| Abstrakt: |
Core IdeasWe measured SSA of eight tropical soils formed from eight rocks.Soil SSA varied from 2.8 to 45 m2g−1and was most affected by clay contents.Soil SSA for the 0‐ to 1‐m depth could be modeled by regression using clay and organic C%.The model was further improved using amorphous Al/Fe oxide data. Specific surface area (SSA) is a key property of soils that affects nearly all soil ecological functions that involve aggregation and sorption. However, data on soil SSA are seldom reported in the literature due to time‐consuming analysis or equipment constraints in most soil laboratories. Here, we measured external SSA by means of N2sorption with the Brunauer–Emmett–Teller isotherm using fine earth samples from eight tropical soils of contrasting texture and mineralogy collected at depths of 0 to 5, 30 to 40, and 90 to 100 cm. With these and soil particle‐size distribution and soil organic carbon (SOC) data, we developed a multiple linear regression for SSA description. Soil SSA varied from 2.85 to 45.37 m2g–1, generally increasing with an increase in depth for the same soil. The factor most strongly correlated with SSA was clay content, and the weakest correlations were those with SOC concentration. The best multiple regression obtained was SSA (m2g–1soil) = 0.455(clay %) – 1.641(SOC %) (P< 0.01; n= 72). This equation explained well the observed values (r2= 0.84), including both ends of the measured range. Furthermore, the equation had the advantages of simplicity, using only textural and SOC data of routine determination, and validity for any depth within a 0‐ to 1‐m depth interval. When oxalate‐extractable Fe and especially Al data were included as inputs, the prediction power of the model increased to r2= 0.92. However, the use of equations proposed here to predict SSA for soils of other regions must be accompanied by proper validation due to unpredictable variations in soil organic matter composition and mineral crystallinity, among other factors. |
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