A collection of 18 soil profiles, consisting of select soil morphologic attributes, associated with a stratigraphic study conducted near Honcut Creek, California.

Format

A data frame with 154 observations on the following 21 variables.

id

profile id

surface

dated surface

top

horizon top in cm

bottom

horizon bottom in cm

bound_distinct

horizon lower boundary distinctness class

bound_topography

horizon lower boundary topography class

name

horizon name

texture

USDA soil texture class

prop

field-estimated clay content

structure_grade

soil structure grade

structure_size

soil structure size

structure_type

soil structure type

stickiness

stickiness

plasticity

plasticity

field_ph

field-measured pH

hue

Munsell hue

value

Munsell value

chroma

Munsell chroma

r

RGB red component

g

RGB green component

b

RGB blue component

soil_color

R-friendly encoding of soil color

Source

Busacca, Alan J.; Singer, Michael J.; Verosub, Kenneth L. 1989. Late Cenozoic stratigraphy of the Feather and Yuba rivers area, California, with a section on soil development in mixed alluvium at Honcut Creek. USGS Bulletin 1590-G.

Author

Dylan E. Beaudette

Examples


# keep examples from using more than 2 cores
data.table::setDTthreads(Sys.getenv("OMP_THREAD_LIMIT", unset = 2))

data(sp2)

# convert into SoilProfileCollection object
depths(sp2) <- id ~ top + bottom

# transfer site-level data
site(sp2) <- ~ surface

# generate a new plotting order, based on the dated surface each soil was described on
p.order <- order(sp2$surface)

# plot
par(mar=c(1,0,3,0))
plot(sp2, plot.order=p.order)


# setup multi-figure output
par(mfrow=c(2,1), mar=c(0,0,1,0))

# truncate plot to 200 cm depth
plot(sp2, plot.order=p.order, max.depth=200)
abline(h=200, lty=2, lwd=2)

# compute numerical distances between profiles
# based on select horizon-level properties, to a depth of 200 cm
d <- NCSP(sp2, vars=c('prop','field_ph','hue'), maxDepth = 100, k = 0)
#> Computing dissimilarity matrices from 18 profiles
#>  [0.4 Mb]

# plot dendrogram with ape package:
if(require(ape) & require(cluster)) {
h <- diana(d)
p <- as.phylo(as.hclust(h))
plot(p, cex=0.75, label.offset=0.01, font=1, direct='down', srt=90, adj=0.5, y.lim=c(-0.125, 0.5))

# add in the dated surface type via color
tiplabels(col=as.numeric(sp2$surface), pch=15)

# based on distance matrix values, YMMV
legend('topleft', legend=levels(sp2$surface), col=1:6, pch=15, bty='n', bg='white', cex=0.75)
}
#> Loading required package: ape
#> Loading required package: cluster