The Interpretation of Ecological Data: A Primer on Classification and OrdinationA 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. |
Contents
INTRODUCTION | 1 |
CLASSIFICATION BY CLUSTERING | 13 |
TRANSFORMING DATA MATRICES | 83 |
13 | 104 |
ORDINATION | 133 |
DIVISIVE CLASSIFICATION | 203 |
DISCRIMINANT ORDINATION | 223 |
333 | 239 |
| 257 | |
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Common terms and phrases
analysis axis centered PCA centroid clustering computations consider coordinate frame correlation matrix covariance matrix d²(j data matrix data points data swarm defined dendrogram denotes described diagonal matrix dimensions dissimilarity measure distance matrix ecological ecologists eigenanalysis eigenvalues eigenvectors equation Euclidean distance example farthest-neighbor clustering Figure fusion given gives gradient Hence j)th element labeled main diagonal minimum spanning tree nearest-neighbor Noy-Meir number of species obtained one-dimensional ordination ordination method orthogonal matrix pair of points partitioning pattern PCA ordination plane plotted possible postmultiplied principal axes principal component scores procedure projected Q-type quadrat scores RA ordination result rotated row and column s-dimensional s-space sampling units scatter diagram segments shows species quantities species scores square matrix SSCP matrix standardized swarm of data swarm of points symbols symmetric matrix three-dimensional transformed transpose two-dimensional ordination two-space u₁ uncentered PCA values variables weighted within-cluster dispersion x₁ y-axis y₁