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(Fagus Sylvatica L.) Provenances Grown in Common Garden Experiments

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(Fagus Sylvatica L.) Provenances Grown in Common Garden Experiments Stojnic et. al.·Silvae Genetica (2015) 64-4, 133-147 Provenance by site interaction and stability analysis of European beech (Fagus sylvatica L.) provenances grown in common garden experiments By S. STOJNIC´1),*), S. ORLOVIC´1), D. BALLIAN2), M. IVANKOVIC´3), M. ŠIJAC˘IC´-NIKOLIC´4), A. PILIPOVIC´1), S. BOGDAN5), S. KVESIC´2), M. MATARUGA6), V. DANIC˘IC´6), B. CVJETKOVIC´6), D. MILJKOVIC´7) and G. VON WUEHLISCH8) (Received 24th February 2015) Abstract variance showed that effects of provenance, site, and P S interaction are highly significant Fifteen provenances of European beech ϫ (p<0.001) in both age groups. Linear regression ( L.) were evaluated for stability Fagus sylvatica model evidenced that most of the provenances and adaptability by height growth at four test sites in Bosnia and Herzegovina (1), Croatia (1) had regression coefficients not significantly dif- and Serbia (2). Provenance trials were estab- ferent from unity (b=1.0), except for prove- lished in spring 2007 by planting 2- and 3-year- nances Sjeverni Dilj Caglinski (HR24) and old seedlings and arranged in a randomized Vranica-Bistrica (BA59). The partitioning of the complete block design. The data from seven 6- total sum of squares (SS) exhibited that the site year-old and eight 5-year-old provenances were effect was the predominant source of variation obtained in 2009 and analyzed separately. Fin- in both age groups of provenances (50.7% and lay and Wilkinson’s regression analysis and 38.5%, respectively). Additionally, regression Additive main effects and multiplicative inter- analysis explained 15.8% and 33.2% of prove- action model (AMMI model) were used to assess nance by site interaction terms, in provenances age six and five years, respectively, while the provenance by site interaction (PϫS) and to identify beech provenances that have high and AMMI analysis accounted for 62.2% and 78.7% stable performance in different environments, in PϫS interaction. The results of AMMI at the juvenile stage of development. Analysis of showed that the first principal component (PC1) was statistically significant in both age groups. Adaptability and stability of provenances to the test sites were estimated with AMMI1 and 1) University of Novi Sad, Institute of Lowland Forestry AMMI2 biplots. Provenance Sjeverni Dilj and Environment, Antona C˘ehova 13, 21000 Novi Sad, Caglinski (HR24) showed constant performance Republic of Serbia. over tested sites, characterizing with above- 2) University of Sarajevo, Faculty of Forestry, Zagrebac˘ka average height growth at low yielding environ- 20, 78000 Sarajevo, Bosnia and Herzegovina. ments. Provenances HR25 and BA61 showed 3 ) Forest Research Institute, Cvjetno naselje 41, 10450 the opposite type of adaptation, being adapted Jastrebarsko, Croatia. to high yielding sites. Provenance Valkonya 4) University of Belgrade, Faculty of Forestry, Kneza Višeslava 1, 11000 Belgrade, Republic of Serbia. (HU42) was characterized by IPCA1 score close 5) University of Zagreb, Faculty of Forestry, Svetošumska to zero and above average mean height growth, cesta 25, 10000 Zagreb, Croatia. suggesting general adaptation to the tested 6) University of Banja Luka, Faculty of Forestry, Bulevar environments. The implication of PϫS was dis- vojvode Stepe Stepanovića 75a, 78000 Banja Luka, cussed in light of impact of climate change on Bosnia and Herzegovina. beech and selection of most suitable prove- 7) University of Belgrade, Institute for Biological nances for future reforestation programs. Research Siniša Stankovic´, Department of Evolution- ary Biology, Bulevar Despota Stefana 132, 11000 Bel- European beech, provenance trial, prove- grade, Republic of Serbia. Key words: nance site interaction, linear regression model, 8) Thünen-Institute for Forest Genetics, Grosshansdorf, ϫ Germany, Sieker Landstr. 2, D-22927 Großhansdorf, AMMI analysis, biplot. Germany. *) Corresponding author: SRD– AN STOJNIC´. University of Novi Sad, Institute of Lowland Forestry and Environ- Introduction ment, Antona C˘ehova 13d, 21000 Novi Sad, Serbia. Phone: +38121540382, Fax: +38121540385. E-Mail: European beech (Fagus sylvatica L.) is one of [email protected]. the main tree species in Europe. Covering an Silvae Genetica 64, 4 (2015) 133 DOI:10.1515/sg-2015-0013 edited by Thünen Institute of Forest Genetics Stojnic et. al.·Silvae Genetica (2015) 64-4, 133-147 area of approximately 14 million ha (VON region (20 provenances). Such an approach pro- WUEHLISCH, 2010a), beech is ecologically and vided the opportunity to compare performance economically one of the most important species in the field trials among the Balkan prove- for European forestry. Due to its known sensi- nances and provenances originating from the tivity to drought, beech is threatened by climate core of Europe. Due to the fact that experiments change. It is assumed that most endangered were established across several sites, it also beech populations are those at the southern provided possibility to assess genotype by envi- limit of the species distribution (JUMP et al., ronment interaction (GϫE). The magnitude of 2006). On the other hand, in large parts of tem- GϫE interaction is essential in a tree breeding perate and boreal regions, natural conifer programs for decision making about testing and forests (e.g. Norway spruce stands) are sup- deployment strategies (PSWARAYI et al., 1997; posed to be replaced with the more competitive ZAS et al., 2004). Thus, the key objective in European beech forests (BUGMANN, 1997; studies of GϫE interaction is the assessment of AMMER et al., 2008). stability and adaptability of provenances against a series of stressors that prevail at Provenance trials may provide a good basis given environments. for evaluation of genetic diversity and potential of various provenances to adjust to given cli- Analysis of variance (ANOVA) is certainly the mate conditions (STOJNIC et al., 2013a). Recent most frequently used method for studying GϫE studies demonstrated that beech populations interaction, besides regression models and mul- from Southern Europe might be potential tar- tivariate techniques (HANNRUP et al., 2008). It is gets in the search for drought-resistant eco- primarily used in determination and testing of types (THIEL et al., 2014). For example, ROBSON sources of variability (e.g. genotype, environ- et al. (2013) showed that southern provenances ment, GϫE interaction). However ANOVA from Spain and Bulgaria maintained high rates allows adequate interpretation of main effects, of assimilation even in mid-summer, whereas it does not offer the insight into the response of provenances from cooler sites in central and the genotypes in the non-additive (interaction) north Europe demonstrated reduced photosyn- term (SHAFII and PRICE, 1998; ZOBEL et al., thetic capacity under such conditions. Similarly, 1988). In other words, ANOVA does not provide studying physiological differences of beech information about the performances of single provenances exposed to drought stress, DOUNAVI genotype against environmental variations et al. (2016) reported that Greek population (ABBOTT et al., 2012). Thus, it is necessary to showed better adaptability to future environ- apply other methods to identify interaction rela- mental conditions in comparison with prove- tionships. nances from central Europe. Linear regression analysis was reviewed by International beech provenance trials were numerous authors (FINLAY and WILKINSON, established in five series in 1986, ‘87, ‘89, ‘95 1963; EBERHART and RUSSELL, 1966; PERKINS and ‘98 (VON WUEHLISCH, 2004). Unfortunately, and JINKS, 1968, etc.). The method is based on within these series, the provenances from the the regression of genotypic means against the central Balkan region (Bosnia and Herzegovina, mean values of an environmental effect at each and Serbia) were omitted, while the prove- site (environmental index), and could be used nances from Croatia were poorly represented. for the identification of good general performers Due to the expected genetic variation in this across a wide range of sites (FINLAY and WILKIN- region, new trial series were established in SON, 1963; MATHESON and RAYMOND, 1986). This order to cover this area (VON WUEHLISCH, 2004). approach is widely used in plant breeding, The most recent series of international beech although the analysis has several limitations. provenance trials were established in 2007. For CROSSA (1990) provided a comprehensive review this purpose, seven provenance trials were of statistical and biological limitations of regres- established across a range of environments: sion analysis in studying of GϫE interaction. Bosnia and Herzegovina, Croatia, Italy, Ger- many (2) and Serbia (2), involving 32 prove- The most commonly used multivariate tech- nances from eight countries (VON WUEHLISCH et nique is additive main effects and multiplica- al., 2010b). Contrary to previously established tive interaction method (AMMI) (BOSE et al., series, this was the first time that the majority 2014a). AMMI analysis integrates analysis of of the provenances originated from the Balkan variance and principal components analysis 134 DOI:10.1515/sg-2015-0013 edited by Thünen Institute of Forest Genetics Stojnic et. al.·Silvae Genetica (2015) 64-4, 133-147 (PCA) into a unified approach (GAUCH, 1988). Material and methods AMMI has several models: AMMI0 which esti- Provenance by site interaction (P S) of 15 mates additive main effects of genotypes and ϫ European beech ( L.) prove- environments and does not include
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