Homogeneity, 107, 238, 239, 264
Horseshoe effect, 183
I
Identification function, see Function,
identification
Imputation, 171–174
Independent variable, see Variable,
independent
Indicator, 61, 84, 85, 98, 110, 120–126, 131,
134, 135, 362
Indicator value, see Species, indicator value
(IndVal)
IndVal, see Species, indicator value (IndVal)
Inertia, 156, 175, 183, 185, 209, 222, 256,
261, 280, 281, 360
Interval
confidence, 123, 124, 126, 356, 358, 359
sampling, 302, 314, 317, 349
Intrinsic assumption, 308
J
Jaccard, see Dissimilarity, Jaccard
K
Kaiser-Guttman, 221
k-means, 35, 55, 60, 61, 96–104, 112, 113,
126, 141, 198, 256
k-means partitioning, see Partitioning, k-means
Kriging, 301
Kruskal-Wallis, see Test, Kruskal-Wallis
L
Large scale, see Scale, large
Level
cutting, 74, 75
fusion, 65, 74–77, 81, 139, 405
Linear discriminant analysis (LDA), 107, 203,
204, 263–268, 297
Lingoes, see Correction, Lingoes
Local contribution to beta diversity (LCBD),
382–388, 396
Log-chord distance, see Distance, log-chord
Log-chord transformation, see Transformation,
log-chord
LOWESS, 31, 32, 72
M
Mahalanobis distance, see Distance,
Mahalanobis
Mantel
correlogram, 306, 308
Matrix
association, 35, 43, 45, 57, 59, 60, 63,
152, 153, 187, 193
binary, 83, 84, 345
connectivity, 333–335, 337, 342–347, 349
cophenetic, 71
data, 131, 135, 160, 170, 171, 175, 184,
203, 204, 206, 220, 221, 227, 229,
277, 278, 281, 289, 290, 296, 297,
356, 382
dispersion, 153, 169, 264
dissimilarity, 35, 38–52, 71, 72, 74, 83,
84, 97, 98, 103, 136, 142, 153,
189, 192–195, 197, 198, 250, 251,
306, 384, 386, 389, 395, 396, 404,
408, 409
distance, 47, 48, 315, 316, 335, 346
weighting, 334
MCA, see Correspondence analysis (CA),
multiple (MCA)
Medium scale, see Scale, medium
MEM, see Moran’s eigenvector maps (MEM)
Metric, 38, 46, 142, 170, 197
MFA, see Multiple factor analysis (MFA)
Minimum spanning tree, 62, 316, 328, 342, 404
Minimum variance, see Clustering, minimum
variance
Model
broken stick, 139, 157, 158, 171, 176,
192, 283, 372
Monothetic, see Clustering, monothetic
Moran’s eigenvector maps (MEM), 188, 314,
315, 333–350, 355, 357–361
MRT, see Regression tree, multivariate (MRT)
Multiclass, 37, 49–51
Multinormal, see Distribution, multinormal
Multiple factor analysis (MFA), 203, 204, 274,
282–287, 297
Multiple testing, see Test, multiple
Multiscale, 79, 80, 303, 314, 355–361, 367, 412
Multiscale ordination (MSO), 355–361
Multivariate analysis of variance (MANOVA),
188, 203, 238, 239, 244, 250, 264
N
Nearest neighbours, 62
Neighbourhood
relative, 342
Nested, 60, 67, 115, 117, 171, 316, 342, 347,
348, 384, 394
Nestedness, 117, 369, 388–404
Network, 117–119, 349–351
430
Index
Horseshoe effect, 183
I
Identification function, see Function,
identification
Imputation, 171–174
Independent variable, see Variable,
independent
Indicator, 61, 84, 85, 98, 110, 120–126, 131,
134, 135, 362
Indicator value, see Species, indicator value
(IndVal)
IndVal, see Species, indicator value (IndVal)
Inertia, 156, 175, 183, 185, 209, 222, 256,
261, 280, 281, 360
Interval
confidence, 123, 124, 126, 356, 358, 359
sampling, 302, 314, 317, 349
Intrinsic assumption, 308
J
Jaccard, see Dissimilarity, Jaccard
K
Kaiser-Guttman, 221
k-means, 35, 55, 60, 61, 96–104, 112, 113,
126, 141, 198, 256
k-means partitioning, see Partitioning, k-means
Kriging, 301
Kruskal-Wallis, see Test, Kruskal-Wallis
L
Large scale, see Scale, large
Level
cutting, 74, 75
fusion, 65, 74–77, 81, 139, 405
Linear discriminant analysis (LDA), 107, 203,
204, 263–268, 297
Lingoes, see Correction, Lingoes
Local contribution to beta diversity (LCBD),
382–388, 396
Log-chord distance, see Distance, log-chord
Log-chord transformation, see Transformation,
log-chord
LOWESS, 31, 32, 72
M
Mahalanobis distance, see Distance,
Mahalanobis
Mantel
correlogram, 306, 308
Matrix
association, 35, 43, 45, 57, 59, 60, 63,
152, 153, 187, 193
binary, 83, 84, 345
connectivity, 333–335, 337, 342–347, 349
cophenetic, 71
data, 131, 135, 160, 170, 171, 175, 184,
203, 204, 206, 220, 221, 227, 229,
277, 278, 281, 289, 290, 296, 297,
356, 382
dispersion, 153, 169, 264
dissimilarity, 35, 38–52, 71, 72, 74, 83,
84, 97, 98, 103, 136, 142, 153,
189, 192–195, 197, 198, 250, 251,
306, 384, 386, 389, 395, 396, 404,
408, 409
distance, 47, 48, 315, 316, 335, 346
weighting, 334
MCA, see Correspondence analysis (CA),
multiple (MCA)
Medium scale, see Scale, medium
MEM, see Moran’s eigenvector maps (MEM)
Metric, 38, 46, 142, 170, 197
MFA, see Multiple factor analysis (MFA)
Minimum spanning tree, 62, 316, 328, 342, 404
Minimum variance, see Clustering, minimum
variance
Model
broken stick, 139, 157, 158, 171, 176,
192, 283, 372
Monothetic, see Clustering, monothetic
Moran’s eigenvector maps (MEM), 188, 314,
315, 333–350, 355, 357–361
MRT, see Regression tree, multivariate (MRT)
Multiclass, 37, 49–51
Multinormal, see Distribution, multinormal
Multiple factor analysis (MFA), 203, 204, 274,
282–287, 297
Multiple testing, see Test, multiple
Multiscale, 79, 80, 303, 314, 355–361, 367, 412
Multiscale ordination (MSO), 355–361
Multivariate analysis of variance (MANOVA),
188, 203, 238, 239, 244, 250, 264
N
Nearest neighbours, 62
Neighbourhood
relative, 342
Nested, 60, 67, 115, 117, 171, 316, 342, 347,
348, 384, 394
Nestedness, 117, 369, 388–404
Network, 117–119, 349–351
430
Index