Optimal control of spatial diseases spreading in networked reaction–diffusion systems

Physics Reports, Journal Year: 2025, Volume and Issue: 1111, P. 1 - 64

Published: Feb. 1, 2025

Language: Английский

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Vegetation pattern formation in Daisyworld model with greenhouse effect

Ecological Modelling, Journal Year: 2025, Volume and Issue: 502, P. 111034 - 111034

Published: Feb. 8, 2025

Language: Английский

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Multimodal learning for vegetation patterns classification in global arid and semi-arid regions

Chaos Solitons & Fractals, Journal Year: 2025, Volume and Issue: 194, P. 116187 - 116187

Published: March 4, 2025

Language: Английский

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Vegetation pattern formation and transition in dryland ecosystems with finite soil resources and inertia

Physica D Nonlinear Phenomena, Journal Year: 2025, Volume and Issue: unknown, P. 134601 - 134601

Published: March 1, 2025

Language: Английский

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Prediction of vegetation pattern evolution in arid ecosystems using 3D-Var data assimilation

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2025, Volume and Issue: 35(5)

Published: May 1, 2025

In arid regions, ecosystems are fragile, and vegetation exhibits high sensitivity to changes in climatic conditions. Vegetation patterns–non-uniform macroscopic structures formed by through temporal spatial self-organization–serve as critical indicators of an ecosystem’s adaptive capacity, post-disturbance resilience, early warning signals ecosystem degradation. Investigating the formation mechanisms patterns using reaction–diffusion (RD) models represents a vital approach deciphering evolution dynamics, with significant implications for protecting ecosystems. However, heterogeneous steady-state solutions RD systems, such Turing patterns, often reside multistable regions. This implies that minute variations initial conditions may lead markedly divergent outcomes. When distribution data imprecise, predictions trends distributions given position become highly sensitive errors—a case where “minor discrepancies input yield vastly results.” study applies three-dimensional variational assimilation method model coupling vegetation, soil moisture, surface water dynamics The results demonstrate incorporating modest amount observational can substantially enhance model’s predictive accuracy trajectories.

Language: Английский

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Optimizing infectious disease control: A study on local and boundary control strategies in spatial domains

Physica A Statistical Mechanics and its Applications, Journal Year: 2024, Volume and Issue: unknown, P. 130302 - 130302

Published: Dec. 1, 2024

Language: Английский

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