Population admixture, biological invasions and the balance between local adaptation and inbreeding depression

Abstract

When previously isolated populations meet and mix, the resulting admixed population can benefit from several genetic advantages, including increased genetic variation, the creation of novel genotypes and the masking of deleterious mutations. These admixture benefits are thought to play an important role in biological invasions. In contrast, populations in their native range often remain differentiated and frequently suffer from inbreeding depression owing to isolation. While the advantages of admixture are evident for introduced populations that experienced recent bottlenecks or that face novel selection pressures, it is less obvious why native range populations do not similarly benefit from admixture. Here we argue that a temporary loss of local adaptation in recent invaders fundamentally alters the fitness consequences of admixture. In native populations, selection against dilution of the locally adapted gene pool inhibits unconstrained admixture and reinforces population isolation, with some level of inbreeding depression as an expected consequence. We show that admixture is selected against despite significant inbreeding depression because the benefits of local adaptation are greater than the cost of inbreeding. In contrast, introduced populations that have not yet established a pattern of local adaptation can freely reap the benefits of admixture. There can be strong selection for admixture because it instantly lifts the inbreeding depression that had built up in isolated parental populations. Recent work in Silene suggests that reduced inbreeding depression associated with post-introduction admixture may contribute to enhanced fitness of invasive populations. We hypothesize that in locally adapted populations, the benefits of local adaptation are balanced against an inbreeding cost that could develop in part owing to the isolating effect of local adaptation itself. The inbreeding cost can be revealed in admixing populations during recent invasions.

Figure 1.

Fitness effects of heterozygosity and genome dilution of locally adapted wild barley in native and novel environments. A cross was made between plants from two locally adapted wild barley populations (AQ and ME) and performance of recombinant F₃ families (derived by selfing from the F₁) was evaluated at the natural field sites of the AQ and ME populations (a, native environments) and in an experimental garden at different nutrient levels (b, novel environments). Using genome-wide markers, the proportion of heterozygous loci (one allele derived from each parent) and the proportion of genome content derived from either parent were estimated for each of 140 F₃ families (proportion ME = 1 − (proportion AQ)). Seed output (total biomass [g] of all seeds produced) was positively associated with heterozygosity only in the novel environments, while genome dilution had an effect only under native field conditions where a high proportion of AQ genome was positively associated with seed output at the AQ site but not at the ME site. Regression coefficients and p-values are from simple linear regressions (data from [23], see that paper for details).

Figure 2.

Effect of population crossing distance on offspring biomass in native and introduced ranges of S. latifolia. Crosses were made within and between populations from the species' native European range (a, six populations) and the introduced North American range (b, 15 populations). F₁ progeny individuals were all raised in one common garden experiment and their biomass is plotted against the geographical distance between their parental populations (within-population crosses: distance = 0 km; between-population crosses: distance > 0 km). Dashed lines indicate the mean value of within-population crosses. Inset tables show results of second-order polynomial regression analysis; p-values indicate significance of sequential addition of linear and quadratic distance terms to the model (type I analysis, proc GLM in SAS, SAS Institute, Cary, NC, USA). Model fit is generally low (native range: r² = 0.14; introduced range: r² = 0.01), but in the native range, model fit was significantly improved by adding the quadratic term. Data are from [36]; aboveground biomass at the end of the 2004 growing season, MLBS transplant site.