Factors affecting soil microbial community structure in tomato cropping systems

Buyer, Jeffrey S.; Teasdale, John R.; Roberts, Daniel P.; Zasada, Inga A.; Maul, Jude E.

doi:10.1016/j.soilbio.2010.01.020

Cited by 272 publications

(138 citation statements)

References 61 publications

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“…Soil PLFA extraction and purification followed the methods described by Chen et al (2013), which was modified from Buyer et al (2010). A gas chromatograph with flame ionization detector (GCeFID) (HP 6890, Agilent Technologies, Santa Clara, CA) was used to separate fatty acid methyl esters.…”

Section: Plfa Analysismentioning

confidence: 99%

Soil organic carbon and soil structure are driving microbial abundance and community composition across the arid and semi-arid grasslands in northern China

Hu¹,

Xiang²,

Veresoglou³

et al. 2014

Soil Biology and Biochemistry

171

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a b s t r a c tMicrobial biogeography through the study of the assembly rules of microbes has the potential to yield ecological information that is generalizable for a wide range of microorganisms. Here we performed a large-scale field investigation of the distribution patterns of microbes across the arid and semi-arid grassland ecosystems covering an area of 690,000 km 2 in northern China. Soil microbial abundance and community composition were examined through quantifying microbial phospholipid fatty acids (PLFAs) at fifty sampling sites along environmental gradients. A multi-model inference analysis identified soil organic carbon (SOC) as a key driving factor for microbial biomass and quantified its effect. Structural equation models (SEM) were further fitted to the data to provide a better mechanistic resolution of direct and indirect pathways that connected PLFAs and environmental variables. The SEM analysis also supported that SOC was the main positive predictor of microbial biomass, while MAT served as the main negative factor via an indirect pathway. To visualize complex relationships between microbial community and environmental variables we engaged in a redundancy analysis. The result showed that PLFA profiles could be largely explained by the soil variables including soil structure (PSD) and pH. Overall, our report through the analysis of an unprecedented amount of primary data yields unique insights into the relative importance of abiotic factors in shaping microbial communities at large scales.

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Section: Plfa Analysismentioning

confidence: 99%

Soil organic carbon and soil structure are driving microbial abundance and community composition across the arid and semi-arid grasslands in northern China

Hu¹,

Xiang²,

Veresoglou³

et al. 2014

Soil Biology and Biochemistry

171

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“…The biomass and composition of the soil microbial community was measured using PLFA analysis with a modified Buyer method (Buyer et al, 2010). Four grams of lyophilized soil was placed in a 30-mL glass centrifuge tube with a Teflon-lined screw cap.…”

Section: Phospholipid Fatty Acid Analysismentioning

confidence: 99%

Soil microbial community structure and function responses to successive planting of Eucalyptus

Chen

Zheng

Zhang

et al. 2013

Journal of Environmental Sciences

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Many studies have shown soil degradation after the conversion of native forests to exotic Eucalyptus plantations. However, few studies have investigated the long-term impacts of short-rotation forestry practices on soil microorganisms. The impacts of Eucalyptus successive rotations on soil microbial communities were evaluated by comparing phospholipid fatty acid (PLFA) abundances, compositions, and enzyme activities of native Pinus massoniana plantations and adjacent 1st, 2nd, 3rd, 4th generation Eucalyptus plantations. The conversion from P. massoniana to Eucalyptus plantations significantly decreased soil microbial community size and enzyme activities, and increased microbial physiological stress. However, the PLFA abundances formed "∪" shaped quadratic functions with Eucalyptus plantation age. Alternatively, physiological stress biomarkers, the ratios of monounsaturated to saturated fatty acid and Gram+ to Gram-bacteria, formed "∩" shaped quadratic functions, and the ratio of cy17:0 to 16:1ω7c decreased with plantation age. The activities of phenol oxidase, peroxidase, and acid phosphatase increased with Eucalyptus plantation age, while the cellobiohydrolase activity formed "∪" shaped quadratic functions. Soil N:P, alkaline hydrolytic nitrogen, soil organic carbon, and understory cover largely explained the variation in PLFA profiles while soil N:P, alkaline hydrolytic nitrogen, and understory cover explained most of the variability in enzyme activity. In conclusion, soil microbial structure and function under Eucalyptus plantations were strongly impacted by plantation age. Most of the changes could be explained by altered soil resource availability and understory cover associated with successive planting of Eucalyptus. Our results highlight the importance of plantation age for assessing the impacts of plantation conversion as well as the importance of reducing disturbance for plantation management.

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“…Likewise, Gonzalez-Chavez et al, (2010) reported that NT soils had nearly double contents of MBC and microbial biomass nitrogen as compared to CT. Dong et al, 2009 also reported that the mean annual MBC was highest in the ZT with residue, while lowest in CT without residue. Similarly, Silva et al, 2010 consistently found higher values of MBC and microbial biomass nitrogen up to more than 100 % under NT in comparison to CT. NT soils with crop residue addition had more available substrates than CT and this promotes microbial growth and assimilation of nutrients, leading to an increase in soil microbial biomass and activity of such soils (Buyer et al, 2010). Cartert and Rennie, 1982 observed that the surface depth under zero tillage was enriched in MBC which was l4-28% higher in comparison to the corresponding depth under CT, while the reverse phenomenon was observed at lower depths.…”

Section: Microbial Biomass Carbon (Mbc)mentioning

confidence: 99%