Microbial hotspots represent the soil volume where process rates are increased compared to bulk soil. Therefore, microbial hotspots drive nutrient cycling in soil and affect nutrient availability for crops.
Due to their high relevance a direct identification and characterization of microbial hotspots would be desirable, but often they cannot be well identified morphologically. Therefore, molecular apporaches, which enable not only the quantification of microbial hotspots versus bulk soil volume but also the differentiation of single hotspots would be favorable. In this dissertation a classical biomarker class, the fatty acids, were investigated in microbial hotspots. It could be demonstrated that classical molecular proxies like the average chain length or the carbon preference index did not reveal a clear differentiation of microbial hotspots, because complex processes during the formation of microbial hotspots lead to an overprinting of the fatty acid fingerpring of the original C source by various transformations that finally form the hotspot OM. However, using multivariate statistical approaches, a linear discriminant model, enabled a siginificant differentiation of distinct microbial hotspot OM with unsaturated fatty acids and dicarboxylic acids being most important. However, to finally categorize OM of unknown origin into drilosphere, rhizosphere and bulk soil OM requires the evaluation of the linear discriminant model based on various soils from other sites and ecosystems. To understand the molecular pattern underlying the separation power of linear discrimant functions request a validation using biopore OM produced under controlled conditions.
This complexity in biopore OM sources and transformation demonstrates the complex interactions of processes occurring in microbial hotspots such as biopores. This process complexity can even be observed if only a single type of a microbial hotspot, e.g. the rhizosphere, is investigated along depth gradients or between different plant species. The investigation of rhizosphere properties along a depth gradient demonstrated that the ability of individual plant species to maintain microbial hotspots is strongly deviating. The comparison between taprooted plants, alfalfa and chicory, clearly suggests that the ability to form microbial hotspots is related to growth and especially to belowground C allocation. The investment of recent C into belowground biomass growth and rhizodepostition by alfalfa exceeded that of chicory 8 times. The continuous C investment into subsoil not just stimulates
microbial decomposition functions in subsoil due to the input of more substantial C sources.
This was not found in chicory subsoil as the main part of root biomass and the investment of recent C into root growth and rhizodeposition were focused in topsoil.
Besides of net growth also the shape of the root system strongly affects the hotspot distribution in soil. Deeper rooting of plants and the subsequent increase in subsoil plant biomass strongly reduced the generally decreasing gradient in microbial biomass with depth.
To evaluate whether this increase in hotspot abundance and biopore formation in deep subsoil by precrops will lead to an increased nutrition from subsoil-mobilized nutrients requires further experiments with controlled crop sequencing and multiple-isotope labeling approaches for tracing input and re-mobilization of subsoil OM.
To understand the relevance and role of microbial hotspots for nutrient cycling it is crucial to understand the extend of the soil volume with increased process rates and to know the gradients with which the process rates decrease towards bulk soil. Therefore, this dissertation aimed not only at describing depth-related changes in hotspot properties but also their lateral extend in top- and subsoil. The diffusion distance of root exudates was equal in top- and subsoil rhizosphere although it was expected that root exudates will be decomposed faster under topsoil properties due to higher microbial activity resulting in lower exudate extent.
Concluding, the spatial distribution and therefore the soil volume affected by root exudates is equal in top- and subsoil as higher root exudation into topsoil rhizosphere is compensated by higher microbial decomposition. Root exudates were found at a distance of 28 mm (DO14C) and 20 mm (TO14C) from the root surface and therefore exceeded previously reported distances. Higher 14C activity used for labeling compared with previous studies enabled the detection of low exudate concentrations at longer distances from the root surface.
The maintenance of microbial aerobic respiration and the related process rates depend on O2
supply towards the root surface. Within this thesis it was shown that the rhizosphere effect on O2 gradients was independent from microbial activity. Soil water content clearly governed O2
supply for sustaining aerobic respiration. No limitation in O2 supply towards the root surface was found below a matric potential of -200 hPa.
Although it is known that arbuscular mycorrhizal symbioses extends the soil volume affected by root activity the experimental setup failed in determining this effect, presumably due to a lack in mycorrhization. To determine the effect of the extent of the rhizosphere into the mycorrhizosphere, experiments based on inoculation of the plants with arbuscular
mycorrhizal fungi and the measurement of root-derived C in external hyphae extracted from soil are required. Generally, the parameters of the lateral gradients determined by T-pot model systems would be desirable to measure in different soil depth directly at distinct functional root parts at roots growing through soil to finally assess hotspot extend and dynamic under field conditions.
Finally, this dissertation demonstrated the complexity in hotspot processes and dynamics: An intensification of studies is needed to assess C and nutrient inputs, its microbially-mediated transformation dynamics and the resulting nutrient mobilization. This is especially important as these processes strongly depend on biotic factors like plant root properties and abiotic factors like water potential. To finally assess and predict the role of such hotspots for soil process modelling, more detailed investigations on their spatial distribution, their extend, their lifespan and their C and nutrient dynamic are required.