Skip to main content
Log in

Predator–Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

We develop a novel eco-evolutionary modelling framework and demonstrate its efficacy by simulating the evolution of trait distributions in predator and prey populations. The eco-evolutionary modelling framework assumes that population traits have beta distributions and defines canonical equations for the dynamics of each total population size, the population’s average trait value, and a measure of the population’s trait differentiation. The trait differentiation is included in the modelling framework as a phenotype analogue, Q, of Wright’s fixation index \(F_\mathrm{ST}\), which is inversely related to the sum of the beta distribution shape parameters. The canonical equations may be used as templates to describe the evolution of population trait distributions in many ecosystems that are subject to stabilising selection. The solutions of the “population model” are compared with those of a “phenotype model” that simulates the growth of each phenotype as it interacts with every other phenotype under the same trade-offs. The models assume no sources of new phenotypic variance, such as mutation or gene flow. We examine a predator–prey system in which each population trades off growth against mortality: the prey optimises devoting resources to growth or defence against predation; and the predator trades off increasing its attack rate against increased mortality. Computer solutions with stabilising selection reveal very close agreement between the phenotype and population model results, which both predict that evolution operates to stabilise an initially oscillatory system. The population model reduces the number of equations required to simulate the eco-evolutionary system by several orders of magnitude, without losing verisimilitude for the overarching population properties. The population model also allows insights into the properties of the system that are not available from the equivalent phenotype model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data Availability Statement

Not applicable.

References

  • Abrams P (1991) The effects of interacting species on predator–prey coevolution. Theor Pop Biol 39:241–262

    Article  MATH  Google Scholar 

  • Balding D, Nichols R (1995) A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity. Genetica 96(1–2):3–12

    Article  Google Scholar 

  • Berardo C, Geritz S (2021) Coevolution of the reckless prey and the patient predator. J Theor Biol 530:1–12. https://doi.org/10.1016/j.jtbi.2021.110873

    Article  MathSciNet  MATH  Google Scholar 

  • Bulmer M (1971) The effect of selection on genetic variability. Am Naturalist 105(943):201–211

    Article  Google Scholar 

  • Coutinho R, Klauschies T, Gaedke U (2016) Bimodal trait distributions with large variances question the reliability of trait-based aggregate models. Theor Ecol 9:389–408

    Article  Google Scholar 

  • Cropp R, Norbury J (2015) Population interactions in ecology: a rule-based approach to modeling ecosystems in a mass-conserving framework. SIAM Rev 57(3):437–465

    Article  MathSciNet  MATH  Google Scholar 

  • Cropp R, Norbury J (2019) Obligate mutualism in a resource-based framework. SIAM Rev 61(2):596–622

    Article  MathSciNet  MATH  Google Scholar 

  • Cropp R, Norbury J (2021) The eco-evolutionary modelling of populations and their traits using a measure of trait differentiation. J Theor Biol 531(110893):1–24

    MathSciNet  MATH  Google Scholar 

  • Cropp R, Norbury J (2021) Modelling the evolution of naturally-bounded traits in a population. Theor Ecol 14(2):255–268

    Article  MATH  Google Scholar 

  • Fisher R (1930) The genetical theory of natural selection. The Clarendon Press, Oxford

    Book  MATH  Google Scholar 

  • Fleischer S, terHorst C, Li J (2018) Pick your trade-offs wisely: predator–prey eco-evo dynamics are qualitatively different under different trade-offs. J Theor Biol 456:201–212

    Article  MathSciNet  MATH  Google Scholar 

  • Geritz S, Kisdl E, Meszena G, Metz J (1998) Evolutionarily singular strategies and the adaptive growth and branching of the evolutionary tree. Evolu Ecol 12:35–57

    Article  Google Scholar 

  • Gibert J, Yeakel J (2019) Eco-evolutionary origins of diverse abundance, biomass, and trophic structures in food webs. Front Ecol Evol 7(15):1–11

    Google Scholar 

  • Gilpin W, Feldman M (2017) A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape. PLOS Comput Biol 13(7):e1005644

    Article  Google Scholar 

  • Govaert L, Fronhofer E, Lion S, Eizaguirre C, Bonte D, Egas M, Hendry A, De Brito Martins A, Melian C, Raeymaekers J, Ratikainen I, Saether B, Schweitzer J, Matthews B (2019) Eco-evolutionary feedbacks -theoretical models and perspectives. Funct Ecol 33:13–30

    Article  Google Scholar 

  • Holling C (1965) The functional response of predators to prey density and its role in mimicry and population regulation. Memoirs Entomol Soc Canada 45:3–60

    Google Scholar 

  • Kasada M, Yamamichi M, Yoshida T (2014) Form of an evolutionary tradeoff affects eco- evolutionary dynamics in a predator-prey system. PNAS 111(45):16035–16040

    Article  Google Scholar 

  • Khater M, Murariu D, Gras R (2016) Predation risk tradeoffs in prey: effects on energy and behaviour. Theor Ecol 9:251–268

    Article  Google Scholar 

  • Klauschies T, Coutinho R, Gaedke U (2018) A beta distribution-based moment closure enhances the reliability of trait-based aggregate models for natural populations and communities. Ecol Model 381:46–77

    Article  Google Scholar 

  • Klausmeier C, Kremer C, Koffel T (2020) Trait-based ecological and eco-evolutionary theory. Oxford University Press, chap 11:161–194

    Google Scholar 

  • Kolmogorov A (1936) Sulla teoria di volterra della lotka per l’esisttenza. Giornale dell Instituto Italiano Degli Attuari 7:74–80

    Google Scholar 

  • Kuehn C (2015) Moment closure - a brief review. Springer Complexity, chap 13:253–271

    Google Scholar 

  • Lande R (1976) Natural selection and random genetic drift in phenotype evolution. Evolution 30:314–334

    Article  Google Scholar 

  • Le Quere C, Harrison S, Prentice I, Buitenhuis E, Aumont O, Bopp L, Claustre H, Da Cunha L, Geider R, Giraud X, Klaas C, Kohfeld K, Legendre L, Manizza M, Platt T, Rivkin R, Sathyendranath S, Uitz J, Watson A, Wolf-Gladrow D (2005) Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models. Glob Change Biol 11(11):2016–2040

    Google Scholar 

  • Levin S, Udovic J (1977) A mathematical model of coevolving populations. Am Naturalist 111(980):657–675

    Article  Google Scholar 

  • Loreau M (2010) From populations to ecosystems, monographs in population biology, vol 46. Princeton University Press, Woodstock, Oxfordshire

    Book  Google Scholar 

  • McCauley D, Gellner G, Martinez N, Williams R, Sandin S, Micheli F, Mumby P, McCann K (2018) On the prevalence and dynamics of inverted trophic pyramids and otherwise top-heavy communities. Ecol Lett 21(3):439–454

    Article  Google Scholar 

  • Merico A, Bruggeman B, Wirtz K (2009) A trait-based approach for downscaling complexity in plankton ecosystem models. Ecol Model 220:3001–3010

    Article  Google Scholar 

  • Nei M (1973) Analysis of gene diversity in subdivided populations. PNAS 70(12):3321–3323

    Article  MATH  Google Scholar 

  • Norberg J, Swaney D, Dushoff J, Lin J, Casagrandi R, Levin S (2001) Phenotypic diversity and ecosystem functioning in changing environments: A theoretical framework. PNAS 98(20):11376–11381

    Article  Google Scholar 

  • Patel S, Buerger R (2019) Eco-evolutionary feedbacks between predator’s linkage disequilibrium and prey densities maintain diversity. Evolution 73(8):1533–1548

    Article  Google Scholar 

  • Patel S, Cortez M, Schreiber S (2018) Partitioning the effects of ecology, evolution, and eco-evolutionary feedbacks on community stability. Am Naturalist 191:381–394

    Article  Google Scholar 

  • Ronce O, Kirkpatrick M (2001) When sources become sinks: migrational meltdown in heterogeneous habitats. Evolution 55(8):1520–1531

    Article  Google Scholar 

  • Rosenzweig M, MacArthur R (1963) Graphical representation and stability conditions of predator-prey interaction. Am Naturalist 97:209–223

    Article  Google Scholar 

  • Schiesser W (2017) Numer Method Lines. Academic Press, Cambridge, Massachusetts

    Google Scholar 

  • Schoener T (2011) The newest synthesis: understanding the interplay of evolutionary and ecological dynamics. Science 331:426–429

    Article  Google Scholar 

  • Shnol E, Kondrashov A (1993) The effect of selection on the phenotypic variance. Genetics 134:995–996

    Article  Google Scholar 

  • Spitze K (1993) Population structure in Daphnia obtusa: quantitative genetic and allozymic variation. Genetics 135:367–374

    Article  Google Scholar 

  • Stark J, Iannelli P, Baigent S (2001) A nonlinear dynamics perspective of moment closure for stochastic processes. Nonlinear Anal: Theory Methods Appl 47(2):753–764

    Article  MathSciNet  MATH  Google Scholar 

  • Tien R, Ellner S (2012) Variable cost of prey defense and coevolution in predator-prey systems. Ecol Monographs 82(4):491–504

    Article  Google Scholar 

  • Van Kampen N (2007) Stochastic processes in physics and chemistry. Elsevier, Amsterdam

    MATH  Google Scholar 

  • van Velzen E, Gaedke U (2017) Disentangling eco-evolutionary dynamics of predator–prey coevolution: the case of antiphase cycles. Sci Rep 7(17125):1–11

    Google Scholar 

  • Vitousek P, Matson P (2012) Nutrient cycling and biogeochemistry. In: Levin S (ed) The Princeton guide to ecology. Princeton University Press, Princeton, pp 330–339

    Google Scholar 

  • Wilson D, Turelli M (1986) Stable underdominance and the evolutionary invasion of empty niches. Am Naturalist 127(6):835–850

    Article  Google Scholar 

  • Wright S (1950) Genetical structure of populations. Nature 166(4215):247–249

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank the reviewers for their careful reading and helpful comments which have significantly improved the original manuscript.

Author information

Authors and Affiliations

Authors

Contributions

The authors contributed equally.

Corresponding author

Correspondence to Roger Cropp.

Ethics declarations

Funding

Not applicable.

Conflicts of interests

All authors declare no conflict of interests.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Code availability

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1 (pdf 579 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cropp, R., Norbury, J. Predator–Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation. Bull Math Biol 84, 50 (2022). https://doi.org/10.1007/s11538-022-01004-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11538-022-01004-8

Keywords

Navigation