Site percolation threshold of composite square lattices and its agroecology applications.

Autor:	Herrera DR; Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico., Velázquez-Castro J; Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico., Téllez AF; Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico., López-Olguín JF; Herbario y Jardín Botánico, Vicerrectoría de Investigación y Estudios de Posgrado, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico.; Centro de Agroecología, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico., Ramírez JE; Centro de Agroecología, Instituto de Ciencias, Benemérita Universidad Autónoma de Puebla, Apartado Postal 165, 72000 Puebla, Pue., Mexico.
Jazyk:	angličtina
Zdroj:	Physical review. E [Phys Rev E] 2024 Jan; Vol. 109 (1-1), pp. 014304.
DOI:	10.1103/PhysRevE.109.014304
Abstrakt:	We analyze the percolation threshold of square lattices comprising a combination of sites with regular and extended neighborhoods. We found that the percolation threshold of these composed systems smoothly decreases with the fraction of sites with extended neighbors. This behavior can be well-fitted by a Tsallis q-Exponential function. We found a relation between the fitting parameters and the differences in the gyration radius among neighborhoods. We also compared the percolation threshold with the critical susceptibility of nearest and next-to-nearest neighbor monoculture plantations vulnerable to the spread of phytopathogen. Notably, the critical susceptibility in monoculture plantations can be described as a linear combination of two composite systems. These results allow the refinement of mathematical models of phytopathogen propagation in agroecology. In turn, this improvement facilitates the implementation of more efficient computational simulations of agricultural epidemiology that are instrumental in testing and formulating control strategies.
Databáze:	MEDLINE
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