HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Rasmussen, C. Articles by Tabor, N. J. Search for Related Content PubMed Articles by Rasmussen, C. Articles by Tabor, N. J. GeoRef GeoRef Citation Agricola Articles by Rasmussen, C. Articles by Tabor, N. J. Related Collections Soil Geomorphology and Geography Soil Classification and Mapping Pedology

PEDOLOGY

Applying a Quantitative Pedogenic Energy Model across a Range of Environmental Gradients

^a Soil, Water and Environmental Science Dep., Univ. of Arizona, 1177 E. Fourth St., Shantz Bldg. Rm. 429, Tucson, AZ 85721-0038
^b Dep. of Geological Sciences, 3225 Daniels Rd., Southern Methodist Univ., Dallas, TX 75275-0395

^* Corresponding author (crasmuss{at}ag.arizona.edu).

Conceptual energy-based pedogenic models present a framework for quantitatively linking pedon energy throughflow to soil development. In this study, we utilized a quantitative pedogenic energy model (QPEM) based on rates of effective energy and mass transfer (EEMT, kJ m^–2 yr^–1) to the soil system to predict pedogenesis across a wide range of pedogenic environments. Our objectives were to: (i) derive a global equation for estimating EEMT; (ii) test the QPEM framework at the pedon scale across a series of environmental gradients on igneous rock residuum; and (iii) develop quantitative transfer functions between pedogenic indices and EEMT. We derived a simplified two-dimensional Gaussian expression for estimating EEMT from mean annual temperature (MAT) and mean annual precipitation (MAP) (R² = 0.96, significant at P 0.001) using a global climate data set. Environmental gradient data indicated significant differences in EEMT between soil orders (i.e., Entisol = 14,586 vs. Ultisol = 36,521 kJ m^–2 yr^–1), whereas neither MAT nor MAP demonstrated significant differences among soil orders. Pedon data from the gradients were used to derive quantitative transfer functions between EEMT and pedogenic indices, including pedon depth, clay content, subsurface chemical index of alteration minus potassium (CIA–K), and the ratio of free Fe oxides to total Fe (Fe_d/Fe_T). Significant linear and nonlinear functions were derived between EEMT and all of the pedogenic indices, whereas no significant functions could be fit between pedogenic indices, MAT, or MAP. The favorable results from this study suggest that the QPEM framework and EEMT may provide a basis for quantitative pedogenic modeling and prediction of soil properties.

Abbreviations: AN, andesite • BS, basalt • CR, Cascade Range • CIA–K, chemical index of alteration minus potassium • EEMT, effective energy and mass transfer • E_NPP, energy transfer from net primary production • ET_p, potential evapotranspiration • Fe_d/Fe_T, ratio of free iron oxides to total elemental iron • GR, granite • IAEA, International Atomic Energy Administration • MAP, mean annual precipitation • MAT, mean annual temperature • NPP, net primary production • QPEM, quantitative pedogenic energy model • SN, Sierra Nevada Range • SSPM, Sierra San Pedro Martír

This article has been cited by other articles:

				D. J. Field and B. Minasny Comments on "Modeling Energy Inputs to Predict Pedogenic Environments Using Regional Environmental Databases" Soil Sci. Soc. Am. J., May 1, 2008; 72(3): 858 - 859. [Full Text] [PDF]

				C. Rasmussen Response to Comments on "Modeling Energy Inputs to Predict Pedogenic Environments Using Regional Environmental Databases" Soil Sci. Soc. Am. J., May 1, 2008; 72(3): 860 - 860. [Full Text] [PDF]