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Self-perpetuating ecological–evolutionary dynamics in an agricultural host–parasite system

Abstract

Ecological and evolutionary processes may become intertwined when they operate on similar time scales. Here we show ecological–evolutionary dynamics between parasitoids and aphids containing heritable symbionts that confer resistance against parasitism. In a large-scale field experiment, we manipulated the aphid’s host plant to create ecological conditions that either favoured or disfavoured the parasitoid. The result was rapid evolutionary divergence of aphid resistance between treatment populations. Consistent with ecological–evolutionary dynamics, the resistant aphid populations then had reduced parasitism and increased population growth rates. We fit a model to quantify costs (reduced intrinsic rates of increase) and benefits of resistance. We also performed genetic assays on 5 years of field samples that showed persistent but highly variable frequencies of aphid clones containing protective symbionts; these patterns were consistent with simulations from the model. Our results show (1) rapid evolution that is intertwined with ecological dynamics and (2) variation in selection that prevents traits from becoming fixed, which together generate self-perpetuating ecological–evolutionary dynamics.

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Fig. 1: Field experiment showing eco–evo dynamics.
Fig. 2: Dynamics of aphid abundance and parasitism from 2011 to 2016.
Fig. 3: Field surveys of Hamiltonella and simulations of resistance.

Data availability

Experimental and observational data that support the findings of this study have been deposited in figshare.com at https://doi.org/10.6084/m9.figshare.11828865.v1.

Code availability

Codes used for analyses in this study have been deposited in figshare.com at https://doi.org/10.6084/m9.figshare.11828865.v1

References

  1. 1.

    Kingsolver, J. G. et al. The strength of phenotypic selection in natural populations. Am. Nat. 157, 245–261 (2001).

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Endler, J. A. Natural Selection in the Wild (Princeton Univ. Press, 1986).

  3. 3.

    Thompson, J. N. Rapid evolution as an ecological process. Trends Ecol. Evol. 13, 329–332 (1998).

    CAS  PubMed  Article  Google Scholar 

  4. 4.

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

    CAS  PubMed  Article  Google Scholar 

  5. 5.

    Pelletier, F., Garant, D. & Hendry, A. P. Eco-evolutionary dynamics. Phil. Trans. R. Soc. Lond. B 364, 1483–1489 (2009).

    CAS  Article  Google Scholar 

  6. 6.

    Hairston, N. G., Ellner, S. P., Geber, M. A., Yoshida, T. & Fox, J. A. Rapid evolution and the convergence of ecological and evolutionary time. Ecol. Lett. 8, 1114–1127 (2005).

    Article  Google Scholar 

  7. 7.

    Nosil, P. et al. Natural selection and the predictability of evolution in Timema stick insects. Science 359, 765–770 (2018).

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Auld, S. K. J. R. et al. Variation in costs of parasite resistance among natural host populations. J. Evol. Biol. 26, 2479–2486 (2013).

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Duffy, M. A. et al. Ecological context influences epidemic size and parasite-driven evolution. Science 335, 1636–1638 (2012).

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Travis, J. et al. in Eco-Evolutionary Dynamics Vol. 50 (eds Moya-Laraño, J. et al.) 1–40 (Academic Press, 2014).

  11. 11.

    Schaffner, L. R. et al. Consumer-resource dynamics is an eco-evolutionary process in a natural plankton community. Nat. Ecol. Evol. 3, 1351–1358 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  12. 12.

    De Meester, L. et al. Analysing eco-evolutionary dynamics: the challenging complexity of the real world. Funct. Ecol. 33, 43–59 (2019).

    Article  Google Scholar 

  13. 13.

    Yoshida, T., Jones, L. E., Ellner, S. P., Fussmann, G. F. & Hairston, N. G. Rapid evolution drives ecological dynamics in a predator–prey system. Nature 424, 303–306 (2003).

    CAS  PubMed  Article  Google Scholar 

  14. 14.

    Papkou, A. et al. The genomic basis of Red Queen dynamics during rapid reciprocal host–pathogen coevolution. Proc. Natl Acad. Sci. USA 116, 923–928 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Saccheri, I. & Hanski, I. Natural selection and population dynamics. Trends Ecol. Evol. 21, 341–347 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Govaert, L. et al. Eco-evolutionary feedbacks—theoretical models and perspectives. Funct. Ecol. 33, 13–30 (2019).

    Article  Google Scholar 

  17. 17.

    Siepielski, A. M., DiBattista, J. D. & Carlson, S. M. It’s about time: the temporal dynamics of phenotypic selection in the wild. Ecol. Lett. 12, 1261–1276 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Carroll, S. P., Hendry, A. P., Reznick, D. N. & Fox, C. W. Evolution on ecological time-scales. Funct. Ecol. 21, 387–393 (2007).

    Article  Google Scholar 

  19. 19.

    Lankau, R. A., Nuzzo, V., Spyreas, G. & Davis, A. S. Evolutionary limits ameliorate the negative impact of an invasive plant. Proc. Natl Acad. Sci. USA 106, 15362–15367 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    van den Bosch, R., Schlinger, E. I., Hall, J. C. & Puttler, B. Studies on succession, distribution and phenology of imported parasites of Therioaphis trifolii (Monell) in southern California. Ecology 45, 602–621 (1964).

    Article  Google Scholar 

  21. 21.

    Mackauer, M. Growth and developmental interactions in some aphids and their hymenopterous parasites. J. Insect Physiol. 32, 275–280 (1986).

    Article  Google Scholar 

  22. 22.

    Oliver, K. M., Degnan, P. H., Burke, G. R. & Moran, N. A. Facultative symbionts in aphids and the horizontal transfer of ecologically important traits. Annu. Rev. Entomol. 55, 247–266 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  23. 23.

    Oliver, K. M., Russell, J. A., Moran, N. A. & Hunter, M. S. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. Proc. Natl Acad. Sci. USA 100, 1803–1807 (2003).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  24. 24.

    Meisner, M. H., Harmon, J. P. & Ives, A. R. Temperature effects on long-term population dynamics in a parasitoid-host system. Ecol. Monogr. 84, 457–476 (2014).

    Article  Google Scholar 

  25. 25.

    Snyder, W. E. & Ives, A. R. Interactions between specialist and generalist natural enemies: parasitoids, predators, and pea aphid biocontrol. Ecology 84, 91–107 (2003).

    Article  Google Scholar 

  26. 26.

    Ives, A. R. & Settle, W. H. Metapopulation dynamics and pest control in agricultural systems. Am. Nat. 149, 220–246 (1997).

    Article  Google Scholar 

  27. 27.

    Bender, E. A., Case, T. J. & Gilpin, M. E. Perturbation experiments in community ecology: theory and practice. Ecology 65, 1–13 (1984).

    Article  Google Scholar 

  28. 28.

    Oliver, K. M. & Higashi, C. H. V. Variations on a protective theme: Hamiltonella defensa infections in aphids variably impact parasitoid success. Curr. Opin. Insect Sci. 32, 1–7 (2019).

    PubMed  Article  PubMed Central  Google Scholar 

  29. 29.

    Martinez, A. J., Doremus, M. R., Kraft, L. J., Kim, K. L. & Oliver, K. M. Multi-modal defences in aphids offer redundant protection and increased costs likely impeding a protective mutualism. J. Anim. Ecol. 87, 464–477 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Oliver, K. M., Degnan, P. H., Hunter, M. S. & Moran, N. A. Bacteriophages encode factors required for protection in a symbiotic mutualism. Science 325, 992–994 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Martinez, A. J., Kim, K. L., Harmon, J. P. & Oliver, K. M. Specificity of multi-modal aphid defenses against two rival parasitoids. PLoS ONE 11, e0154670 (2016).

  32. 32.

    Rock, D. I. et al. Context-dependent vertical transmission shapes strong endosymbiont community structure in the pea aphid, Acyrthosiphon pisum. Mol. Ecol. 27, 2039–2056 (2018).

    PubMed  Article  Google Scholar 

  33. 33.

    Doremus, M. R. & Oliver, K. M. Aphid heritable symbiont exploits defensive mutualism. Appl. Environ. Microbiol. 83, AEM.03276-16 (2017).

  34. 34.

    Oliver, K. M., Smith, A. H. & Russell, J. A. Defensive symbiosis in the real world—advancing ecological studies of heritable, protective bacteria in aphids and beyond. Funct. Ecol. 28, 341–355 (2014).

    Article  Google Scholar 

  35. 35.

    Losey, J. E., Ives, A. R., Harmon, J., Brown, C. & Ballantyne, F. A polymorphism maintained by opposite patterns of parasitism and predation. Nature 388, 269–272 (1997).

    CAS  Article  Google Scholar 

  36. 36.

    Harmon, J., Losey, J. & Ives, A. R. The use of color vision in Coccinellidae. Oecologia 115, 287–292 (1998).

    PubMed  Article  Google Scholar 

  37. 37.

    Langley, S. A., Tilmon, K. J., Cardinale, B. J. & Ives, A. R. Learning by the parasitoid wasp, Aphidius ervi (Hymenoptera: Braconidae) alters individual fixed preferences for pea aphid color morphs. Oecologia 150, 172–179 (2006).

    PubMed  Article  Google Scholar 

  38. 38.

    Tomasetto, F., Tylianakis, J. M., Reale, M., Wratten, S. & Goldson, S. L. Intensified agriculture favors evolved resistance to biological control. Proc. Natl Acad. Sci. USA 114, 3885–3890 (2017).

    CAS  PubMed  Article  Google Scholar 

  39. 39.

    Hufbauer, R. A. & Roderick, G. K. Microevolution in biological control: mechanisms, patterns, and processes. Biol. Control 35, 227–239 (2005).

    Article  Google Scholar 

  40. 40.

    Mills, N. J. Rapid evolution of resistance to parasitism in biological control. Proc. Natl Acad. Sci. USA 114, 3792–3794 (2017).

    CAS  PubMed  Article  Google Scholar 

  41. 41.

    Vorburger, C. & Perlman, S. J. The role of defensive symbionts in host–parasite coevolution. Biol. Rev. Camb. Philos. Soc. 93, 1747–1764 (2018).

    PubMed  Article  Google Scholar 

  42. 42.

    Caltagirone, L. E. Landmark examples in classical biological control. Annu. Rev. Entomol. 26, 213–232 (1981).

    Article  Google Scholar 

  43. 43.

    Desneux, N. et al. Intraspecific variation in facultative symbiont infection among native and exotic pest populations: potential implications for biological control. Biol. Control 116, 27–35 (2018).

    Article  Google Scholar 

  44. 44.

    Kach, H., Mathe-Hubert, H., Dennis, A. B. & Vorburger, C. Rapid evolution of symbiont-mediated resistance compromises biological control of aphids by parasitoids. Evol. Appl. 11, 220–230 (2018).

    PubMed  Article  Google Scholar 

  45. 45.

    Dennis, A. B., Patel, V., Oliver, K. M. & Vorburger, C. Parasitoid gene expression changes after adaptation to symbiont-protected hosts. Evolution 71, 2599–2617 (2017).

    PubMed  Article  Google Scholar 

  46. 46.

    Barbosa, P. in Conservation Biological Control (ed. Barbosa, P.) 39–54 (Academic Press, 1998).

  47. 47.

    Snyder, W. E., Chang, G. C. & Prasad, R. P. in Ecology of Predator–Prey Interactions (eds Barbosa, P. & Castellanos, I.) 324–343 (Oxford Univ. Press, 2004).

  48. 48.

    Tscharntke, T. et al. When natural habitat fails to enhance biological pest control—five hypotheses. Biol. Conserv. 204, 449–458 (2016).

    Article  Google Scholar 

  49. 49.

    Oliver, K. M., Campos, J., Moran, N. A. & Hunter, M. S. Population dynamics of defensive symbionts in aphids. Proc. R. Soc. B 275, 293–299 (2008).

    PubMed  Article  Google Scholar 

  50. 50.

    Lynn-Bell, N. L., Strand, M. R. & Oliver, K. M. Bacteriophage acquisition restores protective mutualism. Microbiology 165, 985–989 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  51. 51.

    Henry, L. M. et al. Horizontally transmitted symbionts and host colonization of ecological niches. Curr. Biol. 23, 1713–1717 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Gehrer, L. & Vorburger, C. Parasitoids as vectors of facultative bacterial endosymbionts in aphids. Biol. Lett. 8, 613–615 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  53. 53.

    Li, Q., Fan, J., Sun, J., Wang, M.-Q. & Chen, J. Plant-mediated horizontal transmission of Hamiltonella defensa in the wheat aphid Sitobion miscanthi. J. Agric. Food Chem. 66, 13367–13377 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  54. 54.

    Moran, N. A. & Dunbar, H. E. Sexual acquisition of beneficial symbionts in aphids. Proc. Natl Acad. Sci. USA 103, 12803–12806 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Brandt, J. W., Chevignon, G., Oliver, K. M. & Strand, M. R. Culture of an aphid heritable symbiont demonstrates its direct role in defence against parasitoids. Proc. R. Soc. B. 284, 20171925 (2017).

  56. 56.

    Martinez, A. J., Weldon, S. R. & Oliver, K. M. Effects of parasitism on aphid nutritional and protective symbioses. Mol. Ecol. 23, 1594–1607 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  57. 57.

    Russell, J. A. et al. Uncovering symbiont-driven genetic diversity across North American pea aphids. Mol. Ecol. 22, 2045–2059 (2013).

    PubMed  Article  PubMed Central  Google Scholar 

  58. 58.

    Moran, N. A., Degnan, P. H., Santos, S. R., Dunbar, H. E. & Ochman, H. The players in a mutualistic symbiosis: insects, bacteria, viruses, and virulence genes. Proc. Natl Acad. Sci. USA 102, 16919–16926 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  59. 59.

    Ives, A. R. et al. Variability and parasitoid foraging efficiency: a case study of pea aphids and Aphidius ervi. Am. Nat. 154, 652–673 (1999).

    PubMed  Article  PubMed Central  Google Scholar 

  60. 60.

    Ives, A. R. & Dakos, V. Detecting dynamical changes in nonlinear time series using locally linear state-space models. Ecosphere 3, art58 (2012).

    Article  Google Scholar 

  61. 61.

    Harvey, A. C. Forecasting, Structural Time Series Models and the Kalman Filter (Cambridge Univ. Press, 1989).

  62. 62.

    Rauwald, K. S. & Ives, A. R. Biological control in disturbed agricultural systems and the rapid re-establishment of parasitoids. Ecol. Appl. 11, 1224–1234 (2001).

    Article  Google Scholar 

  63. 63.

    Olson, A. C., Ives, A. R. & Gross, K. Spatially aggregated parasitism on pea aphids, Acyrthosiphon pisum, caused by random foraging behavior of the parasitoid Aphidius ervi. Oikos 91, 66–76 (2000).

    Article  Google Scholar 

  64. 64.

    Caswell, H. Matrix Population Models (Sinauer Associates, 1989).

  65. 65.

    Caillaud, M. C. & Losey, J. E. Genetics of color polymorphism in the pea aphid, Acyrthosiphon pisum. J. Insect Sci. 10, 95 (2010).

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Acknowledgements

This work could not have been done without help from the UW Arlington Agricultural Research Station staff, in particular J. Breuer and M. Bertram. Many undergraduate, graduate and postdoctoral students helped to collect and administer our long-term data. Funding was provided by NASA/NSF-DEB Dimensions of Biodiversity grant nos. 1240804 and 1240892.

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A.R.I., K.O., B.T.B., J.P.H. and V.C.R. were involved in the conceptualization of this project. A.R.I. and K.O. conducted the formal analysis. A.R.I., J.P.H., K.O. and V.C.R. obtained funding. B.T.B., R.M.P., K.L.K., A.R.I., J.P.H. and K.O. carried out investigations. A.R.I., B.T.B., R.M.P. and K.O. were responsible for the project adminstration. A.R.I. wrote the original draft and all authors were involved in editing and reviewing.

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Correspondence to Anthony R. Ives.

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Extended data

Extended Data Fig. 1 Field experiment hoop houses.

a, Photograph of a hoop house experimental screen cage with lucerne harvested asynchronously in four strips (photo credit A. R. Ives). b, Google Earth satellite image of the four hoop houses in September, 2010. (A different experiment was being performed that compared treatments within and outside the hoop houses).

Extended Data Fig. 2 Assay for phenotypic resistance of aphid clones.

Normal-Poisson GLMM for the number of aphids recovered in the assays for resistance depending on whether the line contains or does not contain Hamiltonella-APSE3 (Ham+ or Ham-) and whether parasitoids were added (parasitoid+) or not (parasitoid-), with random effects for the focal line, the competing line and the observation. See Supplementary Information: ‘Assays for resistance in experimental aphid clones’.

Extended Data Fig. 3 Experiment to measure phenotypic resistance among Hamiltonella-containing aphid clones.

In a field experiment investigating resistance to parasitism, final aphid abundances for clones with and without Hamiltonella-APSE3 (Ham+ and Ham-) when parasitic wasps were not supplemented (F) or were supplemented (T). In the top panel all trials are included, whereas in the bottom panel only trials containing the clones used to inoculate the hoop houses are included. See Supplementary Information: ‘Assays for resistance in experimental aphid clones’.

Extended Data Fig. 4 Results from symbiont assays.

Numbers of assayed pea aphids containing Hamiltonella and the numbers containing no symbionts in hoop houses and cages within hoop houses at three sampling dates. See ‘Hoop house experiment’.

Extended Data Fig. 5 Likelihood function for the model fit to hoop house data from summer-autumn 2015 graphed for the benefits and costs of resistance.

The benefit of resistance is the probability that an aphid attacked by a parasitoid kills the parasitoid egg, given by (1—b) in the fitted model. The cost of resistance is the proportional reduction in fecundity, given by (1—c). The maximum likelihood estimates of both parameters are marked by the red cross and the contour lines are at intervals of ΔlogLik = 5.99/2; 5.99 is the value of a chi-square distribution with df = 2, so the first contour corresponds to the joint approximate 95% confidence interval given by a Likelihood Ratio Test.

Extended Data Fig. 6 Analyses of changes in the proportion of pea aphid clones containing Hamiltonella-APSE3 relative to uninfected clones between 23 September, 2015, and 22 April, 2016.

a, Binomial ANOVA analysis of the proportion of aphid clones with Hamiltonella-APSE3, showing a decrease in infections over winter. b, Binomial ANOVA analysis of the proportion of aphid clones with Hamiltonella-APSE3 in spring including the proportion infected in autumn as a predictor, showing that harvesting treatment (synchronous versus asynchronous) does not affect this change. See Supplementary Information: ‘Hoop house experiment—Additional statistical analyses (ii) Levels of resistance’.

Extended Data Fig. 7 Regional stability of the simulation model showing the frequency of resistant aphid clones (black line) and the proportion parasitism (red line) calculated from all 40 simulated fields.

To illustrate regional dynamics of the simulation model (Fig. 3), we removed the log-normal variation in aphid survival within fields and iterated the model for 4000 days. On days 667 and 2667, a perturbation was applied in which the proportion of the resistant clone was sharply increased. This caused parasitism to decrease, and with decreased parasitism selection favoured the non-resistant clone. After roughly 1000 days the proportion of resistant clones and proportion parasitism returned to their regional equilibrium values.

Extended Data Fig. 8 Model parameter estimates.

Model parameter estimates. Parameter estimates from the state-space model fit to the hoop house experiment for summer-autumn 2015 and spring 2016. See ‘Model of resistance fitted to hoop house experiment data’ and Supplementary Information: ‘Model of resistance fitted to hoop house experiment data—Model fitting’.

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Ives, A.R., Barton, B.T., Penczykowski, R.M. et al. Self-perpetuating ecological–evolutionary dynamics in an agricultural host–parasite system. Nat Ecol Evol 4, 702–711 (2020). https://doi.org/10.1038/s41559-020-1155-0

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