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Coexistence in a Two-Dimensional Lotka-Volterra Model

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Coexistence in a Two-Dimensional Lotka-Volterra Model
2.	Creator	Author's name, affiliation, country	J Theodore Cox; Syracuse University; United States
2.	Creator	Author's name, affiliation, country	Mathieu Merle; Université Paris VII (Diderot); France
2.	Creator	Author's name, affiliation, country	Edwin A Perkins; The University of British Columbia; Canada
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Lotka-Volterra; voter model; super-Brownian motion; spatial competition; coalescing random walk; coexistence; survival
3.	Subject	Subject classification	Primary 60K35, 60G57; Secondary 60J80
4.	Description	Abstract	We study the stochastic spatial model for competing species introduced by Neuhauser and Pacala in two spatial dimensions. In particular we confirm a conjecture of theirs by showing that there is coexistence of types when the competition parameters between types are equal and less than, and close to, the within types parameter. In fact coexistence is established on a thorn-shaped region in parameter space including the above piece of the diagonal. The result is delicate since coex- istence fails for the two-dimensional voter model which corresponds to the tip of the thorn. The proof uses a convergence theorem showing that a rescaled process converges to super-Brownian motion even when the parameters converge to those of the voter model at a very slow rate.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)	NSERC; NSF
7.	Date	(YYYY-MM-DD)	2010-08-09
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ejp.ejpecp.org/article/view/795
10.	Identifier	Digital Object Identifier	10.1214/EJP.v15-795
11.	Source	Journal/conference title; vol., no. (year)	Electronic Journal of Probability; Vol 15
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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