Spatial analysis: A guide for ecologists

Cover......Page 1
Half-title......Page 3
Title......Page 5
Copyright......Page 6
Dedication......Page 7
Contents......Page 9
Preface......Page 13
Introduction......Page 17
1.1 Process and pattern......Page 18
1.2 Spatial pattern: spatial dependence versus spatial autocorrelation......Page 22
1.3 The concept of stationarity......Page 27
1.4 Sampling......Page 29
1.4.1 Ecological data......Page 30
1.4.2 Sampling design......Page 34
1.5 Spatial statistics......Page 41
1.5.1 Significance testing of ecological data......Page 42
1.6 Concluding remarks......Page 46
Introduction......Page 48
2.1.1 Distance to neighbours methods......Page 49
2.1.2 Refined nearest neighbour analysis......Page 51
2.1.3 Second-order point pattern analysis......Page 53
2.1.4 Bivariate data......Page 59
2.1.5 Multivariate point pattern analysis......Page 63
2.2 Mark correlation function......Page 71
2.3 Networks of events......Page 73
2.4 Network analysis of areal units......Page 80
2.5.1 One dimension......Page 91
Lacunarity......Page 95
2.5.2 Three or more dimensions......Page 97
2.6.1 Quadrat variance methods......Page 98
2.6.2 Significance tests for quadrat variance methods......Page 101
2.6.3 Adaptations for two or more species......Page 104
2.6.4 Two or more dimensions......Page 107
SADIE......Page 110
2.6.5 Spectral analysis and related techniques......Page 111
2.6.6 Wavelets......Page 112
2.7 Circumcircle methods......Page 114
2.7.1 Univariate analysis......Page 115
2.7.2 Bivariate analysis......Page 116
2.8 Concluding remarks......Page 119
Introduction......Page 127
3.1 How to determine ‘nearby’ relationships among sampling units......Page 129
3.2 Join count statistics......Page 134
3.2.1 Considerations and other join count statistics......Page 136
3.3 Global spatial statistics......Page 138
3.3.1 Spatial autocorrelation coefficients for one variable......Page 140
3.3.2 Variography......Page 148
3.3.3 Fractal dimension......Page 155
3.3.4 Sampling design effects on the estimation of spatial pattern......Page 158
3.3.6 Spatial relationships among several variables......Page 163
3.4 Local spatial statistics......Page 169
3.5 Interpolation and spatial models......Page 175
3.5.1 Proximity polygons......Page 176
3.5.2 Trend surface analysis......Page 177
3.5.3 Inverse distance weighting......Page 180
3.5.4 Kriging......Page 181
3.6 Concluding remarks......Page 186
Introduction......Page 190
4.1.1 Patch properties......Page 191
4.1.2 Spatial clustering......Page 192
4.1.3 Fuzzy classification......Page 196
4.2.2 Boundary properties......Page 200
4.2.3 Boundary detection based on several variables......Page 202
4.2.3.2 One-dimensional transect data......Page 203
4.2.3.3 Two-dimensional area data......Page 205
4.2.4 Boundary statistics......Page 215
4.2.5 Overlap statistics......Page 218
4.2.6.1 Hierarchical global partitioning using wavelets......Page 221
4.2.6.2 Edge enhancement with kernel filters......Page 222
4.3 Concluding remarks......Page 226
Introduction......Page 228
5.1.1 Quick fixes......Page 237
5.1.2 Adjusting the effective sample size......Page 238
5.1.3 Other kinds of models......Page 245
Tests for proportions......Page 250
Correlation and linear regression......Page 254
5.1.5 Restricted randomization and bootstrap......Page 255
5.1.6 Model and Monte Carlo......Page 258
5.2 More on induced autocorrelation and the relationships between variables......Page 259
5.3 Models and reality......Page 263
5.4.1 Sampling......Page 264
5.4.2 Experimental design......Page 269
5.5 Concluding remarks......Page 270
Introduction......Page 272
6.1 Change in spatial statistics......Page 277
6.2 Spatio-temporal join count......Page 279
6.3 Spatio-temporal analysis of clusters and contagion......Page 282
6.4 Polygon change analysis......Page 285
6.5 Analysis of movement......Page 290
6.6.1 Tree regeneration, growth and mortality......Page 307
6.6.2 Plant mobility......Page 308
6.6.3 Lichen boundaries......Page 309
6.7 Spatio-temporal orderliness and spatial synchrony......Page 315
6.8 Chaos......Page 321
6.9 Concluding remarks......Page 331
6.9.1 Recommendations......Page 332
Back to basics......Page 333
7.2 Stationarity......Page 336
7.3 Null hypotheses......Page 338
7.4 Numerical solutions......Page 339
7.5 Statistical difficulties......Page 341
7.6 Randomization and restricted randomization tests......Page 342
7.7 Complementarity of methods......Page 344
7.8 Future work......Page 349
Appendices......Page 352
References......Page 354
Index......Page 374