Research Collection
Total Page:16
File Type:pdf, Size:1020Kb
Research Collection Doctoral Thesis Genetic characterization of soil bacterial communities in the DOK long-term agricultural field experiment Influences of management strategies and crops Author(s): Hartmann, Martin Publication Date: 2006 Permanent Link: https://doi.org/10.3929/ethz-a-005335472 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Diss. ETHNo. 16963 Genetic characterization of soil bacterial communities in the DOK long-term agricultural field experiment: influences of management strategies and crops A dissertation submitted to the SWISS FEDERAL INSTITUTE OF TECHNOLOGY ZURICH for the degree of DOCTOR OF SCIENCES presented by MARTIN HARTMANN Dipl. Natw. ETH born 16th February 1977 citizen of Schiers (GR) accepted on the recommendation of Prof. Dr. Emmanuel Frossard, examiner Dr. Franco Widmer, co-examiner Prof. Dr. Alex Widmer, co-examiner Prof. Dr. Jakob Pernthaler, co-examiner 2006 TABLE OF CONTENTS Table of Contents Table of Contents 1 Summary 5 Zusammenfassung 7 1 General Introduction 10 1.1 Assessing soil quality 10 1.1.1 Definition of soil quality 10 1.1.2 Soil quality monitoring 11 1.2 Agricultural management and ecological impact 12 1.2.1 Trends in agricultural production 12 1.2.2 Agricultural impact on ecosystems 14 1.2.3 Agricultural sustainability and soil quality 15 1.3 Soil characteristics 16 1.4 Microbial soil characteristics and soil quality 18 1.4.1 Microbial roles in soil processes 18 1.4.2 Microbial soil quality indicators 19 1.5 Soil biodiversity 20 1.5.1 Agricultural influence on soil microbiota 21 1.5.2 Soil microbial diversity 21 1.6 Assessing soil microbial community parameters 23 1.6.1 Soil microbial biomass 23 1.6.2 Diversity and community structure 26 1.7 The DOK long-term field experiment 37 1.7.1 Fertilization 39 1.7.2 Plant protection 40 1.7.3 Experimental field, tillage, and crop rotations 41 1.7.4 Soil organic carbon, soil acidity, and phosphorus dynamic 42 1.7.5 Crop yield 44 1.8 Objectives and outline of this thesis 46 1.8.1 Objectives 46 1.8.2 Outline 47 1 TABLE OF CONTENTS Community structures and substrate utilization of bacteria in soils from organic and conventional farming systems of the DOK long-term field experiment 50 2.1 Abstract 50 2.2 Introduction 51 2.3 Material and Methods 54 2.3.1 Experimental system 54 2.3.2 Soil sampling 55 2.3.3 Soil microbial biomass 56 2.3.4 Community level substrate utilization (CLSU) 56 2.3.5 Soil DNA extraction 57 2.3.6 Quantification of DNA 57 2.3.7 PCR-amplification of bacterial SSU rRNA genes 58 2.3.8 Terminal restriction fragment length polymorphism (T-RFLP) analysis 58 2.3.9 Descriptive and discriminative statistical analyses 59 2.4 Results 60 2.4.1 Soil microbial biomass (Cmic) and colony forming units 60 2.4.2 Total soil DNA content 61 2.4.3 Community level substrate utilization 62 2.4.4 Terminal restriction fragment length polymorphisms analyses 65 2.5 Discussion 69 2.5.1 Soil biomass parameters 69 2.5.2 Soil bacterial community structures 70 2.6 Conclusions 73 2.7 Acknowledgments 74 Ranking the magnitude of crop and farming system effects on soil microbial biomass and genetic structure of bacterial communities 76 3.1 Abstract 76 3.2 Introduction 76 3.3 Material and Methods 79 3.3.1 Experimental system and soil sampling 79 3.3.2 Soil microbial biomass 80 3.3.3 Extraction and quantification of DNA from soil 81 2 TABLE OF CONTENTS 3.3.4 Genetic profiling of soil bacterial populations 81 3.3.5 Statistical analyses 81 3.4 Results 82 3.4.1 Biomass and DNA content 82 3.4.2 Soil bacterial community structures 84 3.5 Discussion 90 3.6 Conclusions 94 3.7 Acknowledgments 94 Community structure analyses are more sensitive to differences in soil bacterial communities than anonymous diversity indices 96 4.1 Abstract 96 4.2 Introduction 96 4.3 Material and Methods 99 4.3.1 Agricultural management systems 99 4.3.2 Amplification and cloning of bacterial 16S rRNA gene fragments 99 4.3.3 Gene library screening 100 4.3.4 T-RFLP analysis 100 4.3.5 Sequence analysis 100 4.3.6 Diversity analyses 101 4.3.7 Nucleotide sequence accession numbers 102 4.4 Results 102 4.4.1 Phylogenetic affiliation 102 4.4.2 Richness and relative abundance of operational taxonomic units 104 4.4.3 Estimated complexity of the gene libraries 106 4.4.4 Comparison of in silico and experimental T-RF sizes 107 4.4.5 Community structures represented in the gene libraries 108 4.4.6 Potential treatment associated indicator taxa 109 4.5 Discussion 111 4.6 Acknowledgements 116 General Discussion 118 5.1 Potentials and limitations in assessing microbial communities 118 5.1.1 Spatial and temporal heterogeneity of microbial soil characteristics 118 5.1.2 Potential and advantages of molecular analyses 119 3 TABLE OF CONTENTS 5.1.3 Biases and limitations of molecular analyses 122 5.2 Impact of agricultural factors on soil bacterial communities 129 5.2.1 Changes in bacterial community structures 129 5.2.2 Abundances of bacteria in soils 131 5.3 Soil bacterial diversity as soil quality indicator 135 5.3.1 Biodiversity and functional redundancy in microbial communities 135 5.3.2 Limitations of common diversity estimations 138 5.3.3 Novel identity-based similarity estimations 139 5.4 Perspectives and Conclusions 140 5.4.1 The'full-cycle'molecular approach 140 5.4.2 Alternative gene families 143 5.4.3 Active groups 144 5.4.4 Molecular large-scale approaches 147 5.4.5 Final conclusions 149 Appendix: Residual polymerase activity-induced bias in terminal restriction fragment length polymorphism analysis 152 References 159 Curriculum Vitae 194 Publications 195 Published Abstracts and Presentations 196 Acknowledgments 197 4 SUMMARY Summary In agriculturally managed ecosystems preservation and improvement of soil fertility and quality is of great importance. As a consequence, strategies and tools are required to gain detailed information on soil characteristics and which allow for definition and monitoring of soil quality. Soil chemical and soil physical characteristics have successfully been analyzed for this purpose, whereas soil biological indicators are less defined. Soil microorganisms directly influence soil structure, nutrient cycles, transformation processes, and plant pathogenesis, and may therefore represent key determinants of soil fertility and high quality crop production. Microbial communities may respond highly sensitive to environmental and anthropogenic influences such as pollution, erosion or unsustainable land use and may therefore serve as indicators for changes in soil quality. Due to technical limitations, analyses of soil microbial communities have not been well established, but recent advances in molecular genetic analyses reveal a great potential to close this gap. Therefore, the aims of this thesis were (i) to investigate effects of different agricultural management regimes and crops on soil bacterial diversity and underlying community structures, and (ii) to evaluate the feasibility of novel molecular techniques to monitor environmental effects on soil characteristics. For this purpose, soil bacterial community structures and diversities were analyzed in the DOK agricultural long-term field experiment. The DOK experiment was established in Therwil (Switzerland) in 1978 designed for evaluation of biodynamic (BIODYN), bio-organic (BIOORG), and conventional (CONFYM) farming practices along with a minerally (CONMIN) and an unfertilized (NOFERT) control system. Results obtained in this thesis demonstrated that after 25 years of continuous and defined agricultural management, different farming systems and crop rotations significantly and consistently altered microbial biomass and bacterial community structures as assessed by cultivation-based and molecular techniques. Application of solid and liquid farmyard manure (FYM) revealed a primary effect on bacterial communities, whereas crop effects were of secondary magnitude but revealed a clear short-term influence, which faded after one season. Differences between organic and conventional farming were partially significant for the biodynamic system. In contrast, commonly used bacterial diversity indices as assessed by large- scale sequence analysis of almost 2000 ribosomal RNA genes was highly similar 5 SUMMARY and among the different farming systems. Different fertilization plant protection regimes did not affect bacterial diversity parameters and the significant differences in results of crop yield were not reflected in diversity estimations. However, large-scale of bacterial gene library screening supported results obtained from analyses community structures. The genetic profiling techniques revealed great potential for consistent, rapid, high-throughput monitoring of changes in microbial soil characteristics. In addition, large-scale sequence analysis allowed the detection of several potential management-specific bacterial indicator taxa, which may help to gain more detailed information on effects of the agricultural management on soil bacterial communities. In conclusion, detection of changes in microbial community structures may allow for the development of indicator systems for changes in soil condition due to environmental or anthropogenic influences. The combination of genetic profiling techniques with specific identification of potential indicator taxa may provide a further step towards diagnostic of key processes in defined systems. Linking this specific for information on community composition with microbial soil functions may help better understanding of soil quality in the future. 6 ZUSAMMENFASSUNG Zusammenfassung Die Erhaltung und Verbesserung der Bodenfruchtbarkeit und -qualität in landwirtschaftlichen Ökosystemen ist von grosser Bedeutung. Strategien und Methoden, welche detaillierte Informationen über die Bodeneigenschaften liefern und eine Definition sowie Überwachung der Bodenqualität erlauben, sind daher notwendig. Chemische und physikalische Bodeneigenschaften sind zu diesem Zweck erfolgreich untersucht worden, die biologischen Indikatoren hingegen sind weniger gut etabliert.