411
The genetic differentiation among Argentinean natural populations of A. angustifolia was examined by an analysis of molecular variance (AMOVA, GenAlEx 6.3
software, Peakall and Smouse 2006). Most of the genetic variation (91%) was distributed within populations, showing moderate and significant genetic differentiation among them (Φ PT = 0.090, p ≤ 0.001; Inza et al. 2018). This is in accordance to
the expected values for gymnosperms and long-lived perennials, woody, and outcrossing species (Hamrick et al. 1992; Nybom 2004). A moderate level of genetic
differentiation might be associated with short distances of seed dispersion (Nybom
2004). On the other hand, while we have expected some restriction of pollen flow
due to forest fragmentation in Argentina (Inza et al. 2018), this was not clearly evidenced because the estimated historical gene flow (Nm = 3.5, Crow and Aoki 1984)
was above from minimum proposed (Nm = 1) to reduce genetic structuring by drift
(Young et al. 1996). Besides, this value agreed with gene flow estimations from
similar studies in Brazil (Auler et al. 2002; Bittencourt and Sebbenn 2009; Stefenon
et al. 2009).
The differentiation among Argentinean populations was lower than that exhibited among Brazilian populations, both estimated with AFLP (10% by Stefenon
et al. 2007; 19% and 12% by Ferreira de Souza et al. 2009) and with SSRs (13% by
Stefenon et al. 2007). These differences could be explained by the geographical
distances between the populations surveyed, which are quite larger in Brazil. Even
though Bekessy et al. (2002) studied a similar range (~150 km) of A. araucana
populations throughout Chile and Argentina with RAPDs, they observed a higher
genetic differentiation (12.8%). However, clustering of the populations at both sides
of the Andes may explain this result, acting the mountain range, instead of the distance, as a gene flow barrier.
Furthermore, an analysis of the genetic structure among the Argentinean populations was performed (Inza et al. 2018) by means of pairwise population differentiation (F ST indexes), a dendrogram of Nei’s genetic distances among populations
(Rohlf 1998, data no shown, see Inza et al. 2018) and a Bayesian cluster analysis
(Pritchard et al. 2000; Falush et al. 2007). The Bayesian analysis allowed us to recognize a structure of six genetic clusters (Fig. 15.10). As expected, the populations
that registered more clusters in their composition were the nearest to Brazil and less
disturbed, which have also shown the higher diversity (Manuel Belgrano natural
forest and Gramado). On the other hand, the highly logged populations showed
fewer clusters but with different composition. Although this could be associated to
a genetic erosion process during migration events from Brazil, further studies
including Brazilian populations should be performed to acquire comprehensive
knowledge (Inza et al. 2018). All these results are evidence of a genetic structure
according to geographical location and logging history. Besides, in agreement with
studies of Brazilian A. angustifolia populations, genetic differentiation increased
with the geographical distance between them (Stefenon et al. 2007; Ferreira de
Souza et al. 2009).
15 Paraná Pine (Araucaria angustifolia): The Most Planted Native Forest Tree…
The genetic differentiation among Argentinean natural populations of A. angustifolia was examined by an analysis of molecular variance (AMOVA, GenAlEx 6.3
software, Peakall and Smouse 2006). Most of the genetic variation (91%) was distributed within populations, showing moderate and significant genetic differentiation among them (Φ PT = 0.090, p ≤ 0.001; Inza et al. 2018). This is in accordance to
the expected values for gymnosperms and long-lived perennials, woody, and outcrossing species (Hamrick et al. 1992; Nybom 2004). A moderate level of genetic
differentiation might be associated with short distances of seed dispersion (Nybom
2004). On the other hand, while we have expected some restriction of pollen flow
due to forest fragmentation in Argentina (Inza et al. 2018), this was not clearly evidenced because the estimated historical gene flow (Nm = 3.5, Crow and Aoki 1984)
was above from minimum proposed (Nm = 1) to reduce genetic structuring by drift
(Young et al. 1996). Besides, this value agreed with gene flow estimations from
similar studies in Brazil (Auler et al. 2002; Bittencourt and Sebbenn 2009; Stefenon
et al. 2009).
The differentiation among Argentinean populations was lower than that exhibited among Brazilian populations, both estimated with AFLP (10% by Stefenon
et al. 2007; 19% and 12% by Ferreira de Souza et al. 2009) and with SSRs (13% by
Stefenon et al. 2007). These differences could be explained by the geographical
distances between the populations surveyed, which are quite larger in Brazil. Even
though Bekessy et al. (2002) studied a similar range (~150 km) of A. araucana
populations throughout Chile and Argentina with RAPDs, they observed a higher
genetic differentiation (12.8%). However, clustering of the populations at both sides
of the Andes may explain this result, acting the mountain range, instead of the distance, as a gene flow barrier.
Furthermore, an analysis of the genetic structure among the Argentinean populations was performed (Inza et al. 2018) by means of pairwise population differentiation (F ST indexes), a dendrogram of Nei’s genetic distances among populations
(Rohlf 1998, data no shown, see Inza et al. 2018) and a Bayesian cluster analysis
(Pritchard et al. 2000; Falush et al. 2007). The Bayesian analysis allowed us to recognize a structure of six genetic clusters (Fig. 15.10). As expected, the populations
that registered more clusters in their composition were the nearest to Brazil and less
disturbed, which have also shown the higher diversity (Manuel Belgrano natural
forest and Gramado). On the other hand, the highly logged populations showed
fewer clusters but with different composition. Although this could be associated to
a genetic erosion process during migration events from Brazil, further studies
including Brazilian populations should be performed to acquire comprehensive
knowledge (Inza et al. 2018). All these results are evidence of a genetic structure
according to geographical location and logging history. Besides, in agreement with
studies of Brazilian A. angustifolia populations, genetic differentiation increased
with the geographical distance between them (Stefenon et al. 2007; Ferreira de
Souza et al. 2009).
15 Paraná Pine (Araucaria angustifolia): The Most Planted Native Forest Tree…