Prey-Predator Models Revisited: Uncertainty, Herd Instinct, Fear, Limited Food, Epidemics, Evolution, and Competition

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Interacting Complexities of Herds and Social Organizations

Part of the book series: Evolutionary Economics and Social Complexity Science ((EESCS,volume 19))

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Abstract

The classic model of the prey-predator system is described by Lotka-Volterra (L-V) equations. In the simplest case of two species, the prey population (e.g., rabbits) grows according to the birth-and-death process. The growth would be exponential, but there is a limitation: the predator (e.g., wolves) is eating rabbits. The population of wolves grows when they have food, but if there are few rabbits available, the wolves die. Denote the rabbit population size as x1 and the wolves as x2. The classical form of two-species Lotka-Volterra equations is as follows:

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References

  • Aubin JP, Cellina A (1984) Differential inclusions. Springer, Berlin. https://doi.org/10.1007/978-3-642-69512-4. ISBN: 978-3-642-69514-8

    Book  Google Scholar 

  • Ayala FJ, Gilpin ME, Ehrenfeld JG (1973) Competition between species: theoretical models and experimental tests. Theor Popul Biol Elsevier 4(3):331–356. https://doi.org/10.1016/0040-5809(73)90014-2

    Article  Google Scholar 

  • Bandini S, Manzoni S, Vizzan G (2009) Agent based Modeling and simulation: an informatics perspective. J Artif Soc Soc Simul 12(4):4. ISBN/ISSN 1460–7425

    Google Scholar 

  • Blanchard OJ, Katz LF (1992) Regional evolutions. Brook Pap Econ Act 1:1–37

    Article  Google Scholar 

  • Borshchev A, Filippov A (2004) AnyLogic – multi-paradigm simulation for business, engineering and research. Conference paper: The 6th IIE annual simulation solutions conference, March 15–16, Orlando, Florida, USA

    Google Scholar 

  • Coakley S, Gheorghe M, Holcombe M et al (2012) Exploitation of high performance computing in the FLAME agent-based simulation framework. Conference paper: IEEE 14th international conference on high performance computing and communications

    Google Scholar 

  • Cropp RA, Norbury J (2015) Population interactions in ecology: a rule-based approach to modeling ecosystems in a mass-conserving framework. SIAM REVIEW, Soc Ind Appl Math 57(3):437–465

    Google Scholar 

  • Gasull A, Kooij RE, Torregrosa J (1997) Limit cycles in the Holling-Tanner model. 41. ISBN/ISSN ISSN 0214-1493

    Article  Google Scholar 

  • Goldberg A, Robson D (1989) Smalltalk 80: the language. Addison-Wesley Professional. ISBN: 0-201-13688-0

    Google Scholar 

  • Gras R, Devaurs D, Wozniak A, Aspinall A (2009) An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model. Artif Life 15(4):423–463. https://doi.org/10.1162/artl.2009.Gras.012

    Article  Google Scholar 

  • Hoppensteadt F (2006) Predator-prey model. Scholarpedia 1(10):1563. http://www.scholarpedia.org/article/predator-prey_model

    Article  Google Scholar 

  • Klein J (2002) Breve: a 3D environment for the simulation of decentralized systems and artificial life. Conference paper: ICAL 2003 Proceedings of the eighth international conference on Artificial life, MIT Press, Cambridge, MA. ISBN/ISSN 0-262-69281-3

    Google Scholar 

  • Leslie PH, Gower JC (1958) The properties of a stochastic model for two competing species. Biometrica 45:316–330

    Article  Google Scholar 

  • Lotka AJ (1910) Contribution to the theory of periodic reaction. J Phys Chem 14(3):271–274

    Article  Google Scholar 

  • Luke S, Cioffi-Revilla C, Panait L, Sullivan K (2005) MASON: a multiagent simulation environment. Simulation 81(7):517–527

    Article  Google Scholar 

  • Mangioni SE (2012) A mechanism for pattern formation in dynamic populations by the effect of gregarious instinct. Phys A Stat Mech Appl 391:113–124

    Article  Google Scholar 

  • McDougall W (1926) The gregarious instinct. In: Introduction to social psychology (revised edition) series: chapter 12. John W Luce & Co

    Google Scholar 

  • Nowak AM (2006) Evolutionary dynamics. Harvard University Press, Cambridge, MA. ISBN: 9780674023383

    Book  Google Scholar 

  • Pontryagin LS, Boltyanskii VG, Gamkrelidze RV, Mishchenko EF (1962) The mathematical theory of optimal processes. Interscience, New York. ISBN: 2-88124-077-1

    Google Scholar 

  • Raczynski S (2002) Differential inclusion solver. Conference paper: International Conference on Grand Challenges for Modeling and Simulation, SCS, San Antonio

    Google Scholar 

  • Railsback SF, Lytinen SL, Jackson SK (2006) Agent-based simulation platforms: review. Simulation 82(9):609–623. https://doi.org/10.1177/0037549706073695

    Article  Google Scholar 

  • Takeuchi Y (1996) Global dynamical properties of Lotka-Volterra systems. World Scientific, Singapore

    Google Scholar 

  • Tanner JT (1975) The stability and intrinsic growth rates of prey and predator populations. Ecology 56(1):856–867. https://doi.org/10.2307/1936296

    Article  Google Scholar 

  • Tanuma H, Deguchi H, Shimizu T (2005) Agent-based simulation: from modeling methodologies to real-world applications, vol 1. Springer, Tokyo

    Google Scholar 

  • Tanuma H, Deguchi H, Shimizu T (2006) SOARS: Spot Oriented Agent Role Simulator – design and implementation. In: Agent-based simulation: from modeling methodologies to real-world applications. Springer, Tokyo, ISBN 9784431269250

    Google Scholar 

  • Tatai G, Gulyas L, Laufer L, Ivanyi M (2005) Artificial agents hel** to stock up on knowledge. Conference paper: 4th International Central and Eastern European Conference on Multi-Agent System, Budapest, Hungary, ISBN:3-540-29046-X 978-3-540-29046-9. https://doi.org/10.1007/11559221_3

    Book  Google Scholar 

  • Volterra V (1926) Variazioni e fluttuazioni del numero d’individui in specie animali conviventi. 2

    Google Scholar 

  • Volterra V (1931) Variations and fluctuations of the number of individuals in animal species living together. McGraw-Hill, New York

    Google Scholar 

  • Williams BA (1933) Gregariousness: a critical examination of the concept of the gregarious instinct. Australasian J Psychol Philos 11(1):50–68

    Article  Google Scholar 

  • Zhang Z, Yang H, Liu J (2012) Stability and Hopf bifurcation in a modified Holling-Tanner predator-prey system with multiple delays. Abstr Appl Anal, Euclid,https://doi.org/10.1155/2012/236484

    Google Scholar 

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Raczynski, S. (2020). Prey-Predator Models Revisited: Uncertainty, Herd Instinct, Fear, Limited Food, Epidemics, Evolution, and Competition. In: Interacting Complexities of Herds and Social Organizations. Evolutionary Economics and Social Complexity Science, vol 19. Springer, Singapore. https://doi.org/10.1007/978-981-13-9337-2_8

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  • DOI: https://doi.org/10.1007/978-981-13-9337-2_8

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