Abstract
Dispersal-induced growth (DIG) occurs when several populations with time-varying growth rates, each of which, when isolated, would become extinct, are able to persist and grow exponentially when dispersal among the populations is present. This work provides a mathematical exploration of this surprising phenomenon, in the context of a deterministic model with periodic variation of growth rates, and characterizes the factors which are important in generating the DIG effect, and the corresponding conditions on the parameters involved.
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References
Abbott KC (2011) A dispersal-induced paradox: synchrony and stability in stochastic metapopulations. Ecol Lett 14:1158–1169. https://doi.org/10.1111/j.1461-0248.2011.01670.x
Allen LJ, Bolker BM, Lou Y, Nevai AL (2007) Asymptotic profiles of the steady states for an SIS epidemic patch model. SIAM J Appl Math 67:1283–1309. https://doi.org/10.1137/060672522
Baguette M, Benton TG, Bullock JM (2012) Dispersal ecology and evolution. Oxford University Press, Oxford
Bansaye V, Lambert A (2013) New approaches to source-sink metapopulations decoupling demography and dispersal. Theor Popul Biol 88:31–46. https://doi.org/10.1016/j.tpb.2013.06.003
Bascompte J, Possingham H, Roughgarden J (2002) Patchy populations in stochastic environments: critical number of patches for persistence. Am Nat 159:128–137. https://doi.org/10.1086/324793
Benaïm M, Lobry C, Sari T, Strickler E (2021) Untangling the role of temporal and spatial variations in persistance of populations. arXiv preprint arXiv:2111.12633
Bhatia R (1997) Matrix analysis. Springer, New-York
Chen S, Shi J, Shuai Z, Wu Y (2022) Two novel proofs of spectral monotonicity of perturbed essentially nonnegative matrices with applications in population dynamics. SIAM J Appl Math 82:654–676. https://doi.org/10.1137/20M1345220
Cheong KH, Koh JM, Jones MC (2019) Paradoxical survival: examining the Parrondo effect across biology. BioEssays 41:1900027. https://doi.org/10.1002/bies.201900027
Chicone C (2006) Ordinary differential equations with applications. Springer, New-York
Cousens R, Dytham C, Law R (2008) Dispersal in plants: a population perspective. Oxford University Press, Oxford
Dias PC (1996) Sources and sinks in population biology. TREE 11:326–330. https://doi.org/10.1016/0169-5347(96)10037-9
Evans SN, Ralph PL, Schreiber SJ, Sen A (2013) Stochastic population growth in spatially heterogeneous environments. J Math Biol 66:423–476. https://doi.org/10.1007/s00285-012-0514-0
Guiver A, Packman D, Townley S (2017) A necessary condition for dispersal driven growth of populations with discrete patch dynamics. J Theor Biol 424:11–25. https://doi.org/10.1016/j.jtbi.2017.03.030
Hale JK (2009) Ordinary differential equations. Dover, New-York
Hanski IA, Gaggiotti OE (eds) (2004) Ecology, genetics and evolution of metapopulations. Elsevier Academic Press, San Diego
Hirsch MW, Smith H (2006) Monotone dynamical systems. In: Drábek P, Fonda A (eds) Handbook of differential equations: ordinary differential equations 2. Elsevier, Amsterdam
Hudson PJ, Cattadori IM (1999) The Moran effect: a cause of population synchrony. TREE 14:1–2. https://doi.org/10.1016/S0169-5347(98)01498-0
Jansen VA, Yoshimura J (1998) Populations can persist in an environment consisting of sink habitats only. PNAS 95:3696–3698. https://doi.org/10.1073/pnas.95.7.3696
Kawecki TJ (2004) Ecological and evolutionary consequences of source-sink population dynamics. In: Hanski IA, Gaggiotti OE (eds) Ecology, genetics and evolution of metapopulations. Elsevier Academic Press, San Diego, pp 387–414
Klausmeier CA (2008) Floquet theory: a useful tool for understanding nonequilibrium dynamics. Theor Ecol 1:153–161. https://doi.org/10.1007/s12080-008-0016-2
Kortessis N, Simon MW, Barfield M, Glass GE, Singer BH, Holt RD (2020) The interplay of movement and spatiotemporal variation in transmission degrades pandemic control. PNAS 117:30104–30106. https://doi.org/10.1073/pnas.2018286117
Krantz SG, Parks HR (2002) The implicit function theorem: history, theory, and applications. Springer, New-York
Lewis MA, Petrovskii SV, Potts JR (2016) The mathematics behind biological invasions. Springer, New-York
Liu S, Lou Y (2022) Classifying the level set of principal eigenvalue for time-periodic parabolic operators and applications. J Funct Anal 282:109338. https://doi.org/10.1016/j.jfa.2021.109338
Liu S, Lou Y, Peng R, Zhou M (2022) Monotonicity of the principal eigenvalue for a linear time-periodic parabolic operator. Proc Am Math Soc 147:5291–5302. https://doi.org/10.1090/proc/14653
Liu S, Lou Y, Song P (2022) A new monotonicity for principal eigenvalues with applications to time-periodic patch models. SIAM J Appl Math 82:576–601. https://doi.org/10.1137/20M1320973
Lobry C (2022) Entry-exit in the halo of a slow semi-stable curve. arXiv preprint arXiv:2203.10357
Matthews DP, Gonzalez A (2007) The inflationary effects of environmental fluctuations ensure the persistence of sink metapopulations. Ecology 88:2848–2856. https://doi.org/10.1890/06-1107.1
Metz JAJ, De Jong TJ, Klinkhamer PGL (1983) What are the advantages of dispersing; a paper by Kuno explained and extended. Oecologia 57:166–169. https://doi.org/10.1007/BF00379576
Morita S, Yoshimura J (2012) Analytical solution of metapopulation dynamics in a stochastic environment. Phys Rev E 86:045102. https://doi.org/10.1103/PhysRevE.86.045102
Perthame B (2007) Transport equations in biology. Birkhäuser Verlag, Basel
Pulliam HR (1988) Sources, sinks, and population regulation. Am Nat 132:652–661. https://doi.org/10.1086/284880
Roy M, Holt RD, Barfield M (2005) Temporal autocorrelation can enhance the persistence and abundance of metapopulations comprised of coupled sinks. Am Nat 166:246–261. https://doi.org/10.1086/431286
Rudin W (1976) Principles of mathematical analysis. McGraw-hill, New-York
Schreiber SJ (2010) Interactive effects of temporal correlations, spatial heterogeneity and dispersal on population persistence. Proc R Soc B Biol Sci 277:1907–1914. https://doi.org/10.1098/rspb.2009.2006
Su YH, Li WT, Lou Y, Yang FY (2020) The generalised principal eigenvalue of time-periodic nonlocal dispersal operators and applications. J Differ Equ 269:4960–4997. https://doi.org/10.1016/j.jde.2020.03.046
White ER, Hastings A (2020) Seasonality in ecology: progress and prospects in theory. Ecol Complex 44:100867. https://doi.org/10.1016/j.ecocom.2020.100867
Williams PD, Hastings A (2011) Paradoxical persistence through mixed-system dynamics: towards a unified perspective of reversal behaviours in evolutionary ecology. Proc R Soc B Biol Sci 278:1281–1290. https://doi.org/10.1098/rspb.2010.2074
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I am grateful to the referees for comments and references which have led to significant improvement of the manuscript.
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Katriel, G. Dispersal-induced growth in a time-periodic environment. J. Math. Biol. 85, 24 (2022). https://doi.org/10.1007/s00285-022-01791-7
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DOI: https://doi.org/10.1007/s00285-022-01791-7