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Evolution of an inferior competitor increases resistance to biological invasion

Abstract

Biodiversity is imperilled by the spatial homogenization of life on Earth. As new species invade ecological communities, there is urgent need to understand when native species might resist or succumb to interactions with new species. In the California Floristic Province, a global biodiversity hotspot, we show that populations of a native grass (Vulpia microstachys) have evolved to resist the competitive impacts of a dominant European invader (Bromus hordeaceus). Contrary to classic theory, which predicts that competing species co-evolve to differentiate their niches, our evidence is instead most consistent with the native species having evolved to better compete for those resources used by the invader, curtailing the invader’s spread. Evolution to resist an invader was achieved despite populations interacting within a diverse background community (22 species 0.5 m–2 on average), refuting the oft-cited hypothesis that high diversity precludes the evolution of pairwise species interactions. Lastly, unlike studies that have explored the demographic consequences of evolution under competition, ours does so with naturally evolved populations. Our study highlights evolution as an underappreciated coexistence mechanism, acting to buffer species from extinction in the face of biological invasion.

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Fig. 1: Experimental test of evolutionary history and predicted outcomes for competitive interactions.
Fig. 2: Conceptual schematic of how pre-existing differences among competing species might lead to alternate outcomes after co-evolution.
Fig. 3: Evolution in sympatry reduces the sensitivity of an inferior competitor (Vulpia) to interspecific competition, equalizing species’ competitive abilities.
Fig. 4: Per capita competitive effect of Vulpia on Bromus (αbv) in a diverse natural community is stronger when Bromus populations evolved with the resident Vulpia population.
Fig. 5: No evidence that phenotypic traits evolve in response to history of interaction with an interspecific competitor.

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Data availability

Data are posted to Zenodo (https://doi.org/10.5281/zenodo.3555544). Correspondence and requests for materials should be directed to R.M.G. (rgermain@zoology.ubc.ca).

Code availability

Code is posted to Zenodo (https://doi.org/10.5281/zenodo.3555544).

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Acknowledgements

We thank M. Urquhart-Cronish, A. Kushnir, A. Wilkinson and M. Zink for greenhouse assistance, M. Urquhart-Cronish and N. Jones for field assistance, S. Harrison for environmental data and B. Bolker for advice with our mixed models. Funding is provided to R.M.G. by the Biodiversity Research Centre, Killam Trust and an NSERC Discovery Grant (no. 2019-04872).

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Contributions

R.M.G. conceived of the research, carried out the experiment/analyses and wrote the initial manuscript. A.L.A. and D.S. provided feedback and editing at all stages.

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Correspondence to Rachel M. Germain.

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Extended data

Extended Data Fig. 1 A simulation demonstrating that our findings presented in Fig. 3 are most consistent with a reduced competitive asymmetry.

We use a Beverton-Holt model25 of two-species competition to show how the evolution of the relationship between population growth rates and relative frequency of an interspecific competitor depends on whether competitive asymmetries (A,B) or niche differentiation (C,D) evolve. Parameters in the allopatric group were λi = 500, λj = 200, αii = 2, αij = 5 αjj = 5, αji = 0.5 – in the top panel (simulating a reduction in a competitive asymmetry), the sympatric group was modified so αij was 3.5 and αji was 0.71, and in the bottom panel (simulating increased niche differentiation), αij was 3.5 and αji was 0.35.

Extended Data Fig. 2 Rank-abundance (as percent cover) of all species at each sympatric site, showing where Bromus (blue) and Vulpia (red).

Note that these data are from previous diversity surveys in plots that represent a small sample of diversity compared to the scale at which seeds were collected from each population. For example, at site 18, Bromus was abundant at the site but not observed in the surveyed plots despite being generally quite abundant.

Extended Data Fig. 3 Experimental design in Fig. 1 and data with a treatment added to test if sympatric populations evolve in a repeatable or non-repeatable fashion.

(A) The three treatments are: sympatric (blue line; exactly as in Fig. 1), allopatric (red; exactly as in Fig. 1), and competing Bromus and Vulpia that are sympatric (that is, the two species are found together at both sites) with a different population (that is, not the specific population they evolved with). (B) If the evolution of phenotypic traits was not repeatable, a Vulpia that evolved in sympatry with a specific Bromus population would not have an advantage when competing with other, foreign Bromus populations, even if those Bromus also evolved sympatrically with a different Vulpia population. As a result, these Vulpia are more likely to respond to competition with Bromus similarly to allopatric Vulpia populations (scenario ii). If the evolution of phenotypic traits is repeatable, sympatric Vulpia should have an advantage over allopatric Vulpia when competing with a sympatric Bromus, regardless of whether that is the specific Bromus population it evolved to. (C) Evolution in response to an interspecific competitor proceeds repeatably among replicated sympatric populations (that is, scenario depicted in panel B (i)). Solid lines are fitted marginal values from a glmer with 95% confidence bands. Inset shows significant (solid line, P < 0.05) vs. non-significant (dashed line, P > 0.10) differences in slopes among treatments.

Extended Data Fig. 4 Map of 25 sympatric (blue) and allopatric (red) Vulpia populations at McLaughlin Natural Reserve; sympatric populations also contain Bromus.

The populations are >100 m apart and were selected because environmental data were available from prior research (data of 23 sites from33 and two from S. Harrison). Additional populations not used in our experiment (grey) but that were used to assess abiotic similarity among sites are also shown here and in biplots (Extended Data Figs. 6 and 7). corresponds to our common garden experiment (data used in Extended Data Fig. 5).

Extended Data Fig. 5 Density distributions of (A) Vulpia abundance, (B) Bromus abundance, (C) their relative abundances (1.0 = 100% Bromus), and (D) their total abundances in the field in plant neighbourhoods of identical size to our greenhouse pots.

480 neighbourhoods were surveyed in 2018 as part of a separate experiment (see Methods, ‘Evolution of interaction strengths in the field’), each neighbourhood being a 15-cm diameter sampling circle. The blue vertical line shows the median abundance across neighbourhoods. Note that these abundances are only of a single site ( in Extended Data Fig. 4) at McLaughlin Natural Reserve – population densities will undoubtedly vary among sites and years, but this detailed examination of species abundances on a scale relevant to our greenhouse competition experiment provides a point estimate of an approximate order of magnitude. Arrows indicate the correspondence between the relative frequency ratios (*1-*3) and total plant density (*4) used in our competition experiment and the natural field frequencies/densities.

Extended Data Fig. 6 Biplot of multivariate abiotic conditions of sites Vulpia populations originated from, showing (A) sites and (B) loadings of environmental variables.

Numbers correspond to site number and are colored by the treatment they were used in our competition experiment (i.e., blue=sympatric with Bromus, red=allopatric, grey=unused sites used to construct biplot). Key to loading labels: Ca/Mg=ratio of soil calcium to magnesium, cec=cation exchange capacity, ele=elevation, K=soil potassium, max.s=slope of ground at coarse scale (for example, hillside), N=soil nitrogen, Na=soil sodium, om=soil organic matter, P=soil phosphorus, pH=soil pH, p.sm=percent soil moisture, sun=sunlight, tot.s=slope of ground at fine scale (m2). Environmental data for two sites (“S2”, “S33”) were collected by a separate research group (S. Harrison) and were thus not directly comparable to data for the rest of the sites (see Extended Data Fig. 7 for analysis of environmental similarity of these two sites, relative to other sites measured by S. Harrison’s research group).

Extended Data Fig. 7 Biplot of multivariate abiotic conditions of subset of sites Vulpia populations originated from S. Harrison’s long-term plots at McLaughlin Reserve, showing (A) sites and (B) loadings of environmental variables.

Numbers correspond to site number, and are colored by the treatment they were used in our competition experiment (i.e., blue=sympatric with Bromus, red=allopatric, grey=unused sites used to construct biplot). Key to loading labels: B=soil boron, Ca/Mg=ratio of soil calcium to magnesium, cec=cation exchange capacity, CLAY=soil clay content, Co=soil cobalt, Cu=soil copper, ele=elevation, Fe=soil iron, K=soil potassium, M=soil manganese, N=soil nitrogen, Na=soil sodium, Ni=soil nickel, om=soil organic matter, P=soil phosphorus, pH=soil pH, SAND=soil sand content, SILT=soil silt content, Zn=zinc.

Extended Data Fig. 8 Population growth rates of Vulpia in the absence of competition (i.e., intrinsic rate of increase) does not vary with history of sympatry or allopatry.

Each violin plot is data from a single Vulpia population. There were seven replicate pots per population, each containing a single individual. Pots were arranged on a greenhouse bench in a completely randomized design intermixed with the two-species competition pots.

Extended Data Fig. 9 Raw population growth rate data for Bromus with fitted lines from our mixed effects models.

Each Bromus population (identified by facet text) was competed against two Vulpia populations: one sympatric (blue) and one allopatric (red) population, testing for a difference in slope depending on evolutionary history. Because both treatments were performed with the same Bromus population, we would not expect a difference in intercepts among treatments for any given Bromus population. Vulpia populations are indicated in the panel text and correspond to biplots Extended Data Figs. 6 and 7).

Extended Data Fig. 10 Raw population growth rate data for Vulpia with fitted lines from our mixed effects models.

The facet text corresponds to each Bromus population, each of which were competed against two Vulpia populations: one sympatric (blue) and one allopatric (red) population. We are testing for a difference in slope based on history of sympatry across Vulpia populations. Since two different Vulpia populations were competed with each Bromus, each Vulpia may have a unique intercept regardless of treatment. Vulpia populations are indicated in text and correspond to biplots (Extended Data Figs. 6 and 7). The dashed line at λ=1 denotes the boundary between populations replacing themselves (λ≥1) or not (λ < 1), at present densities and relative frequency ratios; seven allopatric populations cross or touch this threshold, whereas a single sympatric population crosses it.

Supplementary information

Supplementary Information

Supplementary Table 1: Statistical model testing population growth rates in response to the evolutionary history (EH) treatments (sympatric vs. allopatric), the relative frequency (RF) of heterospecific competitors, their interaction and total plant density.

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Germain, R.M., Srivastava, D. & Angert, A.L. Evolution of an inferior competitor increases resistance to biological invasion. Nat Ecol Evol 4, 419–425 (2020). https://doi.org/10.1038/s41559-020-1105-x

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