×

The impact of dormancy on evolutionary branching. (English) Zbl 07874519

Summary: In this paper, we investigate the consequences of dormancy in the ‘rare mutation’ and ‘large population’ regime of stochastic adaptive dynamics. Starting from an individual-based micro-model, we first derive the Polymorphic Evolution Sequence of the population, based on a previous work by M. Baar and A. Bovier [Electron. J. Probab. 23, Paper No. 72, 27 p. (2018; Zbl 1415.92120)]. After passing to a second ‘small mutations’ limit, we arrive at the Canonical Equation of Adaptive Dynamics, and state a corresponding criterion for evolutionary branching, extending a previous result of N. Champagnat and S. Méléard [Probab. Theory Relat. Fields 151, No. 1–2, 45–94 (2011; Zbl 1225.92040)]. The criterion allows a quantitative and qualitative analysis of the effects of dormancy in the well-known model of U. Dieckmann and M. Doebeli [Nature 400, No. 6748, 354–357 (1999 doi:10.1038/22521)] for sympatric speciation. In fact, quite an intuitive picture emerges: Dormancy enlarges the parameter range for evolutionary branching, increases the carrying capacity and niche width of the post-branching sub-populations, and, depending on the model parameters, can either increase or decrease the ‘speed of adaptation’ of populations. Finally, dormancy increases diversity by increasing the genetic distance between subpopulations.

MSC:

92-XX Biology and other natural sciences
60J85 Applications of branching processes
92D25 Population dynamics (general)

References:

[1] Athreya, K. B.; Ney, P. E., Branching Processes, 1972, Springer · Zbl 0259.60002
[2] Baar, M.; Bovier, A., The polymorphic evolution sequence for populations with phenotypic plasticity, Electron. J. Probab., 23, 1-27, 2018 · Zbl 1415.92120
[3] Baar, M.; Bovier, A.; Champagnat, N., From stochastic, individual-based models to the canonical equation of adaptive dynamics in one step, Ann. Appl. Probab., 27, 2, 1093-1170, 2017 · Zbl 1371.92094
[4] Baar, M.; Coquille, L.; Meyer, H., A stochastic model for immunotherapy of cancer, Sci. Rep., 6, 24169, 2016
[5] Blath, J.; Paul, T.; Tóbiás, A., A stochastic adaptive dynamics model for bacterial populations with mutation, dormancy and transfer ALEA, Lat. Am. J. Prob. Math. Stat., 20, 313-357, 2023 · Zbl 1509.60156
[6] Blath, J.; Tóbiás, A., Invasion and fixation of microbial dormancy traits under competitive pressure, Stoch. Proc. Appl., 130, 12, 7363-7395, 2020 · Zbl 1454.60134
[7] Champagnat, N.; Méléard, S., Polymorphic evolution sequence and evolutionary branching probab, Theory Relat. Fields, 151, 45-94, 2011 · Zbl 1225.92040
[8] Christiansen, F. B.; Loeschke, V., Evolution and intraspecific exploitative competition I. One-locus theory for small additive gene effects, Theo. Pop. Biol., 18, 297-313, 1980 · Zbl 0468.92013
[9] Collet, P.; Méléard, S.; Metz, J. A.J., A rigorous model study of the adaptive dynamics of mendelian diploids, J. Math. Biol., 67, 569-607, 2013 · Zbl 1300.92075
[10] Costa, M.; Hauzy, C.; Loeuille, N., Stochastic eco-evolutionary model of a predator-prey community, J. Math. Biol., 72, 573-622, 2016 · Zbl 1335.60159
[11] Coyne, J. A., Sympatric speciation, Curr. Biol., 17, 18, R787-R788, 2007
[12] Dieckmann, U.; Doebeli, M., On the origin of species by sympatric speciation, Nature, 400, 354-357, 1999
[13] Doebeli, M., (Adaptive Diversification. Adaptive Diversification, Princeton University Press Monographs in Population Biology, vol. 48, 2011)
[14] Doebeli, M.; Hauert, C.; Killingback, T., The evolutionary origin of cooperators and defectors, Science, 306, 859, 2004
[15] Ethier, S. N.; Kurtz, T. G., Markov Processes: Characterization and Convergence, 1986, Wiley: Wiley New York · Zbl 0592.60049
[16] Geritz, S. A.H.; Kisdi, É., Adaptive dynamics in diploid, sexual populations and the evolution of reproductive isolation, Proc. Biol. Sci., 267, 1453, 1671-1678, 2000
[17] Geritz, S. A.H.; Kisdi, É.; Meszéna, G.; Metz, J. A.J., Evolutionarily singular strategies and the adaptive growth of branching of the evolutionary tree, Evol. Ecol., 12, 35-57, 1998
[18] Jones, S. E.; Lennon, J. T., Dormancy contributes to the maintenance of microbial diversity, Proc. Natl. Acad. Sci. USA, 107, 5881-5886, 2010
[19] Lennon, J. T.; den Hollander, F.; Wilke Berenguer, M.; Blath, J., Principles of seed banks and the emgergence of complexity from dormancy, Nat. Commun, 12, 4807, 2021
[20] Metz, J. A.J.; Geritz, S. A.H.; Meszéna, G., Adaptive dynamics, a geometrical study of the consequences of nearly faithful reproduction, Stoch. Spatial Struct. Dynam. Syst., 45, 183-231, 1996 · Zbl 0972.92024
[21] Roughgarden, J., Evolution of niche width, Amer. Nat., 106, 952, 683-718, 1972
[22] Russo, M., A modified fluctuation-test framework characterizes the population dynamics and mutation rate of colorectal cancer persister cells, Nat. Genet., 54, 7, 1-9, 2022
[23] Sagitov, S.; Mehlig, B.; Jagers, P.; Vatutin, V., Evolutionary branching in a stochastic population model with discrete mutational steps, Theor. Pop. Bio., 83, 145-154, 2013 · Zbl 1275.92080
[24] Wakano, J. Y.; Iwasa, Y., Evolutionary branching in a finite population: deterministic branching vs. Stochastic branching, Genetics, 193, 229-241, 2013
[25] Waxmann, D.; Gavrilets, S., 20 Questions on adaptive dynamics, J. Evol. Bio., 18, 1139-1154, 2005
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.