Empirical Models for Predicting Soil-Climate and Related Pasture Grass Preformance in Maui, Hawaii (An Evaluation of Soil-Climate Criteria of Soil Taxonomy)

Kourouma, Laye
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Soil Taxonomy requires soil-climate for soil classification and the interpretation of the relationships between soil, climate, and plant. The depth at which soil temperature and soil moisture regimes are currently measured or estimated have been, however, given without presenting any evidence of any particular importance of soil-climate at these depths to soil genesis and/or plant growth. The objectives of this study were to develop mathematical models that can provide first approximations of soil temperatures at different depths and evaluate the depth at which soil temperature and/or soil moisture correlate most to herbage production. Such a knowledge can be used as a criterion for better identification of soil-climate and serve as a basis for the evaluation of the current soil-climate criteria of Soil Taxonomy. Located on the island of Maui, Hawaii, the area of the study extended along a climosequence with a wide range of ecological zones. The altitudes vary from 36 to 1620 m, the soils from Inceptisols (Andepts) to Mollisols and Oxisols, mean annual air temperatures from 13 to 24 °c, and total mean annual precipitation from 100 to 872 mm. Computerized automatic weather stations were installed to monitor air and soil-climate environment at 11 sites and pasture grass growth was observed at four of the sites. The measurements included air temperature, soil temperatures at 0.1- and 0.5- m depths, soil moisture at 0.1- and 0.5-m depths, relative humidity, rainfall, and solar radiation. The dominant grass species were buffel grass, kikuyu grass, and an admixture of fescue, sweet vernal, rattail, Yorkshire fog, and white clover. Simple linear, multiple, and quadratic regression models were developed to estimate the soil temperatures at 0.1- and 0.5-m depths from air temperature and other environmental factors. All of the models showed a satisfactory coefficient of determination, but the quadratic models were judged to have a greater predictive ability than the others because of their slightly higher R2 and smaller residual mean squares. In addition, the quadratic models depicted better the curvilinear relationship between the air and soil temperatures. Soil temperatures predicted by the quadratic models were in better agreement with the measured temperatures than those predicted by the model currently used in Soil Taxonomy. A modification of the Soil Taxonomy model is proposed for soil temperature, that is, to add 2 °c to the air temperature if the air temperature is less than 22 °c or to add 4 °c if the air temperature is equal to or greater than 22 °c. Such a modification gives a close approximation of the measured soil temperature at 0.5-m depth. Seasonal fluctuations of herbage production were more correlated to soil-climate at 0.5-m depth than to atmospheric weather or soil-climate at 0.1-m depth. The-use of soil-climate properties in Soil Taxonomy is, therefore, justified. The greater impact of soil moisture at 0.5-rn depth suggests the location of the soil moisture control section at or below that depth, regardless of soil texture. It is concluded that if Soil Taxonomy is to be a basis of prognosis of plant response to soil, soil-climate, and other crop production parameters, the diagnostic criteria of soil-climate at 0.5-m depth best serve the purpose.
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