Invasive species

GIS Applications in Agriculture. Volume Three: Invasive Species......Page 1
GIS Applications in Agriculture......Page 2
GIS Applications in Agriculture Volume Three: Invasive Species......Page 3
Contents......Page 5
Series Preface......Page 8
Preface......Page 9
Acknowledgments......Page 11
Editor......Page 12
Contributors......Page 13
1.1 Executive Summary......Page 17
1.2.1 Remote Sensing......Page 18
1.2.2 Geographic Information Systems......Page 20
1.3 Conclusions......Page 23
References......Page 24
2.2 Definitions......Page 25
2.3 Factors to Consider When Acquiring and Using Spatial Data......Page 28
2.5.1 Digital Raster Graphic......Page 29
2.5.2 Satellite and Aerial Imagery......Page 33
2.5.3 Digital Elevation Data......Page 39
2.6 Vector Data Sources and Examples......Page 41
2.7 Software for Spatial Data Visualization and Analysis......Page 42
References......Page 43
Contents......Page 44
3.2 Introduction......Page 45
3.3 Arrival......Page 46
3.3.1 Invasion Pathways......Page 47
3.3.2 Monitoring the Arr ival of Biological Invaders......Page 48
3.4.1 Factors That Influence Establishment Success......Page 49
3.4.2 Monitoring the Establishment of Nonnative Species: Space?Time Population Pers istence......Page 50
3.5.1 Types of Spread......Page 52
3.5.2 Estimating Invasive Species Spread......Page 53
3.6 Managing Biological Invasions......Page 55
3.7.1 Introduction......Page 57
3.7.3 Performing OLS Regress ion Analysis......Page 58
3.7.5 Testing for Spatial Autocorr elation......Page 61
3.7.6 Calculating Temporal Spread Rates......Page 62
3.7.7 Calculating Regional Spread Rates......Page 64
Answers to Questions......Page 65
References......Page 66
Contents......Page 73
4.2 Introduction......Page 74
4.3.1 Disease Management Principle 1: Exclusion......Page 75
4.3.2.2 Avoidance of Disease Risk in Time t......Page 76
4.3.3.1 Roguing of Diseased Plants y0......Page 77
4.3.4.1 Use of Chemical Barriers to Protect Crops y0 and r......Page 78
4.3.6 Disease Management Principle 6: Therapy y0 and Sometimes r......Page 79
4.4 Case Study: Asian Soybean Rust......Page 80
4.5 Case Study: Ash Yellows Disease of Green Ash......Page 82
4.6 Case Study: Plum Pox Virus of Prunus spp.......Page 85
4.7 Case Study: Moko Disease of Banana......Page 87
4.8 Case Study: Stewart's Disease of Corn......Page 90
4.9 Case Study: Gray Leaf Spot of Corn......Page 92
4.10 Case Study: Be an Pod Mottle Virus of Soybean......Page 93
4.11.3 Changing Map Symbology......Page 98
4.11.4 Creating and Printing Map Layouts......Page 99
4.12 Conclusions......Page 101
References......Page 102
Contents......Page 105
5.1 Executive Summary......Page 106
5.2 Introduction......Page 107
5.3 Information Needs......Page 109
5.4 Previous Mapping Initiatives......Page 112
5.5 Current Initiatives......Page 113
5.6 Predicting Invasive Species Distributions......Page 114
5.7 Methods......Page 117
5.7.3 Consistent Data Collection Methods /Protocol......Page 118
5.7.4.1 Geographic Information Systems Tool......Page 119
5.7.4.2.1 Step 1: Assessing Species Occurrence......Page 121
5.7.4.2.3 Step 3: Classifying Species Abundance......Page 122
5.7.4.2.5 Step 5: Classifying Data Quality......Page 123
5.7.4.4 Data Aggregation and Scaling-Up......Page 124
5.7.4.5 Climate/Habitat Matching Methods......Page 125
5.7.4.7 Land-Use Classifications......Page 126
5.8.1 Challenges for Large-Scale Mapping and Monitoring Efforts......Page 127
5.8.2.5 R eporting Predictive Model Outputs UsingHabitat and Climate Suitability......Page 128
5.8.3.1 Data Collation and Reporting......Page 130
5.8.3.2 Climate/Habitat Matching: Potential Distribution Prediction Models......Page 132
5.8.3.3 Habitat Matching Using Land Use Data......Page 133
5.9.1 Reporting at the National Level......Page 134
Acknowledgments......Page 135
5.A.1.4 Step 4 Trend......Page 136
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 137
References......Page 139
Contents......Page 143
6.2 Introduction......Page 144
6.3.1 Basic Biology of Ug99......Page 145
6.3.2 Dispersal......Page 146
6.3.3 Resistance Mechanisms and Virulence of Ug99......Page 147
6.4.1 GI S-Based Surveillance and Monitoring Systems......Page 149
6.4.2 Where Is Ug99??Known Distribution and Range Expansion of Stem Rust Ug99 Lineage......Page 150
6.4.3 Movements of Ug99......Page 151
6.5 Deposition/ Colonization Factors......Page 157
6.5.1 Wheat Areas......Page 158
6.5.3 Crop Calendars /Crop Growth Stage......Page 159
6.5.4 Climate/Environment......Page 160
6.6.2 Rust Mapper Web......Page 162
6.7 Challenges / Future Activities......Page 163
6.8 Conclusion......Page 167
References......Page 168
7.1 Executive Summary......Page 172
7.3 Principles of an Aerobiology P rocess Model......Page 173
7.4 Configuration of the Aerobiology Process Model......Page 175
7.5 Online Simulation of the Aerobiology Process Model......Page 176
References......Page 179
8.1 Executive Summary......Page 180
8.2 Introduction......Page 181
8.3.1 Exercise 1: Describe the Spatiotemporal Colonization Patterns of M. persicae in Seed Potato......Page 187
8.3.1.1 Description of Dataset......Page 188
8.3.1.2 Assessing Spatial Autocorrelation Using Semivariograms in GS+......Page 189
8.3.1.3 Plot the Data from the Dataset in ArcMap......Page 192
8.3.1.4 Discussion of Observed Colonization Patterns......Page 195
8.3.2.1 U sing HY SPLIT to Examine LL J to Facilitate Movementof Aphids into the Red River Valley......Page 196
References......Page 199
Contents......Page 203
9.2 Introduction......Page 204
9.3.1 Mapping WN v Cases in a GIS......Page 205
9.4.1 Smoothed Maps of Disease Risk......Page 206
9.4.2 Spatial Autocorr elation Analysis......Page 209
9.4.3 Spatiotemporal Clustering......Page 210
9.5 Summary and Conclusions......Page 213
9.6.1 Opening a Shapefile in GeoDa......Page 214
9.6.5 Adding Calculated Rates to the Attribute Table......Page 215
9.6.7 Computing the Local Moran’s I Index of Spatial Autocorrelation......Page 216
References......Page 217
Contents......Page 219
10.2 Introduction......Page 220
10.2.1 Lesser Grain Borer Economic Impact and Management......Page 221
10.2.2 Behavior and Ecology outside Grain Storage......Page 223
10.3.1 Agent-Based Simulation and Modeling......Page 224
10.3.2 About NetLogo......Page 225
10.4.1 Overview: Creating a NetLogo Model......Page 226
10.4.2.1 Setup and Go Buttons and Energy Switch......Page 227
10.4.2.2 Turtle Variables and Setup Procedure......Page 228
10.4.2.3 Defining Initial Variables with Sliders......Page 230
10.4.2.4 Go Procedure......Page 231
10.4.2.5 Bug Movement, Eating, Reproduction, and Death Procedures......Page 232
10.4.2.7 Forest Regrowth Procedure and Control Slider......Page 234
10.4.2.8 Show Energy and Display Labels......Page 235
10.4.3 Plot Procedure......Page 237
10.4.3.1 Create Plot Window and Monitors......Page 238
10.5 Conclusions......Page 240
Acknowledgments......Page 241
References......Page 242
11.1 Executive Summary......Page 245
11.2 Introduction......Page 246
11.3.2 System Requirements......Page 247
11.4 Getting Started with ArcGIS......Page 248
11.4.1 Importing Latitude?Longitude Trap Data......Page 249
11.4.2 Symbolizing Map Layers......Page 250
11.5 Analysis of Adult CRW Population and Distribution......Page 252
11.5.1 Spatial Autocorr elation, Moran’s I......Page 253
11.5.2 Interpolation, Invers e Distance Weighting......Page 255
11.5.3 Comparing CRW Population with Soil Texture......Page 257
11.6 Conclusion......Page 263
References......Page 264
Contents......Page 266
12.2 Introduction......Page 267
12.3.1 Design Elements of the Toolbox......Page 269
12.3.2 Modeling Seed Dispers al......Page 270
12.3.3.1 Modeling the Influence of Wind Direction and Strength......Page 273
12.3.3.2 Modeling Terrain Influences Wind Dispersal......Page 274
12.3.3.3 Modeling Dispersal along Roads and Rivers......Page 275
12.3.4 Modeling Life History......Page 276
12.3.5 Simulating Surveillance......Page 277
12.3.6.2.2 Dispersal along Watercourses......Page 278
12.3.6.3 Life History Parameters......Page 279
12.3.6.4 Evaluating Surveillance......Page 280
12.4.1 Evaluating Surveillance......Page 281
12.4.3 Implications for Management of CNG......Page 284
References......Page 285
Contents......Page 288
13.2.1 Background......Page 289
13.3.1 Model of Development......Page 290
13.3.2 Productivity Model Components......Page 292
13.3.3 Spatial Network Models......Page 294
13.4.2 Topographic Correlates of the Site Slope, Aspect, andSunlight Difference between Spring and Summer “Sundiff?......Page 296
13.4.2.1 Preliminary Steps......Page 297
13.4.2.2 Steps for Importing and Calculating Slope, Aspect,and Sun Angle Differencing......Page 298
13.4.3.1 Atmospheric Correction......Page 300
Step 1: Re-project data......Page 303
13.4.3.3 Vegetation Index......Page 304
Step 3: Calculate the regression intercept and slope values......Page 305
13.4.4 Productivity Modeling with the Logit Regress ion Module......Page 306
13.4.5 Network Modeling......Page 307
References......Page 309
14.1 Executive Summary......Page 311
14.2 Introduction......Page 312
14.3 Materials and Me thods......Page 314
14.3.2 Unsupervised Image Class ification and Accuracy Ass ess ment......Page 316
14.3.3 Supervised Image Class ification in ERDASand Accuracy Ass ess ment......Page 319
14.4.1 Crop Health Ass ess ment......Page 324
14.4.3 On-Farm Use of GI S-Based Weed Mapping......Page 325
Acknowledgments......Page 326
References......Page 327
Contents......Page 328
15.2 Introduction......Page 329
15.3 Analysis Steps......Page 330
15.4.2 Sampling Grid......Page 331
15.5.1 Objective......Page 332
15.5.2 Method......Page 333
15.5.3 Results......Page 334
15.7.2 Median Polishing......Page 339
15.7.3 Estimating Trend with Linear Regress ions......Page 340
15.8.1 Objective......Page 343
15.9.1 Objective......Page 344
15.9.3 Results......Page 349
15.10.2 Method......Page 355
15.11.1 Objective......Page 363
15.12.1 Objective......Page 365
15.12.3 Cokriging......Page 369
15.13.2 Prediction of Weed Locations......Page 372
Glossary......Page 378
References......Page 379
Contents......Page 381
16.2 Introduction......Page 382
16.3.3 Analyses Method Overview......Page 383
16.3.4.1 Aggregating Weed Densities by Year......Page 384
16.3.4.2 Weed Density and Species Change Calculations......Page 385
16.3.4.3 Data for Estimating Direction Distribution......Page 386
16.3.5.1 Creating Layers Using ArcMap?......Page 388
16.3.5.2 Creating Data Subsets......Page 391
16.3.5.3 Data Exploration in ArcMap?......Page 392
16.4.1 Spatial Data Exploration......Page 395
16.4.2 Creating Interpretive Maps......Page 400
16.4.2.1 Spatial Data Interpolation Using an Ordinary Kriging Method......Page 401
16.4.2.2 Spatial Data Interpolation Using an InverseDistance Weighting Method......Page 405
Acknowledgments......Page 410
References......Page 411
17.1 Executive Summary......Page 412
17.2.2 Determining Economic Optimal Herb icide Rate Basedon Weed Spatial Distribution......Page 413
17.3.1 General Procedures......Page 415
17.3.2 Development of a Prescription Map......Page 416
17.4.1 Weed Species Composition and Herb icide Usage......Page 418
17.4.2 Yield Results......Page 420
References......Page 424