Post-termination Effects of Cover Crop Monocultures and Mixtures on Soil Inorganic Nitrogen and Microbial Communities on Two Organic Farms in Illinois

Cover crops can continue to affect agricultural systems even after they have been terminated by influencing nitrogen dynamics and by altering soil microbial communities. These post-termination effects can influence soil fertility, weed pressure, and the dynamics of potential plant pathogens in the narrow window of time between cover crop termination and cash crop emergence. We evaluated the post-termination effects of 12 different spring-sown cover crop mixtures and monocultures on soil nitrogen and microbial communities on two different organic farms in Central Illinois (on Lawson silt loam soil) and Northern Illinois (on Virgil silt loam soil). In comparison to control plots with no cover crops, all cover crop treatments significantly reduced soil nitrate levels but increased the potentially mineralizable nitrogen pool following termination. Nitrate levels of cover crop plots approached those of controls after 2 and 4 weeks, respectively, but potentially mineralizable nitrogen levels in cover plots remained elevated for at least 4 weeks following termination. Monocultures of Brassica cover crops showed the greatest decrease in soil nitrate, while Brassicas and unplanted control plots containing high biomass of weeds showed the greatest increase in potentially mineralizable nitrogen in comparison to plant-free control plots. In contrast to their effect on soil nitrogen, cover crops had very limited impact on the composition of soil microbial communities. Overall microbial community composition varied across sites and years, and only soil fungi significantly responded to cover cropping treatments. Nevertheless, we found that some highly correlated groups of soil microbes showed significant responses to soil nitrate and to high plant biomass. Key members of these correlated groups included ammonia-oxidizing organisms and saprotrophic fungi. Our results suggest that cover crops may reduce the potential for springtime nitrogen leaching losses by retaining nitrogen in the soil organic pool, and they may also have impacts on the soil microbial community that are particularly relevant for nitrogen cycling and decomposition of plant residues

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader–microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant

Evaluation of Swine-Specific PCR Assays Used for Fecal Source Tracking and Analysis of Molecular Diversity of Swine-Specific bacteroidales Populations

In this study, we evaluated the specificity, distribution, and sensitivity of Prevotella strain-based (PF163 and PigBac1) and methanogen-based (P23-2) PCR assays proposed to detect swine fecal pollution in environmental waters. The assays were tested against 222 fecal DNA extracts derived from target and nontarget animal hosts and against 34 groundwater and 15 surface water samples from five different sites. We also investigated the phylogenetic diversity of 1,340 Bacteroidales 16S rRNA gene sequences derived from swine feces, swine waste lagoons, swine manure pits, and waters adjacent to swine operations. Most swine fecal samples were positive for the host-specific Prevotella-based PCR assays (80 to 87%), while fewer were positive with the methanogen-targeted PCR assay (53%). Similarly, the Prevotella markers were detected more frequently than the methanogen-targeted assay markers in waters historically impacted with swine fecal contamination. However, the PF163 PCR assay cross-reacted with 23% of nontarget fecal DNA extracts, although Bayesian statistics suggested that it yielded the highest probability of detecting pig fecal contamination in a given water sample. Phylogenetic analyses revealed previously unknown swine-associated clades comprised of clones from geographically diverse swine sources and from water samples adjacent to swine operations that are not targeted by the Prevotella assays. While deeper sequencing coverage might be necessary to better understand the molecular diversity of fecal Bacteroidales species, results of sequence analyses supported the presence of swine fecal pollution in the studied watersheds. Overall, due to nontarget cross amplification and poor geographic stability of currently available host-specific PCR assays, development of additional assays is necessary to accurately detect sources of swine fecal pollution

Evaluation of Swine-Specific PCR Assays Used for Fecal Source Tracking and Analysis of Molecular Diversity of Swine-Specific “Bacteroidales” Populations

In this study, we evaluated the specificity, distribution, and sensitivity of Prevotella strain-based (PF163 and PigBac1) and methanogen-based (P23-2) PCR assays proposed to detect swine fecal pollution in environmental waters. The assays were tested against 222 fecal DNA extracts derived from target and nontarget animal hosts and against 34 groundwater and 15 surface water samples from five different sites. We also investigated the phylogenetic diversity of 1,340 “Bacteroidales” 16S rRNA gene sequences derived from swine feces, swine waste lagoons, swine manure pits, and waters adjacent to swine operations. Most swine fecal samples were positive for the host-specific Prevotella-based PCR assays (80 to 87%), while fewer were positive with the methanogen-targeted PCR assay (53%). Similarly, the Prevotella markers were detected more frequently than the methanogen-targeted assay markers in waters historically impacted with swine fecal contamination. However, the PF163 PCR assay cross-reacted with 23% of nontarget fecal DNA extracts, although Bayesian statistics suggested that it yielded the highest probability of detecting pig fecal contamination in a given water sample. Phylogenetic analyses revealed previously unknown swine-associated clades comprised of clones from geographically diverse swine sources and from water samples adjacent to swine operations that are not targeted by the Prevotella assays. While deeper sequencing coverage might be necessary to better understand the molecular diversity of fecal Bacteroidales species, results of sequence analyses supported the presence of swine fecal pollution in the studied watersheds. Overall, due to nontarget cross amplification and poor geographic stability of currently available host-specific PCR assays, development of additional assays is necessary to accurately detect sources of swine fecal pollution

An Affinity–Effect Relationship for Microbial Communities in Plant–Soil Feedback Loops

Feedback loops involving soil microorganisms can regulate plant populations. Here, we hypothesize that microorganisms are most likely to play a role in plant–soil feedback loops when they possess an affinity for a particular plant and the capacity to consistently affect the growth of that plant for good or ill. We characterized microbial communities using whole-community DNA fingerprinting from multiple "home-and-away" experiments involving giant ragweed (Ambrosia trifida L.) and common sunflower (Helianthus annuus L.), and we looked for affinity–effect relationships in these microbial communities. Using canonical ordination and partial least squares regression, we developed indices expressing each microorganism's affinity for ragweed or sunflower and its putative effect on plant biomass, and we used linear regression to analyze the relationship between microbial affinity and effect. Significant linear affinity–effect relationships were found in 75% of cases. Affinity–effect relationships were stronger for ragweed than for sunflower, and ragweed affinity–effect relationships showed consistent potential for negative feedback loops. The ragweed feedback relationships indicated the potential involvement of multiple microbial taxa, resulting in strong, consistent affinity–effect relationships in spite of large-scale microbial variability between trials. In contrast, sunflower plant–soil feedback may involve just a few key players, making it more sensitive to underlying microbial variation. We propose that affinity–effect relationship can be used to determine key microbial players in plant–soil feedback against a low "signal-to-noise" background of complex microbial datasets

Changes in N-Transforming Archaea and Bacteria in Soil during the Establishment of Bioenergy Crops

Widespread adaptation of biomass production for bioenergy may influence important biogeochemical functions in the landscape, which are mainly carried out by soil microbes. Here we explore the impact of four potential bioenergy feedstock crops (maize, switchgrass, Miscanthus X giganteus, and mixed tallgrass prairie) on nitrogen cycling microorganisms in the soil by monitoring the changes in the quantity (real-time PCR) and diversity (barcoded pyrosequencing) of key functional genes (nifH, bacterial/archaeal amoA and nosZ) and 16S rRNA genes over two years after bioenergy crop establishment. The quantities of these N-cycling genes were relatively stable in all four crops, except maize (the only fertilized crop), in which the population size of AOB doubled in less than 3 months. The nitrification rate was significantly correlated with the quantity of ammonia-oxidizing archaea (AOA) not bacteria (AOB), indicating that archaea were the major ammonia oxidizers. Deep sequencing revealed high diversity of nifH, archaeal amoA, bacterial amoA, nosZ and 16S rRNA genes, with 229, 309, 330, 331 and 8989 OTUs observed, respectively. Rarefaction analysis revealed the diversity of archaeal amoA in maize markedly decreased in the second year. Ordination analysis of T-RFLP and pyrosequencing results showed that the N-transforming microbial community structures in the soil under these crops gradually differentiated. Thus far, our two-year study has shown that specific N-transforming microbial communities develop in the soil in response to planting different bioenergy crops, and each functional group responded in a different way. Our results also suggest that cultivation of maize with N-fertilization increases the abundance of AOB and denitrifiers, reduces the diversity of AOA, and results in significant changes in the structure of denitrification community

Geographic and Environmental Sources of Variation in Lake Bacterial Community Composition

This study used a genetic fingerprinting technique (automated ribosomal intergenic spacer analysis [ARISA]) to characterize microbial communities from a culture-independent perspective and to identify those environmental factors that influence the diversity of bacterial assemblages in Wisconsin lakes. The relationships between bacterial community composition and 11 environmental variables for a suite of 30 lakes from northern and southern Wisconsin were explored by canonical correspondence analysis (CCA). In addition, the study assessed the influences of ARISA fragment detection threshold (sensitivity) and the quantitative, semiquantitative, and binary (presence-absence) use of ARISA data. It was determined that the sensitivity of ARISA was influential only when presence-absence-transformed data were used. The outcomes of analyses depended somewhat on the data transformation applied to ARISA data, but there were some features common to all of the CCA models. These commonalities indicated that differences in bacterial communities were best explained by regional (i.e., northern versus southern Wisconsin lakes) and landscape level (i.e., seepage lakes versus drainage lakes) factors. ARISA profiles from May samples were consistently different from those collected in other months. In addition, communities varied along gradients of pH and water clarity (Secchi depth) both within and among regions. The results demonstrate that environmental, temporal, regional, and landscape level features interact to determine the makeup of bacterial assemblages in northern temperate lakes