Note: Intro -- Introduction: Spatial Synthesis in Computational Social Science and Humanities -- 1. Towards Computational Spatial Social Science and Humanities -- 2. Synthesis and Convergence -- 3. Spatial Synthesis in Humanities, Regional Science, and Urban Science -- 4. Conclusion -- References -- Contents -- Part IForeword -- 1 Foreword I: Charting Computational Social Science from a Spatial Perspective -- References -- 2 Foreword II: Convergence and Synthesis -- References -- Part IISpatial Synthesis in Humanities -- 3 The China Family Tree Geographic Information System -- 3.1 Family Tree and GIS -- 3.1.1 Family Tree -- 3.1.2 GIS and Family Tree Research -- 3.1.3 Concept and Objectives of Family Tree GIS -- 3.2 A Unified Spatial-Temporal Framework for Family Trees -- 3.2.1 Why Is a Unified Spatial-Temporal Framework Needed? -- 3.2.2 How Can a Unified Spatial-Temporal Framework Be Constructed? -- 3.3 FTGIS Data Model -- 3.3.1 Content and Information of Family Trees -- 3.3.2 Overview of the Models -- 3.4 Family Tree Information Specification and Sharing -- 3.4.1 Existing Specifications Associated with Family Trees -- 3.4.2 Family Tree Information Specification -- 3.5 Mass Family Tree Information Collection -- 3.6 FTGIS Platform -- 3.6.1 Architecture of the FTGIS Platform -- 3.6.2 Functions of the FTGIS Platform -- 3.7 Conclusions and Future Research -- References -- 4 GIS for Chinese History Research -- 4.1 The Construction of Typical Geographic Information Systems for China Study -- 4.2 The Research Regarding Climate, Rivers, Hydrology and Geomorphology Through the Application of the GIS Technology -- 4.2.1 The Historical Climate Research with the GIS -- 4.2.2 The Research of Rivers and Hydrology in History Through the GIS -- 4.2.3 The Geomorphology and the Research of Environmental Changes Through the GIS. , 4.3 The Research of Towns and Villages in History via the Application of the GIS -- 4.3.1 The Urban History and the Research of Urban Historical Geography Under the GIS Platforms -- 4.3.2 The Research of Town Economy of Jiangnan Region in Ming and Qing Dynasty by the GIS -- 4.3.3 The Research on the Rural Settlements in History Through the GIS -- 4.4 The Research of the Economy and Society in History via the GIS -- 4.5 The Research of Ancient Maps and Their Digitization by the GIS Technology -- 4.6 The Exploratory Research for the Methodology for Digitizing the History Geographic Information -- References -- 5 Digital Historical Yellow River -- 5.1 Digital Historical Yellow River -- 5.2 The Relationship Between Qing Government Finance and the Yellow River Management -- 5.3 The Collapse of the Yellow River Finance in 1820-1840 -- 5.3.1 The Changing of the Hydrological Environment Over the Yellow River in 1820-1840 -- 5.3.2 The Hydrological Challenge of Daoguang Period -- 5.4 Conclusion -- References -- 6 Visualizing Classic Chinese Literature -- 6.1 Visualization of Writers' Trajectory and Activity Distribution -- 6.2 Visualization of the Geographical Distribution of Writers' Social Relations with CBDB and the Aforementioned GIS Software -- 6.3 The Point-Line Visualization of Social Relations with Databases and Software Such as CBDB and GEPHI -- 6.4 Conclusion -- 7 Quantifying Spatial Variation in Aggregate Cultural Tolerance -- 7.1 Introduction -- 7.2 Conceptual Background -- 7.3 Data and Measures -- 7.4 Methods -- 7.5 Results -- 7.5.1 Descriptive Statistics -- 7.5.2 Small Area Estimation Results -- 7.5.3 Predicting Individual Cultural Values -- 7.6 Discussion -- References -- 8 Conservation of Cave-dwelling Village using Cultural Landscape Gene Theory -- 8.1 Introduction -- 8.2 The First Genetic Characteristic of CDVCL: Natural Gene. , 8.2.1 The Loess Landform -- 8.2.2 Semi-arid Climate -- 8.2.3 Dry Farming -- 8.3 The Second Genetic Characteristic of CDVCL: Cultural Gene -- 8.3.1 Village Pattern of Along the River -- 8.3.2 Village Pattern of Along the Cliff -- 8.3.3 Village Pattern of Along the Slope -- 8.4 The Third Genetic Characteristic of CDVCL: Spatial Gene -- 8.4.1 Production Space -- 8.4.2 Living Space -- 8.4.3 Mental Space -- 8.5 The Fourth Genetic Characteristic of CDVCL: Material Gene -- 8.5.1 Construction Materials -- 8.5.2 Facade Forms -- 8.5.3 Flat Pattern -- 8.5.4 Partial Adornment -- 8.6 The Fifth Genetic Characteristic of CDVCL: Intangible Gene -- 8.6.1 Religion -- 8.6.2 Traditional Customs -- 8.7 Conclusions -- References -- 9 Digitalized Enka-Style Taipei -- 9.1 Introduction -- 9.2 Taiwanese Enka-Style Ballad Performers in the 1960s: Two Cases -- 9.3 Digitalized Enka Pertaining to Taipei that Reflected a Mixed-Race Cultural Space -- 9.4 Interviews and Digital Mapping Interpretation -- 9.5 Concluding Remarks -- References -- Part IIISpatial Synthesis in Regional Science -- 10 Research Progress on Spatial Demography -- 10.1 Introduction -- 10.2 Core Concept of Spatial Demography -- 10.2.1 The Definition of Spatial Demography -- 10.2.2 Space and Spatial Analysis in Spatial Demography -- 10.2.3 The Relations and Differences Between Spatial Demography and Related Disciplines -- 10.3 The Course of Development in Spatial Demography -- 10.4 The Trans-Century Research Focuses in Spatial Demography -- 10.4.1 Differentiation and Isolation -- 10.4.2 Birth and Death -- 10.4.3 Migration and Urbanization -- 10.4.4 Regional Population Forecast -- 10.4.5 Population and the Environment -- 10.5 Research Technique in Spatial Demography -- 10.6 Prospect of Future Development of Spatial Demography -- References -- 11 Complex Network Theory on High-Speed Transportation Systems. , 11.1 Introduction -- 11.2 Methodologies Used in Complex Network Theory on Quantifying the Air and HSR Systems -- 11.2.1 Centrality Measures -- 11.2.2 General Characteristics About the Complex Networks -- 11.3 Empirical Analysis for HSR and Airline Networks -- 11.3.1 HSR Networks -- 11.3.2 Airline Networks -- 11.4 The Differences Between Weighted and Non-weighted High-Speed Transportation Networks -- 11.5 Conclusion -- References -- 12 Economic Impact Analysis for an Energy Efficient Home Improvement Program -- 12.1 Introduction -- 12.2 Literature Review -- 12.3 Methodology -- 12.4 Empirical Study -- 12.4.1 Data -- 12.4.2 Economic Impact Analysis -- 12.5 Conclusions and Discussions -- References -- 13 Exploring the Dynamics of Carbon Emission in China via Spatial-Temporal Analysis -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Data -- 13.3.1 Unit of Analysis -- 13.3.2 Dependent Variable -- 13.3.3 Independ Variables -- 13.3.4 Other Control Variables -- 13.4 Exploratory Spatial Data Analysis (ESDA) -- 13.5 Spatial Econometrics Analysis -- 13.6 Conclusion and Discussion -- References -- 14 Spatial Visualization and Analysis of the Development of High-Paid Enterprises in the Yangtze River Delta -- 14.1 Introduction -- 14.2 Methord -- 14.2.1 Data Acquisition -- 14.2.2 Data Visualization -- 14.3 Realization -- 14.4 Conclusion -- References -- 15 High Performance Spatiotemporal Visual Analytics Technologies and Its Applications in Big Socioeconomic Data Analysis -- 15.1 Introduction -- 15.2 Spatial Index and Storage Mechanisms -- 15.2.1 Spatial Indexing -- 15.2.2 Spatial Databases -- 15.2.3 Distributed File System -- 15.3 High Performance Computing Technologies -- 15.3.1 Computing Paradigms -- 15.3.2 Mainstream Frameworks -- 15.3.3 Applications in Spatial Humanities and Social Sciences -- 15.4 Web-Based Visualization. , 15.4.1 JavaScript-Based Visualization Libraries -- 15.4.2 Web Framework and Communication Technologies -- 15.5 Enterprise Registration Data Visual Analytics as a Use Case -- 15.5.1 HPC-Accelerated Data Preprocessing -- 15.5.2 HPC-Enabled Dynamic Visual Analytics -- 15.6 Conclusions -- References -- 16 Demystifying the Inequality in Urbanization in China Through the Lens of Land Use -- 16.1 Introduction -- 16.2 Data and Methodology -- 16.2.1 Data Sources -- 16.2.2 Methodology -- 16.3 Spatial Inequality in Land Urbanization -- 16.3.1 Land Urbanization Patterns by County in 2000 -- 16.3.2 Land Urbanization Patterns by County in 2015 -- 16.3.3 Evolution of Land Urbanization Patterns in Chinese Counties -- 16.3.4 Land Urbanization Types in Chinese Counties -- 16.4 Determinants of Spatial Inequality in Land Urbanization -- 16.4.1 Comprehensive Analysis of Elements Based on the OLS Model -- 16.4.2 Spatial Heterogeneity Analysis of Elements Based on GWR Model -- 16.5 Discussion -- 16.6 Conclusions and Future Development -- References -- 17 Analyzing Spatial Patterns of Intergenerational Education Mobility in China -- 17.1 Introduction -- 17.2 Data -- 17.3 Methods -- 17.3.1 Intergenerational Education Index -- 17.3.2 Indices to Estimate the Intergenerational Mobility -- 17.3.3 Geographically Weighed Regression -- 17.4 The Overall Situation of Intergenerational Education Mobility in China -- 17.5 Analysis of Influencing Factors of Children's Education Level and Their Spatial Distribution -- 17.6 Conclusion and Discussion -- References -- 18 Can Social Media Rescue Child Beggars? -- 18.1 Introduction -- 18.2 Volunteered Geographic Information (VGI), Social Media, Child Beggars, and Missing Children -- 18.3 Data and Methods -- 18.4 Results -- 18.5 Discussion -- 18.6 Conclusions -- References -- Part IVSpatial Synthesis in Urban Science. , 19 Spoofing in Geography: Can We Trust Artificial Intelligence to Manage Geospatial Data?.

Note: Intro -- Preface -- Contents -- Editor and Contributors -- Authors' Biography -- Acronyms -- Abstract -- 1 News on Eight Chip Technologies -- Abstract -- 1.1 Overview -- 1.2 Bipolar-Transistor Technology -- 1.3 CMOS Integrated Circuits -- 1.4 Silicon-on-Insulator (SOI) CMOS Technology -- 1.5 3D CMOS Technologies -- 1.6 Ultra-Low-Voltage Differential Transmission-Gate CMOS Logic -- 1.7 Chip Stacks -- 1.8 Single-Electron-Transistor Technology -- 1.9 Conclusion -- References -- 2 The Future of Low-Power Electronics -- Abstract -- 2.1 Electronics Systems and Power-Efficiency -- 2.2 Low-Power CMOS Technology -- 2.2.1 Hybrid SOTB CMOS Technology -- 2.2.2 Low-Voltage SRAM -- 2.2.3 Low-Voltage Microprocessor and Logic Circuits -- 2.3 Low-Power Non-volatile Memories and Switches -- 2.3.1 MRAM for Cache Applications -- 2.3.2 Complementary Atom-Switch for Programmable Logic After Fabrication -- 2.3.3 SOTB-CMOS Microprocessor with Atom-Switch PROM -- 2.3.4 TRAM for Low-Power Storage -- 2.4 3D Integration -- 2.5 The Future of Low-Power Integrated Circuits -- References -- 3 Monolithic 3D Integration -- Abstract -- 3.1 Why Monolithic 3D -- 3.1.1 Lithography -- 3.1.2 On-Chip Interconnect -- 3.1.3 Transistor Variation -- 3.2 Historical Review of Monolithic 3D Technologies -- 3.2.1 Thin-Film Polysilicon-Based Monolithic 3D -- 3.2.2 Crystalline Overlay -- 3.2.3 Layer Transfer -- 3.2.4 Transistor Activation -- 3.2.4.1 The RCAT Process -- 3.2.4.2 The Gate Replacement Process -- 3.2.4.3 Laser-Annealing Process -- 3.3 Precision Bonders---A Game Changer for Monolithic 3D -- 3.3.1 Monolithic 3D IC Using Precision Bonders -- 3.3.2 Smart Alignment -- 3.3.3 Strata 2, 3---Examples -- 3.3.4 Monolithic 3D Cost Estimates -- 3.4 EDA for Monolithic 3D -- 3.5 Managing the Heat -- 3.6 3D Memories: 3D NAND,2026 -- 3.6.1 Introduction to BiCS -- 3.6.2 3D-NAND. , 3.6.3 Making Contact Without Adding Lithography Steps -- 3.6.4 3D-NOR Flash -- 3.7 Advanced Work---Non-silicon Monolithic 3D -- 3.7.1 III--V Semiconductor 3D Integration -- 3.7.2 Monolithic 3D Integration of Semiconductor, Carbon Nano Tube, STT MRAM and RRAM -- 3.8 The Monolithic 3D Advantages -- 3.8.1 Introduction -- 3.8.2 Reduction in Die Size and Power -- 3.8.2.1 Reduction in Die Size -- 3.8.2.2 Reduction in Power -- 3.8.3 Significant Advantages for Using the Same Fab and Design Tools -- 3.8.3.1 Depreciation -- 3.8.3.2 Learning Curve---Yield -- 3.8.4 Heterogeneous Integration -- 3.8.4.1 Logic, Memory, I/O -- 3.8.4.2 Strata of Logic -- 3.8.4.3 Strata of Different Substrate Crystals and Fabrication Processes -- 3.8.5 Multiple Layers Processed Simultaneously---BiCS -- 3.8.6 Logic Redundancy Allowing 100x Integration with Good Yield -- 3.8.7 3D-FPGA -- 3.8.8 Modular Platform -- 3.8.9 Stacked Layers Are Naturally SOI -- 3.8.10 Local Interconnect Above and Below Transistor Layer -- 3.8.11 Re-buffering Global Interconnect by Upper Strata -- 3.8.12 Other Ideas -- 3.8.12.1 Image Sensor with Pixel Electronics -- 3.8.12.2 Micro-display -- 3.9 Conclusion -- References -- 4 Analog-Digital Interfaces---Review and Current Trends -- Abstract -- 4.1 Introduction -- 4.2 General ADC Performance Trends -- 4.3 Trends in Nyquist A/D Converters -- 4.3.1 SAR ADCs -- 4.3.2 Pipelined ADCs -- 4.3.3 Flash ADCs -- 4.3.4 Digitally Assisted Design -- 4.4 Trends in Delta-Sigma A/D Converters -- 4.4.1 Loop Filter -- 4.4.2 Quantizer -- 4.4.2.1 Voltage-Controlled Oscillator-Based Quantizer -- 4.4.2.2 Time-Encoding Quantizer -- 4.4.3 DAC -- 4.4.4 Conclusion on Delta-Sigma A/D Converters -- 4.5 Analog-to-Information Converters -- 4.6 Conclusions -- References -- 5 Interconnects and Communication -- Abstract -- 5.1 On-Chip and Chip-Chip Communication. , 5.2 Projections Wireline Communication -- 5.3 Wireless Communication -- 5.4 Optical Communication -- 5.5 Global Mobile Communication -- 5.6 Conclusion -- References -- 6 Superprocessors -- Abstract -- 6.1 Evolving Workloads -- 6.2 POWER8---a Big-Data Processor -- 6.3 Security -- 6.4 Optimization Across the Stack -- 6.5 Accelerators -- 6.6 Open Computing -- 6.7 Outlook -- References -- 7 ITRS 2028---International Roadmap of Semiconductors -- Abstract -- 7.1 General Observations -- 7.2 ORTC---Overall Roadmap Technology Characteristics -- 7.3 System Drivers -- 7.4 PIDS---Process Integration, Devices and Structures -- 7.5 ERD---Emerging Research Devices -- 7.6 Interconnects -- 7.7 RF-AMS: Radio-Frequency and Analog-Mixed-Signal Technologies -- 7.8 Conclusion -- References -- 8 Nanolithographies -- Abstract -- 8.1 The Progression of Optical Lithography -- 8.2 Extreme-Ultraviolet (EUV) Lithography -- 8.3 Multiple-Electron-Beam (MEB) Lithography -- 8.4 Comparison of Three Nanolithographies -- 8.5 2015 Perspective on 7 nm Lithography -- References -- 9 News on Energy-Efficient Large-Scale Computing -- Abstract -- 9.1 History and Background -- 9.2 Energy Efficiency -- 9.3 Conclusions -- References -- 10 High-Performance Computing (HPC) -- Abstract -- 10.1 Highlights on Standard Processors -- 10.2 Special-Purpose Processors and Energy Efficiency -- 10.3 Supercomputers -- 10.4 Internet Servers -- 10.5 Conclusion -- References -- 11 Memory -- Abstract -- 11.1 Static Random-Access Memory (SRAM) -- 11.2 The DRAM (Dynamic Random-Access Memory) at Its Final Stage -- 11.3 Breakthroughs in Non-volatile Memories (NV-RAM's) -- 11.4 Conclusion -- References -- 12 Intelligent Data Versus Big Data -- Abstract -- 12.1 Progress in Nano-Chips Fosters Data Explosion -- 12.2 Intelligent Data from and for Our World -- 12.3 Digital Multipliers for Reality Data -- 12.4 Conclusion. , References -- 13 HDR- and 3D-Vision Sensors -- Abstract -- 13.1 Scaled CMOS Image Sensors -- 13.2 Hi-Speed Feature-Recognition Chips -- 13.3 High-Dynamic-Range HDR Video Sensors -- 13.4 HDRC Stereo Cameras -- 13.5 3D Time-of-Flight (TOF) Sensors -- 13.6 Conclusion -- References -- 14 Perception-Inspired High Dynamic Range Video Coding and Compression -- Abstract -- 14.1 Introduction -- 14.2 HDR Pixel Encoding -- 14.3 High Bit-Depth Compression -- 14.4 Backward-Compatible Compression -- 14.5 Perceptual Depth Compression for Stereoscopic Applications -- 14.6 Conclusion -- References -- 15 MEMS---Micro-Electromechanical Sensors for the Internet of Everything -- Abstract -- 15.1 Unique Growth of the MEMS Market -- 15.2 Automotive MEMS Applications and Scaling -- 15.3 Mobile Consumer Electronics -- 15.4 The ``Bosch'' Process -- 15.5 Sensors and Systems-Integration -- 15.6 MEMS-Enabled Systems and Their Consistent Development -- 15.7 Conclusion -- Disclaimer -- References -- 16 Networked Neural Systems -- Abstract -- 16.1 Introduction -- 16.2 Health Monitor -- 16.2.1 PPG (Photo-Plethysmo-Graphical) Analysis -- 16.2.2 The Need for Modelling -- 16.3 Integrated Neural Systems -- 16.3.1 Synaptic Chips -- 16.3.2 Memristor -- 16.4 Distributed Neural Networks -- 16.4.1 Event-Directed Synchronization -- 16.4.2 Self-healing -- 16.5 Conclusion -- References -- 17 Insertion of Retinal Implants in Worlwide Prostheses -- Abstract -- 17.1 HDR Subretinal Implant Inspired by the Human Visual System -- 17.2 Chronicle of the Subretinal Implant -- 17.3 CE Certification and Results for Blind Patients Worldwide -- 17.4 Conclusion -- References -- 18 Brain-Inspired Architectures for Nanoelectronics -- Abstract -- 18.1 Introduction -- 18.2 Some Features of the Human Brain -- 18.3 Brain Simulation Approaches -- 18.4 Neurocomputers Based on Standard ICs. , 18.5 Neurocomputers Based on Neuro-ASICs -- 18.6 The Blue Brain Project -- 18.7 The SpiNNaker System -- 18.8 The SyNAPSE Program and the IBM TrueNorth Architecture -- 18.9 The BrainScaleS Wafer-Scale Neuromorphic Hardware System -- 18.10 Neurogrid -- 18.11 Comparison -- 18.12 Outlook -- References -- 19 Energy-Harvesting Applications and Efficient Power Processing -- Abstract -- 19.1 Systems and Applications -- 19.1.1 Wearable Devices -- 19.1.2 Condition Monitoring -- 19.2 Circuit Components for Energy Harvesting Applications -- 19.2.1 AC Sources -- 19.2.1.1 Wireless Power Transmission Circuits -- 19.2.1.2 Interfaces for Vibration-Based Kinetic Energy Harvesting -- 19.2.2 DC Sources -- 19.2.2.1 Micro Fuel Cells -- 19.2.2.2 Interface Circuits for Thermoelectric Generators -- 19.2.2.3 Interface Circuits for Solar Cells -- 19.2.3 Ultra-Low-Voltage Control Circuits -- 19.2.3.1 Analog -- 19.2.3.2 Digital -- 19.3 Conclusion -- References -- 20 2020 and Beyond -- Abstract -- 20.1 Chip Market Forecasts for 2020 -- 20.2 The Electric-Power Singularity of 2020 -- 20.3 Monolithic and Heterogeneous 3D Integration -- 20.4 Low-Voltage, New Digital Computing -- 20.5 New Video -- 20.6 Reliable Intelligent-Learning Nano-Systems -- 20.7 The Era of Energy-Autonomous Nano-Chip Systems -- 20.8 Another Singularity? -- References -- Titles in this Series -- Index.

Note: Intro -- Dedication -- Series Preface -- Foreword -- Volume Preface -- Contents -- Chapter 1: Towards a Unified Understanding of Evolution, Habitat and Niche -- 1.1 Introduction -- 1.2 Evolution -- 1.3 Habitat -- 1.4 Niche -- 1.4.1 Evolution and Niche -- 1.4.1.1 Evolution and Community Cooperation -- 1.4.1.2 Morphometrics and Morphospace: Studying Evolution by Measuring a Physical Form -- 1.4.2 Are There Definable Rules? -- 1.4.2.1 First Rule: Nothing Lasts Forever -- 1.4.2.2 Second Rule: Evolution Is Driven by Either Necessity or Opportunity -- 1.4.2.3 Third Rule: Evolution Leads to Conformity with the Requirements of Function -- 1.4.3 Evolutionary Pressure and How It Works Along with the Concept of Niche Space -- 1.4.3.1 Using Sculpture to Envision the Dimensionality of an Individual Species Niche Space -- 1.4.3.2 And, Using Sculpture to Envision the Total Niche Space of a Biological Group -- 1.4.4 Does Persistence of a Niche Equate to Long Term Evolutionary Success for Its Occupying Species? -- 1.4.4.1 Persistence of a Niche may Lead to Success of the Occupant Group -- 1.4.4.2 But, Keeping Ones Place in a Niche Is Not Guaranteed and Your Defenders may Be Few! -- 1.4.4.3 Using Vertebrates as a Reference Point for Studying the Cyclical Nature of Niche Openings and Closings -- 1.4.4.4 The Only Species Which Can Be Said to Represent End-Products of Evolution Are Those Species Which Are Extinct -- References -- Chapter 2: Defining the Concept of a Species Physiological Boundaries and Barriers -- 2.1 Introduction -- 2.2 Further Understanding the Nature and Limitations Imposed by Boundaries and Barriers -- 2.2.1 Barriers Are Not Fixed in Location and Time -- 2.2.2 Understanding the Factors that Define a Species Vital Boundaries -- 2.2.2.1 Defining Those Factors as Mathematical Variables. , 2.2.2.2 Level of Available Atmospheric Molecular Oxygen as an Example Variable -- 2.2.3 Organisms Which Utilize Other Species as Biological Vectors -- 2.2.4 Understanding the Use of Vital Boundaries When Treating Infectious Disease -- 2.2.5 How This Concept of Vital Boundaries Applies to Virus -- 2.3 Example Species -- 2.3.1 Human (Homo sapiens) -- 2.3.2 Atlantic Ridley (Lepidochelys kempii) -- 2.3.3 Dog (Canis lupus familiaris) -- 2.3.4 Red-Tailed Hawk (Buteo jamaicensis) -- 2.3.5 House Mouse (Mus musculus) -- 2.4 The Possiblilty of Mathematically Estimating Vital Boundaries -- 2.4.1 Linear Regression Model -- 2.4.1.1 Step One of the Linear Regression Technique -- 2.4.1.2 Step Two of the Linear Regression Technique -- 2.4.1.3 Adapting the Two Step Linear Regression Technique for Use with Longevity Values -- 2.4.2 Non-Linear Regression Model -- 2.4.3 My Best Suggestion for Mathematically Estimating Vital Boundaries -- 2.5 Relating This Concept to the Process of Evolution and the Niche of a Species -- 2.6 Some Questions and Answers Regarding This Concept -- References -- Chapter 3: Microbes and the Fossil Record: Selected Topics in Paleomicrobiology -- 3.1 Microbial Fossils: A Vast Field of Study -- 3.2 Microbial Fossil Preservation -- 3.2.1 Body Fossils -- 3.2.2 Microbially Induced Structures -- 3.2.2.1 Microbialites -- Microbially Induced Sedimentary Structures -- Stromatolites -- 3.2.2.2 Microborings -- 3.3 Recognizing Microbial Fossils -- 3.3.1 Recognizing Microbial Body Fossils -- 3.3.1.1 The Traditional Approach -- Indigenousness -- Syngenicity -- Biogenicity -- 3.3.1.2 The Contextual Approach -- 3.3.2 Recognizing Microbially Induced Structures -- 3.3.2.1 Microbialites -- Microbially Induced Sedimentary Structures -- Stromatolites -- 3.3.2.2 Microborings -- 3.4 Earth´s Oldest Fossils and the Archean Fossil Record. , 3.4.1 An Archean-Proterozoic Disparity -- 3.4.2 Brief History of Discovery -- 3.4.3 Salient Patterns in the Archean Fossil Record -- 3.4.4 Reevaluating Archean Fossil Datapoints -- 3.4.4.1 The Apex Chert Debate -- 3.4.4.2 The Isua and Akilia Debates -- 3.4.4.3 The Alan Hills 84001 Martian Meteorite Controversy -- 3.4.5 Oldest Traces of Life -- 3.5 Microbial Eukaryotes: Recognition and Early Fossil Record -- 3.5.1 Recognizing Early Eukaryotes -- 3.5.1.1 Morphological Criteria -- 3.5.1.2 Geochemistry: Hydrocarbon Biomarkers -- 3.5.2 Oldest Evidence for Eukaryotes -- 3.5.2.1 Acritarchs -- 3.5.2.2 Macrofossils -- 3.5.2.3 Eukaryotes in the Archean? -- 3.5.3 Salient Patterns in the Early Eukaryotic Fossil Record -- 3.6 Roles of Microbes in Taphonomic Pathways -- 3.6.1 Cautionary Tales -- 3.6.2 Authigenic Mineralization -- 3.6.2.1 Organomineralization -- 3.6.2.2 Biomineralization -- Burgess Shale-Type Preservation -- Phosphate Mineralization of Soft Tissue -- Iron Minerals and Pyritization -- Compression-Impression Leaf Fossilization -- 3.6.3 Doushantuo ``Embryos´´ -- 3.6.4 Microbial Mats -- 3.6.4.1 Death Masks -- 3.6.4.2 Trackways -- 3.6.5 Microbial Interactions with Bone -- 3.7 Microbial Symbioses in the Fossil Record -- 3.7.1 Lichen Symbioses -- 3.7.2 Mycorrhizal Symbioses -- 3.7.3 Microbial Endophytes -- 3.8 Future Directions -- References -- Chapter 4: Endolithic Microorganisms and Their Habitats -- 4.1 Introduction -- 4.2 Global Distribution of Endolithic Microorganisms -- 4.3 Microbial Diversity of Endolithic Habitats -- 4.4 Geology of Endolithic Habitats -- 4.5 Light Regime Within Endolithic Habitats -- 4.6 Nutrients -- 4.7 Microclimatic Conditions Within Endolithic Habitats -- 4.8 Microbial Activity in the Absence of Liquid Water -- 4.9 Adaptation to Stress -- 4.10 Colonization Extent -- 4.11 Controls on Endolithic Microbial Community Structure. , 4.12 Microbial Activity, Geochemistry, and Microbe-Mineral Interactions in Endolithic Habitats -- 4.13 Endolithic Biosignatures -- 4.14 Astrobiological Significance -- 4.15 Conclusions -- References -- Chapter 5: The Snotty and the Stringy: Energy for Subsurface Life in Caves -- 5.1 Introduction -- 5.2 Cavern Development and the Cave Environment -- 5.3 Energy and Carbon in Caves -- 5.3.1 Cave Ecosystems Based on Surface-Derived Organic Carbon -- 5.3.2 Cave Ecosystems Based on Inorganic Chemical Energy from Sulfide Oxidation -- 5.3.3 Cave Ecosystems Based on Nitrogen Oxidation: The Nullarbor Caves, Australia -- 5.3.4 Other Inorganic Chemical Energy Sources in Caves -- 5.3.5 Chemical Energy from the Host Rock: Lava Tube Caves -- 5.3.6 Communities Based on Photosynthesis: Artificial Lighting in Show Caves -- 5.4 Microbial Role in the Formation of Speleothems and Other Cave Deposits -- 5.4.1 Moonmilk -- 5.4.2 Pool Fingers -- 5.4.3 Vermiculations -- 5.4.4 Iron and Manganese Deposits -- 5.5 Microbial Contributions to Cave Formation -- 5.6 Conclusion -- References -- Chapter 6: Microbiology of the Deep Continental Biosphere -- 6.1 Introduction -- 6.2 Comparison of Deep Continental and Marine Biospheres -- 6.3 Methods for Sampling the Subsurface -- 6.4 Microbial Abundance -- 6.5 What Controls the Depth Limit of the Biosphere? -- 6.6 Geogas and SLiMES -- 6.7 Subsurface Biodiversity -- 6.8 Outlook for the Deep Continental Biosphere -- References -- Chapter 7: Microbiology of the Deep Subsurface Geosphere and Its Implications for Used Nuclear Fuel Repositories -- 7.1 Introduction -- 7.2 Microbial Diversity in the Deep Subsurface -- 7.2.1 Microbial Growth, Activity, and Survival -- 7.2.1.1 Microbial Energetics -- 7.2.1.2 Spores, Cell Dormancy, and Death -- 7.2.2 Biofilms -- 7.3 Deep Geological Repositories -- 7.3.1 The Host Rock Environment. , 7.3.2 The Engineered Barrier System -- 7.3.2.1 Metal Containers -- 7.3.2.2 Bentonite -- 7.3.2.3 Seals and Tunnel Backfill -- 7.3.2.4 Repository Interfaces -- 7.3.3 Environmental Factors -- 7.3.3.1 Temperature and Water Activity -- 7.3.3.2 Radiation -- 7.3.3.3 Salinity, Pressure, and Pore Size -- 7.3.3.4 Carbon and Energy Sources -- 7.4 Perturbation and Deep Subsurface Successional Change: Deep Geological Repositories for Used Nuclear Fuel as a Perturbation... -- 7.4.1 Sources of Microbes and Their Activity -- 7.4.2 Impact of Microbes on Introduced Materials -- 7.4.2.1 Microbial Metabolites and Extracellular Materials -- 7.4.2.2 Effect of Microbes on Permeability in the EBS -- 7.4.2.3 Microbiologically Influenced Corrosion of the Used Fuel Container -- Corrosion of Iron and Steel -- Corrosion of Copper -- Corrosion of Copper-Iron -- 7.4.2.4 Impact of Microbes on Radionuclide Speciation, Fate, and Movement -- 7.5 Concluding Remarks -- References -- Chapter 8: Life in Hypersaline Environments -- 8.1 Introduction -- 8.2 Diversity of Halophilic and Halotolerant Microorganisms -- 8.2.1 Archaea -- 8.2.2 Bacteria -- 8.2.3 Eukarya -- 8.2.4 Viruses -- 8.3 Strategies of Osmotic Adaptation in the Microbial World -- 8.4 Trophic Interrelationships Between Different Types of Halophiles Based on Organic Osmotic Solutes -- 8.5 Microbial Processes at High Salt: Possibilities and Limitations -- 8.6 Hypersaline Ecosystems: Case Studies -- 8.6.1 Solar Saltern Evaporation Ponds -- 8.6.2 Great Salt Lake -- 8.6.3 The Dead Sea -- 8.6.4 The Hypersaline Alkaline Lakes of Wadi an Natrun, Egypt -- 8.6.5 Deep-Sea Brines -- 8.6.6 Life Within Brine Inclusions in Salt Crystals -- 8.7 Final Comments -- References -- Chapter 9: Microbes and the Arctic Ocean -- 9.1 What Is a Food Web? -- 9.2 What Is Special About the Arctic Ocean? -- 9.3 The Fundamental Importance of Sea Ice. , 9.4 Structure of the Arctic Marine Food Web.

Note: Intro -- List of Publications -- Journal Articles -- Conference Proceedings -- Supervisor's Foreword -- Abstract -- Acknowledgments -- Contents -- 1 Introduction -- 2 Quantum Chromodynamics -- 2.1 Mathematical Formulation -- 2.2 Lattice Quantum Field Theory -- 2.2.1 The Discretised Action -- 2.2.2 Lattice Expectation Values -- 2.2.3 Scale Setting -- 2.3 Strangeness and Charge Symmetry Violation in the Nucleon -- 2.3.1 Nucleon Strangeness -- 2.3.2 Charge Symmetry Violation -- References -- 3 Chiral Perturbation Theory -- 3.1 Effective Field Theory -- 3.2 Chiral Symmetry -- 3.3 The Chiral Effective Lagrangian -- 3.3.1 Pseudo-Goldstone Bosons -- 3.3.2 Octet Baryons -- 3.3.3 Decuplet Baryons and Resonances -- 3.3.4 Feynman Rules -- 3.4 Chiral Power Counting -- 3.5 Finite-Range Regularisation -- 3.6 The Nucleon Mass -- 3.7 Finite-Volume Corrections -- References -- 4 Octet Baryon Mass Splittings -- 4.1 SU(3) Chiral Extrapolation -- 4.2 Fits to Isospin-Averaged Lattice QCD Simulation Results -- 4.3 Mass Splittings -- 4.4 Summary and Discussion -- References -- 5 Sigma Commutators -- 5.1 The Feynman-Hellmann Theorem -- 5.2 Light and Strange Sigma Terms -- 5.3 Charge Symmetry Violation -- 5.4 Summary and Discussion -- References -- 6 Parton Distribution Moments -- 6.1 Moments of Quark Distribution Functions -- 6.2 Chiral Perturbation Theory -- 6.2.1 Feynman Rules -- 6.2.2 Feynman Diagrams -- 6.2.3 Loop Integrals -- 6.2.4 Loop Contributions -- 6.2.5 Fit Functions -- 6.3 Fits to Lattice QCD Simulation Results -- 6.4 Hyperon Spin Fractions and the Proton Spin Puzzle -- 6.5 Charge Symmetry Violation -- 6.5.1 Linear Flavour Expansion -- 6.5.2 Chiral Expansion -- 6.6 Summary and Discussion -- References -- 7 Electromagnetic Form Factors -- 7.1 Dirac, Pauli and Sachs Form Factors -- 7.2 Lattice QCD Simulation -- 7.2.1 Simulation Parameters. , 7.2.2 Lattice Method -- 7.2.3 Lattice Results for F1 and F2 -- 7.3 Connected Chiral Perturbation Theory -- 7.3.1 Partially-Quenched Chiral Perturbation Theory -- 7.3.2 Electromagnetic Form Factors of the Octet Baryons -- 7.4 Fits to Lattice Simulation Results -- 7.4.1 Finite-Volume Corrections -- 7.4.2 Binning in Q2 -- 7.4.3 Fits -- 7.4.4 Test of Finite-Volume Effects -- 7.5 Electromagnetic Form Factors at the Physical Point -- 7.5.1 Isovector Quantities -- 7.5.2 Connected Baryon Form Factors -- 7.5.3 Magnetic and Electric Radii -- 7.5.4 Quark Form Factors -- 7.5.5 Ratio of Electric and Magnetic Form Factors -- 7.6 Charge Symmetry Violation -- 7.6.1 CSV Form Factor Formalism -- 7.6.2 Disconnected Contributions to the CSV -- 7.6.3 CSV Relevant to the Strange Electromagnetic Form Factors -- 7.7 Strange Nucleon Form Factors -- 7.7.1 Indirect Determination of the Strange Form Factors -- 7.7.2 Strange Form Factors at Q2> -- 0 -- 7.7.3 Strange Magnetic Moment -- 7.8 Summary and Discussion -- References -- 8 Summary and Outlook -- Appendix A Formal Details of Heavy Mass Techniques -- Appendix B Definitions and Identities -- Appendix C Derivations for Chapter 3 -- Appendix D Tables of Chiral Coefficients -- Appendix E Deep Inelastic Scattering and the OperatorProduct Expansion -- Appendix F Chiral Extrapolation Formulae for Momentsof PDFs -- Appendix G Lattice Simulation Results for theElectromagnetic Form Factors -- Appendix H Additional Results for Chapter 7.

Note: Intro -- Preface -- Contents -- Part I History and Origins -- 1 Origins of the Hayflick System, the Phenomenon and the Limit -- 1.1 The Paradigm Shift -- 1.2 Human Vaccines in WI-38 Cells -- 1.3 Strength of Character and the Lawsuit -- 1.4 Humble Beginnings -- 1.5 Biogerontology as a Mature Science -- 1.6 The Hayflick Phenomenon and Cancer -- 1.7 Aging In Vivo -- 1.8 The Aim of Biogerontology -- 1.9 The Future -- 1.10 And Finally… -- 2 Experimental Foundations of the Hayflick System -- 2.1 Coming in Picture -- 2.2 Program or Stochastic? -- 2.3 Cristofalo Index -- 2.4 Paul Phillips -- 2.5 Aging as a Science -- 2.6 Cosmetics and Aging -- 2.7 Dilemma and Cellular Aging In Vitro -- 2.8 The Future -- Part II Serial Passaging and Progressive Changes -- 3 Slowing Down of the Cell Cycle During Fibroblast Proliferation -- 3.1 Evolution of Cell Types During Slowing Down of the Cell Cycle -- 3.2 Kinetics of Proliferation During Slowing Down of the Cell Cycle -- 3.3 Changes Coupled with the Kinetics of Proliferation During Slowing Down of the Cell Cycle -- 3.3.1 Structure-Dependent Functional Changes -- 3.3.2 Metabolic Events -- 3.3.3 Gene Related Events -- 3.3.4 Shortening of Telomeres -- 3.3.5 Asymmetric Cell Division -- 3.4 Other Cell Systems -- 3.5 Conclusions -- References -- 4 Influence of Donor Age and Species Longevity on Replicative Cellular Senescence -- 4.1 Introduction -- 4.1.1 Senescent Arrests -- 4.1.2 Cell Replication Capacity as "Anti-aging" Mechanism -- 4.2 Technique: Mass Culture Maximum Replicative Potential Versus Colony Forming Ability -- 4.3 Donor Age -- 4.3.1 Donor Age and Mass Culture Proliferative Life Span -- 4.3.2 Donor Age and Colony Forming Ability -- 4.4 Species Longevity -- 4.5 Replicative Senescence Appears as a Not Universal Phenomenon -- 4.6 Summary and Conclusions -- References. , 5 Ageing of the Stem Cells: The Conjoined Twosome Growing Old: Stem Cell and Its Niche -- 5.1 Background -- 5.2 Current Distinctions of What an Adult Stem Cells Is -- 5.3 Somatic Stem Cell Aging and Loss of Tissue Regenerative Potential -- 5.4 Aging of Stem Cell Niches and Extrinsic Aging of Stem Cells -- 5.5 Perspective -- References -- 6 Ageing and Senescence in Immune Cells In Vitro and In Vivo -- 6.1 Introduction -- 6.2 Culture and Cloning of Human T Lymphocytes -- 6.2.1 Cloning Conditions and Cloning Efficiencies -- 6.2.2 Clonal Expansion -- 6.2.3 Human TCC from Different Sources of Lymphocytes -- 6.2.4 Culturing at Lower Oxygen Levels and Use of Anti-oxidants -- 6.3 Progressive Changes to TCC with Accumulating PD -- 6.3.1 Surface Phenotype -- 6.3.2 Functional Changes -- 6.3.3 Telomere Lengths, DNA Damage Levels, Mitochondrial Damage, miRNA -- 6.3.4 Changes in Gene Expression -- 6.3.5 Proteomic Changes -- 6.4 Conclusions -- References -- 7 Telomeres Shortening: A Mere Replicometer? -- 7.1 Telomeres and Senescence -- 7.1.1 Cellular Senescence -- 7.1.2 What Are Telomeres? -- 7.1.3 The Role of Dysfunctional Telomeres in Replicative Senescence -- 7.1.4 Stress and Telomere Shortening -- 7.2 Persistent DNA Damage Is Important for Stabilising Senescence -- 7.3 Dysfunction in Telomeres Irrespective of Length -- References -- 8 Modeling Cellular Aging: An Introduction - Mathematical and Computational Approaches -- 8.1 Models of Cellular and Subcellular Aging -- 8.1.1 Thinking About, Building and Analyzing Mathematical Models and Computer Simulations -- 8.1.2 Constructing a Model -- Thinking About the Time Variable -- Thinking About the Dependent Variable(s) -- More Than One Dependent Variable -- More Than One Independent Variable -- 8.2 Senescence at the Sub-cellular and the Single Cellular Levels -- 8.2.1 Mathematics of Somatic Mutations. , 8.2.2 Mathematics of Error Catastrophe -- 8.2.3 Mathematics of Error Propagation -- 8.2.4 Mathematics of Recombination -- 8.2.5 Mathematics of Accumulation/Depletion -- 8.3 Concluding Chapter Thoughts -- References -- Part III Ageing, Cancer and Senescence -- 9 Cell Cycle Checkpoints and Senescence -- 9.1 Cellular Senescence -- 9.2 Triggers of Senescence -- 9.3 Stress Induced Premature Senescence (SIPS) -- 9.4 Cellular Senescence and Cancer -- 9.5 Cell Cycle Checkpoints and Senescence -- 9.6 p53 Checkpoint -- 9.7 pRB Checkpoint -- References -- 10 Mitochondrial Reactive Oxygen Species in Cellular Senescence -- 10.1 Introduction: Mitochondria and Cellular Senescence -- 10.2 The Generation of Mitochondrial ROS -- 10.3 Mitochondrial ROS and Longevity -- 10.4 Mitochondrial ROS as an Inducer of Senescence -- 10.5 ETC Dysfunction in Generating Mitochondria ROS -- 10.6 Impaired Mitochondrial Dynamics in Generating Mitochondrial ROS -- 10.7 Metabolic Disruption in Promoting Mitochondrial ROS -- 10.8 Senescence Induction of Mitochondrial ROS: p53 Effector Response -- 10.9 Senescence Induction of Mitochondrial ROS: Metabolic Disruption -- 10.10 Mitochondrial ROS Interventions for Suppressing Cellular Senescence -- 10.11 Conclusion -- References -- 11 Cellular Aging and Tumor Regulation -- 11.1 History -- 11.2 Cell Senescence and Tumor Formation -- 11.3 Cellular Signaling in Tumorigenesis and Senescence -- 11.3.1 DNA Damage, Telomere Shortening and Senescence -- 11.3.2 Oncogene-Induced Senescence -- 11.3.3 Stress-Induced Premature Senescence -- 11.3.4 Interfering with Senescence Signaling: A Therapeutic Approach? -- 11.4 Cellular Senescence in the Immune System and Tumor Growth -- 11.4.1 Definition and Features of Immunosenescence -- 11.4.2 Involvement of the Innate and Adaptive Immune System in Immunosenescence -- 11.4.3 Immunosenescence and Cancer. , 11.4.4 Strategies to Revert Immunosenescence -- 11.5 Conclusions -- References -- 12 Biomarkers of Replicative Senescence Revisited -- 12.1 Introduction -- 12.2 Criteria to Define Biomarkers of Aging -- 12.3 Biomarkers of Replicative Senescence -- 12.3.1 Replication Potential -- 12.3.2 Morphological Biomarkers: Cell Size and Ultrastructural Changes -- Shape and Size -- Lysosomes -- Mitochondria -- Nucleus and Nucleolus -- Endoplasmic Reticulum-Polysomes -- Golgi and Vacuoles -- 12.3.3 Telomere Length and Telomerase -- 12.3.4 Resistance to Apoptosis -- 12.3.5 Cell Cycle-Dependent Kinase Inhibitors -- p16 -- p21 (CIP1/WAF1/SDI1) -- 12.3.6 Tumor Suppressor Proteins -- pRb -- p53 -- 12.3.7 Lamin B -- 12.3.8 Promyelocytic Leukemia Nuclear Bodies - PML NB's -- 12.3.9 Chromatin-Associated Biomarkers -- Senescence-Associated Heterochromatic Foci (SAHF) -- Gamma-Histone A2X and DNA Damage -- 12.3.10 DNA, Lipid and Protein Oxidative Damage -- 12.3.11 Sirtuins and NAD+ -- 12.3.12 Lysosomal Markers -- Senescence-Associated Beta Galactosidase -- Lipofuscin -- 12.3.13 Mitochondrial Activities -- 12.4 Senescent Cell Plasma-Membrane Associated Biomarkers -- 12.5 Epigenetic Biomarkers -- 12.6 Small and Long Non-coding RNAs -- 12.7 Senescence Secretome and Metabolome, Frailty and Whole-Body Physiological Biomarkers -- 12.8 Concluding Remarks -- References -- Part IV Ageing Modulators -- 13 Stress-Induced (Premature) Senescence -- 13.1 Introduction -- 13.2 Different Types of Senescence -- 13.2.1 Replicative Senescence or Telomere-Dependent Senescence -- 13.2.2 Oncogene-Induced Senescence -- 13.2.3 Stress-Induced Senescence: Premature or Not? -- 13.3 Models of Stress-Induced Senescence -- 13.4 Damage Induced by SIS -- 13.4.1 DNA Damage -- 13.4.2 Oxidative Stress -- 13.5 Cellular and Molecular Characteristics of SIS -- 13.5.1 Biomarkers of Senescence. , 13.5.2 Gene and Protein Expression: Are RS and SIS Identical Phenotypes? -- 13.6 SIS, Telomeres and Telomerase -- 13.7 Molecular Pathways -- 13.7.1 TGF-ß1 Pathway -- 13.7.2 IGF-1R -- 13.8 Stress-Induced Senescence In Vivo -- 13.9 SIS in Cancer Treatment -- References -- 14 Implications of Cellular Senescence on Aging and Disease in the Brain -- 14.1 Introduction -- 14.2 The Aging Brain -- 14.3 Senescence-Related Changes in CNS Cell Types -- 14.3.1 Neurons -- 14.4 Neural Stem/Progenitor Cells -- 14.5 Oligodendrocytes -- 14.6 Microglia -- 14.7 Astrocytes -- 14.8 Discussion -- References -- 15 Small Noncoding RNAs in Senescence and Aging -- 15.1 Introduction -- 15.2 miRNAs -- 15.2.1 miRNAs and the Advent of Deep Sequencing -- 15.2.2 Intracellular miRNAs in Senescence, Aging, and Calorie Restriction -- 15.2.3 Extracellular miRNAs -- 15.2.4 Extracellular miRNAs in Senescence, Aging and Calorie Restriction -- 15.3 tRNA- and YRNA-Derived Small RNAs -- 15.3.1 Intracellular tRNA- and YRNA-Derived Small RNAs -- 15.3.2 Extracellular tRNA- and YRNA-Derived Small RNAs -- 15.3.3 Functions of tRNA- and YRNA-Derived Small RNAs -- 15.3.4 Potential Role of tRNA- and YRNA-Derived Small RNAs in Senescence, Aging and Calorie Restriction -- References -- 16 Targeting Senescent Cells to Improve Human Health -- 16.1 Cellular Senescence and the Senescence-Associated Secretory Phenotype -- 16.2 Senescence Drives Age-Related Phenotypes -- 16.3 Clearance of Senescent Cells Delays Aging-Associated Phenotypes -- 16.4 Clearance of Senescent Cells for Therapeutic Purposes -- 16.5 Clearance of Senescent Cells in Chronic Age-Related Diseases -- 16.5.1 Cancer -- 16.5.2 Side Effects of Cancer Therapy -- 16.5.3 Atherosclerosis -- 16.5.4 Obesity -- 16.5.5 Type 2 Diabetes -- 16.5.6 Neurodegenerative Disorders -- 16.5.7 Chronic Obstructive Pulmonary Disease. , 16.5.8 Idiopathic Pulmonary Fibrosis.

Note: Intro -- Foreword -- Preface -- Acknowledgment -- Contents -- Symbols -- Roman Letters -- Greek Letters -- Abbreviations -- Abstract -- 1 Basic Principles of ERP Research, Surprise, and Probability Estimation -- 1.1 Data Acquisition and Initial Analysis -- 1.2 Signal-to-Noise Ratio Estimation for Event-Related Potentials -- 1.3 Circularity in Data Analyses -- 1.4 Probabilities and Surprise -- 1.4.1 Bayesian Updating -- 1.4.2 Predictive Surprise -- 1.5 Probability Weighting Functions -- 2 Introduction to Model Estimation and Selection Methods -- 2.1 An Example Study -- 2.2 Classical Single-Level Models -- 2.2.1 The Null and Informative Hypotheses -- 2.2.2 The General Linear Model -- 2.3 Hierarchical Multiple-Level Models -- 2.3.1 The First Level -- 2.3.2 The Second Level -- 2.3.3 The Third Level -- 2.4 Model Estimation and Selection -- 2.4.1 Collapsing and Augmenting the Hierarchical Model -- 2.4.2 Model Parameter Optimization and Likelihood Calculation -- 2.4.3 Model Selection Using Bayes Factors and Posterior Model Probabilities -- 2.4.4 Group Studies -- 2.5 A Transfer Example Experiment---Setup -- 2.5.1 Signal-to-Noise Ratio Simulation -- 2.5.2 Synthetic Data and Experimental Conditions -- 2.5.3 The Model Space -- 2.6 A Transfer Example Experiment---Results -- 2.6.1 A Single Subject -- 2.6.2 Multiple Subjects -- 2.7 Evaluation Summary -- 3 A New Theory of Trial-by-Trial P300 Amplitude Fluctuations -- 3.1 Overview -- 3.2 Participants, Experimental Design, Data Acquisition, and Data Analysis -- 3.3 State-of-the-Art Observer Models and Surprise -- 3.3.1 Approach by Squires et al. (SQU) -- 3.3.2 Approach by Mars et al. (MAR) -- 3.3.3 Approach by Ostwald et al. (OST) -- 3.3.4 Surprise Based on the SQU, MAR, and OST Models -- 3.4 The Digital Filtering Model (DIF) -- 3.4.1 Short-Term Memory -- 3.4.2 Long-Term Memory -- 3.4.3 Alternation Expectation. , 3.4.4 Explanatory Notes -- 3.4.5 Surprise Based on the DIF Model -- 3.4.6 DIF Model Parameter Training -- 3.5 Specification of the Design Matrices for Model Estimation -- 3.6 Results -- 3.6.1 Conventional ERP Analyses -- 3.6.2 Model-Based Trial-by-Trial Analyses -- 3.7 Summary and Discussion -- 4 Bayesian Inference and the Urn-Ball Task -- 4.1 Overview -- 4.2 Participants, Experimental Design, Data Acquisition, and Data Analysis -- 4.3 The Bayesian Observer Model -- 4.3.1 Bayes' Theorem and the Urn-Ball Task -- 4.3.2 The Belief Distribution (BEL) -- 4.3.3 The Prediction Distribution (PRE) -- 4.3.4 Surprise Based on the Bayesian Observer Model -- 4.3.5 Summary and Visualization of Bayesian Inference -- 4.4 Incorporating Probability Weighting Functions into the Bayesian Observer Model -- 4.4.1 Probability Weighting of the Inference Input (BELSI and PRESI) -- 4.4.2 Probability Weighting of the Inference Output (BELSO and PRESO) -- 4.4.3 Weighting Parameter Optimization -- 4.5 The DIF Model in the Urn-Ball Task -- 4.5.1 The Objective Initial Prior (DIFOP) -- 4.5.2 The Initial Prior Using Weighting Functions (DIFSP) -- 4.6 Specification of the Design Matrices for Model Estimation and Selection in the Urn-Ball Task -- 4.7 Results -- 4.7.1 Conventional ERP Analyses -- 4.7.2 Model-Based Trial-by-Trial Analyses -- 4.8 Summary and Discussion -- 5 Summary and Outlook -- Appendix -- Bibliography.

Note: Intro -- Contents -- Introduction -- Part I Isostatic Control of Basin Subsidence in Response to Extension and Thermal Activation of the Lithosphere -- 1 Amplitude and Duration of Thermal and Tectonic Activation of Basins-An Assessment in the GALO System -- Abstract -- 1.1 The Principles of the Numerical Reconstruction of the Thermal History of the Basin -- 1.1.1 Equation and Physical Attributes of Sedimentary Rocks -- 1.1.2 The Basement of the Basin -- 1.1.3 The Base of the Lithosphere and Latent Heat Effect -- 1.1.4 Boundary and Initial Conditions -- 1.1.5 Numerical Solution of the Equation -- 1.2 Tectonic Subsidence in Burial History of Sedimentary Basin-Algorithm of Calculation -- 1.2.1 The First Method of Tectonic Subsidence Calculation -- 1.2.2 Calculation of Tectonic Subsidence by Second Method -- 1.3 Numerical Simulation of Thermal Activation and Stretching of the Basin Lithosphere in the GALO System -- 1.4 Analysis of the Tectonic Subsidence in Application to Concrete Basin -- 1.5 Isostatic Approach and Yield Strength of the Lithosphere -- 1.6 Conclusion -- References -- 2 The Lithosphere Extension and Hydrocarbon Generation in the Eastern Continental Passive Margin of India -- Abstract -- 2.1 Geological History of the Krishna-Godavari and Mahanadi Basins -- 2.1.1 Tectonic History of the Bay of Bengal -- 2.1.2 Sedimentation History -- 2.2 Thermal, Burial and Maturity Histories of the Krishna-Godavari and Mahanadi Basins -- 2.2.1 Input Data for Modeling -- 2.2.2 Thermal and Maturation Histories of Sedimentary Basins in the Eastern Shelf of India: Results of Modeling -- 2.3 A Comparison Temperature and Maturation Histories of the Probable Source Rocks in the Basins in the Shallow and Deep-Sea Areas -- 2.3.1 Estimation of Smectite/Illite Ratio During Diagenesis of Clays. , 2.3.2 Comparison of Thermal and Maturation Histories of the Probable Source Rocks -- 2.3.3 Correlation Between Smectite/Illite Transformation and Ro% -- 2.4 Hydrocarbon Generation by Probable Source Rocks in Shelf Areas of the Krishna-Godavary and Mahanady Basins -- 2.5 Conclusion -- References -- 3 Thermal Activation and Stretching of the East Barents Sea Lithosphere, Russia -- Abstract -- 3.1 Short Geological and Geophysical Description of the East Barents Basin -- 3.2 Burial, Thermal and Maturation Histories of the Sedimentary Rocks in the Basin -- 3.2.1 Calculation of Temperature Distribution with Depth in Sedimentary Sections of the Basin -- 3.2.2 Calculation of Maturity Degree of Organic Matter in Sedimentary Section of the Basin in the EASY%Ro and Basin%Ro Models of Vitrinite Maturation -- 3.2.3 Realization History of Hydrocarbon Potential of Probable Source Rocks of the East Barentz Basin -- 3.3 Thermal Evolution and Two Stage of Stretching of the Basin Lithosphere -- 3.3.1 Heat Flow and Thermal State of the Basin -- 3.3.2 An Analysis of Tectonic Subsidence of the Basin -- 3.4 Conclusion -- References -- 4 Thermal Regime and Extension of the Lithosphere in Different Tectonic Structures of the Sirte Basin, Libya -- Abstract -- 4.1 Tectonic and Geological History of the Basin -- 4.2 Temperature and Maturation Histories of the Sirte Basin -- 4.2.1 The Principles of Thermal History Computation -- 4.2.2 Evolution of the Temperature Regime of Sedimentary Rocks in the Basin -- 4.2.3 Maturation History of Organic Matter in the Sirt Basin -- 4.2.4 Realization of Hydrocarbon Potential in the Sirt Basin -- 4.3 Variations in Amplitude of the Lithosphere Extension in Different Structures of the Sirte Basin -- 4.3.1 Estimation of Amplitude of Tectonic Subsidence -- 4.3.2 Comparison with the Model [7] of Tectonic Subsidence. , 4.3.3 Analysis of Tectonic Subsidence in Other Models -- 4.4 Conclusion -- References -- 5 Tectonic History and Thermal Evolution of Sedimentary Basin in the North-Eastern Shelf of Sakhalin Island, Russia -- Abstract -- 5.1 Some Problems of the Region Study (Introduction) -- 5.2 Tectonic and Geological History of the North and Middle Sakhalin -- 5.3 Burial, Thermal and Maturation Histories of Sedimentary Rocks -- 5.3.1 The Initial Data for Basing Modeling -- 5.3.2 Temperature and Maturity Variations in the Sedimentary Blanket of the Basin -- 5.3.3 Realization of Hydrocarbon Potential by the Main Formations of the Basin -- 5.4 Analysis of Tectonic Subsidence in Two Variants of Tectonic History of the Basin -- 5.5 Conclusion -- References -- Part II The Maturation of Organic Matter and Hydrocarbon Generation in the Vicinity of Intrusions and Subtrappean Sedimentary Complexes -- 6 The Trappean Complex of the Siberian Platform -- Abstract -- 6.1 Geological Setting -- 6.2 Burial and Thermal Histories of Sedimentary Basins in Kamo Arch of Bayakitskaya Anticline and the Kureika Basin of the Siberian Platform -- 6.3 Evolution of Maturation Degree of Organic Matter During Burial History of the Kuyumba-12 and Kiramkinskaya-1 Sedimentary Sections -- 6.3.1 Formation of Maturity Aureole in the Kuyumba-12 Sedimentary Section Under the Influence of Intrusions -- 6.3.2 Formation of Maturity Aureole in the Kiramkinskaya-1 Sedimentary Section Under the Influence of Intrusions -- 6.4 Estimation of Hydrocarbon Generation in Sedimentary Sections with Intrusions -- 6.5 Conclusion -- References -- 7 Duration of the Intrusion Formation and Its Relation to the Size of Thermal and Maturity Aureoles of the Intrusion Bodies -- Abstract. , 7.1 Difference Between Maturity and Thermal Aureoles in the Models of Instantaneous and Finite Time Intrusions on the Examples of the Well Dated Intrusions -- 7.1.1 Model with Finite Times of Intrusion Formation -- 7.1.2 The 118 m Thick Sill from Midland Valley, Scotland -- 7.1.3 Example of the 400 m sill in the Kiramkinskaya Well of the Kureika Basin in Siberia Platform -- 7.2 Thermal and Maturity Aureoles in Subtrappean Sedimentary Complex-Dependence on the Time of the Trap Formation -- 7.2.1 The Trap's Provinces in the World -- 7.2.2 Principles and Input Parameters of the Modeling -- 7.2.3 Maturity Aureole Under Trap: Results of Numerical Modeling -- 7.2.4 Influence of Some Factors on Estimated Size of Maturity Aureole -- 7.3 Conclusion -- References -- 8 Deccan Trap, India -- Abstract -- 8.1 Introduction -- 8.2 Geological Setting and Rock Lithology -- 8.3 The Western Passive Margin of India -- 8.3.1 Initial Data for Modeling -- 8.3.2 Modeling of Burial and Thermal Histories of the Basin -- 8.3.3 Analysis of Tectonic Subsidence of the Basin -- 8.3.4 Maturation of Organic Matter in the Over- and Sub-Trappean Sedimentary Complexes -- 8.3.5 Realization of Hydrocarbon Potential by Probable Source Rocks of Sub- and Over-Trappean Sedimentary Complexes in the Bombay Offshore -- 8.4 The Subtrappean Basins of the Indian Shield -- 8.4.1 Saurashtra Region, North-Western India (Profile 1) -- 8.4.2 Kutch Region, North-Western India (Profile 2) -- 8.4.3 Western Part of the Deccan Syneclise, Central India (Profile 3) -- 8.4.4 Central Part of the Deccan Syneclise, India (Profile 4) -- 8.5 Conclusion -- References -- Part III Change in Heat Flow and Rock Temperature Due to Sharp Climate Variations in the Quaternary -- 9 Evolution of Permafrost and of Gas Hydrate Stability Zone -- Abstract -- 9.1 Introduction. , 9.2 Analysis a Thermal Evolution of the Regions with Permafrost Formation Using of Basin Modeling System -- 9.2.1 Formation of Initial Distribution of Temperature and Petrophysical Parameters of Sedimentary Rocks in the FROST Program -- 9.2.2 Heat Conductivity of Frozen and Thawed Rocks -- 9.2.3 Heat Capacity of Frozen and Thawed Rocks -- 9.2.4 Change in Ice Liquidus and Thickness of Permafrost Due to Salt Content in Porous Water -- 9.2.5 Unfrozen Water Content in Porous Space at Negative Temperatures and Its Influence on Permafrost Evolution -- 9.2.6 Some Specific Features of Numerical Scheme in Solution of Heat Transfer Equation in the Permafrost Problem -- 9.3 Estimations of the Depths of the Gas Hydrate Stability Zone -- 9.3.1 Gas Hydrates: Occurrence and Mechanism of Origin -- 9.3.2 Bottom Simulating Reflector and Gas Hydrate Occurence -- 9.3.3 Estimate of Depth of the Zones of Gas Hydrate Stability in the Basin Modeling Procedure -- 9.4 Conclusion -- References -- 10 Influence of Climate Variations on Rock Temperature and Heat Flow -- Abstract -- 10.1 Problem Statement and Initial Data for Modelling the Evolution of Permafrost -- 10.2 Change of Temperature and Heat Flow with Depth in Permafrost Zones -- 10.3 Permafrost Thickness and Zone of Gas-Hydrate Stability -- 10.4 Contribution of Different Time-Periods of Climate Variations to Formation of Permafrost -- 10.5 Influence of Climate Variations on the Temperature and Heat Flow Distributions with Depth in the Regions of Total Degradation of Permafrost -- 10.6 Formation the Present-Day Temperature Distribution with Depth in the Arctic Field of the East Barents Basin -- 10.7 Paleoclimate and Depth-Variations in Rock Temperatures in the North-East Sakhalin Shelf -- 10.8 Conclusion -- References -- Conclusions.

Note: Intro -- Supervisor's Foreword -- Preface -- Declaration -- Contents -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 A Brief History of the Discovery of Galaxies and AGN -- 1.1.1 Galaxies -- 1.1.2 Active Galactic Nuclei -- 1.2 AGN Structure and Multi-wavelength Emission -- 1.2.1 The Growing BH -- 1.2.2 AGN Standard Model and Broad-Band Continuum SEDs -- 1.2.3 AGN Standard Model and the Emission-Line Regions -- 1.2.4 Bolometric Luminosities -- 1.3 The Census of AGN Activity -- 1.3.1 Optical/UV Surveys -- 1.3.2 X-Ray Surveys -- 1.3.3 Infrared Surveys -- 1.3.4 Radio Surveys -- 1.3.5 The AGN Demography -- 1.4 The Co-evolution of BH and Galaxy Growth -- 1.4.1 The Cosmic Space Density of BH Growth and Star Formation Are Similar -- 1.4.2 Most BH Growth Occurs in Star-Forming Galaxies -- 1.4.3 BH Masses Are Related to Galaxy Bulge Properties -- 1.5 The Influence of AGN on the Evolution of Galaxies -- 1.5.1 Matching Models to Observations: AGN to the Rescue -- 1.5.2 Outflows -- 1.5.3 The SFRs of Luminous AGN -- 1.6 Thesis Outline -- References -- 2 Integral Field Spectroscopy and Spectral Energy Distributions -- 2.1 Integral Field Spectroscopy -- 2.1.1 Introduction -- 2.1.2 Integral Field Spectroscopy -- 2.1.3 The Instruments Used in This Thesis -- 2.1.4 Data Reduction -- 2.2 Spectral Energy Distributions -- 2.3 Calculation of SFRs and AGN Luminosities -- References -- 3 Energetic Galaxy-Wide Outflows in High-z ULIRGs Hosting AGN Activity -- 3.1 Motivation -- 3.2 Introduction -- 3.3 Observations and Data Reduction -- 3.3.1 Target Selection -- 3.3.2 IFU Observations -- 3.3.3 Flux Calibration and Stacking -- 3.4 Star-Formation Rates and AGN Luminosities -- 3.5 Analysis and Results -- 3.5.1 Galaxy-Integrated Spectra -- 3.5.2 Surface Brightness, Velocity and FWHM Maps -- 3.5.3 Regions Dominated by Narrow and Broad Emission Lines. , 3.5.4 Velocity Profiles -- 3.6 Discussion -- 3.6.1 Tracing Galaxy Dynamics, Mergers and Outflows -- 3.6.2 Outflow Properties -- 3.7 Conclusions -- References -- 4 Kiloparsec Scale Outflows Are Prevalent in Luminous AGN: Outflows and Feedback in the Context of the Overall AGN Population -- 4.1 Motivation -- 4.2 Introduction -- 4.3 Targets, Observations and Data Reduction -- 4.3.1 Target Selection -- 4.3.2 Gemini-South GMOS Observations and Data Reduction -- 4.3.3 SFRs, AGN Luminosities and the Origin of the Radio Emission -- 4.4 Velocity Definitions and Spatially Resolved Kinematics -- 4.4.1 Non-parametric Velocity Definitions -- 4.4.2 Emission-Line Profile Fitting Procedure -- 4.4.3 Velocity Maps and Velocity-Distance Profiles -- 4.5 Results -- 4.5.1 Extended Emission-Line Regions: Sizes and Morphologies -- 4.5.2 Spatially-Resolved Ionised Gas Kinematics -- 4.5.3 Outflow Properties: Estimates of Mass, Energy and Momentum -- 4.6 Discussion -- 4.6.1 What Drives the Outflows? -- 4.6.2 What Role Do These Outflows Play in Galaxy Evolution? -- 4.7 Conclusions -- References -- 5 Storm in a ``Teacup'': A Radio-Quiet Quasar with approx10kpc Radio-Emitting Bubbles and Extreme Gas Kinematics -- 5.1 Motivation -- 5.2 Introduction -- 5.3 Data Acquisition, Reduction and Analysis -- 5.3.1 VLA Radio Data -- 5.3.2 VIMOS IFU Data -- 5.3.3 HST Imaging -- 5.4 Results and Discussion -- 5.4.1 Summary of Source Structure -- 5.4.2 What Powers the Core Radio Emission and Outflow? -- 5.4.3 What Powers the approx10kpc Radio Bubbles? -- 5.5 Conclusions -- References -- 6 No Submillimetre Signature of Star Formation Suppression Among X-Ray Luminous AGN -- 6.1 Motivation -- 6.2 Introduction -- 6.3 Catalogues and Data -- 6.3.1 X-Ray Data -- 6.3.2 IR Data -- 6.4 Measuring Average Star Formation Rates -- 6.5 Results -- 6.5.1 Discussion -- References -- 7 Conclusions. , 7.1 The Identification and Characterisation of Galaxy-Wide Outflows in ULIRGs Hosting AGN Activity -- 7.2 Galaxy-Wide Outflows in the Context of the Overall AGN Population -- 7.3 Observations to Understand the Relationship Between Radio Emission and Outflows -- 7.4 Searching for Observational Evidence That Luminous AGN Suppress Star Formation -- 7.5 Overall Summary and Outstanding Issues -- Reference -- 8 Ongoing and Future Work -- 8.1 What Physical Processes Drive the Outflows in AGN? -- 8.2 What Are the Multi Gas-Phase Properties of Galaxy-Wide Outflows? -- 8.3 What Is the Prevalence of Ionised Outflows in Galaxies Across Cosmic Time? -- 8.4 What Impact Do Outflows Have on Galaxy Evolution? -- 8.5 Final Remarks -- References -- Appendix A AGN Emission Lines: Some RelevantInformation and Applications -- Appendix B Assumed Cosmology -- Appendix C Acronyms -- Index.

Note: Intro -- Contents -- Contributors -- Chapter 1: Introduction: Exotic Annual Bromus in the Western USA -- 1.1 The Spectrum of Exotic Annual Bromus -- 1.2 Synthesis of Patterns, Challenges, and Opportunities -- References -- Part I: Environmental Impacts of Bromus Species -- Chapter 2: Exotic Annual Bromus Invasions: Comparisons Among Species and Ecoregions in the Western United States -- 2.1 Introduction -- 2.1.1 Resistance and Resilience to Bromus Invasions -- 2.1.2 Species, Ecoregions, and Chapter Structure -- 2.2 Warm Deserts -- 2.2.1 Invasion Potential of Warm Deserts by Bromus -- 2.2.2 Ecosystem Threats to Warm Deserts from Bromus -- 2.2.3 Management Strategies for Bromus in Warm Deserts -- 2.3 Mediterranean California -- 2.3.1 Invasion Potential of Mediterranean California by Bromus -- 2.3.2 Ecosystem Threats to Mediterranean California from Bromus -- 2.3.3 Management Strategies for Bromus in Mediterranean California -- 2.4 Cold Deserts -- 2.4.1 Invasion Potential of Cold Deserts by Bromus -- 2.4.2 Ecosystem Threats to Cold Deserts from Bromus -- 2.4.3 Management Strategies for Bromus in Cold Deserts -- 2.5 Western Great Plains -- 2.5.1 Invasion Potential of Western Great Plains by Bromus -- 2.5.2 Ecosystem Threats to Western Great Plains from Bromus -- 2.5.3 Management Strategies for Bromus in Western Great Plains -- 2.6 Western Forests -- 2.6.1 Invasion Potential of Western Forests by Bromus -- 2.6.2 Ecosystem Threats to Western Forests from Bromus -- 2.6.3 Management Strategies for Bromus in Western Forests -- 2.7 Management Implications -- 2.8 Research Needs -- Appendix -- References -- Chapter 3: Ecosystem Impacts of Exotic Annual Invaders in the Genus Bromus -- 3.1 Introduction -- 3.2 Impacts on Plant Communities -- 3.2.1 Changes to Above- and Belowground Community Structure. , 3.2.2 Effects of Litter Accumulation on Community Structure -- 3.3 Impacts on Landscape Disturbance, Specifically Fire -- 3.3.1 Mechanisms Underlying Altered Fire Regime -- 3.4 Impacts on Soil Stability -- 3.4.1 Direct Effects on Erosion -- 3.5 Impacts on Soil Hydrology and Water Balance -- 3.5.1 Spatial and Temporal Patterns of Soil-Water Use -- 3.6 Impacts on Ecosystem Fluxes and Energy Partitioning -- 3.7 Impacts on Soil Nutrients -- 3.7.1 Effects on Soil C in Topsoil Versus Subsoil -- 3.7.2 Effects on Soil Nitrogen Cycling -- 3.7.3 Phosphorus and Other Nutrients -- 3.8 Impacts on Soil Microbiological and Microfaunal Communities -- 3.9 Impacts on Higher Trophic Levels, Aboveground -- 3.9.1 Impacts on Invertebrates and Small Vertebrates -- 3.9.1.1 Impacts on Nutrition, Shelter, and Locomotion -- 3.9.2 Changes in Bird and Large-Mammal Communities -- 3.10 Management Implications -- 3.11 Research Needs -- References -- Part II: Invasiveness of Bromus Species (Emphasis on Biological Attributes of Bromus) -- Chapter 4: Mating System, Introduction and Genetic Diversity of Bromus tectorum in North America, the Most Notorious Product of Evolution Within Bromus Section Genea -- 4.1 Introduction -- 4.2 Evolutionary Relationships among Species in Section Genea -- 4.3 Mating Systems -- 4.3.1 Mating System of Bromus tectorum: Seed Set, Floral Characteristics, and Sex Allocation Pattern -- 4.3.2 Mating System of Bromus tectorum: Genetic Markers and Outcrossing Rates -- 4.4 Biological Invasions: Propagule Pressure, Preadaptation, and Post-immigration Evolution -- 4.5 Introduction of B. tectorum in North America: Historical Information and Genetic Data -- 4.6 Source Populations -- 4.7 Genetic Diversity within and among Populations of B. tectorum -- 4.8 Management Implications -- 4.9 Research Needs -- References. , Chapter 5: Ecological Genetics, Local Adaptation, and Phenotypic Plasticity in Bromus tectorum in the Context of a Changing Climate -- 5.1 Introduction -- 5.2 Evidence for Broad Environmental Tolerance -- 5.3 Evidence for Local Adaptation via Neutral Genetic Variation -- 5.4 Evidence for Broad Environmental Tolerance via Phenotypic Plasticity -- 5.5 Implications of Local Adaptation and Phenotypic Plasticity for Invasion Success -- 5.6 Ecological and Evolutionary Adaptations to Climate Change -- 5.6.1 Elevated CO2 -- 5.6.2 Warming -- 5.7 Management Implications -- 5.8 Research Needs -- References -- Chapter 6: Attributes That Confer Invasiveness and Impacts Across the Large Genus Bromus: Lessons from the Bromus REEnet Database -- 6.1 Introduction -- 6.2 Methods -- 6.2.1 Creation and Population of the Database -- 6.2.2 Statistical Analysis -- 6.2.3 Histograms -- 6.3 Results and Discussion -- 6.3.1 Summary of Results -- 6.3.2 Taxonomy and Life Span (Hypotheses 1 and 2) -- 6.3.3 Year (Hypothesis 3) -- 6.3.4 Seed Awns and Seed Mass (Hypotheses 4 and 5) -- 6.3.5 Ploidy Level (Hypothesis 6) -- 6.3.6 Human Use and Cultivar Availability (Hypotheses 7 and 8) -- 6.3.7 Temperature and Precipitation (Hypotheses 9, 10, 11 and 12) -- 6.4 Management Implications -- 6.5 Research Needs -- References -- Chapter 7: Community Ecology of Fungal Pathogens on Bromus tectorum -- 7.1 Introduction -- 7.2 Principal Pathogens on Bromus tectorum -- 7.2.1 Ustilago bullata (Head Smut Pathogen) -- 7.2.1.1 Ustilago bullata Life Cycle -- 7.2.1.2 Host Range -- 7.2.1.3 Ustilago bullata Distribution, Epidemiology, and Genetics -- 7.2.2 Tilletia bromi (Chestnut Bunt Pathogen) -- 7.2.2.1 Tilletia bromi Life Cycle -- 7.2.2.2 Tilletia bromi Host Range -- 7.2.2.3 Tilletia bromi Distribution and Epidemiology -- 7.2.3 Pyrenophora semeniperda (Black Fingers of Death Pathogen). , 7.2.3.1 Pyrenophora semeniperda Life Cycle -- 7.2.3.2 Pyrenophora semeniperda Host Range -- 7.2.3.3 Pyrenophora semeniperda Distribution and Epidemiology -- 7.2.3.4 Pyrenophora semeniperda Genetics -- 7.2.4 Fusarium sp. n. (Fusarium Seed Rot Pathogen) -- 7.2.4.1 Fusarium Seed Rot Life Cycle -- 7.2.4.2 Fusarium Seed Rot Host Range -- 7.2.4.3 Fusarium Seed Rot Distribution and Epidemiology -- 7.2.5 Rutstroemiaceae sp. n. (Bleach Blonde Pathogen) -- 7.2.5.1 Bleach Blonde Pathogen Life Cycle -- 7.2.5.2 Bleach Blonde Syndrome Pathogen Host Range -- 7.2.5.3 Bleach Blonde Pathogen Distribution and Epidemiology -- 7.3 Community Ecology of Pathogens on Bromus tectorum -- 7.4 Management Implications -- 7.5 Research Needs -- References -- Part III: Understanding Environmental Controls and Bromus Distribution (Invasibility of Landscapes by Bromus) -- Chapter 8: Soil Moisture and Biogeochemical Factors Influence the Distribution of Annual Bromus Species -- 8.1 Introduction -- 8.2 Soil Nutrient Availability and Water in Dryland Settings -- 8.3 Studies on the Potential Soil Controls on B. rubens and B. tectorum Distribution -- 8.3.1 Chihuahuan and Mojave Deserts -- 8.3.2 Colorado Plateau Desert -- 8.3.3 Great Basin/Intermountain Region and Columbia Plateau -- 8.3.4 Coastal Sage Scrub -- 8.4 Manipulative Studies -- 8.4.1 Nitrogen -- 8.4.2 Phosphorus and Others Nutrients -- 8.4.3 Soil Moisture -- 8.5 Discussion -- 8.5.1 How Soil Texture and Biochemistry Can Limit Bromus -- 8.5.2 Why Were Different Nutrients Limiting in Different Regions and What Does This Mean for Predicting Annual Grass Distribution in Western US Semiarid and Arid Lands? -- 8.6 Management Implications -- 8.7 Research Needs -- References -- Chapter 9: Bromus Response to Climate and Projected Changes with Climate Change -- 9.1 Introduction -- 9.1.1 Climate Projections for the Western USA. , 9.1.2 Climate Effects on Native Ecosystems in the Western USA -- 9.2 Climate Effects on Bromus -- 9.2.1 Fall/Spring Precipitation -- 9.2.2 Summer Precipitation -- 9.2.3 Winter Precipitation -- 9.2.4 Winter and Spring Temperature -- 9.2.5 Future Range Shifts with Climate Change -- 9.2.6 Climate-Fire Feedbacks with Growing Season Precipitation -- 9.3 Management Implications -- 9.4 Research Needs -- References -- Chapter 10: Plant Community Resistance to Invasion by Bromus Species: The Roles of Community Attributes, Bromus Interactions with Plant Communities, and Bromus Traits -- 10.1 Introduction -- 10.2 Effects of Environmental Factors on Plant Community Resistance to Bromus -- 10.3 Interactions of Bromus with Plant Communities -- 10.3.1 Bromus Plant Traits and Resource Dynamics -- 10.3.2 Interactions of Bromus with Perennial Grasses -- 10.3.3 Interactions of Bromus with Woody Plants -- 10.3.4 Interactions of Bromus with Forbs -- 10.4 Bromus Reproductive Traits, Propagule Supply, and Priority Advantage -- 10.4.1 Seed Production and Propagule Supply -- 10.4.2 Seed Characteristics and Dispersal -- 10.4.3 Seed Banks -- 10.4.4 Seed Germination -- 10.5 Effects of Biological Crusts on Seed Dispersal and Germination -- 10.6 Herbivory -- 10.6.1 Grazing Impacts on B. tectorum -- 10.6.2 Native Herbivores and Community Resistance -- 10.6.3 Potential Effects on Disturbance Regimes and Community Resilience -- 10.7 Management Implications -- 10.8 Research Needs -- References -- Part IV: Relating the Science to Human Uses and Restoration of Western Rangeland Landscapes -- Chapter 11: Land Uses, Fire, and Invasion: Exotic Annual Bromus and Human Dimensions -- 11.1 Introduction -- 11.2 Fire Regimes and Uses Across Regions -- 11.3 Land Uses -- 11.3.1 Native American Land Uses before Exotic Annual Bromus Introduction. , 11.3.2 Role of Land Uses and Regulatory Policies in Exotic Annual Bromus Colonization and Spread.