Spatial structure in soil chemical and microbiological properties in an upland grassland
Karl Ritz, James W. McNicol, Naoise Nunan, S. J. Grayston, Peter Millard, David Atkinson, Armelle Gollotte, David Habeshaw 等 15 位
Cranfield University Biomathematics and Statistics Scotland Scottish Agricultural Science Agency University of Aberdeen
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
We characterised the spatial structure of soil microbial communities in an unimproved grazed upland grassland in the Scottish Borders. A range of soil chemical parameters, cultivable microbes, protozoa, nematodes, phospholipid fatty acid (PLFA) profiles, community-level physiological profiles (CLPP), intra-radical arbuscular mycorrhizal community structure, and eubacterial, actinomycete, pseudomonad and ammonia-oxidiser 16S rRNA gene profiles, assessed by denaturing gradient gel electrophoresis (DGGE) were quantified. The botanical composition of the vegetation associated with each soil sample was also determined. Geostatistical analysis of the data revealed a gamut of spatial dependency with diverse semivariograms being apparent, ranging from pure nugget, linear and non-linear forms. Spatial autocorrelation generally accounted for 40-60% of the total variance of those properties where such autocorrelation was apparent, but accounted for 97% in the case of nitrate-N. Geostatistical ranges extending from approximately 0.6-6 m were detected, dispersed throughout both chemical and biological properties. CLPP data tended to be associated with ranges greater than 4.5 m. There was no relationship between physical distance in the field and genetic similarity based on DGGE profiles. However, analysis of samples taken as close as 1 cm apart within a subset of cores suggested some spatial dependency in community DNA-DGGE parameters below an 8 cm scale. Spatial correlation between the properties was generally weak, with some exceptions such as between microbial biomass C and total N and C. There was evidence for scale-dependence in the relationships between properties. PLFA and CLPP profiling showed some association with vegetation composition, but DGGE profiling did not. There was considerably stronger association between notional sheep urine patches, denoted by soil nutrient status, and many of the properties. These data demonstrate extreme spatial variation in community-level microbiological properties in upland grasslands, and that despite considerable numeric ranges in the majority of properties, overarching controlling factors were not apparent.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
生物医学Soil Carbon and Nitrogen Dynamics
Soil and Water Nutrient Dynamics · Microbial Community Ecology and Physiology
参考文献 61
此处列出前 3 条
引用本文 188
按被引量排序,此处列出前 3 条