Mapping soil carbon particle size fractions and water retention in tropical dry forest in Brazil

This research paper compares ordinary kriging and regression-kriging methods for mapping 11 soil attributes across three depths in a 102 km2 Tropical Dry Forest area in Brazil.

• The study evaluated 11 soil attributes—including organic carbon content and stock, soil density, clay, sand, and silt contents, cation exchange capacity, pH, water retention at field capacity and permanent wilting point, and available water—using samples from 327 locations at depths of 0.0-0.10, 0.10-0.20, and 0.20-0.40 m.
• Stepwise linear regression models provided the best fit for water retention properties and particle size fractions, utilizing relief and parent material covariates in 31 of 33 models and vegetation covariates in 29 models.
• External validation showed that ordinary kriging was more accurate for 21 out of 33 attribute-depth combinations, suggesting that adding a linear trend model before kriging does not always improve predictions and that geostatistical methods should be compared on a case-by-case basis.

APA

Inter-American Institute for Global Change Research (2025). Mapping soil carbon particle size fractions and water retention in tropical dry forest in Brazil. https://iai.int/es/pub_acad/mapping-soil-carbon-particle-size-fractions-and-water-retention-in-tropical-dry-forest-in-brazil/

Chicago

Inter-American Institute for Global Change Research. Mapping soil carbon particle size fractions and water retention in tropical dry forest in Brazil. 2025. https://iai.int/es/pub_acad/mapping-soil-carbon-particle-size-fractions-and-water-retention-in-tropical-dry-forest-in-brazil/.

Wikipedia

{{cite report |author=Inter-American Institute for Global Change Research |title=Mapping soil carbon particle size fractions and water retention in tropical dry forest in Brazil |date=13 January 2025 |url=https://iai.int/es/pub_acad/mapping-soil-carbon-particle-size-fractions-and-water-retention-in-tropical-dry-forest-in-brazil/ |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{interamericaninstituteforglobalchangeresearch2025mapping, author = {{Inter-American Institute for Global Change Research}}, title = {{Mapping soil carbon particle size fractions and water retention in tropical dry forest in Brazil}}, institution = {Inter-American Institute for Global Change Research}, year = {2025}, month = jan, url = {https://iai.int/es/pub_acad/mapping-soil-carbon-particle-size-fractions-and-water-retention-in-tropical-dry-forest-in-brazil/}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }