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Mathematical modeling in biological populations through branching processes. Application to salmonid populations

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Abstract

This work deals with mathematical modeling through branching processes. We consider sexually reproducing animal populations where, in each generation, the number of progenitor couples is determined in a non-predictable environment. By using a class of two-sex branching processes, we describe their demographic dynamics and provide several probabilistic and inferential contributions. They include results about the extinction of the population and the estimation of the offspring distribution and its main moments. We also present an application to salmonid populations.

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References

  • Alsmeyer G, Rösler U (2002) Asexual versus promiscuous bisexual Galton–Watson processes: the extinction probability ratio. Ann Appl Probab 12:125–142

    Article  MathSciNet  MATH  Google Scholar 

  • Bernardo JM, Smith AF (2000) Bayesian theory. Wiley, Chichester

    MATH  Google Scholar 

  • Bruss FT (1984) A note on extinction criteria for bisexual Galton–Watson processes. J Appl Probab 21:915–919

    Article  MathSciNet  MATH  Google Scholar 

  • Bruss FT, Slatvchova-Bojkova M (1999) On waiting times to populate and environment and a question of statistical inference. J Appl Probab 36:261–267

    Article  MathSciNet  MATH  Google Scholar 

  • Cornell EJ, Isham V (2004) Ultimate extinction of the promiscuous bisexual Galton–Watson metapopulation. Aust N Z J Stat 46:87–98

    Article  MathSciNet  MATH  Google Scholar 

  • Daley DJ (1968) Extinction conditions for certain bisexual Galton–Watson branching processes. Z Wahrscheinlichkeitsth 9:315–322

    Google Scholar 

  • Guttorp P (1991) Statistical inference for branching processes. Wiley, New York

    MATH  Google Scholar 

  • Haccou P, Jagers P, Vatutin V (2005) Branching processes: variation, growth, and extinction of populations. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Hille E, Philips RS (1957) Functional analysis and semi-groups. American Mathematical Society, Providence

    Google Scholar 

  • Hull DM (2003) A survey of the literature associated with the bisexual Galton–Watson branching process. Extracta Math 18:321–343

    MathSciNet  MATH  Google Scholar 

  • Jagers P (1975) Branching processes with biological applications. Wiley, London, New York

    MATH  Google Scholar 

  • Kendall AW Jr, Ahistrom EH, Moser HG (1984) Early life history stages of fishes and their characters. Am Soc Ichthyol Herpetol 1:11–12 (Special publication)

    Google Scholar 

  • Kimmel M, Axelrod DE (2002) Branching processes in biology. Springer, Berlin

    Book  MATH  Google Scholar 

  • Laufle JC, Pauley GB, Shepard MF (1986) Species profile: life histories and environmental requirements of coastal fishes and invertebrates (pacific Northwest). Coho salmon, US Fish and Wildlife Service. Biological Report. 82 (11.48), US Army Corps of Engineers, TR EL-82-4

  • Mendoza M, Gutiérrez-Peña E (2000) Bayesian conjugate analysis of the Galton–Watson process. Test 9:149–172

    Article  MathSciNet  MATH  Google Scholar 

  • Molina M (2010) Two-sex branching process literature. Lectures notes in statistics, vol 197. Springer, Berlin, Heidelberg, pp 279–293

    Google Scholar 

  • Molina M, Jacob C, Ramos A (2008) Bisexual branching processes with offspring and mating depending on the number of couples in the population. Test 17:265–281

    Article  MathSciNet  MATH  Google Scholar 

  • Molina M, Mota M, Ramos A (2002) Bisexual Galton–Watson branching process with population-size-dependeng mating. J Appl Probab 39:479–490

    Article  MathSciNet  MATH  Google Scholar 

  • Molina M, Mota M, Ramos A (2012) Two-sex branching models with random control on the number of progenitor couples. Methodol Comput Appl Probab 14:35–48

    Article  MathSciNet  MATH  Google Scholar 

  • Muller A, Stoyan D (2002) Comparison methods for stochastic model and risk. Wiley, Chichester

    Google Scholar 

  • R Development Core Team (2009). A language and environment for statistical computing, R Foundation for Statistical Computing (http://www.r-project.org)

  • Silverman BW (1986) Density estimation. Chapman and Hall, London, New York

    Book  MATH  Google Scholar 

  • Xing Y, Wang Y (2005) On the extinction of a class of population-size dependent bisexual branching processes. J Appl Probab 42:175–184

    Article  MathSciNet  MATH  Google Scholar 

  • Xing Y, Wang Y (2008) On the extinction of population-size dependent bisexual Galton–Watson processes. Acta Math Sci Ser B 42:210–216

    MathSciNet  Google Scholar 

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Acknowledgments

We would like to thank the referees and the associate editor for their constructive comments and interesting suggestions which have improved the paper. This research has been supported by the Gobierno de Extremadura (Grant GR10118), the Ministerio de Economía y Competitividad of Spain (Grant MTM2012-31235) and the FEDER.

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Correspondence to Manuel Molina.

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Molina, M., Mota, M. & Ramos, A. Mathematical modeling in biological populations through branching processes. Application to salmonid populations. J. Math. Biol. 70, 197–212 (2015). https://doi.org/10.1007/s00285-014-0762-2

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  • DOI: https://doi.org/10.1007/s00285-014-0762-2

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