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Summary Soils provide a heterogeneous environment varying in space and time; consequently, the biodiversity of soil microorganisms also differs spatially and temporally. For soil microbes tightly associated with plant roots, such as arbuscular mycorrhizal fungi (AMF), the diversity of plant partners and seasonal variability in trophic exchanges between the symbionts introduce additional heterogeneity. To clarify the impact of such heterogeneity, we investigated spatiotemporal variation in AMF diversity on a plot scale (10 × 10 m) in a grassland managed at low intensity in southwest Germany. AMF diversity was determined using 18S rDNA pyrosequencing analysis of 360 soil samples taken at six time points within a year. We observed high AMF alpha‐ and beta‐diversity across the plot and at all investigated time points. Relationships were detected between spatiotemporal variation in AMF OTU richness and plant species richness, root biomass, minimal changes in soil texture and pH. The plot was characterized by high AMF turnover rates with a positive spatiotemporal relationship for AMF beta‐diversity. However, environmental variables explained only ≈20% of the variation in AMF communities. This indicates that the observed spatiotemporal richness and community variability of AMF was largely independent of the abiotic environment, but related to plant properties and the cooccurring microbiome.

Land‐use intensification drives changes in microbial communities and the soil functions they regulate, but the mechanisms underlying these changes are poorly understood as land use can affect soil communities both directly (e.g. via changes in soil fertility) and indirectly (e.g. via changes in plant inputs). The speed of microbial responses is also poorly understood. For instance, whether it is long‐term legacies or short‐term changes in land‐use intensity that drive changes in microbial communities. To address these topics, we measured multiple microbial functions, bacterial and fungal biomass and abiotic soil properties at two time intervals 3 years apart. This was performed in 150 grassland sites differing greatly in management intensity across three German regions. Observed changes in microbial soil properties were related to both long‐term means and short‐term changes in: abiotic soil properties, land‐use intensity, community abundance‐weighted means of plant functional traits and plant biomass properties in regression and structural equation models. Plant traits, particularly leaf phosphorus, and soil pH were the best predictors of change in soil microbial function, as well as fungal and bacterial biomass, while land‐use intensity showed weaker effects. Indirect legacy effects, in which microbial change was explained by the effects of long‐term land‐use intensity on plant traits, were important, thus indicating a time lag between plant community and microbial change. Whenever the effects of short‐term changes in land‐use intensity were present, they acted directly on soil microorganisms. Synthesis. The results provide new evidence that soil communities and their functioning respond to short‐term changes in land‐use intensity, but that both rapid and longer time‐scale responses to changes in plant functional traits are at least of equal importance. This suggests that management which shapes plant communities may be an effective means of managing soil communities and the functions and services they provide.

Evidence from experimental and established grasslands indicates that plant biodiversity can modify the water cycle. One suspected mechanism behind this is a higher infiltration capacity (νB) and hydraulic conductivity (K) of the soil on species‐rich grasslands. However, in established and agriculturally managed grasslands, biodiversity effects cannot be studied independent of land‐use effects. Therefore, we investigated in established grassland systems how land‐use intensity and associated biodiversity of plants and soil animals affect νB and K at and close to saturation. On 50 grassland plots along a land‐use intensity gradient in the Biodiversity Exploratory Schwäbische Alb, Germany, we measured νB with a hood infiltrometer at several matrix potentials and calculated the saturated and unsaturated K. We statistically analysed the relationship between νB or K and land‐use information (e.g., fertilising intensity), abiotic (e.g., soil texture) and biotic data (e.g., plant species richness, earthworm abundance). Land‐use intensity decreased and plant species richness increased νB and K, while the direction of the effects of soil animals was inconsistent. The effect of land‐use intensity on νB and K was mainly attributable to its negative effect on plant species richness. Our results demonstrate that plant species richness was a better predictor of νB and K at and close to saturation than land‐use intensity or soil physical properties in the established grassland systems of the Schwäbische Alb., Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, Stiftung Landesbank Baden‐Württemberg, Swiss National Science Foundation http://dx.doi.org/10.13039/501100001711, http://doi.org/10.17616/R32P9Q

The objective of our study was to test whether limited microbial degradation at low pesticide concentrations could explain the discrepancy between overall degradability demonstrated in laboratory tests and their actual persistence in the environment. Studies on pesticide degradation are often performed using unrealistically high application rates seldom found in natural environments. Nevertheless, biodegradation rates determined for higher pesticide doses cannot necessarily be extrapolated to lower concentrations. In this context, we wanted to (i) compare the kinetics of pesticide degradation at different concentrations in arable land and (ii) clarify whether there is a concentration threshold below which the expression of the functional genes involved in the degradation pathway is inhibited without further pesticide degradation taking place. We set up an incubation experiment for four weeks using 14C-ring labeled 2-methyl-4-chlorophenoxyacetic acid (MCPA) as a model compound in concentrations from 30 to 20,000 μg kg–1 soil. To quantify the abundance of putative microorganisms involved in MCPA degradation and their degradation activity, tfdA gene copy numbers (DNA) and transcripts (mRNA) were determined by quantitative real-time PCR. Mineralization dynamics of MCPA derived-C were analyzed by monitoring 14CO2 production and 14C assimilation by soil microorganisms. We identified two different concentration thresholds for growth and activity with respect to MCPA degradation using tfdA gene and mRNA transcript abundance as growth and activity indices, respectively. The tfdA gene expression started to increase between 1,000 and 5,000 μg MCPA kg–1 dry soil, but an actual increase in tfdA sequences could only be determined at a concentration of 20,000 μg. Accordingly, we observed a clear shift from catabolic to anabolic utilization of MCPA-derived C in the concentration range of 1,000 to 5,000 μg kg–1. Concentrations ≥1,000 μg kg–1 were mainly associated with delayed mineralization, while concentrations ≤1,000 μg kg–1 showed rapid absolute dissipation. The persistence of pesticides at low concentrations cannot, therefore, be explained by the absence of functional gene expression. Nevertheless, significant differences in the degradation kinetics of MCPA between low and high pesticide concentrations illustrate the need for studies investigating pesticide degradation at environmentally relevant concentrations.

In heterogeneous environments such as soil it is imperative to understand the spatial relationships between microbial communities, microbial functioning and microbial habitats in order to predict microbial services in managed grasslands. Grassland land-use intensity has been shown to affect the spatial distribution of soil microorganisms, but so far it is unknown whether this is transferable from one geographic region to another. This study evaluated the spatial distribution of soil microbial biomass and enzyme activities involved in C-, N- and P-cycling, together with physico-chemical soil properties in 18 grassland sites differing in their land-use intensity in two geographic regions: the Hainich National Park in the middle of Germany and the Swabian Alb in south-west Germany. Enzyme activities associated with the C- and N-cycles, namely β-glucosidase, xylosidase and chitinase, organic carbon (Corg), total nitrogen (Nt), extractable organic carbon, and mineral nitrogen (Nmin) were higher in the Swabian Alb (Leptosols) than in the Hainich National Park (primarily Stagnosols). There was a negative relationship between bulk density and soil properties such as microbial biomass (Cmic, Nmic), urease, Corg, and Nt. The drivers (local abiotic soil properties, spatial separation) of the enzyme profiles (β-glucosidase, chitinase, xylosidase, phosphatase, and urease) were determined through a spatial analysis of the within site variation of enzyme profiles and abiotic properties, using the Procrustes rotation test. The test revealed that physical and chemical properties showed more spatial pattern than the enzyme profiles. β-glucosidase, chitinase, xylosidase, phosphatase, and urease activities were related to local abiotic soil properties, but showed little spatial correlation. Semivariogram modeling revealed that the ranges of spatial autocorrelation of all measured variables were site specific and not related to region or to land-use intensity. Nevertheless, land-use intensity changed the occurrence of spatial patterns measurable at the plot scale: increasing land-use intensity led to an increase in detectable spatial patterns for abiotic soil properties on Leptosols. The conclusion of this study is that microbial biomass and functions in grassland soils do not follow general spatial distribution patterns, but that the spatial distribution is site-specific and mainly related to the abiotic properties of the soils.

Management of forest sites has the potential to modulate soil organic matter decomposition by changing the catalytic properties of soil microorganisms within a soil profile. In this study we examined the impact of forest management intensity and soil physico-chemical properties on the variation of enzyme activities (β-glucosidase, β-xylosidase, α-glucosidase, phenol oxidase, N-acetyl-glucosaminidase, l -leucine aminopeptidase, phosphatase) in the topsoil and two subsoil horizons in three German regions (Schorfheide-Chorin, Hainich-Dun, Schwabische Alb). The sandy soils in the Schorfheide-Chorin (SCH) showed lower ratios of the activity of carbon (C) acquiring enzymes (β-glucosidase) relative to nitrogen (N) acquiring enzymes (N-acetyl-glucosaminidase + l -leucine aminopeptidase), and activity of C acquiring enzymes relative to phosphorous (P) acquiring enzymes (phosphatase) than the finer textured soils in the Hainich-Dun (HAI) and Schwabische Alb (ALB), indicating a shift in investment to N and P acquisition in the SCH. All enzyme activities, except phenol oxidase activity, decreased in deeper soil horizons as concentrations of organic C and total N did, while the decrease was much stronger from the topsoil to the first subsoil horizon than from the first subsoil to the second subsoil horizon. In contrast, phenol oxidase activity showed no significant decrease towards deeper soil horizons. Additionally, enzyme activities responsible for the degradation of more recalcitrant C relative to labile C compounds increased in the two subsoil horizons. Subsoil horizons in all regions also indicate a shift to higher N acquisition, while the strength of the shift depended on the soil type. Further, our results clearly showed that soil properties explained most of the total variance of enzyme activities in all soil horizons followed by study region, while forest management intensity had no significant impact on enzyme activities. Among all included soil properties, the clay content was the variable that explained the highest proportion of variance in enzyme activities with higher enzyme activities in clay rich soils. Our results highlight the need for large scale studies including different regions and their environmental conditions in order to derive general conclusions on which factors (anthropogenic or environmental) are most influential on enzyme activities in the whole soil profile in the long term at the regional scale.

Temporal dynamics create unique and often ephemeral conditions that can influence soil microbial biogeography at different spatial scales. This study investigated the relation between decimeter to meter spatial variability of soil microbial community structure, plant diversity, and soil properties at six dates from April through November. We also explored the robustness of these interactions over time. An historically unfertilized, unplowed grassland in southwest Germany was selected to characterize how seasonal variability in the composition of plant communities and substrate quality changed the biogeography of soil microorganisms at the plot scale (10 m × 10 m). Microbial community spatial structure was positively correlated with the local environment, i.e. physical and chemical soil properties, in spring and autumn, while the density and diversity of plants had an additional effect in the summer period. Spatial relationships among plant and microbial communities were detected only in the early summer and autumn periods when aboveground biomass increase was most rapid and its influence on soil microbial communities was greatest due to increased demand by plants for nutrients. Individual properties exhibited varying degrees of spatial structure over the season. Differential responses of Gram positive and Gram negative bacterial communities to seasonal shifts in soil nutrients were detected. We concluded that spatial distribution patterns of soil microorganisms change over a season and that chemical soil properties are more important controlling factors than plant density and diversity. Finer spatial resolution, such as the mm to cm scale, as well as taxonomic resolution of microbial groups, could help determine the importance of plant species density, composition, and growth stage in shaping microbial community composition and spatial patterns.

The objective of this study was to underpin the capability of diffuse reflectance Fourier transform mid-infrared spectroscopy (midDRIFTS)-based partial least squares regression (PLSR) analyses to accurately predict soil microbiological properties across six temperate grassland ecosystems differing in their land-use intensity; three sites of low land-use intensity (low LUI) and three fertilized mown meadows (high LUI). In addition, the potential of midDRIFTS-PLSR analyses for spatial studies between soils of contrasting grassland ecosystems was evaluated. 304 samples were subjected to midDRIFTS-PLSR-based predictions of soil microbial biomass, activities of beta- d -glucosidase, xylosidase and urease, as well as bacterial abundance based on 16S rRNA gene quantification. Accuracies of midDRIFTS-PLSR-based predictions across both LUI were, on basis of the residual prediction deviation (RPD), ‘acceptable’ for all soil microbiological properties, in particular soil microbial biomass (coefficient of determination ( R 2 ) = 0.92; RPD = 3.55), urease (0.91; 3.42) and beta- d -glucosidase (0.89; 3.01). Predictions of ‘moderately successful’ accuracy were developed for 16S rRNA gene copies (0.88; 2.93) and xylosidase (0.84; 2.55). Spatial midDRIFTS-PLSR-based predictions between grassland ecosystems were only ‘acceptable’ for soil microbial biomass, while the other studied soil microbiological properties revealed only ‘moderately successful’ predictions. The potential of midDRIFTS-PLSR to predict a range of soil microbiological properties including molecular data with ‘acceptable’ accuracies across the two investigated grassland ecosystems with contrasting land-use intensities was substantiated. However, the prevailing ‘moderately successful’ prediction accuracies between grassland ecosystems were probably due to the dependence on land use-specific data sets for calibration and validation. For prospective application of cost- and time-efficient midDRIFTS-PLSR-based approaches, predictions of soil microbiological properties considering particularly, but not yet ‘acceptable’ molecular data will greatly advance the understanding on the abundance and functional dynamics of soil microbial communities across spatial and temporal scales of contrasting ecosystems.

The aim of the present study was to investigate whether land-use intensity (LUI) contributes to spatial variation in microbial abundance and function in grassland ecosystems. At one time point, three sites at low (unfertilized pastures), at intermediate (fertilized mown pastures) and at high (fertilized mown meadows) LUIs were selected in southern Germany. Within each of these nine grassland sites, 54 soil samples (0–10 cm) were taken in a 10 m × 10 m area in spring. Plot-scale spatial dependence and autocorrelation of soil biogeochemical properties, microbial biomass and enzymes involved in C-, N- and P-cycling were analyzed. Applying geostatistics (exponential or spherical model) revealed that most chemical and microbiological properties showed at least a moderate spatial autocorrelation. Chemical soil properties (e.g. C org , N t , pH) were characterized by practical ranges (pRange) of between 1 and 14 m, whereas soil microbiological properties showed a greater variation of pRanges, providing evidence of spatial heterogeneity at multiple scales. The expected decrease in small-scale spatial heterogeneity in high LUI could not be confirmed for microbiological soil properties, because sampling in early spring might have reduced the influence of growing plants and fertilization. However, microbial biomass carbon was significantly greater in high LUIs, indicating that the benefit to soil microbial populations from the long-term increase in substrate and nutrient availability in fertilized grasslands is independent from factors affecting spatial structures in the short-term.

A geostatistical approach using replicated grassland sites (10 m × 10 m) was applied to investigate the influence of grassland management, i.e. unfertilized pastures and fertilized mown meadows representing low and high land-use intensity (LUI), on soil biogeochemical properties and spatial distributions of ammonia-oxidizing and denitrifying microorganisms in soil. Spatial autocorrelations of the different N-cycling communities ranged between 1.4 and 7.6 m for ammonia oxidizers and from 0.3 m for nosZ-type denitrifiers to scales >14 m for nirK-type denitrifiers. The spatial heterogeneity of ammonia oxidizers and nirS-type denitrifiers increased in high LUI, but decreased for biogeochemical properties, suggesting that biotic and/or abiotic factors other than those measured are driving the spatial distribution of these microorganisms at the plot scale. Furthermore, ammonia oxidizers (amoA ammonia-oxidizing archaea and amoA ammonia-oxidizing bacteria) and nitrate reducers (napA and narG) showed spatial coexistence, whereas niche partitioning was found between nirK- and nirS-type denitrifiers. Together, our results indicate that spatial analysis is a useful tool to characterize the distribution of different functional microbial guilds with respect to soil biogeochemical properties and land-use management. In addition, spatial analyses allowed us to identify distinct distribution ranges indicating the coexistence or niche partitioning of N-cycling communities in grassland soil.

Very few principles have been unraveled that explain the relationship between soil properties and soil biota across large spatial scales and different land-use types. Here, we seek these general relationships using data from 52 differently managed grassland and forest soils in three study regions spanning a latitudinal gradient in Germany. We hypothesize that, after extraction of variation that is explained by location and land-use type, soil properties still explain significant proportions of variation in the abundance and diversity of soil biota. If the relationships between predictors and soil organisms were analyzed individually for each predictor group, soil properties explained the highest amount of variation in soil biota abundance and diversity, followed by land-use type and sampling location. After extraction of variation that originated from location or land-use, abiotic soil properties explained significant amounts of variation in fungal, meso- and macrofauna, but not in yeast or bacterial biomass or diversity. Nitrate or nitrogen concentration and fungal biomass were positively related, but nitrate concentration was negatively related to the abundances of Collembola and mites and to the myriapod species richness across a range of forest and grassland soils. The species richness of earthworms was positively correlated with clay content of soils independent of sample location and land-use type. Our study indicates that after accounting for heterogeneity resulting from large scale differences among sampling locations and land-use types, soil properties still explain significant proportions of variation in fungal and soil fauna abundance or diversity. However, soil biota was also related to processes that act at larger spatial scales and bacteria or soil yeasts only showed weak relationships to soil properties. We therefore argue that more general relationships between soil properties and soil biota can only be derived from future studies that consider larger spatial scales and different land-use types. peerReviewed