GIS Applications in Agriculture, Volume Three: Invasive Species

GIS Applications in Agriculture. Volume Three: Invasive Species......Page 2
GIS Applications in Agriculture......Page 3
GIS Applications in Agriculture Volume Three: Invasive Species......Page 4
Contents......Page 6
Series Preface......Page 10
Preface......Page 12
Acknowledgments......Page 14
Editor......Page 16
Contributors......Page 18
1.1 Executive Summary......Page 22
1.2.1 Remote Sensing......Page 23
1.2.2 Geographic Information Systems......Page 25
1.3 Conclusions......Page 28
References......Page 29
2.2 Definitions......Page 30
2.3 Factors to Consider When Acquiring and Using Spatial Data......Page 33
2.5.1 Digital Raster Graphic......Page 34
2.5.2 Satellite and Aerial Imagery......Page 38
2.5.3 Digital Elevation Data......Page 44
2.6 Vector Data Sources and Examples......Page 46
2.7 Software for Spatial Data Visualization and Analysis......Page 47
References......Page 48
Contents......Page 50
3.2 Introduction......Page 51
3.3 Arrival......Page 52
3.3.1 Invasion Pathways......Page 53
3.3.2 Monitoring the Arr ival of Biological Invaders......Page 54
3.4.1 Factors That Influence Establishment Success......Page 55
3.4.2 Monitoring the Establishment of Nonnative Species: Space–Time Population Pers istence......Page 56
3.5.1 Types of Spread......Page 58
3.5.2 Estimating Invasive Species Spread......Page 59
3.6 Managing Biological Invasions......Page 61
3.7.1 Introduction......Page 63
3.7.3 Performing OLS Regress ion Analysis......Page 64
3.7.5 Testing for Spatial Autocorr elation......Page 67
3.7.6 Calculating Temporal Spread Rates......Page 68
3.7.7 Calculating Regional Spread Rates......Page 70
Answers to Questions......Page 71
References......Page 72
Contents......Page 80
4.2 Introduction......Page 81
4.3.1 Disease Management Principle 1: Exclusion......Page 82
4.3.2.2 Avoidance of Disease Risk in Time (t)......Page 83
4.3.3.1 Roguing of Diseased Plants (y0)......Page 84
4.3.4.1 Use of Chemical Barriers to Protect Crops (y0 and r)......Page 85
4.3.6 Disease Management Principle 6: Therapy (y0 and Sometimes r)......Page 86
4.4 Case Study: Asian Soybean Rust......Page 87
4.5 Case Study: Ash Yellows Disease of Green Ash......Page 89
4.6 Case Study: Plum Pox Virus of Prunus spp.......Page 92
4.7 Case Study: Moko Disease of Banana......Page 94
4.8 Case Study: Stewart's Disease of Corn......Page 97
4.9 Case Study: Gray Leaf Spot of Corn......Page 99
4.10 Case Study: Be an Pod Mottle Virus of Soybean......Page 100
4.11.3 Changing Map Symbology......Page 105
4.11.4 Creating and Printing Map Layouts......Page 106
4.12 Conclusions......Page 108
References......Page 109
Contents......Page 112
5.1 Executive Summary......Page 113
5.2 Introduction......Page 114
5.3 Information Needs......Page 116
5.4 Previous Mapping Initiatives......Page 119
5.5 Current Initiatives......Page 120
5.6 Predicting Invasive Species Distributions......Page 121
5.7 Methods......Page 124
5.7.3 Consistent Data Collection Methods /Protocol......Page 125
5.7.4.1 Geographic Information Systems Tool......Page 126
5.7.4.2.1 Step 1: Assessing Species Occurrence......Page 128
5.7.4.2.3 Step 3: Classifying Species Abundance......Page 129
5.7.4.2.5 Step 5: Classifying Data Quality......Page 130
5.7.4.4 Data Aggregation and Scaling-Up......Page 131
5.7.4.5 Climate/Habitat Matching Methods......Page 132
5.7.4.7 Land-Use Classifications......Page 133
5.8.1 Challenges for Large-Scale Mapping and Monitoring Efforts......Page 134
5.8.2.5 R eporting Predictive Model Outputs UsingHabitat and Climate Suitability......Page 135
5.8.3.1 Data Collation and Reporting......Page 137
5.8.3.2 Climate/Habitat Matching: Potential Distribution Prediction Models......Page 139
5.8.3.3 Habitat Matching Using Land Use Data......Page 140
5.9.1 Reporting at the National Level......Page 141
Acknowledgments......Page 142
5.A.1.4 Step 4 Trend......Page 143
5.A.2 Classes for the Occurrence, Distribution, and Density Attributes for Pest Animals and Weeds (Modified from Queensland Government’s Pest Survey Group)......Page 144
References......Page 146
Contents......Page 150
6.2 Introduction......Page 151
6.3.1 Basic Biology of Ug99......Page 152
6.3.2 Dispersal......Page 153
6.3.3 Resistance Mechanisms and Virulence of Ug99......Page 154
6.4.1 GI S-Based Surveillance and Monitoring Systems......Page 156
6.4.2 Where Is Ug99?—Known Distribution and Range Expansion of Stem Rust (Ug99 Lineage)......Page 157
6.4.3 Movements of Ug99......Page 158
6.5 Deposition/ Colonization Factors......Page 164
6.5.1 Wheat Areas......Page 165
6.5.3 Crop Calendars /Crop Growth Stage......Page 166
6.5.4 Climate/Environment......Page 167
6.6.2 Rust Mapper Web......Page 169
6.7 Challenges / Future Activities......Page 170
6.8 Conclusion......Page 174
References......Page 175
7.1 Executive Summary......Page 180
7.3 Principles of an Aerobiology P rocess Model......Page 181
7.4 Configuration of the Aerobiology Process Model......Page 183
7.5 Online Simulation of the Aerobiology Process Model......Page 184
References......Page 187
8.1 Executive Summary......Page 188
8.2 Introduction......Page 189
8.3.1 Exercise 1: Describe the Spatiotemporal Colonization Patterns of M. persicae in Seed Potato......Page 195
8.3.1.1 Description of Dataset......Page 196
8.3.1.2 Assessing Spatial Autocorrelation Using Semivariograms in GS+......Page 197
8.3.1.3 Plot the Data from the Dataset in ArcMap......Page 200
8.3.1.4 Discussion of Observed Colonization Patterns......Page 203
8.3.2.1 U sing HY SPLIT to Examine LL J to Facilitate Movementof Aphids into the Red River Valley......Page 204
References......Page 207
Contents......Page 212
9.2 Introduction......Page 213
9.3.1 Mapping WN v Cases in a GIS......Page 214
9.4.1 Smoothed Maps of Disease Risk......Page 215
9.4.2 Spatial Autocorr elation Analysis......Page 218
9.4.3 Spatiotemporal Clustering......Page 219
9.5 Summary and Conclusions......Page 222
9.6.1 Opening a Shapefile in GeoDa......Page 223
9.6.5 Adding Calculated Rates to the Attribute Table......Page 224
9.6.7 Computing the Local Moran’s I Index of Spatial Autocorrelation......Page 225
References......Page 226
Contents......Page 228
10.2 Introduction......Page 229
10.2.1 Lesser Grain Borer Economic Impact and Management......Page 230
10.2.2 Behavior and Ecology outside Grain Storage......Page 232
10.3.1 Agent-Based Simulation and Modeling......Page 233
10.3.2 About NetLogo......Page 234
10.4.1 Overview: Creating a NetLogo Model......Page 235
10.4.2.1 Setup and Go Buttons and Energy Switch......Page 236
10.4.2.2 Turtle Variables and Setup Procedure......Page 237
10.4.2.3 Defining Initial Variables with Sliders......Page 239
10.4.2.4 Go Procedure......Page 240
10.4.2.5 Bug Movement, Eating, Reproduction, and Death Procedures......Page 241
10.4.2.7 Forest Regrowth Procedure and Control Slider......Page 243
10.4.2.8 Show Energy and Display Labels......Page 244
10.4.3 Plot Procedure......Page 246
10.4.3.1 Create Plot Window and Monitors......Page 247
10.5 Conclusions......Page 249
Acknowledgments......Page 250
References......Page 251
11.1 Executive Summary......Page 254
11.2 Introduction......Page 255
11.3.2 System Requirements......Page 256
11.4 Getting Started with ArcGIS......Page 257
11.4.1 Importing Latitude–Longitude Trap Data......Page 258
11.4.2 Symbolizing Map Layers......Page 259
11.5 Analysis of Adult CRW Population and Distribution......Page 261
11.5.1 Spatial Autocorr elation, Moran’s I......Page 262
11.5.2 Interpolation, Invers e Distance Weighting......Page 264
11.5.3 Comparing CRW Population with Soil Texture......Page 266
11.6 Conclusion......Page 272
References......Page 273
Contents......Page 276
12.2 Introduction......Page 277
12.3.1 Design Elements of the Toolbox......Page 279
12.3.2 Modeling Seed Dispers al......Page 280
12.3.3.1 Modeling the Influence of Wind Direction and Strength......Page 283
12.3.3.2 Modeling Terrain Influences Wind Dispersal......Page 284
12.3.3.3 Modeling Dispersal along Roads and Rivers......Page 285
12.3.4 Modeling Life History......Page 286
12.3.5 Simulating Surveillance......Page 287
12.3.6.2.2 Dispersal along Watercourses......Page 288
12.3.6.3 Life History Parameters......Page 289
12.3.6.4 Evaluating Surveillance......Page 290
12.4.1 Evaluating Surveillance......Page 291
12.4.3 Implications for Management of CNG......Page 294
References......Page 295
Contents......Page 298
13.2.1 Background......Page 299
13.3.1 Model of Development......Page 300
13.3.2 Productivity Model Components......Page 302
13.3.3 Spatial Network Models......Page 304
13.4.2 Topographic Correlates of the Site (Slope, Aspect, andSunlight Difference between Spring and Summer “Sundiff”)......Page 306
13.4.2.1 Preliminary Steps......Page 307
13.4.2.2 Steps for Importing and Calculating Slope, Aspect,and Sun Angle Differencing......Page 308
13.4.3.1 Atmospheric Correction......Page 310
Step 1: Re-project data......Page 313
13.4.3.3 Vegetation Index......Page 314
Step 3: Calculate the regression intercept and slope values......Page 315
13.4.4 Productivity Modeling with the Logit Regress ion Module......Page 316
13.4.5 Network Modeling......Page 317
References......Page 319
14.1 Executive Summary......Page 322
14.2 Introduction......Page 323
14.3 Materials and Me thods......Page 325
14.3.2 Unsupervised Image Class ification and Accuracy Ass ess ment......Page 327
14.3.3 Supervised Image Class ification in ERDASand Accuracy Ass ess ment......Page 330
14.4.1 Crop Health Ass ess ment......Page 335
14.4.3 On-Farm Use of GI S-Based Weed Mapping......Page 336
Acknowledgments......Page 337
References......Page 338
Contents......Page 340
15.2 Introduction......Page 341
15.3 Analysis Steps......Page 342
15.4.2 Sampling Grid......Page 343
15.5.1 Objective......Page 344
15.5.2 Method......Page 345
15.5.3 Results......Page 346
15.7.2 Median Polishing......Page 351
15.7.3 Estimating Trend with Linear Regress ions......Page 352
15.8.1 Objective......Page 355
15.9.1 Objective......Page 356
15.9.3 Results......Page 361
15.10.2 Method......Page 367
15.11.1 Objective......Page 375
15.12.1 Objective......Page 377
15.12.3 Cokriging......Page 381
15.13.2 Prediction of Weed Locations......Page 384
Glossary......Page 390
References......Page 391
Contents......Page 394
16.2 Introduction......Page 395
16.3.3 Analyses Method Overview......Page 396
16.3.4.1 Aggregating Weed Densities by Year......Page 397
16.3.4.2 Weed Density and Species Change Calculations......Page 398
16.3.4.3 Data for Estimating Direction Distribution......Page 399
16.3.5.1 Creating Layers Using ArcMap™......Page 401
16.3.5.2 Creating Data Subsets......Page 404
16.3.5.3 Data Exploration in ArcMap™......Page 405
16.4.1 Spatial Data Exploration......Page 408
16.4.2 Creating Interpretive Maps......Page 413
16.4.2.1 Spatial Data Interpolation Using an Ordinary Kriging Method......Page 414
16.4.2.2 Spatial Data Interpolation Using an InverseDistance Weighting Method......Page 418
Acknowledgments......Page 423
References......Page 424
17.1 Executive Summary......Page 426
17.2.2 Determining Economic Optimal Herb icide Rate Basedon Weed Spatial Distribution......Page 427
17.3.1 General Procedures......Page 429
17.3.2 Development of a Prescription Map......Page 430
17.4.1 Weed Species Composition and Herb icide Usage......Page 432
17.4.2 Yield Results......Page 434
References......Page 438