Glomalin-related soil protein (GRSP) correlations with soil properties like cation exchange capacity and calcium content were analyzed across diverse Czech soils. The dataset, created by Vojtěch Polách and last updated in April 2026, likely contains results from a study evaluating linear and nonlinear predictors for GRSP accumulation. Prediction accuracy for GRSP was highest using calcium and cation exchange capacity, at 43% and 37% respectively.
Use Cases
- Modeling GRSP accumulation potential based on soil chemical properties like CEC and calcium content.
- Analyzing nonlinear relationships between soil pH and glomalin-related soil protein.
- Investigating the influence of soil type and climatic region on soil organic carbon and humic-to-fulvic acid ratios.
- Comparing soil aggregation predictors across contrasting soil environments like luvisols and chernozems.
Strengths
- Data is openly licensed under CC-BY-4.0, permitting reuse with attribution.
- The study integrates both linear and nonlinear predictors for GRSP estimation, as described.
- Analysis covers a diverse range of soil types and climatic regions within the Czech Republic.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is very small at 9.5 KB, indicating limited scope.
Provenance
- Source
- figshare
- Collection Method
- Likely contains results from a study evaluating soil chemical properties and soil type influence on GRSP accumulation.
- Time Range
- null
- Freshness
- Last updated 2026-04-23 06:16:39; freshness should be verified.
- Geography
- Czech Republic