In this paper we study a generalized Klausmeier model replacing the integer derivative by a local fractional derivative. This derivative enables us to consider a wide range of systems with already well-known derivatives. We analyze the stability of this new model as well as the homotopic perturbation method. Finally, an inverse problem associated with a real data set is solved.
Citation: Martha Paola Cruz de la Cruz, Daniel Alfonso Santiesteban, Luis Miguel Martín Álvarez, Ricardo Abreu Blaya, Hernández-Gómez Juan Carlos. On a generalized Klausmeier model[J]. Mathematical Biosciences and Engineering, 2023, 20(9): 16447-16470. doi: 10.3934/mbe.2023734
In this paper we study a generalized Klausmeier model replacing the integer derivative by a local fractional derivative. This derivative enables us to consider a wide range of systems with already well-known derivatives. We analyze the stability of this new model as well as the homotopic perturbation method. Finally, an inverse problem associated with a real data set is solved.
[1] | C. A. Klausmeier, Regular and irregular patterns in semiarid vegetation, Science, 284 (1999), 1826–1828. |
[2] | J. A. Sherratt, Pattern solutions of the Klausmeier Model for banded vegetation in semi-arid environments I, Nonlinearity, 23 (2010), 2657–2675. https://doi.org/10.1088/0951-7715/23/10/016 doi: 10.1088/0951-7715/23/10/016 |
[3] | J. A. Sherratt, Pattern solutions of the Klausmeier model for banded vegetation in semi-arid environments II: patterns with the largest possible propagation speeds, Proceed. Royal Soc. A Math. Phys. Eng. Sci., 467 (2011), 3272–3294. https://doi.org/10.1098/rspa.2011.0194 doi: 10.1098/rspa.2011.0194 |
[4] | J. A. Sherratt, Pattern solutions of the Klausmeier model for banded vegetation in semi-arid environments III: The transition between homoclinic solutions, Phys. D Nonlinear Phenom., 242 (2013), 30–41. https://doi.org/10.1016/j.physd.2012.08.014 doi: 10.1016/j.physd.2012.08.014 |
[5] | G. Consolo, C. Currò, G. Valenti, Turing vegetation patterns in a generalized hyperbolic Klausmeier model, Math. Methods Appl. Sci., 43 (2020), 10474–10489. https://doi.org/10.1002/mma.6518 doi: 10.1002/mma.6518 |
[6] | S. Stelt, A. Doelman, G. Hek, Rademacher, J. D. M. Rise, Fall of Periodic Patterns for a Generalized Klausmeier–Gray–Scott Model, J. Nonlinear Sci., 23 (2013), 39–95. https://doi.org/10.1007/s00332-012-9139-0 doi: 10.1007/s00332-012-9139-0 |
[7] | R. Abreu, A. Fleitas, J. Núñez, R. Reyes, J. M. Rodríguez, J. M. Sigarreta, On the conformable fractional logistic models. Math. Methods in Appl. Sci., 43 (2020), 4156–4167. https://doi.org/10.1002/mma.6180 |
[8] | P. Bosch, J. F. Gómez-Aguilar, J. M. Rodríguez, J. M. Sigarreta, Analysis of dengue fever outbreak by generalized fractional derivative, Fractals, 28 (2020). https://doi.org/10.1142/s0218348x20400381 |
[9] | A. Fleitas, J. F. Gómez-Aguilar, J. E. Nápoles, J. M. Rodríguez, J. M. Sigarreta, Analysis of the local Drude model involving the generalized fractional derivative, Optik, 193 (2019). https://doi.org/10.1016/j.ijleo.2019.163008 |
[10] | J. C. Hernández-Gómez, R. Reyes, J. M. Rodríguez, J. M. Sigarreta, Fractional model for the study of the tuberculosis in Mexico, Math. Methods Appl. Sci., 45 (2022). https://doi.org/10.1002/mma.8392 |
[11] | X. J. Yang, D. Baleanu, H. M. Srivastava, Local Fractional Integral Transforms and Their Applications, Academic Press is an imprint of Elsevier, (2016), ISBN: 978-0-12-804002-7. |
[12] | R. Abreu, J. M. Rodríguez, J. M. Sigarreta, On the generalized Fourier transform, Math. Methods Appl. Sci., (2023), 1–2. https://doi.org/10.1002/mma.9471 |
[13] | R. Khalil, M. Al Horani, A. Yousef, M. Sababheh, A new definition of fractional derivative, J. Comput. Appl. Math., 264 (2014). https://doi.org/10.1016/j.cam.2014.01.002 |
[14] | R. Almeida, M. Guzowska, T. Odzijewicz, A remark on local fractional calculus and ordinary derivatives, Open Math., 14 (2016). https://doi.org/10.1515/math-2016-0104 |
[15] | A. Atangana, E. F. Goufo Extension of matched asymptotic method to fractional boundary layers problems, Math. Probl. in Eng., 2014 (2014). https://doi.org/10.1155/2014/107535 |
[16] | P. M. Guzmán, G. Langton, L. M. Lugo, J. Medina, J. E. Nápoles, A new definition of a fractional derivative of local type, J. Math. Anal., 9 (2018). |
[17] | A. Fleitas, J. E. Nápoles, J. M. Rodríguez, J. M. Sigarreta, Note on the generalized conformable derivative. Revista de la Unión Matemática Argentina, 62 (2021). https://doi.org/10.33044/revuma.1930 |
[18] | P. Bosch, H. J. Carmenate García, J. M. Rodríguez, J. M. Sigarreta, On the Generalized Laplace Transform. Symmetry, 13 (2021), 669. https://doi.org/10.3390/sym13040669 |
[19] | J. A. Sherratt, Pattern solutions of the Klausmeier model for banded vegetation in semiarid environments IV: slowing moving patterns and their stability, SIAM J. Appl. Math., 73 (2013), 330–350. https://doi.org/10.1137/120862648 doi: 10.1137/120862648 |
[20] | J. A. Sherratt, An analysis of vegetation stripe formation in semi-arid landscapes, J. Math. Biol., 51 (2005), 183–197. |
[21] | J. A. Sherratt, History-dependent patterns of whole ecosystems, Ecolog. Complex., 14 (2013), 8–20. |
[22] | A. B. Rovinsky, M. Menzinger, Chemical Instability Induced by a Differential Flow, Phys. Rev. Letters, 69 (1992). |
[23] | H. Rezazadeh, H. Aminikhah, A. H. Refahi Sheikhani, Stability Analysis of Conformable Fractional Systems, Iranian J. Numer. Anal. Optimiz., 7 (2017), 13–32. https://doi.org/10.22067/ijnao.v7i1.46917 doi: 10.22067/ijnao.v7i1.46917 |
[24] | O. Jaïbi, A. Doelman, M. Chirilus-Bruckner, E. Meron, The existence of localized vegetation patterns in a systematically reduced model for dryland vegetation, Phys. D Nonlinear Phenom., 412 (2020). https://doi.org/10.1016/j.physd.2020.132637 |
[25] | Y. Maimaiti, W. Yang, J. Wu, Turing instability and coexistence in an extended Klausmeier model with nonlocal grazing, Nonlinear Anal. Real World Appl., 64 (2022). https://doi.org/10.1016/j.nonrwa.2021.103443 |
[26] | H. Malchow, S. V. Petrovskii, E. Venturino, Spatiotemporal patterns in Ecology and Epidemiology: Theory, models, and simulation, Math. Comput. Biol., Chapman and Hall/CRC: Boca Raton, FL, USA, 2008. |
[27] | L. Elsgoltz, Ecuaciones Diferenciales y Cálculo Variacional, Editorial Mir Moscú, 1969. |
[28] | L. C. Evans, Partial Differential Equations, Graduate Studies in Mathematics, 19, American Mathematical Society, Providence, Rhode Island, Second Edition, 2010. |
[29] | D. Zwillinger, Handbook of Differential Equations, 3rd Edition, Academic Press, 1997. |
[30] | S. J. Liao, The proposed homotopy analysis technique for the solution of nonlinear problems, PhD thesis, Shanghai Jiao Tong University, 1992. |
[31] | J. H. He, Homotopy perturbation technique, Comput. Methods Appl. Mechan. Eng., 178 (1999), 257–262. |
[32] | S. J. Liao, An approximate solution technique not depending on small parameters: a special example, Int. J. Non-Linear Mechan., 30 (1995), 371–380. |
[33] | S. J. Liao, Boundary element method for general nonlinear differential operators, Eng. Anal. Boundary Elements, 20 (1997), 91–99. |
[34] | G. L. Liu, New research directions in singular perturbation theory: Artificial parameter approach and inverse-perturbation technique, in Proceedings of the 7th Conference of modern Mathematics and Mechanics, Shanghai (September 1997), 47–53, 1997. |
[35] | J. H. He, Variational iteration method-a kind of nonlinear analytical technique: some examples, Int. J. Non-LinearMechan., 34 (1999), 699–708. |
[36] | N. H. Sweilam, M. M. Khader, Exact solutions of some coupled nonlinear partial differential equations using the homotopy perturbation method. Comput. Math. Appl., 58 (2009), 2134–2141. |
[37] | E. Süli, D. Mayers, An Introduction to Numerical Analysis, Cambridge University Press, 2003, ISBN: 0-521-00794-1. |
[38] | F. Liang, C. Liu, R. Carroll, Advanced Markov chain Monte Carlo methods: Learning from past samples, John Wiley & Sons, 2011. |
[39] | M. Plummer, JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling, in Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), 1–10, Viena, 2013. |
[40] | A. Gelman, J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, D. B. Rubin, Bayesian data analysis.CRC Press, 2013, ISBN: 9781439898208. |
[41] | F. J. Ariza Hernández, L. M. Martín Álvarez, M. P. Árciga Alejandre, J. Sánchez Ortiz, Bayesian inversion for a fractional Lotka-Volterra model: An application of Canadian lynx vs. snowshoe hares, Chaos Solit. Fract., (2021). https://doi.org/10.1016/j.chaos.2021.111278 |
[42] | R. Meyer, Deviance information criterion (DIC) Wiley StatsRef: Statistics Reference Online, Wiley Online Library, 2014. |
[43] | R. Bastiaansen, O. Jaïbi, V. Deblauwe, M. B. Eppinga, K. Siteur, E. Siero, et al., Multistability of model and real dryland ecosystems through spatial self-organization, Proceed. Nat. Acad. Sci., (2018). |
[44] | Food and Agriculture Organization of the United Nations, WAPOR: The FAO portal to monitor WAter Productivity through Open access of Remotely sensed derived data, WaPOR v2.1, November 29th, 2019. Available from: https://wapor.apps.fao.org/catalog/WaPOR_2/1/L1_GBWP_A |