Note: Intro -- Contents -- Foreword -- Acknowledgments -- 1. Foraging: An Overview -- Part I - Foraging and Information Processing -- 2. Models of Information Use -- 3. Neuroethology of Foraging -- 4. Cognition for Foraging -- Part II - Processing, Herbivory, and Storage -- 5. Food Acquisition, Processing, and Digestions -- 6. Herbivory -- 7. Energy Storage and Expenditure -- Part III - Modern Foraging Theory -- 8. Provisioning -- 9. Foraging in the Face of Danger -- 10. Foraging with Others: Games Social Foragers Play -- Part IV - Foraging Ecology -- 11. Foraging and Population Dynamics -- 12. Community Ecology -- 13. Foraging and the Ecology of Fear -- 14. On Foraging Theory, Humans, and the Conservation of Diversity: A Prospectus -- Contributors -- Literature Cited -- Index.

Note: Cover -- Half-title -- Title -- Copyright -- Dedication -- Contents -- Figures -- Preface -- 1 Understanding natural selection -- 1.1 Natural selection -- 1.1.1 Historical perspective -- 1.1.2 As Darwin saw it -- 1.1.3 The Modern Synthesis -- 1.2 Genetical approaches to natural selection -- 1.3 Natural selection as an evolutionary game -- 1.3.1 Game theory and evolution -- 1.3.2 Games Nature plays -- 1.3.3 ESS concept -- 1.3.4 Scope of evolutionary game theory -- 1.4 Road map -- 1.4.1 The simplest problem -- 1.4.2 Vector strategies -- 1.4.3 Evolving systems with resources -- 1.4.4 Multiple G-functions -- 1.4.5 Frequency dynamics -- 1.4.6 Multistage systems -- 1.4.7 Non-equilibrium dynamics -- 2 Underlying mathematics and philosophy -- 2.1 Scalars, vectors, and matrices -- 2.1.1 Elementary operations -- 2.1.1.1 Addition -- 2.1.1.2 Multiplication -- 2.1.1.3 Division -- 2.2 Dynamical systems -- 2.2.1 Difference equations -- 2.2.2 Differential equations -- 2.3 Biological population models -- 2.3.1 A special class of dynamical systems -- 2.3.2 The fitness concept with scalar Fi -- 2.3.3 Continuous versus discrete modeling with scalar fitness -- 2.4 Examples of population models -- 2.4.1 Single-species logistic model -- 2.4.2 Lotka-Volterra models for many species of individuals -- 2.4.3 Leslie model of one prey and one predator -- 2.4.4 Many prey and many predators model -- 2.4.5 Identifying strategies in the Lotka-Volterra model -- 2.4.6 Consumer-resource models -- 2.4.7 Multistage models -- 2.5 Classical stability concepts -- 2.5.1 Equilibrium solutions -- 2.5.2 Asymptotic stability -- 2.5.3 Linearization -- 2.5.4 Equilibrium point stability for linear difference equations -- 2.5.5 Equilibrium point stability for linear differential equations -- 2.5.6 Other situations -- 2.5.7 Non-equilibrium dynamics -- 3 The Darwinian game -- 3.1 Classical games. , 3.1.1 The optimization problem -- 3.1.2 Matrix games -- 3.1.3 Solution concepts: max-min, Nash equilibrium, etc. -- 3.1.4 Continuous games -- 3.2 Evolutionary games -- 3.2.1 Collapsing a population's fitness functions into a single G-function -- 3.2.2 Bauplans, G-functions, and taxonomic hierarchies -- 3.3 Evolution by natural selection -- 3.3.1 Tautology and teleology in Darwinian evolution -- 3.3.2 Darwin's postulates in evolutionary game theory -- 3.3.3 Heritable variation and fitness -- 4 G -functions for the Darwinian game -- 4.1 How to create a G-function -- 4.2 Types of G-functions -- 4.3 G-functions with scalar strategies -- 4.4 G-functions with vector strategies -- 4.5 G-functions with resources -- 4.6 Multiple G-functions -- 4.7 G-functions in terms of population frequency -- 4.8 Multistage G-functions -- 4.9 Non-equilibrium dynamics -- 5 Darwinian dynamics -- 5.1 Strategy dynamics and the adaptive landscape -- 5.2 The source of new strategies: heritable variation and mutation -- 5.3 Ecological time and evolutionary time -- 5.4 G-functions with scalar strategies -- 5.4.1 Mean strategy dynamics -- 5.4.1.1 Large difference in time scales -- 5.4.1.2 Small difference in time scales -- 5.5 G-functions with vector strategies -- 5.6 G-functions with resources -- 5.8 G-functions in terms of population frequency -- 5.9 Multistage G-functions -- 5.10 Non-equilibrium Darwinian dynamics -- 5.11 Stability conditions for Darwinian dynamics -- 5.12 Variance dynamics -- 6 Evolutionarily stable strategies -- 6.1 Evolution of evolutionary stability -- 6.2 G-functions with scalar strategies -- 6.2.1 Population dynamics -- 6.2.2 Ecological stability -- 6.2.3 Evolutionary stability -- 6.2.4 Convergent stability -- 6.2.5 Using G-functions with scalar strategies -- 6.3 G-functions with vector strategies -- 6.3.1 Using G-functions with vector strategies. , 6.4 G-functions with resources -- 6.4.1 Using G-functions with resources -- 6.5 Multiple G-functions -- 6.5.1 Using multiple G-functions -- 6.6 G-functions in terms of population frequency -- 6.6.1 Using G-functions in terms of population frequency -- 6.7 Multistage G-functions -- 6.7.1 Using multistage G-functions -- 6.8 Non-equilibrium Darwinian dynamics -- 6.8.1 Using G-functions with non-equilibrium dynamics -- 7 The ESS maximum principle -- 7.1 Maximum principle for G-functions with scalar strategies -- 7.2 Maximum principle for G-functions with vector strategies -- 7.3 Maximum principle for G-functions with resources -- 7.4 Maximum principle for multiple G-functions -- 7.5 Maximum principle for G-functions in terms of population frequency -- 7.6 Maximum principle for multistage G-functions -- 7.7 Maximum principle for non-equilibrium dynamics -- 8 Speciation and extinction -- 8.1 Species concepts -- 8.2 Strategy species concept -- 8.2.1 Species archetypes -- 8.2.2 Definition of a species -- 8.3 Variance dynamics -- 8.3.1 Strategies over a fixed interval -- 8.3.2 Clump of strategies following a mean -- 8.4 Mechanisms of speciation -- 8.4.1 Sympatric speciation at an evolutionarily stable minimum -- 8.4.2 Stable maxima and allopatric speciation -- 8.4.3 Adaptive radiation -- 8.5 Predator-prey coevolution and community evolution -- 8.6 Wright's shifting balance theory and frequency-dependent selection -- 8.7 Microevolution and macroevolution -- 8.8 Incumbent replacement -- 8.9 Procession of life -- 9 Matrix games -- 9.1 A maximum principle for the matrix game -- 9.1.1 Frequency formulation -- 9.1.2 Strategies -- 9.1.3 Payoff function -- 9.1.4 Frequency dynamics -- 9.1.5 Matrix-ESS -- 9.1.6 Maynard Smith's original ESS definition -- 9.2 The 2 × 2 bi-linear game -- 9.2.1 Pure strategies -- 9.2.1.1 Coalition of one -- 9.2.1.2 Coalition of two. , 9.2.2 Mixed strategies -- 9.2.2.1 Coalition of one -- 9.2.3 Evolution of cooperation -- 9.3 Non-linear matrix games -- 9.3.1 Sex ratio game -- 9.3.1.1 The politically correct solution -- 9.3.1.2 Other possible solutions -- 9.3.2 Kin selection -- 10 Evolutionary ecology -- 10.1 Habitat selection -- 10.1.1 Ideal free distribution -- 10.2 Consumer-resource games -- 10.2.1 Competition between plants -- 10.2.2 Carcinogenesis -- 10.2.2.1 Conditions promoting carcinogenesis -- 10.2.2.2 A route to carcinogenesis -- 10.3 Plant ecology -- 10.3.1 Flowering time for annual plants -- 10.3.2 Root competition -- 10.4 Foraging games -- 10.4.1 Gerbil-owl fear game -- 10.4.2 Patch-use model of fierce predators seeking wary prey -- 10.4.2.1 Prey with imperfect information -- 10.4.2.2 Predator's response to prey with imperfect information -- 11 Managing evolving systems -- 11.1 Evolutionary response to harvesting -- 11.1.1 Necessary conditions for an ESS coalition of one -- 11.1.2 Necessary conditions for an ESS coalition of two -- 11.1.3 Specific examples -- 11.2 Resource management and conservation -- 11.2.1 Evolutionarily stable harvest strategies -- 11.2.1.1 Yield -- 11.2.1.2 Ecologically enlightened manager -- 11.2.1.3 Evolutionarily enlightened manager -- 11.2.2 Sustainable yield -- 11.2.3 The Schaeffer model in an evolutionary context -- 11.3 Chemotherapy-driven evolution -- References -- Index.