Computational protocol: Morphological versus molecular markers to describe variability in Juniperus excelsa subsp. excelsa (Cupressaceae)

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Protocol publication

[…] Plant material was sampled from 14 populations from Greece, Cyprus, Ukraine (Crimea), Turkey (Anatolia) and Lebanon (Fig. ). The samples of cones and twigs from the last ramification were collected only from arborescent adults bearing seed cones and were gathered separately from the southerly exposed parts of the individuals, at a height of ∼1.0–5.0 m above ground level, as described by . Three hundred and ninety-four individuals of J. excelsa were examined. Around 30 individuals per population were examined except for the Lebanese population LB3, where only 18 individuals with cones were found (Table ). Each individual from every population tested was represented by 10 cones and 10 pieces of twig. Some individuals in the analysed populations had <10 twigs. Nine morphological characters and eight ratios were examined (Table ) in order to assess the variation within and between populations. The measurements of the shoots were performed under a stereoscopic microscope of ×8 magnification with a scaled ocular (LN and ST), as described by . Cone dimensions (CL and CD; Table ) were measured using a numerical calliper (0.01 mm) and the numbers of cone scale rows and cone scales (CSR and CSN) were counted manually. Seed dimensions (SL and SW) were measured automatically using the WinSEEDLE software and the number of seeds in a cone (SN) was counted manually. [...] The symmetry and unimodality of the distribution frequency of the measured character were verified using Shapiro–Wilks' W-test to assess the possibility of conducting a statistical analysis (; ; ). The main statistics (arithmetic means, standard deviation, coefficient of variation) were calculated for the particular characters for individuals and populations. The correlations between the measured characters were verified using Pearson's correlation coefficient to avoid the most redundant ones. Tukey's T-test was performed to verify the influence of particular characters on the differentiation between individuals within populations and between populations. The level of intra-population variation was assessed using Ward's agglomeration on the shortest Euclidean distances among individuals (; ).The discrimination analysis was performed to identify the discriminate power of each character and to determine the inter-population variation (; ). A dendrogram of the closest Euclidean distances on the basis of the unweighted pair-group method using arithmetic averages was constructed to check the affinities revealed in the discrimination analysis (; ). The discrimination analysis was calculated on the characters obtained from the ratios, except for the ratio of cone diameter to the number of cone scale rows (CD/CSR), because of the stable characteristic cone scale rows. All the above-mentioned statistical analyses were performed using STATISTICA 8 (StatSoft Poland, Tulsa, USA).The geographical distances between the populations were calculated using MapInfo (Pitney Bowes Software Inc., New York, USA). The geographical structure of the populations was further analysed using Monmonier's maximum difference algorithm, implemented in BARRIER 2.2 software (). This analysis reveals discontinuities in morphological differentiation in relation to the populations' geographical arrangement. The barriers can be interpreted as breaks between adjacent populations in their morphological construction.A K-mean analysis was performed on the calculated characters. This analysis reveals the number of K-clusters, which optimally illustrates the differentiation between populations. A classification matrix was constructed to show the percentage of individuals from each population that could be properly included in particular groups and to assess the number of individuals that fell into another K-group (). […]

Pipeline specifications

Software tools WinSEEDLE, Statistica
Applications Miscellaneous, Macroscope & basic digital camera imaging
Organisms Meleagris gallopavo