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United States Department of Agriculture

Agricultural Research Service

Research Project: LANDSCAPE-BASED CROP MANAGEMENT FOR FOOD, FEED, AND BIOENERGY

Location: Cropping Systems and Water Quality Research

Title: Biological indicators of soil quality and soil organic matter characteristics in an agricultural management continuum

Authors
item Veum, Kristen
item Goyne, Keith -
item Kremer, Robert
item Miles, Randall -
item Sudduth, Kenneth

Submitted to: Biogeochemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 4, 2013
Publication Date: January 9, 2014
Citation: Veum, K.S., Goyne, K.W., Kremer, R.J., Miles, R.J., Sudduth, K.A. 2014. Biological indicators of soil quality and soil organic matter characteristics in an agricultural management continuum. Biogeochemistry. 117(1):81-99.

Interpretive Summary: Various practices used in management of our soils for production of food, feed and fiber crops have different effects on soil quality and on long-term sustainability of soils and crop productivity. Soil quality is the ability of soils to function to support sufficient crop production and maintain environmental quality. Integration of management practices that minimize soil disturbance including reduced tillage, retention of vegetative crop remains on the soil surface, and adding organic materials such as composts, manures and living vegetation (cover crops) to soils aid in maintaining or improving soil quality. Thus these practices contribute to the buildup of soil organic matter and preservation of a highly diverse soil microbial community. Soil organic matter is a key soil quality characteristic because its various carbon (C) components are involved in soil physical and chemical properties as well as sustaining the diverse microbial populations that produce a comprehensive suite of enzymes that drive biological processes including decomposition of organic materials and making nutrients available for plant growth. However, we know little about the relationship between long-term agricultural practices, the microbial community, and the dynamics of soil organic matter. In order to better understand impacts of soil management on soil quality, we assessed soil enzyme activity and soil organic C dynamics in soils from a long-term agricultural production site. Soils were collected from Sanborn Field in Columbia, Missouri, where a range of crop production practices are established, some since 1888; and from a nearby native prairie on a similar soil. Two soil enzymes were measured: dehydrogenase, an indicator of overall soil microbial metabolic activity, and phenol oxidase, involved in biodegradation of complex organic compounds and representing decomposition ability of the soil microbial community. The various C components of soil organic matter were determined because these components contribute to different functions within the soil and may be more important in assessing soil quality than simply the overall soil organic matter content. We found that soil enzyme activities were strongly and positively related with these biologically reactive components of soil organic matter as well as soil aggregation. The soil enzyme and C fraction values were considerably higher for soils under native prairie and perennial vegetation in managed grassland/pasture situations compared with those continuously cultivated to corn and wheat crops. Furthermore, when soils were assessed for soil quality using a model (Soil Management Assessment Framework), the soil quality scores again correlated positively with the soil enzyme and C fraction values and soil quality ranked from highest for prairie and grassland soils to lowest for soils under continuous cultivation under corn with no fertilizer or organic amendments. This study demonstrated that soil microbial enzyme activity and soil organic matter quality (measured as different C components) represent critical links between soil management and agricultural sustainability. The results are important for soil scientists, agricultural consultants and extension personnel because they provide valuable information useful in soil and crop management decisions and provide bases for including additional indicators (enzyme activity and C fractions) in soil quality models that will strengthen overall soil quality assessments.

Technical Abstract: Relationships among biological indicators of soil quality and soil organic matter characteristics in a claypan soil were evaluated across a continuum of long-term agricultural practices in Missouri, USA. In addition to chemical and physical soil quality indicators, dehydrogenase and phenol oxidase activity were measured, 13C nuclear magnetic resonance (13C NMR) and diffuse reflectance Fourier transform (DRIFT) spectra of soil organic matter were collected, and visible, near-infrared reflectance (VNIR) spectra of whole soil were collected. Enzyme activities were positively correlated with several soil quality indicators and labile fractions of soil organic matter (r = 0.58 – 0.92), and were negatively correlated with DRIFT indices of decomposition and recalcitrance (r = -0.62 to -0.76). A comparison of crop and fertilization practices corresponded to soil quality scores using the Soil Management Assessment Framework (SMAF) – a soil quality index. Perennial (i.e., native prairie, prairie restoration, and timothy) plots exhibited the greatest soil quality (SMAF scores 98.6 – 93.6), followed by no-till and conventionally cultivated plots, with wheat outranking corn (SMAF scores 92.6 – 65.5). Among fertilization practices, soil quality followed the order: manure > inorganic fertilizer > unamended soil. Finally, in the estimation of soil properties, VNIR spectra generally outperformed DRIFT spectra using partial least squares regression (PLSR) and multiple, linear regression (MLR). The strongest estimates of dehydrogenase and phenol oxidase activity were found using MLR models of VNIR spectra (R2 > 0.78, RPD > 2.20). Overall, this study emphasizes the benefits of maintaining long-term agricultural experiments and demonstrates the potential utility and versatility of enzymes in soil quality modeling.

Last Modified: 11/28/2014
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