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1 Why Care About Trapping Small Organisms Moving Randomly? |
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1 | (6) |
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1.1 Most Animals Are Small and Forage Using Simple Behavioral Rules |
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1 | (1) |
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1.2 The Most Serious Animal Pests Are Small |
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1 | (1) |
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1.3 Responsible Pest Management Decisions Require Knowledge of Pest Numbers |
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2 | (1) |
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1.4 Current Methods of Estimating Absolute Densities of Pests Are Prohibitively Costly |
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2 | (2) |
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1.5 Can Traps and Trapping Fill This Need? |
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4 | (1) |
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1.6 Aims and Approach of This Book |
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5 | (2) |
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2 Trap Function and Overview of the Trapping Process |
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7 | (8) |
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2.1 Definition and Functions of Traps |
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7 | (1) |
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2.2 Overview of the Trapping Process |
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8 | (7) |
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3 Random Displacement in the Absence of Cues |
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15 | (10) |
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3.1 The Classical Random Walk |
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15 | (1) |
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3.2 The Correlated Random Walk |
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16 | (1) |
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3.3 Outward Dispersion as Influenced by c.s.d. |
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17 | (2) |
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3.4 Outward Dispersion as Influenced by Time |
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19 | (1) |
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3.5 Does a Population of Random Walkers Spread Indefinitely Away from the Point of Origin and, If So, Why? |
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20 | (1) |
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3.6 Maximum Net Outward Dispersion as Influenced by Mover Sample Size |
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20 | (1) |
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3.7 Patterns in Random-Walker Ending Positions After a Short Period of Dispersion as Influenced by c.s.d. |
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21 | (1) |
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3.8 Experimental Analyses of Tracks and Measures of Meander for Individuals |
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22 | (3) |
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4 Intersections of Movers with Traps |
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25 | (14) |
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4.1 Ballistic Movers---The Simplest Case |
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25 | (1) |
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26 | (3) |
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4.3 Gain as Influenced by c.s.d. and Run Time |
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29 | (1) |
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4.4 Optimal c.s.d. as Influenced by Trap or Resource Size |
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30 | (2) |
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4.5 What Aspect of Plume Geometry Correlates Best with Capture Probability? |
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32 | (1) |
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4.6 Contrasts of Ellipsoid Plumes with Discoid Plumes |
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33 | (3) |
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4.7 Setting the Stage for Estimating Plume Reach from Field Experiments Measuring spTfer |
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36 | (3) |
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5 Interpreting Catch in a Single Trap |
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39 | (28) |
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5.1 A Simple Trapping Equation |
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39 | (1) |
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5.2 Converting spTfer into Tfer |
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39 | (2) |
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5.3 From Where Does most of the Catch Accumulating in a Trap Originate? |
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41 | (4) |
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5.4 Preparing to Put Eq. (5.1) to Work |
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45 | (2) |
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5.5 Measures of Variation around Estimates of Absolute Animal Density Derived from Trapping |
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47 | (1) |
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5.6 Examples of Eq. 5.1 at Work |
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48 | (15) |
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5.7 Patterns in Tfer Values and Plume Reaches for Organisms Displacing Randomly |
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63 | (1) |
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5.8 This Single Trap Approach is Ready for Testing and Implementation Where Proven Reliable |
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63 | (2) |
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65 | (2) |
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67 | (18) |
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6.1 Definition of Trap Competition |
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67 | (1) |
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67 | (1) |
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6.3 Test for Whether or Not Competition is Complete |
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68 | (2) |
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6.4 Incomplete Competition |
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70 | (3) |
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6.5 Trapping Radius Does Not Equate to Competition Threshold |
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73 | (1) |
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6.6 Equation for Incompletely Competing Traps |
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73 | (6) |
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6.7 Estimating Mover Numbers and Trapping Area Simultaneously by Competitive Trapping |
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79 | (3) |
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6.8 Computer Simulations Demonstrating How Absolute Density of Biological Random Walkers Can Be Estimated by Competitive Trapping under Variable Run Times |
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82 | (2) |
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6.9 Suggested Plan for Employing Competitive Trapping Under Field Conditions |
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84 | (1) |
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84 | (1) |
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7 Experimental Method for Indirect Estimation of c.s.d. for Random Walkers via a Trapping Grid |
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85 | (4) |
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85 | (1) |
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7.2 Translation of the Idea to Field Tests with Real Organisms |
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86 | (3) |
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8 Trapping to Achieve Pest Control Directly |
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89 | (14) |
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89 | (1) |
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8.2 Time-Dependency and Dynamics of Mass Trapping |
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89 | (1) |
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8.3 Damage Suppression as Influenced by Trap Number and Spacing: Simulations |
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90 | (7) |
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8.4 Examples of Successful Pest Control by Mass Trapping |
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97 | (3) |
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8.5 New Approaches to Mass Trapping |
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100 | (3) |
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9 Automated Systems for Recording, Reporting, and Analyzing Trapping Data |
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103 | (8) |
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9.1 Need for Such Systems |
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103 | (1) |
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9.2 History of Insect Trap Automation |
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103 | (4) |
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9.3 Recent Developments and Future Prospects |
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107 | (2) |
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109 | (2) |
References |
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111 | |