(Bitou Bush) on Coastal Ecosystem Processes

University of Wollongong Research Online

University of Wollongong Thesis Collection 1954-2016 University of Wollongong Thesis Collections

2004

The impact of Chrysanthemoides monilifera spp. rotundata (bitou bush) on coastal ecosystem processes

Elizabeth A. Lindsay University of Wollongong

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Recommended Citation Lindsay, Elizabeth A, The impact of Chrysanthemoides monilifera spp. rotundata (bitou bush) on coastal ecosystem processes, PhD thesis, Department of Biological Sciences, University of Wollongong, 2004. http://ro.uow.edu.au/theses/203

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The impact of Chrysanthemoides monilifera spp. rotundata (bitou bush)

on coastal ecosystem processes

A thesis submitted in fulfilment of the

requirements for the award of the degree of

Doctorate of Philosophy

from the

University of Wollongong

Elizabeth A. Lindsay B. Med. Chem (Hons)

Department of Biological Sciences

2004

Thesis Certification

Certification

I, Elizabeth Lindsay, declare that this thesis, submitted in fulfilment for the requirements for the award of Doctor of Philosophy, in the Department of Biological

Sciences, University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution.

Elizabeth A. Lindsay

November 2003

Table of Contents

Page Number

List of Tables i

List of Figures iv

List of Abbreviations x

Abstract xi

Acknowledgments xiv

CHAPTER 1: Introduction 1

Plant invasions in Australia 2

Bitou bush 2

Control techniques and their implications 7

Litter decomposition 9

Invertebrates and weeds 11

Invertebrates and decomposition 13

Aims 14

Thesis format 15

CHAPTER 2: The affect of Chrysanthemoides monilifera ssp. rotundata

invasion on decomposition rates and environmental parameters

Introduction 17

Methods 19

Study area 20

Decomposition study 21

Statistical analysis 22 Leaf structure 24

Soil moisture 24

Soil surface temperature 25

Light transmittance 25

Results 26

Decomposition study 26

Decomposition constants 29

Leaf quality 32

Environmental Differences 33

Discussion 39

Environmental parameters 39

Decomposition rates 41

Leaf quality 42

Leaf litter invertebrates 43

Site variation 44

Conclusion 46

CHAPTER 3: Nutrient cycling and litterfall in coastal areas invaded

by Chrysanthemoides monilifera ssp. rotundata

Introduction 48

Methods 51

Study Sites 51

Soil nitrogen 52

Soil pH 53

Bulk density 53 Litterfall 54

Leaf litter layer 55

Leaf nutrient analysis 55

Nutrient loss from decomposing leaves 56

Results 57

Soil nitrogen 57

Soil properties 59

Leaf fall and ground litter layer 61

Leaf nutrients 65

Nutrient flux from decomposing litter 67

Discussion 74

Litterfall and the litter layer 74

Nutrient loss from leaf litter 76

Senescence 79

Soil nitrogen 81

Soil properties 83

Effect of nutrient enrichment 84

Implications for regeneration 84

Conclusions 85

CHAPTER 4: The affect of Chrysanthemoides monilifera ssp. rotundata

invasion on coastal leaf litter invertebrates

Introduction 87

Methods 89

Study Sites 89

Invertebrate sampling 90

Data analysis 91

Results 93

Invertebrate abundance 94

Taxa and species composition 105

Temporal variation 109

Discussion 111

Litter quality 113

Temporal variation 114

Spatial variation 114

Conclusions 116

CHAPTER 5: The impact of the herbicide Roundup® Biactive™ (glyphosate), on

leaf litter invertebrates within bitou bush infestations

Introduction 118

Methods 121

Study sites 121

Invertebrate sampling 122

Change in abundance 122 Community composition 123

Results 125

Changes in abundance of taxa 126

Community composition 129

Discussion 133

Direct toxic effects 133

Indirect effects 134

Rainfall and temperature 135

Conclusions 137

CHAPTER 6: Conclusions 138

REFERENCES 142

APPENDIX

Newton iteration technique 168 i

List of Tables

Page number Table 2.1: Summary of the soil and vegetation characteristics of each field 20 site.

Table 2.2: Summary of a four-factor ANOVA for each field site for the 28 mean mass lost of C. monilifera and native leaves with time. The leaves were either in coarse or fine litterbags (Bag type) in a C. monilifera infested area or a native un-infested area (Weed)

Table 2.3. The mean percent original mass remaining for all time periods, 29 for each leaf type within each habitat at each site.

Table 2.4. The decomposition constants (k) for the single and double 30 exponential decay models. The regression coefficients (R2) for the double exponential decay model were calculated from observed vs. predicted values.

Table 2.5. The mean initial leaf carbon and nitrogen concentrations of each 32 species, and the native leaf mixture, ± one standard error

Table 2.6: The percent moisture and physical leaf parameters for each 33 species.

Table 2.7: Summary of a two-factor ANOVA, performed to determine the 34 difference in soil moisture between the C. monilifera infested areas and native un-infested areas at each site.

Table 2.8: Summary of a three-factor ANOVA performed to determine the 36 difference in soil surface temperatures at day (6am-5pm) and night (6pm- 5am) within the C. monilifera invaded and native area at each site.

Table 2.9: Summary of a two-factor ANOVA performed to determine the 38 difference in percent light transmittance between C. monilifera infested and native areas at each site

Table 3.1: Summary of the two factor ANOVA results performed to determine 57 the difference in total soil nitrogen concentration between native and C. monilifera invaded areas at each site. P<0.05 significance level.

Table 3.2: Summary of the two factor ANOVA results performed to determine 58 the difference in soil ammonia and nitrate concentration between native and C. monilifera invaded areas at each site. P<0.05 significance level.

Table 3.3. Summary of a two factor ANOVA performed to determine the 60 difference in soil bulk density between native and C. monilifera areas at each site. P<0.05 significance level.

Table 3.4: Summary of the three factor ANOVA performed to determine the 64 difference in total ground litter weight per metre squared and leaf weight per metre squared between native and C. monilifera (weed) invaded areas. P<0.05 significance level

Table 3.5: The nutrient content of green leaves (± one standard error) and the 66 carbon to nutrient ratios.

Table 3.6: The nutrient content of abscised leaves (± one standard error) and 66 the carbon to nutrient ratios.

Table 3.7: The approximate annual nutrient input from the leaf fall from the 67 three dominant species in the native areas and C. monilifera in the weed infested areas.

Table 4.1: The number of beetle morphospecies identified. Selected 92 morphospecies were first classified to family or superfamily before being identified further.

iii

Table 4.2: Summary of the ANOVA for total abundance, number of taxa and 95 abundance of certain orders and classes. P>0.05 significance level. Significant results are in bold.

Table 4.3: Summary of the ANOVA for total abundance per gram of litter and 97 total number of taxa per gram of litter. P>0.05 significance level. Significant results are in bold.

Table 4.4: The ANOSIM results for each site testing for differences between 97 native and C. monilifera areas at each collection time. Data was either square root or presence/ absence transformed. P=0.05 significance level.

Table 4.5: The average dissimilarity between the invertebrate assemblages 99 within the native and C. monilifera areas of each site. SIMPER analysis was not performed on presence/absence data for Anna Bay as the ANOISM was not significant.

Table 5.1: Summary of the unreplicated repeated measures ANOVA for the 125 abundance of each group analysed. Significant values are in bold. P<0.05 significant level.

Table 5.2: Results of the analysis of similarity, comparing the before impact 130 time with the four after impact sampling times, for impact and control sites.

Data were square root transformed.

List of Figures

Page number Figure 1.1: The distribution of C. monilifera spp. rotundata in Australia. 3

Map adapted from Weiss et al. (1998).

Figure 1.2: a. Native coastal shrubland at Warrain Beach N.S.W, b. Bitou 6 bush infestation on Comerong Island, c. Bitou bush infestation at Anna Bay

N.S.W d. A bitou bush flower.

Figure 2.1: The mean percentage of the original weight remaining in small 27 and large litterbags in C. monilifera (bitou) and native un-infested areas, through time pooled across all sites. Error bars are one standard error.

Figure 2.2. The fitted curves from a, the single exponential decay model for 31 the native leaf mix litterbags and b, the double exponential decay model for

C. monilifera litterbags.

Figure 2.3: The mean percent soil moisture (dry weight) within the C. 34 monilifera invaded (bitou) and un-infested (native) areas of each field site.

Error bars are one standard error

Figure 2.4: The total precipitation at each field site during the decomposition 35 study (November 2000 to June 2002)

Figure 2.5: The average day (6am-5pm) and night (6pm-5am) soil surface 37 temperatures at three sites, in C. monilifera infested (bitou) or native un- infested areas. The error bars are one standard error. Included are the results of the SNK post-hoc test, a b denotes significant difference, a a indicates not significantly different.

Figure 2.6: The mean percent light transmittance at four sites, within the C. 38 monilifera infested (bitou) or native un-infested areas. Error bars are one standard error.

Figure 3.1:The average total percent soil nitrogen within the native and C. 57 monilifera (weed) infested areas of each site. Error bars are one standard error.

The weed and native areas of every site were significantly different from each other (P<0.05).

Figure 3.2: a. The average soil ammonia and b. the average soil nitrate 59 concentrations (mg kg-1) within the native and C. monilifera (weed) infested areas of three field sites.

-3 Figure 3.3: The soil bulk density (Pdry, g cm ) at each site within the native 60 and C. monilifera (weed) infested areas. * denotes a significant difference.

Figure 3.4: The average soil pH (1:5 soil/0.01M CaCl2) within the native and 61

C. monilifera (weed) infested areas of each site. Error bars are one standard error.

Figure 3.5: The total litterfall (kg ha day-1) and leaf fall within native and C. 62 monilifera infested areas (weed) averaged for all sites over 12 months (May

2001 to May 2002). Error bars are one standard error.

Figure 3.6: The percent contribution of leaves, sticks, reproductive parts and 63 other to the total litterfall within native and C. monilifera (weed) areas.

Figure 3.7: The litterfall (kg.ha.day-1) due to reproductive plant parts only 63

(seeds, seed capsules, flowers) from May 2001 to May 2002. Error bars are one standard error.

Figure 3.8: The average amount of ground leaf litter per metre square within 64 the native and C. monilifera infested (weed) areas of each site. Error bars are one standard error. * denotes a significant difference between the native and weed sample.

Figure 3.9: Nutrient loss from the first 10 months of decomposition of a native 68 leaf mix and C. monilifera leaves. The leaves were placed in coarse and fine litterbags in either native or C. monilifera infested vegetation.

Figure 3.10: Changes in the leaf nutrient concentration of a native leaf mix 71 and C. monilifera leaves during decay. The leaves were in fine or coarse mesh litterbags in either native or C. monilifera infested (weed) vegetation.

vii

Figure 4.1: The average monthly precipitation (mm) and air temperature (°C) 89 across all sites during the collection period. Error bars are one standard error.

Figure 4.2: The average abundance (square root transformed) of each order or 92 class in the native and weed areas averaged for all five sites and four collection times. Error bars are one standard error.

Figure 4.3: The total invertebrate abundance per gram of litter in the native 96 and C. monilifera areas of each site. Error bars are one standard error, * denotes a significant difference.

Figure 4.4. The nMDS plots for habitat type, either native or C. monilifera 98 infested for each site. Data was square root transformed prior to ordination.

Stress values are given in brackets.

Figure 4.5: The average abundance of Acarina at each site, in either the native 100 or C. monilifera areas. Error bars are one standard error, * denotes a significant difference.

Figure 4.6: The average abundance of Hymenoptera at each site in the native 100 and C. monilifera areas. Error bars are one standard error, * denotes a significant difference

Figure 4.7: The average abundance of Chilopoda in each collection at each site 101 in either a. the native or b. C. monilifera area. Error bars are one standard error.

viii

Figure 4.8: The average abundance of Thrysanoptera in each collection at 102 each site in either, a. the native area or b. the C. monilifera area. Error bars are one standard error.

Figure 4.9: The average abundance of Pseudoscorpions in each collection at 104 each site in either, a. the native area or b. the C. monilifera area. Error bars are one standard error.

Figure 4.10: The number of taxa per gram of litter in the native and C. 105 monilifera invaded area of each site. Error bars are one standard error, * denotes a significant difference.

Figure 4.11: The nMDS plots for habitat type, either native or C. monilifera 106 infested, for each site with a significant ANOSIM of weed x time. Data was presence/absence transformed prior to ordination. Stress values are given in brackets.

Figure 4.12: The nMDS plots for the four collection times at each site. The 109 data was presence/absence transformed prior to ordination. Stress values are given in brackets.

Figure 5.1: The mean (± S.E) abundance of each taxa in the control and 124 herbicide impact sites across all sample times.

Figure 5.2: The mean total abundance of invertebrates and abundance of 127 dominant groups (± S.E), before and after glyphosate application for the herbicide impact and control sites.

Figure 5.3: The daily precipitation (mm) and mean air temperature (◦C) at 129

Jervis Bay during the experiment.

Figure 5.4: nMDS ordination of a, control and impact sites across and 131 sampling times and b, the before and after impact sample times. Stress =

0.13.

List of Abbreviations

Statistical:

ANOVA Analysis of variance

ANOSIM Analysis of similarity nMDS non-metric multidimensional scaling

SIMPER Similarity percentage analysis

SNK Student-Newman-Keuls test

S.E Standard error

Litterbags:

NC Native leaf mix in coarse litterbag

NF Native leaf mix in fine litterbag

CF C. monilifera in fine litterbag

CC C. monilifera in coarse litterbag

Site names:

AB Anna Bay

7M Seven Mile Beach

COM Comerong Island

WB Warrain Beach

JB Jervis Bay

Other:

LMA Leaf mass area

Abstract

On the southeast coast of Australia, there are extensive infestations of the environmental weed Chrysanthemoides monilifera ssp. rotundata (L.) T. Norl. (Bitou bush). This weed is highly invasive and persistent, yet little is known about how it impacts on coastal ecosystems. Plant invasions can greatly alter the area they invade, and can modify primary productivity, plant species composition, species diversity, decrease ecosystem stability and disrupt ecosystem processes.

This research aimed to determine if C. monilifera invasion changes leaf litter decomposition and nutrient cycling. Leaf litter invertebrates were also investigated as they play key roles in functioning of forest ecosystems and can greatly enhance litter decomposition and nutrient cycling. The herbicide glyphosate is widely used to control

C. monilifera, however there have been few studies examining the effects of this herbicide on invertebrate communities in the field, especially on sand dunes. I aimed to determine if glyphosate application impacts leaf litter invertebrate involved in decomposition.

Field studies and experiments were undertaken in five sites along the N.S.W coastline, each with an area heavily infested with C. monilifera and in native un-infested area. A litterbag decomposition study found that the succulent C. monilifera leaves decomposed at least three times faster than a sclerophyllous native leaf mix (Acacia longifolia var. longifolia, Banksia integrifolia and Leptospermum laevigatum) with the decomposition rates being related to the physical properties of the leaves. Nutrients were leached and mineralised quicker from the C. monilifera leaves, mostly due to the rapid decay. There was some immobilisation of sulphur and phosphorous in the native leaves when placed in the native sites and more immobilisation is expected with time.

xii

C. monilifera leaves decayed significantly faster in coarse mesh litterbags compared to the fine mesh, indicating leaf litter invertebrates positively influenced their decomposition. Mesh size had little effect on the native leaf decomposition rate. All C. monilifera litterbags and the coarse native litterbags decomposed faster and generally had greater nutrient loss within the C. monilifera infestations. This is due to an increase in invertebrate detritivores within the C. monilifera, and dense infestations creating a protected environment with an altered microclimate.

There was a greater input of litter to the native sites, and this was highly seasonal compared to the C. monilifera areas. Maximal litter fall corresponded with periods of peak flowering and growth (spring –summer). Due to the higher leaf fall rate there is a greater input of nutrients to the forest floor in the native sites, even though large amounts of nutrients were withdrawn from the leaves before abscission. The slow decomposition and high litter fall resulted in greater amounts of litter accumulating on the native forest floor, which appears to act as a nutrient sink.

Invasion by C. monilifera in coastal areas does not appear to change the nitrogen budget, but there are differences in where nitrogen is stored in comparison to uninvaded areas. The total soil nitrogen and ammonia nitrogen were significantly greater in most of the bitou bush sites, whereas in the native vegetation there was more nitrogen held within the leaf litter layer. Nitrogen appears to be cycled faster in the weedy areas, mainly as result of the increase in leaf quality and the speed of breakdown.

Leaf litter invertebrate abundance and assemblage were compared between habitats over twelve months. The total abundance was not significantly reduced in the weedy habitat but the abundance of mites, thrips, spiders, ants, and centipedes was reduced at many sites. The invertebrate assemblages also differed between habitats, with the C. monilifera supporting a lower diversity of beetles. However, the millipedes,

xiii amphipods, earthworms, pseudoscorpions and isopods appeared to respond positively to the invasion, occurring in higher abundance and detected more frequently in the weedy areas. This has been attributed to the change in microclimate within C. monilifera infestations, which are moister and darker, which these invertebrates tend to prefer.

Furthermore as the leaf litter is of lower quantity and higher quality, and possibly higher palatability, than the native sclerophyllous vegetation, the detritivores assemblages seems to have responded positively.

To determine the impact of the herbicide glyphosate on non-target litter invertebrates control and impact sites were selected in coastal hind dunes heavily infested with C. monilifera. The impact sites were sprayed with a 1:100 dilution of

Roundup® Biactive™. The herbicide application had no direct or indirect effect on leaf litter invertebrate abundance or community composition in the four months following application. The litter invertebrate assemblages were highly variable on a small spatial scale with abiotic factors more strongly regulating leaf litter invertebrate numbers than glyphosate application. These results conflict with previous studies, indicating the detrimental indirect effects herbicide application has on non-target litter invertebrates may depend upon the application rate, the vegetation community and structure and post- spray weather.

Invasion by C. monilifera has changed the movement of leaf litter and the cycling of nutrients within coastal ecosystems, mainly through a change in quality and quantity of leaf litter. It has impacted on the litter invertebrates, which has amplified the increase in decomposition rate. The change in soil nutrient availability could increase the competitive superiority of C. monilifera directly by increasing growth rate, or indirectly by impairing the establishment of native species.

xiv

Acknowledgements

I would firstly like to thank my supervisor Kris French, for her constant support and advice throughout this study. I would like to thank Alan York for help with the leaf litter invertebrates and offering advice.

A big thanks to everyone who assisted with fieldwork and construction of experimental equipment; Colin Lindsay, Matt Misdale, Beth Mott, Ramish Pillai, Tara

Rees, Andrew Thomas, Sarah Buckley, Allan Lindsay, Suzanne Lindsay, Grant

Vormister, Beth Mott, Dave McKenna, Sarah Buckley, Monica Sherman, Cath Blakey,

Tristan Epstein, Shannon Taylor and Julie Haywood.

Thanks to all in the French lab for feedback and a providing a place to bounce around ideas, especially Louise Meades and Holly Parsons for assistance with beetle identification.

Thankyou to Shoalhaven City Council (Ian Booradale), N.S.W National Parks and Wildlife Service and Environment Australia for field site access, and not removing the bitou bush. Thankyou to Matt Hudson, Bruce Rafferty and Gary McLeod (Booderee

National Park) for making the glyphosate impact experiment happen.

A special thanks to all my friends and family, especially my brother Colin, for putting up with hearing about the world of bitou bush.

A Linnean Society of Australia Travel Grant funded part of decomposition study and an Ecological Society of Australia Student Research Grant funded the herbicide impact study.

Chapter 1

Introduction

Plant Invasions in Australia

Most plant species now considered as weeds in Australia were introduced by humans either inadvertently as seeds, or as plants to create more favourable conditions

(Humphries et al. 1991). At least fifteen percent of Australian flora consists of introduced species with around half of the introduced plants invading native plant communities. Of the species that invade natural areas one quarter are, or could become, significant environmental weeds. Environmental weeds are plants that are undesirable from an ecological perspective and have established self-propagating populations in native vegetation outside their natural range (Cronk & Fuller 2001; Csurches &

Edwards 1998). Plant invasions can cause many ecological problems including changing biodiversity and abundance of flora (Adair 1995; Breytenbach 1986; Holmes

& Cowling 1997) and fauna (Belnap & Phillips 2001; Fraser & Lawton 1994; Samways et al. 1996; Toft et al. 2001) and altering ecosystem processes (Ehrenfeld & Scott 2001;

Mack et al. 2001; Tilman & Knops 1997; Vitousek 1990).

Bitou bush

Chrysanthemoides monilifera (Asteraceae) originates from South Africa. There are two sub-species of this perennial evergreen shrub present and naturalised in

Australia. These are Chrysanthemoides monilifera ssp. rotundata, known commonly as bitou bush, and spp. monilifera, known as boneseed (Lane 1981). It is thought that bitou bush was introduced to Australia around 1908 as seeds in the ballast water of a South

African ship (Gray 1976; Humphries et al. 1991). Bitou bush grows closer to the coast than boneseed, but there are locations where both are present and hybrids of the two subspecies occur (Weiss et al. 1998). Bitou bush is an environmental weed in Australia, and habitats at risk from invasion include dunes, coastal headlands and dry sclerophyll

3 forests and woodlands within 25km of the coastline (National Parks and Wildlife

Service 2001).

Bitou bush occurs predominately along the east coast of Australia, including

Queensland, New South Wales (N.S.W) and Lord Howe Island (Figure 1). There are also small populations at Menindee in western N.S.W and near Melbourne, Victoria

(Vranjic 2000). In 1985 bitou bush was estimated to cover 59% of the N.S.W coastline, with 21% of the coast covered in dense infestations (Love 1984). Mapping in 2001 determined there had been a 30% increase in cover, with bitou now occurring on over

80% or 36770 ha of the coastline. On around 7000ha of this land, bitou bush is continuous and dominates the native vegetation (Thomas 2002).

Figure 1.1: The distribution of C. monilifera spp. rotundata in Australia. Map adapted from Weiss et al. (1998).

The spread of bitou bush was aided by plantings between 1946 and 1970 to stabilise coastal sand drifts, and to revegetate dunes after mining operations (Cooney et al. 1982; Gray 1976). Deliberate planting was stopped when it was realised how fast it could spread and that it invaded native vegetation (Love 1984). As an infestation becomes older it has less effect on stabilising dunes and increased wind erosion occurs

(Thomas 1997, Stanley et al. 1989). Bitou bush is listed under the Noxious Weeds Act

1993, meaning it must be prevented from spreading and the infestation reduced

(National Parks and Wildlife Service 2001). In N.S.W invasion of native plant communities by bitou bush has been listed as a key threatening process under the

Threatened Species Conservation Act, 1995. It was also declared a ‘Weed of National

Significance’ by the Commonwealth Government in 1999.

Invasion by bitou bush has had detrimental effects on native flora and fauna.

Invasion changes the vegetation structure (Weiss and Noble 1984), and decreases the floristic diversity (Scott 1991). Two examples of typical infestations are shown in

Figure 1.2, with no native vegetation present within the infestations. The dense canopy formed excludes native grasses, herbs and seedlings (Wickham & Stanley 1984) and it also out competes and can eliminate many shrubs including Acacia longifolia var. sophoraae (Weiss & Noble 1984a) Leucopogon parviflorus (Toth et al. 1996), Correa alba (Gray 1976) and Banksia integrifolia (Dodkin & Gilmore 1985). A. longifolia growing in close proximity to bitou bush has reduced seed production, decreased cover and volume (Weiss & Noble 1984b). The leaf litter and soil within C. monilifera infestations has been shown to decrease A. longifolia seed germination, and decrease seedling shoot and root biomass (Vranjic et al. 2000).

The shift towards simpler vegetation, approaching monoculture in highly infested areas could lead to a loss of habitat for native fauna, with several animal species at risk have been identified (Dodkin & Gilmore 1985; Thomas 1997). These include migrating birds that feed on flowering heath species (Stanley et al. 1989) and birds that rely exclusively on plant material for food (French & Zubovic 1997).

However the impact of bitou bush on other fauna including invertebrates is still largely unknown (Humphries et al. 1991).

Figure 1.2: a. Native coastal shrubland at Warrain Beach N.S.W, b. Bitou bush infestation on Comerong Island, c. Bitou bush infestation at Anna Bay N.S.W d. A bitou bush flower.

a. b.

c. d.

Bitou bush grows one to three metres tall and two to six metres wide, but when growing under shade it can climb up other trees, and smother their canopy to a height of ten metres (Vranjic 2000). Bitou bush produces leaves with a large area. The leaf area per plant increases when it is in competition, and this shading may suppress other species (Weiss & Noble 1984a). Bitou bush has a greater mass of roots than native shrubs of similar size, which penetrate deeper and grow rapidly during water stress.

Bitou bush flowers all year round, with the peak flowering time from April to

September (Carolin & Clarke 1991; Weiss et al. 1998). The flowers are shown in Figure

1.2. The berries ripen from green to glossy black, and are attractive to birds, foxes, rabbits and cattle, which aid in seed dispersal (Dodkin & Gilmore 1985). Bitou bush can reproduce vegetatively and like many Australian native species seed germination is stimulated by fire (Stanley et al. 1989). Bitou bush has a greater reproductive output than native shrubs with each plant producing up to 50 000 seeds per year (Weiss 1984), with some seeds remaining viable in the soil for up to ten years (Agriculture and

Resource Management Council of Australia et al. 2000). Seedlings have a rapid initial growth even under the bitou bush canopy (Weiss & Noble 1984b), and they can withstand infertile soils, shading and lack of moisture (Lane 1981; Weiss et al. 1998).

Control techniques and their implications

Complete eradication of large infestations is difficult and expensive, especially with there being no significant natural pathogen of C. monilifera in Australia (Benson

1991, Lane 1981). Many control programs have been undertaken, and not all have been successful, but there is increased success when two or more control methods are used together. Control methods include hand removal, slashing, fire and herbicide application. Recently biological control agents have been released, which are considered

8 a more feasible long term approach. These include the bitou tip moth (Comostolopsis germana) and the bitou seed fly (Mesoclanis polana) (Adair 1993; Scott & Adair 1991).

Currently chemical control is the most successful method for removing large infestations. The herbicide glyphosate (N-(phosphonomethly)glycine) is the most widely used herbicide, applied via aerial application or high pressure spraying equipment (Cooney et al. 1982; Toth et al. 1993). This is carried out in winter when bitou bush is most sensitive, and when the impact to native vegetation is minimal (Toth et al. 1996). Due to the large scale of bitou bush infestation, a considerable amount of herbicide is applied to the N.S.W coastline. The fate of glyphosate in the sand dunes is unknown (Toth 1997) nor is its toxicity to non-target fauna such as insects (Ainsworth

1997). There is also very little known about the breakdown products of glyphosate and their persistence in the soil.

Many herbicides have had detrimental effects on soil fauna (Eijsackers & Van de Bund 1980). Glyphosate has been shown to be harmful to certain arthropods in the field (Brust 1990; Santillo et al. 1989) and in the laboratory (Eijsackers 1985; Hassan et al. 1988). Application of glyphosate to field margins was found to decrease the abundance of spiders, carabid beetles and bugs, with the abundance decreasing as the glyphosate concentration increased. (Haughton et al. 1999b). There have been no studies on the impact of glyphosate on ground dwelling invertebrates in Australia and none world wide on coastal dunes environments.

Herbicides can negatively affect fauna through direct toxicity effects and/or indirect effects through habitat modification. As the treated vegetation dies the decreased canopy cover can change the microclimate (Brust 1990). The invertebrates often become more exposed to the desiccating sun and wind, accompanied by an increase in surface temperature and decrease in soil moisture (Eijsackers & Van de

Bund 1980; Haughton et al. 1999a; Haughton et al. 2001a).Vegetation death following herbicide application can also remove a food source for insects, leading to a decline in the population. The recovery of the fauna after the plants have grown back can result in changes to the community composition (Eijsackers & Van de Bund 1980).

Litter decomposition

Litterfall accumulates on the ground providing a habitat for many fauna, while its subsequent decay also recycles vital resources (Ashton 1975). Litter decomposition involves the mechanical breakdown of plant tissue, followed by the chemical deterioration of the tissue. This vital process assists in maintaining soil fertility and organic matter content (Staff & Berg 1981; Witkamp 1971). While litter is decaying, soluble compounds are leached from the litter into the soil and microbes transform elements from organic to inorganic form. This mineralisation process makes nutrients available to plants and can regulate nutrient availability (Couteaux et al. 1995; Lavelle et al. 1996) and plant growth (Ananthakrishnan 1996). Leaf litter decomposition also provides soil organic matter (humification) which aids in the retention of exchangeable cations (Spain et al. 1983).

The decomposition rate is controlled by both biotic and abiotic factors

(Couteaux et al. 1995). The most important biotic factor is the litter chemistry and quality while the most important abiotic factor is climate, in particular temperature and moisture (Berg & Staff 1981; Meentemeyer 1978; Shaw & Harte 2001). Soil microflora

(bacteria, fungi and yeasts) and leaf litter invertebrates also aid leaf litter decay (Douce

& Crossley 1982; Reichle 1977; Vossbrink et al. 1979), and this will be discussed in more detail in the following section.

Weeds can disrupt ecological processes and the structure of ecosystems

(Breytenbach 1986; Chapin et al. 2000; Usher 1988). Numerous weed invasions have altered nutrient cycling, especially of the often limiting nutrient nitrogen (Fogarty &

Facelli 1999; Matson 1990; Standish et al. In press; Vitousek et al. 1987) and changed soil nutrient availability (Fogarty & Facelli 1999; Matson 1990; Musil & Midgley

1990). This can decrease ecosystem stability (Evans et al. 2001; McIvor 2001) and modify primary productivity, plant species composition and species diversity (Maron &

Connors 1996; Wedin & Tilman 1990).

Numerous weeds produce leaf litter of different quality and quantity to the invaded community. Changes in the leaf litter available to the decomposer community can alter the decomposition rate (Ehrenfeld et al. 2001; Pereira et al. 1998) and subsequently nutrient cycling (Knoepp et al. 2000). There are strong positive feedbacks between plant species composition and soil properties, such that introduction of a new species can change nutrient cycling (Hobbs 1991; Wedin & Tilman 1990). It has been proposed that the ability to change soil-based ecosystem processes may be an important characteristic that enables an exotic species to invaded and spread (Ehrenfeld et al.

2001; Fogarty & Facelli 1999).

Invasion by Tradescantia flumensis in New Zealand forests increased the litter decomposition rate, with leaves being less sclerophyllous with a lower C: N ratio than the native species (Standish et al. In press). This lead to a reduced leaf litter layer and increased soil nitrate concentration. There were also changes to the litter invertebrate community. Similarly in South Africa the weed Acacia saligna had a higher leaf fall rate and litter that decayed faster than the native vegetation (Witkowski 1991). This has increased the available soil nitrogen and increased the soil pH, which has resulted in

11 changes in the vegetations growth form and species composition (Musil & Midgley

1990).

In North America the invasive grass Bromus tectorum also produces more litter, but of a lower quality than the native grassland species (Evans et al. 2001). This decreased the potential rates of net nitrogen mineralisation, by decreasing the nitrogen available for microbial activity during decomposition (Evans et al. 2001). This has lead to a decrease in soil inorganic nitrogen.

Weeds and Invertebrates

Arthropods are major components of numerous ecosystems and important in the functioning of ecosystem processes (Kim 1993). They occupy a wide range of functional niches and microhabitats across a range of spatial and temporal scales

(Seastedt & Crossley 1984), representing 85% of total global fauna and 65% of the known biodiversity (Kim 1993). Unfortunately, in Australian there is a lack of knowledge on the diversity, systematics and ecology of most invertebrate communities

(New 1993; Woinaerski & Cullen 1984).

Invertebrate communities can be useful tools for monitoring ecological change

(Springett 1976b), with many terrestrial arthropod populations sensitive to habitat modification and disturbance, especially as some species are relatively sedentary and have limited dispersal capabilities (Kremen et al. 1993). Disruptions in the composition of invertebrate communities can influence important processes such as nutrient cycling and decomposition (Anderson 1975; Olson 1963; Seastedt & Crossley 1984; Zimmer &

Topp 2002).

Weed invasion has been shown to modify invertebrate abundance and assemblage. The changes in abundance or community composition have been related to

12 the lower plant diversity (Haddad et al. 2001; Toft et al. 2001), low diversity of leaf litter (Springett 1976, Slobodchikoff et al. 1977), changes in the mass of litterfall and the leaf litter layer (McIvor 2001) and the invading plant having differing characteristics to the native vegetation (Haddad et al. 2001; Wardle et al. 1999).

Stabilisation of sand dunes in California with the exotic grass Ammophila arenaria decreased arthropod abundance and species diversity when compared to native vegetation (Slobodchikoff & Doyen 1977). Similar results were found on sand dunes stabilised with Ammophilia arenaria on the N.S.W coastline of Australia (Webb et al.

2000). The invertebrate assemblages in the exotic grass were different to those in native areas (Webb et al. 2000), thought mainly due to a lack of structural complexity. Isopoda abundance was much greater on native dunes due to a more developed heterogeneous litter layer and lower insolation. There were also significant differences in the abundance of individual morphospecies between the control and A. arenaria covered dunes (Webb et al. 2000).

Invasion by Tradescantia fluminensis in New Zealand also reduced the abundance of most invertebrates (Standish In Publication), with weedy sites supporting a different community with lower species richness. However, some species reacted favourably to the invasion, possibly responding to a change in microclimate. Another

New Zealand study found that undisturbed bushland contained a greater richness and diversity of beetles than disturbed sites (Crisp et al. 1998). The weedy habitats still contained a high number of native beetle species, but the dominant species were different.

Invertebrates and decomposition

Fungi and bacteria are responsible for most of the organic matter breakdown

(Howard & Howard 1974; Mellio et al. 1982), but invertebrates still play key roles in the decomposition of organic matter and the mineralisation of inorganic nutrients (Lee

1983; Seastedt 1984).

A succession of species is involved in the decomposition of litter (Crossley and

Hoglund 1962) and positive correlations between fauna and litter decomposition have been found in numerous studies (Hassall et al. 1987; Santos & Whitford 1981; Songwe et al. 1995; Spain & Hutson 1983; Yamashita & Takeda 1998). A review of papers found the average reduction in litter mass when microarthropods were present was 23%, with it varying between 4 to 69% (Seastedt 1984).

Millipedes (Smit & Van Aarde 2001) and amphipods are important in decomposition on coastal sand dunes (Friend & Richardson 1986). These and other litter and soil invertebrates directly affect the decomposition rate through digestion and assimilation of organic material. Generally less than 10% of the litter energy is utilised in each pass through the digestive tract, comprising of easily digestible sugars and protein (Douce & Crossley 1982). The excreted remains are however preferentially invaded by microorganisms over undigested material (Kautz et al. 2002; Standen 1978).

Litter invertebrates have been shown to be important in regulating the mineralisation and immobilisation of nitrogen, and can increase the turnover of N

(Parker et al. 1984). Litter invertebrates can increase the nutrient loss by reducing litter to fine particles, increasing the area for leaching (Attiwill & Adams 1993; Seastedt &

Crossley 1980). Invertebrates mobilising nutrients in low fertility soils can produce nutrient hotspots which can be important in maintaining plant diversity (Bolger et al.

2000).

Invertebrates can further enhance these processes by affecting the community composition and activity of microbes (Lavelle et al. 1996; Seastedt & Crossley 1980).

They inoculate the litter with microflora and stimulate the microbial activity (Beare et al. 1992; Parker et al. 1984; Witkamp 1966). Grazing and fragmenting of litter by invertebrates also increases the litter surface area for microbes to attack (Barley &

Jennings 1959; Standen 1978). The physiochemical characteristics of the leaf litter affect the abundance and diversity of microbes and invertebrates (Blair et al. 1990;

Pereira et al. 1998).

Soil fauna are also important in removing litter from the surface and incorporating it into the soil, even before decomposition starts (Hart 1995). Burrowing and transportation of material between soil horizons mixes organic and inorganic components and affects the soil profile development and hydrology (Greensdale &

Greenslade 1983; Lee 1983).

Aims

I aimed to determine the impact of bitou bush invasion on coastal ecosystem processes, namely decomposition and nutrient cycling, and the leaf litter invertebrate community. Overall, I hoped the results from this study would further the knowledge on how bitou bush invades and persists as a dominant species in coastal areas, and assist in the management of bitou bush infestations and regeneration of impacted sites.

The specific objectives of this study were to compare coastal areas with native sclerophyllous vegetation with long-term bitou bush infestations with regards to:

• The leaf litter decomposition rate and release of nutrients from leaf litter

(Chapter 2 and 3),

• Seasonal litter production, leaf litter accumulation and nutrient input from leaf

fall (Chapter 3),

• Soil nitrogen availability and soil physical properties (Chapter 3),

• The abundance and assemblage of leaf litter invertebrates (Chapter 4),

• The importance of invertebrates in the decomposition and nutrient release of

native and bitou bush leaves (Chapter 2 and 3) and

• Microclimatic parameters that could influence the decomposition and

invertebrate populations (Chapter 2).

As a separate field study, I aimed to determine the impact of the herbicide glyphosate on the abundance and composition of non-target leaf litter invertebrates within bitou bush infestations (Chapter 5).

Thesis format

Each chapter of this thesis has been written as a journal article, and the general format has been left this way. On the base of the title page of each chapter it states where the chapter was submitted for publication in a shorter format. As a result there is some repetition between the general introduction and the introduction of each chapter, and some repetition in the methodology, particularly in regards to site descriptions. The references from each journal article have been compiled together to form one reference chapter at the end of the thesis.

Chapter 2

The affect of Chrysanthemoides monilifera ssp. rotundata

invasion on decomposition rates and environmental

parameters

Forest Ecology and Management (In press)

Introduction

Leaf litter decomposition is a major pathway for supplying energy and nutrients to soils in ecosystems (Spain & Hutson 1983; Staff & Berg 1981). Decomposition involves mechanical break down of litter, leaching of soluble compounds and chemical deterioration of plant tissue (Lavelle et al. 1996; Witkamp 1971). Litter quality and climate, in particular temperature and moisture, are the main controlling factors of decomposition (Meentemeyer 1978; Shaw & Harte 2001). Soil microflora and leaf litter invertebrates also aid leaf litter decay (Douce & Crossley 1982; Vossbrink et al. 1979) and their abundance and diversity is affected by the physiochemical characteristics of the leaf litter (Blair et al. 1990; Pereira et al. 1998).

Weeds can disrupt ecological processes and the structure of ecosystems

(Breytenbach 1986; Usher 1988), by changing soil nutrient availability (Fogarty &

Facelli 1999; Matson 1990; Musil & Midgley 1990) and disrupting nutrient cycling

(Standish et al. 2002; Vitousek 1990). Weeds are likely to produce leaf litter of different quality and quantity to the community it invades. Changes in the leaf litter available to the decomposer community can alter the decomposition rate (Ehrenfeld et al. 2001;

Pereira et al. 1998). This disturbance can be further magnified by the low diversity of leaf litter in weed monocultures often supporting fewer invertebrates (Slobodchikoff &

Doyen 1977; Springett 1976a). Invasion by Tradescantia flumensis in New Zealand forests increased the local decomposition rate, with leaves being less sclerophyllous with a lower C: N ratio than the native species. This lead to a reduced leaf litter layer, increased soil nitrate and changes to the litter invertebrate community (Standish et al.

2002). Similarly in South Africa the weed Acacia saligna increased soil nutrients and pH (Musil & Midgley 1990), through its higher leaf fall and decomposition rates

(Witkowski 1991). In contrast, the grass Bromus tectorum produces litter of lower

18 quality than the native grassland species in Colorado USA, and has decreased the nitrogen available in the soil (Evans et al. 2001).

The evergreen shrub Chrysanthemoides monilifera ssp. rotundata (Family

Asteraceae), commonly known as bitou bush, is native to South Africa (Weiss & Noble

1984b). It was introduced to Australia around 1908 and is now a common environmental weed along the south east coast. It was planted to stabilise sand dunes after disturbance (Humphries et al. 1991; Weiss 1986), but increased wind erosion occurs once native species are displaced and the infestation ages (Thomas 1997). C. monilifera now covers approximately 80% of the New South Wales coastline, growing on headlands and dunes, where it is the dominant species in 40% of the vegetation

(Holtkamp 2002; Toth et al. 1996). C. monilifera is taller than native grasses and herbs, and shorter than the tree-shrub canopy (Lane 1981). The dense canopy formed excludes native grasses, herbs and seedlings (Wickham & Stanley 1984), and in highly infested areas there is a shift towards simpler vegetation, approaching a monoculture (Dodkin &

Gilmore 1985; Thomas 1997). The leaf litter and soil within C. monilifera infestations has been shown to impede the growth of native seedlings (Vranjic et al. 2000). Weeds that form a dense canopy can change the light regime and microclimate (Breytenbach

1986). This can lead to changes in the decomposition process and nutrient cycling

(Belyea 1996; Heneghan et al. 1999; Shaw & Harte 2001).

The aim of this study was to compare decomposition rates of litter from C. monilifera and three native species. This was undertaken within native vegetation and

C. monilifera infestations to determine if invasion altered the decomposition process.

Litterbags were used to assess the importance of invertebrates in the decomposition of each leaf type and within each habitat. Several microclimatic and physiochemical leaf parameters that could influence the decomposition process were also examined.

Methods

Study Areas

Five sites were chosen along the NSW coastline, these were located at Anna Bay

(32°46’S, 152°05’E), Seven Mile Beach (34°48’S, 152°32’E), Comerong Island

(34°52’S, 150°44’E), Warrain Beach (34°58’S, 150°47’E) and Jervis Bay (35°08’S,

150°40’E). Within each site, two 30 x 30m areas were chosen at least 100m apart. One area was heavily infested with C. monilifera, with a minimum 70% cover, and the other area was un-infested. It is not known why these native areas have not been invaded by

C. monilifera. The sites were chosen for having no chemical or mechanical weed control work had been undertaken for at least the past ten years, and there being a weedy and native area in close proximity. The infestations were estimated to be between

22 and 33 years old from National Park and Wildlife Service and Shoalhaven Council

Records. The dominant vegetation within the un-infested native areas consisted of the shrubs Acacia longifolia var. longifolia or Acacia longifolia var. sophorae, Banksia integrifolia and Leptospermum laevigatum. Westringia fruticosa was also dominant at

Anna Bay. For a summary of site characteristics see table 2.1.

Sites were located on foredunes, except for the native area at Jervis Bay and the

C. monilifera area at Anna Bay. The native area at Jervis Bay is situated on top of a

25m pebbly-quartz sandstone cliff (Taylor et al. 1995). This was the only site with the required vegetation community not infested by weeds within the area. The C. monilifera area at Anna Bay is located on bedrock of rhyolitic ignimbrite at sea level, forming part of the Carboniferous Nerong Volcanics (Whitehouse 1997).

Table 2.1: Summary of the soil and vegetation characteristics of each field site.

Maximum Site Canopy Site Soil Type Vegetation Location cover (%) Height (m) Native Sand dune Loamy quartz 3 60 sand Anna Bay Weed Headland Sandy clay 2 75 loam Native Sand dune Loamy quartz 4 65 Seven Mile sand Beach Weed Sand dune Loamy quartz 15 85 sand Native Sand dune Loamy quartz 4 50 Comerong sand Island Weed Sand dune Loamy quartz 3 85 sand Native Sand dune Loamy quartz 2 70 Warrain sand Beach Weed Sand dune Sandy clay 4 85 loam Native Cliff top Sandy loam 6 70 Jervis Bay Weed Sand dune Loamy quartz 10 80 sand

Most soils were loose loamy quartz sands, with low fertility and high permeability (Hazelton 1992, 1993; Murphy 1995). The exceptions were the C. monilifera areas at Warrain Beach and Anna Bay, which are sandy clay loams. All soils were slightly to strongly acidic, with varying amounts of organic matter. Low levels of carbonates were present at the Jervis Bay C. monilifera area (Taylor et al. 1995).

The most northern site, at Anna Bay, has a mean maximum day temperature of

23.1°C and a minimum of 12.9°C. The mean annual rainfall is 1342mm. Sites further south on the coastline are cooler and receive slightly less rainfall. Jervis Bay has a mean maximum day temperature of 19.9°C, a minimum of 13.6°C and a mean annual rainfall of 1244mm (Australian Bureau of Meteorology).

Decomposition Study

B. integrifolia, L. laevigatum and C. monilifera leaves and A. longifolia phyllodes were collected from plants on the foredunes and hind-dunes of the NSW

South Coast during September and October 2000. New growth was avoided. Freshly fallen leaves were not used, as there were insufficient quantities of C. monilifera.

Litterbags were used to monitor decomposition (Crossley & Hoglund 1962).

Two types of bags were used, a fine (0.50 x 0.25mm) mesh polyester netting sewn into bags of 200 x 200mm, and a coarse (4.0 x 4.0mm) mesh nylon tube of 200 x 250mm.

The coarse mesh was used to allow mesofauna (Collembola, Acarina) and most macrofauna (Diplopoda, Isopoda, earthworms) inside. The fine mesh excluded most of these soil animals, and was used to monitor the effects of microbial activity and leaching.

Leaves were air dried to constant weight at approximately 25°C for three weeks.

Six samples of each leaf species were oven dried at 60°C for 24h to obtain a dry weight conversion factor. These leaves were also analysed for total carbon and total nitrogen using a LECO CN 2000 TM analyser. The leaves in the litterbags were not artificially dried as this could affect microbial activity, and consequently the decomposition rate

(Tanner 1981). The bags were filled with either C. monilifera leaves (18.09± 0.17g, dry weight) or a native leaf mix (18.50± 0.13g, dry weight). The native leaf mix contained

22 equal amounts of B. integrifolia, A. longifolia and L. laevigatum, to mimic the natural litter layer (Blair et al. 1990). The four types of bags are referred to as fine native, coarse native, fine bitou and coarse bitou.

The bags were placed in the field during November and December 2000 in contact with the mineral soil. They were placed in twenty-four groups of four, with one of each bag type in each group. Each group of bags was at least 2m apart. Most sites were either well protected or densely vegetated, prevented bag displacement. In highly exposed areas one end of the bag was secured with a metal stake.

Four groups (four litterbags of each type) were randomly retrieved after 78, 165,

220, 292 and 609 days. These were placed in labelled airtight plastic bags and stored in the freezer. They were oven dried at 60°C for 24h, cleaned and reweighed to determine mass loss. Sand was the main contaminant, and was easy to separate from the decaying leaves. During the last collection generally less than four bags were retrieved at each site. Most losses were due to bags being torn open by animals and a heavy storm that resulted in sand dunes collapsing into the ocean. These results were not included in the analysis.

Statistical analysis

The decomposition data (mass loss) was fitted to two different models. The first model assumed single negative exponential decay (Olson 1963). The decomposition constant

(k) was calculated from the following expression

–kt Mt/ Mi = e where Mt is the litter mass at time t, Mi is the initial litter mass and time is expressed in years.

The time (t) for 99% of the initial mass to decay was determined from the equation:

t (99% decay) = (ln 0.01)/-k

The C. monilifera data fitted poorly to this model, so the data was also fitted to a double exponential decay model (Hunt 1977; Lousier & Parkinson 1976; Wieder &

Lang 1982). This model separates leaf material into two components, one that is soluble or easy to decompose and another that is recalcitrant or insoluble. This was performed using the nonlinear (least squares, Gauss Newton) function of SYSTAT version 10

(SYSTAT 2000), with the expression

-k1t -k2 t Mt/ Mi=Ae + (1-A) e where A is a constant that indicates the easily decomposable fraction of the leaf, and (1-

A) the recalcitrant fraction. The value of A is related to the carbon to nitrogen ratio of the leaf material and was determined using the equation developed by (Hunt 1977)

A = 0.07 + 1.11 (N/C)1/3 where N is the nitrogen concentration and C the carbon concentration. To determine the time for 99% decay the equation was solved for t and a substitution of U=et was used.

The Newton iterative technique was then used to solve for U (Anton 1992).

A three-factor analysis of variance was performed for each site, using SYSTAT

(2000). This was to determine differences in the decomposition rate between C. monilifera infested and un-infested areas, leaf types and bag types. The proportion of material remaining was arcsine square root transformed before analysis (Zar 1999) to improve normality and homogeneity (Cochrans Test). Multiple comparisons of means were performed using a Student-Newman-Keuls test (SNK) at the 0.05 level. Each site was analysed separately, as an appropriate model could not be found with site as a random factor; as there were no appropriate mean squares for the denominator for several factors of interest (Underwood 1997).

Leaf Structure

Several parameters were measured to determine the degree of sclerophylly of the four leaves used. The initial moisture content of each leaf type was determined by oven drying at 60°C, for 72 hours on the day of collection. Samples were then reweighed and the mass difference determined. The sclerophylly of a leaf is related to its density and leaf mass per unit area (LMA) (Groom & Mamont 1999; Witkowski & Lamont 1991)

Leaf area was determined on ten leaves by scanning them and analysing in AutoCAD

2000 (AutoCAD 2000). Leaf thickness was measured with vernier callipers at the widest part of the leaf. LMA was determined by dividing air dried mass by area. Leaf density was determined by dividing LMA by thickness. The area of C. monilifera leaves was determined before drying, as the leaves curled and changed shape.

Environmental Differences between Weed Infested and Un-infested Areas

Soil Moisture

Eighteen soil samples were taken per site along two 20m transects. A 7cm diameter core was taken to the A1 horizon. The approximate depth of the A1 horizon at

Anna Bay was 15cm, Seven Mile Beach 50cm, Warrain beach 35cm, and Jervis Bay

40cm. Samples were stored in airtight plastic bags and transported in insulated containers. Sieved (2mm) soil was weighed (~60g) in aluminium trays and dried for three days at 105°C, before being re-weighed. The percent moisture dry weight was determined by the difference between wet and dry weights. A two-factor analysis of variance was performed on arcsine-transformed data, to determine if moisture varied between weed infested and un-infested areas (fixed factor) for all sites (random factor).

A SNK post-hoc test was performed at the 0.05 level.

Soil Surface Temperature

The soil surface temperature was measured at Jervis Bay, Warrain Beach and

Seven Mile Beach in spring 2002 using digital thermometer ibuttons. The top organic leaf litter layer was removed to expose the soil surface and the data loggers placed inside large mesh bags to prevent them moving. Four buttons were randomly placed at each site. The temperature was recorded every hour for seven days. Data was divided into night (6pm-5am) and day (6am-5pm) for analysis. A three factor ANOVA was performed to determine if the maximum temperature varied at each site (random factor), within the weed infested and un-infested areas (fixed factor) and at day and night time

(fixed factor). A SNK post-hoc test was performed at the 0.05 level.

Light Transmittance

A light sensor was used to measure the relative light intensity in light moles/m2 at ground level at Seven Mile Beach, Comerong Island, Warrain Beach and Jervis Bay.

Readings above the vegetation and 5cm above ground level were taken every 1m along two 20m transects. If a reading could not be taken above the vegetation because it was too tall, a reading was taken in the open. This was done between 10am and 2pm in spring when there was little cloud cover. The percent mean transmittance was calculated. A two-factor analysis of variance was performed on 4th root arcsine transformed data to determine if light transmittance was lower in weed infested areas than in un-infested areas (fixed factor), for all sites (random factor).

Results

Decomposition Study

The C. monilifera leaves decomposed much faster than the native leaf mix

(F1,94= 324-729, P=0.001) (Table 2.2). This occurred in both habitats and bag types

(Figure 2.1). Leaf material remained in all native litterbags on the last collection, whereas most C. monilifera leaves had completely decomposed.

At Warrain Beach decomposition was faster in the C. monilifera areas than in the native areas (F1,91 =8.81, P=0.004). At Seven Mile Beach and Comerong Island only the C. monilifera leaves decomposed faster within the C. monilifera areas than the native areas (F1,94 =9.71, P=0.002 and F1,96 =4.86, P=0.03). At Jervis Bay there was a non-significant trend for C. monilifera leaves to decompose faster in the C. monilifera area.

Native leaf decomposition was generally unaffected by the habitat type. At Anna

Bay only the native coarse bag treatment decomposed faster in the C. monilifera area

(F1,95 =13.5, P=0.001) and at Warrain Beach all treatments were faster in the C. monilifera area (F1,91 =8.81, P=0.004).

At Jervis Bay decomposition was faster within the coarse bag treatments than the fine (F1,92 =6.24, P=0.014). Only the C. monilifera leaves decomposed faster within the coarse litterbags than in the fine at Seven Mile Beach (F1,94 =15.4, P=0.001) and

Comerong Island (F1,96 =4.61, P=0.034). This trend was also evident at Warrain Beach.

At these sites the native leaf mix tended not to decompose significantly faster in the coarse bags within a habitat type.

There were differences in the decay rates between sites. Overall, leaves decayed the fastest at Jervis Bay. Seven Mile Beach and Warrain Beach had intermediate rates, and Comerong Island and Anna Bay were the slowest (Table 2.3).

Figure 2.1: The mean percentage of the original weight remaining in small and large litterbags in C. monilifera (bitou) and native un-infested areas, through time pooled across all sites. Error bars are one standard error.

100 Native fine in bitou Native fine in native 90 Native coarse in bitou Native coarse in native Bitou fine in native 80 Bitou fine in bitou Bitou coarse in native 70 Bitou coarse in bitou

60 g 50

20 Percent mass remainin

0 0 2 4 6 8 101214161820 Months

Table 2.2: Summary of a four-factor ANOVA for each field site for the mean mass lost of C. monilifera and native leaves with time. The leaves were either in coarse or fine litterbags (Bag type) in a C. monilifera infested area or a native un-infested area (Weed). Anna Bay Seven Mile Beach Jervis Bay Comerong Island Warrain Beach Source d.f. F P d.f. F P d.f. F P d.f. F P d.f. F P Weed 1 0.157 0.690 1 3.90 0.051 1 2.89 0.093 1 23.0 0.001 1 8.81 0.004 Leaf type 1 729 0.001 1 560 0.001 1 432 0.001 1 444 0.001 1 324 0.001 Bag type 1 4.59 0.035 1 47.3 0.001 1 6.24 0.014 1 2.14 0.150 1 0.197 0.660 Time 3 24.4 0.001 3 47.7 0.001 3 29.4 0.001 3 26.7 0.001 3 13.9 0.001 Weed x Leaf 1 2.41 0.120 1 9.71 0.002 1 0.056 0.810 1 4.86 0.030 1 0.028 0.870 Weed x Bag 1 4.99 0.028 1 2.48 0.119 1 0.040 0.840 1 1.77 0.190 1 0.960 0.330 Weed x Time 3 1.85 0.140 3 2.94 0.037 3 0.801 0.500 3 0.612 0.610 3 0.720 0.540 Leaf x Bag 1 1.59 0.210 1 15.4 0.001 1 0.235 0.630 1 4.61 0.034 1 0.001 0.980 Leaf x Time 3 0.56 0.640 3 0.450 0.001 3 0.365 0.790 3 0.438 0.730 3 0.440 0.730 Bag x Time 3 4.12 0.009 3 2.66 0.720 3 0.576 0.630 3 0.295 0.830 3 0.250 0.860 Weed x Leaf x Bag 1 13.5 0.001 1 0.031 0.053 1 1.08 0.301 1 0.729 0.400 1 2.33 0.130 Weed x Leaf x Time 3 1.23 0.300 3 0.440 0.860 3 1.28 0.290 3 0.417 0.740 3 0.450 0.720 Weed x Bag x Time 3 0.530 0.670 3 1.23 0.720 3 0.955 0.420 3 0.053 0.980 3 0.160 0.920 Leaf x Bag x Time 3 0.610 0.610 3 1.64 0.300 3 0.621 0.600 3 0.731 0.540 3 0.520 0.670 Weed x Leaf x Bag x Time 3 0.820 0.490 3 1.00 0.190 3 0.397 0.760 3 1.77 0.120 3 0.390 0.760 Error 95 94 92 96 91 P<0.05 significance level

Table 2.3. The mean percent original mass remaining for all time periods, for each leaf type within each habitat at each site. Percent Original Mass Remaining

C. monilifera Leaves Native Leaves Site C. monilifera Native area C. monilifera Native area

area area

Anna Bay 22.1 19.0 53.0 54.0

Seven Mile Beach 17.2 16.1 45.4 51.3

Comerong Island 17.9 21.7 47.8 52.4

Warrain Beach 14.9 19.2 44.8 49.4

Jervis Bay 13.1 16.0 45.3 47.5

Decomposition Constants

Decomposition of the native litter mix fitted the single exponential decay model better than the double exponential decay model based on the regression coefficients

(Figure 2.2a, Table 2.4). For the double exponential decay model, A was calculated as

0.42 from the nutrient values (Table 2.5). The results were highly variable as shown by the large standard errors in Figure 1. As a result, the ANOVA analyses were unclear on the effect of weed infestation on native leaf decomposition; however the decay constants indicate that native leaves do decay faster in the C. monilifera areas (Table

2.4). The decomposition results reinforced the ANOVA results for the effect of mesh size on decay rates, with the coarse bag treatment being faster than the fine treatment in

C. monilifera areas, where as there was little difference within the native areas (Table

2.4).

The double exponential decay model explained C. monilifera decay better than the single exponential model based on the regression coefficients (Figure 2.2b, Table

2.4). The constant A was calculated as 0.47 (Table 2.5). The k2 values were more influenced by the treatment type than k1, with all having a rapid initial decay. The trends in the ANOVA results were again reinforced by the decomposition constants. When comparing k2 values, the coarse mesh treatment was faster than the fine in both habitats and both mesh sizes decayed faster within the C. monilifera infestations (Table 2.4).

Table 2.4. The decomposition constants (k) for the single and double exponential decay models. The regression coefficients (R2) for the double exponential decay model were calculated from observed vs. predicted values.

Single Exponential Double Exponential Model Model

Litter K K1 K2 Decay time Habitat R2 R2 Bag (yr-1) (yr-1) (yr-1) 99% (yrs)

Weed 1.48 0.88 4.19 0.532 0.79 3.11 NC Native 0.970 0.93 3.68 -0.255 0.70 4.75

Weed 1.12 0.73 4.46 0.232 0.65 4.11 NF Native 1.04 0.80 4.08 0.193 0.69 4.43

Weed 7.20 0.89 19.7 4.30 0.96 0.923 CC Native 6.30 0.77 19.9 3.70 0.95 1.07

Weed 6.60 0.76 19.8 3.41 0.91 1.16 CF Native 6.33 0.71 18.9 3.14 0.91 1.26

NC: Native coarse, NF: native fine, CF: C. monilifera fine, CC: C. monilifera coarse

Figure 2.2. The fitted curves from a, the single exponential decay model for the native leaf mix litterbags and b, the double exponential decay model for C. monilifera litterbags.

100

90 Native coarse in bitou Native coarse in native

80 Native fine in bitou Native fine in native

70 g

20 Percent original mass remainain 10

0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Time (years)

100

90 Bitou coarse in bitou Bitou coarse in native 80 Bitou fine in bitou Bitou fine in native 70 g 60

Percent original mass remainain 10

0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Time (years)

Table 2.5. The mean initial leaf carbon and nitrogen concentrations of each species, and the native leaf mixture, ± one standard error

Species Carbon (%) Nitrogen (%) C:N ratio

C. monilfera 39.4±1.7 1.9±0.2 20.7

L. laevigatum 51.5±0.5 1.4 ±0.2 36.8

A. longifolia 49.8±0.2 2.6 ±0.4 19.2

B. integrifolia 50.2±0.7 1.2 ±0.02 41.8

Native mix 50.5±0.5 1.7±0.2 29.7

Leaf Quality

The native leaves all had a higher percentage of carbon then the C. monilifera leaves (Table 2.5). A. longifolia leaves had the lowest C:N ratio, followed closely by the

C. monilifera leaves.

The C. monilifera leaves were moister than the native leaves (Table 2.6), and native leaves were denser and had higher LMA values than C. monilifera leaves. A. longifolia and L. laevigatum leaves were thicker than C. monilifera leaves. The L. laevigatum leaves had the highest density, whereas the A. longifolia phyllodes were the thickest and had the highest LMA (Table 2.6).

Table 2.6: The percent moisture and physical leaf parameters for each species.

Moisture Thickness LMA Density

(%) (mm) (µg mm-2) (µg mm-3)

C. monilifera 90.0±0.08 0.57±0.02 90.8±7.6 160.1±16.4

L. laevigatum 58.8±0.64 0.79±0.01 152.5±5.9 817.0±24.2

A. longifolia 73.6±1.6 0.87±0.07 278.7±23.7 324.3±17.1

B. integrifolia 46.4±4.9 0.48±0.02 268.0±9.4 557.1±16.1

LMA: leaf mass area

Environmental Differences between Weed Infested and Un-infested Areas

The C. monilifera areas at Anna Bay, Comerong Island and Warrain Beach were all significantly moister than the native areas (F4,169=50.1, P=0.001) (Table 2.7, Figure

2.3). The Seven Mile C. monilifera area was moister than the native area (Figure 2.3), but not significantly. The Jervis Bay results were the opposite, with the native area being moister (F4,169=50.1, P=0.001). This difference is likely to be due to this site being located on a cliff top, not a sand dune. Higher moisture levels were obtained towards the cliff edge, suggesting poor drainage.

Table 2.7: Summary of a two-factor ANOVA, performed to determine the difference in soil moisture between the C. monilifera infested areas and native un-infested areas at each site.

Source d.f. Mean-Square F P

Site 4 766.0 1.51 0.374

Weed 1 450.0 0.890 0.544

Site x Weed 4 506.5 50.1 <0.001

Error 169 10.11

P<0.05 significance level.

Figure 2.3: The mean percent soil moisture (dry weight) within the C. monilifera invaded (bitou) and un-infested (native) areas of each field site. Error bars are one standard error

25 Native Bitou

Percent Soil Moisture 5

0 Anna Bay Seven Mile Comerong Warrain Jervis Bay Beach Island Beach

The rainfall was higher than average during the study. Normally there is less then 200mm difference in annual precipitation across all sites (Australian Bureau of

Meteorology). However, Anna Bay received more than double the rainfall of Seven

Mile Beach during the study (Figure 2.4). The two sites with the highest rainfall also had the highest soil moisture.

Figure 2.4: The total precipitation at each field site during the decomposition study

(November 2000 to June 2002)

3500

3000

2500

2000

1500

1000 Total precipitation (mm)

500

0 Anna Bay Seven Mile Beach Comerong Island Warrain Beach Jervis Bay

The soil surface temperature differed at each site amongst habitats and time periods (3 way interaction, F2,2988=95.6, P=0.001) (Table 2.8). The soil surface within the C. monilifera areas of Seven Mile Beach and Warrain Beach were significantly cooler than the native areas during the day (Figure 2.5). At Warrain beach the C. monilifera area were warmer during the night. The results were again the opposite at

Jervis Bay, with the native site being significantly cooler then the C. monilifera site during the day and warmer during the night (F2,2988=95.6, P=0.001) (Figure 2.5).

Table 2.8: Summary of a three-factor ANOVA performed to determine the difference in soil surface temperatures at day (6am-5pm) and night (6pm-5am) within the C. monilifera invaded and native un-infested areas at each site.

Source d.f. Mean-Square F ratio P

Site 2 250.7 19.2 <0.001

Weed 1 788.3 1.95 0.297

Time 1 20291 86.0 0.011

Site x Time 2 235.9 18.1 <0.001

Site x Weed 2 404.5 31.1 <0.001

Time x Weed 1 288.0 0.231 0.678

Site x Time x weed 2 1245 95.6 <0.001

Error 2988 13.03

P<0.05 significance level.

Figure 2.5: The average day (6am-5pm) and night (6pm-5am) soil surface temperatures at three sites, in C. monilifera infested (bitou) or native un-infested areas. The error bars are one standard error. Included are the results of the SNK post-hoc test, a b denotes significant difference, a a indicates not significantly different.

Native 25 Bitou b a a

a 20 b b a a a b b a 15

10 Temperature (°C)

0 Seven Mile Day Seven Mile Night Warrain Beach Warrain Beach Jervis Bay Day Jervis Bay Night Day Night

The percent light transmittance was much lower in all C. monilifera areas than the native areas (F1,3= 46.1, P=0.007) (Table 2.9, Figure 2.6). The maximum value in the native area was 98% but only 15.2% for the C. monilifera areas. The large standard errors in Figure 2.6 show how variable the results were for the native areas, reflecting the diversity in vegetation.

Table 2.9: Summary of a two-factor ANOVA performed to determine the difference in percent light transmittance between C. monilifera infested and native areas at each site.

Source d.f. Mean-Square F P

Site 3 575.3 3.7 0.012

Weed 1 13460 46.1 0.007

Site x weed 3 310.3 1.99 0.115

Error 307 155.6

P<0.05 significance level.

Figure 2.6: The mean percent light transmittance at four sites, within the C. monilifera infested (bitou) or native un-infested areas. Error bars are one standard error

Native 30 Bitou

10 Percent light transmittance 5

0 Seven Mile Beach Comerong Island Warrain Beach Jervis Bay

Discussion

Environmental Parameters

C. monilifera invasion appears to change several environmental parameters and consequently alter the microclimate. This combined with the high quality C. monilifera leaf litter results in rapid leaf litter decomposition. The decomposition constants, (k2) were faster for the C. monilifera leaves within the C. monilifera infestations with this clearly reflected in the faster times for 99% decay (Table 2.5). There was a similar pattern for the native leaves, especially the coarse bag treatments, which decomposed faster within the C. monilifera areas.

In temperate climates adequate soil moisture is required for rapid decomposition

(Heneghan et al. 1999; Meentemeyer 1978). Sand dunes are dry areas, and changes in moisture within dry areas can have large impacts on decomposition (Murphy et al.

1998). Overall Jervis Bay had the fastest decomposition rates, with the moistest native cliff area and the second moistest C. monilifera area (Figure 2.3). In contrast, Comerong

Island was the driest site with the slowest decay within a native area and the second slowest decay within a C. monilifera area. The C. monilifera leaves also had a higher moister content than the native leaves, so the leaf litter layer under C. monilifera is probably also moister, which would further enhance decomposition.

Temperature and moisture interact in a complicated manner in controlling leaf litter decomposition. The response also depends on the initial soil microclimate and the microorganisms present (Couteaux et al. 1995; Guo & Sims 2001; Shaw & Harte 2001).

The areas invaded by C. monilifera were generally moister and cooler than the uninvaded native areas. The magnitude of difference between sites was greater for moisture than temperature. The higher temperatures within the native areas had minimal effects on mass loss, most likely due to the lack of moisture (Murphy et al. 1998).

Moisture is critical to decomposition rates in many Australian forests, especially during summer (Woods & Raison 1982), and it appears to be one of the limiting factors to leaf litter decomposition on the sand dunes. The high quality leaf litter and moist protective environment within dense C. monilifera infestations, results in rapid leaf litter decomposition.

Environmental conditions influence which microorganisms will be present to break down plant debris, and controls their metabolism (Couteaux et al. 1995). C. monilifera invasion appears to change several environmental parameters and consequently alter the microclimate. The C. monilifera sites had a much lower light transmittance with little light detected at ground level (Figure 2.6). The dense infestations were almost monocultures with a closed canopy and few gaps. This gave protection to the ground and leaf litter beneath. The uninvaded foredunes were a mixture of herbs, grasses, ferns and shrubs of various heights and canopy cover. This produced a variable light transmittance across the sites. More of the ground litter within the native areas is exposed and could be desiccated by the sun and wind, especially as it takes considerably longer to decompose.

Soil surface temperature was related to soil moisture and light transmittance.

The native areas of Seven Mile Beach and Warrain Beach were several degrees warmer than the native areas during the day (Figure 2.5). These areas had low soil moisture and high light transmittance (Guo & Sims 2001). At Jervis Bay the results were the opposite, with the native cliff area being cooler then the C. monilifera area during the day. This area had the highest soil moisture and lowest light transmittance of all native areas.

Decomposition Rates

For the C. monilifera leaves the double exponential decay model explained more of the variation than the single exponential decay model (Table 2.4). This model is considered to be more realistic as it separates decomposition into two stages (O'Connell

1987). The initial stage is faster, represented by k1, and involves soluble components leaching out, and easily degraded compounds (sugars, starches, proteins) being utilised by decomposers, usually microorganisms (Crossley & Hoglund 1962; Songwe et al.

1995). The initial mass loss was fastest in the first eight months for all treatments

(Figure 2.1). It was extremely rapid for C. monilifera, indicating these leaves contain more soluble compounds or simple sugars and soft leaf tissue than the native leaves. k2 represents the second stage of decomposition, and involves the breakdown of resistant components, including cellulose, waxes, tannins and lignin (Lousier & Parkinson 1976).

With time the relative amount of recalcitrant material increases and the rate decreases

(Wieder & Lang 1982). k2 was considerably lower then k1 for all C. monilifera leaf treatments. The treatment type (ie. bag type, leaf type and habitat) also had more impact on the k2 values.

The single exponential decay model explained more of the variation in the native leaf decomposition than the double exponential decay model. However, there was a large bias in the decay constant, with the model trying to fit to the initial rapid loss of labile components (Spain & Le Feuvre 1987). This is evident for all treatments, with the model over estimating mass loss as time increased. With complete decomposition data the double exponential model may have explained more variance in the data, and made more accurate long-term predictions. The decomposition rates for the native leaf mix are comparable to that found by Maggs and Pearson (1977a). They determined that the mean turnover time for the litter layer in coastal scrub in Sydney N.S.W was 3.8 years.

In this study the time for 99% of the native leaf mix to decay in the native areas was calculated to be between four and five years (Table 2.3). It would naturally take longer than this, as the decomposition constants were determined using fresh leaves. These have a higher nutrient content than senescent leaves and will consequently decompose faster.

Leaf Quality

The initial C:N ratio and nitrogen concentration of leaves have been used to predict decomposition rates (Meentemeyer 1978; Mellio et al. 1982) as nitrogen is essential but often limiting to the growth of the decomposer community, especially microbes (Palm & Rowland 1997). However in this study the C:N ratio did not predict the decomposition of all species. The A. longifolia and C. monilifera leaves had similar

C:N ratios, which were considerably lower than the C:N ratios for the B. integrifolia and L. laevigatum leaves (Table 2.5). Low C:N ratios are often associated with fast decomposing nutritious leaves, where as leaves with high C:N ratios, like that obtained for B. integrifolia and L. laevigatum, are generally tough and resistant to the early stages of decomposition (Blair 1988; Taylor et al. 1989; Witkamp 1966). The C. monilifera leaves decayed the fastest, yet the A. longifolia leaves were still observed in the mixed litterbags on the final collection. The high nitrogen concentration of the A. longifolia leaves is probably due to this plant being an active nitrogen fixer (Lawrie 1981).

Litter quality and physical leaf characteristics have been suggested as better predictors of decomposition rates (Akanil & Middleton 1997; Gallardo & Merino 1993;

Hobbie 2000). They also reflect the chemical properties of the leaf (Palm & Rowland

1997) and the palatability to soil fauna (Witkamp 1966). The more sclerophyllous and tough a leaf, the poorer the carbon quality and the slower the decay (Akanil &

Middleton 1997; Gallardo & Merino 1993; Hobbie 2000). Sclerophyllous leaves have extra structural tissue, generally from increased cell lignification or cutinization

(Dickson 2000). Density and LMA are good indicators of sclerophylly, with values increasing as leaves become more sclerophyllous (Groom & Mamont 1999; Witkowski

& Lamont 1991). The native leaves were low in moisture and had high density and

LMA values (Table 2.5). The A. longifolia leaves had the highest lamina thickness and

LMA values. This is related to their stem morphology (phyllodes), which incorporates many fibres and a thick cuticle (New 1984). In contrast, the C. monilifera leaves were very moist, and had low LMA and density values. Therefore, the extra cellulose, hemicellulose and/or lignin in the native leaves slowed their decomposition (Hobbie

2000). The thick cell walls and thick cuticles could also retard decomposition by preventing toxic compounds from leaching out and/or reduce fungal penetration (Pereira et al. 1998).

Low LMA, which is the inverse of specific leaf area, is also a characteristics common to many exotic invasive species (Lake & Leishman In Press; Williams &

Alastair 1996). This attribute is thought to add to the invasiveness of a weed by increasing its ability to capture and maintain space over native species. It is also an indicator of a weeds potential for fast growth (Lake & Leishman In Press).

Leaf Litter Invertebrates

Many studies have shown that invertebrates and microbes will invade litter bags and consequently simple microclimates will form (Anderson 1975; Crossley & Hoglund

1962; Vossbrink et al. 1979). The effect invertebrates have on decomposition appears to be highly variable, but positive (Douce & Crossley 1982; Heneghan et al. 1999; Santos

& Whitford 1981). For the native leaf mix at most sites, the coarse bag treatment did not

44 decay significantly faster than the fine bag treatment, indicating the leaf litter invertebrates didn’t greatly enhance decay. Leaf species and quality affects arthropod and microbial diversity and density (Blair et al. 1990; Heneghan et al. 1999; Wiegert

1974). Tough leaves with higher C:N ratios are a low quality food source, with lower palatability and digestibility to mesofauna (Witkamp 1966). If the leaves were left until they were fully decomposed and the C:N ratio lowered, the leaves could have become more appealing to the invertebrates and more of an impact might have been evident.

The C. monilifera leaves in the coarse treatment decomposed slightly faster than the fine bag treatment, especially within the C. monilifera areas. This is clearly indicated in the k2 values (Table 2.4). Therefore, leaf litter invertebrates had a positive impact on C. monilifera decay. Invertebrates enhance decomposition by directly feeding on leaf material, and indirectly by inoculating litter with microflora and stimulating microbes (Douce & Crossley 1982; Seastedt 1984). The invertebrates increased decomposition by up to 20%. The C. monilifera leaves are high in moisture, which would aid microbial and fungal colonisation (Couteaux et al. 1995).

Site Variation

The decomposition rates varied between sites, due to local climate and geography. The C. monilifera area at Anna Bay had the highest soil moisture and the slowest decomposition rate of all the C. monilifera areas. This soil contains 11% clay, and has lower permeability than the other sites (Murphy 1995). Combining this with the heavy rainfall (Figure 2.4), the soil could have become saturated. Anaerobic conditions may have resulted, and decomposition impaired (Couteaux et al. 1995).

Decomposition and microclimate results were consistently opposite at the Jervis

Bay native area. This was the only B. integrifolia L. laevigatum heath within this

45 national park not to be affected by weeds. Being located behind a cliff edge, not on a sand dune, the leaf litter and vegetation were highly protected. This combined with the poorer soil drainage and old vegetation age, made the microclimate similar to the C. monilifera areas. These results reinforce how decomposition can be influenced by microclimate and soil properties.

Conclusion

This study has established that weed infestations can alter ecosystem processes in coastal sand dunes. C. monilifera leaves decompose faster than those of the common coastal shrubs B. integrifolia, L. laevigatum and A. longifolia. Dense infestations of C. monilifera alter the decomposition process by increasing the quality of the leaf litter layer and modifying the microclimate. This is likely to have implications for other elements in the ecosystem, such as the soil microflora and may result in the system being less resilient to perturbations, or other climatic impacts that adversely affect this weed compared with the native species. The rapid decomposition within C. monilifera infestations is likely to increase the speed of nutrient cycling on the sand dunes, leading to alterations in soil nutrient availability. Ultimately, the nutrient cycling regime could shift to one that favours C. monilifera at the expense of native vegetation. Increasing the rates of nutrient cycling may influence the rate of loss of nutrients from the ecosystem, especially as sand has a low retention capacity. Such impacts have rarely been measured in coastal systems, and yet the consequences of weed invasion could be extensive.

Chapter 3

Nutrient cycling and litterfall in coastal areas invaded by

Chrysanthemoides monilifera ssp. rotundata

Submitted to Journal of Applied Ecology

Introduction

Litterfall plays a major role in energy and nutrient transfer, maintaining soil fertility (Lavelle et al. 1996) and replenishing soil organic matter (Ashton 1975).

Inorganic nutrients within litter are made available to plants by being leached from the litter or mineralised by microbes. These process can regulate nutrient availability

(Couteaux et al. 1995, Lavelle et al. 1996) and subsequently plant growth

(Ananthakrishnan 1996). Nutrient dynamics are affected by the litter quality (Berg and

Staff 1981), microclimate (Meentemeyer 1978), and the microbial and litter fauna

(Reichle 1977, Seastedt and Crossley 1984). Fungi and bacteria are responsible for most of the organic matter breakdown (Seastedt 1984). However, litter invertebrates can increase the nutrient loss by reducing litter to fine particles (Seastedt and Crossley 1980,

Attiwill and Adams 1993) and can be important in regulating mineralisation and immobilisation of nitrogen (Parker et al. 1984). Invertebrates also further enhance these processes by affecting the community composition and activity of microbes (Seastedt and Crossley 1980).

Weed invasion can change ecosystem processes, especially if the invasive species changes the flow of energy and materials (Chapin et al. 2000). Numerous weed invasions have altered nutrient cycling, especially nitrogen which is often limiting

(Vitousek et al. 1987, Matson 1990, Fogarty and Facelli 1999, Standish et al. 2004).

This can decrease ecosystem stability (Evans et al. 2001, McIvor 2001) and modify primary productivity, plant species composition and species diversity (Wedin and

Tilman 1990, Maron and Connors 1996). Alterations in the litterfall and litter layer can also have consequences for the litter fauna (McIvor 2001).

There are strong positive feedbacks between plant species composition and soil properties, such that introduction of a new species can change nutrient cycling (Wedin

49 and Tilman 1990, Hobbs 1991) and soil properties (Ehrenfeld 2001). It has been proposed that the ability to change soil based ecosystem processes may be an important characteristic that enables an exotic species to invaded and spread (Fogarty and Facelli

1999, Ehrenfeld et al. 2001).

Many weeds produce leaf litter of different quality and quantity to the community it invades. Changes in the leaf litter available to the decomposer community can alter the decomposition rate (Pereira et al. 1998, Ehrenfeld et al. 2001) and subsequently nutrient cycling (Knoepp et al. 2000). For example in North America the invasive grass Bromus tectorum produces more litter of a lower quality. This decreased the potential rates of net nitrogen mineralisation, by decreasing the nitrogen available for microbial activity during decomposition (Evans et al. 2001). This has lead to a decrease in soil inorganic nitrogen. In South Africa the weeds Acacia saligna and

Acacia cyclops also produce more litter, but with a higher nitrogen concentration than the native fynbos species (Witkowski 1991). This has increased the available soil nitrogen and increased the soil pH, resulting in changes to the vegetations growth form and species composition (Musil and Midgley 1990). Berberis thunbergii is an exotic shrub that has invaded deciduous forests in the U.S.A (Ehrenfeld et al. 2001). The litter is higher in nitrogen and decomposes more readily than that from the native shrubs.

This resulted in higher net mineralisation rates and an increase in soil pH. Favoured uptake of nitrate by the exotic shrub was proposed as the mechanism for the pH elevation (Ehrenfeld et al. 2001).

Chrysanthemoides monilifera ssp. rotundata is an environmental weed occurring along the south east coast of Australia. It is highly persistent (Csurches and Edwards

1998) and is the dominant species on over 36000 ha of headlands and sand dunes

(Thomas and Leys 2002). This evergreen shrub was planted to stabilise sand dunes after

50 disturbance (Weiss 1986, Humphries et al. 1991), but increased wind erosion occurs when the infestation ages (Stanley et al. 1989, Thomas 1997). C. monilifera is very competitive (Toth et al. 1996) and displaces native shrubs (Weiss and Noble 1984). One of the species it frequently displaces is the legume Acacia longifolia. C. monilifera has a greater reproductive output than native shrubs (Weiss 1984), and in highly infested areas there is a shift towards simpler vegetation, approaching a monoculture (Dodkin and Gilmore 1985, Thomas 1997). The leaf litter and soil within C. monilifera infestations have been shown to impede the germination and growth of native seedlings

(Vranjic et al. 2000), and this alleopathy may aid invasion (Copeland 1985). The rate of spread of C. monilifera is enhanced by disturbance and the New South Wales coastline has a history of disturbance and exploitation (Love 1984, Humphries et al. 1991).

Coastal dune soils, especially those in Australia, have a low nutrient status and are deficient in phosphorous and nitrogen (Groves 1981, Skiba and Wainbright 1984).

Productivity is nutrient limited and the soil nitrification process is not very active, with most soils having a C:N ratio exceeding 15 (Specht 1979, Groves 1981). A change in nutrient cycling following weed invasion may have important effects on the regeneration of native species. These changes may highlight the mechanisms for invasion, which could assist in the management of C. monilifera. In order to investigate if C. monilifera changes the nutrient cycle in coastal shrublands three main processes were assessed. The native sclerophyllous vegetation was compared with long-term C. monilifera infestations with regards to (1) soil nitrogen availability and soil physical properties, (2) litter production and accumulation and (3) nutrient release from decaying litter.

Methods

Study Sites

Five study sites were chosen along the New South Wales coastlinefrom Anna

Bay (32°46’S, 152°05’E), to Jervis Bay (35°08’S, 150°40’E). Within each site, two 30 x

30m areas were chosen at least 100m apart. One area was heavily infested with C. monilifera, with a minimum 70% cover, and the other area was un-infested. No chemical or mechanical weed control work had been undertaken on the C. monilifera for at least ten years and all infestations were estimated to be between 22 and 33 years old.

The dominant vegetation within the un-infested native areas consisted of the shrubs Acacia longifolia var. longifolia or Acacia longifolia var. sophorae, Banksia integrifolia and Leptospermum laevigatum. Westringia fruticosa was also dominant at

Anna Bay. The understorey in the native sites consisted of ferns (eg. Pteridium esculentum), grasses (eg. Themeda australis) and herbs (eg. Lomandra longifolia).

These vegetation communities are commonly known as foredune shrublands and foredune thickets (Carolin & Clarke 1991). There was little to no vegetation present underneath the C. monilifera.

Sites were located on sand dunes, except for the native area at Jervis Bay, which was situated on top of a 25m sandstone cliff (Taylor et al. 1995). This was the only site with the required vegetation community not infested by weeds within the area. The soil types ranged from loose loamy quartz sands to sandy clay loams (Hazelton 1992;

Murphy 1995; Taylor et al. 1995). The most northern site, at Anna Bay, has a mean maximum day temperature of 23.1°C and a minimum of 12.9°C. The mean annual rainfall is 1342mm. Sites further south on the coastline are cooler and receive slightly less rainfall with Jervis Bay having a mean maximum day temperature of 19.9°C, a

52 minimum of 13.6°C and a mean annual rainfall of 1244mm (Australian Bureau of

Meteorology).

Soil Analysis

Twelve soil samples were collected at each site along two 20m transects during spring and summer 2002 within each plot. The samples were taken to the A1 horizon with a 7cm diameter auger at Anna Bay (15cm) and Comerong Is. (25cm). The A1 horizon was deeper than 30cm at Seven Mile Beach, Warrain Beach and Jervis Bay, therefore a 20cm sample was taken. The soil was placed in sealed plastic bags, and transported in an insulated container. The soil was dried at 37°C for 3 days in a drying oven and sieved (2mm).

Soil Nitrogen

For nitrogen analysis the twelve samples were combined into four samples. The samples combined were those taken adjacent to each other along the transects. Samples

(1g) were analysed for total nitrogen using a Leco Analyser (CNS2000) with a thermal conductivity detector.

Samples from Seven Mile Beach, Comerong Island and Warrain Beach were also analysed for ammonia and nitrate plus nitrite. The soil (3g) was extracted with 2M

KCl (30ml) and analysed using an automated segmented flow (injection) analyser with in line dialyser on both channels. Soil analysis was performed by C.S.I.R.O Forestry and Forest Products Plantation Forest Research Centre.

A two factor ANOVA was performed to determine the difference in soil nitrogen, nitrate and ammonia between weed and native areas (fixed) at each site

(random). The total nitrogen data was arcsine transformed to improve normality and homogeneity.

Soil pH

Soil pH was measured and compared in the weed and native sites, as the soil chemistry can be altered by the vegetation community it supports (Ehrenfeld 2001).

Air-dry sieved (2mm) soil was weighed (5g) and mixed with a 0.01M CaCl2.2H2O solution (25ml), to form a 1:5 ratio. Samples were periodically stirred over 60min, and then left to settle for 30min. The pH of the supernatant was then measured with a pH meter (Combination electrode) without stirring (Rayment & Higginson 1992). The pH meter was calibrated using commercial pH 7 and pH 4 (Sigma Aldrich) solutions.

Bulk density

Plants can modify the physical arrangement of the soil, their roots can affect pore size distribution and the chemistry of their litter can change the nature and amount of organic matter present (Ehrenfeld 2001; Millar et al. 1966). Bulk density is dependent on many factors including the density of the constituent soil particles and their packing arrangement (White 1997). Six samples were taken at each site for bulk density measurement along the same transects as for the pH and nutrient samples.

Soil was collected using a fixed volume steel core-sampling device (Volume = 7.577 x

10-4m3). The soil was weighed upon return to the laboratory and dried in aluminium trays in a drying oven (105°C) for three days. Samples were reweighed and bulk density

3 (Pdry) calculated as mass of soil per m . A two factor ANOVA was performed to determine the difference in bulk density between C. monilifera and native areas (fixed) within each field site (random).

Leaf litter

Litterfall

Litterfall was measured by collecting falling material in fixed traps. The traps consisted of a square metal frame (0.5m x 0.5m) covered in nylon netting of mesh size 1 x 1mm. The netting was loose enough to allow the litter to collect below the metal frame. The traps were suspended from trees with rope approximately 1m from the ground. This was to reduce interference from animals such as bandicoots and keep the litter dry, and therefore delay decomposition.

The leaf fall traps were not placed at every site for ease of collection. Three sets of traps were placed in the C. monilifera infested areas of Warrain Beach, Seven Mile

Beach and Jervis Bay. The third site was disbanded after being vandalised and then burnt after it was re-established. Six sets of traps were placed within native areas of three sites. One set was placed at Warrain Beach, two sets at Booderee National Park

Jervis Bay and three sets at Seven Mile Beach. At Jervis Bay the first set was in the main study area and the second in a site 500m to the north. At Seven Mile Beach

National Park one set was within the main study area while the other two were in an area 5km southwest. One site at Seven Mile Beach was dominated by Acacia longifolia, while the remaining five native sites were dominated by Banksia integrifolia and

Leptospermum laevigatum. More native sites were sampled to ensure that the leaf fall was collected for a variety of species.

Traps were placed in sets of eight during May 2001, and emptied after one month and then approximately bimonthly for twelve months. The material was air-dried and sorted into leaves, reproductive parts (flowers, seeds, seed pods, fruits), stems

(twigs, sticks and bark) and other (predominantly faecal matter) then weighed. The presence of Banksia fruits was also noted, as they are heavy and fall infrequently

(Bennett & Attiwill 1996). The A. longifolia phyllodes are treated as leaves throughout.

The litterfall per hectare per day was calculated for the total litter, leaves and reproductive parts and compared between the native and weedy areas.

Leaf Litter Layer

The leaf litter layer was sampled to the soil surface in December 2000, April,

July and October 2001. Four random samples with an area of 2.6m2 were collected at each site. The litter was oven dried (70°C, 24h), sieved to remove sand and weighed. To investigate the differences in litter composition the litter was sorted into leaves and woody material (sticks, twigs and bark), and weighed on the last two collecitons. The difference in litter and leaf weight between C. monilifera and native areas (fixed) within each field site (random) with time (fixed) was determined using a three factor analysis of variance (ANOVA).

Leaf Nutrient Analysis

Fully expanded green leaves and recently abscised leaves of B. integrifolia, A. longifolia, L. laevigatum and C. monilifera were collected from each field site and pooled into two samples for each species for nutrient analysis. The leaves were oven dried at 65°C for 72h and finely ground. They were analysed for total carbon, nitrogen and sulphur using a LECO CNS 2000 TM analyser. Total phosphorous was measured as described by Rayment and Higgens (1992). Total potassium was analysed by inductively coupled plasma optimal emission spectrometry (APHA 3120). This was performed by the Environmental Analysis Laboratory at Southern Cross University. The amount of each nutrient withdrawn before abscission was then estimated as:

Percent nutrient absorbed = 100 x (Fresh leaf concentration – dead leaf concentration) Fresh leaf concentration

Nutrient loss from decomposing leaves

To investigate the changes in nutrient composition of decaying leaves with time, leaves form litterbags were analysed for total carbon, nitrogen, sulphur, potassium and phosphorous as outlined above (See Lindsay and French (In Press) for a full description). Four litterbag treatments using fresh leaves were used. This included two mesh sizes (coarse and fine), which were filled with either a native leaf mix (B. integrifolia, A. longifolia, L. laevigatum) or C. monilifera leaves. All treatments were placed in the native and C. monilifera areas of each site. The litterbags were collected on five occasions over 1.7 years. Replicates from each treatment were combined together and a representative sub-sample taken for nutrient analysis. By the fifth collection most of the C. monilifera had decomposed, therefore no results are presented for the last two collections. There was also an insufficient quantity of some C. monilifera samples in the fourth collection for analysis. Several samples were also rejected as they were too contaminated by invertebrate faecal matter or soil.

Results

Soil Nitrogen

The total soil nitrogen was significantly higher in the C. monilifera areas of all sites but Jervis Bay (F 4, 30 =50.8, P= 0.001) (Table 3.1, Figure 3.1). At Jervis Bay the results were the opposite with the native area having the higher nitrogen concentration.

Table 3.1: Summary of the two factor ANOVA results performed to determine the difference in total soil nitrogen concentration between native and C. monilifera invaded areas at each site. P<0.05 significance level.

Source d.f Mean square F P Site 4 3.70 65.8 <0.001 Weed 1 4.17 1.46 0.293 Site x weed 4 2.86 50.8 <0.001 Error 30 0.056

Figure 3.1:The average total percent soil nitrogen within the native and C. monilifera (weed) infested areas of each site. Error bars are one standard error. The weed and native areas of every site were significantly different from each other (P<0.05).

0.5 Native

Weed

0.4 )

0.3

0.2 Total nitrogen concentration (% 0.1

0 Anna Bay Seven Mile Beach Comerong Is. Warrain Beach Jervis Bay

The soil ammonia concentration was significantly higher in the C. monilifera areas (Weed F 1,2 =57.2, P= 0.017) (Table 3.2, Figure 3.2a). The soil nitrate concentration was also significantly higher in the Warrain Beach C. monilifera area (F 2,

18 =7.44, P=0.004, Weed x site) (Table 3.2). The same trend was noted at Comerong Is.

(Figure 3.2b). There was no significant difference in the nitrate concentration at Seven

Mile Beach. The nitrate and ammonia were only a small fraction of the total soil nitrogen, and comprised on average 1.2% of the total nitrogen in the native areas and

0.67% in the C. monilifera areas.

Table 3.2: Summary of the two factor ANOVA results performed to determine the difference in soil ammonia and nitrate concentration between native and C. monilifera invaded areas at each site. P<0.05 significance level.

Ammonia Nitrate

Source Mean Mean d.f F P F P square square

Site 2 0.523 1.08 0.362 0.208 1.35 0.284

Weed 1 2.63 57.2 0.017 1.04 5.01 0.155

Site x weed 2 0.046 0.095 0.91 1.14 7.44 0.004

Error 18 0.485 0.154

Figure 3.2: a. The average soil ammonia and b. the average soil nitrate concentrations

(mg kg-1) within the native and C. monilifera (weed) infested areas of three field sites. a. b.

3 3 Native

Weed

2.5 2.5 )

2 2

1.5 1.5

1 1 Nitrate concnetration (mg/kg Ammonia concentration (mg/kg

0.5 0.5

0 0 Seven Mile Comerong Is. Warrain Beach Seven Mile Comerong Is. Warrain Beach Beach Beach

Soil Properties

The soil bulk density was significantly lower in the C. monilifera areas of Seven

Mile Beach, Anna Bay and Comerong Island (F4, 49= 8.55, P=0.001, weed x site). The same trend was present at Warrain Beach, but there was no significant difference at

Jervis Bay (Table 3.3, Figure 3.3). The largest difference between the native and C. monilifera areas was at Anna Bay.

Table 3.3. Summary of a two factor ANOVA performed to determine the difference in soil bulk density between native and C. monilifera areas at each site. P<0.05 significance level.

Source d.f Mean square F P

Site 4 0.206 12.9 <0.001

Weed 1 0.430 3.23 0.147

Site x weed 4 0.133 8.55 <0.001

Error 49 0.016

-3 Figure 3.3: The soil bulk density (Pdry, g cm ) at each site within the native and C. monilifera (weed) infested areas. * denotes a significant difference.

1.6 Native Weed * 1.4 * * 1.2 **

0.8 *

0.6 Bulk density (g.cm-3) 0.4

0.2

0 Anna Bay Seven Mile Beach Comerong Island Warrain Beach Jervis Bay

There was a large spread in the soil pH values between sites, but there was little variation within a site. The pH was similar at Warrain Beach, Seven Mile Beach and

Comerong Is., with the native areas all slightly acidic, and the C. monilifera areas more acidic (Figure 3.4). The soil at Anna Bay and Jervis Bay was more acidic, especially within the native areas.

Figure 3.4: The average soil pH (1:5 soil/0.01M CaCl2) within the native and C. monilifera (weed) infested areas of each site. Error bars are one standard error.

8 Native

7 Weed

4 pH

0 Anna Bay Seven Mile Beach Comerong Island Warrain Beach Jervis Bay

Leaf fall and ground litter layer

The average annual input of total litter to the native areas was 4800±450 kg ha-1.

The results varied between sites with a range of 3230 to 6110 kg ha-1 at Warrain Beach and Jervis Bay respectively. The average annual litter input to the C. monilifera areas was much lower at 1690±150 kg ha-1 (Figure 3.5). The C. monilifera results were less variable, with a minimum of 1450 kg ha-1 at Seven Mile Beach and a maximum of 2000 kg ha -1 at Warrain beach. In the weed areas, C. monilifera was not the only shrub to contribute to the litterfall; there was a small input from surrounding remnant native vegetation.

Litterfall was highly seasonal in the native areas, peaking in summer (Figure

3.5). There was no clear seasonal variation for C. monilifera. Similar results were obtained for the native sites dominated by either B. integrifolia or L. laevigatum. The

62 litterfall at the A. longifolia dominated site at Seven Mile Beach was similar to these for all seasons but summer, when there was a slightly smaller input.

Figure 3.5: The total litterfall (kg ha day-1) and leaf fall within native and C. monilifera infested areas (weed) averaged for all sites over 12 months (May 2001 to May 2002). Error bars are one standard error.

30 Native total Native leaves Weed total 25 Weed leaves ) 20

Litterfalll (kg/hectare/day 10

0 MJ JASONDJFMAM Collection date (months)

Leaves were the major component of the litterfall all year round in both habitats

(Figure 3.5 and 3.6). The average annual contribution of leaves to the litterfall in the native areas was 2930±140 kg ha–1, whereas it was only 1496±150 kg ha-1 in the C. monilifera areas. There was a consistently small input of reproductive material in the C. monilifera areas all year round (Figure 3.7). The reproductive input in the native sites was much greater and highly seasonal like the litterfall, peaking in spring and summer.

Reproductive parts had a greater contribution to the total litterfall in the native vegetation (Figure 3.6). In the A. longifolia dominated area the traps collected numerous flowers in spring and empty seedpods in summer. In late spring many L. laevigatum flowers, fruits and seed capsules were collected. The woody B. integrifolia fruits fell

63 infrequently, and summer was the only season when notable quantities of seeds were collected.

Figure 3.6: The percent contribution of leaves, sticks, reproductive parts and other to the total litterfall within native and C. monilifera (weed) areas.

100% Other Reproductive Sticks 80% Leaves n

60%

40% Percent Contributio

20%

0% Native Weed

Figure 3.7: The litterfall (kg.ha.day-1) due to reproductive plant parts only (seeds, seed capsules, flowers) from May 2001 to May 2002. Error bars are one standard error.

9 Native

8 Weed

6 )

4 (kg/hectare/day 3

0 MJ JASONDJFMAM Collection date

There was a greater amount of litter on the ground in the native areas of all sites with this significant at Jervis Bay, Comerong Is and Anna Bay (F 4, 120 =6.14, P=0.001)

(Table 3.4, Figure 3.8). The mean litter mass across all native areas was 9600 ± 560 kg ha-1 and in the C. monilifera areas, 3750± 170 kg ha-1. Leaves were the main component of the leaf litter layer in both vegetation types (81±0.02%), as in the litterfall. As a result, there was also a significantly greater mass of leaves in the native areas of most sites (F 4, 60 = 4.68, P= 0.003). Within the C. monilifera litter layer there was also material from native plants, which was mainly woody, from surrounding remnant vegetation and plants that had died following invasion.

Table 3.4: Summary of the three factor ANOVA performed to determine the difference in total ground litter weight per metre squared and leaf weight per metre squared between native and C. monilifera (weed) invaded areas. P<0.05 significance level.

Total Litter weight Leaf weight

Source d.f F ratio P d.f F ratio P

Site 4 1.16 0.333 4 0.881 0.481

Weed 1 6.16 0.067 1 12.3 0.025

Time 3 4.15 0.03 1 0.472 0.531

Site x weed 4 6.14 0.000 4 4.58 0.003

Site x time 12 3.04 0.001 4 5.12 0.001

Weed x time 3 0.964 0.426 1 1.55 0.275

Site x weed x time 12 1.334 0.208 4 1.21 0.314

Error 120 60

Figure 3.8: The average amount of ground leaf litter per metre square within the native and C. monilifera infested (weed) areas of each site. Error bars are one standard error. * denotes a significant difference between the native and weed sample.

1200 Native * Weed * 1000

* 800

* * 600

* 400 Leaf litter per metre square

200

0 Anna Bay Seven Mile Comerong Island Warrain Beach Jervis Bay Beach

Leaf Nutrients

Before abscission a large proportion of most leaf nutrients were reabsorbed (Table 3.5 and 3.6). The carbon and sulphur concentrations were relatively unchanged following abscission in the native and C. monilifera leaves. Similar proportions were withdrawn from the A. longifolia and B. integrifolia leaves, 48-50% of the nitrogen, 77-80% of the phosphorous and 67-70% of the potassium. Similar quantities were also withdrawn from the L. laevigatum and C. monilifera leaves, 60-66% of the nitrogen, 38-58% of the phosphorous and 44-50% of the potassium. As a result of the decrease in nitrogen content the C:N ratio doubled for the native leaves, and almost tripled for the C. monilifera leaves. The C:P ratio also greatly increased in the C. monilifera, A. longifolia and B. integrifolia leaves (Table 3.5 and 3.6).

Table 3.5: The nutrient content of green leaves (± one standard error) and the carbon to nutrient ratios.

Species Nitrogen C:N Phosphorous Potassium Carbon (%) C:P ratio Sulphur (%) C:S ratio (%) ratio (%) (%) C. monilifera 39.4±1.7 1.90±0.20 20.7 0.151±0.01 261 0.280±0.03 141 0.122±0.01 L. laevigatum 51.5±0.5 1.40±0.20 36.8 0.21±0.04 175 0.185±0.02 278 0.932±0.15 A. longifolia 49.8±0.2 2.60±0.40 19.2 0.175±0.05 285 0.137±0.04 453 0.598±0.11 B. integrifolia 50.2±0.7 1.20±0.02 41.8 0.088±0.01 570 0.133±0.01 377 0.268±0.03

Table 3.6: The nutrient content of abscised leaves (± one standard error) and the carbon to nutrient ratios.

Species Nitrogen C:N Phosphorous Potassium Carbon (%) C:P ratio Sulphur (%) C:S ratio (%) ratio (%) (%) C. monilifera 38.6±4.3 0.64±0.14 60.7 0.06±0.09 643 0.27±0.02 143 0.18±0.09 L. laevigatum 52.0±0.01 0.56±0.02 83.1 0.13±0.01 639 0.14±0.02 371 0.31±0.002 A. longifolia 47.5±2.0 1.34±0.21 35.4 0.03±0.02 1580 0.16±0.02 297 0.20±0.11 B. integrifolia 49.5±0.63 0.60±0.02 92.6 0.02±0.02 2480 0.25±0.15 198 0.08±0.003

Due to the higher annual leaf fall, the leaves contributed a greater nutrient input to the native areas, especially of nitrogen and phosphorous (Table 3.7).

Table 3.7: The approximate annual nutrient input from the leaf fall from the three dominant species in the native areas and C. monilifera in the weed infested areas. This was calculated from average leaf fall and senescent leaf concentration.

Nitrogen Phosphorous Potassium Sulphur (kg.ha-1) Native leaf mix 24 2.6 5.8 5.4 C. monilifera 9.6 0.90 2.7 4.0

Nutrient flux from decomposing litter

There was a net loss of minerals for both litter types (Figure 3.9). There was little difference in the loss of potassium in the two leaf types (Figure 3.9 a, b), with it being the element mineralised the fastest from the native litter. Sulphur was the only mineral immobilised in the early stages of decomposition, this occurring in the native coarse litterbag treatment (Figure 3.9c). There was a continual loss of phosphorous for all treatments but the native fine litterbag treatment, with a small amount of immobilisation occurring after seven months (Figure 3.9e). Nitrogen was initially lost rapidly from both leaf types, the amount remaining then slowly decreased (Figure 3.9g and h).

There was a large variation in the rate of loss of nutrients from the native leaf mix, with the fastest to slowest being potassium> phosphorous> nitrogen> sulphur. All nutrients from the C. monilifera leaves were lost at a similar rate. Nutrient loss was generally greater from the coarse bag treatments and when the bags were within the C. monilifera infestations.

Figure 3.9: The percent original mass remaining of each nutrient from the first 10 months of decomposition of either a native leaf mix or C. monilifera leaves. The leaves were placed in coarse and fine litterbags in either native or C. monilifera infested vegetation.

a) Potassium native b) Potassium C. monilifera

100 Native coarse in native 100 C. monilifera coarse in native Native coarse in weed 90 C. monilifera coarse in weed Native fine in native 90

g C. monilifera fine in native 80 Native fine in weed 80 C. monilifera fine in weed 70 70 60 60

50 50

40 40

30 30

20 20 Percent original mass remainin 10 10

0 0 0246810 0246810 Time (months) Time (months)

c) Sulphur native d) Sulphur C. monilifera

110 110 100 100 90

g 90 80 80 70 70 60 60 50 50 40 40

30 30

Percent original mass reminin 20 20

10 10

0 0 0246810 0246810 Time (months) Time (months)

70 e) Phosphorous native f) Phosphorous C. monilifera

100 100

90 90

80 80

70 70

60 60

50 50

40 40

30 30

20 20 Percent original mass remining 10 10

0 0 0246810 0246810 Time (months) Time (months)

g) Nitrogen native h) Nitrogen C. monilifera

100 100 90 90 g 80 80 70 70 60 60 50 50

40 40

30 30

Percent original mass reminin 20 20

10 10

0 0 0246810 0246810 Time (months) Time (months)

The change in nutrient concentrations with time for the C. monilifera and native leaves are shown in Figure 3.10. Potassium was the only element that the concentration decreased greatly with time, this was for all native litter treatments (Figure 3.10a). The phosphorous concentration decreased with time (Figure 3.10e), while the concentration

71 of sulphur and nitrogen was similar throughout for the all native leaf treatments (Figure

3.10c and f).

For the C. monilifera leaves the sulphur and phosphorous concentrations generally decreased with time after an initial increase (Figure 3.10 and f). The nitrogen concentration was similar with time for the C. monilifera leaves in coarse litterbags, but there was an increase in the fine mesh litterbag (Figure 3.10 g and h).

Overall, the mesh size appeared to influence the change in nutrient concentration more then the habitat the bag was placed in.

Figure 3.10: Changes in the leaf nutrient concentration of a native leaf mix and C. monilifera leaves during decay. The leaves were in fine or coarse mesh litterbags in either native or C. monilifera infested (weed) vegetation.

a. Native Potassium b. C. monilifera Potassium

0.5 Native coarse in native 0.5 C. monilifera coarse native Native coarse in weed C. monilifera coarse weed Native fine in native C. monilifera fine in native 0.4 Native fine in weed 0.4 C. monilifera fine in weed

0.3 0.3

0.2 0.2 [Potassium] (g/100g) [Potassium] (g/100g)

0.1 0.1

0 0 0246810 0246810 Time (months) Time (months)

c. Native sulphur d. C. monilifera sulphur

0.5 0.5

0.4 0.4

0.3 0.3

0.2 0.2 [Sulphur] (g/100g) [Sulphur] (g/100g)

0.1 0.1

0 0 0246810 0246810 Time (months) Time (months)

73 e. Native phosphorous f. C. monilifera phosphorous

0.25 0.25

0.2 0.2 ) )

0.15 0.15

0.1 0.1 [Phosphorous] (g/100g [Phosphorous] (g/ 100g 0.05 0.05

0 0 0246810 0246810 Time (months) Time (months)

g. Nitrogen Native h. C. monilifera nitrogen

3 3

2.5 2.5 ) 2 2

1.5 1.5

1 1 [Nitrogen] (g /100g [Nitrogen] (g /100g)

0.5 0.5

0 0 0246810 0246810 Time (months) Time (months)

Discussion

Invasion by C. monilifera in coastal areas does not appear to change the pool of nitrogen, but there are differences in where nitrogen is stored in comparison to uninvaded areas. Within the C. monilifera areas there is more nitrogen stored in the soil, whereas in the native vegetation there is more nitrogen held within the leaf litter layer.

Nitrogen appears to be cycled faster in the weedy areas, due to an increase in litter quality, which results in rapid decomposition and mineralisation. This is further assisted by a change in microclimate within dense infestations and an increase in invertebrate detritivores (Lindsay & French In press B). In the native uninvaded areas there is a higher litterfall rate and slower decomposition rate, resulting in the forest floor acting as a nutrient sink (Turner & Lambert 2002).

Litterfall and the litter layer

There was a higher nutrient input to the forest floor on the native uninvaded areas from the litter fall, due to a larger quantity falling, not a higher leaf nutrient content. Even in areas where Acacias are not present, there is still more nitrogen in the leaf fall of the native areas. The litterfall was approximately two times greater than the litter layer in the native and C. monilifera areas. However, the litterfall and litter layer were 2.8 and 2.6 times greater in the native than C. monilifera areas respectively. The total annual litterfall in the native areas was comparable to that of other studies in warm temperate Australian forests (Attiwill et al. 1978; Baker 1983; Bennett & Attiwill

1996), including a stand of Banksia integrifolia (Bennett & Attiwill 1996). The litterfall was also comparable to that from A. longifolia growing in the cape of South Africa, where leaves were also the main component (Milton 1981).

The litterfall within the C. monilifera areas was lower than that for temperate forests and coastal heathlands. The litterfall isn’t known for C. monilifera in its native habitat, but it was almost half that of other South African fynbos species (Witkowski

1991). There was also less variation in litterfall in the C. monilifera sites. This could be because these areas are almost monocultures with a closed canopy, therefore each trap received a similar input. Guo and Sims (1999) also found less variation when the canopy had closed in a Eucalyptus forest.

The litter fall peaked in summer and spring within the native vegetation as this is the period of maximum shoot growth and near, or during, the time of flowering (Specht et al. 1981). Other Australian studies have also found litterfall to peak in summer

(Ashton 1975; Baker 1983; Bennett & Attiwill 1996; Specht et al. 1981). A. longifolia flowers late winter and spring with the seeds ripening in late spring-early summer in long woody pods. L. laevigatum flowers in spring, followed by the production of fruits with small woody capsules (Cronin 1988). B. integrifolia flowers most of the year, with seed release dependent on heat.

There were no obvious peaks in the leaf fall within C. monilifera, but there was a slight increase in the contribution from reproductive parts in winter and spring. This is in agreement with the observations that C. monilifera flowers all year round, but mainly peaking in April to June (Carolin & Clarke 1991; Weiss et al. 1998) and that fruiting peaks from June to September (Vranjic 2000). Less seeds and fruits were collected than expected for an invasive weed, especially since a mature plant can produce up to 50 000 seeds per year, and the average soil seed bank contains 2000 to 3000 seeds per m2

(Weiss 1984). C. monilifera seeds can remain on the shrub for up to one year and are dispersed by foxes, rabbits and birds (Dodkin & Gilmore 1985), all of which are present in N.S.W. It is possible that many fruits were eaten from the bush and therefore were

76 not collected in the traps. The reproductive parts of the native shrubs are also heavier than the small C. monilifera seeds, with A. longifolia and L. laevigatum both producing woody seed capsules and fruits.

The litter layer biomass in the native areas was considerably less then that reported in other Australian studies (Ashton 1975; Maggs & Pearson 1977b; Turner &

Lambert 2002), and for A. longifolia in the Cape of South Africa (Milton 1981). This was not expected considering the similarities in litterfall. The litter biomass within the

C. monilifera infestations was again considerably lower then previously published values, but it was comparable to that found by Kruger (1977) for South African fynbos.

Fire in Australian coastal heathlands can remove large amounts of accumulated litter (Specht 1979). Depending on the time since the last fire, it can not be assumed that the floor litter is in steady state (Hart 1995; Turner & Lambert 2002). Therefore, decomposition constants were not determined from the litterfall and litter layer masses.

Litter is also an important source of fuel for fire (McIvor 2001), and the reduced litter loads in the weed infested sites, and the litter being moist, could retard fire or decrease the intensity within C. monilifera infestations. Fire is an integral part of Australian heathland ecosystems, with plants adapted to fire with it common for fire to be required germinate (Specht 1979). Once native shrubs near, or in C. monilifera infestations have aged or died, they may not be replaced due to an altered fire regime. This should be further investigated as another indirect mechanism that aids the spread of C. monilifera.

Nutrient loss from leaf litter

All elements were lost faster from the decaying C. monilifera leaves than the native leaf mix. Nutrient return depends upon the decomposition rate and rate of absorption by roots (Ashton 1975). The mesophyllous C. monilifera leaves decay three

77 to four times faster than the native leaf mix (Lindsay & French In Press), with the three native species all having dry sclerophyllous leaves with high carbon content. Even though the A. longifolia leaves (phyllodes) have a high nitrogen content, the thick cuticle and large amount of structural material means they are still slow to decompose and leaching is impaired (Lindsay & French In Press; Pereira et al. 1998).

Carbon to nutrient ratios have been used as indicators as to weather an element is immobilised or released as decomposition proceeds. Nitrogen is generally mineralised when the C:N ratio falls between 20 to 35 (Ashton 1975; Berg & Staff 1981; O'Connell

1988). The C. monilifera leaves were below this initially critical value, as was the overall C:N of the native leaf mix. Therefore, mineralisation was initially observed and there was no immobilisation.

The initial loss of phosphorous from both leaf types was likely due to leaching, as a large amount of phosphorous in leaves can be in inorganic form, which is readily leached out and lost quickly in the initial stages of decomposition (Attiwill & Adams

1993). Mineralisation of phosphorous has been found to be occur when the C:P ratio falls below 300 (Blair 1988). The C:P ratio of the C. monilifera leaves was initially below this and therefore there was continual loss throughout the decay. The native mix had an initial average C:P ratio of 365. The C:P ratio increased in the mixture with time, and immobilisation occurred in the coarse native treatments after seven months.

Sulphur has been reported to be mineralised when the C:S ratio falls below 300

(Blair 1988). Sulphur was continually lost from the C. monilifera leaves, with the C:S ratio initially below 300. The native leaf mix initially had a C:S ratio of 355, with this falling to 280 after 2.5 months, possibly due to loss of mass, indicated by the concentration slightly increasing. Immobilisation occurred in the native coarse litterbags within the native habitat at the beginning and again after 10 months, but there was still

78 net loss of sulphur. In all the other native leaf treatments, there was continual leaching and/or mineralisation of sulphur.

The loss of sulphur and nitrogen was proportional to the mass lost for the native leaf mix, as indicated by the constant concentration (Figure 3.10). For the C. monilifera coarse bag treatment the sulphur and nitrogen concentration was also similar throughout, however the concentration in the leaves within the fine bags increased, indicating mass was lost faster than loss of nitrogen and sulphur. Phosphorous was lost faster than mass loss in all native treatments and the C. monilifera coarse litterbag treatments. However, again in the C. monilifera fine bag treatments the phosphorous concentration tended to increase indicating that mass was lost faster then phosphorous.

Potassium was lost quickly from all leaves, and in most studies where it is measured it is the mineral lost the fastest (Laskowski et al. 1995; Maggs & Pearson

1977a; Yamashita & Takeda 1998). Potassium is highly mobile and most would have been lost by leaching (Swift 1977). Potassium was lost faster than mass for all native treatments, which is shown with the decrease in concentration with time.

Nutrient loss was slightly greater from the coarse mesh litterbag treatments.

Leaves in the coarse bags decomposed faster, and this was most noticeable when placed within the C. monilifera habitat (Lindsay & French In Press). The coarse mesh bags allow litter invertebrates to enter, with invertebrates shown to enhance both decomposition and nutrient release (Attiwill & Adams 1993; Gonzalez & Seastedt

2001; Seastedt & Crossley 1980; Swift 1977; Yamashita & Takeda 1998). They reduce the litter to fine particles, which increases the surface area for leaching and export nutrients when they remove material from the bag (Swift 1977).

Nutrient loss was also slightly faster in the leaves placed within the weed habitat, most notably in the coarse litterbags. Decomposition was faster within the C.

79 monilifera habitats, due to changes in microclimate (Lindsay & French In Press), and increase in detritivore abundance following invasion (Lindsay & French In press B).

The time for 99% of the native leaves to decay is 8 to 16 months quicker, and for the C. monilifera leaves one to two months quicker for the coarse and fine bags respectively when in the C. monilifera habitat. Increasing decomposition rates can accelerate nutrient cycling, which can indicate increased soil quality (Knoepp et al. 2000).

The carbon to nutrient ratios were higher in the abscised leaves (Table 3.6) than the fresh leaves used in this experiment, as expected due to nutrient withdrawal. The lower nutrient content could mean slower decomposition (Corbeels et al. 2003).

Therefore, in the litter layer some immobilisation would be expected, especially of nitrogen and phosphorous in the native leaves, before mineralisation would occur. The greater quantity of litter and the slower release of nitrogen, phosphorous and sulphur from the native litter, means there would be more nutrients stored within the litter layer of the uninvaded areas. It is estimated that the leaves in the litter layer of the native areas hold at least twice as much nitrogen and phosphorous as in the C. monilifera areas.

Senescence

Nutrient resorption during leaf senescence is a mechanism for reusing nutrients within a plant, rather than being lost in litterfall. Nutrients were resorbed from the native and C. monilifera leaves. Nitrogen resorption was lowest for A. longifolia, inline with results for other acacia species (Witkowski 1991; Wright & Westoby 2003). This could be related to this plant being a N2 fixer (Lawrie 1981). C. monilifera resorbed the highest proportion of nitrogen, even though it was growing on the more fertile soil. This supports several studies which have shown that the soil nutrient status has no effect on

80 the efficiency of resorption (Chapin & Moilanen 1991; Nambiar & Fife 1987; Wright &

Westoby 2003). The residual concentration rather than the amount withdrawn might be where selection has acted to minimise loss (Wright & Westoby 2003), with the nitrogen content more similar for the abscised leaves of all species than of the green leaves.

A greater amount of phosphorous was absorbed from the B. integrifolia and A. longifolia leaves than the C. monilifera laves. Other studies have found high levels of phosphorous resorption in sclerophyllous Australian plants (Bennett & Attiwill 1996;

Wright & Westoby 2003). This could be a mechanism for phosphorous conservation, with phosphorous a limiting nutrient in many Australian ecosystems (Groves 1981;

Skiba & Wainbright 1984). The proportion of phosphorous resorbed in L. laevigatum was lower then expected. The nutrient content of the B. integrifolia leaves was similar to that found by (Bennett & Attiwill 1996) for a healthy B. integrifolia stand. Large amounts of potassium were reabsorbed (44 to 70%) even though coastal areas generally receive a significant input of potassium from salt spray (van der Valk 1974). These sand dunes could have low cation retention, with most potassium potentially removed through leaching.

As well as being absorbed, nitrogen, phosphorous and potassium are also leached from leaves by rain from leaves prior to abscission (Ashton 1975; Chapin &

Moilanen 1991), potentially overestimating reabsorption values. The percentage of an element withdrawn can vary with season with lower concentrations of nitrogen and phosphorous have been reported in summer when the leaf fall is highest (Baker 1983;

Bennett & Attiwill 1996; Guo & Sims 1999). This study was only undertaken at one time of the year, but it gives an initial comparison between the nutrients present in native shrubs and C. monilifera.

Soil Nitrogen

The total soil nitrogen and ammonia concentrations were higher in the C. monilifera areas of most sites, indicating there is a greater pool of nitrogen available for plant growth. The increase in soil nitrogen is possibly a result of the increase the rate of nitrogen mineralisation. One of the two subspecies of the legume Acacia longifolia is found within four of the study sites, and both are known to be symbiotic nitrogen fixers.

-1 It has been estimated that A. longifolia var. sophorae fixes 0.004-0.746 kg ha yr of N2

(Lawrie 1981). Acacias can also add nutrients through nitrogen rich leaf and pod fall

(Lawrie 1981; New 1984; Witkowski 1991). Acacias in Australia are often pioneer species, being the first shrubs to grow after a disturbance (New 1984). C. monilifera could preferentially invade nutrient rich micro-sites where Acacias had been present

(this could facilitate their growth and capture sunlight). In areas where the nitrogen fixing shrub Lupinus arboreus had been, the soil was high in ammonium and nitrate

(Maron & Connors 1996). The diversity decreased in these patches when they invaded by exotic weeds, with the nutrient enrichment thought as the mechanism that promoted the invasion.

It is unlikely that the increase in soil nitrogen underneath C. monilifera is a result of nitrogen fixation from the Acacias alone, as on average the C. monilifera sites had at least 333 kg N ha-1 more than the native sites. Vesicular-arbuscular mycorrhizal fungi have been observed on the roots of C. monilifera (Copeland 1983). Improved nitrogen and phosphorous uptake often results from mycorrhizal associations. This could enhance the competitive ability of C. monilifera on low fertility soils (Weiss et al.

1998), and may contribute to the change in nitrogen cycling.

Ammonium was present in higher concentration than nitrate at most sites, and there are several explanations for this. Microorganisms preferentially utilise ammonium

82 and therefore most nitrogen is liberated as ammonium (Morot-Gaudry & Touraine

2001; Paul & Juma 1981). Ammonium can bind reversibly to negatively charged clay and soil colloids, whereas nitrate can not and is therefore more readily leached from sandy soils (Hassink 1997; Morot-Gaudry & Touraine 2001). All soils were acidic and the conversion of ammonium to nitrite and nitrate by bacteria is slower in acidic soils. It has also been proposed that individual plant species may affect the relative availabilities of ammonium and nitrate (Wedin & Tilman 1990).

The total nitrogen has highest at the Warrain beach and Anna Bay sites, as these soils are sandy clay loams, where as the other soils are sandy loams. The main soil type along Warrain Beach is a brown sandy loam, which is high in organic matter and contains silt. Clay is present, occurring predominately in the swales and hind dunes

(Hazelton 1992, 1993). The Anna Bay Pleistocene dunes are situated on top of a bedrock which forms part of the Nerlong Volcanics (Whitehouse 1997). These irregular outcrops are more prominent around the C. monilifera area. These soil contain 5 to 11% clay, and there is more organic matter and silt present (Murphy 1995). The higher organic matter, silt and clay content of these sites contributed to the higher soil nitrogen.

The total nitrogen was higher in the Jervis Bay native area as this is a cliff site, which is much higher in organic matter and silt than any other site. Less leaching would occur here than on the sand dunes and the soil is less mobile. The vegetation is older with a greater canopy cover, and Acacias are absent, as they often are in mature forests

(New 1984). This native area was not a good comparison for the C. monilifera dune area, but it was the only area without weeds or to recently have weeds removed.

However, this site does provide a clearer understanding of soil minerals in dune areas compared to cliff areas. The total nitrogen in the C. monilifera dune area was comparable to that of the weed areas at Seven Mile Beach and Comerong Island.

Soil properties

The soil bulk density was lower in four of the C. monilifera areas. Bulk density decreases as soil organic matter content increases or if the proportion of sand decreases

(White 1997). The soils within the C. monilifera areas could contain a higher proportion of organic matter as a result of the rapid leaf litter decomposition. This increase in organic matter could contribute to the higher total nitrogen concentration. The bulk density of the Anna Bay C. monilifera site was the lowest due to sand being a smaller proportion of the soil. The native area at Jervis Bay had a higher bulk density than the

C. monilifera area, due to the age of the vegetation and the site being situated behind a cliff. The vegetation is mature and dense and has the highest litterfall and thickest litter layer of all the native sites. The soil is less mobile than it is on the dunes and it has a high organic matter content. It is different to the shrublands on the sand dunes and many attributes turned out to be more similar to the weed infested areas, indicating that C. monilifera invasion could be changing the nutrient cycling on the sand dunes to be more like cliff areas.

There was no consistent pattern with the change in pH between native and C. monilifera areas, but the pH was not the same in the weed and native area within any site. For four of the sites, the area with the lowest bulk density had a lower soil pH. An increase in soil organic matter could contribute to the increase in acidity (Tang & Yu

1999), as decomposition of organic matter produces humic and fulvic acids (Attiwill &

Adams 1993). The areas with the lowest pH had the fastest decomposition including three C. monilifera areas and the native area at Jervis Bay. It appears as though C. monilifera invasion has the potential to alter soil properties. Future research is needed including looking at the soil organic matter content, to determine if it is influenced by the change in litter input and decomposition rate.

Effect of nutrient enrichment

Native seedlings may not be able to survive in the nitrogen rich soil around the

C. monilifera. The addition of fertiliser containing nitrogen has been shown to considerably decrease the survival of Australian heathland seedlings that grow on infertile soil (Specht 1963). Even when the seedlings were planted on soil that was naturally more fertile (no fertiliser added) the seedlings still failed to survive and were out-competed by herbaceous plants that have a more vigorous growth (Specht 1963).

Another study found that areas of nutrient poor Australian soils which had been enhanced with nutrients had a higher exotic species cover and a reduced native species richness (Lake & Leishman In Press). Lake and Leishman concluded that on infertile soils nutrient enrichment (N and P) was a prerequisite for successful invasion. The nutrient enrichment of soil beneath C. monilifera could benefit its survival, but also prevent the establishment of native plants, however it wasn’t a perquisite for invasion.

Implications for regeneration

After the removal of C. monilifera the high soil nitrogen concentration could impair the establishment of native shrubs, especially if seedlings are planted for regeneration. Some soil conditioning or soil nutrient monitoring would be needed to ensure successful regeneration of the area. With time nitrate would be leached from the sandy soil and if the area were burnt some of the nitrogen would be volatised.

Therefore, the increased nitrogen should not be a long-term problem on sandy soils. In other coastal areas, such as headlands and cliff tops the soil generally has lower drainage and a better ability to retain nutrients, so soil remediation would be of greater importance. The control technique of spraying C. monilifera with herbicide, burning and spraying C. monilifera seedlings again as practiced by some land managers (Vranjic

2000) could lead to greater regeneration success than areas that are only applied with herbicide due to potential greater loss of nitrogen.

Conclusions

More information is required to determine the full extent to which nutrient cycling is altered in C. monilifera infestations. This includes determining the above and below ground biomass of common native shrubs and C. monilifera and any other major nitrogen stores. The above ground live biomass appears greater within the weed infestations, with C. monilifera a dense shrub with a greater total leaf area then common native shrubs (Weiss et al. 1998). Other soil nutrients such as phosphorous which is often limiting in Australian coastal soils should also be examined to see if their budget and storage is changed.

Invasion by C. monilifera has changed the movement of leaf litter and the cycling of nutrients within coastal ecosystems. This has been promoted by the change in quality and quantity of litter, which could alter the primary productivity and ecosystem stability. There can be strong interactions between the soil and plants, with a change in plant species capable of altering numerous soil properties, however this usually occurs over a long time. The rapid mineralisation and decomposition could augment this change. The changes in soil nutrients could either accelerate the growth of C. monilifera or promote a competitive superiority to the native species.

Chapter 4

Chrysanthemoides monilifera ssp. rotundata invasion alters

coastal leaf litter invertebrates

Biological Invasions (In press)

Introduction

Leaf litter invertebrates are important in the functioning of ecosystem processes

(Kim 1993). These communities can be useful tools for monitoring ecological change

(Springett 1976b) as disruptions in the composition of invertebrate communities can influence important processes such as nutrient cycling and decomposition (Kremen et al. 1993; Seastedt & Crossley 1984).

Weed invasion has been shown to modify invertebrate assemblages. Changes in abundance or community composition have been related to the low diversity of plants

(Haddad et al. 2001), low diversity of leaf litter (Springett 1976, Slobodchikoff et al.

1977) and the invading plant having differing characteristics to the native vegetation

(Haddad et al. 2001; Wardle et al. 1999). Stabilisation of sand dunes in California with the exotic grass Ammophila arenaria decreased arthropod abundance and species diversity when compared to native vegetation (Slobodchikoff & Doyen 1977).

Invasion by Tradescantia fluminensis in New Zealand also reduced the abundance of most invertebrates (Standish In Publication), with weedy sites supporting a different community with lower species richness. However some species reacted favourably to the invasion, possibly responding to a change in microclimate (Standish

In Publication). Another New Zealand study found that undisturbed bushland contained a greater richness and diversity of beetles than disturbed sites (Crisp et al. 1998).

Interestingly in this study the weedy habitats still contained a high number of native beetle species, but the species that dominated had changed.

In Australia the shrub Chrysanthemoides monilifera ssp. rotundata is an invasive environmental weed, which has invaded most of the New South Wales coastline. It is highly competitive (Toth et al. 1996) and effective at displacing native vegetation (Weiss & Noble 1984b). This leads to the formation of large dense

88 infestations that approach monocultures (Dodkin & Gilmore 1985; Thomas 1997). A prelimary study by French and Eardley (1997) examined surface active invertebrates in

C. monilifera and native habitats at one point in time. Their findings suggested that invertebrates involved in litter decomposition could be affected by C. monilifera invasion.

C. monilifera changes several parameters that could affect leaf litter invertebrate populations. The infestations are generally moister and cooler than native areas, with the dense closed canopy greatly reducing the amount of light reaching the ground

(Lindsay & French In Press). C. monilifera also produces a higher quality leaf litter and within the protective environment of the infestation it decomposes much faster than the native litter (Lindsay & French In Press). This study aims to determine if C. monilifera invasion alters the abundance and assemblage of leaf litter invertebrates in coastal areas, especially those involved in leaf litter decomposition.

Methods

Study Sites

Five field sites were chosen along the N.S.W coastline, located at Anna Bay

(AB) (32°46’S, 152°05’E), Seven Mile Beach (7M) (34°48’S, 152°32’E), Comerong

Island (COM) (34°52’S, 150°44’E), Warrain Beach (WB) (34°58’S, 150°47’E) and

Jervis Bay (JB) (35°08’S, 150°40’E). Within each site, two 30 x 30m areas were chosen at least 100m apart. One area was heavily infested with C. monilifera, with a minimum

70% cover, while the other had few to no weeds. The ages of the infestations were estimated at between 22 and 33 years old, and no chemical or mechanical weed control work had been undertaken on them for at least ten years. The C. monilifera areas had an average vascular plant richness of 6.8 ± 1.6 species and the native areas 12 ±1.1 species.

The dominant vegetation within the un-infested native areas consisted of the shrubs

Banksia integrifolia, Leptospermum laevigatum and Acacia longifolia var. longifolia or

Acacia longifolia var. sophorae. Westringia fruticosa was also dominant at Anna Bay.

Sites were located on foredunes, except for the native area at Jervis Bay and the

C. monilifera area at Anna Bay. The native area at Jervis Bay is situated on top of a

25m pebbly-quartz sandstone cliff (Taylor et al. 1995). This was the only site with the required vegetation community not infested by weeds within the area. Most soils were loose loamy quartz sands with low fertility, the exceptions were the C. monilifera areas at Warrain Beach and Anna Bay, which are sandy clay loams (Hazelton 1992, 1993;

Murphy 1995). More details on soil and geology are given in Lindsay and French (In

Press).

During the study the mean minimum and maximum day temperatures at the most northern site, Anna Bay (13.7°C and 23.6°C) were higher then at Kiama near

Seven Mile Beach (13.7°C and 22.4°C) and the most southern site, Jervis Bay (14.3°C

90 and 20.9°C). The total precipitation from November 2000 to October 2001 was

1613mm at Anna Bay, 1421mm at Kiama and 1191mm at Jervis Bay (Australian

Bureau of Meteorology) (Figure 4.1).

Figure 4.1: The average monthly precipitation (mm) and air temperature (°C) across all sites during the collection period. Error bars are one standard error.

400 25

350

20 300

250 15

200

10 150 Temperature (C) Precipitation (mm)

100 5

0 0 Nov Dec Jan Feb Mar Apr May June July Aug Sept Oct Nov 00 00 01 01 01 01 01 01 01 01 01 01 01

Invertebrate Sampling

Sampling was carried out in December 2000 (summer), April 2001 (autumn),

July 2001 (winter) and October 2001 (spring). Leaf litter invertebrates were sampled by collecting fixed areas of the leaf litter layer to soil level. Sixteen random samples each covering 0.16m2 were collected and pooled into four groups, therefore each sample covered 0.64m2. The litter was placed in sacks and kept moist and cool until extraction.

Samples were extracted for five to seven days into 75% mono ethylene glycol within 48 hours of collection using a modified Tullgren Funnel. After extraction, the

91 litter was dried (48hours, 65ºC) and weighed. The invertebrates were stored in 70% ethanol and sorted to order using a binocular microscope. The Isopoda, Coleoptera, and

Diplopoda were also sorted to morphospecies, with morphospecies being individuals with easy to see external features. This form of identification has been successfully used as a substitute for species in biodiversity studies (Oliver & Beattie 1993, 1996). For

Australian invertebrates, there is a lack of knowledge on systematics for most communities (New 1993). All invertebrates were classified to order with Harvey and

Yen (1997) and the Coleoptera families with Lawrence and Britton (1991). No other larvae apart from the Lepidoptera were identified, and juvenile Diplopoda and

Chilopoda were not classified beyond class.

Data Analysis

A three factor analysis of variance was performed using SYSTAT (2000) to test for differences in total abundance, taxa richness and abundance of each taxa. The factors were time (fixed), site (random) and weed (fixed). Time was selected as fixed in the model as samples were deliberately taken in different seasons (temporal variation).

Most small invertebrates also have short generation times and rapid population growth rates (Kremen et al. 1993), this ensures that samples taken at different times at a site are independent of each other. Only taxa with sufficient number were analysed by

ANOVA, and this was generally at the level of order. Data was either log(x+1) or square root transformed prior to analysis to improve normality and homogeneity. For several groups the degrees of freedom are reduced, due to samples being destroyed and taken during building refurbishments.

Multiple comparisons of means were performed using a Student-Newman-Keuls test (SNK) at the 0.05 level to determine significant differences among the site, weed

92 and time combinations. The SNK test was used as more conservative multiple comparison procedures often fail to detect differences (Underwood 1997).

The number of invertebrates and taxa per gram of litter was calculated. The

Pearson Correlation Coefficient (r) was calculated to determine if there was a relationship between the mass of litter collected and invertebrate abundance, and litter mass and taxa richness. A three factor ANOVA (time, weed, site) was also performed to determine if there were differences in the abundance and number of taxa per gram of litter in the native and weed areas.

Multivariate non-parametric analysis was performed using PRIMER (1999) to determine if weed invasion affected invertebrate assemblages. The community composition was significantly different between each site, therefore each site was analysed separately.

To assess and display the impact of weed invasion, the data was ordinated using non-metric multidimensional scaling (nMDS) following the calculation of the Bray-

Curtis indices of similarity. A two-way analysis of similarity (ANOSIM) was performed to determine differences between the four collection periods and the native and weed areas. When significant differences were found similarity percentage analysis

(SIMPER) was used to look at which taxa differed between habitats (% dissimilarity) and which species contributed the most to the similarity within a habitat. Analyses were undertaken on square root transformed and presence/absence data to distinguish if differences were due to the abundance of a particular taxa or the presence of specific taxa (Clarke & Warwick 1994).

Results

A total of 107 065 invertebrates were collected during the study from 32 orders

(Figure 4.2). Three of these orders were further sorted into 103 morphospecies. There were only two distinctive types of Isopoda, one with clinger morphology and the other with roller morphology (Paoletti & Hassall 1999), with the clinger morphology occurring in higher abundance. Centipedes were identified from three orders, with the

Geophilida being the most abundant. Millipedes were identified from three orders, which were sorted into fourteen morphospecies. The Spirobolida were the most abundance and had the highest species richness. The Coleoptera were sorted into 89 morphospecies (Table 4.1). Of the superfamilies identified, the Staphylinidea were the most diverse and the Curculionidea the most abundant.

Table 4.1: The number of beetle morphospecies identified. Selected morphospecies were first classified to family or superfamily before being identified further.

Number of Superfamily Family Morphospecies Curculionidea Curculionidae 5 Brentidae 2 Scarabaeidae Passalidae 1 Scarabaeidae 1 Staphylinoidea Ptiliidae 1 Scydmaenidae 2 Pselaphidae 1 Other 16 Cucujoidea 9 Caraboidea Carabidae 6 Other 47

Figure 4.2: The average abundance (square root transformed) of each order or class in the native and weed areas averaged for all five sites and four collection times. Error bars are one standard error.

20 Native C. monilifera 18

2 Abundance (Square root transformed) 0 Acarina Acraneae Amphipoda Blattodea Chilopoda Coleoptera Collembola Dermaptera Diplura Diptera Embioptera Haplotaxida Hemiptera Hymenoptera Isopoda Isoptera Lepidoptera Millipedes Neuroptera Orthoptera Pseudoscorpion Pscoptera Symphyla Scorpionida Thysanoptera

Invertebrate Abundance

The total abundance of invertebrates was similar within the C. monilifera and native areas of all sites except Jervis Bay, where there were more within the native cliff area (F12, 110= 1.986, P=0.032, site x weed x time) (Table 4.2). On average, the native areas had 1206±93 (S.E) invertebrates per m2, and the C. monilifera areas 1001±96 invertebrates per m2. Within the C. monilifera habitats there was a weak positive correlation between the mass of litter collected and the invertebrate abundance (r=0.49,

P=0.003). This was less evident in the native habitats (r=0.34, P=0.001). There was a higher abundance per gram of litter in several C. monilifera areas (Figure 4.3) with this

95 significant for Seven Mile Beach for most collections (F12, 109=2.70, P=0.003, Site x weed x time) (Table 4.3). However, the native areas at Jervis Bay had significantly more than the C. monilifera area.

Table 4.2: Summary of the ANOVA for total abundance, number of taxa and abundance of certain orders and classes. P>0.05 significance level. Significant results are in bold.

Acarina Amphipoda Araneae Chilopoda Source d.f F P d.f F P d.f F P d.f F P Site 4 3.409 0.011 4 14.901 0.001 4 1.623 0.175 4 2.504 0.046 Weed 1 1.926 0.238 1 0.361 0.58 1 4.717 0.096 1 0.228 0.658 Time 3 7.935 0.004 3 0.207 0.89 3 1.366 0.299 3 5.584 0.012 Site x weed 4 9.055 0.001 4 7.278 0.001 4 5.409 0.001 4 13.41 0.001 Site x time 12 2.395 0.009 12 1.338 0.206 12 1.117 0.357 12 1.872 0.044 Weed x time 3 1.571 0.248 3 1.414 0.288 3 0.208 0.890 3 0.511 0.682 Site x weed x time 12 1.613 0.098 12 1.057 0.403 12 0.688 0.765 12 2.658 0.003 Error 113 113 115 120 Coleoptera Collembola Diplopoda Diptera Source d.f F P d.f F P d.f F P d.f F P Site 4 5.208 0.001 4 0.968 0.427 4 10.35 0.001 4 1.442 0.225 Weed 1 0.813 0.414 1 0.005 0.945 1 16.97 0.015 1 0.420 0.552 Time 3 3.651 0.044 3 13.562 0.001 3 1.249 0.335 3 5.495 0.010 Site x weed 4 6.904 0.001 4 8.028 0.001 4 0.654 0.628 4 1.143 0.343 Site x time 12 4.656 0.001 12 2.119 0.021 12 2.963 0.001 12 2.805 0.002 Weed x time 3 0.464 0.600 3 0.134 0.733 3 3.720 0.042 3 3.649 0.044 Site x weed x time 12 1.568 0.109 12 3.857 0.001 12 0.766 0.069 12 0.740 0.707 Error 120 112 113 114 Hemiptera Hymenoptera Isopoda Lepidoptera Source d.f F P d.f F P d.f F P d.f F P Site 4 3.449 0.010 4 3.121 0.018 4 32.370 0.001 4 6.952 0.001 Weed 1 0.632 0.471 1 0.350 0.586 1 0.000 0.993 1 1.333 0.313 Time 3 1.308 0.310 3 0.814 0.508 3 4.351 0.027 3 7.105 0.005 Site x weed 4 7.110 0.001 4 7.634 0.001 4 21.104 0.001 4 7.867 0.001 Site x time 12 1.265 0.248 12 0.866 0.582 12 2.566 0.005 12 3.981 0.001 Weed x time 3 1.065 0.400 3 1.083 0.759 3 1.613 0.239 3 2.338 0.125 Site x weed x time 12 1.471 0.144 12 1.080 0.381 12 1.434 0.163 12 1.324 0.214 Error 120 112 113 115 Pseudoscoprion Thrysanoptera Number of Taxa Total Abundance Source d.f F P d.f F P d.f F P d.f F P Site 4 12.31 0.001 4 4.246 0.003 4 5.776 0.001 4 4.079 0.004 Weed 1 0.861 0.382 1 1.551 0.281 1 0.533 0.506 1 0.409 0.557 Time 3 8.053 0.003 3 2.349 0.124 3 8.092 0.003 3 8.039 0.003 Site x weed 4 11.09 0.001 4 2.823 0.029 4 16.65 0.001 4 10.21 0.001 Site x time 12 1.74 0.067 12 2.160 0.018 12 5.198 0.001 12 3.183 0.001 Weed x time 3 0.348 0.791 3 0.827 0.504 3 0.311 0.803 3 1.220 0.345 Site x weed x time 12 1.98 0.033 12 2.880 0.002 12 2.547 0.005 12 1.986 0.032 Error 113 114 117 110

Figure 4.3: The total invertebrate abundance per gram of litter in the native and C. monilifera areas of each site. Error bars are one standard error, * denotes a significant difference.

3.5 Native C. monilifera * 3

) 2.5

2 *

1.5 *

Abundance/ littermass (g 1

0.5

0 AB 7M COM WB JB

The ANOSIM results for the abundance data (square root transformed) showed that the invertebrate assemblages within the weed and native areas were significantly different at all sites (Global R=0.195-0.761, P=0.001-0.024) (Table 4.4). The average dissimilarity between habitats, in terms of Bray Curtis indices, ranged from 56.9% for

Jervis Bay to 38.7% for Seven Mile Beach (Table 4.5). The nMDS plots show clear clustering of the native and weed areas for all sites but Anna Bay (Figure 4.4). The taxa that consistently produced the dissimilarity at most sites were the Acarina (11-16%),

Isopoda (clinger morphospecies) (4.1-8.9%), Pseudoscorpionida (2.1-7.0%) and the

Geophilida centipedes (2.1-3.2%).

Table 4.3: Summary of the ANOVA for total abundance per gram of litter and total number of taxa per gram of litter. P>0.05 significance level. Significant results are in bold.

Abundance Taxa Source df F-ratio P df F-ratio P Site 4 3.63 0.008 4 2.44 0.051 Weed 1 0.69 0.453 1 20.9 0.100 Time 3 5.64 0.012 3 1.00 0.500 Site x weed 4 3.71 0.007 4 1.25 0.294 Site x time 12 1.45 0.156 12 3.19 0.001 Weed x time 3 1.45 0.277 3 1.00 0.426 Site x weed x time 12 2.70 0.003 12 3.49 0.001 Error 109 117

Table 4.4: The ANOSIM results for each site testing for differences between native and

C. monilifera areas at each collection time. Data was either square root or presence/ absence transformed. P=0.05 significance level.

Square Root Presence/Absence Weed Time Weed Time Site Global Global Global Global P P P P R R R R AB 0.195 0.021 0.563 0.001 0.113 0.086 0.406 0.001 7M 0.616 0.001 0.549 0.001 0.361 0.003 0.294 0.001 COM 0.648 0.001 0.612 0.001 0.199 0.012 0.36 0.001 WB 0.211 0.024 0.131 0.043 0.194 0.027 0.134 0.026 JB 0.761 0.010 0.168 0.023 0.680 0.001 0.248 0.002

Figure 4.4. The nMDS plots for habitat type, either native or C. monilifera infested for each site. Data was square root transformed prior to ordination. Stress values are given in brackets.

a. Anna Bay (0.13)

b. Seven Mile Beach (0.14) c. Comerong Island (0.12)

d. Warrain Beach (0.17) e. Jervis Bay (0.09)

100

Table 4.5: The average dissimilarity between the invertebrate assemblages within the native and C. monilifera areas of each site. SIMPER analysis was not performed on presence/absence data for Anna Bay as the ANOISM was not significant.

Average Dissimilarity (%) Site Square root Presence /absence Anna Bay 42.5 na Seven Mile Beach 38.7 36.2 Comerong Is. 43.6 40.8 Warrain Beach 40.0 34.5 Jervis Bay 56.9 49.7 Average 44.3 41.1

Several groups were more abundant within the native areas. For most taxa this was highly dependent on either collection time and/or site. There was higher Acarina abundance in the native areas of some sites (F4, 113=9.06, P=0.001), i.e. Comerong Is. and Jervis Bay (Figure 4.2, Table 4.2). However, at Warrain Beach there was a higher abundance in the C. monilifera area (Figure 4.5). The Acarina were the most abundant group in both habitats, comprising 41% of native total abundance and 32% of C. monilifera abundance.

A significantly higher abundance of Araneae was found in the native areas of

Jervis Bay, Comerong Is. and Anna Bay (F4, 115=5.41, P=0.001) (Table 4.2). Similar numbers were found in each habitat at the other two sites.

The Hymenopterans occurred in greater abundance within the native areas of every site except Seven Mile Beach (Figure 4.2 and 4.6). There were significantly more in the Jervis Bay native area and the Seven Mile beach C. monilifera area (F4, 112=7.63,

P=0.001) (Table 4.2). The Hymenoptera were predominantly from the Formicidae

101 family and were the third most abundant group, comprising 7.6% of native samples and

7.9% of C. monilifera samples.

Figure 4.5: The average abundance of Acarina at each site, in either the native or C. monilifera areas. Error bars are one standard error, * denotes a significant difference.

700 Native C. monilifera 600 *

500 * 400 * 300 Abundance

200 * 100

0 AB 7M COM WB JB

Figure 4.6: The average abundance of Hymenoptera at each site in the native and

C. monilifera areas. Error bars are one standard error, * denotes a significant difference.

120 Native * C. monilifera 100

80 *

60 Abundance 40 *

20 *

0 AB 7M COM WB JB

102

The Chilopoda also occurred in greater abundance within the native areas of every site except Seven Mile Beach (Figure 4.2 and 4.7). There was significantly more in the native areas for all collections at Jervis Bay, the fourth collection at Comerong Is. and the third collection at Warrain Beach. However, at Seven Mile they were more abundant within the C. monilifera area (F 12, 120=2.66, P=0.003, site x weed x time)

(Table 4.2). The Geophilida dominated Anna Bay, Warrain Beach, Comerong Is., the C. monilifera area of Seven Mile Beach and the native area of Jervis Bay. The Lithobidda dominated the Seven Mile Beach native area and the Jervis Bay C. monilifera area.

Figure 4.7: The average abundance of Chilopoda in each collection at each site in either a. the native or b. C. monilifera area. Error bars are one standard error.

a. b.

70 70 1 60 60 2

50 50 3 4 40 40

30 30 Abundance

20 20

10 10

0 0 AB 7M WB COM JB AB 7M WB COM JB Native C. monilifera

The Thysanoptera were more abundant within the native areas of four sites, with this being dependent upon the time of collection (F12, 114=2.880, P=0.002, site x weed x time) (Figure 4.2 and 4.8, Table 4.2).

103

The Diptera were more abundant within the native areas of most sites, with this significant for the second collection (F3, 12 =3.65, P=0.044) (Table 4.2). A higher abundance of Hemiptera occurred in the native areas of Jervis Bay and Anna Bay (F4,

120=7.11, P=0.001) (Table 4.2). This trend was also evident at Warrain Beach.

Figure 4.8: The average abundance of Thrysanoptera in each collection at each site in either, a. the native area or b. the C. monilifera area. Error bars are one standard error.

a. b.

60 60 1 50 2 50 3 40 4 40

30 30 Abundance 20 20

10 10

0 0 AB 7M WB COM JB AB 7M WB COM JB Native C. monilifera

The native cliff area at Jervis Bay contained a high abundance of many taxa.

Consequently, it was the only native area to have significantly more Coleoptera (F4, 120=

6.904, P=0.001) and Lepidoptera larvae (F4, 115 =7.87, P=0.001). The Symphyla

(2.9±1.1 native, 0.73±1.5 weed) and Blattodea (3.75±1.9 native, 1.81± 0.84 weed) also occurred in higher abundance in all native areas, however there were insufficient numbers to be analysed by ANOVA.

The Isopoda, Diplopoda, Pseudoscorpionida, Amphipoda and Haplotaxida generally occurred in higher abundance within the C. monilifera areas. This was again

104 dependent on site and/or time. Significantly more Isopoda were found within the C. monilifera areas of Comerong Is., Warrain Beach and Seven Mile Beach (F4, 113=20.1,

P=0.001) (Table 4.2). The clinger morphospecies was more abundant in C. monilifera areas whereas the roller morphospecies was more abundant in the native areas. The

Isopoda were the fourth most abundant group, comprising 4.5% of native samples and

6.1% of C. monilifera samples.

There were significantly more Diplopoda (millipedes) in the C. monilifera sites for the third and fourth collections (F3, 12 =3.72, P=0.042) (Table 4.2, Figure 4.2). This trend was also evident in the second collection. The Pseudoscorpions were found in significantly higher numbers in the C. monilifera areas of Seven Mile Beach, Warrain

Beach, and Comerong Is for most collection times (F12, 113=1.975, P=0.033, site x weed x time) (Table 4.2). There was however a higher abundance in the native area of Jervis

Bay for all collection periods (Figure 4.2 and 4.9).

Figure 4.9: The average abundance of Pseudoscorpions in each collection at each site in either, a. the native area or b. the C. monilifera area. Error bars are one standard error. a. b.

90 90 80 1 80 70 2 70 3 60 60 4 50 50 40

Abundance 40 30 30 20 20 10 10 0 0 AB 7M WB COM JB AB 7M WB COM JB Native C. monilifera

105

The Amphipoda (Family Talitridae) occurred in higher abundance in the C. monilifera areas of Seven Mile Beach, Warrain Beach and Comerong Is (Figure 4.2).

This was only significant at Seven Mile Beach (F4, 113=7.28, P=0.001) (Table 4.2). The native cliff area of Jervis Bay again had significantly more Amphipoda than the C. monilifera area.

There were insufficient numbers of Haplotaxida (earthworms) to be analysed by

ANOVA, but they were present in higher numbers in the C. monilifera areas (0.48±0.24 native, 2.03±0.84 weed) (Figure 4.2).

In general, the Collembola occurred in similar numbers in the native and C. monilifera areas. There was however significantly more in the native area of Jervis Bay for all collection times and the C. monilifera area of Warrain Beach for some collections

(F12, 112 =3.857, P=0.001, site x weed x time) (Table 4.2). The Collembola were the second most abundant group comprising 21% of native sample and 29% of C. monilifera samples (Figure 4.2).

Taxa and Species Composition

The total number of taxa collected varied between sites, times and habitats (F12,

117=2.547, P=0.005). At Jervis Bay, Seven Mile Beach and Warrain Beach there was a trend for more taxa to be present within the native areas. This was significant for all collections at Jervis Bay and once at Seven Mile Beach (Table 4.2). Similar numbers of taxa were present in both habitats at Anna Bay and Comerong Is. throughout the study.

There was a higher diversity of taxa per gram of litter within the C. monilifera areas (5.1±0.2 taxa per100g) than the native areas (4.1 ±0.2 taxa per 100g) (Figure

4.10), however this was only significant for Comerong Is (F12, 117=3.49, P=0.001, Site x weed x time) (Table 4.3). There was a weak correlation for taxa richness per gram of

106 litter in the native areas (r= 0.53, P=0.001) and even less in the C. monilifera areas

(r=0.36, P=0.001).

Figure 4.10: The number of taxa per gram of litter in the native and C. monilifera invaded area of each site. Error bars are one standard error, * denotes a significant difference.

0.07 Native * C. monilifera 0.06

0.05 * 0.04

0.03

0.02 Taxa per gram of litter 0.01

0 AB 7M COM WB JB

The ANOSIM analysis of presence/absence transformed data showed the native and C. monilifera habitats were significantly different from each other at every site

(Global R=0.199-0.68, P=0.001-0.027) except Anna Bay (Global R=0.113, P=0.086)

(Table 4.4). In comparison to the abundance data there was less dissimilarity between habitats with presence/absence transformation (Table 4.4). Nevertheless, clustering of native and C. monilifera sites is still clear in the nMDS plots for several sites, but all ordinations had high stress levels (Figure 4.11).

Most taxa were common between the native and C. monilifera sites, with the

SIMPER analysis indicating that the native and C. monilifera sites were both generally characterised by the presence of Acarina, Araneae, Collembola, Hymenoptera,

107

Thysanoptera, Lepidoptera larvae and Isopoda of clinger morphology. The same result was obtained from analysis of the abundance data.

Figure 4.11: The nMDS plots for habitat type, either native or C. monilifera infested, for each site with a significant ANOSIM of weed x time. Data was presence/absence transformed prior to ordination. Stress values are given in brackets.

a. Seven Mile Beach (0.21) b. Comerong Island (0.20)

c. Warrain Beach (0.23) d. Jervis Bay (0.50)

The groups that distinguished between C. monilifera and native areas varied with site. Within a site many taxa only occurred in the native or C. monilifera area, but at ordinal level no group was absent from a habitat type across all sites. For Coleoptera

47% morphospecies were present in both habitats, with 32% only occurring in the

108 native habitats. Twenty-seven of the morphospecies were singletons, most of which occurred in the native areas of Jervis Bay and Comerong Is. The same beetle morphospecies dominated both habitats. These were from the Curculionidea family

(Subfamily Cossoninae) and the Scydmaenidae family. The opposite trend was seen for the millipedes, with three of the ten morphospecies only occurring in C. monilifera habitat.

Of the five groups that occurred in higher abundance in the C. monilifera sites the millipedes, Amphipoda and earthworms were also present in more of the C. monilifera samples from Seven Mile, Comerong Is. and Warrain Beach. The pseudoscorpions were present in more of the C. monilifera samples from Seven Mile

Beach, Comerong Is. and Jervis Bay. For the groups that were more abundant in the native areas, there was little difference in their presence in the C. monilifera or native samples.

Two groups contributed to the difference in species composition between the two habitats on Comerong Is. The Lithobidda centipedes were present regularly in the native area, but only once in the C. monilifera area, contributing to 5.3% of the dissimilarity. The Pseudoscorpions (3.9%) were present three times as often in the C. monilifera area. At Seven Mile beach the presence of three taxa varied between habitats.

The Haplotaxida (5.9%) were only present in the C. monilifera, while the Amphipoda

(4.2%) were always present in C. monilifera but only occasionally in the native. The

Geophilida centipedes (4.2%) were present in most of the C. monilifera samples, but in only half of the native samples. At Warrain Beach the Haplotaxida (5.3%) were present more than twice as often in the C. monilifera area. The Embioptera (4.5%) were only present in the native area of Jervis Bay. An isopod (roller morphospecies) (3.7%), a staphylinid (4.6%) and a weevil (Curculionidea: subfamily Cossoninae) (4.6%) were

109 also consistently present in the native area, but were only present twice in the C. monilifera area.

Temporal Variation

As seen with the ANOVA results the invertebrate abundance often differed between sampling periods at each site (Table 4.3). The ANOSIM results indicate the invertebrate assemblages also frequently differed between collections. The assemblage were different between all sample times at Seven Mile Beach (Global R= 0.549,

P=0.001) and Comerong Island (Global R=0.612, P=0.001) (Tables 4.4 and 4.6), and between most times at Anna Bay (Global R= 0.563, P=0.001). However, at Warrain

Beach (Global R=0.245, P=0.022) and Jervis Bay (Global R=0.554, P=0.002) almost all collections had a similar invertebrate assemblage (Table 4.6). The nMDS plots with presence/ absence transformed data, do not show clear clustering for any site. The

ANOSIM results were significant, but the global R values are very low for most sites

(Table 4.4). There is some grouping of collections times for Anna Bay and Comerong

Is. (Figure 4.12).

The invertebrate assemblages differed more in their abundance than composition with time. For a given habitat within a site, at no time did an order become absent.

Several groups including the Araneae, Hymenoptera, Hemiptera and Amphipoda were present in similar numbers throughout the study, whereas the abundance of all other orders fluctuated.

110

Figure 4.12: The nMDS plots for the four collection times at each site. The data was presence/absence transformed prior to ordination. Stress values are given in brackets.

a. Anna Bay (0.19)

b. Comerong Island (0.2) c. Jervis Bay (Stress 0.15)

d. Warrain Beach (0.23) e. Seven Mile (0.21)

111

Discussion

Long term C. monilifera invasion in coastal areas altered the abundance of leaf litter invertebrates and changed the invertebrate assemblage. Several invertebrate groups were impacted by weed invasion and were found in lower abundance in the weed areas of most sites. There was an increase in the abundance of five groups in the weedy habitat, with four of these also occurring more often. This included the isopods, amphipods, earthworms and millipedes, all which are involved in litter decomposition

(detritivores).

C. monilifera invasion alters the microclimate, with the ground becoming cooler, moister and darker (Lindsay & French In Press). This is due to the formation of a protected environment by the dense C. monilifera canopy. Invertebrates could be responding to this change in microclimate. The weed Tradescantia fluminensis also has a dense structure and invasion creates a moist microclimate. This change in microclimate was thought to contribute to the change in invertebrate community within the infestations (Standish In Publication). Most isopod, millipede, amphipod and earthworm species require adequate moisture from the litter or soil to survive (Lee

1983; Moeed & Meeds 1985; Nakamura et al. 2003). When it becomes too dry or warm, isopods and especially earthworms will retreat into the soil (Lee 1983; Wichard

& Eisenbis 1987). It is possible these organisms were present in higher numbers in the native areas than detected but they were not active on the surface at the time of collection. This could be verified with soil sampling. It is not known why the pseudoscorpions occurred in higher abundance within the C. monilifera bush.

Millipedes also avoid bright light (Wichard & Eisenbis 1987), and the lower solar insolation within the C. monilifera areas could have helped them thrive. There was also higher millipede morphospecies richness in the C. monilifera areas, which could

112 have originated from two places. Firstly they could be introduced species, as some of the C. monilifera infestations occurred in disturbed areas close to housing, parks and farms, or more likely they have originated in the heath or littoral rainforests that occur behind the dunes.

At the ordinal level, no change in the Coleoptera abundance or presence was detected, however changes in the community were detected at morphospecies level.

Other studies have found a similar result (Samways et al. 1996; Sirra-Pietikainen et al.

2003). The dominant species did not change with invasion, but many species were specific to a habitat. The most abundant beetle in both habitats, a weevil (Curculionidae: subfamily Cossoninae), was a decomposer which generally feeds on rotten wood or bark (Phytophagous) (Lawrence & Britton 1991).

The decreased abundance of many orders (mites, thrips, spiders, ants, centipedes) and beetle morphospecies within the weedy areas may be a result of the decrease in plant biodiversity. Previous studies have found that some species respond positively to plant biodiversity, with greater abundance or species richness occurring in areas with higher plant diversity (Crisp et al. 1998; Dennis et al. 1998; Haddad et al.

2001; Moeed & Meeds 1985). Higher plant species richness can provide greater structural complexity (structural heterogeneity) (Dennis et al. 1998), more habitat types and a greater number of alternate resources (Haddad et al. 2001). The leaf litter layer within the native areas was of higher diversity with a greater quantity of litter and little to no bare ground. Litter depth and the amount of litter cover have been related to ground active arthropod biodiversity and abundance (Levings & Windsor 1984;

Plowman 1979; Seastedt & Crossley 1988). Diverse litters and high litter volumes can increase the microhabitat and resource heterogeneity (Hassan 2000; Oliver et al. 2000).

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Litter quality

Overall there were fewer invertebrates per unit area in the C. monilifera areas, however at some sites the C. monilifera areas supported more invertebrates per gram of litter. This is perhaps associated with the increased quality of the C. monilifera leaves.

The leaves comprising the native litter are generally thicker, more sclerophyllous and have a higher C:N ratio (Lindsay & French In Press). This makes them a poorer quality food source (poor carbon quality), and subsequently they could also be of lower palatability and digestibility to the leaf litter invertebrates (Witkamp 1966). Several studies have found that the leaf species and quality can affect arthropod diversity and density (Blair et al. 1990; Heneghan et al. 1999; Wiegert 1974). The abundance of invertebrates, including detritivores and herbivores, has been shown to increase with improved leaf palatability (Scheu et al. 2003) and with decreasing plant tissue C:N ratio

(Haddad et al. 2001). Increased resource quality has also been associated with a more diverse herbivorous arthropod community (Wardle et al. 1999). To some invertebrates the characteristics and quality of the plant species present and litter added could be more important then the litter quantity and diversity (Wardle et al. 1999).

The litter decomposition rates within C. monilifera are faster than in uninvaded vegetation. This, accompanied with the moister environment, could lead to increased bacterial and fungal growth (Levings & Windsor 1984). Many invertebrates feed on microbes and dead vegetation that has been attacked by microbes, especially those involved in decomposition. This C. monilifera invaded areas could provide more of a preferred food source. Future work could examine the microbial biomass and diversity within the C. monilifera infestations. As microbes are also affected by plant community composition (Kourtev et al. 2002; Yeates & Williams 2001).

114

Temporal Variation

There was a high level of temporal variation, with the community composition and abundance frequently differing between collections at three of the sites. One reason for this is the change in seasons. Invertebrate communities are influenced by seasonal abiotic factors such as temperature, humidity and rainfall (Kremen et al. 1993; Reddy &

Ventatiah 1990; Wichard & Eisenbis 1987). This experiment was not designed to analyse seasonal change, and to do so sampling would have to be carried out regularly over several years. Sampling was instead designed not to impact on the invertebrate communities and to determine if the impact of C. monilifera invasion was evident throughout the year.

Secondly invertebrate communities often exhibit high levels of temporal variation (Gering et al. 2003; Plowman 1979). Temporal change in communities is partly due to the different life history attributes of insects (Gering & Crist 2000). In this study individual taxa responded differently to temporal change. Some groups occurred in similar numbers throughout the year, while others appeared to respond to high rainfall (eg. Collembola and Acarina) or cooler temperatures (eg. Millipedes). This could be partly due to different schedules of emergence and voltinism. Site characteristics appeared to have influenced the outcomes more than the time of collection.

Spatial Variation

There were site specific differences in abundance and especially composition, within a habitat type. These high levels of variation may have prevented the detection of further impacts. Slight differences in geography, soil type and weather contributed to the observed variation. For instance although the temperatures were similar at each site,

115 and on average did not vary by more them 1ºC, the rainfall was more variable between sites. Furthermore, the C. monilifera area of highest biodiversity was at Warrain Beach, which could be related to variability in soil type (a sandy clay loam vs. a sandy loam at other sites). Finally, the Jervis Bay native cliff area had the highest diversity and abundance overall. This native site was different to the other native sites, due to it being a cliff area, not a sand dune. The leaf litter layer was more protected from the wind and sun, with the lowest solar insolation of all native sites. The soil was moister than all other native areas, especially towards the cliff edge, and unlike all other sites, this native area was also moister then the corresponding C. monilifera area. These factors may explain why this area had such a high abundance of pseudoscorpions and amphipods like the weed infested areas

There was also a high amount of variation between replicates within a site, with the amount of variation varying between taxa. Different taxa may have different spatial distributions and habitat requirement (Huhta 2002; Maudsley et al. 2002). Invertebrate distribution can be patchy and populations are generally not continuous across a geographical range (Greenslade & Greenslade 1983; Samways 1994). Patterns of distribution maybe social, with signalling leading to spacing or clumping (Greenslade &

Greenslade 1983).

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Conclusions

The leaf litter invertebrates varied in their response to the disturbance of weed invasion, some benefited, some decreased and others were unchanged. Further species specific responses are likely if other groups are identified to lower taxonomic levels.

However, this study has identified groups of animals that vary with weed infestation and provide a template for the development of further studies.

In general, the coastal invertebrate fauna appear resilient to weed invasion with the C. monilifera infestations supporting a large number of leaf litter invertebrates.

However, the diversity is reduced compared to the un-infested areas. Changes to ecosystem level processes are likely to be at least partially mediated through these changes.

117

Chapter 5

The impact of the herbicide Roundup® Biactive™

(glyphosate), on leaf litter invertebrates within bitou bush

infestations

Pesticide Science (In press)

118

Introduction

The South African shrub Chrysanthemoides monilifera ssp. rotundata (Family

Asteraceae) (bitou bush) is a common environmental weed along the southeast coast of

Australia (Gray 1976; Humphries et al. 1991). C. monilifera was planted extensively between 1946 and 1971 to stabilise coastal sand drifts, and to revegetate dunes after mining operations (Cooney et al. 1982; Weiss et al. 1998). The use of C. monilifera as a dune stabiliser was halted when it became apparent that it competed with native coastal plant communities (Thomas & Leys 2002; Weiss & Noble 1984b) and dune erosion occurred as infestations aged (Stanley et al. 1989; Thomas 1997).

C. monilifera now covers more than 36000ha of the New South Wales coastline, being the dominant species on over 400km of headlands and dunes (Holtkamp 2002;

Toth et al. 1996). Many techniques have been used to control C. monilifera, including physical removal, burning, slashing and biological control agents (Adair 1993; Weiss

1993). Currently chemical control is the most successful method for removing large infestations. The herbicide glyphosate (N-(phosphonomethly)glycine) is the most widely used herbicide, applied via aerial application or high pressure spraying equipment (Cooney et al. 1982; Toth et al. 1993).

Glyphosate is a broad-spectrum, non-selective water-soluble systemic herbicide

(Franz 1985). There are several commercial formulations with the glyphosate isopropylamine salt as the active ingredient, including Roundup® Biactive™. This product differs to Roundup® in having a surfactant that is reported to be readily biodegradable (Monsanto 2000) and less harmful to the environment (Toth et al. 1996).

Glyphosate does not bioaccumulate (Monsanto 2000) and is considered to be non-toxic

(Baylis 2000). The half-life depends on the soil type, and can vary from days to years.

Glyphosate can be inactivated in the soil by becoming bound to clay particles

119

(Torstensson 1985) and when desorption occurs it can be degraded by soil microorganisms (Coupland 1985).

In plants glyphosate inhibits the enzyme 5-enolpyruvylshikimate 3 –phosphate synthase, which leads to the inhibition of protein synthesis. This is the only enzymatic process glyphosate is known to target, but it could affect many other physiochemical and physiological processes (Baylis 2000). Many herbicides have had detrimental effects on soil fauna (Eijsackers & Van de Bund 1980). Glyphosate has been shown to be harmful to certain arthropods in the field (Brust 1990; Santillo et al. 1989) and in the laboratory (Eijsackers 1985; Hassan et al. 1988). Application of Roundup® Biactive™ to field margins was found to decrease the abundance of Araneae, Carabids, and

Heteroptera for four months, with the abundance decreasing as the glyphosate concentration increased (Haughton et al. 1999b). However laboratory toxicity tests and field trials have often produced different results (Brust 1990; Eijsackers 1985; Haughton et al. 2001b). For example, glyphosate had no short-term toxicity to the spider

Lepthyphantes tenuis in laboratory tests, but in the field numbers were significantly reduced at the same application rates (Haughton et al. 2001b). It is thought that herbicides can affect fauna negatively through direct toxicity effects and/or indirect effects through habitat modification. As the treated vegetation dies the decreased canopy cover can change the microclimate. The invertebrates often become more exposed to the desiccating sun and wind, accompanied by an increase in surface temperature and decrease in soil moisture (Eijsackers & Van de Bund 1980; Haughton et al. 1999a; Haughton et al. 2001a).

Roundup® Biactive™ is commonly used to control C. monilifera on the N.S.W coastline (M. Hudson personal communication). There have been few studies examining the effects of this herbicide on invertebrate communities in the field. This

120 study aims to determine if Roundup® Biactive™ affects the abundance and composition of non-target leaf litter invertebrates within C. monilifera infestations. In particular, invertebrates involved in leaf litter decomposition and some of their predators were investigated, as the loss of these species from sites may influence the nutrient cycling following weed removal.

121

Methods

Study Sites

The experiment was carried out on the hind dunes of Caves Beach (35°16’S,

150°66’E), within Booderee National Park, Jervis Bay N.S.W. C. monilifera was introduced to this area in approximately 1968. All sites were heavily infested with C. monilifera (>75% cover) and had a sparse overstorey of Banksia integrifolia,

Eucalyptus botryoides and Leptospermum laevigatum.

Jervis Bay has a mean maximum day temperature of 19.9°C, a minimum of

13.6°C and a mean annual rainfall of 1244mm (Australian Bureau of Meteorology). The soil is a fine Aeolian sand with low amounts of carbonates. It is slightly acidic with low fertility and high permeability (Taylor et al. 1995; Waring 1954).

Two control quadrats and three treatment quadrats were selected which had not been previously sprayed with herbicide. The control quadrats were 20m x 10m and the herbicide treatment quadrats were each 10m x 10m. All quadrats were at least 5m apart from each other. Treatments were not randomly allocated to plots as we were constrained by the management objectives of the national park.

Invertebrate Sampling

All quadrats were initially sampled for leaf litter invertebrates four days prior to herbicide application in January 2002. Five samples were collected within each site, with each sample consisting of four 0.16 x 0.16m ground leaf litter scraping. Samples were transported in moistened cotton sacks until extraction. No area was ever sampled twice, and the following sample was never taken adjacent to a previous sample.

The treatment quadrats were sprayed with a 1:100 dilution of Roundup®

Biactive™ (360g/L a.i., Monsanto) at a rate of 3-4L glyphosate per hectare. This was

122 done with a high volume sprayer (Quickspray Model 9TBE) from the back of a vehicle.

All sites were sampled for litter invertebrates two, four, eight and sixteen weeks after spraying. Sampling stopped after this as the C. monilifera was dead and seasonal changes could alter the invertebrate population and make interpretation of results difficult.

All samples were extracted within 48 hours of collection, using a modified

Tullgren Funnel. The leaf litter was extracted for five days into 75% mono ethylene glycol and the invertebrates stored in 70% ethanol. Samples were sorted using a binocular microscope for the following taxa: Amphipoda (landhoppers), Araneae,

Blattodea (cockroaches), Haplotaxida (earthworms), Isopoda, Pseudoscorpionida, the millipede orders Julida, Sphaerotheriida and Spirobolida and the centipede orders

Scolopendrida, Geophilida and Lithobidda.

Change in Abundance

An unreplicated repeated measures analysis of variance was performed (JMP

2000) to test for differences in abundance and richness in relation to site (random factor), time (random factor), control/impact (fixed factor) and before/after treatment

(fixed factor) (Zar 1999). There was no appropriate mean squares for the denominator for the site(Control/Impact) and site x time(control/impact x before/after) factors

(Underwood 1997). Therefore no F or P values are displayed in table 5.1 for these factors. The data were also analysed with SYSTAT (2000) without the before/after factor to test for the assumption of sphericity (assumption of independent sampling across time) (Keough & Mapstone 1995). All data except Amphipoda met this assumption, and therefore the degrees of freedom were corrected by the Huynh-Feldt

Epsilon value (Quinn & Keough 2002).

123

Analyses were performed for total abundance, number of taxa and abundance of

Isopoda, Amphipoda and Araneae. There were insufficient numbers in the other groups for them to be analysed individually, so analyses also investigated differences in

Diplopoda, decomposers (Amphipoda, Blattodea, Julida, Sphaerotheriida, Spirobolida,

Haplotaxida, Isopoda, Scolopendrida) and predators (Pseudoscorpionida, Araneae,

Scolopendrida, Geophilida and Lithobidda). All groups except number of taxa, were log(x+1) transformed prior to analysis to improve normality and homogeneity of variances.

Community Composition

Multivariate analysis was performed using PRIMER (1999) to determine if herbicide treatment affected invertebrate assemblages. Following the calculation of the

Bray-Curtis indices of similarity, data were ordinated using non-metric multidimensional scaling (nMDS) to visually assess the impact of the herbicide. A nested analysis of similarity (ANOSIM) with site nested in spray/control was initially undertaken to determine if there were any differences among sites within treatments

(Clarke & Warwick 1994). The assemblages in each quadrat within each treatment were significantly different (Site: Global R=0.153, P=0.001). Therefore, each site could be seen as a replicate, and the three impact quadrats and the two control quadrats could be grouped together for analysis.

A two way ANOSIM was then performed to determine differences between the five time periods and the control/impact samples. When significant differences were found similarity percentage analysis (SIMPER) was used to reveal which taxa changed between times and sites (% dissimilarity). Analyses were undertaken on square root transformed and presence/absence data to distinguish if differences were due to the

124 abundance of a particular taxa or the presence of specific taxa (Clarke & Warwick

1994). Results presented are for square root transformed data unless otherwise stated.

125

Results

The herbicide was effective at killing the C. monilifera plants as expected. Two weeks after application, the C. monilifera leaves had started to turn yellow and by eight weeks all C. monilifera plants were dead. A total of 11630 invertebrates were collected during the study. The amphipods were the most abundant order in the impact plots

(Figure 5.1, Figure 5.2b) and spiders the most abundant order in the control plots

(Figure 5.1, Figure 5.2c).

Figure 5.1: The mean (± S.E) average abundance of each taxa in the control and herbicide impact sites across all sample times.

120 Herbicide Control

100

60 Abundance

0 Acraneae Pseudoscorpian Amphipoda Blattodea Haploxida Isopda Sphaerotheriida Julida Spirobolida Scolopendrida Geophilida Lithobidda

126

Table 5.1: Summary of the unreplicated repeated measures ANOVA for the abundance of each group analysed. Significant values are in bold. P<0.05 significant level. Taxa Abundance Predators Mean Mean Mean df F P F P F P Square Square Square Site(Control/Impact) 3 4.056 - 0.4577 - - 0.1009 - - Sitex Time(Control/Impact,Before/After) 9 1.870 - 0.0416 - - 0.1612 - - SitexBefore/After(Control/Impact) 3 1.442 0.771 0.539 0.0491 1.18 0.371 0.2077 1.29 0.336 Control/Impact 1 38.08 9.39 0.055 14.76 32.2 0.011 0.2517 2.49 0.213 Control/Impact*Before/After 1 1.633 1.13 0.366 0.0183 0.372 0.585 0.0207 0.010 0.773 Time(Before/After) 3 22.13 11.8 0.002 0.5710 13.7 0.001 0.6138 3.81 0.052 TimexControl/Impact(Before/After) 3 6.882 3.68 0.056 0.2166 5.21 0.023 0.0314 0.195 0.897 Before/After 1 40.83 28.3 0.013 1.216 24.8 0.016 0.3685 1.77 0.275 Decomposers Diplopod Isopoda Source Mean Mean Mean df F P F P F P Square Square Square Site(Control/Impact) 3 0.631 - - 1.44 - - 3.35 - - SitexTime(Control/Impact,Before/After) 9 0.043 - - 0.095 - - 0.083 - - SitexBefore/After(Control/Impact) 3 0.033 0.764 0.542 0.312 3.28 0.805 0.096 1.15 0.381 Control/Impact 1 25.9 41.0 0.008 0.990 0.686 0.468 4.44 1.33 0.332 Control/Impact*Before/After 1 0.008 0.003 0.963 0.166 0.532 0.963 0.008 0.084 0.791 Time(Before/After) 3 0.756 17.5 0.000 0.404 4.23 0.041 0.141 1.69 0.238 Time*Control/Impact(Before/After) 3 0.396 9.14 0.004 0.250 2.63 0.114 0.0890 1.07 0.409 Before/After 1 1.50 45.4 0.007 2.32 7.43 0.072 0.060 0.622 0.088 Spiders Amphipoda Mean Corrected Mean df F P F P Square d.f Square Site(Control/Impact) 3 0.0503 - - 2.6 0.1716 - - SitexTime(Control/Impact,Before/After) 9 0.1417 - - 7.4 0.0290 - - Site*Before/After(Control/Impact) 3 0.1160 0.818 0.561 2.6 0.1130 3.90 0.762 Control/Impact 1 0.2796 5.56 0.100 0.88 45.21 264 0.007 Control/Impact*Before/After 1 0.0127 0.110 0.923 0.88 0.1107 0.980 0.395 Time(Before/After) 3 0.5805 4.10 0.043 2.6 0.7417 25.6 0.000 TimexControl/Impact(Before/After) 3 0.0396 0.279 0.839 2.6 0.3845 13.3 0.003 Before/After 1 0.0845 0.728 0.456 0.88 1.460 12.9 0.037

127

Changes in Abundance of Taxa

There was no significant short or long-term decrease in invertebrate abundance following herbicide application. The short-term impacts are indicated by a significant control/impact x time (before/after) interaction (Keough & Mapstone 1995). This interaction was only significant for the amphipods (F3, 7=13.3, P=0.003) (Table 5.1).

However, there was an increase, in abundance of amphipods two, four and sixteen weeks after impact compared to the pre-impact samples (Figure 5.2b). Longer-term impacts are indicated in the control/impact x before/after interaction (Keough &

Mapstone 1995). This interaction was not significant for any of the groups analysed.

The control and impact sites were different in total abundance, despite their close proximity (F1, 3=32.2, P=0.011) (Figure 5.2). This difference was mainly due to the high abundance of amphipods in the impact sites (Figure 5.1) which also had a significant control/impact effect (F1,3 =264, P=0.007).

There was considerable variation in abundance of most taxa between sampling times for the control and impact sites (Figure 5.2). The lowest numbers were collected in both the control and impact sites before spraying, and again eight weeks after spraying. These sampling times received the lowest rainfall (Figure 5.3). The spiders, pseudoscorpions and centipedes were all present in similar numbers in the control and impact sites, and numbers fluctuated in a similar pattern during sampling (Figure 5.2c, d and h).

128

Figure 5.2: The mean total abundance of invertebrates and abundance of dominant groups(± S.E), before and after glyphosate application for the herbicide impact and control sites.

a. Total Abundance b. Amphipods

250 Herbicide 180 Control 160 200 140 120 150 100 80 100 Abundance Abundance 60

50 40 20 0 0 Before 2 4 8 16 Before 2 4 8 16 Time (weeks) after herbicide treatment Time (weeks) after herbicide application

c. Araneae d. Chilopoda

14 6

12 5 10 4 8 3 6 Abundance Abundance 2 4

2 1

0 0 Before 2 4 8 16 Before24816 Time (weeks) after herbicde application Time (weeks) after herbicide application

129 e. Diplopoda f. Earthworms

35 16 30 14

25 12 10 20 8 15 6 Abundance Abundance 10 4 5 2 0 0 Before24816 Before 2 4 8 16 Time (weeks) after herbicide application Time (weeks) after herbicide application

g. Isopoda h. Pseudoscorpions

4 35

30 3 25

20 2 15 Abundance Abundance 10 1

0 0 Before 2 4 8 16 Before24816 Time (weeks) after herbicide application Time (weeks) after herbicide application

130

Figure 5.3: The daily precipitation (mm) and mean air temperature (◦C) at Jervis Bay during the experiment.

30 120

25 100

20 80

15 60

10 40 Temperature (°C) Precipitation (mm)

5 20

0 0 10-Jan 24-Jan 7-Feb 21-Feb 7-Mar 21-Mar 4-Apr 18-Apr 2-May 16-May

Community Composition

There were significant differences in the invertebrate assemblages between sampling times (Global R =0.109, P=0.001) and control and impact sites (Global R

=0.796, P=0.001) when these two factors were analysed using an ANOSIM. The before samples were significantly different to all post treatment samples, except at sixteen weeks (Table 5.2). These after impact samples had an average dissimilarity of 53.4% to the before samples, with the amphipods (32.9%) and isopods (15.7%) contributing to most of the dissimilarity.

131

Table 5.2: Results of the analysis of similarity, comparing the before impact time with the four after impact sampling times, for impact and control sites. Data were square root transformed.

Test R P

Global test 0.109 0.001

Pairwise

2 weeks 0.183 0.001

4 weeks 0.230 0.001

8 weeks 0.073 0.025

16 weeks 0.045 0.091

The average dissimilarity amongst sites within the impact group was 40.6% and for the control group 59.6%. The average dissimilarity between the impact and control samples was high at 73.7% (Figure 5.4). SIMPER analysis of abundance data indicated the earthworms (12.3%) and amphipods (42.3%) consistently contributed to the dissimilarity between the two groups. However, for presence/absence data only the earthworms (15.2%) had a high contribution to the dissimilarity. They were consistently present in the spray sites, but only occasionally in the control sites.

132

Figure 5.4: nMDS ordination of a, control and impact sites across and sampling times and b, the before and after impact sample times. Stress = 0.13. a.

133

Discussion

The application of Roundup® Biactive™ to the C. monilifera had no direct or indirect effect on leaf litter invertebrate abundance or community composition in the four months following application. The litter invertebrate assemblages were highly variable on a small spatial scale (tens of meters) and were sensitive to the micro- environmental changes. Rainfall and temperature appeared more important in regulating invertebrate numbers than glyphosate application.

Direct Toxic effects

Glyphosate has been shown to be toxic to invertebrates in laboratory tests

(Eijsackers 1985; Hassan et al. 1988; Mohamed et al. 1992), but this study demonstrates that it is non-toxic in the field (Brust 1990; Haughton et al. 2001b). Direct toxic effects would be indicated by a decrease in abundance in the initial post application samples. There was only a small decrease in Araneae and Pseudoscorpions two weeks post impact (Table 5.1). This decrease was not significant and could be due natural fluctuation in the communities.

The amount of direct exposure the invertebrates had to the herbicide is not known. Glyphosate decays slowly in sandy soils, and can still be detected in sandy loam

120 days after application (Eberbach & Douglas 1983). However, the consistent rainfall that began the day after application (Figure 5.3) may have removed or diluted any soil residue. The amount of herbicide that reached the leaf litter and ground is also unknown. C. monilifera is a dense shrub, and the abundant foliage could have prevented spray drift contacting the ground.

134

Indirect effects

The negative impact of glyphosate on invertebrate communities in the field is generally due to indirect affects (Brust 1990; Haughton et al. 2001b; Haughton et al.

1999b; House et al. 1987). Indirect effects include changes in vegetation structure, microclimate changes, loss of food source and decrease in habitat quality. No indirect effects were detected in this study. Invertebrate numbers did not decrease up to 16 weeks after impact (Table 5.1, Figure 5.3), and changes in community composition appear to be due to abiotic factors. Samples were collected for four months following impact, even though the C. monilifera plants were dead by eight weeks. The large sudden leaf input following herbicide application can alter leaf litter invertebrate communities (Eijsackers & Van de Bund 1980). However, the dying C. monilifera lost few leaves, and it has been observed that the leaves usually stay on herbicide sprayed plants until they are uprooted or are physically removed (B. Rafferty, personal communication). The leaf litter under the C. monilifera also contained native leaves from surrounding remnant vegetation. These are much slower to decompose (Lindsay &

French In Press) and could have provided a safe habitat and food source for the invertebrates once the C. monilifera was dead and the existing C. monilifera leaves had decomposed.

These results of this study conflict with those found by Haughton (1999b) and

House (1987), but both experiments used higher application rates of glyphosate. In field margins applied with 360g a.i.hectare-1 of Roundup® Biactive™, there was a significant decrease in total invertebrate abundance (31%) and Araneae abundance (18%) in treated areas (Haughton et al. 1999b). While in wheat fields applied with 1.57kg a.i. hectare-1 macro-arthropod abundance decreased, with the significance varying with season

(House et al. 1987). In both cases, the decrease in abundance was thought to be due to a

135 decline in habitat quality and/or loss of food source. The vegetation structure and microclimate of these sites would have been considerably different to the C. monilifera infestations investigated in this study, which were not isolated vegetation patches in an agricultural landscape. The remnant native vegetation could have protected the invertebrates from desiccation and temperature extremes. Larger mobile invertebrates could also have used the adjacent areas to forage. This indicates that the detrimental indirect effects herbicide application has on non-target litter invertebrates may depend upon the application rate, the vegetation community and structure and the post-spray climate.

Rainfall and Temperature

The invertebrate communities were highly variable at a small spatial scale, with assemblages differing between spray sites and between the spray and control sites before impact. The same taxa were present in the control sites as in the impact sites, but in lower abundance. Many abiotic factors including temperature, rainfall and soil moisture can regulate invertebrate populations (Remmert 1981). The control area was closer to the beach and was more exposed to onshore winds. The litter microclimate, especially the moisture level, would have been different possibly making the protected impact site a more favourable habitat.

Invertebrate assemblages were different between the majority of sampling times.

The large increase in some taxa with increasing rainfall (Figure 5.2 and 5.3) appears to have caused most of this difference. The rainfall fluctuated during the study, but was average for this time of the year.

Sampling times with lower rainfall (before spraying and at eight weeks) had a lower abundance of Haplotaxida, Chilopoda, Diplopoda and Amphipoda. The

136 abundance of these animals has been correlated with rainfall and/or moisture

(Greenslade & Greenslade 1983; Lee 1983; Reddy 1984; Reddy & Ventatiah 1990). In

Australia earthworms (Haplotaxida) are limited in their activity and abundance by their need for moisture (Lee 1983). When it is dry they spend less time in the leaf litter and more time in the soil to prevent desiccation (Reddy 1984). The Amphipoda prefer moist conditions, and can occur in large numbers when the conditions are right (Moeed &

Meeds 1985). Unlike earthworms, Amphipods and many other arthropods can’t burrow deeply into the soil and are not highly mobile, therefore when it becomes dry or hot they may die (Greenslade & Greenslade 1984; Reddy & Ventatiah 1990).

There was more rainfall during the final sampling (sixteen week) than the previous sample (eight weeks), yet there was a decrease in isopods, spiders, and centipedes especially in the control sites. The final samples were collected in autumn, where as the experiment had begun in summer and as such, the mean air temperature had decreased by 7.3 °C (Figure 5.3). The abundance and surface activity of many arthropods changes with season (Reddy 1984; Reddy & Ventatiah 1990) and the abundance of these taxa has been correlated with temperature (Moeed & Meeds 1985).

The combined affect of rainfall and temperature on invertebrate abundance and composition could have overridden any indirect affects of the herbicide.

137

Conclusions

Application of dilute Roundup® Biactive™ in summer had no short-term impact on the abundance of leaf litter invertebrates examined in this study. Further studies are needed to determine the effects of glyphosate and the Roundup® Biactive™ formulation on the long-term life history of the litter invertebrates, especially their growth rate, behaviour and reproduction.

Abiotic factors appeared more significant in regulating leaf litter invertebrates numbers than glyphosate application. House (1987) drew the same conclusion when examining microarthropod populations in agricultural field sites. The response to glyphosate could depend on the season of application, current rainfall and temperature.

This is the first study looking at invertebrates and glyphosate application to an environmental weed. These results conflict with the other limited studies in agricultural systems, indicating the impact could depend upon the vegetation community and structure.

138

Chapter 6

Conclusion

139

The ability to change ecosystem processes has been proposed as a mechanism that could assist weeds to invade undisturbed native vegetation (Ehrenfeld et al. 2001).

This study has demonstrated that C. monilifera invasion can change the ecosystem processes of decomposition and nutrient cycling, which may help explain how C. monilifera has the ability to invade and establish in both disturbed and intact vegetation communities. These changes were attributed to alterations in quality and quality of leaf litter, abundance of detritivores and microclimate following C. monilifera invasion.

Overall, C. monilifera had negative impacts on leaf litter invertebrate abundance and diversity. This study has shown however, that weed invasion does not impact all invertebrates and for some invertebrates C. monilifera is a new habitat providing an alternative food source. Few insect herbivores or parasites are known to utilise C. monilifera in Australia (Edwards 1993), however leaf litter invertebrates were involved in the leaf litter decomposition. Once the leaves have fallen from the trees biochemical changes and/or leaching of phytotoxins (secondary metabolites) could make it more susceptible to attack.

The differential response of invertebrates to weed invasion in this study indicates that the use of one or two indicator species or orders may not detect the full range of effects of weed invasion. While most studies choose taxa that will be susceptible to impact, the consequences of taxa that respond positively to invasion can have just as significant as effects on the ecosystem. This reinforces the need for careful use and selection of indicator species/groups.

There were no detectable impacts on leaf litter invertebrates under C. monilifera after application of the minimum recommended dose of glyphosate as the formulation

Roundup® Biactive™. This formulation is publicised as being environmentally sensitive, and this study supports this claim in regards to litter fauna. Roundup Biactive

140 should still be used cautiously and only as prescribed, as impacts on many other fauna are unknown. Other glyphosate formulations should also be used with caution as additives other than the active ingredient can have impacts on invertebrates.

Weed invasion could be more detrimental to the litter invertebrate fauna when the vegetation structure is also modified, as well as there being a change in floristics.

However the invertebrate biodiversity study and the control/impact study both highlighted that invertebrates are sensitive to microclimatic changes, and sometimes more so than to changes in the vegetation structure and composition.

Recent studies have suggested that there are strong correlations between soil processes and plant species composition (Matson 1990; Wardle et al. 1999; Wedin &

Tilman 1990) and that species composition is important in controlling ecosystem fertility (Hobbie 1992). The change in soil nutrient status and possibly soil physical properties following a change in the dominant plant species in coastal scrublands supports these theories. The creation of positive feedback mechanisms between C. monilifera and the soil could increase the invasibility, as soil fertility can affect the long-term vegetation composition. The increased soil nitrogen could also assist in establishing high density infestations and provide a source of nitrogen to utilise if competition from native plants increased. The alteration in soil nutrient availability could affect further colonisation of the site with these changes having important ramifications for the restoration of native communities.

In studies where there has been an increase in soil nitrogen following invasion by an exotic plant species, the plant has generally been a nitrogen fixer (Fogarty &

Facelli 1999; Matson 1990; Musil 1993; Vitousek et al. 1987; Witkowski 1991). While

C. monilifera may have an association with vesicular-arbuscular mycorrhizal fungi to enhance nutrient uptake (Copeland 1983), there have been no reports of C. monilifera

141 fixing atmospheric nitrogen. There have been few studies demonstrating increases in soil nitrogen with non-nitrogen fixing exotic species. Where it has been examined, similar findings have been obtained to this study, with the change in nutrient cycling attributed to a higher quality litter that decomposed more readily than the native species

(Ehrenfeld et al. 2001; Standish et al. In press). However, the possibility that the changes in microclimate under C. monilifera might enhance free-living nitrogen-fixing microbes should be investigated.

These results have implications for other coastal weed invasions and for C. monilifera spp. monilifera (Boneseed). Bone seed is a weed in woodlands, forests and coastal Victoria. The leaves are very similar to those on C. monilifera spp. rotundata and are likely to decompose quickly. The soils where Boneseed grows are more developed and of a higher nutrient status than sand dunes. Therefore, the extent of impact should not be as great, but this would be dependent on the establishment of positive feedbacks.

Three examples of invasive environmental weeds that occur on the dunes of south-eastern Australia are Lantana camara, Lycium ferocissimum (African Boxthorn), and Myrsiphyllum asparagoides (Bridal creeper) (Carolin & Clarke 1991; Muyt 2001).

Like many exotic species in Australia, they have softer leaves than native species (Lake

& Leishman In Press). The leaves of the shrub L. ferocissimum are fleshy and the leaves

(cladodes) of the climber M. asparagoides are flexible and shinny. While the lignin or

C:N ratio of these species is not known, all appear less tough, less sclerophyllous and overall of higher quality. L. camara is known to decompose faster than wet sclerophyll forest species (Rees 1998) and is it is likely the other two species would decompose quickly as well. Depending on factors such as the annual leaf fall and biomass allocation, these species have the potential to alter nutrient cycling.

142

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Appendix

The Newton iterative technique (Anton 1992) was used to determine the time for 99% decay for the double exponential decay model in Chapter 2.

-k1t -k2 t Mt/ Mi=Ae + (1-A) e

At t Mt/ Mi=0.01 -k1t -k t 0.01=Ae + (1-A) e 2 k t Multiply by e 1 0.01ek1t=A + (1-A) ek1t e-k2t (1-A) (et) (k1-k2) –0.01 (et)k1 + A = 0 Substitute U= et (1-A) U(k1-k2) – 0.01Uk1 + A =0 (k1-k2) k1 f (Un)= (1-A) U – 0.01U + A (k1-k2-1) k1-1 f’(Un)=(1-A)(k1-k2)U – 0.01k1 U (k1-k2) k1 Un+1=Un - (1-A) U – 0.01U + A (k1-k2-1) k1-1 (1-A)(k1-k2)U – 0.01k1 U

Iteration was performed until there was no significant difference in the result. U was then substituted into: t= ln U