R/data-documentation.R
rowley2019.Rd
Data from Table 1 and Supplementary Tables 1 and 2 from "A cascading influence of calcium carbonate on the biogeochemistry and pedogenic trajectories of subalpine soils, Switzerland".
data(rowley2019)
A SoilProfileCollection
object:
site-level attributes
profile ID
profile group
horizon-level attributes
sample ID
horizon name
pH
cmol(+) / kg, exchangeable Al
cmol(+) / kg, exchangeable Ca
cmol(+) / kg, cation exchange capacity calculated as the sum of exchangeable cations, not including H+
percent
percent
percent, total nitrogen
percent, soil organic carbon
carbon to nitrogen ratio
g/kg, oxalate-extractable Al
g/kg, oxalate-extractable Fe
g/kg, dithionite-extractable Al
g/kg, dithionite-extractable Fe
Fe_o to Fe_d ratio
profile ID
horizon top (cm)
horizon bottom (cm)
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
g/kg by x-ray fluorescence
percent by x-ray diffraction spectra
percent by x-ray diffraction spectra
percent by x-ray diffraction spectra
percent by x-ray diffraction spectra
percent by x-ray diffraction spectra
percent by x-ray diffraction spectra
percent
percent
percent
percent <2um
percent 2-50um
percent 50-2000um
Milliq ex: grams of Ca per kilogram of dry soil (g kg-1)
2M KCl: grams of Ca per kilogram of dry soil (g kg-1)
0.05 M Na2EDTA: grams of Ca per kilogram of dry soil (g kg-1)
0.5 M CuCl2: grams of Ca per kilogram of dry soil (g kg-1)
horizon ID
Mike C. Rowley, Stephanie Grand, Thierry Adatte, Eric P. Verrecchia, Cascading influence of calcium carbonate on the biogeochemistry and pedogenic trajectories of subalpine soils), Switzerland, Geoderma, 2019, 114065, ISSN 0016-7061, doi:10.1016/j.geoderma.2019.114065 .
library(lattice)
# load data
data('rowley2019')
# check first 5 rows and 10 columns of horizon data
horizons(rowley2019)[1:5, 1:10]
#> sample_id name pH Al_exch Ca_exch CEC_sum Ca_exch_saturation
#> 1 B1.1 Ah1 6.3 0 23.2 23.7 97.6
#> 2 B1.2 Ah2 6.4 0 23.0 23.4 98.4
#> 3 B1.3 ABh 6.3 0 20.3 20.6 98.5
#> 4 B1.4 Bh 6.4 0 16.9 17.2 98.4
#> 5 B1.5 B1 6.4 0 15.2 15.5 98.3
#> Al_exch_saturation TON SOC
#> 1 0 0.8 7.7
#> 2 0 0.8 6.8
#> 3 0 0.6 5.3
#> 4 0 0.5 4.3
#> 5 0 0.4 3.4
# check site data
site(rowley2019)
#> id group
#> 1 B1 CaCO3-bearing
#> 2 B2 CaCO3-bearing
#> 3 B3 CaCO3-bearing
#> 4 F1 CaCO3-free
#> 5 F2 CaCO3-free
#> 6 F3 CaCO3-free
# graphical summary
par(mar=c(1,1,3,1))
plotSPC(rowley2019, color='Feo_Fed', name='name', cex.names=0.85)
plotSPC(rowley2019, color='Ca_exch', name='name', cex.names=0.85)
# grouped plot
groupedProfilePlot(rowley2019, groups = 'group', color='Ca_exch',
name='name', cex.names=0.85, group.name.offset = -10)
# aggregate over 1cm slices, for select properties
a <- slab(rowley2019, group ~ Reactive_carbonate + Ca_exch + pH + K_Feldspar + Na_Plagioclase + Al)
# plot styling
tps <- list(superpose.line=list(lwd=2, col=c('royalblue', 'firebrick')))
# make the figure
xyplot(top ~ p.q50 | variable, data=a, ylab='Depth', groups=group,
main='', as.table=TRUE,
xlab='median bounded by 25th and 75th percentiles',
lower=a$p.q25, upper=a$p.q75, ylim=c(55,-5),
panel=panel.depth_function,
prepanel=prepanel.depth_function,
cf=a$contributing_fraction,
alpha=0.33, sync.colors=TRUE,
scales=list(x=list(relation='free', alternating=1)),
par.settings=tps,
auto.key=list(columns=2, lines=TRUE, points=FALSE),
strip=strip.custom(bg=grey(0.9))
)