p.q50'))
a.wide.q75 <- cast(a, top + bottom ~ variable, value=c('p.q75'))

# add a new id for the 25th, 50th, and 75th percentile pedons
a.wide.q25$id <- 'Q25'
a.wide.q50$id <- 'Q50'
a.wide.q75$id <- 'Q75'

# combine original data with "mean profile"
vars <- c('top','bottom','id','clay','cec','ph','h','s','v')
# make data.frame version of sp3
sp3.df <- as(sp3, 'data.frame')
sp3.grouped <- rbind(
sp3.df[, vars], a.wide.q25[, vars], a.wide.q50[, vars], a.wide.q75[, vars]
)

# re-constitute the soil color from HSV triplets
# convert HSV back to standard R colors
sp3.grouped$soil_color <- with(sp3.grouped, hsv(h, s, v))

# give each horizon a name
sp3.grouped$name <- paste(round(sp3.grouped$clay), '/' , 
round(sp3.grouped$cec), '/', round(sp3.grouped$ph,1))



## perform comparison, and convert to phylo class object
## D is rescaled to [0,]
d <- profile_compare(sp3.grouped, vars=c('clay','cec','ph'), max_d=100, 
k=0.01, replace_na=TRUE, add_soil_flag=TRUE, rescale.result=TRUE)

require(cluster)
h <- agnes(d, method='ward')
p <- ladderize(as.phylo(as.hclust(h)))


# look at distance plot-- just the median profile
plot_distance_graph(d, 12)

# similarity relative to median profile (profile #12)
round(1 - (as.matrix(d)[12, ] / max(as.matrix(d)[12, ])), 2)

## make dendrogram + soil profiles
# first promote to SoilProfileCollection
depths(sp3.grouped) <- id ~ top + bottom

# setup plot: note that D has a scale of [0,1]
par(mar=c(1,1,1,1))
p.plot <- plot(p, cex=0.8, label.offset=3, direction='up', y.lim=c(2,0), 
x.lim=c(1.25,length(sp3.grouped)+1), show.tip.label=FALSE)

# get the last plot geometry
lastPP <- get("last_plot.phylo", envir = .PlotPhyloEnv)

# the original labels, and new (indexed) order of pedons in dendrogram
d.labels <- attr(d, 'Labels')

new_order <- sapply(1:lastPP$Ntip,
function(i) which(as.integer(lastPP$xx[1:lastPP$Ntip]) == i))

# plot the profiles, in the ordering defined by the dendrogram
# with a couple fudge factors to make them fit
plot(sp3.grouped, color="soil_color", plot.order=new_order,
scaling.factor=0.01, width=0.1, cex.names=0.5,
y.offset=max(lastPP$yy)+0.1, add=TRUE)