|NEUPANE, J - Texas Tech University|
|GUO, W - Texas Tech University|
|ZHANG, F - Texas Tech University|
|LIN, Z - Texas Tech University|
|CANO, A - Texas Tech University|
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/21/2019
Publication Date: 11/11/2019
Citation: Neupane, J., Guo, W., Acosta Martinez, V., Zhang, F., Lin, Z., Cano, A. 2019. Assessing spatial pattern of soil microbial community at landscape scale for precision soil management. ASA-CSSA-SSSA Annual Meeting Abstracts. 1.
Technical Abstract: The soil microbial community structure at the landscape scale is complicated by the interactions among topography, soil type and distribution of water in the field. The spatial and temporal distribution of soil microorganisms in the field can influence plant growth and possibly yield. Therefore, understanding the distribution of soil microbes in the field and factors influencing this distribution is a prerequisite for soil health assessment and site-specific management to improve crop production. The objectives of this study were to: 1) characterize the soil microbial community distribution at field scale; 2) assess the influence of soil physicochemical properties and topography on soil microbial distribution. This study was conducted in a 194-ha commercially managed field in Hale County, Texas in 2017 and 2018. A total of 230 composite soil samples were collected at the depth of 0-15 cm and analyzed for microbial community structure using the fatty acid methyl ester (FAME) method. Soil electrical conductivity (EC), elevation, slope, pH, soil texture, soil water content (SWC), total soil organic carbon (SOC) and total nitrogen (TN) were determined for the field. A statistical model was then developed to assess soil microbial distribution as influenced by soil physicochemical properties and topography. Results showed that total microbes in the field were significantly related to SWC, SOC and elevation. Gram positive, gram negative and actinobacteria were significantly related to soil texture. Arbuscular Mycorrhizal Fungi (AMF) distribution was also related to clay and SOC as well as interaction between sand and slope. Saprophytic fungi were mostly related to SWC and C: N ratio. This model helps to identify spatial and temporal variability of microbial community and biomass in relation to soil physicochemical properties, SWC, EC, elevation and slope. Results of this study has the potential to enhance site-specific soil health management.