Case Applications of Statistical Models in Ecology and Evolution


Youhua Chen, PhD
University of Alberta

Series: Environmental Science, Engineering and Technology
BISAC: SCI027000

Since the 20th century, there have been many exciting achievements in the field of ecology and evolution, many of which were formulated using statistical and mathematical functions. In particular, statistical and mathematical models are a necessity for developing some sub-disciplines and theories like population genetics and ecology, neutral theory of molecular evolution and biodiversity, and machine-learning techniques for species distribution modeling.

This book serves as an elementary guide to showcase some statistical and mathematical models that have been applied and used in contemporary ecological or evolutionary research. Some models may be old-fashioned, whilst some others have been further extended or developed so as to better address special research questions presented in each chapter of the book. Technical aspects of each statistical model are presented in detail to allow readers to follow and apply their own research and practices. (Imprint: Nova)




Table of Contents


Part 1: Case Applications

Chapter 1. Permutation-free Fisher’s Z-transform Method for Significance Testing of Mantel’s Statistic

Chapter 2. Random Species/Population Change and Multiple-site Beta Diversity Indices: A Comparison of Contradictory Scenarios from Simulation- and Empirical BCI Tree-derived Data Sets

Chapter 3. On the Relationship between Community-level Beta Diversity and Partitioning Variation for Space and Environment: BCI Tree Community as a Case Study

Chapter 4. Distinguishing Niche and Neutral Processes: Issues in Variation Partitioning Statistical Methods and Further Perspectives

Chapter 5. Estimating Ancestral Ranges in Historical Biogeography: On the Development of Alternative Range Evolution Models for Maximum Likelihood Inference

Chapter 6. On the Relationships of Clade Age, Species Richness, and Phylogenetic Diversity of Global Mammals

Chapter 7. Spatial Point Pattern Analysis of County Locations of Mainland China: The Relative Roles of Anthropogenic Factors, Climatic Fluctuation and Water Availability

Chapter 8. Modeling Species-area Relationship with Measurement Uncertainty

Chapter 9. Estimating Population Change of Species Under Climate Change Using Occupancy-abundance Relationship

Chapter 10. ‘Coexist’: An R Package for Performing Species Coexistence Modeling and Analysis

Chapter 11. Fitness Equivalence Promotes Species Coexistence under Fluctuating Environments with Simultaneous Coupling of Dispersal and Competition

Part 2: Appendices of R Codes used for Computation and Simulation

Appendix 1. R code for Fisher Transform and Simulation

Appendix 2. R code for Simulating Asymmetric Dispersal and Coexistence

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