Tesfaye Wubet

Horizon-Specific Bacterial Community Composition of German Grassland Soils, as Revealed by Pyrosequencing-Based Analysis of 16S rRNA Genes

ABSTRACT The diversity of bacteria in soil is enormous, and soil bacterial communities can vary greatly in structure. Here, we employed a pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to characterize the overall and horizon-specific (A and B horizons) bacterial community compositions in nine grassland soils, which covered three different land use types. The entire data set comprised 752,838 sequences, 600,544 of which could be classified below the domain level. The average number of sequences per horizon was 41,824. The dominant taxonomic groups present in all samples and horizons were the Acidobacteria, Betaproteobacteria, Actinobacteria, Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Chloroflexi, Firmicutes, and Bacteroidetes. Despite these overarching dominant taxa, the abundance, diversity, and composition of bacterial communities were horizon specific. In almost all cases, the estimated bacterial diversity (H′) was higher in the A horizons than in the corresponding B horizons. In addition, the H′ was positively correlated with the organic carbon content, the total nitrogen content, and the C-to-N ratio, which decreased with soil depth. It appeared that lower land use intensity results in higher bacterial diversity. The majority of sequences affiliated with the Actinobacteria, Bacteroidetes, Cyanobacteria, Fibrobacteres, Firmicutes, Spirochaetes, Verrucomicrobia, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria were derived from A horizons, whereas the majority of the sequences related to Acidobacteria, Chloroflexi, Gemmatimonadetes, Nitrospira, TM7, and WS3 originated from B horizons. The distribution of some bacterial phylogenetic groups and subgroups in the different horizons correlated with soil properties such as organic carbon content, total nitrogen content, or microbial biomass.

Choosing and using diversity indices: Insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon’s diversity (H’), Simpson’s diversity (D1), Simpson’s dominance (D2), Simpson’s evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H’, even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality

Many experiments have shown that loss of biodiversity reduces the capacity of ecosystems to provide the multiple services on which humans depend. However, experiments necessarily simplify the complexity of natural ecosystems and will normally control for other important drivers of ecosystem functioning, such as the environment or land use. In addition, existing studies typically focus on the diversity of single trophic groups, neglecting the fact that biodiversity loss occurs across many taxa and that the functional effects of any trophic group may depend on the abundance and diversity of others. Here we report analysis of the relationships between the species richness and abundance of nine trophic groups, including 4,600 above- and below-ground taxa, and 14 ecosystem services and functions and with their simultaneous provision (or multifunctionality) in 150 grasslands. We show that high species richness in multiple trophic groups (multitrophic richness) had stronger positive effects on ecosystem services than richness in any individual trophic group; this includes plant species richness, the most widely used measure of biodiversity. On average, three trophic groups influenced each ecosystem service, with each trophic group influencing at least one service. Multitrophic richness was particularly beneficial for ‘regulating’ and ‘cultural’ services, and for multifunctionality, whereas a change in the total abundance of species or biomass in multiple trophic groups (the multitrophic abundance) positively affected supporting services. Multitrophic richness and abundance drove ecosystem functioning as strongly as abiotic conditions and land-use intensity, extending previous experimental results to real-world ecosystems. Primary producers, herbivorous insects and microbial decomposers seem to be particularly important drivers of ecosystem functioning, as shown by the strong and frequent positive associations of their richness or abundance with multiple ecosystem services. Our results show that multitrophic richness and abundance support ecosystem functioning, and demonstrate that a focus on single groups has led to researchers to greatly underestimate the functional importance of biodiversity.

Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China

Summary 1. Biodiversity–ecosystem functioning (BEF) experiments address ecosystem-level consequences of species loss by comparing communities of high species richness with communities from which species have been gradually eliminated. BEF experiments originally started with microcosms in the laboratory and with grassland ecosystems. A new frontier in experimental BEF research is manipulating tree diversity in forest ecosystems, compelling researchers to think big and comprehensively. 2. We present and discuss some of the major issues to be considered in the design of BEF experiments with trees and illustrate these with a new forest biodiversity experiment established in subtropical China (Xingangshan, Jiangxi Province) in 2009/2010. Using a pool of 40 tree species, extinction scenarios were simulated with tree richness levels of 1, 2, 4, 8 and 16 species on a total of 566 plots of 25� 8 9 25� 8m each. 3. The goal of this experiment is to estimate effects of tree and shrub species richness on carbon storage and soil erosion; therefore, the experiment was established on sloped terrain. The following important design choices were made: (i) establishing many small rather than fewer larger plots, (ii) using high planting density and random mixing of species rather than lower planting density and patchwise mixing of species, (iii) establishing a map of the initial ‘ecoscape’ to characterize site heterogeneity before the onset of biodiversity effects and (iv) manipulating tree species richness not only in random but also in trait-oriented extinction scenarios. 4. Data management and analysis are particularly challenging in BEF experiments with their hierarchical designs nesting individuals within-species populations within plots within-species compositions. Statistical analysis best proceeds by partitioning these random terms into fixed-term contrasts, for example, species composition into contrasts for species richness and the presence of particular functional groups, which can then be tested against the remaining random variation among compositions. 5. We conclude that forest BEF experiments provide exciting and timely research options. They especially require careful thinking to allow multiple disciplines to measure and analyse data jointly and effectively. Achiev

Interannual variation in land-use intensity enhances grassland multidiversity

Significance Land-use intensification is a major threat to biodiversity. So far, however, studies on biodiversity impacts of land-use intensity (LUI) have been limited to a single or few groups of organisms and have not considered temporal variation in LUI. Therefore, we examined total ecosystem biodiversity in grasslands varying in LUI with a newly developed index called multidiversity, which integrates the species richness of 49 different organism groups ranging from bacteria to birds. Multidiversity declined strongly with increasing LUI, but changing LUI across years increased multidiversity, particularly of rarer species. We conclude that encouraging farmers to change the intensity of their land use over time could be an important strategy to maintain high biodiversity in grasslands. Although temporal heterogeneity is a well-accepted driver of biodiversity, effects of interannual variation in land-use intensity (LUI) have not been addressed yet. Additionally, responses to land use can differ greatly among different organisms; therefore, overall effects of land-use on total local biodiversity are hardly known. To test for effects of LUI (quantified as the combined intensity of fertilization, grazing, and mowing) and interannual variation in LUI (SD in LUI across time), we introduce a unique measure of whole-ecosystem biodiversity, multidiversity. This synthesizes individual diversity measures across up to 49 taxonomic groups of plants, animals, fungi, and bacteria from 150 grasslands. Multidiversity declined with increasing LUI among grasslands, particularly for rarer species and aboveground organisms, whereas common species and belowground groups were less sensitive. However, a high level of interannual variation in LUI increased overall multidiversity at low LUI and was even more beneficial for rarer species because it slowed the rate at which the multidiversity of rare species declined with increasing LUI. In more intensively managed grasslands, the diversity of rarer species was, on average, 18% of the maximum diversity across all grasslands when LUI was static over time but increased to 31% of the maximum when LUI changed maximally over time. In addition to decreasing overall LUI, we suggest varying LUI across years as a complementary strategy to promote biodiversity conservation.

General Relationships between Abiotic Soil Properties and Soil Biota across Spatial Scales and Different Land-Use Types

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.

Effects of long-term differential fertilization on eukaryotic microbial communities in an arable soil: a multiple barcoding approach.

To understand the fine‐scale effects of changes in nutrient availability on eukaryotic soil microorganisms communities, a multiple barcoding approach was used to analyse soil samples from four different treatments in a long‐term fertilization experiment. We performed PCR amplification on soil DNA with primer pairs specifically targeting the 18S rRNA genes of all eukaryotes and three protist groups (Cercozoa, Chrysophyceae‐Synurophyceae and Kinetoplastida) as well as the ITS gene of fungi and the 23S plastid rRNA gene of photoautotrophic microorganisms. Amplicons were pyrosequenced, and a total of 88 706 quality filtered reads were clustered into 1232 operational taxonomic units (OTU) across the six data sets. Comparisons of the taxonomic coverage achieved based on overlapping assignment of OTUs revealed that half of the eukaryotic taxa identified were missed by the universal eukaryotic barcoding marker. There were only little differences in OTU richness observed between organic‐ (farmyard manure), mineral‐ and nonfertilized soils. However, the community compositions appeared to be strongly structured by organic fertilization in all data sets other than that generated using the universal eukaryotic 18S rRNA gene primers, whereas mineral fertilization had only a minor effect. In addition, a co‐occurrence based network analysis revealed complex potential interaction patterns between OTUs from different trophic levels, for example between fungivorous flagellates and fungi. Our results demonstrate that changes in pH, moisture and organic nutrients availability caused shifts in the composition of eukaryotic microbial communities at multiple trophic levels.

Protein-SIP enables time-resolved analysis of the carbon flux in a sulfate-reducing, benzene-degrading microbial consortium

Benzene is a major contaminant in various environments, but the mechanisms behind its biodegradation under strictly anoxic conditions are not yet entirely clear. Here we analyzed a benzene-degrading, sulfate-reducing enrichment culture originating from a benzene-contaminated aquifer by a metagenome-based functional metaproteomic approach, using protein-based stable isotope probing (protein-SIP). The time-resolved, quantitative analysis of carbon fluxes within the community supplied with either 13C-labeled benzene or 13C-labeled carbonate yielded different functional groups of organisms, with their peptides showing specific time dependencies of 13C relative isotope abundance indicating different carbon utilization. Through a detailed analysis of the mass spectrometric (MS) data, it was possible to quantify the utilization of the initial carbon source and the metabolic intermediates. The functional groups were affiliated to Clostridiales, Deltaproteobacteria and Bacteroidetes/Chlorobi. The Clostridiales-related organisms were involved in benzene degradation, putatively by fermentation, and additionally used significant amounts of carbonate as a carbon source. The other groups of organisms were found to perform diverse functions, with Deltaproteobacteria degrading fermentation products and Bacteroidetes/Chlorobi being putative scavengers feeding on dead cells. A functional classification of identified proteins supported this allocation and gave further insights into the metabolic pathways and the interactions between the community members. This example shows how protein-SIP can be applied to obtain temporal and phylogenetic information about functional interdependencies within microbial communities.

Genome sequences of two dehalogenation specialists – Dehalococcoides mccartyi strains BTF08 and DCMB5 enriched from the highly polluted Bitterfeld region

The genomes of two novel Dehalococcoides mccartyi strains, DCMB5 and BTF08, enriched from the heavily organohalide-contaminated megasite around Bitterfeld (Germany), were fully sequenced and annotated. Although overal lsimilar, the genome sequences of the two strains reveal remarkable differences in their genetic content, reflecting a specific adaptation to the contaminants at the field sites from which they were enriched. The genome of strain BTF08 encodes for 20 reductive dehalogenases, and is the first example of a genome containing all three enzymes that are necessary to couple the complete reductive dechlorination of PCE to ethene to growth. The genes encoding trichloroethene and vinyl chloride reductive dehalogenases, tceA and vcrA, are located within mobile genetic elements, suggesting their recent horizontal acquisition.The genome of strain DCMB5 contains 23 reductive dehalogenase genes,including cbrA, which encodes a chlorobenzene reductive dehalogenase, and a gene cluster encoding arsenic resistance proteins, both corresponding to typical pollutants at its isolation site.

TaqMan Real-Time PCR Assays To Assess Arbuscular Mycorrhizal Responses to Field Manipulation of Grassland Biodiversity: Effects of Soil Characteristics, Plant Species Richness, and Functional Traits

ABSTRACT Large-scale (temporal and/or spatial) molecular investigations of the diversity and distribution of arbuscular mycorrhizal fungi (AMF) require considerable sampling efforts and high-throughput analysis. To facilitate such efforts, we have developed a TaqMan real-time PCR assay to detect and identify AMF in environmental samples. First, we screened the diversity in clone libraries, generated by nested PCR, of the nuclear ribosomal DNA internal transcribed spacer (ITS) of AMF in environmental samples. We then generated probes and forward primers based on the detected sequences, enabling AMF sequence type-specific detection in TaqMan multiplex real-time PCR assays. In comparisons to conventional clone library screening and Sanger sequencing, the TaqMan assay approach provided similar accuracy but higher sensitivity with cost and time savings. The TaqMan assays were applied to analyze the AMF community composition within plots of a large-scale plant biodiversity manipulation experiment, the Jena Experiment, primarily designed to investigate the interactive effects of plant biodiversity on element cycling and trophic interactions. The results show that environmental variables hierarchically shape AMF communities and that the sequence type spectrum is strongly affected by previous land use and disturbance, which appears to favor disturbance-tolerant members of the genus Glomus. The AMF species richness of disturbance-associated communities can be largely explained by richness of plant species and plant functional groups, while plant productivity and soil parameters appear to have only weak effects on the AMF community.