Absence of geographical structure of morphological variation in Juniperus oxycedrus L. subsp. oxycedrus in the Balkan Peninsula

Abstract

We examined leaf and mature seed cone variation of Juniperus oxycedrus L. subsp. oxycedrus in 12 natural populations across the species range in the Balkan Peninsula. We measured 10 morphological traits from a minimum of 100 leaves in each of 190 individuals, and two morphological traits from 30-50 seed cones in each of 94 females. High phenotypic variation was found, but no geographical structure or cline across populations was detected for any of the studied traits. Mean values of comparable leaf and cone morphological traits did not differ considerably from values reported elsewhere. Gender dimorphism in leaf morphology was detected, but it was not distributed uniformly throughout the studied area. An ANOVA model with both nested and crossed effects revealed that the largest proportion of the total variation was, as expected, contained within populations, partly as among-tree variation (18-47%, depending on the trait) and partly as within-tree variation (33-77%), which was remarkably high. Gender dimorphism explained only 0-3% of the total variation. Differences among populations (2-23%) were significant for all studied traits except one; however, PCA showed no clear geographical differentiation of the studied populations. This lack of phylogeographical structure may be the consequence of repeatedly occurring colonisation-retreat scenarios and suggests the existence of several small refugial populations scattered over a large part of the Balkan Peninsula in the Pleistocene. Further research including palaeobotanical and molecular genetic studies will be needed to better understand the forces that shaped current variation patterns of J. oxycedrus L. subsp. oxycedrus in the Balkan Peninsula.

Seasonal Variation and Resin Composition in the Andean Tree Austrocedrus chilensis

“…Principal Component Analysis was carried out to explain the relation of the p = 12 original compounds (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12) in r < p components. It allows an optimal representation in a smaller dimensional space (r) of the multivariate problem (p).…”

“…Multivariate statistical analysis is used as a valuable tool for biometric analysis of plant populations [8][9][10]. It is extensively employed to detect differences in chemical composition that can be associated to parameters such as age, sex and mating status [11] to discriminate between sample origin in medicinal and food plants [12] and archaeological samples [13].…”

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

“…Moreover, Brus et al (2011) on their study on morphological variation of Juniperus oxycedrus using 12 characters from leaves and fruit noted that morphological variation among populations did not show any geographical differentiation. Results of these studies indicated that geographical separation did not play as a Science Publications AJABS driving force for phenotypic variability.…”

Fruit and seedling diversity among sweet chestnut (Castanea sativa Mill.) populations in Turkey

“…In many fields of plant sciences, morphological information's are still very important (Douaihy et al 2012; such as different taxon delimitation (Mac-Key 1988;Poljak et al 2014a;Sękiewicz et al 2016), population variability (Brus et al 2011(Brus et al , 2016Douaihy et al 2012;Poljak et al , 2014aPoljak et al , 2018Zebec et al 2014Zebec et al , 2015, cultivar characterization (Ertan 2007;Ertan et al 2007;Poljak et al 2016) and selection (Polat and Özkaya 2005;Solar et al 2001Solar et al , 2005, morphological and physiological seed characterization (Powell 2010;Yilmaz and Yüksel 2014;Drvodelić et al 2015;Daneshvar et al 2016), and trends in leaf morphology regarding the branch position and patterns of crown plasticity (Bruschi et al 2003;Bednorz 2006;Pol-jak et al 2014b). The studies of European and Turkish sweet chestnut populations revealed high morphological variation within populations and low differentiation between populations (Villani et al 1991;Pereira-Lorenzo et al 1996;Serdar 1999;Podjavorsek et al 1999;Serdar and Soylu 1999;Solar et al 2001Solar et al , 2005Miguelez et al 2004;Bolvanský and Užík 2005;Ertan 2007;Idžojtić et al 2009;Mujić et al 2010;.…”