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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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.
Codes used for analyses in this study have been deposited in figshare.com at https://doi.org/10.6084/m9.figshare.11828865.v1
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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.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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).
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’.
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.
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
Nature Ecology & Evolution (2022)
Nature Ecology & Evolution (2020)