Darwinia masonii and - epa.wa.gov.au · PDF fileC O M M E R C I A L – I N – C O N F I D E N C E DRN: QTE-006 Date: 30 June 2015 Document Title: MGX-101 Mt Gibson Conservation Genetics

FORESTRY | CROPPING | REHABILITATION | RENEWABLES | CARBON | WATER MANAGEMENT | MINING SERVICES

Darwinia masonii and Lepidosperma gibsonii Conservation Genetics Review

Prepared for Mt Gibson Mining

30 June 2015

C O M M E R C I A L – I N – C O N F I D E N C E DRN: QTE-006 Date: 30 June 2015 Document Title: MGX-101 Mt Gibson Conservation Genetics Review Page i

Verterra

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Dr Glenn Dale

Chief Technical Officer

30 June 2015

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Revision history

Revision Author/Reviewer Date Remarks1

0.1 G. Dale 16 April 2015 Working Draft

0.2 G. Dale 10 June 2015 Working Draft

0.3 G. Dale 19 June 2015 Draft for approval

1.0 G. Dale 30 June 2015 Final copy

1. Working draft; Draft for approval; Approved for release; Final copy.

Distribution list

Date Revision Name Title

15 June 2015 0.2 T. Collie Project director – Environment & approvals



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Table of contents

TABLE OF CONTENTS ....................................................................................................................................... III

LIST OF TABLES ................................................................................................................................................. V

LIST OF FIGURES ............................................................................................................................................... V

GLOSSARY ...................................................................................................................................................... VII

EXECUTIVE SUMMARY .................................................................................................................................... IX

1. INTRODUCTION ........................................................................................................................................ 1

1.1 OUR UNDERSTANDING ................................................................................................................................. 1

1.2 TERMS OF REFERENCE ................................................................................................................................. 2

1.3 OBJECTIVES ............................................................................................................................................... 2

1.4 REGISTER OF DISCUSSIONS ............................................................................................................................ 2

2. REVIEW OF METHODS USED..................................................................................................................... 3

2.1.1 Phylogenetic analysis ........................................................................................................................ 3

2.1.2 Population genetic structure ............................................................................................................. 3

2.1.2.1 Population genetic structure (within species) .......................................................................................... 3

2.1.2.2 Population genetic diversity (within species) ........................................................................................... 3

2.1.2.3 Population genetic structure (comparison with other species) ............................................................... 4

2.1.3 Measures of Heterozygosity and Fixation ......................................................................................... 4

3. SUMMARY REVIEW OF BGPA FINDINGS AND CONSERVATION RECOMMENDATIONS .............................. 5

3.1 PHYLOGENETIC ANALYSIS – RELATIONSHIP TO OTHER SPECIES ............................................................................... 5

3.1.1 Darwinia masonii .............................................................................................................................. 5

3.1.2 Lepidosperma gibsonii ....................................................................................................................... 5

3.2 POPULATION GENETIC STRUCTURE - DARWINIA MASONII .................................................................................... 5

3.2.1 Populations and markers................................................................................................................... 5

3.2.2 Population genetic differentiation (within species) ........................................................................... 7

3.2.2.1 AMOVA ..................................................................................................................................................... 7

3.2.2.2 Principal coordinates analysis .................................................................................................................. 7

3.2.2.3 Pairwise comparisons ............................................................................................................................... 8

3.2.3 Population genetic diversity (within and between species) ............................................................ 10

3.2.3.1 Genetic diversity (Heterozygosity index) ................................................................................................ 10

3.2.3.2 Inbreeding (Fixation index) ..................................................................................................................... 11

3.2.4 Spatial Genetic Structure ................................................................................................................. 13

3.2.5 Chloroplast haplotypes .................................................................................................................... 13

3.3 POPULATION GENETIC STRUCTURE - LEPIDOSPERMA GIBSONII ............................................................................ 15

3.3.1 Populations and markers................................................................................................................. 15

3.3.2 Population differentiation (within species) ..................................................................................... 15

3.3.2.1 AMOVA ................................................................................................................................................... 15

3.3.2.2 Principal coordinates analysis ................................................................................................................ 16

3.3.2.3 Pairwise comparisons ............................................................................................................................. 16

3.3.3 Population genetic diversity (within and between species) ............................................................ 17

3.3.3.1 Genetic diversity (Heterozygosity) ......................................................................................................... 17

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3.3.3.2 Inbreeding (Fixation index) ..................................................................................................................... 17

4. BENCHMARK REVIEW............................................................................................................................. 20

4.1 COMPARISON OF DATA INTERPRETATION AND CONSERVATION IMPLICATIONS........................................................ 20

4.1.1 Random drift ................................................................................................................................... 20

4.1.2 Wahlund effect ................................................................................................................................ 23

4.1.3 Allelic frequencies ............................................................................................................................ 24

4.1.4 Migration and recruitment .............................................................................................................. 25

4.2 CONSERVATION STRATEGY OPTIONS ............................................................................................................. 25

4.2.1 Findings from comparative studies ................................................................................................. 25

4.2.2 Studies along the gradient of variance between sub-populations .................................................. 28

4.2.2.1 Banksia cuneata, Maguire and Sedgley, 1997 ........................................................................................ 28

4.2.2.2 Eucalyptus amygdalina and E. risdonii hybrid swarm, Sale et al., 1996 ................................................. 28

4.2.2.3 Grevillea scapigera, Rosetto et al., 1995 ................................................................................................ 29

4.2.2.4 Tetraena mongolica, Ge et al., 2003 ....................................................................................................... 29

4.2.2.5 Eucalyptus globulus, Nesbit et al., 1995 ................................................................................................. 30

4.2.2.6 Acacia raddiana, Shresthaa et al. (2002) ................................................................................................ 30

4.2.2.7 Multi-paper literature review, Nybom and Bartish, 2000 ...................................................................... 31

5. DISCUSSION ........................................................................................................................................... 33

5.1 BENCHMARKING CONSERVATION OPTIONS FOR D. MASONII AND L. GIBSONII ........................................................ 33

5.2 INTERPRETATION OF FINDINGS FOR SPECIES CONSERVATION AND RECOVERY ......................................................... 34

5.3 PRACTICAL APPLICATION TO MINE DEVELOPMENT AND REHABILITATION ............................................................... 35

5.4 RECOMMENDATIONS FOR FUTURE WORK AND RESEARCH .................................................................................. 36

6. REFERENCES ........................................................................................................................................... 37

APPENDIX 1: EXTRACTS OF CORRESPONDENCE ............................................................................................. 40

APPENDIX 2: D. MASONII AND L. GIBSONII POPULATION LOCATIONS ........................................................... 41

APPENDIX 3: SUMMARY OF FINDINGS FROM MILLER AND BARRETT, 2010 ................................................... 42

6.1 POPULATION GENETIC STRUCTURE ............................................................................................................... 42

6.2 POPULATION DEMOGRAPHICS ..................................................................................................................... 43

6.3 SEED BIOLOGY .......................................................................................................................................... 44

6.4 SEED GERMINATION AND DORMANCY ........................................................................................................... 45

6.5 PLANT CHARACTERISTICS AND ADAPTATION .................................................................................................... 46

6.6 PROPAGATION, RESTORATION AND TRANSLOCATION ....................................................................................... 47

6.7 CONSERVATION RECOMMENDATIONS ........................................................................................................... 48

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List of Tables

TABLE 1: SUMMARY OF DARWINIA MASONII SUB-POPULATION DISTRIBUTION CHARACTERISTICS AND REPORT CROSS-REFERENCE ...... 6

TABLE 2: PAIRWISE PERMUTATION TEST OF SUB-POPULATION DIFFERENTIATION FOR DARWINIA MASONII ..................................... 9

TABLE 3: SUB-POPULATIONS ASSIGNED TO COMMON GROUPS (INDICATED BY LETTER) AND PERCENTAGE OF INDIVIDUALS WITHIN

SUB-POPULATIONS ASSIGNED TO THAT GROUP (PARENTHESES) FOR NUMBER OF CLUSTERS (K) BETWEEN 2 AND 5 ......................... 10

TABLE 4: HETEROZYGOSITY AND FIXATION – DARWINIA SPECIES ......................................................................................... 11

TABLE 5: OBSERVED HAPLOTYPE GROUPINGS BY SUB-POPULATION. ..................................................................................... 14

TABLE 6: SUMMARY OF LEPIDOSPERMA GIBSONII SUB-POPULATION DISTRIBUTION & SAMPLING CHARACTERISTICS ....................... 15

TABLE 7: PAIRWISE PERMUTATION TEST OF POPULATION DIFFERENTIATION FOR LEPIDOSPERMA GIBSONII ................................... 17

TABLE 8: HETEROZYGOSITY AND FIXATION – L. GIBSONII AND L. COSTALE COMPLEX ................................................................ 18

TABLE 9: SUMMARY OF POPULATION STATISTICS FROM COMPARATIVE STUDIES OF (PREDOMINANTLY) RARE PLANT SPECIES ........... 27

TABLE 10: SUMMARY OF KEY FINDINGS ON POPULATION GENETIC STRUCTURE ....................................................................... 42

TABLE 11: SUMMARY OF KEY FINDINGS ON POPULATION DEMOGRAPHICS............................................................................. 43

TABLE 12: SUMMARY OF KEY FINDINGS ON SEED BIOLOGY ................................................................................................. 44

TABLE 13: SUMMARY OF KEY FINDINGS ON SEED GERMINATION AND DORMANCY .................................................................. 45

TABLE 14: SUMMARY OF KEY FINDINGS ON PLANT CHARACTERISTICS AND ADAPTATIONS ......................................................... 46

TABLE 15: SUMMARY OF KEY FINDINGS ON PROPAGATION, RESTORATION AND TRANSLOCATION ............................................... 47

TABLE 16: SUMMARY OF KEY CONSERVATION RECOMMENDATIONS BASED ON POPULATION GENETIC STUDIES ............................. 48

List of Figures

FIGURE 1: MINING FOOTPRINT AND THE DISTRIBUTION OF LEPIDOSPERMA GIBSONII (BROWN DOTS) AND DARWINIA MASONII (BLUE

DOTS) (MILLER AND BARRETT, 2010) .............................................................................................................................. 1

FIGURE 2: PRINCIPAL COORDINATES ANALYSES OF SAMPLES FROM SEVEN SUB-POPULATIONS OF D. MASONII (MILLER AND BARRETT,

2010) ....................................................................................................................................................................... 7

FIGURE 3: PRINCIPAL COORDINATES ANALYSES OF SAMPLES FROM TEN SUB-POPULATIONS OF D. MASONII (BARRETT AND KRAUSS, IN

PREP.) ........................................................................................................................................................................ 8

FIGURE 4: HETEROZYGOSITY AND FIXATION – DARWINIA SPECIES ........................................................................................ 12

FIGURE 5: MANTEL CORRELATION OF NEI’S GENETIC DISTANCE BETWEEN SUB-POPULATIONS AND GEOGRAPHIC DISTANCE BETWEEN

SUB-POPULATION CENTRES ........................................................................................................................................... 13

FIGURE 6: DISTRIBUTION OF OBSERVED CHLOROPLAST HAPLOTYPES. SHADING INDICATES DIFFERENT HAPLOTYPES. ....................... 14

FIGURE 7: LEPIDOSPERMA GIBSONII PRINCIPAL COORDINATES ANALYSIS ............................................................................... 16

FIGURE 8: HETEROZYGOSITY AND FIXATION – L. GIBSONII AND L. COSTALE COMPLEX .............................................................. 19

FIGURE 9: RANDOM DRIFT IN A POPULATION WHERE NATURAL SELECTION FAVOURS THE WILD-TYPE ALLELE (FALCONER, 1990) ..... 21

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FIGURE 10: DISPERSAL OF POLLEN WITH DISTANCE INDICATED BY HYBRID PROGENY OF SYNCHRONOUSLY FLOWERING EUCALYPT

SPECIES (POTTS ET AL., 2001) ...................................................................................................................................... 23

FIGURE 11: FREQUENCY DISTRIBUTION OF ALLELES PER LOCUS FOR D. MASONII ..................................................................... 24

FIGURE 12: DERIVED RELATIONSHIP BETWEEN ALLELE FREQUENCY IN THE TOTAL POPULATION, AND OCCURRENCE IN D. MASONII SUB-

POPULATIONS ............................................................................................................................................................ 24

FIGURE 13: D. MASONII POPULATIONS. PUTATIVELY ISOLATED POPULATIONS CIRCLED RED ...................................................... 41

FIGURE 14: L. GIBSONII POPULATIONS. PUTATIVELY ISOLATED POPULATIONS CIRCLED RED ...................................................... 41

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Glossary

Assortative mating The reproductive pairing of individuals that have traits more traits in common

than would be likely by random mating alone

AFLP Amplified fragment length polymorphism – a type of genetic marker

Allele A gene mutation or variant

Allopatric Speciation in which populations are physically isolated by an extrinsic barrier

and evolve intrinsic (genetic) reproductive isolation, such that if the barrier

breaks down, individuals of the population can no longer interbreed.

AMOVA Analysis of Molecular Variance. A technique to partition the proportion of total

variance components to within and among sub-populations, analogous to

standard Analysis of Variance.

BGPA Botanic Gardens and Parks Authority (Kings Park and Botanic Garden)

BIF Banded ironstone formation

Disssortative

mating

The reproductive pairing of individuals that have traits more dissimilar than

would be likely by random mating alone

DRF Declared Rare Flora

Dysploid

chromosome-

reduction series

Dysploidy is a change in the basic chromosome number (x) of a genome

without concomitant loss or gain of genes.

Fixation Occurs when every individual in a certain population has the same allele (gene

variant) at a particular locus (specific location of a gene).

FIS The inbreeding coefficient on an individual (I) relative to its own sub-

population (S).

FST The inbreeding coefficient on a sub-population (S) relative to the whole

population (T).

Group A local group of plants of a given species, spatially closer to each other than to

plants in other groups and representing a sub-group of the wider population.

Used interchangeably with sub-populations.

Heterozygosity A measure of genetic variation at a locus. It is the measured as the proportion

of individuals that carry two different alleles at a locus.

Homozygosity A measure of the lack of genetic variation at a locus. It is the measured as the

proportion of individuals that carry two identical alleles at a locus.

Locus Specific location of a gene or position on a chromosome

https://en.wikipedia.org/wiki/Chromosome

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Microsatellite A type of genetic marker based on simple sequence tandem repeats (SSTRs) of

nucleotides (the elements of DNA). The repeat units are generally di-, tri-

tetra- or penta-nucleotides, e.g. Can where A and C are Adenosine and

Cytosine, two of the four nucleotides that comprise the building blocks of DNA.

Microsatellite are useful genetic markers because they tend to be highly

polymorphic, and co-dominant (i.e., heterozygotes can be distinguished from

homozygotes.

Nm The gene flow parameter representing the product of the effective population

number and rate of migration among sub-populations.

PCA Principal Coordinates analysis

Population A group of individuals of the same species occupying a specific habitat or other

defined area.

Sub-population A local occurrence of plants of a given species, spatially closer to each other

than to plants in other occurrences and representing a sub-group of the wider

population. Used interchangeably with groups.

RAPD Random amplified polymorphic DNA – a type of genetic marker

SSR Simple sequence (tandem) repeat, also known as microsatellites, usually

consist of di or tri-nucleotide repeats, e.g., ATGATGATG.

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Executive Summary

Overview

Mount Gibson Mining’s proposal to mine and process iron ore from Extension Hill and associated

assets will impact on two Declared Rare Flora Species, Darwinia masonii and Lepidosperma gibsonii.

Development approvals were granted subject to conservation of significant flora and communities

and Research and Recovery Plans for these species. Mount Gibson Mining commissioned Botanic

Gardens and Parks Authority (Kings Park and Botanic Garden) (BGPA) to undertake an integrated

research program. The BGPA study found, inter alia statistical evidence for weak genetic structuring

within populations of both species. Mount Gibson Iron commissioned Verterra to critically review

the genetics finding of the BGPA studies and provide recommendations on a way forward.

Verterra’s review includes Phase 1 investigation reports into both species (Barrett et al., 2005, 2006),

an integrated Phase 2 report into both species (Miller and Barrett, 2010) and an unpublished

manuscript in relation to the conservation genetics of D. masonii.

Summary of prior studies

The succession of reports collate progressively more information in relation to the genetic structure

of both species. Principal Coordinates Analysis (PCA) for D. masonii found sub-populations strongly

overlap in, but predominant segregation of some sub-population pairs suggests a weak but

significant population structure. PCA for L. gibsonii found that samples within different sub-

populations do not cluster together, but are completely intermixed.

AMOVA analyses found statistically significant evidence for weak genetic structure (90% within and

10% between sub-populations for D. masonii; 96% within and 4% between sub-populations for

L. gibsonii).

Pairwise analyses for both species found evidence that some sub-populations are statistically

supported (p< 0.001) as being genetically ‘isolated’ from each other and all remaining sub-

populations (i.e., not mating randomly with other sub-populations).

Estimation of the gene flow parameter for D. masonii found the effective level of gene flow (Nm) at

4.4 individuals per generation between sub-populations. This result is presented as being consistent

with weak observed structure, and migration biased by distance. This result is considerably higher

than reported in other species with weak genetic structure (e.g. Tetraena mongolica, Nm =1.223;

genetic variance = 84.8% within and 15.2% between sub-populations). Other reports suggest Nm

values greater than 1 indicate gene flow sufficient to homogenize populations to some degree (tend

not to diverge in allele frequency from one another). Nm values greater than 0.5 are considered

sufficient to overcome the diversifying effects of random drift.

Based on evidence for weak genetic structuring Barrett and Miller (2010) recommend the

precautionary principle should apply to avoid mixing genotypes between sub-populations without

careful consideration of consequences.

Review findings

A review of a wide range of other species, both threatened and widespread species, found a wide

range of genetic structuring between sub-populations from 100% of population genetic variance

within sub-populations, to 33% within and 67% between sub-populations. The review was addressed

in the context of answering the question:

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“Should conservation efforts be aimed at maintaining genetic diversity (the range of allelic variants

occurring across each sub-population) or genotype diversity (the packages of alleles and allele

frequencies inherent in different sub-populations?”

The case studies illustrate a trend in recommended conservation strategy from:

Species with weak genetic divergence where recommendations centre around capturing a

larger number of plants from sub-populations displaying the greatest level of genetic

diversity and promote mixing across sub-populations during the recovery process; to

Species with strong genetic divergence where recommendations centre around conserving

each sub-population separately.

Compared to the case studies, results for both D. masonii and L. gibsonii indicate a relatively low

level of genetic divergence between sub-populations, relatively high gene flow and high level of

allelic diversity.

Based on consideration of the population genetic structure of both D. masonii and L. gibsonii,

supported by evidence for conservation recommendations for a wide range of other (predominantly

rare and threatened) species, it is recommended that conservation of these species would best be

served by a strategy that:

1. Samples germplasm from across the range (thereby capturing representative samples of

both nuclear allelic and chloroplast haplotype variants); and

2. Promotes inter-breeding of genotypes to the greatest possible extent to facilitate inter-

mixing of the available pool of common and rare alleles, and thereby preserve the

evolutionary potential of the two species to adapt to changing environmental, climatic,

biological and anthropogenic conditions.

This recommendation contradicts the conservation recommendation of the BGPA study.

Having regard to approaches that best support the preferred conservation strategy, it is also

suggested that the broader “enabling” requirements for successful plant reproduction, propagation

and cultivation are addressed including:

coexisting vegetation community diversity and structure to support pollinators (esp. for

D. masonii);

knowledge of breeding systems and capacity to promote inter-breeding, to support

maintenance of variation in the population, and ensure capacity to produce and store viable

propagules;

knowledge of growing conditions requirements (physical, chemical, biological) to support

successful translocation and cultivation;

knowledge of environmental and stress interactions in order to inform relevant

management strategies (e.g. fire regime).

It is suggested that the practical application of the recommended genetic conservation strategy to

mine development and rehabilitation requires collection and management of ex-situ gene

conservation banks to provide the capacity to produce seed and/or seedlings for use in post-mining

rehabilitation. The ex-situ gene conservation bank should aim to capture “genes” as opposed to

genotypes of both DRF species from both the mine development area as well as non-disturbed areas.

This gene-pool should be captured and secured in advance of mine development and associated

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disturbance, reducing the risk associated with loss of translocated plants. The floristic composition

and structure of vegetation surrounding the ex-situ gene conservation banks will need to provide

conditions conducive to natural bird pollinators and ideally promote movement of pollinators

between natural and ex-situ populations.

Recommendations for further research are presented, focussing on knowledge gaps that support

effective management of the two species, both in response to mine disturbance, other anthropogenic

disturbance, and natural environmental influences.

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1. Introduction

1.1 Our understanding

Mount Gibson Mining Ltd is an established independent Australian iron ore producer. Mount

Gibson’s assets include Extension Hill DSO (Direct Shipping Ore) – a 3-million tonne per annum iron

ore mine in the Mount Gibson Range, 260km east-southeast of Geraldton. Production at Extension

Hill commenced in 2011.

The area approved for disturbance by the mine supports, inter alia, communities including Declared

Rare Flora (DRF) species Darwinia masonii and Lepidosperma gibsonii. The concurrence of the

mining footprint relative to sub-populations of these DRF species is illustrated in Figure 1.

Mount Gibson Mining’s proposal to mine and process iron ore from Extension Hill and associated

assets was approved subject to conditions 6, 7 and 8 of Ministerial Statement No. 753. Respectively,

these conditions specify requirements for:

Darwinia masonii - Research and Recovery Plans;

Lepidosperma sp. Mount Gibson - Research and Recovery Plans;

Conservation of significant flora and ecological communities.

Figure 1: Mining footprint and the distribution of Lepidosperma gibsonii (brown dots) and Darwinia

masonii (blue dots) (Miller and Barrett, 2010)

Conditions 6.1 and 7.1 of Ministerial Statement No. 753 (Templeton, 2007) require Mount Gibson

Mining to facilitate the continued in situ survival and improvement in the conservation status of

D. masonii and L. gibsonii over time through targeted research to assist in the development of a

recovery plan for each species. In compliance with these conditions, Mount Gibson Mining

commissioned Botanic Gardens and Parks Authority (Kings Park and Botanic Garden) (BGPA) to

undertake an integrated research program.


A sub-component of that research program involved genetic marker studies to understand the

population structure of D. masonii and L. gibsonii. Phase 1 reports on each species were prepared in

2005 (Barrett et al., 2005) and 2006 (Barrett et al., 2006). A Phase 2 Conservation and Restoration

Research report for both species, including results of further genetic marker studies, was prepared in

October 2010 (Miller and Barrett, 2010). BGPA have also carried out subsequent independent

research, which is currently in preparation for publication (Krauss and Barrett, in prep.). Extracts of

this research have been provided to Mount Gibson Mining, and a draft manuscript has been provided

for this review. So that it is consistent with recovery plan actions and its proposed D. masonii

translocation program, Mount Gibson Mining has an interest in relation to the outcomes and

implications of the conservation genetics research.

1.2 Terms of Reference

Mount Gibson Mining have requested Verterra to provide a critical but succinct appraisal of the

genetics data, the level of certainty made in interpretations to date and extracts from publication(s)

currently in preparation. Verterra will provide recommendations on a way forward. This may

include recommendations for additional research if required.

1.3 Objectives

The objective of this report is to critically review the BGPA study findings, benchmark to others

studies, and make recommendations on:

information gaps;

the need for further research;

considerations for conservation of the genetic diversity of each species; and

considerations for restoration activities with regard to the genetic structuring of each DRF

species.

1.4 Register of discussions

Date Details

13 March 2015 Initial discussion with Lara Jefferson.

25 March 2015 Phone discussion with Troy Collie.

5 May 2015 Submission of questions to BGPA arising from the initial review (conveyed to BGPA

by Mt Gibson Mining).

4 June 2015 Discussion with Matt Barrett re questions presented to BGPA.

8 June 2015 Provision of additional reports from BGPA.

10 June 2015 Further clarification with Matt Barrett.


2. Review of methods used

Initial studies by Barrett et al., (2005, 2006) undertook a number of levels of analysis of genetic

diversity and structure for two DRF species using approaches described below. These studies present

no underlying hypothesis on the nature of the population genetic structure of each DRF species. In

the context of this review, given the relatively small geographic range of both DRF species, the null

hypothesis has been made that there is no genetic structuring within the overall population. On this

basis, spatially separated nodes of each species have been referred to using the neutral terms

“groups” or “sub-populations”. Use of the term “population” for different nodes implies, a priori, a

material level of genetic differentiation. The alternate hypothesis, therefore, is that spatially

separated nodes of each species are sufficiently genetically isolated to be referred to as

“populations” in their own right.

2.1.1 Phylogenetic analysis

Phylogenetic analysis was carried out using two markers - a nuclear marker (inherited from both

parents) and a chloroplast marker (maternally inherited only) to determine the relative relatedness

of specimens of each DRF species to specimens of other species in their respective genus. This was

used to identify the comparison species for the assessment of genetic diversity in each species.

2.1.2 Population genetic structure

2.1.2.1 Population genetic structure (within species)

Amplified fragment length polymorphism (AFLP) and Microsatellite markers (both nuclear markers)

were used to investigate the within and between sub-population genetic variance of each of the DRF

species. The first of three studies in D. masonii (Barrett et al., 2005) used 78 informative AFLP

markers. The second study (Miller and Barrett, 2010) used a set of 14 microsatellite loci with an

unidentified number of alleles. The third study (Krauss and Barrett, in prep.) used 15 microsatellite

loci with a combined total of 157 alleles (an average of 11.2 per locus). Eight microsatellite markers

were developed for L. gibsonii (Barrett et al., 2006). These provided a total of 130 alleles (an average

of 16.2 per locus).

Data from marker studies was used to perform a number of analyses:

Analysis of Molecular Variance (AMOVA) to partition the within and between sub-

population genetic variance;

Principal Coordinates Analysis computes co-ordinates (in n dimensions) of individual

samples such that the distance between each object pair correlates as close as possible to

the dissimilarity between the pair. This multivariate technique allows the major patterns

within a dataset (e.g. multiple loci and multiple samples) to be plotted and visualised;

Pairwise permutation tests of sub-population differentiation to investigate genetic isolation

(departures from random mating) between sub-populations.

2.1.2.2 Population genetic diversity (within species)

Microsatellite markers were also used to investigate the genetic diversity within and between sub-

populations of each species. Two measures were estimated:

Estimates of heterozygosity: Observed (Ho), Expected (He) and unbiased (UHe):


Fixation Index (F) as an indicator of relative inbreeding.

2.1.2.3 Population genetic structure (comparison with other species)

In the case of D. masonii, this part of the study was carried out due to the inability of prior work to

determine whether or not the apparently “low” genetic variation was due to: (a) low chromosome

number; or (b) past low population size or population bottleneck. The inability to distinguish

between these reasons was raised as a significant concern by Department of Environment and

Conservation (since renamed as Department of Parks and Wildlife) reviewers of the initial report.

For both DRF species, Microsatellite markers were used to compare genetic diversity with the most

closely related species identified from the phylogenetic analysis above. Three measures were

estimated:

Expected Heterozygosity as an indicator of relative diversity;

Fixation Index as an indicator of relative inbreeding;

Principal Coordinates Analysis (calculated using Nei’s genetic distance) to estimate

divergence between spatially separated groups or sub-populations of each DRF species of

interest, and sub-populations of the closest related species (D. masonii only).

2.1.3 Measures of Heterozygosity and Fixation

Heterozygosity is a measure of the genetic variation at a locus. It is measured as the proportion of

individuals that carry two different alleles at a locus. Observed heterozygosity is the number of

heterozygotes observed. Expected and expected unbiased heterozygosity are measures of the

expected number of heterozygotes assuming Hardy-Weinberg equilibrium, based on the observed

frequency of different alleles. Fixation index is then a measure of the proportion of homozygotes,

generally calculated in the form:

𝐹 = 1 − observed heterozygosity

expected heterozygosity

A variation of observed from expected heterozygosity is an indication of inbreeding, natural selection

or other influences causing a departure from Hardy-Weinberg equilibrium. It can be seen from the

form of this equation that when F = 0, inbreeding is absent. Values of F significantly greater than 0

represent a deficient of observed heterozygotes to the number expected and may indicate

inbreeding (but not always as will be discussed later). Negative values of F indicate an excess of

observed heterozygotes relative to the number expected. This may occur, for example, if

homozygotes are less fit than heterozygotes (i.e., positive selection pressure for heterozygotes), or

due to disassortative mating (where genotypes that differ from each other mate more often than

expected by random mating).


3. Summary review of BGPA findings and conservation recommendations

Key findings of the BGPA study are summarised below.

3.1 Phylogenetic analysis – relationship to other species

3.1.1 Darwinia masonii

Two gene regions were used to detect potentially incongruent signals resulting from gene trees

versus species trees: the nuclear ribosomal External Transcribed Spacer (ETS), and the chloroplast

trnK intron (including the matK gene).

Analysis of phylogenetic relationships between species of Darwinia, using the nuclear and chloroplast

marker, found it is most closely related to D. purpurea, D. acerosa, and the undescribed species

D. sp. chiddarcooping.

Relationships between these four Darwinia species remained unresolved by either of the

phylogenetic markers, indicating that they are closely related, and possibly speciated allopatrically,

i.e., through isolation of populations and subsequent adaptation of a previously widespread species.

3.1.2 Lepidosperma gibsonii

Two genes were used to assess relationships; the nuclear ribosomal External Transcribed Spacer

(ETS) and the chloroplast trnL intron + trnL-trnF spacer. The latter proved to be less variable than

ETS, and so sampling was less comprehensive for that region, with ETS being used only for subsets of

taxa within clades.

L. gibsonii was clearly closely related to a group of taxa around L. costale, and only more distantly

related to the morphologically similar species L. ferricola. Lepidosperma gibsonii is a diploid species

(two sets of chromosomes).

In turn, between- and within-population diversity in the L. costale species complex can be

considerable. Most populations are tetraploid (four sets of chromosomes), some populations are of

allopolyploid-hybrid origin (four sets of chromosomes, two each from two different species), and

some are diploids.

Only the diploid populations of L. costale were useful for comparative genetic diversity in L. gibsonii.

The diploid populations of L. costale are almost entirely restricted to the semi-arid inter-zone

between Mt Gibson, Mt Karara and Wubin.

3.2 Population genetic structure - Darwinia masonii

3.2.1 Populations and markers

An initial genetic survey of D. masonii (Barrett et al., 2005) was based on 75 samples from four sub-

populations on the Mt Gibson range system, using 78 informative Amplified Fragment Length

Polymorphism (AFLP) markers. The number of loci sampled cannot be identified with AFLP markers.

The study found low variability in the AFLP markers, which lowered the power to test for population

differentiation. This was further hampered by an insufficient sample size in the number of samples

and the number of sub-populations. The study concluded that:


“The (sub) population within the proposed mine1 footprint is generally homogenous

with the adjacent (sub) population outside the footprint2 and broadly with all (sub)

populations sampled.”

A second study (Miller and Barrett, 2010) developed microsatellite or simple-sequence repeat (SSR)

markers. A total of 14 microsatellite loci providing 157 alleles from 15 loci (an average of 10.5 per

locus; range 2 to 30) were produced for use in various analyses of genetic diversity and the mating

system in D. masonii. The second study examined 179 samples from seven sub-populations as

detailed Table 1. A further study (Barrett and Krauss, in preparation) sampled 284 plants from 9 sub-

populations (Table 1). Note, the identification code for sub-populations varies between studies.

Table 1: Summary of Darwinia masonii sub-population distribution characteristics and report cross-

reference

Sub-population

Label (Miller and Barrett

2010)

(Figure 13)

Sub-population

Label

(Barrett and Krauss,

in prep.)

Location Sampled (Miller and

Barrett, 2010)

No. of samples

(Barrett and Krauss

in prep.)

No. plants per sub-

population (2004

census)

Nearest sub-populations

and (Distance, m)

C 1 Extension Hill North X 34 557 2A (540)

D (west) 2A Extension Hill (west side and summit)

31

1936

2B (<50) 1 (540)

D (east) 2B Extension Hill (east side) 32 2A (<50) 3 (210)

E 3 Extension Hill South 21 1900 2B (210) 4 (360)

Unlabelled (4) Iron Hill North (north peak)

X 28 619 10 (300) 3 (360)

B 5 Iron Hill 33 2571 10 (180) 6 (380)

G 6 Iron Hill East 28 81 7 (270) 5 (380)

MW 7 Unnamed ridge on east side of Iron Hill (Mt Gibson West)

22 c. 503

8 (180) 6 (270)

A 8 Mt Gibson 28 7082 9 (210) 7 (180)

F 9 Mt Gibson South 27 325 8 (210)

Unlabelled (10) Iron Hill North (south peak)

X Un-

sampled 967

5 (180) 4 (300)

Total 284 c. 16,088

1 Population “D” (Extension Hill) in Figure 13

2 Populations “E” (Extension Hill South), “A” (Mount Gibson) and “B” (Iron Hill) in Figure 13.

3 Not included in 2004 census


3.2.2 Population genetic differentiation (within species)

3.2.2.1 AMOVA

The initial AFLP study (Barrett et al., 2005) found both limited diversity with 50.6% of markers

polymorphic (very low for AFLP), and low population differentiation (AMOVA found that 94% of

genetic variation was contained within sub-populations, and 6% between sub-populations).

Analysis of Molecular variance in the second study (Miller and Barrett, 2010) using 14 microsatellite

markers and 157 alleles partitioned 94% of variation within sub-populations and 6% between sub-

populations, indicating weak population structure (weak differentiation between localities).

Partitioning of variation by AMOVA in the third study (Barrett and Krauss, in prep.) found that 90% of

variation was contained within sub-populations, and 10% between sub-populations. A global non-

parametric permutation test for deviation from the null model of no differentiation was significant

(p<0.001).

3.2.2.2 Principal coordinates analysis

The weak population structure found in Miller and Barrett (2010), illustrated in Figure 2, clearly

shows samples within different sub-populations do not group together, but are completely

intermixed, i.e. any individual is also related to individuals in other sub-populations or groups just as

closely as they are to individuals in the same sub-population.

Figure 2: Principal Coordinates Analyses of samples from seven sub-populations of D. masonii

(Miller and Barrett, 2010)

The same analysis using the latest data (Barrett and Krauss, in prep.) indicates a slightly different

story. Sub-populations strongly overlap in the PCA, but predominant segregation of some sub-

population pairs (C (1) and F (9)), suggests a visual representation of weak but significant population

structure (Figure 3). It is notable that three individuals out of a total of 27 from node F (occurring to

the right of the main cluster in Figure 3) leverage the relationship of this node to the rest of the sub-

population. In the absence of these three individuals, node F would be considered completely


intermixed with individuals from other nodes. The contribution of low frequency alleles to this result

has not been analysed.

Figure 3: Principal Coordinates Analyses of samples from ten sub-populations of D. masonii (Barrett

and Krauss, in prep.)

3.2.2.3 Pairwise comparisons

Pairwise permutation tests reported in Miller and Barrett (2010) between spatially separated sub-

populations show that some are statistically different (p< 0.001) so may be genetically ‘isolated’ from

each other (Table 2). In this context, ‘isolated’ means not mating randomly with other sub-

populations. There are a number of possible explanations.

In relation to the two sub-populations on Extension Hill South “E” and Mt Gibson South “F” Miller

and Barrett (2010) state that:

“Aside from these two (sub) populations, other (sub) populations are scarcely

significantly different from a single panmictic, interbreeding population.”

However the associated table caption states:

“Sub-populations “E” and “F” are significantly supported as departing from random

mating with other sub-populations; occasional other pairwise comparisons are also

significant.”

The results, reproduced in (Table 2) indicate that 9 out of the possible 21 pairwise combinations are

statistically significant at p< 0.001.

Axis

2

Axis 1

Principal Coordinates (1 vs 2)

A

B

C

D

DW

E

F

G

MDW

MID


Table 2: Pairwise permutation test of sub-population differentiation for Darwinia masonii

Possible explanations for the putative non-random mating of D. masonii sub-populations “E”

(Extension Hill South) and “F” (Mt Gibson South) are:

The sub-population from Mt Gibson South “F” is at the southern end of the range and known

area of occurrence, and may be diverging in physical isolation. In this regard, it was notable

that sub-population “F” was not significantly different from the two sub-populations due

north being at Mount Gibson and Iron Hill East. This result may be better explained by a

continuum of variation rather than a disjunction (refer Section 3.2.4);

The Mt Gibson South sub-population “F” has not been burnt for > 50 years, unlike most other

sub-populations, and the result could be an artefact of sampling different generations;

Significant differences for sub-population “F” may be artefactual due to the influence of

three outlier individuals, which map well outside the main sub-population. The contribution

of low frequency alleles to this result has not been analysed.

Sub-population “E” on Extension Hill South is close to the sub-population on Extension Hill

"D”, occupies an intermediate position on the western ridge, and the observed result is

surprising. This sub-population is only statistically different to the adjacent sub-population at

p>0.005, so this result may reflect a gradation rather than disjunction;

Putative divergence from non-random mating for the sub-population on Extension Hill South

“E” could be due to differences in sub-population age, or differential selection at loci linked

to some microsatellite markers as sampled plants came from a variety of plant ages, fire

history, substrate and landscape position.

Barrett and Krauss (in prep.) did not repeat the pair-wise permutation test, but examined sub-

population clustering using Bayesian model-based clustering techniques (Pritchard et al., 2000,

Falush et al., 2003, 2007) to compare hypotheses about the number of groups, which best explains

spatial patterns of allelic diversity.

The results of this approach best supported two clusters (K = 2) within D. masonii sub-populations,

broadly corresponding to those from Extension Hill (sub-populations C (1), D (2A & 2B) and E (3)), and

the remaining samples from Iron Hill and Mt Gibson (sub-populations Iron Hill north (4), B (5), G (6),

MW (7), A (8) and F (9)) (Table 3).


Table 3: Sub-populations assigned to common groups (indicated by letter) and percentage of

individuals within sub-populations assigned to that group (parentheses) for number of clusters (K)

between 2 and 5

Sub-population Sub-population K=2 K=3 K=4 K=5

ln K4 -12250 -12167 -12064 -12011

K 38.3 2.1 5.3 1.6

C 1 A (0.937) A (0.923) A (0.877) A (0.869)

D west 2A A (0.905) A (0.796) B (0.846) B (0.820)

D east 2B A (0.883) A (0.767) B (0.766) B (0.728)

E 3 A (0.539) B (0.540) B (0.469) C (0.501)

Iron Hill (north) 4 B (0.842) B (0.739) C (0.671) C (0.723)

B (Iron Hill) 5 B (0.832) B (0.521) D (0.443) C (0.414)

G 6 B (0.895) C (0.670) D (0.802) D (0.638)

MW 7 B (0.897) C (0.748) D (0.692) D (0.709)

A 8 B (0.910) C (0.772) D (0.698) D (0.678)

F 9 B (0.920) C (0.620) C (0.718) E (0.765)

A Log-likelihood of the data given number of clusters = K.

3.2.3 Population genetic diversity (within and between species)

3.2.3.1 Genetic diversity (Heterozygosity index)

Miller and Barrett (2010) found genetic diversity within and between sub-populations of D. masonii,

and D. purpurea and D. chiddacooping (measured by the Unbiased Heterozygosity) was similar with

the exception of one sub-population of D. purpurea (Bunjil) and one of D. chiddacooping (Corrigin).

Mean unbiased heterozygosity for the three species was 0.629, 0.709 (0.742 excluding Bunjil) and

0.578 (0.699 excluding Corrigin), respectively. Means and ranges are summarised in Table 4 and

illustrated in Figure 4.

The Binjil sub-population is a small, highly disturbed patch of remnant vegetation with only a few

scattered plants. The Corrigin sub-population, restricted to a small area on a single granite rock,

contains less than 100 plants and is geographically disjunct from other members of the genetic

complex.

Similar values of Ho and UHe were found by Barrett and Krauss (in prep.), with a slightly higher range

in values of observed heterozygosity (range: 0.503 to 0.650, mean = 0.580); slightly lower range in

unbiased expected heterozygosity (range: 0.519 to 0.685, mean = 0.626); and slightly lower Fixation

Index (range -0.071 to 0.135, mean = 0.051).

4 Log-likelihood of the data given number of clusters = K


3.2.3.2 Inbreeding (Fixation index)

Excluding the Binjil and Corrigin sub-populations, Miller and Barrett (2010) found fixation index low

within and between sub-populations of D. masonii, D. purpurea and D. chiddacooping (-0.067 to

0.216; -0.008 to 0.109; and 0.020 to 0.243 respectively). These values for F suggest a range from no

inbreeding to low but significant level of inbreeding in some sub-populations. These values may also

suggest assortative mating (where genotypes similar to one another mate more often than expected

by random mating). Darwinia masonii and populations of D. purpurea and D. chiddacooping

(excluding Binmjil and Corrigin) show no indication of recent inbreeding depression. Means and

ranges are summarised in Table 4 and illustrated in Figure 4.

Again, similar values of F were found by Barrett and Krauss (in prep.), with a lower Fixation Index

(range: -0.071 to 0.135, mean = 0.051), indicating some sub-populations show preferential selection

for heterozygotes, some show no selection pressure (no inbreeding or departure from expected

genotype frequencies) and some show low levels of inbreeding or assortative mating).

Table 4: Heterozygosity and fixation – Darwinia species

Species Observed

Heterozygosity (Ho)

Expected

Heterozygosity (He)

Unbiased expected

Heterozygosity (UHe)

Fixation Index (F)

Range Mean Range Mean Range Mean Range Mean

D. masonii

(7 sub-populations)

0.474-

0.657

0.549 0.586-

0.647

0.616 0.600-

0.657

0.629 -0.067-

0.216

0.105

D. purpurea

(9 sub-populations)

0.396-

0.806

0.651

(0.682)

0.434-

0.801

0.695

(0.728)

0.444-

0.822

0.709

(0.742)

-0.008-

0.184

0.070

(0.056)

D. chiddacooping

(4 sub-populations)

0.111-

0.693

0.493

(0.620)

0.214-

0.750

0.569

(0.687)

0.217-

0.762

0.578

(0.699)

-0.020-

0.365

0.166

(0.100)

Numbers in brackets exclude the outlier sub-populations of Corrigin (D. chiddacooping) and Bunjinl (D.

purpurea).

This part of the Miller and Barrett (2010) study was undertaken to address the question of the basis

for apparently low genetic diversity in D. masonii due to the lack of a comparable study in Darwinia.

The comparable level of genetic diversity between sub-populations of D. masonii, and between

D. masonii, the more widely distributed D. purpurea and D. chiddacooping, even after excluding the

outlying sub-populations of Corrigin (D. chiddacooping) and Bunjinl (D. purpurea), would indicate

that the observed level of genetic diversity for D. masonii is typical and in the observed range for this

genus.


Figure 4: Heterozygosity and fixation – Darwinia species

Ho = Observed heterozygosity

He = Expected Heterozygosity

UHe = Unbiased expected Heterozygosity

F = Fixation Index

0

2

4

6

8

100

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Mo

re

Freq

uen

cy

D. masonii Ho

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fre

qu

ency

D. masonii He

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fre

qu

ency

D. masonii UHe

0

2

4

6

8

10

-0.1 0 0.1 0.2 0.3 0.4 0.5 More

Freq

uen

cy

D. masonii F

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

ue

ncy

D. purpurea Ho

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

ue

ncy

D. purpurea He

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

ue

ncy

D. purpurea UHe

0

2

4

6

8

10

-0.1 0 0.1 0.2 0.3 0.4 0.5 More

Freq

ue

ncy

D. purpurea F

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

D. chiddacooping Ho

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

D. chiddacooping He

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

D. chiddacooping UHe

0

2

4

6

8

10

-0.1 0 0.1 0.2 0.3 0.4 0.5 More

Freq

uen

cy

D. chiddacooping F


3.2.4 Spatial Genetic Structure

An additional test conducted by Barrett and Krause (in prep.) explored the correlation between

physical and genetic distance. The Mantel test between geographic distance and Nei’s genetic

distance between spatially separated sub-populations for isolation by distance detected a positive

correlation between the two distances (R2 = 0.63). Permutation tests show that this result is

significant (p<0.001). This result illustrates a continuum of variation throughout the range of

D. masonii rather than abrupt disjunctions between spatially separated sub-populations. This

pattern of variation may be explained by the Wahlund effect (refer Section 4.1.2), illustrating that

individuals tend to mate with those that are nearby. In turn, this indicates that the full range of

D. masonii represents a single population with local variation in allele frequency due to more

frequent mating between neighbours as would be expected in any population.

Figure 5: Mantel correlation of Nei’s genetic distance between sub-populations and geographic

distance between sub-population centres

3.2.5 Chloroplast haplotypes

Results from mapping chloroplast haplotypes (Barrett and Krause, in prep.) support the observations

for groupings as indicated by nuclear microsatellite markers. Chloroplast genomes are maternally

inherited, and so indicate the movement and flow of genes from seed (as opposed to pollen).

A single chloroplast microsatellite was used to distinguish eight chloroplast haplotypes. As indicated

in Table 5 and Figure 6, sub-populations 1 (C) and 2 (D) share a common haplotype; sub-populations

3 (E) and 4 share a common haplotype; sub-populations 6 (G) and 8 (A) each have their own unique

haplotype; sub-population 5 (B) carries two haplotypes not found in other populations (in equal

proportions); and population 9 (F) carries two haplotypes not found in other populations (in the

ration of 17:2).

Molecular differences between haplotypes indicate that different haplotypes from adjacent sub-

populations or groups are usually also sister haplotypes (except for the two haplotypes of sub-

y = 0.0379x + 0.0517 R² = 0.6347

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.000 1.000 2.000 3.000 4.000 5.000 6.000

Nei's d

ista

nce b

etw

een

po

ps

distance (km)


population 5 (B), which are not sisters).

Table 5: Observed haplotype groupings by sub-population.

Sub-

population

Code

Sub-

population

No.

Location No. of

samples B

Haplotype

label

C 1 Extension Hill North 16 A

D 2 (A+B pooled) Extension Hill (east side and summit) 14 A

E 3 Extension Hill South 11 B

Unlabelled 4 Iron Hill North (north peak) 10 B

B 5 Iron Hill 14 C (7), D (7)

G 6 Iron Hill East 12 E

MW 7 Unnamed ridge on east side of Iron Hill East Not sampled NA

A 8 Mt Gibson 13 F

F 9 Mt Gibson South 18 G (17), H (2)

Unlabelled 10 Iron Hill Central Not sampled NA

Total 8 sub-populations 106 samples 8 haplotypes

Figure 6: Distribution of observed chloroplast haplotypes. Shading indicates different haplotypes.


3.3 Population genetic structure - Lepidosperma gibsonii

3.3.1 Populations and markers

ATA (2006) first estimated the total known population of L. gibsonii at 17,500 plants. Subsequent

work by the Department of Parks and Wildlife has increased this estimate to 60 to 70,000 individuals

(Department of Parks and Wildlife, 2014). An initial genetic survey of Lepidosperma gibsonii using an

unspecified number of microsatellite markers was based on 145 samples from seven sub-populations

on the Mt Gibson range system. Subsequently to that report, additional sub-populations were

identified off the Mt Gibson Range, with one new sub-population identified at Mt Gibson South at

the extreme southern end of the range. Samples from an additional six sub-populations were

collected, giving a total of 292 samples from 13 sub-populations as detailed in Table 6.

Table 6: Summary of Lepidosperma gibsonii sub-population distribution & sampling characteristics

Sub-population Sample number

Mt Gibson Range

A - Mt Gibson 20

C - Extension Hill North 20

D – Extension Hill 25

E – Extension Hill South (west side) 22

I - Extension Hill South (east side) 25

J – Iron Hill 21

K – Mt Gibson (south end) 12

MG Saddle – (between Mt Gibson & Mt Gibson Sth) Unspecified

MGS – Mt Gibson South Unspecified

North of the Mt Gibson Range

EFN – Emu Fence North Unspecified

EFS – Emu Fence south Unspecified

West of the Mt Gibson range

WC – western breakaway north end Unspecified

WD – western breakaway south end Unspecified

Total 292

3.3.2 Population differentiation (within species)

3.3.2.1 AMOVA

The initial study (Barrett et al., 2006) found high levels of microsatellite variation and low population

differentiation. AMOVA partitioned 98% of genetic variation within sub-populations, and 2%

between sub-populations.

Genetic differentiation was also tested in this study using Fisher’s Exact Test, which did not detect

any population differentiation significantly different from that expected assuming all sub-populations


are freely inter-breeding. This in turn suggests gene flow between sub-populations is high

(presumed due to wind pollination).

In contrast to the first study, analysis of molecular variance in the second study (Miller and Barrett,

2010) partitioned 96% of variation within sub-populations, and 4% between sub-populations. The

authors concluded that this indicated weak population structure (weak differentiation between

localities).

3.3.2.2 Principal coordinates analysis

The low level of variation between sub-populations found by Miller and Barrett (2010), illustrated in

Figure 7, where samples belonging to the same sub-population do not group together, but are

completely intermixed, i.e. any individual is just as closely related to individuals in other sub-

populations as to individuals in the same sub-population).

Figure 7: Lepidosperma gibsonii principal coordinates analysis

3.3.2.3 Pairwise comparisons

Pairwise permutation tests in the initial microsatellite study using seven spatially separate sub-

populations (Barrett et al., 2006) found no significant, genetically distinct sub-populations of

L. gibsonii.

In contrast, the same analysis in the second study by Barrett et al. (2006) using 13 sub-populations

found a few significant comparisons, in particular, the sub-population from Mt Gibson Saddle, which

is statistically supported (p< 0.001) as being genetically ‘isolated’ from nearly all remaining sub-

populations (Table 7). However, it was most similar (and not significantly different) to samples

directly to the north at Mt Gibson (south end).

Geographically, the Mt Gibson Saddle sub-population is only moderately isolated from other sub-

populations, and intermediate between sub-populations that are genetically uniform. In contrast,

the samples from the sub-population at the end of the range at Mount Gibson South were similar to

other sub-populations, other than Extension Hill at the range’s northern end.


Plants from neither of the sub-populations (C and D) to be cleared by pit development on Extension

Hill are supported as being genetically distinct from other sub-populations, except both are isolated

from the Mt Gibson Saddle sub-population, and D is isolated from the Mt Gibson South sub-

population at the southern extremity of the range.

Table 7: Pairwise permutation test of population differentiation for Lepidosperma gibsonii

Possible explanations given for the putative genetic isolation of the Mt Gibson Saddle sub-population

of L. gibsonii are:

physical isolation;

inbreeding in small sub-populations; or

strong selection at one or more linked loci.

It is of note that the location of the Mt Gibson Saddle sub-population of L. gibsonii corresponds to

the location of the genetically isolated sub-population “F” of D. masonii (refer Appendix 2). Given

the continuum of variation shown in Figure 5, this may indicate a gap in physical distance between

sub-populations rather than genetic isolation. Similarly for D. masonii, it may be a function of the

physical distance of sub-population “F” from other sub-populations (as indicated in Figure 5 by the

point at the extreme right of the diagram).

3.3.3 Population genetic diversity (within and between species)

3.3.3.1 Genetic diversity (Heterozygosity)

Genetic diversity within and between sub-populations of L. gibsonii and diploid sub-populations of

the L. costale complex (measured by Unbiased Heterozygosity) was similar, with a range of 0.507-

0.759 for L. gibsonii and 0.576-0.715 for L. costale (Table 8 and Figure 8).

3.3.3.2 Inbreeding (Fixation index)

Fixation index was low within and between sub-populations of L. gibsonii and diploid sub-populations

of the L. costale complex, and suggests a low but significant level of inbreeding. It may also indicate

assortative mating. The range in Fixation index was 0.044-0.261 for L. gibsonii and 0.088-0.243 for

diploid sub-populations of the L. costale complex (Table 8 and Figure 8).

Although sampled sub-populations of both L. gibsonii and L. costale were sometimes quite small (e.g.

sub-populations EFN and Beanthiny Hill, where the c. 25 sampled plants represent most or a

significant portion of the entire sub-population), the fixation index data suggest there is limited


evidence of inbreeding and population bottlenecks, suggesting either that gene flow is high over the

scale of these populations (quite possible given the wind-dispersed pollen), or that the current small

populations are relicts of past populations, and their observed diversity is due to persistence of

plants dating from a period of greater population size.

Table 8: Heterozygosity and fixation – L. gibsonii and L. costale complex

Species Homozygosity

(Ho)

Heterozygosity (He) Unbiased

Heterozygosity (UHe)

Fixation Index (F)

Range Mean Range Mean Range Mean Range Mean

L. gibsonii

(13 sub-

populations)

0.407-

0.638

0.549

+/-0.022

0.493-

0.733

0.660

+/-0.014

0.507-

0.759

0.676

+/-0.015

0.044-

0.261

0.175

+/-0.026

L. costale complex

(4 sub-

populations)

0.454-

0.595

0.533 0.565-

0.699

0.625 0.576-

0.715

0.642 0.088-

0.243

0.186


Figure 8: Heterozygosity and fixation – L. gibsonii and L. costale complex

Ho = Observed heterozygosity

He = Expected Heterozygosity

UHe = Unbiased expected Heterozygosity

F = Fixation Index

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. gibsonii Ho

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. gibsonii He

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. gibsonii UHe

0

2

4

6

8

10

-0.1 0 0.1 0.2 0.3 0.4 0.5

Freq

uen

cy

L. gibsonii F

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. costale Ho

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. costale He

0

2

4

6

8

10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Freq

uen

cy

L. costale UHe

0

2

4

6

8

10

-0.1 0 0.1 0.2 0.3 0.4 0.5

Freq

uen

cy

L. costale F


4. Benchmark review

4.1 Comparison of data interpretation and conservation implications

The most notable difference in the outputs of the test results for population genetic structure

reported in Miller and Barrett (2010) is that AMOVA results for both DRF species indicate weak

genetic structure, but results of Principal Coordinates Analysis indicate samples from different sub-

populations are completely intermixed (as closely related to individuals in other sub-populations as

to individuals in the same sub-population). Pairwise comparisons support the AMOVA results,

indicating a number of sub-populations for which there is statistically significant evidence (p< 0.001)

for departure from random mating. This inconsistency is acknowledged in the report. This means

that, while an effect is statistically detectable between certain groupings, it is not pronounced or

large.

The later report for D. masonii (Barrett and Krause, in prep.) provides evidence for a level of genetic

structuring, with general overlap between sub-populations, but predominant divergences between

some sub-population pairs (Figure 3). The pattern for distribution of chloroplast haplotypes (Figure

6), and the positive correlation between Nei’s genetic distance and geographic distance (Figure 5)

adds further weight to geographic genetic structuring of the D. masonii population, generally from

one end of the range to the other.

Due to evidence for weak genetic structuring for both DRF populations, the 2010 study recommends

that the precautionary principle should apply to avoid mixing genotypes between sub-populations

without careful consideration of consequences.

It is a feature of both DRF species that the sub-populations studied comprise relatively small

numbers of individuals. It is noted for Lepidosperma species that for some sub-populations, sampled

individuals (approx. 25) represented most of the sub-population. While sub-population sizes are not

specifically reported (Table 6), the identification of individual plants on distribution maps (Miller and

Barrett, 2010, Figure 1) indicates that the size of some sub-populations is not large.

In contrast to the conclusion drawn from pairwise analyses that a number of sub-populations of each

DRF species are genetically isolated, the finding of different allelic frequencies between

geographically isolated sub-populations is an expected result that is consistent with the finding that

94 to 96% of genetic variation is within sub-populations and 4 to 6% (10%) of genetic variation is

between sub-populations, or that samples from different sub-populations are completely intermixed

(as closely related to individuals in other sub-populations as to individuals in the same sub-

population).

4.1.1 Random drift

The assumption of Hardy-Weinberg equilibrium, or stable gene and genotype frequencies from

generation to generation (in the absence of migration, mutation or selection) is the property of a

large population with random mating. This property of stability does not necessarily hold for small

populations, where gene frequencies are subject to random fluctuations arising from sampling of the

gametes (Falconer, 1990). The gametes that transmit genes from one generation to the next carry a

sample of the genes from the parent generation and, if the sample is not large, the gene frequencies


are liable to change between generations (Falconer, 1990). The random change of gene frequency is

known as the dispersive process. Falconer (1990) identifies four ways of viewing consequences that

may arise from the dispersive process:

1. Random drift: Gene frequency in a small population may change in an erratic manner from

one generation to the next, with no tendency to revert to its original value;

2. Differentiation between sub-populations: Random drift occurring independently in

different sub-populations leads to genetic differentiation between sub-populations;

3. Uniformity within sub-populations: Genetic variation within each sub-population becomes

progressively reduced;

4. Increased homozygosity: Homozygotes increase in frequency at the expense of

heterozygotes due to a level of inbreeding.

The consequence of unrepresentative gene sampling in small populations that leads to random drift

is illustrated in Figure 9. In this diagram, there are 12 lines (genotypes) in each population, with two

population sizes - 10 (upper panel) and 100 (lower panel). The two populations are subject to natural

selection favouring the wild-type allele.

For the larger population, a gradual increase in frequency of the wild-type allele is observed in

response to selection, with individual lines tightly clustered around the mean. For the small

population, any individual line illustrates erratic change in gene frequency between generations, so

this random drift in each line manifests in progressive differentiation between lines.

Figure 9: Random drift in a population where natural selection favours the wild-type allele

(Falconer, 1990)


The expected result of the dispersive process includes:

differentiation between the inhabitants of different localities;

differences between successive generations.

Both these conditions are well-known in sub-divided or small isolated populations (Falconer, 1990).

Notwithstanding, other possible causes may include variation in environmental conditions between

localities and seasons, with corresponding variation in the intensity and direction of selection.

To attribute differentiation between the inhabitants of different localities to genetic drift alone

requires knowledge of:

effective population size now and in the past;

whether or not sub-populations are sufficiently well isolated (or the size of the

neighbourhoods sufficiently small); and

whether or not the genes concerned are subject to selection.

Past population size effects giving rise to dispersion may include:

restriction in population numbers due to unfavourable seasons; or

colonisation of a new area by a small number of individuals (Founder Effect).

In the former, the dispersion taking place in generations of lowest numbers may be permanent and

cumulative. In the latter, random drift may be substantial in the first generation. If a population

expands, dispersion may seem too great to be consistent with present numbers.

In contrast, even a low level of selection may be sufficient to counteract dispersion in all but the

smallest populations.

While pairwise analysis may indicate isolated sub-populations, these may indeed be genetically

isolated at one extreme, or may be arbitrarily bounded portions of a continuum at the other. Gene

frequencies may be distributed at random in the total population, or in an orderly cline (Long et al.,

1987).

These consequences of the dispersive process acting on small populations appear to reflect the

available genetic study results:

The majority of observed variation is within sub-populations, with only limited variation

between sub-populations;

Pairwise comparisons between each small sub-population indicate some sub-populations

that display allelic frequencies that differ from the wider population (putatively as a

consequence of random drift);

Genetic variation expressed as heterozygosity is reduced relative to values expected in fully

outcrossed, large populations; and

Homozygosity (and inbreeding), expressed as Fixation Index is increased relative to values

expected in fully outcrossed, large populations.


4.1.2 Wahlund effect

The various BGPA study results indicate low but statistically significant levels of inbreeding,

evidenced by estimates of Fixation Index values significantly greater than zero. This is postulated as

support for restricted gene-flow between sub-populations.

The Wahlund effect provides another explanation for the observation of Fixation Index values

significantly greater than zero and, indeed, is an expected outcome for nearly all populations. The

Wahlund effect arises due to the fact that, in virtually all populations, individuals tend to mate with

those that are nearby. This may arise due to nearest neighbour pollination in flowering plants or

home-site fidelity in animals, which can cause mates to be selected in a geographically non-random

way (Holsinger, 2012). Stated another way, it is a feature of small population size that pairs mating

at random are more closely related to each other in small populations than in a large one (Falconer,

1990). In this regard, F is the cumulative effect of random drift.

This Wahlund effect can be appreciated when considering the pattern of pollen dispersion in tree

species. Numerous studies indicate a rapid decline in pollen load with distance from the source,

particularly for wind pollinated species (Potts et al., 2001; Jones et al., 2008; Barbour et al., 2005).

An example is illustrated in Figure 10.

Figure 10: Dispersal of pollen with distance indicated by hybrid progeny of synchronously flowering

Eucalypt species (Potts et al., 2001)

The rate at which pollen flow declines with distance tends to vary according to the nature of

pollinators, with birds generally moving more widely than insects (Ford et al. 1979; Eldridge et al.

1993; Paton 1993). Curiously, the results of Miller and Barrett (2010) indicate a higher level of gene

flow between sub-populations for wind-pollinated L. gibsonii than for bird pollinated D. masonii.

Notwithstanding, since individuals that occur close to one another tend to be more genetically

similar than those that occur far apart, the population genetic consequences of non-random mating

due to proximity will mimic those of inbreeding within a single, well-mixed population (Holsinger,

2012). The observed results for Fixation Index are therefore a wholly expected outcome for the sub-

populations studied.


4.1.3 Allelic frequencies

Microsatellite makers were used to amplify a total of 157 alleles from 15 loci for D. masonii (an

average of 10.5 alleles per locus). Allele number per locus ranged from 2 to 30. The frequency

distribution is illustrated in Figure 11.

Figure 11: Frequency distribution of alleles per locus for D. masonii

The representation of alleles across 10 sampled and tested sub-populations varied significantly. In

general, alleles occurring at a low frequency across the entire population also occurred in a small

number of sub-populations as illustrated in Figure 10. This result, derived from allele frequency x

sub-population data provided to Verterra by Matt Barrett, supports limited genetic differentiation

among sub-populations. Evidence of strong genetic differentiation (and limited gene-flow) would be

indicated by the occurrence of alleles at medium to high frequency in a limited number of sub-

populations. This is not the case in Figure 12.

Figure 12: Derived relationship between allele frequency in the total population, and occurrence in

D. masonii sub-populations

0

1

2

3

4

5

6

7

5 10 15 20 25 30

Fre

qu

en

cy

Number of alleles per locus

0

2

4

6

8

10

12

0.000 0.200 0.400 0.600 0.800 1.000

Nu

mb

er

of

sub

-po

pu

lati

on

s in

w

hic

h a

llele

occ

urs

Frequency in total population


4.1.4 Migration and recruitment

Using the private allele method, Barrett and Krause (in prep.) report the effective level of gene flow

(Nm) for D. masonii at 4.4 individuals per generation between sub-populations. The authors report

that the value of Nm =4.4 suggests a moderate number of migrants (either via pollen or seed)

between sub-populations of D. masonii, consistent with the low genetic differentiation and weak

observed structure, and that migration is biased by distance, as indicated by presence of population

structure and isolation by distance.

In a comparable study, Ge et al. (2003) found Nm for the endangered Inner Mongolia endemic shrub,

Tetraena mongolica to be 1.223 individuals per generation between sub-populations. In that

population, AMOVA analysis partitioned 84.8% of total genetic diversity within sub-populations and

15.2% between sub-populations. These partitioning values indicate a much higher level of genetic

structuring between sub-populations than found for D. masonii.

Notwithstanding, Ge et al. (2003) suggested the effective gene flow per generation (Nm =1.223),

greater than one successful migrant per generation, was indicative of considerable gene flow among

sub-populations that effectively homogenized these to some degree. Similarly, Ellstrand and Elam

(1993) considered a migration rate of 0.5 sufficient to overcome diversifying effects of random drift.

These conclusions from other studies contrast the conclusions of Barrett and Krause and suggest

that, despite statistical evidence for population structuring, a biologically effective level of gene flow

between sub-populations is likely to be operating. Notwithstanding, Larsen et al. (1984) suggest that

effective levels of gene flow may differ greatly among species.

4.2 Conservation strategy options

Notwithstanding details of the occurrence of genetic structuring within populations of D. masonii and

L gibsonii, or the basis for development of such structuring, the key consideration for these species is

how findings of the genetic studies undertaken to date can best be applied to further the

conservation of these two DRF species. In this regard, an important question arises:

“Should conservation efforts be aimed at maintaining genetic diversity (the range of allelic variants

occurring within and across each sub-population) or genotype diversity (the packages of alleles and

allele frequencies inherent in different sub-populations)?”

The answer to this question has important implications for not only a conservation strategy per se,

but also for maximising potential long-term species fitness and capacity for survival and recovery,

including in response to other anthropogenic influences such as fire frequency, and influences such

as climatic variability. This question will first be explored by consideration of conservation strategies

adopted for other species, and later, by consideration of the evolutionary consequences of

alternative conservation strategy options.

4.2.1 Findings from comparative studies

Table 9 presents a summary of population statistics from a wide range of comparative studies

spanning the range from unstructured (all genetic variance occurs within sub-populations and none

occurs between sub-populations), to studies where the minority of genetic variance occurs within


sub-populations and the majority occurs between sub-populations. Individual studies along this

gradient are discussed in detail in the following sections.

Before reviewing these studies, it can be seen from Table 9 there is a clear trend (with some

exceptions) for outcrossing species to be characterised by a greater proportion of genetic variation

occurring within rather than between sub-populations, while inbreeding species are characterised by

the majority of genetic variation occurring between rather than within sub-populations. This is a

wholly expected outcome. For example, when taken to the extreme, no genetic variation will occur

within sub-populations comprised of highly inbred commercial crop varieties, and all variation will

occur between sub-populations, each comprised of different varieties.


Table 9: Summary of population statistics from comparative studies of (predominantly) rare plant species

Species Reference No of sub-

populations

Informative

markers

Within sub-

population

genetic

variance

Between sub-

population

genetic

variance

Significant

pairwise

Population

structure /

differ-

entiation

Ho He UHe Shannons

Diversity

Index

F Max.

distance

between sub-

populations

(km)

Breeding

system

Banksia cuneata5 Maguire and Sedgley (1997) 10 169 104.7% -4.7% NR Nil 195 Outcrosser

E. phylacis5,6 Rossetto et al. (1999) 1 (173 stems) 0 100% 0% Outcrosser

Populus tremuloides Yeh et al. (1995) 8 28 97.4% 2.6% Yes7 0.58 - 0.69 607a Outcrosser

Lepidosperma gibsonii5 Miller and Barrett (2006) 13 8 (130 alleles) 96% 4% Yes (1/13) Weak 0.454-0.595 0.565-0.699 0.576-0.715 0.088-0.243 8 Outcrosser

Dawinia masonii5 Miller and Barrett (2010) (Barrett and Kraus, in prep.)

7 (9)

14 (NR) 15 (157 alleles)

94% (92%

6% (8%)

Yes (2/7) NR

Weak (Weak)

0.407-0.638 (0.503-0.650)

0.493-0.733 (NR)

0.507-0.759 (0.519-0.685)

0.044-0.261 (-0.071-0.135)

6 Outcrosser

Eucalyptus risdonii5 Sale et al. (1996) 91.4% 8.6% ? Outcrosser

Grevillea scapigera5 Rossetto et al. (1995) 4 167 87% 13% 0.20-0.328 540 Outcrosser

Grevillea barklyana5 Hogbin et al. (1998) 87% 13% 20 Outcrosser

Hippophae rhamnoides Bartish et. al. (1999) 85% 15% 4.5 Outcrosser

Tetraena mongolica Ge et al. (2003) 8 79 84.8% 15.2% NR Yes (P<0.001) 0.161-0.208 0.177-0.213

9

0.213-0.305 122 Outcrosser

Eucalyptus globulus5 Nesbitt et al. (1995) 74 149 80.2% 19.9% 150 Outcrosser

Buchloe dactyloides Huff et al. (1993) 72.9-80.5% 19.5–27.1% 70 Outcrosser

Zieria prostrata Hogbin and Peakall (1999) 63% 37% 3 Selfing?

Hordeum spontaneum Dawson et al. (1993) 57% 43% 250 Selfing

Medicago trunculata Bonnin et al. (1996) 55.2% 44.8% 200 Selfing

Limonium dufourii Palacios et al. (1997) 45.4% 54.6% 231a Selfing

Saxifraga cespitosa Tollefsrud et al. (1998) 41.9% 58.1% > 700 Selfing

Acacia raddiana Shrestha et al. (2002) 12 290 40.6% 59.4% Strong 258 Outcrosser

Vicia dumetorum Black-Samuelsson et al. (1997)

36.5% 63.5% 1241a Selfing

Vaccinium macrocarpon Stewart and Excoffier (1996) 33.1% 66.9% ? Selfing

5 Endemic Australian species

6 An extreme example, representing a single stand comprising 173 stems, all believed to be a single clone and as a result, possibly the rarest, largest, potentially oldest mallee eucalypt known

7 18 of 28 population pairs

8 Variability , where Variability = 1-S and S = similarity

9 Nei’s expected heterozygosity Ht at the species level


4.2.2 Studies along the gradient of variance between sub-populations

4.2.2.1 Banksia cuneata, Maguire and Sedgley, 1997

Banksia cuneata is a rare and endangered species known only from 10 sub-populations (550 plants)

in the central area of south-western Australia in an area of 90 km2 (Maguire and Sedgley, 1997).

Maximum distance between extreme sub-populations is approximately 195km. Banksia cuneata

occurs on deep yellow sands which occupy 10—15 per cent of the area, giving it a fragmented

distribution. Land clearing for agriculture and other disturbances over the last 50 to 60 years has

reduced the B. cuneata population size to about 7 per cent of its original distribution. Four sub-

populations comprise > 50 plants, three comprise 10-50 plants and three comprise <10 plants.

A total of 125 plants (approx. 25% of the entire population) were sampled for this study using 169

informative RAPD genetic markers. Prior studies using allozyme markers (Coates and Sokolowski,

1992) indicated high outcrossing rates ranging from 0.67 to 0.95, with low levels of selfing.

Analysis using 169 RAPD genetic markers found genetic diversity to be high for a geographically

restricted rare and endangered species. Diversity within sub-populations (using the method of Nei

and Li, 1979) ranged from 0.65 to 0.74, being highest in the larger, least disturbed sub-populations.

AMOVA analysis attributed all genetic variation to individuals within sub-populations. Analysis

between sub-populations showed a small negative variance component, indicating lack of population

structure, with some plants being more related between sub-populations than within.

The results of Maguire and Sedgley (1997) contrast with a prior study of six sub-populations using six

polymorphic allozyme markers (Coates & Sokolowski, 1992), which found significant differentiation

of sub-populations into east and west groups, and gene flow within groups but not between them,

suggesting an ecological barrier (possibly a salt river system) to pollinator movement. Maguire and

Sedgley (1997) fail to speculate on the basis for the contrasting result, but it may possibly be due to

the small number of makers used in the study by Coates & Sokolowski (1992).

The lack of significant genetic differentiation between sub-populations found using RAPD markers

may be due to the remnant sub-populations being visited by bird pollinators which, in turn, are

supported by the presence of surrounding vegetation. It is also possible that the sub-populations are

ageing and there have been too few generations since clearing to see significant genetic

differentiation. The results point to the importance of maintaining reserves of coexisting vegetation

to support pollinators.

4.2.2.2 Eucalyptus amygdalina and E. risdonii hybrid swarm, Sale et al., 1996

Sale et al. (1996) used RAPD genetic markers to investigate a natural hybrid swarm between

Eucalyptus amygdalina and E. risdonii and nearby stands isolated from genetic interchange. The

authors found that, despite clear morphological differences, all RAPD bands were shared between

species, however, frequency differences revealed genetic divergence between species, sub-

populations within species, and individuals within sub-populations, with variation greatest between

individuals within sub-populations and lowest between species. Marker results suggested that sub-

population differences were not due to introgression but were the result of genetic isolation and/or

strong localised selection. The study suggests detectable genotypic differences between spatially


close sub-populations of the same species may be as great as or greater than the differences

between species.

4.2.2.3 Grevillea scapigera, Rosetto et al., 1995

Grevillea scapigera is a prostrate, woody perennial, with emergent inflorescences. It is a short-lived,

outbreeding species. Only 27 wild plants were known in early 1994. These were distributed

between four main sub-populations, the largest of which included 16 plants of various ages.

Seeds germinate only after soil disturbance, which naturally may have been fire or fossicking mammal activity but now appears limited to fortuitous road maintenance activities. The species relies on seed banks that can survive in the soil for long periods of time until disturbance events occur. All known sub-populations have been associated with recent mechanical disturbance in isolated remnants of natural vegetation on road verges in a 50-km radius in the wheatbelt region of Western Australia.

AMOVA analysis of 47 plants (27 living wild plants, 15 dead and 5 in-vitro plants) using 169 RAPD

markers attributed most of the variability to single plants, with 87% of genetic variation within sub-

population and 13% between sub-populations.

Variability, calculated as V=1-S where S is the similarity co-efficient, ranged between 0.20 and 0.32

for the four sub-populations. This measure is comparable to Heterozygosity in other studies. The

level of variability, comparable to that for a common species of the same genus, is considered high

given the small number of plants studied.

The study concluded that the absence of major differences between G. scupigera sub-populations

indicates that plants may be safely mixed across sub-populations during the recovery process.

4.2.2.4 Tetraena mongolica, Ge et al., 2003

Tetraena mongolica, the sole species of its genus, is a shrub of 0.5 m in height, endemic to the

western part of Inner Mongolia (Ge et al., 2003). It has a restricted geographic distribution of

approx. 2700 km2, where it occurs primarily in the rocky or sandy Gobi desert, characterized by an

average annual rainfall of 139 mm. Seedset is as low as 1.9% (Wang et al., 2000, cited by Ge et al.,

2003), although the seeds display a 90% germination rate. The species was locally dominant but has

declined in recent decades due to harvesting for firewood habitat destruction resulting from a rapid

human population increase and associated habitat destruction (Ge et al., 2003).

A total of 192 individuals were sampled representing eight sub-populations throughout the species’

entire range (over a maximum extent of approx. 121km). AMOVA analysis found 84.8% of total

genetic variation within sub-populations and 15.2% among sub-populations, with no significant

correlation between genetic distance and geographic distance (Ge et al., 2003). Sub-populations

shared high levels of genetic identities (I), ranging from 0.9272 to 0.9737 with a mean of 0.950+/-

0.013. The level of gene flow (Nm) was estimated to be 1.223 individuals per generation between

sub-populations.

Within sub-population genetic diversity for this species was expected to be low based on its limited

distribution, but was found to be higher than expected. Using two measures, within sub-population

genetic diversity was 0.324 using the Shannon index (Hsp) and 0.213 for Nei’s expected

heterozygosity measure (HT). Other studies have found Hsp = 0.398 for Isotoma petraea (Bussell,


1999); 0.192 for hex paraguariensis (Gauer and Cavalli-Molina, 2000); and 0.450 for

Swietenia macrophylla (Gillies et al., 1999). Similarly, Mattner et al. (2002) found HT = 0.267 for

Hernigenia exilis. On the basis of these studies, T. mongolica showed an intermediate level of intra-

population genetic diversity.

The effective level of gene flow per generation (Nm) was estimated to be 1.223 individual per

generation between sub-populations. This value is greater than one successful migrant per

generation, indicating considerable gene flow among sub-populations. In T. mongolica, insect

pollination and easily dispersed light seeds (average weight = 1.112 mg) are considered to have

facilitated extensive gene flow that has effectively homogenized sub-populations to some degree

reflecting the present-day structure of genetic variation (Slatkin, 1987). A migration rate of 0.5 is

considered sufficient to overcome the diversifying effects of random drift (Ellstrand and Elam, 1993,

cited by Ge et al., 2003).

Based on the genetic structure of this species, indicating a low amount of genetic differentiation

among sub-populations (15.2%) and high level within sub-populations (84.8%), the authors contend

that a considerable amount of the overall genetic variation of the species could be captured when

sampling a larger number of plants from one or two sub-populations rather than smaller collections

from many different sites. To maintain the genetic diversity of this species through in-situ

conservation, the authors suggest priority should be given to one or two sub-populations displaying

the greatest level of within-population genetic diversity. This should be informed by knowledge of

breeding systems, which will affect the maintenance of variation in the sub-populations.

4.2.2.5 Eucalyptus globulus, Nesbit et al., 1995

Eucalyptus globulus is divided into four subspecies: globulus, bicostata, pseudoglobulus and maidenii.

The complex extends over a wide geographic range from ssp. maidenii in southern NSW, through ssp.

pseudoglobulus and bicostata, to ssp. globulus in Tasmania. The core populations of the subspecies

are geographically and morphologically distinct, but extensive areas of integration occur.

Samples were collected from 173 trees representing 37 localities across the four subspecies. The

samples were analysed using 149 RAPD markers. AMOVA analysis found 74.3% of variation within

locations (range 73.8 to 94.9%) and 19.9% between localities (range 5.1 to 26.2%). This is despite the

large distance over with this species occurs. Patterns of variation indicate that variation in this

species is consistent with a latitudinal cline.

The pattern of variation suggests that sampling from a few localities for either breeding or

conservation may capture a large proportion of the genetic variation; however, sampling from range-

wide localities is still advisable due to significant differences between localities. In addition, the

distribution of genetic marker variation may not reflect the pattern of variation in adaptive genes,

although observations indicate they are consistent with results obtained for growth traits.

4.2.2.6 Acacia raddiana, Shresthaa et al. (2002)

There is widespread concern over the mortality of the three native Acacia tree species (Acacia

raddiana, A. tortilis and A. pachyceras in the Negev desert of Israel. Total mortality of Acacia trees

varies widely and may reach as high as 61% in some sub-populations. This mortality is reputed to be

an effect of water limitation imposed by anthropogenic misuse. Recruitment of young seedlings is


rare and there is high seed infestation by bruchid beetles. It is not known whether or not diminished

genetic diversity has resulted from this population decline.

The study sampled 8 to 25 individual trees per sub-population and 12 isolated natural sub-

populations of A. raddiana, chosen to represent a range of different geographical locations.

A. raddiana is confined largely to the major wadis (ephemeral rivers) in the Negev and sub-

populations are effectively isolated from one another, except in those cases where the rivers join

where they enter the Arava valley. The two sub-populations from the extreme ends of the

distribution (north to south) were located approximately 258 km apart.

RAPD markers revealed a high level of polymorphism within sub-populations, with 18 primers

generating 290 markers. Of these, 90.69% were polymorphic. This result was contrary to the

conventional expectation of small, isolated sub-populations (Shrestha et al., 2000).

AMOVA revealed that 59.4% of the total genetic variance occurred among sub-populations and

40.6% occurred among individuals within sub-populations, indicating that there is a high degree of

population differentiation. Similarly, an AMOVA of geographic regions revealed that 37% of total

variation was distributed among Arava valley and western Negev sub-populations (including ZE’ELIM)

and 63% among individuals within geographic regions. The high sub-population divergence in

A. raddiana was mainly due to divergence among Arava valley and western Negev sub-populations

(including ZE’ELIM).

Principal coordinates analysis revealed that there is very little overlap among sub-populations and

that groups of sub-populations are not strictly defined on the basis of geographic distance. This

result supports the AMOVA result.

This level of population differentiation is far higher than is usually encountered in outcrossing

species. A high level of population differentiation may be explained by several factors, including the

species’ breeding system, genetic drift or genetic isolation of sub-populations (Hogbin and Peakall,

1998).

The divergence among A. raddiana sub-populations may be explained by genetic drift due to limited

gene flow caused by a combination of disruption to streamflow by road-crossings, and disruption to

dispersion by herbivores due to reduction in the number of wild herbivores and limitations imposed

on movements of domestic livestock.

Due to the extensive genetic divergence detected among A. raddiana sub-populations, the authors

recommend that each sub-population should be conserved separately because they are genetically

different and loss of any one sub-population would lead to a dramatic loss of genetic variation. Also,

the mixing of genetically distinct sub-populations may give rise to outbreeding depression, whereby

reductions in fitness arises due to loss of local adaptation or breakup of co-adapted gene complexes

(Templeton, 1986).

4.2.2.7 Multi-paper literature review, Nybom and Bartish, 2000

In a review of 84 papers published in the period 1993–2000 using RAPD markers for evaluating

population differentiation, Nybom and Bartish (2000) affirmed the results of prior studies indicating

that long-lived, outcrossing, late successional (climax) taxa retain most of their genetic variability

within sub-populations, while annual, selfing and/or early successional taxa allocate most of the


genetic variability among sub-populations. Moreover, in outcrossing taxa, estimates of between-

sub-population diversity were closely correlated with maximum geographic distance between

sampled sub-populations, whereas a corresponding association was not found in selfing taxa.


5. Discussion

5.1 Benchmarking conservation options for D. masonii and L. gibsonii

The genetic structure of plant populations reflects the interactions of different processes including

the long-term evolutionary history of the species (shifts in distribution, habitat fragmentation, and

sub-population isolation), mutation, genetic drift, mating system, gene flow, and selection (Slatkin,

1987; Schaal et al., 1998; cited by Ge et al, 2003).

As seen in the case studies, examples exist for rare and threatened plants ranging from lack of

genetic structure with all genetic variation residing within sub-populations (Maguire and Sedgley,

1997), to a high degree of population differentiation with only 40.6% of total variation distributed

within sub-populations and 59.4% between sub-populations (Shresthaa et al. ,2002).

Compared to the case studies discussed above, results for both D. masonii and L. gibsonii indicate a

relatively low level of genetic divergence between sub-populations, relatively high gene flow and

high level of allelic diversity. Zawko et al., 2001 (cited by Ge et al., 2003) suggest high diversity and

low population partitioning in rare plants may be attributed to a number of factors, including:

insufficient length of time for genetic diversity to be reduced following a natural reduction

in population size and isolation;

adaptation of genetic system to small population conditions;

recent fragmentation (human disturbance) of a once continuous genetic system; and

extensive gene flow due to the combination of bird pollination and high outcrossing rates

(Maguire and Sedgley, 1997).

The case studies illustrate a trend in recommended conservation strategy from:

species with weak genetic divergence where recommendations centre around capturing a

larger number of plants from one or two sub-populations rather than smaller collections

from many different sites, with priority given to the one or two sub-populations displaying

the greatest level of within-population genetic diversity and that plants may be safely mixed

across sub-populations during the recovery process; to

species with strong genetic divergence where recommendations centre around each sub-

population being conserved separately because loss of any one sub-population would lead

to a dramatic loss of genetic variation, and mixing of genetically distinct sub-populations

may give rise to outbreeding depression.

The findings relating to D. masonii and L. gibsonii suggest the use of the former conservation

strategy.

For all species, the case studies highlight the importance of other factors including:

the importance of maintaining reserves of coexisting vegetation to support pollinators;

a knowledge of breeding systems, which will affect the maintenance of variation in the

populations; and

considering the distribution of genetic marker variation, which may not reflect the pattern

of variation in adaptive genes.


5.2 Interpretation of findings for species conservation and recovery

One of the primary objectives of nature conservation is the maintenance of genetic diversity (Ge et

al., 2003). The preservation of genetic diversity is a fundamental aim of conservation, since genetic

diversity ameliorates survival potential by enhancing the adaptation of a species to present and

future environmental changes (Rossetto et al., 1995; Frankel and Soule, 1981). Quoting from

Shresthaa et al. (2002):

“Genetic diversity within populations is considered to be of great importance for

possible adaptation to environmental changes and consequently, for long-term survival

of a species (Vida, 1994). Without an appropriate amount of genetic diversity, species

are thought to be unable to cope with changing environments and evolving competitors

and parasites (sensu the Red Queen Theory; Van Valen, 1973). One of the necessary

consequences of evolution in a small population is the loss of genetic variation via

genetic drift (Wright, 1951). Because future evolutionary adaptation depends on the

existence of genetic variation, loss of variation reduces the possibility of future

adaptation. A second consequence of the loss of genetic variation is that the number of

homozygous individuals necessarily increases within a population. Such inbreeding may

be associated with a reduction in individual fitness. Thus, maintenance of (or at least

quantification of) genetic variation is currently regarded as a primary goal in

conservation efforts (Falk and Holsinger, 1991; Hoelzel, 1992).”

Thus to preserve genetic diversity in a species is to preserve its evolutionary potential (Shresthaa et

al., 2002).

Coming back to the question raised in Section 4.2:

“Should conservation efforts be aimed at maintaining genetic diversity (the range of

allelic variants occurring across each sub-population) or genotype diversity (the

packages of alleles and allele frequencies inherent in different sub-populations)?”

Consideration of the population genetic structure of both D. masonii and L. gibsonii populations,

strongly supported by evidence for conservation recommendations for a range of other

(predominantly rare and threatened) species, is that conservation of these species would best be

served by a strategy that maximises whole-of-population genetic diversity by:

1. Sampling germplasm from across the range (thereby capturing representative samples of

both nuclear allelic and chloroplast haplotype variants); and

2. Promoting inter-breeding of genotypes to the greatest possible extent to facilitate inter-

mixing of the available pool of common and rare alleles, and thereby preserve the

evolutionary potential of the two species to adapt to changing environmental, climatic,

biological and anthropogenic conditions.

Conversely, conservation of the two DRF species would not be well served by primarily maintaining

the weak isolation of the existing sub-populations or “allelic cohorts”. Miller and Barrett (2010)

recommended, based on evidence for weak population structuring, that the precautionary principle

should be adopted to avoid mixing genotypes between (sub) populations. However further

consideration of consequences should be given. The precautionary principle is often applied as a

means to avoid unintended consequences where outcomes are uncertain, but in this case it may


constitute a default decision to take a deliberate action (by avoiding full population mixing) where

the available evidence supports taking the alternative action of promoting sub-population mixing to

preserve genetic diversity and evolutionary potential of the two DRF species in the face of changing

natural and anthropogenic influences.

Having regard to approaches that best support the preferred conservation strategy, it is also

important that the broader “enabling” habitat requirements for successful plant reproduction,

propagation and cultivation are addressed including:

coexisting vegetation community diversity and structure to support pollinators (esp. for

Darwinia);

knowledge of breeding systems and capacity to promote inter-breeding, to support

maintenance of variation in the population, and ensure capacity to produce and store viable

propagules;

knowledge of growing condition requirements (physical, chemical, biological) to support

successful translocation and cultivation;

knowledge of environmental and stress interactions in order to inform relevant

management strategies.

Considerable good work has been carried out on these aspects to date (in particular, Miller and

Barrett (2010). The relevant findings of this research should be implemented in managing mine-

disturbed areas and the wider populations of both DRF species.

5.3 Practical application to mine development and rehabilitation

Practical application of the recommended genetic conservation strategy to mine development and

rehabilitation requires the collection and management of an ex-situ gene conservation bank to

provide the capacity to produce seed and/or seedlings for use in post-mining rehabilitation. This

could be sited remotely, but if sited locally could expand the effective population size (or provide

partial compensation of the reduced population size that will occur as a result of clearing for mine

development). The ex-situ gene conservation bank should aim to capture “genes” as opposed to

genotypes of both DRF species from both the mine development area as well as undisturbed areas.

Collection of seed from undisturbed areas should be at a level that does not- compromise natural

seed-based regeneration.

The demonstrated capacity to store and propagate seed of D. masonii will enable a gene-pool to be

captured and secured in advance of mine development and associated disturbance, will reduce the

risk associated with loss of plants. Notwithstanding, translocated plants may also contribute to

establishment of this ex-situ bank once mining disturbance commences. The floristic composition

and structure of vegetation surrounding ex-situ gene conservation bank will need to provide

conditions conducive to natural bird pollinators and ideally promote movement of pollinators

between natural and ex-situ populations.

The difficulties encountered with propagation of L. gibsonii seed may require a different strategy.

This may require a combination vegetative propagation by harvesting and re-location of partial

clumps, combined with attempts at seed harvesting and germination by the best available means

(e.g., seed coat removal and heat treatment, or retrieval of buried seed). As for D. masonii, the

strategy should also aim to establish ex-situ stock prior to site development.


5.4 Recommendations for future work and research

Although some aspects of the genetic structure of D. masonii and L. gibsonii remain unresolved,

additional work in this area is only expected to offer refinements to the current status of genetic

knowledge, which, with the work carried out to date, can be considered superior to the conservation

genetic knowledge of many other species, both threatened and common species with important

commercial, cultural or environmental value. The work of Barret et al., (2005, 2006), Miller and

Barrett (2010) and Barrett and Krauss (in prep.), is both valuable and informative. When it is

considered in the context of other species, the approach to conserving genes from across the

population and promoting inter-breeding to preserve the evolutionary potential of both species is

clear, and independent of any further finer-scale understanding of population differentiation.

Rather, further research should focus on matters that influence the effective management of the two

species, both in response to mine disturbance, other anthropogenic disturbance, and natural

environmental influences. These matters are largely addressed by the Restoration Strategy

developed by EnPeritus (2014) for Mount Gibson Mining.


6. References

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Report to Mt Gibson Iron Ltd. from ATA Environmental, Report No. 2006/090 Version 2 August

2006.

Barrett, M., Krause, S., and Dixon, K. (2005). Research benchmarks for conservation of Darwinia

masonii at Mt Gibson: Stage 1 Report. BGPA D. masonii Stage 1 Project Report. BGPA

Genetics Laboratory Report 29. Research report to Mt Gibson Iron Ore. 35pp.

Barrett, M., Anthony, J., Bradbury, D., Messina, G. Krauss, S. and Dixon, K. (2006). An integrated

research program into practical outcomes for the ex situ and in situ conservation, restoration

and translocation of the Lepidosperma sp. Mt Gibson. Phase One: Genetic Variation. Research

Report to Mt Gibson Mining Limited September 2006. 58pp.

Barrett, M. and Krauss, S. (In prep.). Consequences of habitat loss on genetic diversity in Darwinia

masonii (Myrtaceae), a rare ironstone endemic shrub.

Bussell, J.D., (1999). The distribution of random amplified polymorphic DNA (RAPD) diversity

amongst populations of Isotoma petraea (Lobeliaceae). Molecular Ecology 8, 775–789.

Barbour, R.C., Potts, B.M. and Vaillancourt, R.E. (2005). Pollen dispersal from exotic eucalypt

plantations. Conservation Genetics (2005) 6:253–257.

Botanic Gardens and Parks Authority (2008). Conservation and Restoration Research Proposal

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in situ conservation, restoration and translocation of Darwinia masonii and Lepidosperma

gibsonii 2007-2010. Version 5, 26 August 2008

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Banksia cuneata A. S. George (Proteaceae). Heredity, 69, 11—20.

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Recovery Plan 2008-2012. Interim Recovery Plan No. 282. Department of Environment and

Conservation, Western Australia.

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for the Department of Parks and Wildlife. 2014.

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Clarendon Press, Oxford, UK.

Ellstrand, N.C., Elam, D.R., 1993. Population genetic consequences of small population size:

implications for plant conservation. Annual Review of Ecology and Systematics 24, 217–242.

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Gibson Mining. 30pp.

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438pp.

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Mongolia endemic shrub Tetraena mongolica Maxim. (Zygophyllaceae). Biological

Conservation 111 (2003) 427–434.

GHD (2008). Mount Gibson Iron Ore Mine and Infrastructure Project Extension Hill & Extension Hill

North Environmental Management Plan (Rev 2). 189pp.

Gillies, A.C.M., Navarro, C., Lowe, A.J., Newton, A.C., Hemandez, M., Wilson, J., Cornelius, J.P. (1999).

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management of the endangered plant Zieria prostrata. Conservation Biology 13, 514–522.

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Biology, U-3043, University of Connecticut Storrs, CT 06269-3043. 325pp.

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levels of genetic fragmentation. Genetics 106 293-308 February, 1984

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paternity analysis using microsatellite markers. Tree Genetics & Genomes (4):37-47.

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speaking people. 11. The genetic distance between population subdivisions. Genetics. 117:

273-283

Maguire, T.L., Sedgley, M., 1997. Genetic diversity in Banksia and Dryandra (Proteaceae) with

emphasis on Banksia cuneata, a rare and endangered species. Heredity 79, 394–401.

MGX & EHPL (2014). Mount Gibson Iron Ore Mine and Infrastructure - Iron Hill Deposit.

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mine-and-infrastructure-iron/consult_view.

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diversity estimates obtained with RAPD markers in plants. Perspectives in Plant Ecology,

Evolution and Systematics. Vol. 3/2, pp. 93–114.

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serpentine endemic from Western Australia. Biological Conservation 107, 37–45.

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Miller, M and Barrett, M (2010). Darwinia masonii and Lepidosperma gibsonii conservation and

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conservation, restoration and translocation requirements of Darwinia masonii and

Lepidosperma gibsonii. May 2007- June 2010 Report to Sponsors October 2010.

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restriction endonucleases. Proc. Natl. Acad. Sct. USA Vol. 76, No. 10, pp. 5269-5273, October

1979 Genetics.

Paton, D.C. (1993). Honeybees in the Australian environment. Does Apis mellifera disrupt or benefit

the native biota? Bioscience 43, 95-103.

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using eucalypt species and hybrids. RIRDC Publication No. 01/114. Project No. CPF 3A. 108pp.

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Appendix 1: Extracts of Correspondence

Three key extracts of correspondence from BGPA provided to Mount Gibson Iron include the

following:

Extract 1: This study found genetic structuring of Darwinia masonii is generally low suggesting that

the entire Mount Gibson Ranges population should, for the present, be treated as a single

provenance unit. The study also focussed on the genetics at a landscape scale for Darwinia masonii

using microsatellites. This found that some populations do not mate randomly with other

populations, suggesting that there are some weak barriers to gene flow across the Mount Gibson

Range. It was found that plants growing on Extension Hill South and Mount Gibson South are

genetically diverging in isolation from each other and all other plants across the ranges. In contrast,

all other plants from across the Mount Gibson Range intermixed with no geographic isolation

pattern. The plants found at Mount Gibson South are at the southern end of the Mount Gibson

Ranges, however, they do not represent an outlier group as individuals are scattered right across the

landform (ELA 2014). The plants found at Extension Hill South occupy an intermediate position on

the western ridge and BGPA (2010) found the isolation result surprising given the location. It was

noted, however, that the results could have been influenced by a number of factors, including

difference in plant age, fire history and substrate (BGPA 2010). <AMOVA found that 94% of genetic

variation was contained within populations, and just 6% between populations>

Extract 2: The BGPA (2010) analysis of molecular variance partitioned 96% of variation within

populations, and 4% between populations, indicating weak population structure that are completely

intermixed with individuals being as closely related to individuals in other populations as they are to

individuals in the same population (high genetic diversity). BGPA (2010), after further testing, found

that Lepidosperma gibsonii had some barriers to complete gene flow across the Mount Gibson

Ranges. It was found that some populations do not mate randomly with other populations, with

genetic isolation found for the populations at Mount Gibson from nearly all remaining populations

sampled. This was also found for the population at the southern end of Extension Hill from

populations at the extreme end of the ranges (Mount Gibson Saddle). BGPA (2010) suggested the

most likely explanations are physical isolation, inbreeding in small populations, or strong selection at

one or more linked loci. The population on Mount Gibson is only moderately isolated from other

populations and geographically intermediate between populations that are genetically uniform

(BGPA 2010). Further exhaustive genetic sampling studies would be required to fully determine the

mating system patterns and pollen dispersal to fully understand the complete mating system

dynamics of Lepidosperma gibsonii.

Extract 3: "Results of a recent assessment of D. masonii, however, confirm a weak genetic structure

in the nuclear microsatellite data, with nearly all populations exhibiting isolation-by-distance (M

Barrett 2013, pers. comm.). The further any two populations are from each other, the more

different they are on average. Nearly all populations show unique chloroplast haplotypes,

suggesting that seed dispersal is very limited, and has been for a considerable time. These recent

findings imply that the genetic diversity of D. masonii is partly described by the populations of this

taxon, and the inference is that loss of important population diversity may have implications for the

genetic diversity of the species."


Appendix 2: D. masonii and L. gibsonii population locations

Figure 13: D. masonii populations. Putatively isolated populations circled red

Figure 14: L. gibsonii populations. Putatively isolated populations circled red


Appendix 3: Summary of findings from Miller and Barrett, 2010

6.1 Population genetic structure

Table 10: Summary of key findings on population genetic structure

Attribute Darwinia masonii Lepidosperma gibsonii

Between population genetic

structuring

Low, however, some

populations do not mate

randomly with other

populations – suggesting that

there are some weak barriers

to gene flow across the Mt

Gibson range

Very low genetic structuring

between populations of L.

gibsonii, but tests show that

there are some barriers to

complete gene flow across the

Mt Gibson range system

Other features None specified Multiple genotypes may occur

in individual clumps

Population bottlenecks Although results indicate a

suggesting a low but significant

level of inbreeding, They do not

indicate any level of inbreeding

depression due to past

bottlenecks.

Although results indicate a

suggesting a low but significant

level of inbreeding, They do not

indicate any level of inbreeding

depression due to past

bottlenecks.


6.2 Population demographics

Table 11: Summary of key findings on population demographics


Estimated life span Approx. 100 years Approx. 100 years

Fire tolerance Fire killed 50% of plants exposed to fire

appear to survive and resprout

Fire Recruitment long-lived soil-stored

seedbanks in a single cohort

following fire

long-lived soil-stored

seedbanks in a single post-fire

cohort

Inter-fire recruitment Limited inter-fire recruitment

may occur in older populations

There is no evidence for inter-

fire recruitment

Post fire seedling recruitment

per pre-fire adult

3.2 4.2

Seedling mortality % of seedlings died over their

1st summer

75% do not survive to 2 years

4 to 6 year old plant mortality 2.5-15% per year 3% per year

Mature plant mortality Rare, but up to 10% in severe

drought years

50% from fires

Age of reproduction Six years and increases over

time

Six years and increases over

time


6.3 Seed biology

Table 12: Summary of key findings on seed biology


Pollination vector Single species of honeyeater

(White-fronted honeyeater)

Wind

Capacity for selfing Possible Unknown

Selfed seed viability Less fit than outcrossed seed Unknown

Seed fill rate 15 to 30% Unknown

Seed predation rate 6 to 22% Unknown

Seed dispersal Principally by ants Unknown

Seed production per mature plant 9 to 59 Unknown


6.4 Seed germination and dormancy

Table 13: Summary of key findings on seed germination and dormancy


Germination of fresh seed Low Assumed poor

Treatment requirements Seed cost nicking

Seed coat removal

Retrieval of buried seed (months

to years)

Smoke water

Seed coat breakdown

Seed coat removal

Retrieval of buried seed

Smoke water

Heat treatment

Germination of treated

(filled) seed

90% (for 9 months burial +

smoke water)

60% (for seed coat removal +

heat treatment)

Seed germination reliability Satisfactory Unresolved


6.5 Plant characteristics and adaptation

Table 14: Summary of key findings on plant characteristics and adaptations


Drought tolerance Physiological dormancy over

summer

Physiological dormancy over

summer

Root depth perhaps to >10m perhaps to >10m

Grazing impact from goats

and rabbits

Negligible Significant impact

Seed predation Significant from larvae of an

unidentified moth species

Unknown

Translocation capacity Demonstrated for BIF rock and

BIF gravel substrate

Demonstrated for BIF rock and

BIF gravel substrate

Translocation survival Under 40% at 9 months on BIF

rocky loam site.

Poorer on other sites

Increased by irrigation

70% on BIF gravel sites.

High on BIF rock sites


6.6 Propagation, Restoration and Translocation

Table 15: Summary of key findings on propagation, restoration and translocation


Vegetative propagation Cuttings Separated clumps

Seed propagation Reliable Unreliable

Other propagation methods None required Seed embryos in tissue culture

Ecological niche Broadly adapted to BIF rocky

loam soils Possible association

with unmapped sub-surface

features

Preference for cooler sites sloped

to minimise solar radiation

Substrate requirements Implication that sand and clay

materials may not be effective,

and that a large proportion of BIF

rock or gravel is required

successful restoration

Implication that sand and clay

materials may not be effective,

and that a large proportion of BIF

rock or gravel is required

successful restoration


6.7 Conservation recommendations

Table 16: Summary of key conservation recommendations based on population genetic studies


Conservation

recommendations

Based on pairwise tests showing

that some populations are

statistically supported as non-

randomly mating with other

populations, suggesting that

there are some barriers to

complete gene flow across the

Mt Gibson range system, the

precautionary principle is

recommended to avoid mixing

genotypes between populations

without careful consideration of

consequences.

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