154
verified as a cross between related individuals. Non-random pollination has been
shown in a marginal population (Pastorino and Gallo 2006), as well as evidence of
bi-parental inbreeding, although of a low degree, thanks to effective long-distance
pollen flow (Colabella et al. 2014). Thus, it seems inbreeding does not compromise
the population’s levels of genetic diversity.
Likewise, the occurrence of genetic drift processes in these steppe populations
has been shown by comparing the isozyme genetic pattern of neighboring forest
patches, for which demographic, adaptive, and external genetic flow processes must
be assumed to be the same (Pastorino and Gallo 2009). Not only a difference in the
proportion of genetic variants was verified between neighboring populations but
also the presence of exclusive allelic variants in one populations that are absent in
the other (Pastorino and Gallo 2002; Arana et al. 2010). Despite the proven genetic
drift, the species somehow manages to preserve a high genetic variation in these
marginal forests, which still represents an unexpected result.
The pattern of neutral genetic variation described above was the basis for delineating a map of genetic zones (GZ) which can serve as preliminary operational
genetic management units (OGMUs). We define a GZ as a group of natural populations with geographic continuity and genetic similarity shown with neutral genetic
markers. Based on the isozyme genotypes of 746 adult trees corresponding to 27
Argentine populations, a structure analysis was performed (Pastorino and Gallo
2009) by means of different analytical approaches (UPGMA cluster analysis and
PCoA main coordinates based on genetic distances; Bayesian inference with the
BAPS program; hierarchical analysis of variance with the SAMOVA program) and
also based on environmental features (i.e., precipitation, last glacial maximum, distance). Thus, five regional clusters of populations with similar genetic pools were
identified:
1. North GZ: composed of populations north of 41° 30′ S
2. Central GZ: composed of populations between 41° 30′ S and 42° 30′ S
3. South GZ: composed of populations south of 42° 30′ S
4. Glacier Edge GZ: composed of populations located outside the glaciated area,
close to the border of last glacial maximum, in the current ecotone, in the center
of the Argentine distribution of the species (there is a certain continuity of these
populations with the most conspicuous forest patches in the west)
5. Ancestral Distribution GZ: composed of populations located outside the glaciated area, extremely isolated, situated in the northern half of the Argentine distribution (there are several kilometers of discontinuity with the most conspicuous
forest patches in the west)
This zonation is based not only on data from the analyzed, relatively few markers
but rather on the inference of biological processes that affect the entire genome
(e.g., population extinctions, recolonization after glaciations, etc.), which allows
some extrapolation to populations not included in the sampling.
A. G. Aparicio and M. J. Pastorino
verified as a cross between related individuals. Non-random pollination has been
shown in a marginal population (Pastorino and Gallo 2006), as well as evidence of
bi-parental inbreeding, although of a low degree, thanks to effective long-distance
pollen flow (Colabella et al. 2014). Thus, it seems inbreeding does not compromise
the population’s levels of genetic diversity.
Likewise, the occurrence of genetic drift processes in these steppe populations
has been shown by comparing the isozyme genetic pattern of neighboring forest
patches, for which demographic, adaptive, and external genetic flow processes must
be assumed to be the same (Pastorino and Gallo 2009). Not only a difference in the
proportion of genetic variants was verified between neighboring populations but
also the presence of exclusive allelic variants in one populations that are absent in
the other (Pastorino and Gallo 2002; Arana et al. 2010). Despite the proven genetic
drift, the species somehow manages to preserve a high genetic variation in these
marginal forests, which still represents an unexpected result.
The pattern of neutral genetic variation described above was the basis for delineating a map of genetic zones (GZ) which can serve as preliminary operational
genetic management units (OGMUs). We define a GZ as a group of natural populations with geographic continuity and genetic similarity shown with neutral genetic
markers. Based on the isozyme genotypes of 746 adult trees corresponding to 27
Argentine populations, a structure analysis was performed (Pastorino and Gallo
2009) by means of different analytical approaches (UPGMA cluster analysis and
PCoA main coordinates based on genetic distances; Bayesian inference with the
BAPS program; hierarchical analysis of variance with the SAMOVA program) and
also based on environmental features (i.e., precipitation, last glacial maximum, distance). Thus, five regional clusters of populations with similar genetic pools were
identified:
1. North GZ: composed of populations north of 41° 30′ S
2. Central GZ: composed of populations between 41° 30′ S and 42° 30′ S
3. South GZ: composed of populations south of 42° 30′ S
4. Glacier Edge GZ: composed of populations located outside the glaciated area,
close to the border of last glacial maximum, in the current ecotone, in the center
of the Argentine distribution of the species (there is a certain continuity of these
populations with the most conspicuous forest patches in the west)
5. Ancestral Distribution GZ: composed of populations located outside the glaciated area, extremely isolated, situated in the northern half of the Argentine distribution (there are several kilometers of discontinuity with the most conspicuous
forest patches in the west)
This zonation is based not only on data from the analyzed, relatively few markers
but rather on the inference of biological processes that affect the entire genome
(e.g., population extinctions, recolonization after glaciations, etc.), which allows
some extrapolation to populations not included in the sampling.
A. G. Aparicio and M. J. Pastorino