Keywords:
Paleolimnology.
;
Electronic books.
Description / Table of Contents:
This book details an array of numerical and statistical techniques used in palaeolimnology and other branches of palaeoecology, including exploratory data analysis, error estimation, clustering, ordination and modern statistical learning techniques.
Type of Medium:
Online Resource
Pages:
1 online resource (750 pages)
Edition:
1st ed.
ISBN:
9789400727458
Series Statement:
Developments in Paleoenvironmental Research Series ; v.5
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=971785
DDC:
560.45630727
Language:
English
Note:
Intro -- Tracking Environmental Change Using Lake Sediments -- Preface -- Structure of the Book -- About The Editors -- Contents -- Contributors -- Part I Introduction, Numerical Overview, and Data-Sets -- Chapter 1: The March Towards the Quantitative Analysis of Palaeolimnological Data -- Palaeolimnology -- Types of Palaeolimnological Data -- Different Temporal Scales: From Surface-Sediment Calibration Sets to Detailed Sediment-Core Studies -- Opportunities and Challenges -- Outline of the Book -- References -- Chapter 2: Overview of Numerical Methods in Palaeolimnology -- Introduction -- Types of Palaeolimnological Data -- The Role of Quantification in Palaeolimnology -- Overview of Numerical Methods -- Identification, Classification, and Assignment -- Exploratory Data Analysis -- Regression Analysis and Statistical Modelling -- Introduction to Regression Analysis and Statistical Modelling -- General Linear Models -- Extending the General Linear Model -- Introduction -- Generalised Linear Models -- Mixed-Effects Models -- Non-parametric Regression Models -- Classification and Regression Trees (CARTs) -- Artificial Neural Networks (ANNs) and Self-Organising Maps (SOMs) -- Multivariate Regression -- Model Selection and Shrinkage -- Quantitative Environmental Reconstruction, Calibration, and Inverse Regression -- Temporal-Series Analysis -- Confirmatory Data Analysis -- Conclusions -- References -- Chapter 3: Data-Sets -- Introduction -- The Round Loch of Glenhead Data-Set -- The SWAP Data-Set -- Data Availability -- References -- Part II Numerical Methods for the Analysis of Modern and Stratigraphical Palaeolimnological Data -- Chapter 4: Introduction and Overview of Part II -- Introduction -- Data Collection and Data Assessment -- Identification -- Error Estimation -- Data Storage and Data-Bases -- Exploratory Data Analysis -- Data Summarisation.
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Data Analysis -- Gradient Lengths and Compositional Turnover in Palaeolimnological Data -- Estimating Richness from Palaeolimnological Data -- Estimating Species Optima and Tolerances Using Palaeolimnological Data -- Comparison of Clusterings and Ordinations of Palaeolimnological Data -- Data Interpretation -- Conclusions -- References -- Chapter 5: Exploratory Data Analysis and Data Display -- Introduction -- Exploring Univariate Distributions -- Graphical Tools -- Data Transformation -- Graphical Techniques for Categorical (Nominal and Ordinal) Data -- Exploring Bivariate Relationships -- Multivariate Techniques -- Time-Series Data -- Outlier Detection and Treatment -- Missing Values -- Graph Drawing -- Software -- Conclusions -- References -- Chapter 6: Assessment of Uncertainties Associated with Palaeolimnological Laboratory Methods and Microfossil Analysis -- Introduction -- Single Parameter Estimates -- Microfossil Counts -- Percentages (Taxa as Proportions of an Overall Sum) -- Treating Taxa as Ratios of Types (Counting Outside the Sum) -- Treating Taxa as Numbers of Individuals Per Volume or Weight (Microfossil Concentrations) -- Treating Taxa as Numbers of Individuals Per Unit Surface Per Year (Accumulation Rates, Influx) -- Artificial Count Data to Assess the Errors Associated with Low Microfossil Counts -- Inter-laboratory Comparisons -- Software Availability -- Estimating Varve-Counting Errors -- Multi-core Studies -- Conclusions -- References -- Chapter 7: Clustering and Partitioning -- Introduction -- Artificial Example -- Basic Concepts in Clustering -- Unconstrained Agglomerative Clustering Methods -- K-Means Partitioning -- Example: The SWAP-UK Data -- Constrained Clustering in One Dimension -- Example: The Round Loch of Glenhead (RLGH) Fossil Data -- Constrained Clustering in Two Dimensions -- Example: The SWAP-UK Data.
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Clustering Constrained by Canonical Analysis -- Indicator Species Analysis -- Example: The Round Loch of Glenhead (RLGH) Fossil Data -- Two-Way Indicator Species Analysis -- Example: The SWAP-UK Data -- Multivariate Regression Trees -- Example: The SWAP-UK Data -- Conclusions -- References -- Chapter 8: From Classical to Canonical Ordination -- Introduction -- Basic Concepts in Simple Ordination -- Transformation of Physical Data -- Transformation of Assemblage Composition Data -- Choice of an Appropriate Distance Function -- Euclidean or Cartesian Space, Euclidean Representation -- Metric or Non-metric Ordination? -- How Many Axes Are Required? -- Simple Ordination Methods: PCA, CA, PCoA, NMDS -- Introduction to Canonical Ordination -- Canonical Ordination Methods -- Linear RDA -- Linear CCA -- Other Forms of Asymmetric Canonical Analyses -- Spatial or Temporal Analysis Through Variation Partitioning -- Modelling Temporal Structure in Sediment Cores [and Environmental Structure in Modern Assemblages] -- Testing Hypotheses in (Multi-) Factorial Experiments -- Software -- References -- Chapter 9: Statistical Learning in Palaeolimnology -- Introduction -- Classification and Regression Trees -- Multivariate Regression Trees -- Other Types of Tree-Based Machine-Learning Methods (Bagging, Boosted Trees, Random Forests, Multivariate Adaptive Regression Splines) -- Bagging -- Random Forests -- Boosting -- Multivariate Adaptive Regression Splines -- Artificial Neural Networks and Self-organising Maps -- Artificial Neural Networks -- Self-organising Maps -- Bayesian Networks -- Genetic Algorithms -- Principal Curves and Surfaces -- Shrinkage Methods and Variable Selection -- Discussion and Conclusions -- References -- Part III Numerical Methods for the Analysis of Stratigraphical Palaeolimnological Data -- Chapter 10: Introduction and Overview of Part III.
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Introduction -- Data Collection and Data Assessment -- Identification -- Data Assessment and Error Estimation -- Data Summarisation -- Single Stratigraphical Data-Sets -- Two or More Stratigraphical Sequences -- Data Analysis -- Rate-of-Change Analysis -- Population Analysis -- Stratigraphical Changes in Taxonomic Richness -- Temporal-Series Analysis -- Quantifying Recent Change -- Quantitative Palaeoenvironmental Reconstructions -- Data Interpretation -- Community and Assemblage Reconstruction -- Causative Factors -- Conclusions -- References -- Chapter 11: Analysis of Stratigraphical Data -- Introduction -- Zonation -- Techniques -- Determining the Number of Zones -- Software -- Example of Use -- Splitting of Individual Stratigraphical Sequences -- Example of Use -- Summarising Stratigraphical PatternsUsing Ordination Results -- Summarising Palaeoecological PatternsUsing Cluster Analysis -- Quantifying Recent Change -- Rate-of-Change Analysis -- Example of Use -- Future Developments -- Conclusions -- References -- Chapter 12: Estimation of Age-Depth Relationships -- Introduction -- Radiocarbon Dating -- Errors -- The Need for Radiocarbon Calibration -- Calibration Methods -- Reduction to Single Point Estimates -- Age-Depth Models -- Analytical vs. Monte Carlo Age-Depth Models -- Basic Age-Depth Models -- Linear Interpolation -- Polynomials -- Splines -- Other Models -- Mixed-Effects Models -- Implementation -- Bayesian Age-Depth Modelling -- Chronological Ordering -- Wiggle-Match Dating -- Other Models -- Software Packages -- Discussion -- Choice of Model -- Conclusions and Future Developments -- References -- Chapter 13: Core Correlation -- Introduction -- Theory and Method -- Case Studies -- Ice Chronology -- Mountain and Arctic Lakes -- Other Palaeolimnological Applications -- Conclusions -- References.
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Chapter 14: Quantitative Environmental Reconstructions from Biological Data -- Introduction -- Training-Set Development -- Numerical Methods -- Introduction -- Classical Methods -- Inverse Methods -- Weighted-Averaging (WA) Regression and Calibration -- Partial Least Squares (PLS) and Weighted-Averaging Partial Least Squares Regression and Calibration (WAPLS) -- Artificial Neural Networks (ANN) -- Modern Analogue Technique (MAT) -- Locally-Weighted Weighted-Averaging (LWWA) Regression and Calibration -- Bayesian Methods -- Model Selection and Evaluation -- Spatial Autocorrelation and Environmental Reconstruction -- Reconstruction Testing, Evaluation, and Validation -- Assessing the Statistical Significance of a Quantitative Reconstruction -- RMSEP and Sample-Specific Error Estimates -- Goodness-of-Fit and Analogue Measures -- Comparison of Reconstructions Using DifferentNumerical Methods -- Comparison of Reconstructions Using Different Proxies -- Case Study -- Assumptions and Limitations -- Software -- Conclusions and Future Work -- References -- Chapter 15: Analogue Methods in Palaeolimnology -- Introduction -- The Modern Analogue Technique (MAT) -- Analogue Matching -- Dissimilarity and Dimensionality -- The Curse of Dimensionality -- How Similar Is Similar Enough? -- Choosing k to Optimise RMSEP -- Choosing k via Dissimilarity Jumps -- Reference Distributions of Dissimilarities -- Monte Carlo Resampling -- Receiver Operating Characteristic (ROC) Curves -- Logistic Regression Modelling -- Evaluation of Environmental Reconstructions -- Software -- Conclusions and Future Work -- References -- Chapter 16: Autocorrelogram and Periodogram Analyses of Palaeolimnological Temporal-Series from Lakes in Central and Western North America to Assess Shifts in Drought Conditions -- Introduction -- Statistical Background -- Time-Domain Approach.
,
Frequency-Domain Approach.
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