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Linear and Weakly Nonlinear Stability Analyses of Turing Patterns for Diffusive Predator–Prey Systems in Freshwater Marsh Landscapes

Overview of attention for article published in Bulletin of Mathematical Biology, January 2017
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Article details
Title
Linear and Weakly Nonlinear Stability Analyses of Turing Patterns for Diffusive Predator–Prey Systems in Freshwater Marsh Landscapes
Published in
Bulletin of Mathematical Biology, January 2017
DOI 10.1007/s11538-017-0245-x
Pubmed ID
Authors

Li Zhang, Fan Zhang, Shigui Ruan

Abstract

We study a diffusive predator-prey model describing the interactions of small fishes and their resource base (small invertebrates) in the fluctuating freshwater marsh landscapes of the Florida Everglades. The spatial model is described by a reaction-diffusion system with Beddington-DeAngelis functional response. Uniform bound, local and global asymptotic stability of the steady state of the PDE model under the no-flux boundary conditions are discussed in details. Sufficient conditions on the Turing (diffusion-driven) instability which induces spatial patterns in the model are derived via linear analysis. Existence of one-dimensional and two-dimensional spatial Turing patterns, including rhombic and hexagonal patterns, are established by weakly nonlinear analyses. These results provide theoretical explanations and numerical simulations of spatial dynamical behaviors of the wetland ecosystems of the Florida Everglades.

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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Other 1 13%
Student > Doctoral Student 1 13%
Student > Master 1 13%
Student > Postgraduate 1 13%
Other 0 0%
Unknown 2 25%
Readers by discipline
Readers by discipline Count As %
Mathematics 2 25%
Chemical Engineering 1 13%
Environmental Science 1 13%
Biochemistry, Genetics and Molecular Biology 1 13%
Agricultural and Biological Sciences 1 13%
Other 0 0%
Unknown 2 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 March 2017.
All research outputs
#27,205,565
of 32,950,213 outputs
Outputs from Bulletin of Mathematical Biology
#1,219
of 1,478 outputs
Outputs of similar age
#358,178
of 455,391 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#12
of 17 outputs
Altmetric has tracked 32,950,213 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,478 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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