Dynamic Modeling in Behavioral Ecology

by Marc Mangel, Colin Whitcomb Clark

Overview

This 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.


The authors show how to construct and use dynamic behavioral models. Part I covers the mathematical background and computer programming, and then uses a paradigm of foraging under risk of predation to exemplify the general modeling technique. Part II consists of five "applied" chapters illustrating the scope of the dynamic modeling approach. They treat hunting behavior in lions, reproduction in insects, migrations of aquatic organisms, clutch size and parental care in birds, and movement of spiders and raptors. Advanced topics, including the study of dynamic evolutionarily stable strategies, are discussed in Part III.

Product Details

ISBN-13:	9780691206967
Publisher:	Princeton University Press
Publication date:	12/31/2019
Series:	Monographs in Behavior and Ecology , #8
Sold by:	Barnes & Noble
Format:	eBook
Pages:	320
File size:	11 MB
Note:	This product may take a few minutes to download.

Table of Contents

	Preface and Acknowledgements	xi
	Introduction	3
1	Fundamentals	9
1	Basic Probability	11
1.1	Notation	11
1.2	Discrete Random Variables and Distributions	15
1.3	Conditional Expectation	18
	Appendices
1.1	The Poisson Process	19
1.2	Continuous Random Variables	25
1.3	Some Other Probability Distributions	29
1.4	Renewal Processes	37
2	Patch Selection	41
2.1	Patch Selection as a Paradigm	41
2.2	Biological Examples	42
2.3	The Simplest State Variable Model	45
2.4	An Algorithm for the Dynamic Programming Equation	52
2.5	Elaborations of the Simplest Model	58
2.6	Discussion	63
	Appendices
2.1	Further Elaborations of the Patch Selection Paradigm	63
2.1.1	Alternative Constraints	63
2.1.2	Variable Handling Times	64
2.1.3	A Diet Selection Model	65
2.1.4	A Model with "Fat Reserves" and "Gut Contents"	67
2.1.5	Sequential Coupling	69
2.1.6	Uncertain Final Time	71
2.2	Lifetime Fitness and Utility	73
2.3	Behavioral Observations and Forward Iteration	76
2.4	The Fitness of Suboptimal Strategies	79
	Addendum to Part I: How to Write a Computer Program	82
II	Applications	105
3	The Hunting Behavior of Lions	107
3.1	The Serengeti Lion	108
3.2	Some Possible Explanations of Lions' Hunting Behavior	109
3.3	A Dynamic Model	113
3.4	Communal Sharing	121
3.5	Discussion	124
4	Reproduction in Insects	126
4.1	Fitness from Egg Production and Experimental Background	126
4.2	A Model with Mature Eggs Only	131
4.3	A Model with Mature Eggs and Oocytes	142
4.4	Parasitism and Density Dependence	143
4.5	Discussion	148
5	Migrations of Aquatic Organisms	149
5.1	Diel Vertical Migrations of Zooplankton	152
5.1.1	Cladocerans	153
5.1.2	Copepods	162
5.2	Diel Migrations of Planktivores	165
5.2.1	A Model of Aquatic Predation	167
5.2.2	A Dynamic Model of Diel Migrations	171
5.3	Predictions of Zooplankton Migrations	178
6	Parental Allocation and Clutch Size in Birds	182
6.1	A Single-Year Model of Parental Allocation and Clutch Size	183
6.2	A Multi-Year Model of Parental Allocation and Clutch Size	192
6.3	Hypothesis Generation and Testing Dynamic Behavioral Models	195
7	Movement of Spiders and Raptors	198
7.1	Movement of Orb-Weaving Spiders	199
7.2	Population Consequences of Natal Dispersal	204
III	Additional Topics	213
8	Formulation and Solution of State Variable Models	215
8.1	Identifying State Variables, Constraints, and Dynamics	217
8.2	The Optimization Criterion: Fitness	223
8.3	The Dynamic Programming Algorithm	225
8.3.1	Computer Realization	228
8.3.2	Discretization and Interpolation	228
8.3.3	Sequential Coupling	231
8.3.4	Stationarity	232
8.4	Alternative Modeling 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	Optimal Control Theory	238
	Appendix
8.1	Fitness in Fluctuating Environments	240
9	Some Extensions of the Dynamic Modeling Approach	247
9.1	Learning	247
9.2	Dynamic Behavioral Games	259
9.2.1	A Dynamic Game between Tephritid Flies	261
9.2.2	A Game between Juvenile Coho Salmon	270
	Epilogue: Perspectives on Dynamic Modeling	280
	References	289
	Author Index	303
	Subject Index	306