|Van Pelt, Robert - Scott|
Submitted to: International Symposium on Soil Erosion and Dryland Farming
Publication Type: Abstract Only
Publication Acceptance Date: 2/22/2006
Publication Date: 10/1/2006
Citation: Zobeck, T.M., Van Pelt, R.S., Acosta Martinez, V., Bronson, K.F., Upchurch, D.R., Crownover, J. 2006. Assessing the effects of land managementusing the soil conditioning index as a soil quality assessment tool[CD-ROM]. International Symposium on Soil Erosion and Dryland Farming. October 1-5, 2006. Yangling, Shaanxi, People's Republic of China.
Technical Abstract: As new questions and concerns arise concerning our ability to sustain our limited land and water resources, the importance of adequate assessment tools for evaluating the effects of land management practices on soil, air, and water resources grows. In some instances, soil quality assessment tools have been used to promote conservation practices among land users. The United States Department of Agriculture, Natural Resources Conservation Service (NRCS) has proposed the Soil Conditioning Index (SCI) to predict the consequences of management actions on the state of soil organic carbon (SOC), a soil quality indicator. The SCI is used to determine enrollment eligibility for the USDA conservation program known as the Conservation Security Program, an important voluntary program that provides financial and technical assistance to promote the conservation and improvement of soil, water, air, energy, plant and animal life, and other conservation purposes on Tribal and private working lands. The SCI predicts qualitative changes in soil organic matter and considers biomass produced and returned to the soil, the influence of climate on organic matter decay, and the influence of tillage practices and erosion. In practice, the tool is applied at the field level using computer spreadsheets or software programs that include estimates of residue returned to the soil, tillage intensity, and wind and water erosion estimates. In this study, we relate SCI with measured SOC, particulate organic matter carbon content (POM-C), nitrogen content, and wet aggregate stability (WAS) in semiarid, thermic, sandy soils under a variety of land management practices. Forty-six study sites were identified in the Southern High Plains of west Texas where long-term native rangelands or conservation grasslands were adjacent to cropped land. Management systems included native rangeland, conservation grassland, cotton, wheat, wheat-cotton rotation, sorghum, high residue sorghum/forages, sunflowers, and black eyed peas. The cropland included dryland and irrigated crops. Samples were collected at depths 0 to 5-cm and 5 to10-cm on three replications of each site. Soil property data for the 0 to 10-cm depths were combined to make comparisons with SCI values by cropping systems. Carbon and nitrogen was measured with a CN analyzer. Bulk density, measured by the core method, was used to determine the values of selected soil variables on a mass basis. Correlation coefficients of SCI with C mass (Mg ha-1), N mass (Mg ha-1), POM-C (Mg ha-1), and WAS (%) were 0.22, 0.43, 0.56 and 0.59, respectively. All native rangelands and conservation grasslands and no-tillage fields (dryland and irrigated) had positive SCI values, which indicates increasing organic matter levels. In contrast, all of the conventionally-tilled cotton fields had negative SCI values, indicating decreasing organic matter levels. Fields with a wheat cover crop that was subsequently chemically killed before cotton planting had positive and negative SCI values. The SCI does seem to be a useful soil quality assessment tool but it must be used with caution. The SCI was not related to total SOC in this study, but did show significant correlations with POM-C and WAS. The SCI successfully identified fields with the highest levels of SOC and when no-tillage management was practiced but had difficulty in distinguishing among fields when the same cover crop was used with limited tillage (terminated wheat cover in cotton). Additional research is needed to adjust the SCI sub-factors to better relate the index with SOC.