Tuesday, 7 October 2008: 8:30 AM
George R. Brown Convention Center, 370C
Phospholipid ester-linked fatty acids (PLFA) were analyzed to fingerprint soil microbial communities under different tillage, residue, and crop rotation treatments of a long-term experiment established in 1991. After 16 years, no-till and residue retention both increased soil total C, total N, and microbial biomass compared to tillage and residue removed treatment, respectively. Crop rotation did not show significant effect on total N and total PLFA, but the treatment of annual maize-wheat rotation had the highest total C value while continuous maize had the lowest total C. Both tillage and residue management had significant impact on the abundance of PLFA as well as community structure of soil microorganisms. In most of the cases, no-till treatment had an average amount of individual PLFA higher than tillage treatment. Similarly, the mean residue retained treatment had a higher amount of most individual PLFA than without residue treatment. No-till combined with residue retention was a most efficient way to increase soil C, N, and microbial biomass levels. We also found that three PLFAs, a17:0, 18:1ω9, and 18:0, were not influenced by any of the treatments. They appeared to be most insensitive to management changes. About half of the PLFAs were affected by cropping types, among them, mostly were gram positive bacteria and actinomyces. Fungi and arbuscular mycorrhizal (AM) fungi were not affected. Tillage increased the ratios of total fungi/total bacteria and total fungi/total PLFA whiled decreased the ratios of actinomycetes/total PLFA and bacteria/total PLFA. Residue retention increased the ratio of gram-negative bacteria (Gm-)/total PLFA but decreased actinomycets/total PLFA. Seven PLFA: i15:0, a15:0, i16:0, a17:0, 16:0, 18:1ω9, and 16:0ω5 were identified by principal component analysis as the most important in explaining the variation among microbial communities and Gm+ is the single most important group. Soil microbial communities were definitively separated by tillage and residue treatments with tillage had the most discriminatory power. With and without residue were much better differentiated in no-till treatment than in tillage treatment. CART analysis revealed the predicting power of PLFA to tillage and residue treatments. Just based on two PLFA: 10Me17:0 and 18:1ω7, the observed microbial communities could be classified into different tillage treatments with 97% of accuracy.