Preface |
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Acknowledgements |
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2 | (20) |
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2 | (1) |
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3 | (3) |
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1.3 Common continuous distributions |
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6 | (1) |
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1.4 Common discrete probability distributions |
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7 | (4) |
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1.5 Compound Poisson distributions |
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11 | (1) |
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1.6 Estimation and inference |
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12 | (3) |
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15 | (1) |
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1.8 Testing the goodness of fit of a model |
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16 | (1) |
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1.9 AIC and related measures |
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17 | (1) |
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1.10 Quantile-quantile plots |
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18 | (4) |
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Part II Stationary individuals |
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22 | (29) |
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22 | (1) |
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23 | (3) |
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26 | (2) |
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28 | (5) |
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2.5 Quadrats for estimating frequency |
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33 | (4) |
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37 | (4) |
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2.7 Quadrats for estimating cover |
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41 | (8) |
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2.8 `Variation between and within quadrats' |
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49 | (2) |
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51 | (8) |
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3.1 The point quadrat frame |
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51 | (1) |
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3.2 Line-intercept sampling (LIS) |
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51 | (3) |
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3.3 Point-count transect sampling |
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54 | (5) |
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59 | (20) |
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59 | (1) |
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4.2 Locations for sampling points |
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60 | (1) |
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4.3 Simple point-to-plant measures |
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61 | (1) |
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4.4 Using the distance to the fcth nearest plant |
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62 | (5) |
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4.5 The point-centred quarter method (PCQM) |
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67 | (2) |
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4.6 Angle-order estimators |
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69 | (1) |
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4.7 Nearest-neighbour distances |
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70 | (1) |
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4.8 Combined point-to-plant and nearest-neighbour measures |
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71 | (3) |
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74 | (2) |
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4.10 Handling mixtures of species |
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76 | (2) |
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78 | (1) |
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79 | (11) |
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5.1 Variable area transect (VAT) |
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79 | (4) |
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83 | (1) |
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83 | (3) |
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5.4 Perpendicular distance sampling (PDS) |
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86 | (4) |
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Part III Mobile individuals |
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6 Quadrats, transects, points, and lines-revisited |
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90 | (25) |
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90 | (1) |
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90 | (2) |
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6.3 Using frequency to estimate abundance |
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92 | (3) |
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6.4 Point counts (point transects) |
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95 | (7) |
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6.5 Double-observer sampling |
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102 | (5) |
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107 | (1) |
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107 | (8) |
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7 Capture-recapture methods |
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115 | (27) |
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7.1 Capture-recapture models for a closed population |
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116 | (14) |
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7.2 Capture-recapture models for an open population |
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130 | (5) |
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7.3 Pollock's robust design |
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135 | (2) |
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7.4 Spatial capture-recapture models |
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137 | (3) |
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7.5 Mark-resight estimation |
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140 | (2) |
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142 | (18) |
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142 | (1) |
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143 | (1) |
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144 | (5) |
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8.4 Using imprecise distance data |
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149 | (1) |
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8.5 Introducing covariates |
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150 | (1) |
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151 | (2) |
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153 | (1) |
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153 | (7) |
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160 | (15) |
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161 | (1) |
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162 | (2) |
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9.3 The dependence of richness on area |
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164 | (5) |
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9.4 Estimating the unobserved |
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169 | (4) |
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9.5 The limitation of using richness as a measure of diversity |
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173 | (1) |
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9.6 An occupation-detection model |
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173 | (2) |
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175 | (13) |
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10.1 Berger-Parker dominance |
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175 | (2) |
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177 | (1) |
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178 | (1) |
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178 | (1) |
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179 | (2) |
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10.6 Taking account of differences between species |
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181 | (2) |
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10.7 Measuring /S-diversity |
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183 | (5) |
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11 Species abundance distributions (SADS) |
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188 | (7) |
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11.1 Illustrating abundance distributions |
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188 | (2) |
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11.2 The log-series distribution |
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190 | (1) |
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11.3 Truncated Poisson-lognormal distribution |
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190 | (2) |
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192 | (1) |
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11.5 Testing the goodness of fit of a model to a set of octave counts |
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193 | (1) |
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11.6 Determining the drivers for species abundance distributions |
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194 | (1) |
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12 Other aspects of diversity |
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195 | (6) |
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195 | (1) |
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12.2 Similarity and complementarity |
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196 | (2) |
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198 | (1) |
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198 | (3) |
Appendix |
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201 | (2) |
Notes |
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203 | (3) |
Further reading |
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206 | (3) |
References |
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209 | (13) |
Index of Examples |
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222 | (1) |
General Index |
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223 | |