Spatial structure in soil chemical and microbiological properties in an upland grassland

Abstract

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.

Assessment of mycorrhizal colonisation and soil nutrients in unmanaged fire-impacted soils from two target restoration sites

“…The C:N ratio at Site 2 (more recently exposed to fire) was significantly different and higher than at Site 1, probably due to the upward movement of organic compounds caused by the transfer of heat downwards after the fire event (DeBano, 2000). The positive correlations between total N and total organic C contents suggest common microscale variability for these chemical properties (Ritz et al, 2004). High levels of spatial heterogeneity in soil chemical properties were found, confirming what was reported for other ecosystems (Jackson and Caldwell, 1993;Gross et al, 1995;Ritz et al, 2004).…”

Stochastic distribution of small soil eukaryotes resulting from high dispersal and drift in a local environment

“…Soil pH and N may be spatially autocorrelated up to 5 m (Ettema and Wardle, 2002;Pärtel et al, 2008;Baldrian et al, 2010). Besides the great spatial variability of soil nutrients and pH that is commonly observed in forest soil (Ettema and Wardle, 2002;Štursová and Baldrian, 2011), soil microbial biomass may also be spatially autocorrelated up to 10 m (Ritz et al, 2004), which may affect soil spatial heterogeneity and in turn microbial communities (Lauber et al, 2009). The neighbourhood effect of trees and influence of understorey vegetation were relatively more important in shaping communities of biotrophic fungi rather than freeliving organisms.…”

Genetic and Functional Diversities of Microbial Communities in Amazonian Soils Under Different Land Uses and Cultivation

“…The variation in the composition of microbial community DNA between replicate soil samples was found to be as great as the variation between treatments in field based studies. The reasons for such variability are not clear, however it is likely that are attributable to the effect of soil chemical attributes plus the contents and composition of organic matter (Clayton et al, 2005;Ritz et al, 2004). According to the authors the DGGE profiling revealed lower number of bands per area in the dry season, but differences in the genetic diversity of bacterial communities along the sequence forest to pasture was better defined than for wet season.…”