LEADER 05995nam 2200733Ia 450 001 9910784701603321 005 20230721031038.0 010 $a1-281-91178-X 010 $a9786611911782 010 $a981-277-158-1 035 $a(CKB)1000000000407517 035 $a(EBL)3050886 035 $a(OCoLC)922951739 035 $a(SSID)ssj0000127247 035 $a(PQKBManifestationID)11157322 035 $a(PQKBTitleCode)TC0000127247 035 $a(PQKBWorkID)10052084 035 $a(PQKB)10291039 035 $a(MiAaPQ)EBC3050886 035 $a(WSP)00006600 035 $a(Au-PeEL)EBL3050886 035 $a(CaPaEBR)ebr10255657 035 $a(CaONFJC)MIL191178 035 $a(EXLCZ)991000000000407517 100 $a20071016d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aComplex population dynamics$b[electronic resource] $enonlinear modeling in ecology, epidemiology, and genetics /$feditors, Bernd Blasius, Ju?rgen Kurths, Lewi Stone 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific$dc2007 215 $a1 online resource (257 p.) 225 1 $aWorld Scientific lecture notes in complex systems ;$vv. 7 300 $aDescription based upon print version of record. 311 $a981-277-157-3 320 $aIncludes bibliographical references and indexes. 327 $aContents; Preface; References; 1. Chaotic dynamics in food web systems; 1.1. Introduction; 1.2. Food web model formulation; 1.3. Detecting and quantifying chaotic dynamics in model food webs; 1.4. Dynamical patterns in food webs; 1.5. Chaos in real food webs and conclusion; References; 2. Generalized models ; 2.1. Introduction; 2.2. The basic idea of generalized models; 2.3. Example: A general predator-prey system; 2.4. Additional difficulties in complex models; 2.5. A generalized spatial model; 2.6. Local stability in small and intermediate models; 2.7. Some results on global dynamics 327 $a2.8. Numerical investigation of complex networks2.9. Discussion; References; 3. Dynamics of plant communities in drylands ; 3.1. Introduction; 3.2. Model for dryland water-vegetation systems; 3.3. Landscape states; 3.3.1. Mapping the landscape states along aridity gradients; 3.3.2. Coexistence of landscape states and state transitions; 3.3.3. Landscape states and aridity classes; 3.4. Plants as ecosystem engineers; 3.4.1. Facilitation vs. resilience; 3.4.2. Facilitation vs. competition; 3.5. Species richness: Pattern formation aspects; 3.5.1. The niche concept and the niche map 327 $a3.5.2. Landscape diversity3.5.3. Environmental changes; 3.6. Conclusion; Acknowledgments; References; 4. Metapopulation dynamics and the evolution of dispersal ; 4.1. Introduction; 4.1.1. What is a metapopulation?; 4.1.2. Levins metapopulation model; 4.2. Metapopulation ecology in different models; 4.2.1. Local dynamics; 4.2.2. Finite number of patches with the Ricker model; 4.2.3. Infinite number of patches; 4.2.3.1. Model presentation; 4.2.3.2. Resident equilibrium; 4.3. Adaptive dynamics; 4.3.1. Invasion fitness; 4.3.2. Pairwise Invasibility Plots (PIP); 4.4. Evolution of dispersal 327 $a4.4.1. Finite number of patches4.4.1.1. Fitness; 4.4.1.2. Fixed-point attractor; 4.4.1.3. Cyclic orbits; 4.4.2. Infinite number of patches; 4.4.2.1. Invasion fitness for the mutant; 4.4.2.2. Results; 4.4.3. Local growth with an Allee effect can result in evolu- tionary suicide; 4.4.3.1. Local population growth with an Allee effect; 4.4.3.2. Allee effect in the metapopulation model; 4.4.3.3. Bifurcation to evolutionary suicide; 4.4.3.4. Theory of evolutionary suicide; 4.5. Summary; References; 5. The scaling law of human travel - A message from; References 327 $a6. Multiplicative processes in social systems 6.1. Introduction; 6.2. Models for Zipf's law in language; 6.3. City sizes and the distribution of languages; 6.4. Family names; 6.4.1. The effects of mortality; 6.4.2. The distribution of given names; 6.5. Conclusion; Acknowledgments; References; 7. Criticality in epidemiology ; 7.1. Introduction; 7.2. Simple epidemic models showing criticality; 7.2.1. The SIS epidemic; 7.2.2. Solution of the SIS system shows criticality; 7.2.3. The spatial SIS epidemic; 7.2.4. Dynamics for the spatial mean; 7.2.5. Moment equations; 7.2.6. Mean field behavior 327 $a7.3. Accidental pathogens: the meningococcus 330 $a"This collection of review articles is devoted to the modeling of ecological, epidemiological and evolutionary systems. Theoretical mathematical models are perhaps one of the most powerful approaches available for increasing our understanding of the complex population dynamics in these natural systems. Exciting new techniques are currently being developed to meet this challenge, such as generalized or structural modeling, adaptive dynamics or multiplicative processes. Many of these new techniques stem from the field of nonlinear dynamics and chaos theory, where even the simplest mathematical rule can generate a rich variety of dynamical behaviors that bear a strong analogy to biological populations." 410 0$aWorld Scientific lecture notes in complex systems ;$vv. 7. 606 $aPopulation biology$xMathematical models 606 $aEcology$xMathematical models 606 $aEpidemiology$xMathematical models 606 $aGenetics$xMathematical models 615 0$aPopulation biology$xMathematical models. 615 0$aEcology$xMathematical models. 615 0$aEpidemiology$xMathematical models. 615 0$aGenetics$xMathematical models. 676 $a577.8/8 701 $aBlasius$b Bernd$01501194 701 $aKurths$b J$g(Ju?rgen),$f1953-$0517276 701 $aStone$b Lewi$01501195 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784701603321 996 $aComplex population dynamics$93728310 997 $aUNINA