/AnMtgsAbsts2009.52951 Assessing Linkages Between Soil Chemical Properties and Microbial Activity.

Monday, November 2, 2009
Convention Center, Exhibit Hall BC, Second Floor

Rongzhong Ye, Univ. of Florida, Gainesville, FL, Alan Wright, Everglades Research & Education Center, Univ. of Florida, Belle Glade, FL and K. R. Reddy, Wetland Biogeochemistry Laboratory, Univ. of Florida, Gainesville, FL
Abstract:
Soil physical-chemical properties and microbial activity are key components of ecosystem function.  Net results of reciprocal interactions between the two define ecosystem processes.  The objectives were to determine whether different land management practices resulted in contrasting soil chemical properties and to evaluate how variances in chemical properties regulate microbial activity. Soil was evaluated from three land uses with distinct land management history: sugarcane, cypress, and uncultivated soil. Cluster analysis (CA) was used to classify soil properties by land use while principal component analysis (PCA) was used to detect dissimilarity of carbon utilization patterns.  Discriminant function analysis (DA) was conducted to determine differences in enzyme activities among land uses.  Canonical correlation analysis (CCA) was employed to identify and assess linkages between soil chemical properties and microbial activity.  Soil samples were perfectly clustered into three groups based on chemical properties.  The Na2CO3-P (r2 = 0.91), K2SO4-NH4 (r2 = 0.87), and dissolved organic carbon (r2 = 0.86) contributed most to the classification.  Two principal components (PCs) were extracted and explained 40% of the variance in carbon utilization efficiency.  Principal component 2 clearly separated the uncultivated sites from sugarcane and cypress.  Canonical variate 1 (87%) and 2 (79%) separated land uses by overall enzyme activities.  The PCA reduced 11 chemical variables to 2 principal components representing 72% of the variance.  The Na2CO3-P had the highest correlation coefficient (r2 = -0.93) with PC1.  Two components were extracted from seven microbial variables to catch 75% of the variance of microbial activities.  Canonical correlation between soil chemical properties and microbial activities was strong (r2 = 0.89, p = 0.005).  Approximately 80% of the variance in microbial activity was explained by soil chemical properties in the first pair of canonical variates.  Overall, different land management practices resulted in distinct chemical distributions in soil and consequently altered microbial activities.