Ecologists need to analyze their field data to interpret relationships within plant and animal communities and with their environments. The purpose of this book is to show ecologists and environmental scientists what numerical and statistical methods are most useful, how to use them and interpret the results from them, and what pitfalls to avoid. Subjects treated include data requirements, regression analysis, calibration (or inverse regression), ordination techniques, cluster analysis, and spatial analysis of ecological data. The authors take pains to use only elementary mathematics and explain the ecological models behind the techniques. Exercises and solution are provided for practice. This is the only book written specifically for ecologists that explains such techniques as logistic regression, canonical correspondence analysis, and kriging (statistical manipulation of data). This is a reissue of a book first published in 1987 by Pudoc (The Netherlands).
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"The book's strong point is the explanation of how the various analysis methods work. The authors include a surprising amount of detail without difficult mathematics." Michael F. Merigliano, Natural Areas Journal
Book Description
Originally published in 1987, the purpose of this reissue is to show ecologists and environmental scientists the most useful numerical and statistical methods and how to interpret results and avoid pitfalls. Written for ecologists, it explains such techniques as logistic regression, canonical correspondence analysis, and "kriging."
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22 of 22 people found the following review helpful:
4.0 out of 5 stars
A standard work in vegetation ecology,
By Meirmans (Amsterdam, the Netherlands) - See all my reviews
This review is from: Data Analysis in Community and Landscape Ecology (Paperback)
This is a standard in the discipline of vegetation ecology and probably the best introductiion to the field. This is a thoroughly revised new edition of the original book from 1986. It is a good introduction to the various methods available for analysis of vegetation data, like correspondence analysis, principle components analysis and regression analysis. A good point about this book is that consistently works with the same example dataset for explaining all different analysis methods. This clearly shows the differences in outcome of the different methods. A bad point is that its not always written very clearly and includes some very theoretical parts.
0 of 1 people found the following review helpful:
4.0 out of 5 stars
Data Analysis in Community and Landscape Ecology,
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This review is from: Data Analysis in Community and Landscape Ecology (Paperback)
Esse livro é excelente para estudos e análises ecológicos de vegetação e ordenação com técnicas multivairada.
0 of 2 people found the following review helpful:
5.0 out of 5 stars
Data Analysis in Community and Landscape Ecology,
By
This review is from: Data Analysis in Community and Landscape Ecology (Paperback)
A easy reading and comprehensive book about data analysis in community and landscape ecology. This is the book that every young ecologist should have in his/her bookshelf
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Inside This Book
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First Sentence:
This book deals with the analysis of ecological data. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
new species scores, initial site scores, refined ordination, new site scores, meadow data, weighted averaging algorithm, quantitative abundance data, distance biplot, maximum likelihood calibration, unimodal response curves, total residual sum, canonical ordination, logit curve, ordination diagram, first ordination axis, simple discriminant functions, composite gradients, moisture explains, indirect gradient analysis, ordination axes, onmental variables, previous axes, brook system, artificial brooks, canonical coefficients Key Phrases - Capitalized Phrases (CAPs): (learn more)
Eigenvalue Axis, Term Parameter, New South Wales New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
This book deals with the analysis of ecological data. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
new species scores, initial site scores, refined ordination, new site scores, meadow data, weighted averaging algorithm, quantitative abundance data, distance biplot, maximum likelihood calibration, unimodal response curves, total residual sum, canonical ordination, logit curve, ordination diagram, first ordination axis, simple discriminant functions, composite gradients, moisture explains, indirect gradient analysis, ordination axes, onmental variables, previous axes, brook system, artificial brooks, canonical coefficients Key Phrases - Capitalized Phrases (CAPs): (learn more)
Eigenvalue Axis, Term Parameter, New South Wales New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 6
books:
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51
books
cite this book:
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- Flora Europaea, Vol. 5: Alismataceae to Orchidaceae (Monocotyledones) by D. A. Webb on page 259, and Back Matter
- Geostatistics for natural resources characterization (NATO Asi Series. Series C, Mathematical and Physical Science) (Pt. 2) by G. Verly in Back Matter
- Computer Graphics by Acm Press in Back Matter
- Experimental Designs by William Gemmel Cochran in Back Matter
- Statistics and Data Analysis in Geology by John C. Davis in Back Matter
See all 6 books this book cites
- Vegetation Description and Analysis: A Practical Approach by Martin Kent in Back Matter (1), Back Matter (2), and Back Matter (3)
- Living Rivers: Trends and Challenges in Science and Management (Developments in Hydrobiology) by R.S.E.W. Leuven on page 119, and page 198
- Multivariate Statistics for the Environmental Sciences (Mathematics) by Peter J. A. Shaw in Back Matter (1), and Back Matter (2)
- Spatial Analytical Perspectives on GIS : GISDATA 4 by M Fisher on page 182, and page 184
- Trends in Research in Ephemeroptera and Plecoptera by Eduardo Dominguez on page 178
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