Analyzing vegetation pattern formation through a time-ordered fractional vegetation-sand model: A spatiotemporal dynamic approach DOI Open Access

Yimamu Maimaiti,

Zhiguo Lv, Ahmadjan Muhammadhaji

et al.

Networks and Heterogeneous Media, Journal Year: 2024, Volume and Issue: 19(3), P. 1286 - 1308

Published: Jan. 1, 2024

<p>This paper contributes to the field by developing a fractional-order vegetation-sand model that incorporates memory effects into traditional integer-order framework. By studying spatiotemporal dynamics of time-order fractional model, research aimed deepen our understanding complex interactions between vegetation and sand environments, providing insights for effective management conservation strategies in arid semi-arid regions. First, using linear stability theory differential equations, we conducted analysis spatially homogeneous provided parametric conditions instability. Next, performed utilizing Turing instability reveal diffusion order on distribution. Through numerical simulations, demonstrated evolution patterns under different environmental discussed implications these dynamic changes ecological restoration land management.</p>

Language: Английский

Nonlocal Models in Biology and Life Sciences: Sources, Developments, and Applications DOI Creative Commons
Swadesh Pal, Roderick Melnik

Physics of Life Reviews, Journal Year: 2025, Volume and Issue: 53, P. 24 - 75

Published: Feb. 27, 2025

Language: Английский

Citations

3

Analyzing vegetation pattern formation through a time-ordered fractional vegetation-sand model: A spatiotemporal dynamic approach DOI Open Access

Yimamu Maimaiti,

Zhiguo Lv, Ahmadjan Muhammadhaji

et al.

Networks and Heterogeneous Media, Journal Year: 2024, Volume and Issue: 19(3), P. 1286 - 1308

Published: Jan. 1, 2024

<p>This paper contributes to the field by developing a fractional-order vegetation-sand model that incorporates memory effects into traditional integer-order framework. By studying spatiotemporal dynamics of time-order fractional model, research aimed deepen our understanding complex interactions between vegetation and sand environments, providing insights for effective management conservation strategies in arid semi-arid regions. First, using linear stability theory differential equations, we conducted analysis spatially homogeneous provided parametric conditions instability. Next, performed utilizing Turing instability reveal diffusion order on distribution. Through numerical simulations, demonstrated evolution patterns under different environmental discussed implications these dynamic changes ecological restoration land management.</p>

Language: Английский

Citations

0