Effects of phenotypic variation on consumer coexistence and prey community structure

Abstract

A popular idea in ecology is that trait variation among individuals from the same species may promote the coexistence of competing species. However, theoretical and empirical tests of this idea have yielded inconsistent findings. We manipulated intraspecific trait diversity in a ciliate competing with a nematode for bacterial prey in experimental microcosms. We found that intraspecific trait variation inverted the original competitive hierarchy to favour the consumer with variable traits, ultimately resulting in competitive exclusion. This competitive outcome was driven by foraging traits (size, speed and directionality) that increased the ciliate's fitness ratio and niche overlap with the nematode. The interplay between consumer trait variation and competition resulted in non-additive cascading effects-mediated through prey defence traits-on prey community assembly. Our results suggest that predicting consumer competitive population dynamics and the assembly of prey communities will require understanding the complexities of trait variation within consumer species.

Keywords: bacteria; coexistence; community assembly; competition; intraspecific variation; nematodes; predator; prey; protists; traits.

FIGURE 1

Study setup. (a) The experimental bacterial community with different consumer combinations. Ctrl ‐ bacteria only, N ‐ bacteria with nematode, CLTV ‐ bacteria with isogenic low trait diversity ciliate, CHTV ‐ bacteria high trait diversity mixed ciliate populations, NCLTV ‐ bacteria + nematode + low trait diversity ciliate, NCHTV ‐ bacteria +nematode + high trait diversity ciliate. (b) Schematic representation of the serial transfer experiment. Each experimental condition from A) was performed in four biological replicates with 15 transfers/samplings. (c) Traits of individual bacterial species were measured in monoculture and inferred from genome sequences. (d) Consumers were grown on each bacterial species to assess consumer grazing efficiency (see methods)

FIGURE 2

Consumer competitive hierarchy depends upon ciliate ITV. (a) Consumer and bacterial biomass during the course of the experiment. Points are observations, and lines are estimated marginal means (mean response and 95% confidence levels) from generalised additive models. Black crosses are target consumer starting densities at T0. Model summaries and contrasts of marginal means are available in Tables S2‐S4. (b) Niche overlap and competitive ratio between the ciliate and the nematode depending on whether the ciliate had low trait variation (NCLTV) or high trait variation (NCHTV). Coexistence is defined by the inequality $\rho <\frac{k_{\mathit{ciliate}}}{k_{\mathit{nematode}}}<\frac{1}{\rho }$. Points and line ranges show the mean and standard deviation from four biological replicates

FIGURE 3

Prey community response to consumer competition and ITV. (a) Prey species abundance distributions from each experimental treatment. X‐axis ranks prey species (1977 most abundant) by average across all conditions. Y‐axis shows relative abundance. (b) Replicate mean abundance trajectories over time (normalised to each species maximum) for each of the 24 bacterial prey species. (c) Non‐metric multidimensional scaling ordination of trajectories through community space. Larger, outlined circles show means across replicates, whereas small circles are replicates. Colours represent days from the experiment start. Means are connected in chronological order.

FIGURE 4

Effects of prey traits and consumer arrangement on prey community assembly. Joint Species Distribution Model (JSDM) results from (a) the sorting phase (days 0–13) and (b) the equilibrium phase (days 17–61). Bar plots show the explanatory power for each bacterial prey species in the JSDMs. The bars are coloured by the proportion of variance explained by fixed and random effects and their interactions. Heatmaps show the influence of fixed effects on bacterial prey species abundance (β) and the influence of prey traits on bacterial prey species association with fixed effects (γ). The sign of the coefficient (i.e. the direction of the effect) is included only if the 95% credibility interval excludes zero (i.e. the probability the effect is not zero is 95%). Trait abbreviations: D, defence against CLTV; N carbon, number of carbon sources the species can use; r, maximum specific growth rate; relative biofilm, biofilm production

FIGURE 5

Consumer ITV drives partitioning of the predation response. (a) Relative abundance of prey species in the presence of ciliate or nematode consumers (vertical axis) versus the corresponding relative abundance in the consumer‐free controls. The regression includes prey species >1% relative abundance and samples from first 21 days. The axes are arcsin square‐root transformed. $\beta$, $R^2$ is the median for the posterior of the slope and Bayesian $R^2$, respectively, from linear regression (Table S12). (b) Consumer response (prey clearance) as a function of prey species identity. Prey clearance is the number of bacterial cells removed per consumer individual after 144 h. Long tick marks on the vertical axis show the mean clearance rate of each consumer. Prey species are ordered by increasing susceptibility to the HTV ciliate. The curve is a simple polynomial fit to aid visualisation. Asterisks show significant differences in mean prey clearance between consumers Table S12. CV, coefficient of variation