SciELO - Scientific Electronic Library Online

 
vol.38 issue2Soil strength in degraded pasture assessed by multivariate analysis techniquesDatabase “NAPA”: First synthesis of the pampean water- table dynamic since 1950 to the present author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

  • Have no cited articlesCited by SciELO

Related links

  • Have no similar articlesSimilars in SciELO

Share


Ciencia del suelo

On-line version ISSN 1850-2067

Abstract

CIARLO, Esteban Ariel et al. Spatial variability of soil properties: effect of land use and type. Cienc. suelo [online]. 2020, vol.38, n.2, pp.249-261. ISSN 1850-2067.

Soil spatial variability can be altered by agricultural practices. The understanding of the spatial structure and variability of soil properties is vital for implementing sustainable agricultural practices. This work aimed to assess the spatial variability of relevant soil properties at field scale under different land use (grassland vs. cropping) in contrasting soil types located in the Pampas region of Argentina. Two adjacent fields with different land use were located in two different soils. In each field, surface soil samples (0-20 cm) were collected from a regular grid with 100 points. Descriptive, multivariate and geostatistical analyses were performed on soil descriptors. pH showed a low short-range (0-17 m) spatial variability, while soil extractable P had the greatest variability (CV= 47- 84%). Soil organic carbon (SOC) content and particle size distribution showed a steady coefficient of variation, regardless the soil type or land use. Continuous cropping tended to increase the variability of soil extractable P and penetration resistance. SOC showed a significant spatial autocorrelation in most sites. An average distance of 70 m is proposed when the sampling purpose is to obtain independent soil sub-samples. These results have implications for site-specific crop management, since they can assist in soil sampling optimization.

Keywords : Autocorrelation; mollisols; geostatistics; sampling.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )