Dynamic Modeling in Behavioral EcologyThis book describes a powerful and flexible technique for the modeling of behavior, based on evolutionary principles. The technique employs stochastic dynamic programming and permits the analysis of behavioral adaptations wherein organisms respond to changes in their environment and in their own current physiological state. Models can be constructed to reflect sequential decisions concerned simultaneously with foraging, reproduction, predator avoidance, and other activities. |
From inside the book
Results 1-5 of 53
... Approaches 233 8.4.1 Average - Rate Models 233 8.4.2 Mean - Variance Models 235 8.4.3 Life - History Models 238 8.4.4 ... Approach 247 9.1 Learning 247 9.2 Dynamic Behavioral Games 259 9.2.1 A Dynamic Game between Tephritid Flies 261 9.2 ...
... approach will clearly show that the modeling techniques we describe are well worth mastering . First , we be- lieve that dynamic optimization models are tremendously powerful and useful for understanding many aspects of animal behavior ...
... approach based on quantita- tive , mathematical optimization models have recently been recog- nized . In behavioral ecology , for example , the development of a class of models subsumed under the title " optimal foraging the- ory " has ...
... approach to the modeling of behavior and ontogeny . The present book is very much consistent with this line of thought : we agree that a state - space approach is essential . By adopting the relatively elementary methodology of discrete ...
... approach described in this book will help to nar- row the gap between what is realistic and what is operational in behavioral modeling . In a sense , the gap now seems largely tech- nological . Faster computers and better data sets will ...
Contents
Fundamentals | 9 |
Basic Probability | 11 |
12 Discrete Random Variables and Distributions | 15 |
13 Conditional Expectation | 18 |
Patch Selection | 41 |
22 Biological Examples | 42 |
23 The Simplest State Variable Model | 45 |
24 An Algorithm for the Dynamic Programming Equation | 52 |
51 Diel Vertical Migrations of Zooplankton | 152 |
52 Diel Migrations of Planktivores | 165 |
53 Predictions of Zooplankton Migrations | 178 |
Parental Allocation and Clutch Size in Birds | 182 |
61 A SingleYear Model of Parental Allocation and Clutch Size | 183 |
62 A MultiYear Model of Parental Allocation and Clutch Size | 192 |
63 Hypothesis Generation and Testing Dynamic Behavioral Models | 195 |
Movement of Spiders and Raptors | 198 |
25 Elaborations of the Simplest Model | 58 |
26 Discussion | 63 |
How to Write a Computer Program | 82 |
Applications | 105 |
The Hunting Behavior of Lions | 107 |
31 The Serengeti Lion | 108 |
32 Some Possible Explanations of Lions Hunting Behavior | 109 |
33 A Dynamic Model | 113 |
34 Communal Sharing | 121 |
35 Discussion | 124 |
Reproduction in Insects | 126 |
42 A Model with Mature Eggs Only | 131 |
43 A Model with Mature Eggs and Oocytes | 142 |
44 Parasitism and Density Dependence | 143 |
45 Discussion | 148 |
Migrations of Aquatic Organisms | 149 |
71 Movement of OrbWeaving Spiders | 199 |
72 Population Consequences of Natal Dispersal | 204 |
Additional Topics | 213 |
Formulation and Solution of State Variable Models | 215 |
81 Identifying State Variables Constraints and Dynamics | 217 |
Fitness | 223 |
83 The Dynamic Programming Algorithm | 225 |
84 Alternative Modeling Approaches | 233 |
Some Extensions of the Dynamic Modeling Approach | 247 |
92 Dynamic Behavioral Games | 259 |
Epilogue Perspectives on Dynamic Modeling | 280 |
References | 289 |
303 | |
306 | |