78
determined with different molecular markers (Marchelli and Gallo 2004, 2006;
Azpilicueta et al. 2013; Marchelli et al. 2017). More genetic diversity implies not
only more importance for conservation purposes but also for growth performance.
Both trials together occupied an area of 0.8 ha and originally contained 1188 trees.
Best forestry phenotypes were mass-selected regardless of the trial at the ages of 10
and 12 years, and two thinning interventions were subsequently carried out in 2009
and 2011, leaving almost 400 trees. Seed production begun in 2016. Aiming to perform a genetic selection, the trees were genotyped by means of 11 microsatellite
markers in order to build a matrix of genomic relationships (Pastorino et al. 2016).
A preliminary analysis showed in many cases a relationship closer than the assumed
between half-sibs among trees of the same family (data not published). This analysis also allowed detecting the presence of five natural hybrids among the selected
trees, which must be cut down to maintain the purity of the stand.
3.7 Definition of Genetic Zones Based on Genetic Markers
Appropriate measures for forest management and conservation demand the identification of genetically homogeneous zones across the distribution of each species to
steer germplasm transfer within and between areas, for example, in restauration and
reforestation activities (Newton et al. 1999). Genetic zones are defined as genetically homogeneous regions within which propagation material can be transferred,
minimizing the risk of introducing changes in the genetic structure (Honjo et al.
2009; Pastorino and Gallo 2009). Therefore, the identification of genetic zones is
relevant for the definition of management units, because they reflect a population of
interbreeding trees adapted to geographically restricted areas (Azpilicueta
et al. 2013).
A first regional approach for N. alpina was done by Vergara (2000), who defined
14 provenance regions for the entire natural range (Chile and Argentina). This definition was predominantly based on climatic and geographic information and only to
minor extent on morphological characterization of the individuals of several natural
populations. The 11 provenance regions identified for the Chilean forests have a
clear practical importance for management and conservation programmes (Gutiérrez
2003). By contrast, the three main provenance regions identified for the Argentinean
forests are less satisfactory, considering the high fragmentation and spatial heterogeneity of these forests. Therefore, a more specific definition was necessary.
Molecular markers are useful tools for defining genetic zones, with better definitions being obtained by combining different genetic markers (e.g. Bucci et al. 2007).
Therefore, a definition of genetic zones for N. alpina was done by combining
genetic diversity at maternal inherited chloroplast DNA (Marchelli and Gallo 2006)
with nuclear genetic variation detected with isozymes (Marchelli and Gallo 2004)
and microsatellites (Azpilicueta et al. 2013). Bayesian clustering analyses (BAPS,
Corander et al. 2008) identified five groups among Argentinean populations
(Azpilicueta et al. 2013): three of them compound each by a unique peripheral population, another represented by marginal populations towards the east and northwest
P. Marchelli et al.
determined with different molecular markers (Marchelli and Gallo 2004, 2006;
Azpilicueta et al. 2013; Marchelli et al. 2017). More genetic diversity implies not
only more importance for conservation purposes but also for growth performance.
Both trials together occupied an area of 0.8 ha and originally contained 1188 trees.
Best forestry phenotypes were mass-selected regardless of the trial at the ages of 10
and 12 years, and two thinning interventions were subsequently carried out in 2009
and 2011, leaving almost 400 trees. Seed production begun in 2016. Aiming to perform a genetic selection, the trees were genotyped by means of 11 microsatellite
markers in order to build a matrix of genomic relationships (Pastorino et al. 2016).
A preliminary analysis showed in many cases a relationship closer than the assumed
between half-sibs among trees of the same family (data not published). This analysis also allowed detecting the presence of five natural hybrids among the selected
trees, which must be cut down to maintain the purity of the stand.
3.7 Definition of Genetic Zones Based on Genetic Markers
Appropriate measures for forest management and conservation demand the identification of genetically homogeneous zones across the distribution of each species to
steer germplasm transfer within and between areas, for example, in restauration and
reforestation activities (Newton et al. 1999). Genetic zones are defined as genetically homogeneous regions within which propagation material can be transferred,
minimizing the risk of introducing changes in the genetic structure (Honjo et al.
2009; Pastorino and Gallo 2009). Therefore, the identification of genetic zones is
relevant for the definition of management units, because they reflect a population of
interbreeding trees adapted to geographically restricted areas (Azpilicueta
et al. 2013).
A first regional approach for N. alpina was done by Vergara (2000), who defined
14 provenance regions for the entire natural range (Chile and Argentina). This definition was predominantly based on climatic and geographic information and only to
minor extent on morphological characterization of the individuals of several natural
populations. The 11 provenance regions identified for the Chilean forests have a
clear practical importance for management and conservation programmes (Gutiérrez
2003). By contrast, the three main provenance regions identified for the Argentinean
forests are less satisfactory, considering the high fragmentation and spatial heterogeneity of these forests. Therefore, a more specific definition was necessary.
Molecular markers are useful tools for defining genetic zones, with better definitions being obtained by combining different genetic markers (e.g. Bucci et al. 2007).
Therefore, a definition of genetic zones for N. alpina was done by combining
genetic diversity at maternal inherited chloroplast DNA (Marchelli and Gallo 2006)
with nuclear genetic variation detected with isozymes (Marchelli and Gallo 2004)
and microsatellites (Azpilicueta et al. 2013). Bayesian clustering analyses (BAPS,
Corander et al. 2008) identified five groups among Argentinean populations
(Azpilicueta et al. 2013): three of them compound each by a unique peripheral population, another represented by marginal populations towards the east and northwest
P. Marchelli et al.