The limiting behaviour of a mainland-island metapopulation
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Publication:455711
DOI10.1007/s00285-011-0429-1zbMath1252.92056OpenAlexW2066099630WikidataQ51563247 ScholiaQ51563247MaRDI QIDQ455711
Philip K. Pollett, Ross S. McVinish
Publication date: 22 October 2012
Published in: Journal of Mathematical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00285-011-0429-1
Central limit and other weak theorems (60F05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Ecology (92D40)
Related Items (7)
The limiting behaviour of a stochastic patch occupancy model ⋮ A spatially structured metapopulation model within a stochastic environment ⋮ Connecting deterministic and stochastic metapopulation models ⋮ Normal approximations for discrete-time occupancy processes ⋮ Chain Binomial Models and Binomial Autoregressive Processes ⋮ The Limiting Behaviour of Hanski's Incidence Function Metapopulation Model ⋮ A metapopulation model with Markovian landscape dynamics
Cites Work
- Asymptotic behavior of a metapopulation model
- Exact asymptotic analysis for metapopulation dynamics on correlated dynamic landscapes
- Analysis of a stochastic SIR epidemic on a random network incorporating household structure
- Differential equation approximations for Markov chains
- Limit theorems for discrete-time metapopulation models
- Asymptotic analysis of multiscale approximations to reaction networks
- Convergence of a structured metapopulation model to Levins's model
- Metapopulation theory for fragmented landscapes
- Asymptotically exact analysis of stochastic metapopulation dynamics with explicit spatial structure
- Limits of large metapopulations with patch-dependent extinction probabilities
- A threshold limit theorem for the stochastic logistic epidemic
- Foundations of Modern Probability
- Deterministic approximation of a stochastic metapopulation model
- The quasistationary distribution of the stochastic logistic model
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