LEADER 04688nam 22006735 450 001 9910921015503321 005 20250918120711.0 010 $a9783031647956 010 $a3031647955 024 7 $a10.1007/978-3-031-64795-6 035 $a(CKB)37156282800041 035 $a(MiAaPQ)EBC31874094 035 $a(Au-PeEL)EBL31874094 035 $a(DE-He213)978-3-031-64795-6 035 $a(OCoLC)1484071260 035 $a(EXLCZ)9937156282800041 100 $a20250104d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDiscrete Mathematical Models in Population Biology $eEcological, Epidemic, and Evolutionary Dynamics /$fby Saber N. Elaydi, Jim M. Cushing 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (793 pages) 225 1 $aSpringer Undergraduate Texts in Mathematics and Technology,$x1867-5514 311 08$a9783031647949 311 08$a3031647947 327 $aPreface -- 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. 330 $aThis 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. 410 0$aSpringer Undergraduate Texts in Mathematics and Technology,$x1867-5514 606 $aBiomathematics 606 $aDifference equations 606 $aFunctional equations 606 $aMathematical and Computational Biology 606 $aDifference and Functional Equations 606 $aBiomatemātica$2thub 606 $aEquacions diferencials$2thub 606 $aEquacions funcionals$2thub 608 $aLlibres electrōnics$2thub 615 0$aBiomathematics. 615 0$aDifference equations. 615 0$aFunctional equations. 615 14$aMathematical and Computational Biology. 615 24$aDifference and Functional Equations. 615 7$aBiomatemātica 615 7$aEquacions diferencials 615 7$aEquacions funcionals 676 $a570.285 700 $aElaydi$b Saber N$0441707 701 $aCushing$b Jim M$01363391 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910921015503321 996 $aDiscrete Mathematical Models in Population Biology$94308412 997 $aUNINA