Conservation Genetics

, Volume 17, Issue 4, pp 761–774 | Cite as

How many conservation units are there for the endangered grassland earless dragons?

  • Emma Carlson
  • Anna J. MacDonald
  • Aaron Adamack
  • Tim McGrath
  • Lisa I. Doucette
  • William S. Osborne
  • Bernd Gruber
  • Stephen D. SarreEmail author
Research Article


Species are the most commonly recognised unit for conservation management, yet significant variation can exist below the level of taxonomic recognition and there is a lack of consensus around how a species might be defined. This definition has particular relevance when species designations are used to apportion conservation effort and when definitions might be made through legislation. Here, we use microsatellite DNA analyses to test the proposition that the last remaining populations of the endangered grassland earless dragon (Tympanocryptis pinguicolla) harbour substantial cryptic genetic variation. Our study provides strong evidence that long historical isolation and the recent impacts of urbanization, have led to genetic differentiation in microsatellite DNA allele frequencies and high numbers of private alleles among three genetic clusters. This differentiation is partially concordant with previous mitochondrial DNA analyses, which show the two regions (Canberra and Monaro) where this species exists, to be reciprocally monophyletic, but differs through the identification of a third genetic cluster that splits a northern Canberra cluster from that of southern Canberra. Our data also identify a stark contrast in population genetic structure between clusters such that high levels of genetic structure are evident in the highly urbanised Canberra region but not in the largely rural Monaro region. We conclude that this species, like many reptiles, harbours considerable cryptic variation and currently comprises three distinct and discrete units. These units could be classified as separate species for the purpose of conservation under the relevant Australian and international Acts drawing management appropriate to that status.


Conservation units Evolutionary significant units Microsatellite DNA Temperate grasslands 



We thank all the landholders for access to their property. We also thank Murray Evans and a large number of volunteers for the collection of the tissue samples and Alica Tschierschke for producing Fig. 2. This project was partly funded by ARC Grants LP0776987 and LP110200029 and industry partners the Canberra International Airport and Environment ACT. All aspects of this study were conducted under the University of Canberra’s Animal Ethics permit numbers CEAE 05–11, CEAE 07–05, CEAE 08–18, and CEAE 11-14. Trapping was conducted under ACT Government Territory and Municipal Services Licenses LT2006241, LT2008290, LT2009383, LT2010454, LT2012617, LT2014770 and National Parks and Wildlife Act 1974 Section 132c (Clause 23) Scientific Licences SL100290, SL100756 and SL101118.

Supplementary material

10592_2016_819_MOESM1_ESM.pdf (342 kb)
Supplementary material 1 (PDF 341 kb) Supplementary Fig. 1: Estimates of average pairwise relatedness within Canberra and Monaro sampling sites for T. pinguicolla. Sites with 2 individuals or less are not included. A value of 0.5 indicates a parent-sibling or full sibling relationship, 0.25 indicates half-siblings and below 0.125 indicates unrelated individuals (Queller and Goodnight 1989). Supplementary Fig. 2: STRUCTURE analysis pathway for the admixed with popinfo STRUCTURE runs. The initial data set consisted of 190 individuals. Following each STRUCTURE run, STRUCTURE harvester was run on the results to identify the number of likely clusters. We then examined plots of individual cluster assignments for consistency across the 20 replicate runs and spatial plots of cluster assignments for genographic consistency. Once the number of clusters had been determined, individuals were placed into sub-cluster and the analysis was repeated for the sub-cluster until no further sub-clustering was detected. QNR/Pop. = Queanbeyan Nature Reserve/. Supplementary Fig. 3: STRUCTURE analysis pathway for the no admixture without popinfo STRUCTURE runs. The initial data set consisted of 190 individuals. Following each STRUCTURE run, STRUCTURE harvester was run on the results to identify the number of likely clusters. We then examined plots of individual cluster assignments for consistency across the 20 replicate runs and spatial plots of cluster assignments for genographic consistency. Once the number of clusters had been determined, individuals were placed into sub-cluster and the analysis was repeated for the sub-cluster until no further sub-clustering was detected
10592_2016_819_MOESM2_ESM.pdf (15 kb)
Supplementary material 2 (PDF 14 kb) Supplementary Fig. 4: Supplemental Figure XXX Deviance information criterion (DIC) plot for each replicate of K (replicates = 20) for K = 2 to 10 (grey points). Durand et al. (2009) recommend examining the DIC values of the lowest 10 to 20 % of replicate values for each K in order to identify the ideal number of clusters as the K value at which DIC values plateau. The average value of the lowest 20 % of DIC values for each K is indicated using red points


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Institute for Applied EcologyUniversity of CanberraBruceAustralia

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