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Original Essays | April 11, 2014

Paul Laudiero: IMG Shit Rough Draft



I was sitting in a British and Irish romantic drama class my last semester in college when the idea for Shit Rough Drafts hit me. I was working... Continue »
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Cambridge Studies in Mathematical Biology #11: Modelling Biological Populations in Space and Time

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Cambridge Studies in Mathematical Biology #11: Modelling Biological Populations in Space and Time Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

This volume unifies population studies emphasising the interplay between modelling and experimentation.

Synopsis:

Emphasising the interplay between modelling and experimentation, this volume unifies population studies.

Synopsis:

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.

Product Details

ISBN:
9780521448550
Editor:
Renshaw, Eric
Publisher:
Cambridge University Press
Editor:
Renshaw, Eric
Author:
Segel, L. A.
Author:
Cannings, C.
Author:
Renshaw, Eric
Author:
Hoppensteadt, F. C.
Location:
Cambridge ;
Subject:
Biology
Subject:
Ecology
Subject:
Statistics
Subject:
Applied
Subject:
Population biology
Subject:
Spatial analysis (statistics)
Subject:
Population biology -- Statistical methods.
Subject:
Spatial analysis.
Subject:
Life Sciences - Ecology
Subject:
Environmental Studies-General
Subject:
Physics
Edition Number:
1st pbk ed.
Edition Description:
Trade paper
Series:
Cambridge studies in mathematical biology ;
Series Volume:
êarg 1, nr 211
Publication Date:
19930831
Binding:
TRADE PAPER
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
Yes
Pages:
424
Dimensions:
8.98x6.44x1.03 in. 1.39 lbs.

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Related Subjects


Science and Mathematics » Environmental Studies » General
Science and Mathematics » Mathematics » Applied

Cambridge Studies in Mathematical Biology #11: Modelling Biological Populations in Space and Time New Trade Paper
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Product details 424 pages Cambridge University Press - English 9780521448550 Reviews:
"Synopsis" by , This volume unifies population studies emphasising the interplay between modelling and experimentation.
"Synopsis" by , Emphasising the interplay between modelling and experimentation, this volume unifies population studies.
"Synopsis" by , 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.
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