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Other titles in the Cambridge Studies in Mathematical Biology series:
Cambridge Studies in Mathematical Biology #11: Modelling Biological Populations in Space and Timeby Eric Renshaw
Synopses & Reviews
This volume develops a unifying approach to population studies that emphasizes the interplay between modeling and experimentation and that will provide mathematicians and biologists with a framework within which population dynamics can be fully explored and understood. A unique feature of the book is that deterministic and stochastic models are considered together; spatial effects are investigated by developing models that highlight the consequences that geographical restriction and species mobility may have on population development. Model-based simulations of processes are used to explore hitherto unforeseen features and thereby suggest further profitable lines of both experimentation and theoretical study. Most aspects of population dynamics are covered, including birth-death and logistic processes, competition and predator-prey relationships, chaos, reaction time delays, fluctuating environments, spatial systems, velocities of spread, epidemics, and spatial branching structures.
This volume unifies population studies emphasising the interplay between modelling and experimentation.
Emphasising the interplay between modelling and experimentation, this volume unifies population studies.
Emphasizing the interplay between modeling and experimentation, this volume aims to develop a unifying approach to population studies that will provide mathematicians and biologists with a framework within which population dynamics can be fully explored and understood.
Table of Contents
Preface; A list of symbols and notation; 1. Introductory remarks; 2. Simple birth-death processes; 3. General birth-death processes; 4. Time-lag models of population growth; 5. Competition processes; 6. Predator-prey processes; 7. Spatial predator-prey systems; 8. Fluctuating environments; 9. Spatial population dynamics; 10. Epidemic processes; 11. Linear and branching architectures; References; Author index; Subject index.
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