Toan D. Ha , Vyacheslav G. Tsybulin , Pavel A. Zelenchuk
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How to model the local interaction in the predator–prey system at slow diffusion in a heterogeneous environment?
We examine the nonlinear reaction–diffusion–advection equations to modeling of the predator–prey system under heterogeneous carrying capacity of the prey, and Holling type II functional response. When advection and diffusion fluxes are absent or small, we detect the discrepancy between the resource (carrying capacity) and species distributions. The large diffusion eliminates this effect. We propose a modification of the functional response coefficients to provide the correlation between species distribution and resource in both cases. The numerical simulation of several models both under small and moderate advection–diffusion fluxes is carried out.
期刊介绍:
Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales.
Ecological Complexity will publish research into the following areas:
• All aspects of biocomplexity in the environment and theoretical ecology
• Ecosystems and biospheres as complex adaptive systems
• Self-organization of spatially extended ecosystems
• Emergent properties and structures of complex ecosystems
• Ecological pattern formation in space and time
• The role of biophysical constraints and evolutionary attractors on species assemblages
• Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory
• Ecological topology and networks
• Studies towards an ecology of complex systems
• Complex systems approaches for the study of dynamic human-environment interactions
• Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change
• New tools and methods for studying ecological complexity