Advances in Applied Probability

Limits of large metapopulations with patch-dependent extinction probabilities

R. McVinish and P. K. Pollett
Source: Adv. in Appl. Probab. Volume 42, Number 4 (2010), 1172-1186.

Abstract

We propose a model for the presence/absence of a population in a collection of habitat patches. This model assumes that colonisation and extinction of the patches occur as distinct phases. Importantly, the local extinction probabilities are allowed to vary between patches. This permits an investigation of the effect of habitat degradation on the persistence of the population. The limiting behaviour of the model is examined as the number of habitat patches increases to ∞. This is done in the case where the number of patches and the initial number of occupied patches increase at the same rate, and for the case where the initial number of occupied patches remains fixed.

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Primary Subjects: 60J20
Secondary Subjects: 60G55, 60F05
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Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aap/1293113156
Digital Object Identifier: doi:10.1239/aap/1293113156
Zentralblatt MATH identifier: 05848656
Mathematical Reviews number (MathSciNet): MR2796681

References

Abramowitz, M. and Stegun, I. A. (eds) (1965). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Dover Publications, New York.
Andersson, H. and Djehiche, B. (1998). A threshold limit theorem for the stochastic logistic epidemic. J. Appl. Prob. 35, 662–670.
Mathematical Reviews (MathSciNet): MR1659540
Zentralblatt MATH: 0921.92027
Digital Object Identifier: doi:10.1239/jap/1032265214
Project Euclid: euclid.jap/1032265214
Andersson, M. (1999). The asymptotic final size distribution of multitype chain-binomial epidemic processes. Adv. Appl. Prob. 31, 220–234.
Mathematical Reviews (MathSciNet): MR1699669
Zentralblatt MATH: 0926.92028
Digital Object Identifier: doi:10.1239/aap/1029954274
Project Euclid: euclid.aap/1029954274
Arrigoni, F. (2003). Deterministic approximation of a stochastic metapopulation model. Adv. Appl. Prob. 35, 691–720.
Mathematical Reviews (MathSciNet): MR1990610
Zentralblatt MATH: 1051.37043
Digital Object Identifier: doi:10.1239/aap/1059486824
Project Euclid: euclid.aap/1059486824
Buckley, F. M. and Pollett, P. K. (2010). Analytical methods for a stochastic mainland-island metapopulation model. Ecol. Modelling 221, 2526–2530.
Buckley, F. M. and Pollett, P. K. (2010). Limit theorems for discrete-time metapopulation models. Prob. Surveys 7, 53–83
Mathematical Reviews (MathSciNet): MR2645217
Zentralblatt MATH: 1194.60024
Digital Object Identifier: doi:10.1214/10-PS158
Project Euclid: euclid.ps/1273670365
Chan, C. K. (2009). Limiting conditional distribution of continuous time Markov chains and their application to metapopulation model. Masters Thesis, University of Queensland.
Cornell, S. J. and Ovaskainen, O. (2008). Exact asymptotic analysis for metapopulation dynamics on correlated dynamic landscapes. Theoret. Pop. Biol. 74, 209–225.
Daley, D. J. and Vere-Jones, D. (2008). An Introduction to the Theory of Point Processes, Vol. II, 2nd edn. Springer, New York.
Mathematical Reviews (MathSciNet): MR2371524
Zentralblatt MATH: 1159.60003
Daley, D. J., Gani, J. and Yakowitz, S. (2000). An epidemic with individual infectivities and susceptibilities. Math. Comput. Modelling 32, 155–167.
Mathematical Reviews (MathSciNet): MR1783546
Zentralblatt MATH: 0970.92020
Digital Object Identifier: doi:10.1016/S0895-7177(00)00126-6
Darling, R. W. R. and Norris, J. R. (2008). Differential equation approximations for Markov chains. Prob. Surveys 5, 37–79.
Mathematical Reviews (MathSciNet): MR2395153
Zentralblatt MATH: 1189.60152
Digital Object Identifier: doi:10.1214/07-PS121
Project Euclid: euclid.ps/1208958281
Gani, J. and Stals, L. (2004). The spread of a viral infection in a plantation. Environmetrics 15, 555–560.
Hanski, I. and Gilpin, M. E. (1997). Metapopulation Biology: Ecology, Genetics and Evolution. Academic Press, San Diego.
Zentralblatt MATH: 0913.92025
Hanski, I. and Ovaskainen, O. (2003). Metapopulation theory for fragmented landscapes. Theoret. Pop. Biol. 64, 119–127.
Hill, M. F. and Caswell, H. (2001). The effects of habitat destruction in finite landscapes: a chain-binomial metapopulation model. Oikos 93, 321–331.
Moilanen, A. (2004). SPOMSIM: software for stochastic patch occupancy models of metapopulation dynamics. Ecol. Modelling 179, 533–550.
Ovaskainen, O. (2001). The quasistationary distribution of the stochastic logistic model. J. Appl. Prob. 38, 898–907.
Mathematical Reviews (MathSciNet): MR1876547
Zentralblatt MATH: 0997.92036
Digital Object Identifier: doi:10.1239/jap/1011994180
Project Euclid: euclid.jap/1011994180
Ovaskainen, O. and Cornell, S. J. (2006). Asymptotically exact analysis of stochastic metapopulation dynamics with explicit spatial structure. Theoret. Pop. Biol. 69, 13–33.
Pellet, J. et al. (2007). An empirical evaluation of the area and isolation paradigm of metapopulation dynamics. Biol. Conservation 136, 483–495.
Preston, C. J. (1977). Spatial birth-and-death processes. Bull. Internat. Statist. Inst. 46, 371–391.
Mathematical Reviews (MathSciNet): MR474532
Ter Braak, C. J. F. and Etienne, R. S. (2003). Improved Bayesian analysis of metapopulation data with an application to a tree frog metapopulation. Ecology 84, 231–241.
Weiss, G. H. and Dishon, M. (1971). On the asymptotic behavior of the stochastic and deterministic models of an epidemic. Math. Biosci. 11, 261–265.
Mathematical Reviews (MathSciNet): MR295451
Zentralblatt MATH: 0224.92018
Digital Object Identifier: doi:10.1016/0025-5564(71)90087-3

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Advances in Applied Probability

Advances in Applied Probability