Overview of the different locations of the ten clusters identified by k-means clustering.

<p>The three subclusters of cluster 6 are highlighted with different colours, clearly distinguishing the group that is largely composed of the Nacional cultivar of the Ecuadorean coastal plains (red colour).</p

Averages of genetic parameters per locus for clusters 1 to 10, based on 1,000 bootstrap samples of 35 trees (i.e. the size of the smallest cluster).

<p>Four highest values for each of the parameters are underlined.</p

Observed locally common alleles compared to past and current modeled distribution of cacao.

<p>Upper: distribution of areas with modeled habitat suitability of cacao during the LGM; red dashed polygons show potential relatively isolated refugia associated with areas holding high levels of locally common alleles. Lower: changes in cacao habitat suitability from the LGM until present; red areas represent potential habitat suitability during LGM but no longer at present (high impact or restriction areas); green indicates areas with continued habitat suitability from LGM until present (low impact or stable areas); and blue indicates areas that were probably not suitable for cacao at the LGM, but are suitable at present (new or expansion areas).</p

Cluster richness, i.e. the number of different clusters shown in <b>figure 5</b> that occur in a given area.

<p>Cluster richness, i.e. the number of different clusters shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047676#pone-0047676-g005" target="_blank"><b>figure 5</b></a> that occur in a given area.</p

Averages of genetic parameters per locus for trees from coastal Ecuador (Nacional cultivar) and the remaining trees from cluster 6 (Contamana + Nacional (+Purus)), based on 1,000 bootstrap samples of 20 trees (i.e. the number of trees from coastal Ecuador).

<p>Averages of genetic parameters per locus for trees from coastal Ecuador (Nacional cultivar) and the remaining trees from cluster 6 (Contamana + Nacional (+Purus)), based on 1,000 bootstrap samples of 20 trees (i.e. the number of trees from coastal Ecuador).</p

Species richness of genus <i>Theobroma</i>.

<p>Left: observed species richness in 10 minute grid cells and a circular neighborhood of 1 decimal degree; Right: modeled species richness in 2.5 minute grid cells.</p

Complete linkage clustering based on Nei’s distance (cophenetic correlation = 0.92).

<p>Complete linkage clustering based on Nei’s distance (cophenetic correlation = 0.92).</p

Scores of sampled trees as projected on the first ordination axis of the biplot of a Spatial Analysis of Principal Components.

<p>Location of the genetic cline coincides with the bean-shaped area (and particularly the southern part of it) where the highest values of the measured genetic parameters were observed (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047676#pone-0047676-g002" target="_blank">figure 2</a>).</p

Potential wild barley distributions in current (A), past (B) and future (C) climates.

<p>Distributions are based on ecological niche modelling using MaxEnt (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086021#s2" target="_blank">Materials and Methods</a>). D, differences between current and past modelled distributions, including areas lost and gained since the LGM. E, differences between future and current modelled distributions, including areas expected to be lost and gained by the 2080s. Note that past and future distribution maps take no account of rises or falls in sea levels or of other water bodies, and that these distributions are shown superimposed on current country boundaries.</p

Spatial autocorrelation analysis profiles for wild barley accessions based on BOPA SNPs, nSSRs and cpSSRs.

<p>Geographic distances on the <i>x</i>-axis are the mean values of distance classes. The symbols at the top of the figure mark observations significantly larger or smaller (<i>P</i>≤0.01) than the average for distance classes. Values for the <i>Sp</i> statistic, calculated from the regression slope of the graph and the kinship coefficient of the first distance class <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086021#pone.0086021-Vekemans1" target="_blank">[76]</a>, are also shown. Placing all three data sets on the same graph allows profiles to be compared. Increases in similarity at a distance class of around 1,000 km, and an earlier additional increase for cpSSRs at around 500 km, illustrate that a simple isolation-by-distance model is not sufficient to describe genetic variation in wild barley.</p