Negligible contribution from roots to soil-borne phospholipid fatty acid fungal biomarkers 18:2ω6,9 and 18:1ω9

The phospholipid fatty acid biomarkers 18:1ω9, 18:2ω6,9 and 18:3ω3,6,9 are commonly used as fungal biomarkers in soils. They have, however, also been found to occur in plant tissues, such as roots. Thus, the use of these PLFAs as fungal biomarkers in sieved soil, which may still contain small remains of roots, has been questioned. We used data from a recent beech tree girdling experiment to calculate the contribution of roots to these biomarkers and were able to demonstrate that not more than 0.61% of 18:1ω9 and 18:2ω6,9 in sieved soil samples originated from roots (but 4% of 18:3ω3,6,9). Additionally, the abundance of the biomarker 18:2ω6,9 in the soil was found to be highly correlated to ectomycorrhizal root colonization, which further corroborates its fungal origin. PLFA biomarkers were substantially reduced in vital roots from girdled trees compared to roots of control trees (by up to 76%), indicating that the major part of PLFAs measured in roots may actually originate from ectomycorrhizal fungi growing inside the roots. We calculated, that even a near to 50% reduction in fine root biomass – as observed in the girdling treatment – accounted for only 0.8% of the measured decrease of 18:2ω6,9. Our results demonstrate that both 18:1ω9 and 18:2ω6,9 are suitable biomarkers for detecting fungal dynamics in soils and that especially 18:2ω6,9 is a reliable biomarker to study mycorrhizal dynamics in beech forests

Microbial processes and community composition in the rhizosphere of European beech – The influence of plant C exudates

Plant roots strongly influence C and N availability in the rhizosphere via rhizodeposition and uptake of nutrients. This study aimed at investigating the effect of resource availability on microbial processes and community structure in the rhizosphere. We analyzed C and N availability, as well as microbial processes and microbial community composition in rhizosphere soil of European beech and compared it to the bulk soil. Additionally, we performed a girdling experiment in order to disrupt root exudation into the soil. By this novel approach we were able to demonstrate that enhanced resource availability positively affected N mineralization and hydrolytic enzyme activities in the rhizosphere, but negatively affected nitrification rates and oxidative enzyme activities, which are involved in the degradation of soil organic matter. Both rhizosphere effects on N mineralization and oxidative enzyme activities disappeared in the girdling treatment. Microbial community structure in the rhizosphere, assessed by phospholipid fatty acid analysis, differed only slightly from bulk soil but was markedly altered by the girdling treatment, indicating additional effects of the girdling treatment beyond the reduction of root exudation. Differences in oxidative enzyme activities and nitrification rates between rhizosphere soil and bulk soil, however, suggest considerable differences in the (functional) microbial community composition

Responses of belowground carbon allocation dynamics to extended shading in mountain grassland

Carbon (C) allocation strongly influences plant and soil processes. Short-term C allocation dynamics in ecosystems and their responses to environmental changes are still poorly understood. Using in situ (13)CO(2) pulse labeling, we studied the effects of 1 wk of shading on the transfer of recent photoassimilates between sugars and starch of above- and belowground plant organs and to soil microbial communities of a mountain meadow. C allocation to roots and microbial communities was rapid. Shading strongly reduced sucrose and starch concentrations in shoots, but not roots, and affected tracer dynamics in sucrose and starch of shoots, but not roots: recent C was slowly incorporated into root starch irrespective of the shading treatment. Shading reduced leaf respiration more strongly than root respiration. It caused no reduction in the amount of (13)C incorporated into fungi and Gram-negative bacteria, but increased its residence time. These findings suggest that, under interrupted C supply, belowground C allocation (as reflected by the amount of tracer allocated to root starch, soil microbial communities and belowground respiration) was maintained at the expense of aboveground C status, and that C source strength may affect the turnover of recent plant-derived C in soil microbial communities

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiolog