Multivariate Analysis Of Ecological Data Using Canoco 5
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Author |
: Jan Lepš |
Publisher |
: Cambridge University Press |
Total Pages |
: 296 |
Release |
: 2003-05-29 |
ISBN-10 |
: 0521891086 |
ISBN-13 |
: 9780521891080 |
Rating |
: 4/5 (86 Downloads) |
Synopsis Multivariate Analysis of Ecological Data Using CANOCO by : Jan Lepš
Table of contents
Author |
: Petr Šmilauer |
Publisher |
: Cambridge University Press |
Total Pages |
: 375 |
Release |
: 2014-04-17 |
ISBN-10 |
: 9781139953047 |
ISBN-13 |
: 1139953044 |
Rating |
: 4/5 (47 Downloads) |
Synopsis Multivariate Analysis of Ecological Data using CANOCO 5 by : Petr Šmilauer
This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.
Author |
: Petr Šmilauer |
Publisher |
: Cambridge University Press |
Total Pages |
: 375 |
Release |
: 2014-04-17 |
ISBN-10 |
: 9781107694408 |
ISBN-13 |
: 110769440X |
Rating |
: 4/5 (08 Downloads) |
Synopsis Multivariate Analysis of Ecological Data using CANOCO 5 by : Petr Šmilauer
An accessible introduction to the theory and practice of multivariate analysis for graduates, researchers and professionals dealing with ecological problems.
Author |
: Michael Greenacre |
Publisher |
: Fundacion BBVA |
Total Pages |
: 336 |
Release |
: 2014-01-09 |
ISBN-10 |
: 9788492937509 |
ISBN-13 |
: 8492937505 |
Rating |
: 4/5 (09 Downloads) |
Synopsis Multivariate Analysis of Ecological Data by : Michael Greenacre
La diversidad biológica es fruto de la interacción entre numerosas especies, ya sean marinas, vegetales o animales, a la par que de los muchos factores limitantes que caracterizan el medio que habitan. El análisis multivariante utiliza las relaciones entre diferentes variables para ordenar los objetos de estudio según sus propiedades colectivas y luego clasificarlos; es decir, agrupar especies o ecosistemas en distintas clases compuestas cada una por entidades con propiedades parecidas. El fin último es relacionar la variabilidad biológica observada con las correspondientes características medioambientales. Multivariate Analysis of Ecological Data explica de manera completa y estructurada cómo analizar e interpretar los datos ecológicos observados sobre múltiples variables, tanto biológicos como medioambientales. Tras una introducción general a los datos ecológicos multivariantes y la metodología estadística, se abordan en capítulos específicos, métodos como aglomeración (clustering), regresión, biplots, escalado multidimensional, análisis de correspondencias (simple y canónico) y análisis log-ratio, con atención también a sus problemas de modelado y aspectos inferenciales. El libro plantea una serie de aplicaciones a datos reales derivados de investigaciones ecológicas, además de dos casos detallados que llevan al lector a apreciar los retos de análisis, interpretación y comunicación inherentes a los estudios a gran escala y los diseños complejos.
Author |
: Jan Leps |
Publisher |
: |
Total Pages |
: 0 |
Release |
: 2003 |
ISBN-10 |
: OCLC:638826507 |
ISBN-13 |
: |
Rating |
: 4/5 (07 Downloads) |
Synopsis Multivariate Analysis of Ecological Data Using CANOCO by : Jan Leps
Author |
: R. H. Jongman |
Publisher |
: Cambridge University Press |
Total Pages |
: 325 |
Release |
: 1995-03-02 |
ISBN-10 |
: 9780521475747 |
ISBN-13 |
: 0521475740 |
Rating |
: 4/5 (47 Downloads) |
Synopsis Data Analysis in Community and Landscape Ecology by : R. H. Jongman
Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
Author |
: Bryan F. J. Manly |
Publisher |
: CRC Press |
Total Pages |
: 294 |
Release |
: 2024-10-04 |
ISBN-10 |
: 9781040126332 |
ISBN-13 |
: 1040126332 |
Rating |
: 4/5 (32 Downloads) |
Synopsis Multivariate Statistical Methods by : Bryan F. J. Manly
Multivariate Statistical Methods: A Primer offers an introduction to multivariate statistical methods in a rigorous yet intuitive way, without an excess of mathematical details. In this fifth edition, all chapters have been revised and updated, with clearer and more direct language than in previous editions, and with more up-to-date examples, exercises, and references, in areas as diverse as biology, environmental sciences, economics, social medicine, and politics. Features • A concise and accessible conceptual approach that requires minimal mathematical background. • Suitable for a wide range of applied statisticians and professionals from the natural and social sciences. • Presents all the key topics for a multivariate statistics course. • The R code in the appendices has been updated, and there is a new appendix introducing programming basics for R. • The data from examples and exercises are available on a companion website. This book continues to be a great starting point for readers looking to become proficient in multivariate statistical methods, but who might not be deeply versed in the language of mathematics. In this edition, we provide readers with conceptual introductions to methods, practical suggestions, new references, and a more extensive collection of R functions and code that will help them to deepen their toolkit of multivariate statistical methods.
Author |
: Alan E. Gelfand |
Publisher |
: CRC Press |
Total Pages |
: 798 |
Release |
: 2019-01-15 |
ISBN-10 |
: 9781351648547 |
ISBN-13 |
: 1351648543 |
Rating |
: 4/5 (47 Downloads) |
Synopsis Handbook of Environmental and Ecological Statistics by : Alan E. Gelfand
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
Author |
: Jan Lepš |
Publisher |
: Cambridge University Press |
Total Pages |
: 385 |
Release |
: 2020-07-30 |
ISBN-10 |
: 9781108480383 |
ISBN-13 |
: 1108480381 |
Rating |
: 4/5 (83 Downloads) |
Synopsis Biostatistics with R by : Jan Lepš
A straightforward introduction to a wide range of statistical methods for field biologists, using thoroughly explained R code.
Author |
: John Verzani |
Publisher |
: CRC Press |
Total Pages |
: 522 |
Release |
: 2018-10-03 |
ISBN-10 |
: 9781315360300 |
ISBN-13 |
: 1315360306 |
Rating |
: 4/5 (00 Downloads) |
Synopsis Using R for Introductory Statistics by : John Verzani
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.