<i>Prunus africana</i> populations of conservation priority based on the second selection method proposed (S2).

<p>Priorities are identified within 32 <i>Prunus africana</i> populations for which genetic data are available. The method is based on the ‘<i>reserve selection</i>’ analysis carried out in DIVA-GIS. The method is aimed at enhancing complementary of the genetic diversity represented within the populations selected for conservation priority. The 18 populations selected for conservation priority are listed (2 of the original populations fall within the same grid cell due to their closeness, therefore are treated as one population and have the same ranking).</p

<i>Prunus africana</i> modeled potential distribution under past, current and future conditions in 2050.

<p>(6a) The spatial distribution of all <i>P. africana</i> observation points is shown. Areas in red are expected to be highly affected by future climate change; in low impact areas (blue) no changes in species distribution are expected; areas in green are expected to become suitable for <i>P. africana</i>. (6b) The past scenario refers to the last glacial maximum (LGM), about 21,000 years before present. Blue indicates areas with continued habitat suitability since LGM until present (original areas). Green indicates areas most likely unsuitable for <i>P. africana</i> at the LGM, but suitable at present (recent areas of expansion). Red represents areas suitable during LGM but no longer suitable at present (lost areas). The spatial distribution of the 32 sampled populations, for which genetic data are available, is indicated by yellow triangles.</p

Current conservation status and expected modeled future climate suitability (2050) for 32 <i>Prunus africana</i> populations, across 9 African countries.

<p>Populations highlighted in bold are those selected for conservation priority based on both selection approaches (S1 and S2) presented in this study. Sites that are not officially protected or are expected to present future climate conditions unsuitable for <i>P.africana</i> are highlighted in capital letters, together with areas falling at the margin of the modeled distribution under future climate scenario in 2050. For some protected areas the IUCN category is not available.</p

Clustering of 1,500 <i>Prunus africana</i> observations based on level of similarity of bioclimatic variables.

<p>Bioclimatic values for 19 variables were associated with all <i>P. africana</i> records. Bioclimatic values were extracted from 2.5 minute rasters obtained from the Worldclim website. The observation points are grouped (each cluster is highlighted with a different colour) by Euclidean distance.</p

<i>Prunus africana</i> populations of conservation priority based on the first selection method proposed (S1).

<p>A subset of 32 <i>Prunus africana</i> populations, from across 9 African countries is characterized by genetic data (number of individuals, haplotype richness, allelic richness, occurrence of locally common alleles, similarity in allelic composition) and climatic data. Haplotype/allelic richness and presence of locally common alleles are ranked, with highest ranking attributed to populations with the highest value of these parameters. Priority populations for conservation are highlighted in bold.</p

Clustering of <i>Prunus africana</i> populations based on molecular marker data.

<p>The 32 populations, represented by 30 minute grid cells, are grouped by Nei’s distance, based on similarity of haplotypes (cpSSR) (2a) and similarity of nuclear microsatellite (nSSRs) allelic composition (2b).</p

<i>Prunus africana</i> haplotype richness and allelic richness.

<p>Haplotype (cpSSR) (3a) and allelic (nSSR) (3b) richness are determined for 32 populations, after rarefaction, using a 30 minute grid cell size.</p

<i>Prunus africana</i> observations and modeled potential distribution.

<p>Probability of occurrence of <i>P. africana</i> is determined on the basis of climatic/environmental parameters and indicated by different colors, from dark brown (high probability) to yellow (low probability).</p

<i>Prunus africana</i> modeled potential distribution in Kenya, Tanzania and Uganda with respect to croplands and protected areas.

<p><i>P. africana</i> modeled potential distribution is shown with respect to areas occupied by >50% croplands (5a), and to the location of protected areas (5b). Areas with expected high and low impact of climate change in 2050 are also highlighted (5b). In low impact areas (blue), no changes in species distribution are expected, while in areas of high impact (red), climatic conditions are expected to become unsuitable for <i>P. Africana.</i> The location of 19 populations, for which genetic data are available, is also shown.</p

<i>Boscia senegalensis</i>.

<p><b>Threat magnitude levels of (A) ‘Overexploitation’, (B) ‘Overgrazing’, (C) ‘Fire’, (D) ‘Climate change’, (E) ‘Cotton production’, (F) ‘Mining’ and (G) ‘Combined threat’.</b> The criteria to define the threat levels are presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0184457#pone.0184457.t005" target="_blank">Table 5</a>.</p