evaluating emergence, survival, and assembly of …...evaluating emergence, survival, and assembly...

Evaluating emergence, survival, and

assembly of Banksia woodland

communities to achieve restoration

objectives following topsoil transfer.

by

Paweł Waryszak

A thesis submitted to the Murdoch University

to fulfill the requirements for the degree of

PhD

in the discipline of

Environmental Science

Murdoch University, 2017

iii

Author’s declaration

I declare that this thesis is my own account of my research and contains as its main

content work which has not previously been submitted for a degree at any tertiary education

institution.

Paweł Waryszak

v

Abstract

The science of restoration ecology seeks ways to advance the understanding of how to

restore native ecosystems that have been degraded or destroyed. Ecological theory suggests that

environmental filters influence the outcome of ecological restoration and ultimately long-term

restoration success. In this study, three types of environmental filters: dispersal, abiotic, biotic

were manipulated to improve understanding of how to successfully re-establish native plant

communities. The abiotic filter was manipulated by decreasing soil compaction (ripping) and

evaporation (shade). The biotic filter was addressed with control of herbivory (fencing) and

weeds (herbicide). The dispersal limitation was examined by altering the application depth of

the transferred topsoil (deep and shallow topsoil volume) and application of germination cues

(smoke and heat).

This study was located in Banksia woodland - a Mediterranean-type ecosystem

restricted to the Swan Coastal Plain in Western Australia that is diminishing due to rapid urban

expansion. Topsoil from Banksia woodland vegetation contains a large native soil seed bank.

Here, topsoil from a newly cleared site was stripped, transferred and applied to six recipient

sites within two months of vegetation clearing. The recipient sites had been grazed for about 80

years prior to purchasing for conservation as part of a biodiversity offset program. Following

topsoil transfer, a fully factorial combination of three filter manipulation treatments was applied

across the six sites to identify successful restoration techniques. The dispersal filter was tested

by altering the volume of topsoil seed bank applied. The abiotic filter experimental

manipulation was performed using topsoil ripping. The biotic filter was examined by installing

herbivore exclosures.

Emergence and survival of Banksia woodland species were quantified in spring and

autumn for two consecutive years after topsoil transfer. Manipulation of the abiotic filter in soil

ripping treatment reduced the densities of the emerging native perennials significantly (t = 4, P

< 0.001). Overall, the most successful technique was the application of a high volume of

unripped topsoil, with resulting mean densities of native perennials of 15.9 ± 0.2 (SE) m-2

in the

first year. Similarly, high volume of unripped topsoil resulted in the highest mean densities of

native perennials of 7.6 ± 0.1 (SE) m-2

in the second year after topsoil transfer. Application of

plot-scale heat treatments in the second year recorded 4.5 % increase in the emergence densities

of native perennials compared with site-scale control plots (t = 11.4, P < 0.001). Mean seedling

survival over the 2-year sampling period was 2.44% ± 0.2 (SE). The highest survival through

the first summer drought occurred within topsoil ripping treatment in combination with artificial

shade (mean survival of 27.3 % ± 5.6 (SE), t=7.8, P<0.001). High mortality occurred during the

second summer drought and overall mean seedling survival over the 2-year sampling period was

2.44% ± 0.2 (SE).

Breaking plant species into key functional groups, the number of non-resprouters

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oscillated around 70% in both years. Nitrogen-fixers comprised 50% of total native flora

richness in the first year after topsoil transfer and decreased markedly to 20% in the second

year. Plant assemblages in the second year after topsoil transfer comprised mostly of non-native

perennial grasses and perennial, small-seeded native woody shrubs.

The transferred topsoil seed bank contained a close-to-reference species richness of

native species propagules. Deep topsoil returned the highest mean densities of native plant

species and second highest number of native plant taxa (163 on deep topsoil, 166 on fenced

topsoil, of total 171 plant species recorded in this study). The recorded plant species richness

comprised about 25% of total species pool recorded in Banksia woodland ecosystems in its

natural distribution on Swan Coastal Plain, Western Australia and about 105% of total plant

taxa recorded in the reference site before clearing. These plant taxa were mostly understorey

species that suggests a high potential for mitigating environmental barriers on restoration sites

with the use of transferred topsoil, but more research needs to focus on improving survival of

native seedlings in their early stages of establishment.

vii

Acknowledgements

I owe my deepest gratitude to Murdoch University and my four supervisors: Dr. Joe

Fontaine, Dr. Phil Ladd, Prof. Neal Enright and Dr. Rachel Standish who supported me on this

unique journey of scientific endeavor. They made my dream come to true that is to work in the

scientific field I feel very passionate about – The Ecology. I have learned a good deal of

philosophical, computational and practical skills that I do want to build on in my future career.

I am especially thankful to Dr. Joe Fontaine who supported me through the rocky road

of the Ph.D. project. I thank him for the patience and calmness that suited perfectly to the wide

range of PhD-related challenges. Many thanks to Prof. Neal Enright for providing me with so

much needed support throughout my Ph.D. project. Many Thanks to Dr. Rachel Standish who

joined in half way and provided a much-needed fresh look at my work. I won a significant

element of clarity and applicability of my findings thanks to her contributions.

Many thanks go to Dr. Phil Ladd for helpful reviews and strong belief that I can reach

the end of that journey. Phil also inspired me to join the community of passionate nature

enthusiasts at the Wildflower Society of Western Australia. In the end, I became a part of the

local committee at the Murdoch Branch and had a great chance to work for and with the

amazing Western Australian environment. I do appreciate the excellent company I found in the

team of passionate people that ran with me the committee of the Murdoch Branch of Wildflower

Society: Christina Birnbaum, Diana Corbyn, Liz Edwards, Lesleigh Curnow, Eddy Wajon,

Angus King, Neil Goldsborough, Ross Young, Mathews Woods, and Ben Sims.

Completion of the Ph.D. study would not be possible without Dr. Christina Birnbaum -

my wife who put me on that road. I would not have accomplished it without Christina’s trust

and belief in me.

To Renaud Jaunatre and Dr. Adrian Hordyk for the incredible intellectual help in

developing programming tools to analyze my “big” data – Big thanks for making your R-codes

available and contributing to the reproducibility level of my research.

Many thanks to people who help me greatly with an extensive collection of vegetation

data: Dr. Phil Ladd, Dr. Joe Fontaine, Billi Veber, Mark Gerlach, Dr. Christina Birnbaum,

William Fowler, Amity Williams, Niels Brouwers, and Megan Brown.

Many thanks and hugs to those who showed that Ph.D. life has a fun aspect to it too:

Afshin Nikrouh, Mae Shahabi, Christine Allen, Niels Brouwers, Wieneke Maris, Bridget and

Nathan Johnson, Maggie Triska, Sébastian Lamoureux, Jenny Smith, Alex Brown, Sofie De

Meyer, Daniel Kohlmann, Dean Laslett, Natacha Wirenfeldt-Petersen, Kate Hegarty, Jonathan

Haws, Katinka Ruthrof, Jodi Price, Kasia and Ellery Mayence.

This research was funded by WA Department of Environment and Conservation (now

Department of Parks and Wildlife). Ph.D. project was carried out as a part of biodiversity offset

program in relation to Jandakot Airport development.

ix

Table of contents

Author’s declaration .................................................................................................................... iii

Abstract ........................................................................................................................................ v

Acknowledgements .................................................................................................................... vii

Table of contents ......................................................................................................................... ix

List of figures ............................................................................................................................. xv

List of tables .............................................................................................................................. xix

List of abbreviations .................................................................................................................. xxi

Chapter 1 Introduction ......................................................................................................... 22

1.1 Thesis structure ................................................................................................... 26

Chapter 2 Literature review ................................................................................................. 28

2.1 Introduction ......................................................................................................... 28

2.2 Restoration principles ......................................................................................... 29

2.2.1 Identification of controlling variables in ecosystem restoration ......................... 29

2.2.2 Theories and models in restoration ..................................................................... 30

2.2.2.1 Succession theory and practice .................................................................... 31

2.2.2.2 Filter-based community assembly model .................................................... 31

2.2.2.3 Alternative stable state models .................................................................... 32

2.3 Restoration of plant diversity .............................................................................. 32

2.4 Restoration of plant functions ............................................................................. 33

2.5 Restoration of Mediterranean-type ecosystems .................................................. 33

2.5.1 Climate-related restoration tools ......................................................................... 34

2.5.2 Soil-related restoration tools ............................................................................... 35

2.5.3 Disturbance-related restoration tools .................................................................. 37

2.5.4 Native seedling establishment in sandy soils ...................................................... 39

2.5.5 Translocations ..................................................................................................... 40

2.6 Topsoil seed bank ................................................................................................ 40

2.6.1 Topsoil seed bank transfer .................................................................................. 41

Chapter 3 Study setting ........................................................................................................ 43

3.1 Climate ................................................................................................................ 44

3.2 Geology ............................................................................................................... 45

3.3 Vegetation ........................................................................................................... 45

3.3.1 Origin of Banksia woodland of Western Australia ............................................. 47

3.3.2 Distribution and threats for Banksia woodlands ................................................. 48

3.4 Study sites ........................................................................................................... 50

3.4.1 Topsoil donor sites .............................................................................................. 50

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3.4.2 Topsoil recipient sites ......................................................................................... 50

3.4.2.1 Forrestdale Lake study sites ........................................................................ 53

3.4.2.2 Anketell Road study sites ............................................................................ 55

3.4.3 Topsoil seed bank collection and three study site-scale treatments .................... 58

3.4.3.1 Dispersal filter manipulation treatment (topsoil volume)............................ 60

3.4.3.2 Abiotic filter manipulation treatment (topsoil ripping) ............................... 60

3.4.3.3 Biotic filter manipulation treatment (topsoil fencing) ................................. 61

Chapter 4 Germination: Filter-based restoration ecology: utilization of translocated

topsoil seed bank to overcome abiotic, biotic and dispersal barriers .................. 63

4.1 Abstract ............................................................................................................... 63

4.2 Introduction ......................................................................................................... 64

4.3 Methods ............................................................................................................... 67

4.3.1 Plot-level treatments ........................................................................................... 67

4.3.1.1 Two Smoke-related Treatments .................................................................. 67

4.3.1.2 Plastic Cover Treatment .............................................................................. 67

4.3.1.3 Heat Treatment ............................................................................................ 67

4.3.1.4 Chemical Weed Control Treatment ............................................................. 68

4.3.2 Experimental design ............................................................................................ 71

4.3.2.1 Aim .............................................................................................................. 72

4.3.2.2 Data collection (vegetation surveys) ........................................................... 73

4.3.2.3 Data analysis................................................................................................ 73

4.3.2.3.1 Site-scale treatments analysis – main model ....................................... 73

4.3.2.3.2 Plot-scale treatments analysis – additional effects .............................. 74

4.3.2.3.3 Supplementary effects ......................................................................... 74

4.3.3 Native annuals in spring 2012 ............................................................................. 75

4.4 Results ................................................................................................................. 75

4.4.1 Abiotic filter ........................................................................................................ 75

4.4.2 Biotic filter .......................................................................................................... 78

4.4.3 Dispersal filter ..................................................................................................... 78

4.4.4 Interactions between site-scale filter manipulation treatments ........................... 78

4.4.5 Additional plot-scale treatments effects .............................................................. 79

4.5 Discussion ........................................................................................................... 81

4.5.1 Abiotic filter ........................................................................................................ 82

4.5.2 Biotic filter .......................................................................................................... 83

4.5.3 Dispersal filter ..................................................................................................... 84

4.5.4 Weeds and filters ................................................................................................. 85

4.6 Conclusions ......................................................................................................... 86

4.7 Appendices .......................................................................................................... 89

4.7.1 Site effects ........................................................................................................... 89


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4.7.4 Invasive plants densities (two figures) ................................................................ 92

4.7.5 Invasive plants statistical tables (four tables) ...................................................... 93

4.7.6 2012 Species list .................................................................................................. 96

4.7.7 2013 Species list ................................................................................................ 110

Chapter 5 Seedling survival after emergence from transferred topsoil seed bank ............. 124

5.1 Abstract ............................................................................................................. 124

5.2 Introduction ....................................................................................................... 125

5.3 Methods ............................................................................................................. 127

5.3.1 Topsoil treatments ............................................................................................. 127

5.3.1.1 Site-level treatments .................................................................................. 127

5.3.1.1.1 Topsoil volume .................................................................................. 127

5.3.1.1.2 Topsoil ripping treatment .................................................................. 127

5.3.1.1.3 Topsoil fencing treatment .................................................................. 128

5.3.1.2 Plot-level treatments .................................................................................. 128

5.3.1.2.1 Smoke treatments............................................................................... 128

5.3.1.2.2 Heat treatment .................................................................................... 128

5.3.1.2.3 Chemical weed control treatment ...................................................... 129

5.3.1.2.4 Shade and shade-semi treatments ...................................................... 129

5.3.2 Data collection .................................................................................................. 129

5.3.2.1 Vegetation surveys .................................................................................... 129

5.3.2.2 Soil moisture.............................................................................................. 129

5.3.2.3 Soil chemical properties ............................................................................ 130

5.3.2.4 Soil resistance ............................................................................................ 131

5.3.3 Data analysis ..................................................................................................... 131

5.3.3.1 Effect of site-scale treatments – main model ............................................ 131

5.3.3.2 Effects of plot-scale treatments – additional effects .................................. 132

5.3.3.3 Effect of site-scale treatments on soil moisture ......................................... 133

5.3.3.4 Effect of site-scale treatments on soil physical and chemical

properties. .................................................................................................. 133

5.4 Results ............................................................................................................... 133

5.4.1 The effect of site-scale treatments on survival of native perennials. ................ 134

5.4.2 The effect of plot-scale treatments on survival of native perennials. ................ 136

5.4.3 The effect of site-scale treatments on soil moisture and soil chemical

properties. .......................................................................................................... 139

5.5 Discussion ......................................................................................................... 148

5.5.1 Site-level treatments: role of topsoil depth, ripping, and fencing ..................... 148

5.5.1.1 Altering depth of topsoil spread ................................................................ 148

5.5.1.2 Topsoil ripping treatment .......................................................................... 149

5.5.1.3 Herbivore exclosures installation .............................................................. 150

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5.5.2 Plot-scale treatments: the role of smoke, herbicide application, and

artificial shade ................................................................................................... 151

5.5.2.1 Smoke treatments ...................................................................................... 151

5.5.2.2 Herbicide ................................................................................................... 152

5.5.2.3 Shade installation ...................................................................................... 152

5.5.2.4 Heat ........................................................................................................... 152

5.6 Conclusions ....................................................................................................... 153

5.7 Appendices ........................................................................................................ 155

5.7.1 Three periods’ survival (%) under site-scale treatments ................................... 155

5.7.2 Three periods’ survival (%) under plot-scale treatments .................................. 156

5.7.3 Survival Odds .................................................................................................... 159

5.7.4 Species frequencies (%) in autumn 2014 .......................................................... 160

5.7.5 Soil resistance (FSW pilot study) ...................................................................... 167

5.7.6 Mean moisture content ...................................................................................... 168

5.7.7 Final densities across all treatments .................................................................. 169

Chapter 6 The effects of environmental filter manipulations on plant functional trait

space in a Banksia woodland restoration project .............................................. 171

6.1 Abstract ............................................................................................................. 171

6.2 Introduction ....................................................................................................... 172

6.3 Methods ............................................................................................................. 174

6.3.1 Experimental design .......................................................................................... 174

6.3.2 Vegetation surveys ............................................................................................ 174

6.3.3 Statistical analysis ............................................................................................. 174

6.3.3.1 Rationale behind the chosen traits ............................................................. 174

6.3.3.2 Functional richness and functional dispersion .......................................... 175

6.3.3.3 Species composition .................................................................................. 176

6.4 Results ............................................................................................................... 177

6.4.1 Effects of filter treatments on functional dispersion and functional richness ... 177

6.4.2 Functional space of the reference and restoration sites ..................................... 182

6.5 Discussion ......................................................................................................... 184

6.5.1 Filters and functional richness .......................................................................... 184

6.5.2 Filters and functional dispersion ....................................................................... 184

6.5.3 Remnant and restoration site ............................................................................. 186

6.6 Conclusions ....................................................................................................... 187

6.7 Appendices ........................................................................................................ 189

6.7.1 Effects of six topsoil transfer stages on functional indices ............................... 189

6.7.2 Dominant trait suites in autumn 2014 ............................................................... 190

6.7.3 Mean heights of plants recorded in the last vegetation survey (autumn

2014) ................................................................................................................. 194

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6.7.4 NMDS ordination of plant composition in the first and the last vegetation

survey season .................................................................................................... 195

6.7.5 NMDS ordination of plant compositions during three consecutive spring

seasons .............................................................................................................. 196

6.7.6 NMDS ordination of plant compositions during three autumn seasons ............ 197

6.7.7 Correlation between density and diversity indices in spring 2012 .................... 198

6.7.8 Correlation between density and diversity indices in spring 2013 .................... 199

Chapter 7 Discussion and conclusions............................................................................... 201

7.1 Introduction ....................................................................................................... 201

7.2 Filtering processes: emergence ......................................................................... 203

7.3 Filtering processes: survival .............................................................................. 207

7.4 Filtering of plant functional types ..................................................................... 208

7.5 Offsetting biodiversity ...................................................................................... 210

7.6 Conclusions ....................................................................................................... 211

Chapter 8 Reference .......................................................................................................... 212

xv

List of figures

Figure 1-1 Filter conceptual framework that presents the role of environmental filter

manipulation treatments in restoration of native ecosystems. ............................. 24

Figure 3-1 Distribution of Banksia woodlands (green shade) on Swan Coastal Plain,

Western Australia (light brown shade). Credit The Northern Agricultural

Catchments Council (Environment 2017). .......................................................... 49

Figure 3-2 Location of topsoil donor site at Jandakot (circle) and two topsoil recipient

sites at Forrestdale Lake (upper triangle) and Anketell Road (bottom

triangle). Topsoil was collected and transferred in April-May 2012. ................. 50

Figure 3-3. Map of SW Australia showing the location of the study sites - produced using

“ggmap” package (Keeley, Lubin & Fotheringham 2003). ................................ 51

Figure 3-4. Satellite image of three study sites at Forrestdale Lake: ForSW, ForNW, and

ForSE. Two site-level treatments are shown: shallow topsoil depth [light

blue], deep topsoil depth [purple] and exclosure line [yellow]. The study

block (clusters) are drawn as[dark blue squares. Insert depicts the location

of the study sites within the Swan Coastal Plain (Google Earth 2014b).

Forrestdale Lake topsoil recipient sites of the total size of 6 ha, are situated

25 km SE of Perth. The marked planting and direct seeding were

undertaken simultaneously in a separate project run by Western Australia

Department of Parks and Wildlife . Credit: Anna Wisolith. ............................... 54

Figure 3-5. Satellite image of three study sites at Anketell Road: AnkW, AnkM, and

AnkE. Two site-level treatments are shown: shallow topsoil depth [light

blue], deep topsoil depth [purple] and fence line [yellow]. The study blocks

(clusters) are drawn as dark blue squares. Insert depicts the location of the

study sites within the Swan Coastal Plain (Google Earth 2014a). The

marked planting and direct seeding were undertaken simultaneously in a

separate project run by Western Australia Department of Parks and

Wildlife . Credit: Anna Wisolith. ........................................................................ 56

Figure 3-6 Image of the front-end loader in the process of land-clearing at the topsoil

donor site in Jandakot, Western Australia, 16th June 2012. ................................ 58

Figure 3-7 Close-up image of the front-end loader with customized plate adhered to its

front bucket. Jandakot, Western Australia, April 2012. Credit: Joe

Fontaine. .............................................................................................................. 59

Figure 3-8, Image of the front-end loader in the process of topsoil spreading at the

recipient site in Anketell, Western Australia, 16th June 2012. ............................ 60

Figure 3-9 Topsoil ripping treatment with use of tractor and single winged tine, June

2012. .................................................................................................................... 61

Figure 3-10 Topsoil fencing. The additional upper line was mounted to prevent large

macropods from entering the restoration study sites, July 2012. ........................ 62

Figure 4-1. Illustration of study design. The effects of the site-scale treatments were

investigated within eight clusters per site, also denominated as controls [C].

The effects of plot-scale treatments that were superimposed on site-scale

treatments were studied within four clusters [T]. The white squares indicate

the combinations of three main site-scale treatments: topsoil volume,

ripping, and fencing. The coloured squares indicate four additional plot-

scale treatments, subsequently applied only within the fenced area: two

smoke-related [red], herbicide [green], heat application [yellow], and shade

[blue]. Each cluster comprised of 8 to 12 plots (sampling units). See

detailed description of treatments in Table 4-1 and Table 4-2. ........................... 72

xvi

Figure 4-2. Mean native perennial and native annual densities (m-²±95%CI) emerging

under filter manipulation treatments during the springs of year one and two

since topsoil transfer. Abiotic Filter Manipulation treatments: ripped and

unripped, Biotic: fenced and open. Dispersal: deep and shallow topsoil

transfer. The filled circles represent the means of native annuals, and the

filled triangles represent the mean density of native perennials. The x-axis

depicts vegetation survey period: “one” – spring 2012 of the year I since

topsoil transfer, n= 207±16SD and “two” – spring 2013 of the year II,

n=284±7SD. Data back-transformed. ................................................................. 77

Figure 4-3. Mean ±95%CI of native perennial and native annual densities (m-²) emerging

under plot-scale treatments, n=12, superimposed on a combination of two

site-scale filter manipulation treatments: dispersal filter manipulation

treatments: deep (D) and shallow (S) topsoil transfer and abiotic filter

manipulation: ripped (R) and unripped (U). The empty squares represent

the means of native annuals, and the filled squares the mean density of

native perennials. All densities account for new emergents in the respective

years . The right panel depicts vegetation survey period: “I” – spring 2012

of year one since topsoil transfer and “II” – spring 2013 of year two. Data

back-transformed. ............................................................................................... 80

Figure 4-4 Mean densities ± 95% CI of invasive plant densities (1m2) emerging in the

first (one, spring 2012)) and second (two, spring 2013) year after topsoil

transfer under three site-scale filter manipulation treatments. ............................ 92

Figure 4-5 Mean densities ± 95% CI of invasive plant densities (1m2) emerging in the

first (one, spring 2012)) and second (two, spring 2013) year after topsoil

transfer under five plot-scale filter manipulation treatments .............................. 93

Figure 5-1 Mean Survival Percentage in three survival periods across site-scale

treatments: from spring 2012 to autumn 2013 (autumn.2013), from spring

2013 to autumn 2014 (autumn.2014) and over two year period from spring

2012 to autumn 2014 (Two.Years). .................................................................. 134

Figure 5-2 Mean final densities (m-2

) of native perennials with 95% confidence Intervals

in the second year after topsoil transfer, autumn 2014. Site-scale treatments

only: 1 Topsoil Depth (deep and shallow), 2) Topsoil Rip (ripped and

unripped), and 3) Herbivore Exclosures (fenced and open). ............................. 136

Figure 5-3 Mean final densities of native perennials in the second year after topsoil

transfer, autumn 2014. Control represents the mean±95CI of all site-scale

treatments. Plot-scale treatment represents the mean ± SE of all respective

treatments: 1) heat, 2) herbicide 3) shade, 4) smoke. ........................................ 137

Figure 5-4 Mean volumetric soil moisture content (± 95% CI) measured under the

combination of two site-scale treatments: topsoil volume (deep and

shallow) and topsoil ripping (unripped and ripped). The monthly

measurements were recorded at six depths: 100, 200, 300, 400, 600, and

1000 mm. Year 2012 in spring (the start of the project) and summer only. ..... 142





1000 mm. Year 2013. ........................................................................................ 143





1000 mm. Year 2014. ........................................................................................ 144

xvii





1000 mm. Year 2015 in summer and autumn only (the end of the project). .... 145

Figure 5-8 Chemical and physical properties of soil samples collected from the topsoil

donor (intact) and topsoil recipient (Transfer): conductivity

[ds/m],concentration of ammonium nitrogen [NH4 mg/kg ], nitrate

nitrogen [NO3 mg/kg ], organic carbon [OC %], phosphorus[P mg/kg] and

sulphur [S mg/kg ], soil texture (scale of 5 categories where 1=sand, 1.5 =

sand/loam, 2 = loam, 2.5 = loam/clay and 3 = clay )and soil pH (in CaCl2).

The lower and upper box bars correspond to first and third quartiles of data

(the 25th and 75th percentiles). The upper whisker extends from upper box

bar to value of 1.5 of inter-quartile range (distance between the first and

third quartiles). Data beyond the end of the whiskers may be considered as

outliers and are plotted as points. ...................................................................... 146

Figure 5-9 Mean soil resistance (MPa) with 95% confidence intervals at the seven depths:

100, 200, 300, 400 ,600, and 1000 mm. Soil resistance was measured at the

combination of topsoil ripping treatments (ripped: in and out of furrow and

unripped) and topsoil volume (deep and shallow), in spring 2013. .................. 147

Figure 5-10 Odds of survival of native perenials over two year period (spring 2012 –

autumn 2014) in relation to recorded weed densities (Weed cover [1m-2

] in

spring 2013),site-scale filter manipulation treatments (deep topsoil volume,

topsoil ripping and fencing) and small-scale plot treatments(smoke, shade,

herbicide). Model:

glmer(Survival~Transdepth+rip+fence+plot2+rip*fence+fence*Transdepth

+rip*Transdepth+WeedDensity.spr13+(1|site/plot)+(1|specCode),

family="binomial") ........................................................................................... 159

Figure 5-11 Pilot Study on the effect of ripping treatment on soil compaction: y-axis

depicted soil compaction (MPa) on unripped and ripped (“in” inside

furrow, “out” between the furrows) and the x-axis shows the depth at

which the resistance was measured (cm). ......................................................... 167

Figure 5-12 Mean moisture content (%) over period of 2012-2014 on restoration study

sites (within fence). Soil moisture was measured once a month across six

study sites and combinations of two treatments: topsoil volume (deep

[10cm] and shallow [5cm]) and topsoil ripping (ripped and unripped). ........... 168

Figure 5-13 The final densities of invasive perennials in the second year after topsoil

transfer, autumn 2014. ...................................................................................... 169

Figure 6-1 Graphical representation of how functional dispersion (FDis) is computed in

the multivariate trait space. Y-axis and X-axis depict the potential trait

values that can express continuous, ordinal, nominal, or binary trait values.

Star shape represents a centroid, and the size of the circle relates to the

abundance of the given species in the plant community. Credit: James

Lawson. ............................................................................................................. 176

Figure 6-2 Functional dispersion of traits measured in the reference sites and topsoil

recipient sites: Ref.Spr – Reference Site in spring 2011, Ref.Aut =

Reference site in autumn 2011, Top.Spr.I – Topsoil site in spring 2012,

Top.Spr.II – Topsoil site in spring 2013, Top.Aut.I – Topsoil site in

autumn 201, Top.Aut.II – Topsoil site in autumn 2014. The topsoil control

sites include the plots (4 m-2

) situated on deep unripped restoration study

sites only (the most successful), and reference control plots (100 m-2

) were

located in the remnant bushland where the topsoil was sourced following

land clearing. ..................................................................................................... 183

xviii

Figure 6-3 Functional richness of the reference sites and topsoil recipient sites: Ref.Spr –

Reference Site in spring 2011, Ref.Aut = Reference site in autumn 2011,

Top.Spr.I – Topsoil site in spring 2012, Top.Spr.II – Topsoil site in spring

2013, Top.Aut.I – Topsoil site in autumn 2013, Top.Aut.II – Topsoil site in

autumn 2014. The topsoil control sites include the plots (4 m2) situated on

deep unripped restoration study sites, and reference control plots (100 m2)

were located in the remnant bushland where the topsoil was stripped

following land clearing. .................................................................................... 184

Figure 6-4 Distribution of mean (±SE) plant heights recorded in the second year after

topsoil transfer (autumn 2014) across all topsoil treatments. The plant

heights bars are presented in ascending order: heat (n = 102), open (n =

291), shallow (n = 123), ripped (n = 125), unripped (n = 409), deep (n =

411), herbicide (n = 59), smoke.plastic (n = 83), smoke (n = 58), fenced (n

= 243), plastic (n= 31), shade (n = 34). ............................................................. 194

Figure 6-5 NMDS ordination (stress = 6.88%) of plant topsoil communities in spring

2012 (first survey after topsoil transfer) and autumn 2014 (last survey after

topsoil transfer.). The figure presents vegetation data from deep unripped

treatment plots that represented the most successful treatment combination

in terms of native species densities. Changes in the assemblages over a

period of 2 years were significant (ANOSIM, R = 0.5, P = 0.001). ................. 195


seasons at reference site (topsoil donor - Ref.spr2011) and offset sites

(topsoil recipient - Off.spr2012 and Off.spr2013). The figure presents

vegetation data from deep unripped treatment plots that represented the

most successful treatment combination in terms of native species densities.

Changes in the assemblages over a period of two years were statistically

significant (ANOSIM, R = 0.001 , P = 0.001). ................................................. 196


seasons at reference site (topsoil donor - Ref.spr2011) and offset sites

(topsoil recipient - Off.spr2012 and Off.spr2013). The figure presents

vegetation data from deep unripped treatment plots that represented the

most successful treatment combination in terms of native species densities.

Changes in the assemblages over a period of two years were statistically

significant (ANOSIM, R = 0.04 , P = 0.001). ................................................... 197

Figure 6-8 Correlation between density and three diversity indices: Shannon-Wiener,

Simpson, and Richness in the first growing season since topsoil transfer

(spring 2012). Pielou’s evenness index also included. ...................................... 198

Figure 6-9 Correlation between density and three diversity indices: Shannon-Wiener,

Simpson, and Richness in the second growing season since topsoil transfer

(spring 2013). Pielou’s evenness index also included. ...................................... 199

Figure 7-1 Image of Banksia woodland stand prior clearing in 2012, Jandakot Airport,

Western Australia. ............................................................................................. 202

Figure 7-2 Image of restoration site (ForNW) immediately after topsoil transfer, June

2012 ................................................................................................................... 204

Figure 7-3 Conceptual diagram presents the effects of filter manipulation treatments on

native plant richness in in the first year after topsoil transfer. .......................... 206

Figure 7-4 Image of restoration site (ForNW) 2 years after topsoil transfer, August2014 ...... 208

xix

List of tables

Table 3-1 – List of selection criteria used in the assessment of potential recipient sites.

Adapted from Fowler (2012). ............................................................................. 43

Table 3-2: Historical climate [1986—2015] recorded at Forrestdale climate station

nearest the study sites, compared with the climate experienced in the first

[2012], the second [2013] and third [2014] year since topsoil transfer. The

wet season was defined for between May and September inclusively.

Rainfall evenness was calculated after Pielou’s: PE = SW/ ln(M) where

SW - Shannon-Wiener for rainfall in mm, M - number of months with

rainfall. Evenness ranged from 0.0 with entire rainfall in one month to 2.3

with even rainfall across all months. ................................................................... 44

Table 4-1: Detailed description of the treatments applied in the restoration study at

Forrestdale Lake and Anketell site, Western Australia. ...................................... 69

Table 4-2: Descriptions of the site-scale and plot-scale filter-manipulation treatments. For

a detailed description of the treatments see Table 4-4. ....................................... 71

Table 4-3: Effect of site-scale filter manipulation treatments on native perennial plant

densities emerging in the first year [spring 2012] after topsoil transfer. ............ 76

Table 4-4: Effect of site-scale filter manipulation treatments on native perennial plant

densities emerging in the second year [spring 2013] after topsoil transfer. ........ 79

Table 4-5: Interactive effect of site-scale filter manipulation treatments and small-scale

plot treatments on perennial plant densities emerging in the first year

[spring 2012] after topsoil transfer. ..................................................................... 79

Table 4-6: Interactive effect of site-scale filter manipulation treatments and small-scale

plot treatments on perennial plant densities emerging in the second year

[spring 2013] after topsoil transfer. ..................................................................... 81

Table 4-7: Site effects on native perennial plant densities emerging in year one and two

since topsoil transfer. .......................................................................................... 89

Table 4-8: Effect of site-scale filter manipulation treatments on native annual plant

densities emerging in the first year [spring 2012] since topsoil transfer. ............ 90

Table 4-9: Effect of site-scale filter manipulation treatments on native annual plant

densities emerging in the second year [spring 2013] since topsoil transfer. ....... 90

Table 4-10: Effect of site-scale filter manipulation treatments on invasive plant densities

(1m2) emerging in the first year after topsoil transfer (spring 2012). ................. 93

Table 4-11 Effect of site-scale filter manipulation treatments on invasive plant densities

(1m2) emerging in the second year after topsoil transfer (spring 2013). ............. 94

Table 4-12 Interactive effect of site- and plot-scale filter manipulation treatments on

invasive plant densities (1m2) emerging in the first year after topsoil

transfer (spring 2012). ......................................................................................... 95

Table 4-13 Interactive effect of site- and plot-scale filter manipulation treatments on

invasive plant densities (1m2) emerging in the second year after topsoil

transfer (spring 2013). ......................................................................................... 96

Table 4-14 List of plant species that emerged in the first year since topsoil transfer and

their occurrence frequencies, spring 2012. ......................................................... 96

Table 4-15 List of plant species that emerged in the second year after topsoil transfer and

their occurrence frequencies, spring 2013. ....................................................... 110

xx

Table 5-1 Effect of site-scale treatments on survival odds of native perennial seedlings

over the first growing season after topsoil transfer - from spring I (spr12) to

autumn I (aut13). ............................................................................................... 134

Table 5-2 Effect of site-scale treatments on survival odds of native perennial seedlings

that emerged in the second spring after topsoil transfer - from spring II

(spr13) to autumn II (aut14). ............................................................................. 135

Table 5-3 Effect of site-scale treatments on survival over a two-year period of native

perennial plants, from spring I (spr12) to autumn II (aut14). ........................... 136

Table 5-4 Interactive effects of two site-scale treatments and additional plot-scale

treatments on survival of native perennial seedlings over the first growing

season after topsoil transfer - from spring I (spr12) to autumn I (aut13). ......... 137


treatments on survival of native perennial seedlings over the second

growing season after topsoil transfer - from spring II (spr13) to autumn II

(aut14). .............................................................................................................. 138


treatments on survival of native perennial seedlings over two growing

season after topsoil transfer - from spring II (spr12) to autumn II (aut14). ...... 138

Table 5-7 Interactive effects of topsoil ripping and topsoil volume treatment on soil

moisture at six different depths of 100, 200, 300, 400, 600 and 1000 mm in

February in year 2013 – 2015. .......................................................................... 140

Table 5-8 Interactive effects of ripping topsoil depth treatment on soil moisture at six

different depths of 100, 200, 300, 400, 600 and 1000 mm in July in year

2013 and 2014. .................................................................................................. 140

Table 5-9 Mean Survival Percentages of native perennials with 95% confidence intervals

in three survival periods [spr2012.to.aut2013, spr2013.to.aut2014 and spr2012.to.aut2014] under three site-scale treatments. .................................... 155

Table 5-10 Mean Survival Percentages of native seedlings with 95% confidence intervals

in three survival periods [spr2012.to.aut2013, spr2013.to.aut2014 and spr2012.to.aut2014] under seven plot-scale treatments. .................................. 156

Table 5-11 Overall frequencies (%) of native plant species recorded for the two year

period: from the first emergence event in spring 2012 to autumn 2014. .......... 160

Table 6-1: Effect of filter manipulation treatments on functional dispersion weighted by

species abundances. Four separate seasons are shaded out and effects with

P value < 0.05 are presented in bold font. ......................................................... 177

Table 6-2: Effect of filter manipulation treatments on functional richness (FRic). Four

survey seasons are shaded out and effects with P value < 0.05 are presented

in bold font. ....................................................................................................... 180

Table 6-3: Overall effects of six topsoil transfer stages, from donors remnant site in

autumn 2012 to recipient restoration site in autumn 2014, on functional

dispersion (FDis) and functional richness (FRic, in grey shade) indices. ......... 189

Table 6-4: Dominant trait suites across three site-scale filter manipulation treatments in

the last survey season [autumn 2014, n=573]. .................................................. 190

xxi

List of abbreviations

CWM – Community Weighted Mean

DPaW –Department of Parks and Wildlife

DEC – Department of Environment and Conservation

FDis – Functional Dispersion Index

FRic – Functional Richness Index

MTE –Mediterranean-type Ecosystem

m.y.a –millions years ago

NMDS - non-metric multidimensional scaling

SWA – Southwestern Australia

SE – Standard Error

22

Chapter 1 Introduction

Globally, land-use change continues to drive conversion of native vegetation to human

uses (e.g., agriculture, urbanisation, road construction) to meet the needs of the growing human

population (Smith et al. 2016). The resulting degradation of natural lands is a major factor

contributing to the current biodiversity crisis (Carpenter et al. 2014; Joppa et al. 2016).

Although it is evident that conservation of extant biodiversity should be of paramount

importance (Thant 1970), restoration of degraded ecosystems is necessary to ameliorate the loss

of biodiversity (Hobbs & Harris 2001; Hobbs 2007; Boughton et al. 2016). As reported by

Benayas (2009) in a meta-analysis of restoration studies undertaken around the world,

restoration projects increased biodiversity by 44% and ecosystem services by 25% compared

with the unrestored, degraded sites. Restoration is also necessary to reduce ongoing chronic

disturbance of remnant habitats that persist within a matrix of anthropogenic land uses. In cases

where land managers plan to reconnect habitat patches and reduce fragmentation in a landscape,

restoration is the only suitable action (Possingham, Bode & Klein 2015).

Restoration success is defined most frequently as the full recovery of a degraded

ecosystem and evaluated against appropriate indigenous reference habitats (McDonald, Jonson

& Dixon 2016). While the science of restoration ecology sets out a clear goal to repair damaged

ecosystems many, sometimes conflicting, ideas exist as to how to reach that goal (Hobbs &

Harris 2001; McDonald, Jonson & Dixon 2016). Among the challenges faced by restoration,

practitioners include the difficulty of assimilating vast quantities of published ecological theory

and distilling it to a form that generates effective, locally relevant knowledge to guide actions to

treat degraded sites and enhance local ecological values. For example, new theories and models

developed for restoration projects are largely untested and may not provide a clear

understanding of where a particular model or theory might apply (Bestelmeyer et al. 2009).

Thus, there is an urgent need to undertake and translate ecological findings into provisions for

on-ground restoration guidelines (DeSimone 2013).

Environmental filtering is an example of an ecological concept (Figure 1-1, see also

Figure 7-3) deployed to guide successful reinstatement of indigenous plant communities

(Temperton & Hobbs 2004). Filters carry a notion of environmental conditions that sieve out

species able to establish from a broader regional species pool (Fattorini & Halle 2004). Hence,

the successful use of the filter concept to re-assemble indigenous vegetation requires knowledge

on two aspects of the local ecosystem: the available species pool and species-level traits (e.g.,

functional diversity and propagule availability) and habitat properties (e.g., climate, soil

characteristics, biotic agents such as herbivores). Entry to the community is also governed by

dispersal capabilities as well as by plant species reaction to local abiotic and biotic factors (He

et al. 2016). Multiple stochastic environmental filters, e.g., propagule pressure (Hulvey &

Aigner 2014), soil conditions (Oksanen et al. 2015), grazing (Westoby, Walker & Noy-Meir

23

1989; Yates, Norton & Hobbs 2000) or fire (Odion, Moritz & DellaSala 2010; Pyke, Brooks &

D'Antonio 2010) may influence ultimate species composition. Thus, different environmental

filters may allow for many alternative plant assembly compositions to exist in a given habitat

(Suding, Gross & Houseman 2004). Rebuilding a new ecosystem requires a set of premeditated

strategies that modify existing environmental filters to encourage native species recruitment

while suppressing the performance of non-native species that may be present on-site.

Recognition of the filters that inhibit the transition from degraded land into a reconstructed

near-natural stable state is one of the fundamental questions in restoration ecology (Hobbs &

Norton 2004).

24

Figure 1-1 Filter conceptual framework that presents the role of environmental filter manipulation treatments in

restoration of native ecosystems.

Another important aspect of restoration is to understand how plant functional types

respond to local environmental conditions and whether we can sustain the ecosystem in a

desirable state over a long-term period. The ultimate goal of the restoration project is to re-

assemble a diverse community with the highest possible provision of ecosystem functions

(Oksanen et al. 2013; Oksanen et al. 2015). Environmental filters present on degraded

ecosystems may lead to a community that carries a limited range of functions (Funk et al. 2008)

25

thus retaining the ecosystem in a degraded state. Degraded sites can often be characterized by

trait clumping where for example, small seeded and fast-growing ruderal species dominate the

ecosystem (Bakker et al. 1996; Standish, Cramer & Hobbs 2008). Understanding how to

manipulate onsite environmental filters to move a degraded ecosystem towards its desired state

is crucial (Vitelli & Pitt 2006; Vellend et al. 2014). A fully restored ecosystem accommodates a

high dispersion of functional traits that support central ecosystem functions and processes, e.g.,

in carbon cycling, soil resource acquisition strategies or fire disturbance responses. Functional

dispersion and functional richness maintains the ecosystem processes and improves resistance to

future disruptions (Dodson & Macphail 2004).

In this study, a filter concept was adopted to guide the restoration efforts with the

application of a topsoil seed bank to re-assemble a Mediterranean-type ecosystem (MTE) with

an end goal of achieving a system resembling intact reference plant assemblages. Banksia

woodland ecosystems, the focus of this work, have high species richness and approximately 60

– 80% of occurring species are also represented in the topsoil seed bank (Rokich & Dixon

2007). Accumulation of the propagules in the topsoil has been described as an adaptive response

to fire with fire-stimulated germination of dormant seeds maximising fitness and time between

fires for reproduction (Pausas & Bradstock 2007). The long-term seed persistence and their

proneness toward in situ accumulation make the topsoil a valuable resource to maintain plant

communities (Vécrin & Muller 2003). Ongoing anthropogenic disturbance in coastal Australia,

e.g., land clearing and weed infestation have destabilized local ecosystems and contributed to

unprecedented species loss in these species-rich ecosystems (Wood & Bowman 2012). Thus,

topsoil seed banks may serve as a valuable restoration tool to stem biodiversity loss in this

quickly developing region (Pöll, Willner & Wrbka 2016).

The use of topsoil seed bank salvaged from cleared sites represents one of the promising

approaches to restore indigenous vegetation in degraded areas (Tacey & Glossop 1980). The top

of the A Horizon of the local soil can store a large seed bank of the local plant species pool (as

well as native microbiota) that can facilitate the re-assembling of the native ecosystem.

Restoration with the use of topsoil involves sourcing the top ~5 – 10 cm of the A horizon from

freshly cleared natural areas (donor sites) and transferring this to degraded recipient sites (Koch

2007a). Globally, topsoil transfer presents a useful restoration technique to rehabilitate post-

mining landscapes (Roche, Koch & Dixon 1997; Holmes 2001; Parrotta & Knowles 2001;

Norman et al. 2006; Herath et al. 2009; Hall, Barton & Baskin 2010), urban areas (Pausas &

Bradstock 2007) and farmlands (Vécrin & Muller 2003; Fowler et al. 2015). Topsoil transfer

comprises four stages: topsoil stripping from a donor site, short-term stockpiling, transfer, and

spreading over the recipient site (Koch 2007a). Although it is recommended that the removal of

the topsoil to be minimized, land clearing is often unavoidable and topsoil presents an

exceptionally valuable resource that can be used to deliver improved restoration outcomes

(Hopper 2009).

26

In this study, field-based experiments were implemented following the transfer of

topsoil in Banksia woodlands of the Perth, Western Australia metropolitan region. Treatments

manipulated environmental filters present on the degraded restoration site in order to enhance

germination and survival of native plant species assemblages. Environmental filters present at

the sites were classified into three categories: abiotic, biotic and dispersal limitation (Belyea &

Lancaster 1999). Subsequently, filter manipulation treatments with the use of transferred topsoil

were applied to test their interactive effect on restoration success. The abiotic filter was

manipulated by decreasing soil compaction and evaporation. The biotic filter was addressed

with control of herbivory and weeds. The dispersal limitation was examined by altering the

application depth of the transferred topsoil and application of germination cues, i.e., smoke and

heat. Success was measured by quantifying emergence and survival of all plant species over two

years. Density, richness, and measures of functional diversity were quantified and analysed in

light of filter treatments as well as climate and site covariates. The main goals was to investigate

how filter manipulation techniques affect both functional richness and dispersion on restoration

sites and how functional diversity at restoration sites compares with the reference ecosystem.

This study also offers practical insights on topsoil handling in applied restoration

settings while testing the role of ecological theories. Transfer of the topsoil provides a rare

opportunity to study how the native seed bank contained therein can be used in manipulating

environmental filters present on degraded sites. Subsequently, this study will contribute the

ecological knowledge about restoring the MTE of Banksia woodland facing the threat of

extinction from land clearing (Odion, Moritz & DellaSala 2010).

1.1 Thesis structure

The effects of the restoration techniques on plant emergence (Chapter 4), survival

(Chapter 5), taxonomic composition, and functional diversity (Chapter 6) over a two-year

sampling period and two seasons (spring and autumn) were investigated. Each data chapter is

presented as a self-contained manuscript; hence some portions of the methods contain

unavoidable repetition of the study site and design descriptions. The section describing study

settings and topsoil donor sites were placed in a separate chapter (Chapter 3). These four

chapters are preceded by a literature review (Chapter 2) and are jointly discussed in the overall

thesis discussion (Chapter 7):

Chapter 2 presents an overview of current restoration ecology research. Given the vast

amount of published research in the field of restoration ecology and continuous release of new

reports on advances in topsoil seed bank management, the literature review aimed to identify the

gaps in our understanding of restoration practices with the use of topsoil seed bank. The

literature review provided practical information as well as the rationale for the manipulative

techniques used and studied in this project.

27

Chapter 4 presents an analysis of emergence data encompassing two growing seasons

i.e., the first year since topsoil transfer, in spring 2012, and the second year since topsoil

transfer, in spring 2013. In this Chapter, the emerging seedlings’ densities and how they were

affected by the combination of all site and plot-scale treatments are presented and discussed.

Chapter 5 investigates the effects of the applied site and plot-scale treatments on

survival of native perennial seedlings. The survival through summer drought was estimated

based on four field surveys conducted in the first and second year after topsoil transfer: from

spring 2012 to autumn 2013 (first summer survival) and from spring 2013 to autumn 2014

(second summer survival). This chapter has a more practical approach where findings are

presented as a set of practical conclusions for land management considering use of the topsoil

seed bank as a restoration tool.

Chapter 6 presents an analysis of the plant traits that reflect the fundamental plant

community processes following the start of the restoration project. The selected traits describe a

broad range of plant functions, i.e., growth form, longevity, height, nitrogen fixing, resprouting

capacity, and seed size. Functional diversity indices were computed to gain insights into how

the plant community that undergoes an early stage assembly process responds to the present

abiotic, biotic and dispersal filters that were experimentally manipulated. The functional indices

were also used to understand whether the filter manipulation treatments mitigated the negative

impact of onsite abiotic and biotic filters. Lastly, the patterns in plant communities emerged on

the restoration sites were compared with the reference Banksia woodland ecosystem.

Chapter 7 discusses all the main findings from each data chapter and places these into

the wider ecological context of restoration ecology. The ecological implications of these

findings are discussed in view of future research recommendations in relation to environmental

filters and the use of the topsoil seed bank in restoration projects.

28

Chapter 2 Literature review

2.1 Introduction

Over 40 years ago U Thant, the third secretary-general of the United Nations wrote that

while much work had been done to preserve threatened ecosystems, a great deal more action

was needed to conserve biodiversity (Thant 1970). In the 21st century, the situation is even more

pressing and it is now clear that concentrating only on conservation of intact natural systems is

not an adequate strategy - restoration of degraded sites is necessary (Hobbs & Harris 2001;

Hobbs 2007; Possingham, Bode & Klein 2015). If the scale and pace of the current human

socio-economic practices continue a decline in biodiversity is certain (Laliberté et al. 2012) and

resulting levels of known ecosystem services e.g., microclimate provision of suitable and water

purification might be impaired (Cairns 1993). Current scientific knowledge of ecological

processes e.g., nutrient cycling, soil seed bank processes, and disturbance regime, can be used to

minimize the effects of fast-growing economies on natural ecosystems but the economic cost of

implementing ecologically informed land management solutions is still high (Milner-Gulland et

al. 2013) and natural systems continue to be removed or damaged for development purposes. In

response to the broadly recognized need to repair systems and return species, restoration

ecology as a discipline has emerged to provide the conceptual and practical tools to facilitate

recovery of damaged or degraded ecosystems (Jackson & Hobbs 2009). In times of rapid

economic growth (Hamilton 2011; Ehrlich & Ehrlich 2013), restoration of natural areas is

crucial to slow down the biodiversity loss and repair the degradation of remnant habitats (Gann

2008). The intense demand for restoration and rehabilitation has meant that restoration ecology,

as a scientific discipline, is under significant pressure to mature quickly and develop a broad

literature of theory and applied, on-ground technical knowledge (Bestelmeyer et al. 2009;

Roberts, Stone & Sugden 2009) and is likely to become for Band-Aid on flawed environmental

policies (Bestelmeyer et al. 2009).

The inexorable increase in human population leads to an escalation of conflict between a

need for human residential development, government policies encouraging urban densification,

and the need to conserve the rapidly declining number of habitats for wildlife and plants

(Suding 2011). One policy approach to addressing this tension was the development of a new

paradigm for “biodiversity loss offset” (Maron et al. 2012b) – an argument that ecosystems can

be relocated or damaged systems fully restored to ‘offset’ losses due to development. To

achieve such a policy, substantial research is required in order to gain the necessary confidence

that biodiversity and ecosystem values can be measured and are feasible to restore once

damaged (Maron et al. 2012b). To date, restoration ecology science cannot reliably provide the

means to achieve a full recovery of an ecosystem to its pre-disturbance function and structure

(Walker, Walker & Del Moral 2007; Pöll, Willner & Wrbka 2016). This review aims to provide

29

context for this dissertation where the significance and potential of topsoil seed bank transfer in

restoring a Mediterranean-type ecosystem in Western Australia have been investigated. Driving

and developing understanding of broad restoration ecology principles as well as technical

knowledge to progress restoration practices is of particular importance when local native plant

distribution is reduced to small patches of remnant vegetation (Sayer, Chokkalingam & Poulsen

2004) as is the case of Banksia woodland on the Swan Coastal Plain in Western Australia,

recently recognised by the Australian federal government as an endangered ecological

community (DEE 2016). Under section 184 of the Environment Protection and Biodiversity

Conservation Act Western Australia Banksia woodland is considered to be under threat of

extinction and all its features, including its species-rich understorey, are directed to be

adequately protected.

2.2 Restoration principles

2.2.1 Identification of controlling variables in

ecosystem restoration

Ecosystem response to spatiotemporal changes in environmental drivers can be used to

delineate resilience of individual systems (Carpenter et al. 2001). To gauge broader ecosystem

stability, it is critical to understand the “safe operating space” of each ecosystem in order to be

able to maintain its functions and avoid degradation (Walker & Salt 2012). Significant attention

should be paid to environmental factors that do not show a straightforward and linear effect on

the state e.g., nutrient level or water deficit (Pausas & Bradstock 2007; Walker, Walker & Del

Moral 2007). Once the threshold is reached, acting environmental factors may cause a sudden

regime shift (Schwinning et al. 2004) which in turn may result in locking the ecosystem in an

undesired degraded state (Folke et al. 2004). A deliberate effort to identify thresholds of

potential concern should be part of any landscape conservation strategy (Lindenmayer et al.

2008).

To reverse ecosystem degradation, critical thresholds e.g., limited dispersal, change in

soil hydrology must be overcome (Cortina et al. 2006). Enhancing the dispersal of native

propagules into the degraded ecosystem is one of the promising restoration tools (Koch 2007b).

For example, topsoil spread can be utilized to enhance the reinstatement of native flora on

degraded land as a result of the native seed bank contained therein (Rokich et al. 2002). Within

Western Australia systems, topsoil transfer accounts for 60-90% of species richness in post-

mining rehabilitation underlining its importance in achieving restoration objectives (Rokich &

Dixon 2007). Use of topsoil containing native propagules for restoration has been used across

many settings and locations e.g., SE France (Zhang et al. 2001), South Africa (Holmes 2001),

Brazil (Parrotta & Knowles 2001). Therefore, deeper exploration of topsoil transfer as a

30

mechanism of achieving restoration merits further research.

2.2.2 Theories and models in restoration

Without agreement on overarching conceptual frameworks (Hobbs & Norton 1996),

restoration ecology will be relegated to a set of techniques or art that is based on one’s creativity

and intuition (Halle et al. 2004). Conceptual frameworks allow the exchange of unifying

principles between people involved in restoration, contribute to consensus on agreed goals in

restoration and build a knowledge base where a new scientific discipline may mature.

Moreover, accumulating knowledge addressing answers to local ecological issues by linking

them into the larger conceptual frameworks provides a clear narrative to a broad range of

stakeholders. Science of restoration ecology that is capable of making predictions, e.g., success

rate of the available restoration tools, may be subsequently translated into policy that is clear to

local governments as well as to ecologists and landowners (Keddy 1992; DeSimone 2013).

Restoration ecology derives its principles from the science of ecology and serves as

means to test them in on-ground actions (Bradshaw 1984). The theory on assembly rules

appears to be one of most relevant in the restoration of the local plant communities (Temperton

& Hobbs 2004). Assembly rules provide a set of concepts that can assist in successful

rehabilitation of a degraded or destroyed ecosystem by providing a predictive function of

vegetation change in relation to environmental conditions. Assembly rules require two initial

datasets: available species pool and habitat properties. Plant species with traits aligned with a

matrix of future habitat are selected and used in a restoration context (Keddy 1992). Three main

models that explain future vegetation compositions might be employed to understand how the

local species pool establishes under field conditions (Temperton & Hobbs 2004):

Deterministic model describes how abiotic and biotic factors result in a limited

community assemblage e.g., climax in the succession theory. Species composition might be

determined by edaphic and historical factors, e.g., climatic conditions, nutrients availability and

soil hydrology (Svenning et al. 2004).

Stochastic, also known as “carousel models”, emphasize randomness; community

structure depends on order of arrival, e.g., ant assembly (Cole 1983). Propagules move around

in the community in an unpredictable way and are capable of establishing at any microsites

provided a favourable set of environmental conditions (Maarel & Sykes 1993).

Alternative Stable State (ASS] – is a combination of deterministic and stochastic

models. Development of communities is restricted to some extent, and there are many

alternative combinations of coexistence.

The vegetation assembly models are very useful in assessing any constraints on species

establishment and coexistence. The principal aim of presented models is an ability to guide and

describe the factors controlling the assembly rules of local plant community in response to local

31

environmental conditions and species pool available for a given region. The role of succession,

filter and ASS models in restoration ecology are described below.

2.2.2.1 Succession theory and practice

Contrary to the framework of Alternative Stable State Models, the theory of succession

promotes an idea that every region can be characterized by one type of plant community being a

final stage of successional processes (Clements 1916 as cited in Krebs 1994). The climate is

seen therefore as a key driver of how vegetation composition assembles. The process of plant

community development follows a trajectory of successional stages towards a final stage

defined as the climax. Succession provides a useful conceptual framework to understand

changes in site substrate and microclimate as members of each successional stage are

confronted by any site-related barriers in order to reach a climax condition. For example, in a

study of early forest succession on Chiloe Island, pioneer species may supply shaded microsites

and alleviate poor soil drainage, which are essential conditions for late-successional tree

seedlings to establish (Bustamante-Sánchez & Armesto 2012).

The development of plant communities towards the desired climax stage can be

hindered by dispersal capabilities of the members of given ecosystems. For example, the

delayed occurrence of a species in an old field is most likely due to limited dispersal. An

experiment on bare ground showed that old fields five and fifteen years after abandonment

could be populated by all species from the local species pool but failed to do so due to the late

arrival of their propagules (Jordan, Gilpin & Aber 1987).

Forced introduction of organisms that does not suit the current successional stage is

likely to be a waste of scarce resources. If succession can be facilitated to occur naturally the

required restoration effort might be minimal (Palmer, Ambrose & Poff 1997). This passive form

of restoration may save a significant amount of time and capital. In the case of partial ecosystem

recovery, any missing desirable species might be simply inter-seeded, e.g., in prairie habitat

(Lockwood & L. 2004) or inter-planted as suggested for the restoration of Eucalyptus

woodlands in WA wheat belt (Yates & Hobbs 1997).

2.2.2.2 Filter-based community assembly model

Filter concepts in ecology carry the notion of mechanisms and conditions that sieve out

species able to establish locally from a regional species pool (Fattorini & Halle 2004). Keddy

(1992) compared the filter mechanism to natural selection where only the best-suited species

survive and are able to reproduce. Entry to the community is governed by plant species reaction

to local abiotic and biotic factors (Maher, Standish & Hallett 2008). The filters can also be

understood as multiple processes, e.g., plant interactions, environmental conditions, herbivory,

32

that structure the extant vegetation at the given site by determining what species from the local

pool adapt and survive best (Koch 2007b).

Rebuilding a new ecosystem requires a set of premeditated strategies that modify

existing environmental filters in order to encourage native species recruitment while

suppressing the performance of non-native species that may be present on-site. Recognition of

the filters that inhibit the transition from degraded land into a reconstructed near-natural stable

state is one of the key questions in restoration ecology (Hobbs & Norton 2004). For example,

investigation of native grassland community restoration suggested that manipulating a

combination of environmental barriers i.e., abiotic (e.g., soil nutrients, climatic conditions),

biotic (e.g., competition, herbivory) and dispersal (e.g., propagule availability) is necessary in

order to achieve the best outcomes (Hulvey & Aigner 2014). Knowledge about multi-scale

processes, both temporal and spatial, is crucial to understand how manipulation of local

environmental barriers is linked to ecosystem functioning (Shackelford et al. 2013b).

2.2.2.3 Alternative stable state models

The alternative stable state model is the closest to natural dynamics in the opinion of

many ecologists (Pausas & Bradstock 2007; Odion, Moritz & DellaSala 2010; Wood &

Bowman 2012). Establishment of species is certainly determined by local conditions but

regulated by stochastic events such as disturbances. Disturbances like fire (Odion, Moritz &

DellaSala 2010; Pyke, Brooks & D'Antonio 2010) or grazing pressure (Westoby, Walker &

Noy-Meir 1989; Palmer, Ambrose & Poff 1997) affect species composition and allow many

alternative plant establishments in a given location. This hypothesis transforms our

understanding of how disturbance influences plant recruitment. Human land management

might, therefore, be described as disturbance manipulation by means of its creation or

suppression or altering of disturbance type, frequency, and intensity (Boughton et al. 2016). The

main question, for ecological restoration and land management, is whether the trajectory of

change is moving in the desired direction and if not how we can correct it (White & Jentsch

2004; Keddy 2005).

2.3 Restoration of plant diversity

Plant diversity indices e.g., Shannon-Wiener’s index, Simpson’s index, species richness,

serve as a tool to evaluate restoration success and are mostly assessed against those of reference

sites (Ruiz‐Jaen & Mitchell Aide 2005). However, many reference sites are characterized by

high species turnover and to account for that variation more reference sites should be

investigated to set accurate comparative benchmarks. As shown in a study on the plant diversity

on Swan Coastal Plain in WA, characterized by high gamma diversity, it is a challenge to

33

ensure benchmarks are adequate (Gibson et al. 1994). Ideally, long-term studies would be

necessary for providing a profound understanding of Australian ecosystem ecology and their

long-term dynamics (Lindenmayer et al. 2012), but such efforts are rare in the Australian

context.

2.4 Restoration of plant functions

Plant diversity frequently is expressed in terms of species composition and abundance.

While this might be an easy tool to assess potential success of restoration, it does not provide

sufficient information on function and structure of rehabilitated ecosystems (Reay & Norton

1999). A thorough examination of diversity, i.e., species richness, species abundance in single

or multiple taxa, structure i.e., plant cover, height, growth form or reproductive output and

function, i.e., nutrient cycling and pollination services together is paramount to understanding

restoration progress and restoration success (Montoya, Rogers & Memmott 2012). These three

assays of restoration outcome are widely recognized by ecologists but rarely measured together

(Ruiz‐Jaen & Mitchell Aide 2005) with ecosystem function (also variously titled ecological

processes or biological interactions), being assessed most rarely (Chambers, Brown & Williams

1994).

A diverse plant assemblage will provide a broad variety of traits and support a diversity

of functions (Boughton et al. 2016). A wide range of plant traits ensures a wide diversity of

responses to disturbance, e.g., fire, floods, diseases and therefore will assist in sustaining the

viability of core ecosystem functions and services (Shackelford et al. 2013a). These services

might be human-related e.g., firewood, timber, but also fauna related, e.g., number of perches,

food, and shelter for birds. Based on a meta-analysis of more than 400 experiments on

biodiversity and ecosystem functioning Duffy (2008) provides strong evidence that ecosystem

diversity strengthens system functionality.

2.5 Restoration of Mediterranean-type

ecosystems

Gathering comprehensive experimental and observational data is pivotal to advance the

science of restoration ecology. Conservation lands are now embedded within an agricultural

production-oriented matrix and coupled with little knowledge on the ecology of many genera,

sets a difficult target for land managers and restoration scientists (Hobbs 1992b). Knowledge

about multi-scale processes, both temporal and spatial, is crucial to understand how

manipulation of local environmental barriers is linked to ecosystem function (Shackelford et al.

2013b). The most important aspects of the challenge to develop a successful restoration plan are

presented below.

34

2.5.1 Climate-related restoration tools

Climate is recognized as a major force shaping Mediterranean-type ecosystems (Lavorel

et al. 1998) where a small reduction in precipitation may shift plant communities towards low-

cover arid shrubland. In light-abundant Mediterranean-type ecosystems (MTE), growth rates

and biomass accumulation in plant species is strongly related to annual rainfall (Ogaya &

Peñuelas 2007). Water availability is a key factor affecting plant survival in Mediterranean

conditions, and most of the restoration efforts should be focused on increasing water-use

efficiency (Vallejo et al. 2006). An ideal seed or seedling material would develop those traits

that allow it to withstand transplantation shock, persistence under hot and dry summer

conditions and display enhanced performance during the rainfall events as observed in Pistacia

spp saplings (Valladares et al. 2005). In restoration actions, we must also consider the

importance of historical and natural baseline for vegetation composition (Whipple, Grossinger

& Davis 2011) as well as its resilience to future changes (Suding 2011).

To maximize performance of transferred plant material, which is rarely ideal, use of

different restoration techniques are practiced under Mediterranean conditions. Here, some of the

key techniques for maximising the restoration outcomes are presented. For seeds these are:

Early sowing is the low-cost approach to optimize plant recruitment and

establishment (Turner et al. 2006; Commander et al. 2009) - before an advent of

winter temperature and precipitation.

Polymer coating, usually incorporating growth-stimulating agents, pesticides or

fungicides, shows positive effects on recruitment in WA (Turner et al. 2006)

Application of smoke, especially important in fire-prone ecosystems (Pérez-

Fernández et al. 2000; Wills & Read 2002), active chemical compounds being

identified recently (Flematti et al. 2004)

Exposure of seeds to heat stimulates germination in many MTE species

(Gashaw & Michelsen 2002), i.e., surface burning (Went, Juhren & Juhren

1952). This may be accomplished via fire or oven and include wet or dry air

with some suggestion of hot water vapour elevating germination in lab

conditions (Cushwa, Martin & Miller 1968).

Exposure to winter temperature may break seed dormancy in MTE species i.e.,

in genus Hibbertia (Hidayati & Walck 2012).

Shallow- up to 10 mm burial (Tobe, Zhang & Omasa 2005) or topsoil raking

(Rokich & Dixon 2007) protects seeds from predation and erosion

Avoidance of stockpiling in case when the seeds are sourced from the topsoil

(Tacey & Glossop 1980; Rokich et al. 2000; Koch 2007b)

Installation of artificial shading shows positive results on germination (McLaren

& McDonald 2003)

35

Micro-catchments proved to be a successful tool in initiating autogenic

restoration at semi-arid sites in Australia (Whisenant, Thurow & Maranz 1995).

Drought is also a consistent feature in agricultural areas and development of

seed invigoration methods i.e., pre-soaking, seed priming, osmo-priming, halo-

priming, matri-priming is used to control their germination in water-limited

edaphic environment (Farooq et al. 2011)

For seedlings these are (Vallejo et al. 2006):

Drought-preconditioning minimizes transplant shock followed outplanting from

nurseries and improves seedling’s response to drought

Selection of drought-tolerant species

Improvement of below-ground performance and avoidance of root spiraling

Introduction of tree shelters

Selection for favorable microsites in relation to their hydrological and

nutritional properties

Utilization of the facilitative properties of nurse plants

Addition of fertilizers

Installation of artificial shading (Rey Benayas 1998; Rey Benayas et al. 2005)

Deep planting protects from irradiation and allows roots to reach groundwater

faster (Oliet et al. 2012)

2.5.2 Soil-related restoration tools

Soil preparation techniques developed for restoration of MTEs converge mostly upon

two aspects: improvement of water supply to restored vegetation and amelioration of soil

biological, physical and chemical properties. In cases when topsoil is lost, i.e., mining areas, the

chance of recovery of the original ecosystem is very low if none (Cooke & Johnson 2002).

Degraded areas that are characterized by a long-term agricultural land-use legacy may carry

over a detrimental environmental signature, e.g., increased compaction and excessive soil

nutrient level that may affect the establishment of native plant communities (Proulx &

Mazumder 1998).

Ripping. As studies on Jarrah Forest post mine sites show, the process of ripping

improves soil porosity, creating a friable rooting zone (Koch 2007a). Ripping alleviates soil

compaction and therefore increases water infiltration, and plant growth rate is higher (Kew,

Mengler & Gilkes 2007; Ruthrof 2012). It also allows for greater soil aeration. Oxygen is

required in a concentration not smaller than 2 % of soil air available at the root surface for a

proper root growth (Kirkham 2011). Application of a ripping treatment might be equally

important in studies where the topsoil has been translocated by means of heavy machinery,

leading to possible compaction and increased hydrophobicity. A study from the Rocla sand

36

quarry in the northern Perth metropolitan area showed that ripping may have a positive effect on

survival of seedling recruiting from a returned topsoil seed bank (Rokich et al. 2000).

Irrigation is strongly recommended in high-level erosion areas, i.e., opencast mines

(Josa, Jorba & Vallejo 2012) but must be applied carefully (Leiva, Mancilla-Leyton & Martín-

Vicente 2013). Irrigation may hinder proper root development and may lead to increased plant

mortality in later stages of stand growth when irrigation ceased. The importance of robust root

development able to reach a deep and moist soil horizon has been reported from sand mine

rehabilitation sites at Eneabba (Enright & Lamont 1992).

Organic matter. Soils in MTEs are water repellent and on average deficient in organic

matter (Vallejo et al. 2006), a condition associated with frequent fires (DeBano 2000). Those

typical soil properties of Mediterranean areas translate into very low water-holding capacity. It

might be mediated by either application of non-ionic chemical water agent (DeBano 2000) or

addition of organic matter (Rawls et al. 2003; Celik et al. 2010). Early growth of seedlings is

definitely stimulated by the presence of organic matter in the soil (Goodall 1973). Seedlings of

Banksia attenuata and Banksia menziesii showed better water status and greater survival when

grown on a mixture of sandy substrate enriched with native-sourced mulch (Benigno, Dixon &

Stevens 2012). Similarly, the growth of Acacia saligna was promoted at a bauxite mine

revegetation site by addition of compost (Jones, Haynes & Phillips 2012). Pinus halapensis

seedlings showed greater survival after soil organic matter amendment (Barberá et al. 2005).

Where impedance of rehabilitation soils is higher, i.e., where clay content is high, ripping must

be accompanied by the addition of organic matter in order to reduce soil penetration resistance

(Bateman & Chanasyk 2001).

Soil solarization. Shade might reduce summer mortality of young seedlings in

Mediterranean-type regions by lessening the impacts of solar radiation. A lower sun exposure

reduces potential evaporation and is closely correlated with plant-soil-water relations. In an

experiment on Quercus ilex seedlings, artificial shading had nearly as positive an effect on

survival rate as did an irrigation treatment (Rey Benayas 1998). The reduction in incident

photosynthetically active radiance (PAR) also lowered the risk of photo-damage (Rey Benayas

et al. 2005) and reduced soil surface temperature (Jurado & Westoby 1992). In an experiment in

Arizona, installation of shade in the first week after germination in Carnegiea gigantea

improved seedling survival (Turner et al. 1966). A study on the effect of 70% shading (30% of

daylight allowed) on Eucalyptus seedlings resulted in higher biomass and lowered root/shoot

ratio (Withers 1979). For an optimal performance in seedling growth a balance between water

availability and compensation point must be achieved (Howard 1973), and a reduction of

daylight influx by nearly half in comparison to open plots (929 lux vs. 498 Lux) appears to be

optimal for seedling survival in arid zones (Turner et al. 1966).

37

2.5.3 Disturbance-related restoration tools

Fire. Impacts of fire every level of biological organization (White & Jentsch 2004) and

is one of the dominant terrestrial disturbances globally (Thonicke et al. 2001). Fire disturbance

was an active environmental force since terrestrial plants appeared on Earth (Bowman et al.

2009; Krawchuk et al. 2009; He et al. 2016). Fire was also used by the first humans to manage

wildlife and vegetation composition; interventions into fire regimes by Aboriginal people in

Australia were very common (Yibarbuk et al. 2001; Gammage 2011). Mediterranean vegetation

is characterized by a number of fire-adaptive traits, i.e., serotiny, resprouting, seed germination

cued by smoke and heat (Keeley et al. 2011b) although their fire-related evolution is still argued

(Bradshaw et al. 2011; Keeley et al. 2011a).

Approximately 60-80% of the seeds produced by plants in the Banksia woodland

ecosystem become incorporated as dormant propagules in the topsoil (Rokich & Dixon 2007).

Seed dormancy is believed to have evolved as an adaptation to a regime of frequent fire and

requires cues associated with fire (heat, smoke) to stimulate germination (Pérez-Fernández et al.

2000; Wills & Read 2002; Cochrane, Monks & Lally 2007). This specific adaptation to fire is

often utilized in restoration contexts where spread topsoil or broadcast seeds are treated with

smoke agents to break seed dormancy and stimulate emergence. There are contrasting results on

the efficacy of applying smoke agents such as smoke water and smoke aerosol. While (Norman

et al. 2006) state that seeds were more responsive to smoke water, Roche (1997) found aerosol

to be more stimulative. Although fire-related cues are very useful in overcoming the dormancy

of topsoil-stored seeds the process of stripping and respreading the soil may also stimulate some

germination via seed scarification (Fowler et al. 2015).

Fire regime. Understanding the impact of fire regime on the diversity of Banksia

woodland and how this translates into management of both restored and mature ecosystems is

also important. Changes in fire intensity and frequency, i.e., during European settlement,

resulted in changes in vegetation composition as well as in resident bird and mammal species

abundances (How & Dell 1989). Additionally, size of burn patches will also influence stand

resilience. For instance insect herbivores, i.e., grasshoppers or kangaroos, were particularly

damaging in small burnt areas (Whelan & Main 1979; Holz et al. 2015). Fragmented areas of

bushland are more often invaded by non-native annual plants dispersing along the tracks than

are intact areas (Keighery 1989; Keeley, Lubin & Fotheringham 2003). There may be a

reciprocal relationship where stands become more fire-prone due to die off of annual weeds in

the summer while increased fire frequency leads to higher susceptibility of Banksia woodlands

to weed invasions (Fisher et al. 2009a).

Weeds. Alien species pose a serious threat to native plant diversity and ecosystem

stability (Gaertner et al. 2009). Biological invasions are recognized worldwide as a major

environmental problem (Vitousek et al. 1997). In climate zones with intense summer drought

38

and short rainfall events during winter, competitive advantage tends to shift from “slow water-

users” - native perennial vegetation, toward “fast water-users” - annual invasive species

establishment (D'Antonio & Vitousek 1992; Dyer & Rice 1999). A number of studies have

shown that fast-growing annuals are very likely to inhibit regeneration of native perennial

species (Gordon, Menke & Rice 1989; Auken & Bush 1990; Melgoza, Nowak & Tausch 1990;

Hobbs & Atkins 1991; Welker, Gordon & Rice 1991; Bakker & Wilson 2001; Standish, Cramer

& Hobbs 2008; Fisher et al. 2009a; Standish & Hobbs 2010). Reduction in native perennial

biomass may reach 70% compared to conditions with no invading competitors present (Yelenik

& Levine 2010). Understanding the ecology of annual invasive species is essential in the

restoration of MTEs (Clary et al. 2004).

Annual fast-growing species may also have a detrimental effect on whole MTEs

(Lambrinos 2000). Some species show the ability to transform soil properties e.g., increase in

total inorganic nitrogen, (Musil 1993; Hamman & Hawkes 2013) or utilize moisture more

rapidly than native species (Pérez-Fernández et al. 2000) thereby altering species interactions

and eventual establishment. Exotic species appear to respond more quickly to increased nutrient

and water availability than do natives even after soaking native propagules in smoke water as

reported from three field studies located at Jandakot, Kings Park and Curtin University in

Western Australia (Pérez-Fernández et al. 2000). Invasive species also germinate more quickly

and show a faster response to light when compared with native species (Raphael et al. 2015).

Grass-related pressure on limited soil water and nutrient resources might be significantly

reduced by browsing (Montaña, Cavagnaro & Briones 1995; Heyden & Stock). Graminaceous

weeds show a drastic decrease in root production in response to aboveground biomass removal

(Caldwell et al. 1987; Mott et al. 1992; Danckwerts 1993). This might be related to investment

in grass defense systems, i.e., phenolic compounds (Walling 2000) or increased silica

accumulation (Massey, Ennos & Hartley 2007). Therefore applying a specialized browser could

be a potential solution to grassy weed domination (Cushman, Lortie & Christian 2011).

Unfortunately, most of herbivores are generalists, thus chemical weed control in combination

with fencing is widespread in managing fragmented bushland areas.

Water availability. There has been a reduction in annual rainfall within recent decades

in the southwestern region of Western Australia (BOM 2015) which, in conjunction with a trend

of lowering depth to groundwater across the Swan Coastal Plain, may affect the vigor and

fitness of local species (Froend & Sommer 2010). Mortality and loss of wetland-associated

species (Eucalyptus marginata, Banksia littoralis, Hypocalymma angustifolium and Regelia

ciliata) and subsequent replacement with species from upland sites (Banksia attenuata, B.

menziesii, Gompholobium tomentosum, Hibbertia subvaginata and Leucopogon

conosthephioides) has been reported from portions of the Swan Coastal Plain (Dodd & Heddle

1989; Froend et al. 2013). Documented rapid groundwater decline exceeded the capacity of

some Banksia species to elongate roots and maintain groundwater connection leading to tree

39

mortality (Canham 2011). Such mortality and loss of vegetation suggest that assisted

colonisation, e.g., via topsoil transfer, may be required in order to retain native vegetation in

affected sites.

2.5.4 Native seedling establishment in sandy soils

Well-drained and nutrient poor quartz sand of depositional origin forms the substrate for

the Swan Coastal Plan where this restoration study is located. Understanding role of sandy

substrate in the emergence of seedlings and their survival is crucial. Sandy soils that evolved on

sand were reported to stimulate seedling growth due to better wetting properties but also

induced higher mortality over summer due to high infiltration rates (Hallett et al. 2014). High

water infiltration may increase seed germination and enable emerging seedlings to readily

extract water after rainfall (Maestre & Cortina 2002). Rainfall is relatively reliable in the winter

period when most seeds germinate in regions with a Mediterranean climate (Cowling et al.

2005). However some sandy soils are also hydrophobic, i.e., increased water repellency due to

hydrophobic organic compounds developing on sand grains, particularly in autumn may lead to

localized water logging. Consequently, rate of water infiltration in hydrophobic sandy soils may

be more important than soil water repellency for seedling emergence in MTEs and need to be

addressed in restoration works (Schütz, Milberg & Lamont 2002; Ruthrof et al. 2016).

Additionally, soil texture in sandy soils promotes leaching of nutrients to lower portions of the

soil profile effectively making them unavailable to plants (He & Dimmock 1998). Such a long-

term process has driven myriad adaptations to low nutrient soils in native plant species which,

in some cases, may confer an advantage over exotic weeds that require higher nutrient

concentration (Leishman 1999).

Sandy soils that wet up thoroughly due to high infiltration properties stimulate

emergence but may also have an adverse effect on seedlings survival over the subsequent

summer drought typical for MTEs. Fast development of the tap root is crucial. The native tree

Banksia prionotes, for example, utilizes its tap root mostly during the summer to counteract

water deficiency in the surface soil (Pate et al. 1998). It is vital information for restoration

where early seedling growth must be accomplished before the drought season encroaches.

Similarly, development of an effective root-mycorrhizal network is essential for adequate water

and nutrient acquisition by many terrestrial plant species (Lambers et al. 2009). As the fungal

growth is often impeded by soil disturbance, e.g., arbuscular mycorrhizae (Jasper, Abbott &

Robson 1991) restoration of the local ecosystem should also take into account timing and scale

of the onsite preparation works. However one of the main families (Proteaceae) in the Kwongan

vegetation does not require fungal symbionts.

40

2.5.5 Translocations

Human-induced disturbance that leads to the degradation of the landscape might also be

viewed as a chance to enhance it by introducing alternative ecosystems (also called novel

ecosystems) to the landscape matrix (Bradshaw 1984; He et al. 2016). This is a complex

philosophical matter but is an especially crucial question in the present era when climate change

may provide a strong argument for translocating species onto the area to be rehabilitated in a

process called assisted colonization (McLachlan, Hellmann & Schwartz 2007). Introducing a

new and fit taxon may bring potential biodiversity benefits to the rehabilitated ecosystem by

maintaining its ecological functions (Lunt et al. 2013). For example, in southwestern Australia

(SWA) where higher average temperatures, an ongoing reduction in rainfall and longer dry

spells are projected (Hughes 2003; Keeley et al. 2011b), an introduction of species adapted to

drier future climate might be beneficial for maintaining ecological processes. Although

managed relocation of species outside their native range is ethically unresolved (Richardson et

al. 2009) and ecologically under-investigated (Lindenmayer et al. 2008) this technique is very

likely to be used in a restoration of shifting ecosystems under climate change (Harris et al.

2006). In addition, recent studies on facilitation support introduction of phylogenetically distant

plant species in restoration practices to enhance their resilience (Verdú, Gómez-Aparicio &

Valiente-Banuet 2012).

2.6 Topsoil seed bank

The occurrence of seed dormancy in fire-prone MTEs is considered very advantageous

in the rehabilitation of degraded sites by means of topsoil transfer (Koch 2007b). Many

Australian genera display a deep dormancy, i.e., Persoonia (Chia 2012), Hibbertia, with some

embryos requiring a lengthy process of growth inside the seed coat (Hidayati et al. 2012).

Germination biology of dormant seed is very complex, and many other environmental factors

might be involved in regulating germination responses (Baskin & Baskin 1998), i.e., mineral

nutrition, smoke, heat, competition, temperature, carbon dioxide concentration, mother plant

position. In fire-adapted MTEs recruitment of many plant species is triggered by fire-related

cues (Keeley et al. 2012) such as heat (Cushwa, Martin & Miller 1968; Gashaw & Michelsen

2002) and smoke (Dixon, Roche & Pate 1995; Wills & Read 2002; Crosti et al. 2006).

Importantly, the signal starting germination comes from the embryo itself and does not depend

on sturdiness or architecture of a seed coat (Junttila 1973).

Soil-stored seeds in SWA ecosystems are on average of small size (Enright et al. 2007)

which plays a major role in exposure to the risk of predation (Crawley 1992) – small size

protects them from specialist arthropod seed-feeders and in conjunction with low palatability

makes them unattractive to generalist seed predators (Brenchley & Warington 1936) – a

41

required attribute in assessing use of topsoil seed bank in restorative operations. Rodent

predators, for example, have a very negative effect on large-seeded species in the African

savannah, i.e., or Acacia drepanolobium (Keesing 2000) or Acacia karoo (Chidumayo 2013).

Predation and possibly many other factors, i.e., the age of stand, location and size of the stand,

the number of invasive species, reproductive strategy, may contribute to the composition of

propagules in the topsoil seed bank. As a result, its composition and amount of viable

propagules may be different from the standing vegetation (Enright & Cameron 1988; Sem &

Enright 1995). Importantly, a trade-off appears to be very explicit in SWA plant species

between a complexity of intercellular anti-inbreeding mechanisms, i.e., heterozygosity

translocation and the level of seed set (Hopper 1992). The resulting low seed set in many SWA

flora underpins the importance of preserving topsoil seed bank for restoration efforts.

It is believed that small size and high level of dormancy (long-living) propagules are the

major factors that contribute to the large topsoil seed banks found in MTE (Holmes & Cowling

1997). Large local seed banks represent a high potential for restoration purposes following land

clearing. The viability of the seed strongly depends though on conditions of stockpiling and

climatic conditions – with higher seed survival rate in arid waterproof conditions (Golos &

Dixon 2014). Hence, topsoil seed bank forms an additional source of viable propagules that are

otherwise unavailable or stored in low quantities in relation to the demand from restoration

projects (Merritt & Dixon 2011).

2.6.1 Topsoil seed bank transfer

Topsoil transfer is a novel approach to offsetting the damage inflicted on remnant

bushland by increasing urbanization. However, the ecology of many local species is still poorly

known, and information on topsoil transfer outcomes is mostly confined to restoration activities

at mine sites. Ecosystems studied in the mining context (e.g., Jarrah forest restoration by Alcoa)

conform predominantly to an initial floristic composition successional model – with all species

entering the site at the same time (Bell, Plummer & Taylor 1993). Topsoil transfer for Banksia

woodland restoration varies somewhat from this as it includes site legacy effects in the

restoration area, with pre-existing plants and seeds present in situ and likely to influence

restoration outcomes, particularly weeds.

Although it is recommended that the removal of topsoil is minimized to facilitate in situ

vegetation recovery after clearing (Hopper & Gioia 2004), if the cleared site is to be converted

to other uses, then salvage and use of the topsoil elsewhere represents one of the best potential

means to restore vegetation quality in degraded areas (Tacey & Glossop 1980). Topsoil in

Mediterranean-type regions is an incredibly important ecosystem component; it contains soil-

stored seeds of many species as well as nutrients and other soil micro-organisms. In places like

SWA topsoil is the only manner by which to move many species between sites over a large

42

scale. The long-term seed persistence and their proneness toward in situ accumulation make the

topsoil a good measure to avoid the complete destruction of the remnant plant communities

(Vécrin & Muller 2003).

In this study, topsoil was transferred from cleared Banksia woodlands associated with

the expanding Jandakot Airport development in southern Perth, WA (DEC 2009). It provided a

rare opportunity to use the topsoil resource from a high-quality bushland to help reconstruct the

understorey of Banksia woodlands in two nearby areas that had been agricultural land. Many

previous studies in SWA region and elsewhere have investigated topsoil seed bank ecological

values in relation to mine site rehabilitation (Roche, Koch & Dixon 1997; Holmes 2001;

Parrotta & Knowles 2001; Norman et al. 2006; Herath et al. 2009; Hall, Barton & Baskin 2010)

but little is known about reconstruction of Banksia ecosystems on to degraded ‘old-field type’

sites by means of transferring local topsoil seed bank.

43

Chapter 3 Study setting

The restoration experiment was embedded within a broader management plan aimed at

restoring degraded land and returning native woodland vegetation in southwestern Australia.

The relevance of the work is underscored by the ranking of the ecosystems surrounding Perth

capital city as the most threatened portion of a globally designated biodiversity hotspot (Myers

et al. 2000; Hopper & Gioia 2004).

The restoration study sites were located within areas reserved for conservation but

existed in a degraded condition, primarily from agricultural use (see site description for further

details). This project was part of a compensatory mitigation programme, also termed a

‘biodiversity offset.' Biodiversity offsets are increasingly used in an attempt to resolve the

conflict between nature conservation and urban development (Maron et al. 2012b; Hrabanski

2015). In a situation when land clearing is unavoidable the developer agrees to purchase or

restore an equivalent area elsewhere to compensate for the impact on the local ecosystem

(Hrabanski 2015). Similarly, in Western Australia implementation of the biodiversity offset

agreements aims at mitigating the removal of native vegetation by land clearing. Developers of

the Jandakot Airport, Perth, Western Australia agreed to support a topsoil transfer restoration

project as part of a biodiversity offset program to compensate for the destruction of high-quality

remnant woodland vegetation from land earmarked for commercial airport expansion. The

identified restoration offset sites would originally have supported similar vegetation to that of

the cleared development area and occur on the same landform type - low, nutrient poor sand

dunes with iron or humus podzols of the Bassendean Sand Complex (as classified in 1980).

Local government agreed to the clearing of 167 ha of remnant Banksia vegetation at Jandakot

Airport in accordance with the Environmental Protection and Biodiversity Conservation Act

1999 as described in Jandakot Airport Offset Plan (JAH 2014). Agreed land clearing was part of

the development of future airport infrastructure where developer, Jandakot Airport Holding,

agreed to transfer the topsoil from the cleared land on to two designated restoration study sites

approximately 20 km away (DEC 2009).

Table 3-1 – List of selection criteria used in the assessment of potential recipient sites. Adapted from Fowler

(2012).

Criterion Importance

Banksia woodland similar to vegetation at donor site Very high

Proximity to donor site Very high

Area of remnant vegetation adjacent to recipient site High

Conservation status of vegetation adjacent to recipient site High

44

Criterion Importance

Records of rare species in vegetation adjacent to recipient

site High

Historical records of Carnaby’s cockatoo habitat High

Carnaby’s cockatoo breeding site proximity High

Carnaby’s cockatoo night roost proximity High

Site with secure tenure High

Threatened or priority ecological community Medium

3.1 Climate

The climate of SW Australia is Mediterranean, with hot, dry summers and mild, wet

winters (Bates et al. 2008). Air temperatures in summer months (Dec, Jan & Feb) over the

previous 25 years (1989—2013) averaged 16.2° C minimum and 30.7° C maximum, while over

the winter months of the same period (Jun, Jul & Aug) minimum and maximum temperature

averages were 7.0° C and 18.5° C, respectively (BOM 2015). The air temperatures fall within a

general trend of warming climate in southwestern Australia (Bates et al. 2008; Diffenbaugh &

Field 2013) - mean maximum temperature of the summer months of 2012 and 2013 was on

average 1.1° C warmer than the 25 years mean (BOM 2015).

Mean annual rainfall in the study area is 833.4 mm with ca. 80% falling during the

growing season (wet season) between May and September, inclusively (Table 3-2). The total

rainfall for the growing season of 2012 was 182.6 mm lower than the mean rainfall for the

growing season (mean growing season rainfall 1986-2013 632.6 ± 122.8 SE mm). Regional

variability characterizes the rainfall pattern on the Swan Coastal Plain. Annual rainfall in 2012

recorded at topsoil source site at Jandakot Weather Station was 684.4, while two weather

stations located near topsoil recipient sites recorded rainfall of 733.4 mm at Forrestdale Weather

Station, ca. 20 km away and 760.8 mm at Anketell Weather Station, ca 25 km away (BOM

2015).

Table 3-2: Historical climate [1986—2015] recorded at Forrestdale climate station nearest the study sites,

compared with the climate experienced in the first [2012], the second [2013] and third [2014] year since topsoil

transfer. The wet season was defined for between May and September inclusively. Rainfall evenness was

calculated after Pielou’s: PE = SW/ ln(M) where SW - Shannon-Wiener for rainfall in mm, M - number of months

with rainfall. Evenness ranged from 0.0 with entire rainfall in one month to 2.3 with even rainfall across all

months.

Climate Variable 1986—2015 ±SD 2012 2013 2014

Annual 833.4±146.8 733.4 872.8 762.4

45

Climate Variable 1986—2015 ±SD 2012 2013 2014

Dry season % 24.0±7.7 38.6 31.5 31.5

Wet season % 75.9±7.7 61.4 68.5 68.5

Evenness ±SD 1.92±0.09 2.01 1.86 1.93

3.2 Geology

The Swan Coastal Plain is primarily composed of Quaternary terrestrial sand that

originated mostly from marine shoreline deposits and erosion of the continental materials to the

east (Bolland 1998). These deposits form dunal ridges up to 80 m high, running in parallel

bands formed by repeated incursions of coastal waters due to changes in sea levels during the

two last geological epochs (Smith et al. 2016). The Swan Coastal Plain sand deposits are bound

on their east side by the continental escarpment formed of Precambrian Australian Shield

igneous rocks (Kendrick 1991). Therefore the age of dune bands in general increases eastward,

away from the present day coastline (Dixon 2011; Smith et al. 2016). The depositional material

of the Bassendean Dune System is considered the oldest – ca. 300.000 years old and ca. 22 km

wide (McArthur et al. 1991). Bassendean dunes consist mostly of aeolian sands on which iron

podsols with a pale grey to faint yellow sandy A-horizon (Bastian 1996) and a B-horizon

containing iron and organic cemented sand have formed. Bassendean sand, due to its age and

composition, is leached of minerals and nutrients and has an acidic pH ranging from 5.4 to 6.0

at depths of 0-90 cm (Profile no.: SCP11; McArthur et al. 1991).

3.3 Vegetation

The dominating feature of southwestern Australian (SWA) flora, that Banksia woodland

focus ecosystem of in this study is part of, is a high gamma diversity (Hopper 1992), in other

words, there is a high turnover of species across the landscape. Many field samples support this

view. Moreover, surveys often struggle to find all species with species richness across pre-

cleared areas increasing with time spent on exploring and surveying (DEC Brundrett pers.

communication). Only a handful of southwestern species has been recorded throughout the

entire SWA region, and they are examples of plants with a well-developed mode of dispersal,

for instance Millotia tenuifolia, orchids: Spiculaea ciliata, Caladenia flava, Leporella fimbriata,

mistletoes: Amyema miquellii, Nuytsia floribunda. The most common species found out

throughout Banksia woodlands on Swan Coastal Plain belong to excessive seeders i.e.,

Gompholobium tomentosum, Hibbertia subvaginata, H. hypericoides Mesomaleaena

pseudostygia and Xanthorrhoea preissi, the endemic and rare understorey species have not been

46

fully assessed yet (Dodd & Griffin 1989).

Banksia woodland is a Mediterranean-type ecosystem (MTE) where drought and fire

disturbances are the main drivers of plant community structure and composition (Fisher et al.

2009a; Enright et al. 2011; Holz et al. 2015). Typical vegetation of MTEs is characterized by a

number of drought and fire-adaptive functional traits e.g., seed dormancy, serotiny, resprouting

and fire-related germination cues that increase species persistence in fire-prone environments.

Accumulation of a dormant seed bank in MTE plant communities is very common (Enright et

al. 2007) and is important from the standpoint of restoration projects that utilize the topsoil seed

bank. Approximately 60-80% of the total seeds produced by plants in the Banksia woodland

ecosystem become incorporated as dormant propagules in the soil (Rokich & Dixon 2007).

Thus, the topsoil seed bank is a potentially effective resource to restore degraded areas.

Banksia woodland overstorey typically consists of a few dominant low canopy Banksia

species and a rich understorey - up to 100 species per 100 m-² (Keighery 2011; Stevens et al.

2016). The main structural features of the Banksia woodland community are:

- Distinctive upper sclerophyllous layer of low trees, more than 2 m tall, typically

dominated by one or more of the Banksia species i.e., Banksia attenuata, B. menziesi, B.

prionotes or B.ilicifolia.

- Highly species-rich understorey that consists of shrubs, herbaceous ground layer of

rushes, sedges and perennial and ephemeral forbs, or grasses. The development of a ground

layer depends greatly on light permeability of the upper layer as well as on disturbance history.

Many understorey species are endemic and may not occur across the entire range of the Banksia

woodland community. Presently, 1130 plant species were recorded for the Swan Coastal Plain

(Stevens et al. 2016).

- Emergent tree layer that may include tall Eucalyptus or Allocasuarina species that may

sometimes be present above the Banksia canopy. For example. Eucalyptus todtiana and

Allocasuarina fraseriana.

Fourteen floristic community types have been delineated and grouped within four

categories following floristic analysis of Swan Coastal Plan flora (Gibson et al. 1994). The

community that existed at the study sites prior to them being cleared for agriculture was of type

23a that is Banksia attenuata – B. menziesii-dominated woodland (Gibson et al. 1994), with the

most common understorey shrubs belonging to families Fabaceae, Ericaceae and, Myrtaceae

e.g., Gompholobium tomentosum, Bossiaea eriocarpa, Leucopogon conostephioides, Scholtzia

involucrata and herbs, sedges and rushes belonging to families of Araliaceae, Anarthriacaceae,

Iridaceae and Goodeniaceae e.g., Trachymene pilosa, Lyginia barbata, Patersonia occidentalis

and Dampiera linearis.

Monitoring of endemic species like Banksia laricina, Eremaea purpurea, Caladenia

speciosa is essential to understand their ecology and potential to survive (Hopper & Burbidge

1989). Some species, i.e., Conostylis lantens from Canning Vale whose main area of occurrence

47

has been cleared are present only in remnant patches of Banksia woodland. To this date,

Banksia woodland includes 16 nationally listed threatened plant species (Environment 2017).

3.3.1 Origin of Banksia woodland of Western Australia

While the landscape of Western Australia is widely recognized as ancient, the

Mediterranean-type climate in Western Australia developed quite recently beginning about 3

million years ago (Holz et al. 2015) as the Australian continent moved north on its journey

separating from Antarctica. While the Mediterranean-type climate regime may be young,

evidence of Proteaceae-dominated heathlands in central Australia of late Cretaceous age

(Carpenter et al. 2015) suggests that open heathland vegetation in Australia predates

Mediterranean climates by many millions of years. Fossil Banksia leaves from Western

Australia dated as Eocene (56 to 33.9 m.y.a) in age also show that one of the current dominant

genera of heathy woodlands of the Swan Coastal Plain was present well before Mediterranean–

type climates developed (Carpenter et al.). Heathland taxa were also present with what are

generally thought of as closed forest taxa about 2.5 million years ago where the vegetation may

have resembled that in present day New Caledonia where heath taxa co-occur with emergent

tree taxa such as Agathis, Araucaria and Anacolosa (Dodson & Macphail 2004). In the

Quaternary (2.5 m.y.a.) rainfall decreased considerably from earlier times and led to the survival

of only a relatively small number of rainforest species (Whitelock, Brereton & Webb 1970) but

possibly contributed to diversification of southwestern flora (Hopper 1979).

Diversification of the flora in Southwestern Australia (SWA) has often been attributed

to the age of the landscape in concert with low soil nutrients and xeric conditions preventing

competitive exclusion amongst taxa plants must endure a broad range of environmental

conditions in order to survive (Lamont 1984; Groves & Hobbs 1992) and allowed for

widespread plant speciation with most diverse plant communities occurring presently in a south-

western corner of the Australian Mediterranean climatic zone (Hopper & Gioia 2004).

Speciation occurred particularly within genera of Acacia and Eucalyptus (Cowling et al.

1996) and together with the families Asteraceae, Ericaceae, Proteaceae, Rhamnaceae and

Rutaceae dominate the southwestern floristic landscape (Keeley et al. 2011b). Contrary to

Australian rainforest plant diversity that is characterized by a high number of families,

speciation of SWA flora occurred within a few genera (Hopper 1992). This species richness was

recognised in SWA by early European explorers (Hooker 1860). 3600 plant species were

recorded in 1979 (Hopper 1979), 5469 in 2000 (Myers et al. 2000) and presently, on average

50-100 new species of plants are discovered each year in Western Australia (Thiele 2012). As

we are stepping into the new human-dominated geological epoch of Homogenocene (Crutzen

2002) the future of the many ecosystems including SWA biodiversity hotspot depends on

human actions (Myers et al. 2000).

48

3.3.2 Distribution and threats for Banksia woodlands

Banksia woodland vegetation found in southwestern Australia (SWA) is composed of a

number of community types adapted to summer drought and low nutrients soils typical of MTEs

evolved on a weathered substrate (Cowling et al. 1996; Hopper 2009). Banksia woodland

community typically occurs on well-drained, low nutrient soils – in this study on deep

Bassendean sandplain landforms. This study is situated on Swan Coastal Plain, in Western

Australia, where Banksia Woodlands form dominant vegetation type (Cummings 2000). The

Swan Coastal Plain delineates also a separate bioregion that covers coastal dunes ca 200 km

north and south of Perth, capital of Western Australia (Figure 3-1 ,see also section on Geology).

Banksia woodlands are increasingly fragmented and disappearing due to the rapid

expansion of metropolitan Perth. Ongoing and future expansion of the metropolitan area and its

satellite towns will lead to inevitable increases in degradative processes imposed on the natural

areas. The areas south and north of the Swan River are occupied by MTEs that comprise mostly

Banksia woodlands of which seventy percent have been cleared. The remaining pockets of

native vegetation are exposed to threats resulting from landscape fragmentation processes e.g.,

weed invasion, Phytophthora invasion, nutrient enrichment, changes in fire regime,

hydrological change, genetic diversity loss and further land clearing. Currently, Banksia

woodland is listed as potentially threatened ecological community (DEE 2016) and restoration

works are very likely to slow down the ongoing degradation process (Stevens et al. 2016).

49

Figure 3-1 Distribution of Banksia woodlands (green shade) on Swan Coastal Plain, Western Australia (light

brown shade). Credit The Northern Agricultural Catchments Council (Environment 2017).

50

3.4 Study sites

3.4.1 Topsoil donor sites

Offset fund from Jandakot Airport Holdings Pty Ltd (JAH) was established to offset the

impacts of clearing 167 hectares of Banksia woodland at Jandakot Airport, Perth, Western

Australia. Following the clearing in 2012 the topsoil was collected and transferred to restoration

study sites examined in this study. Topsoil donor sites, located at the Jandakot Airport, were

within a 40 km north of topsoil recipient study sites (Figure 3-2).

Figure 3-2 Location of topsoil donor site at Jandakot (circle) and two topsoil recipient sites at Forrestdale Lake

(upper triangle) and Anketell Road (bottom triangle). Topsoil was collected and transferred in April-May 2012.

The topsoil donor sites were relatively undisturbed an overall native species richness of

80 as recorded by Department of Parks and Wildlife (DPaW) prior topsoil collection (Brundrett

et al. 2017). The Banksia woodland that was cleared at the Jandakot Airport was long unburnt.

These areas were also grazed by the large macropods which may affected the species richness.

The physical and chemical properties of topsoil samples collected from topsoil donor (intact)

were examined in Chapter 1 (see also Figure 5-8 ).

3.4.2 Topsoil recipient sites

Department of Parks and Wildlife (DPaW) agreed to the clearing of 42 ha of remnant

Banksia vegetation at Jandakot Airport for the development of future airport infrastructure

under the condition that the developer, - Jandakot Airport Holding transferred the topsoil from

the cleared land on to six designated restoration study sites approximately 20 km away (Figure

51

3-3, Figure 3-4, Figure 3-5).

Figure 3-3. Map of SW Australia showing the location of the study sites - produced using “ggmap” package

(Keeley, Lubin & Fotheringham 2003).

Six recipient sites for the transferred topsoil sourced from Jandakot Airport precinct,

three at Forrestdale Lake (Figure 3-4) and three at Anketell Road (Figure 3-5), were selected by

DPaW based on a set of selection criteria that encapsulate the main restoration and offset goals

(Table 3-1). Both recipient sites bordered remnant native vegetation but had been degraded by

approximately 80 year-long agricultural use immediately before the restoration, predominantly

as pastures. Prior to spreading the topsoil from the donor site, weed-laden top layer (ca. 5-10

cm) of soil was stripped from the recipient sites and stockpiled off-site. Stripping the top layer

of ex-pasture resident soil reduces considerably the negative effect of weedy seed bank of

undesirable species and hinders the potential colonization from the seed rain by reducing soil

fertility (Jaunatre, Buisson & Dutoit 2014). Subsequently, the surface of the onsite soil was

subject to furrowing to further impede the growth of weeds.

Topsoil donor sites were used for agricultural activities that span a period of about 80

years prior topsoil transfer. These sites were used for low-intensity pastoral agriculture, hence

52

were very unlikely to be highly fertilised. The examination of soil pits and trenching undertaken

prior fence installations not show much variation in the shallow subsoil (pers. comm. Mark

Brundrett). Soil samples were collected to examine the effect of transfer process on topsoil

properties. Figure 5-8 displays physical and chemical properties of soil samples collected from

topsoil donor (intact) and topsoil recipient (transfer) sites.

53

3.4.2.1 Forrestdale Lake study sites

There were three study sites at Forrestdale Lake (see Figure 3-4). The Forrestdale Lake sites were situated within Forrestdale Lake Nature Reserve on

Bassendean dunes – the same dunal system as topsoil source sites. These were:

1) Forrestdale South West (ForSW) - ca 1ha, surrounded on its eastern verge by native vegetation and with private property on the western side.

2) Forrestdale North West (ForNW) - ca 1.5 ha, situated 500 m north of For SW, in close proximity to Forrestdale Lake with a transitional type of vegetation,

from Banksia woodland to Melaleuca and Kunzea wetland, occupying its eastern border and agricultural land on remaining sides.

3) Forrestdale South East (ForSE) - ca 3.5 ha, located ca. 500 m east of For SW, dotted with remains of old agricultural buildings, with the northern side

delineated by a limestone track and remainder of the site perimeter occupied by native vegetation dominated by Eucalyptus todtiana.

54

Figure 3-4. Satellite image of three study sites at Forrestdale Lake: ForSW, ForNW, and ForSE. Two site-level treatments are shown: shallow topsoil depth [light blue], deep topsoil depth

[purple] and exclosure line [yellow]. The study block (clusters) are drawn as[dark blue squares. Insert depicts the location of the study sites within the Swan Coastal Plain (Google Earth

2014b). Forrestdale Lake topsoil recipient sites of the total size of 6 ha, are situated 25 km SE of Perth. The marked planting and direct seeding were undertaken simultaneously in a separate

project run by Western Australia Department of Parks and Wildlife . Credit: Anna Wisolith.

55

3.4.2.2 Anketell Road study sites

Three study sites were located at Anketell Road (see Figure 3-5) and were also situated on Bassendean dunal system. These were:

1) Anketell West study site (AnkW) - ca 2 ha, was located at the western end of Anketell Road. AnkW site bordered with a Melaleuca stand in the south-

eastern corner and Banksia vegetation on its eastern and western sides.

2) Anketell Middle site (AnkM) - ca 5 ha, was located between the far western and far eastern topsoil recipient sites, delineated by Anketell Road at its

northern side. AnkM site was surrounded by vegetation on its southern end, dominated by Allocasuarina sp. and Kunzea sp.

3) Anketell East (AnkE) - ca 5 ha, was located at the far eastern end of eastern topsoil recipient site, at the corner of Anketell and Thomas Road. The site was

surrounded by native vegetation consisted mostly of Allocasuarina sp. and Kunzea sp. on is southern fringe.

56

Figure 3-5. Satellite image of three study sites at Anketell Road: AnkW, AnkM, and AnkE. Two site-level treatments are shown: shallow topsoil depth [light blue], deep topsoil depth [purple]

and fence line [yellow]. The study blocks (clusters) are drawn as dark blue squares. Insert depicts the location of the study sites within the Swan Coastal Plain (Google Earth 2014a). The

marked planting and direct seeding were undertaken simultaneously in a separate project run by Western Australia Department of Parks and Wildlife . Credit: Anna Wisolith.

58

3.4.3 Topsoil seed bank collection and three study

site-scale treatments

Soil stripping at the Jandakot donor site commenced in mid-April 2012 following

vegetation clearing in autumn 2012 (March-April). The top 5-10 cm of soil, where most of the

propagules are stored (Rokich et al. 2000), was harvested using heavy front-end loader with

customised plates adhered to its front bucket to strip down to ~7 cm depth and usually less than

10 cm, where practically possible (DEC 2012; Brundrett, Collins & Clark 2017).

Figure 3-6 Image of the front-end loader in the process of land-clearing at the topsoil donor site in Jandakot,

Western Australia, 16th

June 2012.

59

The top 5-10 cm of soil, where most of the propagules are stored (Rokich et al. 2000),

was harvested using heavy front-end loader with customised plates adhered to its front bucket

(Figure 3-7) to strip away the top ~7 cm of the topsoil (DEC 2012).

Topsoil that was harvested from cleared Banksia woodland near Jandakot Airport was

piled for a brief period of time and subsequently loaded on heavy transport vehicles. The

transfer distances between topsoil donor and topsoil recipient sites were no longer than 25 km.

Following the transfer the topsoil was unloaded onto mounds at the restoration sites and spread

using heavy machinery according to the experimental design (at two depths 5 and 10 cm)

across all six restoration sites.

Figure 3-7 Close-up image of the front-end loader with customized plate adhered to its front bucket. Jandakot,

Western Australia, April 2012. Credit: Joe Fontaine.

Following the topsoil stripping combinations of all three topsoil treatments, i.e.,

alternating topsoil volume, topsoil ripping and fencing were applied evenly across entire

restoration study sites. The collected topsoil was transported to six recipient sites - three at

Forrestdale Lake (Figure 3-4) and three at Anketell Road (Figure 3-5) that covered an area of

approximately 18 ha (DEC 2012). Allocation of the topsoil was according to the initial

experimental design described below. The fine-scale plot-level treatments were superimposed

across the site-level treatments to examine their potential interactive effect and are described in

the respective data chapters.

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3.4.3.1 Dispersal filter manipulation treatment (topsoil

volume)

Half of each restoration site was capped with a 5 cm deep layer of topsoil (shallow

depth treatment), and the remaining area was capped with a 10 cm deep layer of topsoil (deep

depth treatment) using heavy machinery (grader).

Figure 3-8, Image of the front-end loader in the process of topsoil spreading at the recipient site in Anketell,

Western Australia, 16th

June 2012.

3.4.3.2 Abiotic filter manipulation treatment (topsoil ripping)

To ameliorate the compacted soil conditions a heavy vehicle equipped with a single or

triple winged tine was used to rip the top 30 cm of topsoil at all restoration sites – the ripped

topsoil comprised the newly transferred topsoil as well as the underlying ex-farm subsoil

(Figure 3-9). The rip line spacing was set at 0.5 m. The ripping treatment was applied to both

shallow and deep topsoil depth treatments, treating half of the area of all six restoration sites.

The soil ripping treatment loosened the soil substrate and produced deep V-shape furrows. The

ripping treatment was carried out in mid-June 2012 over the period of two weeks, 5-7 weeks

after the topsoil transfer.

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Figure 3-9 Topsoil ripping treatment with use of tractor and single winged tine, June 2012.

3.4.3.3 Biotic filter manipulation treatment (topsoil fencing)

In this study, plots were fenced to protect germinants from herbivores, mainly rabbits

(Oryctolagus cuniculus) and western grey kangaroos (Macropus fuliginosus). Eight study

clusters were fenced at each site (Figure 3-10, Figure 4-1). Four unfenced clusters per site were

used as controls to examine the interactive effects of herbivore grazing and other site-level

treatments.

62

Figure 3-10 Topsoil fencing. The additional upper line was mounted to prevent large macropods from entering

the restoration study sites, July 2012.

63

Chapter 4 Germination: Filter-based

restoration ecology: utilization

of translocated topsoil seed

bank to overcome abiotic,

biotic and dispersal barriers

4.1 Abstract

Ecological theory suggests that environmental filters influence the outcome of plant

community assembly. This study aims at advancing our understanding on how to manipulate

onsite filters to increase emergence of native plant communities on degraded land. In this study,

a translocated topsoil seed bank was used to manipulate three site-scale environmental filters:

dispersal (seed bank), abiotic (soil compaction), biotic (grazing). Additional plot-scale

experiments were conducted to further investigate a role of onsite filters and improve our

understanding of how to successfully re-establish native plant communities.

This study was located in Banksia woodland - a Mediterranean-type ecosystem in

Western Australia. Topsoil from this vegetation type contains a large native soil seed bank.

Here, topsoil from a newly cleared site (for development purposes) was stripped, transferred

and applied to six recipient sites within two months of vegetation clearing. The recipient sites

had been in agricultural use for about 80 years prior to the restoration effort with the

translocated topsoil seed bank.

A fully factorial combination of three filter manipulation treatments was applied across

six sites to identify successful restoration techniques. The dispersal filter was tested by altering

the volume of topsoil seed bank used. The abiotic filter manipulation was topsoil ripping. The

biotic filter was examined by installing herbivore exclosures. Additional plot-scale treatments

investigated the role of smoke and heat (dispersal), weed control (biotic) and reduced

evaporation (abiotic). Emergence of all vascular plant species was quantified for two growing

seasons after topsoil transfer (spring 2012 and spring 2013).

Overall, the most successful technique was the application of a high volume of

unripped topsoil, with resulting mean densities of native perennials of 17.4 ± 1.4 (SE) m-2

in the

first year. The emergence in the second year after topsoil transfer was abundant but on average

10% lower compared to year one (t=30.7, P< 0.01). The application of plot-scale treatments did

not have the expected stimulative effect on seedlings’ emergence densities except for the heat

application in year two where an 8% increase was recorded compared to the controls (t = 9.1,

64

P<0.01). The number of native species propagules detected in the transferred topsoil seed bank

approximated the number of germinants detected in the corresponding intact Mediterranean

ecosystem (14.6 ± 1.4 m-2

) The topsoil seed bank has a high potential for mitigating

environmental barriers on degraded sites.

4.2 Introduction

In the face of ongoing clearing of native vegetation and landscape degradation, it is

evident that conservation alone is not an adequate strategy to impede further biodiversity loss.

Thus ecological restoration is necessary (Robinson et al. 1992; Hobbs & Harris 2001; Hobbs

2007). An integration of ecological concepts with technical expertise is a major challenge to

restoration success (Hobbs & Harris 2001; Jackson & Hobbs 2009). In order to undertake

successful restoration of an ecosystem, understanding plant community assembly rules appear

to be one of the most relevant issues (Temperton & Hobbs 2004). Community assembly rules

attempt to formalise a rule set describing and enumerating how plant communities assemble

given a species pool and environmental conditions present in a given habitat (Keddy 1992).

Plant propagules arriving at a habitat are influenced by dispersal limitations as well as by the

abiotic and biotic factors, collectively termed environmental filters (Hulvey & Aigner 2014).

Filters are a set of mechanisms and conditions that sequentially remove species from the

species pool that should be able to establish (Fattorini & Halle 2004). Rebuilding a new

ecosystem can require modification of environmental filters to encourage native species

recruitment while suppressing the performance of undesirable, typically non-native, species

that may be present onsite. Thus, understanding how filtering processes impact the composition

and abundance of local plants are essential in guiding restoration actions (Dıaz et al. 2003).

Environmental filters are most often separated into three categories: abiotic, biotic and

dispersal limitation (Belyea & Lancaster 1999). Manipulation of abiotic filters, also termed

environmental constraints, may involve manipulation of soil compaction, substrate fertility,

landscape structure and microclimate conditions (Hobbs & Norton 2004). Soil compaction, due

to heavy machinery used during restoration activities, may be a critical filter that exacerbates

the difficulty seedling roots experience in penetrating deeper soil layers for successful

establishment (Bassett, Simcock & Mitchell 2005; Gilardelli et al. 2015). Installation of shade

can provide a more favorable microclimate for propagules to emerge (McLaren & McDonald

2003; Valladares et al. 2005). Biotic filters include species interactions, e.g., grazing and

competition. Herbivores may represent a major biotic filter preventing native seedling

establishment (Westoby, Walker & Noy-Meir 1989). Control of wildlife traffic, e.g., via

exclosures, may reduce trampling (Duncan & Holdaway 1989) and grazing pressure (Schultz,

65

Morgan & Lunt 2011) which can facilitate seedling emergence and establishment. Similarly,

competition from fast-growing exotic species may hinder the restoration efforts (Gaertner et al.

2009) and weed control might be imperative (Vitelli & Pitt 2006). Dispersal filters and

dispersal constraints can result from variable seed dormancy and longevity (Thompson 1987)

but also landscape context or site history (Belyea & Lancaster 1999). High dispersal limitation

tends to lead to poor recruitment and intervention relies mostly on assisted migration via seed

sowing and planting seedlings (Zobel et al. 2000; Öster et al. 2009). The technology of topsoil

transfer presents a potentially cost-effective way to overcome dispersal limitations when

undertaking ecological restoration (Tacey & Glossop 1980; Koch et al. 1996). Topsoil in many

ecosystems contains a large number of viable propagules that if stored and transferred

adequately (Rokich et al. 2000) can serve as a relatively large pool of native plant species at

restoration sites (Holmes 2001; Parrotta & Knowles 2001; Hall, Barton & Baskin 2010; Fowler

et al. 2015). Thus, increasing the volume of the applied topsoil seed bank can trade-off against

the limited dispersal of native propagules on a restoration site.

Recruitment from topsoil is widely utilized for rehabilitation of post-mining disturbed

sites by spreading the topsoil over the degraded substrate. If the topsoil is harvested at the time

of vegetation clearance, stored in dry conditions and re-spread as soon as possible, it has a high

potential to facilitate the restoration of degraded land (Roche, Koch & Dixon 1997; Holmes

2001; Parrotta & Knowles 2001; Hall, Barton & Baskin 2010). For instance, Banksia woodland

(Benigno, Dixon & Stevens 2012) as well as jarrah forest in southwestern Australia (Koch

2007b) - two Mediterranean-type ecosystems were successfully re-established by re-applying

the topsoil once mining operations ceased with relatively lower loss of native plant diversity,

compared to traditional techniques of planting and seed broadcast (Ward, Koch & Ainsworth

1996; Fowler et al. 2015). Topsoil is most useful when collected during the dry summer and

autumn months (Rokich et al. 2000) and relocated within the shortest time possible to the site

to be rehabilitated (Koch et al. 1996).

Transfer of topsoil from intact to degraded areas has proven to be an effective approach

in restoring forest, woodland and heathland vegetation due to the in situ accumulation of

dormant propagules in these types of ecosystems (Enright et al. 2007; Hopfensperger 2007).

Long term dormancy of soil-stored propagules is often one of the plant strategies to survive

frequent fire events (Baker et al. 2005). Propagules of many species in fire-prone ecosystems

are hard-coated and equipped with a number of fire-related physiological cues that enable

timely germination following fire disturbance (seed dormancy broken by heat or the chemical

components of smoke; Wills & Read 2002; Flematti et al. 2004). After fire, native plant species

tend to have robust recruitment from the soil seed bank (Pausas & Keeley 2014). Additionally,

topsoil may also contain underground vegetative plant parts: bulbs, rhizomes, lignotubers and

beneficial microorganisms that may increase native perennial plant re-establishment (Jasper

66

2007; Craig & Buckley 2013).

Recognition of filters that inhibit the transition from degraded land into a reconstructed

near-natural stable state is one of the fundamental questions in restoration ecology (Prober,

Thiele & Lunt 2002; Hobbs & Norton 2004). Based on these findings it is proposed to broaden

the utilization of the topsoil-stored seed bank and investigate its restoration potential to

manipulate environmental barriers on degraded agricultural land. In order to examine the

potential role of the native seed bank contained within the transferred topsoil, the experiment

was designed to utilize the topsoil in a way that manipulates the environmental barriers present

on a degraded restoration site. The overall goal was to maximize the density and diversity of

native plant species recruitment. To optimize the recruitment of native plants this study focused

on evaluating three major environmental filters (abiotic, biotic, and dispersal). The onsite

environmental filters were investigated by manipulating soil compaction and microclimate

(abiotic), grazing pressure, weed invasion (biotic), the volume of seed-containing topsoil and

smoke-related cues (dispersal). The outcome of this study will further our understanding of

ecological theory as well as contribute to developing new restoration techniques.

The three environmental filters manipulated at the site scale were:

1. The dispersal filter by altering the volume of topsoil applied, thus

varying the amount of seeds that are widely under-dispersed in

Southwest Australia (Standish et al. 2007; Hopper 2009).

2. The biotic filter by the installation of the herbivore exclosures across

the restoration sites in order to minimize grazing pressure (Neave &

Tanton 1989).

3. The abiotic filter by ripping the compacted substrate in order to

disrupt the compacted original soil surface to improve root penetration

and enhance the soil properties (Kew, Mengler & Gilkes 2007).

The propagules stored in transferred topsoil may require an additional set of treatments

that might invigorate the native seedlings emergence. Hence, three other environmental filters

were experimentally manipulated at the fine plot-scale:

1. Fire-related cues (dispersal) of smoke and heat are widely recognized as the cues

that break seed dormancy of many species in MTEs (Dixon, Roche & Pate 1995;

Roche, Koch & Dixon 1997; Ruthrof et al. 2016).

2. Herbicide application (biotic) might protect the late germinating native seed bank

by minimizing the negative impact of competition by non-native and fast emerging

annuals (Gordon, Menke & Rice 1989; Auken & Bush 1990; Melgoza, Nowak &

Tausch 1990; Hobbs & Atkins 1991; Welker, Gordon & Rice 1991; Bakker &

Wilson 2001; Standish, Cramer & Hobbs 2008; Fisher et al. 2009a; Standish &

Hobbs 2010).

67

3. Plastic cover (abiotic) reduces potential evaporation and is closely correlated with

plant-soil-water relations that can improve seedlings emergence (Rey Benayas

1998). The reduced evaporation may also provide conditions to promote gaseous

germination stimulants, e.g., ethylene (Froend et al. 2013).

4.3 Methods

4.3.1 Plot-level treatments

Plot-level treatments were fine-scale treatments carried out on 2 m × 2 m plots

superimposed across the combination of site-level treatments to examine their potential

interactive effect on native seedling emergence success. Five fine-scale treatments were applied

immediately after the three site-level treatments were established [Table 4-1). The plot-level

treatments were carried out only within the fenced area to minimize the risk of damage to the

installations from wildlife and human traffic.

4.3.1.1 Two Smoke-related Treatments

Two smoke-related treatments were tested in this study. In the first smoke experiment,

an aqueous extract of wood smoke was used and applied to 2 m × 2 m treatment plots across a

combination of all site-level treatments within the fenced area [Table 4-1). In the second smoke

experiment, the plots were firstly treated with smoke and then covered with the plastic sheet for

a period of four days. The plastic cover was applied to detect possible effects of the reduction

in soil gases evaporation as well as to prevent the dilution effect of natural rainfall in the first

few days after treatment.

4.3.1.2 Plastic Cover Treatment

The treatment plots were also covered with the plastic sheet only to account for any

cover effect on seedling emergence. The expected effect of plastic cover on seedling emergence

was hypothesized to be associated with a reduction in soil respiration and retaining soil

moisture.

4.3.1.3 Heat Treatment

Due to a high risk of uncontrolled wildfire, no burning treatments were carried out in

this study. Instead, 2 m × 2.4 m plastic covers were used for three consecutive cloudless days

on 19-21 February 2013 when the air temperature was ca. 38° C. The covers were placed onto

the deep and unripped topsoil treatments across all six sites in the second year since topsoil

68

treatment. The top five cm of the soil was removed in order to target seeds located five cm

below the surface and presumably still alive and dormant. Plastic covers were placed directly

onto the ground to generate a heat pulse that went through the lower part of the topsoil profile.

Temperature loggers (iButton) were placed beneath the plastic cover to monitor the magnitude

of the soil heating.

4.3.1.4 Chemical Weed Control Treatment

In this study, two herbicides in combination were tested to investigate how recruitment

levels and composition of the native plant species from the transferred topsoil seed bank

respond to chemical weed control treatment (Table 4-1). Chemical weed control was carried

out in the combination of all site-level treatments within the fenced area during the winter

growing season of 2012 – 3 months after the topsoil transfer.

69

Table 4-1: Detailed description of the treatments applied in the restoration study at Forrestdale Lake and Anketell site, Western Australia.

Filter Scale Treatment Detailed Description Replicates/sites

Abiotic Site Rip

Carried out from mid to the end of June 2012. A heavy vehicle

pulling a winged tine was used to rip the top 30 cm of the transferred

soil/subsoil. The rip line spacing was set at 0.5m. Ripping occurred

across both deep and shallow soil depth treatments, treating half of the

area of all sites.

192/6

Abiotic Plot Plastic only

Sheets of 2.0 m × 2.4 m black plastic were laid down on top of

transferred topsoil for five days to test for its independent effect on

seedlings emergence. Plastic cover was applied as a control for smoke

and plastic treatment.

48/6

Biotic Site Fence

Rabbit proof fencing was installed across all locations

encompassing 95% of the restoration sites. It extended 90 cm above

ground and 30 cm below ground.

192/6

Biotic Plot Herbicide

The amount of herbicide used depended on the scale of

infestation Chemical weed control was applied across all sites using: 1.

Glyphosate with 360g/L of active constituent, “Banish 360”. All

broadleaf weeds were spot-sprayed with an herbicide concentration at

the recommended level = 10ml/L that translates into 40ml of Gl per 4L

of water. 2. Grass-specific Fusilade, with 128g/L Fluazifop-P and

156g/L hydrocarbon solvent, was evenly sprayed across the entire

surface of 2m x 2m plots. The treatments plots were sprayed at half of

the recommended rate = 1ml/1L.

48/6

70

Filter Scale Treatment Detailed Description Replicates/sites

Dispersal Site Shallow

Topsoil

The topsoil transferred from cleared Banksia woodland had

been evenly spread at a depth of 5 cm; ~3 ha at Forrestdale and ~6ha at

Anketell site

192/6

Dispersal Site Deep Topsoil

The topsoil transferred from cleared Banksia woodland has been

evenly spread at a depth of 10 cm;~3 ha at Forrestdale and ~6 ha at

Anketell site

192/6

Dispersal Plot Heat

The 2 m × 2 m black plastic covers were laid down for three

consecutive days of 19-21 February 2013 with air temperature reaching

38oC straight onto the topsoil. “i-Button” temperature loggers were in

place to record the heat range across soil profile.

24/6

Dispersal Plot Smoke only

Smoke water was applied to treatment plots. Watering cans

were used to deliver a mix of smoke water evenly at a 1:10 ratio –

“Regen 2000 Smokemaster”, manufactured in Australia by GRAYSON

AUSTRALIA, Bayswater, Victoria.

48/6

Dispersal Plot Smoke +

Plastic

Smoke and Plastic Cover. Smoke water was applied in June

2012 onto the plots (as noted above). Subsequently, plots were covered

with 2.0 m × 2.4 m sheets of plastic for 5 days

48/6

71

4.3.2 Experimental design

Working with industry and DPaW, a fully factorial experimental design was created

across the six sites to permit investigation of the potential interactive effect of site and plot-

level treatments on survival of native plants germinating from the topsoil seed bank.

Table 4-2: Descriptions of the site-scale and plot-scale filter-manipulation treatments. For a detailed

description of the treatments see Table 4-4.

Filter Treatment Scale of Application

Abiotic Rip Site

Abiotic Plastic cover Plot

Biotic Fence Site

Biotic Herbicide Plot

Dispersal Topsoil depth Site

Dispersal Smoke Plot

Dispersal Smoke + plastic cover Plot

Dispersal Heat Plot

Six study sites consisted of twelve study clusters (13 x 13 m). Each cluster consisted

mostly of eight to twelve 2 m × 2 m plots spaced 1m apart (0.5 m in a few cases where fencing

constrained space). Site-scale treatment study clusters were allocated across the combination of

three site-level treatments: deep and shallow topsoil, ripped and unripped topsoil, fenced and

unfenced. Plot-scale treatments (germination enhancement via smoke water, germination

enhancement via heat, reduced competition via weed herbicide, stress reduction via increased

shading) were imposed on 2 m × 2 m plots. Plot-scale treatments accommodated two replicates

of each plot-level treatment i.e., three smoke-related, herbicide, heat application and shade

installation, superimposed on a combination of all site-level treatments within the fenced area,

i.e., deep and shallow topsoil, ripped and unripped topsoil. Plot-scale treatment study clusters

were situated randomly across all site-level treatments and enclosed within the fenced area. It

was not possible to impose plot-level treatments outside the fenced area due to lack of space

and high probability of damage from wildlife and human entry. The total number of 2 m × 2 m

survey plots was 856.

72

Figure 4-1. Illustration of study design. The effects of the site-scale treatments were investigated within eight

clusters per site, also denominated as controls [C]. The effects of plot-scale treatments that were

superimposed on site-scale treatments were studied within four clusters [T]. The white squares indicate the

combinations of three main site-scale treatments: topsoil volume, ripping, and fencing. The coloured squares

indicate four additional plot-scale treatments, subsequently applied only within the fenced area: two smoke-

related [red], herbicide [green], heat application [yellow], and shade [blue]. Each cluster comprised of 8 to 12

plots (sampling units). See detailed description of treatments in Table 4-1 and Table 4-2.

4.3.2.1 Aim

The resilience of MTE plant communities to disturbance depends greatly on soil stored

propagules (Sahib, Rhazi & Grillas 2011). Thus, the main goal of this study was to assess the

efficacy of a range of the novel treatment techniques to manipulate local environmental filters

i.e., abiotic, biotic and limited dispersal, using harvested topsoil to facilitate the re-

establishment of natural vegetation in the degraded ex-farmland sites. The study builds on

knowledge acquired from the previous soil seed bank studies that indicated the potential to

improve the restoration outcome of the transferred topsoil (TERG 2012; Fowler et al. 2015).

In order to advance Banksia woodland restoration projects that utilize topsoil seed bank

in returning the native vegetation, treatments were applied as follows: transferred topsoil depth

alteration, ripping, fencing, application of smoke, heat, and herbicide. The study sites are

situated adjacent to remnant Banksia woodland at Forrestdale Lake Nature Reserve and

Jandakot Regional Park.

Firstly, the restoration sites were subjected to the combination of three site-level

treatments: topsoil depth alteration, ripping and fencing. Subsequently, the five plot-level

treatments were superimposed onto the combination of site-level treatments. The study

investigates the restoration outcome by looking at the effect of the combination of all topsoil

treatment techniques. The effect of the topsoil treatments was examined by measuring

73

seedlings densities and diversity. The vegetation surveys were carried out in two sequential

emergence seasons (spring 2012 and 2013).

4.3.2.2 Data collection (vegetation surveys)

Field plots were established to capture the emergence of all plant species in the springs

of 2012 (first growing season after topsoil placement) and 2013 ( the second growing season

after topsoil placement). Field plots were set up in early May through to late June 2012.

Surveys of emerging native seedlings were carried out in spring 2012 & 2013. The vegetation

surveys were conducted within all 2 m × 2 m plots situated within each of a total of twelve

(Figure 4-1) per restoration study sites (replicated 8-12 times per cluster). The spring 2012

survey was carried out for five consecutive weeks starting on 29 October 2012 and the spring

2013 survey for ten consecutive weeks starting on 17 October 2013. The density of the weed

species was recorded four times inside the 2 m × 2 m plot within 0.25 m × 0.25 m micro-plots

due to the high level of infestation. The micro-plot was placed in the centre of each 1 m × 1 m

quarter. The sampled densities were standardised to 1 m².

4.3.2.3 Data analysis

4.3.2.3.1 Site-scale treatments analysis – main model

To estimate the effect of three site-scale environmental filter manipulation treatments

on restoration success the densities of emerging plant cohorts were analysed. These were the

densities of emerging native annuals, native perennials and invasive plant species in the first

and second growing season since topsoil transfer. Site-scale manipulations of environmental

filters were treated as fixed effects. Site (n = 6) and cluster (n = 8 per site, 48 total) were

implemented as random effects.

Hierarchical general linear mixed-effect modeling was applied for data analysis to

accommodate the combination of fixed and random effects. Data were non-normally

distributed, which is typical for count data (Wickham & Francois 2015) and modeled with a

Poisson distribution on natural numbers recorded per survey plot (4 m-2

). Scatterplots and

histograms of model residuals were assessed visually to ensure the homogeneity of variance,

with no issues detected. The statistical computations were performed using R-software (Team

2014) including the “lme4” R-package (Bates et al. 2014). P-values were calculated using

Satterthwaite approximation to degrees of freedom (Schaalje, McBride & Fellingham 2002).

Mean densities displayed in the figures were computed on log-transformed data and back-

transformed in “fishmethods” R-package (Nelson 2014) and standardized to 1 m-2

.

74

4.3.2.3.2 Plot-scale treatments analysis – additional effects

To estimate a potential interactive effect of smoke and weed control on restoration

success five additional small plot-scale treatments were applied in combination with two of the

above site-scale filter manipulation treatments i.e., abiotic and dispersal, within the exclosures

only. The potential interactive effect of five plot-scale treatments and two site-scale treatments

were analysed as their effect on densities of emerging native perennials in the first and second

spring since topsoil transfer. Four plot-scale treatments, n= 12, i.e., herbicide, smoke only,

smoke+plastic and plastic were applied in the first year. The heat treatment was applied during

the summer preceding the second spring survey. Data were structured by two site-scale

treatments, i.e., rip and topsoil volume as fixed effects. Location of six study sites and location

of four study clusters on each site that comprised eight survey plots were incorporated as

random effects. The hierarchical general linear mixed-effect model was applied as above with

additional five small plot treatments as fixed factors and site and plot locations as random

effects.

4.3.2.3.3 Supplementary effects

The effect of site on emergence densities was tested in the corresponding main model

where the site was incorporated as an additional categorical factor (Table 4-7). The densities of

perennial woody plants germinating during the both spring seasons differed significantly

between the six study sites.

The main model type was also used to evaluate effects of three filter manipulation

treatments on emergence densities of native annuals in the first year after topsoil transfer (

Site effects

Table 4-7: Site effects on native perennial plant densities emerging in year one and two since topsoil transfer.

Filter [Topsoil Treatment] Term Estimate SE t P

(intercept) intercept 3.53 0.14 25.95 0.001

Dispersal [Volume] shallow -0.01 0.19 -0.04 0.97

Abiotic [Rip] ripped -0.26 0.19 -1.39 0.17

Biotic [Fence] open -0.10 0.23 -0.45 0.65

Year two -0.37 0.01 -31.06 0.001

Site AnkM -0.16 0.02 -6.50 0.001

Site AnkW 0.40 0.02 18.26 0.001

75


Site ForNW 0.53 0.02 25.40 0.001

Site ForSE 0.16 0.02 7.27 0.001

Site ForSW 0.05 0.02 2.14 0.03

Volume:Rip shallow:ripped -0.50 0.27 -1.84 0.07

Volume:Fence shallow:open -0.06 0.33 -0.19 0.85

Rip:Fence ripped:open 0.10 0.33 0.31 0.75

4.3.3 Native annuals in spring 2012

Table 4-8) and in the second year (Table 4-9). Similarly, the effects of treatments on

emergence of invasive plants in the first and the second year after topsoil transfer were

computed (Table 4-10, Table 4-11). Site (n=6) and plot locations (n=12) were parameterized as

random effects.

The total number of native perennial species that was detected in the first year was 114

(Table 4-14) and was higher compared to the number of species in the second year (96, Table

4-15). The seedling densities were strongly correlated with species richness and diversity

indices in spring 2012 (Figure 6-8) and in spring 2013 (Figure 6-9).

4.4 Results

4.4.1 Abiotic filter

There was a significant difference (t = 4.0, P < 0.001, Table 4-3) between the mean

density of native perennial plants on ripped soils (abiotic filter manipulation) in the first year

after transfer 5.0 ±0.3 m-2

(SE) versus unmanipulated controls with a mean of 12.5 ±0.8 m-2

. In

the second year, the effect of ripping was virtually nonexistent; mean germination rate for all

native perennials was 5.8 ±0.3 m-2

in ripped compared with 5.9 ±0.4 m-2

in unripped (t = 0.8, P

= 0.4, Table 4-4, Figure 4-2).

76

Table 4-3: Effect of site-scale filter manipulation treatments on native perennial plant densities emerging in the

first year [spring 2012] after topsoil transfer.

Filter [Topsoil Treatment] Term ESTIMATE SE t P

(Intercept) intercept 3.9 0.2 20.1 <0.001

Abiotic [Rip] ripped -1.0 0.2 -4.0 <0.001



Biotic: Abiotic ripped:open 0.1 0.3 0.4 0.70

Biotic: Dispersal open:shallow 0.1 0.3 0.4 0.67

Abiotic: Dispersal ripped:shallow 0.0 0.3 0.0 0.98

Model: glmer (Density ~ rip+fence+Volume+rip*fence+fence*Volume+rip*Volume (1|site/plot), family = poisson(link="log"), data=spr12. native.perennials)

The mean densities in the first year since transfer differed significantly between species

with annual life histories but not in the second year (Table 4-8, Table 4-9). The native annuals

were significantly negatively impacted by the abiotic filter manipulation treatment with a mean

density of 6.4 ±0.6 m-2

as compared to unmanipulated control plots 17.6 ±0.9 m-2

(t = 6.9, P <

0.001) in the first year since the transfer. Regarding plant composition, the ripping treatment

negatively impacted the following low frequency perennial species (Table 4-14): Eremaea

pauciflora, Banksia attenuata, Stylidium brunonianum and Amphipogon turbinatus. In the

second year (Table 4-15), Thysanotus manglesianus and Philotheca spicata did not

emerge on ripped sites.

77

Figure 4-2. Mean native perennial and native annual densities (m-²±95%CI) emerging under filter manipulation treatments during the springs of year one and two since topsoil transfer.

Abiotic Filter Manipulation treatments: ripped and unripped, Biotic: fenced and open. Dispersal: deep and shallow topsoil transfer. The filled circles represent the means of native

annuals, and the filled triangles represent the mean density of native perennials. The x-axis depicts vegetation survey period: “one” – spring 2012 of the year I since topsoil transfer,

n= 207±16SD and “two” – spring 2013 of the year II, n=284±7SD. Data back-transformed.

78

4.4.2 Biotic filter

The introduction of the fence as a biotic filter manipulation treatment had no significant

effect on the density of native germinants (Figure 4-2). The mean densities of native perennial

plants in the first year, within fenced and unfenced plots, were 8.8 ±0.6 m-2 and 8.5 ±0.6 m-2

(t= 0.4, P = 0.7, Table 4-3). In the following 2013 spring, the native perennial plants emerged at

lower overall densities: 6.1 ±0.4 m-2 and 5.6 ±0.3 m-2 (t= 0.9, P = 0.37, Table 4-4),

respectively. The mean densities of the native annuals in the first year within the fenced area

were higher than outside the fence 10.7 ±0.9 m-2 and 8.8 ±0.2 m-2 (t = 0.4, P = 0.7, Table 4-8).

In the second year, annuals emerged with slightly higher overall mean densities in fenced and

open: 16.3 ±1 m-2 and 16.1 ±1.3 m-2 (t= 0.1. P = 0.94, Table 4-9).

4.4.3 Dispersal filter

Manipulation of the dispersal limitation filter by increasing the depth of transferred

topsoil seed bank had a positive but not significant effect on the density of native perennials in

the first year after topsoil transfer (Figure 4-2). Mean densities of native perennial plants in the

first year after transfer were on average higher in plots where topsoil seed bank was allocated at

the higher volume, i.e., mean plant emergence density on deep topsoil was 10.4 ±0.6 m-2

as

compared with the shallow topsoil spread: 6.9 ±0.5 m-2

but this was not statistically significant

(t= 1.9, P = 0.06, Table 4-3). In the second year, in spring 2013, the mean densities of emerging

perennials did not differ appreciably between the deep and shallow topsoil treatments, i.e.,

native perennial emerged at the mean rate of 6.2 ± 0.3 m-2

and 5.4 ±0.3 m-2

, respectively (t =

0.5, P = 0.62, Table 4-4). In the second year since transfer the native annuals were relatively

less abundant on deep topsoil: 14.5 ±1.1 m-2

as compared with shallow 17.8 ±1.1 m-2

(t = 1.4, P

= 0.17, Table 4-9).

Compositionally, the deep spread of the topsoil increased the size of the native

perennial species pool in the first year after the transfer, i.e., the rare species e.g., Xanthosia

huegelii, Eremaea asterocarpa, Stylidium junceum, Lepidosperma squamatum, Lepidosperma

tenue were more likely to be detected on deep topsoil.

4.4.4 Interactions between site-scale filter

manipulation treatments

A multiplicative interaction between the abiotic, biotic and dispersal filter manipulation

treatments on emergence densities of the native perennial and native annual plant densities was

not prominent in spring 2012 nor in spring 2013 (control panel in Figure 4-3). For example,

manipulation of biotic filter (fence) did not have a significant interactive effect with any of the

79

two remaining two site-scale treatments, i.e., topsoil ripping (spring 2012: t = 0.4, P < 0.70,

spring 2013: t = 0.3, P < 0.73) and topsoil volume (spring 2012: t = 0.4, P < 0.67, spring 2013: t

= 0.9, P < 0.35), on emergence of perennial plants (Table 4-3, Table 4-4). The highest mean

density of native perennial plants in the restoration areas occurred where topsoil was applied at

the deep volume and not exposed to the ripping treatment, i.e., the mean emergence density of

native perennials in deep, unripped in the first year after topsoil transfer, was 15.9 ±0.2 m-2

and

in the second year 7.6 ±0.1 m-2

, respectively. The native annuals emerged at a mean density of

19.1 ±0.2 m-2

on deep and unripped topsoil in the first year and with mean density of 19.3 ±0.3

m-2

in the second year, respectively (Figure 4-3). There was no statistically significant

interactive effect of site-scale filter manipulation treatments on emergence densities of native

annual plants, nor in the first year after topsoil transfer (Table 4-8) nor in the second year

(Table 4-9).

Table 4-4: Effect of site-scale filter manipulation treatments on native perennial plant densities emerging in the

second year [spring 2013] after topsoil transfer.

Filter [Topsoil Treatment] Term ESTIMATE SE t P

(Intercept) intercept 3.0 0.2 12.5 <0.001

Abiotic [Rip] ripped 0.2 0.3 0.8 0.40



Biotic: Abiotic ripped:open 0.1 0.4 0.3 0.73

Biotic: Dispersal open:shallow 0.3 0.4 0.9 0.35

Abiotic: Dispersal ripped:shallow -0.4 0.3 -1.2 0.22

4.4.5 Additional plot-scale treatments effects

The effect of treatments in the 2 m × 2 m plots on the native plant emergence densities

was overall negative and relatively insignificant in the first year (Table 4-5).

Table 4-5: Interactive effect of site-scale filter manipulation treatments and small-scale plot treatments on

perennial plant densities emerging in the first year [spring 2012] after topsoil transfer.

Filter [Topsoil Treatment]

Treatment Scale

Term ESTIMATE SE t P

(Intercept)

intercept 4.1 0.2 24.4 <0.001

Abiotic [Rip] Site ripped -1.0 0.2 -5.8 <0.001

80


Treatment Scale


Dispersal [Volume] Site shallow -0.7 0.2 -3.8 <0.001

Biotic [herbicide] Plot herbicide 0.0 0.0 1.2 0.24

Abiotic [plastic] Plot plastic 0.0 0.0 -1.0 0.32

Dispersal [smoke] Plot smoke 0.0 0.0 0.0 1.00

Dispersal [smoke.plastic]

Plot smoke.plastic -0.1 0.0 -1.8 0.07

Abiotic:Dispersal [Rip:Volume]

Site ripped:shallow 0.2 0.3 0.9 0.38

† Model: glmer(Density ~ Volume*Rip + Small.Plot.Treatment + (1 | site/plot), family = poisson(link="log"), data=spr12.native.perennials

The highest mean native perennial plant density occurred under herbicide treatment -

18.3 ±1.1 m-2

on deep and unripped topsoil in the first year and only slightly higher compared

to control plots with mean densities of 17.4 ±1.37 m-2

(t= 1.2, P < 0.24, Table 4-5, Figure 4-3).

Similarly, smoke and plastic plot-treatment resulted in mean densities of perennials of 16.5

±0.7 m-2

(t=1.8, P < 0.07).

Figure 4-3. Mean ±95%CI of native perennial and native annual densities (m-²) emerging under plot-scale

treatments, n=12, superimposed on a combination of two site-scale filter manipulation treatments: dispersal

filter manipulation treatments: deep (D) and shallow (S) topsoil transfer and abiotic filter manipulation: ripped

(R) and unripped (U). The empty squares represent the means of native annuals, and the filled squares the

mean density of native perennials. All densities account for new emergents in the respective years . The right

panel depicts vegetation survey period: “I” – spring 2012 of year one since topsoil transfer and “II” – spring

2013 of year two. Data back-transformed.

In the second year after transfer the heat plot-scale treatment, carried out across the

81

deep and unripped (applied in the second year after topsoil transfer), produced the highest mean

densities of 12.1 ±0.5 m-² compared with controls of 7.6 ±0.1 m

-2 (t = 11.4, P < 0.001). Smoke-

related treatments showed a slight but significant effect on emergence densities in the second

year compared with control plots (t =3, P < 0.001, Table 4-6).

Table 4-6: Interactive effect of site-scale filter manipulation treatments and small-scale plot treatments on

perennial plant densities emerging in the second year [spring 2013] after topsoil transfer.

4.5 Discussion

Translocation of the topsoil seed bank from cleared Banksia woodland onto the

restoration site proved to be a vital tool in reintroducing a native plant community in the

degraded paddock. The highest density of native seedling emergence occurred from the deep

and unripped topsoil, with no effect of fencing, suggesting that “maximum volume, minimum

disturbance” technique is a valuable restoration means to overcome the environmental barriers

for native propagules on degraded sites. The more abundant emergence occurred in both

growing seasons after the topsoil transfer with year one being significantly higher. On average,

estimated field densities of native perennials emerging from the transferred deep and unripped

topsoil in year one (3.76 m-2

) were similar to other studies in intact Banksia woodland with a

mean of 2 seedlings m-2

(see spring control in: Roche, Dixon & Pate 1998). Other studies on


Treatment Scale


(Intercept) Intercept 3.2 0.3 12.0 <0.001

Abiotic [Rip] Site Ripped -0.1 0.2 -0.5 0.60

Dispersal [Volume] Site Shallow -0.6 0.2 -2.4 0.02

Dispersal [heat] Plot heat 0.5 0.0 11.4 <0.001

Biotic [herbicide] Plot herbicide 0.0 0.0 0.2 0.80

Abiotic [plastic] Plot plastic -0.1 0.0 -1.6 0.10

Dispersal [smoke] Plot smoke 0.1 0.0 3.0 <0.001


Plot smoke.plastic 0.1 0.0 3.1 <0.001

Abiotic:Dispersal [Rip:Volume]

Site ripped:shallow 0.0 0.3 0.0 0.98

† Model: glmer(Density ~ Volume*Rip + Small.Plot.Treatment + Year + (1 | site/plot), family = Poisson(link="log"), data=spr13.native.perennials

82

topsoil transfer imply that the potential density of native perennials could be higher as a mean

of 152 germinants m-2

was recorded in 5 cm deep soil samples in the post-transfer topsoil from

the same Jandakot site in a glasshouse study (Fowler et al. 2015). However in situ results will

always be less than in ex situ trials because conditions in the field cannot be controlled to the

same extent as can be done in the glasshouse.

4.5.1 Abiotic filter

Manipulation of the abiotic filter by means of topsoil ripping was designed to alleviate

the properties of compaction due to vehicle movement over freshly spread topsoil and the

difference in compaction between the spread soil and the underlying substrate. Ripping

facilitates soil aeration and enhances oxygen supply for root growth (Kirkham 2011). Soil

ripping is widely utilized in post-mining restoration sites (Kew, Mengler & Gilkes 2007; Koch

2007a). Other studies such as those from gold mine (Comino, Miller & Enright 2004) and sand

mine sites (Mounsey 2014) and other revegetation projects (Maher 2009) have suggested that

compacted topsoil may often form a physical barrier to seedling establishment constituting a

considerable environmental filter (Rokich et al. 2000). The disruption of the underlying highly

compacted substrate is often critical for successful seedling recruitment from topsoil transfer in

post-mine rehabilitation projects (Kew, Mengler & Gilkes 2007). Soil ripping increased the

performance of emerging native seedlings via an increase in water infiltration rates and

decreases in soil penetration resistance at a sand mine site (Mounsey 2014). Lower soil

compaction leads to faster radicle growth and tap root development (Szota et al. 2007; TERG

2012).

In the Jandakot study reported here, the ripping treatment applied to the transferred

topsoil did the opposite of what was predicted. Ripping had a negative impact on the densities

of native seedlings emerging from the topsoil in the first year after topsoil transfer. Mean

densities of both native perennial plants and native annuals were significantly lower on ripped

sites when compared to unripped.

It is likely that ripping-induced variability in soil moisture caused a spatial variation in

the density of native perennial recruitment (Bustamante-Sánchez, Armesto & Halpern 2011).

Soils in MTEs are often characterized by a high level of water repellence due to hydrophobic

soil grain coating derived from sclerophyll vegetation (Wallis & Horne 1992; Doerr, Shakesby

& Walsh 1996; Harper et al. 2000; Walden et al. 2015). Hydrophobicity might exacerbate the

poor seedling emergence from inter-furrow mounds as opposed to the furrows (Madsen et al.

2012). Furthermore, the concentration of rainwater in furrows could stimulate the emergence of

invasive plants derived from former pre-transfer soil surface and as well as drain away into

lower parts of the soil profile with reduced availability to germinants (Müller & Deurer 2011).

83

The success of seedling establishment may depend considerably on the specific timing

of disturbance and amounts of rainfall that are effective in priming seeds for germination

(Audet et al. 2013). In 2013, the second year after topsoil transfer, there was no legacy of the

abiotic filter manipulation treatment and densities of emerging seedlings were similar across

ripped and unripped clusters. In 2013 rainfall was above 100 mm in May, July, and August,

providing a relatively consistent soil moisture level over the time seeds were germinating. In

contrast, in 2012 during the time that topsoil was being transferred, rainfall was low (69 mm

April, 54 mm May) but at the time of ripping 168 mm fell in June followed by very low rainfall

in July (34 mm). A rapid increase in soil moisture could stimulate the earlier release of

dormancy and hence advance germination in the topsoil-stored seed bank species (Pérez-

Fernández et al. 2000; Merritt et al. 2007). As a result, the ripping treatment decreased the

emergence densities of fast emerging annual species, both native and invasive when compared

to unripped controls. The scarifying effect of topsoil ripping machinery could also cue an

additional number of the hard-coated dormant seeds, mostly fast-growing Fabaceae, to emerge

(Ward, Koch & Ainsworth 1996; Gresta, Avola & Abbate 2007) and the proportion of native

woody perennials was increased over that of control in 2012.

4.5.2 Biotic filter

Manipulation of the biotic filter did not affect the emergence of native seedlings either

in the first year after topsoil transfer or the second. Exclosures are a common tool used to

prevent grazing of established saplings (Pulido et al. 2010; Nield et al. 2015), however in this

study i.e., fenced versus unfenced, there was no difference in emergence between areas inside

and outside of the fence. The effect of grazers on young seedlings is likely to be variable

throughout the year with annuals utilised during the wet season (Landsberg et al. 2002). Hence,

the pressure on perennials is most intense in the critical summer dry season when annuals have

disappeared (Mancilla-Leytón, Joffre & Martín Vicente 2014). However, grazing was not a

problem in this study, and this may be due to the small population size of grazers such as

kangaroos and rabbits in the semi-urban landscape of this study area. Personal observation in

the area showed there were few signs of grazing animal activity indicating grazing pressure at

this local scale was not important over the time of the study. Rabbit numbers in Western

Australia have been shown to fluctuate over a number of years in agricultural area (Crosti

2011) in relation to epizootic outbreaks (Myxamatosis in the 20th Century and/or calici virus in

the 21st century). High variability in size of the herbivore populations is likely also to be the

case in semi-urban areas where reinvasion may be slower than in agricultural areas due to the

discontinuity of suitable habitat. Similarly, kangaroo population numbers will also be low in

semi-urban areas and may not cause the problems that are apparent in rangeland sites where

84

grazing pressure is often an issue for plant regeneration (Westoby, Walker & Noy-Meir 1989).

The outcome of fencing in relation to seedlings emergence densities is likely to be dependent

on year as well as site location caused by different levels of human and wildlife traffic.

4.5.3 Dispersal filter

Manipulation of the dispersal filter by applying two different topsoil volumes onto the

restoration sites had a positive effect on native perennial species emergence in both years.

Higher emergence densities of native perennials were recorded on deep topsoil (~10 cm)

compared with the shallow topsoil volume (~5 cm). This is in contrast to other work where

shallow topsoil spread is recommended due to low emergence capabilities of propagules found

in Mediterranean environments (Grant et al. 1996; Traba, Azcárate & Peco 2004; Rivera,

Jáuregui & Peco 2012). Small-sized seeds are typically found in the soil seed banks of the

MTEs in Australia (Enright et al. 2007) and the majority of the seedlings emerging from the

topsoil used in this study were small-seeded species (See Chapter 6). During the topsoil

stripping and transfers the seed bank contained within the topsoil will undergo a process of

mixing and homogenization i.e., densities of viable seeds are evened out to similar levels across

depth gradient in post-transfer topsoil as opposed to pre-transfer topsoil (Fowler et al. 2015).

While size may limit the regeneration of deeply buried propagules (Bond, Honig & Maze 1999;

Traba, Azcárate & Peco 2004) in this study the greater volume of soil in the deep treatment was

beneficial in producing increased recruitment over the shallow topsoil treatment so the

disadvantage of deep burial was counteracted by the greater number of seeds contained in the

greater volume of soil. If the topsoil resource is not limited by the area of land to be restored it

is beneficial to apply a greater volume of topsoil if this is available, although depths greater

than 10cm may too thick for some very small seeded species to emerge.

Shallow vs. deeper topsoil placement represents an important issue from a land

management point of view because quality topsoil is a cost-effective but scarce resource (Koch

2007a; TERG 2012). Studies on topsoil in other Mediterranean areas suggest there should be

thinner topsoil layers in order to maximize the area of vegetation rehabilitation (Holmes 2001;

Rivera et al. 2014). Conversely, spreading topsoil as a thinner layer may result in overall lower

native perennial species densities as shown in this study. Additionally, an increase in the

volume of transferred soil is likely to have a suppressing effect on local weed species (Fisher et

al. 2009b) but as shown in this study the invasive plants tended to be evenly distributed across

the alternating depths of the transferred topsoil.

In our study, the dispersal filter manipulation (deep topsoil) produced the best

restoration outcomes in terms of native species density and richness. The mean densities of

native perennials in the first year since topsoil transfer were the highest in the combination of

85

deep and unripped topsoil with no effect of the biotic filter manipulation (fenced vs. open

areas) on emerging plant densities. The positive effect of deep topsoil on native perennial

densities was consistent during both germination seasons.

In addition to manipulating the depth of transferred topsoil two plot-scale treatments,

i.e., heat and smoke, aimed at increasing the dispersal of seeds contained within the topsoil by

sending germination cues to otherwise dormant seeds. While smoke treatments showed no

significant effect the heat treatment applied in the second year after topsoil transfer increased

significantly the densities of emerging native perennials when compared with the untreated

plots. It is likely that the abrasive technique of the heat treatment application in this study, that

is scraping the top 5 cm of topsoil before applying ~80C heat pulse on remainder 5 cm of the

transferred topsoil reduced the weedy seed bank and stimulated the buried propagules. Most of

the propagules in MTE are of small size and would be unable to emerge from under 5 cm that

accumulated over the first year (Rokich et al. 2000). Hence, application of heat treatment is

recommended in the second year after topsoil transfer if the plant cohort from the previous

years was poor or dominated by weed species.

4.5.4 Weeds and filters

Invasive germinant densities increased over time with densities in the second year 51%

higher than the first year after topsoil transfer. The site-scale filter manipulation treatment

(applied in the first year) associated with the lowest weed densities was the abiotic filter

manipulation treatment. Manipulation of the abiotic filter, via a site-scale ripping treatment,

significantly reduced densities of emerging weeds in the first and the second year after topsoil

transfer (Figure 4-4). Soil ripping led to a simultaneous reduction of densities in both non-

native and native germinants in the first year and therefore may demonstrate the importance of

treatment timing if weed invasion to be minimized (Hierro et al. 2009). In particular, using a

ripping treatment to reduce weed densities may be most effective when difference in timing of

weed and native germinations is present. For example, native perennial species have dormant

seeds which tend to delay their emergence while invasive annual seedlings emerge rapidly in

autumn and winter following onset of rain (Bell et al. 1995; Groves & Willis 1999; Jones,

Norman & Rhind 2010). Hence, an immediate application of ripping treatment after topsoil

transfer might have minimized the negative effect on emergence densities of native seedlings

and sustain lower weed densities.

The effects of the plot-scale treatments on weed densities were most apparent in year

one (Table 4-12). For example, herbicide did reduce weed densities in year one but with no

carry-on effect on densities of native and non-native seedlings in year two (Figure 4-5). Weed

re-emerged quickly in year two and spread evenly across all sites and treatments. The only plot-

86

scale treatment that reduced weed densities significantly, by 47%, when compared with control

plots, was the heat treatment (applied in the second year). Similar to ripping, the heat

application was an abrasive technique whereby the soil was directly impacted. It is

hypothesised that the scale of disturbance caused by the heat treatment removed the weedy

competitors (accumulated on soil surface over the first year following topsoil transfer) and

enhanced the emergence of native seedlings from lower part of topsoil profile. It is very likely

that lower topsoil profile could contain viable native seed bank that stayed dormant during the

first year after topsoil transfer. Hence, heat treatment could serve as last resource technique to

stimulate emergence if the establishment of native was unsuccessful in the growth season after

topsoil transfer, for example, due to infestation or severe drought.

4.6 Conclusions

Restoration projects strive to rehabilitate the local ecosystems in a cost effective way. A

growing number of restoration projects use the transfer of a topsoil seed bank, i.e., stripping

topsoil from undisturbed donor sites and spreading on degraded receiver sites in order to

overcome onsite environmental barriers to native species recruitment. This technique has been

shown to be a useful restoration tool that facilitates the re-growth of the species-rich

understorey (See Chapter 6). The transferred topsoil seed bank contains an equivalent number

of natives species in comparison to post-fire regeneration sites in functionally similar remnant

ecosystems (Hobbs & Atkins 1990). This study builds on those results and indicates that topsoil

transfer can also be utilized in managing the environmental filters present on restoration sites. It

is really the only cost effective way of reconstructing an understorey of Banksia woodland on

degraded agricultural land due to the extreme species richness of this plant community type.

The manipulation of the dispersal filter via application of the deep volumes of the

transferred topsoil seed bank contributed to the most successful emergence of native plants in

both years post topsoil transfer. The emergence densities of native seedlings were abundant in

both years with significantly higher densities recorded in year one. Hence, this study could

evidence the general community assembly rule i.e., manipulation of dispersal limitation is most

likely to predict an increase in species richness and diversity (Cornell & Harrison 2014; Ojima

& Jiang 2016). Grazing pressure was not as intensive as expected but may be idiosyncratic to

the particular sites and years and not generalizable to other semi-urban situations. Application

of the ripping treatment to manipulate the abiotic filter had a negative effect on both annual and

perennial plant densities most probably due to a combination of soil hydrophobicity and the

timing of winter rains (Rokich et al. 2000; Merritt et al. 2007).

The additional application of the plot-level treatments (smoke water-related and

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herbicide) that aimed at enhancing the germination process were unsuccessful. Lack of

expected additional emergence under plot-level treatments is very likely attributed to the scale

of disturbance to which the topsoil was exposed during the transfer process, e.g., additional

aeration, exposure to light and soil moisture alteration carried an important set of cues that was

enough to stimulate germination of the plant cohort contained within the topsoil.

The timing of high rainfall as the topsoil was ripped and the following very dry July

plus hydrophobic soil properties are suggested to be the main drivers of the poorer than

expected native plant emergence. Additionally, a strong site effect on densities of emerging

seedlings suggests a high internal variation in seed bank composition contained within the

transferred topsoil that has also been reported in the previous seed bank studies (Enright &

Lamont 1989; Fowler et al. 2015). Thus, topsoil seed bank variability and field conditions need

to be carefully taken into account when planning to manipulate the environmental filters in

future restoration projects. A specific site sensitivity based on climatic parameters for a

rehabilitation location can be calculated and unsurprisingly sites in inland Australia are more

sensitive than sites closer to the coast (Audet et al. 2013). This can be helpful in scheduling

rehabilitation processes such as site preparation, the timing of soil spreading and whether there

needs to be addition of substances such as wetting agents to the soil, amongst others.

89

4.7 Appendices

4.7.1 Site effects

Table 4-7: Site effects on native perennial plant densities emerging in year one and two since topsoil transfer.


(intercept) intercept 3.53 0.14 25.95 0.001


Abiotic [Rip] ripped -0.26 0.19 -1.39 0.17


Year two -0.37 0.01 -31.06 0.001

Site AnkM -0.16 0.02 -6.50 0.001

Site AnkW 0.40 0.02 18.26 0.001

Site ForNW 0.53 0.02 25.40 0.001

Site ForSE 0.16 0.02 7.27 0.001

Site ForSW 0.05 0.02 2.14 0.03

Volume:Rip shallow:ripped -0.50 0.27 -1.84 0.07

Volume:Fence shallow:open -0.06 0.33 -0.19 0.85

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Table 4-8: Effect of site-scale filter manipulation treatments on native annual plant densities emerging in the first year [spring 2012] since topsoil transfer.

Filter [Topsoil Treatment] Term Treatment Scale ESTIMATE SE t P

(Intercept) intercept

4.3 0.4 11.5 <0.001

Abiotic [Rip] ripped Site -1.9 0.3 -6.9 <0.001

Biotic [Fence] open Site -0.1 0.3 -0.4 0.7

Dispersal [Volume] Shallow Site -0.1 0.3 -0.4 0.7

Abiotic:Biotic [Rip:Fence] ripped:open Site 0.2 0.3 0.7 0.5

Biotic:Abiotic [Fence:Volume] open:shallow Site -0.3 0.3 -0.9 0.4

Abiotic:Dispersal [Rip:Volume] ripped:shallow Site 0.3 0.3 0.9 0.4

Model: glmer(Density ~ Rip+Fence+Volume+Rip*Fence+Fence*Volume+Rip*Volume +(1|site/cluster), family = poisson(link="log"), data=annuals.year.one)


Table 4-9: Effect of site-scale filter manipulation treatments on native annual plant densities emerging in the second year [spring 2013] since topsoil transfer.


91


(Intercept) intercept Site 3.5 0.4 8.3 <0.001

Abiotic [Rip] ripped Site 0.1 0.4 0.3 0.79

Biotic [Fence] open Site 0.0 0.4 -0.1 0.94

Dispersal [Shallow] Shallow Site 0.5 0.4 1.4 0.17

Abiotic:Biotic [Rip:Fence] ripped:open Site -0.7 0.4 -1.6 0.12

Biotic:Abiotic [Fence:Volume] open:shallow Site 0.3 0.4 0.7 0.50

Abiotic:Dispersal [Rip:Volume] ripped:shallow Site -0.3 0.4 -0.8 0.45

Model: glmer(Density ~ Rip+Fence+Volume+Rip*Fence+Fence*Volume+Rip*Volume +(1|site/cluster), family = poisson(link="log"), data=annuals.year.two)

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4.7.4 Invasive plants densities (two figures)

Figure 4-4 Mean densities ± 95% CI of invasive plant densities (1m2) emerging in the first (one, spring 2012)) and second (two, spring 2013) year after topsoil transfer under three site-

scale filter manipulation treatments.

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Figure 4-5 Mean densities ± 95% CI of invasive plant densities (1m2) emerging in the first (one, spring 2012)) and second (two, spring 2013) year after topsoil transfer under five plot-

scale filter manipulation treatments

4.7.5 Invasive plants statistical tables (four tables)

Table 4-10: Effect of site-scale filter manipulation treatments on invasive plant densities (1m2) emerging in the first year after topsoil transfer (spring 2012).


(Intercept) (Intercept) 116.69 17.54 6.65 <.001

94


Dispersal [Volume] deep -28.60 12.53 -2.28 .071

Abiotic [Rip] ripped -39.26 12.53 -3.13 .026

Biotic [Fence] open 12.23 14.68 0.83 .442

Rip:Fence ripped:open -26.40 16.95 -1.56 .178

Volume:Fence deep:open 10.61 16.95 0.63 .558

Volume:Rip deep:ripped 7.57 15.89 0.48 .654

†Model: lmer(Weed.Density.1m2 ~Volume+rip+fence+rip*fence+fence*Volume+rip*Volume+(1|site)+(1|cluster),data = weeds.Year.One)

Table 4-11 Effect of site-scale filter manipulation treatments on invasive plant densities (1m2) emerging in the second year after topsoil transfer (spring 2013).


(Intercept) (Intercept) 175.29 17.34 10.11 <.001

Dispersal [Volume] deep 8.21 16.80 0.49 .646

Abiotic [Rip] ripped -10.70 16.87 -0.63 .553

Biotic [Fence] open -8.41 19.51 -0.43 .684

Rip:Fence ripped:open -43.11 22.54 -1.91 .114

Volume:Fence deep:open 47.36 22.54 2.10 .090

95


Volume:Rip deep:ripped -18.43 21.30 -0.87 .426

†Model: lmer(Weed.Density.1m2 ~ Volume+rip+fence+rip*fence+fence* Volume +rip*Volume+(1|site)+(1|cluster),data = weeds.Year.Two)

Table 4-12 Interactive effect of site- and plot-scale filter manipulation treatments on invasive plant densities (1m2) emerging in the first year after topsoil transfer (spring 2012).

Filter [Topsoil Treatment] Treatment Scale Term ESTIMATE SE t P

(Intercept) intercept 126.26 16.51 7.65 <.001

Abiotic [Rip] Site ripped -42.59 8.92 -4.77 .010

Dispersal [Volume] Site deep -29.70 8.92 -3.33 .032

Biotic [herbicide] Plot herbicide -33.41 7.04 -4.75 <.001

Abiotic [plastic] Plot plastic -16.75 7.04 -2.38 .020

Dispersal [smoke] Plot smoke -8.00 7.04 -1.14 .259

Dispersal [smoke.plastic] Site smoke.plastic -15.41 7.04 -2.19 .032

Abiotic:Dispersal [Rip:Volume] ripped:deep 11.30 12.61 0.90 .424

† Model: lmer(Weed.Density.1m2 ~ Volume*Rip + Small.Plot.Treatment + (1 | site)+(1|cluster), "), data= weeds.Year.One

96

Table 4-13 Interactive effect of site- and plot-scale filter manipulation treatments on invasive plant densities (1m2) emerging in the second year after topsoil transfer (spring 2013).

Filter [Topsoil Treatment] Treatment Scale Term Estimate SE t P

(Intercept) intercept 188.80 17.40 10.85 <.001

Abiotic [Rip] Site ripped -35.89 11.20 -3.20 .001

Dispersal [Volume] Site deep 1.63 11.13 0.15 .884

Dispersal [heat] Plot heat -99.66 19.67 -5.07 <.001

Biotic [herbicide] Plot herbicide 15.07 13.82 1.09 .276

Abiotic [plastic] Plot plastic 16.57 13.82 1.20 .231

Dispersal [smoke] Plot smoke -18.18 13.82 -1.32 .189

Dispersal [smoke.plastic] Plot smoke.plastic -14.93 13.82 -1.08 .281

Abiotic:Dispersal [Rip:Volume] Site ripped:deep 4.71 15.91 0.30 .767

†Model: lmer(Weed.Density.1m2 ~ Volume*Rip + Small.Plot.Treatment + (1 | site)+(1|cluster), "), data= weeds.Year.Two

4.7.6 2012 Species list

Table 4-14 List of plant species that emerged in the first year since topsoil transfer and their occurrence frequencies, spring 2012.

Genus Species Family Origin Longevity GrowthCat Year Frequency

Acacia cyclops Fabaceae native perennial woody one 0.30%

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Acacia huegelii Fabaceae native perennial woody one 3.12%

Acacia pulchella Fabaceae native perennial woody one 46.66%

Acacia saligna Fabaceae native perennial woody one 3.57%

Acacia sp. Fabaceae native perennial woody one 0.15%

Acacia stenoptera Fabaceae native perennial woody one 12.18%

Acacia willdenowiana Fabaceae native perennial woody one 0.30%

Acetosella vulgaris Polygonaceae invasive perennial herb one 1.78%

Adenanthos cygnorum Proteaceae native perennial woody one 28.53%

Aira caryophyllea Poaceae invasive annual grass one 47.10%

Alexgeorgia nitens Restionaceae native perennial grass one 0.15%

Allocasuarina humilis Casuarinaceae native perennial woody one 1.49%

Allocasuarina sp. Casuarinaceae native perennial woody one 0.15%

Amphipogon turbinatus Poaceae native perennial grass one 12.78%

Anigozanthos humilis Haemodoraceae native perennial herb one 4.61%

Anigozanthos manglesii Haemodoraceae native perennial herb one 0.89%

Arctotheca calendula Asteraceae invasive annual herb one 91.08%

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Arnocrinum preissii Hemerocallidaceae native perennial herb one 2.67%

Asclepias curassavica Apocynaceae invasive perennial woody one 0.15%

Astroloma sp. Ericaceae native perennial woody one 0.59%

Austrostipa compressa Poaceae native annual grass one 79.35%

Austrostipa sp. Poaceae native annual grass one 3.71%

Avena barbata Poaceae invasive annual grass one 53.94%

Banksia attenuata Proteaceae native perennial woody one 1.93%

Banksia grandis Proteaceae native perennial woody one 0.30%

Banksia menziesii Proteaceae native perennial woody one 0.15%

Boronia ramosa Rutaceae native perennial woody one 4.31%

Bossiaea eriocarpa Fabaceae native perennial woody one 79.94%

Brachypodium distachyon Poaceae invasive annual grass one 6.69%

Brassica sp. Brassicaceae invasive perennial herb one 0.15%

Briza maxima Poaceae invasive annual grass one 89.60%

Briza minor Poaceae invasive annual grass one 1.34%

Bromus diandrus Poaceae invasive annual grass one 54.09%

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Burchardia congesta Colchicaceae native perennial herb one 1.04%

Calandrinia corrigioloides Portulacaceae native annual succulent one 1.04%

Calandrinia granulifera Portulacaceae native annual succulent one 1.49%

Calothamnus quadrifidus Myrtaceae native perennial woody one 0.15%

Calytrix sp. Myrtaceae native perennial woody one 0.45%

Cardamine hirsuta Brassicaceae invasive annual herb one 1.63%

Carpobrotus edulis Aizoaceae invasive perennial succulent one 38.63%

Cartonema philydroides Commelinaceae native perennial herb one 1.78%

Cassytha racemosa Lauraceae native perennial herb one 0.15%

Cassytha sp. Lauraceae native perennial woody one 0.15%

Caustis dioica Cyperaceae native perennial grass one 0.45%

Centrolepis glabra Centrolepidaceae native annual grass one 1.34%

Centrolepis alepyroides Centrolepidaceae native annual herb one 18.13%

Cerastium glomeratum Caryophyllaceae invasive annual herb one 0.30%

Chamaescilla corymbosa Asparagaceae native perennial herb one 0.15%

Cirsium arvense Asteraceae invasive perennial herb one 0.30%

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Cirsium vulgare Asteraceae invasive annual herb one 0.74%

Conostylis aculeata Haemodoraceae native perennial grass one 5.79%

Conostylis juncea Haemodoraceae native perennial grass one 0.45%

Conostylis setigera Haemodoraceae native perennial grass one 15.30%

Conyza bonariensis Asteraceae invasive annual herb one 6.98%

Corynotheca micrantha Antheriaceae native perennial herb one 1.78%

Cotula australis Asteraceae native annual herb one 0.15%

Crassula decumbens Crassulaceae native annual herb one 46.21%

Crassula colorata Crassulaceae native annual succulent one 0.59%

Cynodon dactylon Poaceae invasive perennial grass one 4.61%

Cyperus eragrostis Cyperaceae invasive perennial woody one 1.34%

Dampiera linearis Goodeniaceae native perennial herb one 0.30%

Dasypogon bromeliifolius Dasypogonaceae native perennial grass one 22.88%

Daviesia divaricata Fabaceae native perennial woody one 0.30%

Daviesia nudiflora Fabaceae native perennial woody one 0.15%

Daviesia physodes Fabaceae native perennial woody one 0.15%

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Daviesia triflora Fabaceae native perennial woody one 2.08%

Desmocladus flexuosus Restionaceae native perennial herb one 23.48%

Dianella revoluta Hemerocallidaceae native perennial grass one 0.30%

Dischisma capitatum Scrophulariaceae invasive annual herb one 6.24%

Dittrichia graveolens Asteraceae invasive annual herb one 0.59%

Ehrharta calycina Poaceae invasive perennial grass one 97.18%

Ehrharta longiflora Poaceae invasive annual grass one 23.18%

Epilobium ciliatum Onagraceae invasive perennial herb one 0.45%

Eremaea asterocarpa Myrtaceae native perennial woody one 2.23%

Eremaea pauciflora Myrtaceae native perennial woody one 3.71%

Erodium botrys Geraniaceae invasive annual herb one 53.34%

Euphorbia terracina Euphorbiaceae invasive perennial herb one 3.27%

Euphorbia peplus Euphorbiaceae invasive annual herb one 0.15%

Ficus carica Moraceae invasive perennial woody one 0.30%

Gamochaeta calviceps Asteraceae invasive annual herb one 0.45%

Gamochaeta coarctata Asteraceae invasive annual herb one 0.45%

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Gastrolobium capitatum Fabaceae native perennial woody one 66.72%

Gladiolus caryophyllaceus Iridaceae invasive perennial herb one 69.54%

Gnaphalium indutum Asteraceae native annual herb one 0.45%

Gompholobium tomentosum Fabaceae native perennial woody one 94.06%

Hardenbergia comptoniana Fabaceae native perennial woody one 0.89%

Hedypnois rhagadioloides Asteraceae invasive annual herb one 15.16%

Hemiandra pungens Lamiaceae native perennial woody one 0.89%

Hensmania turbinata Hemerocallidaceae native perennial grass one 1.93%

Hesperantha falcata Iridaceae invasive perennial herb one 9.96%

Hibbertia aurea Dilleniaceae native perennial woody one 0.15%

Hibbertia huegelii Dilleniaceae native perennial woody one 42.79%

Hibbertia hypericoides Dilleniaceae native perennial woody one 32.10%

Hibbertia subvaginata Dilleniaceae native perennial woody one 60.92%

Homalosciadium homalocarpum Apiaceae native annual herb one 3.27%

Hovea elliptica Fabaceae native perennial woody one 1.49%

Hovea trisperma Fabaceae native perennial woody one 38.63%

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Hypocalymma angustifolium Myrtaceae native perennial woody one 27.19%

Hypocalymma robustum Myrtaceae native perennial woody one 12.04%

Hypocalymma sp. Myrtaceae native perennial woody one 0.30%

Hypochaeris glabra Asteraceae invasive annual herb one 93.61%

Isolepis marginata Cyperaceae native annual herb one 43.54%

Isolepis stellatus Cyperaceae native annual herb one 0.45%

Jacksonia furcellata Fabaceae native perennial woody one 26.75%

Jacksonia sternbergiana Fabaceae native perennial woody one 0.45%

Juncus capitatus Juncaceae invasive annual grass one 3.57%

Kennedia prostrata Fabaceae native perennial woody one 0.74%

Kunzea glabrescens Myrtaceae native perennial woody one 3.42%

Lachenalia reflexa Asparagaceae invasive perennial herb one 0.15%

Lactuca serriola Asteraceae invasive annual herb one 0.15%

Lagurus ovatus Poaceae invasive annual grass one 0.89%

Laxmannia sessiliflora Asparagaceae native perennial grass one 24.22%

Laxmannia squarrosa Asparagaceae native perennial grass one 34.47%

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Laxmannia ramosa Asparagaceae native perennial herb one 4.01%

Lechenaultia floribunda Goodeniaceae native perennial woody one 8.62%

Lepidosperma drummondii Cyperaceae native perennial grass one 1.49%

Lepidosperma tenue Cyperaceae native perennial grass one 0.30%

Lepidosperma squamatum Cyperaceae native perennial woody one 0.59%

Leucopogon conostephioides Ericaceae native perennial woody one 79.49%

Leucopogon sp. Ericaceae native perennial woody one 35.36%

Levenhookia pusilla Stylidiaceae native annual herb one 15.90%

Levenhookia stipitata Stylidiaceae native annual herb one 0.30%

Lobelia heterophylla Campanulaceae native annual herb one 0.15%

Lobelia sp. Campanulaceae native annual herb one 0.45%

Lolium sp. Poaceae invasive annual herb one 35.22%

Lomandra caespitosa Asparagaceae native perennial grass one 0.15%

Lomandra sp. Asparagaceae native perennial grass one 50.82%

Lotus angustissimus Fabaceae invasive perennial herb one 5.20%

Lupinus cosentinii Fabaceae invasive annual herb one 3.42%

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Lyginia barbata Anarthriaceae native perennial grass one 25.41%

Lysimachia arvensis Primulaceae invasive annual herb one 24.37%

Lysinema sp. Ericaceae native perennial woody one 0.45%

Lythrum hyssopifolia Lythraceae invasive annual herb one 0.15%

Medicago lupulina Fabaceae invasive annual herb one 10.10%

Melaleuca systena Myrtaceae native perennial woody one 0.30%

Melaleuca thymoides Myrtaceae native perennial woody one 1.78%

Mesomelaena pseudostygia Cyperaceae native perennial grass one 5.35%

Mirbelia sp. Fabaceae native perennial woody one 0.15%

Monoculus monstrous Asteraceae invasive annual herb one 0.89%

Monopsis debilis Campanulaceae invasive annual herb one 2.97%

Opercularia spermacocea Rubiaceae native perennial herb one 0.30%

Ornithopus pinnatus Fabaceae invasive annual herb one 0.15%

Orobanche minor Orobanchaceae invasive annual herb one 46.06%

Oxalis pes.caprae Oxalidaceae invasive perennial herb one 5.35%

Patersonia occidentalis Iridaceae native perennial grass one 27.19%

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Pelargonium capitatum Geraniaceae invasive perennial herb one 4.31%

Pentameris airoides Poaceae invasive annual grass one 0.15%

Persoonia saccata Proteaceae native perennial woody one 1.93%

Petrophile linearis Proteaceae native perennial woody one 0.30%

Petrorhagia dubia Caryophyllaceae invasive annual herb one 1.78%

Philotheca spicata Rutaceae native perennial woody one 0.59%

Phlebocarya ciliata Haemodoraceae native perennial grass one 0.15%

Phlebocarya filifolia Haemodoraceae native perennial grass one 4.16%

Phoenix dactylifera Arecaceae invasive perennial grass one 0.45%

Phyllangium paradoxum Loganiaceae native annual herb one 4.46%

Pimelea sp. Thymelaeaceae native perennial woody one 1.49%

Platysace compressa Apiaceae native perennial herb one 5.50%

Podolepis lessonii Asteraceae native annual herb one 0.15%

Podotheca gnaphalioides Asteraceae native annual herb one 55.27%

Poranthera microphylla Phyllanthaceae native annual herb one 3.57%

Pultenaea sp. Fabaceae native perennial woody one 0.45%

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Quinetia urvillei Asteraceae native annual herb one 2.67%

Rhodanthe chlorocephala Asteraceae native annual herb one 0.45%

Rhodanthe corymbosa Asteraceae native annual herb one 1.19%

Rhodanthe laevis Asteraceae native annual herb one 0.15%

Romulea rosea Iridaceae invasive perennial grass one 38.19%

Rytidosperma sp. Poaceae native perennial grass one 21.84%

Sagina procumbens Caryophyllaceae native perennial herb one 6.69%

Schoenus curvifolius Cyperaceae native perennial grass one 0.30%

Schoenus sp. Cyperaceae native perennial herb one 0.30%

Scholtzia involucrata Myrtaceae native perennial woody one 3.86%

Siloxerus humifusus Asteraceae native annual herb one 17.38%

Siloxerus humifusus Asteraceae native annual herb one

Siloxerus multiflorus Asteraceae native annual herb one 0.30%

Sisyrinchium exile Iridaceae invasive annual herb one 0.30%

Solanum americanum Solanaceae invasive perennial herb one 3.27%

Solanum nigrum Solanaceae invasive perennial herb one 3.42%

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Sonchus asper Asteraceae invasive annual herb one 1.93%

Sonchus oleraceus Asteraceae invasive annual herb one 4.46%

Stackhousia monogyna Celastraceae native perennial herb one 0.15%

Stenanthemum notiale Rhamnaceae native perennial herb one 0.15%

Stenotaphrum secundatum Poaceae invasive perennial grass one 0.15%

Stirlingia latifolia Proteaceae native perennial woody one 2.38%

Stylidium brunonianum Stylidiaceae native perennial herb one 3.42%

Stylidium ciliatum Stylidiaceae native perennial herb one 0.30%

Stylidium crossocephalum Stylidiaceae native perennial herb one 0.59%

Stylidium hesperium Stylidiaceae native perennial herb one 0.15%

Stylidium junceum Stylidiaceae native perennial herb one 0.59%

Stylidium piliferum Stylidiaceae native perennial herb one 1.19%

Stylidium repens Stylidiaceae native perennial herb one 0.15%

Stylidium sp. Stylidiaceae native perennial herb one 0.30%

Sympyotrichum squamatum Asteraceae invasive perennial herb one 2.82%

Synaphea spinulosa Proteaceae native perennial woody one 5.79%

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Tetraria octandra Cyperaceae native perennial grass one 0.30%

Thysanotus asper Asparagaceae native perennial herb one 0.30%

Thysanotus sp. Asparagaceae native perennial herb one 0.45%

Thysanotus sparteus Asparagaceae native perennial herb one 1.63%

Thysanotus thyrsoideus Asparagaceae native perennial herb one 0.15%

Trachymene pilosa Araliaceae native annual herb one 86.63%

Tricoryne elatior Hemerocallidaceae native perennial herb one 2.53%

Trifolium arvense Fabaceae invasive annual herb one 10.25%

Trifolium campestre Fabaceae invasive annual herb one 1.63%

Trifolium glomeratum Fabaceae invasive annual herb one 1.19%

Trifolium hirtum Fabaceae invasive annual herb one 0.45%

unkGen. sp. Monocot native perennial grass one 11.74%

Ursinia anthemoides Asteraceae invasive annual herb one 80.24%

Vulpia sp. Poaceae invasive annual grass one 56.76%

Wahlenbergia preissii Campanulaceae native annual herb one 29.57%

Wahlenbergia capensis Campanulaceae invasive annual herb one 24.81%

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Watsonia meriana Iridaceae invasive perennial herb one 0.15%

Xanthosia candida Apiaceae native perennial herb one 23.33%

Xanthosia huegelii Apiaceae native perennial herb one 0.30%

4.7.7 2013 Species list

Table 4-15 List of plant species that emerged in the second year after topsoil transfer and their occurrence frequencies, spring 2013.

Genus Species Family Origin Longevity Growth Year Frequency

Acacia cyclops Fabaceae native perennial woody two 5.47%

Acacia huegelii Fabaceae native perennial woody two 1.37%

Acacia pulchella Fabaceae native perennial woody two 39.91%

Acacia saligna Fabaceae native perennial woody two 2.05%

Acacia sp. Fabaceae native perennial woody two 0.80%

Acacia sp. Fabaceae native perennial woody two 11.29%

Acacia stenoptera Fabaceae native perennial woody two 0.11%

Acacia willdenowiana Fabaceae native perennial woody two 0.68%

Acetosella vulgaris Polygonaceae invasive perennial herb two 25.88%

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Adenanthos cygnorum Proteaceae native perennial woody two 48.12%

Aira caryophyllea Poaceae invasive annual grass two 0.57%

Alexgeorgia nitens Restionaceae native perennial grass two 15.28%

Amphipogon turbinatus Poaceae native perennial grass two 20.64%

Anigozanthos humilis Haemodoraceae native perennial herb two 3.65%

Anigozanthos manglesii Haemodoraceae native perennial herb two 69.67%

Arctotheca calendula Asteraceae invasive annual herb two 5.13%

Arnocrinum preissii Hemerocallidaceae native perennial herb two 0.23%

Arrhenatherum elatius Poaceae invasive annual grass two 0.23%

Asphodelus fistulosus Asphodelaceae invasive annual herb two 0.11%

Austrostipa compressa Poaceae native annual grass two 37.06%

Austrostipa sp. Poaceae native annual grass two 0.91%

Avena barbata Poaceae invasive annual grass two 66.59%

Boronia ramosa Rutaceae native perennial woody two 4.33%

Bossiaea eriocarpa Fabaceae native perennial woody two 31.47%

Brachypodium distachyon Poaceae invasive annual grass two 3.31%

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Brassica sp. Brassicaceae invasive perennial herb two 0.57%

Briza maxima Poaceae invasive annual grass two 92.36%

Briza minor Poaceae invasive annual grass two 0.11%

Bromus diandrus Poaceae invasive annual grass two 20.30%

Bromus madritensis Poaceae invasive annual herb two 2.39%

Burchardia congesta Colchicaceae native perennial herb two 6.27%

Calandrinia corrigioloides Portulacaceae native annual succulent two 2.39%

Calandrinia granulifera Portulacaceae native annual succulent two 2.39%

Calytrix sp. Myrtaceae native perennial woody two 1.48%

Cardamine hirsuta Brassicaceae invasive annual herb two 0.80%

Carpobrotus edulis Aizoaceae invasive perennial succulent two 19.50%

Cartonema philydroides Commelinaceae native perennial herb two 3.19%

Cassytha sp. Lauraceae native perennial woody two 0.23%

Centrolepis glabra Centrolepidaceae native annual grass two 0.23%

Centrolepis aristata Centrolepidaceae native annual herb two 1.37%

Chamaescilla corymbosa Asparagaceae native perennial herb two 10.26%

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Cirsium vulgare Asteraceae invasive annual herb two 0.11%

Conostylis aculeata Haemodoraceae native perennial grass two 8.67%

Conostylis juncea Haemodoraceae native perennial grass two 1.60%

Conostylis setigera Haemodoraceae native perennial grass two 8.44%

Conostylis teretifolia Haemodoraceae native perennial grass two 0.23%

Conyza bonariensis Asteraceae invasive annual herb two 2.17%

Crassula decumbens Crassulaceae native annual herb two 58.72%

Crassula colorata Crassulaceae native annual succulent two 1.60%

Cynodon dactylon Poaceae invasive perennial grass two 8.32%

Cyperus eragrostis Cyperaceae invasive perennial woody two 0.91%

Dampiera linearis Goodeniaceae native perennial herb two 0.68%

Dasypogon bromeliifolius Dasypogonaceae native perennial grass two 12.43%

Daviesia nudiflora Fabaceae native perennial woody two 0.23%

Daviesia physodes Fabaceae native perennial woody two 0.11%

Daviesia triflora Fabaceae native perennial woody two 0.11%

Desmocladus flexuosus Restionaceae native perennial herb two 3.31%

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Dianella revoluta Hemerocallidaceae native perennial grass two 0.11%

Dischisma capitatum Scrophulariaceae invasive annual herb two 8.89%

Dittrichia graveolens Asteraceae invasive annual herb two 0.34%

Drosera parvula Droseraceae native perennial herb two 3.31%

Ehrharta calycina Poaceae invasive perennial grass two 94.98%

Ehrharta longiflora Poaceae invasive annual grass two 3.08%

Eragrostis cumingii Poaceae invasive annual grass two 0.11%

Eremaea pauciflora Myrtaceae native perennial woody two 1.60%

Erodium botrys Geraniaceae invasive annual herb two 68.30%

Eucalyptus sp. Myrtaceae native perennial woody two 0.11%

Euphorbia terracina Euphorbiaceae invasive perennial herb two 1.37%

Euphorbia peplus Euphorbiaceae invasive annual herb two 0.11%

Gamochaeta coarctata Asteraceae invasive annual herb two 0.46%

Gastrolobium capitatum Fabaceae native perennial woody two 25.66%

Gladiolus caryophyllaceus Iridaceae invasive perennial herb two 76.05%

Gnaphalium indutum Asteraceae native annual herb two 0.11%

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Gnephosis angianthoides Asteraceae native annual herb two 16.31%

Gomphocarpus fruticosus Apocynaceae invasive perennial woody two 0.46%

Gompholobium tomentosum Fabaceae native perennial woody two 79.25%

Grevillea sp. Proteaceae native perennial woody two 0.23%

Hardenbergia comptoniana Fabaceae native perennial woody two 0.57%

Hedypnois rhagadioloides Asteraceae invasive annual herb two 6.04%

Hemiandra pungens Lamiaceae native perennial woody two 3.08%

Hensmania turbinata Hemerocallidaceae native perennial grass two 1.25%

Hesperantha falcata Iridaceae invasive perennial herb two 18.81%

Hibbertia huegelii Dilleniaceae native perennial woody two 55.53%

Hibbertia hypericoides Dilleniaceae native perennial woody two 20.52%

Hibbertia subvaginata Dilleniaceae native perennial woody two 75.37%

Homalosciadium homalocarpum Apiaceae native annual herb two 11.74%

Hovea elliptica Fabaceae native perennial woody two 0.46%

Hovea trisperma Fabaceae native perennial woody two 6.84%

Hypocalymma angustifolium Myrtaceae native perennial woody two 53.14%

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Hypocalymma robustum Myrtaceae native perennial woody two 26.80%

Hypochaeris glabra Asteraceae invasive annual herb two 89.28%

Isolepis marginata Cyperaceae native annual herb two 12.77%

Isolepis stellatus Cyperaceae native annual herb two 0.91%

Jacksonia furcellata Fabaceae native perennial woody two 17.45%

Jacksonia sternbergiana Fabaceae native perennial woody two 0.23%

Juncus acutus Juncaceae invasive perennial grass two 0.11%

Kennedia prostrata Fabaceae native perennial woody two 0.91%

Kunzea glabrescens Myrtaceae native perennial woody two 2.85%

Lagurus ovatus Poaceae invasive annual grass two 1.82%

Laxmannia sessiliflora Asparagaceae native perennial grass two 37.40%

Laxmannia squarrosa Asparagaceae native perennial grass two 2.74%

Laxmannia ramosa Asparagaceae native perennial herb two 50.06%

Lechenaultia floribunda Goodeniaceae native perennial woody two 32.95%

Lepidosperma drummondii Cyperaceae native perennial grass two 0.11%

Lepidosperma tenue Cyperaceae native perennial grass two 0.23%

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Leucopogon conostephioides Ericaceae native perennial woody two 71.84%

Leucopogon sp. Ericaceae native perennial woody two 21.66%

Levenhookia pusilla Stylidiaceae native annual herb two 35.58%

Levenhookia stipitata Stylidiaceae native annual herb two 0.57%

Lobelia heterophylla Campanulaceae native annual herb two 0.23%

Lolium sp. Poaceae invasive annual herb two 33.18%

Lomandra preissii Asparagaceae native perennial grass two 0.11%

Lomandra sp. Asparagaceae native perennial grass two 25.88%

Lomandra suaveolens Asparagaceae native perennial grass two 0.11%

Lotus angustissimus Fabaceae invasive perennial herb two 9.81%

Lupinus cosentinii Fabaceae invasive annual herb two 4.45%

Luzula campestris Juncaceae invasive perennial grass two 0.11%

Lyginia barbata Anarthriaceae native perennial grass two 24.63%

Lysimachia arvensis Primulaceae invasive annual herb two 24.40%

Lythrum hyssopifolia Lythraceae invasive annual herb two 0.91%

Medicago lupulina Fabaceae invasive annual herb two 13.68%

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Melaleuca systena Myrtaceae native perennial woody two 1.82%

Melaleuca thymoides Myrtaceae native perennial woody two 2.05%

Mesomelaena pseudostygia Cyperaceae native perennial grass two 3.88%

Microtis media Orchidaceae native perennial herb two 0.23%

Monoculus monstrous Asteraceae invasive annual herb two 1.03%

Monopsis debilis Campanulaceae invasive annual herb two 1.14%

Orobanche minor Orobanchaceae invasive annual herb two 62.60%

Oxalis pes.caprae Oxalidaceae invasive perennial herb two 8.78%

Patersonia occidentalis Iridaceae native perennial grass two 21.32%

Pelargonium capitatum Geraniaceae invasive perennial herb two 2.51%

Pentameris airoides Poaceae invasive annual grass two 0.11%

Persoonia saccata Proteaceae native perennial woody two 2.05%

Petrophile linearis Proteaceae native perennial woody two 0.11%

Petrorhagia dubia Caryophyllaceae invasive annual herb two 5.02%

Philotheca spicata Rutaceae native perennial woody two 1.14%

Phlebocarya ciliata Haemodoraceae native perennial grass two 0.46%

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Phlebocarya filifolia Haemodoraceae native perennial grass two 0.34%

Phyllangium paradoxum Loganiaceae native annual herb two 14.94%

Pimelea sp. Thymelaeaceae native perennial woody two 1.03%

Platysace compressa Apiaceae native perennial herb two 3.08%

Podolepis lessonii Asteraceae native annual herb two 0.11%

Podotheca gnaphalioides Asteraceae native annual herb two 66.25%

Poranthera microphylla Phyllanthaceae native annual herb two 3.19%

Pultenaea sp. Fabaceae native perennial woody two 0.46%

Quinetia urvillei Asteraceae native annual herb two 1.14%

Regelia sp. Myrtaceae native perennial woody two 0.11%

Romulea rosea Iridaceae invasive perennial grass two 50.51%

Rytidosperma sp. Poaceae native perennial grass two 0.57%

Sagina procumbens Caryophyllaceae native perennial herb two 2.39%

Scaevola sp. Goodeniaceae native perennial herb two 0.23%

Schoenus curvifolius Cyperaceae native perennial grass two 0.11%

Scholtzia involucrata Myrtaceae native perennial woody two 6.16%

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Siloxerus humifusus Asteraceae native annual herb two 0.80%

Siloxerus humifusus Asteraceae native annual herb two 6.50%

Siloxerus multiflorus Asteraceae native annual herb two 0.11%

Sisyrinchium exile Iridaceae invasive annual herb two 1.03%

Solanum americanum Solanaceae invasive perennial herb two 0.68%

Solanum nigrum Solanaceae invasive perennial herb two 0.11%

Sonchus asper Asteraceae invasive annual herb two 0.57%

Sonchus oleraceus Asteraceae invasive annual herb two 0.80%

Stenotaphrum secundatum Poaceae invasive perennial grass two 0.23%

Stirlingia latifolia Proteaceae native perennial woody two 3.53%

Stylidium brunonianum Stylidiaceae native perennial herb two 1.48%

Stylidium ciliatum Stylidiaceae native perennial herb two 1.14%

Stylidium crossocephalum Stylidiaceae native perennial herb two 0.46%

Stylidium emarginatum Stylidiaceae native perennial herb two 0.11%

Stylidium piliferum Stylidiaceae native perennial herb two 1.48%

Stylidium sp. Stylidiaceae native perennial herb two 0.11%

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Sympyotrichum squamatum Asteraceae invasive perennial herb two 1.25%

Synaphea spinulosa Proteaceae native perennial woody two 2.51%

Thysanotus manglesianus Asparagaceae native perennial herb two 0.23%

Thysanotus sp. Asparagaceae native perennial herb two 0.34%

Thysanotus sparteus Asparagaceae native perennial herb two 0.57%

Trachymene pilosa Araliaceae native annual herb two 83.58%

Trifolium arvense Fabaceae invasive annual herb two 18.36%

Trifolium campestre Fabaceae invasive annual herb two 0.23%

Trifolium glomeratum Fabaceae invasive annual herb two 4.68%

Trifolium hirtum Fabaceae invasive annual herb two 0.23%

unkGen. sp. Dicot native perennial woody two 4.22%

Ursinia anthemoides Asteraceae invasive annual herb two 70.01%

Vulpia sp. Poaceae invasive annual grass two 56.67%

Wahlenbergia preissii Campanulaceae native annual herb two 64.08%

Wahlenbergia capensis Campanulaceae invasive annual herb two 27.14%

Watsonia meriana Iridaceae invasive perennial herb two 0.11%

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Xanthosia candida Apiaceae native perennial herb two 8.67%

Zantedeschia aethiopica Araceae invasive perennial herb two 0.11%

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Chapter 5 Seedling survival after

emergence from transferred

topsoil seed bank

5.1 Abstract

Restoration practices seek new ways to reinstate and sustain an indigenous ecosystem after its

degradation. Restoration ecology suggests that environmental barriers present on degraded sites need

to be adequately addressed to reinstate native ecosystem successfully. In this study, the following

environmental barriers: dispersal (native and invasive propagule pressure), abiotic (soil compaction

and sun exposure), biotic (grazing and weed competition) were manipulated to improve understanding

of how to re-establish native plant communities.

This restoration study was located on post-agricultural land that had been grazed for ~80 years

prior to purchasing for conservation. Prior to agricultural use, the restoration site was occupied by

Banksia woodland – a Mediterranean-type ecosystem restricted to the Swan Coastal Plain of Western

Australia. As part of the biodiversity offset agreement, topsoil containing a seed bank from another

Banksia woodland site being cleared for urban expansion was transferred to restore the degraded ex-

farm land. To better understand topsoil transfer and improve outcomes, a fully factorial combination

of three site level and six plot-level treatments was applied across six sites. Three site-scale treatments

were tested by altering the depth of topsoil seed bank applied (dispersal filter), topsoil ripping (abiotic

filter) and installing herbivore exclosures (biotic filter). A further, four fine-scale treatments were

tested by applying smoke and heat (dispersal filter), herbicide (biotic filter) and installing artificial

shade (abiotic filter).

Following topsoil transfer in late autumn, emergence and subsequent survival of Banksia

woodland species were quantified in spring and autumn for two consecutive years. The highest

survival through the first summer drought occurred within topsoil ripping treatment in combination

with artificial shade (mean survival of 27.3 % ± 5.6 (SE), t=7.8, P<0.001). High mortality occurred

during the second summer drought and overall mean seedling survival over the 2-year sampling

period was 2.44% ± 0.2 (SE) which is similar to average percent survival recorded for native

seedlings in the intact Banksia woodland two years after fire disturbance.

Mitigating the adverse effects of environmental barriers (with summer drought as major

factor) on survival of the native seedlings that emerged from the transferred topsoil seed bank was

very challenging. Further research on how to address the environmental barriers present on restoration

sites is crucial if to improve effectiveness of biodiversity offset programmes. Undertaking restoration

works in summer-dry environments is difficult with heat and water stress often suppressing the

125

positive treatments effects.

5.2 Introduction

As increasing human populations drive land-use change (Corlett 2015), it has become clear

that maintaining biodiversity, ecosystem function and services has become a complex and arduous

task for land managers (Bluthgen et al. 2016). With accelerating change in land use, it is increasingly

evident that conservation of extant biodiversity alone is not a sufficient strategy – adequate ecological

restoration is needed to complement conservation efforts (Hobbs & Harris 2001; Hobbs 2007;

Possingham, Bode & Klein 2015). Conservation lands are ever more embedded within a human

production-oriented matrix. Additionally, the ecology of many indigenous species is still poorly

known further complicating an already difficult goal for land managers to successfully manage

projects restoring local biodiversity (Hobbs 1992a). Knowledge about multi-scale processes, both

temporal and spatial, is crucial to understand how manipulation of local environmental barriers is

linked to ecosystem functions (Shackelford et al. 2013b).

Myers (2000) delineated global biodiversity hotspots where exceptional biological diversity is

at the highest risk of degradation. All five Mediterranean-type ecosystems (MTEs) were classified as

exceptionally rich in rare and endemic plant species and also exposed to extremely high risk of

species losses due to land transformation and climate change (Cowling et al. 1996). All MTEs floras

developed under the specific climatic conditions characterized by hot, dry summers and cool, wet

winters (Raven, Evert & Eichhorn 1992). Each MTE region has evolved its own distinctive plant

communities, that is in southwestern Australia, California, Chile, Mediterranean Europe, and South

Africa. The MTEs occupy only 5% of Earth’s surface but comprise nearly 20% of global plant

diversity (Cowling et al. 1996).

Widespread shrublands and heathy woodlands, known locally as kwongan, is a MTE that

evolved in southwestern Australia (SWA), with its range entirely within one of the identified

biological hotspots (Myers et al. 2000). Unique plant diversity in the kwongan ecosystem is believed

to be driven not only by climate but also by harsh environmental conditions such as impoverished

soils which, together with long-term geologic stability and recurrent disturbances such as fire, are

thought to be the primary drivers that maintain remarkable SWA plant diversity, the highest in

Australia (Hopper & Gioia 2004). Diverse SWA plant communities are characterized by open

canopies, relatively small growth forms and diverse nutrient acquisition strategies (Lamont, Downes

& Fox 1977).

Restoration of the MTE in SWA is more difficult compared to regions in the northern

hemisphere due to much longer periods of unbroken evolution in locally specific plant traits (Hopper

2009). Restoration of these complex ecosystems demands a great effort to recreate such species-rich

126

assemblies (Dodd & Griffin 1989) at least in part, because of the knowledge needed to understand the

complex suite of life histories, particularly those surrounding regeneration from dormant seed banks

(i.e. smoke-related germination cues Rokich et al. 2002; Keeley et al. 2012). Deep dormancy in seeds

found in MTEs is believed to be related to their seed physiology (Dixon, Roche & Pate 1995) and is

attributed to their strategy to survive in harsh, fire-prone environments. Ability to emerge immediately

after a fire in natural conditions increases chances of seedlings’ odds to survive as the fire-affected

environment is clear of competitive species and more nutrient rich. Further, fire-cued recruitment

ensures seedlings have the maximum time between fires thereby maximising lifetime reproductive

output (Smith et al. 2016). Thus, appropriate use of smoke water in the restoration of the fire-prone

ecosystem may increase these chances by providing a head start in competition with often non-native

species and ample time to establish before summer drought (Roche, Koch & Dixon 1997; Ruthrof et

al. 2011). Production of long-lived and dormant propagules also translates into their extensive

accumulation in the ecosystem. Up to 80% of the seed bank is stored in the topsoil (Rokich & Dixon

2007) thus use of native seed banks contained therein may provide a useful restoration tool when

available, for example after land-clearing for development or mining (Rokich et al. 2000; Koch &

Richard 2007; Murcia et al. 2014). Additionally, lack of available green stock and seed banks in

commercial nurseries is also an obstacle to full restoration (Koch 2007b). Hence, appropriate

utilization of the seed bank contained within the topsoil sourced from the cleared land may help to

overcome the challenge of reinstating diverse native vegetation on degraded lands (Koch & Richard

2007; Pöll, Willner & Wrbka 2016). Restoration practitioners that use topsoil as a restoration tool are

mainly focused on rehabilitating the post-mine areas (Roche, Koch & Dixon 1997; Holmes 2001;

Parrotta & Knowles 2001; Norman et al. 2006; Herath et al. 2009; Hall, Barton & Baskin 2010).

Topsoil sourced from remnant ecosystems may also serve to increase the biological viability of

degraded sites by providing the assorted soil biota (Jasper 2007).

This study attempted to assess the potential of topsoil in restoring post-agricultural land.

Translocated topsoil contained high densities of native plant seeds based on glasshouse germination

assessment (Fowler et al. 2015). Therefore, given appropriate handling and treatment, the topsoil seed

bank presented an excellent opportunity for rehabilitating degraded post-agricultural site. Building on

accumulated knowledge from mine site restoration practices this study aimed at utilizing the seed

bank contained within topsoil to mitigate environmental barriers (aka filters, see 2.6) present on ex-

farm restoration study sites. The most crucial barriers to restoration that were identified in this study

were typical of farm land-use legacies, i.e., altered soil properties, weed-rich seed banks, wildlife and

human traffic. To optimize emergence and subsequently survival of the native plant communities

emerging from the transferred topsoil the degraded ex-farm study site received a combination of three

site-level treatments with the use of acquired topsoil. The site-scale treatments were designed to

mitigate the negative effect of three environmental barriers present on study restoration site, and these

were: topsoil ripping (soil compaction effect), altered topsoil depth treatment (seed bank effect) and

127

fencing treatments (herbivory effect). There were two emergence events following the topsoil

application (in spring I and spring II). The study looked at the survival of the native perennial

seedlings that emerged in the first and the second year after the application of transferred topsoil as

well as how soil chemical and physical properties responded to the experimental restoration

treatments. It was hypothesised that:

1. Reduction in soil compaction (topsoil ripping), pressure from herbivores (exclosures),

competition from the in situ weeds (topsoil depth and chemical weed control) and sun

exposure (artificial shade) will increase the odds of seedling survival.

2. Inducing rapid germination by applying fire-related stimulants, i.e., smoke-water and heat

treatments will give a head start to outcompete exotics and increase survival

3. Topsoil treatments may also affect soil chemical and physical properties and subsequently

seedling survival.

5.3 Methods

5.3.1 Topsoil treatments

The collected topsoil was transported to six recipient sites - three at Forrestdale Lake (Figure

3-4) and three at Anketell Road (Figure 3-5) that covered an area of approximately 18 ha (DEC 2012).

Allocation of the topsoil was according to the experimental design described in details in Figure 4-1.

Six study sites consisted of twelve study clusters (13 x 13 m). Each cluster consisted mostly of eight

to twelve 2 m × 2 m plots spaced 1m apart (0.5 m in a few cases where fencing constrained space).

5.3.1.1 Site-level treatments

Eight clusters were randomly allocated to examine effects of the combination of the three site-

scale treatments on seedling survival, i.e., altering volume of topsoil spread, ripping and topsoil

fencing. These treatments are described in details in section 3.4.3.

5.3.1.1.1 Topsoil volume

Half of each restoration site was capped with a 5 cm deep layer of topsoil (shallow depth

treatment), and the remaining area was capped with a 10 cm deep layer of topsoil (deep depth

treatment).

5.3.1.1.2 Topsoil ripping treatment

To ameliorate the compacted soil conditions a heavy vehicle equipped with a single or triple

winged tine was used to rip the top 30 cm of topsoil at all restoration sites – the ripped topsoil

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comprised the newly transferred topsoil as well as the underlying ex-farm subsoil. The rip line

spacing was set at 0.5 m. The ripping treatment was applied to both shallow and deep topsoil depth

treatments, treating half of the area of all six restoration sites. The soil ripping treatment loosened the

soil substrate and produced deep V-shape furrows. The ripping treatment was carried out in mid-June

over the period of two weeks 2012, 5-7 weeks after the topsoil transfer.

5.3.1.1.3 Topsoil fencing treatment

In this study, plots were fenced to protect germinants from herbivores, mainly rabbits

(Oryctolagus cuniculus) and western grey kangaroos (Macropus fuliginosus). Eight study clusters

were fenced at each site. Four unfenced clusters per site were used as controls to examine the

interactive effects of herbivore grazing and other site-level treatments.

5.3.1.2 Plot-level treatments

Plot-level treatments were small-scale treatments carried out on 2 m × 2 m plots superimposed

across the combination of site-level treatments to examine their potential interactive effect on native

seedling emergence and subsequently survival success. Six small-scale treatments were applied

immediately after the three site-level treatments were established (Table 4-1). The plot-level

treatments were carried out only within the fenced area to minimize the risk of damage to the

installations from wildlife and human traffic.

5.3.1.2.1 Smoke treatments

In the smoke-related treatments, an aqueous extract of wood smoke was used and applied to 2

m × 2 m treatment plots across a combination of all site-level treatments within the fenced area. The

two remaining smoke-related treatments, i.e., plastic cover and smoke in conjunction with plastic

cover presented in the previous chapter (Table 4-1) were removed from the survival analysis as their

primary focus was to exam effect on emergence.

5.3.1.2.2 Heat treatment

Due to a high risk of uncontrolled wildfire, no burning treatments were carried out in this

study. Instead, 2 m × 2.4 m plastic covers were used for three consecutive cloudless days on 19-21

February 2013 when the air temperature was ca. 38° C. The covers were placed onto the deep and

unripped topsoil treatments across all six sites in the second year since topsoil treatment. The top five

cm of the soil was removed to target seeds located five cm below the surface which remained dormant

and did not recruit after transfer of the topsoil. The plastic covers were placed directly onto the ground

to generate a heat pulse that went through the lower part of the topsoil profile. The heat treatment was

applied solely within deep, unripped and fenced topsoil within all six study sites (n=24).

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5.3.1.2.3 Chemical weed control treatment

In this study, two herbicides in combination were tested to investigate how recruitment levels

and composition of the native plant species from the transferred topsoil seed bank respond to chemical

weed control treatment (Table 4-1). Chemical weed control was carried out in the combination of all

site-level treatments within the fenced area during the winter growing season of 2012 – 3 months after

the topsoil transfer.

5.3.1.2.4 Shade and shade-semi treatments

In this study, the effect of 50% shading on over-summer survival and growth of seedlings was

examined. Artificial shading (3.6 m × 12.5 m in size), allowing 50% of daylight influx, was installed

0.5 m above the ground across, 2 m × 2 m plots within the treatment clusters on three sites across all

site-treatments (n= 48). The artificial shading was repeatedly installed at the end of spring 2012 and

spring 2013 before the onset of high summer temperatures and removed in May each year before the

onset of winter rainfall. The shade treatments were demolished due to onsite vandalism and vandalism

only 16 installations remained (1/3 of initial replicates).

5.3.2 Data collection

5.3.2.1 Vegetation surveys

Following topsoil transfer and spreading, field plots were established in late autumn and early

winter (May through to late June) 2012. Data collection was structured to capture emergence and

over-summer survival via seasonal surveys in spring and autumn for two years. Early establishment in

MTEs is critical and determines longer term plant assembly composition (Enright et al 2014).

Measurements commenced in spring (October 2012) and ran through autumn 2013, spring 2013 to

autumn 2014, providing two years of data for species abundance and community composition. Within

each 2 m × 2 m plot, the species identity and count of every native annual and native perennial

seedling were recorded. The density of the weed species was recorded four times inside the plot

within small 0.25 m × 0.25 m micro-plots due to high densities of weeds. The micro-plot was placed

in the centre of each plot 1 m × 1 m plot quarter. Counts of all plants were standardised to density per

square meter. The number of survey plots per cluster was increased from 8 to 12 in the second survey,

in spring 2013, to gain an adequate estimate of mortality of native perennials as seedling mortality

following the first summer drought after topsoil transfer was high.

5.3.2.2 Soil moisture

To examine the effect of filter manipulation treatments on soil water infiltration, volumetric

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soil moisture was monitored across six depths, i.e.,100, 200, 300, 400, 600, 1000 mm, for three

consecutive years of 2012-2015, following topsoil transfer in autumn 2012. Soil moisture was

measured across a combination of two site-level restoration treatments, i.e. ripped/unripped and

shallow topsoil/deep topsoil.

Soil moisture content was measured using a PR2/6 multi-depth soil moisture probe compatible

with pre-installed access tubes (Delta-T Devices 2008). Four access tubes were randomly situated at

each site (N = 6) within the fenced areas to account for the combination of two site-scale treatments,

i.e., topsoil volume and topsoil rip. The access tubes were located inside the cluster of plots but away

from the vegetation survey plots to avoid disturbance to the soil profile during tube placement. Access

tubes for soil moisture probe were installed only inside the fenced area due to a high risk of damage

outside the fence (rabbits, kangaroos). The access tubes were fitted tightly into pre-augured channels

to adepth of 1000 mm, reaching perpendicularly to the soil surface.

The PR2/6 probe was inserted into the access tube to measure volumetric soil moisture content

at depths of 100, 200, 300, 400, 600 and 1000 mm. The PR2/6 Probe consists of a sealed

polycarbonate rod, 25 mm diameter, with six electronic ring sensors arranged at six fixed intervals

along its length. The ring sensors located on a probe send out a 100 MHz signal which transmit an

electromagnetic field extending laterally about 100 mm into the soil. Soil water content influences the

soil permittivity around the ring sensors, resulting in a voltage reading (millivolts) which can be

converted to volumetric soil moisture (%) using a sixth order polynomial equation (Delta-T Devices

2008).

Three replicate soil moisture reading at each depths at each access tube were taken monthly

from September 2012 to September 2015. These data permitted examination of soil moisture

dynamics across both treatments and time and space.

5.3.2.3 Soil chemical properties

To reveal any changes in soil chemistry due to topsoil transfer soil samples were collected

from both the Jandakot topsoil donor as well as topsoil recipient sites in Forrestdale Lake and

Anketell Road. Using samples collected as part of another study (Fowler 2012; Fowler et al. 2015),

samples from the top 5 cm of the soil profile were collected. Each sample comprised five composited

subsamples from a 10 x 10 m plot where subsamples were collected at the centre and mid-way along

each subcardinal plot diagonal. In total 8 samples from the donor site and 10 samples from recipient

sites (4 from Anketell sites, 6 from Forestdale Lake sites) were analysed. Soil sampling tubes made

from PVC pipe, 155 mm of diameter x 100 mm of length, were used to collect the top five centimeters

of soils from the studied sites

The comparative study of chemical and physical properties investigated the impact of topsoil

transfer process on topsoil quality. Total soil ammonium nitrogen (NH4), nitrate nitrogen (NO3),

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sulphur (S), Colwell’s phosphorus (P), conductivity (ds/m), soil texture, soil pH in H2O and pH in

CaCL2 were analysed by CSBP Wesfarmers Soil Laboratory, Bibra Lake, Western Australia, in

September 2013. Colwell N and P is an estimate of N and P in the soil that are potentially available to

plants. Organic carbon and soil conductivity were measured according to standard methodologies for

measuring soil chemical and physical properties (Rayment & Higginson 1992). While replication of

soil chemistry was limited, the data permitted us to evaluate evidence for strong differences pre-post

topsoil transfer and general conditions experienced by seedlings.

5.3.2.4 Soil resistance

To measure effect of two site-scale treatments (topsoil ripping and depth) on soil resistance

(MPa) three sites were selected (ForNW, AnkW and ForSW). At each site, data were recorded in

spring 2013 (September – October), within six spatially distinct clusters to account for all two site-

scale treatment combinations. The soil resistance was measured in clusters to resemble spatial

distribution of vegetation survey plots. Each cluster comprised five replicates and was situated in

close vicinity to cluster of vegetation survey plots (1.5 m – 2.5 m). Effect of ripping treatment on soil

resistance was examined both inside the furrow and between furrows at each site. Soil resistance

across a 1000 mm (deep) soil profile was recorded using a cone penetrometer (Penetrologger with 1

cm2 and a 60

O top angle cone, Eijkelkamp, Netherlands) that logged data every 10 mm. The

penetrometer comprised a square housing and a small cone connected to 800 mm long bipartite

probing rod. The penetrologger was inserted vertically into the ground at a constant speed as set in the

plan (2 cm/s). To measure soil resistance at the bottom 800 -1000 mm of soil profile additional hole of

200 mm deep were dug (within 1 m of the first measurement. The penetrometer observations within

each clusters (n = 5) were spaced by at least 2 m intervals.

To assess effect of site-scale treatments on soils resistance mean values of soil resistance and

their 95% confidence intervals were computed in bands of 100 mm around respective depths of 100,

200, 300, 400, 600 and 1000 mm. Effects were visually assessed - if the confidence intervals did not

overlap, differences in soil resistance values, and therefore compaction, at each depth were deemed

significant.

5.3.3 Data analysis

5.3.3.1 Effect of site-scale treatments – main model

To quantify the effect of the three site-scale treatments on seedling survival the data were

analysed by looking at individual years (spring I to autumn I, spring II to autumn II) and also across

the two year period (spring I to autumn II). Data were structured by three site-scale treatments, i.e.,

topsoil spread volume, topsoil ripping, and herbivore exclosure (fencing). For each time interval, the

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following number (N of 2 m × 2 m subplots) of comparisons were used with elevated numbers in year

two reflecting more sampling to better sample sparse native germination (germination rates in year

two were lower than year one; see previous chapter):

Spring I to autumn II, N = 192,

Spring II to autumn II, N = 288,

Spring I to autumn II, N = 192.

Individual seedlings were treated as unique observations with their survival being a binary

outcome. Therefore a binomial error distribution was applied within a hierarchical general linear

mixed-effects framework to analyse the odds of survival of seedlings in relation to applied treatments

and their two-way interactions during each of the three named time intervals. The response of the

seedlings (survived and not survived) was structured as presence-absence data. The species id, six

study sites and eight study clusters on each site constituted random terms in the model. The

assumptions for the random effects to be normally distributed with a variance of one and mean of zero

were met (assessed graphically). Computations were performed using R-software (Team 2014)

including “lme4” R-package (Bates et al. 2014). Model fit was computed using Laplace

Approximation of the maximum likelihood (Raudenbush, Yang & Yosef 2000).

Data visualisation reports mean densities ± 95% confidence intervals relative to treatments in

the final year performed in “Rmisc” and “dplyr” R-packages (Wickham & Francois 2015) while

statistical output reflects the change in survival odds in relation to all treatments over all three survival

periods. Effect estimates with P < 0.05 were interpreted as statistically significant outcomes.

5.3.3.2 Effects of plot-scale treatments – additional effects

Beyond site-scale treatments, the potential additive or interactive effects of artificial shade

installation, heat, smoke and herbicide application on seedling survival were investigated. Survival

odds were estimated for native perennials in the same manner as for site-scale treatments with three

time periods (from spring I to autumn I, from spring II to autumn II and from spring I to autumn II).

However, plot-scale treatments were limited to two of three site-scale treatments and only applied

once (three smoke-related, herbicide, and artificial shade in the first year and heat in the second year

only). The heat treatment was applied solely within deep, unripped and fenced topsoil within all six

study sites (n=24). As with site-scale treatment analysis, a generalised mixed linear model with the

binomial error distribution was applied to the data. Dataset structure comprised five data columns

with site-scale treatments, plot-scale treatments, and periods of measured survival as fixed terms plus

study sites and study plot clusters as random terms. The data structure included site (N=6), study

cluster (13 x 13 m area and scale of site-level treatments; N=8 control, N=4 treatment per site) and

plot (2 x 2 m and scale of plot-scale treatment; see Table 5-9 and Table 5-10 for sample size of each

treatment group). Hierarchical general linear mixed-effect model was applied with site-scale

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treatments, additional six small plot treatments and time of survival as fixed factors and site and plot

locations as random effects.

5.3.3.3 Effect of site-scale treatments on soil moisture

To examine an interactive effect of two site-scale treatments on soil moisture profile in

summer and winter an ordinary least square regression was employed for months July and February

representing soil moisture in winter and summer, respectively to avoid repeated measure error.

Statistical differences in soil moisture profile between four combinations of the site-scale treatments

(deep.unripped, deep.ripped, shallow.unripped and shallow.ripped) and six different soil depths (100,

200, 300, 400, 600 and 1000 mm), at each observation time (n=6) were tested. Six different depths of

100, 200, 300, 400, 600 and 1000 mm were incorporated together with two site-scale treatments as

predictor variables.

5.3.3.4 Effect of site-scale treatments on soil physical and

chemical properties.

Determining soil chemistry and physical structure is relevant to understanding potential

impact of topsoil transfer on the environment in which seedlings were trying to establish. To examine

the effect of topsoil transfer on topsoil chemistry and its physical properties, the top 100 mm of the

surface soil were assessed. The samples included soil from the donor site before the land clearing and

from the topsoil recipient sites after the application of the topsoil (deep unripped volume only). Soil

samples were tested for differences in the concentration of the following soil nutrients: total soil

ammonium nitrogen, nitrate nitrogen, sulphur, phosphorus and sulphur (mg/kg). The content of

organic carbon (%), conductivity (ds/m) and soil pH (in H2Oand CaCl2) were also measured.

Independent samples t-tests were conducted to investigate evidence for changes in soil characteristics

due to the transfer.

5.4 Results

At the conclusion of vegetation surveys there were 906 live perennial plants. Of these 505

survived from the first year’s cohort. Therefore plants from the first spring emergence contributed

55% of the final plant assemblies. The dominant plant species, Gompholobium tomentosum

(Fabaceae), contributed 29.5% to the total species pool of plant cohort recorded during the last

vegetation survey in autumn 2014, substantially higher than the second most abundant species,

Hibbertia subvaginata (Dilleniaceae), representing 11.3% of total individuals. Overall, 109 native

species survived over the two year period after topsoil transfer (Table 5-11). Some plots were never

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occupied by native perennial plants; 1.2% in the first year (spring 2012) and 20.4% in the second

(spring 2013).

5.4.1 The effect of site-scale treatments on survival of

native perennials.

Mean survival of perennial native seedlings over the first growing season (spring 2012 to

autumn 2013) ranged from 5.6 % to 19.8 % (Figure 5-1). Sites receiving the topsoil ripping treatment

(abiotic filter) recorded higher survival, of 12.5 % ± 1.1 (SE) relative to 7.8 % ± 0.7 (SE) in unripped

treatments during the first summer drought after topsoil transfer (t =2.3, P = 0.02, Table 5-1).

Figure 5-1 Mean Survival Percentage in three survival periods across site-scale treatments: from spring 2012 to

autumn 2013 (autumn.2013), from spring 2013 to autumn 2014 (autumn.2014) and over two year period from spring

2012 to autumn 2014 (Two.Years).

The other two site-scale treatments (dispersal and biotic filter manipulations) had no

significant influence on survival over the first summer drought (topsoil volume: t=0.7, P = 0.47;

fencing: t=1.2, P = 0.23, Table 5-1). No two-way interactions among the site-scale treatments were

significant (Table 5-1).

Table 5-1 Effect of site-scale treatments on survival odds of native perennial seedlings over the first growing season

after topsoil transfer - from spring I (spr12) to autumn I (aut13).

Topsoil Treatment Term EST SE t P Survival.Time

(Intercept) intercept -3.7 0.5 -7.7 <0.001 spr12.to.aut13

Topsoil Ripping ripped 1.2 0.5 2.3 0.02 spr12.to.aut13

Fence Installation open 0.7 0.6 1.2 0.23 spr12.to.aut13

Topsoil Volume shallow 0.4 0.5 0.7 0.47 spr12.to.aut13

Rip:Fence ripped:open -1.1 0.7 -1.6 0.11 spr12.to.aut13

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Topsoil Treatment Term EST SE t P Survival.Time

Fence:Volume open:shallow -0.8 0.7 -1.2 0.23 spr12.to.aut13

Rip:Volume ripped:shallow -0.4 0.7 -0.6 0.58 spr12.to.aut13

Model: glmer(Survival~rip+fence+Volume+ rip*fence+fence*Volume+rip*Volume+(1|site/cluster) +(1|SpeciesCode), data=spr12.to.aut13,

family="binomial")

Mean survival of perennial native seedlings that emerged in the second growing season

(spring 2013 to autumn 2014) ranged from 0.1 % to 5.1 %. In contrast to the first summer, seedlings

that emerged in the second spring after topsoil transfer recorded significantly lower survival on sites

receiving the topsoil ripping treatment of 2.5 % ± 0.4 compared with unripped sites over the second

summer drought after topsoil transfer 3.3 % ± 0.3 (t = 1.8, P < 0.01, Table 5-2). The fencing treatment

(t=0.2, P = 0.86, Table 5-2) and the topsoil volume treatments showed no significant effect on

survival over the second summer season (t=0. 9, P < 0.34; Table 5-2).

Table 5-2 Effect of site-scale treatments on survival odds of native perennial seedlings that emerged in the second

spring after topsoil transfer - from spring II (spr13) to autumn II (aut14).

Topsoil Treatment

Term EST SE t P survival.time


Topsoil Ripping ripped -1.8 0.7 -2.5 0.01 spr12.to.aut13

Fence Installation open -0.1 0.8 -0.2 0.86 spr12.to.aut13

Topsoil Volume shallow -0.7 0.7 -0.9 0.34 spr12.to.aut13

Rip:Fence ripped:open 1.6 0.9 1.7 0.10 spr12.to.aut13

Fence:Volume open:shallow 0.6 0.9 0.6 0.52 spr12.to.aut13

Rip:Volume ripped:shallow 0.1 0.9 0.2 0.87 spr12.to.aut13

Model: glmer(Survival~rip+fence+Volume+rip*fence+fence*Volume +rip*Volume+(1|site/cluster)+(1|SpeciesCode), data=spr13.to.aut14,

family="binomial")

Seedlings survival over two year period after emerging during the first spring after topsoil

transfer ranged from 0.6 % to 5 % (from spring 2012 to autumn 2014, Figure 5-1, Table 5-9) and was

relatively even across the combination of all site-scale treatments (opposite ripping effects in first vs.

second summer counterbalanced one another) with overall mean of 2.4 % ± 0.2 (SE). The fencing

treatments recorded a slightly better effect on survival compared to unfenced sites (t= 0.7, P = 0.46,

Table 5-3).

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Table 5-3 Effect of site-scale treatments on survival over a two-year period of native perennial plants, from spring I

(spr12) to autumn II (aut14).

Topsoil Treatment

Term EST SE t P Survival.Tim

e


Topsoil Ripping ripped -0.7 0.6 -1.2 0.24 spr12.to.aut14

Fence Installation open -0.5 0.6 -0.7 0.46 spr12.to.aut14

Topsoil Volume shallow -0.3 0.6 -0.5 0.65 spr12.to.aut14

Rip:Fence ripped:open 0.8 0.8 1.0 0.31 spr12.to.aut14

Fence:Volume open:shallow -0.1 0.8 -0.2 0.86 spr12.to.aut14

Rip:Volume ripped:shallow -0.1 0.8 -0.1 0.93 spr12.to.aut14

Model: glmer(Survival~rip+fence+Volume+rip*fence+fence*Volume+rip*Volume+(1|site/cluster)+(1|SpeciesCode) ,data=spr12.to.aut14,

family="binomial")

The mean final densities in the second growing season ranged from 0.08 to 0.4 seedlings m-2

.

The highest recorded mean density of 0.36 ± 0.05 (SE) in the second year following topsoil transfer

was on sites with deep topsoil (Figure 5-2).

Figure 5-2 Mean final densities (m-2) of native perennials with 95% confidence Intervals in the second year after topsoil

transfer, autumn 2014. Site-scale treatments only: 1 Topsoil Depth (deep and shallow), 2) Topsoil Rip (ripped and

unripped), and 3) Herbivore Exclosures (fenced and open).

5.4.2 The effect of plot-scale treatments on survival of

native perennials.

Mean percent survival of perennial native seedlings over the first growing season (spring 2012

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to autumn 2013) was significantly higher in the shade plot-scale treatment with mean 27.3 % ± 5.6

(SE) compared with survival in respective control plots (9.8 %, t=7.8, P < 0.01; Figure 5-3, Table 5-4)

and ranged from 9.1 % to 27.3 %.

Figure 5-3 Mean final densities of native perennials in the second year after topsoil transfer, autumn 2014. Control

represents the mean±95CI of all site-scale treatments. Plot-scale treatment represents the mean ± SE of all respective

treatments: 1) heat, 2) herbicide 3) shade, 4) smoke.

Table 5-4 Interactive effects of two site-scale treatments and additional plot-scale treatments on survival of native

perennial seedlings over the first growing season after topsoil transfer - from spring I (spr12) to autumn I (aut13).

Topsoil Treatment Term ESTIMATE SE t P

(Intercept) Intercept -3.7 0.4 -8.9 <0.001

Site-scale [Topsoil Ripping ]

ripped 1.0 0.5 2.1 0.03

Site-scale [Fence Installation]

open 0.7 0.5 1.4 0.17

Site-scale [Topsoil Volume]

shallow 0.3 0.5 0.8 0.44

Plot-scale herbicide 0.4 0.2 2.6 0.01

Plot-scale shade 1.9 0.2 7.8 <0.001

Plot-scale smoke 0.2 0.2 1.2 0.21

Rip:Fence ripped:open -0.9 0.6 -1.4 0.16

Fence: Volume open:shallow -0.8 0.6 -1.3 0.20

Rip: Volume ripped:shallow -0.3 0.6 -0.5 0.61

† Model: glmer(Survival~rip+fence+Volume+rip*fence+fence*Volume+rip*Volume+ plot-scale.treatment

+(1|site/cluster)+(1|specCode),data=spr12.to.aut13,family="binomial")

Mean survival of perennial native seedlings over the second growing season (spring 2013 to

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autumn 2014) ranged from 0.7 % to 6.4 % (Figure 5-3). Overall, the additional plot-scale treatments

did not have significant positive effect on seedling survival compared with seedling survival in the

control plots. Shade plot-scale treatment was not associated with significant increase in survival of

native perennials that emerged in the second spring to the second autumn season (t=0.8, P = 0.43,

Table 5-5).


perennial seedlings over the second growing season after topsoil transfer - from spring II (spr13) to autumn II (aut14).




ripped -1.9 0.6 -3.0 <0.001


open 0.0 0.7 -0.1 0.95


shallow -1.0 0.6 -1.7 0.09

Plot-scale heat 0.1 0.3 0.3 0.74

Plot-scale herbicide -0.4 0.3 -1.3 0.20

Plot-scale shade 1.0 1.3 0.8 0.43

Plot-scale smoke 0.1 0.3 0.3 0.73


Fence: Volume open:shallow 0.6 0.8 0.8 0.44

Rip: Volume ripped:shallow 0.7 0.8 0.8 0.42

† Model: glmer(Survival~rip+fence+Volume+rip*fence+fence*Volume+rip*Volume+ plot-scale.treatment

+(1|site/cluster)+(1|specCode),data=spr13.to.aut14,family="binomial")

Mean survival of perennial native seedlings over two year period (spring 2012 to autumn

2014) ranged from 1.7. % to 5.5 % (Figure 5-3). None of the additional plot-scale treatments was

associated with an increase in survival of native perennials. The highest positive effect on seedlings

survival was recorded under the shade treatment (t = 1.8, P = 0.07, Table 5-6).


perennial seedlings over two growing season after topsoil transfer - from spring II (spr12) to autumn II (aut14).



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ripped -0.29 0.52 -0.6 0.58


open -0.38 0.60 -0.6 0.52


shallow -0.08 0.52 -0.2 0.87

Plot-scale herbicide -0.60 0.42 -1.4 0.15

Plot-scale shade 1.31 0.72 1.8 0.07

Plot-scale smoke 0.72 0.71 1 0.31


Fence: Volume open:shallow -0.15 0.72 -0.2 0.83

Rip: Volume ripped:shallow -0.38 0.70 -0.5 0.59

† Model: glmer(Survival~rip+fence+Volume+rip*fence+fence*Volume+rip*Volume+ plot-scale.treatment +(1|site/cluster) +

(1|specCode), data=spr12.to.aut14,family="binomial")

5.4.3 The effect of site-scale treatments on soil moisture

and soil chemical properties.

Volumetric soil moisture ranged from 0.2% to 10.3% (Figure 5-4, Figure 5-5, Figure 5-6,

Figure 5-7) during the three consecutive years after topsoil transfer. On average, volumetric soil

moisture in summer was near zero at the surface increasing to 3.3 % at 400 mm and highest of 6.9 %

at 1000 mm. In winter, frequent rain led to a more saturated profile with 5.8 % to 9.3 %.

Mean soil moisture was on average 0.3 % higher in soil under ripping treatment during the

summer month of Februrary (t= 1.0, P = 0.30, Table 5-7) and 0.5 % in the winter month of July,

respectively (t = 0.9.0, P = 0.36, Table 5-8). A significant reduction of soil moisture was detected at

the depth of 300 mm under ripping treatment in both seasons: summer (-1.0 %, t= 2.3, P = 0.03, Table

5-7) and in winter (-2.4 %, t= 0.8, P < 0.01, Table 5-8).

There were no significant differences in soil ammonium nitrogen, nitrate nitrogen, sulphur and

organic carbon content between topsoil samples from pre-clearing and post-transfer sites (Figure 5-8).

There was a significantly lower pHCa of 4.3 ± 0.093 (SE) detected in transferred soil compared to

pHCa in the pre-cleared soil of 4.81 ± 0.125 (SE) (t= 4.7, P < 0.001). The transferred soil also

recorded significantly lower conductivity 0.03 ±0.004 (SE) (ds/m) when compared to intact soil 0.019

± 0.005 (SE) (t = 3.4, P < 0.01).

Soil resistance increased gradually across the soil profile and peaked at the depth of 600 mm

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(Figure 5-9). The maximum soil resistance of 7.5 MPa ± 0.1 (SE) was detected under ripping

treatment (at the depth of 600 mm, under inter-furrow mounds). A significant loosening effect of

furrowing was observed at the depth of 100 mm with 0.6 MPa recorded in shallow and ripped in

contrast to 1.4 MPa ± 0.03(SE) in shallow and unripped soil. The sites where soil was unripped

showed significantly lower soil resistance at 300 and 400 mm across both topsoil volumes compared

with ripped sites. Soil resistance at the depth of 800 and 1000 mm was significantly lower on deep

and ripped sites as compared with deep and unripped (Figure 5-9).

Table 5-7 Interactive effects of topsoil ripping and topsoil volume treatment on soil moisture at six different depths of

100, 200, 300, 400, 600 and 1000 mm in February in year 2013 – 2015.

Term Treatment EST SE t P

Intercept Intercept 5.9 0.3 23.2 <0.001

Depth (mm) 600 -1.9 0.3 -5.8 <0.001

Depth (mm) 400 -3.4 0.3 -10.5 <0.001

Depth (mm) 300 -4.1 0.3 -12.6 <0.001

Depth (mm) 200 -4.1 0.3 -12.6 <0.001

Depth (mm) 100 -5.6 0.3 -17.4 <0.001

Rip ripped 0.3 0.3 1.0 0.300

Volume shallow -0.2 0.1 -1.5 0.131

Year 2014 -0.5 0.2 -3.3 <0.001

Year 2015 1.9 0.2 11.5 <0.001

Depth:Rip 600:ripped 0.0 0.5 0.1 0.940

Depth:Rip 400:ripped -0.2 0.5 -0.5 0.641

Depth:Rip 300:ripped -1.0 0.5 -2.3 0.023

Depth:Rip 200:ripped -0.9 0.5 -2.1 0.038

Depth:Rip 100:ripped -0.2 0.5 -0.5 0.639

Model: lm(Moisture ~ depth * rip + Volume. + year , data= February)

Table 5-8 Interactive effects of ripping topsoil depth treatment on soil moisture at six different depths of 100, 200, 300,

400, 600 and 1000 mm in July in year 2013 and 2014.


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(Intercept) Intercept 9.1 0.4 20.9 <0.001

Depth (mm) 600 -1.9 0.6 -3.3 <0.001

Depth (mm) 400 -2.6 0.6 -4.6 <0.001

Depth (mm) 300 -2.4 0.6 -4.2 <0.001

Depth (mm) 200 -1.1 0.6 -2.0 0.047

Depth (mm) 100 0.0 0.6 0.0 0.963

Rip ripped 0.5 0.6 0.9 0.368

Volume shallow -0.3 0.2 -1.2 0.239

Year 2014 0.1 0.2 0.5 0.603

Depth:Rip 600:ripped 0.8 0.8 1.0 0.315

Depth:Rip 400:ripped -0.2 0.8 -0.2 0.832

Depth:Rip 300:ripped -2.4 0.8 -3.0 0.003

Depth:Rip 200:ripped -2.0 0.8 -2.5 0.012

Depth:Rip 100:ripped -1.9 0.8 -2.4 0.018

Model: lm(Moisture ~ depth * rip + Volume. + year , data= July)

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Figure 5-4 Mean volumetric soil moisture content (± 95% CI) measured under the combination of two site-scale treatments: topsoil volume (deep and shallow) and topsoil ripping

(unripped and ripped). The monthly measurements were recorded at six depths: 100, 200, 300, 400, 600, and 1000 mm. Year 2012 in spring (the start of the project) and summer only.

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(unripped and ripped). The monthly measurements were recorded at six depths: 100, 200, 300, 400, 600, and 1000 mm. Year 2013.

144


(unripped and ripped). The monthly measurements were recorded at six depths: 100, 200, 300, 400, 600, and 1000 mm. Year 2014.

145


(unripped and ripped). The monthly measurements were recorded at six depths: 100, 200, 300, 400, 600, and 1000 mm. Year 2015 in summer and autumn only (the end of the project).

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Figure 5-8 Chemical and physical properties of soil samples collected from the topsoil donor (intact) and topsoil recipient (Transfer): conductivity [ds/m],concentration of ammonium

nitrogen [NH4 mg/kg ], nitrate nitrogen [NO3 mg/kg ], organic carbon [OC %], phosphorus[P mg/kg] and sulphur [S mg/kg ], soil texture (scale of 5 categories where 1=sand, 1.5 =

sand/loam, 2 = loam, 2.5 = loam/clay and 3 = clay )and soil pH (in CaCl2). The lower and upper box bars correspond to first and third quartiles of data (the 25th and 75th percentiles).

The upper whisker extends from upper box bar to value of 1.5 of inter-quartile range (distance between the first and third quartiles). Data beyond the end of the whiskers may be

considered as outliers and are plotted as points.

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Figure 5-9 Mean soil resistance (MPa) with 95% confidence intervals at the seven depths: 100, 200, 300, 400 ,600, and 1000 mm. Soil resistance was measured at the combination of

topsoil ripping treatments (ripped: in and out of furrow and unripped) and topsoil volume (deep and shallow), in spring 2013.

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5.5 Discussion

5.5.1 Site-level treatments: role of topsoil depth, ripping,

and fencing

5.5.1.1 Altering depth of topsoil spread

The depth of topsoil placement had no impact on survival in either year neither of the study

nor across the entire two year period but did impact germination (see 2.6). The density of arriving

propagules is very likely to affect the recruitment process via propagule pressure and competition for

available resources (Duncan et al. 2009; Warren, Bahn & Bradford 2012). However the summer of

2013 –2014 was unusually dry and long, it is not possible to estimate the role of the seedlings’

densities on their survival as most of the seedlings, both native and invasive, died in the drought.

Mortality in the semiarid and MTE ecosystems is on average very high – above 90% (James, Svejcar

& Rinella 2011) and is mainly driven by the harsh summer drought conditions (Atwater, James &

Leger 2015). Thus, native species that have xerophytic traits (i.e., traits that allow species to persist

despite very low water availability) are more likely to survive in harsh environmental conditions

experienced on the restoration sites (Valladares et al. 2002; Rey Benayas et al. 2005). The xerophytic

strategy evolved as an adaptation to high disturbance and is characterized by plants with high water

use efficiency and rapid root turnover during the winter rainfall events (Grime 1977). Seedlings that

established on both shallow and deep topsoil were typically xerophytic pioneer species (see Chapter

6). Final seedling densities on deep topsoil were slightly higher compared with shallow topsoil mainly

due to their higher emergence on deep topsoil. The mean final densities of 0.2 – 0.4 m-2

for native

perennials recorded in this study were lower compared with densities recorded in remnant ecosystem,

for example, mean 1.51 m-2

germinants were recorded in a study on post-fire recruitment in Banksia

woodland (Crosti 2011). No effect of topsoil volume on seedlings survival suggests the use of thinner

layer of the topsoil in the future projects could be justified provided optimal conditions for seedlings

survival (Fowler et al. 2015).

The process of topsoil transfer and spreading resulted also in slight changes in physical and

chemical properties between the soil samples from the topsoil recipient and the intact topsoil donor

sites. The transferred topsoil contained fewer fine particles such as clay, most likely lost during the

topsoil transfer process. Topsoil transfer occurred during the dry autumn season what might cause

light clay particles to suspend in the air and be sieved out from the main substrate (Sharifi, Gibson &

Rundel 1997). The observed changes in soil texture towards a lower ratio of clay particles in the

transferred topsoil could result in depletion of Phosphorus anions recorded on restoration sites. Loss

of clay content reduces ions retention and is also associated with lower soil conductivity (Corwin &

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Lesch 2005). Overall, topsoil transfer and its spread on restoration sites resulted in lower topsoil

conductivity, lower P content and higher pH compared to native intact topsoil and is consistent with

findings from similar studies (Stahl et al. 2002).

5.5.1.2 Topsoil ripping treatment

Soil furrowing (ripping) had a strong positive effect on survival in the first year but this effect

dissipated by the second summer season. Elevated survival in ripped soils over the first summer may

have been due to either reduced densities and thereby reduced competition or increased access to

deeper soil layers and moisture due to lowered soil compaction (Rockström & Valentin 1997). In this

study, germinant densities were reduced by ripping (2.6) and ripping treatment did not reduce soil

compaction (e.g., 600 mm deep, Figure 5-9 ) therefore reduced competition is the more likely scenario

(Tamado & Milberg 2004). Evidence from studies in similar ecosystems demonstrated that reduction

in proliferation of weedy annuals increased the survival probability for native perennials that are,

generally characterized by more stringent germination cue mechanisms compared to invasive plants

(Smith, Bell & Loneragan 1999; Wainwright & Cleland 2013).

Reduction in soil compaction with the application of the ripping treatment could increase

water infiltration as ripped soils were drier at shallower depths ( < 300 mm) and slightly more moist

below 600 mm and stimulate root system growth of newly emerged seedlings (Figure 5-5, Figure

5-6). Soil ripping is believed to increase water infiltration thereby saving the topsoil seed bank from

water logging but this is unlikely to be important in freely draining sand-dominated soils such as those

examined in this study. However, it might also allow for a reduction in early-emerging weed density

and greater soil aeration that is pivotal to proper root growth of target species (Kirkham 2011). Some

previous studies also showed a positive effect of soil ripping on soil water conditions (Koch 2007a).

Soil ripping creates a friable rooting zone and alleviates soil compaction (Kew, Mengler & Gilkes

2007; Ruthrof 2012) which, in turn, is likely to increase plant survival (Enright & Lamont 1992). A

study from the Rocla sand quarry in the northern Perth metropolitan area provides additional evidence

that soil ripping may have a positive effect on seedling survival recruited from returned topsoil seed

bank via a reduction in the ground impedance (Rokich et al. 2000; Mounsey 2014).

The final densities of the native seedlings surviving over the two-year period were higher on

unripped sites as compared to ripped. It is possible that seedlings encountered a more compact soil

layer below the soil ripping depth ( > 300 mm) as detected in the soil resistance data (Figure 5-11, in

the appendix). The reduced soil moisture at a depth of 300 mm may be due to a delay in moisture

reaching this depth after the dry summer and autumn leading to the 300 mm level wetting more

slowly than the more shallow layers. This together with the sudden change in the soil compaction

could have a negative effect on survival of the emerging seedlings as the construction of an efficient

root system is the key plant strategy in semi-arid conditions (Gleason, Butler & Waryszak 2013).

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Development of the tap root is vital in supporting the plant throughout the period of summer thus

reducing the negative impact of the drought on survival. As indicated in a study on root sensitivity to

soil impedance, elevated soil compaction led to increased numbers of lateral roots and reduced tap

root growth (Manning, Cunningham & Lindenmayer 2013). The use of heavy machinery in spreading

the topsoil at recipient sites is likely to have had a compacting effect on the soil profile, hence

affecting the ability of native perennial seedlings to develop efficient root architecture. Plants that

invested in a lateral root system early after emergence, due to high soil compaction, likely

experienced decreased survival rates given reduced access to deeper soil water stores over summer.

The ripping treatment appears not to have loosened the substrate sufficiently to permit plants to access

deeper soil layers.

The higher final densities of seedlings surviving through the second summer drought seasons

recorded on unripped sites may also suggest that positive effects of ripping on seedling survival were

counter-balanced by higher emergence densities across unripped sites. Overall, average rates of

survival over two year period after emergence (i.e., below 4.5%.) were extremely low. The rapid fall

in percentage survival by the end of the second summer since emergence is typical of the region

(Lamont et al. 1999). Prolific seeder plants (small seed size) show a clear tendency to grow fast that

may lead to fiercer competition for limited resources and induce self-thinning (Kikuzawa 1999; West,

Enquist & Brown 2009) that reduce survival over the second summer drought (Lloret, Casanovas &

Peñuelas 1999).

5.5.1.3 Herbivore exclosures installation

Herbivores have a direct effect on local vegetation through changing the plant composition

and reducing the above-ground biomass (Côté et al. 2004). A reduction in the herbivory pressure, by

means of fenced exclosures, might be critical for emerging seedlings to survive (Edwards & Crawley

1999; Fensham, Silcock & Dwyer 2011; Bird et al. 2012). Although fencing is widely recognized as a

reliable tool to increase the probability of rehabilitation success (Godefroid et al. 2011) in our study,

fenced exclosures did not have any significant positive effect on seedling emergence nor seedling

survival over the first and second summer drought. An exhaustive suite of vegetation survey plots

confirmed a high variability in plant densities surviving within and outside the fenced exclosures as

well as between the six study sites. The strong site effect is likely due to heterogeneity in

environmental factors, e.g., edaphic properties (Jusaitis 2005) or factors related to site topography like

solar exposure, slope aspect (Navarro-Cerrillo et al. 2014), sun-shelter effect from nearby vegetation

(Withers 1979) and presence of coarse woody material (Manning, Cunningham & Lindenmayer

2013). In this study for example, the unfenced areas that recorded the high mean survival were close

to the intact native vegetation. Additionally, lack of fence effect was also likely caused by failure to

stop large macropods from grazing, e.g., kangaroo or rabbits; incursions of herbivores into the fenced

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areas occurred several times over the course of the study having to impact the vegetation evenly on

both side of the fence. Kangaroos were readily able to jump the 90 cm tall fence (pers obs, Neave &

Tanton 1989).

The drying climate is likely to be a major driver of the overall low seedling survival (Hughes

2003; Brouwers et al. 2015; Dalmaris et al. 2015). Summer of 2013 –2014 was one of the driest on

record with no mid-summer rain (BOM 2015). Furthermore, future projections suggest that changes in

rainfall and temperature patterns will considerably increase the suitability of present southwestern

Australia habitats to non-native plant species (O'Donnell et al. 2012). Therefore, the success of

fencing or other restoration treatments may be further impeded.

5.5.2 Plot-scale treatments: the role of smoke, herbicide

application, and artificial shade

5.5.2.1 Smoke treatments

The experimental small plot-scale treatments investigated the potentially interactive effect on

both emergence and survival of the native perennials that emerged from the transferred topsoil. It was

hypothesized that plot-scale treatments would increase the survival of native perennials by stimulating

the prompt emergence of native species using a smoke water application, thus overcoming the

competition from onsite weeds. Faster emergence may provide a major advantage in competition with

fast-growing exotics (Öster et al. 2009).

Smoke treatments were expected to reduce seed limitation by imitating the natural cues that

overcome the dormancy of many species with soil-stored seed. Increasing the number of germinants

would also assist in overcoming the dispersal barrier and increase the chance for native seedlings to

establish. Moreover, the survival of MTE seedlings was reported to be time-dependent in that

breaking seed dormancy early in the growing season allows the young seedlings longer to grow under

optimal conditions and consequently increases their chance to survive the first summer drought

(Prévosto et al. 2015).

Smoke treatments, i.e., smoke water application, smoke water in conjunction with plastic

cover and control plastic cover only, had a positive but relatively small effect on native seedlings

survival when compared to shade effect. Vegetation clearing and bulk soil movement disturb the seed

bank during the process of topsoil transfer (Fowler 2012). This physical disturbance may imitate

smoke germination cues for the plant species in the soil seed bank (Roche, Koch & Dixon 1997;

Rokich et al. 2002). This phenomenon may explain in part why smoke water treatment did not

promote the positive emergence response followed by the faster establishment and expected higher

survival.

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5.5.2.2 Herbicide

Chemical spot-control of the emerging invasive species had a slight positive effect on survival

of native seedlings only in the first year after topsoil transfer but not over the course of the entire two-

year study. Invasive species typically show rapid germination and seedling establishment, which in

turn, reduces soil water availability for the slower germinating native species (Pérez-Fernández et al.

2000; Goldin & Brookhouse 2015). A very fast response of invasive species to water availability was

reported to impede the emergence and growth of native species that display more conservative growth

strategies (Pérez-Fernández et al. 2000). The initial aim to reduce weed densities in this study did not

have a persistent effect. Exotics displayed a high capability to re-establish quickly after die-back and

may require successive long-term management (Sheley & Krueger-Mangold 2003). In this study, one-

off chemical control treatment was applied owing to logistical limitations. One-off weed control did

not provide enough head-start time for natives to establish and increase the chance of surviving the

upcoming summer drought. One-time herbicide application did not prevent invasive alien species

from recolonizing the restoration sites that may suggest a high dispersal capability of the exotic

species in urban settings (DiTomaso 2000; Reid et al. 2009). Ripping treatment had a negative effect

on invasive annuals (See 2.6) but the rapidly growing invasive species re-established relatively

quickly and probably further impeded the establishment of the young native perennials (Fried et al.

2014).

5.5.2.3 Shade installation

Artificially shaded plots had substantially elevated mean percent survival (27% over year one

and 6.2% over two years). Shade installation was likely to reduce summer mortality of young

seedlings in Mediterranean-type regions by lessening the impacts of heat and drought (Rey Benayas

1998). The reduction in incident PAR also tends to lower the risk of photo-damage (Rey Benayas et

al. 2005) and reduce soil surface temperature (Jurado & Westoby 1992). A lower sun exposure

reduces potential evaporation and improves plant-soil-water relations (Rey Benayas 1998). Hence,

shade could provide suitable conditions for survival, i.e. a moister substrate. Artificial shade was a

successful restoration outcome for seedling survival in this study. Importantly, while shading may not

be practical over many hectares, the size of the treatment effect confirms the summer physical

conditions are likely the single most important biological filter acting on native seedlings (Stein,

Gerstner & Kreft 2014). However, due to a high level of vandalism recorded onsite and prohibitive

costs of installation the artificial shading is unlikely to be applied on a wider scale in restoration

works.

5.5.2.4 Heat

Application of heat treatment did initiate higher emergence densities (2.6) and subsequently a

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relatively high survival rate. Owing to the abrasive technique of the heat treatment application in this

study (scraping the top 5 cm of topsoil and applying ~80C heat pulse) it is believed that this treatment

very likely reduced the weedy seed bank that accumulated over the first year of the restoration works.

Reduction in competition from the invasive species allowed the emerging native cohort to establish

more successfully when compared with the remainder of the plot treatments.

The heat cue caused the dormant topsoil seed bank to germinate and the reduction in

competition allowed the germinants to establish (Keeley et al. 2012). When topsoil is initially spread

the conditions are similar to those that would be found after a severe disturbance (Santana, Baeza &

Maestre 2012). There is reduced competition for light and nutrients and some nutrients such as

nitrogen may be in a more available form than the topsoil donor site. Heat treatment will cue hard-

seeded species to germinate and may make some weed seeds unviable which will benefit native

woody slow-growing species if competition from faster growing weed species can be diminished

(Dixon, Roche & Pate 1995). Application of fire-related cues, e.g., heat (Cushwa, Martin & Miller

1968; Junttila 1973; Gashaw & Michelsen 2002), is likely to assist in the management of the topsoil

seed bank that is used in the restoration works. Application of heat is likely to contribute to activating

the topsoil seed bank for use in restoring native vegetation to a degraded site.

5.6 Conclusions

Restoration practitioners that use topsoil as a restoration tool are mainly focused on

rehabilitating the post-mine areas (Roche, Koch & Dixon 1997; Holmes 2001; Parrotta & Knowles

2001; Norman et al. 2006; Herath et al. 2009; Hall, Barton & Baskin 2010). The most efficient topsoil

handling requires reduced stockpiling time and topsoil spread should be undertaken in the dry season

(Rokich et al. 2000). Based on current knowledge this study examined a series of methods to use

topsoil seed bank in addressing environmental barriers to restoration of native vegetation to degraded

post-agricultural land.

Topsoil proved to be a valuable tool in overcoming the environmental filters present on

degraded sites. The seed bank contained within the transferred topsoil increased the diversity of

indigenous plant species remarkably, on previously weed-dominated post-agricultural land. Although

the final survival of native seedlings that emerged from the transferred topsoil was relatively low

(2.44 % over the two-year sampling period) it is close to the level of early stage seedlings survival

experienced in natural conditions (Stein, Gerstner & Kreft 2014). The highest final densities of native

perennials were recorded on unripped sites. The average end density of seedlings surviving over the

two-year sampling period, i.e., 0.6 m-2

, recorded on a combination of deep and unripped topsoil,

suggests that the lower percent survival was offset by the higher emergence in the first spring after

topsoil transfer. A relatively low survival recorded at the end of the survey may relate to a substantial

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effect of both summer droughts and/or thinning process at play (Kikuzawa 1999). The survival of the

same cohort through the first summer drought to the following growing season (one year after

emergence) oscillated between 0 % – 25 %. The high mortality in the second year after topsoil

transfer indicates the importance of the long-term monitoring of the biodiversity offset in an attempt

to assess the outcome of the related restoration project adequately.

Among the small plot-scale treatments installation of the artificial shade proved to be the most

beneficial. Due to high costs and vulnerability to theft implementation of a shading treatment away

from secure sites is not recommended for broadscale application though it may be quite relevant for

focal species. Additionally, the highest survival of invasive plant species was also recorded under the

shade (Figure 5-13). The additional treatment that may assist in stimulating another cohort of

seedlings to emerge in the case of high mortality in the first year is the heat treatment. The transferred

topsoil contains a large number of dormant propagules across its profile even after the first year it is

spread that if stimulated by an extra heat treatment may progress the project.

The absence of important structuring species, such as Banksia menziesii, B. attenuata,

Allocasuarina fraseriana and Eucalyptus todtiana, from the early restored assemblages, is expected as

they store their seeds in the canopy. Reinstatement of the structuring species requires additional

restoration effort if these species do not recruit from the transferred topsoil in the short term. Planting

seedlings (vs. direct seeding) of these species may be the best strategy to ensuring their establishment.

Longer-term efforts might be needed to control weeds while these key native species establish

(Kettenring & Adams 2011; Johnson et al. 2015). However, clearly, any benefit of weed control has

to be balanced by the risk of killing native species that have already established.

Even though glasshouse trials showed that the topsoil had the potential for returning a high

diversity of understorey plants (Fowler et al. 2015), field conditions and climate apply a very much

more severe filtering on establishment. Considerable attention needs to be paid to site preparation

before topsoil is transferred, many species (such as serotinous species) cannot be re-established from

just the topsoil and resources to support weed control need to be in place to assure the best outcome

possible. In this particular study as well as in many previous reports (Maron et al. 2012a; May, Hobbs

& Valentine 2017), it has been shown that the outcomes of the biodiversity offset approach incur

greater deal of improvement.

.

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5.7 Appendices

5.7.1 Three periods’ survival (%) under site-scale treatments

Table 5-9 Mean Survival Percentages of native perennials with 95% confidence intervals in three survival periods [spr2012.to.aut2013, spr2013.to.aut2014 and spr2012.to.aut2014] under three

site-scale treatments.

Topsoil Treatment

Filter Percent N SD SE 96% CI Survival.Time

Volume Dispersal 11.8 336 18.2 1 1.9 spr2012.to.aut2013

Volume Dispersal 2.5 432 7.6 0.4 0.7 spr2013.to.aut2014

Volume Dispersal 2.8 336 6 0.3 0.6 spr2012.to.aut2014




rip Abiotic 12.5 336 19.9 1.1 2.1 spr2012.to.aut2013





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Topsoil Treatment

Filter Percent N SD SE 96% CI Survival.Time


fence Biotic 11 480 16.9 0.8 1.5 spr2012.to.aut2013

fence Biotic 1.5 564 6 0.3 0.5 spr2013.to.aut2014

fence Biotic 2.4 480 4.8 0.2 0.4 spr2012.to.aut2014




5.7.2 Three periods’ survival (%) under plot-scale treatments

Table 5-10 Mean Survival Percentages of native seedlings with 95% confidence intervals in three survival periods [spr2012.to.aut2013, spr2013.to.aut2014 and spr2012.to.aut2014] under

seven plot-scale treatments.

Treatment Filter Percent N SD SE 95% CI Survival.Time

heat Dispersal 6.4 24 7 1.4 3 spr2013.to.aut2014

herbicide Biotic 9.7 48 17.2 2.5 5 spr2012.to.aut2013



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Treatment Filter Percent N SD SE 95% CI Survival.Time

plastic Abiotic 9.1 48 13.1 1.9 3.8 spr2012.to.aut2013



shade Abiotic 27.3 16 22.2 5.6 11.8 spr2012.to.aut2013

shade Abiotic 6.2 16 25 6.2 13.3 spr2013.to.aut2014

shade Abiotic 5.5 16 7.5 1.9 4 spr2012.to.aut2014

shade.semi Abiotic 10.6 32 10.7 1.9 3.8 spr2012.to.aut2013

shade.semi Abiotic 0.7 32 2.3 0.4 0.8 spr2013.to.aut2014

shade.semi Abiotic 3.4 32 5.7 1 2.1 spr2012.to.aut2014

smoke Dispersal 11.5 48 18 2.6 5.2 spr2012.to.aut2013

smoke Dispersal 2.1 48 6.4 0.9 1.9 spr2013.to.aut2014

smoke Dispersal 2.2 48 5 0.7 1.5 spr2012.to.aut2014

smoke.plastic Dispersal 9.5 48 14 2 4.1 spr2012.to.aut2013

smoke.plastic Dispersal 1.8 48 5.9 0.8 1.7 spr2013.to.aut2014

smoke.plastic Dispersal 1.9 48 3.2 0.5 0.9 spr2012.to.aut2014

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5.7.3 Survival Odds

Figure 5-10 Odds of survival of native perenials over two year period (spring 2012 – autumn 2014) in relation to recorded weed densities (Weed cover [1m-2] in spring 2013),site-scale filter

manipulation treatments (deep topsoil volume, topsoil ripping and fencing) and small-scale plot treatments(smoke, shade, herbicide). Model:

glmer(Survival~Transdepth+rip+fence+plot2+rip*fence+fence*Transdepth+rip*Transdepth+WeedDensity.spr13+(1|site/plot)+(1|specCode), family="binomial")

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5.7.4 Species frequencies (%) in autumn 2014

Table 5-11 Overall frequencies (%) of native plant species recorded for the two year period: from the first emergence event in spring 2012 to autumn 2014.

Genus Species Family Frequency (%) Survival Time

Gompholobium tomentosum Fabaceae 29.5 Two.Years

Hibbertia subvaginata Dilleniaceae 11.3 Two.Years

Laxmannia sessiliflora Asparagaceae 9.7 Two.Years

Laxmannia ramosa Asparagaceae 6.3 Two.Years

Jacksonia furcellata Fabaceae 5.7 Two.Years

Leucopogon conostephioides Ericaceae 5.1 Two.Years

Scholtzia involucrata Myrtaceae 4.2 Two.Years

Adenanthos cygnorum Proteaceae 3.6 Two.Years

Lyginia barbata Anarthriaceae 3.6 Two.Years

Lechenaultia floribunda Goodeniaceae 2.2 Two.Years

Acacia pulchella Fabaceae 2.0 Two.Years

Hibbertia huegelii Dilleniaceae 1.8 Two.Years

Hypocalymma angustifolium Myrtaceae 1.6 Two.Years

Arnocrinum preissii Hemerocallidaceae 1.4 Two.Years

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Lomandra sp. Asparagaceae 1.2 Two.Years

Conostylis aculeata Haemodoraceae 1.0 Two.Years

Leucopogon sp. Ericaceae 1.0 Two.Years

Lomandra sp. Asparagaceae 1.0 Two.Years

Bossiaea eriocarpa Fabaceae 0.8 Two.Years

Hypocalymma robustum Myrtaceae 0.8 Two.Years

Kunzea glabrescens Myrtaceae 0.8 Two.Years

Calytrix sp. Myrtaceae 0.6 Two.Years

Gastrolobium capitatum Fabaceae 0.6 Two.Years

Stirlingia latifolia Proteaceae 0.6 Two.Years

Burchardia congesta Colchicaceae 0.4 Two.Years

Dasypogon bromeliifolius Dasypogonaceae 0.4 Two.Years

Hibbertia hypericoides Dilleniaceae 0.4 Two.Years

Jacksonia sternbergiana Fabaceae 0.4 Two.Years

Patersonia occidentalis Iridaceae 0.4 Two.Years

Acacia huegelii Fabaceae 0.2 Two.Years

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Acacia stenoptera Fabaceae 0.2 Two.Years

Conostylis setigera Haemodoraceae 0.2 Two.Years

Daviesia triflora Fabaceae 0.2 Two.Years

Hemiandra pungens Lamiaceae 0.2 Two.Years

Hensmania turbinata Hemerocallidaceae 0.2 Two.Years

Laxmannia squarrosa Asparagaceae 0.2 Two.Years

Phlebocarya filifolia Haemodoraceae 0.2 Two.Years

Stylidium ciliatum Stylidiaceae 0.2 Two.Years

Acacia cyclops Fabaceae <0.1 Two.Years

Acacia saligna Fabaceae <0.1 Two.Years

Acacia willdenowiana Fabaceae <0.1 Two.Years

Allocasuarina humilis Casuarinaceae <0.1 Two.Years

Amphipogon turbinatus Poaceae <0.1 Two.Years

Anigozanthos humilis Haemodoraceae <0.1 Two.Years

Anigozanthos manglesii Haemodoraceae <0.1 Two.Years

Astroloma sp. Ericaceae <0.1 Two.Years

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Banksia attenuata Proteaceae <0.1 Two.Years

Banksia grandis Proteaceae <0.1 Two.Years

Banksia menziesii Proteaceae <0.1 Two.Years

Boronia ramosa Rutaceae <0.1 Two.Years

Calothamnus quadrifidus Myrtaceae <0.1 Two.Years

Cassytha racemosa Lauraceae <0.1 Two.Years

Cassytha sp. Lauraceae <0.1 Two.Years

Caustis dioica Cyperaceae <0.1 Two.Years

Chamaescilla corymbosa Asparagaceae <0.1 Two.Years

Conostylis juncea Haemodoraceae <0.1 Two.Years

Corynotheca micrantha Antheriaceae <0.1 Two.Years

Dampiera linearis Goodeniaceae <0.1 Two.Years

Daviesia divaricata Fabaceae <0.1 Two.Years

Desmocladus flexuosus Restionaceae <0.1 Two.Years

Dianella revoluta Hemerocallidaceae <0.1 Two.Years

Eremaea asterocarpa Myrtaceae <0.1 Two.Years

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Eremaea pauciflora Myrtaceae <0.1 Two.Years

Hardenbergia comptoniana Fabaceae <0.1 Two.Years

Hibbertia aurea Dilleniaceae <0.1 Two.Years

Hovea elliptica Fabaceae <0.1 Two.Years

Hovea trisperma Fabaceae <0.1 Two.Years

Kennedia prostrata Fabaceae <0.1 Two.Years

Lepidosperma drummondii Cyperaceae <0.1 Two.Years

unkGen. sp. Monocot <0.1 Two.Years

Lepidosperma squamatum Cyperaceae <0.1 Two.Years

Lepidosperma tenue Cyperaceae <0.1 Two.Years

Lobelia sp. Campanulaceae <0.1 Two.Years

Lomandra caespitosa Asparagaceae <0.1 Two.Years

Lomandra sp. Asparagaceae <0.1 Two.Years



Lysinema sp. Ericaceae <0.1 Two.Years

165


Melaleuca systena Myrtaceae <0.1 Two.Years

Melaleuca thymoides Myrtaceae <0.1 Two.Years

Mesomelaena pseudostygia Cyperaceae <0.1 Two.Years

Mirbelia sp. Fabaceae <0.1 Two.Years

unkGen. sp. Myrtaceae <0.1 Two.Years

Opercularia spermacocea Rubiaceae <0.1 Two.Years

Persoonia saccata Proteaceae <0.1 Two.Years

Petrophile linearis Proteaceae <0.1 Two.Years

Philotheca spicata Rutaceae <0.1 Two.Years

Pimelea sp. Thymelaeaceae <0.1 Two.Years

Platysace compressa Apiaceae <0.1 Two.Years

Pultenaea sp. Fabaceae <0.1 Two.Years

Rytidosperma sp. Poaceae <0.1 Two.Years

Sagina procumbens Caryophyllaceae <0.1 Two.Years

Schoenus curvifolius Cyperaceae <0.1 Two.Years

Schoenus sp. Cyperaceae <0.1 Two.Years

166


Stackhousia monogyna Celastraceae <0.1 Two.Years

Stenanthemum notiale Rhamnaceae <0.1 Two.Years

Stylidium brunonianum Stylidiaceae <0.1 Two.Years

Stylidium crossocephalum Stylidiaceae <0.1 Two.Years

Stylidium junceum Stylidiaceae <0.1 Two.Years

Stylidium piliferum Stylidiaceae <0.1 Two.Years

Stylidium repens Stylidiaceae <0.1 Two.Years

Synaphea spinulosa Proteaceae <0.1 Two.Years

Tetraria octandra Cyperaceae <0.1 Two.Years

Thysanotus asper Asparagaceae <0.1 Two.Years

Thysanotus sp. Asparagaceae <0.1 Two.Years

Thysanotus sparteus Asparagaceae <0.1 Two.Years

Tricoryne elatior Hemerocallidaceae <0.1 Two.Years

Xanthosia candida Apiaceae <0.1 Two.Years

Xanthosia huegelii Apiaceae <0.1 Two.Years

167

5.7.5 Soil resistance (FSW pilot study)

Figure 5-11 Pilot Study on the effect of ripping treatment on soil compaction: y-axis depicted soil compaction (MPa) on unripped and ripped (“in” inside furrow, “out” between the furrows) and

the x-axis shows the depth at which the resistance was measured (cm).

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5.7.6 Mean moisture content

Figure 5-12 Mean moisture content (%) over period of 2012-2014 on restoration study sites (within fence). Soil moisture was measured once a month across six study sites and combinations

of two treatments: topsoil volume (deep [10cm] and shallow [5cm]) and topsoil ripping (ripped and unripped).

169

5.7.7 Final densities across all treatments

Figure 5-13 The final densities of invasive perennials in the second year after topsoil transfer, autumn 2014.

171

Chapter 6 The effects of environmental

filter manipulations on plant

functional trait space in a

Banksia woodland restoration

project

6.1 Abstract

The re-establishment of plants on a degraded landscape is controlled by environmental

factors. These can be envisaged as a group of filters that select plant species that are able to

survive under the conditions on the site and exclude species that cannot. Understanding the way

the filters operate can help focus on the factors that have a strong control over the survival of

species in restoration projects.

Here, topsoil seed bank was exposed to a combination of environmental filter

manipulation treatments (abiotic, biotic and dispersal filters) to investigate the effect on the

functional diversity of native plants emerging on the restoration site. Topsoil was sourced from

under a cleared Mediterranean-type ecosystem and transferred onto the degraded sites to

facilitate the re-establishment of native Banksia woodland community.

Emergence and survival of plants were quantified in spring and autumn for two

consecutive years after topsoil transfer. The densities of emerging and surviving plant species

were positively correlated with species richness and plant functional richness. The topsoil seed

bank contained mostly small-seeded plant species that are typical of the species-rich understorey

of Banksia woodland. Canopy-stored large-seeded plants comprised only ~0.6% of seedlings

recorded on the restoration study site. The most successful plant functional type of the native

species pool that established in this restoration study was small-seeded, perennial shrub with a

maximum height of 1 m, non-N-fixer, and capable of resprouting.

The emerging plant communities comprised close-to-reference functional richness. The

diversity of functional plant types was evenly dispersed across the restoration site and was

negatively affected by summer drought and topsoil ripping (abiotic filter manipulation). More

research needs to focus on improving survival of the native seedlings in their early stages of

establishment to maintain functional diversity into the next phase of the successional trajectory.

A trait-based approach offers a means to move beyond species-specific assessments of

restoration practice while also providing valuable insight into the restoration of ecosystem

functions.

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6.2 Introduction

The science of restoration ecology, developed in the 1980s (Young, Petersen & Clary

2005), utilizes ecological theories to restore the biological richness and the ecological functions

to degraded sites. Ecological theories are tested in field conditions to provide science-based

guidelines for restoration ecologists and practitioners (Jackson & Hobbs 2009). Development of

ecological theories and their testing in the field can guide human activities in their attempt to

heal and restore the indigenous ecosystems. Currently, the planet is at a critical stage regarding

land-use and environmental changes that pose a threat of losing the information on how natural

world functions without human intervention. Understanding the functions and services provided

by ecosystems is critical in convincing society to reduce the pace of global biological diversity

loss.

Environmental filtering is one of the fundamental concepts in ecology that presents an

understanding of how plant assembly processes work in natural ecosystems following a major

disturbance event (Drake 1990). The theory of environmental filtering precedes the beginning of

restoration ecology science (Jordan III, Gilpin & Aber 1987; Keddy 1992) and is still being

developed to assist the recovery of degraded ecosystems globally (Fattorini & Halle 2004). The

filter model (Keddy 1992) describes the sequential sorting of species due to environmental

conditions; that is filters, present on site that ultimately determine the composition of species

and functions they perform in the newly assembled community. For example, species with

certain functional properties in relation to disturbance-associated adaptation, e.g., small and

soft-coated seeds are predicted to disperse and establish faster compared with the large and

hard-coated seeds if the acting environmental filter is only dispersal limitation (seed volume per

distance unit). Studies of how environmental filters shape plant community structure and

function can provide crucial information for planning restoration works. Knowledge of the

abiotic, biotic and dispersal filters can assist in choosing restoration techniques that are most

likely to be successful (Hulvey & Aigner 2014). Reinstatement of the reference ecosystem,

according to the environmental filtering concept, requires research to identify the critical

environmental filters existing onsite to undertake an informed set of restoration treatments. A

well-planned manipulation of the identified environmental filters might result in the desired

dispersion of the plant functional types that resembles the composition, structure and function of

the remnant reference ecosystem (Dıaz et al. 2003; Benayas et al. 2009). The most commonly

identified environmental filters in restoration ecology are:

Abiotic – e.g., temperature, precipitation or soil fertility that may result in different plant

species composition (Clements 1916 as cited in Krebs 1994; Andersen et al. 2015),

Biotic – interactions with other species present onsite, e.g., herbivory or competition

(Funk et al. 2008),

Dispersal limitation – environmental barriers that prevent propagules from establishing

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on the site, e.g., the wind (Coulson et al. 2001) or ex-arable soil legacy (Standish et al. 2007).

Environmental conditions (filters) often restrict the diversity of the plant species

assemblages. As a result of filtering processes, the most adaptable fraction of the local species

pool is capable of establishing. The resulting reduction in species richness may affect the

functional diversity of the newly established plant community (Lawson et al. 2015). The

environmental filters have a converging impact on the functional diversity that in turn may lead

to the establishment of functionally similar assemblages (Laliberté, Norton & Scott 2013).

Hence, altering the onsite environmental conditions by means of pre-mediated filter

manipulation treatment is envisaged to have a positive effect on diversity of plant functional

types (Stein, Gerstner & Kreft 2014). For example, manipulation of abiotic and dispersal filters

was reported to assist in reinstating the functions provided by the native plant communities

largely through soil nutrients immobilization and the addition of the seed mixes carrying high

functional diversity (Cleland, Larios & Suding 2013).

As reported in the previous studies, manipulating environmental filters, with the use of

the transferred topsoil, can alter the abundances of the plants emerging on degraded sites of the

local Mediterranean-type ecosystem (see Chapter 3). Multiple techniques tested how to target

the onsite filters to reach the regenerative potential of the transferred topsoil seed bank (Rokich

et al. 2000). The seed bank stored in the topsoil can serve as a reliable tool for suppression of

alien plants and reinstatement of native ecosystem restoration as shown in many locally-

oriented and post-mining projects, e.g., in Australia (Rokich et al. 2000), in Brazil (Parrotta &

Knowles 2001), in USA (Hall, Barton & Baskin 2010).

The previous chapters report the germination and survival of native and non-native

seedlings after experimental manipulations of the available species pool contained within the

transferred topsoil seed bank. In this chapter the results from the functional perspective, using

data for plant traits, are reported. The overall aim was to find the combination of treatments that

assists in establishing a community with the dispersion of traits and ecological functions

resembling the reference ecosystem of Banksia woodland. Indices measuring plant functional

dispersion and functional richness were used to describe patterns in communities that re-

established on the degraded sites. The key morphological and ecophysiological responses of

plants to their local environment as well as plants’ origin represented by suite of traits were

investigated (Mouillot et al. 2013). These traits were: growth form, longevity, height, nitrogen-

fixing capabilities, resprouting capacity, seed size and provenance. The main goal was to answer

the following question:

How does restoration of local Banksia woodland with the use of environmental filter

manipulation techniques affect the functional trait space in the restored ecosystem?

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6.3 Methods

6.3.1 Experimental design

The experiment was part of a broader restoration study. For a detailed description of

study settings refer to Chapter 1.

6.3.2 Vegetation surveys

Field plots were established to capture the emergence of all plant species in the springs

of 2012 (first growing season after topsoil placement) and 2013 (second growing season after

topsoil placement) as well as survival in autumn 2013 and 2014. The vegetation surveys were

conducted within all 2 m × 2 m plots situated within each of a total of twelve clusters of plots

(Figure 4-1) per study restoration site. The density of weed species was recorded four times

inside the 2 m × 2 m plot within 0.25 m × 0.25 m micro-plots due to the high level of

infestation. The sampled densities were standardised to 1 m2. The vegetation surveys in the

mature reference site were conducted on 100 m2 plots. The plant traits were compiled using

established trait data sets (FloraBase, WA Herbarium).

6.3.3 Statistical analysis

6.3.3.1 Rationale behind the chosen traits

Following seven categorical traits were selected to understand how plant functional

types assemble in the events of emergence and survival after topsoil transfer. The aim of

manipulating abiotic, biotic and dispersal filters was investigate how to restore the plant

functional composition and species richness that corresponded to the original reference site. The

selection of seven traits were studied:

Growth Form the change in relative abundance of species with different life

growth forms can carry information about how plant communities establish in

relation to the reference ecosystems (Capitanio & Carcaillet 2008; Buzzard et

al. 2015).

Longevity: similarly to growth form the change in relative abundance of

annuals versus perennials serves as evidence of the transition from the early

stage of disturbance to a more stable target stage.

Maximum height – is a trait that relates strongly to life history, seed set and

community structure (Westoby et al. 2002) and provides information about how

well they establish on restoration sites.

Nitrogen fixing – Ability to fix nitrogen from the atmosphere can play a major

role in facilitating plant establishment in initially disturbed conditions on the

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restoration sites.

Provenance – provides information about whether the plant species is native or

non-native.

Resprouters: the presence of native resprouting species is a good indicator of

ecosystem recovery as resprouters are relatively difficult to establish from seed

(Clarke et al. 2013).

Seed size: indicates the dispersal capabilities of the topsoil transfer technique as

small seeds are less prone to damage during the transfer process and are less

exposed to seed predation than large seeds (Maron et al. 2012a).

6.3.3.2 Functional richness and functional dispersion

The “FD” package was implemented to calculate the functional diversity indices of

functional richness and functional dispersion (Fdis and Fric in Laliberté & Legendre 2010). The

FD indices are computed using the PCA-like distance-based framework in the multidimensional

species and trait space (Figure 6-1). The species × species distance matrix was not Euclidean,

and thus, Lingoes correction was applied (Laliberté & Legendre 2010). Functional Dispersion

(FDis) was weighted by species abundances (Laliberté & Legendre 2010). FD is zero in

communities with only one functionally singular species in multivariate space that is very often

a case of survival data with very high mortality. The computation of the functional dispersion

can only be obtained from a matrix with non-zero values. Hence, empty rows were removed

from the species matrix (i.e.: 200 rows out of 3125). The trait and species matrices could be

multiplied only when the number and order of columns in the species matrix was equal to the

number of rows in the trait matrix (McCune, Grace & Urban 2002). Functional Richness index

(FRic) was measured as the number of unique trait combinations, not as the convex hull volume

as only categorical and ordinal traits were measured.

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Figure 6-1 Graphical representation of how functional dispersion (FDis) is computed in the multivariate trait

space. Y-axis and X-axis depict the potential trait values that can express continuous, ordinal, nominal, or

binary trait values. Star shape represents a centroid, and the size of the circle relates to the abundance of the

given species in the plant community. Credit: James Lawson.

To analyse the difference between remnant and restoration sites the FD indices (FDiv,

FRic) computed on binary data for all the subsequent seasons were compared. The ordinary

linear regression were implemented to compare functional diversity and richness at the remnant

and restoration sites. To analyse the effect of the filter manipulation treatments on FD indices,

hierarchical linear mixed effect model was implemented where sites and plots were incorporated

as random effects.

To select the top five dominant functional trait suits the community level weighted

means of trait values were computed (Harmon et al. 2004) and expressed their overall

frequencies in percentages. There were a total of 118 functionally unique plant functional types

recorded in this study. The choice of functional traits should eliminate any internal redundancy,

i.e., the correlation between the trait values (Villéger, Mason & Mouillot 2008). This process

assistd us to select the following functional traits: growth form, longevity, maximum height,

nitrogen fixation, provenance, resprouting capabilities and seed size.

6.3.3.3 Species composition

The difference in plant community compositions between the sites and treatments was

illustrated using the non-metric multidimensional scaling (NMDS) of changes (presence-

177

absence data) in plant compositions between the topsoil donor and topsoil recipient sites.

Package “vegan” available in R statistical software was used to perform NMDS (Oksanen et al.

2013). Rows with sums less than 5 in species matrix were removed and the spring and autumn

season were presented separately for clarity (Supplementary: springs Figure 6-6, autumns

Figure 6-7). Richness, Shannon-Wiener, and Simpson indices were used to illustrate the

correlation between the species richness and density in first (spring 2012, Figure 6-8) and the

second growing season (spring 2013, Figure 6-9).

6.4 Results

6.4.1 Effects of filter treatments on functional

dispersion and functional richness

Functional dispersion indices were mostly unaffected by the implemented

environmental filter manipulation treatments in the two growing seasons following the topsoil

transfer. In the first growing season, spring 2012, sites where topsoil was spread (dispersal

filter) at the low (shallow) volume recorded lower functional dispersion compared with the sites

where topsoil was spread at the high (deep) volume (t = 2.4, P = 0.02, Table 6-10). In the

second growing season, of spring 2013, two dispersal filter manipulation treatments i.e., heat (t

= 7.4, P < 0.001) and smoke (t = 2, P = 0.04) increased the functional dispersion on restoration

sites compared with the control plots (Table 6-1).

In the two respective autumn seasons following the two summer droughts after the

topsoil transfer functional dispersion indices were relatively even. In the first survival season,

autumn 2013, the most significant increase in functional dispersion was recorded under the

shade treatment (abiotic filter, t = 1.9, P < 0.06, Table 6-1). In the second survival season,

autumn 2014, topsoil ripping recorded a significant decrease in dispersion of plant functional

types compared to unripped sites( abiotic filter, t = 2.3, P = 0.03, Table 6-1).

Season represented the most significant effect on FDis values (Figure 6-2). Functional

richness was significantly lower during the last season of autumn 2013, when compared with

reference donor site (t= 12.96, P < 0.01, Table 6-3).

Table 6-1: Effect of filter manipulation treatments on functional dispersion weighted by species abundances.

Four separate seasons are shaded out and effects with P value < 0.05 are presented in bold font.

Filter [Topsoil

Treatment Term

Treatment

Scale EST SE t P Season


0.315 0.014 22.2 <0.001 spring2012

Dispersal [Volume]

shallow Site -0.031 0.013 -2.4 0.02 spring2012

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Filter [Topsoil

Treatment Term

Treatment


Abiotic [Rip] ripped Site -0.024 0.013 -1.9 0.06 spring2012

Biotic [Fence] open Site -0.024 0.015 -1.6 0.11 spring2012

Biotic [herbicide]

herbicide Plot 0.001 0.009 0.2 0.87 spring2012

Abiotic [plastic] plastic Plot -0.005 0.009 -0.6 0.56 spring2012

Dispersal [smoke]

smoke Plot -0.007 0.009 -0.8 0.45 spring2012


smoke.plastic Site -0.011 0.009 -1.3 0.20 spring2012

Abiotic:Dispersal ripped:open Site 0.028 0.017 1.7 0.10 spring2012

Dispersal:Biotic shallow:open Site 0.013 0.017 0.8 0.44 spring2012

Dispersal:Abiotic shallow:ripped Site 0.011 0.016 0.7 0.47 spring2012


0.221 0.012 18.5 <0.001 spring2013

Dispersal [Volume]

shallow Site 0.010 0.015 0.7 0.50 spring2013

Abiotic [Rip] ripped Site 0.018 0.015 1.2 0.24 spring2013


Dispersal [heat] heat plot 0.082 0.011 7.4 <0.001 spring2013

Biotic [herbicide]

herbicide plot 0.002 0.008 0.3 0.77 spring2013

Abiotic [plastic] plastic plot 0.000 0.008 0.0 0.97 spring2013

Dispersal [smoke]

smoke plot 0.016 0.008 2.0 0.04 spring2013


smoke.plastic plot 0.012 0.008 1.5 0.14 spring2013



Dispersal:Abiotic shallow:ripped Site -0.024 0.019 -1.3 0.20 spring2013


0.226 0.026 8.8 <0.001 autumn2013

Dispersal shallow Site 0.013 0.023 0.6 0.58 autumn2013

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Filter [Topsoil

Treatment Term

Treatment


[Volume]

Abiotic [Rip] ripped Site -0.014 0.023 -0.6 0.55 autumn2013

Biotic [Fence] open Site -0.003 0.027 -0.1 0.92 autumn2013

Dispersal [heat] heat plot 0.024 0.022 1.1 0.27 autumn2013

Biotic [herbicide]

herbicide plot -0.018 0.016 -1.1 0.26 autumn2013

Abiotic [plastic] plastic plot 0.012 0.016 0.7 0.47 autumn2013

Abiotic [shade] shade plot 0.052 0.028 1.9 0.06 autumn2013

Dispersal [smoke]

smoke plot -0.012 0.016 -0.7 0.46 autumn2013


smoke.plastic plot -0.001 0.016 -0.1 0.93 autumn2013

Abiotic:Dispersal ripped:open Site -0.041 0.031 -1.3 0.19 autumn2013

Dispersal:Biotic shallow:open Site -0.011 0.031 -0.4 0.72 autumn2013

Dispersal:Abiotic shallow:ripped Site 0.003 0.029 0.1 0.91 autumn2013


0.106 0.020 5.3 <0.001 autumn2014

Dispersal [Volume]

shallow Site -0.006 0.024 -0.2 0.82 autumn2014

Abiotic [Rip] ripped Site -0.055 0.024 -2.3 0.03 autumn2014


Dispersal [heat] heat plot -0.008 0.027 -0.3 0.78 autumn2014

Biotic [herbicide]

herbicide plot 0.005 0.020 0.3 0.80 autumn2014



Dispersal [smoke]

smoke plot -0.005 0.021 -0.2 0.82 autumn2014


smoke.plastic plot -0.006 0.020 -0.3 0.75 autumn2014

Abiotic:Dispersal ripped:open Site 0.057 0.033 1.7 0.09 autumn2014

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Filter [Topsoil

Treatment Term

Treatment



Dispersal:Abiotic shallow:ripped Site -0.002 0.031 -0.1 0.95 autumn2014

† Model: lmer(FDis~Volume+Rip+Fence+ Rip*Fence + Fence*Volme + Rip*Volume +plot.scale.treatment +(1|site/plot), data=spr12|spr13|aut13|aut14)

Similar to functional dispersion, manipulation of the environmental filters showed little

effect on functional richness in the first and second growing season after the topsoil transfer.

Functional richness was significantly higher in unripped sties (abiotic filter) as compared with

the ripped site (t =7.5, P < 0.01, Table 6-2) in the first growing season, of spring 2012. In the

second growing season, of spring 2013, manipulation of the dispersal filter with use of heat

treatment increased significantly functional richness compared with the controls (t = 2, P = 0.04,

Table 6-2).

During the two autumn seasons following the topsoil transfer functional richness was

positively affected by shade treatment (abiotic filter). The recorded functional richness was

significantly higher under the shade treatment in both autumn seasons when compared with

controls (in autumn 2013: t = 2.9, P < 0.01, and in autumn 2014: t = 2.3, P = 0.02, Table 6-2).

Manipulation of another abiotic filter by means of soil ripping decreased the FRic indices

significantly in both autumn seasons (in autumn 2013: t = 3.4, P < 0.01, and in autumn 2014: t =

3.3, P < 0.01, Table 6-2) when compared with unripped sites.

Similarly to functional dispersion seasons represented the most significant effect on

FRic values (Figure 6-2). The effect of the seasons on functional richness was higher compared

with the remaining treatments and their combinations.

Table 6-2: Effect of filter manipulation treatments on functional richness (FRic). Four survey seasons are

shaded out and effects with P value < 0.05 are presented in bold font.

Filter [Topsoil Treatment

Term Treatment



24.5 1.5 16.8 <0.01 spring2012

Dispersal [Volume]


Abiotic [Rip] ripped Site -10.3 1.4 -7.5 <0.01 spring2012

Biotic [Fence] open Site 0.0 1.6 0.0 0.99 spring2012

Biotic [herbicide] herbicide Plot -0.2 0.7 -0.3 0.77 spring2012

Abiotic [plastic] plastic Plot 0.0 0.7 0.1 0.95 spring2012

Dispersal [smoke] smoke Plot -0.3 0.7 -0.4 0.66 spring2012

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Term Treatment



smoke.plastic Site -0.8 0.7 -1.1 0.27 spring2012


Dispersal:Biotic shallow:open Site -1.9 1.9 -1.0 0.31 spring2012



19.7 1.6 12.5 <0.01 spring2013

Dispersal [Volume]


Abiotic [Rip] ripped Site -2.8 1.4 -1.9 0.06 spring2013


Dispersal [heat] heat plot 2.1 1.0 2.0 0.04 spring2013

Biotic [herbicide] herbicide plot -0.9 0.8 -1.2 0.25 spring2013

Abiotic [plastic] plastic plot -0.1 0.8 -0.1 0.89 spring2013

Dispersal [smoke] smoke plot -0.3 0.8 -0.4 0.70 spring2013


smoke.plastic plot -0.8 0.8 -1.1 0.27 spring2013





5.8 0.7 8.6 <0.01 autumn2013

Dispersal [Volume]


Abiotic [Rip] ripped Site -2.1 0.6 -3.4 <0.01 autumn2013

Biotic [Fence] open Site 0.5 0.7 0.7 0.49 autumn2013


Biotic [herbicide] herbicide plot 0.3 0.4 0.9 0.36 autumn2013


Abiotic [shade] shade plot 1.8 0.6 2.9 <0.01 autumn2013

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Term Treatment


Dispersal [smoke] smoke plot 0.2 0.4 0.6 0.52 autumn2013


smoke.plastic plot 0.2 0.4 0.5 0.63 autumn2013

Abiotic:Dispersal ripped:open Site -0.6 0.8 -0.7 0.49 autumn2013




2.7 0.3 8.7 <0.01 autumn2014

Dispersal [Volume]


Abiotic [Rip] ripped Site -1.3 0.4 -3.3 <0.01 autumn2014



Biotic [herbicide] herbicide plot 0.2 0.3 0.7 0.49 autumn2014



Dispersal [smoke] smoke plot 0.2 0.3 0.6 0.52 autumn2014


smoke.plastic plot 0.2 0.3 0.8 0.42 autumn2014

Abiotic:Dispersal ripped:open Site 0.9 0.5 1.6 0.13 autumn2014



† Model: lmer(FRic~Volume+Rip+Fence+ Rip*Fence + Fence*Volme + Rip*Volume +plot.scale.treatment +(1|site/plot), data=spr12|spr13|aut13|aut14)

The plant assemblages that dominated the study sites in the second vegetation survey

were small-seeded non-native perennial grasses and small-seeded perennial native woody

shrubs, both non-nitrogen fixers with capabilities to resprout (Table 6-4).

6.4.2 Functional space of the reference and

restoration sites

Functional dispersion indices (FDis, Figure 6-2) were highly affected by the seasons and

183

specifically a significantly negative effect of the last autumn survey season (t= 6.1, P < 0.001)

where topsoil recipient site showed a decrease in FDis indices. The only significantly positive

effect on FDis was recorded under plot-scale heat treatment (Table 6-1, t= 3.36, P < 0.001).

Figure 6-2 Functional dispersion of traits measured in the reference sites and topsoil recipient sites: Ref.Spr –

Reference Site in spring 2011, Ref.Aut = Reference site in autumn 2011, Top.Spr.I – Topsoil site in spring 2012,

Top.Spr.II – Topsoil site in spring 2013, Top.Aut.I – Topsoil site in autumn 201, Top.Aut.II – Topsoil site in

autumn 2014. The topsoil control sites include the plots (4 m-2) situated on deep unripped restoration study

sites only (the most successful), and reference control plots (100 m-2) were located in the remnant bushland

where the topsoil was sourced following land clearing.

The patterns of variation in functional richness (FRic, Figure 6-3) differed significantly

between the remnant donor sites and the topsoil recipient sites in the following autumn season

(t= 12.96, P< 0.001) but not between the respective spring seasons at the restoration sites

(t=2.43, P = 0.02, Table 6-3). The ripping treatment (abiotic filter) had a significantly negative

effect on functional richness. Functional richness was significantly higher in unripped sties 6.48

±0.74 (abiotic filter) as compared with the ripped site 3.36 ± 0.83 (t=4.21, P < 0.001, Table 6-2)

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Figure 6-3 Functional richness of the reference sites and topsoil recipient sites: Ref.Spr – Reference Site in

spring 2011, Ref.Aut = Reference site in autumn 2011, Top.Spr.I – Topsoil site in spring 2012, Top.Spr.II –

Topsoil site in spring 2013, Top.Aut.I – Topsoil site in autumn 2013, Top.Aut.II – Topsoil site in autumn 2014.

The topsoil control sites include the plots (4 m2) situated on deep unripped restoration study sites, and

reference control plots (100 m2) were located in the remnant bushland where the topsoil was stripped following

land clearing.

6.5 Discussion

6.5.1 Filters and functional richness

Functional richness decreased significantly under the abiotic filter manipulation of soil

ripping, with the most negative effect recorded in the first spring after topsoil transfer. The

significant difference in functional richness between ripped and unripped topsoil treatments is

likely to have resulted from the exposure of the native topsoil seed bank to a range of stressful

factors related to its transfer, dispersal, and emergence in the new conditions. None of the

additional filter manipulation treatments nor their combinations had as significant a negative

effect on plant functional and species richness as topsoil ripping. This abiotic filter manipulation

treatment altered the abiotic conditions and acted most likely as an additional disturbance factor.

The additional stress factor resulted in a decrease of the emerging plant cohort density and

subsequently reduced overall species richness and diversity of plant functional types. The

combination of soil ripping and drought could make the ground desiccate more abruptly given a

higher surface exposure with the furrows and ridges putting additional pressure on plant water

uptake (Lamont, Downes & Fox 1977). Conversely, as studies on the restoration of the similar

ecosystem in the post mine settings show, the process of ripping improves soil porosity, creating

a friable rooting zone (Koch 2007a), that reduces soil compaction, increases water infiltration

that enhances seedling establishment (Ruthrof 2012). Clearly, in this case, the disadvantages of

ripping outweighed the benefits. The resulting decrease in FRic as well as in plant densities

emerging under the ripping treatment may also suggest (see 2.6) improper technique. Heavy

vehicle traffic or other onsite processes, e.g., cementation (Prévosto et al. 2015) are very likely

to induce highly compacted soil layers below the 300 mm ripping line that was applied in this

study. The presence of the detected cemented layer might further hinder the growth of the

juvenile root system (Prévosto et al. 2015). Future restoration techniques that utilize topsoil

seed bank may need to consider application of soil ripping prior topsoil spread and address

compaction gradients in soil profile.

6.5.2 Filters and functional dispersion

Functional dispersion of seedlings emerging from the transferred topsoil showed no

significant differences between the sites-scale nor plot-scale treatment combinations during the

four respective survey seasons, with the exception of the heat treatment. Application of heat

treatment, in the second growing season, significantly increased the dispersion of the plant

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functional types recorded on the study restoration site. It is believed that heat treatment imitated

fire-related cues to overcome a major physiological filter that retains the propagules in the

prolonged dormant phase. Many SWA plant species, especially those characterized by hard-

seededness, e.g., Fabaceae (Brown, Enright & Miller 2003), are responsive to heat treatment.

Heating the soil to 80 – 100°C degrees has been shown to promote germination (Auld &

O'Connell 1991; Wills & Read 2002). A study on the effect of both smoke and heat on

eucalyptus woodland soil seed bank showed that heat treatment might have complimentary

effect (Enright et al. 1997). This phenomenon is also well demonstrated in a study on species

from fire-prone vegetation in other regions (Thomas, Morris & Auld 2003). In this study, heat

treatment was accompanied with scraping the top half layer of the transferred topsoil to activate

the propagules that were believed unable to emerge. Most of the seed bank in the study came

from small-seeded plants that are more likely to persist buried in soil (Bakker et al. 1996;

Dobson, Bradshaw & Baker 1997; Sheley & Krueger-Mangold 2003) and form most of the soil-

stored seed bank for Mediterranean-type plant species (Rokich et al. 2000). Soil moving could

work as a further disturbance factor that stimulated a diverse range of plant functional types to

emerge but due to short duration of the vegetation surveys information on two-year survival of

plants that emerged under the heat treatment is not available.

The resulting even distribution of functional dispersion between the remainder of the

environmental filter manipulation treatments in respective seasons suggests a primary

association of plant emergence and establishment with the environmental conditions outside the

scale of the site. A significant seasonal change in FDis indices was observed. The highest

increase in functional dispersion occurred during the two emergence surveys, year one and two

since topsoil transfer. The favourable winter conditions led to an increase in plant species

abundances across all topsoil treatments that in turn resulted in the higher functional dispersion.

Conversely, the highest decrease in the functional dispersion was recorded in surveys that

followed both summer droughts. Summer seasons had a converging impact on the plant

functional types surveyed at the restoration site. A similar strong convergence of plant

functional types is often associated with high disturbance, e.g., frequent fire, and low

productivity habitats, e.g., poor soils (Weiher & Keddy 1995). Hence, seasonal conditions can

be regarded as an additional environmental filter that demonstrated a stronger effect on local

plant functional diversity compared to applied treatments in this study. Dispersion of functional

types recorded in other studies also showed a tendency to be minimally affected by onsite

gradients as reported for onsite productivity (Laliberté, Norton & Scott 2013), elevation (Mori

et al. 2015) or grazing intensity (Guo et al. 2016).

The most dominant plant functional type that persisted on topsoil restoration sites (as

measured by community-level weighted means of trait values) occupied the functional space

that is typical for invasive species: perennial, small-seeded and grass-type resprouter with a

maximum height of 0.7 m and comprised 24.6 % of surveyed communities. The second most

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abundant trait suit recorded at the same time (during the last vegetation survey carried out two

years after the topsoil transfer) was: small-seeded, perennial shrubs with a maximum height of 1

m that were part of native functional space that overlapped with invasive species and dominated

7.3 % of recorded plant communities. The restoration sites two years after topsoil transfer were

dominated by twelve out of a total of 118 identified plant functional types that comprised 64%

of the recorded vegetation surveys. Small seeds and low maximum height characterized the two

most abundant plant functional types in this study. Small seed size is strongly correlated with

the fast growth rate are in the constellation of plant traits (Westoby et al. 2002). Small-seeded

plants display a higher effectiveness in their reproductive effort (Raphael et al. 2015) that in

turn may correlate with relatively higher accumulation of small propagules in the topsoil seed

bank as recorded in this study. The relatively high success of small-seeded non-natives on

restoration site is consistent with this suggestion. Small-seeded native species, however, were

not as successful as the small-seeded non-natives indicating that sieving out the exotic species

from entering the restoration site, with the use of filter manipulation techniques, was

challenging. This may be due in part to human-led land-use legacies, e.g., accumulation of the

weed seed bank during agricultural land-use and heavy traffic, which tend to produce a strong

environmental gradient that re-structure the local plant assemblages towards disturbance-

tolerant types (Mendes et al. 2015; Smith et al. 2016).

Compositionally, the topsoil plant assemblage comprised 253 plant species (171

natives). There were significant differences in the composition of the emerging and surviving

plant assemblages. The changes in composition across multiple site locations were stochastic in

character rather than reflection of a treatment effect (Vellend et al. 2014). Furthermore, three

common species of with highly variable densities were driving the compositional differences

between the surveyed communities. Plant taxa abundances display typically higher rate of

variation compared to plant functional types as shown in previous studies on level of

redundancy across a range of the environmental filters and gradients (Mori et al. 2015).

Diversity indices (Shannon-Wiener and Simpson) were positively correlated with plant

species densities in this study which may indicate that the seed bank contained within the

transferred topsoil was homogenously spread onto the restoration site as multiple topsoil layers

mix during the transfer (Fowler et al. 2015).

6.5.3 Remnant and restoration site

The functional richness of plant assemblages emerging from the transferred topsoil was

marginally lower than that of the remnant ecosystem in this study. Relatively high functional

richness recorded in both growing seasons at the restoration site indicates that the transferred

topsoil carries an extensive native seed bank. The most important trait that contributed to the

higher functional richness in remnant stands was the height of the plant species recorded

therein. Mature stands accommodated a higher number of species and a structurally wider

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variety of plant functional types when compared with study restoration sites. Thus, functional

richness indices were positively influenced by species richness as recorded in other studies as

well (Laliberte et al 2010).

The plant species that emerged from the seed bank contained within the transferred

topsoil reflected most of the vegetation in the remnant ecosystem but virtually no representation

of the large-seeded trees that form canopy layer. However, high densities of native seedlings

during the emergence season produced an overwhelmingly wider distribution of plant functional

types compared with the remnant ecosystem (FDis). A decrease in functional dispersion

following the summer drought mortality was steeper on topsoil restoration sites when compared

with the remnant Banksia woodland site. Moreover, tree species typical for the Banksia

woodland ecosystem were absent on the transferred topsoil sites. These tree species contribute

to vegetation structure and are characterized by large seeds contained in serotinous fruits that

are unlikely to be represented in the soil bank (Enright et al. 2007). Lack of canopy, thus lack of

positive shading effect on emerging seedlings, was likely to lead to a rapid decrease in

functional dispersion indices recorded in autumn seasons owing to seedlings mortality.

Functional groups, among the perennial plants, that were most probable to die during the

summer drought were herbaceous, small-seeded non-N-fixers and non-resprouters. The

mortality on the restoration sites was higher compared with the native pre-cleared ecosystem

(unpubl. data). Survival rates of native plants were very low with mortality reaching on average

98.4% of emergence levels; similarly, 98.6% of invasive species died (Chapter 1).

6.6 Conclusions

Dry summer conditions had the strongest filtering effect on native plant species when

related to the effect size of the experimentally applied onsite filter manipulation treatments.

Additionally, the second summer drought ensued higher mortality compared to the first summer

season. As a result, both autumn surveys recorded significantly lower diversity of plant

functional types as compared with the remnant (reference) ecosystem. Topsoil transfer

represents a high potential for future restoration projects in Mediterranean-type ecosystem

owing to large native seed bank contained therein. Higher priority should be devoted to

overcoming the adverse effects of dry climatic conditions and superior dispersal capabilities of

exotic colonist plants to increase the utility of native topsoil transfer technology in sustaining

functionally diverse plant communities. All large-seeded native plants were lost and maximum

height trait space was reduced by 46% over the two year period after emergence.

Successful restoration requires a considerable multi-scale information, both temporal

and spatial information, on how environmental conditions (filters) are linked to ecosystem

functioning (Shackelford et al. 2013b). Further investigations are needed into how manipulation

of these conditions can maintain a trajectory towards a biodiverse and resilient native ecosystem

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(White & Jentsch 2001). Some rare species may increase in abundance followed by application

of an adequate disturbance factor (Whitford, Nielson & de Soyza 2001; Walker et al. 2004;

Shackelford et al. 2013b) but if misapplied it may also lead to loss of diversity (Beecham,

Lacey & Durell 2009). Gathering comprehensive experimental and observational data to capture

the exact mechanisms of habitat filtering is crucial to advance the science of

restoration ecology (Kraft et al. 2015). Summarizing the data by traits rather than species

increases the generality of the results and so the application to restoration sites elsewhere in the

world.

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6.7 Appendices

6.7.1 Effects of six topsoil transfer stages on functional indices

Table 6-3: Overall effects of six topsoil transfer stages, from donors remnant site in autumn 2012 to recipient restoration site in autumn 2014, on functional dispersion (FDis) and functional

richness (FRic, in grey shade) indices.

Stage Season EST SE t P Index

Remnant Site autumn I Autumn2012 0.29 0.02 12.81 0.001 FDis

Restoration Site Autumn II Autumn2013 0.03 0.02 1.29 0.20 FDis

Restoration Site Autumn III Autumn2014 -0.14 0.02 -6.10 0.001 FDis

Remnant Site Spring I Spring2011 0.04 0.03 1.32 0.19 FDis

Restoration Site Spring II Spring2012 0.10 0.02 4.38 0.001 FDis

Restoration Site Spring III Spring2013 0.09 0.02 3.83 0.001 FDis

Remnant Site Autumn I Autumn2012 23.25 1.50 15.47 0.001 FRic

Restoration Site Autumn II Autumn2013 -17.07 1.54 -11.07 0.001 FRic

Restoration Site Autumn III Autumn2014 -20.18 1.56 -12.96 0.001 FRic

Remnant Site Spring I Spring2011 6.42 2.13 3.02 0.001 FRic

Restoration Site Spring II Spring2012 0.96 1.56 0.62 0.54 FRic

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Stage Season EST SE t P Index

Restoration Site Spring III Spring2013 -3.75 1.54 -2.43 0.02 FRic

† Model: lm(FDIndex ~ Stage., data=deep.unripped.topsoil)

6.7.2 Dominant trait suites in autumn 2014

Table 6-4: Dominant trait suites across three site-scale filter manipulation treatments in the last survey season [autumn 2014, n=573].

Growth Category

Longevity Max Height [m]

Nfixer Provenance Resprouter Seed Size

Filter Term %

grass perennial 0.7 nonNfixer invasive yes small Dispersal deep 12.04

woody perennial 1. nonNfixer native yes small Dispersal deep 6.46

woody perennial 1. nonNfixer native no medium Dispersal deep 3.14

woody perennial 1. nonNfixer native no small Dispersal deep 2.79

woody perennial 1.5 nonNfixer native yes small Dispersal deep 2.79

grass perennial 0.7 nonNfixer invasive yes small Dispersal shallow 12.57

woody perennial 1. nonNfixer native yes small Dispersal shallow 0.87

woody perennial 1. nonNfixer native no medium Dispersal shallow 1.05

woody perennial 1. nonNfixer native no small Dispersal shallow 1.92

woody perennial 1.5 nonNfixer native yes small Dispersal shallow 1.22

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Growth Category



Filter Term %

grass perennial 0.7 nonNfixer invasive yes small Abiotic ripped 15.18

woody perennial 1. nonNfixer native no medium Abiotic ripped 2.44

woody perennial 1. Nfixer native no small Abiotic ripped 2.09

woody perennial 1. nonNfixer native no small Abiotic ripped 2.09

woody perennial 1. nonNfixer native yes small Abiotic ripped 1.75

grass perennial 0.7 nonNfixer invasive yes small Abiotic unripped 9.42

woody perennial 1. nonNfixer native yes small Abiotic unripped 5.58

herb perennial 0.5 nonNfixer native yes small Abiotic unripped 2.97

woody perennial 1.5 nonNfixer native yes small Abiotic unripped 2.79

woody perennial 1. nonNfixer native no small Abiotic unripped 2.62

grass perennial 0.7 nonNfixer invasive yes small Biotic fenced 20.24

woody perennial 1. nonNfixer native yes small Biotic fenced 5.93

woody perennial 1. nonNfixer native no small Biotic fenced 2.97

herb perennial 0.5 nonNfixer native yes small Biotic fenced 2.97

woody perennial 1. Nfixer native no small Biotic fenced 2.79

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Growth Category



Filter Term %

grass perennial 0.7 nonNfixer invasive yes small Biotic open 4.36

woody perennial 1.5 nonNfixer native yes small Biotic open 2.79

woody perennial 1. nonNfixer native no small Biotic open 1.75

woody perennial 1. nonNfixer native no medium Biotic open 1.57

herb perennial 0.3 nonNfixer native no small Biotic open 1.57

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6.7.3 Mean heights of plants recorded in the last vegetation survey (autumn 2014)

Figure 6-4 Distribution of mean (±SE) plant heights recorded in the second year after topsoil transfer (autumn 2014) across all topsoil treatments. The plant heights bars are presented in

ascending order: heat (n = 102), open (n = 291), shallow (n = 123), ripped (n = 125), unripped (n = 409), deep (n = 411), herbicide (n = 59), smoke.plastic (n = 83), smoke (n = 58), fenced (n = 243),

plastic (n= 31), shade (n = 34).

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6.7.4 NMDS ordination of plant composition in the first and the last vegetation survey season

Figure 6-5 NMDS ordination (stress = 6.88%) of plant topsoil communities in spring 2012 (first survey after topsoil transfer) and autumn 2014 (last survey after topsoil transfer.). The figure

presents vegetation data from deep unripped treatment plots that represented the most successful treatment combination in terms of native species densities. Changes in the assemblages

over a period of 2 years were significant (ANOSIM, R = 0.5, P = 0.001).

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6.7.5 NMDS ordination of plant compositions during three consecutive spring seasons

Figure 6-6 NMDS ordination (stress = 1.52%) of plant topsoil communities in spring seasons at reference site (topsoil donor - Ref.spr2011) and offset sites (topsoil recipient - Off.spr2012 and

Off.spr2013). The figure presents vegetation data from deep unripped treatment plots that represented the most successful treatment combination in terms of native species densities.

Changes in the assemblages over a period of two years were statistically significant (ANOSIM, R = 0.001 , P = 0.001).

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6.7.6 NMDS ordination of plant compositions during three autumn seasons

Figure 6-7 NMDS ordination (stress = 0.43%) of plant topsoil communities in spring seasons at reference site (topsoil donor - Ref.spr2011) and offset sites (topsoil recipient - Off.spr2012 and

Off.spr2013). The figure presents vegetation data from deep unripped treatment plots that represented the most successful treatment combination in terms of native species densities.

Changes in the assemblages over a period of two years were statistically significant (ANOSIM, R = 0.04 , P = 0.001).

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6.7.7 Correlation between density and diversity indices in spring 2012

Figure 6-8 Correlation between density and three diversity indices: Shannon-Wiener, Simpson, and Richness in the first growing season since topsoil transfer (spring 2012). Pielou’s evenness

index also included.

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6.7.8 Correlation between density and diversity indices in spring 2013

Figure 6-9 Correlation between density and three diversity indices: Shannon-Wiener, Simpson, and Richness in the second growing season since topsoil transfer (spring 2013). Pielou’s

evenness index also included.

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Chapter 7 Discussion and conclusions

7.1 Introduction

The most significant environmental barrier present on restoration site was the propagule

limitation. Manipulation of the limited dispersal with the use of the high volume of the

transferable topsoil seed bank resulted in the highest mean densities of native perennials of 17.4

± 1.4 (SE) m-2

in the first year. Moreover, an abundant cohort of native seedlings emerged in the

second year with mean densities of 5.9 ± 0.3 (SE) m-2

.

The topsoil treatments did not affect the survival rate of emerging native seedlings. The

average seedling survival over the 2-year sampling period was low, i.e., 2.44% ± 0.2 (SE). The

highest end densities were recorded on the sites where topsoil was applied at the highest

volume, i.e., 0.36 ± 0.05 m-2

. Herbivore exclosures showed no effect on emergence nor survival.

In relation to functional traits, species emerging from the topsoil seed bank were

disproportionately non-sprouting (70% in both emergence events). Nitrogen-fixers comprised

50% of total native flora richness in the first year after topsoil transfer and decreased

significantly to 20% in the second year. A common trait within intact communities, canopy seed

storage was, as anticipated, extremely rare in the transferred topsoil (~0.6%). The plant

assemblages at year two comprised mostly of non-native perennial grasses and perennial, small-

seeded native woody shrubs.

This study built on knowledge acquired from restoration works that collect, store and

move topsoil with its native seed bank contained therein to rehabilitate post-mine landscape.

The main focus of this study was on how to use the transferable topsoil seed bank salvaged from

cleared Banksia woodland ecosystem (Figure 7-1) to overcome environmental filters present on

degraded, post-agricultural land.

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Figure 7-1 Image of Banksia woodland stand prior clearing in 2012, Jandakot Airport, Western Australia.

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7.2 Filtering processes: emergence

Although the process of topsoil transfer negatively affected the viability of the

propagules contained therein (Fowler et al. 2015) the resulted emergence of native seedlings

onsite was still abundant. The densities of the native seedlings that emerged from the topsoil

were similar to the densities recorded in the reference ecosystem (Roche, Dixon & Pate 1998).

Use of the topsoil to manipulate the three main environmental filters present on degraded study

site (site-scale treatments in fully factorial design) resulted in variable densities in the first year

with no carry-on treatment effect on emergence in the second year with an exception of topsoil

volume. The volume of the transferred topsoil (dispersal filter) was positively correlated with

densities of emerging seedlings, with deep topsoil volume producing more germinants

compared to shallow topsoil. Topsoil ripping (abiotic filter) had a negative effect on emergence

while herbivore exclosures (biotic filter) recorded no significant effect (Figure 7-3).

Manipulation of the abiotic filter was carried out in two ways: 1) reduction of soil

compaction (site-scale), and 2) reduction of soil evaporation (plot-scale). Reduction of the soil

compaction by means of deep ripping (30 cm) did affect seedling emergence negatively in the

first year when compared to unripped sites. Topsoil ripping reduced the densities of both native

and non-native seedling significantly. Ripping treatment did the opposite of what was predicted.

The previous studies on Banksia woodland restoration (Comino, Miller & Enright 2004; Maher

2009; Mounsey 2014) suggested that compacted topsoil may constitute a considerable

environmental filter (Szota et al. 2007). Hence, the disruption of the highly compacted substrate

could be critical for the seedling emergence. Soil ripping can decrease the soil penetration

resistance (Mounsey 2014) and allow for faster radicle growth (Szota et al. 2007; TERG 2012).

The most plausible explanation for the opposite effect of soil ripping to the prediction is

that the ripping treatment could have been performed too late in relation to an earlier than the

usual onset of the winter rain following the topsoil transfer (pers. obs.). Early rains could

stimulate the earlier emergence of all seedlings including native perennials (Pérez-Fernández et

al. 2000; Raphael et al. 2015) as the sudden increase in soil moisture could stimulate the earlier

release of dormancy in topsoil seed bank as well (Merritt et al. 2007).

Reduction of the ground evaporation with temporary use of plastic cover did not affect

emergence densities. The expected increase in gaseous stimulants to the germination, e.g.,

ethylene (Froend et al. 2013) was not effective. A trial to alter the concentration of the gases

under the plastic cover did not stimulate higher emergence densities compared to controls. The

stress related to the topsoil transfer could act as a strong stimulant that mimicked the natural

germination cues related to naturally occurring disturbance factors.

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Figure 7-2 Image of restoration site (ForNW) immediately after topsoil transfer, June 2012

Manipulation of the limited dispersal filter was carried out in two ways: 1) altering the

volume of topsoil seed bank application (site-scale) and 2) application of smoke-related

germination cues (plot-scale). The volume of the applied topsoil seed bank was reported to play

the most important role in overcoming the onsite barriers to the successful emergence on

restoration sites. The emergence densities were significantly higher in deep topsoil, applied at

ca.10 cm, than in the shallow topsoil volume applied at ca. 5 cm. The size of the majority of the

seeds was small and could be a limiting factor to recruitment when deeply buried (Bond, Honig

& Maze 1999; Traba, Azcárate & Peco 2004), but in this study greater volume of topsoil,

application reported an increased recruitment when compared to shallow topsoil treatment. The

observed higher emergence densities on deep topsoil appeared to counteract the adverse effect

of burial depth.

The explanatory factors of higher densities of native perennials at the sites where topsoil

seed bank was applied at the deep volume compared with the shallow may lay in topsoil transfer

technique. During the process of topsoil stripping and transferring the seed bank contained

205

therein is very likely to be evenly mixed (Fowler et al. 2015). The mixing may have lead to

higher emergence densities from the higher volume of the transferred topsoil seed bank. The

higher volume of the processed topsoil could also buffer from the mechanical damage during

spreading the topsoil on restoration sites as well as have a higher initial suppressing effect on

local weedy soil seed bank. Hence, native propagules applied in high volumes could emerge

more abundantly.

Fire-related cues applied at the plot level tested whether smoke and heat can stimulate

an additional recruitment from the transferred topsoil seed bank. Many plant species that

adapted to live in the fire-prone Mediterranean-type ecosystems require fire-related cues to

break dormancy (Baker et al. 2005; Merritt et al. 2007). It was hypothesized that propagules

stored in the topsoil might not germinate, hence not disperse, into the restoration site if fire-

related cues do not break their dormancy.

The additional application of smoke was unsuccessful. Lack of expected stimulative

effect of smoke treatments is very likely due to the scale of disturbance to which the topsoil was

exposed during the transfer process, e.g., aeration and scarification, that could lead to

stimulation required by the propagules to germinate. The smoke cues could also have a

stimulatory effect on germination of the invasive plants hence reducing its effectiveness on

emergence of local native seedlings (Adkins & Peters 2001).

Application of the heat treatment was useful in terms of promoting an additional cohort

of seedling emergence in the second growing season after topsoil transfer. Heat application may

work as a helpful tool in future projects that utilize transferable topsoil seed banks. The

additional scraping and heat impulse can stimulate viable but dormant propagules stored at the

deeper topsoil profile (Martin, Miller & Cushwa 1975; Wills & Read 2002). It is very likely that

the heat-application technique developed in this study assisted in the emergence of the

propagules that would not otherwise emerge due to preventive burial depth.

Installation of the herbivore exclosures had no effect on emergence densities nor their

subsequent survival. Lack of exclosure effect on seedlings densities is likely due to slower

invasion by local herbivores compared to agricultural areas as the suitable habitats are scattered

in the highly fragmented semi-urban landscape (Westoby, Walker & Noy-Meir 1989).

Furthermore, the effect of exclosures can be dependent on year and site location and their

relation to levels of human and wildlife traffic. While clear effects of herbivory on restoration

outcomes and vegetation dynamics are well described, little evidence was found for their role

during this study.

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Figure 7-3 Conceptual diagram presents the effects of filter manipulation treatments on native plant richness in

in the first year after topsoil transfer.

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7.3 Filtering processes: survival

The survival rate of the native perennial seedlings that emerged from the transferred

topsoil was highly variable in the first year after topsoil transfer (from spring to autumn)

ranging from 5.6 % in the smoke treatment to 39.1% under the shade installation. The survival

rate decreased significantly over the second summer drought after topsoil transfer and evened

out across all the filter manipulation treatments to a very low level. On average 2.44% of the

perennial cohort that emerged during the first growing season after the topsoil transfer survived

over the two-year sampling period. The highest mean end densities of native perennials were

recorded on experimental plots that were treated with artificial shading - 0.5 plants m-2

.

Although artificial shade installation showed the highest improvement in seedling survival, it

was relatively low when compared with the second highest survival recorded on unripped sites -

0.4 plants m-2

. Neither topsoil depth nor fencing affected survival odds.

One of the exceptional levels of survival recorded in the second year was detected for

the seedlings emerging from under the heat treatment - 9.7 %. Application of heat treatment was

carried out in autumn following the first summer drought since the topsoil transfer. Owing to

the scraping technique of heat treatment where the top 5 cm of topsoil was removed before the

application of the thermal impulse ~80⁰C. It is believed that this treatment activated the soil

seed bank that otherwise was not able to germinate. Physical size of propagules in the

Mediterranean-type ecosystems is on average minuscule (Enright et al. 2007) which in turn

reduces their potential to emerge from burial depths greater that 1-3 cm (Traba, Azcárate &

Peco 2004). It is also very likely that the scraping technique applied before applying the heat

impulse could reduce the weed seed bank that accumulated over the first year of the restoration

works. The reduction in competition in conjunction with heat cue and decreased burial depth

caused the dormant seed bank contained within the transferred topsoil to germinate. Survival of

the seedlings emerged from the under the heat treatment is expected to decrease as documented

for the remainder of the treatments.

Survival of seedlings native to Mediterranean-type ecosystems is, on average, very low

under natural conditions. Harsh hot and dry summers are believed to be the strongest driver of

mortality thus emphasizing the importance of fast root growth (Lloret, Casanovas & Peñuelas

1999). Manipulation of the local environmental barriers in this study, with an exception of

artificial shade treatment, did not eventuate in higher saplings densities at the end of the survey

period. Study sites were exposed to one of the driest summer seasons on record (summer 2013–

2014). Additionally, a relatively low percentage survival recorded at the end of the survey may

suggest a substantial thinning process at play (Figure 7-4).

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Figure 7-4 Image of restoration site (ForNW) 2 years after topsoil transfer, August2014

7.4 Filtering of plant functional types

There was a strong positive relationship between the density and plants species richness

emerging in the two growing seasons after the topsoil transfer. A total of 124 plant species were

detected during the two emergence seasons. The plant species richness was correlated with plant

functional richness measured as a number of combinations of the plant functional types related

to the following plant trait: native/exotic, longevity, growth form, maximum height, seed size,

nitrogen fixing abilities, and resprouting abilities. The functional richness of native seedlings

communities that emerged from the most effective combination of the filter treatments (deep

and unripped) attained nearly the level of remnant reference ecosystem in this study.

The plant species richness did not translate into the functional dispersion though as the

present plant functional types were relatively evenly distributed across the environmental filter

treatments. The resulting even distribution of functional traits between the applied filter

treatments suggests a primary association of plant emergence and establishment with the

environmental conditions outside the scale of the site. The observed significant seasonal change

in functional dispersion indices was evident. The favourable winter conditions led to increasing

while summer drought resulted in a decrease of the functional dispersion indices. Summer

seasons, with high temperatures and low rainfall, had a strongly converging impact on the plant

209

functional types that in turn led to sieving out the least stress-resistant plant assemblies.

The topsoil sourced from under the cleared Banksia woodland has proven to

accommodate a large number of dormant and viable propagules. Sandy soils that are typical for

southwestern Australian Mediterranean-type ecosystems have a high water infiltration rates

which have a positive effect on storage and viability of the propagules contained therein

(Maestre & Cortina 2002). Additionally, propagules produced in Banksia woodland show

typical adaptation to prolonged droughts and other types of disturbance typical for fire-prone

ecosystems. The seed traits like a hard seed coat (physical dormancy) and physiological

dormancy allow the soil seed bank to stay dormant for an extended period until the

unpredictable disturbance event occurs. As shown in this study, physical topsoil disturbance

associated with its transfer from a source site to the donor restoration sites can also be an

important cueing germination factor (Bradshaw et al. 2011 Lambers, & Turner, 2011; Muñoz-

Rojas et al. 2016 Dixon, & Merritt, 2016). The sites that underwent the least soil-disruptive set

of treatments (deep and unripped) were linked to prolific seedling emergence. The application

of other fire-related treatments (smoke water) did not induce new emergence.

However, higher water infiltration in sandy soils in a Mediterranean climate may also

induce higher mortality over the summer season compared to other soil types (Cowling et al.

2005 Rundel, & Lechmere-Oertel, 2005; Hallett et al. 2014 & Hobbs, 2014). The resulting

lower water retention in the upper profile of sandy soils coupled with the summer drought had

the strongest effect on survival of the native seedlings that emerged abundantly during the both

spring seasons. As a result, the field surveys recorded significantly lower functional diversity

and functional dispersion when compared to the respective surveys in the reference Banksia

woodland.

The most dominant native plant functional that survived through to the last field survey

(autumn 2014) was: perennial shrubs with a maximum height of 1 m, small-seeded, non-N-

fixer, capable of resprouting. Overall the restoration sites as recorded in the last field survey

were dominated by twelve out of a total of 118 identified plant functional types that comprised

64% of the recorded individual plants in vegetation surveys. The relative success of the small

seeded seedlings in surviving the harsh conditions on the restoration sites provide further

evidence of the trade-off between the seed size and ability to disperse into new, often highly

disturbed, habitats. Moreover, small-seeded shrubs tend to display a higher effectiveness in their

reproductive effort (Raphael et al. 2015) that in turn may correlate with relatively higher

accumulation of small propagules in the topsoil seed bank and their observed successful

establishment in this study. The relatively large success of small-seeded non-native plants in

contrast to small-seeded natives indicates that that manipulation of the environmental filters

implemented in this study did not manage to sieve out the exotic species from entering the

restoration site. Hence, rehabilitation of the degraded land is challenging especially in highly

disturbed and human-dominated areas (Smith et al. 2016).

210

7.5 Offsetting biodiversity

Development of biodiversity offsetting policies as an instrument to mitigate biodiversity

loss is ongoing globally (Quétier, Regnery & Levrel 2014; OECD 2016). Governments and

private companies increasingly exercise offset policies in their enterprises to release land for

development projects. Unsurprisingly, as the net area of natural habitat decreases land-clearing

permits become more and more difficult to obtain (Evans 2016). A number of serious

shortcomings with offset policies have been pointed out spanning multiple environmental,

social and ethical constraints, for example:

impact of offsetting policies on societal values are hard to evaluate (Maron et al.

2016)

The presumption of achieving no net loss of indigenous biodiversity has been

widely criticized (Gibbons & Lindenmayer 2007; Maron et al. 2012b; Virah-

Sawmy, Ebeling & Taplin 2014; May, Hobbs & Valentine 2017)

If avoidance and minimization approaches have been exhausted then land development

that entails natural habitat clearing often has to adhere to strict offsetting policies (as is the case

in Western Australia when significant biodiversity assets are present and subject to the

Environment Protection and Biodiversity Conservation Act of 1999). An important part of the

offsetting agreement is to rely on advances in restoration ecology science. Current technical

reports provide key recommendations on design and implementation of biodiversity offset but

the target of no net biodiversity loss demanded by offsetting policies is still difficult to achieve

(Sonter et al. 2017) with success occurring sporadically or under very long timeframes. The no

net biodiversity loss requirement is especially challenging in regions with highly diverse

ecosystems e.g., Banksia woodlands of southwestern Australia.

This study, part of Jandakot Airport Biodiversity Offset project, investigated land

management measures to reduce the gap in ecological knowledge thereby providing improved

pathways to enhanced restoration outcomes within the Banksia woodland ecosystem. The

conceptual framework of this study was to apply environmental filtering theory and directly

manipulate key filters to assist in restoring degraded Banksia woodland. Environmental filters

identified on restoration study sites fell into three categories: abiotic, biotic and dispersal and

were manipulated with use of topsoil sourced from Banksia woodland undergoing clearing.

Manipulation of the dispersal filter i.e., applying a deep volume of transferred topsoil, resulted

in the most positive effect on native plant densities and richness. Deep topsoil volume, i.e. 10

cm vs 5 cm, assisted in not only reinstating a diverse and dense community of native seedlings

during the two spring seasons after transfer but also had fewer annual weeds. A similar positive

result, where returning a deep volume of topsoil horizon encouraged reinstatement of native

flora, were recorded in MTE in France (Bulot, Provost & Dutoit 2014).

Although application of a high volume of unripped topsoil resulted in the highest

211

emergence of native plants, totalling 155 native species, the Mediterranean-type climate exerted

an additional force that reduced survival of native plants. As a result of restoration efforts in this

study novel ecosystems were formed where plants with ruderal traits thrived in the initial period

following topsoil transfer. The plant assemblages in the second year after topsoil transfer

comprised mostly of non-native perennial grasses and perennial, small-seeded native woody

shrubs. These results demonstrate the limited success of restoring native MTE of Banksia

woodland. The outcomes of the restoration projects rely greatly not only on onsite conditions

but also depend greatly on changing climatic conditions.

7.6 Conclusions

Topsoil transfer presents a high potential for future restoration projects in

Mediterranean-type ecosystem owing to the large size of the dormant native seed bank

contained therein. The highest emergence densities were recorded on sites with topsoil seed

bank spread at the highest volume (dispersal filter, see conceptual diagram Figure 7-3) and left

unripped what suggests that transport-related disturbance was efficient enough to cue the

germination of the topsoil seed bank. Higher priority should be attributed to overcoming the

adverse effects of dry climatic and exotic colonist plants recorded on restoration site as the

survival of native seedlings was very low compared to the initial emergence densities.

Successful restoration requires a vast information about the multi-scale, both temporal

and spatial information, on how environmental conditions (filters) affect ecosystem functioning

(Shackelford et al. 2013b & Hobbs, 2013). Further investigations are needed as to how to

manipulate these conditions to maintain a trajectory towards a biodiverse and resilient native

ecosystem (White & Jentsch 2001). Gathering a comprehensive experimental and observational

data to capture the exact mechanisms of habitat filtering accurately is crucial to advance the

science of restoration ecology (Kraft et al. 2015).

212

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