Historical range contraction, and not taxonomy, explains the contemporary genetic structure of the Australian tree Acacia dealbata Link

Abstract

Irrespective of its causes, strong population genetic structure indicates a lack of gene flow. Understanding the processes that underlie such structure, and the spatial patterns it causes, is valuable for conservation efforts such as restoration. On the other hand, when a species is invasive outside its native range, such information can aid management in the non-native range. Here we explored the genetic characteristics of the Australian tree Acacia dealbata in its native range. Two subspecies of A. dealbata have previously been described based on morphology and environmental requirements, but recent phylogeographic data raised questions regarding the validity of this taxonomic subdivision. The species has been widely planted within and outside its native Australian range and is also a highly successful invasive species in many parts of the world. We employed microsatellite markers to investigate the population genetic diversity and structure among 42 A. dealbata populations from across the species' native range. We also tested whether environmental variables purportedly relevant for the putative separation of subspecies are linked with population genetic differentiation. We found no relationship between population genetic structure of A. dealbata in Australia and these environmental features. Rather, we identified two geographically distinct genetic clusters that corresponded with populations in the northeastern part of mainland Australia, and the southern mainland and Tasmanian range of the species. Our results do not support the taxonomic subdivision of the species into two distinct subspecies based on environmental features. We therefore assume that the observed morphological differences between the putative subspecies are plastic phenotypic responses. This study provides population genetic information that will be useful for the conservation of the species within Australia as well as to better understand the invasion dynamics of A. dealbata.

Ghosts from the past: even comprehensive sampling of the native range may not be enough to unravel the introduction history of invasive species—the case of Acacia dealbata invasions in South Africa

“…We amplified ten nuclear microsatellites in two multiplex PCR reactions (for further details see Hirsch et al., and Appendix S1). All PCR reactions were carried out in a volume of 10 μl containing 2 μl template DNA (100ng/μl), 5 μl KAPA2G Fast Multiplex Mix (Kapa Biosystems, Cape Town, South Africa), 1 μl primer mix of the corresponding multiplex set (Thermo Scientific, Waltham, Massachusetts, USA), 2 μl purified H 2 O. PCR cycling was performed in a MultiGene OptiMax thermal cycler (Labnet International, Edison, New Jersey, USA) with an initial denaturation of 95°C for 3 min, followed by 30 cycles of denaturation at 95°C for 15 sec, annealing at 60°C for 30 sec, elongation at 72°C for 30 sec, and a final elongation at 72°C for 10 min.…”

“…These were combined with the native range genotypes from Hirsch et al. (), resulting in a final dataset of 1057 samples, representing 42 native Australian and 18 South African populations (Table ).…”

“…To assess whether genetic diversity indices (i.e., A R , H O, and H E ) differed between the native and invasive populations of A. dealbata , we carried out analyses of variance (ANOVA) in R (R Core Team, ). For these analyses, we considered the previously described population genetic structure among the native populations (Hirsch et al., ). That is, native populations were assigned to two groups: (1) ‘NAT1’ (corresponding to Cluster 1 in Hirsch et al.…”

“…That is, native populations were assigned to two groups: (1) ‘NAT1’ (corresponding to Cluster 1 in Hirsch et al. (), containing the majority of Australian mainland populations); and (2) ‘NAT2’ (i.e., Cluster 2 in Hirsch et al. (), containing all Tasmanian and some populations from the southernmost Australian mainland) (Table ).…”

“…We used microsatellite data from 18 South African and a previously generated dataset for 42 native A. dealbata populations which were sampled across the species’ entire native range (Hirsch et al., ) with the aim of: (1) gaining information on the genetic diversity and structure present in A. dealbata 's invasive range in South Africa; and (2) shedding light on the introduction/invasion history of A. dealbata in South Africa by testing our data against different introduction scenarios using Approximate Bayesian Computation.…”