COSha30: Soil organic carbon database at a sampling depth of 0-30 cm

In amsantac/geospt: Geostatistical Analysis and Design of Optimal Spatial Sampling Networks

Soil organic carbon database at a sampling depth of 0-30 cm

Description

Soil organic carbon database of samples taken in several soil and land cover types at La Libertad Research Center at a sampling depth of 0-30 cm

Usage

data(COSha30)

Format

A data frame with 118 observations on the following 10 variables:

ID

ID of each sampling site

x

x-coordinate of each site. Spatial reference system: UTM 18N

y

y-coordinate of each site. Spatial reference system: UTM 18N

DA30

measured soil bulk density (g cm^{-3})

CO30

measured soil carbon concentration (%)

COB1r

land cover at each sampling site in 2007. See details below

S_UDS

soil type at each sampling site. See details below

COSha30

calculated total soil carbon stock (t ha^{-1}). See details below

Cor4DAidep

total soil carbon stock (t ha^{-1}) corrected by soil compaction factors

CorT

corrected total soil carbon stock with Box-Cox transformation applied

Details

A total of 150 samples for a 0-30 cm depth was collected and analyzed for soil bulk density and organic carbon concentration in 2007 at La Libertad Research Center in Villavicencio, Colombia. The samples were taken in soils under different land cover types: rice crops (Az), citrus crops (Ci), forest plantations (Cpf), annual crops (Ctv), grasses (P), and oil palm crops (Pl). In the soil type names, the first two letters correspond to the short name of the soil series, the lower-case letters indicate the slope class, and the number denotes the type of soil drainage.

Total soil carbon stock COSha was calculated as follows (Guo & Gifford, 2002):

COSha=DA*CO*d

where DA is soil bulk density (g cm^{-3}), CO is soil organic carbon concentration (%) and d is sampling depth (cm).

Given that the data did not fit a normal distribution, a Box-Cox transformation was applied (Box & Cox, 1964). Some samples were discarded for the design of sampling networks. The complete database and description can be found in Santacruz (2010) and in Santacruz et al., (2014).

Source

Santacruz, A. 2010. Design of optimal spatial sampling networks for the monitoring of soil organic carbon at La Libertad Research Center through the application of genetic algorithms. M.Sc. Thesis. National University of Colombia, Bogota. 162 p. (In Spanish)

References

Santacruz, A., Rubiano, Y., Melo, C., 2014. Evolutionary optimization of spatial sampling networks designed for the monitoring of soil carbon. In: Hartemink, A., McSweeney, K. (Eds.). Soil Carbon. Series: Progress in Soil Science. (pp. 77-84). Springer. [link]

Santacruz, A., 2011. Evolutionary optimization of spatial sampling networks. An application of genetic algorithms and geostatistics for the monitoring of soil organic carbon. Editorial Academica Espanola. 183 p. ISBN: 978-3-8454-9815-7 (In Spanish) [link]

Guo, L., Gifford, R., 2002. Soil carbon stocks and land use change: a meta analysis. Global Change Biology 8, 345-360.

Box, G., Cox, D., 1964. An analysis of transformations. Journal of the Royal Statistical Society. Series B (Methodological) 26 (2), 211-252.

See Also

COSha30map

Examples

data(COSha30)
str(COSha30)

amsantac/geospt documentation built on Feb. 21, 2024, 12:23 p.m.