Population dynamics between a prey and a predator using spectral collocation method


Thirumalai S., SESHADRI R., YÜZBAŞI Ş.

INTERNATIONAL JOURNAL OF BIOMATHEMATICS, cilt.12, sa.5, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 5
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1142/s1793524519500499
  • Dergi Adı: INTERNATIONAL JOURNAL OF BIOMATHEMATICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: Prey-predator model, spectral collocation method, Chebyshev, Legendre and Jacobi polynomials, error estimation, DIFFERENTIAL QUADRATURE METHOD, NUMERICAL-SOLUTION, INTEGRODIFFERENTIAL EQUATIONS, MODEL, SCHEME, COMPETITION
  • Akdeniz Üniversitesi Adresli: Evet

Özet

The struggle for the existence of the biological species is a well-known Prey-Predator model study in the literature. In this study, we present an improved model of Jerri [J. Abdul, Introduction to Integral Equations with Applications, Vol. 10 (Wiley, New York, 1999)] by introducing the intra-species competition term between the same species in addition to the existing environmental changes and few other factors in the model. The demand from the existing (limited) resources and other requirements induces competition between the same species which may alter the survival tactics among themselves. This intra-species term provides strength to the model as it makes the model more realistic. The governing equations are a system of two nonlinear delay integro differential equations, which are solved using spectral collocation method. The role of intra-species coefficients denoting the logistic growth/decay of the two species and two other parameters affecting the population dynamics are analyzed with the three basis functions such as Chebyshev, Legendre and Jacobi polynomials. With the help of simple matrix analysis, the governing equations are converted into a system of nonlinear algebraic equations. Detailed error estimation is computed to compare our results with the existing methods. It is shown with the help of tables and figures that the present method is very efficient, has better accuracy and has least computational cost.