Historical range contraction, and not taxonomy, explains the contemporary genetic structure of the Australian tree Acacia dealbata Link
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.
KeywordsBiological invasions Fabaceae Genetic diversity and structure Microsatellites Tree invasions
We thank M.J. Mathese and P.H. Du Preez for their assistance in the laboratory, L. Gallien for advice on statistical approaches, and C. Gairifo, J. Ndlovu, and J.R.U. Wilson for assistance with collecting and/or providing samples used in this study.
Funding for this study was provided by the DST-NRF Centre of Excellence for Invasion Biology and the Working for Water Programme through the collaborative research project “Integrated Management of invasive alien species in South Africa,” a Subcommittee B grant from Stellenbosch University (to JLR), and the Drakenstein Trust. Additional support was provided by the DST-NRF Centre of Excellence for Invasion Biology, Stellenbosch University, and the National Research Foundation of South Africa (grant 85417 to DMR).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Byrne M, Steane DA, Joseph L, Yeates DK, Jordan GJ, Crayn D, Aplin K, Cantrill DJ, Cook LG, Crisp MD, Keogh JS, Melville J, Moritz C, Porch N, Sniderman JMK, Sunnucks P, Weston PH (2011) Decline of a biome: evolution, contraction, fragmentation, extinction and invasion of the Australian mesic zone biota. J Biogeogr 38:1635–1656CrossRefGoogle Scholar
- Doyle J, Doyle J (1990) Isolation of plant DNA from fresh tissue. Focus 12:13–15Google Scholar
- Erst PJ (2017) Geographic Distance Matrix Generator (version 1.2.3). American Museum of Natural History, Center for Biodiversity and Conversation. http://biodiversityinformatics.amnh.org/open_source/gdmg/. Accessed 24 Jan 2017
- Guillemaud T, Broadhurst L, Legoff I, et al (2015) Development of 23 polymorphic microsatellite loci in invasive silver wattle, Acacia dealbata (Fabaceae). Appl Plant Sci 3:apps.1500018Google Scholar
- Jombart T (2015) An introduction to adegenet 2.0.0. http://adegenet.r-forge.r-project.org/files/tutorial-basics.pdf Assessed 12 Feb 2017
- Le Roux JJ, Richardson DM, Wilson JRU, Ndlovu J (2013) Human usage in the native range may determine future genetic structure of an invasion: insights from Acacia pycnantha. BMC Ecol 13(37)Google Scholar
- Leys M, Petit EJ, El-Bahloul Y, Liso C, Fournet S, Arnaud J-F (2014) Spatial genetic structure in Beta vulgaris subsp. maritime and Beta macrocarpa reveals the effect of contrasting mating system, influence of marine currents, and footprints of postglacial recolonization routes. Ecol Evol 4:1828–1852CrossRefPubMedPubMedCentralGoogle Scholar
- Mahalanobis PC (1936) On the generalized distance in statistics. Proceedings of the National Institute of Sciences India 12:49–55Google Scholar
- Oksanen J, Blanchet FG, Friendly M, et al (2017) vegan: community ecology package. R package version 2.4–2. https://CRAN.R-project.org/package=vegan
- Peel B (2010) Rainforest restoration manual for south-eastern Australia. CSIRO PublishingGoogle Scholar
- Poynton RJ (2009) Tree planting in southern Africa. Other genera, vol 3. Department of Agriculture, Forestry and Fisheries, Pretoria, South AfricaGoogle Scholar
- Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:170–181Google Scholar
- Pyšek P, Hulme PE, Meyerson LA, et al (2013) Hitting the right target: taxonomic challenges for, and of, plant invasions. AoB PLANTS 5:plt042Google Scholar
- R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
- Tasmanian Landcare Group (2013) Restoring our landscape—a basic revegetation guide for fire-affected areas of Tasmania. http://www.nrmsouth.org.au/wp-content/uploads/2014/11/Restoring-our-Landscape-bushfire-recovery-2013-Tasman-and-NRM-South.pdf. Accessed 15 Mar 2017
- Weir BS (1996) Genetic data analysis II. Sinauer Associates, SunderlandGoogle Scholar