Author: Nicholas J. Gotelli Publisher: Sinauer ISBN: 9781605350646 Category : Science Languages : en Pages : 0
Book Description
A Primer of Ecological Statistics, Second Edition explains fundamental material in probability theory, experimental design, and parameter estimation for ecologists and environmental scientists. The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject. The book is divided into four parts. Part I discusses the fundamentals of probability and statistical thinking. It introduces the logic and language of probability (Chapter 1), explains common statistical distributions used in ecology (Chapter 2) and important measures of central tendency and spread (Chapter 3), explains P-values, hypothesis testing, and statistical errors (Chapter 4), and introduces frequentist, Bayesian, and Monte Carlo methods of analysis (Chapter 5). Part II discusses how to successfully design and execute field experiments and sampling studies. Topics include design strategies (Chapter 6), a 'bestiary' of experimental designs (Chapter 7), and transformations and data management (Chapter 8). Part III discusses specific analyses, and covers the material that is the main core of most statistics texts. Topics include regression (Chapter 9), analysis of variance (Chapter 10), categorical data analysis (Chapter 11), and multivariate analysis (Chapter 12). Part IV—new to this edition—discusses two central topics in estimating important ecological metrics. Topics include quantification of biological diversity (Chapter 13) and estimating occupancy, detection probability, and population sizes from marked and unmarked populations (Chapter 14). The book includes a comprehensive glossary, a mathematical appendix on matrix algebra, and extensively annotated tables and figures. Footnotes introduce advanced and ancillary material: some are purely historical, others cover mathematical/statistical proofs or details, and still others address current topics in the ecological literature. Data files and code used for some of the examples, as well as errata, are available online.
Author: M. Henry Stevens Publisher: Springer Science & Business Media ISBN: 0387898824 Category : Science Languages : en Pages : 404
Book Description
Provides simple explanations of the important concepts in population and community ecology. Provides R code throughout, to illustrate model development and analysis, as well as appendix introducing the R language. Interweaves ecological content and code so that either stands alone. Supplemental web site for additional code.
Author: John A. Ludwig Publisher: John Wiley & Sons ISBN: 9780471832355 Category : Mathematics Languages : en Pages : 362
Book Description
Ecological community data. Spatial pattern analysis. Species-abundance relations. Species affinity. Community classification. Community ordination. Community interpretation.
Author: Nicholas J. Gotelli Publisher: ISBN: 9780878932740 Category : Biologie des populations - Modèles mathématiques Languages : en Pages : 236
Book Description
A detailed exposition of the most common mathematical models in population and community ecology, covering exponential and logistic population growth, age-structured demography, metapopulation dynamics, competition, predation, and island biogeography. Intended to demystify ecological models and the math behind them by deriving the models from first principles. The primer may be used as a self-teaching tutorial, as a primary textbook, or as a supplemental text to a general ecology textbook. Annotation copyright by Book News, Inc., Portland, OR
Author: Jeffrey K. Conner Publisher: Sinauer Associates Incorporated ISBN: 9780878932023 Category : Science Languages : en Pages : 304
Book Description
This book covers basic concepts in population and quantitative genetics, including measuring selection on phenotypic traits. The emphasis is on material applicable to field studies of evolution focusing on ecologically important traits. Topics addressed are critical for training students in ecology, evolution, conservation biology, agriculture, forestry, and wildlife management. Many texts in this field are too complex and mathematical to allow the average beginning student to readily grasp the key concepts. A Primer of Ecological Genetics, in contrast, employs mathematics and statistics-fully explained, but at a less advanced level-as tools to improve understanding of biological principles. The main goal is to enable students to understand the concepts well enough that they can gain entry into the primary literature. Integration of the different chapters of the book shows students how diverse concepts relate to each other.
Author: Samuel M. Scheiner Publisher: Oxford University Press ISBN: 0198030223 Category : Science Languages : en Pages : 432
Book Description
Ecological research and the way that ecologists use statistics continues to change rapidly. This second edition of the best-selling Design and Analysis of Ecological Experiments leads these trends with an update of this now-standard reference book, with a discussion of the latest developments in experimental ecology and statistical practice. The goal of this volume is to encourage the correct use of some of the more well known statistical techniques and to make some of the less well known but potentially very useful techniques available. Chapters from the first edition have been substantially revised and new chapters have been added. Readers are introduced to statistical techniques that may be unfamiliar to many ecologists, including power analysis, logistic regression, randomization tests and empirical Bayesian analysis. In addition, a strong foundation is laid in more established statistical techniques in ecology including exploratory data analysis, spatial statistics, path analysis and meta-analysis. Each technique is presented in the context of resolving an ecological issue. Anyone from graduate students to established research ecologists will find a great deal of new practical and useful information in this current edition.
Author: Benjamin M. Bolker Publisher: Princeton University Press ISBN: 0691125228 Category : Computers Languages : en Pages : 408
Book Description
Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author: N. Thompson Hobbs Publisher: Princeton University Press ISBN: 1400866553 Category : Science Languages : en Pages : 315
Book Description
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models
Author: Aaron M. Ellison Publisher: Yale University Press ISBN: 0300169302 Category : Science Languages : en Pages : 422
Book Description
This book is the first user-friendly regional guide devoted to ants—the “little things that run the world.” Lavishly illustrated with more than 500 line drawings, 300-plus photographs, and regional distribution maps as composite illustrations for every species, this guide will introduce amateur and professional naturalists and biologists, teachers and students, and environmental managers and pest-control professionals to more than 140 ant species found in the northeastern United States and eastern Canada. The detailed drawings and species descriptions, together with the high-magnification photographs, will allow anyone to identify and learn about ants and their diversity, ecology, life histories, and beauty. In addition, the book includes sections on collecting ants, ant ecology and evolution, natural history, and patterns of geographic distribution and diversity to help readers gain a greater understanding and appreciation of ants.
Author: Alain Zuur Publisher: Springer Science & Business Media ISBN: 0387874585 Category : Science Languages : en Pages : 579
Book Description
This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.
Author: Nicholas J. Gotelli
Author: M. Henry Stevens
Author: John A. Ludwig
Author: Nicholas J. Gotelli
Author: Jeffrey K. Conner
Author: Samuel M. Scheiner
Author: Benjamin M. Bolker
Author: N. Thompson Hobbs
Author: Aaron M. Ellison
Author: Alain Zuur