Genomic diversity guides conservation strategies among rare terrestrial orchid species when taxonomy remains uncertain

Abstract

Background and aims: Species are often used as the unit for conservation, but may not be suitable for species complexes where taxa are difficult to distinguish. Under such circumstances, it may be more appropriate to consider species groups or populations as evolutionarily significant units (ESUs). A population genomic approach was employed to investigate the diversity within and among closely related species to create a more robust, lineage-specific conservation strategy for a nationally endangered terrestrial orchid and its relatives from south-eastern Australia.

Methods: Four putative species were sampled from a total of 16 populations in the Victorian Volcanic Plain (VVP) bioregion and one population of a sub-alpine outgroup in south-eastern Australia. Morphological measurements were taken in situ along with leaf material for genotyping by sequencing (GBS) and microsatellite analyses.

Key results: Species could not be differentiated using morphological measurements. Microsatellite and GBS markers confirmed the outgroup as distinct, but only GBS markers provided resolution of population genetic structure. The nationally endangered Diuris basaltica was indistinguishable from two related species ( D. chryseopsis and D. behrii ), while the state-protected D. gregaria showed genomic differentiation.

Conclusions: Genomic diversity identified among the four Diuris species suggests that conservation of this taxonomically complex group will be best served by considering them as one ESU rather than separately aligned with species as currently recognized. This approach will maximize evolutionary potential among all species during increased isolation and environmental change. The methods used here can be applied generally to conserve evolutionary processes for groups where taxonomic uncertainty hinders the use of species as conservation units.

Keywords: Diuris; Orchidaceae; genotyping by sequencing (GBS); microsatellite markers; next-generation sequencing; population genomics.

Fig. 1.

Diuris populations of four species sampled in the Victorian Volcanic Plain (VVP) and an outgroup sampled from the alpine region. Historical distributions for the four VVP species were generated from the Atlas of Living Australia (ala.org.au).

Fig. 2.

Principal co-ordinates analyses for (A) morphology, (B) microsatellites, (C) genotyping by sequencing (GBS) ‘stringent’ data set and (D) GBS ‘relaxed’ data set. Colours represent putative species, and the shapes within colour groups represent different populations. Inset in (D) PCoA of the ‘relaxed’ data set with all 17 populations (including D. monticola).

Fig. 3.

Phylogenetic representation of the ‘relaxed’ data set using genetic distance. Unrooted dendrogram calculated using PCoA on the ‘stringent’ data set. The inset shows the F_ST dendrogram from the ‘stringent’ data set. Some populations were removed from the F_ST dendrogram because the populations were either too small or had too much missing data.

Fig. 4.

A species complex tree obtained from a coalescent MCMC analysis of 97 individuals using SNAPP and BEAST on the ‘stringent’ data set. Support values are given for clades present in > 80 % of the iterations. Branch lengths are interpreted as relative time. Branches are identified by population abbreviations given in Table 1. Species are represented by colours.

Fig. 5.

Bayesian clustering analysis of the ‘stringent’ data set using (A) two genetic clusters (k = 2) and three genetic clusters (k = 3) in STRUCTURE. Each column (individual) is assigned a specific suite of colours corresponding to the membership coefficient. Populations are labelled according to Table 1. The line above STRUCTURE figures represents the five species (from left to right D. basaltica, D. gregaria, D. behrii, D. chryseopsis and D. monticola). (B) The posterior probability of the STRUCTURE analysis in geographical space. Genetic clusters are averaged across populations, and genetic cluster are analogous to Fig. 4A.

Fig. 6.

Results from correlation analyses between the ‘relaxed’ data set [genotyping by sequencing (GBS)] and morphology for the Diuris species. Genetic distance vs. morphological distance along with a best-fit line from a GLM model, with D. monticola (A) where the grouping on the right contains the individuals from the outgroup and (B) without.