Bulbophyllum occultum, AFLP-matrix

Bulbophyllum occultum, AFLP-matri

Evidence for Isolation-by-Habitat among Populations of an Epiphytic Orchid Species on a Small Oceanic Island

<div><p>Identifying factors that promote population differentiation is of interest for understanding the early stages of speciation. Gene flow among populations inhabiting different environments can be reduced by geographical distance (isolation-by-distance) or by divergent selection resulting from local adaptation (isolation-by-ecology). Few studies have investigated the influence of these factors in small oceanic islands where the influence of geographic distance is expected to be null but where habitat diversity could have a strong effect on population differentiation. In this study, we tested for the spatial divergence of phenotypes (floral morphology and floral scent) and genotypes (microsatellites) among ten populations of <i>Jumellea rossii</i>, an epiphytic orchid endemic to Réunion growing in three different habitats. We found a significant genetic differentiation between populations that is structured by habitat heterogeneity rather than by geographic distance between populations. These results suggest that ecological factors might reduce gene flow among populations located in different habitats. This pattern of isolation-by-habitat may be the result of both isolation-by-ecology by habitat filtering and asynchrony in flowering phenology. Furthermore, data on floral morphology match these findings, with multivariate analysis grouping populations by habitat type but could be only due to phenotypic plasticity. Indeed floral scent compounds were not significantly different between populations indicating that specific plant-pollinator mutualism does not seem to play a major role in the population differentiation of <i>J. rossii.</i> In conclusion, the results from our study emphasize the importance of habitat diversity of small oceanic islands as a factor of population differentiation.</p></div

Location of Réunion and study populations.

<p>The top map shows the location of Réunion (in red) in the southwest Indian Ocean. The bottom map shows the location of study populations and the distribution of the three natural habitats types of <i>Jumellea rossii</i>.</p

Characteristics of the studied populations of Jumellea rossii in Réunion.

<p><i>N</i>_m, <i>N</i>_g, <i>N</i>_c number of sampled individuals for morphometric, genetic and aromatic chemical analyses respectively.</p

Spatial genetic structure of <i>Jumellea rossii</i> populations obtained by two different methods.

<p>Genetic structure is inferred (A) by a model-based clustering method implemented in InStruct and (B) by discriminant analysis of principal components with habitat type as grouping factor. At each location, pie charts indicate the mean proportion of individual memberships in each cluster for K = 3 (A) or each habitat type (B) and their size is proportional to the number of individuals sampled.</p

Canonical discriminant analysis of 10 morphological floral traits with habitat type as grouping factor.

<p>Flowers of one population of each habitat (PF, CL and RBV) are drawn. The colours correspond to the type of habitat, dark blue for the mountain windward rainforest, light blue for the submountain windward rainforest and orange for the mountain leedward rainforest.</p

Estimates of genetic diversity at 13 microsatellite loci in 12 populations of Jumellea rossii and means per habitat type.

<p><i>A</i>_L, mean number of alleles per locus ± s.d.; <i>A</i>_R, mean allelic richness per locus ± s.d.; <i>A</i>_P, private allelic richness; <i>H</i>_E, expected heterozygosity over all loci ± s.d.; <i>H</i>_O, observed heterozygosity over all loci ± s.d.; HWE, result of test for departures from Hardy–Weinberg Equilibrium, ***<i>P</i><0.001; <i>F</i>_IS, fixation index of Weir and Cockerham <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087469#pone.0087469-Weir1" target="_blank">[34]</a>; MWR, mean per population of mountain windward rainforest; MLR, mean per population of mountain leeward rainforest; SWR, mean per population of submountain windward rainforest.</p

Posterior model probabilities for models explaining migration rates among populations of Jumellea rossii.

<p>Values represent means of the 10 runs.</p

Multiple matrix regression with randomization (MMRR) analysis performed on genetic distances.

<p>Scatterplots show patterns of isolation-by-distance (A), isolation-by-ecology (B) and the absence of eco-spatial autocorrelation (C) according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0087469#pone.0087469-ShaferAB1" target="_blank">[4]</a>. When correlations are significant (Mantel test, P<0.05), regression lines are drawn. Plot (D) is based on the results of the multiple matrix regression analysis for the effects of both geographical and environmental distances on genetic distances.</p