Statistical analysis of reduction in tensile strength of cotton strips as a measure of soil microbial activity

The cotton strip assay (CSA) is an established technique for measuring soil microbial activity. The technique involves burying cotton strips and measuring their tensile strength after a certain time. This gives a measure of the rotting rate, R, of the cotton strips. R is then a measure of soil microbial activity. This paper examines properties of the technique and indicates how the assay can be optimised. Humidity conditioning of the cotton strips before measuring their tensile strength reduced the within and between day variance and enabled the distribution of the tensile strength measurements to approximate normality. The test data came from a three-way factorial experiment (two soils, two temperatures, three moisture levels). The cotton strips were buried in the soil for intervals of time ranging up to 6 weeks. This enabled the rate of loss of cotton tensile strength with time to be studied under a range of conditions. An inverse cubic model accounted for greater than 90% of the total variation within each treatment combination. This offers support for summarising the decomposition process by a single parameter R. The approximate variance of the decomposition rate was estimated from a function incorporating the variance of tensile strength and the differential of the function for the rate of decomposition, R, with respect to tensile strength. This variance function has a minimum when the measured strength is approximately 2/3 that of the original strength. The estimates of R are almost unbiased and relatively robust against the cotton strips being left in the soil for more or less than the optimal time. We conclude that the rotting rate X should be measured using the inverse cubic equation, and that the cotton strips should be left in the soil until their strength has been reduced to about 2/3.

Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.

Microbial indicators related to yield and disease and changes in soil microbial community structure with ginger farm management practices

TRFLP (terminal restriction fragment length polymorphism) was used to assess whether management practices that improved disease suppression and/or yield in a 4-year ginger field trial were related to changes in soil microbial community structure. Bacterial and fungal community profiles were defined by presence and abundance of terminal restriction fragments (TRFs), where each TRF represents one or more species. Results indicated inclusion of an organic amendment and minimum tillage increased the relative diversity of dominant fungal populations in a system dependant way. Inclusion of an organic amendment increased bacterial species richness in the pasture treatment. Redundancy analysis showed shifts in microbial community structure associated with different management practices and treatments grouped according to TRF abundance in relation to yield and disease incidence. ANOVA also indicated the abundance of certain TRFs was significantly affected by farming system management practices, and a number of these TRFs were also correlated with yield or disease suppression. Further analyses are required to determine whether identified TRFs can be used as general or soil-type specific bio-indicators of productivity (increased and decreased) and Pythium myriotylum suppressiveness.

Responses of soil microbial communities to clonal variation of Norway spruce

In boreal forests, microorganisms have a pivotal role in nutrient and water supply of trees as well as in litter decomposition and nutrient cycling. This reinforces the link between above-ground and below-ground communities in the context of sustainable productivity of forest ecosystems. In northern boreal forests, the diversity of microbes associated with the trees is high compared to the number of distinct tree species. In this thesis, the aim was to study whether conspecific tree individuals harbour different soil microbes and whether the growth of the trees and the community structure of the associated microbes are connected. The study was performed in a clonal field trial of Norway spruce, which was established in a randomized block design in a clear-cut area. Since out-planting in 1994, the spruce clones showed two-fold growth differences. The fast-growing spruce clones were associated with a more diverse community of ectomycorrhizal fungi than the slow-growing spruce clones. These growth performance groups also differed with respect to other aspects of the associated soil microorganisms: the species composition of ectomycorrhizal fungi, in the amount of extraradical fungal mycelium, in the structure of bacterial community associated with the mycelium, and in the structure of microbial community in the organic layer. The communities of fungi colonizing needle litter of the spruce clones in the field did not differ and the loss of litter mass after two-years decomposition was equal. In vitro, needles of the slow-growing spruce clones were colonized by a more diverse community of endophytic fungi that were shown to be significant needle decomposers. This study showed a relationship between the growth of Norway spruce clones and the community structure of the associated soil microbes. Spatial heterogeneity in soil microbial community was connected with intraspecific variation of trees. The latter may therefore influence soil biodiversity in monospecific forests.

Soil microbial community analysis using denaturing gradient gel electrophoresis

The most biological diversity on this planet is probably harbored in soils. Understanding the diversity and function of the microbiological component of soil poses great challenges that are being overcome by the application of molecular biological approaches. This review covers one of many approaches being used: separation of polymerase chain reaction (PCR) amplicons using denaturing gradient gel electrophoresis (DGGE). Extraction of nucleic acids directly from soils allows the examination of a community without the limitation posed by cultivation. Polymerase chain reaction provides a means to increase the numbers of a target for its detection on gels. Using the rRNA genes as a target for PCR provides phylogenetic information on populations comprising communities. Fingerprints produced by this method have allowed spatial and temporal comparisons of soil communities within and between locations or among treatments. Numerous samples can be compared because of the rapid high throughput nature of this method. Scientists now have the means to begin addressing complex ecological questions about the spatial, temporal, and nutritional interactions faced by microbes in the soil environment.

Soil microbial community analysis using terminal restriction fragment length polymorphisms

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a polymerase chain reaction (PCR)-fingerprinting method that is commonly used for comparative microbial community analysis. The method can be used to analyze communities of bacteria, archaea, fungi, other phylogenetic groups or subgroups, as well as functional genes. The method is rapid, highly reproducible, and often yields a higher number of operational taxonomic units than other, commonly used PCR-fingerprinting methods. Sizing of terminal restriction fragments (T-RFs) can now be done using capillary sequencing technology allowing samples contained in 96- or 384-well plates to be sized in an overnight run. Many multivariate statistical approaches have been used to interpret and compare T-RFLP fingerprints derived from different communities. Detrended correspondence analysis and the additive main effects with multiplicative interaction model are particularly useful for revealing trends in T-RFLP data. Due to biases inherent in the method, linking the size of T-RFs derived from complex communities to existing sequence databases to infer their taxonomic position is not very robust. This approach has been used successfully, however, to identify and follow the dynamics of members within very simple or model communities. The T-RFLP approach has been used successfully to analyze the composition of microbial communities in soil, water, marine, and lacustrine sediments, biofilms, feces, in and on plant tissues, and in the digestive tracts of insects and mammals. The T-RFLP method is a user-friendly molecular approach to microbial community analysis that is adding significant information to studies of microbial populations in many environments.