| Title |
Analysis of a Prey–Predator Model with Non-local Interaction in the Prey Population
|
|---|---|
| Published in |
Bulletin of Mathematical Biology, March 2018
|
| DOI | 10.1007/s11538-018-0410-x |
| Pubmed ID | |
| Authors |
S. Pal, S. Ghorai, M. Banerjee |
| Abstract |
Non-local reaction-diffusion equation is an important area to study the dynamics of the individuals which compete for resources. In this paper, we describe a prey-dependent predator-prey model with Holling type II functional response with a generalist predator. In particular, we want to see the behavior of the system in the presence of non-local interaction. Introduction of non-local intraspecific competition in prey population leads to some new characteristics in comparison with the local model. Comparisons have been made between the local and non-local interactions of the system. The range of non-local interaction enlarges the parametric domain on which stationary patterns exist. The periodic oscillation for the local model in the Hopf domain can be stabilized by suitable limit of strong non-local interaction. An increase in the range of non-local interaction increases the Turing domain up to a certain level, and then, it decreases. Also, increasing the range of non-local interaction results in the overlap of nearby foraging areas and hence alters the size of the localized patches and formation of multiple stationary patches. Numerical simulations have been carried out to validate the analytical findings and to establish the existence of multiple stationary patterns, oscillatory solution, two-periodic solution and other spatiotemporal dynamics. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| India | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 25% |
| Student > Bachelor | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Professor | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 5 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 6 | 50% |
| Social Sciences | 1 | 8% |
| Unknown | 5 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 08 May 2018.
All research outputs
#13,241,759
of 23,047,237 outputs
Outputs from Bulletin of Mathematical Biology
#509
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Outputs of similar age
#165,085
of 332,343 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#13
of 30 outputs
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