000164212 001__ 164212
000164212 005__ 20251127172931.0
000164212 0247_ $$2doi$$a10.1016/j.matcom.2025.11.009
000164212 0248_ $$2sideral$$a146412
000164212 037__ $$aART-2025-146412
000164212 041__ $$aeng
000164212 100__ $$aGupta, R.P.
000164212 245__ $$aNonlinear study of interacting population with increasing functional response: The significance of fear and movement
000164212 260__ $$c2025
000164212 5060_ $$aAccess copy available to the general public$$fUnrestricted
000164212 5203_ $$aThe study of hunting cooperation and fear effects is emerging as important ecological factors in population dynamics. These two features are analyzed independently in the literature by several researchers in detail. It is observed that both effects are important but poorly understood mechanisms that mediate the way predators organize ecosystems. The literature suggests that the outcomes of predator–prey interactions and their impact on ecosystems can be influenced together by these two factors. Therefore, we review the expanding body of research that integrates hunting cooperation and/or the effect of fear phenomena into the ecology of predator–prey. Our aim is to provide a framework for examining how the increasing type of functional response is affected by fear factor. The temporal dynamics, including the stability and bifurcation analysis of the system, is discussed briefly. Various parametric planes are analyzed to identify the regions of stability, instability, and bistability, along with some invariant manifolds in the phase plane that divide the basins of attraction. The temporal model is extended to the spatiotemporal framework to capture the movements of populations, and the conditions for Turing instability are derived, revealing spatial dynamics that produce various Turing patterns (spots, stripes, and mixed type) in response to the changes in fear effect and diffusion coefficients. Extensive numerical simulations are also performed to illustrate the dynamics of the model in temporal and spatio-temporal contexts.
000164212 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2021-122961NB-I00$$9info:eu-repo/grantAgreement/ES/DGA/E24-23R$$9info:eu-repo/grantAgreement/ES/DGA/LMP94_21$$9info:eu-repo/grantAgreement/ES/MCINN/PID2024-156032NB-I00
000164212 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000164212 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000164212 700__ $$aSingh, Harinand
000164212 700__ $$0(orcid)0000-0002-8089-343X$$aBarrio, Roberto$$uUniversidad de Zaragoza
000164212 700__ $$aKumar, Arun
000164212 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDpto. Matemática Aplicada$$cÁrea Matemática Aplicada
000164212 773__ $$g241 (2025), 783-804$$pMath. comput. simul.$$tMATHEMATICS AND COMPUTERS IN SIMULATION$$x0378-4754
000164212 8564_ $$s8497801$$uhttps://zaguan.unizar.es/record/164212/files/texto_completo.pdf$$yVersión publicada
000164212 8564_ $$s2068369$$uhttps://zaguan.unizar.es/record/164212/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000164212 909CO $$ooai:zaguan.unizar.es:164212$$particulos$$pdriver
000164212 951__ $$a2025-11-27-15:17:11
000164212 980__ $$aARTICLE