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Discrete mathematical models in population biology = ecological, epidemic, and evolutionary dynamics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Discrete mathematical models in population biology/ by Saber N. Elaydi, Jim M. Cushing.
其他題名:	ecological, epidemic, and evolutionary dynamics /
作者:	Elaydi, Saber.
其他作者:	Cushing, Jim M.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xiv, 481 p. :ill., digital ;24 cm.
內容註:	Preface -- 1.Scalar Population Models -- 2. Linear Structured Population Models -- 3. Linear and Nonlinear Systems -- 4. Infectious Disease Models I -- 5. Models with Multiple Attractors -- 6. Nonlinear Structured Population Models -- 7. Infectious Disease Models II -- 8. Evolutionary Models -- 9. Autonomous Models -- Bibliography -- Index.
Contained By:	Springer Nature eBook
標題:	Population biology - Mathematical models. -
電子資源:	https://doi.org/10.1007/978-3-031-64795-6
ISBN:	9783031647956

Discrete mathematical models in population biology = ecological, epidemic, and evolutionary dynamics /
Elaydi, Saber.

Discrete mathematical models in population biologyecological, epidemic, and evolutionary dynamics /[electronic resource] :by Saber N. Elaydi, Jim M. Cushing. - Cham :Springer Nature Switzerland :2025. - xiv, 481 p. :ill., digital ;24 cm. - Springer undergraduate texts in mathematics and technology,1867-5514. - Springer undergraduate texts in mathematics and technology..

Preface -- 1.Scalar Population Models -- 2. Linear Structured Population Models -- 3. Linear and Nonlinear Systems -- 4. Infectious Disease Models I -- 5. Models with Multiple Attractors -- 6. Nonlinear Structured Population Models -- 7. Infectious Disease Models II -- 8. Evolutionary Models -- 9. Autonomous Models -- Bibliography -- Index.

This text lays the foundation for understanding the beauty and power of discrete-time models. It covers rich mathematical modeling landscapes, each offering deep insights into the dynamics of biological systems. A harmonious balance is achieved between theoretical principles, mathematical rigor, and practical applications. Illustrative examples, numerical simulations, and empirical case studies are provided to enhance mastery of the subject and facilitate the translation of discrete-time mathematical biology into real-world challenges. Mainly geared to upper undergraduates, the text may also be used in graduate courses focusing on discrete-time modeling. Chapters 1-4 constitute the core of the text. Instructors will find the dependence chart quite useful when designing their particular course. This invaluable resource begins with an exploration of single-species models where frameworks for discrete-time modeling are established. Competition models and Predator-prey interactions are examined next followed by evolutionary models, structured population models, and models of infectious diseases. The consequences of periodic variations, seasonal changes, and cyclic environmental factors on population dynamics and ecological interactions are investigated within the realm of periodically forced biological models. This indispensable resource is structured to support educational settings: A first course in biomathematics, introducing students to the fundamental mathematical techniques essential for biological research. A modeling course with a concentration on developing and analyzing mathematical models that encapsulate biological phenomena. An advanced mathematical biology course that offers an in-depth exploration of complex models and sophisticated mathematical frameworks designed to tackle advanced problems in biology. With its clear exposition and methodical approach, this text educates and inspires students and professionals to apply mathematical biology to real-world situations. While minimal knowledge of calculus is required, the reader should have a solid mathematical background in linear algebra.

ISBN: 9783031647956

Standard No.: 10.1007/978-3-031-64795-6doiSubjects--Topical Terms:

545791
Population biology
--Mathematical models.

LC Class. No.: QH352 / .E43 2025

Dewey Class. No.: 577.88015118

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