The Benthic Macrofauna of Pool Habitats in Temperate Coastal

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2003 The benthic macrofauna of pool habitats in temperate coastal streams of the Illawarra, New South Wales: community ecology and response to natural and human induced disturbance Glenn James Johnstone University of Wollongong

Recommended Citation Johnstone, Glenn James, The benthic macrofauna of pool habitats in temperate coastal streams of the Illawarra, New South Wales: community ecology and response to natural and human induced disturbance, Doctor of Philosophy thesis, Department of Biological Sciences, University of Wollongong, 2003. http://ro.uow.edu.au/theses/1058

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The benthic macrofauna of pool habitats in temperate coastal streams of the Illawarra, New South Wales: Community ecology and response to natural and human induced disturbance

A thesis submitted in (partial) fulfilment of the

requirements for the award of the degree

DOCTOR OF PHILOSOPHY

from UNIVERSITY OF WOLLONGONG

By Glenn James Johnstone, Bachelor of Environmental Science (Hons)

DEPARTMENT OF BIOLOGICAL SCIENCES

2003 CERTIFICATION

I, Glenn James Johnstone, declare that this thesis, submitted in partial fulfilment of 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.

Glenn James Johnstone

4tn August 2003 DEDICATION

I dedicate this thesis to my mother and friend, Barbara Brien. Thank you for a lifetime of love, support, and friendship. Marshall Mount Creek, Illawarra, New South Wales Table of Contents

Table of Contents

Page Table of Contents I List of Figures VI List of Tables IX List of Plates XII Abstract XIII Acknowledgments XVI

Chapter 1 - General Introduction 1 1.1: Common features of stream macrofaunal assemblages 2 1.2: Spatial and temporal variability in the composition of macrofaunal assemblages 3 1.3: Factors influencing the distribution and structure of benthic macrofaunal assemblages 4 1.3.1: Water flow and the structure of benthic macrofauna assemblages 6 1.3.2: Flooding and the structure of macrofaunal assemblages 8 1.3.3: The affect of drying on benthic macrofauna 9 1.3.4: Urbanisation and human impacts on freshwater ecosystems.... 11 1.3.5: Substratum heterogeneity, benthic macrofaunal distribution, and disturbance 13 1.4: Accessing human impacts on the macrofauna of streams 14 1.5: Spatial independence in running waters: Unique issues for liner systems 15 1.6: Beyond-BACI impact assessment 16 1.7: Describing ecological assemblages: Univariate verses multivariate techniques 19 1.8: The West Dapto Monitoring Program 21 1.9: Aims and objectives 23

I Table of Contents

Chapter 2 - Regional setting, sampling design and methodology, and general characteristics of the fauna 28 2.1: Introduction 29 2.2: Regional Setting 30 2.2.1: Substratum variation and channel size 32 2.2.2: Climate, rainfall, and stream discharge 35 2.2.3: Drying events and definition as intermittent streams 38 2.2.4: Past and present landuse 40 2.2.5: Non-invertebrate fauna of the Ulawarra's streams 41 2.2.6: Freshwater invertebrate fauna of the Ulawarra's streams 42 2.3: Sampling Design and Methodology 43 2.3.1: Sampling design 43 2.3.2: Field Procedure 45 2.3.3: Sorting and Identification 47 2.4: General characteristics and distribution of the fauna 50 2.4.1: General description of the fauna 52 2.4.2: Global biogeographical distribution of collected families 59 2.4.3: Distribution within Australia 62 2.4.4: Distribution in New South Wales 64 2.4.5: Taxa collected in low numbers 63 2.4.6: Relatively abundant taxa 66

Chapter 3 - Spatial variability in the benthic macrofaunal assemblages in three coastal streams of the Illawarra 75 3.1: Introduction 76 3.2: Methods 78 3.2.1: Level of taxonomic resolution used in Chapters 3,4, and 6 78 3.2.2: Separation of analyses for control and putatively impacted streams in Chapter 3, 4, and 6 81 3.2.3: Tests for spatial variability in Chapter 3 82 3.2.4: Core and rare taxa in Chapter 3 84 3.2.5: Tests among substrate groups in the control streams in Chapter 3 84

II Table of Contents

3.2.6: Partitioning of variability among the control streams in Chapter 3 86

3.3: Results 87 3.3.1: The macrofaunal assemblages of Duck Creek 87 3.3.2: The macrofaunal assemblages of Mullet Creek 88 3.3.3: The macrofaunal assemblages of Marshall Mount Creek...... 93 3.3.4: Among site differences for each sampling occasion 96 3.3.5: Core and rare taxa in the control streams 96 3.3.6: Within and among creek similarity in the composition of macrofaunal assemblages 98 3.3.7: Differences among streams 98 3.3.8: Substrate Comparisons 101 3.4: Discussion 102

Chapter 4 — Temporal variability in the benthic macrofaunal assemblages of three temperate coastal streams in the Illawarra 108 4.1: Introduction 109 4.2: Methods 112 4.2.1: Long-term changes in assemblage composition 112 4.2.2: Seasonal variability in assemblage composition 113 4.2.3: The effect of flow cessation and drying on assemblage composition. 114 4.2.5: The effect of flood events on assemblage composition 115 4.3: Results 116 4.3.1: Overview 116 4.3.2: The effect of flow cessation and drying on assemblage composition 117 4.3.3: The effect of flood events on assemblage composition 129 4.3.4: Long-term changes in assemblage composition 132 4.3.5: Among season variability in assemblage composition 134 4.3.6: Tests among reallocated temporal periods for Marshall Mount Creek 136 4.4: Discussion 139

III Table of Contents

AAA: Overview 139 4.4.2: The lack of distinct seasonal variability 139 4.4.3: The influence of flow 142 4.4.4: The affect of drying 145 4.4.5: Independence, Type I errors, and the limitations of multivariate analysis of complex designs 150

Chapter 5 - Do rare taxa alter the interpretation of multivariate hypothesis tests of community structure? 152 5.1: Introduction 153 5.2: Methods 157 5.3: Results 158 5.3.1: Tests for Spatial and Temporal differences - rare taxa included 158 5.3.2: Elimination of Rare Taxa 160 5.4: Discussion 162

Chapter 6 - Impact Assessment - Univariate and multivariate approaches 167 6.1: Introduction 168 6.2: Methods I72 6.2.1: Description of the macrofaunal assemblages of Robin's and Reid Park Creeks I72 6.2.2: Univariate impact assessment 173 6.2.3: Multivariate impact assessment 176

6.3: Results I78 6.3.1: Composition and structure of the macrofaunal assemblages of Robin's and Reid Park Creeks 178 6.3.2: Temporal variability in the composition of the macrofaunal assemblages of Robin's and Reid Park Creeks 182 6.3.3: Univariate impact assessment - REML analysis 195 6.3.4: Multivariate impact assessment 199

6.4: Discussion 204 6.4.1: Overview 204 6.4.2: Univariate impact assessment 204

IV Table of Contents

6.4.3: Multivariate impact assessment 205 6.4.4: Assessing impacts using the proposed multivariate methodology 207

Chapter 7- General Discussion 212 7.1: Overview 213 7.2: Scale and the factors influencing the stream macrofauna of the Illawarra 215 7.3: The affect of drying 217 7.4: Impact Assessment 219 7.5: Conservation Implications 221

References 225

Appendix A 255 Appendix B 258 Appendix C 260 Appendix D 262 Appendix E 265

V List of Figures

List of Figures

Page Chapter 2

Figure 2.1: Location of study area in Australia and study streams in the Illawarra. ..31

Figure 2.2: Generalised profile, plan view, and general information regarding the coastal streams of the Illawarra, New South Wales, and their surrounds 33

Figure 2.3: Mean monthly rainfall for a) Albion Park and, b) Dapto, Illawarra, New South Wales 36

Figure 2.4: Total monthly rainfall recorded at Albion Park between March 1997 and February 1999 39

Figure 2.5: Hierarchical design used to sample benthic macroinvertebrate assemblages from five streams in the Illawarra, New South Wales 44

Figure 2.6: Broad geographic zones used to describe generalised distributional patterns of macroinvertebrates families in New South Wales 52

Figure 2.7: The mean number of macroinvertebrate a) individuals and b) taxa collected fromfive temperate coastal streams of the Illawarra, New South Wales, between 1997 and 1999 58

Figure 2.8: Frequency histogram of the number of taxa collected from five temperate coastal streams of the Illawarra, New South Wales, between 1997 and 1999 64

Chapter 3

Figure 3.1: Mean number of a) rare and, b) core taxa collected per sampling event from sites on Mullet, Duck and Marshall Mount Creeks between February 1997 and

February 1999 97

VI List of Figures

Chapter 4

Figure 4.1: The total number of each of 19 core taxa collected from three sites on Mullet Creek, Duck Creek, and Marshall Mount Creek between 1997 and 1999.. ..118

Figure 4.2: The total number of individual a) Chironominae, b) Triplectides, c) Tasmanocoenis, d) Atalophlebia, e) Centroptilium, f) Jappa, g) Ceratopogonidae, h) Orthocladinae, i) Tanypodinae, j) Hellythira, k) Ecnomus, /) Micronecta, m) Berosus adults, n) Berosus larvae, o) Paratya, p) Necterosoma adults, q) Necterosoma larvae, collected from Mullet Creek, Duck Creek, and Marshall Mount Creek in the Illawarra region of New South Wales 122

Figure 4.3: non-Metric Multidimensional Scaling plots of benthic macrofauna samples collected a) pre-drying and b) post-drying from nine sites on three coastal streams in the Illawarra, New South Wales 127

Figure 4.4: Mean density of benthic macroinvertebrates collected per m from a) Mullet Creek, b) Duck Creek, and c) Marshall Mount Creek in the Illawarra region of New South Wales between 1997 and 1999 131

Chapter 5

Figure 5.1: Examples chosen to illustrate the high proportion of rare taxa within communities of: a) fish collected from a stream in South Carolina, USA (Meffe & Sheldon 1988), b) Lepidoptera collected from a light trap in England (Williams 1964), and c) plants in a peat bog in Michigan, USA (Kenoyer 1927) 154

Figure 5.2: The mean number of a) rare taxa, and b) core taxa collected per sampling event from the benthic macrofaunal assemblages of three streams in the Illawarra region of New South Wales 159

VII List of Figures

Figure 5.3: The frequency of change in the Global R-value and the P-value following the elimination of rare taxa from 44 analysis of similarity tests conducted on a) untransformed quantitative, b) 4th root transformed quantitative, and c) binary data (presence or absence of taxa) 161

Chapter 6

Figure 6.1: non-Metric Multidimensional Scaling plots of 4th root transformed data from benthic macrofaunal samples taken pre and post-development at sites on Robin's Creek and Reid Park Creek in the Illawarra region, New South Wales 183

Figure 6.2: Mean number of a) core individuals and, b) core taxa collected per sampling event from sampling conducted between 1993 and 1995, and 1997 and 1999 infive stream s in the Illawarra, New South Wales 186

VIII List of Tables

List of Tables

Page Chapter 2

Table 2.1: Benthic macroinvertebrate taxa collected from sampling conducted in five temperate coastal streams of the Illawarra, New South Wales, between 1997 and 1999 53

Table 2.2: Distribution within New South Wales, Australia, and worldwide of the families of macroinvertebrates collected from five coastal streams in the Illawarra, New South Wales, between 1997 and 1999 60

Chapter 3

Table 3.1: Analysis of Similarities results for all tests performed in Chapter 3 89

Table 3.2: Non-parametric multivariate analysis of variance results for permutation of residuals under the full model for a 2 factor, nested design 99

Table 3.3: Mean Global R and P-values for Analysis of Similarity comparisons between different substrate and same substrate combinations for nine sites on three streams in the Illawarra, New South Wales 101

Chapter 4

Table 4.1: Results for analysis of similarity tests between pre and post-drying samples of benthic macrofaunal assemblages in three streams of the Illawarra, New South Wales 126

IX List of Tables

Table 4.3: Summary of analysis of similarities tests for differences among pre and post-development sampling periods 133

Table 4.4: Summary of analysis of similarities tests for differences among seasons in each year of sampling 135

Table 4.5: Summary of analysis of similarities tests for differences among individual seasons across all four years of sampling 137

Table 4.6: Summary of analysis of similarities tests for differences among reallocated temporal sampling periods for Marshall Mount Creek and Marshall Mount Creek Site 3 138

Chapter 5

Chapter 6

Table 6.1: Taxa for which a large percentage of the total number of individuals recorded across the entire study were collected from Robin's Creek Site 1 179

Table 6.2: Index of Multivariate Dispersion values for comparison of pre and post- development sampling events for four putatively impacted sites on Robin's Creek and Reid Park Creek in the Illawarra region of New South Wales 185

Table 6.3: Summary of Residual Maximum Likelihood (REML) analyses for differences between pre and post-impact periods 196

Table 6.4: Residual Maximum Likelihood model fitted to assess impact at four putatively impacted sites on temperate coastal streams in the Illawarra, New South

Wales 200

X List of Tables

Table 6.5: Index of Multivariate Dispersion for untransformed quantitative data, 4th root transformed quantitative data, and binary data calculated between pre and post- impact sampling periods for 15 sites sampled infive stream s in the Illawarra, New South Wales 201

Table 6.6: Mean and standard deviation of the Index of Multivariate Dispersion for untransformed quantitative data, 4th root transformed quantitative data, and binary data calculated between four putatively impacted and eleven control sites sampled in five streams in the Illawarra, New South Wales 202

XI List ofPlates

List of Plates

Page

Chapter 2

Plate 2.1: The Illawarra Escarpment and coastal plain looking south 32

Plate 2.2: Hess Sampler used to collect benthic macrofaunal samples from five coastal streams in the Illawarra region between 1997 and 1999 46

Plate 2.3: The author using a Hess Sampler to collect a benthic macrofaunal sample from Sitel on Robins Creek 47

XII Abstract

Abstract

The type and number of macrofauna present in streams changes markedly in space and time. Accurately and informatively describing changes in the composition of macrofaunal assemblages requires well replicated, quantitative sampling and the use of qualitative and quantitative descriptive and statistical techniques. I used a hierarchical design to quantitatively sample the benthic macroinvertebrate assemblages of pool habitats in five adjacent, temperate coastal streams of the

Illawarra region of New South Wales between 1997 and 1999. Sampling was replicated spatially (3 sites on each stream) and temporally (12 sampling occasions per year). The collected macrofauna were identified to the lowest taxonomic level possible with available keys. I used quantitative and qualitative univariate and multivariate statistical techniques to describe how the type and number of macroinvertebrates I collected changed in space and time. I also used multivariate hypothesis testing techniques (Analysis of Similarities) to test hypotheses regarding how these assemblages changed over a number of temporal scales and at two relatively small spatial scales, within and among adjacent streams.

Aquatic insects dominated the diverse benthic macroinvertebrate fauna that I collected from the five study streams, with (82.7%) of individuals and 110 (82.1%) of the 134 taxa identified being insects. Dipterans (mainly the Chironomidae), and

Ephemeropterans were particularly numerous. I also collected 24 non-insect taxa.

Twenty taxa, mostly insects, accounted for 95.4% of the total number of individuals I collected.

XIII Abstract

I detected significant spatial variability in the composition of the assemblages I sampled. This finding represents an important demonstration of fine scale spatial variability in the macrofaunal assemblages of pool habitats in temperate Australian streams. Interestingly, the complex pattern of variability displayed by major taxonomic groups (mainly insect orders) at the finest spatial scale sampled here, within creeks, was not evident at the among creeks scale. These assemblages also exhibited considerable temporal variability. I detected differences among years, among seasons in each year, within seasons, and among this study and Gregory's

(unpublished data) earlier study of the same sites. Differences among seasons were a reflection of the generally high degree of temporal variability present during the study and did not indicate specifically seasonal variability.

Abnormally severe climatic fluctuations experienced during this study appear to have been influential in structuring the macrofaunal assemblages that I sampled. I detected dramatic declines in the density of macrofauna after two flash flood events. Severe drying, which occurred during the 1997/98 El Nino induced drought, substantially altered not only the number but also the type of macrofauna I sampled. Air-breathing taxa dominated the shrinking pools of water that formed when flow ceased in late

1997. The response to drying and flooding detected here was similar to that documented for the macrofaunal assemblages of running water systems worldwide.

This study also represented the post-development sampling stage of an assymetrical

Beyond-BACI impact assessment that was designed to assess the potential impact of the construction phase of a major housing development at Horsley Park on the macrofauna of two streams adjacent to the development. The assemblages of four

XIV Abstract potentially impacted sites were compared to eleven control sites to determine whether changes occurring between pre-development (Gregory - unpublished data) and post- development (this study) periods indicated that an impact had occurred. The impact assessment design used to conduct this study is unique in that it contains both multiple putatively impacted and multiple control sites.

Neither the univariate or multivariate impact assessments provided evidence that an impact had occurred at any of the four putatively impacted sites. The high degree of temporal variability exhibited by these assemblages and associated with the severe climatic fluctuations that occurred during this study may have limited the study's ability to detect an impact and made a statistically valid univariate test for impact impossible. Differences in the macrofaunal composition and degree of variability exhibited by one putatively impacted site, Robin's Creek Site 1, can not be attributed to the effect of the Horsley Park housing development. Rather, they appear to reflect differences in substratum composition and flow variability between this site and all other sites I sampled. The results of this study highlight the difficulties inherent in detecting human impacts in spatially and temporally dynamic stream systems.

XV Acknowledgments

Acknowledgments

First and foremost my deepest thanks go my supervisors David Ayre and Andy Davis. The support, guidance, andfriendship they have shown me over the last few years have been invaluable to me. Thank you guys for the patience and confidence in me you have shown as I stumbled my way through some of life's little hiccups, became sidetracked by interesting yet ultimately fruitless tangents in my project, and even when I ran away to Antarctica for a few months.

At the beginning of this thesis Mick Gregory provided me with a great deal of guidance for which I am most appreciative. Thanks mate. Thanks also to all of the staff and students of the University of Wollongong Biological Sciences Department. At some time or another I have asked a question or sort some assistance from just about all of you and I thank you for the thoughtfulness of your replies and your readiness to help. I also owe thanks to Ken Russell of the Statistics Department of Wollongong University for much appreciated statistical advice and all the hard work he put into the REML analysis.

I'd also like to thank Richard Marchant for his comments on a draft manuscript of Chapter 5, Bob Clarke for advice on using the Index of Multivariate Dispersion, Simon Williams and his fellow workers at Sydney Water for their help with identifications, Peter Cranston for examining chironomid stomach contents for me, and Gunter Theischinger for help with a range of identifications, particularly dragonflies. A special thanks to Marti Jane Anderson for general statistical advice and the generosity with which she gave her time and expertise, much appreciated.

Many thanks to Ern, Karin, Jeff and everyone else who gave up a day to help me do my fieldwork. To the other members of the 54th Australian National Antarctic Research Expedition to Casey station thanks for your friendship and for sharing with me an experience and place like no other on earth. Particular thanks to my mates Drew Lee and Jonny Stark, hope your enjoying your stay down south this year guys. Many thanks to Eren Turak, Dan Mawer, and Gunter Theisinger. Your support and

XVI Acknowledgments help over the last few months has greatly influenced thefinal shap e of my thesis, much appreciated guys.

I give my thanks and love to my friends and family. To Andrew Ryan, Brett Shaw, and Andrew Gilmour my deepest love and respect for your friendship. I won't try to name everyone else but I will thank each of you in person over a quiet beer when the chance arrises. However, particular thanks go to Tom Celebrezze, who, as a fellow PhD student and great friend, shared the academic, psychological, and emotional ride that doing this thesis has been.

To my family, Andrew, Gen, Stuart, Brianna, Emma, and Cliff, I can not hope to fully express my appreciation for your support, friendship, and love over the past few years and throughout my entire life. Thank you for being such and important part of my life.

Lastly, to the unwavering pillar of love and support that has stood by me throughout my life, my mother, Barbara Brien, I give my deepest love. Without your strength and devotion none of this would have been possible.

XVII Chapter 1

Chapter 1 — General Introduction Chapter 1

1.1: Common features of stream macrofaunal assemblages

The benthic macrofauna of streams display several strikingly uniform features at higher taxonomic levels wherever in the world they are sampled. Insects dominate both in terms of the type and number of organisms present (Hynes 1970). For example, insects accounted for 93% of the individual macroinvertebrates collected from 199 sites across Victoria by Marchant et al. (1999), while 82 out of 107 taxa collected from 88 rivers across New Zealand by Quinn & Hickey (1990) were insects.

Typically, a small number of the macroinvertebrates collected from a stream assemblage are relatively abundant, while the rest are only collected in low numbers

(Gauch 1982, Marchant 1999). Most highly abundant taxa are insects, with the dipteran family Chironomidae and the Ephemeroptera often being particularly numerous (Hynes 1970, Williams 1981). Coleopterans and Trichopterans are also commonly collected in large numbers, while among non-insect taxa Oligochaetes and

Molluscs often contribute substantially to macrofaunal densities (Williams 1981,

Brooks & Boulton 1991). These basic features of benthic macrofaunal stream assemblages have been documented in prairie streams in Canada (Whiting & Clifford

1983) and the United States (Shieh et al. 1999), in the stony riffles of central Scotland

(Morrison 1990), south-eastern Australia (Downes et al. 1993), and Ghana (Hynes

1975), in the highland streams of the South American Andes (Flecker & Feifarek

1994, Jacobsen 1998, Miserendino 2001), in the Nepalese Himalayas (Suren 1994), in the rivers of northern Finland (Tikkanen et al. 1994), in tropical streams of northern

Australia (Outridge 1987) and southern India (Aranachalam et al. 1991), in intermittent desert streams in Arizona (Fisher et al 1982), and in the pools and riffles of intermittent and permanent streams in Australia (Boulton & Lake 1992a) and the

United States (McElravy et al. 1989, Miller & Golladay 1996). While many other

2 Chapter 1 references could be added to those above the message is clear: these basic features of stream macrofaunal assemblage structure are ubiquitous wherever we may sample, regardless of the habitat type, substratum, longitudinal section, or degree of water permanence in a system.

1.2: Spatial and temporal variability in the composition of macrofaunal assemblages

It is perhaps surprising then that at greater taxonomic resolution macrofaunal assemblages often vary so markedly in space and time. Macrofaunal assemblages differ not only in the relative abundance of macrofaunal species but also in their species composition (Hynes 1970). The resulting distribution of stream macrofauna is often described as patchy or heterogeneous (Palmer et al. 1997). Spatially this heterogeneity has been documented along the longitudinal gradients of streams

(Vannote et al. 1980), among major habitat types such as pools and riffles (Logan &

Brooker 1983), between edge and mid-channel habitats (Marchant et al. 1999), and among and within similar habitats (i.e., riffles) (Downes et al. 1993). Within habitats, aggregation of macrofauna in particular microhabitats is also common. For example, leaf litter may contain a more diverse and numerous macrofauna than surrounding areas of sand or cobble Baptista et al. (2001). At broader spatial scales variability is apparent among streams within the same catchments (Bunn et al. 1986, Growns &

Davis 1991) and across sizeable areas containing many catchments (Corkum 1989,

Quinn & Hickey 1990, Kay et al. 1999, Marchant et al. 1999). Indeed, spatial variability in the composition of macrofaunal assemblages has been well documented at almost all possible spatial dimensions within and among streams (Palmer et al.

1997).

3 Chapter 1

Temporal changes in the composition of macrofaunal assemblages occur over various time spans. However, temporal variability has received far less attention than the issue of spatial variability (Palmer et al. 1997) and subsequently we have a poorer understanding of how stream macrofauna change over time. Diurnal drift may alter assemblage composition on a daily basis (Boulton & Brock 1999, Ramirez & Pringle

2001). Seasonal variability in macrofaunal composition is commonly identified in temperate streams in the northern hemisphere (Doledec 1989, Feijoo et al. 1999,

Linke et al. 1999), yet shows no clear pattern with regard to season in temperate

Australian streams (Bunn et al. 1986), or in tropical stream systems (Melo &

Froehlich 2001) (seasonal variability is further discussed below). Moreover, while macrofaunal assemblages may display substantial variability from year to year, particularly among years in which extreme flow events occur (i.e., flash-flooding or drying) (McElravy et al. 1989), their basic composition may remain relatively stable over time. For example, Williams & Hynes (1977) found that the most abundant taxa in temporal streams in Canada changed little over time, while De Marmels (1998) detected little variation in the type or density of Odonata over five years in a mountain stream in northern Venezuela.

1.3: Factors influencing the distribution and structure of benthic macrofaunal assemblages

A multitude of biotic and abiotic processes interact to determine the type and number of organisms present in an ecological community (Roughgarden & Diamond 1986).

Biotic processes such as competition and predation are thought to be influential in determining the structure of benthic macrofaunal stream assemblages (Sih et al.

4 Chapter 1

1985). The macrofaunal assemblages of streams contain a range of invertebrate predators and are a major source of prey items for vertebrate predators such as fish

(Sih et al. 1985, Wooster 1994). However, experimental evidence of the effect of predation remains ambiguous. While some studies have demonstrated strong declines in macrofaunal density due to predation (Cooper et al. 1990), others find little if any impact caused by predators (Allan 1983). Similarly, the precise role of competitive interactions (i.e., competition for food, space, and refuge from predation), are unclear

(Sih et al. 1985, Wootten 1994). The importance of predation and competition may vary among habitats and over time and may be modified by disturbances to the structure of the physical habitat in which they take place (Sih et al. 1985).

The constantly changing physiochemical environment of streams also exerts a strong influence on macrofaunal assemblages. The volume and velocity of water flow in streams changes over time and differs at any one time along the course of a stream and among adjacent habitats (i.e., riffles and pools) (Boulton & Brook 1999).

Furthermore, high flow events may rearrange, destroy, or create new habitat (Erskine

& Warner 1988, Nanson & Erskine 1988). Drying events not only reduce or remove the medium in which all stream invertebrates are immersed and upon which they rely, water, but may also cause chemical and morphological changes to the stream channel and substratum (Boulton & Brook 1999). Water chemistry changes over the course of a year and may be substantially altered by inputs derived from human activity (Allan

1995, Boulton & Brook 1999).

Clearly, the potential matrix of biotic and physiochemical interactions and their possible role in structuring benthic stream assemblages is immense. Simply

5 Chapter 1 summarising the vast literature that documents the processes structuring macrofaunal stream assemblages is a lengthy undertaking and would be cumbersome here. Instead

I have focused the following discussion on four important influences on benthic stream assemblages; the flow of water (1.3.1), disturbance caused by extreme flow variability (1.3.2 & 1.3.3), the urbanisation of catchments (1.3.4), and substratum composition (1.3.5). These are important structural influences on benthic stream assemblages worldwide and have been suggested as particularly relevant to Australian macrofaunal assemblages (Lake et al. 1986, Barmuta 1989, Turak & Bickel 1994,

Downes et al. 1998, Townsend et al. 1997).

1.3.1: Water flow and the structure of benthic macrofauna assemblages

The flow of water is one of the most pervasive, variable, and regularly modified physical forces structuring stream assemblages (Boulton & Brook 1999). Spatial variability in the composition of macrofaunal assemblages is strongly influenced by the substantial differences in flow velocity that exist among habitats. Riffles are areas of fast turbulent flow, while pools contain relatively slow flowing or stagnant edges and areas of more rapid flow in the mid-channel. Morphological adaptations enable macroinvertebrates to exploit habitats that experience a range of flow velocities (See reviews in Hynes 1970 and Williams & Feltmate 1992).

The assemblages of riffle habitats are characterised by organisms that display adaptations for remaining attached to solid surfaces in turbulent, fast flow conditions

(Cummins & Merritt 1984). Such adaptations are widespread across various groups of aquatic insects but appear to be particularly prevalent among the Ephemeroptera,

Plecoptera, Coleoptera, and to a lesser extent the Diptera (See the habit category

6 Chapter 1

"dingers" in the "Summary of ecological and distributional data" tables in chapters 9-

25 of Merritt & Cummins (1984)). For example, many leptophlebiid mayflies and psephenid Coleoptera are dorso-ventrally flattened allowing them to exploit the relatively slow flowing waters of the boundary layers that form around solid surfaces in high flow areas (Hynes 1970, Boulton & Brook 1999). Leptophlebiids in particularly, are prominent members of the riffle assemblages of Australian streams

(Campbell 1990, Gooderham & Tsyrlin 2002).

In contrast, relieved of the immediate necessity to battle fast flows, the macrofauna of slow flowing and still water areas of streams (i.e., pools), utilise both benthic surfaces and the water column (Merritt & Cummins 1984, Boulton & Brooks 1999). For example, water skaters (Gerridae, Hemiptera) swim on the surface of the water, while other macroinvertebrates swim through the water column either via leg movements

(i.e., diving beetles - Dytiscidae, Coleoptera, and some Trichopterans) or undulating movements of the entire body (i.e., mayflies such as the Leptophlebiidae) (Merritt &

Cummins 1984). However, benthic surfaces are the most commonly inhabited areas of streams (Hynes 1970, Merritt & Cummins 1984). Macrofaunal organisms burrow into deposited sediments (i.e., caenid mayflies, many bivalve molluscs, and the

Chironominae, Diptera), attach to macrophytes (i.e., many odonates and gastropod molluscs), or move freely over the substratum (Merritt & Cummins 1984, Boulton &

Brooks 1999).

Temporal fluctuations in water flow may be important influences on the structure of macrofaunal assemblages. Seasonal variability in macrofaunal composition is commonly identified in temperate streams in the northern hemisphere (Doledec 1989,

7 Chapter 1

Feijoo et al. 1999, Linke et al. 1999). However, the macrofaunal assemblages of temperate Australian streams show no clear pattern with regard to season (Bunn et al.

1986). The expectation of higher macrofaunal densities in summer, derived mainly from Northern Hemisphere studies, has been demonstrated in some temperate

Australian streams (Marchant et al. 1984), but not in others (Lake 1982, Marchant et al. 1985, Lake et al. 1986). A similarly ambiguous picture emerges in tropical stream systems. Melo & Froehlich (2001) note that many previous studies detected differences in the composition of macrofaunal assemblages between wet and dry seasons in tropical streams. However, their study in 10 tropical streams in southern

Brazil and Ramirez & Pringle's (1998) study of a lowland stream in Costa Rica found no differences in either the richness or abundance of macroinvertebrates among seasons. Flow variability among seasons is less marked in the temperate stream systems of Australia than in the tropics or in temperate systems in the Northern

Hemisphere (Lake et al. 1986). Boulton & Lake (1992a, 1992b) suggest that extremes of flow variability (i.e., flooding and drying) may be an important influence on the structure of macrofaunal assemblages in temperate Australian systems.

1.3.2: Flooding and the structure of macrofaunal assemblages

High flow events (floods) cause drastic yet relatively short-lived changes in the structure of benthic macrofaunal assemblages. Studies have repeatedly demonstrated that even relatively minor flood events may drastically decrease the density of benthic macrofauna, with decreases of up to 98% having been recorded (Fisher et al. 1982).

Reductions of 70% to 90% are commonly detected in temperate Australian streams

(Brooks & Boulton 1991, Boulton & Lake 1992a). However, recovery to pre-flood densities is normally rapid, usually taking only a few weeks (Fisher et al 1982,

8 Chapter 1

McElravy et al. 1989, Scrimgeour & Winterbourn 1989, Scrimgeour et al. 1988,

Brooks & Boulton 1991). Importantly, there is often little change in the type of macrofaunal taxa present between pre and post-flood assemblages (Boulton & Lake

1992a & 1992b). Furthermore, post-flood macrofauna have been found to have similar size and age distributions as those recorded pre-flood (Hynes 1968, Bishop

1973). These findings suggest the use of refuges in which the benthos ride out the disturbance caused by flooding, rather than recovery via post-flood recruitment mechanisms (Boulton & Lake 1992a).

1.3.3: The affect of drying on benthic macrofauna

Drying is a regular phenomenon in temporary and intermittent streams and exerts a strong influence on the structure of macrofaunal assemblages. Stream systems range from those permanently containing flowing water to temporary streams in arid areas, which may only contain running water for brief periods after rainfall events (Boulton

& Brook 1999). The assemblages of temporary streams are characterised by macrofauna with short life cycles, desiccation resistant dormant phases, mostly as eggs, and species able to colonise from nearby more permanent water bodies (Lake

1995). Most of the streams in Australia are temporary due to the low levels and sporadic nature of rainfall across the vast arid interior of the continent (Lake 1995,

Boulton & Brook 1999).

The use of moisture refuges is common in intermittent streams, allowing macrofauna to ride out dry spells. However, the period over which the stream remains dry may be an important factor in the success of this strategy. Boulton (1989) identified five refugial strategies allowing the benthic macrofauna of two intermittent streams in

9 Chapter 1 central Victoria to survive annual summer drying. These included desiccation- resistant life-cycle stages and four strategies associated with survival in remaining patches of moisture, either in the stream channel or in nearby water bodies. However,

Boulton et al. (1992) found that aerial re-colonisation rather than emergence from moisture refuges was responsible for the re-establishment of macrofaunal assemblages after a dry spell in Sycamore Creek, Arizona. They concluded that differences between the two systems were the result of the much longer period of drying in Sycamore Creek, which may have exhausted moisture refuges or made them uninhabitable. The findings of these studies suggest that the temporal scale of drying

(i.e., how long the dry spell lasts) may substantially affect the strategies which fauna adopt to re-establish assemblages. Re-colonisation may lead to assemblages that are, initially at least, quite different from those present before drying.

The effect of drying on the macrofauna of permanent streams is unclear. Permanent streams are those that almost always contain water (i.e., in at least 90% of years

(Boulton & Brock 1999). Drying, although very irregular, can occur during the most severe of droughts (Boulton & Brock 1999). Studies in the Northern Hemisphere suggest that the macrofauna of permanent streams may be well adapted to short-term drying (Delucchi 1988). Boulton & Lake (1992a) have suggested that the macrofauna of permanent streams in Australia may have evolved from a fauna exposed to regular drying and may therefore exhibit adaptations to surviving dry spells. However, this suggestion was drawn from a comparison of the assemblages of intermittent streams, which experienced summer dry spells, and nearby permanent streams that did not.

Although Chessman & Robinson (1987) concluded that a period of record low flow levels during a drought in 1982/83 had little effect on the macrofauna of the lower La

10 Chapter 1

Trobe River in Victoria, there do not appear to have been any studies directly documenting the affects of drying on the macrofauna of permanent streams in

Australia. This is perhaps unsurprising given that by definition permanent streams dry up only very rarely and unpredictably.

1.3.4: Urbanisation and human impacts on freshwater ecosystems

A broad range of human activities detrimentally impact upon benthic macrofaunal assemblages (see the many examples listed in Turak & Bickel 1994 and Richter et al.

1997). Anthropogenic changes to the physical and chemical nature of stream systems since European settlement in Australia have been substantial (Cullen & Lake 1995,

Chessman & Williams 1999). Brierley et al. (1999) found that European settlement has drastically altered the nature of channel and floodplain interactions, habitat availability and stability, and the dynamics of water flow along watercourses in the

Bega Valley catchment in south-eastern New South Wales. In Australia, documented impacts on macrofaunal assemblages include, but are certainly not limited to, the effect of organic pollutants (Jolly & Chapman 1966, Arthington et al. 1982, Cosser

1988), treated sewage effluent (Watson et al. 1982, Wright et al. 1995), treated sugar mill effluent (Pearson & Penridge 1987), treated pulp mill waste water (Harris et al.

1992), the construction of impoundments (Hogg & Norris 1991, Blyth et al. 1984,

Doeg & Koehn 1994, Storey et al. 1991), logging operations (Richardson 1985,

Growns & Davis 1991), and changes in landuse (Marchant et al. 1984, Pettigrove

1990).

Runoff from urban areas may contain a multitude of potential pollutants. The biological response to urbanisation will depend on the type of pollutants generated

11 Chapter 1 and their affect on the physical habitat and water chemistry of the receiving stream.

Development of land for urban use involves clearing of vegetation and an increase in the proportion of a catchment covered by impervious surfaces (Walsh 2000).

Consequently, the volume of surface runoff entering drainage channels increases substantially (Walsh 2000). Urban runoff contains suspended sediments, dissolved and particulate organic material, and a wide range of potential pollutants in concentrations far higher than those in pre-development surface runoff (Arthington et al. 1982, Walsh 2000).

The increased sediment loads often identified in streams receiving urban runoff may detrimentally affect the structure of benthic macrofaunal assemblages. Elevated sediment loads increase turbidity and may reduce available habitat by smothering surfaces suitable for larval recruitment and filling in interstitial spaces (Metzeling et al. 1995). Doeg & Milledge (1991) demonstrated increased rates of macrofaunal drift in response to experimentally increased concentrations of suspended sediments in the

Acheron River in Victoria. Hogg & Norris (1991) detected decreased macrofaunal numbers and species richness at sites downstream of an area of land clearing and urban development on Tuggeranong Creek in the ACT. They concluded that these decreases were caused by an increase in fine inorganic sediment load in runoff from the development altering the substratum of the pool habitats they sampled. Metzeling et al. (1995), in reviewing the effect of sedimentation on the macrofauna of Australian streams, concluded that sedimentation decreases species richness and alters assemblage composition.

12 Chapter 1

Decreased diversity appears to be a common affect of urban runoff on the

macrofaunal assemblages of streams. However, macrofaunal abundances may remain

steady or even increase due to marked increases in the abundance of a few tolerant

taxa. Whiting & Clifford (1983) found that urban runoff reduced the diversity of

macrofaunal assemblages in a small stream in Alberta, Canada. Moreover, they found

that taxa tolerant of organic enrichment (i.e., tubificid worms) and increased silt

deposition (i.e, caenid mayflies, Pisidium (Mollusca)) dominated sites receiving urban

runoff. Similarly, Pouliot (1993) found reduced species diversity and an assemblage

dominated by oligochaetes and chironomids at sites downstream of a discharge from

an urban drain in Darebin Creek in Victoria.

1.3.5: Substratum heterogeneity, benthic macrofaunal distribution, and

disturbance

Physically heterogeneous substratum generally support more diverse and numerous

macrofaunal assemblages than relatively homogenous substrata. Experimental

evidence suggests that substrate heterogeneity influences key stream ecosystem

processes such as algal productivity and benthic biofilm respiration (Cardinale et al.

2002). Studies of benthic macrofaunal assemblages have repeatedly demonstrated that

physically heterogeneous substrata support more diverse and abundant communities

than more uniform, homogenous substrata (Beisel et al. 2000). In the La Trobe River

in Victoria, Marchant et al. (1985) found that cobble substrata had a more diverse and numerous macrofauna than sandy substrata. However, Downes et al. (1993) documented significant differences among the macrofaunal assemblages of structurally similar habitats (riffles), and even among groups of stones within the

3 0009 0330015

13 Chapter 1 same habitat. Clearly, the composition of macrofaunal assemblages may differ not only among different substrata, but also within similar substrata types.

The effect of disturbance events, particularly those involving sheer stress such as flooding, may vary among substratum types. The amount of sheer stress necessary to mobilise substrata increases as the particle size of the substrata increases (Allan

1995). Given that substratum composition may vary substantially along the course of a stream the physical impact of a disturbance event such as a flood event may also be highly variable even among the habitats of a single stream. Death (1996) found that the magnitude of reductions in the abundance and diversity of macrofaunal assemblages due to disturbance events depended on the stability of the substrata. Less stable, and therefore more frequently disturbed substrata, displayed the largest decreases (Death 1996). Such findings suggest that to adequately quantify and generalise about the effect of disturbance events on the macrofaunal assemblages of streams requires that the macrofauna from a range of the available substratum types be sampled.

1.4: Accessing human impacts on the macrofauna of streams

Describing how assemblages change from place to place and over time remains a central task in ecological research. Accurately and quantitatively describing distributional patterns and how they vary in space and time requires properly replicated sampling designs (Underwood 1992, 1997b). Replication of sampling at appropriate spatial and temporal scales is a particularly relevant issue when assessing the impact of human activities on stream macrofauna (Underwood 1994b). Rigorous, well replicated sampling designs are particularly important when assessing impacts

14 Chapter 1 from diffuse sources of pollution such as urban runoff which may contain unknown and potential multitudinous pollutants. Importantly, any impact assessment design employed must addressed issues of spatial independence, some of which are unique to running water systems.

1.5: Spatial independence in running waters: Unique issues for linear systems

The linear nature of running water systems creates particular problems associated with ensuring independence among sampling locations (Faith et al. 1991, Underwood

1994b). If the measurements taken at one location are in some way correlated with those taken at another location, usually one close-by, then the samples are not independent (Underwood 1994a, 1994b). For example, if macrofaunal drift from one location provides the main supply of colonisers to a downstream location, macrofaunal densities in the two locations are correlated. Samples taken in the two locations are therefore not independent of one another (Underwood 1994a). Non- independence increases the probability of a statistical test rejecting the null hypothesis, and therefore concluding a significant difference, when in reality there is no evidence that the null should be rejected (i.e., a Type I error) (Sokal & Rolf 1995).

Ensuring independence involves both biological and statistical considerations, and is of paramount importance when designing a sampling program or impact assessment.

Unlike other statistical assumptions, data cannot be transformed after collection to remedy a lack of independence (Sokal & Rolf 1995).

The issue of independence in sampling programs designed to detect environmental impacts has received much attention in recent decades (Green 1979, Stewart-Oaten et

15 Chapter 1 al. 1986, Underwood 1991, 1992, 1994a) and is particularly problematic in running water systems. The linear nature of rivers and streams means that upstream sites may exert physical and biological influences on sites further downstream. Indeed, the existence of these influences is a central tenant of stream ecology (Hynes 1970) and has lead to influential theories attempting to explain stream fauna distribution such as the River Continuum Concept (Vannote et al. 1980). However, recognition of potential correlations between upstream and downstream sites has not always been taken into account in assessing impacts to running water systems. Hellawell (1986) contends that sites both upstream and downstream of a putative impact may be affected by pollutants other than those directly associated with the impact. While noting that this may confound attempts to detect differences due to the impact alone,

Hellawell (1986) fails to recognise that the biota of upstream and downstream sites may show differences regardless of the presence or absence of a putative impact.

Differences detected in sampling can therefore not be attributed to the influence of the impact alone. In such a design the upstream site is not an effective control for changes taking place at the downstream site, and may lead to irrelevant conclusions regarding an impact (Faith et al. 1991, Dostine et al. 1993). Careful biological and statistical decisions must be made to ensure independent locations are used when sampling in stream systems. Sampling designs, based on analysis of variance, have recently been developed that provide a logical framework for the design of spatially unconfounded impact assessment programs in running water systems (Underwood 1994a).

1.6: Beyond-BACI impact assessment

Beyond-BACI (Before-After-Impact-Control) designs provide logical, flexible frameworks with which to design impact assessments. Of particular importance in

16 Chapter 1 these designs is the issue of the spatial independence of samples and the appropriate temporal scales at which to sample to ensure unconfounded impact assessments. The progressive development of Beyond-BACI designs from the original BACI designs of

Green (1979) have been repeatedly detailed by Underwood (1991, 1992, 1994a &

1994b). Beyond-BACI designs assess impacts through sampling at a single putatively impacted site and multiple control sites on several occasions both before and after the onset of the suspected impact. These designs are therefore asymmetrical, comparing a number of controls to a single putatively impacted site (Underwood 1991, 1992). This asymmetry holds even if multiple putatively impacted sites are available, as long as the number of control sites is greater than the number of impacted sites. However, replicate impacted sites are rare (Underwood 1992), although not impossible, as the present study demonstrates (See Chapter 2). Where multiple putatively impacted sites are available they will most likely be few in number and will usually all be sampled.

However, selection of control sites requires careful consideration of the possible extent of the impact, and the physical and biological characteristics of both putatively impacted and control sites (Underwood 1992). When designing impact assessments in aquatic ecosystems such considerations are particularly relevant.

Control sites should come from a population of sites that are biologically and physically similar to the putatively impacted site or sites (Underwood 1992).

Obviously, the one characteristic control sites will lack is the presence of the impact.

Other than this feature, control sites should be chosen from a group or population of sites that for any particular characteristic, biological or physical, could include the impacted site (Underwood 1994b). This requirement stems from the basis for any scientific experimentation, that only a single variable should be manipulated between

17 Chapter 1 treatments. However, in natural systems exact concordance between any two sites, let alone a group of sites, is extremely unlikely. Therefore, control sites need not be exactly the same as the impacted site in every aspect, but should share as high a degree of similarity as possible (Underwood 1992, 1994b). In aquatic systems control sites have often incorrectly been chosen within the same water body (i.e., in the same lake and estuary), or the same stream (i.e., upstream of the impact site) (Underwood

1994b). For example, the release of a pollutant from a point source in an enclosed water body such as a lake, may have localised effects in the immediate area of the release, or may create a pollution gradient, spreading contamination in some measure throughout the entire water body. In the later case, any site within the lake may be affected by the pollutant. Therefore, no site within the lake can act as a control for the effect of the pollutant. Similarly, sites situated upstream of a putative impact can not on their own act as independent controls (Underwood 1994b). Unconfounded spatial sampling in such situations requires sampling in water bodies or streams completely unaffected by the potential impact.

Sampling at hierarchical spatial and temporal scales allows the flexibility necessary to address issues of independence and confounding in aquatic impact assessment designs. The sampling regime utilised for an impact assessment must be structured around the particular requirements dictated by the situation in question (Underwood

1994a). Sampling at several spatial scales allows the inclusion of multiple unimpacted controls. In stream systems, control sites may be located on a number of streams, each similar to the stream upon which the putative impact is to occur, but obviously lacking the presence of the impact. Temporally, sampling occasions maybe nested within particular periods (i.e., years or seasons). The random allocation of sampling

18 Chapter 1 dates within each of these periods increases the chance that sampling will account for within period temporal fluctuations in whatever variable is being measured (Stewart-

Oaten et al. 1986). Such fluctuations may not be accounted for by fixed interval sampling (Stewart-Oaten et al. 1986, Underwood 1994a). These hierarchically structured asymmetrical designs allow rigorous assessment of impacts in highly variable natural systems. Detailed examination of the considerable analytical complexity such designs can contain, and the logical steps necessary to determine whether an impact has occurred or not, have been set out by Underwood (1991, 1993,

1992, 1994a).

1.7: Describing ecological assemblages: Univariate verses multivariate techniques

The type and number of organisms present in any ecological assemblage changes from place to place and over time, complicating accurate description of assemblage composition (Norris & Georges 1993). Single samples, or snapshots, cannot account for the dynamic nature of assemblage composition. Well replicated sampling conducted over any reasonable time span can generate extremely large and complex data sets, presenting ecologists with the challenge of informatively describing the potentially multitudinous, intricate, and subtle changes in assemblage composition that these samples detect (Norris & Georges 1993). Moreover, such data sets also present the opportunity to test patterns of variability among highly dynamic assemblages within and across various spatial and temporal scales. To meet this challenge and this opportunity requires the use of both qualitative and quantitative descriptive and statistical techniques.

19 Chapter 1

Multivariate analysis techniques are useful tools with which to describe patterns and test hypotheses on large ecological data sets and have advantages over traditional univariate analysis methods (Boulton & Lake 1992a & 1992b). Differences between ecological assemblages have traditionally been measured as univariate differences between summary measures of assemblage composition (i.e., the mean number of individuals or taxa). However, univariate statistical tests do not include any assessment of the number of taxa common to both assemblages. Indeed, the result of a univariate test for differences among two assemblages will be the same even if they share absolutely no taxa in common. This inability to account for changes in the type of taxa present or how the relative abundance of these taxa may have changed is a major weakness of univariate statistics analysis of community data (Johnson et al.

1993). Changes in the type of taxa present and their relative abundance are important and potentially informative differences among assemblages (Rosenberg & Resh

1993).

Multivariate analysis techniques have been found to be more sensitive to changes in assemblage composition, while also being better able to illustrate such changes (Cao et al. 1996, Clarke 1993, Warwick & Clarke 1993). Multivariate analysis techniques allow each sample to characterise an assemblage via multiple descriptor variables, taking into account both the presence or absence and the abundance of a taxon (Norris

& Georges 1993, Legendre & Legendre 1998). Techniques such as ordination provide a powerful visual tool with which to interpret patterns, while hypothesis testing techniques such as analysis of similarities (Clarke 1993) provide a sound methodology for testing for differences in the relative abundance and presence or absence of macrofauna. The underlying assumptions of multivariate analyses are

20 Chapter 1 often less rigorous than those of univariate tests and are therefore more easily met by ecological data sets (Norris & Georges 1993, Legendre & Legendre 1998). However, multivariate statistical techniques have one major weakness; they do not provide appropriate, sophisticated models with which to design complex, multi-factored ecological sampling or experimentation.

Sampling via univariate designs does not preclude multivariate analysis of the resultant data set. At present, univariate analysis of variance principles are the most logical and flexible for designing complex, multi-factorial ecological experiments, sampling programmes and impact assessments (See discussion of Beyond-BACI designs above). An important assumption of multivariate analyses is that the groups in any analysis are defined a priori, particularly for multivariate hypothesis tests for differences among groups. The strict attention to appropriate site selection and temporal replication implicit in univariate designs such as Beyond-BACI impact assessments provides such groups. Moreover, the replication of sampling inherent in hierarchical, multi-factorial univariate designs provides data over a variety of spatial and temporal scales among which multivariate pattern analysis and hypothesis tests can be performed. Therefore, the more powerful descriptive abilities of multivariate analysis techniques can be used under the framework of rigorous univariate sampling designs

1.8: The West Dapto Monitoring Program

The present study was initiated to assess whether the initial construction phase of

Horsley Park residential housing development impacted upon the benthic macrofaunal assemblages at four putatively impacted sites in streams adjacent to the development.

21 Chapter 1

This program was initiated by the Wollongong City Council, in conjunction with researchers from the University of Wollongong. The program aims to utilise a combination of biological, engineering, and water quality studies to assess the effect on adjacent streams of stormwater runoff from the Horsley Park Stage 1 land release

(Roden 1995, Wollongong City Council 1995). The Stage 1 land release covers 130 hectares and will eventually include 1300 dwellings. It covers 8.6% of Robins Creek, and 9.9%) of Reid Park Creek's total catchment area. Approximately 3300 hectares of formally rural land in the West Dapto area will eventually be released for residential development and will contain approximately 50000 residents (Sinclair Knight 1994).

The West Dapto Monitoring Program is intended to guide the implementation of urban stormwater containment strategies for subsequent development in the area. The program aims to ensure ecological sustainable development that minimises impacts upon the areas streams and Lake Illawarra, into which the streams running through the area to be developed eventually discharge (Roden 1995).

All stormwater runoff arising from Horsley Park Stage 1 was intended to be directed into one of three water pollution control ponds. These control ponds were constructed in the initial stages of development with the intention of catching runoff from the construction phase of development, as well as runoff generated once the residential suburb was established (Wollongong City Council 1995). The ponds have maximum depths of between 2.5m and 5m, an average depth of 1.5m to 2m, and a surface area of between 0.90 and 1.14 hectares. The storage capacity of the ponds varies between

13ML and 20ML, and each pond in designed to have an excess storage capacity to retain a 1/100 year flood (Sinclair Knight 1994). The ponds trap sediment, bacteria, and other pollutants contained in surface runoff, thereby prohibiting their entry into

22 Chapter 1 adjacent streams. The construction phase of development has been designed to proceed in sections, with drainage channels located in each section to ensure that all runoff enters the retention ponds. By retaining potential pollutants in the ponds it is hoped that the hydrological and biological integrity of streams adjacent to the development will be maintained (Roden 1995).

Several mechanisms, including settlement, coagulation, and organic growth aid in retaining, utilising, and decomposing pollutant inputs into the ponds. Each pond contains a variety of macrophytes (Bolboschoenus fluviatilis, Cyperus polystachyos,

Juncus usitatus, Phragmites australis, Philydrum lanuginosum, and Triglochin procera), which cover approximately 30 to 40% of the total pond area (Sinclair

Knight 1994). These macrophyte assemblages are intended to utilise nutrients contained in the stormwater runoff and provide structural habitat complexity for freshwater macroinvertebrates, another group useful in filtering, decomposing, and cycling nutrients in pond waters and sediments. The majority of sediments present in the runoff will settle out onto the bottom of the pond. Lighter sediments will be forced to settle out of the water column via the periodic addition of gypsum to coagulate and flocculate suspended particulate matter. Metals bound to these sediments will also be retained in the ponds, which can be dredged if infilling becomes substantial

(Wollongong City Council 1995).

1.9: Aims and objectives

In conducting this study I had several aims, all of which were components of a single general aim - to describe the composition and structure of benthic macrofaunal stream assemblages in the Illawarra and to test hypotheses regarding how this composition

23 Chapter 1 and structure changed from place to place and over time. Interestingly, during the course of the study several different forms of potential disturbance occurred. These included both long and short-term climatic fluctuations and the commencement of major alterations to the surrounds and potentially to the type and volume of possible pollutants entering two of the study streams. These events allowed several potential influences upon the composition and structure of the sampled assemblages to be described.

The most obvious and pre-planned influence was the construction of a residential housing development. The sampling conducted in this study was designed to assess the impact of this housing development on the composition of the benthic macrofauna of adjacent streams. An asymmetrical Beyond-BACI impact assessment design was used to sample four putatively impacted and eleven control sites across five adjacent streams in the West Dapto area. All four putatively impacted sites, two on one stream and two on another, are located below the outlets of the water pollution control ponds in the Horsley Park development. The design is unique in that it contains both multiple putatively impacted and multiple control sites (Refer to Chapter 2 for full details). Although the nature of the impact to the two putatively impacted streams is the same, the construction of residential housing development, impacts to each stream are independent of one another. A ridge between the two streams ensures that all runoff entering each control pond comes from separate, unconnected sections of the development. Each creek therefore represents an independent replicate of the impact of housing development on benthic macrofaunal stream assemblages.

24 Chapter 1

The impact assessment conducted here is, in effect, aimed at assessing whether the pollution control ponds have functioned effectively. If functioning correctly, the control ponds should stop all surface runoff and associated pollutants from entering the adjacent streams and I should not be able to detect any impact to the benthic macrofaunal assemblages at the four putatively impacted sites. In this case the null hypothesis of no impact relative to the control sites will be retained. However, an impact, if detected (i.e., rejection of the null hypothesis), will indicate that the control ponds have failed to retain pollutant inputs and furthermore, that those inputs reaching the streams have affected the composition of the benthic macrofaunal assemblages at the putatively impacted sites relative to the control sites.

Replication of sampling across five adjacent streams allowed these macrofaunal assemblages to be rigorously described, as well as allowing hypotheses regarding spatial variability within and among streams to be tested. In Australia, stream ecologists have mostly focused on mapping broad scale distributional patterns

(Downes et al. 1993, Marchant et al. 1999). Marchant et al. (1999) argue that given the considerable areas of Australia for which we know little of the stream macrofauna, broad scale models of distribution are initially the most important to develop.

However, changes in the composition of benthic assemblages occurring over small spatial scales may confound models of macrofaunal distribution derived from larger sampling scales (Downes et al. 1993, Underwood 1994b). Significant variability identified by Downes et al. (1993) at very small spatial scales within and among riffles emphasises the need to sample benthic macrofaunal assemblages at a number of spatial scales if we are to fully understand their distribution. Moreover, pool habitats in Australia have not previously been sampled and compared at the small,

25 Chapter 1 local spatial scales at which Downes et al. (1993) sampledriffles. Th e present study is therefore significant in that it describes and tests for spatial variability among a poorly sampled habitat type, pools, at a spatial scale rarely sampled in Australia, within and among adjacent streams. Furthermore, the type of substrata present differed among the sampled pools, including spatially complex cobbles and relatively homogeneous sand, mud, and clay substrata. These differences presented the opportunity to describe and test for differences in the benthic macrofaunal assemblages present on substrata of varying heterogeneity.

Despite an ever growing body of literature on spatial variability, the temporal component of variability in benthic stream macrofaunal distribution has received far less attention (Palmer et al. 1997). Describing and understanding changing patterns of distribution within and among macrofaunal assemblages and assessing the affect of disturbances requires quantification of temporal variability (Boulton & Lake 1992a).

Moreover, having properly replicated samples taken both before and after a disturbance allows quantification not only of whether and how the assemblages may have changed, but also how variability in composition over time may have been affected by the disturbance. Disturbance events have been documented to change the degree of temporal variability experienced by a community (Warwick & Clarke

1993). This study presents an excellent opportunity to determine if and in what way variability over time in the composition of macrofaunal stream assemblages are affected by several different types of disturbance.

Unpredictable events occurring during the course of a study present the opportunity to describe how stream macrofauna respond to unmanipulated disturbances such as

26 Chapter 1 climatic fluctuations (Townsend 1989). Such accounts, even if in essence phenomenological (Townsend 1989), are important if we are to fully understand the dynamics of Australia's stream biota (Lake 2000). The replication of sampling within several spatial and temporal levels in the Beyond-BACI design employed in this study provided the opportunity to describe and test hypotheses regarding the effect of several flood events and a prolonged period of drying that occurred during sampling.

These opportunities are significant as such events occur irregularly and their occurrence is unlikely to be predicted in advance, particularly for short-term disturbances such as floods. Moreover, unless a sampling program is already underway, data on the composition of an assemblage immediately prior to the disturbance are not often available. The chance to study the affect of such events where well replicated pre and post-event samples are available is therefore important, particularly for drying events, the affect of which we know little about for the benthic macrofaunal assemblages of Australia's temperate streams. Furthermore, the replication of sampling at 15 sites on 5 adjacent streams and the range of substrata types from which macrofauna were sampled presented the opportunity to detect how the affect of these climatic disturbances differed spatially, particularly among different types of substrata.

27 Chapter 2

Chapter 2 — Regional setting, sampling design and methodology, and general characteristics of the fauna

28 Chapter 2

2.1: Introduction

The aim of this chapter is to provide a regional background to the study, detail how the study was conducted and to give an initial description of the macroinvertebrates collected here in terms of their distribution, their biological, and their ecological characteristics. Subsequently, the chapter is divided into three sections.

Firstly, I describe the climatic and topographic setting of the study region, detail past and present land-use in the area, and describe the study streams in terms of their physical nature, flow conditions, and their invertebrate, and non-invertebrate inhabitants (section 2.2 - Regional Setting). Next I detail the sampling design, field procedure, sorting, and identification techniques used in the study (section 2.3 -

Sampling Design and Methodology). It is important to note that the methodologies detailed in section 2.3 apply to the entire sampling program conducted in this study during which five streams were sampled over a period of two years, 1997 to 1999. In several subsequent chapters in the thesis I use only a sub-set of the complete data set compiled during the study. To avoid unnecessary repetition, the Methods sections of later chapters will only detail which parts of the data set are being used in that particular chapter as well as the hypotheses being tested and analyses being performed on that data.

Lastly, section 2.4 - General characteristics and distribution of the fauna - combines a results and discussion format to describe the distribution in New South Wales,

Australia-wide, and globally of macroinvertebrate families collected during this study.

Furthermore, I discuss the distribution of the taxa I collected across the five study

29 Chapter 2 streams and present possible biological and ecological explanations for the observed distributions. The aim of this discussion is to provide an initial exploration of the macrofauna I collected and their distribution that may suggest appropriate statistical hypotheses to be tested in later chapters.

2.2: Regional Setting

The five streams sampled in this study are located in the Illawarra region of New

South Wales, approximately 90km south of Sydney on the eastern coastline of

Australia (Figure 2.1). The Illawarra region is a narrow coastal plain flanked on the eastern side by the Pacific Ocean, and to the west by an escarpment, the south-eastern arm of the Sydney Basin. The escarpment rises to a maximum height of 770m and is formed of claystone and shales, with sandstone cliffs lining its top (Nanson & Young

1981a).

Originating as several tributaries on the slopes of the Illawarra Escarpment, each of the study streams flow in an easterly direction, crossing alluvial floodplains before discharging into an impounded coastal lagoon (Figure 2.1). All of these streams are relatively short, approximately 10 to 12 kilometres in length, and run almost parallel to each other across their floodplain sections. On the escarpment slopes they consist of steep boulder steps and associated step pools which descend through patches of remanent littoral rainforest within the dominantly wet sclerophyll eucalypt woodlands

(Nanson & Young 1981a, Nanson & Hean 1985). After a marked decrease in channel slope at the foot of the escarpment each stream crosses a mildly undulating alluvial floodplain (Plate 2.1). This floodplain extends for several kilometres from the base of the escarpment and is dominated by cleared pastureland used for dairy

30 Chapter 2

Figure 2.1: Location of study area in Australia and study streams in the Illawarra.

Sites are numbered 1 to 3 on each of the five streams sampled during this study.

farming. The lower sections of these streams flow cross a uniformly flat floodplain, moving through urbanised areas consisting mainly of residential housing before discharging into Lake Illawarra (Nanson & Young 1981a, Nanson & Hean 1985).

These streams are non-migratory along most of their course, particularly the lower floodplain sections. All five streams have suffered alterations to their channel structure to some extent, due mostly to clearing of riparian zones and channel modification in rural and urban areas. Along the floodplain sections of these streams grasses are the dominant vegetation type in the riparian zone, with tree and shrub coverage being minimal (Figure 2.2).

31 Chapter 2

Plate 2.1: The Illawarra Escarpment and coastal plain looking south. Labels indicate a) the Illawarra Escarpment, b) escarpment foothills, the area in which sampling was conducted in this study, c) lower floodplain, and d) the southern edge of Lake

Illawarra into which all study streams discharge.

2.2.1: Substratum variation and channel size

The streams sampled in this study contain three main substratum types; cobbles, sand, and mud (Figure 2.2(g)). Changes in substrata type can occur over relatively short stretches of each stream. Robin's and Reid Park Creeks have a mix of sand and clay substrates, with clay predominant in the floodplain sections sampled in this study.

The substratum on Mullet Creek is dominated by course sand, while Duck Creek and

Marshall Mount Creek consist of either course sand, medium sized rounded cobbles, or a mix of the two. Submerged Willow roots (Salix sp.) cover most of Robin's Creek

Site 1. These submerged roots form extensive mats around the base of several large

Willows that ring the site, trapping large amounts of sediment within their fibrous matrix. Samples at this site were taken from within this root mat. The substrata of

32 / - Chapter 2

0 Top of Escarpment Undulating hills formed by alluvial Gently sloping coastal plain Impounded Escarp slopes terraces shallow ment coastal a lagoon n c) Landfor n

Open Wet Pasture grasses, with thin riparian zones Introduced pasture grasses Seagrasses Eucalypt schlerophyll along some stream sections of native Forests & forest & Eucalypts & Casuarinas, and exotic Heathlarvd patches of LanXana carnara, Coral Trees (Erythrina littoral xsykesii), and willows (Salicaccae) rainforest d) Domini it Vegetation ' yp« •

Reserve Reserve Dairy fanning Urban residential & light Urban n/a with some industry, large flood prone residential pasture on areas undeveloped and usee around lower slope; for cattle grazing lakeshore e) Landuse

n/a Steep, Mild slope, channels relatively large & Gentle slope, small channel: n/a n/a narrow with increasing in size downstream. Confined, decreasing in size some deep narrow floodplains downstream, extensive pools below floodplains small waterfalls 0 Stream < Channel Form

n/a Boulders & Coarse sand & cobbles dominant, some sand, silt & clay n/a n/a bedrock clay in lower reaches

g) Domina it Substratum fype

Figure 2.2: Generalised profile, plan view, and general information regarding the coastal streams of the Illawarra, New South Wales, and their surrounds, a) Stream profile, a.s.l = above sea level (metres), b) generalised plan view of stream course, dotted lines indicate associated level on stream profile c) landform, d) dominant vegetation type, e) dominant landuse, f) stream channel form, and g) stream

substratum.

33 Chapter 2

stream sections retaining some form ofriparian zon e were often overlain by layers of vegetative material, including leaves, twigs, and seeds. Vegetative material is particularly prominent in sections surrounded by River Oaks (Casuarina cunninghamiana), the leaves of which often form substantial layers over the bottom of sites on Reid Park and Marshall Mount Creeks. Sites with cobble substrata were always the most upstream of the three sites sampled on a creek, while sandy sites were the furthest downstream.

At the time of writing, sediment composition and particle size data from hydrological studies of these streams were not available. Several studies are being conducted by the

Geo-Environment-Mine Engineering Research Centre at the University of

Wollongong under the supervision of Associate Professor M.Sivakumar. However, the findings of these studies are yet to be submitted.

The small coastal streams of the Illawarra are geomorphologically distinct from the majority of running water systems. It is generally accepted, and repeatedly observed, by fluvial geomorphologists that river channels increase in size in a downstream direction. However, in contrast, Nanson & Young (1981a) found that for streams in the Illawarra channel size decreases in a downstream direction. They suggest that the decrease in stream power associated with the sudden decrease in channel slope at the base of the escarpment, combined with the cohesive nature of the alluvium that forms the floodplain, are responsible for this phenomena. This situation has since been identified in other stream systems but remains the exception rather than the rule

(G.Nanson pers. comm.).

34 Chapter 2

2.2.2: Climate, rainfall, and stream discharge

The Illawarra region has a moist temperate maritime climate with no marked wet or dry season. Temperatures are mild throughout most of the year. July is generally the coolest month of the year (average minimum 8.2°C, average maximum 16.7°C), with the summer months of January (average minimum 17.9°C, average maximum 25.5°C), and February (average minimum 18.6°C, average maximum 25.5°C) being the warmest (Bureau of Meteorology 1988).

On average, precipitation levels are generally higher in summer (31.1% of total annual rainfall) and autumn (27.4%), than in winter (21.9%), or spring (19.6%).

However, these averages can be highly variable in any one year (Cox 1983). Such variability is apparent at the two rain gauge stations located close to the study streams,

Albion Park (Figure 2.3a) and Dapto (Figure 2.3b). The rain gauge at Dapto is within

100 metres of Robins Creek, the northern most creek sampled here, while the gauge at

Albion Park is half a kilometre from the southern most stream sampled, Marshall

Mount Creek.

Sporadic high rainfall events are responsible for the large standard deviations around the monthly mean in several highly variable months. For example, high rainfall during two cyclonic storm events in August 1998 led to almost 3x the monthly average for

August falling in just 4days, the 8th, 17th, 18th, and 19th of August (Sydney Water - unpublished data). Indeed, the rainfall over these 4 days alone accounted for 46.8% of the total annual rainfall recorded at the Albion Park gauge. These high rainfall events appear to translate to elevated flow levels and high discharge events in the streams sampled in this study. In 1993, 56% of the total annual discharge from Mullet

35 Chapter 2

450 400 - 350 - ^ 300 E •§ 250 To "£ 200 '5 K 150 100 50 a) * 0 m _L 1* & u S3 i S f o * X> ua CfiO ca < o o> u Z a Month

450 i

400 i

350 i

.-. 300 1 •§- 250 200 I I 1 150 1 1

100 I

b) 50 ih 1 •c >> V3 U S3 fe in 3 o c —5 § S & 1 1 •8 < < 1 o u o C/5 O > Q Month o Z Figure 2.3: Mean monthly rainfall for a) Albion Park and, b) Dapto, Illawarra, New

South Wales. Data for Albion Park are for the period 1990 to 1998 and 1990 to 1996 for Dapto. Data was provided by Sydney Water for rainfall gauges 68000 (Albion

Park) and 68022 (Dapto). Error bars are one standard deviation either side of the mean.

36 Chapter 2

Creek was due to a single rainfall event lasting 3-4 days in September (Simeoni et al.

1994).

There is little latitudinal variability yet a marked altitudinal gradient in rainfall in the study area. The relative differences among mean monthly rainfall are very similar for both the Albion Park and Dapto rain gauges (Figure 2.3a & b), suggesting little north south variability in rainfall within the study area. However, a distinct orographic rainfall effect, created by the Illawarra Escarpment, produces a marked rainfall gradient between the top and base of the escarpment. Annual rainfall increases with altitude, with approximately 1600mm falling at the top of the escarpment compared to

1200mm on the coastal plain below (Cox 1983). Runoff from the escarpment slopes, an average of 1100mm per year, is high by Australian standards (Young & Johnson

1977), leading to the area's streams experiencing a relative high frequency of large magnitude flood events for catchments of their size (Nanson & Hean 1985).

Flow patterns in these streams are typical of Australian streams in general. Flow levels in the area's streams are generally low and relatively even for the majority of the year. However, short-term (usually 2-3 days) cyclonic storm events, with associated intense rainfall, particularly those centred on the escarpment slopes, cause flash flooding, dramatically increasing water levels and flow rates in these relatively short, narrow streams. As detailed above, such events may be responsible for the majority of flow variability in these streams and can represent a large percentage of total annual discharge. This pattern of high flow variability with a large percentage of the annual discharge resulting from relatively short-term rainfall events is typical of

Australian running water systems (Lake 1995).

37 Chapter 2

Drought conditions severely reduced water levels in allfive study streams between early summer 1997/98 and early winter 1998. For example, total monthly rainfall recorded at the Albion Park gauge during November and December 1997, and

February and March 1988 was between 3 and 9x lower (Figure 2.4) than the mean monthly rainfall between 1990 and 1998 (Figure 2.3a). While several sites retained shrinking pools of water throughout the drought period (See Chapter 4), a continuous, although low, flow was observed at Robin's Creek Site 1 during the drought. This flow was due to the presence of a spring located upstream of Robin's Creek Site 1 but below Robin's Creek Site 2.

2.2.3: Drying events and definition as intermittent streams

I have defined the study streams as intermittent due to their periodic complete or partial drying. Williams (1988, p412) states that "bodies of water are temporary in the sense that for a predictable part of the year (or perhaps every few years) they dry up".

Temporary streams are the most prevalent type of running water system in Australia due to highly variable rainfall patterns and the large expanses of low relief, arid landscapes (Boulton & Brock 1999). Temporary water bodies range from ephemeral, containing water for only a short time after rainfall episodes, to the seasonal wetlands and rivers of the tropical north that have a distinct wet and dry season every year

(Boulton & Brock 1999). Although they do not dry as regularly or predictably as seasonal wetlands, intermittent streams may dry frequently (Boulton & Brock 1999).

For example, Boulton & Lake (1992a) described both the Werribee River (annual summer drying) and Lerderberg River (dry during one summer in three) as intermittent.

38 Chapter 2

700 650 600 550 500 •g 450 £. 400 | 350 .E 300 (0 DC 250 200 150 100 50 •,, 1-UM=V_J. ,l,n,m,DjJl, 111] ln,rr-.l [• D >. .^ tn co g> co CD D.

0) O 0) CD C XI 3 0> O CD d) C J2 < £ CO OD < g- ° o g CO CD -> u. -3 LL Wu Z Q Year / Month

Figure 2.4: Total monthly rainfall recorded at Albion Park between March 1997 and

February 1999. Data was provided by Sydney Water for rainfall gauge 68000 (Albion

Park).

Available evidence suggests regular summer drying for the streams sampled in this study. Hickey et al. (1994) reported zero discharge from Mullet Creek during

December 1992 and January 1993. Two years later Gregory (unpublished data) was unable to sample at many of the same sites that were sampled in the present study due to these sites being completely dry from mid-September 1994 to early February 1995

(Refer to Appendix B, pre-development sampling, for details). In the summer of

1997/98 drying was even more drastic with water being completely absent from most sites between early summer 1997/98 and early winter 1998 during a severe El Nino induced drought (Refer to Appendix B, post-development sampling, for details).

Limited drying at several sites occurred once again in summer 1999 (Refer to

Appendix B, post-development sampling, for details). Summer rainfall is on average higher than at most other times of year (Figure 2.3a & b). However, the spring months of October and November have rainfall that is on average among the lowest

39 Chapter 2 experienced throughout the year (Figure 2.3a & b), potentially contributing to low summer flows and drying. Admittedly these records of drying are limited to relatively short time span of only eight years. This limitation does not allow assessment of whether over the longer term these streams may fit the definition for permanent streams detailed by Boulton & Brock (1999, table 9.1), that "annual flow > minimum annual loss in 90% of years". Therefore, in the context of definitions detailed above and based on the available, although limited, record of drying events for the five study and the areas streams in general I have considered these streams to be intermittent.

2.2.4: Past and present landuse

The Illawarra region has a long history of human settlement. At least five Aboriginal tribal groups, with an estimated collective population of around 3000 individuals, were present in the region when European settlement began in the early 1800's

(Cumming 1996). Timber cutting, cattle grazing, and coal mining were the main activities conducted by European settlers during the 1800's. Present landuse in the

Illawarra region is a mix of urban and residential development, light and heavy industry, and farming (See Figure 2.2).

Landuse in the catchments of streams sampled in this study is typical of the region in general, a mix of rural, urban and industrial. Of the 1920.4ha catchment of Duck

Creek, 44% is rural, 23.1% urban, 6.1% industrial, 23.6% forested, and the remainder a combination of roads, railways and open space (Forbes Rigby 1999). Mullet Creek, of which Robin's Creek and Reid Park Creek are sub-catchments, has the largest catchment area, 7216ha. Although a larger area of land is devoted to rural use in

Mullet Creek compared to Duck Creek, 2617.5ha compared to 845. lha, this

40 Chapter 2 represents a smaller percentage (36.3%) of Mullet Creeks catchment area. Forests cover 38.0% of Mullet Creek's catchment, mainly in the escarpment slopes and foothills, while urban and industrial land uses account for 11.1% and 4.8% of the catchment respectively (Forbes Rigby 1999). The sub-catchments of the other three sampled streams have a similar mix of landuse types. However, Robin's Creek and

Reid Park Creek are more highly urbanised than the other streams, while the area surrounding Marshall Mount Creek is mostly rural.

2.2.5: Non-invertebrate fauna of the Ulawarra's streams

The streams of the Illawarra are inhabited and utilised by a diverse range of non- invertebrate fauna, including fish, birds, reptiles, and mammals. Twenty-two fish species (21 native, 1 introduced, Gambusia holbrooki), are known to inhabit the areas streams (Gregory - unpublished data). European Carp (Cyprinus carpio) have been observed in some of the areas ponds and farm dams, however, to date they have not been observed in any of the areas streams. Longfinned freshwater eels, Anguilla reinhartii, are the dominant vertebrate predators in these streams, representing by far the greatest biomass of any vertebrate organism in this system (Johnstone - unpublished data).

A variety of reptiles live in or around the regions streams. Several snakes, including the Red-Bellied Black Snake (Pseudechisporphyriacus), and the Eastern Tiger Snake

(Notechis scutatus), feed in and around streams and wetlands in the area. The Eastern

Water Dragon (Physignathus lesueurii) and Eastern Long-Necked Tortoise

{Chelodina longicollis) are common, as they are in many streams and rivers of the

Australian east coast. These reptiles share these areas with, and most likely feed on

41 Chapter 2 some of the regions frogs, including Brown Froglets (Crinia signifera), the Striped

Marsh Frog (Limnodynastes peronii), the Green & Golden Bell Frog (Litoria aurea), and Lesueur's Frog {Litoria lesueuri).

The crepuscular and nocturnal feeding habits of the two mammalian inhabitants of the

Ulawarra's streams, Water-Rats (Hydromys chrysogaster) and Platypus

(Ornithorhynchus anatinus), mean they are rarely observed. However, trapping has indicated that Platypus are present in relatively high densities in some of the regions larger streams such as Macquarie Rivulet (Tom Grant - pers. comm). The remains of large bivalve shells (Hyridella sp.) I have found at particular spots along the banks of several streams suggests the presence of Water Rats (Hydromys chrysogaster).

The streams and coastal wetlands of the Illawarra region are host to a variety of resident and migratory waterbirds. Several egret and heron species (Ardea spp.), cormorants (Phalacrocorax spp.), ibis (Threskionis spp.), ducks such as the Chestnut

Teal (Anas castanea) and Wood Duck (Chenonettajubata), as well as the Purple

Swamphen (Porphyrio porphyrio), the Dusky Moorhen (Gallinula tenebrosa), and the

Azure Kingfisher (Alcedo azurea), utilise these streams and associated habitats on a permanent or transitory basis.

2.2.6: Freshwater invertebrate fauna of the Ulawarra's streams

To date, sampling of the regions stream invertebrate fauna has been minimal.

Kininmonth et al. (1992) sampled the stream invertebrates of American and Byarong

Creeks, lOkm's north of the present study area. However, their sample size was extremely limited and the study was temporally unreplicated. Prior to the present

42 Chapter 2 study, the only intensive sampling of the Ulawarra's stream macrofauna was conducted by University of Wollongong PhD student Michael Gregory. Gregory collected benthic macroinvertebrates over a two-year period, 1993-1995, from the same 15 sites that were sampled in the present study. His work represents the pre- development sampling period of an asymmetrical Beyond-BACI impact assessment design, with the present study representing the post-development sampling. Gregory's data, although at present unpublished, are used here with his consent in Chapters 4, 5, and 6 of this thesis. To date, Gregory's PhD thesis has not been submitted does not have a working title.

Two freshwater decopods, not collected by either Gregory (unpublished data) or

Krninmonth et al. (1992), have distributions that may be limited to the Wollongong area. The freshwater decapod Euastacus keirenis (the Keira Crayfish) has only been collected from swampy habitats around Mount Keira, part of the Illawarra escarpment

(Merrick 1993). The Hairy Crayfish (Euastacus hirsutus) is only found in the forested, rocky sections of streams of the escarpment slopes to the south of

Wollongong and in the upper Shoalhaven River (Merrick 1993).

2.3: Sampling Design and Methodology

2.3.1: Sampling design

I used a hierarchical design to sample benthic macroinvertebrate assemblages from the five study streams (Figure 2.5). Twelve sampling events were conducted per year to give a total of twenty four sampling events over the entire two years of sampling.

During each sampling event three replicate samples were taken at each site, with three

43 Chapter 2 sites visited on each of thefive study streams (Figure 2.5). A total of forty five samples (3 replicates x 3 sites x 5 creeks), were collected during each sampling event.

Three sampling events were conducted in each of four seasons per year, Autumn

(March - May), Winter (June - August), Spring (September - November) and

Summer (December - February). Sampling events were therefore nested within seasons. The date upon which each sampling event was performed was randomly allocated within each season. Too randomly chose dates the days in each season were sequentially numbered (i.e., 1-90 days) and a random numbers table was used to choose three numbers and thus the corresponding dates. A minimum of 7 days between sampling events was observed.

Season(4/year) Autumn Winter Spring Summer

\ Sampling Event(3) A1 2 3

Stream(5) 1J2 3V 4 5

/ \ Site(3) 1 2 3

/ \ Replicate Samples(3) 1 2 3

Figure 2.5: Hierarchical design used to sample benthic macroinvertebrate assemblages from five

streams in the Illawarra, New South Wales. A single sampling event is illustrated. Each of the two

years of sampling, 1997/98 and 1998/99, were conducted using this design. A total of twenty four

sampling events were conducted over the two years of sampling. Samples were taken using a Hess

Sampler that samples a benthic surface area of 0.086m2 with a 700um mesh.

44 Chapter 2

2.3.2: Field Procedure

All fifteen sites were visited and sampled during each sampling event. Each sampling event began at approximately 7am when Site 1 on Robins Creek was sampled. To avoid sediment and other dislodged materials from affecting downstream sites before they were sampled, all creeks were sampled in site number order, moving from Site 1 upstream to Sites 2 and 3 (Figure 2.1). Due to access restrictions on several of the private properties across which these creeks flow, sampling was always conducted in the same creek order during each sampling event, moving from the most northerly creek, Robins Creek, south to Reid Park Creek, Mullet Creek, Duck Creek and then finally Marshall Mount Creek (Figure 2.1). A single sampling event took an average of 6 hours to complete.

A Hess Sampler (Canton & Chadwick 1984) (Plate 2.2 & Plate 2.3) was used to collect three samples per site during each sampling event. Each Hess sample collects benthic organisms, sediment, and associated material from a substratum surface area of 0.086m2 and has a mesh size of 700um. All substrata within the Hess sampler was vigorously disturbed by hand. Any medium to large rocks present within the sampler were removed after surface material on each rock had been dislodged into the water column within the sampler. To standardise the collection of each sample, material floating in the water column after disturbance was moved into the samplers mesh sock, and thus into the sampling jar at the end of this sock (Plate 2.2), with 10 sweeps through the water column with both of the operators hands. Hand sweeps were made both through the middle and around the edges of the sampler to ensure an even coverage of the water column.

45 Chapter 2

To avoid contamination of subsequent samples the initial Hess sample at each site was taken at the downstream edge of the site. A further two samples were taken at each site, each at least one metre upstream of the last sample. All samples were taken in roughly the middle of the stream channel, except were water depth limited sampling. To avoid sample contamination due to inflow of organisms in water entering the top of the sampler, sampling was restricted to water depths of less than

40.6cm, the height of the Hess sampler (Plate 2.2). Each sample was transferred to a

120ml sample jar containing approximately 40ml of 70% ethanol. To minimise the potential for inter-operator sampling error all samples were collected by the author.

Upon completion of each sampling event samples were stored in a freezer to await sorting and identification.

Plate 2.2: Hess Sampler used to collect benthic macrofaunal samples from five coastal streams in the Illawarra region between 1997 and 1999. This Hess Sampler samples a surface area of 0.086m2 and has a 700(im mesh.

46 Chapter 2

Plate 2.3: The author using a Hess Sampler to collect a benthic macrofaunal sample from Site 1 on Robins Creek.

The general physical condition of each site was recorded on each sampling occasion.

Water level, changes in substratum, changes in aquatic vegetation distribution, and any other disturbances or changes to the site and its surrounds were noted.

2.3.3: Sorting and Identification

Organisms were extracted from each sample via a sugar flotation technique

(Anderson 1959) after the sample had been rinsed to remove fine sand and mud.

Sugar flotation separates materials on the basis of their specific densities, heavier materials (rocks, sand), sinking to the bottom of the container, while lighter material

(organisms, twigs, etc), float on or near the surface of the solution. Each sample was placed in a 1mm mesh sieve and thoroughly rinsed with tap water to remove sediment and other fine materials that may have clouded the sugar solution used in the sorting process. A clouded sugar solution inhibited detection of macroinvertebrates. After

47 Chapter 2 rinsing, each sample was placed in a small plastic container (16cm long x 11cm wide x 3.5cm deep) and a sugar solution - 3 kilograms of sugar dissolved in 1200ml water - was poured into the container covering the contents. The solution and contents were then stirred to separate the various materials present in the sample (i.e., organisms, sediment, twigs and other vegetation).

All organisms present in a sample were collected as the container was passed slowly under a dissecting microscope. To ensure that the entire surface of the solution in the container passed under the microscope for inspection I used an overlapping, one row up, one row down, scanning method. After the initial complete inspection, the solution and contents of each container were re-stirred and the inspection process was repeated.

The number of containers I used to sort a single sample (i.e., one sample jar), varied from 1 to 12, depending on the composition of the sediment and other materials present in the sample. The more vegetative material in a sample (i.e., macrophytes, twigs, leaves, and seeds), the greater the number of containers I needed to evenly disperse the contents of each container, ensuring that organisms were not inhibited from floating to the surface. Samples containing sand, pebbles and small rocks that sunk to the bottom of the container could usually be sorted in a single container. The tangle of submerged willow roots that made up samples from Site 1 on Robins Creek required the greatest number of containers, with 9-12 containers often necessary to ensure efficient sorting of a single sample. Regardless of the number of containers required to sort a sample, each container was, as detailed above, inspected twice.

48 Chapter 2

Where identification keys were available I identified collected macrofauna to the lowest taxonomic level in the keys (See Appendix A for list of the keys used). The majority of Coleopteran, Trichopteran, Ephemeropteran, Hemipterans, Odonate, and

Molluscan specimens were identified to species. However, species level identification was not possible for several macrofaunal groups due to a lack of available keys, or a lack of species resolution in many keys. For example, the Oligochaetes, Hirudinae, and Turbellaria were identified to Class, while Ostracods were identified to sub-class.

Time constraints meant that I did not attempt to identify Chironomids beyond sub family, while all other Dipterans were identified to family level. Identifications were conducted using the freshwater invertebrate identification keys produced by the Co operative Research Centre for Freshwater Ecology (Appendix A), and the Aquatic

Invertebrate Voucher Collection held in the Department of Biological Sciences at the

University of Wollongong.

As collected specimens have been identified to a variety of classification levels I differentiate between different specimens or groups of specimens by referring to each specimen or group of specimens as "taxon". Each "taxon" therefore refers to a specimen or group of specimens regardless of the level of classification to which the specimen or group have been identified. For example, the Chironominae, although identified only to sub-family, are referred to as a single taxon, as is the Coleopteran,

Berosus involutus, which was identified to species.

49 Chapter 2

2.4: General characteristics and distribution of the fauna

The following section combines a results and discussion format to describe the distribution in New South Wales, Australia-wide, and globally, of the macroinvertebrate families collected during this study. Global distributions are discussed in terms of the recognised major biogeographical regions of the earth (see chapter 4 in Armitage et al. (1995) - Figure 4.1 for a map of the boundaries of these regions). The term "cosmopolitan" is used here to denote families that are widespread in all biogeographical regions. Distributions within Australia were determined mostly from the distributional information provided in various aquatic macroinvertebrate identification keys (see references in Table 2.2 below). In many cases these distributions are given only as presence in a list of states or broad geographic regions

(for example see Theischinger (2000a), page 2). Therefore, the designation

'widespread - all states" used in Table 2.2 denotes those families listed as occurring in all states. However, this designation cannot be taken to indicate that a particular family is widespread in each state.

Unpublished data collated by the Environmental Protection Authority of New South

Wales is used here to provide information on the distribution of the collected macroinvertebrate families across New South Wales. These data represent sampling at

1138 sites covering all major river types in New South Wales making it by far the most extensive database of macroinvertebrate distributions available in the state.

Samples were collected via a qualitative rapid assessment technique under the

AusRivAS program (Turak & Waddell 2001a). Two habitat types, edges and riffles, were sampled at each site when available. However, riffles are mostly absent from

50 Chapter 2 westward flowing rivers of lowland sites in the Murray Darling Basin (Tural et al.

1997, Turak & Waddell 2001b). The EPA's data is used here with the permission of the custodian of this data set, Eren Turak (EPA, Water Sciences, NSW).

I have divided New South Wales into 4 broad geographic areas (Figure 2.6) on the basis of patterns detected when the sites at which each family were collected were plotted on a map of New South Wales. It should be noted that the analysis of the EPA

(unpublished data) presented here is preliminary in nature. Distributions are presented at a broad spatial scale meant to give a general indication of the distribution of aquatic macroinvertebrate families across the state. More detailed analysis of the distributional patterns detected in this immense data set is beyond the scope of the present study.

In the following section I also discuss the distribution of the taxa I collected across the five streams in my study. Potential biological and ecological explanations for the observed distributions are discussed. In this discussion and throughout subsequent chapters I use the following two-letter abbreviations for site names. Robins Creek =

RC, Reid Park Creek = RP, Mullet Creek = MC, Duck Creek = DC, and Marshall

Mount Creek = MM. Sites are designated as 1, 2, or 3 (refer to Figure 2.1 for the location of sites on each creek). Therefore, for example, site 2 on Duck Creek is denoted as DC2.

51 ChapU

Figure 2.6: Broad geographic zones used to describe generalised distributional patterns of macroinvertebrates families in New South Wales. Zones were determined by preliminary analysis of unpublished data collated by the Environmental Protection

Authority from sampling of 1138 sites across New South Wales between 1994 and

2002. Samples were collected via a qualitative rapid assessment technique under the

AusRivAS program (Turak & Waddell 2001a). Two habitat types, edges and riffles, were sampled at each site when available.

2.4.1: General description of the fauna

I collected a diverse range of benthic macroinvertebrates from the five study streams, most of which were insects (Table 2.1). Over 44362 individual organisms were collected during the two years of sampling. Had the abundance of Oligochaetes been recorded this figure would have been substantially higher. The vast majority of the

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~~(Table 2.1). Furthermore, of the 134 taxa identified here 110 (82.1%) were insects~~

~~(Table 2.1). Macrofaunal stream assemblages the world over are dominated by insects regardless of the habitat type or longitudinal section of stream being sampled (Hynes~~

~~1970). I also collected 24 non-insect taxa including Oligochaetes, Platyhelminthes,~~

~~Huridinae, Crustaceans, Acariformes, and Molluscs. All of these groups are common components of benthic macroinvertebrate assemblages on all continents (Hynes~~

~~1970).~~

The mean number of individuals and the mean number of taxa collected per sampling occasion differed within and among the five study streams (Figure 2.7a & b). The much larger number of macroinvertebrates collected from sites with a cobble substratum (eg. DC2, MC3, MM2, and MM3) were responsible for the marked differences among sites in the mean number of individuals collected in Duck, Mullet, and Marshall Mount Creeks (Figure 2.7a). However, I collected the largest mean number of individuals from RC1, where the substratum is a thick mat of willow roots.

~~By far the lowest numbers of individual macroinvertebrates were collected from Reid~~

Park Creek (Figure 2.7a). Variability around the mean at all sites was substantial, with, in most cases, one standard deviation being larger than the mean or representing a large portion of the mean (Figure 2.7a). Differences among sites and among creeks in the mean number of taxa collected per sampling occasion (Figure 2.7b) were similar to those described above for the number of individuals. However, differences were generally less pronounced than those detected among sites in the number of individuals collected. In several instances, sites that displayed marked differences in

~~57 Chapter 2~~

~~]Site 1 O Site 2 DSite 3 22~~

~~o o 12~~

~~a) Duck Mullet Marshall Mount Robins Reid Park Creek~~

~~400~~

~~350~~

~~300~~

~~cj 250~~

~~y. 150~~

~~50 b) n Duck Mullet Marshall Mount Robins Reid Park Creek~~

~~Figure 2.7: Mean number of benthic macroinvertebrate a) individuals and, b) taxa collected from~~

~~five coastal streams in the Illawarra region of New South Wales from February 1997 to February 1999.~~

~~Each of three sites on each stream was visited on 24 sampling occasions over the two year sampling~~

~~period. Three Hess samples were taken at each site on each sampling occasion. A lack of water due to~~

~~drought conditions between November 1997 and July 1998 restricted or entirely prevented sampling~~

~~during this period at many sites. The means presented are therefore for all sampling events in which 3~~

~~replicate samples were taken at each site. Error bars are standard errors calculated for all samples taken~~

~~at each site over the sampling period (some sites do not have a full compliment of samples (72) due to~~

~~drying). The number of samples taken at each site is detailed in Appendix B.~~

~~58 Chapter 2~~

~~the number of individuals collected showed little difference in the mean number of taxa collected (i.e., D2 & DC3, and RC2 & RC3) (Figure 2.7a & b).~~

~~2.4.2: Global biogeographical distribution of collected families~~

A high proportion of the families collected here have broad geographical distributions, a common finding for benthic macrofaunal assemblages. The majority of the collected families are cosmopolitan (Table 2.2). Moreover, several of the non- cosmopolitan families are widely distributed (Psephenidae, Pleidae, Hydrobiosidae,

Ecnomidae, and Lymnaeidae), being absent from only part of or an entire biogeographical region (Table 2.2). The striking family and even genus level similarity among the macrofaunal communities of all continents is a well recognised feature of stream invertebrate assemblages (Hynes 1970). The macrofaunal assemblages of the Ulawarra's streams are therefore unremarkable at the family level although they do contain several families with restricted distributions.

~~Table 2.2 - Refer to two page fold out section beginning with the following page.~~

~~Several families are limited to landmasses in the southern hemisphere, while a few are~~

~~found only in the Australasian region. Gripopterygidae, Philorhethridae, and Hyriidae~~

~~are restricted to South America, New Zealand, and Australia (Table 2.2). Corixidae~~

~~are found only in New Zealand and Australia and Coenoesucidae in Australia and the~~

~~south-west Pacific, while Isostictidae is a family of Odonata endemic to Australia~~

~~(Table 2.2). Present distributions may not be entirely reflective of the origins of these~~

~~families. For example, fossil evidence suggests a much broader distribution, including~~

~~Europe and Central Asia, for Corixidae (Trueman et al. 1999c).~~

59 ORDER FAMILY Worldwide distribution Distribution in Australia Distribution in NSW Number ot EPA riffle sites Number of EPA edqe sites COLEOPTERA Dytiscidae na widespread - all states28 throuqhout state 180 850 Elmidae na all states but not in Central Aust. or south-west WA1* GDR. EL. scattered in MDB 483 483 Gyrinidae widespread - all states'™ GDR. EL 76 380 Haliplidae na widespread - all states™ EL 0 69 Hydrophilidae cosmopolitan'1 widespread - all states'5 throuqhout state 147 734 Psephenidae cosmopolitan but only in western Palaearctic (Europe)16 mostly eastern Aust.' GDR. EL 323 236 Scirlidae na GDR. EL scattered in MDB 368 231 DIPTERA Ceralopoqonidae widespread - all stales" throuqhout state Chironomidae 226 503 8 Chironominae cosmopolitan widespread - more abudant in north*" throuqhout state 471 970 Orthocladiinae cosmopolitan8 8,1 widespread - more abudant in south-east ' throuqhout state 8 500 733 Tanypodinae cosmopolitan widespread - more abudant in south-east8-" throuqhout state 327 860 Culicidae cosmopolitan8 widespread - all states1" throuqhout state 15 273 Muscidae cosmopolitan9 5 widespread * GDR, EL. very few in MDB 15 19 Psychodidae cosmopolitan8 na GDR. EL, very few in MDB 11 35 Simullidae cosmopolitan8 8 widespread - all states thoughout state - only scattered in W-MDB 480 404 Stratiomyidae cosmopolitan8 widespread - all states8 8 8 Tipulidae cosmopolitan widespread - all states throuqhout state

6 cosmopolitan' widespread - all states throuqhout state Caenidae 8 cosmopolitan' widespread - all states throuqhout state 322 659 Leptophlebidae cosmopolitan' widespread - all states*

HEMIPTERA Corixidae New Zealand & southern Aust." southern Australia11 throughout state 131 cosmopolitan" na few scattered in GDR & EL 4 4 Naucoridae cosmopolitan" na scattered throuqhout state 1 36 Notonectidae cosmopolitan " widespread - all states" throuqhout state Pleidae cosmopolitan except for Alrotropical reqion" widespread - more abundant in tropical north" GDR, EL 2 55 Veliidae 28 cosmopolitan " widespread throuqhout state 125 724

~~18 Pyralidae cosmopolitan widespread - all states'8 GDR, EL, E-MDB 97 156~~

MEGALOPTERA Corydalidae temperate regions but absent from Europe, a lew sp. in tropics'9 eastern states and south-westem WA2 GDR, EL 386 103 Sialidae temperate reqions19 eastern states2 scattered in GDR and EL 8 62

ODONATA Coenaqrionidae cosmopolitan8 widespread - all states9 throuqhout state 19 518 Corduliidae cosmopolitan20 widespread - all states9 GDR. EL, scattered in MDB 65 422 Gomphidae cosmopolitan™ widespread • all states30 GDR. EL, scattered in MDB 244 403 Isostictidae Australia, New Guinea, and New Caledonia'8 eastern states + Northern Territory9 GDR, EL, scattered in MDB 2 117 Ubellulidae cosmopolitan™ widespread - all states9 throuqhout state 10 313 M eqapodaqrion ida e cosmopolitan althouqh rare in Nearctic and Palaearctic29 eastern states & south-westem WA9 GOR, EL, very few scattered in MDB 13 237 Telephlebiidae Oriental, Australia. Nearctic and Palaearctic, Neotropical29 eastern states & south-westem WA29 formerly included in Aeshnidae in EPA samples na na

~~PLECOPTERA Gripopteryqidae Australia, New Zealand, & South America10 Eastern coast. SA, and south-westem WA'0 GDR, EL, and Murrumbidqe River In MDB 427 416~~

TRICHOPTERA Calamoceratidae cosmopolitan" widespread except in south-weslem WA'3 GDR, EL 136 321 Conoesucidae south-western Pacific & Australia13 widespread in east, SA, and Tasmania13 GDR, EL 222 155 Ecnomidae cosmopolitan but not Nearctic19 throuqhout state 205 353 Helicopsychidae cosmopolitan13 GDR. EL 135 127 Hydrobiosidae Nth & Sth America. Oriental & Palaearctic. & Aust." GDR, EL, few scattered in E-MDB 390 166 Hydropsychidae cosmopolitan13 GDR. EL. scattered in E-MDB 488 302 Hydroptilidae GDR, EL + scattered in south-eastern MDB 207 437 Leptoceridae throuqhout state 349 696 Odontoceridae GDR, EL 84 154 Philorheithridae GDR, EL 77 140 GDR. EL 68 70

~~na widespread - all states'~~

MOLLUSCA Hvriidae Sth America, Australia, New Guinea, & New Zealand3,5 All states but onlv in northern Tasmania3,5 very few sites scattered along east coast 2 Lymnaeidae almost cosmopolitan* widespread - all states5 1 133 411 Physidae almost cosmopolitan5 Phvsa acuta - introduced - South-east, SA, Tas. widespread - only scattered in W-MDB Planorbidae cosmopolitan* ia na na Sphaeriidae cosmopolitan5 widespread - but some so. have verv restricted ranqes" combined with in EPA samples with Corbiculidae

~~Oliqochaeta cosmopolitan" widespread - all states27 throuqhout state 214 290 Platyhelminthes na na GDR, EL,+ 1 site in W-MDB Chapter 2~~

~~Table 2.2: Distribution within New South Wales, Australia, and worldwide of the families of macroinvertebrates collected from five coastal streams in the Illawarra,~~

~~New South Wales, between 1997 and 1999. Global distributions are discussed in terms of the recognised major biogeographical regions of the earth (see - chapter 4 in~~

~~Armitage et al. (1995) - Figure 4.1 for a map of the boundaries of these regions). WA~~

~~= Western Australia, SA = South Australia, Qld = Queensland, Vic = Victoria, NSW~~

= New South Wales, Tas = Tasmania. For the purposes of broad distributional patterns detailed here New South Wales is divided into four regions: GDR = western and eastern slopes of the Great Dividing Range, EL = eastern coastal lowlands, W-

~~MDB = western Murray Darling Basin, E-MDB = eastern Murray Darling Basin.~~

Refer to Figure 2.6 for a map of these regions, "na" denotes distributions for which I was unable to locate a reliable or suitable reference. References denoted as numbers in the table are as follows: 1 = Trueman et al. (1999a), 2 = Theischinger (2000a), 3 =

~~Smith (1998), 4 = Trueman & Dimitriadis (1999), 5 = Trueman et al. (1999b), 6 =~~

Surer (1999b), 7 = Campbell (1990), 8 = Colless & McAlpine (1991), 9 = Trueman et al. (1999d), 10 = Trueman et al. (1999e), 11 = Trueman et al. (1999c), 12 = Cranston et al. (1999), 13 = Dean (1999c), 14 = Glaister (1999), 15 = Watts (1998), 16 = Davis

~~(1998), 17 = Miller (1971), 18 = Shaffer et al. (1996), 19 = Williams & Feltmate~~

~~(1992), 20 = Silsby (2001), 21 = Cartwright (1997), 22 = Dean (1997), 23 = Dean~~

~~(1999a), 24 = St Clair (2000), 25 = St Clair (1997), 26 = Cartwright (1998), 27 =~~

~~Pinder & Brinkhurst (1994), 28 = Gooderham & Tsyrlin (2002), 29 = Gunter~~

~~Theischinger - pers. comm., 30 = Theischinger (2000b).~~

~~61 Chapter 2~~

~~2.4.3: Distribution within Australia~~

Most families collected here are widespread in Australian streams, having been collected in all states and territories (Table 2.2). However, many of the taxa I collected are members of families that are found only in the streams of the east, south east, and south-west of the continent (Table 2.2). The Sialidae, Philoreithridae, and

~~Odontoceridae are found along the length of the east coast, while the endemic odonate family Isosticidae is found on the east coast and in the Northern Territory (Table 2.2).~~

~~In addition to their presence in the eastern states, Corydalidae, Megapodagrionidae,~~

Hyriobiosidae, Gripopterygidae, and Conoesucidae are also found in the higher rainfall areas of the south-west of Western Australia (Table 2.2). None of the families collected from the study streams have narrow distributional ranges. All are either widely distributed in the eastern states or are found Australia wide.

~~2.4.4: Distribution in New South Wales~~

~~Preliminary analysis of the EPA's AusRivAS data indicated that at the very least each of the families sampled in this study are distributed along the entire length of eastern~~

New South Wales (Table 2.2, Figure 2.6). Most however are found throughout the state (Table 2.2, Figure 2.6). Several families sampled here, while mostly collected along the Great Dividing Range and the coastal lowlands, were also found at scattered sites in the Murray Darling Basin (i.e., Scirtidae, Simullidae, Corduliidae,

Gomphidae, Physidae, and Planorbidae) (Table 2.2, Figure 2.6). Very few families sampled in this study have limited distributions in the habitats (riffles and edges) sampled by the EPA. One family, Hyriidae (Mollusca), does appear to be restricted to very few sites scattered along the east coast of New South Wales (Table 2.2, Figure

~~2.6). Similarly, this family was not widespread in the study streams with only a few~~

~~62 Chapter 2 individuals being collected from a single site (the distribution of Hyriidae in the study streams is further discussed below).~~

~~2.4.5: Taxa collected in low numbers~~

~~Of the 134 taxa collected during the two years of sampling most were recorded only in low numbers (Figure 2.8). Less than ten individuals were recorded for over half~~

~~(54.5%) of all collected taxa (Figure 2.8). A further 24.6% of taxa were collected in numbers totalling less than 100 individuals over the two years of sampling (Figure~~

2.8, Table 2.1). Such numbers amount to densities of 0.22 individuals or less per metre2 in each creek on each sampling occasion. It is likely that many of these taxa are not regular inhabitants of the mid-channel section of pools in these streams.

The organisms present in a given habitat are classically considered to be those that can reach the habitat (i.e, via dispersal and recruitment) and those for which the physiochemical and biotic parameters of the habitat are within the organism's range of tolerance (Roughgarden & Diamond 1986). However, in running waters diurnal drift and displacement by high flow events may cause macroinvertebrates to use non- optimal habitats as short-term refuges (eg., from visual fish predation in daylight)

(Flecker 1992). Although conditions such as water quality in the refuge habitat may be tolerable the habitat may not be suitable for long-term use (i.e., for reasons such as inadequate or inappropriate food and shelter resources). Some of the taxa that occurred only as single specimens in this study may have been sampled while merely transient between drift episodes. Others are perhaps present in the stream channel due to chance events. Two dipteran families collected here in very low numbers,

~~63 Chapter 2~~

~~45 \ I ,~~

~~40 -|~~

~~35 1~~

~~5 30- P • .~~

~~!25^ o a E | 20 - 15 -~~

~~10 . ,~~

~~5 -~~

0 ' ' 1 1 -J ' 1 1 J 1 . I ,-•,-••; ,3—, 1 <10 11-100 101-1000 1001-10000 10000+ Number of Individuals Collected Figure 2.8: Frequency histogram of the number of benthic macrofaunal taxa collected from five coastal streams in the Illawarra region of New South Wales from February

~~1997 to February 1999. Each of three sites on each stream was visited on 24 sampling occasions over the two year sampling period. Three Hess samples were taken at each site on each sampling occasion.~~

Muscidae and Psychodidae, are more abundant in moist soil and decaying wood in riparian zones than in stream channels (Cranston et .al. 1999). Members of these families are known to end up in stream macroinvertebrate samples after being washed in from these nearby semi-aquatic habitats (Cranston et .al. 1999).

Considering the large number of quantitative samples taken during this study collection in such low numbers clearly indicates that these taxa were not regular members of the macrofaunal assemblages of mid-channel pool habitats in these streams. Rather, for most of these taxa it merely indicates that they were at least part of the macrofauna of the stream in general. It is unlikely, despite their mobility, that these taxa were actually in higher densities and that the sampling technique employed

~~64 Chapter 2~~

~~allowed the bulk of individuals to escape collection. Highly mobile macroinvertebrates were regularly collected in large numbers (i.e., the dytiscid beetle~~

~~Necterosoma penicillatus and atyid shrimp Paratya australiens is). Collection in low numbers may also indicate transience within a pool.~~

Taxa recorded as only one or a few individuals may have distributions concentrated in unsampled microhabitats in these pools. Of the 73 taxa for which less than ten individuals were collected only 3 Trichoptera, Cheumatopsyche sp. AV\,Ecnomia sp., and Plectrocnemia sp., normally build cases or retreats that are fixed to stationary solid objects (Dean 1999c). All other taxa are mobile macroinvertebrates. Even these three Trichopterans are mobile outside of their cases. Marchant et al. (1999) found significant differences in the composition of edge and main channel habitats from sampling of 199 sites in temperate streams across Victoria. Such microhabitat scale differences in macrofaunal composition are commonly identified in stream habitats

(Cooper et al. 1998). Taxa collected in low numbers may be present on an opportunistic basis in the mid-channel section of pools, perhaps moving between more regular microhabitat patches. For example, only three hyriids (Mollusca) were collected in this study from a single site, MM2. Although relatively immobile in comparison to other macroinvertebrates, evidence suggests that hyriids do slowly move across stream bottoms (Smith 1998). Many, large hyriids were observed by the author imbedded in the overhanging banks of this site. This concentration on the stream banks makes it unlikely that hyriids were going to be sampled in high densities in the mid-channel stream habitats sampled in this study. These findings suggest that the macrofauna collected here should be thought of specifically as mid-channel assemblages. Low densities detected for particular taxon in this mid-channel habitat

~~65 Chapter 2 cannot be taken to indicate low densities for that taxon throughout the study streams.~~

~~Microhabitat scale variability in distribution may be responsible for some of the low numbers recorded in this study.~~

Occurrence at low densities may of-course be the normal pattern of distribution for many macroinvertebrates. Samples of ecological communities often contain many taxa that are present only in very low numbers (Cao et al. 1998, Cao & Williams

1999, Marchant 1999) and may be considered rare in the context of the collected samples. This issue is discussed in detail in Chapter 5 and therefore will not be expanded upon here. Naturally low densities are the norm for many large predators

(Sih et al. 1985). Odonates are the largest and most voracious invertebrate predators in many benthic macrofaunal assemblages (Watson et al. 1991). Fewer than ten individuals of six Odonata species were collected, while a total of only 73 individuals of the most abundant odonate, Rhadinosticta simplex, were recorded (Table 2.1).

Therefore, odonate species were present at densities of 0.16 individuals or less per metre2 in each creek on each sampling occasion. Low densities may reflect the ecological role of the macroinvertebrate in question.

~~2.4.6: Relatively abundant taxa~~

Twenty-six of the taxa collected during this study were present in relatively large numbers (Figure 2.8). I use the term "relatively large numbers" here to refer to collection in numbers totalling more than 100 individuals from all five streams over the entire two years of sampling. I chose 100 individuals as a cut of figure as organisms with total abundances larger than this were present at least at a density of one or more individuals per metre2 per sampling occasion (the exact density per

~~66 Chapter 2 metre for 100 individuals in this study being 1.1 individuals per sampling occasion).~~

~~The following discussion refers to these taxa as "relatively abundant".~~

Several discernable patterns are apparent in the distribution of relatively abundant taxa in these streams. All but one of the relatively abundant taxa collected here were present in at least four creeks (Table 2.1). An unidentified mite, Mite 4, was the only relatively abundant taxon that was collected from only a single site, RC1. Indeed, each taxon collected in numbers totalling more than 1000 individuals was present in all five streams. However, each taxon was not collected from all three sites in each creek (Table 2.1). Many taxa were collected in substantially larger numbers from sites with a cobble substratum (Necterosoma penicillatus, Atalophlebia sp., Jappa kutera,

~~Micronecta sp., Pyralid A, Paratya australiensis, Triplectides australicus, Stenosialis australiensis, and the Chironominae). Several other taxa (Berosus involutus,~~

Tasmanocoenis tillyardi, Ecnomus russellius, Glyptophysa gibbosa, and Turbellaria), while most abundant at sites with a cobble substratum, were also collected in large numbers from the willow root mat sampled at RC1. The pisidiid bivalve, Pisidium casertanum, while recorded at its highest densities at RC1 was also abundant at sites with a sand substratum. The structurally complex, silt inundated root mat substratum at RC1 contained a variety of taxa in relatively large numbers. Indeed, the majority of all Scirtid sp. (99.2%), Simullidae (94.2%), Oecetis sp. (67.5%), and Cheumatopsyche sp. (98.8%) recorded during this study were collected from this site.

Several taxa, collected in large numbers from other substrata, were only collected in low numbers from the two types of mud substrata sampled in this study, humic black mud (RC2), and clay (RP1, 2, & 3). For example, Ephemeroptera other than

~~67 Chapter 2~~

~~T.tillyardi (i.e., Atalophlebia sp., Jappa kutera, and Centroptilium sp.), were only recorded as single individuals from sites with mud or clay substrata. Furthermore,~~

~~Necterosoma penicillatus, Turballarians, and the dipteran Chironomidae sub-families~~

Orthocladinae and Ceratopogonidae, were collected in their lowest abundances from these sites. Although the abundance of Oligochaetes was not recorded they were present at all sites, often at substantial densities.

Many of these relatively abundant taxa are commonly collected when sampling the macrofaunal assemblages of Australian streams. For example, members of the molluscan family Planorbidae are regularly the most numerous molluscan family collected from Australian streams (Trueman et al. 1999b). The planorbid,

Glyptophysa gibbosa, was by far the most abundant mollusc collected during this study (Table 2.1). The aytid shrimp, Paratya australiensis, is widespread and commonly collected throughout Australia (Trueman & Dimitriadis 1999). Although collected in substantial numbers during this study, this species may be more numerous in pool edge habitats than in the mid-channel steam habitats sampled here due to its habit of congregating under bank overhangs (Trueman & Dimitriadis 1999).

Similarly, large aggregations along pool edges are commonly observed for the corixid, Micronecta sp., particularly in low flow and backwater areas of eastern flowing rivers and in the slower western flowing rivers of New South Wales (Eren

~~Turak pers. comm.). Although collected in relatively substantial numbers, mid- channel habitats are again unlikely to be the most densely populated habitats for this species.~~

~~68 Chapter 2~~

Members of dipteran family Chironomidae were by far the most numerous organisms collected during this study (Table 2.1), accounting for 30.7% of all collected individuals. The Chironomidae are an abundant and conspicuous part of macrofaunal communities worldwide (Hynes 1970) and are often the most numerous organisms collected from macrofaunal assemblages across Australia (Williams 1980). The

Chironominae were by far the most numerous of the three Chironomid sub-families collected from these streams (Table 2.1). Indeed, the Chironominae were the most numerous taxa collected during this study (Table 2.1), accounting for 28.1% of all individuals I collected.

~~The Chironominae were most abundant at sites at which there was a potential for organic enrichment. The highest densities of Chironominae were recorded at RC3~~

(Table 2.1). This site has a fairly uniform coarse, sandy substratum and is relatively shallow with a depth ranging from 10 to 25cm. It is also a cow crossing that is used on a regular basis. Ruminated vegetation was always present in samples taken from this site. The other three sites at which members of the Chironominae were highly abundant, DC2, MC3, and MM3, are all unshaded sites with cobble substrata. Dairy pastures that are constantly used for grazing either by cows or, in the case of DC2, by cows and horses, surround each of these sites. I have observed cows crossing the stream channel at most of these sites and the potential for organic enrichment in the form of manure seems high. Del Rosario et al. (2002) documented chironomid densities that increased by 5x after treating sites on three upland Californian streams for four weeks with cow manure. Importantly however, they did not find any change in the genera of chironomids present after treatment and no one taxon became relatively more abundant than prior to treatment (Del Rosario et al. 2002). These

69 Chapter 2 findings suggest that a simple numerical response to enrichment (i.e., an increase in number but not in the type of chironomids present) may be a general characteristic of chironomid assemblages. Therefore, a higher density of chironomids, particularly the

~~Chironominae, at sites in these streams with likely organic enrichment is not unexpected.~~

~~Leptophlebiid mayflies were the most numerous and species rich mayfly family collected in this study. Seven of the nine mayfly species collected were leptophlebiids~~

~~(Table 2.1). Atalophlebia sp. was by far the most numerous leptophlebiid (90.3% of all individual leptophlebiids), the most numerous Ephemeroptera, and accounted for~~

~~11.1% of all individual macroinvertebrates collected during the study (Table 2.1).~~

Jappa kutera, another leptophlebiid, was also collected in substantial numbers. The collection of large numbers of leptophlebiids here is not particularly surprising given that leptophlebiids dominate the mayfly fauna of Australian streams (Campbell 1990).

~~Moreover, the prominence of ephemeropterans in general in the assemblages of the~~

~~Ulawarra's streams is also unsurprising given that they are particularly numerous in~~

~~Australian macrofaunal assemblages (Growns & Davis 1991, Hogg & Norris 1991).~~

The caenid mayfly, Tasmanocoenis tillyardi, was another Ephemeroptera collected in large numbers (Table 2.1). Suter et al. (2002) found that in Queensland T.tillyardi inhabits sites with roughly equal mean percentages of sand and cobble substrata.

~~Similarly, in the present study T.tillyardi was numerous at both cobbled and sandy sites (Table 2.1). However, T.tillyardi was also fairly numerous at RC1 (Table 2.1).~~

~~This site has a substratum composed of a thick mat of willow roots that trap large amounts of fine silt. Caenids have a gill structure that protects against their gills~~

~~70 Chapter 2 becoming clogged with fine sediment (Needham et al. 1935), and are commonly found in silt inundated stony habitats in streams across Australia (Peters & Campbell~~

1991). Interestingly, T.tillyardi was the only mayfly collected in any number from the mud and clay sites of Robins and Reid Park Creeks. The humic black mud substrata of RC2, and the clay substrata of sites on Reid Park Creek do not appear to be suitable habit for most mayflies. Other than T.tillyardi., only single individuals of

Centroptilium sp. (RP2), Atalophlebia sp. (RC2 & RP3), and Jappa kutera (RP3), and no other mayflies were collected from these sites. These findings further suggest that the gill structure adaptations of T.tillyardi may allow this species to exploit depositional areas of fine, silty sediment in these streams that are unsuitable for other mayflies.

~~Other relatively abundant mayflies collected in this study, such as the baetid~~

~~Centroptilium sp., are also characteristic of depositional environments (Dean & Suter~~

~~1996, Suter 1999b). In Queensland Suter et al. (2002) collected Centroptilium spp. at~~

~~16 sites that on average had a mostly sandy substratum. In this study Centroptilium sp. was most numerous at two depositional sites, RC1 and MC2. However, here,~~

~~Centroptilium sp. was collected in larger numbers from a site of silt deposition (RC1) than at MC2, a site of sand deposition. In contrast, the abundant leptophlebiids~~

Atalophlebia sp., and Jappa kutera, were markedly more abundant at sites with cobble substrata such as MC3, MM2, and MM3. Interestingly, all five Ephemeroptera species collected in low numbers were only collected from two sites with cobble substrata on

~~Marshall Mount Creek (Table 2.1).~~

~~71 Chapter 2~~

The submerged root-mats sampled at RC1 may represent a unique microhabitat. This particular substratum type is not representative of the substratum types that are prevalent in these streams - sand, cobble, clay and mud. Therefore, RC1 presented an interesting contrast to the other sites sampled in these streams. A greater diversity and number of macrofauna were collected from this site than from any other site I sampled (Figure 2.1). Furthermore, as detailed above, many taxa were collected in large numbers from this site, with the majority of all individual Scirtidae sp.,

~~Simuliidae, Oecetis sp., and Cheumatopsyche sp. being collected from RC1.~~

Interestingly, these findings demonstrate that a habitat created by an introduced species (Salix sp.) supports a more diverse and abundant macrofauna than the more prevalent and perhaps normal substrata present in these streams. Indeed, Wood &

~~Sites (2002) recently demonstrated similar findings for root-mats they sampled in~~

~~Ozark, USA, suggesting that root-mats may represent hot spots of macrofaunal diversity and abundance.~~

~~Mayfly species were associated with particular types of substrate in these streams.~~

~~Adaptations that allow an organism to inhabit a specific type of substratum are common among aquatic insects in general (Hynes 1970, Merritt & Cummins 1984).~~

However, rather than displaying an association with one particular substratum type, the four most abundant mayfly species collected here, Atalophlebia sp., Centroptilium sp., T.tillyardi, and Jappa kutera, were all collected in substantial numbers from at least two or more types of substratum. Clearly, despite displaying strong associatiions with particular habitats, these species are adapted to surviving in a variety of the mid- channel habitat types sampled in these streams. As Hynes (1970) notes, the most

~~72 Chapter 2 broadly adapted species are often the ones found in the greatest number in stream systems.~~

The leptocerid caddisfly, Triplectides australicus, is another relatively abundant taxon that, although clearly adapted to a number of the sampled habitat types, displayed a clear association for the conditions at one particular site. The majority of T.australicus

~~(70.8%) were collected from MM2. This site had a cobble substratum and was well shaded by large River Oaks (Casuarina cunninghamiana). Almost all of the~~

T. australicus individuals collected from this site were housed in casings constructed from Casuarina leaves. However, it does not appear that the presence of Casuarina leaves alone is responsible for the densities recorded at MM2. T. australicus was present at much lower densities in all other substrata types sampled in these streams.

~~At most of these sites sand and mixed leave material were used for case construction.~~

~~Casuarina leaves were available from surrounding River Oaks at RP1 & RP3 and were used for casing material by the T australicus collected from these sites.~~

However, the number of T. australicus collected were 16 times lower at RP3 and 22 times lower at RP1 than at MM2 (Table 2.1). Moreover, other cobbled sites, each of which was unshaded and did not have adjacent River Oaks, had much lower densities of T.australicus than were detected at MM2. These findings and those detailed above for other taxa suggest that many of the relatively abundant taxa collected from these streams are broadly adapted to many of the mid-channel habitat types sampled here.

However, despite these broad adaptations, distinct habitat associations can be discerned for many of these taxa. Clearly, the sampled pools vary in the type or amount of resources available to each of the sampled taxon.

~~73 Chapter 2~~

~~The description and preliminaryfindings detailed above suggest potential differences within and among streams in the type and number of macrofauna I sampled.~~

~~Furthermore, they suggest that substrata heterogeneity may be influencing these~~

~~potential differences. These findings suggest a number of hypotheses regarding spatial~~

~~variability in the composition of these assemblages. I move on to test these~~

~~hypotheses in the next chapter.~~

~~74 Chapter 3~~

~~Chapter 3 - Spatial variability in the composition of benthic macrofaunal assemblages in three coastal streams of the~~

~~Illawarra~~

~~75 Chapter 3~~

~~3.1: Introduction~~

Patchy faunal distributions are a well recognised feature of macrofaunal stream assemblages yet have been poorly studied at small spatial scales in Australia (Downes et al. 1993, 1995, Palmer et al. 1997). Those studies that do exist suggest highly variable distributions even at small, local spatial scales (Barmuta 1989, Downes et al.

1993, Marchant et al. 1999, Downes et al. 2000). Marchant et al. (1999) found that the spatial proximity of sites they sampled in Victoria was not necessarily an indication of the degree of taxonomic similarity between the sampled assemblages.

~~Sampling at local spatial scales among riffle habitats by Downes et al. (1993), also in~~

Victoria, suggests that highly variable macrofaunal distributions may be evident not only among but also within similar habitats. Furthermore, Downes et al. (1993) demonstrated that while the composition of one taxonomically related group of macrofauna (i.e., an insect order), may vary over a particular spatial scale, others may not. With the exception of Barmuta (1989), pool habitats in Australia have not previously been sampled at the local spatial scales sampled in the present study.

My preliminary findings in Chapter 2 suggest the potential for differences both within and among the study streams. For each of the study streams I found substantially different mean numbers of taxa and the mean numbers of individuals at each site. The markedly higher number and diversity of macrofaunal organisms collected from cobble bottomed site suggests that substrata heterogeneity may be influencing these differences. Furthermore, many of the most abundant taxa collected during the study had uneven distributions, with a large proportion of individuals being collected from only one or two streams.

~~76 Chapter 3~~

~~In this chapter I describe and test for spatial variability in the benthic macrofaunal assemblages of pool habitats in three temperate coastal streams of the Illawarra, New~~

~~South Wales. I used only the three control streams, Mullet, Duck, and Marshall~~

Mount Creeks to avoid the potential confounding effect of the putative impact of the housing development at sites on Robin's Creek and Reid Park Creek. I use Analysis of similarities (Clarke 1993, Clarke & Warwick 1994) to test the hypotheses that there will be greater variability among than within sites on individual streams and among than within streams. I also test these hypotheses for each of five taxonomically related macrofauna groups, four orders of the Insecta - the Coleoptera, Ephemeroptera,

Trichoptera, and the Diptera - and a single non-insect group, the Mollusca. Each of these groups contributed substantially to both the number of taxa, and the number of individuals collected from these streams. I also use analysis of similarities to determine whether the compositional differences among substrate types suggested in chapter 2 were statistically significant. Furthermore, I use a non-parametric multivariate analysis of variance, NP-Manova, (Anderson 1999) to partition variance within and among streams.

~~In Chapter 4 I describe changes taking place over time in these same assemblages~~

(temporal variability). Separating the description and testing of these two sources of variability is not meant to imply that they are separate issues. Clearly, changes to ecological communities occur simultaneously in both a spatial and temporal dimension (Palmer et al. 1997). However, for the sake of clarity and brevity I have described each potential source of variability separately.

~~77 Chapter 3~~

~~3.2: Methods~~

~~In the following discussion I detail the reasoning behind the descriptions given, the analyses performed, and the level of taxonomic resolution used in Chapters 3, 4, and~~

6.1 detail these issues here rather than in the Methods sections of each chapter individually for two reasons. First, the logic behind the decisions I made on these issues is relevant to each of these chapters and is therefore more concisely described in one place. Furthermore, options for the format of data that could be used in the analyses performed in Chapter 6 were restricted due to limitations in Gregory's pre- development data set (described below). These limitations influenced my decisions on the level of taxonomic resolution used not only in Chapter 6, but in Chapters 3 and 4 as well and are therefore best placed in context before the analyses performed in these earlier chapters are presented. I also detail why I have separated the description and testing of hypotheses regarding spatial and temporal variability for the control streams

~~(Chapters 3 and 4), and the two streams on which potentially impacted sites are located (Chapter 6).~~

~~3.2.1: Level of taxonomic resolution used in Chapters 3,4, and 6~~

In the following discussion I refer to analyses being performed at genera level. The majority of the macroinvertebrates collected in this study were included in analyses at this level. Genus was the lowest level of resolution appropriate for these analyses for several reasons that are detailed below. However, I also included several taxa in these analyses at higher taxonomic levels as it was impractical to identify these taxa beyond relatively coarse levels of taxonomic resolution. Therefore it should be noted that data used in Chapters 3, 4, and 6, while mostly at the level of genus, included members of three dipteran sub-families, the Oligochaetes, Turbellarians, and the Hirudinea at the

~~78 Chapter 3 class level, the Acarina at the level of order, and the Ostracoda at the subclass level.~~

~~To avoid awkward wording I refer to these data, which includes mostly genera and a few taxa at lower levels of resolution, simply as the genus level of resolution.~~

Genus level resolution allowed the most consistent approach to the analyses and interpretations presented in Chapters 3, 4, and 6. Constraints on the level of taxonomic resolution used in Chapter 6 meant that genus level tests were the most appropriate level of resolution available. Comparisons between Gregory's unpublished pre-development data and the present study were only possible for the most abundant genera collected during both studies. I was not able to directly compare all macrofauna to Gregory's pre-development voucher specimens due to the incomplete or poor condition of some of the specimens. Fortunately, all of the 25 problematic taxa were only collected in low numbers in both studies and could therefore be classified as rare (i.e., representing less than 0.5% of all individuals collected over the combined four years of sampling). Rare taxa have been shown to be redundant information in comparisons of community structure via descriptive multivariate techniques such as ordination (Marchant 1999), and in this system when using multivariate hypothesis testing techniques such as analysis of similarities (See

Chapter 5). Therefore, in Chapter 6 I eliminate all rare taxa from each data set leaving only the 20 most abundant or 'core' genera. These genera are then used for the univariate and multivariate assessment of impact.

In Chapters 3 and 4 I also perform all multivariate analyses (ordinations, ANOSIM, and NP-Manova) using data at the level of genus. The data used in these two chapters differs from that used in Chapter 6 in that these data include all genera and not just the

~~20 most abundant core genera. One of the purposes of the analyses performed in~~

~~79 Chapter 3~~

Chapters 3 and 4 is to set the scene for the impact assessment in Chapter 6 by describing background variability in the macrofaunal assemblages of the control streams. I used the same level of taxonomic resolution in all three chapters to ensure a consistent approach to the analyses performed and to ensure the interpretations derived from these analyses were comparable across all three chapters.

Lowering the level of taxonomic resolution did not substantially alter the outcomes and interpretations gained from the analyses performed in these chapters. A number of studies have demonstrated that lowering the level of taxonomic resolution may have little if any affect on the outcome of univariate (Ferraro & Cole 1992, Wright et al. 1995), or multivariate statistical analyses (Wright et al. 1995, Bowman & Bailey

1997, Olsgard et al. 1998, Pik et al. 1999). However, I could not assume that this would be the case for the data set being analysed in this study. Therefore, to test the effect of lowering the level of taxonomic resolution used here I conducted all 178 analysis of similarity tests for spatial variability performed in this chapter using data at two levels of resolution. The first included each taxon at the lowest level to which it was identified in this study (i.e., at the levels listed in Table 2.1). I will refer here to this as the All Taxa level of resolution. The analyses were also performed with data at the level of genus. For only three of the tests on quantitative data and nine of the tests on binary data was the result of the test at the All Taxa level (i.e., a significant difference or no significant difference) changed when the test was performed at the genus level (See Table 3.1). I did not consider these changes to be substantial as they did not at all alter the interpretations regarding spatial variability gained from these analyses.

~~80 Chapter 3~~

It should be noted that although I present the results for the All Taxa tests in Table 3.1 this was meant only to allow comparison to the genus level tests. I do not interpret or refer to these results elsewhere in this or any other chapter. Rather, these results are presented only as a test of the assumption detailed above.

~~3.2.2: Separation of analyses for control and putatively impacted streams in~~

~~Chapters 3, 4, and 6~~

I analysis and describe spatial and temporal variability in the sampled assemblages separately for the three control streams (Chapters 3 and 4) and the two creeks on which putatively impacted sites were located, Robins and Reid Park Creeks (Chapter

6). My reasons for this separation are two-fold. Firstly, it is against changes in the composition of the macrofauna of control streams that changes in the composition of putatively impacted sites will be judged and an impact detected if one has occurred.

Tests for spatial and temporal variability would be confounded by the presence of a potential impact were they to included Robins and Reid Park Creeks. Therefore, to ensure an unconfounded description of the background variability in the macrofauna of this system I treat the three control and two putatively impacted streams separately.

The present study also represents an important test of hypotheses regarding spatial and temporal variability in the composition of benthic macrofaunal assemblages at a fine, local spatial scale. For the purpose of these tests I am interested in assessing what may be termed natural spatial and temporal changes in assemblage structure in this system. Only the three control streams were appropriate for this purpose as they did not contain a potential impact that is not present across all three streams. I do not contend that the control streams were "pristine" or that they were not potentially

81 Chapter 3 influenced by a variety of human activities in the surrounding area. However, the potential influences on all three control streams were relatively similar and they lack the obvious, localised potential impacts represented by the construction activities adjacent to Robins and Reid Park Creeks.

~~3.2.3: Tests for spatial variability in Chapter 3~~

I used analysis of similarity (ANOSIM) to test the hypothesis that there would be greater variability in macrofaunal composition (the type and number of individual organisms) a) among than within sites and b) among than within creeks. I tested both of these hypotheses for each sampling occasion at the level of genus and for all sampling occasions collectively at the level of genus and family. In all tests 4th root transformed quantitative data and presence or absence data at the genus or family level was used. The null hypothesis of equal variability among sites or creeks was tested at alpha = 0.05. Where pooling was necessary (i.e., for tests on all sampling occasions collectively), I used site centroids (multivariate averages) of the 3 replicates taken at each site in each sampling event. A Bray-Curtis similarity index was used for all quantitative data and a Sorensen's coefficient was used for binary data.

~~I also tested these same hypotheses for each of five major taxonomic groups, the~~

~~Coleoptera, Ephemeroptera, Trichoptera, Diptera, and the Mollusca. Tests for the~~

Coleoptera, Ephemeroptera, Trichoptera, and Mollusca were performed on 4th root transformed quantitative data and presence or absence data at the level of genus. Tests were conducted at the family level for the Diptera as genus level identifications were not attempted in this study for this order.

~~82 Chapter 3~~

~~Analysis of Similarity (ANOSIM) is a useful andflexible multivariat e technique with which to test hypotheses regarding differences among ecological samples (Clarke~~

~~1993). ANOSIM uses a non-parametric permutation procedure to test for differences among a priori defined spatially or temporally separated assemblages (Clarke 1993,~~

Clarke & Warwick 1994). Importantly, ANOSIM can be performed with quantitative compositional data, i.e., the number and type of taxa present, or binary data, the presence or absence of taxa. This overcomes the limitation of univariate tests for differences detailed in Chapter 1 by accounting for differences in the type of taxa present and/or, how the relative abundance of taxa changes over time or spatially.

Moreover, ANOSIM can be conducted within and among the various levels of replication in a data set, with all collected fauna or on sub-sets of the data, such as individual taxonomically related groups (i.e., insect orders) (Clarke 1993, Clarke &

~~Warwick 1994).~~

A variety of transformations and similarity measures can be used in analysis of similarities tests depending on the nature of the data collected and the type of analysis required (Clarke & Warwick 1994, Marchant 1999). In the ANOSIM tests performed here I transformed all data by 4th root prior to analysis and used a Bray-Curtis similarity measure to generate matrices of similarities among samples. Clarke &

Warwick (1994) recommend this transformation/similarity measure combination to alleviate the potential bias a few highly abundant taxa may have on some similarity measures and subsequently the resulting tests for differences. Importantly for ecological data, the Bray-Curtis measure does not assign any weight to joint absences

~~(i.e, a taxon missing from both groups) in determining the matrices of similarities among groups of samples (Clarke & Warwick 1994).~~

~~83 Chapter 3~~

~~3.2.4: Core and rare taxa in Chapter 3~~

In Chapter 2 I distinguished between taxa that were collected in low numbers and those that were "relatively abundant". Clearly, this distinction was somewhat arbitrary and meant only to facilitate the descriptions undertaken in Chapter 2. However, in this chapter (Chapter 3) I use a precise definition to divide the macroinvertebrates collected in this study into two groups based on the total number of individuals collected over the entire two years of sampling. I defined "core taxa" as those taxa collected in numbers that represented more than 0.5% of the total number of individuals collected over the entire two years of sampling. Those taxa collected in numbers that amounted to less than 0.5% of the total number of individuals collected I defined as rare. Although most of the taxa defined as relatively abundant in Chapter 2 were collected in some number from all streams each of these taxa were not present at all sites on each sampling occasion. To determine the relative mix of core and rare taxa present in these assemblages at any one time I calculated the mean number of core and rare taxa collected per sampling occasion for each site. I further discuss the analytical implications of separating the samples of macrofaunal assemblages into core and rare taxa groups in Chapter 5.

~~3.2.5: Tests among substrate groups in the control streams in Chapter 3~~

~~The general description of the distribution of macrofauna in these streams in Chapter~~

2 suggested differences in the type and number of macroinvertebrates among the various types of substrata sampled in this study. The mean number of taxa and the mean number of individual macroinvertebrates collected differed markedly among sites. For Mullet, Duck, and Marshall Mount Creeks greater substratum heterogeneity in the form of cobbles was the most obvious physical feature distinguishing sites with

84 Chapter 3 high mean numbers of taxa and individuals from other sites. Moreover, many taxa were recorded in their highest abundances at cobble sites. These findings suggest that substratum heterogeneity may be influencing the composition of these macrofaunal assemblages. If substratum type has a strong influence on the structure of macrofaunal assemblages in this system I would expect sites with the same type of substratum to have similar macrofaunal assemblages, regardless of the creek on which they were located. Therefore, a test for differences between assemblages collected from the same type of substratum should indicate less difference between these assemblages than between the assemblages collected from different types of substratum.

I used Analysis of Similarity to test for differences among the two main substratum types present in these three streams, sand and cobbles. I tested for differences between the macrofaunal composition of sandy sites and cobbled sites, between sandy sites and other sandy sites, and between cobble sites and other cobble sites, regardless of the creek upon which sites were located. To determine whether differences between sand-sand and cobble-cobble comparisons were larger or smaller than each other I required a relative measure of difference that could be compared between these two groups. The Global R-value generated by ANOSIM provides such a measure (Clarke

& Warwick 1994). For example, if a test for differences between sites A and B generates an R-value close to +1, and a test between sites C and D an R-value closer to zero (zero equals absolutely no difference), then there is a greater degree of difference between the compositions of A and B than there is between C and D

~~(Clarke & Warwick 1994). I predicted that same substratum comparisons (i.e., sand- sand or cobble-cobble) would yield R-values closer to zero than comparisons between~~

~~85 Chapter 3 different substrates (i.e., cobble-sand). Data were 4th root transformed and a Bray-~~

~~Curtis similarity measure was used for all tests.~~

~~3.2.6: Partitioning of variability among the control streams in Chapter 3~~

To partition variability among the two spatial levels sampled in the three control streams, within streams and among streams, I used a non-parametric multivariate analysis of variance, NP-Manova (Anderson 2001). Although analysis of similarities can be used to test for differences in two-factor nested or crossed (orthogonal) designs, it does not provide a measure of how variability is partitioned among levels in such a design (Clarke 1993). NP-Manova is the multivariate analogue of the widely utilised univariate Analysis of Variance. NP-Manova uses permutations to test hypotheses regarding multivariate data in factorial designs and partitions variability among the levels in such design (Anderson 1999, Anderson 2001). It is currently restricted to analysis of factorial or nested designs with two levels (Anderson 1999).

By partitioning the total amount of variability measured in a factorial sampling design, the portion of total variability due to variation among levels, and the portion due to variation within each level can be determined (Sokal & Rohlf 1995).

I used a two-way nested design, with the factor Sites (3 levels) nested within the factor Creeks (also 3 levels). Nine sampling events were removed from the analysis due to missing data (see discussion below). Site centroids (multivariate averages) were used for each of the 15 remaining sampling events for which data was sufficient to be analysed. I used permutations on the full model as recommended by Anderson

~~(1999) for tests with a relatively low number of nested levels (i.e., there are only three levels of Factor 2 nested within Factor 1 in this analyses).~~

~~86 Chapter 3~~

Low or non-existent water levels caused inadequate sample replication at most sites between November 1997 and June 1998. Reduced water levels due to drought conditions during this period meant that all three samples could not be taken at all sites during many sampling events, while at other times no samples were taken at all at many sites (See Appendix B). Therefore, I did not include data from sampling events conducted during summer 1997/98 or autumn 1998 in either the ANOSIM or

~~NP-Manova tests performed in this chapter.~~

~~3.3: Results~~

~~3.3.1: The macrofaunal assemblages of Duck Creek~~

I detected differences in both the type and number of macroinvertebrates collected from the sites sampled on Duck Creek. On average, I collected around 3 times more individuals from the cobble substratum of DC2 than from the sandy substratum of

DC1 or from DC3, where the mixed substratum of course sand and pebbles contains many macrophytes (Figure 2.7). Many of the macroinvertebrates I collected were present at all three sites, with differences only apparent in their relative abundances between sites. For example, Necterosoma, Berosus, Tasmanocoenis, and the

Chironominae were substantially more abundant at DC2 (Table 2.1). I also detected marked differences in the type of Coleoptera and Mollusca present at the three sites on Duck Creek. Three of the six molluscan genera I collected from Duck Creek were only present at a single site. Interestingly, while 17 genera of Coleoptera were collected from DC3,1 only collected five at DC1, and four at DC2. Not surprisingly analysis of similarities revealed significant differences among sites in the relative abundance of genera and families and in the presence or absence of genera and

~~87 I Chapter 3~~

~~families (Table 3.1(a)). I also detected significant differences among sites in the~~

~~relative abundance and the presence or absence of coleopteran and molluscan genera~~

~~(Table 3.1(b)). Differences in the relative abundance of trichopteran genera and~~

~~dipteran families were responsible for the among site differences I detected for these~~

~~orders as there was no significant difference among sites in the presence or absence of~~

~~trichopteran genera or dipteran families (Table 3.1(b)). For the Diptera these~~

~~differences were overwhelming due to the large number of the Chironomidae~~

~~collected at DC2 (more than 3 times the number collected at DC3 and ten times more~~

~~than at DC1). There was no significant difference among sites in the relative~~

~~abundance or presence or absence of ephemeropteran genera (Table 3.1(b)).~~

~~3.3.2: The macrofaunal assemblages of Mullet Creek~~

~~My findings for Mullet Creek are in many respects similar to those for Duck Creek.~~

~~On average, I collected around 2.5 times more individuals from the cobble substratum~~

~~of MC3 than from the sandy substratum of MCI and MC2 (Figure 2.7). Berosus,~~

~~Tasmanocoenis, and the Chironominae were once again substantially more abundant~~

~~in the cobbles at MC3 than at the other two sandy sites (Table 2.1). Jappa,~~

~~Micronecta, Hellyethira, and the aytid shrimp Paratya australiensis were also~~

~~markedly more abundant at this site (Table 2.1). Thirty of the 68 macroinvertebrate~~

~~taxa I collected from Mullet Creek over the entire two years of sampling were only~~

~~recorded at one site (Table 2.1). All of the insect orders and non-insect groups~~

~~detected in these streams were represented among these thirty taxa. Unlike my~~

~~findings in Duck Creek, where the coleopteran fauna differed markedly among sites,~~

~~no one order or group displayed particularly strong differences in the type of taxa~~

~~collected in Mullet Creek.~~

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Once again it is not surprisingly that analysis of similarities revealed significant differences among the sites on this creek in the relative abundance of genera and families and in the presence or absence of genera and families (Table 3.1(a)). I also detected significant differences among sites in the relative abundance and the presence or absence of coleopteran and trichopteran genera (Table 3.1(b)). Presence or absence differences for both of these orders were mainly due to the low number of genera that were common to all three sites (three out of 13 coleopteran genera and five out of 12 trichopteran genera). Moreover, there were marked differences in the relative abundance of several of these common taxa (Necterosoma, Berosus for the

~~Coleoptera, and Hellyethira and Oesetis for the Trichoptera). Unlike my findings for~~

~~Duck Creek I did not detect significant differences among sites on Mullet Creek in the relative abundance or the presence or absence of Molluscan genera (Table 3.1(b)).~~

However, similar to my findings for Duck Creek, I detected no significant difference among sites in the relative abundance or the presence or absence of Ephemeroteran genera or in the presence or absence of dipteran families (Table 3.1(b)). Once again, the significant differences I detected in the relative abundance of dipteran families

~~(Table 3.1(b)) were overwhelming due to the much larger number of the~~

~~Chironomidae collected at the one site with a cobble substratum, MC3.~~

~~3.3.3: The macrofaunal assemblages of Marshall Mount Creek~~

The presence of larger numbers of macroinvertebrate taxa and individuals at sites with a cobble substratum was once again evident in the most southerly of the three control streams, Marshall Mount Creek (Figure 2.7). However, two sites with a cobble substratum (MM2 and MM3) were present on this creek rather than just the single cobbled site sampled on the other two control streams. Differences among sites were

~~93 Chapter 3 more complex than the relatively obvious differences between cobbled and sandy sites detailed for Duck Creek and Mullet Creek.~~

Most of the taxa I collected from Marshall Mount Creek were only present at one or two sites, while those taxa that I did collect at all three sites displayed marked differences in their relative abundances. Of the 87 taxa collected from this creek 35 were only collected from a single site, while 19 others were collected from two sites.

~~Many of the taxa described as "relatively abundant" in Chapter 2 were present at all three of the sites on Marshall Mount Creek. Berosus, Ceratopogonidae,~~

~~Chironominae. Tasmanocoenis, Micronecta, Pyralidae, Stenosialis, Hellyethira,~~

Hirudinea, and Glyptophysa were all most abundant at MM3. This site had a cobble substratum and was situated in cleared diary pasture that had no riparian zone. In contrast, MM2, although again a cobbled site, was very well shaded by large River

Oaks and other native and introduced trees in a five metre wide riparian zone. I collected more Necterosoma, Atalophlebia, Jappa, and Paratya australiensis at this site than at MM1 or MM3. The leptophlibid mayfly, Triplectides australicus, was far more abundant at MM2 than at the other two sites on this creek. Interestingly, I did not collect any Odonates from the sandy substratum at MM1 although a range of

~~Odonates were collected from sites with a sandy substratum on Duck Creek and~~

~~Mullet Creek. The pisidiid clam, Pisidium casertanum, was the only macroinvertebrate that was notably more abundant at MM1 than at other sites on~~

~~Marshall Mount Creek.~~

~~Once again it is not surprising that these differences among sites in relative abundances and in the type of macroinvertebrates present were statistically~~

94 Chapter 3 significant. Analysis of similarities revealed significant differences among sites in the in the relative abundance of genera and families and in the presence or absence of genera and families (Table 3.1(a)). While I detected no significant difference among sites in the relative abundance and the presence or absence of coleopteran or molluscan genera, I did detected significant differences for both of these measures for the Trichoptera (Table 3.1(b)). Nine of the 13 genera of Trichoptera collected from this stream were only present at one or two sites, while differences in the relative abundance of those present at all three sites were apparent, particularly for

Triplectides australicus. I detected no significant difference among sites in the presence or absence of ephemeroteran genera or in the presence or absence of dipteran families (Table 3.1(b)). Differences in the relative abundance of

~~Ephemeroteran genera were due to differences in the number of Jappa,~~

Tasmanocoenis, and particularly Atalophlebia collected at each site. Similar to my findings for Duck Creek and Mullet Creek, I detected large difference in the number of Chironomidae collected at each site on Marshall Mount Creek. Once again, it was these differences that were mostly responsible for the significant differences among sites in the relative abundance of dipteran families that I detected via analysis of similarities (Table 3.1(b)). Surprisingly, I collected relatively low numbers of

Chironomidae from the cobble substratum of MM2. This finding is surprising not only because fewer Chironomidae were collected at this site than from the sand substratum of MM1 but also as the number of Chironomidae collected was many times less than the number collected at other cobbled sites of Duck Creek and Mullet

~~Creek.~~

~~95 Chapter 3~~

~~3.3.4: Among site differences for each sampling occasion~~

For the majority of sampling events conducted during this study I detected significant differences among sites in the relative abundance of genera and in the presence or absence of genera (Table 3.1(c)). However, for each of the control streams there were no differences among sites in either of these measures on at least one or two sampling occasions. At other times (i.e., other sampling occasions), differences among sites were only apparent in relative abundance of genera as the sites did not differ significantly in the presence or absence of genera. On only one occasion, the first sampling event in spring 1997, was there no significant difference among sites in either the relative abundance or presence or absence of genera for all three creeks.

~~3.3.5: Core and rare taxa in the control streams~~

~~At any one time the macrofaunal assemblages sampled from Duck, Mullet, and~~

~~Marshall Mount Creeks consisted of a base of core taxa, repeatedly sampled in relatively large numbers, and a few taxa that were only ever present in low numbers~~

(Figure 3.1). Of the 122 taxa collected from these three streams over the two years of sampling 22 were defined as core taxa. These 22 taxa accounted for 95.4% of all individual macroinvertebrates collected from these creeks during this study. Their presence in at least some number in each creek gives the initial impression that these

22 taxa were always present in the assemblages I sampled. However, this is not the case. At any one time each assemblage consisted of an average of between 7 and 11 core taxa (Figure 3.1a), and between 2 and 5 rare taxa (Figure 3. lb). The assemblages sampled on Marshall Mount Creek displayed slightly higher mean numbers of both core and rare taxa than Mullet or Duck Creeks (Figure 3.1 a & b).

~~96 Chapter 3~~

~~TJ a 12 y o 10 CO co 8~~

~~2 6 CD a I 4 Z a)~~

~~Mullet Duck Marshall Mount~~

~~EJSite 1 • Site 2 • Site 3~~

~~16 14 •a 3 £ O 10 co x „ co 8 I 4 3~~

~~b) Mullet Marshall Mount~~

~~Figure 3.1: Mean number of a) rare and, b) core taxa collected per sampling event from sites on Mullet, Duck and Marshall Mount Creeks between February 1997 and February 1999.~~

Core taxa were those that contributed to more than 0.5% of the total number of individual macrofaunal organisms collected. Each site was visited 24 times over the two-year sampling period and three Hess samples were taken during each visit. Lack of water due to drought conditions between November 1997 and June/ July 1998 restricted, or prevented sampling altogether during this period at many sites. Means are therefore for all sampling events in which 3 replicate samples were taken at a site. Error bars were calculated as one standard deviation either side of the mean of the total number of core or rare taxa collected per sampling event.

~~97 Chapter 3~~

~~3.3.6: Within and among creek similarity in the composition of macrofaunal assemblages~~

I found that sites were more similar in taxonomic composition to other sites on the same creek than they were to sites on other creeks. Percent similarities (i.e., the percentage of the total number of taxa collected that were present at both sites) were always higher between sites situated on the same creek than between sites situated on different creeks. Between site similarities ranged from 37.0% to 51.9% for sites located on the same creek, but were lower, ranging from 20.8% to 34.5%, when sites were compared to sites on other creeks. Moreover, non-parametric multivariate analysis of variance revealed that within creek variation (10.1% of total variance) contributed less to the total variability measured across the three sampled streams than among creek variation (25.9%) (Table 3.2).

~~3.3.7: Differences among streams~~

The macrofaunal assemblages of Marshall Mount Creek were more taxonomically diverse and abundant than those of Mullet or Duck Creeks. The greatest number of individual organisms (13634) and the greatest number of taxa (89) were collected from Marshall Mount Creek. Although more individual organisms were collected from Mullet Creek (10365), compared to Duck Creek (6846), these came from a smaller number of taxa (66) than were present in Duck Creek (73). The mean number of taxa collected per site in each sampling event ranged between 9 and 16 (Figure 2.1a

~~& b), with sites on Marshall Mount Creek displaying slightly higher mean values than sites on either Mullet Creek or Duck Creek.~~

~~98 Chapter 3~~

~~Source of Degrees of Sum of Mean F P Variation Freedom Squares Squares Creek 2 74895.8599 37447.9300 7.7052 <0.0002~~

~~Site(creek) 6 29160.6296 4860.1049 3.3109 O.0002~~

~~Residual 126 184957.5217 1467.9168~~

~~Total 134 289014.0112 Table 3.2: Non-parametric multivariate analysis of variance results for permutation of~~

~~residuals under the full model for a 2 factor, nested design. Sites (3 levels) were~~

~~nested within creeks (3 levels). Data were the type and number of individuals~~

~~collected at the level of genera for 15 sampling events conducted between 1997 and~~

~~1999 from Duck, Mullet, and Marshall Mount Creeks in the Illawarra, New South~~

~~Wales. A fourth-root transformation was used on the data prior to calculation of Bray-~~

~~Curtis dissimilarities. 4999 permutations were performed.~~

~~Each core taxon was detected in each stream. However, for many of these taxa the~~

~~majority of individuals were collected from a single stream. I found that most of the~~

~~Pyralidae (93.5% of all Pyralidae collected), Hirudinae (76.3%), Atalophlebia sp.~~

~~(96.1%), Centroptilium sp. (69.7%), Triplectides sp. (87.3%), Stenosialis sp. (79.1%),~~

~~and Paratya australiensis (70.0%), were collected from Marshall Mount Creek. The~~

~~bulk of Tasmanociesis tillyardi (78.5%) and Ecnomus russellius (66.2%) were~~

~~collected from Mullet Creek, while the Orthocladinae (63.8%) were mostly collected~~

~~from Duck Creek. The remaining core taxa were either relatively evenly spread~~

~~among the three creeks (i.e., Pisidium casertaum, the Chironominae, Tanypodinae,~~

~~and Ceratopogonidae), or were present in two of the creeks in relatively even numbers~~

~~and only in low numbers in the third creek (i.e., Jappa kutera, Micronecta sp., and~~

~~Glyptophysa gibbosa).~~

~~99 Chapter 3~~

Analysis of Similarity revealed differences among creeks over most of the two years of sampling. I detected significant differences among creeks in the relative abundance and the presence or absence of both genera and families over the entire two years of sampling (Table 3.1(d)). However, differences among creeks were not apparent throughout the entire sampling period (Table 3.1(f)). Tests for differences among creeks conducted for each sampling event revealed significant differences during most but not all sampling events. I detected no significant differences among creeks in the relative abundance or the presence or absence of genera during the second sampling event conducted in either winter or spring 1998 (Table 3.1(f)). On another occasion, the first sampling event during spring 1998, significant differences among creeks were due to differences in the relative abundance of genera, but not in the type of genera present (Table 3.1(f)).

Major taxonomic groups tended to reflect the differences found among creeks for all taxa (Table 3.1(e)). I detected significant differences among creeks in the relative abundance and the presence or absence of Coleopteran, Ephemeropteran,

Trichopteran, and Molluscan genera (Table 3.1(e)). However, while I detected significant differences among creeks in relative abundance of Dipteran families, I detected no significant differences in the presence or absence of Dipteran families

(Table 3.1(e)). Therefore, at the largest spatial scale sampled here, among creeks, I detected the same pattern of variability among creeks in all macrofauna as I did for several major taxonomic groups. This was not the case at the smaller, within creek scale, where major taxonomic groups varied among sites in a number of ways, not all of which reflected the variability among sites evident when all macrofauna were tested together.

~~100 Chapter 3~~

~~3.3.8: Substrate Comparisons~~

My expectation that sites with the same type of substratum would have similar compositions at the genera level, regardless of the creek on which sites were located, was not met. Sandy sites were on average more similar to each other than they were to cobbles sites (i.e., the mean R-value was closer to zero) (Table 3.3). However, cobble sites exhibited a greater relative difference to other cobble sites (i.e., a mean R-value closer to 1), than either sand-sand or sand-cobble comparisons (Table 3.3).

~~Comparison~~

~~Test Result Sand/Cobble Sand/Sand Cobble/Cobble~~

~~Global R-value 0.629 ± 0.237 0.542 ± 0.245 0.775 ±0.171~~

~~P-value 0.011 ±0.045 0.060 ±0.127 0.0 ± 0.0~~

~~Table 3.3: Mean Global R and P-values for Analysis of Similarity comparisons between different substrate and same substrate combinations for nine sites on three streams in the~~

~~Illawarra, New South Wales. Data were genera of benthic macrofauna collected from nine sampling events conducted between March and November 1997 at three sites on each of~~

~~Mullet, Duck, and Marshall Mount Creeks. Centroids of three Hess samples per site per sampling event were used. Errors are one standard deviation from the mean.~~

~~Therefore, while the expectation of similar substrata having similar macrofaunal compositions was met for sandy substrata, it was not met for cobble substrata.~~

~~101 Chapter 3~~

~~3.4: Discussion~~

The findings of this study represent an important demonstration of significant heterogeneity in the composition of macrofaunal assemblages among pool habitats at local spatial scales in Australian streams. I detected significant variability at both of the spatial scales sampled, among sites within individual streams and among streams.

Spatial variability among macrofaunal assemblages is not unexpected, having been well documented in stream systems worldwide (Palmer et al. 1997). However, the present study is the first to document highly heterogeneous macrofaunal distributions in pool habitats at such a fine spatial scale in Australia. The findings of this study, add to those of Downes et al. (1993) and (Marchant et al. 1999), and further suggest highly variable macrofaunal distributions within and among similar habitats at relatively fine, local spatial scales in Australian streams. Clearly, much remains to be documented regarding the distribution of macrofauna at small spatial scales in

Australian streams. Just as we would be cautious of unjustifiably scaling up the findings of a sampling program to broader spatial scales (i.e., generalising about regional patterns from the sampling of a single stream) we should also avoid scaling down our findings by assuming that the distributional patterns derived from broad scale sampling are applicable at smaller spatial scales (Levin 1992, Downes et al.

~~1993).~~

The findings of this study also caution against assuming that the patterns detected at the community level are applicable to all constituents of the community. Interestingly, the complex pattern of spatial variability displayed by the Coleoptera, Trichoptera,

~~102 Chapter 3~~

Ephemeroptera, Diptera, and Mollusca at thefinest spatia l scale sampled, within creeks, was not evident at the among creeks scale. At the relatively coarse among creeks scale, significant variability was apparent for both the whole assemblage and for each of these major taxonomic groups when they were tested individually. This was not the case among sites within individual creeks. Each of these groups displayed individual patterns of variability among sites, patterns that differed from creek to creek, and that did not necessarily reflect the significant differences detected among sites for the whole assemblage. These findings suggest that variability in the distribution of these five major taxonomic groups was scale dependent in this system.

~~It is important to recognise that community level tests for variability may mask complex patterns of variation in sub-components of the overall data set.~~

Furthermore, these findings suggest that we can not assume that all elements of a community show similar patterns of spatial variability, or that these patterns are the same irrespective of the scale at which sampling is conducted. Recognition of the scale dependence of both patterns and processes is an important focus in the study of ecological systems (Levin 1986, 1992, Cooper et al. 1998, Underwood & Chapman

1998). It may be equally as important to recognise that even within a particular spatial scale elements of the community may be responding to the same processes in different ways, or each group may be responding to completely different influences from other groups. Here such testing determined that some insect orders display distributional patterns that are scale dependent in this system. However, these findings have a limitation in that using subsets of the data set in the same tests means they are not independent. While recognising this limitation I felt it important to test the same spatial hypotheses for prominent components of the data set to provide a more

~~103 Chapter 3 rigorous and accurate description of distributional patterns than would have been gained by testing for community level patterns alone.~~

Despite the high variability exhibited by these assemblages I detected a basic structure common to all of the sampled assemblages. Each assemblage contained a base of seven to eleven core taxa, which accounted for the vast majority of individuals I collected. A further two to five rare taxa, which were only ever collected in relatively low numbers, were also collected from each assemblage during any one sampling occasion. Numerical dominance by a relatively small number of the collected taxa is a pattern that has been repeatedly documented for the macrofaunal assemblages of

~~Australian streams (Brooks & Boulton 1991, Growns & Davies 1991, Downes et al.~~

~~1993, Marchant 1999, Marchant et al. 1999). Indeed, we may expect to find such a structure when sampling any ecological community (Gauch 1982).~~

Many of the core taxa collected from these streams displayed preferences for particular habitats. Moreover, the findings of this study also suggest that some of these taxa have more general habitat requirements than others. Each core taxon was collected in at least some number from all of the sampled sites. Clearly, this finding suggests that all of the sampled sites were inhabitable to some extent by each core taxon. However, the distribution of many core taxa varied substantially among creeks and within creeks, with many being markedly more numerous at cobble bottomed sites. These findings suggest varying degrees of preference for particular habitats, with the strongest preference displayed by those taxa collected mostly from cobbled sites on a single stream. For example, in Chapter 2 I noted that the majority of the leptocerid trichopteran, Triplectides australicus, were collected from the cobbled

104 Chapter 3 bottomed MM2. Furthermore, I suggested that the higher densities of T. australicus at this site might have been due to several factors, one of which was the availability of casuarina leaves used as casing material by most of the T. australicus collected from this site. Obviously, there are many other habitat features that may be responsible for the higher density of T. australicus at this site. Similarly, I detected a markedly more diverse Coleopteran fauna at DC3 than at any other sampled site. The most obvious difference between this site and others was the presence of a relatively dense stand of macrophytes along the edges of the site. Many of the coleopterans collected from

~~DC3 are herbivorous (i.e., the Hydrophilidae and larval Haliplidae) or potentially may feed on epiphytic algae on the surface of macrophytes (i.e., Psephenidae and adult~~

~~Haliplidae) (Gooderham & Tsyrlin 2002). However, the presence of macrophytes alone does not account for the range of predatory Dytiscidae collected from this site.~~

Furthermore, those taxa whose numbers were relatively evenly distributed among creeks were the most general in their habitat requirements, able to utilise all of the various habitat types sampled to a similar degree. Without measuring a wide range of relevant physiochemical and biological habitat variables I can only suggest that the sampled pools provide both general and in some instances specific habitat requirements for the sampled macrofauna. It is beyond the scope of the data collected in this study to determine which particular habitat features were responsible for these preferences.

Differences among the assemblages of sites with similar substrata also suggest preferences for particular habitats. In Chapter 2 my preliminary findings suggested that substratum type may be an important influence on the type of macrofaunal assemblage present at a site. Clearly, there were significant differences among the

~~105 Chapter 3 assemblages of cobble and sandy substrata. These differences were mostly due to the more diverse and numerous macrofauna collected from cobbled sites. Marchant et al.~~

~~(1985) documented similar differences among sand and cobble substrata in the La~~

Trobe River in Victoria. However, while my expectation that similar substrata would have similar macrofaunal compositions was met for sandy substrata, it was not met for cobble substrata. These findings suggest that sandy substrata in this system represent a fairly specific type of habitat, with a relatively specialised fauna able to exploit this habitat. Furthermore, these findings suggest that the cobble substrata sampled in these streams represent a broader range of habitat types and subsequently support a more varied macrofauna. This is perhaps unsurprising given the relatively homogeneous nature of the sandy sites and the greater variability in the physical structure of the cobbled sites. While most sandy sites had a similar course sand substratum, the size, shape and texture of cobbles varied among sites. Even relatively minor differences in the structure and texture of cobbles may affect the diversity and abundance of macrofauna (Downes et al. 1998).

Compositional differences among macrofaunal assemblages both within and among these three streams were temporally dynamic. Significant differences among sites or among creeks were apparent during most but not all sampling occasions. Moreover, partitioning of the total variance measured among these assemblages indicated that the bulk of variance (64.0%) was not due to spatial variability at either the within or among creeks scale. Variability in any ecological community involves a temporal as well as a spatial aspect (Stewart-Oaten et al. 1995, Stewart-Oaten & Bence 2001). At least some of the unaccounted for residual variability measure here may be due to temporal changes the composition of these assemblages. Although, we are really only

106 Chapter 3 beginning to document patterns of spatial variability in macrofaunal stream assemblages in Australia, study of the temporal changes in these assemblages is even more rudimentary. The replication of sampling at several temporal scales in this study provided an excellent opportunity to document not only how these assemblages change over time, but also, how they respond to irregular climatic disturbances such as flooding and drying. I will consider temporal changes in the assemblages I sampled in the next chapter.

~~107 Chapter 4 - Temporal variability in the benthic macrofaunal assemblages of three temperate coastal streams in the Illawarra~~

~~108 Chapter 4~~

~~4.1: Introduction~~

~~The composition of an ecological community varies from one location to another~~

~~(spatially), and over time (temporally) (Stewart-Oaten et al. 1995, Palmer et al. 1997).~~

~~Accurate description of any ecological community requires that both of these potential sources of variability be quantified (Boulton & Lake 1992a, Underwood~~

1994). In Chapter 3 I detailed significant spatial heterogeneity among the assemblages of three temperate coastal streams. Interestingly, this heterogeneity was temporally dynamic, with differences in macrofaunal composition among sites and among creeks detected during most but not all of the two years of sampling. Moreover, partitioning of the total variability measured during this period indicated that the majority of measured variation was not due to spatial differences among sites or creeks.

~~Therefore, to fully describe these assemblages requires quantification of how they change over time, within and among the various temporally replicated periods in the sampling design.~~

Macrofaunal variability occurring over the course of a study has often been incorrectly described as seasonal. Many researchers appear to presume little variability in macrofaunal composition within the temporal periods they are sampling.

~~Several studies have concluded that fauna vary among seasons yet have not sampled during all seasons nor replicated sampling within each season (Jacobsen & Encalada~~

1998, Feijoo et al. 1999, Linke et al. 1999). Without adequate replication within each temporal period, such conclusions may be confounded by unqualified within period variability (Underwood 1994a, 1994b). Given the high degree of variability exhibited by benthic macrofaunal assemblages, two samples taken in the same season might be

109 Chapter 4 expected to be just as different from one another as samples taken in two different seasons (Palmer et al. 1997). If seasons do represent temporal periods that are relevant to the changes in macrofaunal composition taking place over a year, each season should have a distinct macrofauna, a macrofauna that is statistically different from that collected in other seasons.

Even where differences among seasons do exist this may not of itself be conclusive evidence of seasonal variability in macrofaunal composition. If differences exist among other temporal periods over a year then seasonal differences may be merely a reflection of general temporal variability in the system. If fluctuations in macrofaunal distribution are cyclical then seasons may show a similar composition from one year to another. To adequately test these possibilities sampling must be temporally replicated, with randomly timed samples taken in each temporal period (i.e., within each season). In this way, meaningful, unconfounded conclusions can be drawn about the time scale over which faunal composition fluctuates (Boulton & Lake 1992a,

~~1992b, Underwood 1994).~~

~~Extreme climatic fluctuations severely disrupted sampling during this study.~~

However, the resulting floods and a prolonged dry spell presented an excellent opportunity to describe the affect of such events on the benthic macrofauna of temperate coastal streams. I have used a number of quantitative and qualitative techniques to describe how these events affected the diversity and abundance of macrofauna in this system. Unfortunately, in a number of instances testing for statistically significant differences between pre and post-drought or pre and post-flood periods was not biologically logical. For example, the two flood events that occurred

~~110 Chapter 4 in August 1997 took place shortly after flow had returned in two streams - Mullet and~~

Marshall Mount Creeks - and before flow returned in Duck Creek. Therefore, I could not expect the assemblages of these streams to have recovered to normal densities and diversity in the period between when the dry spell ended and the first flood occurred.

Tests for statistically significant differences among pre and post-flood samples, although computationally possible, were not ecologically justifiable. However, even phenomenological accounts of such events are important (Townsend 1989), and can greatly enhance our understanding of the response of stream macrofauna to irregularly timed climate driven disturbance events (Boulton & Lake 1992a).

In this chapter I also describe and quantify how the assemblages of the three control streams have changed over the course of the study. The hierarchical nature of the sampling design employed in this study provided the opportunity to a) characterise the background fluctuations in the composition of the control streams, against which impacts at putatively impacted sites, if any have occurred, will be measured, c) test hypotheses regarding whether the temporal randomisation periods used here, seasons, are relevant periods over which to characterise the temporal changes taking place in these streams, and d) describe the effect of irregularly timed natural disturbance events (a prolonged drought and 2 floods), on the macrofaunal composition of these assemblages. I also describe long-term changes in the composition of the assemblages

~~I sampled by comparing the findings of this study to the unpublished results of~~

Gregory who sampled the same sites between 1993 and 1995. Gregory's sampling represents the pre-development or "before" sampling in the overall Beyond-BACI impact assessment design used to sample these assemblages.

~~ill Chapter 4~~

~~4.2: Methods~~

~~4.2.1: Long-term changes in assemblage composition~~

To detect long-term changes in the composition of the assemblages I sampled in the three control streams I used data from both the present study and Gregory's study of the same creeks conducted between 1993 and 1995. Gregory's samples were collected and processed using the same sampling and sorting methodologies that I used in this study. To date, Gregory's work remains unpublished but is used here with his permission.

I used non-parametric multivariate analysis of variance (Anderson 2001) to test the null hypothesis that there would be no difference in the composition of the sampled assemblages between the two studies. I used two-way nested NP-Manovas to compare each stream individually and all three streams combined. Sampling events (Factor 2) were randomly timed and nested within each study (Factor 1). A forth-root transformation was used on raw data prior to analysis and a Bray-Curtis similarity measure was used to determine the level of similarity among samples. This transformation/similarity measure combination was also used for all analysis of similarity tests, non-metric multi-dimensional scaling, and SIMPER analyses that I used to describe differences among the studies.

As previously detailed in Chapter 3, to ensure comparability between the two data sets only the 20 most abundant genera were included in analyses between pre and post- development data sets. Again, although being referred to here as "core genera" this

~~112 Chapter 4 group includes 16 genera, 3 sub-families of the Chironomidae, and one class, the~~

~~Oligochaeta.~~

~~4.2.2: Seasonal variability in assemblage composition~~

I used analysis of similarity to test the null hypothesis that there would be no difference in the core genera collected among the four seasons in a year. I included data from all 4 years in which these creeks were sampled, two years by Gregory

(unpublished data) and two years of sampling during the present study. Sampling events were conducted on three random dates within each season. To determine whether there were differences among other temporal periods over the course of a year I reallocated the data for one creek, Marshall Mount Creek, and one site,

Marshall Mount Creek Site 3, into six, four and two month temporal periods and tested for differences among these periods. Sampling events were therefore considered randomly timed within these new temporal periods. However, the timing of several sampling events meant that reallocation into four and two month periods was not possible for some years, and tests for these periods were not conducted.

I also used Analysis of Similarity to test the null hypothesis that there would be no difference in macrofaunal composition among the same season in each of the four sampling years. For example, I tested for differences among the macrofauna collected in summer 93-94, summer 94-95, summer 97-98 and summer 98-99. Tests were conducted for each of the three streams separately and for each site individually. Data used for these tests were the relative abundance and presence or absence of core genera. I used core genera to allow comparison of seasonal variability in the present study and Gregory's (unpublished data) earlier study.

~~113 Chapter 4~~

~~4.2.3: The effect of flow cessation and drying on assemblage composition~~

~~I used an Index of Multivariate Dispersion and non-Metric Multidimensional Scaling~~

(nMDS) ordination plots, to compare variability in macrofaunal composition among sampling events taken before and after a severe drying event. This El Nino induced drying event occurred between summer 1997/98 and late autumn, early winter 1998.1 describe and test for the effect of this drying event using only data from the present study. I used site centroids of the genera collected in each sampling event at each site.

~~All data were 4th root transformed and a Bray-Curtis similarity measure was used. Ten random starts were used for each nMDS ordination.~~

The Index of Multivariate Dispersion, proposed by Warwick & Clarke (1993), can be used to quantify how variability among samples differs from one site to another, or from one time period to another. This index utilises the dissimilarity matrices to gain an average rank dissimilarity among samples from each site or temporal grouping.

Importantly, these dissimilarities are re-ranked to include only dissimilarities among samples for each site or time group individually, eliminating the between group dissimilarities that would normally be part of the dissimilarity matrix. The average rank dissimilarities therefore provide a measure of how much variability exists among samples within each group. A statistic (the IMD), comparing the average rank dissimilarities between the two groups, can then be calculated (See Warwick &

Clarke 1993, p223). The IMD can have a value of between -1 and +1, with zero indicating that all dissimilarities are the same in each group and there is no difference in the variability among samples in the two groups. A positive IMD indicates greater dissimilarities, and therefore greater variability, in the treatment group relative to the control group, while a negative IMD indicates the reverse. Somerfield & Clarke

~~114 Chapter 4~~

~~(1997) have extended these calculations to allow comparisons among more than two groups.~~

~~4.2.4: The effect of flood events on assemblage composition~~

Two flood events occurred in winter 1998, a minor flood on the 10th of August 1998 and a second, more prolonged flood event lasting three days which began one week later. The second of these was a major flood event. I use the term "flood" here to denote large, short-term increases in water volume and flow velocity. Although hydrological records are not available for these stream (against which a more exact definition of flood could be made) flooding is relatively easy to detect in these streams due to their narrow channels, shallowness, normally low, steady base flows, and the flashy nature of discharge increases which are commonly associated with sporadic, intense rainfall events. Indeed, almost a third (31.4%) of the total annual rainfall recorded for Albion Park fell in the three days in which the second, major flood event occurred in August 1998. Evidence I observed along the banks and riparian zones of the study streams immediately after the flooding indicated that water levels had risen by up to two and a half metres during the flood. Water flow had only just returned to Marshall Mount Creek and Mullet Creek in the weeks prior to the first flood event in early August 1998. In Duck Creek, rainwater had collected in several sections of the creek channel, however, there was no connected flow until after the first flood event.

The occurrence of these floods immediately following the initial return of water after a dry spell lasting seven to eight months complicated attempts to assess their impact on the macrofauna of these three streams. I did not attempt to statistically test for the

115 Chapter 4 effect of these floods due to a lack of pre-flood data that were unaffected by the drought. Therefore, I have described the effect of these flood events on the macrofaunal assemblages of these streams in qualitative terms.

~~I used Analysis of Similarity, an Index of Multivariate Dispersion, and non-Metric~~

~~Multidimensional Scaling (nMDS) ordination plots to compare the macrofaunal assemblages present at MC3 before and after a large flood event in August 1998.~~

~~Prior to this flood, medium sized, irregularly shaped cobbles covered the bottom of~~

MC3. When floodwaters receded, these cobbles were no longer present, having been replaced by a uniform, course sand across the entire site. An increased water depth, and the presence of large numbers of cobbles in the field surrounding the site, confirmed that the sand had not merely covered the cobbles.

~~4.3: Results~~

~~4.3.1: Overview~~

The benthic macrofaunal assemblages of these streams exhibited considerable variability over both long and short temporal periods. Their composition differed among seasons, among years, and between this study and Gregory's study of the same sites between 1993 and 1995. Seasons were not the only within year temporal periods over which these assemblages exhibited variability. Significant differences in assemblage composition were evident among various reassigned long and short-term temporal periods within each year. Therefore, seasonal differences were merely a reflection of the generally high temporal variability experienced by these assemblages over the course of a year. Irregularly timed climatic events were also associated with

~~116 Chapter 4 changes to the composition of these assemblages. A change in assemblage composition towards one dominated by air-breathing taxa such as dytiscid~~

~~Coleopterans closely followed the gradual cessation of flow during a prolonged dry spell. Entire assemblages were eliminated when several sites dried up completely.~~

~~Two flood events that occurred immediately following the return of water to these streams decreased macrofaunal densities across all three streams.~~

Macrofaunal numbers peaked at much the same time in each creek, with a similar group of taxa responsible for each peak. All of the nine sites sampled exhibited peaks in the number of individuals collected in spring 1998 and/or summer 1998/99 (Figure

~~4.1). At most sites these peaks were due either to large increases in the number of~~

~~Chironominae. or, to increases in the Chironominae and one or two other taxa - i.e.,~~

~~Tasmanocoenis tillyardi in Mullet Creek, and Atalophlebia and Glyptophysa in~~

Marshall Mount Creek. In 1997 peaks occurred at two main times, winter and late spring/early summer. However, several sites (MC2, MC3, DC1, and MM1), exhibited either a winter 1997 or spring/summer 1997/98 peak, but not both (Figure 4.1).

~~4.3.2: The effect of flow cessation and drying on assemblage composition~~

The gradual reduction, and eventual cessation of flow, had a remarkably similar effect on the macrofaunal assemblages present in the three streams I sampled. I found that most core taxa were absent from samples taken after flow ceased in early 1998

(Figure 4.1). Moreover, most taxa were absent from the ponds that formed at each site as water levels receded in late 1997, only to reappear in samples when flow returned in May 1998 (Figure 4.1). Three taxa - Berosus involutus, Glyptophysa gibbosa, and the Chironominae - were numerically dominant at all sites in the shrinking ponds that

~~117 Chapter 4~~

~~7-20"1 August~~

Minor flood- 10,n 600 August 650 - -Nectrosoma •o -Berosus • 500 u Atalophlebia • 450 -Jappa o -Centroptilium U 400 -Tasmanocoeni CO • 350 -Triplectides -Cheumatopsyche •3n > 300 - -Hellyethira •D 250 Ecnomus E Micronecta 0 200 Stenosialis Orthocladinae 150 - Chironominae F Tanypodinae = 100 z Ceralopogonidae 50 -Paratya b)) 0 - Glyptophysa Pisidium

~~550 500 450 400 350 300 250 200~~

~~150~~

~~Month / Year~~

~~118 Chapter 4~~

~~250~~

~~200~~

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~~119 Chapter 4~~

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~~Figure 4.1: The total number of each of 19 core taxa collected from three sites on Mullet Creek,~~

~~Duck Creek, and Marshall Mount Creek between 1997 and 1999. a) MCI, b) MC2, c) MC3, d) DC1, e)~~

~~DC2, f) DC3, and g) MM1, h) MM2, i) MM3. The timing of drying and flooding events are indicated on graph a.~~

~~120 Chapter 4 formed in early summer 1997/98. Numerical dominance by these three taxa continued at all sites where at least some water remained throughout the drought period.~~

~~However, many of the core taxa that were completely absent from Marshall Mount~~

~~Creek and Duck Creek were collected in low numbers from Mullet Creek, which experienced patchy flow on several occasions during the drought period.~~

Many core taxa, several of which were often among the most abundant taxa collected at many sites, were absent from samples taken after flow ceased. These included three dipteran sub-families (Figure 4.2(i, h, and g)), three ephemeropteran genera (Figure

4.2(e, f, and d)), three trichopteran genera (Figure 4.2(b, j, and k)), and a single hemipteran genus (Figure 4.2(1)). These taxa remained absent for the rest of the dry spell in the receding pools that formed at sites on Marshall Mount Creek. However, low numbers of several of these taxa, most notably the Orthocladinae, Tanypodinae,

Ceratopogonidae (Figure 4.2(g, h, and i)), and Micronecta sp. (Figure 4.2(1)), were collected from Mullet Creek during the intermittent bouts of flow that occurred in this creek during the dry spell. I collected only one of the four core Ephemeropteran genera, the caenid T.tillyardi, in either creek after the initial cessation of flow in late

~~1997. Interestingly, all of these taxa reappeared in samples four weeks after flow returned in May 1998.~~

As flow became disconnected, several taxa initially increased in density, before either returning to lower densities or disappeared for the remainder of the drought. I found that Triplectides austalicus (Trichoptera), Micronecta sp. (Hemiptera), Paratya australiensis (Crustacea), and adult N.penicillatus (Coleoptera) were present in their

~~121 Chapter 4~~

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~~140 120~~

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~~122 Chapter 4~~

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~~140~~

~~120~~

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MJet Creek-*-Duck Creek Marshall Mount Creek MJlet Oeek - -Duck Creek Marshall Mount Creek 200 iao o - Paratya §80 p - Necterosoma adults 0 160 $60 • 1 'J,14 0 §40 c 120 .220 TJ CD 100 •§00 T>J E au 0 60 -60 40 °40 h 20 9 3 P •Sao 0 cocooococococococoaicji *«— ^. -++m- i-'JU-'J COCOCOCOCOCOCOCOCOCOO) aiaiocjicjioiaioicTioioi Nr-r--r^Nr^r-^r-h-r-co COCOCOCOOOCOCOCOCOCOCD COCOCOCOCOCDCDCDCDCOO) COCDCOCDCDCDCDCDCOCDCD 01 CO CO >• c 3 cs a r 5 < § co O 5 < O z a 2 < 2 Month/Year Month/Year 123 Chapter 4

1 Mullet Creek •*- Duck Creek Marshall Mount Creek 200 180 q - Necterosoma larvae o 160 o 140 • 120 re10 0 C3 80 •o 'o5 60 4) 40 E 20 3 Z 0 r- r- r^r^r^h-r^-cocococococococococo go CO CO CO CO CO c0 O) c COCOCOCOCOCOCOCOCOCOCOCOCOCOCJ) CO en O) CO 5 Q. > 3 mar, > 6 e n ;= jr >• c ~=z co a. r; > C A a 3 ® X o a> £ (0 CD 2 o Month / Year Z

~~Figure 4.2: The total number of individual a) Chironominae, b) Triplectides, c)~~

~~Tasmanocoenis, d) Atalophlebia, e) Centroptilium, f) Jappa, g) Ceratopogonidae, h)~~

Orthocladinae, i) Tanypodinae, j) Hellythira, k) Ecnomus, I) Micronecta, m) Berosus adults, n) Berosus larvae, o) Paratya, p) Necterosoma adults, q) Necterosoma larvae, collected from Mullet Creek, Duck Creek, and Marshall Mount Creek in the Illawarra region of New South Wales. Twenty four sampling events were conducted over the two years of sampling. The first sampling event was conducted on the 11th of March

~~1997. Graphs a), b), c), and d) have y-axis to 800 individuals collected, while for all others graphs a y-axis of 200 individuals is used.~~

~~124 Chapter 4 highest abundances in the ponds that initially formed on Marshall Mount Creek~~

(Figure 4.2(b, 1, o, and p)). These higher densities were short lived, all of these taxa being absent for the rest of the drought, even though water was retained in the ponds on this creek throughout the drought period. However, I found that the initial increase in the density of P. australiensis and adult N. penicillatus in the ponds on Mullet Creek lasted only until intermittent flow returned, where upon the density of these species returned to relatively normal levels.

~~Two Coleopteran species were the most abundant taxa collected from ponds on~~

~~Marshall Mount Creek throughout the drought. Necterosoma penicillatus (Figure~~

~~4.2(p)) adults were the most common of several adult Coleopteran species of the family Dytiscidae that were collected from ponds on Marshall Mount Creek.~~

~~Interestingly however, larval N.penicillatus were absent from all creeks as soon as flow ceased (Figure 4.2(q)). This contrasts with the hydrophilid Coleopteran,~~

B.involutus, which was collected in both adult and larval forms from ponds throughout the drought period (Figure 4.2(m and n)). Ponds also contained a range of other less common taxa, present only in low numbers, usually as single specimens.

These included several adult Coleopterans, mainly dytiscids, larval Coleopterans such as elmids, and several Odonate species. Their presence in low numbers across the entire study meant that it was not possible to determine whether the densities of these taxa detected in ponds represented a deviation from the densities that may be expected during more normal flow conditions.

~~Although I detected significant differences between pre and post-drought samples the macrofaunal composition at most sites gradually returned to one similar to that~~

~~125 Chapter 4 detected in pre-drought samples. I detected significant differences between pre and post-drought samples at all but one site, MCI (Table 4.1). Indeed, for MM2 and MM3~~

Site Global R-value P-value Mullet Creek 1 0.003 0.427 2 0.355 0.005 * 3 0.218 0.005 * Duck Creek 1 0.539 0.001 * 2 0.286 0.000 * 3 0.343 0.000 * Marshal Mount Creek 1 0.304 0.001 * 2 0.350 0.000 * 3 0.179 0.010*

~~Table 4.1: Results for analysis of similarity tests between pre and post-drying samples of benthic macrofaunal assemblages in three streams of the Illawarra, New~~

South Wales. Three Hess samples were taken at each site during each sampling event for which water levels were high enough to allow sampling. Asterisks (*) indicate rejection of the null hypothesis of no difference among years.

the initial samples taken after the return of flow in late autumn 1998 were the most distant in multivariate space from pre-drought samples (Figure 4.3(h & i)), and were therefore the most dissimilar in macrofaunal composition from these samples.

However, subsequent samples, taken several months after the return of flow, were closer to pre-drought samples, indicating a return over time to a composition similar to that found prior to the cessation of flow. There was however greater variability among post-drought than among pre-drought samples. Comparison via an Index of

Multivariate Dispersion (IMD) and non-Metric Multidimensional Scaling ordination plots revealed substantially greater dispersion among post-drought samples (i.e., negative IMD values), at most sites (Table 4.2 and, Figure 4.3). IMD values for MCI,

~~126 Chapter 4~~

~~/a\ .. Stress = 0.20~~

~~a 3 b^v 6 KabbM b / bat b kftf/ / b / b b a ba; / \ / a b iy ra b a) ""-- b b)~~

~~c) d)~~

~~e) f)~~

~~^6 "b b b")~~

~~(a """ b "~b "^-^ b b .•-aa M a aa i g) h) Stress = 0.13~~

~~127 Chapter 4~~

Figure 4.3: non-Metric Multidimensional Scaling plots of benthic macrofauna samples collected a) pre-drying (enclosed by solid lines), and b) post-drying (dashed lines), from nine sites on three coastal streams in the Illawarra, New South Wales.

Sites were a) MCI, b) MC2, c) MC3, d) DC1, e) DC2, f) DC3, g) MM1, h) MM2 and, i) MM3. Dashed and solid lines were drawn around pre and post-drying groups to convey the outer limits of each groups dispersion in multivariate space. The first sampling event taken after water returned (i.e., in the post-drying period) are circled in red in graphs h and i. Data were the 4th root transformed centroids of three Hess samples taken at each site during each sampling event. A Bray-Curtis similarity measure was used for each analysis.

~~128 Chapter 4~~

~~MC2, and DC3 were very close to zero, indicating little difference in the variability among samples in pre and post-drought periods.~~

Index of Multivariate Dispersion Site 4th Root Quantitative Data Binary Data Mullet Creek 1 -0.090 -0.170 2 0.018 -0.007 3 -0.713 -0.854 Duck Creek 1 -0.767 -0.837 2 -0.744 -0.763 3 -0.004 -0.052 Marshall Mount Creek 1 -0.556 -0.465 2 -0.243 -0.195 3 -0.559 -0.544

Table 4.2: Index of Multivariate Dispersion (IMD) values for comparisons between replicate temporal samples taken in pre and post-drought periods from 9 sites in three coastal streams of the Illawarra region, New South Wales. Sampling was conducted on randomly allocated dates. Each temporal replicate represents the centroid of three

Hess samples taken at each site during each sampling event. A negative IMD value indicates greater dispersion among samples in the post-drought period. nMDS plots corresponding to each 4th-root quantitative comparison are presented in Figure 4.3.

~~4.3.3: The effect of flood events on assemblage composition~~

~~I found that macrofaunal densities recorded in post-flood samples were generally lower than those I detected in pre-flood samples for Duck Creek and Marshall Mount~~

~~Creek (sampling events 17 and 18 in Figure 4.4(b & c)). However, post-flood densities for both of these creeks were higher than those I detected in the sampling~~

129 Chapter 4 event immediately prior to the first flood event (sampling event 16 in Figure 4.4(b & c)). Only for Mullet Creek were post-flood densities lower than those detected in the previous sampling event. Post-flood macrofaunal densities for sites on Mullet Creek were comparable to the lowest densities detected in collections made during stable flow periods in 1997 (Figure 4.4(a)). Despite decreases in density I did not detected substantial differences in the type of macrofauna present in pre and post-flood samples at three of the sites for which sampling was conducted immediately before the flood spates (MCI, MC2, and MM3). All taxa collected in post-flood samples had previously been collected at these sites.

The most striking physical effect of the second flood event was the complete removal and replacement of the substratum at MC3. Uniform, coarse sand replaced the medium sized, rounded cobbles that were present prior to this flood event. I did not detect any macroinvertebrates at this site in the sampling event conducted immediately after the flood. Ordination plots (nMDS) revealed that the composition of the macrofauna collected after the flood (sampling events labelled with b's in

~~Figure 4.3(c)), were distinct from those collected pre-flood.~~

~~A small flood event may have occurred in early spring 1997. During the first of three sampling events in spring 1997 water levels were noted to be higher than normal.~~

~~Although I did not observe flood conditions, high rainfall in the area 6 days prior to this sampling event may have caused increased water volumes in the areas streams.~~

~~The density of macrofauna at all sites was particularly low during this sampling event~~

~~(Figure 4.4 - sampling event 7). Although the diversity of organisms collected at this time was not particularly low, most core taxa were collected only in relatively low~~

~~130 Chapter 4~~

~~4000 3750 3500 3250 3000 2750 2500 2250 T 2000 1750 1500 r~i 1250 _ 1000~~

750 p-i --i "*• 500 r--. "iririi T j r~ a) 25:-±UJiJJ_ JUJUriririSri^tilSr 1 2 3 4 JliJilLfili5 6 7 8 9 J1 0 11 12 13 14 15 16 17 18 19 20 21 22Jffll 23 24 i 4000 3750 3500 3250 Sj 3000 "- 2750 O 2500 2 2250 ^ 2000 Z 1750 0 !r 1500 S g 1250 j -§ 1000 750 I I r 5:: _ .T JL h Fl *r*i nr mil 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 b) - afiLULi w 22 23 24 -:::

~~3750 •• 3500 3250 3000 2750 2500 2250 2000 [" - 1750 . . 1500 -- 1250 T •• 1000~~

750 r ~] r-, T r~l rn r~i rn . 500 r--i *

~~ty 250 1 — ' I I -i[]cD_ii*i[IllS I¥I 0 LIUU1 2 3 L4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Sampling Event~~

~~Figure 4.4: Mean density of benthic macroinvertebrates collected per m2 from a)~~

~~Mullet Creek, b) Duck Creek, and c) Marshall Mount Creek in the Illawarra region of~~

~~New South Wales between 1997 and 1999. Three Hess samples were taken at each of~~

~~three sites on each creek during each sampling event. Error bars are one standard deviation either side of the mean.~~

131 Chapter 4 numbers (See Figure 4.2 - the first sampling event after the October 97 label on the x- axis). These findings appear to reflect the decreases in density evident after the flood events described above.

~~4.3.4: Long-term changes in assemblage composition~~

~~I detected changes in the macrofaunal composition of the sampled assemblages between the present study and Gregory's earlier study of the same sites. Analysis of~~

~~Similarity revealed significant differences between these studies in the relative abundance and presence (binary data) of core genera at the whole creek level (Table~~

4.3 and Appendix D). I also detected significant differences between studies for each site individually except MCI, where differences were only detected in the presence of core genera (Table 4.3). Moreover, non-parametric multivariate analysis of variance indicated highly significant differences between studies for all three creeks combined

~~(F = 3.7387, d.f = 1, P = <0.0008), and for each creek individually (Mullet Creek; F =~~

~~3.7320, d.f = 1, P = O.0002, Duck Creek; F = 2.3498, d.f = 1, P = O.0160, Marshall~~

~~Mount Creek; F = 5.0787, d.f = 1, P = <0.0002).~~

~~Five core genera and one family were largely responsible for long-term differences detected between the two studies. SIMPER analysis revealed that Glyptophysa~~

(Mollusca), Tasmanocoensis (Ephemeroptera), and the Chironominae (Diptera) were the groups that contributed most to the dissimilarity between studies for Mullet Creek and Duck Creek. Berosus (Coleoptera) and Pisidium (Mollusca) were also important

~~132 Chapter 4~~

Quantitative Binary Data Data Creek Mullet * * Duck * * Marshall Mount * *

Site MCI * MC2 * * MC3 * * DC1 * * DC2 * * DC3 * * MM1 * * MM2 * * MM3 * *

Table 4.3: Summary of analysis of similarities tests for differences among pre and post-development sampling periods. Benthic macroinvertebrates were collected on twenty four sampling occasions during each of two sampling periods, between 1993 and 1995 (pre-development - Gregory (unpublished data)), and between 1997 and

1999 (post-development - the present study). Asterisks (*) indicate rejection of the null hypothesis that the macrofaunal composition of the sampled assemblages would not differ between pre and post-development sampling periods. Global R and P-values for these tests are listed in Appendix D.

~~in defining differences between the two studies for individual sites within these two creeks. For Marshall Mount Creek differences were mostly due to Micronecta~~

~~(Hemiptera), Atalophlebia (Ephemeroptera), and as for the other two control creeks,~~

~~Glyptophysa. At the individual site level on Marshall Mount Creek Pisidium and~~

~~Jappa (Ephemeroptera) were important in defining differences between the two studies. These genera were markedly more abundant during Gregory's two years of~~

133 Chapter 4 sampling between 1993 and 1995 than during the present study. Only a single species was collected in most of these genera, or single species were responsible for the overwhelming majority of individuals collected in each genus (See Table 2.1).

~~Differences between these two-year sampling periods were therefore due mostly to changes in the presence and abundance of the Chironominae and a few other Insect and Molluscan species.~~

~~4.3.5: Among season variability in assemblage composition~~

The composition of the macrofaunal assemblages changed from season to season both at the whole creek and individual site level. Nine of the twelve creek x year combinations tested showed significant differences among seasons for both 4th root transformed quantitative and binary data (Table 4.4 and Appendix D). In the only two instances that differences were not significant among seasons, Duck Creek 97-98 and

98-99, only three seasons were compared as samples could not be collected from this creek due to drought conditions in Summer 97-98 and Autumn 98. Similarly, there were significant differences among seasons in the majority (22) of the 36 site x year test combinations (Table 4.4). Each site exhibited differences among seasons in most but not all years. Patterns of variability among seasons across the four sampling years were different for each site. In 94-95 all sites showed significant differences among seasons for both quantitative and binary data except MC3, where differences were only apparent in quantitative data. Two sites, MCI and MM3, showed significant differences among seasons in all of the four sampling years, while MC2 was the only site for which there was no significant differences among seasons in each year except

~~94-95.~~

~~134 Chapter 4~~

~~Year of Sampling 93-94 94-95 97-98 98-99~~

~~Creeks Quantitative Binary Quantitative Binary Quantitative Binary Quantitative Binary~~

* * * * * * * Mullet

* * * * Duck

~~Marshall * * * * * * * * Mount~~

~~Sites~~

* * * * * * * * MCI

* * MC2

* * * * * * * MC3

* * * DC1 Insufficient data Insufficient data

* * * * * * DC2

* * * * DC3 Insufficient data

* * * * MM1

* * * * MM2

* * * * * * * * MM3

~~Table 4.4: Summary of analysis of similarities tests for differences among seasons in each year of sampling. Each test was performed using quantitative and binary data.~~

Asterisks (*) indicate rejection of the null hypothesis that the macrofaunal composition of individual sites and whole creeks would be the same across all four seasons in a year. Therefore, blank spaces indicate that the null hypothesis could not be rejected at the alpha = 0.05 level. MC = Mullet Creek, DC = Duck Creek, and MM

= Marshall Mount Creek. Site x Year combinations for which data was insufficient to justify testing are indicated as "Insufficient data". Global R and P-values for these tests are listed in Appendix D.

~~135 Chapter 4~~

The macrofauna present in a particular season varied from year to year at both the individual site and creek level. Each of the four seasons showed significant differences among years at both the whole creek and individual site level (Table 4.5 and Appendix D). Winter and spring showed a fairly consistent pattern, with significant differences across years at the creek and site level for both quantitative and binary data. For two sites, MC2 and DC1, there were no significant differences among spring fauna's across the four sampling years. Autumn showed consistent differences across years at all sites, while fauna present in summer appears to have been different across years at some sites but not at others. However, for several sites Summer 97-98 and Autumn 98-99 were not included in the analysis as no samples were taken during these periods due to drought conditions. At all other sites many of the samples taken in Summer 97-98 and Autumn 98-99 periods were extracted from drying pools.

Comparisons among summer and autumn periods are therefore potentially affected by the extreme conditions generated by this severe drought episode, and may not reflect variability across years with less dramatic flow variability.

~~4.3.6: Tests among reallocated temporal periods for Marshall Mount Creek~~

Differences among reallocated long and short temporal periods in each year indicated that seasonal differences are not exceptional in the context of overall temporal variability in these streams. Of the 14 ANOSIM's conducted for Marshall Mount

~~Creek, six out of seven tests on quantitative data, and five out of seven tests on binary data, revealed significant differences among the particular temporal period in question~~

~~(Table 4.6 and Appendix D). The majority of test results for MM3 also indicated significant differences among six, four, and two month periods. All eight tests on~~

~~136 Chapter 4~~

~~Season Autumn Winter Spring Summer~~

~~Creeks Quantitative Binary Quantitative Binary Quantitative Binary Quantitative Binary~~

* * * * * * * Mullet

* * * * * Duck

~~Marshall * * * * * * * * Mount~~

~~Sites~~

* * * * * * * * MCI

* * MC2 Insufficient data

* * * * * * * MC3

* * * DC1 Insufficient data

* * * * * * DC2

* * * * * * DC3 Insufficient data

* * * * * * * MM1

* * * * * * * MM2

* * * * * * MM3 Table 4.5: Summary of analysis of similarities tests for differences among individual seasons across all four years of sampling. Each test was performed using quantitative and binary data. Asterisks (*) indicate rejection of the null hypothesis that the macrofaunal composition of seasons would be the same across all four sampling years. Blank spaces indicate that the null hypothesis could not be rejected at the alpha

~~= 0.05 level. MC = Mullet Creek, DC = Duck Creek, and MM = Marshall Mount~~

~~Creek. Site x Season combinations for which data was insufficient to justify testing are indicated as "Insufficient data". Global R and P-values for these tests are listed in~~

~~Appendix D.~~

137 Chapter 4 quantitative data revealed significant differences among temporal periods, as did seven of the eight tests performed on binary data. Therefore, statistically significant differences were apparent over the course of a year, whether the year was divided into six month, four month, or two month long periods.

~~Temporal Period 6 months 4 months 2 months~~

~~Quantitative Binary Quantitative Binary Quantitative Binary~~

~~Marshall Mount Creek~~

* * * * 94-95 Not Tested

* * 97-98 Not Tested

* * * * * 98-99

~~MM3~~

* Not Tested Not Tested 93-94

* * * * Not Tested 94-95

* * * * Not Tested 97-98

* * * * * * 98-99

~~Table 4.6: Summary of analysis of similarities tests for differences among reallocated temporal sampling periods for Marshall Mount Creek and Marshall Mount Creek Site~~

3. Each test was performed using quantitative and binary data. Asterisks (*) indicate rejection of the null hypothesis that the macrofaunal composition would be the same among sampling periods. Therefore, blank spaces indicate that the null hypothesis could not be rejected at the alpha = 0.05 level. Reallocation could not be justified for all temporal periods and testing was not conducted for these periods, indicated as

~~"Not tested". Global R and P-values for these tests are listed in Appendix D.~~

~~138 Chapter 4~~

~~4.4: Discussion~~

~~4.4.1: Overview~~

The findings of this study emphasised the highly variable temporal structure of macrofaunal assemblages. Significant temporal variability was apparent among and within years and over the longer-term between this study and Gregory's earlier study of the same sites. Interestingly, I detected far greater changes in the composition of the sampled assemblages due to periodic climatic events (i.e., flooding and drying) than were detected among seasons. Despite this high degree of temporal variability the basic structure of these assemblages was stable over time, with the most abundant taxa sampled during the present study being the same as those sampled by Gregory between 1993 and 1995. Flow variability was associated with dramatic changes in the type and relative abundance of macrofauna collected during the present study.

Flooding caused drastic short-term declines in macrofaunal density. The cessation of flow and eventual complete drying of many sites drastically altered not only the number but also the type of macroinvertebrates present in these assemblages.

However, the findings of this study suggest that the macrofauna of these streams are resilient to the disturbance caused by drying, with a return to pre-drying assemblage composition occurring gradually after flow resumed.

~~4.4.2: The lack of distinct seasonal variability~~

I found no evidence for specifically seasonal changes in the composition of the sampled assemblages. Although I did detect significant differences among seasons, I also detected significant variability among several other temporal periods within a year. Moreover, seasons did not display a characteristic macrofauna across the four

139 Chapter 4 years of sampling. Therefore, differences among seasons were a reflection of the generally high degree of temporal variability present during the study and not specifically seasonal variability. Indeed, had we derived our notion of seasonality from other than the temperate Northern Hemisphere model I would still have concluded that the composition of these assemblages differed among pre-assigned

~~"seasons", no matter what time interval was used for a season. For example, had our notion of seasonality been derived from tropical systems, such as those of northern~~

Australia and southern Asia, I would still have derived a conclusion of seasonal variability from the significant differences detected among six month periods. Two or four month long "seasons" would have led to the same conclusion. Clearly, these findings suggest that in this system it is erroneous to treat seasons as unique or distinct periods within a year over which these macrofaunal assemblages exhibit change.

A lack of seasonal variability in macrofaunal composition is perhaps unsurprising given the pattern of flow variability in this system. The decision to use seasons as the periods within which sampling was randomised was not based on previous knowledge of temporal variability in the macrofauna of this stream system (Gregory - unpublished data). Rainfall and discharge information, limited as it was, suggested that seasonal variability in flow maybe a minor component of overall flow variation in these streams. Single high flow events generated by intense rainfall over a few days may be responsible for a very high proportion of discharge in these streams (Nanson

~~& Young 1981b). Unfortunately, reliable, long-term discharge data from which to determine flow cycles in the coastal streams of the Illawarra was not available.~~

~~Boulton & Lake (1992a) suggest that macrofaunal variability may be linked to~~

140 Chapter 4 fluctuating flow patterns and have identified changes in the physiochemical conditions and macrofauna of intermittent streams in Victoria that correspond to flow cycles. Determining how flow variability affects macrofaunal composition in these streams would be desirable and may lead to a more appropriate determination of time periods relevant to macrofaunal changes in this system.

The lack of seasonal variability cannot simply be explained by the severe climatic fluctuations that occurred during the study. Firstly, such an explanation assumes that we should find seasonal variability. As detailed above, this assumption cannot be justified in these streams on the evidence presented by this study. Clearly, the high degree of variability exhibited by these macrofaunal assemblages reflects the influence of the severe climatic fluctuations that occurred during the course of the study (the affect of these fluctuations is further discussed below). Over the two years of sampling these assemblages were heading into, experiencing, or recovering from an unusually severe and prolonged drought and several flood events, one of which was a major flood. Climatically driven disturbances are not unusual in the coastal stream systems of New South Wales (Nanson & Erskine 1988). Geomorphologically these stream systems are structured by such events, particularly the relatively large magnitude floods they experience at irregular intervals (Nanson & Young 1981a,

~~Nanson & Erskine 1988). Moreover, El Nino events substantially affect rainfall and stream discharge levels along Australia's eastern coast (Bryant 1985, Allan et al.~~

1996). Enfield (1992) suggests that a pattern of inter-annual occurrence of El Nino events (i.e., every 2 to 5 years) has existed for at least 5000 years and possibly for much longer. It would therefore be erroneous to conclude that, although clearly dramatic, the climatic pattern experienced during this study was an anomaly. Rather,

141 Chapter 4 as Lake (1995) suggests, such fluctuations and the disturbances they cause may be important features of Australian stream systems and may be influential factors affecting the structure of macrofaunal assemblages in Australian streams.

~~The manner in which I have used multivariate hypothesis tests in this chapter and in~~

~~Chapter 3 treats macrofaunal distributions as discrete units rather than gradients.~~

Although partitioned among various spatial or temporal levels in the sampling design, changes in the fauna sampled at each site on a stream, or in each season or year, do not occur independently of changes to other sites on the same stream or of previous seasons or years. This does not invalidate the multivariate hypotheses tested performed here as all tests were conducted among groups (i.e., sites, creeks, seasons, etc) that were defined a -priori. Clearly, quantifying distributional gradients was not the focus of the sampling conducted here. However, it is important to recognise that my findings in effect represent differences among points along a gradient rather than differences among separate, unconnected ecological units.

~~4.4.3: The influence of flow~~

These assemblages were temporally dynamic during periods of stable flow. During periods when flow was relatively low and constant the assemblages I sampled consisted of a group of core taxa and a few rare taxa (as detailed in previous chapters). Changes appear to have occurred mostly in the relative abundance of core taxa and in the type of rare taxa present. Short-term changes in density, over periods of weeks and several months, were due mostly to fluctuations in the number of

~~Chironomids and Ephemeropterans. Although occurring at different times of year, peaks in macrofaunal density at each site were also driven by large increases in the~~

~~142 Chapter 4 number of individuals collected from these groups, particularly the Chironomidae.~~

Interestingly, each of the sites at which peaks in chironomid numbers were the greatest were close to cow crossings. Drastic increases in chironomid numbers have been detected after instances of organic enrichment (Del Rosaria et al. 2002) and the peaks in chironomid numbers detected here may represent episodes of organic enrichment from cow dung. However, I can not infer process from the patterns detected here. Rather, I can only conclude that these findings suggest localised influences on the structure of these assemblages.

The most dramatic short-term changes in density occurred after flood events. Drastic short-term flow increases (i.e., flooding) greatly reduced macrofaunal densities yet did not lead to any long-term change in the type of macrofauna I collected. Low resistance (i.e., immediate, drastic declines in density), yet rapid recovery to pre- disturbance composition is a commonly documented response of macrofaunal assemblages to flooding (Fisher et al. 1982, Scrimgeour et al. 1988). Such a response suggests the use of refugial strategies to ride out the disturbance caused by floods

~~(Boulton & Lake 1992a). The use of refugial strategies appears to be common among the macrofauna of intermittent (Boulton 1989, Boulton & Lake 1992a), and temporary~~

~~(Brooks & Boulton 1991) streams in Australia, in regularly disturbed streams in New~~

~~Zealand (Scrimgeour et al. 1988, Scrimgeour & Winterbourn 1989), and in intermittent and permanent streams in North America (Miller & Golladay 1996,~~

Angardi 1997, Rempel et al. 1999). The findings of this study suggest that the macrofauna of the intermittent temperate coastal streams of the Illawarra are similarly adapted to survive flood events with no detectable long-term affect to assemblage structure.

~~143 Chapter 4~~

Long-term changes in assemblage composition were detected at one severely scoured site. The affect of a disturbance event may vary among different habitats in a single stream (Death 1995, 1996). Resh et al. (1988) suggest that pool habitats are more severely affected by increased flow volumes than are riffles. The findings of this study suggest that site-specific physical features may cause the affect of disturbances such as floods to differ even among similar habitats. Surprisingly, during the second and largest flood event that occurred during this study medium sized cobbles were completely removed from MC3 and replaced with coarse sand. The substrata in other sections of the same stream and at all other sampled sites were unaltered. A steep, 15 feet high curved embankment that formed the southern bank of this site may have caused a localized increase in flow rate, elevating sheer stress levels enough to shift relatively heavy cobbles. In Chapters 2 & 3 I documented marked differences between the macrofaunal assemblages of cobble and sand substrata in these streams.

Therefore, the substantial change in assemblage composition I detected after a drastic change in substratum composition at MC3 is not surprising. However, this dramatic change further emphasizes the role substrata type may play in determining the composition of macrofaunal assemblages in these streams and suggests that flooding may cause long-term changes in macrofaunal composition.

Clearly, the changes documented here occurred only at one site. Long-term changes due to flooding were not detected in the macrofaunal assemblages of any other sampled sites. However, this single incident suggests that the expectation that flooding causes only short-term changes in macrofaunal density and has little impact on assemblage composition may be dependent upon the scale of the floods physical

~~144 Chapter 4 affects. Flooding may change the relative mixture of substrata in a stream (Erskine &~~

Warner 1988, Nanson & Erskine 1988). Indeed, several studies have documented the removal of substrata by flash-flooding from substantial sections of stream channels and the subsequent removal of all macroinvertebrates has been documented by

Siegfried & Knight (1977), Fisher et al. (1982), and Molles (1985). The changes detected here were more localised, being restricted to a single site. However, these findings suggest that such changes may initiate long-term changes in the number and type of macrofauna present at the whole creek scale. For example, in the streams sampled here the macrofauna of cobble sites were substantially more numerous and diverse than sandy sites. Were flooding to increase the relative proportion of sandy sites in the stream we may expect the density and diversity of macrofauna to decline in the creek as a whole. However, such events probably occur only after extremely large, destructive floods and therefore, although hypothetically possible, are unlikely to be common occurrences.

~~4.4.4: The affect of drying~~

The presence or absence of flowing water exerted a strong influence on the type and number of macrofaunal organisms present in these streams. Gill breathing taxa such as dipterans (Orthocladinae, Tanypodinae, and Ceratopogonidae), ephemeropterans

(Centroptilium sp., Atalophlebia sp., and Jappa kutera), and tricopterans (Triplectides spp., Hellyethira simplex, and Ecnomus russellius), were not present in samples after flow ceased. These taxa may have been eliminated by unsuitable physiochemical conditions (i.e., declining oxygen levels), or have taken refuge in habitats other than those sampled. Macrofaunal densities increased as the water level in pools decreased and peaked just after these pools became disconnected from the rest of the stream.

~~145 Chapter 4~~

Boulton & Lake (1992a) and Miller & Golladay (1996) identified similar density peaks in pools after shallower riffle sections dried up and suggested that this increase reflects emigration from drying riffle sections. A number of taxa that had not previously been collected (mainly dytiscid beetles) were recorded in pools after flow became disconnected. Due to the complete absence of information on the macrofauna of habitats other than pools in these streams I was unable to assess from which habitats these taxa may have emigrated. However, riffle sections were the first to dry up and it is likely that some riffle macrofauna migrated to the only remaining water bodies available, those in nearby pools.

Decreasing oxygen levels in the pools that formed after flow cessation appear to have affected the composition of the sampled assemblages. Surface turbulence maintains oxygen concentrations that are generally high (i.e., near saturation) in running waters

(Allan 1995). When flow ceases water surface area and turbulence decrease, substantially reducing oxygen uptake in the resulting stagnant waters. Decomposition of organic matter and rising temperature may further reduce the amount of oxygen available to biota (Allan 1995). Boulton & Lake (1990) identified hypoxic conditions in the drying pools of intermittent streams in Victoria and although not measured here, it is likely that such conditions developed in the gradually receding pools that formed when flow became disconnected in these streams. The author noted that water temperatures in these drying pools were substantially higher than at any other sampling time, particularly in exposed pools, unshaded by riparian vegetation. The findings of this study indicate that flow cessation has an immediate and dramatic effect upon the structure of these assemblages. Taxa with adaptations to low oxygen or high temperate conditions numerically dominated the stagnant pools. Adaptations

~~146 Chapter 4 to low oxygen level have been identified for Glyptophysa gibbosa (Closs & Lake~~

~~1994), the Chironominae (Boulton & Lake 1992a) and for Berosus involutus~~

(Brigham 1982), the three most commonly collected taxa from the pools that remained throughout the dry spell. A number of air-breathing dytiscid coleopterans were also collected from these pools, some of which were not recorded prior to the onset of drying, again suggesting potential migration from surrounding habitats.

~~However, gill-breathing taxa were absent from samples taken immediately after flow ceased and did not reappear in samples until flow returned.~~

Interestingly, several of the taxa that disappeared from samples taken after flow ceased in this study were common in the samples taken by Boulton & Lake (1992a) from the summer dry pools of intermittent streams in Victoria. Boulton & Lake

(1992a) noted that the respiratory adaptation of Triplectides spp. cases and the uninterrupted oscillatory motion of the large gills of Atalophlebia sp. allowed them to survive the low oxygen conditions in these summer dry pools. However, in this study, three Triplectides sp. and Atalophlebia sp. were absent from samples as soon as flow ceased and were not collected throughout the dry spell. These findings suggest that that not all members of these genera are adapted to surviving in such water bodies during dry spells. Clearly however, I can not discount the possibility that these taxa were eliminated by adverse physiochemical conditions unrelated to oxygen concentrations, or by biotic interactions such as increased predation pressure. The casing materials used by caddisfly species in these streams, mainly sand and cassuarina leaves, may not have allowed enhanced oxygen uptake as did those of the

~~Triplectides spp. sampled by Boulton & Lake (1992a). Increased turbidity levels in these stagnant pools may have clogged gill structures, reducing the effectiveness of~~

~~147 Chapter 4 the rapid, continuous oscillatory motions used by Atalophlebia sp. to increase oxygen uptake. Indeed, the only ephemeropteran collected after flow ceased, the caenid~~

~~Tasmanocoenis tillyardi, possesses gill structure adaptations that allow them to survive in stagnant, turbid waters (Miller & Golladay 1996).~~

~~Over the course of the dry spell the macrofaunal assemblages sampled from these pools became increasingly dissimilar to those sampled pre-drying. Berosus involutus,~~

~~Glyptophysa gibbosa, and the Chironominae, dominated samples taken from pools throughout the dry spell, as they had in the drying pools of an intermittent stream in~~

Victoria sampled by Boulton & Lake (1992a). These taxa were able to survive even when these pools were reduced to a few square metres in surface area. However, all macrofauna were eventually eliminated when many pools dried up completely.

Several weeks after Duck Creek became completely dry I observed numerous empty shells of the Molluscs G gibbosa and Pisidium casertanum under rocks at several sites, suggesting that this moisture refuge of last resort had been exhausted by the continuation of the dry spell. The prolonged nature of the dry spell may have similarly exhausted other moisture refuges. Dry was severe, with terrestrial vegetation (grasses and small shrubs) overtaking the stream channel at all sites that dried up completely.

Therefore, when water returned in May 1998 the physical condition of these sites was radically different from that which had existed pre-drying. Initial samples taken after the return of flow in late autumn 1998 displayed the highest level of dissimilarity in composition to pre-drying assemblages of any samples taken during the study.

~~The sampled assemblages eventually returned to a composition similar to that present before drying and displayed long-term stability in the type of core taxa present. The~~

~~148 Chapter 4~~

20 taxa that were most abundant in Gregory's study were also the most abundant taxa collected during the present study. This finding suggests long-term stability in the core taxa that form the base of these assemblages, with differences between the two studies due to changes in the relative abundance of these taxa. Furthermore, in the present study, these assemblages gradually returned towards a pre-drying composition over the nine months of sampling that was conducted after flow resumed. Rapid recovery from disturbances that occur over relatively short time spans, such as flooding, has been well documented (Palmer et al. 1992). However, I am not aware of any studies documenting such recovery from severe, prolonged disturbances such as drying. Importantly therefore, the findings of this study suggest that at the genera level the basic structure of the macrofaunal assemblages of intermittent coastal streams may be relatively stable over time and moreover, that they may recover this basic structure after severe, drought induced drying episodes.

All of the assemblages I sampled displayed markedly greater temporal variability in macrofaunal composition post-drying. This increased temporal variability mostly reflects the relatively rapid changes in composition that occurred after initial recolonisation of these sites. Increased variability in composition during an initial re- establishment period is perhaps unsurprising. Continued sampling would have been required to establish whether these assemblages remained more temporally variable in the long-term.

~~149 Chapter 4~~

~~4.4.5: Independence, Type I errors, and the limitations of multivariate analysis of complex designs~~

~~The analyses multivariate analyses performed in the two preceding chapters (Chapters~~

3 & 4) are not independent of one another. Multiple tests, such as the ANOSIM tests performed here, can not be considered independent if they are performed on the same population (Quinn & Keough 2002). Adjustments are commonly applied to the P- values resulting from multiple univariate tests to correct for the lack of independence and to ensure that an appropriate probability of a Type I error is maintained (Sokal &

Rohlf 1995, Quinn & Keough 2002). However, these adjustments are not yet clearly defined for multivariate hypothesis testing techniques and Quinn & Keough have recently recommended "no adjustment for multiple testing". While I have not adjusted

P-values here and acknowledge that this a weakness of the approach I have chosen, I have interpreted the results with this weakness in mind. Although a correction factor would have decreased the P-values of some tests I have sort to avoid this problem as much as possible by not giving weight to individual tests in my interpretations.

Rather, I have focused on the trends apparent across sets of tests (or families of tests as they often termed in the literature). Indeed, many of the tests performed here returned highly significant results, with P-values of zero or close to zero. A correction factor would, therefore, have had little if any affect on many test results and the interpretations drawn from these results.

~~Multivariate analyses can not test for interactions in complex designs. Interaction terms are difficult to define in multivariate hypothesis tests such as ANOSIM (Quinn~~

~~& Keough 2002, Legendre & Anderson 1999), a major weakness such techniques~~

~~(Quinn & Keough 2002). Quinn & Keough 2002 recommend that interactions are best~~

~~150 Chapter 4 judged in linear models that include main effects, as they would have been in this study under the 5-factored mixed model analysis of variance with which the Beyond-~~

~~BACI sampling design used here was to be analysed. Such analysis was, however, not possible due to large amounts of missing data (this issue is fully detailed in Chapter~~

6). It was never my intention to use multivariate analyses to test for interactions among factors in the Beyond-BACI sampling design. Clearly, they can not do so and this is a weakness of the approach used here. However, I take advantage of the flexibility of multivariate techniques (an issue more fully discussed in Chapter 3) to describe and test for spatial and temporal patterns of variability in these assemblages.

~~This approach allows specific hypotheses regarding spatial and temporal variability to be tested in the absence of an appropriate univariate test that would have included interaction terms.~~

~~151 Chapter 5~~

~~Chapter 5 - Do rare taxa alter the interpretation of multivariate hypothesis tests of community structure?~~

~~152 Chapter 5~~

~~5.1: Introduction~~

The majority of species collected in ecological samples are often present only in low numbers. These rarely collected species contribute little to the total number of individuals present in a system, yet form the bulk of total species richness (Figure

~~5.1). A few common species are usually responsible for most of the individual organisms collected from ecological communities (Gauch 1982).~~

~~Accurately quantifying the abundance of rare taxa is problematic, even in sampling programs with high levels of spatial and temporal replication (Krebs 1994).~~

Moreover, although some rare taxa may be biologically important, others may be merely transitory in a sampled habitat, potentially playing no functional role in the community under examination (Townsend 1989). The latter consideration is particularly relevant in the linear systems of running waters. Longitudinal differences in composition and diurnal drift cycles combine to create dynamic distribution patterns for dispersing or migrating species (Hynes 1970, Schreiber 1995). Some species may be present at a particular site only as a temporary measure before drifting to a more suitable habitat (Anholt 1995, Fonseca 1999). It is potentially both biologically and statistically irrelevant to include such taxa when making statistical comparisons among communities (Marchant 1999).

Pooling some of the data in large, complex multivariate data sets, by lowering the level of taxonomic resolution at which an analysis is performed, has been found to have little or no effect on the result of the analysis performed on terrestrial (Pik et al.

~~1999), marine (James et al. 1995, Olsgard et al. 1998), or freshwater (Marchant et al.~~

~~153 Chapter 5~~

~~•o z » z 10 O w .S 8 OT 6 0 .Q E~~

~~a) 0-20 21-40 41-60 61-80 81-100 Number of Individuals collected per sample~~

~~100 200 300 400 500 600 700 800 900 1000 1100 Number of Individuals collected~~

~~40 35~~

~~S 30 u §. 25 CO "5 20 e •o 15 3 Z 10 5 ••%V~Vt • 0 1 c) 10 15 20 25 30 35 40 Number of Individuals Collected per Sample~~

Figure 5.1: Examples chosen to illustrate the high proportion of rare taxa within communities of: a) plants in a peat bog in Michigan, USA (Kenoyer 1927), b) fish collected from a stream in South Carolina, USA (Meffe & Sheldon 1988), and c)

~~Lepidoptera collected from a light trap in England (Williams 1964).~~

~~154 Chapter 5~~

~~1994, Wright et al. 1995, Bowman & Bailey 1997), macroinvertebrate assemblages.~~

A certain level of redundant information is present at higher levels of taxonomic resolution in these data sets. However, it is unclear how sensitive multivariate analysis techniques are to the elimination of information, such as the removal of rare taxa, and to what extent this sensitivity may depend on the type of transformation conducted on the raw data. If rare species are statistically unimportant in such analyses then their elimination should have little or no effect on the results and interpretations derived from the analyses.

Despite accumulating evidence that eliminating rare taxa may have little effect on the outcome of multivariate analyses techniques such as ordination (eg: Marchant 1999), their removal from multivariate data sets remains contentious (Cao & Williams 1999).

~~Removing rare species did not change the outcome of ordinations performed by~~

~~Marchant (1990) and Marchant et al. (1994) on large data sets gained from broad scale sampling of benthic macrofaunal communities of running waters. Nevertheless,~~

Cao et al. (1998), and Cao & Williams (1999), contend that the similarity measures used in such analyses under-weight the importance of rare species. They argue that due to this under-weighting, the removal of rare species is, by default, bound to have no effect on the outcome of the analysis. If they are correct we would expect the removal of rare taxa to have a greater impact on tests conducted on transformed data than on untransformed data, in which the bias towards abundant taxa has not been remedied. The impact may be even greater still for binary data, in which each species is on an equal footing. Marchant (1999) argues that transformations used prior to the calculation of similarity measures do adequately remove the dominance of taxa present in large numbers, and concludes that rare species therefore represent redundant information in multivariate analyses. However, such conclusions may be

~~155 Chapter 5 premature as the descriptive nature of ordinations provides no simple empirical basis to compare the results of analyses performed with and without rare taxa.~~

~~Hypothesis testing techniques such as analysis of similarities (ANOSIM) (Clarke~~

1993, Clarke & Warwick 1994) provide the opportunity to empirically test the effect of removing rare taxa from multivariate data sets. Unlike the more subjective results of techniques such as ordination, ANOSIM can be used to test for statistically significant differences among spatially or temporally separated communities.

ANOSIM provides discrete test statistics (R & P values), against which the values generated from the same tests, but with rare species excluded, can be directly compared (Clarke & Warwick 1994, Pik et al. 1999). Ideally, to test the effect of removing rare species we require a data set that is large, has a diverse fauna, and contains a variety of hierarchical spatial and temporal levels, such that numerous possible tests combinations are available. A clearly definable group of rare species, occurring only in low numbers over the entire sampling period, should also be present.

The effect of eliminating rare taxa is an issue of particular importance in the context of this study. As detailed in Chapter 2, eliminating rare taxa from both data sets was the only solution to comparability problems between the pre and post-development data set. The elimination of rare taxa from multivariate analyses conducted on benthic macrofaunal data sets from other Australian stream systems suggested that removing rare taxa was a potentially useful option, one that may have little effect on the results of the analyses performed. However, removal of rare taxa had not previously been reported for the multivariate hypothesis testing techniques (ANOSIM), which I have

156 Chapter 5 used throughout this thesis. Therefore, removal of rare taxa from these analysis techniques and in particular the effect of removing rare taxa in this particular system warranted investigation.

Here, I use a sub-set of the ANOSIM analyses conducted in Chapters 3 and 4 to test whether eliminating rare taxa changes the outcomes and interpretations derived from these analyses. I defined rare taxa as those representing less than 0.5% of all individuals collected over the two years of sampling. To determine whether the effect of removing these taxa differed for analyses performed on different data types I performed all tests on untransformed quantitative, 4th root transformed quantitative, and binary data (presence or absence).

~~5.2: Methods~~

In this chapter I use a sub-set of the ANOSIM analyses conducted in Chapters 3 and 4 to test whether eliminating rare taxa changes the outcomes and interpretations derived from these analyses. Data are from sixteen sampling events conducted over a two year period, 1997 to 1999, in Duck, Mullet, and Marshall Mount Creeks. Data from sampling events during which sampling was not possible or for which replication was reduced due to drying were not included. I performed 44 ANOSIMs both with and without rare taxa. Tests for spatial differences were conducted among sites on individual creeks, and among whole creeks. Tests for temporal differences were conducted among sampling events, and between the first and second years of sampling, at both the individual site and whole creek level.

~~157 Chapter 5~~

To test whether the effect of removing rare taxa differed depending on the type of data transformation used prior to analysis, I performed each of the 44 ANOSIMs with untransformed quantitative data, 4th root transformed quantitative data, and binary data (presence or absence). I used a Bray-Curtis similarity measure to generate similarity matrixes for all tests on quantitative data, while a Sorensen's coefficient was used as the similarity measure for binary data.

~~5.3: Results~~

~~I collected 30845 individual macroinvertebrates representing a total of 122 taxa from~~

Mullet, Duck, and Marshall Mount Creeks. Most of these taxa were collected in low numbers. Thirty taxa were recorded only as single specimens, and for a further 46 taxa less than 10 individuals were collected. Only six taxa had individuals numbering in the thousands, while a further 19 taxa had totals in the hundreds.

One hundred and one taxa, 82.8% of all taxa collected, were classified as rare. Twenty one taxa were therefore classified as core taxa. Core taxa represented 17.2% of the total number of taxa collected yet they accounted for 95.4% of all individuals. On average the elimination of rare taxa removed between 2 and 4 taxa per sample at each site (Figure 5.2), while between 5 and 15 core taxa were presented at a site during each sampling event (Figure 5.2).

~~5.3.1: Tests for Spatial and Temporal differences - rare taxa included~~

~~My analysis revealed significant spatial and temporal heterogeneity in the composition of these stream assemblages when rare taxa were included, regardless of~~

~~158 Chapter 5~~

~~14 •o B 6) 8 10 (0 a 8~~

~~16 BSite 1 BSite2 DSite3~~

~~Mullet Duck Marshall Mount Creek~~

~~Figure 5.2: The mean number of a) rare taxa, and b) core taxa collected taxa per sampling event from the benthic macrofaunal communities of three streams in the~~

Illawarra region of New South Wales. Data are from sixteen sampling events conducted over a two year period, 1997 to 1999. Rare taxa were those taxa collected in numbers that represented less than 0.5% of the total number of individuals collected. Error bars are one standard deviation either side of the mean.

~~159 Chapter 5 whether the data were untransformed, transformed or binary. I found significant differences among sites (Appendix C(a)), and whole creeks (Appendix C(b)).~~

However, differences among creeks were not consistent throughout the study; on 3 occasions I detected no difference among creeks (Appendix C(c)). My analyses revealed significant differences among sampling events for all sites individually and for each creek (Appendix C(d) & (e)). There were significant differences among the first and second years of sampling for each creek, except Duck Creek for untransformed data (Appendix C(g)). Similarly, I detected significant differences among the first and second years of sampling for most sites, except MCI for 4l root transformed data, and MCI, MC3, DC2, and MM3 for untransformed data (Appendix

~~C(f)).~~

~~5.3.2: Elimination of Rare Taxa~~

Removal of 101 rare taxa from the original data set had very little effect on the test results or interpretations made from the ANOSIMs performed using either 4 root transformed, untransformed or binary data. My analyses indicated significant spatial and temporal heterogeneity in the composition of the macrofaunal assemblages of these streams, as did the analyses I conducted with rare taxa included. In only two of the 44 tests I performed using 4th root quantitative data, one of the 44 tests on binary data, and four of the 44 performed using untransformed quantitative data, were the test results changed (i.e., acceptance or rejection of Ho) due to the elimination of rare taxa (Figure 5.3). Moreover, on average Global R and P values for all three data formats were virtually unchanged due to the elimination of rare taxa (Table 5.1).

~~Removal of rare taxa did not alter the P-value at all for 22 of the tests that used 4th root quantitative data, 21 that used binary data, and 19 that used untransformed data.~~

~~160 Chapter 5~~

~~4.5 20< • 3.5 15 3 • 10 2.5 i 24» 1.5 • «••»• • • -0.5 -0.4 -0.3 -0.2 -0.0.1 5 0 0.1 0.2 0.3 0.4 0.5 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0~~

~~> U c 3 O" • • 0) 1 1 1- A* b) -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5~~

~~2.5 25 20 f 1.5 15 10 5 0.5 1 • #_Ji4M -+ C) -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 Change in R value Change in P value~~

~~Figure 5.3: Thefrequency of change in the Global R-value and the P-value following~~

~~the elimination of rare taxa from 44 analysis of similarity tests conducted on a)~~

~~untransformed quantitative, b) 4th root transformed quantitative, and c) binary data~~

~~(presence or absence of taxa). Data were gained from sampling of benthic~~

~~macrofaunal communities of three temperate coastal streams in the Illawarra region of~~

~~New South Wales, Australia, over a two year period, 1997 to 1999. Rare taxa were~~

~~those taxa that represented less than 0.5% of the total number of individual~~

~~macroinvertebrates collected over the entire two years of sampling.~~

~~161 Chapter 5~~

~~Data Format Mean Change in R-value Mean Change in P-value~~

~~Untransformed -0.003 ± 0.074 0.013 ±0.050 4th Root Transformed -0.015 ±0.086 0.020 ± 0.075 Binary -0.013 ±0.095 0.006 ± 0.056~~

Table 5.1: Mean change and standard deviation in Global R-value and P-value's following the elimination of rare taxa from 44 analysis of similarity tests conducted on untransformed quantitative, 4th root transformed quantitative, and binary data. Data were gained from sampling of benthic macrofaunal communities of three temperate coastal streams in the Illawarra region of New South Wales, Australia, over a two year period, 1997 to 1999. Rare taxa were those taxa that represented less than 0.5% of the total number of individual macroinvertebrates collected over the entire two years of sampling.

~~5.4: Discussion~~

My analyses revealed that for a set of diverse benthic macrofaunal stream assemblages the elimination of rare taxa had little or no impact on multivariate hypothesis tests of community structure. Overall I found that the removal of 101 rare taxa, 82.2% of all taxa collected, had very little effect on either the Global R or P- values generated in 44 analysis of similarities tests for spatial and temporal variability. Only a few of the test results, rejection or acceptance of the null hypothesis, were changed by the removal of rare taxa.

Importantly, the outcome of the ANOSIM tests I conducted on quantitative data were not affected by data transformation. Removal of rare taxa from 4th root transformed quantitative data changed even fewer test outcomes than did their removal from the

162 Chapter 5 untransformed quantitative data set. My findings do not support Cao et al's (1999) assertion that similarity measures underweight rare taxa. I found that even after transformation, to reduce the influence of highly abundant taxa on the Bray-Curtis similarity measure, the removal of rare taxa had very little effect on the outcome of tests. Instead, my findings suggest, as Marchant (1999) found for ordinations, that rare taxa are redundant information in multivariate hypothesis tests.

~~Interestingly, the removal of rare taxa from the binary data set changed fewer of the test results than their removal from either of the quantitative data sets, challenging~~

~~Cao & Williams (1999) claim that "the effectiveness of binary data supports the importance of rare species". Clearly, my results strongly suggest just the opposite.~~

Although transformation to binary data gives all taxa equal weighting by ignoring their abundances, this does not necessarily mean that the removal of rare taxa from a binary data set will create a greater loss of information than their removal from quantitative data. I found that the use of binary data is as effective without rare taxa as it is with them, and the results and interpretation derived from binary data were the same as those I gained from quantitative data. On average rare taxa represented only a small portion of the total number of taxa collected in any one of my samples.

Therefore, the bulk of the binary information contained in each sample was still intact despite the removal of rare taxa. The rare taxa in this data set are surplus information in these analyses, regardless of the form of data used. This reflects for the elimination of rare taxa the findings of Pik et al. (1999) who found that lowering the level of taxonomic resolution used in analysis of similarities tests on untransformed, log transformed, and binary data had little effect on the outcome of the analyses

~~163 Chapter 5 performed. It appears that there are potentially several contexts in which some of the information in multivariate analyses may be redundant.~~

Clearly, my analyses have not considered all possible similarity measures or data transformations. Rather I have used similarity measures and transformations that are both commonly utilised on ecological data sets (Ter Braak 1995, Legendre &

Legendre 1998), and were appropriate for this particular data set. Many other data transformations and similarity measures, and their various combinations, are used on ecological data (Legendre & Legendre 1998). The effect of removing rare taxa from other transformation/similarity measure combinations may be different from those revealed here, and certainly warrant testing. However, to accurately quantify the effect of removing rare taxa such tests should be conducted on data for which the transformations and similarity measures used are appropriate.

The biological context of the question under consideration may negate the fact that rare taxa can be removed from analyses without any statistical effect. Here, removal of rare taxa has allowed me to determine that a relatively small group of the sampled taxa were responsible for the detected spatial and temporal heterogeneity among the communities of these streams. Without removing rare taxa from these analyses I would not have gained this understanding. Therefore, eliminating rare taxa from multivariate analyses is a simple and effective method of extracting underlying ecological patterns from complex community data sets. However, some of the rare taxa may be important, indeed perhaps vital to ecosystem function. For example, the removal of predators that are large and voracious consumers, yet are normally present only in low numbers, will be biologically illogical in comparisons of trophic structure.

~~164 Chapter 5~~

In this system Odonates were present only in low numbers and all eleven species present were classified as rare. However, were I to compare the trophic composition of these assemblages, the abundance of individual Odonate species would be a secondary consideration to their collective impact as one of the main invertebrate predators in this system. The biological context of the question under consideration must be paramount if meaningful ecological interpretations are to be made of such analyses (Underwood 1997b).

If the abundance of individual taxa is highly variable then defining a group of rare taxa may be difficult and relevant only to specific time periods. In the temperate stream system sampled here all taxa classified as rare remained rare throughout the study and the rare taxa group could therefore be confidently defined across the entire sampling period. This may not be true of ephemeral or more seasonally fluctuating systems. In freshwater ecosystems, such as those of northern Australia and the

~~Northern Hemisphere, seasonal changes can produce relatively large fluctuations in the type and abundance of species present in a community (Lake et al. 1986, Boulton~~

& Brook 1999). Defining a species as rare in this situation may be relative only to specific time periods, considerably complicating the issue of identifying a group of rare taxa. Although several definitions of "rare" have been utilised in studies of benthic macrofaunal communities (Marchant et al. 1985, Bunn et al. 1986, Growns &

Davis 1991, Marchant et al. 1997), I recommend that any definition make both biological and intuitive sense. Unfortunately, a single mathematical definition is unlikely to be useful across all systems. Here, the definition I have used separated taxa into core and rare groups as I would have expected from observations made during the sorting of samples. Those taxa I repeatedly encountered in large numbers

165 Chapter 5 in sample after sample ended up in the core taxa group. The mathematical definition applied was therefore appropriate in the context of these assemblages. Care should be taken to ensure that the definition of rarity utilised is applicable to the data set in question.

~~166 Chapter 6~~

~~Chapter 6 - Impact Assessment - Univariate and multivariate approaches.~~

~~167 Chapter 6~~

~~6.1: Introduction~~

The streams of the Illawarra have a relatively long history of modification by human activity. All five of the streams sampled in this study run through land mostly used for dairy farming. Subsequently, riparian vegetation has been removed along the majority of each streams course. Moreover, landowners in the area have on occasions modified sections of stream channel and pumped water out of the streams for irrigation purposes. Nevertheless, the sampling of benthic macrofaunal assemblages conducted in this and Gregory's (unpublished data) study, along with fish surveys and general observations made by both Gregory and the present author, indicate that these streams have a diverse and abundant freshwater biota (Refer to sections 2.2.5 & 2.2.6 of

Chapter 2 for details of the areas freshwater biota). However, the development of the area for residential housing has led to a vast increase in the scale of human activity along two of the study streams.

The physiochemical nature of an ecological system is often modified by inputs derived from human activity (Rosenberg & Resh 1993). If functioning correctly, the water pollution control ponds incorporated into the Horsley Park development should stop such modifications by stopping all surface runoff and associated pollutants from entering the adjacent streams. Importantly, if the ponds function correctly, I should not be able to detect any significant impact to the benthic macrofaunal assemblages at the four putatively impacted sites located below the outlet for each pond. For the

Beyond-BACI impact assessment technique used to design sampling in this study this would mean that the null hypothesis of no impact relative to the control sites would be retained. However, on several occasions I observed discharge flowing into Robin's

~~168 Chapter 6~~

Creek from the overflow outlet of the control ponds adjacent to this stream. This discharge appeared to contain suspended sediment. Moreover, during several flood events, particularly the major flood that occurred in August 1998, water from the control ponds may have overflown the retention banks and entered the adjacent stream. Therefore, an impact, if detected (i.e., rejection of the null hypothesis), will indicate not only that the control ponds have failed to retain all of the surface runoff from the development (which appears likely), but more importantly, that those inputs reaching the streams have affected the composition of the benthic macrofaunal assemblages at the putatively impacted sites. In this chapter I use univariate statistical analysis to assess whether an impact has occurred at the four putatively impacted sites. However, I do not use the originally intended analysis of variance as this approach was invalidated by the large amount of data missing for many creeks during the extended dry period.

Changes in the degree of variability exhibited by these assemblages may be a useful measure of impact. Interestingly, in this system, samples taken after a natural disturbance, a prolonged drought, exhibited substantially greater temporal variability than those taken prior to the drought (See Chapter 4). Ecologists have recently begun to focus on differences in variability among spatially or temporally separated communities as an informative descriptor of distributional patterns, rather than merely a statistical inconvenience in univariate analyses (Warwick & Clarke 1993, Smith

1994, Stewart-Oaten et al. 1995, Palmer et al. 1997). Furthermore, increased variability after anthropogenic disturbances have been documented in benthic marine communities (Warwick & Clarke 1993). The degree of post-disturbance temporal variability exhibited by an assemblage, relative to the level of pre-disturbance

169 Chapter 6 variability, may be a useful indication that an impact has occurred. Therefore, changes in the degree of variability among replicate temporal samples at putatively impacted sites, relative to the variability detected at control sites, may be a useful method of assessing whether human activities have impacted upon the composition of the assemblages sampled in this study. However, the univariate analysis of variance that underlies the impact assessment in this study does not account for changes over time in the type of taxa present at each site. Multivariate analysis techniques can account for such changes and have repeatedly proven to be more sensitive than univariate techniques when detecting changes in community composition induced by anthropogenic activities (Clarke 1993, Warwick & Clarke 1993, Clarke & Warwick

~~1994).~~

Initial investigation via non-Metric Multi-dimensional Scaling ordination plots indicated that the pattern of variability among temporal samples at three of the putatively impacted sites was consistent with that detected at the majority of control sites (Figure 6.1). I present these preliminary results here as they form an important part of the rational detailed below for the multivariate methodology I used to assess the impact of the Horsley Park development on the assemblages of the putatively impacted sites. Potentially, these preliminary results indicated that three of the putatively impacted sites displayed the same pattern of variability between pre and post-development periods as the control sites. The remaining putatively impacted site was an exception, with samples collected post-development being less variable than those taken pre-development. However, ordination plots do not provide an exact representation of the dissimilarities in the dissimilarity matrix that underlies the ordination (Clarke & Warwick 1994). Caution is therefore necessary when using

~~170 Chapter 6~~

ordination plots to judge differences among groups in the dispersion of samples. A comparative measure of the degree of dispersion among samples in two groups should therefore be based on the dissimilarities in the dissimilarity matrix that underlies the nMDS. The Index of Multivariate Dispersion (IMD) provides such a measure.

Here, I describe an extension of the logic behind the IMD and Beyond-BACI impact assessment designs that may be useful in determining whether an impact has occurred at putatively impacted sites. The following assumption underlies this approach. If an impacted has occurred, the assemblages of each putatively impacted site will exhibit greater variability among replicate temporal samples relative to control sites in the post-impact period than was detected in the pre-impact period. By utilising an IMD within the framework of a Beyond-BACI sampling design, variability in the relative abundance and type of taxa present among replicate samples can be compared between treatment and control sites. The rank dissimilarities calculated in the IMD among replicate samples within each group therefore represent a measure of temporal variability in the assemblages of each site. The use of multiple control sites allows a general measure of the background variability expected in the absence of an impact to be incorporated into the assessment. I am unaware of any previous attempts to approach impact assessment in the manner that I have formulated here.

~~In this chapter I also describe the macrofaunal assemblages of the sites sampled on~~

Robins and Reid Park Creeks. An impact, if one has occurred, will be determined as a difference in how the assemblages of the putatively impacted sites on these two streams have changed relative to the changes detected in the control assemblages.

~~Therefore, it is appropriate to rigorously describe the putatively impacted assemblages~~

171 Chapter 6 and, where appropriate, contrast their composition and how they change, particularly over time, against the assemblages of the three control streams rather than simply documenting the results of statistical tests for impact.

~~6.2: Methods~~

~~6.2.1: Description of the macrofaunal assemblages of Robin's and Reid Park~~

~~Creeks.~~

The theory and logic behind the Beyond-BACI impact assessment design utilised in this study were detailed in section 1.11 of Chapter 1. The sampling regime and details of field and laboratory procedures employed were set out in the Methods section of

Chapter 2. For reasons detailed in section 3.2.1 and further justified in Chapter 5, only the 20 most abundant taxa collected across the entire 4 years of sampling have been utilised to assess impacts in this chapter.

I used both qualitative and quantitative analyses and graphical techniques to describe the assemblages sampled from Robin's and Reid Park Creeks and how they change spatially and over time. I used Analysis of Similarity to test for spatial and temporal differences among the sampled assemblages and an Index of Multivariate Dispersion to compare the variability among replicate temporal samples between various time periods (i.e., between pre and post-development periods and pre and post-drought periods). I used non-Metric Multi-Dimensional Scaling to display pre and post- development samples in 2-dimensional multivariate space. A Bray-Curtis similarity measure was used for all Analysis of Similarity, Index of Multivariate Dispersion, and non-Metric Multi-dimensional Scaling analyses and all analyses were performed on

~~172 Chapter 6 untransformed quantitative, 4th root transformed quantitative, or presence or absence data.~~

~~6.2.2: Univariate impact assessment~~

The univariate analyses originally envisaged for this study were not appropriate due to several problems with the data set. An asymmetrical five-factored mixed model analysis of variance was the appropriate form of statistical analysis for the Beyond-

BACI design implemented (Gregory - unpublished data). However, dry spells during both the pre and post-development sampling meant that a large number of planned samples (15.5%) could not be taken (Appendix B). Data were "missing" at several scales, with samples from only a single site missing from some sampling events, while on other occasions a number of sites, often the majority of sites, were not sampled. Which sites could not be sampled differed among sampling events, while on one occasion (the third sampling event in summer 1993/94), no sites could be sampled at all (Appendix B).

~~The complex pattern of missing data meant that methods for dealing with missing single replicates or whole sets of replicates in Analysis of Variance designs (See~~

Sokal & Rohlf 1995 and Underwood 1997b), were not appropriate in this instance. In many cases data was missing from all three sites on a creek. Moreover, in the post- development period data were missing from eight sites for at least six sampling events in a row (Appendix B). It would be biologically illogical to generate means for statistical purposes for these prolonged periods when clearly no macrofauna existed.

~~Simply eliminating sampling events for which some, or even most of the data where missing meant the loss of an enormous of amount of information, and also caused the~~

173 Chapter 6 remaining design to be unbalanced between pre and post-development periods. I therefore sought statistical advice on how the putative impact could be assessed by either rearranging the ANOVA analysis, or via an alternative analysis technique.

~~The asymmetrical nature of the Beyond-BACI design meant that rearranging the~~

~~model via more traditional ANOVA designs was not possible. As the factor IMPACT~~

~~does not occur in both sampling periods, it would not be possible to calculate the~~

~~interaction between SAMPLING PERIOD and IMPACT, or any three or four factor~~

~~interactions containing the factor IMPACT. This would severely limit the ability of~~

~~such an analysis to determine whether an impact had occurred (Dr Ken Russell -~~

~~Statistical Consulting Service, Department of Mathematics and Applied Statistics,~~

~~University of Wollongong - pers. comm). Residual Maximum Likelihood (REML)~~

~~(Genstat 5 1993) was chosen as an appropriate form of analysis to address these~~

~~problems (Dr Ken Russell - pers.comm.).~~

~~REML, originally proposed by Patterson & Thompson (1971), allows variance~~

~~components to be estimated in linear mixed models (Genstat 5 1993). Linear models~~

~~also underlie the originally envisaged ANOVA analysis. As a mixed model, both~~

~~random and fixed effects can be dealt with in REML analyses, as is the case for~~

~~ANOVA. REML, unlike ANOVA however, can be used to analyse unbalanced linear~~

~~mixed models. The missing data in this study has, in effect, created an unbalanced~~

~~model and REML, therefore, represents a useful alternative form of analysis in the~~

~~present situation. Both a random and a fixed effects model were determined for the~~

~~present study and all analyses were performed on the total number of individuals~~

~~collected per site in each sampling event. Collective terms (i.e., reg.prd.long) are~~

174 Chapter 6 interactions (as in other linear models), with two, three, or four-factor interactions depending on the number of terms. As there is only one random factor, event (evt), the random model represents the effects of events within periods within regimes and the interaction of events with creek and longitude (Dr Ken Russell - pers.comm.). The models utilised were as follows:

~~Random model = reg.prd.evt + reg.prd.evt.crk + reg.prd.evt.long.~~

~~Fixed model = reg.prd + crk + long + reg.crk + reg.long + crk.long + reg.crk.long + reg.prd.crk + reg.prd.long + reg.prd. crk. long.~~

~~The terms used in the REML analysis are different from those used previously in this study and are listed below.~~

reg = REGIME (2 levels - pre or post-development) - fixed per = PERIOD (8 individual seasons within which sample dates were randomly chosen) - fixed ere = CREEK (5 levels) - fixed long = LONGITUDE (3 levels, nested within CREEK) - fixed eve = EVENT (3 levels nested within PERIOD) - random

Each of these terms corresponds to a level in the Beyond-BACI sampling design detailed in the Methods section of Chapter 2. However, for the purposes of the REML analysis the term LONGITUDE has been used to refer to the three sites sampled on each creek. This terminology derives from the fact that Gregory (unpublished) did not

~~175 Chapter 6 chose sites randomly on each creek. Rather, he chose sites that where roughly at the same longitude on each creek (Gregory - pers. comm.).~~

~~6.2.3: Multivariate impact assessment~~

~~Studies utilising the IMD to detect impacts have neglected to incorporate temporal variability in comparisons between control and impacted sites. Three of the studies~~

~~(Gee etal. 1985, Gray et al. 1990, Dawson-Sheperd et al. 1992,) initially used by~~

Warwick & Clarke (1993) to demonstrate the logic and calculation of the IMD, and subsequent studies that have utilised the IMD (Somerfield & Clarke 1997, Warwick et al. 1997), have no temporal replication of sampling. Although, the IMD and other analyses clearly demonstrate differences among the treatments and controls in these studies, they do so only at a single time. The potential for temporal variability in the composition of both the treatment and control samples is unaccounted for, and the conclusion of impact is therefore temporally confounded. The possibility of temporal confounding in these studies is analogous to the problems Underwood (1992, 1994a,

~~1994b) has repeatedly detailed for the original univariate BACI designs of Green~~

(1979) (See discussion of this topic in Chapter 1). However, the underlying logic of comparing the variability among two groups using the IMD remains sound despite this potential confounding. Extending the use of the IMD to compare variability among temporally replicated samples may provide a useful means of assessing whether anthropogenic influences have increased the variability in community composition at putatively impacted sites relative to control sites.

~~I used an Index of Multivariate Dispersion (Warwick & Clarke 1993) to compare the variability among replicate temporal samples taken at putatively impacted and control~~

176 Chapter 6 sites. Each of the four putatively impacted sites was individually compared to each of the eleven control sites. These comparisons were conducted separately for the pre and post-impact sampling periods. Eleven IMD statistics were therefore generated for each impacted site in the pre-impact period, and eleven in the post-impact period. To take into account spatial differences among control sites I calculated the mean IMD statistic for each impact site x period (pre or post) combination. I determined an impact to have occurred at a putatively impacted site if this mean IMD statistic was greater in the post-impact than the pre-impact period. I conducted all analyses on untransformed, 4th root transformed, and binary data.

I used the data from all 15 sites and for all available sampling events in both the pre and post-impact sampling periods. Replicate temporal samples were the centroid of three Hess samples taken at each site during each sampling event. The number of available temporal replicates varied among sites, with sampling events only included as a temporal replicate for a site if three Hess samples were taken during that sampling event. A Bray-Curtis similarity measure was used for both untransformed and 4th root transformed quantitative data, while a Sorenson's co-efficient was used for binary data. IMD statistics were calculated using the MVDISP program on the

~~PRIMER package (Clarke & Warwick 1994). I used non-metric Multidimensional~~

~~Scaling to display the relationship of impacted site replicates and control site replicates in 2-dimensional ordinations.~~

~~177 Chapter 6~~

~~6.3: Results~~

~~6.3.1: Composition and structure of the macrofaunal assemblages of Robin's and~~

~~Reid Park Creeks~~

The macrofaunal assemblages sampled in Robin's and Reid Park Creeks conformed to the general structural patterns I detected in the control assemblages. They consisted of a group of core taxa and a group of rarely sampled taxa as did the assemblages of the other three study streams. All core taxa detected in the control streams were also collected at each site on Robins and Reid Park Creeks with the exception of RC1 from which I did not collected either the large predator Stenosialis sp., or the leptophlebid mayfly Jappa kutera. A large portion of the total number of several core taxa collected during post-development sampling such as Ecnomus russellius,

~~Centroptilium sp., and nearly all Cheumatopsyche sp. were collected from Robin's~~

~~Creek Site 1 (Table 6.1). In Reid Park Creek several core taxa were collected in very low numbers. For example, only single specimens of Atalophlebia sp., J. kutera, and~~

~~Centroptilium sp. were collected during the entire study. Moreover, E.russellius, and all four core Dipteran taxa were collected in much lower numbers from Reid Park~~

~~Creek than they were from the other study streams.~~

Sites on Robin's Creek differed markedly in the number of individual macrofauna and the number and type of taxa collected. The number of individuals I collected at RC1 was more than ten and a half times the number collected at RC2, and over two and a half times that collected at RC3. Twenty eight of the 60 taxa collected at RC1 were not collected at RC2 or RC3 (Table 2.1). Only 5 of the taxa collected at RC2, and 6 collected at RC3, were not also collected at RC1 (Table 2.1). While almost all core taxa were collected from each site, several, Cheumatopsyche sp., Ecnomus russellius,

~~178 Chapter 6~~

Total number Percentage Taxa Family of individuals collected at collected at Robin's all sites Creek Site 1 Coleoptera Sternopricus wehnckei (a) Dytiscidae 25 68.0 Austrolimnus sp. 2 (1) Elmidae 30 96.7 Austrolimnus sp. 3 (a) Elmidae 24 100 Notriolus sp. 1 (a) Elmidae 41 97.6 Kingolus sp. 1 (a) Elmidae 87 98.8 Simsonia sp. (1) Elmidae 57 93.0 Scritid sp. (1) Scitidae 923 99.2 Trichoptera Oecetis sp. (1) Leptoceridae 246 65.9 Cheumatopsyche sp. (1) ** Hydropsychidae 973 98.8 Ecnomus russellius (1) ** Ecnomidae 984 46.3 Odonata Synthemis regina (n) Isosticidae 44 54.5 Diptera Simuliid sp. (1) Simuliidae 1248 95.4 Odontomyia sp. (1) Stratiomyidae 52 69.2 Arachnida Mite 4 (a) 1230 100 Orabatid sp. (a) Orabatidae 88 100 Mollusca Pisdium casertanum (a) ** Sphaeriidae 1439 28.7 Glyptophysa gibbosa (a) ** Physidae 3113 21.2 Platyhelmintb.es Turbellaria 226 54.0

~~Table 6.1: Taxa for which a large percentage of the total number of individuals~~

recorded across the entire study were collected from Robin's Creek Site 1. Samples were collected on 24 occasions between 1997 and 1999 from 3 sites on each of 5 streams in the Illawarra region of New South Wales. Letters in brackets after each

~~taxon indicates lifecycle stage: a = adult, 1 = larvae, and n = nymph. Double asterisks~~

~~(**) indicate core taxa.~~

~~179 Chapter 6~~

Berosus involutus, Pisidium casertanum, and Glyptophysa gibbosa, were markedly more abundant at RC1 than at the other two sites on this creek. However, the most numerous taxa collected in this study, the Chironominae, was only collected in relatively low numbers from RC1, with more than eleven and a half times the number of Chironominae collected at RC3, and almost twice as many at RC2. Analysis of similarity revealed significant differences among sites in both the number and type of taxa, and the presence or absence of taxa, during both pre and post-development sampling periods (Appendix E(e)).

A relatively small group of core taxa were largely responsible for differences among sites on Robin's Creek. The differences I detected among sites were mainly due to differences in the relative abundance of Stenosialis sp., Glyptophysa gibbosa,

~~Pisidium casertanum, Tasmanocoenis tillyardi, and the Chironominae and~~

Tanypodinae. However, a marked increase in the number of Cheumatopsyche sp. collected at RC1 during in the post-development period meant that this was the taxon most responsible for differences among sites during this period. Moreover, two other core taxa, Berosus involutus and Ecnomus russellius, were markedly more important in defining differences among sites in the post-development period than they were during the pre-development sampling.

The macrofaunal assemblages sampled at RC1 had a distinct composition when compared to other sites on the same creek and in comparison to all other sites sampled in this study. For several core and rare taxa, a large proportion of the total number of individuals recorded across all sites during post-development sampling were collected from RC1 (Table 6.1). This was particularly true of the Elmidae, with 90.5% of all

180 Chapter 6 elmids recorded throughout the post-development period collected from this single site. Three of the total often elmid species collected across all 15 sites were only collected from RC1 (Table 2.1) and for a further four elmid species more than 95% of all individuals were collected from this site (Table 6.1). The tangled willow root mat from which samples were collected at this site also appears to be an important habitat for several other taxa. The majority of Odontomyia sp., Turbellaria, Oecetis sp., all

~~Oribatid sp.2, and the unidentified Small Mite, were collected from this site (Table~~

~~6.1).~~

Fewer individuals and fewer taxa were collected from Reid Park Creek than from any other study stream. During almost all sampling events, fewer core individuals and fewer core taxa were collected from sites on Reid Park Creek from any other site

~~(Figure 2.7). Only three taxa, Liodessuspraelargus, Cheumatopsyche sp. AVI, and~~

~~Microvelia sp., all rare taxa recorded only as single specimens, were collected exclusively from Reid Park Creek (Table 2.1). The macrofaunal assemblages of Reid~~

~~Park Creek exhibited lower densities and were less diverse than those sampled on other study streams.~~

~~The same group of core taxa were largely responsible for differences among sites on~~

Reid Park Creek during both pre and post-development sampling. However, the importance of several taxa in defining among site differences changed between sampling periods. Analysis of similarity revealed significant differences among sites for 4th root transformed quantitative, and presence or absence data, during both the pre and post-development sampling periods (Appendix E(e)). Average dissimilarity figures from SIMPER analysis indicated that there was a greater degree of difference

181 Chapter 6 among sites during the post-development sampling period than during pre- development sampling. Differences among sites were mostly due to differences in the presence or absence, and the relative abundance, of Micronecta sp., Pisidium casertanum, Tasmanocoenis tilltardi, Berosus involutus, Paratya australiensis,

Triplectides australicus, and the Chironominae. However, during the post- development sampling period the Chironominae were substantially more important in defining among sites differences than they had been during the pre-development period. Moreover, the mollusc, Glyptophysa gibbosa, was important in defining differences among sites on this creek only in the post-development period.

~~6.3.2: Temporal variability in the composition of the macrofaunal assemblages of~~

~~Robin's and Reid Park Creeks~~

The type and number of core taxa collected, and the degree of variability among samples, differed between the two sampling periods. Ordination plots revealed varying amounts of overlap in the composition of core taxa collected in the pre and post-development sampling periods (Figure 6.1). However, RC1 was an exception, with complete separation of pre and post-development samples indicating a greater change in composition between sampling periods than was exhibited by other sites

(Figure 6.1(a)). Despite these overlaps, Analysis of Similarity revealed significant differences among pre and post-development periods at all sites for both 44 root transformed quantitative data, and for presence or absence data (Appendix E(e)).

Moreover, I found that all putatively impacted sites, other than RC1, exhibited greater variability among samples events during the post-development period for untransformed quantitative, 4th root quantitative, and presence and absence data

~~(Table 6.2).~~

~~182 Chapter 6~~

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~~183 Chapter 6~~

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~~Caption on next page...~~

~~184 Figure 6.1: non-Metric Multidimensional Scaling plots of 4 root transformed data from benthic macrofaunal samples taken pre and post-development at sites on Robin's~~

~~Creek and Reid Park Creek in the Illawarra region, New South Wales. Sampled sites were a) RC1, b) RC2, c) RC3, d) RP1, e) RP2 and, f) RP3, g) DC1, h) DC2, i) DC3, j)~~

MCI, k) MC2,1) MC3, m) MM1, n) MM2, o) MM3. RC1, RC2, RP1, and RP2 are putatively impacted sites, while all other sites are control sites. Pre-development sampling events (1993-1995) = a, and post-development sampling events (1997-1999)

~~= b. For each sampling event a multivariate centroid of the twenty most abundant taxa~~

~~(core taxa) sampled over the entire study was plotted. A Bray-Curtis similarity measure was used to construct similarity matrices. Chapter 6~~

~~Untransformed 4th root Site Binary data data transformed data RCl -0.241 0.615 0.763~~

~~RC2 -0.500 -0.623 -0.630~~

~~RP1 -0.377 -0.666 -0.702~~

~~RP2 -0.197 -0.367 -0.392 ...~~

~~Table 6.2: Index of Multivariate Dispersion values for comparison of pre and post- development sampling events for four putatively impacted sites on Robin's Creek and~~

Reid Park Creek in the Illawarra region of New South Wales. Data were the centroid of three Hess samples of benthic macrofauna collected from each site during 24 sampling occasions in each of the pre and post-development periods. The Index of

~~Multivariate Dispersion was calculated as per Warwick & Clarke (1993).~~

Only one of the putatively impacted sites exhibited a pattern of change between pre and post-development periods that was unlike that detected at the majority of control sites. I detected fewer core individuals, and fewer core taxa, during post-development sampling at three of the four putatively impacted sites, RC2 (Figure 6.2(2a & b)), and

~~RP1 and RP2 (Figure 6.2(4a & b, and 5a & b)), conforming to the general trend I detected at the majority of control sites (Figure 6.2(3a & 3b, 4a & 4b, 5a to 15a, and~~

5b to 15b)). However, this general trend was not evident for RCl, where I detected a greater number of core individuals and a greater number of core taxa during post- development sampling (Figure 6.2(1 a & b)). Furthermore, all four putatively impacted sites exhibited less variability in the number and type of core taxa collected than control sites in general, with RCl being the least variable of the 15 sites sampled during this study (Figure 6.3).

~~185 c T~~

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Figure 6.2: Mean number of a) core individuals and, b) core taxa collected per sampling event from sampling conducted between 1993 and 1995, and 1997 and 1999 in five streams in the Illawarra, New South Wales. 1) RCl, 2) RC2, 3) RC3, 4) RP1,

~~5) RP2, 6) RP3, 7) MCI, 8) MC2, 9) MC3, 10) DC1, 11) DC2, 12) DC3, 13) MM1,~~

~~14) MM2 and, 15) MM3. Each site was sampled on 45 separate occasions between~~

1993 and 1999, with three Hess samples taken on each occasion. Sampling events one to 21 were conducted between 1993 and 1995 by Gregory (unpublished data) prior to initiation of development at Horsley Park. Post-development samples, 22 to 45 (the present study), were collected between 1997 and 1999. Missing values are sampling events for which all three samples could not be taken due to a lack of water caused by drought conditions during both pre and post-development sampling periods. Error bars are one standard deviation either side of the mean.

~~191 Chapter 6~~

~~SfeS^i 9 10 11 12 13 14 15 16 17 18 19 20 21 Sampling Event~~

~~RC1 ^^RC2 RC3 -*-RP1 -*-RP2 -«-RP3 —<— MC1 MC2 MC3 DC1 DC2 DC3 MM1 MM2 MM3~~

~~•o 650 600 550 500 450 400 350 300 250 200 150 100 bj 50 0 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Sampling Event~~

~~192 Chapter 6~~

~~22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 Sampling Event~~

Figure 6.3: The total number of core individuals collected during a) pre-development and b) post-development sampling and the total number of core taxa collected during c) pre-development and d) post-development sampling from five streams in the Illawarra, New South Wales. Pre-development samples were collected between 1993 and 1995 by Gregory (unpublished data), while post-development samples were collected between 1995 and 1997. Putatively impacted sites - RCl, RC2, RP1, and RP2 - are represented by thickened lines. Due to the low number of core individuals collected from RP1 and RP2 during all sampling occasions in the pre-development period (less than 15 individuals per sampling event), the lines for these sites in graph b) are indistinguishable from those of other sites.

~~193 Chapter 6~~

~~The complex picture of differences among seasons I detected for Robin's and Reid~~

Park Creeks reflects my findings for the three control streams. For example, while the type and number of core taxa did not differ among seasons for the majority of year/site combinations for Robin's Creek (i.e., non-significant differences for 4th root transformed quantitative and presence or absence data), some year site combinations

(97-98 at RCl, and 95-96 at RC2), did show differences (Appendix E(b)). During these years at these sites differences among seasons were due to chances in the relative abundance of a similar set of core taxa (Appendix E(b)). I detected a similarly pattern for Reid Park Creek with differences dependent on the year/site combination being tested (Appendix E(b)).

A similar picture emerges when testing for differences among the same season across all four years of sampling, once again reflecting my findings for the three control streams. For the majority of season/site combinations seasons did not have a core macrofauna that was similar to that sampled in the same season during other sampling years (Appendix E(c)). However, for several season/site combinations I found no significant difference in the macrofauna collected across the four years of sampling

(Appendix E(c)). For the remaining season/site combinations (i.e., spring at RCl and autumn at RP1), although a similar set of core taxa were sampled across years (i.e., no significant difference in presence or absence), the relative abundance of these taxa was different from year to year.

On several occasions during post-development sampling the macrofaunal assemblages of sites on Robin's and Reid Park Creeks displayed similar decreases in abundance and diversity to those I detected at the majority of control sites (Figure 6.3). For

194 Chapter 6 example, a decline in both the number of core individuals and the number of core taxa collected was evident during winter 1997 at all sites sampled during this study (i.e., sampling event 28 - Figure 6.3(b & d)). Moreover, the number of both core individuals and core taxa declined drastically to be either very low, or zero, at most sites during the dry spell in summer 1997/98 and autumn 1998 (Figure 6.3(b & d).

However, RCl, the only site at which water flowed to some extent throughout the sampling period, did not experience the same marked decline in macrofaunal numbers displayed by other sites during this dry spell (Figure 6.3(b & d). Furthermore, as I found for the control streams, the number of both core individuals and core taxa were significantly different between pre and post-drought periods at most sites (Appendix

E(d)). Again, RCl was an exception, with differences between pre and post-drought periods apparent only in the relative abundance of core taxa (Appendix E(d)). Other than on the few occasions detailed above, I did not detect any similarity in the general trend of change over time displayed by the sampled sites (Figure 6.3). The trends identified above (for Figure 6.2 and 6.3) should be viewed with caution due to my inability to discount the effect of sampling variability in these graphs. However, the trends identified are one more form of evidence (of the many presented in this chapter) that RCl has changed over time in a manner that appears to be very different from the changes occurring at other sites.

~~6.3.3: Univariate Impact assessment - REML analysis~~

I was not able to use REML analysis to determine whether an impact had occurred at the four putatively impacted sites. For 25 of the 28 variables tested there were significant forth order interactions, and or a further variable there was a significant third order interaction (Table 6.3). Due to these interactions I was unable to test any

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s 00 oc oo 00 00 00 00 00 00 00 00 00 00 00 2M p p p p p p p p p p cu cu CU IH IM IH IH IH IH IH IH IH IH S l-H VH l-H IH ccj ca ca |H CJ 1 +J '<•••* P- p. s: a S3 PH 4) t o H-" o P.«" o — •V. is. | § CXH 'o •IH 1 TP <+H M-H C+H C+H 1 5 M-H M-H MH C+H 93 <+H .o TO ,o TO TO TO -o rg 1P CJ. Vi z Z Z Z Z Z Z Z Z Z cd 1Z 4> z z ?cl -fe S3 •TH U cu cu cu 4> CU cu CU cu 4) 4) CU 4) Si 4) 'o *5 "a! 2 "3 00 © © m © in p P O CN cd OVH cd © cu S3 £ V d P •n PH -2 r-> V cd T3 © OH IH T3 5 g M9 HH p 'o w GO •H ScS o O C+H sp "C O •a * cu S3 1 3 •2COP PH p p ^^ +-» .o o o c '« Z cd g cd i > * "e3 * *

© © V OH II * PH * e in 00 PH © © p *^"B! *"o^ 00 V OH ^I H p CO o o O T3 CU 1% Vi P s 13 O *o P o o X S cd •J +-» t5 2 IH 4> £O -3 TP3 C+H '5? GO C+H o cu GO o 'H • TH O •fHH +-ed> .cPd 4) cu C+sH T3 Chapter 6 other terms in the model which contained either REGIME, PERIOD, CREEK, or

LONGITUDE (Table 6.4). Therefore, no other terms in the model could be tested for these variables. The term of interest in a REML analysis, in this case IMPACT, should be placed last in the model. However, due to the unbalanced nature of the sampling design (i.e., IMPACT was not present in the pre-development period), this was not possible for this model. Therefore, as IMPACT first occurs in the third last term (Table 6.4), testing for an impact is confounded with the two terms (reg.crk.long and reg.prd.crk.long) below it in the model. As these terms were most often significant, there is no valid test for impact for this particular REML model.

~~6.3.4: Multivariate impact assessment~~

~~I found the pattern of variability among temporal samples at three of the putatively impacted sites to be consistent with that detected at the majority of control sites~~

~~(Table 6.5). I determined negative IMD statistics for all three data formats for RC2, and RP1 and RP2, as well as for seven of the eleven control sites (Table 6.5).~~

Variability among temporal samples was therefore greater in the post-development than in the pre- development period at each of these sites. The mean IMD across all eleven control sites was also negative for all three data formats (Table 6.6).

I found an inconsistent pattern among data formats at five sites, including the putatively impacted RC2. Each of these sites showed an individual pattern that was not consistent with the general trend of negative IMD values detailed above (Table

6.5). The majority of the positive IMD values determined at control sites were not substantially different from zero, indicating little difference in the degree of variability among samples in the pre and post-development periods at these sites.

~~199 Chapter 6~~

Term in REML model Degrees of Freedom reg 1 reg.prd 14 crk 4 long 2 reg.crk 4 reg.long 2 crk. long 8 reg.prd. crk 53 reg.prd.long 28 imp 1 crk. imp 1 long.imp 1 crk.long.imp 1 reg.crk.long 4 reg.prd.crk.long 98

~~Table 6.4: Residual Maximum Likelihood modelfitted t o assess impact at four putatively impacted sites on temperate coastal streams in the Illawarra, New South~~

~~Wales. Two sites were on Robin's Creek, and two on Reid Park Creek. Full terms for the abbreviations used are given in section 6.2.2.~~

~~200 Chapter 6~~

Site Index of Multivariate Dispersion Untransformed 4th Root Binary Robins Creek 1 -0.241 0.615 0.763 2 -0.500 -0.623 -0.630 3 -0.170 -0.457 -0.549 Reid Park Creek 1 -0.377 -0.666 -0.702 2 -0.197 -0.367 -0.392 3 -0.293 -0.675 -0.711 Mullet Creek 1 0.038 -0.094 -0.177 2 0.083 0.051 0.086 3 -0.293 -0.528 -0.500 Duck Creek 1 -0.268 -0.343 -0.237 2 0.122 0.038 0.079 3 -0.062 -0.297 -0.414 Marshall Mount 1 -0.358 -0.594 -0.666 2 0.191 -0.147 -0.333 3 -0.380 -0.496 -0.530

Table 6.5: Index of Multivariate Dispersion for untransformed quantitative data, 4 root transformed quantitative data, and binary data calculated between pre and post- impact sampling periods for 15 sites sampled in five streams in the Illawarra, New

South Wales. The IMD statistics for the four putatively impacted sites are in bold type. The mean IMD statistic for the 11 control sites were: untransformed quantitative data = -0.126 ± 0.208, 4th root transformed quantitative data = -0.322 ± 0.253, binary data = -0.359 ± 0.273. Data used were the centroid of three samples of the benthic macrofauna taken from each site during 24 sampling occasions in each of the pre and post-development periods. The Index of Multivariate Dispersion was calculated as per

~~Warwick & Clarke (1993) using the PRIMER statistical software package.~~

~~201 Chapter 6~~

Pre-impact Post-impact RCl Untransformed -0.367 ± 0.298 -0.370 ± 0.205 4th Root Transformed 0.180±0.311 -0.669 ±0.177 Binary Data 0.412 ±0.322 -0.646 ±0.197 RC2 Untransformed -0.227 ±0.201 0.137 ±0.200 4th Root Transformed -0.111 ±0.286 -0.261 ± 0.204 Binary Data -0.003 ± 0.385 0.293 ± 0.230 RP1 Untransformed -0.178 ±0.199 0.091 ±0.188 4th Root Transformed -0.005 ± 0.282 0.377 ±0.218 Binary Data 0.119 ±0.365 0.447 ± 0.233 RP2 Untransformed 0.099 ±0.194 0.190 ±0.172 4th Root Transformed 0.432 ±0.218 0.461 ±0.161 Binary Data 0.530 ± 0.257 0.515 ±0.179

Table 6.6: Mean and standard deviation of the Index of Multivariate Dispersion for untransformed quantitative data, 4 root transformed quantitative data, and binary data calculated between four putatively impacted and eleven control sites sampled in five streams in the Illawarra, New South Wales. The Index of Multivariate Dispersion

(MD) was calculated between each putatively impacted site and control site combination, giving eleven IMD statistics for each putatively impacted site. Data used were the centroid of three samples of the benthic macrofauna taken from each site during each of 24 sampling occasions. The Index of Multivariate Dispersion was calculated as per Warwick & Clarke (1993) using the PRIMER statistical software package.

~~202 Chapter 6~~

Only RCl displayed IMD values (4th root and binary data) that were both positive and substantial (i.e., close to +1), indicating greater variability among pre-development than among post-development samples. However, the IMD values for this site were inconsistent across the three data formats (Table 6.5). The IMD value for untransformed data was negative, pointing to greater post-impact variability (Table

6.6). Transformation of the data removed the influence several highly abundant genera were having on the similarity measures among post-development samples at this site. I used SIMPER (PRIMER - Clarke & Warwick 1994) to determine that the influential genera in the post-development period were Cheumatopsyche

~~(Trichoptera), Glyptopyhsa (Mollusca), and Pisidium (Mollusca).~~

~~I found that three of the putatively impacted sites exhibited greater variability, relative to control sites, in the post-development period. I detected an increase in the mean~~

IMD values from the pre to post-development period for RC2, and for RP1 and RP2 th (Table 6.6). This increase was reflected in all three data formats, except for 4 root transformed quantitative data for RC2, and binary data for RP2, where the mean IMD value decreased in the post-development period. However, for RCl the mean IMD for all three data formats decreased from the pre to post-development period. This indicated that the assemblages I sampled at this site were less variable than the control sites in the post-development period. Therefore, the pattern of variability for this site was the opposite of that detected at the other putatively impacted sites.

~~203 Chapter 6~~

~~6.4: Discussion~~

~~6.4.1: Overview~~

The results of this study highlight the difficulties inherent in detecting human impacts in spatially and temporally dynamic stream systems. Indeed, the extreme climatic fluctuations experienced during the study invalidated the univariate approaches to impact assessment I attempted to use here. The multivariate statistical analysis I performed did not provide evidence that an impact had or had not occurred. Rather, differences in the degree of temporal variability exhibited by putatively impacted and control sites appear to reflect differences in substratum composition and the dramatic variability in climatic conditions and water flow that occurred during post- development sampling. Moreover, a substratum such as that present at RCl, a submerged willow root mat, may be inappropriate to use as a putatively impacted site, particularly if increased sedimentation is a likely impact. The multivariate impact assessment methodology I have used here has advantages over past impact assessment using the IMD and may also be useful where pre-impact additivity is a problem for univariate impact assessments. However, the methodology has several limitations.

~~6.4.2: Univariate impact assessment~~

The unbalanced nature of the sampling design meant that I could not validly test for an impact using REML analysis. The factor IMPACT was not present during both sampling periods, therefore a appropriate REML model that allowed an unconfounded test for impact could not be fitted. Obviously, fitting a statistical analysis model to a design a posteriori is not an optimal practice. However, performing a priori planned

204 Chapter 6 statistical analyses on data that do notfit the assumptions of the model or are unsuitable for other reasons is also invalid (Sokal & Rolf 1995). The complicated pattern of missing samples in both pre and post-development periods effectively unbalanced the envisaged Analysis of Variance. I was not able to identify a rearrangement of the Analysis of Variance model that was both statistically and biologically valid. Nevertheless, although I could not detect an impact via statistically justifiable univariate techniques, I could not positively conclude that an impact had not occurred.

~~6.4.3: Multivariate impact assessment~~

The findings of the qualitative and multivariate analyses conducted in this study do not provide evidence of an impact. The affect of climatic fluctuations, flow variability, and substratum differences cannot be ruled out as contributing to the observed differences in variability between putatively impacted and control sites.

Importantly, all sites, both putatively impacted and control, display the same general trend: that macrofaunal compositions were most variable during the sampling period in which flow and water level fluctuations were also the greatest.

Three of the four putatively impacted sites changed over time in a manner that was similar to the control sites. Post-development samples at RC2, RP1, and RP2 contained fewer core individuals, fewer core taxa, and exhibited greater variability among post than among pre-development sampling events, as was the case at the majority of control sites. The time course of changes to these assemblages was not substantially different from that I detected at control sites although the IMD analysis I performed indicated that variability in macrofaunal composition had increased,

~~205 Chapter 6 relative to control sites, at each of these three sites in the post-development period.~~

~~This increase in the magnitude of variability between these sites and the control sites in the post-development period cannot be taken to indicate an impact.~~

I cannot rule out that substantial differences between these three putatively impacted sites and the control sites in the type of substratum present were not responsible for the greater variability detected at these sites. In Chapter 3 I found that different types of substrata supported different macrofaunal assemblages. RC2 had a fine, silty mud substratum containing large amounts of decaying vegetation (i.e., branches and twigs of varying sizes), while RP1 and RP2 both had clay substrata. These substrata differ substantially from the sand or cobble substrata of the control creeks. I cannot discount the possibility that the assemblages of these substrata exhibit different degrees of variability over time. The increased variability displayed by these assemblages in the post-development period could be related to such differences.

The differences apparent between RCl and all other sites do not indicate that an impact occurred at this site. This was the only site for which the composition of the sampled macrofaunal assemblage was substantially more variable in the pre than in the post-development period. Moreover, there was less variability in the number of core individuals and core taxa collected during post-development sampling at this site than at any other sampled site. Unlike the other putatively impacted sites, multivariate analysis indicated that the degree of variability in macrofaunal composition at this site was less similar to and lower than that displayed by the control sites during the post- development period than it had been during pre-development. This decrease in variability relative to control sites does not meet the criteria set out earlier as

206 Chapter 6 indicating an impact (i.e., an increase in variability relative to control sites). Rather, the importance of flow rate and water level variability in structuring the macrofaunal assemblages of these streams is again emphasised.

~~Changes detected at RCl at first appear to be an exception to the general trends displayed at other sites. However, variability in macrofaunal composition over time at~~

RCl was greatest during the period in which water level fluctuations were greatest, as was the case for the other three putatively impacted sites and the control sites. Unlike all other sites RCl experienced the most dramatic flow variability in the pre- development sampling period. Robin's Creek Site 1 is the only site that is spring fed, and subsequently the only site that retained flowing water through out the dry spell in

1997/98. The macrofaunal assemblages of this site experienced less variability in flow and water levels during post-development sampling than during pre-development sampling when this site did dry up completely for several months. Therefore, the findings for RCl do not represent an anomaly to the findings detected at all other sites. Furthermore, they give no indication that the observed changes were caused by surface runoff entering the streams from the Horsley Park housing development.

~~Rather, they once again emphasis that macrofaunal variability in this system appears to be strongly influenced by flow rate and water level fluctuations.~~

~~6.4.4: Assessing impacts using the proposed multivariate methodology~~

There are several advantages to using the IMD under the framework proposed here compared to the use of the IMD in previous impact assessments. Most notably, the comparisons conducted here incorporate temporal variability at two levels, among temporal replicates within each site, and between pre and post-impact sampling

~~207 Chapter 6 periods. Previous studies utilising the IMD (Warwick & Clarke 1993, Somerfield &~~

Clarke 1997, Warwick et al. 1997), have failed to incorporate any temporal variability into their assessment of impact. The inclusion of temporal replication ensures that any differences in variability between treatments and controls are not merely an artefact of a single sampling occasion. Similarly, incorporating comparisons to multiple control sites ensures that variability at the putatively impacted site is compared to background variability across several similar ecological units (e.g., across several streams).

~~The IMD may be useful in situations where non-additivity between treatment and controls occurs in the pre-impact period. Non-additivity occurs in BACI and Beyond-~~

BACI designs when either the treatment and controls show different patterns of change over time in the pre-impact period (trend non-additivity), or the same pattern is exhibited but the degree of variability differs among sites (scale non-additivity)

(Smith et al. 1993). Either form of non-additivity may invalidate comparison between changes from pre to post-impact periods, increasing the chance of falsely concluding an impact has occurred. Unfortunately, it is possible for non-additivity to occur even when sites are carefully chosen, particularly in previously unstudied systems. There is no way to transform trend non-additivity, while transformations can deal with the problem of scale non-additivity (Smith et al. 1993). Comparison of variability via the

IMD methodology employed in this chapter does not assume and is not affected by non-additivity in the pre-impact period. This methodology has two advantages if trend non-additivity is present. Firstly, comparison of the degree of variability among each possible treatment and control site combination may uncover revealing biological patterns (i.e., treatments may be more variable than sites on particular streams but not others). Secondly, even though trend non-additivity is present, the treatment sites may

~~208 Chapter 6 have been impacted upon. Confidence in the detection of a significant impact may be lowered for a univariate analysis of variance due to the existence of non-additivity~~

(Smith et al. 1993). The IMD methodology utilised here can be used as a complimentary impact assessment in such a case, providing an assessment that is unaffected by trend non-additivity. However, several problems potentially limit the use of the IMD to determine impacts.

The IMD does not provide a statistical framework within which to make decisions regarding the presence or absence of an impact (Warwick & Clarke 1993). This is true even for the more complex format in which the IMD has been utilised in this study.

The IMD does not provide the ability to determine the magnitude of any change in variability, nor to relate this change to a biologically relevant effect size or change in composition. Due to these shortcomings the conclusions drawn regarding an impact must be treated with appropriate caution. While an increase in variability was detected at three of the putatively impacted sites, the IMD provides no means of judging whether these increases were substantial enough that they indicate a significant change to the assemblages of these sites relative to the changes occurring to control assemblages. Moreover, there appears to be no appropriate way of testing for a statistically significant difference between two mean IMD scores. The assumptions derlying tests for differences between two means are invalidated here by the un ltiple use of the putatively impacted site data in the impact site x control site mul comparisons (i.e., comparisons are not independent). To conclude with confidence that an impact had occurred it would be ideal to detect not only an increase in the mean IMD at a site relative to the control sites, but also, to determine that any increase was statistically significant. The use of the IMD to assess impacts in either

209 Chapter 6 the simple format proposed by Warwick & Clarke 1993, or the more complex format proposed here, may at best be semi-quantitative, allowing only a limited ability to conclude that an impact has occurred.

Several other issues potentially limit the usefulness of the IMD for impact assessments in streams. In this chapter I considered sampling events as random within pre or post-development periods. However, to accurately account for temporal variability in running waters, and indeed in any ecological system, sampling may need to be allocated to random dates within more relevant, shorter temporal periods

(Underwood 1994a, 1994b). Variability in the composition of macrofaunal stream assemblages may follow seasonal patterns (Allan 1995), or, maybe determined by fluctuations in flow levels (Boulton & Lake (1992a). Allocation of sampling to temporal periods of durations longer than those over which differences in variability are actually occurring will not fully quantify temporal changes in community composition. The simplistic IMD methodology utilised here can not account for temporal variability, or indeed spatial variability, that may be partitioned among several hierarchical levels.

The assumption that an impact occurs only as in increase in the level of variability ignores the potential range of biological effects a putative impact may have. Some pollutants, particularly those creating acidic water conditions, have been repeatedly shown to decrease the diversity of benthic macrofaunal communities in streams

(Madarish & Kimmel 2000). A restricted number of taxa are present in such communities (mainly Chironomids), with turnover in composition occurring in the relative abundance of the few taxa present rather than, as may be expected in

210 Chapter 6 unpolluted communities, in both the number and type of taxa present (Hall 1994). It is reasonable to speculate that temporal variability could be reduced in a pollution restricted community in comparison to more diverse, unpolluted communities in similar streams. This would be particular evident in binary data, where only taxonomic changes in composition are accounted for. As the IMD does not include any measure of differences in composition between groups, comparison of such a community to normal or background variability at control sites would reveal only a reduction in variability at the putatively impacted site in the post- development period.

~~A reduction in variability would not constitute an impact via the logic used in the present study. Yet, clearly an impact would have occurred. In a univariate Beyond-~~

BACI design this impact would be detected as a change in the time course of the mean number of taxa in the post-impact period at the putatively impacted site relative to that detected at the control sites. The direction of change is not implicated, only that a "change", relative to background variability, has occurred. Similar arguments may be made regarding spatial variability. Although, Warwick & Clarke (1993) have repeatedly found pollutants in marine environments increase the variability among spatially separated samples, this does not discount the possibility that other systems react in a different manner. Clearly, the presumption that human induced impacts to ecological systems are only detectable as an increase in variability should not be universally applied.

~~211 Chapter 7~~

~~Chapter 7 - General Discussion~~

~~212 Chapter 7~~

~~7.1: Overview~~

~~This study successfully documented the diverse and dynamic benthic macrofauna of mid-channel sections of pool habitats in temperate coastal streams of the Illawarra,~~

New South Wales. I was also able to test a range of hypotheses that revealed that these assemblages were highly variable both spatially and temporally. Furthermore, a drying event, which occurred during the 1997/98 drought, presented a fortuitous opportunity to quantify the affects of flow cessation and drying on benthic macrofaunal assemblages. Multivariate analysis and hypothesis testing techniques proved extremely useful for detecting and describing patterns of change in the large, complex data set gained from the rigorous quantitative sampling conducted in this study. However, I was not able to quantify whether the construction of the Horsley

~~Park housing development had impacted upon the macrofaunal assemblages of these streams, emphasising the difficulty of detecting impacts in highly variable systems.~~

Nevertheless, the results of this study do have implications for the future management and conservation of macrofaunal assemblages in the coastal streams of the Illawarra and New South Wales in general.

The findings of this study represent an important demonstration of fine scale variability in temperate Australian streams. Importantly, I detected significant variability among the macrofaunal assemblages of pool habitats at local spatial scales, within and among adjacent streams. These findings add to previous studies to further suggest that the composition of macrofaunal assemblages in Australian streams is highly variable among different habitats and among and within similar habitats

~~(Downes et al. 1993, Marchant et al. 1999). Such spatial variability is not unexpected given that variability within and among benthic assemblages has been repeatedly~~

213 Chapter 7 documented infreshwater systems worldwide (Palmer et al. 1997). However, quantitative sampling of benthic macrofaunal assemblages at such a fine spatial scale in Australia is rare (Downes et al. 1993, Marchant et al. 1999). Therefore, this study adds to the growing body of evidence that, like stream assemblages worldwide, the macrofaunal assemblages of Australian streams exhibit highly variable distributions at fine spatial scales.

The composition of the assemblages I sampled was one commonly detected for macrofaunal assemblages. Interestingly, all of the assemblages that I sampled displayed a similar basic structure. Each assemblage consisted of a relatively small group of highly abundant and regularly sampled taxa (core taxa) and a much more diverse group of taxa that were only ever sampled in low numbers (rare taxa). The majority of families collected here have cosmopolitan distributions and aquatic insects dominated these assemblages, with the vast majority of the collected taxa and individuals being insects. The most structurally complex physical habitats sampled here, cobbles and willow root-mats, contained the most taxonomically diverse and numerous macrofaunal assemblages. Such findings are typical of benthic macrofaunal assemblages worldwide (Hynes 1970, Palmer et al. 1997, Marchant 1999, Biesel et al.

~~2000) and the assemblages I sampled are therefore unremarkable in their composition or structure.~~

The macrofauna of the Ulawarra's streams are more diverse than is indicated here. I sampled only mid-channel sections of pools of depths up to 40cm and relatively coarse levels of taxonomic resolution were used for several groups, most notably the

~~Chironominae. Pool habitats are generally found to be less diverse habitats than riffles~~

~~214 Chapter 7~~

(Logan & Brooker 1983). Furthermore, these streams contain a range of habitats yet to be sampled (i.e., escarpment headwaters, macrophyte stands). Indeed, sampling by undergraduate students under my supervision in sections of the study streams only 50 metres below several of the sites sampled in this study collected macrofauna that were not recorded at any time during this study. Clearly, the overall diversity of benthic macrofauna in the Ulawarra's streams remains to be documented.

~~7.2: Scale and the factors influencing the stream macrofauna of the~~

~~Illawarra~~

~~The findings of this study suggest that the structure of the sampled macrofaunal assemblages was influenced by factors working at several spatial and temporal scales.~~

~~Recognition of the scale dependence of both patterns and processes is an important focus in the study of ecological systems (Levin 1986, 1992, Cooper et al. 1998,~~

~~Underwood & Chapman 1998). Peaks in density occurred at different times in the same creek suggesting that site-specific processes were responsible for each peak.~~

Flooding, which has no detectable long-term affect on the sampled assemblages, represented a regional influence caused by the interaction of local topography and climatic conditions. The broad scale influence of the El Nino weather anomaly, which affects all continents and landmasses bordering the Pacific Ocean, was also apparent

~~(the effects of drying are discussed in detail below).~~

Unfortunately, in the present study I am limited to making suggestions as to the influences responsible for the observed patterns. This study was mensurative rather than manipulative and can not draw conclusions regarding causal relationships for the observed patterns. This is a major limitation of the study. While I have been able to

215 Chapter 7 rigorously describe patterns I am not able to draw conclusions from these findings that substantially advances our knowledge of the processes responsible for the complex distributional patterns repeatedly documented for the macrofaunal assemblages of streams and clearly apparent in these streams. The extent of sampling necessary in the Beyond-BACI impact assessment design used here limited my ability to perform smaller manipulative experiments to further investigate some of the patterns uncovered. However, the stream systems of the Illawarra are excellent systems in which to perform manipulative experiments. They are narrow, shallow streams, contain a diverse fauna, a number of potential impacts, and the entire longitudinal gradient of each stream, from headwaters to discharge point, is present over a relatively short distance. These interesting streams would be useful sites for future sampling and particularly experimentation to uncover the processes underlying the complex distributional patterns documented in this study.

On the basis of this study I caution against assuming that the patterns detected at the community level are applicable to all constituents of the community. This study determined that some insect orders display distributional patterns that are scale dependent in this system. Furthermore, the patterns of variability detected for these orders did not necessarily reflect the variability detected for the whole assemblage.

Clearly, we can not assume that all elements of a community show similar patterns of spatial variability, or that these patterns are the same irrespective of the scale at which mpling is conducted. Moreover, it may be equally as important to recognise that sa: within a particular spatial scale elements of the community may be responding even to the same processes in different ways, or each group may be responding to

~~216 Chapter 7 completely different influences from other groups. Recognition of these possibilities adds to the already complex picture of macrofaunal distribution.~~

~~7.3: The affect of drying~~

~~The timing of naturally occurring disturbance events can rarely be predicted.~~

Consequently, well replicated pre-disturbance data is often unavailable, even when the onset of the disturbance occurs over a prolonged period, as is the case when streams dry up during droughts. As Townsend (1989) notes, utilising opportunities such as the unexpected occurrence of a disturbance during sampling is important if we are to understand the dynamics of ecological communities and the role disturbance plays in structuring these communities. The present study therefore represented an unusual and important opportunity to quantitatively document changes in the composition of macrofaunal assemblages induced by a severe and prolonged natural disturbance. Importantly, spatial and temporally replicated quantitative pre- disturbance data allowed a rigorous assessment of how macrofaunal composition changed during flow cessation and the eventual complete drying of many sites.

~~Moreover, sampling continued for nine months after water returned to these streams, allowing assessment of how temporal variability in the sampled assemblages was affected by drying.~~

The 1997/98 El Nino event strongly influenced the structure of benthic macrofaunal assemblages in coastal streams of the Illawarra (Refer to Chapter 4 for a detailed account of the changes that occurred). As detailed in Chapter 4 the changes in composition that occurred were once again not unexpected. Air-breathing taxa and taxa adapted to low oxygen, stagnant conditions survived in the drying pools that

217 Chapter 7 remained throughout the drought at some sites. Most gill-breathing taxa disappeared from samples as soon as flow ceased. These are hardly surprising changes for the fauna of running water systems that have lost all flowing water.

Importantly however, the findings of this study suggest that these assemblages display long-term resilience to the drastic changes induced by drying. This is perhaps the most interesting finding of this study as I am not aware of previous studies that have documented resilience to drying episodes, although resilience to the affects of flooding is well documented (Boulton & Lake 1992a). Over the nine months during which sampling was conducted after the return of water the composition of the sampled assemblages gradually returned to one similar to that detected prior to drying. The sampled macrofaunal assemblages displayed a relatively stable long-term structure and appear to be well adapted to drying episodes, which in these systems represent a severe form of disturbance that occurs at irregular intervals and with a variable magnitude.

These findings further suggest that the intermittent streams of Australia's east coast may contain a macrofauna that is well adapted to surviving the drying associated with severe El Nino events. El Nino events substantially affect rainfall and stream discharge levels along Australia's eastern coast (Bryant 1985, Allan et al. 1996).

~~Enfield (1992) suggests that a pattern of inter-annual occurrence of El Nino events~~

(i.e., every 2 to 5 years) has existed for at least 5000 years and possibly for much longer (geological records are ambiguous regarding this issue beyond 5000 years before the present). Clearly, eastern Australia has been exposed to the low precipitation and at times severe drought conditions induced by these irregularly

218 Chapter 7 timed climatic anomalies for a substantial period of time. The findings of this study and those of Boulton & Lake (1992a & 1992b) suggest that the macrofauna of intermittent streams are well adapted to surviving sporadic periods of drying.

~~Furthermore, the present study suggests that even severe and extended drying may have little long-term effect on the basic structure of these assemblages.~~

~~7.4: Impact Assessment~~

I was not able to statistically determine whether the Horsley Park housing development impacted upon the benthic macrofauna of the four putatively impacted sites. The intended analysis was not statistically or biologically justifiable due to the large number and complex arrangement of missing replicates. This does not indicate a weakness in the design and analysis technique chosen for this sampling program.

~~Rather, my inability to detect an impact emphasises the difficulties inherent in detecting impacts in highly variable systems and further underscores the importance of rigorous sampling designs.~~

Beyond-BACI impact assessment designs are logical models with which to design spatially and temporally complex impact assessments (Underwood 1997b). The emphasis such designs place on the spatial independence of sampling sites is a particularly important consideration when designing impact assessments in running waters (Underwood 1991, 1992, Stewart-Oaten & Bence 2001). Furthermore, the flexibility of asymmetrical Beyond-BACI models allowed Gregory (unpublished data) to fit a rigorous design to the unusual situation confronted by this study, the replication of the putative impact on two streams. Replication of the same putative impact is rare (Underwood 1991, 1994a) and I am not aware of any other study that

219 Chapter 7 has had the opportunity to measure the affect of independent and replicated putative impacts. It is therefore unfortunate that I was not able to complete the analysis intended for the asymmetrical five-factored mixed model analysis of variance used to conduct sampling in this study. This analysis would have presented an interesting opportunity to assess the performance of such complicated multi-factorial models when applied to highly variable ecological communities.

The multivariate impact assessment technique I formulated was not able to detect an impact. By attempting to formulate such a technique I aimed to combine the advantages of multivariate analyses and Beyond-BACI impact assessment designs. As discussed in Chapter 6 the technique I formulated has many limitations and further work to identify possible solutions to these limitations is warranted. At present, multi factorial models such as Beyond-BACI remain the most logical basis for the design of spatially and temporally unconfounded impact assessments (Underwood 1997a,

1997b). However, potential impacts may change the type of macrofauna present in a community as well as changing the number of individuals and/or the number of taxa present. Moreover, the degree of variability displayed by a macrofaunal assemblage may change due to the impact of human activities (Warwick & Clarke 1993).

Attempts to formulate multi-factorial designs that utilise multivariate data sets that can account for such changes may provide more accurate assessments of the affect of human activities on ecological communities than are presently available. The recent work of Anderson (2001) and McArdle & Anderson (2001) suggests that such designs and analysis techniques may soon be available.

~~220 Chapter 7~~

~~7.5: Conservation Implications~~

Although I was unable to determine whether an impact had occurred, the findings of this study do have implications for the management and conservation of streams in the Illawarra region. Many human activities detrimentally impact upon streams and their biota (Cullen & Lake 1995, Richter et al. 1997, Postel 2000). The need for restoration and conservation of freshwater ecosystems, many of which are subject to growing levels of anthropogenic activity, has been widely recognised (Cullen & Lake

1995, Finlayson & Rea 1999, Walsh 2000). This need is emphasised by the recognition that freshwater biota are proportionately more vulnerable to extinction than terrestrial biota (Richter et al. 1997). Chessman & Williams (1999) identified the expansion of urban development as the major threat to waterways in western Sydney,

~~90km to the northwest of the present study area. A similar expansion of urban development is occurring not only in the Illawarra but also in many areas of coastal~~

~~New South Wales. Minimising the affect of this expanding urban development is therefore vitally important if the biological health of coastal streams in New South~~

~~Wales is to be maintained.~~

Habitat degradation and destruction is one of the main threats to running water systems (Allan & Flecker 1993, Cullen & Lake 1995, Richter et al. 1997). Habitats may be destroyed by natural or human induced physical alterations that completely eliminate a particular habitat (i.e., severe damage by flood waters or channel modifications by mechanical means). Sedimentation may reduce the structural complexity of heterogeneous habitats, destroying or degrading habitat quality

~~(Metzeling et al. 1995). Macrophyte communities add structural complexity to stream habitats (Allan 1995). If macrophyte communities are detrimentally affected by~~

221 Chapter 7 pollutants the structural complexity of particular habitats may be reduced. The findings of this study suggest that maintaining structural complexity and habitat diversity is an important goal for future management of the Ulawarra's streams.

Substratum heterogeneity exerted a strong influence on macrofaunal distribution in these streams. The substantial influence habitat heterogeneity exerts on the number and diversity of organisms present in ecological communities has long been recognised (MacArther & MacArther 1961, Levin 1976). The number and diversity of macrofauna in stream habitats generally increases as the degree of physical habitat heterogeneity increases (Cooper et al. 1997, Beisel et al. 2000, Cardinale et al. 2002).

In this system physically heterogeneous cobble substrata supported a more numerous and diverse set of macrofauna than sand, mud, or clay substrata. Importantly, at least a few taxa from each of these substratum types were not detected on other substrata.

Differences in substrata within and among streams and the range of substratum types present appear to be responsible at least in some part for maintaining macrofaunal diversity in this system. Obviously, many other factors may be important in maintaining macrofaunal diversity in a stream. However, substratum heterogeneity was the only substantial and readily observable difference among the sampled sites and therefore the only one about which conclusions can be drawn. The findings of this study suggest that to maintain a diverse macrofauna in the pools of these streams the diversity of substratum types present should also be maintained. Furthermore, pools represent only one type of habitat in the coastal streams of the Illawarra. Conserving macrofaunal diversity at the whole creek scale requires the maintenance of a range of habitat types as well as maintaining differences in structural complexity within each of these habitat types.

~~222 Chapter 7~~

These goals can be achieved through minimising the amount of surface runoff reaching the streams adjacent to future developments. Minimising the input of sediments and pollutants into these streams is an important goal for future development in the area. This objective is the desired effect of the water pollution control ponds included in stage 1 of the Horsley Park development. The impact assessment conducted here was not able to determine whether these ponds had or had not stopped surface runoff from the development from impacting upon the macrofauna of adjacent streams. However, the findings of this study do indicate that maintaining habitat diversity and structural complexity is an important means of conserving macrofaunal diversity in these streams. The inclusion of control ponds in all future development in the West Dapto area is an essential method of containing surface runoff and minimising its impact on the biology and hydrology of adjacent streams. Unfortunately, this study did not shed light on the suitability of the design of the control ponds used at Horsley Park in achieving these objectives. Other means will have to be sort to assess the efficiency of different control pond designs. Those that retain the maximum amount of surface runoff, sediment and pollutants, and minimise overflow during flood events will be the most suitable.

Retaining natural flow regimes and minimising impediments to flow may also be important in maintaining the health of coastal streams. Impediments to flow, such as weirs and dams, may alter the morphology of stream channels and restrict natural flow regimes. Chessman & Williams (1999) found that deep pools had formed below a weir on the Hawksbury-Nepean River in western Sydney, replacing the riffle-pool sequence that had existed prior to the weirs construction. The detrimental affects on stream hydrology (Thorns & Walker 1992, Walker & Thorns 1993, Maheshwari et al.

~~223 Chapter 7~~

~~1995), and ecology (Finlayson et al. 1994, Gehrke et al. 1995, Cullen et al. 1996,~~

~~Boulton et al. 1999) of the severe impediments to flow on many regulated rivers in~~

Australia are well documented. Flood waters mobilise sediments, promoting erosion and deposition and maintaining channel form, substratum, and habitat diversity in the coastal streams of the Illawarra (Nanson & Young 1981a & 1981b, Nanson & Hean

1985). High flows may also flush accumulated sediments and debris from stream channels onto flood plains or into the lagoons into which they discharge. Ensuring minimal impediment to water flow in these streams will allow naturally variable flow regimes to maintain substratum heterogeneity and habitat diversity. Maintaining these physical stream qualities is a simple method of promoting macrofaunal diversity in these streams and a worthwhile goal for efforts to minimise the impact of future urban development in the Illawarra.

~~224 References~~

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~~Appendix A~~

~~Macroinvertebrate identification keys used in this study.~~

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Smith B J. 1996. Identification key to the families and genera of bivalves and gastropod Molluscs found in Australian inland waters. Identification Guide No. 6. Cooperative Research Centre for Freshwater Ecology, Albury.

St Clair R.M. 1997. Preliminary guide to the identification of late instar larvae of Australian Philorheithridae, Calamoceratidae and Helicopsychidae (Insecta: Trichoptera). Identification Guide No. 12. Cooperative Reseach Centre for Freshwater Ecology, Albury.

Suter P.J. 1997. Preliminary guide to the identification of nymphs of Australian Baetid Mayflies (Insecta: Ephemeroptera) found in flowing waters. Identification Guide No. 14. Cooperative Research Centre for Freshwater

~~Ecology, Albury.~~

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~~Suter P.J. 1999a. Illustrated Key to the Australian Caenid nymphs (Ephemeroptera: Caenidae). Identification Guide No. 23. Cooperative Research Centre for Freshwater Ecology, Albury.~~

~~Watson J.A.L, Theischinger G, and Abbey H.M. 1991. The Australian Dragonflies: A guide to the identification, distribution, and habitats of Australian Odonata. CSIRO Australia, Canberra.~~

Watts C. 1998. Preliminary Guide to the identification of adult and larval Dytiscidae and adult aquatic Hydophilidae (Insecta: Coleoptera). Identification Guide No. 19. Co-operative Research Centre for Freshwater Ecology, Albury.

~~Wells A. 1997. A preliminary guide to the identification of larval Hydroptilidae (Insecta: Trichoptera). Identification Guide No. 13. Co-operative Research Centre for Freshwater Ecology, Albury.~~

~~Yule C 1997. Identification guide to the Stonefly nymphs of New South Wales & northern Victoria. Australian Water Technologies, Sydney.~~

~~257 Appendix B~~

~~Appendix B~~

^easo"& Robin's Reid Mullet Duck Marshall H Sampling n Park Mount Event "ate o 12 3 No. 12 3 12 3 12 3 12 3 Pre-development Sampling Period > 1 25/5/93 !JL3 3 3 3 3 3 3 3 3 3 3 3 3 45 | 2 27/5/93 3~~3~1 3~~3~1 ~3 3 3 45 3 3/6/93 [T1 3~T"~3 3~^T^ 1 3 3 45 3 3 1

~~a 4 20/8/93 3 3 3 3 | 3 | 3 3 | 3 | 3 3 3 3 3 | 3 | 3 1—l 45 VO vo~~

~~VO Vi 5 20/10/93 3 3 3 3 | 3 | 3 3 | 3 | 3 3 3 3 3 | 3 | 3 45 •a 6 8/11/93 3"T1 r~3~~3 3~^ 3 1 3 3 45 «5a" FT1 7 23/11/93 r~r^3 3 3 3 T~T~3 ~3 3 3 45 3~T~1~~

~~v. 8 19/1/94 3 3 3 3~M~3 3 | 3 | 3 3 | 3 | 3 36 c 9 21/2/94 3~ 3 ~3 3~1~^ •ffl ~3 3 3 42~~

~~> 10 12/4/94 3 3 3 3 | 3 | 3 3 | 3 | 3 3 | 3 | 3 45 e 11 14/4/93 3~~3~~3 1 3 3 45 e 3 FT1 3 12 27/4/94 3~~3~1} 3"T1 3 3 3 ~3 3 3 45~~

-£ 13 10/6/94 3 3 3 3 | 3 | 3 3 | 3 | 3 3 | 3 | 3 45 5" 14 7/7/94 3~~r~3 3 3 3 1 3 3 45 T". FT1 •r vo 15 17/7/94 3 3 3 ~3 3 3 45 -u I—• VO 16 12/9/94 3 313 3 [ 3 | 3 | 3 | 3 | 3 3| | 3 | 3 42 vO C/) •o 3~~3~~3 ~3 3 3 27 3 17 25/10/94 r 3| M 18 1/11/94 r 31 FT^ llPP 21

~~3 | 3 | 3 U 3 | 3 | 3 24 19 12/1/95 s 3 3 J 2 20 2/2/95 FT7 3 3 3 1 3 3 42 3 FT 3 _ _ 21 20/2/95 3"T"3 3 ~3 ~3 1 3 3 45 3~T1~~

~~Post-development Sampling Period~~

~~333 333 333 333 333 45 > 1 11/3/97 c 2 8/5/97 FTT T"~3~T TXT~ TTT i 3 3 45 3 ss 3 20/5/97 3 3 3" ~3 3 T ~3 3~T ~3~~T~ "1 3 3 45 ve ve~~

~~258 Appendix B~~

Seasc>n & Robin's Reid Sampling Mullet Duck Marshall H Event Date Park Mount No. 12 3 o 1 2 3 1 2 3 12 3 12 3 »H> 4 3 11/6/97 3 3 3 3 3 3 3 45 3 5 ——-L 2_JLJL J_ J~l 1 1 1 T»* 29/7/97 45 ni 3_ 6 25/8/97 L_LJ_ j_j__L ]L~^~ ~ ^~~ l~iri 45 3 3 3 3 3 3 ~T~T~ l-"!" "3 3 3 Vi 7 14/10/97 "O 3_^_ 3 3 3 3 3 3 3 3 3 3 3 3 3 45 2_ 8 29/10/97 3_J_1 3~X^ 3~~^3 3 3~~3 45 1—' 3 3 3 3 VO no 9 28/11/97 2~1T~2 3 3 3 43 -VJO 3"T1 ryi N* VO CB 10 12/1/98 1 3 3 19 oVeO c | 11 6/2/98 2 3 3 18 * 12 24/2/98 3 3 3 20

~~> 13 1/4/98 I 3 ^^^H p 12 I 14 24/4/98 3 ~r ^^^H Bj 18 i 15 8/5/98 27~~

«- 16 10/6/98 3 3 3 3 3 3 3 3 3 36 | 17 13/8/98 ym 3~X^ 3~~3 3 3 3 3 45 VO "* 18 27/8/98 3~~~3 3~~3~~3 3 3 3 45 VO 3 3 3 00 3 | 3 ~ VO 19 15/9/98 3 | 3 | 3 45 VO Vi 3 3 3 vo •a 3 20 20/10/98 3~T1 3~1T^ 45 JO 21 11/11/98 2~X~2 3~X~3 3 3 3 43

~~? 22 18/12/98 3 | 3 | 3 | 3 | 3 | 3 3 3 3 3 3 3 45 | 23 6/2/99 3 3 3 3 3 3 3 | 3 3 3 3 39 * 24 17/2/99 3 3^ 3 3 3 3 3 3 B 3 3 3 42~~

Appendix B: Number of samples taken in 45 sampling events conducted at 15 sites acrossfive streams in the Illawarra, New South Wales, between 1993 and 1999. Blackened cells indicate that no samples were taken. Lightly shaded cells highlight occasions on which more than zero but less than three samples were taken. All samples were taken using a Hess Sampler and three sampling events were randomly allocated to dates within each season. The pre-development sample matrix is reproduced here with modifications from Gregory (unpublished data).

~~259 Appendix C~~

~~Appendix C~~

Quantitat tive Data Binary Data Untransformed 4tn Root Transformed Rare taxa Rare taxa Rare taxa Rare taxa Rare taxa Rare taxa included removed included removed included removed R P R P R P R P R P R P a) MC 0.096 0.002 0.093 0.004 0.161 0.000 0.164 0.000 0.158 0.000 0.159 0.000 DC 0.155 0.002 0.124 0.003 0.134 0.000 0.112 0.001 0.407 0.000 0.069 0.014 MM 0.254 0.000 0.254 0.000 0.197 0.000 0.166 0.000 0.129 0.000 0.078 0.003

~~b) 0.418 0.000 0.408 0.000 0.387 0.000 0.314 0.000 0.317 0.000 0.183 0.000~~

c) 1 0.465 0.004 0.473 0.004 0.506 0.004 0.556 0.004 0.403 0.004 0.514 0.004 2 0.440 0.046 0.407 0.054 0.358 0.025 0.342 0.043 0.379 0.011 0.325 0.014 3 0.226 0.139 0.185 0.193 0.514 0.021 0.457 0.032 0.490 0.018 0.391 0.029 4 0.379 0.054 0.346 0.079 0.564 0.004 0.630 0.007 0.551 0.004 0.605 0.004 5 0.457 0.043 0.424 0.057 0.687 0.021 0.753 0.011 0.634 0.025 0.700 0.018 6 0.251 0.057 0.259 0.054 0.506 0.007 0.440 0.014 0.551 0.007 0.461 0.011 7 0.802 0.011 0.819 0.011 0.770 0.004 0.794 0.004 0.741 0.004 0.761 0.004 8 0.745 0.004 0.695 0.004 0.638 0.004 0.580 0.004 0.605 0.004 0.444 0.007 9 0.136 0.229 0.152 0.221 0.416 0.014 0.366 0.021 0.465 0.004 0.403 0.004 17 0.235 0.089 0.374 0.061 0.136 0.211 0.333 0.111 0.049 0.346 0.218 0.164 19 0.671 0.029 0.679 0.021 0.646 0.007 0.646 0.011 0.354 0.007 0.354 0.029 20 0.305 0.071 0.296 0.082 0.111 0.214 0.078 0.293 -0.016 0.500 -0.037 0.593 21 0.671 0.004 0.654 0.004 0.481 0.011 0.362 0.025 0.387 0.014 0 136 0.207 22 0.416 0.014 0.416 0.014 0.366 0.007 0.366 0.007 0.272 0.039 0.333 0.007 23 0.497 0.025 0.034 0.454 0.456 0.018 0.361 0.079 0.551 0.014 0.476 0.036 24 0.306 0.107 0.224 0.182 0.116 0.279 0.374 0.043 0.197 0.196 0.333 0.089

d) MCI 0.441 0.000 0.409 0.000 0.432 0.000 0.415 0.000 0.406 0.000 0.386 0.000 MC2 0.661 0.000 0.667 0.000 0.625 0.000 0.622 0.000 0.573 0.000 0.556 0.000 MC3 0.772 0.000 0.772 0.000 0.754 0.000 0.744 0.000 0.668 0.000 0.639 0.000 DC1 0.527 0.000 0.496 0.000 0.671 0.000 0.648 0.000 0.675 0.000 0.651 0.000 DC2 0.506 0.000 0.497 0.000 0.602 0.000 0.593 0.000 0.549 0.000 0.543 0.000 DC3 0.507 0.000 0.438 0.000 0.589 0.000 0.530 0.000 0.552 0.000 0.475 0.000 MM1 0.630 0.000 0.618 0.000 0.507 0.000 0.492 0.000 0.406 0.000 0.377 0.000 MM2 0.591 0.000 0.589 0.000 0.586 0.000 0.602 0.000 0.471 0.000 0.471 0.000 MM3 0.813 0.000 0.747 0.000 0.881 0.000 0.796 0.000 0.800 0.000 0.695 0.000 e) MC 0.208 0.000 0.403 0.000 0.250 0.000 0.277 0.000 0.226 0.000 0.260 0.000 DC 0.257 0.001 0.252 0.001 0.333 0.000 0.350 0.000 0.302 0.000 0.306 0.000 MM 0.205 0.000 0.202 0.001 0.309 0.000 0.304 0.000 0.286 0.000 0.268 0.000 f) -0.024 -0.008 -0.042 MCI -0.022 0.568 -0.036 0.682 0.003 0.427 0.621 0.506 0.756 0.381 0.004 0.387 0.003 0.401 0.003 MC2 0.201 0.036 0.203 0.035 0.355 0.005 0.218 0.005 0.222 0.002 0.221 0.002 MC3 0 040 0.223 0.0333 0.247 0.218 0.005 0.001 0.468 0.002 0.519 0.001 0.450 0.003 DC1 0 252 0.030 0.219 0.039 0.539 0.286 0.000 0.310 0.001 0.250 0.002 1 0.286 0.001 DC2 0.047 0.204 0.054 0.190

~~260 Appendix C~~

DC3 0.144 0.036 0.029 0.255 0.343 0.000 0.148 0.027 0.333 0.000 0.183 0.010 MM1 0.265 0.011 0.248 0.014 0.304 0.001 0.283 0.002 0.274 0.004 0.232 0.008 MM2 0.227 0.008 0.225 0.007 0.350 0.000 0.407 0.000 0.246 0.003 0.276 0.002 MM3 0.057 0.118 0.058 0.122 0.179 0.001 0.197 0.009 0.204 0.005 0.225 0.003

R) MC 0.175 0.017 0.168 0.017 0.277 0.000 0.286 0.001 0.235 0.000 0.238 0.000 DC 0.076 0.159 0.030 0.297 0.344 0.000 0.289 0.000 0.281 0.000 0.194 0.007 MM 0.174 0.015 0.173 0.016 0.294 0.001 0.361 0.000 0.177 0.011 0.268 0.002

~~Appendix C: Global R and P values generated from 44 analysis of similarities tests~~

~~performed on untransformed, 4th root transformed quantitative data, and binary data.~~

~~Data were generated by sampling the benthic macrofaunal communities of three~~

~~temperate coastal streams in the Illawarra region of New South Wales, Australia, over~~

~~a two year period, 1995 to 1997. Due to the prevalence of significant results (p = <~~

~~0.05), non-significant results (p = > 0.05) are indicated in bold type. Shaded cells~~

~~indicate tests conducted without rare taxa for which the result (acceptance or rejection~~

~~of Ho) differed from the result for the same test conducted with rare taxa. Letters a to~~

~~h indicate the spatial or temporal test configuration, a = among sites on an individual~~

~~creeks,creeks b for= among each creeks,sampling c event= among individually, d =~~

~~among sampling events for each site, e = among sampling events for each creek, f=~~

~~between years (the first and second years of sampling) for each site, and g = between~~

~~years for each creek. MC = Mullet Creek, DC = Duck Creek, MM = Marshall Mount~~

~~Creek, and the numbers 1, 2 and 3 after creek abbreviations indicate site numbers.~~

~~Data was not sufficient to test among creeks for all sampling events. The sampling~~

~~events for which tests among creeks were performed are indicated by a number in~~

~~section (c), which corresponds to the sampling events listed for post-development data~~

~~set in Appendix B.~~

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