A Primer of Ecological Statistics

A Primer of Ecological Statistics
Author: Nicholas J. Gotelli
Publisher: Sinauer
Total Pages: 0
Release: 2013-03-14
Genre: Science
ISBN: 9781605350646

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.

A Primer of Ecology with R

A Primer of Ecology with R
Author: M. Henry Stevens
Publisher: Springer Science & Business Media
Total Pages: 404
Release: 2009-06-02
Genre: Science
ISBN: 0387898824

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.

Statistical Ecology

Statistical Ecology
Author: John A. Ludwig
Publisher: John Wiley & Sons
Total Pages: 362
Release: 1988-05-18
Genre: Mathematics
ISBN: 9780471832355

Ecological community data. Spatial pattern analysis. Species-abundance relations. Species affinity. Community classification. Community ordination. Community interpretation.

A Primer of Ecological Genetics

A Primer of Ecological Genetics
Author: Jeffrey K. Conner
Publisher: Sinauer Associates Incorporated
Total Pages: 304
Release: 2004-01
Genre: Science
ISBN: 9780878932023

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.

A Primer of Ecology

A Primer of Ecology
Author: Nicholas J. Gotelli
Publisher:
Total Pages: 236
Release: 1998
Genre: Biologie des populations - Modèles mathématiques
ISBN: 9780878932740

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

The Interpretation of Ecological Data

The Interpretation of Ecological Data
Author: E. C. Pielou
Publisher: John Wiley & Sons
Total Pages: 278
Release: 1984-09-06
Genre: Science
ISBN: 9780471889502

A detailed introduction to the methods used by ecologists--classification and ordination--to clarify and interpret large, unwieldy masses of multivariate field data. Permits ecologists to understand, not just mechanically use, pre-packaged programs for multivariate analysis. Demonstrates these techniques using artificial data simple enough for every analytical step to be understood.

A Field Guide to the Ants of New England

A Field Guide to the Ants of New England
Author: Aaron M. Ellison
Publisher: Yale University Press
Total Pages: 422
Release: 2012-11-13
Genre: Science
ISBN: 0300169302

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.

Ecological Models and Data in R

Ecological Models and Data in R
Author: Benjamin M. Bolker
Publisher: Princeton University Press
Total Pages: 408
Release: 2008-07-21
Genre: Computers
ISBN: 0691125228

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.

Design and Analysis of Ecological Experiments

Design and Analysis of Ecological Experiments
Author: Samuel M. Scheiner
Publisher: Oxford University Press
Total Pages: 432
Release: 2001-04-26
Genre: Science
ISBN: 0198030223

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.

Bayesian Models

Bayesian Models
Author: N. Thompson Hobbs
Publisher: Princeton University Press
Total Pages: 315
Release: 2015-08-04
Genre: Science
ISBN: 1400866553

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