Statistical Ecology in Practice
A Guide to Analysing Environmental and Ecological Field Data
Published on 23. May 2000
Book
Paperback/Softback
440 pages
978-0-582-23634-9 (ISBN)
Description
This text combines principles of good field ecology research design with practical statistical analysis, suited to the needs of advanced students taking Field Ecology courses or undertaking projects that contribute to their final degree classification.
More details
Language
English
Place of publication
Harlow
United Kingdom
Publishing group
Pearson Education Limited
Target group
Professional and scholarly
Dimensions
Height: 246 mm
Width: 191 mm
Thickness: 23 mm
Weight
846 gr
ISBN-13
978-0-582-23634-9 (9780582236349)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Procedure Index.
A User Guide.
I. CHARATERISATION OF DATA SETS.1. Nature of Environmental Data: Planning Fieldwork and Sampling Regimes.
2. Community and Sample Diversity.
3. Estimating Population Size and Population Parameters.
4. Investigation of Spatial Pattern.
5. Biological and Environmental Indices.
II. COMPARING DATA SETS.
6. Resemblance Functions: Measures of Similarity and Difference.
7. Association and Correlation.
8. Ordination of Data Sets: Looking for Patterns and Gradients Among Samples.
9. Classification of Data Sets: Comparing and Grouping Samples.
III. RELATING DATA SETS WITH ENVIRONMENTAL FACTORS.
10. Relating Single Species of Variable Data to Environmental Factors.
11. Relating Community Data Sets with Environmental Factors: Ordination and Cluster Analysis Revisited.
Index.
A User Guide.
I. CHARATERISATION OF DATA SETS.1. Nature of Environmental Data: Planning Fieldwork and Sampling Regimes.
2. Community and Sample Diversity.
3. Estimating Population Size and Population Parameters.
4. Investigation of Spatial Pattern.
5. Biological and Environmental Indices.
II. COMPARING DATA SETS.
6. Resemblance Functions: Measures of Similarity and Difference.
7. Association and Correlation.
8. Ordination of Data Sets: Looking for Patterns and Gradients Among Samples.
9. Classification of Data Sets: Comparing and Grouping Samples.
III. RELATING DATA SETS WITH ENVIRONMENTAL FACTORS.
10. Relating Single Species of Variable Data to Environmental Factors.
11. Relating Community Data Sets with Environmental Factors: Ordination and Cluster Analysis Revisited.
Index.