Skip to main content

A Method to Derive Discrete Population Models

  • Conference paper
  • First Online:
Advances in Discrete Dynamical Systems, Difference Equations and Applications (ICDEA 2021)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 416))

Included in the following conference series:

Abstract

We propose a derivation method to obtain discrete multi-species population models based on the assumption that the population sizes at time \(t+1\) can be expressed as a multiple of the population sizes at time t. The multiplicative term is determined by placing the growth processes in the numerator and the decline processes in the denominator of the fitness of each population. Each resulting discrete model can be related to a continuous population model based on the same model assumptions using the relationship between discrete and continuous compounding in finance. We exploit this relationship to compare the stability for the continuous and the discrete models and argue that the corresponding continuous model analogues are more stable. We illustrate the derivation technique by providing several examples of discrete models of single and multi-species derived using this method and compare their stability properties with their continuous analogues.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abbas, S., Banerjee, M., Momani, S.: Dynamical analysis of fractional-order modified logistic model. Comput. Math. Appl. 62(3), 1098–1104 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Al-Basyouni, K.S., Khan, A.Q.: Discrete-time predator-prey model with bifurcations and chaos. Math. Probl. Eng. Art. ID 8845926, 14 (2020)

    Google Scholar 

  3. Allen, L.J.: An Introduction to Mathematical Biology, Pearson New Jersey (2007)

    Google Scholar 

  4. Area, I., Losada, J., Nieto, J.J.: A note on the fractional logistic equation. Phys. A 444, 182–187 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  5. Baigent, S.: Convexity of the carrying simplex for discrete-time planar competitive Kolmogorov systems. J. Differ. Equ. Appl. 22(5), 609–622 (2016)

    Google Scholar 

  6. Beddington, J.R.: On the dynamics of sei whales under exploitation. Rep. Int. Whal. Commun. 28, 169–172 (1978)

    Google Scholar 

  7. Beverton, R.J.H., Holt, S.J.: On the Dynamics of Exploited Fish Populations. Volume 19 of Fishery investigations (Great Britain, Ministry of Agriculture, Fisheries, and Food). H. M. Stationery Off., London (1957)

    Google Scholar 

  8. Bohner, M., Stević, S., Warth, H.: The Beverton–Holt difference equation. In: Discrete Dynamics and Difference Equations, (eds: S. Elaydi, H. Oliveira, J. Ferreira, J. Alves), pp. 189–193. World Scientific Inc. (2010)

    Google Scholar 

  9. Brännström, Å., Sumpter, D.J.: The role of competition and clustering in population dynamics. Proc. R. Soc. B 272(1576), 2065–2072 (2005)

    Article  Google Scholar 

  10. Brauer, F., Castillo-Chavez, C.: Mathematical Models in Population Biology and Epidemiology. Texts in Applied Mathematics, Springer, New York (2001)

    Book  MATH  Google Scholar 

  11. Brauer, F.: Multi-species interactions and coexistence. In: Differential Equations and Applications, vol. I, II (eds: A.R. Affabizadeh), pp. 91–96. Ohio University Press, Athens (1989)

    Google Scholar 

  12. Bravo de la Parra, R., Marvá, M., Sánchez, E., Sanz, L.: A discrete predator-prey ecoepidemic model. Math. Model. Nat. Phenom. 12(2), 116–132 (2017)

    Google Scholar 

  13. Chow, Y., Jang, S.R.J., Wang, H.M.: Cooperative hunting in a discrete predator-prey system II. J. Biol. Dyn. 13, 247–264 (2019)

    Google Scholar 

  14. Cushing, J.M., Levarge, S., Chitnis, N., Henson, S.M.: Some discrete competitive models and the competitive exclusion principle. J. Differ. Equ. Appl. 10(13–15), 1139–1151 (2004)

    Article  MATH  Google Scholar 

  15. De la Sen, M., Alonso-Quesada, S.: A control theory point of view on Beverton-Holt equation in population dynamics and some of its generalizations. Appl. Math. Comput. 199(2), 464–481 (2008)

    MathSciNet  MATH  Google Scholar 

  16. Din, Q.: Dynamics of a discrete Lotka-Volterra model. Adv. Differ. Equ. 95, 13 (2013)

    Google Scholar 

  17. Din, Q., Saleem, N., Shabbir, M.S.: A class of discrete predator-prey interaction with bifurcation analysis and chaos control. Math. Model. Nat. Phenom. 15, Paper No. 60, 27 (2020)

    Google Scholar 

  18. Edelstein-Keshet, L.: Mathematical models in biology. In: Classics in Applied Mathematics. Society for Industrial and Applied Mathematics SIAM, (1988)

    Google Scholar 

  19. El-Sayed, A.M.A., El-Mesiry, A.E.M., El-Saka, H.A.A.: On the fractional-order logistic equation. Appl. Math. Lett. 20(7), 817–823 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  20. Elaydi, S.N., Sacker, R.J.: Population models with Allee effect: a new model. J. Biol. Dyn. 4(4), 397–408 (2010)

    Google Scholar 

  21. Fisher, R.A.: The wave of advance of advantageous genes. Ann. Eugen. 7(4), 355–369 (1937)

    Article  MATH  Google Scholar 

  22. Ghadermazi, M.: Multi-species stochastic model and related effective site-dependent transition rates. Rep. Math. Phys. 87(1), 31–43 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  23. Goh, B.: Global stability in many-species systems. Am. Nat. 111(977), 135–143 (1977)

    Article  Google Scholar 

  24. Harry, A.J., Kent, C.M., Kocic, V.L.: Global behavior of solutions of a periodically forced Sigmoid Beverton-Holt model. J. Biol. Dyn. 6(2), 212–234 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  25. Huang, J., Liu, S., Ruan, S., Xiao, D.: Bifurcations in a discrete predator-prey model with nonmonotonic functional response. J. Math. Anal. Appl. 464(1), 201–230 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  26. Ikramov, K.D.: On the inertia law for normal matrices. Doklady Math. 64, 141–142 (2001)

    MATH  Google Scholar 

  27. Kang, Y.: Dynamics of a generalized Ricker-Beverton-Holt competition model subject to Allee effects. J. Differ. Equ. Appl. 22(5), 687–723 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  28. Kangalgil, F., Isik, S.: Controlling chaos and Neimark-Sacker bifurcation in a discrete-time predator-prey system. Hacet. J. Math. Stat. 49(5), 1761–1776 (2020)

    MathSciNet  MATH  Google Scholar 

  29. Kent, C.M., Kocic, V.L., Kostrov, Y.: Attenuance and resonance in a periodically forced sigmoid Beverton-Holt model. Int. J. Differ. Equ. 7(1), 35–60 (2012)

    MathSciNet  Google Scholar 

  30. Khader, M.M., Babatin, M.M.: On approximate solutions for fractional logistic differential equation. Math. Probl. Eng., Art. ID 391901, 7 (2013)

    Google Scholar 

  31. Khan, A.Q., Ahmad, I., Alayachi, H.S., Noorani, M.S.M., Khaliq, A.: Discrete-time predator-prey model with flip bifurcation and chaos control. Math. Biosci. Eng. 17(5), 5944–5960 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  32. Khan, A.Q., Kiyani, A.Z., Ahmad, I.: Bifurcations and hybrid control in a \(3\times 3\) discrete-time predator-prey model. Math. Biosci. Eng. 17(6), 6963–6992 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  33. Kolmogoroff, A., Petrovsky, I., Piscounoff, N.: Study of the diffusion equation with growth of the quantity of matter and its application to a biology problem. In: Dynamics of Curved Fronts, (ed: P. Pelcé) pp. 105–130. Academic Press, San Diego (1988)

    Google Scholar 

  34. Kulenović, M.R.S., Moranjkić, S., Nurkanović, Z.: Global dynamics and bifurcation of a perturbed sigmoid Beverton-Holt difference equation. Math. Methods Appl. Sci. 39(10), 2696–2715 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  35. Liu, X., Chu, Y., Liu, Y.: Bifurcation and chaos in a host-parasitoid model with a lower bound for the host. Adv. Differ. Equ. Paper No. 31, 15 (2018)

    Google Scholar 

  36. May, R.M., Leonard, W.J.: Nonlinear aspects of competition between three species. SIAM J. Appl. Math. 29(2), 243–253 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  37. Méndez, V., Assaf, M., Campos, D., Horsthemke, W.: Stochastic dynamics and logistic population growth. Phys. Rev. E (3) 91(6), 062133, 12 (2015)

    Google Scholar 

  38. Mohd, M.H.: Diversity in interaction strength promotes rich dynamical behaviours in a three-species ecological system. Appl. Math. Comput. 353, 243–253 (2019)

    MathSciNet  MATH  Google Scholar 

  39. Murray, J.: Mathematical Biology. Biomathematics. Springer, Berlin (1989)

    Google Scholar 

  40. Norden, R.H.: On the distribution of the time to extinction in the stochastic logistic population model. Adv. Appl. Probab. 14(4), 687–708 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  41. Pielou, E.C.: An Introduction to Mathematical Ecology. Wiley-Interscience, New york (1969)

    Google Scholar 

  42. Pielou, E.C.: Population and Community Ecology: Principles and Methods. Gordon and Breach, New york (1974)

    Google Scholar 

  43. Rescigno, A.: The struggle for life II. Three competitors. Bull. Math. Biophys. 30, 291–298 (1968)

    Article  Google Scholar 

  44. Royama, T.: Analytical Population Dynamics. Population and Community Biology Series, Springer, Netherlands (2012)

    Google Scholar 

  45. Shi, J., Shivaji, R.: Persistence in reaction diffusion models with weak Allee effect. J. Math. Biol. 52, 807–829 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  46. Skellam, J.G.: Random dispersal in theoretical populations. Biometrika 38(1–2), 196–218 (1951)

    Google Scholar 

  47. Streipert, S.H., Wolkowicz, G.S.K., Bohner, M.: Derivation and analysis of a discrete predator-prey model. Bull. Math. Biol. 84(7), 67 (2022)

    Article  MathSciNet  MATH  Google Scholar 

  48. Sun, J.W., Li, W.T., Wang, Z.C.: A nonlocal dispersal logistic equation with spatial degeneracy. Discret. Contin. Dyn. Syst. 35(7), 3217–3238 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  49. Tan, W.Y.: Logistic stochastic growth models and applications. In: Handbook of the Logistic Distribution. Volume 123 of Statist. Textbooks Monogr, pp. 397–425. Dekker, New York (1992)

    Google Scholar 

  50. Vargas-De-León, C.: Global stability for multi-species Lotka-Volterra cooperative systems: one hyper-connected mutualistic-species. Int. J. Biomath. 8(3), 1550039, 9 (2015)

    Google Scholar 

  51. Verhulst, P.F.: Notice sur la loi que la population suit dans son accroissement. Corr. Math. et Phy. 10, 113–121 (1838)

    Google Scholar 

  52. Streipert, S.H., Wolkowicz, G.S.K.: An augmented phase plane approach for discrete planar map: Introducing next-iterate operators. Math. Biosci. 355 (2023) https://doi.org/10.1016/j.mbs.2022.108924

  53. Xuemei, H.: The indirect method for stochastic logistic growth models. Commun. Statist. Theory Methods 46(3), 1506–1518 (2017)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The research of Gail S. K. Wolkowicz was partially supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant with accelerator supplement.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gail S. K. Wolkowicz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Streipert, S.H., Wolkowicz, G.S.K. (2023). A Method to Derive Discrete Population Models. In: Elaydi, S., Kulenović, M.R.S., Kalabušić, S. (eds) Advances in Discrete Dynamical Systems, Difference Equations and Applications. ICDEA 2021. Springer Proceedings in Mathematics & Statistics, vol 416. Springer, Cham. https://doi.org/10.1007/978-3-031-25225-9_22

Download citation

Publish with us

Policies and ethics