The use of appropriate statistical methods is essential when working with environmental data. Yet, many environmental professionals are not statisticians. A ready reference guide to the most common methods used in environmental applications, Statistics for Environmental Science and Management introduces the statistical methods most frequently used by environmental scientists, managers, and students. Using a non-mathematical approach, the author describes techniques such as: environmental monitoring, impact assessment, assessing site reclamation, censored data, and Monte Carlo risk assessment, as well as the key topics of time series and spatial data. The book shows the strengths of different types of conclusions available from statistical analyses. It contains internet sources of information that give readers access to the latest information on specific topics.The author's easy to understand style makes the subject matter accessible to anyone with a rudimentary knowledge of the basics of statistics while emphasizing how the techniques are applied in the environmental field. Clearly and copiously illustrated with line drawings and tables, Statistics for Environmental Science and Management covers all the statistical methods used with environmental applications and is suitable as a text for graduate students in the environmental science area.
Author(s): Bryan F.J. Manly
Edition: 1
Publisher: Chapman and Hall/CRC
Year: 2000
Language: English
Pages: 323
Statistics for Environmental Science and Management......Page 1
Contents......Page 4
Preface......Page 8
1.2 Some Examples......Page 10
Table of Contents......Page 0
Example 1.1 The Exxon Valdez Oil Spill......Page 11
The Exxon Shoreline Ecology Program......Page 12
The Oil Spill Trustees' Coastal Habitat Injury Assessment......Page 13
The Biological Monitoring Survey......Page 14
General Comments on the Three Studies......Page 15
Example 1.2 Acid Rain in Norway......Page 16
Example 1.3 Salmon Survival in the Snake River......Page 19
Example 1.4 A Large-Scale Perturbation Experiment......Page 22
Example 1.5 Ring Widths of Andean Alders......Page 25
Example 1.6 Monitoring Antarctic Marine Life......Page 26
Example 1.7 Evaluating the Attainment of Cleanup Standards......Page 27
1.4 Chapter Summary......Page 30
2.1 Introduction......Page 32
2.2 Simple Random Sampling......Page 33
2.3 Estimation of Population Means......Page 35
Example 2.1 Soil Percentage in the Corozal District of Belize......Page 38
2.4 Estimation of Population Totals......Page 39
2.5 Estimation of Proportions......Page 40
Example 2.2 PCB Concentrations in Surface Soil Samples......Page 41
2.6 Sampling and Non-Sampling Errors......Page 42
2.7 Stratified Random Sampling......Page 43
Example 2.3 Bracken Density in Otago......Page 46
2.8 Post-Stratification......Page 47
2.9 Systematic Sampling......Page 50
Example 2.4 Total PCBs in Liverpool Bay Sediments......Page 53
2.10 Other Design Strategies......Page 55
2.11 Ratio Estimation......Page 59
Example 2.5 pH Levels in Norwegian Lakes......Page 61
2.12 Double Sampling......Page 63
2.13 Choosing Sample Sizes......Page 64
2.14 Unequal Probability Sampling......Page 67
2.15 The Data Quality Objectives Process......Page 68
2.16 Chapter Summary......Page 70
3.2 Discrete Statistical Distributions......Page 73
The Hypergeometric Distribution......Page 74
The Binomial Distribution......Page 75
3.3 Continuous Statistical Distributions......Page 77
The Normal or Gaussian Distribution......Page 79
The Lognormal Distribution......Page 80
3.4 The Linear Regression Model......Page 81
Example 3.1 Chlorophyll-a in Lakes......Page 85
3.5 Factorial Analysis of Variance......Page 89
One factor Analysis of Variance......Page 91
Two Factor Analysis of Variance......Page 92
Three Factor Analysis of Variance......Page 93
Example 3.2 Survival of Trout in a Metals Mixture......Page 94
Repeated Measures Designs......Page 98
Multiple Comparisons and Contrasts......Page 100
3.6 Generalized Linear Models......Page 101
Example 3.3 Dolphin Bycatch in Trawl Fisheries......Page 105
3.7 Chapter Summary......Page 110
4.2 Observational and Experimental Studies......Page 112
4.3 True Experiments and Quasi-Experiments......Page 114
4.4 Design-Based and Model-Based Inference......Page 116
4.5 Tests of Significance and Confidence Intervals......Page 119
4.6 Randomization Tests......Page 121
Example 4.1 Survival of Rainbow Trout......Page 122
Example 4.2 A Bootstrap 95% Confidence Interval......Page 124
4.8 Pseudoreplication......Page 128
4.9 Multiple Testing......Page 129
Example 4.3 Multiple Tests on Characters for Brazilian Fish......Page 131
4.10 Meta-Analysis......Page 132
Example 4.4 The Exxon Valdez Oil Spill and Intertidal Sites......Page 134
4.11 Bayesian Inference......Page 137
4.12 Chapter Summary......Page 139
5.1 Introduction......Page 142
5.3 Two Special Monitoring Designs......Page 143
5.6 Detection of Changes by Analysis of Variance......Page 147
Example 5.1 Analysis of Variance on the pH Values......Page 148
5.7 Detection of Changes Using Control Charts......Page 150
Example 5.2 Monitoring pH in New Zealand......Page 153
5.8 Detection of Changes Using CUSUM Charts......Page 159
Example 5.3 CUSUM Analysis of pH Data......Page 163
5.9 Chi-Squared Tests for a Change in a Distribution......Page 165
Example 5.4 The pH for Norwegian Lakes in 1976 and 1977......Page 167
5.10 Chapter Summary......Page 170
6.1 Introduction......Page 172
Example 6.1 The Effect of Poison Pellets on Invertebrates......Page 175
6.3 Matched Pairs with a BACI Design......Page 177
Example 6.2 Another Study of the Effect of Poison Pellets......Page 178
6.4 Impact-Control Designs......Page 182
6.5 Before-After Designs......Page 183
6.7 Inferences from Impact Assessment Studies......Page 184
6.8 Chapter Summary......Page 186
7.2 Problems with Tests of Significance......Page 188
Example 7.1 Native Shrubs at Reclaimed and Reference Sites......Page 190
7.4 Two-Sided Tests of Bioequivalence......Page 193
Example 7.2 PCB at the Armagh Compressor Station......Page 196
7.5 Chapter Summary......Page 200
8.1 Introduction......Page 201
8.2 Components of Time Series......Page 202
8.3 Serial Correlation......Page 205
8.4 Tests for Randomness......Page 209
Example 8.1 Minimum Temperatures in Uppsala, 1900 to 1981......Page 211
8.5 Detection of Change Points and Trends......Page 214
Example 8.2 Minimum Temperatures in Uppsala, Reconsidered......Page 217
8.6 More Complicated Time Series Models......Page 219
Example 8.3 Temperatures of a Dunedin Stream, 1989 to 1997......Page 222
Example 8.4 Rainfall in Northeast Brazil, 1849 to 1987......Page 226
8.8 Forecasting......Page 228
8.9 Chapter Summary......Page 230
9.2 Types of Spatial Data......Page 232
9.3 Spatial Patterns in Quadrat Counts......Page 236
Example 9.1 Distribution and Spatial Correlation for Shellfish......Page 239
9.4 Correlation Between Quadrat Counts......Page 243
Example 9.2 Correlation Between Counts for Pipis and Cockles......Page 245
9.5 Randomness of Point Patterns......Page 246
Example 9.3 The Location of Messor Wasmanni Nests......Page 247
9.6 Correlation Between Point Patterns......Page 248
Example 9.4 Autocorrelation in Norwegian Lakes......Page 249
9.8 The Variogram......Page 252
Example 9.5 Variograms for SO4 Values of Norwegian Lakes......Page 255
9.9 Kriging......Page 257
Example 9.6 Kriging with the SO 4 Data......Page 258
9.10 Correlation Between Variables in Space......Page 259
9.11 Chapter Summary......Page 261
10.2 Single Sample Estimation......Page 263
Example 10.1 A Censored Sample of 1,2,3,4-Tetrachlorobenzene......Page 265
10.4 Comparing the Means of Two or More Samples......Page 271
Example 10.2 Upstream and Downstream Samples......Page 272
10.6 Chapter Summary......Page 275
11.1 Introduction......Page 277
11.2 Principles for Monte Carlo Risk Assessment......Page 278
11.3 Risk Analysis Using a Spreadsheet Add-On......Page 279
Example 11.1 Contaminant Uptake Via Tapwater Ingestion......Page 280
11.4 Further Information......Page 283
11.5 Chapter Summary......Page 284
CHAPTER 12: Final Remarks......Page 285
References......Page 286
A2 Distributions for Sample Data......Page 298
A3 Distributions of Sample Statistics......Page 304
A4 Tests of Significance......Page 307
The One Sample Chi-Squared Test......Page 309
The Contingency Table Chi-Squared Test......Page 310
The Wilcoxon Signed-Ranks Test......Page 311
Example A1 Testing the Mean Level of TcCB at a Site......Page 312
A5 Confidence Intervals......Page 313
A6 Covariance and Correlation......Page 315
Appendix B: Statistical Tables......Page 317
B1 The Standard Normal Distribution......Page 318
B2 Critical Values for the t-Distribution......Page 319
B3 Critical Values for the Chi-Squared Distribution......Page 320
B4 Critical Values for the F-Distribution......Page 321
B4 Critical Values for the F-Distribution (Continued)......Page 322
B5 Critical Values for the Durbin-Watson Statistic......Page 323
