Distribution of Foraminifera and sediments from

Twofold Bay, Eden, New South Wales.

Lyndsay Dean

A thesis submitted in partial fulfilment of the requirements for the degree of

Bachelor of Science (Honours)

Research School of Earth Sciences

The Australian National University

October 2011

i

Declaration

All research presented in this thesis is my own, except where otherwise acknowledged.

Lyndsay Dean

October 27, 2011

Natural cave in Edrom Bay, southern Twofold Bay, Eden.

ii

Acknowledgements

First of all, I extend my heartfelt thanks and gratitude to my supervisor, Patrick

De Deckker. This past year has been a steep learning curve, but your guidance and

support have been unwavering. Thank you for the dinner parties, anecdotes, books,

surprise presents and the many, many opportunities you’ve provided me. Your

confidence in my abilities makes me have confidence in myself. I have no idea how a

country girl ended up studying marine micropalaeontology, but it’s undoubtedly in no

small part because of you.

A massive thank you must also go to Jenny Robb, Arthur Robb, Syd Donaldson

and everyone at the South Coast Marine Discovery Centre in Eden. Without your

generous supply of time, boats and enthusiasm, this project would not have been possible.

Thanks also to Sheree Epe, Ray Tynan, Matthew Proctor and Anne Felton for their

supply of local knowledge and willingness to chase endless bits of information for me.

Thank you also to Andrew Kiss (ADFA) for loan of the grab sampler, Shane

Paxton for the wet splitter, and Graham Nash, Claire Thompson, Michael Ellwood and

Steve Eggins for their generous supplies of equipment, support and suggestions

throughout the year. Thanks also to the Australian Hydrographic Service for GeoTIFF

maps, to Sam Eggins for his help in the field, to Joy McDermid and Maree Coldrick for

being the office ladies from heaven, and to my lab support crew – Judith Shelly and Luna

Brentegani – for being my encyclopaedias of lab techniques, foraminiferal identifications

and general nerdy questions. To the amazing Matthew Lendrum and the extraordinary

Kelly Strzepek, there are not enough baked goods in the world to show my appreciation

for your proofing prowess. I don’t know why you willingly took the job on, but boy am I

glad you did. Huge thanks also to my friends – particularly Anthony, Ellen, Gemma,

Jamie, Kate, Leah, Tom, Pikey, and the entire Greenway gang – for your support, forced

social contact, and earnest attempts to comprehend what the heck I was studying.

Finally, to my family. Thank you for all the tech-support, for listening to my

thesis neuroses, for unquestioningly lugging my laptop and plethora of books on every

family trip this year, for giving me the time and space to write, and for constantly

providing food, beverage and general distractions, regardless of whether I wanted them or

not. You guys mean the world to me and I am so, so lucky to have you.

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Abstract

The assessment of marine environmental conditions is a basic prerequisite for the

development and implementation of viable coastal preservation and management plans.

A detailed preliminary study of Twofold Bay (Eden, NSW) was conducted to gather

baseline information on foraminiferal compositions and to determine local foraminiferal

distribution patterns. This was performed in order to gain an understanding of the active

processes within the bay, delineate areas subject to natural environmental stress, and

identify pressures from anthropogenic activities.

Sedimentological and foraminiferal analyses were conducted on 19 surficial

sediment samples collected throughout the bay, and abiotic data gathered from

representative bottom water at each sample station. To identify areas of similar traits

statistical analyses were applied to each dataset. The results were then combined to

provide an overview of the active processes and environmental condition of the bay. A

total of 162 foraminiferal species, 156 benthonic and 6 planktonic, have been recognised

in the open embayment of Twofold Bay. Fauna was found to be diverse and displayed a

high degree of similarity. Four sedimentary associations were identified, with their

distribution linked to a range of hydrographic effects including tidal and fluvial action,

shoaling and strong intermittent oceanic currents. Three geographically restricted

biotopes were identified: the Inner Bay Biotope, the Outer Bay Biotope, and the Harbour

Biotope. Foraminiferal compositions in these biotopes were found to be correlated with

substrate type and related to the degree of mixing and energy experienced at the

sediment-water interface. Fluvio-marine mixing in the bay’s entrance, low sedimentation

in the eastern part of the bay and low-energy environments in Eden Harbour strongly

influenced faunal populations. Anthropogenic effects were minimal, concentrated in the

marine ports of Snug Cove, Cattle Bay and Quarantine Bay. The northern region of

Twofold Bay was identified as being subject to considerable environmental stress due to

poor circulation and, as such, requires further investigation.

This study successfully provides a baseline of foraminiferal compositions within

Twofold Bay and explores ecologic controls over their distributions. A list of

recommendations for future research is also provided.

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CONTENTS Chapter 1: A Review and Thesis Objectives .......................................................... 1

1.1 Preamble ................................................................................................................. 1 1.2 Introduction to foraminifera in the earth sciences .................................................. 1

1.2.1 Multivariate analysis in ecological studies ................................................. 4 1.3 Thesis objectives..................................................................................................... 5 1.4 Previous distribution studies of benthonic foraminifera in coastal environments.. 5

1.4.1 Biotopes of benthonic foraminifera ............................................................ 7 1.5 Previous studies at Twofold Bay ............................................................................ 9

Chapter 2: Field Area – Twofold Bay ...................................................................... 10

2.1 General.................................................................................................................. 10 2.2 Industrial history ................................................................................................... 11 2.3 Climate.................................................................................................................. 12 2.4 Hydrology ............................................................................................................. 13 2.5 Oceanographic setting........................................................................................... 15 2.6 Sediments.............................................................................................................. 17 2.7 Recent meteorological events ............................................................................... 18

Chapter 3: Study Methods and Rationale.............................................................. 19

3.1 Sample collection.................................................................................................. 19 3.2 Sample preparation and analysis........................................................................... 21

3.2.1 Abiotic parameters of water...................................................................... 21 3.2.2 Sediment ................................................................................................... 22 3.2.3 Foraminifera.............................................................................................. 23

3.2.3.1 Foraminiferal density ........................................................................ 24 3.2.3.2 Cluster analysis ................................................................................. 25 3.2.3.3 Wall structure.................................................................................... 25 3.2.3.4 Association scores............................................................................. 25 3.2.3.5 Species diversity ............................................................................... 26

3.3 Rationale ............................................................................................................... 26 Chapter 4: Results ....................................................................................................... 29

4.1 Abiotic parameters ................................................................................................ 29 4.2 Sedimentological study......................................................................................... 32 4.3 Foraminifera.......................................................................................................... 33

Chapter 5: Discussion ................................................................................................ 40

5.1 Abiotic facies ........................................................................................................ 40 5.2 Sedimentary facies ................................................................................................ 41

5.2.1 Association A: Very Fine–Fine Sand ....................................................... 42 5.2.2 Association B: Fine–Medium Sand .......................................................... 43 5.2.3 Association C: Medium–Very Coarse Sand ............................................. 43 5.2.4 Association D: Medium Sand ................................................................... 44

5.3 General distribution of total foraminiferal populations ........................................ 45 5.4 Foraminiferal biotopes .......................................................................................... 52

5.4.1 Inner Bay Biotope – Elphidium advenum................................................. 54 5.4.2 Outer Bay Biotope – Lamellodiscorbus sp. 1 ........................................... 55

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5.4.3 Harbour Biotope – Elphidium advenum var. 1 ......................................... 56 Chapter 6: Conclusions and Recommendations ................................................ 60

6.1 Conclusions........................................................................................................... 60 6.2 Recommendations for further research................................................................. 63

References ..................................................................................................................... 67 APPENDICES ................................................................................................................ 81 Appendix 3.1..................................................................................................................... 82 Appendix 4.1..................................................................................................................... 83 Appendix 4.2..................................................................................................................... 84 Appendix 4.3..................................................................................................................... 86 Appendix 4.4..................................................................................................................... 87 Appendix 4.5..................................................................................................................... 88 Appendix 4.6......................................................................................................... CD-ROM Appendix 4.7......................................................................................................... CD-ROM Appendix 4.8......................................................................................................... CD-ROM

vi

LIST OF TABLES

Table 1.1 ............................................................................................................................. 3 Table 2.1 ........................................................................................................................... 13 Table 2.2 ........................................................................................................................... 15 Table 4.1 ........................................................................................................................... 36 Table 4.2 ........................................................................................................................... 38 Table 4.3 ........................................................................................................................... 39 Table 4.4 ........................................................................................................................... 39

LIST OF FIGURES

Figure 2.1 .......................................................................................................................... 10 Figure 2.2 .......................................................................................................................... 13 Figure 2.3 .......................................................................................................................... 14 Figure 2.4 .......................................................................................................................... 15 Figure 2.5 .......................................................................................................................... 16 Figure 2.6 .......................................................................................................................... 17 Figure 3.1 .......................................................................................................................... 20 Figure 3.2 .......................................................................................................................... 21 Figure 3.3 .......................................................................................................................... 22 Figure 3.4 .......................................................................................................................... 23 Figure 3.5 .......................................................................................................................... 24 Figure 4.1 .......................................................................................................................... 30 Figure 4.2 .......................................................................................................................... 30 Figure 4.3 .......................................................................................................................... 31 Figure 4.4 .......................................................................................................................... 32 Figure 4.5 .......................................................................................................................... 33 Figure 4.6 .......................................................................................................................... 34 Figure 4.7 .......................................................................................................................... 35 Figure 4.8 .......................................................................................................................... 35 Figure 4.9 .......................................................................................................................... 35 Figure 4.10 ........................................................................................................................ 36 Figure 4.11 ........................................................................................................................ 36 Figure 4.12 ........................................................................................................................ 38 Figure 5.1 .......................................................................................................................... 42 Figure 5.2 .......................................................................................................................... 45 Figure 5.3 .......................................................................................................................... 46 Figure 5.4 .......................................................................................................................... 48 Figure 5.5 .......................................................................................................................... 52 Figure 5.6 .......................................................................................................................... 53 Figure 5.7 .......................................................................................................................... 53 Figure 5.8 .......................................................................................................................... 57

1

Chapter 1: A Review and Thesis Objectives

1.1 Preamble

Coastal areas have traditionally been places for human settlement and the

development of industry; however, such activities often result in the degradation of

nearshore ecosystems. With the burgeoning awareness of environmental health, ways to

effectively detect pollution and monitor coastal environments over time are continuously

being sought. Single-celled organisms called foraminifera are widely used as

environmental bioindicators because individual species are known to inhabit defined

niches and habitats. Foraminifera display higher environmental sensitivity than almost

any other group of organisms, with distribution limited by factors such as substrate type,

elevation relative to the sediment surface, nutrient flux, temperature, salinity and

anthropogenic contamination (Scott, 1976; Alve, 1995; Yassini and Jones, 1995;

Hayward et al., 1997b; Horton and Murray, 2007). Despite these well established

controls, it is increasingly becoming evident that foraminifera do not follow ubiquitous

distribution patterns and responses to environmental parameters vary both temporally and

spatially (Albani, 1978; Murray, 2006).

It is crucial to build up a localised knowledge of how foraminiferal populations

are comprised and distributed before effective environmental monitoring can be

undertaken. Foraminiferal studies on the south-east Australian coastline are sparse with

large regions unexplored. Due to the economic significance of several areas on this

coastline, it is extremely important to build up knowledge of how environmental factors

affect foraminifera. Localised ecologic studies are crucial in determining the effects of

environmental parameters on foraminiferal composition and distribution, for these are the

baseline studies which will refine the application of benthonic foraminifera as

bioindicators in Australian coastal environments.

1.2 Introduction to foraminifera in the earth sciences

Foraminifera are single celled organisms which live predominantly in the marine

environment and constitute the most diverse group of shelled microfauna in modern

2

oceans (Sen Gupta and Machain-Castillo, 1993; Goldstein, 1999). Three main groups of

foraminifera are recognized based on habitat: those that live freely in the water column

(planktonic); those that live atop or attached to substrates (benthonic); and those that

dwell within the sediment itself (infaunal benthonic). Nearly all foraminifera possess a

test or shell that encompasses the organism and separates it from the surrounding water

mass. These tests may be organic, agglutinated (constructed of foreign particles and

cemented together by the organism), or comprised of calcium carbonate (CaCO3). Once

foraminifera have completed gametogenesis or die, their empty tests accumulate on the

seafloor. The number, diversity and preservation of these tests is widely utilized for a

range of environmental studies within estuarine and nearshore settings (see reviews in

Murray, 1991; and Haslett, 2002).

Benthonic foraminifera possess several key characteristics which make them

attractive environmental indicators: (1) they have short life spans and occupy specific

niches, making them sensitive to environmental conditions; (2) they are commonly well

preserved in sedimentary records; (3) they are widely distributed, yet relatively immobile;

and (4) they live on and within the sediment, which receives and stores many pollutants.

Consequently, foraminifera can be affected to a greater degree than plankton or nekton

(Yanko et al., 1994). Furthermore, they are (5) taxonomically diverse and evolve quickly,

(6) small, abundant and easily sampled, and therefore cost effective, and (7) stress-

tolerant species are often among the last organisms to disappear completely from heavily

contaminated sites (Schafer, 2000).

Benthonic foraminifera have traditionally been used for stratigraphic control,

hydrocarbon exploration and as palaeoecological indicators (Table 1.1); however, most of

these applications employ isolated species. Total foraminiferal assemblages are largely

utilized in studies assessing anthropogenically polluted environments (see reviews in

Boltvskoy and Wright, 1976; Alve, 1995; Schafer, 2000). Such studies indicate that

population diversity and density are lowest at areas of industrial waste discharge

(Hornung et al., 1989; Alve, 1991). Conversely, foraminifera tend to respond positively

to the presence of organic pollution with test size and population densities both

increasing near the pollution source (Watkins, 1961; Schafer and Cole, 1974; Yanko et

al., 1994). Geographical extent or type of pollutant can be determined by measures of

population abundance and type of morphological abnormalities within total populations

(see reviews in Boltvskoy and Wright, 1976; Alve, 1995; Schafer, 2000).

3

The establishment of ubiquitous distribution trends is rare despite the utility of

benthonic foraminifera in ecological studies. Local distribution of a species is determined

by the parameter/parameters close to the limit of tolerance, however, these limitations

vary both spatially and temporally (Murray, 2006). This variability is due to both the

extreme heterogeneity among coastal environments, and the intercoupled nature of many

oceanographic and hydrological parameters. The degree of flushing a system experiences,

behaviour of currents, hydrography, water temperature, pH, natural salinity, level of

oxygenation and hydrological inputs are all likely to influence the dispersal of individual

foraminiferal species. Due to this fact, field studies are often supported by statistical

analyses to clarify the response of foraminiferal assemblages to specific environmental

factors.

Table 1.1 – Examples of studies using foraminifera as palaeocological indicators.

4

1.2.1 Multivariate analysis in ecological studies

Cluster analysis (CA) is one of the most widely applied multivariate analytical

techniques used to segregate entities (e.g. samples, species, physical measurements) into

similar groups or clusters and to quantify the between-group relationships (Parker and

Arnold, 1999). By quantitatively looking at physical and hydrological factors in unison,

study sites can be defined by their similar traits. These patterns can then be used to

analyse areal distribution of significant parameters, such as foraminiferal populations or

substrate type, based on the relative abundance of characteristic features.

CA programs represent these associations through the generation of dendrograms.

The horizontal lines of the dendrogram track the individual entities in the clusters, while

the linkage bars reflect the similarity of the clustered entities. The degree of similarity

and number of clusters has been used to delineate sedimentary associations, biofacies

(groups of organisms characterized by a common occurrence) and biotopes (groups of

samples characterized by a common faunal association) (Johnson and Albani, 1973).

It is important to remember that CA always produces clusters, regardless of

whether any naturally occurring groupings are present in the data (Parker and Arnold,

1999). The recognition of ‘significant’ clusters within a dendrogram is largely a

subjective process, most commonly defined based on relative spacing of linkages.

Despite the subjective nature of clustering, CA serves to simplify or condense the

complicated structure of multivariate data and makes exploration of relationships easier.

Similarly, while the combination of field studies and statistical analyses allow correlation

between distributions of species and environmental parameters, it must be recognised that

these correlations are by nature circumstantial. Correlations can never be definitively

proven, which accounts for why field studies from different areas can provide conflicting

interpretations of species-parameter relationships (Murray, 2006).

Despite these drawbacks, the combination of field studies and statistical treatment

is useful in exploring patterns of foraminiferal distribution and clarifying their ecologic

controls. This integrated approach serves not only to holistically characterise an

environment but also to reveal relationships between benthic biota and environmental

processes. These associations can then be used to inform environmental monitoring and

palaeoenvironmental interpretation.

5

1.3 Thesis objectives

This study aims to:

1. characterize the composition and distribution of modern foraminiferal

populations in Twofold Bay – a near-pristine open oceanic embayment

on the south coast of New South Wales;

2. determine sedimentary associations, foraminiferal biotopes and

biofacies of Twofold Bay through statistical correlation and cluster

analyses; and

3. determine environmental controls on benthonic foraminiferal

associations by comparing foraminiferal distributions against

sedimentary characteristics and associated environmental conditions.

Reasons for this study are three-fold. Firstly, data on modern distributions are

required to aid the interpretation of past environments; secondly, to provide baseline data

for monitoring anthropogenic influence locally; and thirdly, to assist integrated

environmental management of Twofold Bay.

To achieve these aims, sedimentological and benthonic foraminiferal surveys

were conducted, with abiotic data gathered to complement the findings. Statistical

analysis was employed to define similar assemblages of both foraminiferal and physical

datum, and to determine the principal components of each association.

In this study, recent sediments and total foraminiferal populations were employed

in order to explore an average of conditions over several years. This method offers an

integrated view of the environmental processes and conditions within Twofold Bay.

Measures of the chemical parameters of the water mass or analysis of seasonal shift in

foraminiferal composition were not attempted as these are temporal factors that require

constant monitoring over a time period outside the scope of this study.

1.4 Previous distribution studies of benthonic foraminifera in coastal

environments

Foraminifera are exceptionally useful in coastal ecologic studies as no other group

of organisms appears to have such clear environmental controls over population variation

6

(Albani, 1993). Studies in modern estuarine and nearshore environments have recognised

significant correlations between zonal distribution and diversity and key environmental

parameters such as salinity, dissolved oxygen, sediment grain size, subaerial exposure,

organic carbon flux, heavy metals, or presence/absence of vegetative substrates (Scott

and Medioli, 1980; Murray, 1991; Cann et al., 2002; Leorri and Cearreta, 2009).

Scott and Medioli have demonstrated that foraminiferal distributions and

diversities in modern marshes are a function of salinity (Scott, 1974; Scott, 1976; Scott et

al., 1976; Scott et al., 1980; Smith et al., 1984). These studies demonstrate that estuaries

are dominated by agglutinated morphologies and are characterised by a restricted fauna,

especially in the upper reaches where salinities are lowest. Conversely, higher salinities

generally favour calcareous morphologies and exhibit higher population diversities.

Salinity, tidal exposure and presence of vegetation are also listed as factors which

determine brackish-water faunal distributions in New Zealand (Hayward et al. 1996;

1999). However, in shallow-water (<100 m), normal marine environment assemblages

are determined to be influenced by water depth, wave and current energy, bottom water

oxygen concentrations and substrate type (Hayward et al., 1999). This is also supported

by Hulme (1964), Hayward (1990, 1993) and Hayward et al. (1997a, 1997b).

In Australia, foraminiferal distributions have been linked to depth (Michie, 1987),

salinity and tidal mixing (Haslett, 2001; Wang and Chappell, 2001; Binnie and Cann,

2008; Nash et al., 2010), presence of vegetation (Cann et al., 2002; Nash et al., 2010),

temperature and oxygen content (Quilty and Hosie, 2006; Nobes and Uthicke, 2008),

bottom currents (Albani 1970), sedimentary environments (Palmeiri, 1976), or a

combination of the above. However, the vast majority of distribution studies in Australia

make no attempt to reconcile distribution with environmental controls and purely explore

taxonomic occurrence, e.g. in Western Australia (McKenzie, 1962; Collins, 1981),

Victoria (Apthorpe, 1980), South Australia (Cann and Gostin, 1985; Cann et al., 2000a,

2000b), and Queensland (Woodroffe et al. 2005).

In south-eastern Australia there is a significant paucity in the description of

foraminiferal distributions in addition to a shortage of ecologic studies. Distribution

surveys along the south-eastern coast are geographically limited to the greater Sydney

region, with notable studies published on Broken Bay (Albani and Johnson, 1975;

Albani, 1978), Port Hacking (Albani, 1968) and Lake Illawarra (Yassini and Jones,

1989). In addition, numerous studies deal with eastern Australia in general rather than

one specific location (Albani, 1974; Albani and Yassini, 1989). The main compilations

7

relevant to general distributions of Australasian foraminifera are those by Albani (1979),

Yassini and Jones (1995) and Albani et al. (2001). However, while these works are

important collations of recorded distributions, they do not serve to increase resolution of

ecologic controls on benthonic foraminifera.

1.4.1 Biotopes of benthonic foraminifera

Numerous studies have shown that foraminifera can be effectively used to

delineate ecological provinces (biotopes) (Johnson and Albani, 1973; Albani and

Johnson, 1975; Schafer and Wagner, 1978; Michie, 1987). This method is based on a

statistical approach using relative species abundance as the data base, with the level of

linkage between stations which form a biotope expressing faunal similarity.

Biotopes have been used to identify areas with significant ecological abnormality

in coastal environments subject to industrial pressures. In Chaleur Bay, Canada,

foraminiferal populations were noted to respond to effluent discharge, with the

distribution of pollution-tolerant or -sensitive assemblages used to identify geographical

extent of pollution (Schafer, 1973). Similarly, species distribution has also been

correlated with tolerance of heavy metal contamination, with these biotopes used to

determine the extent of contamination (Alve, 1991; Sharifi et al. 1991).

Major efforts to integrate foraminiferal distributions with physical and biological

parameters have been made by studies conducted overseas and within Australia (Yassini

and Jones, 1995; Hayward et al., 1999). In the Lagoon of Venice, four distinct biotopes

were identified, with depth, availability of nutrients and type of substrate proposed as

factors which limited foraminiferal faunal distribution (Albani and Serandrei Barbero,

1982; Albani et al., 1984). In three separate estuaries in south-western Spain, three main

foraminiferal assemblages were identified, with spatial distribution restricted by

sedimentary environments, grain size classes and variations in salinity (Ruiz et al., 2005).

Conversely, in New Caledonia, it was proposed that 30 foraminiferal species were mainly

influenced by depth, with 18 influenced by the mud content of the sediment (Debenay,

1988).

In Exmouth Gulf, Western Australia, Orpin et al. (1999) concluded that the

distribution of individual foraminiferal species was governed by environmental

parameters such as water depth, salinity and bottom-sediment conditions. Similar

8

correlations between salinity, water depth, foraminiferal diversity and foraminiferal

population densities have been noted in studies from New South Wales (as discussed

below).

In Lake Illawarra, NSW, Yassini and Jones (1989) noted distinct separations

between the lagoonal, inlet channel and intertidal sub-littoral marine faunal assemblages.

Four foraminiferal assemblages were defined by CA, with lowest foraminiferal

diversities recorded from the landward side of the lake and greatest diversities recorded

from the region of marine-lagoonal mixing. CA dendrograms indicated that Ammonia

beccarii and Cribrononion sydneyensis were distinctly linked to deeper water or silty

substrates whereas textularids were associated with shallow sandy substrates.

Similar geographic trends in foraminiferal diversity were reported from Broken

Bay, NSW, where the marine dominated section of the estuary recorded a greater

diversity and density of benthonic foraminifera than the up-stream section (Albani and

Johnson, 1975; Albani, 1978). This pattern was attributed to the presence of variable

fluvial conditions in the up-stream regions. Additionally, in the southern portion of

Broken Bay, four biotopes were recognised from Pitt Water with depth, sediment type

and hydrological parameters such as nutrient levels controlling their geographical extent

(Johnson and Albani, 1973).

Albani (1968) separated Port Hacking into six foraminiferal assemblages

comprising three distinct faunal groups between the upper part of the estuary and its

seaward extent. Faunal Group 1 (made up of Faunal Groups A and B) characterised the

fluvial-dominated section and displayed a restricted fauna. Faunal Group 2 (Faunal

Groups C and D) occupied the area between the fluvial and marine sections, while Faunal

Group 3 (Faunal Groups E and F) characterised the marine dominated section of the

estuary. A comparison of the faunal assemblages with variations in the physical

environment showed a general correlation with salinity, depth and proximity to marine

influences. Faunal diversities were again noted to be lowest at the most fluvial end of the

estuary, and highest at the mouth. Increased NO3 concentration with increased distance

from the estuary mouth was also cited as a control, while temperature and oxygen

concentration were determined not to influence assemblage distribution (Albani, 1968).

The distribution of foraminifera from the Clyde River Estuary and Bateman’s Bay

are somewhat more complicated. Haslett (2007) recognised six foraminiferal

assemblages, two of which are thought to represent geomorphological factors with the

remaining assemblages reflecting downstream increases in salinity. Downstream shifts in

9

diversity were recorded with the low salinity, inner estuary assemblages dominated by

Ammonia beccarii and the higher salinity (normal marine) assemblages of the bay

dominated by Elphidium spp. Overall species diversities also increased with seaward

progression, with the miliolid group only occurring in the outer parts of the estuary.

As these studies indicate, foraminiferal distributions and their limiting factors

vary widely. While controls such as salinity and substrate controls recur frequently, no

uniform trend can be uncovered for south-eastern Australia. This high degree of variation

implies that a national trend of ecological niches is unattainable, and highlights the

importance of localised studies.

1.5 Previous studies at Twofold Bay

This study marks the first investigation into the composition, distribution and

ecologic controls of foraminifera within the Eden area. Samples from Twofold Bay were

collected by Iraj Yassini and appear as type specimens in works by Albani (1989) and

Yassini and Jones (1995); however these have not formed part of any specific publication

(B.G. Jones, 2011, pers. comm.). One study regarding the distribution of sediments in

Twofold Bay has been carried out (Hudson, 1991); however it was restricted to

geomorphic mapping and discussion of texture and composition of regional sediments.

The study presented here is the first in-depth analysis of the distribution of living

foraminifera of Twofold Bay, as well as the first study to define local biotopes and

discuss their controls. This study addresses the paucity of information regarding ecologic

niches of Australian coastal foraminifera and provides a baseline study for the Eden area.

10

Chapter 2: Field Area – Twofold Bay

2.1 General

Twofold Bay is a large (31 km2) open oceanic embayment at Eden on the

southern New South Wales coast (37º05’S 149º54’S at the bay’s centre), approximately

380 km south of Sydney and 40 km north of the NSW-Victoria border (Fig. 2.1a). It is

approximately 4.5 km wide and is comprised of a number of smaller bays (Calle Calle,

Nullica, Quarantine, East Boyd; Fig 2.1a) which are separated by prominent rocky

headlands (Lookout Point, Torarago Point). Population is concentrated on the north-

eastern and south-western foreshores of the bay in the towns of Eden and Boydtown

respectively. The primary port areas are on the northern and southern shores of Twofold

Bay, in Snug Cove and East Boyd Bay, respectively (Fig. 2.1b).

Due to the historical length and areal concentration of settlement, potential

Figure 2.1 – Location maps showing: a) Twofold Bay and surrounding townships in a regional setting;b) detailed map of the study site showing locations mentioned in the text: QBBR = Quarantine BayBoat Ramp and Breakwater; MJEW = Main Jetty/Eden Wharf; MJFW = Mooring Jetty/FishermansWharf; EBW = Eden Breakwater; WWW = Harris-Daishowa Woodchip Wharf; RAN MPNAW = Royal Australian Navy Multi-purpose Navy Ammunition Wharf; green areas symbolise active musselleases (after Pollard and Rankin, 2003; NSW DPI, 2005).

a. b.

11

environmental pressures may exist in these areas. Other factors potentially influencing

foraminiferal densities and distributions are pollution, marine infrastructure, regional

climate, hydrological inputs, sediment distribution and oceanographic regimes.

2.2 Industrial history

Marine pollution is a potential concern due to the area’s long industrial history.

Twofold Bay served as an export station for whale products, wattle bark, farm produce

and livestock from 1828-1930, while several salmon canneries were operational on the

bay’s foreshores from 1920-1999 (Bega Valley Council, 2001; Blaxell, 2008; Eden

Community Access Centre Inc., 2009). Today, Eden is the largest commercial fishing

port in NSW and is a principal export point for timber and timber products (Eden

Community Access Centre Inc., 2009). The Harris Daishowa woodchip mill in East

Boyd Bay exports, on average, 800,000 tonnes of woodchips and more than 60,000

tonnes of softwood each year (Eden Community Access Centre Inc., 2009). Due to these

industries, Eden harbour’s main import commodities are petroleum products, with

hydrocarbon contamination a potential issue in the main ports (Pollard and Rankin,

2003).

The importance of local aquaculture requires ongoing awareness regarding

ecosystem health. A large number of commercial fishing activities operate out of the bay

such as ocean haul fisheries, beach seine nets, garfish nets, trawl fisheries, and dive, trap

and line fisheries (M. Procter, 2011. pers. comm.). In addition, Twofold Bay is utilised by

the mussel aquaculture industry for the production of blue mussels, Mytilus edulis. Since

1998 13.5 hectares of rafts and longlines has been situated between Oman and Cocora

Points and an additional 2 ha of longline at the north western end of Torarago Point,

Nullica Bay. In 2005, local mussel farming extended to 50ha with supplementary leases

developed at Oman Point (4 ha) and Torarago Point (18 ha and 12 ha) (Fig. 2.1b; NSW

DPI, 2005). While total revue figures are not available due to confidentiality reasons, the

economic importance of local aquaculture necessitates the preservation of Twofold Bay

through development and implementation of environmental monitoring programs.

Foraminiferal populations may also be affected by the numerous physical

structures which influence flow and restrict circulation around the bay (Fig. 2.1b). Snug

Cove, Eden’s main port, is characterised by two large jetties (Main Jetty/Eden Wharf,

12

Mooring Jetty/Fishermans Wharf) and Eden Breakwater, a 100 meter blockade (Harris

and O’Brien, 1998; Pollard and Rankin, 2003). To protect small vessel moorings, a

second breakwater is situated in Quarantine Bay. While each structure is purposely built

to increase harbour shelter, breakwaters affect natural circulation, artificially decrease

wave energy, and reduce the effectiveness of flushing. These processes can often result in

unintentionally stressful benthonic environments.

Environmental stress can also result from the maintenance of physical structures,

rather than from the structure itself. On Twofold Bay’s southern headland, two large

wharves are situated at East Boyd Bay: The Royal Australian Navy’s Multi-Purpose

Naval Ammunitioning Wharf and the Harris-Daishowa Woodchip Wharf. These

structures are built on pylons and have no associated breakwater to impede water

circulation; however frequent use necessitates periodic maintenance dredging. During

construction of the ammunitioning wharf, dredging of its turning basin removed sediment

approximately 0.75 m in depth, with maintenance dredging carried out as required (NSW

Department of Urban Affairs and Planning, 2000). The repeat removal and redistribution

of bottom sediment is highly likely to impact the composition and distribution of

sediment-dwelling taxa in the immediate areas.

2.3 Climate

To identify potential seasonality in the relationship between foraminiferal

populations and hydrological parameters an understanding of regional climate is

necessary. Long-term climate statistics for Eden are unavailable, with the nearest

meteorological stations being Green Cape Lighthouse (24.9 km to the south) and

Merrimbula Airport (17.9 km to the north). While both locations show similar seasonal

trends, Merimbula Airport is deemed to be most representative due to comparable aspect,

topography and degree of protection against the Tasman Sea. Regional generalisations

about atmospheric climate are therefore based records from Merrimbula Airport.

The south coast region displays a typical maritime climate with mild winters,

warm summers and year-round rainfall (Table 2.1; Fig. 2.2). Seasonal wind and rainfall

patterns recorded at Merrimbula Airport display a weak tendency towards summer

rainfall maximum and strong south-west winds during winter months. Summer months

are characterized by warm, stable conditions with light to moderate sea breezes

13

associated with slow moving high pressure cells. During winter months the subtropical

high pressure systems shift north, bringing the south coast under the influence of mid

latitude cyclones (Linacre and Hobbs, 1977; Holton, 2004). Cold fronts become more

frequent and generally cooler conditions prevail with a predominantly south to south-

west airstream. Eden would also be affected by mid-latitude cyclones or East Coast Lows

which develop in the Taman Sea at any time throughout the year. These low pressure

systems would result in strong east to south-easterly onshore winds and prolonged

periods of heavy rain which may cause heavy flooding (Commonwealth Bureau of

Meteorology, 2007).

2.4 Hydrology

Foraminiferal distributions within Twofold Bay are also potentially affected by

depth factors and extent of freshwater influence. Average water depth within Twofold

Bay is 20 m, with a maximum of 40 m at the bay entrance (Fig. 2.3). Three main fluvial

systems drain into the bay (Fig. 2.4; Table 2.2), as well as a number of estuaries (e.g.

Towamba River, Nullica River and Fisheries Creek) and a coastal lake (Curalo Lagoon).

Of these fluvial influences, the Towamba River is most dominant, typically recording

Figure 2.2 – Graphical climate statistics for Merrimbula Airport detailing mean monthly rainfall, and mean minimum (blue line) and maximum (red line) daily temperatures(modified from the Commonwealth Bureau of Meteorology, 2011a).

Table 2.1 – Average wind speed direction andrecorded at Merrimbula Airport over theperiod 1998-2011 (modified from the Commonwealth Bureau of Meteorology,2011a; site no: 069147).

14

peak flows during February/March. Low flows are typical between November and

January, however the Towamba River experiences generally high average flows all year-

round (ANRA, 2009).

Foraminiferal distribution would also be influenced by the degree of connection

between an estuary and the open bay. Towamba River is a barrier estuary which

maintains a permanent connection with the bay, while other barrier estuaries (e.g. Nullica

River and Fisheries Creek), have semi-permanent connections (Hudson, 1991). Similarly,

Curalo Lagoon lacks a permanent entrance and is only open to the bay after periods of

heavy rainfall in the Pallestine catchment. The degree to which an estuary exchanges with

the open marine setting greatly affects salinity gradients which, in turn, shape

foraminiferal distributions. An intermittent connection would weaken salinity gradients

and support brackish-water foraminiferal populations, while a permanent connection

would cause the inverse. A permanent connection would also promote the open exchange

and migration of fauna between estuarine and open marine settings.

Figure 2.3 – Bathymetric map for Twofold Bay (from The Australian HydrographicService, 2011: map code AUS192).

15

2.5 Oceanographic setting

The oceanic climate of any region is important in understanding environments

and energy conditions experienced at the bottom-sediment level. Typically, the NSW

south coast is dominated by a high energy, deep-water wave environment and

characterized by highly variable wind waves and persistent southerly swells (Thom and

Hall, 1991). However, Twofold Bay is relatively quiet and sheltered due to shoaling,

diffraction and refraction significantly reducing deep-water wave power (Hudson, 1991).

The bay’s mouth is orientated away from the dominant south-east swell, further resulting

in a progressive decrease of wave energy in a counter-clockwise direction around the bay

Figure 2.4 – Boundaries for the (1) Towamba; (2) Nullica; and (3) Pallestinecatchments which drain into Twofold Bay (after Hudson, 1991).

Table 2.2 – Catchment area and mean annual runoff data for the three major catchments affecting Twofold Bay as described in Fig. 2.4 (after Hudson, 1991).

16

(Hudson, 1991). Swells in the main harbour of Snug Cove are typically low, with

turbulent conditions generally attributed to wind-driven currents and waves (Treloar,

2011). The small difference between the tides on the open coast and within the bay

suggests weak tidal currents in the bay (Harris and O’Brien, 1998). In contrast, tidal

currents are expected to play a significant role in the movement of sediment at the

entrances of the Nullica, Towamba and Fisheries Creek estuaries.

Flushing times in Twofold Bay are likely to vary due to differences in the strength

of the currents penetrating the main entrance, as well as energy reduction as currents

traverse the main bay and enter the smaller bays. This would result in different turnover

rates depending on the geographical point and climatic conditions within the bay.

However, by calculating the bay’s volume, Forteath (1996) estimated a flushing time of

5-8 days.

Water circulation within Twofold Bay is predominantly clockwise, with

prevailing north-east to south-east winds restricting water movement between the main

headlands (Pollard and Rankin, 2003). Active mixing between the Twofold Bay water

mass and the Pacific Ocean occurs only in the presence of extreme southerly winds (A.

Felton, 2011, pers. comm.).

Eden is also influenced by the East Australian Current (EAC) which brings warm

tropical and subtropical water into the cooler temperate waters of NSW. The EAC flows

Figure 2.5 – Broadscale oceanographic processes off the NSW coast represented by sea-surface temperature (SST) satellite images and geostrophic velocities. The Eden study site is marked with a black dot; a) the East Australian Current warming inshore waters of lower NSW during November, 2010; b) an increased southerly reach of warm waters into the Twofold Shelf region during February, 2011; c) a slackening of the EAC, cooling of inshore waters and the development of a warm-water eddy during May, 2011; d) cool inshore waters in the Twofold Shelf region and warm-water eddy projecting into the Tasman Sea during August, 2011. Note the colour scale variesbetween images (from CSIRO Marine Remote Sensing, 2011).

17

strongest in summer, up to twice the strength of winter months (CSIRO Australia, 2001).

During weak winter flows, temperate water masses flood the shelf leading to decreased

sea surface temperatures (Fig. 2.5). Most of the EAC’s flow leaves the Australian coast

somewhere off NSW to head east along the Tasman Front, resulting in decreased

influence with southerly extent. By the time the EAC reaches the Twofold Shelf, it is

estimated to influence inshore coastal waters only 10% of the time (Pollard et al., 1997).

While mostly affected by temperate conditions, this region also experiences warm-core,

anti-cyclonic eddies caused by the unstable mixing of warm EAC and cool temperate

waters (Griffin et al., 2001).

2.6 Sediments

Seven types of surficial sediments from Twofold Bay are defined based on texture

and composition (Hudson, 1991; Fig. 2.6). Mud and muddy sands occupy the deeper

central portion of the bay mouth and are surrounded by coarse-grained quartz-carbonate

sands containing shell detritus (Yassini and Jones, 1995). Sediments of the inner bay area

Figure 2.6 – Sediment distribution within Twofold Bay (after Hudson, 1991; from Yassini and Jones, 1995).

18

are predominantly fine quartz sands with a zone of coarse sand along the southern and

outer parts of the bay. Increased mica and lithics of the inner bay sediments is likely to

represent reworked fluvial detritus from major source rivers.

2.7 Recent meteorological events

It is important to note that this study took place during and immediately following

one of the strongest La Niña events recorded since the late 1800s (Commonwealth

Bureau of Meteorology, 2011b). Due to cooling in the Pacific following the 2009-10 El

Niño cycle, La Niña conditions were established over Australia by July 2010. As a result,

significantly higher than average rainfalls were experienced nationwide, with record high

rainfall occurring across much of northern and eastern Australia resulting in widespread

flooding between September 2010 and February 2011 (Commonwealth Bureau of

Meteorology, 2011b). The townships of Towamba and Kiah (16 km and 8 km from

Twofold Bay, respectively) experienced the worst flooding in almost 40 years over

March 23-24, 2011, when nearly 600 mm of rain fell on the Towamba River catchment

(Campbell, 2011; Stroud, 2011). This flood event resulted in mud plume discharge from

Towamba River that filled Twofold Bay for several days (A. Felton, 2011, pers. comm.).

Smaller, but still sizable flood events also occurred in both April and June, 2011. The

strong La Niña conditions also resulted in warmer than usual sea-surface conditions

experienced across the entire eastern seaboard. This enhanced southerly movement of the

EAC resulted in abnormally warm waters off southern NSW (Figs. 2.5c, 2.5d).

The prevalence of these abnormal conditions potentially exerted significant pressures

on foraminiferal populations and their distributions. The implication of these events will

only be identified through repeat studies.

19

Chapter 3: Study Methods and Rationale

3.1 Sample collection

A total of 46 samples were collected from 4 tributary estuaries and Twofold Bay

over three separate days of sampling (12/13 February and 19 March 2011, respectively).

At each site, three complementary sampling techniques were employed to collect

representative living and sub-fossil microfauna and explore environmental conditions:

foraminiferal and bottom sedimentary samples were gathered using either a 150 µm mesh

hand net, or a grab sampler (as described below); samples were stained with Rose Bengal

(rB) and fixed with ethanol; and temperature, dissolved oxygen concentration (DO),

electrical conductivity (EC), pH and salinity were measured using an Orion 5-Star

Portable Multiparameter Meter and a BRIX refractometer. Sample sites were based on

ease of access, adequate distance of separation from adjacent sites, and presence of

niches of interest such as weed beds, rock substrate and shell deposits.

Eighteen samples were collected from the lower Towamba River between Kiah

Inlet and Whelans Swamp against the gradient of freshwater (Fig. 3.1). Three samples

were collected from each of Curalo Lagoon, Nullica River and Fisheries Creek. At these

sample locations foraminiferal and bottom sediment samples were gathered using a 150

µm mesh hand net raked through the water column and vegetation (when present).

Temperature, DO, EC, pH and salinity were measured in situ. Nineteen bottom-sediment

samples were collected from sites distributed throughout Twofold Bay using a small grab

sampler (Fig. 3.2). Water samples from the sediment/water interface were collected using

a Niskin bottle, with temperature, DO, EC, pH and salinity measured ex situ.

In Eden Harbour two distinct colour bands were noted from bottom sediment

recovered at site TFB14. Two independent sedimentary and foraminiferal samples were

taken from this site and are herein labelled as TFB14 (samples taken from the pale sandy

layer) and TFB26 (samples from the dark organic layer). Abiotic data for this site

remains referenced as TFB14.

Excess sea water was carefully drained from each recovered sediment sample, and

the samples preserved in ethanol. This ethanol treatment not only prevents microbial

decay of foraminiferal tests, but also served to kill individuals that were alive at the time

20

Figure 3.1 – Google Earth image showing sample locations referenced in this study. From top: C =Curalo Lagoon (red markers), TFB = Twofold Bay (yellow markers), N = Nullica River (purplemarkers), T = Towamba River (green markers), F = Fisheries Creek (blue markers). For GPScoordinates of each site, refer to Appendix 3.1.

21

of collection. Following the method described by Bernhard (2000), bio-reactive rB stain

was added to each sample in order to differentiate live and dead specimens. The rB stain

absorbs onto proteins of cytoplasm-containing tests (i.e. those which were recently alive),

turning them an obvious pinkish red colour.

3.2 Sample preparation and analysis

3.2.1 Abiotic parameters of water

Temperature, DO, EC and pH were measured in the field at each sample location

using an Orion 5-Star Portable Multiparameter Meter. Salinity (according to the Practical

Salinity Scale) was measured using a BRIX refractometer. Due to time constraints and

boat size, water samples from the bay study site were analysed onshore at the completion

of sampling. Depth at each sampling site in the bay was recorded using an on-board sonar

system, and checked against the Australian Hydrographic Service bathymetric map.

Figure 3.2 – Bottom sediment samples from Twofold Bay were gathered using a grab sampler. Attached to a rope, the (a) open grab sampler was deployed to the sea floorwhere it was (b) manually closed and brought back to the surface. Sediment held in theclosed grab sampler was then spooned into labelled jars and used for foraminiferal andsedimentary grain size analysis.

a. b.

22

Using the statistical software package, ‘IBM SPSS Statistics 19’, similarity

matrices were constructed for the abiotic data at each site using Ward’s matrix, Euclidian

distance and z-score weighting (so that all parameters contributed equally). Sample

associations were determined using dendrograms derived from these similarity matrices,

with significant clusters identified by the level of linkage between the clusters. A

discussion of single and complete linkage clustering can be found in Sneath and Sokal

(1973). Temperature data from all Twofold Bay stations was excluded from this analysis

due to the high likelihood of it being compromised by a lag between sampling and

testing.

3.2.2 Sediment

A small portion of sediment (5-10 ml) was isolated for particle size analysis using

a wet-dispersant Malvern Mastersizer 2000 (Fig. 3.3). This process uses laser diffraction

to assess the angular dependence of light scattering, with Mie theory applied in order to

theorize the scattering pattern. Grain size is subsequently estimated via comparison with

standard scattering patterns, and the proportion of size fractions automatically estimated.

Figure 3.3 – Grain size analysis was performed using the MalvernMastersizer 2000. A combination of red and blue light sources and 52 light detectors allows this equipment to measure the angulardependence of light scattering of particles spanning a 0.2-2000 µm size range.

23

For increased accuracy of Mie theorisations the optical properties of both the particle and

dispersant must be accurately identified.

Water (refractive index 1.330) was used as a dispersant and quartz (refractive

index 1.540, absorption quotient 0.01) was named as the predominant sample component.

Background and measurement times were set to 12 seconds each. Each sample was

homogenized by vigorous shaking and a fraction of sample was added to the dispersant

until an obscuration range of 8-20% was reached. Results are averages of 5

measurements.

Grain size distributions were determined using the D(0.1), D(0.5) and D(0.9)

scores which indicate the size fraction through which 10%, 50% and 90% of the sample

material passes. Similarity matrices were constructed for the average D-scores of each

station using the aforementioned statistical technique. Sedimentary provinces were

determined from the resulting dendrogram, and each association named for its

characteristic grain size.

3.2.3 Foraminifera

Foraminiferal samples were initially divided into smaller, more workable

fragments, using a wet-splitter (Fig. 3.4a). One half was stored in a large beaker, whilst

the other was split again creating a representative quarter of the initial sample. This

process was repeated, working with only one half, until a small portion of the original

Figure 3.4 – Bulk foraminiferal samples were split into smaller, representative sub-samples by passing the entire collected sample through (a) a wet splitter. These sub-samples were then dried and split further using (b) a micro-splitter and other accessories shown in photo.

a b

8cm 6cm

24

sample was retained. During each split, shells,

shell fragments, pebbles, nematodes, brittle stars,

or other biological or vegetal material were

removed, labelled, and archived for identification.

The split fraction was oven dried at ≤55oC

and weighed using digital laboratory scales. The

dry fraction was then wet-sieved over 100µm

mesh with the retained sediment fraction oven

dried at ≤55oC and weighed again. Dry sediment

material >100 µm was further split using a micro-

splitter (Fig. 3.4b) to create smaller non-biased

sub-samples containing rB stained (living) and

unstained (non-living) specimens. Micro-splits

were weighed and all samples dry picked under a

stereoscopic microscope (Fig. 3.5).

Each sub-sample of rB stained material was picked for foraminifera, ostracods

and other diagnostic biological components including sponge spicules, bryozoan

fragments and echinoid spines. Where possible, 200-300 individual specimens were

extracted from each sub-sample using a fine watercolour brush.

Where possible, foraminifera were identified to species level, or otherwise genus,

based on illustrations and descriptions in Albani (1968, 1970, 1978, 1979), Albani et al.

(2001), Albani and Yassini (1989), Yassini and Jones (1989, 1995), Cann et al. (2002)

and Hayward et al. (1997, 1999). Where variations within species were unable to be

refined to subspecies level, genus was identified and these species noted as variants

(‘var’). Data sheets were compiled for each sample noting the following characteristics:

number of stained and unstained individuals, abrasion levels, and deformities.

The following quantitative and statistical treatments were then carried out:

3.2.3.1 Foraminiferal density

For each site, the live:dead (stained:unstained) ratio was calculated. Foraminiferal

density counts were standardized by calculating the number of identified foraminifera to

a one gram mass of sediment. While this study is primarily concerned with benthonic

Figure 3.5 – All foraminiferal workwas performed using a stereoscopicmicroscope and external light source,using 16x-32x magnifications.

25

foraminifera, the planktonic:benthonic ratio was determined for each site in order to

inform oceanic contributions to and depositional features of Twofold Bay .

3.2.3.2 Cluster analysis

As the number of individuals picked per station ranged between 100-300

benthonic specimens, the data are more comparable to species proportions than species

densities. Higher counts would more accurately indicate the number of species present in

Twofold Bay; however this study is concerned primarily with the most dominant species

which would display larger populations regardless of sample size. Species abundance was

determined by standardizing counts to proportions of sample totals with statistical

analysis applied to this data. Unlike the statistical treatment of abiotic and sedimentary

data, foraminiferal similarity matrices were constructed using unweighted data so that the

most dominant species contributed greatest to the clustering. Sample associations were

then determined from the dendrogram produced.

3.2.3.3 Wall structure

The geographic distribution of dominant wall structures was also determined. All

modern foraminifera are classified as one of three groups (Textulariina, Miliolina and

Rotaliina) which correspond with agglutinated, porcellaneous and hyaline test wall

structures, respectively (Leoblich and Tappan, 1964). In order to determine the

abundance of each form of test, data was standardized by converting counts of each form

to proportions of sample totals. Data from each station was plotted on a ternary diagram.

3.2.3.4 Association scores

Characteristic foraminiferal species of each sample association were determined

following Hayward et al. (1996). All species in each association were ranked using a

value calculated to reflect their importance. This value is based on a combination of 5

criteria:

26

1. Dominance (Dom) – calculated by identifying the 5 most abundant species

from each station in an association. The most abundant species is awarded a

score of 10, the second most abundant a score of 8 and so on, with a taxon’s

dominance determined by its mean score across all stations within that

association.

2. Fidelity (Fid) – reflects the degree to which a species is restricted to an

association and is expressed as the proportion of stations within the

association in which the taxon occurs, minus the proportion of stations outside

the association in which it occurs.

3. Abundance (Abund) – the mean abundance of a species within the association.

4. Relative Abundance (Rel) –the mean abundance of the taxon within the

association minus its mean abundance throughout all stations.

5. Persistence (Pers) – the proportion of stations within the association in which

the taxon occurs.

The overall association score of a taxon is calculated using the formula: 4(0.3

Dom + 2 Fid + 0.11 Abund + 0.08 Rel + Pers) in order to give greater weight to criteria

in the following decreasing order: Abundance, Relative Abundance, Dominance, Fidelity,

Persistence (Hayward et al., 1996). The species with the highest association score is

determined to characterise the association (maximum score 100).

3.2.3.5 Species diversity

The Fisher Alpha measure of species richness was calculated for each station

within the bay. Based on Fisher et al. (1943), this score reflects biodiversity based on the

number of individuals and species recorded from a sample. Values of α (diversity) can be

determined from a base graph by plotting the number of species against the number of

individuals in a sample (Murray, 1991: 319).

3.3 Rationale

There is no standardized approach to accurately estimate benthonic foraminiferal

populations and distributions, despite a vast number of studies. There remains

27

considerable debate within this field and a number of issues must be acknowledged in

order to rationalise the methodology of this study.

For appropriate statistical analysis of population estimates, it is assumed that the

wet splitting process created representative sub-samples with no directional bias in the

machine. This was supported by initial testing of the wet-sampler which achieved almost

identical weights of splits regardless of direction or speed of sample throughput.

rB was chosen for this study due to its efficiency, inexpensiveness and easy

employment in situations where large numbers of samples are acquired over a short time.

However, accurately distinguishing live from dead populations is one of the most widely

debated issues in benthonic foraminiferal studies (see review in Bernhard, 2000). Much

of the controversy regards the phenomena of false positives (the staining of the organic

lining of dead foraminifera; Walker et al., 1974); false negatives (the non-staining of

recently alive foraminifera; Martin and Steinker, 1973); the difficulties in determining

staining outcomes on opaque foraminifera (e.g. agglutinated or miliolid morphologies);

and the difference between wet and dry samples in terms of ease of identification (Scott

et al., 2001). Another issue is the uncertainty regarding stain times. Where the

recommended time for effective staining ranges from hours to weeks, some others

indicate rB can react weeks, months or even years after an individual’s death (Bernhard,

1988).

While there are other more reliable live v. dead staining methods available (see

review in Bernhard, 2000), their use in this project was seen as cost prohibitive and

impractical due to the requirement of specialised equipment. Secondly, as a period of

months had elapsed between the initial sampling and staining and subsequent laboratory

processing and identification work, foraminiferal samples are assumed to be sufficiently

stained. Furthermore, while Scott et al. (2001) recommend that rB-stained samples be

examined in liquid suspension, this study chose a dry technique due to the ease of

working with dry samples and to prevent breathing in alcohol vapours during analysis.

Lastly, there is ongoing debate regarding the number of specimens required for a

representative study. While 200-300 individual specimens is widely accepted to provide

sufficient accuracy for most quantitative examinations (Phleger, 1960), some authors

suggest a minimum of 300-400 individuals (Lowe and Walker, 1997) and others

recommend 800-1000 (Albani and Johnson, 1975). Hayward et al. (1999) suggest that

while extensive picks in qualitative studies are more likely to reveal rarer species, these

are not significant in assessment of faunal associations. Hayward and Grenfell (1994)

28

suggest that 100 specimens are adequate to assesses faunal compositions used for

identifying and map associations. This is because the numerically dominant taxa in each

fauna will still influence statistical analysis regardless of sample size (Hayward et al.,

1999). This study, therefore, aimed for between 200 and 300 individuals, and settled for

counts above 100 where necessary.

29

Chapter 4: Results

While this study collected abiotic, sedimentary and foraminiferal data from

Twofold Bay and a number of tributary estuaries, foraminiferal densities in Towamba

River, Nullica Creek, Fisheries Creek and Curalo Lagoon were deemed too low to

warrant further investigation. Results are therefore restricted to foraminiferal,

sedimentary and abiotic characteristics within the open embayment of Twofold Bay.

4.1 Abiotic parameters

Abiotic parameters of Twofold Bay bottom-water are given in Fig. 4.1 and raw

data in Appendix 4.1. Sampling depth varies around the bay with stations traversing the

mouth of Twofold Bay (TFB10, TFB11, TFB12, TFB13) recording depths consistently

greater than 18 m while the remainder of stations range between 7 and 11 m. EC falls

within the normal marine range, however salinity remains consistent at unusually low

levels (28-30 psu). pH is also constant throughout the bay (8.49-8.61 pH), with no drop

recorded at any major port. Two measurements of dissolved oxygen (DO) indicate lowest

levels in Edrom Bay (TFB9), with stations in the western and southern portions of

Twofold Bay (TFB1, TFB2, TFB3, TFB3, TFB5, TFB6 and TFB7) displaying higher

relative oxygen than stations situated in the eastern and western regions (TFB10, TFB11,

TFB12, TFB13, TFB14, TFB26, TFB15, TFB16, TFB17 and TFB18). Temperature was

shown to steadily increase regardless of station (Fig. 4.1) and is likely attributed to a lag

between sampling and analysis. Temperature data is therefore taken to be erroneous and

excluded.

Cluster analysis indicates three associations which correlate with inner bay, open

water, and harbour locations (Fig. 4.2). Analysis of means and standard deviations of

each parameter in each association identifies depth and DO to be the association drivers.

Association B is clearly defined by depth (20 m mean depth), and Association C records

a greater DO (mean 86.3%; 6.45 mg/L) than the other two associations. All other

parameters are relatively consistent throughout the clusters.

30

Figure 4.1 – Depth, temperature, pH, electrical conductivity (EC), salinity and dissolved oxygen (DO in mg/L and % saturation) plots for the Twofold Bay study site.

Figure 4.2 – Dendrograph for the abiotic parameters (DO, EC, salinity, pH, anddepth) measured at each station within Twofold Bay. Clusters deemed as significant are coloured and labelled with letters corresponding to associations of similarhydrography: A = inner bay; B = outer bay; C = Eden Harbour. Parameters drivingthe clusters are given as mean scores ± standard error at 95% confidence andemboldened where significant (Appendix 4.2).

31

Figure 4.3 – Grain size distribution changes around Twofold Bay. Distributional ranges aredetermined by plotting particle size (as categorized by British sieve sizes; Appendix 4.4) on the horizontal axis against percentage abundance on the vertical axis.

32

4.2 Sedimentological study

Results of laser diffraction indicate a distinct sediment grain size change around

Twofold Bay (Fig 4.3; Appendix 4.3). The western shoreline is characterized by a coarse

silt–fine sand particle range (stations TFB18, TFB1, TFB2, TFB3, TFB4 and TFB5).

Grain size increases to medium sands in the mouth of the Bay (TFB10, TFB11) while

Snug Cove (TFB14, TFB26 and TFB15) displays an increasingly bimodal range of silts

and fine sands. Two sites (TFB6 and TFB13) are dominated by coarse-very coarse sands

with 78.83% and 67.64% of each respective sample falling in the 500-2000 µm size

range.

This trend is further indicated by graphing the distributional range as represented

by the D(0.1), D(0.5) and D(0.9) distribution scores (Fig. 4.4). Stations in the western bay

(TFB1, TFB2, TFB3, TFB4 and TFB5) display a small distributional range, with the

majority of sediments being less than 200 µm. Stations from East Boyd Bay (TFB7,

TFB8, TFB9, TFB10, and TFB11) have an increased range, with 40% of sediment falling

in the medium-coarse size fraction. The bimodality of the Eden harbour sites (TFB14,

TFB26 and TFB15) is demonstrated by the large range between the D(0.1) and D(0.9)

scores, with the D(0.1) score indicating an increase in silt content. The D-score range at

stations TFB12 and TFB18 is observed to be minimal compared to their surrounding

samples.

Figure 4.4 – Trends in grain size regionality throughout Twofold Bay as indicated by the D(0.1),D(0.5) and D(0.9) distribution scores. Two or more data points for the same sample site indicatereplicates. Plotting of stations TFB1, TFB2 and TFB3 has been repeated to highlight the sharpdecline of coarse grains between TFB18 and the aforementioned stations.

33

Figure 4.5 – Dendrograph for the grain size distribution of stations withinTwofold Bay. Clusters deemed as significant are coloured and labelled, with letter corresponding to sedimentary associations described in the text (A = Very Fine-Fine Sand; B = Fine-Medium Sand; C = Medium-Very Coarse Sand; D = Medium Sand).

Cluster analysis confirms the presence of four distinct sedimentary provinces

(Fig. 4.5), with each association characterised by separate principal grain sizes (Fig. 4.6).

TFB6 and TFB13 are deemed a separate association due to their very coarse fractions and

late clustering. Stations TFB9, TFB12 and TFB15 are statistically correlated with the

Bay’s western shore. There is no difference in clusters produced from standard or squared

Euclidian distance, indicating a strong degree of relatedness.

4.3 Foraminifera

A total of 162 species, 156 benthonic and 6 planktonic, representing 28 families

have been recognised in the open embayment of Twofold Bay (Appendix 4.5). Most of

the species found are common to open estuaries and nearshore settings along the eastern

coast of Australia (Albani, 1979; Yassini and Jones, 1995).

34

a.

b.

c.

d.

Figure 4.6 – Sedimentary grain size distributions for each association determined by cluster analysis.

35

Figure 4.7 – Abundance of total foraminiferal assemblage as a number ofindividuals estimated per 1 gm of sediment.

Most species are present in nearly all stations with only a small number of species

recording a narrow range of occurrence. Ammonia beccarii, Quinqueloculina incisa and

Rosalina bradyi are recorded at every station. Species occurring at almost all stations

include Cibicides sp. 2, Glabratella australensis, Lamellodiscorbus sp. 1, Miliolinella

australis, Q. anguina arenata, Q. seminula and Triloculina trigonula. All sites display a

high proponent of the family Elphidiidae with Elphidium crispum, E. macellum, E.

advenum var. 1, E. advenum var. 2, E. advenum var. 3 and Cribroelphidium poeyanum

also displaying widespread occurrence.

Benthonic foraminiferal abundance, as numbers of individuals per 1 gm of

sediment, is unevenly distributed (Fig. 4.7). Maximum abundance is recorded at TFB2

and an abundance of less than 120 individuals per gram is found in stations TFB6, TFB7,

TFB8, and TFB13. A higher percentage of stained (alive) than non-stained (dead)

benthonic foraminifera is also recorded at stations TFB7, TFB8, TFB9, TFB10 and

TFB26 (Fig. 4.8). Planktonic forms have a general abundance of less than 10% but are

recorded as over 20% of the identified sample at stations TFB10 and TFB15 (Fig. 4.9).

Figure 4.8 – Stained (live) versus unstained (dead)benthonic foraminiferids as a percentage of thetotal assemblage.

Figure 4.9 – Abundance of planktonic and benthonic forms as a percentage of total identified foraminiferal assemblage.

36

Table 4.1 – Breakdown of deformities encountered (as a percentage of the total benthonic population) .

Figure 4.10 – Ternary plot of the Twofold Bay marineassemblages. P = porcellaneous, Hy = hyaline, A = agglutinated.

Station

Figure 4.11 – Abundance of wall structure types as percentage of total identifiedbenthonic foraminiferal assemblage. Porcellaneous wall structures correspond withthe Miliolina type, hyaline structures with the Rotaliina type and agglutinated wall structures with the Textulariina type.

37

Deformities among benthonic foraminifera were relatively infrequent with high

abundances generally restricted to a small number of stations (Table 4.1; Appendix 4.6).

The highest occurrence of partial dissolution is found at TFB4 (10%), with dissolution

minimal elsewhere. Chamber distortion is only notably recorded from stations in the

northern region (stations TFB14, TFB26, TFB16, TFB17 and TFB18) and is largely

restricted to irregular chamber sizes in the Elphidiidae group. Almost all stations record

broken foraminifera, with the highest occurrence noted at stations TFB6, TFB9 and

TFB16 (each 5%). Discolouration is identified as the most common deformity with

greatest abundance recorded in the entrance and Eden harbour (TFB11, TFB13, TFB14,

TFB26, TFB15, TFB16, TFB17 and TFB18). These stations record an average

discoloration rate of 20% with highest abundances found at TFB16 (30%). The average

abundance for the remaining stations is 5%. The species most frequently found to be

discoloured were Q. incisa and T. trigonula, with Q. seminula, A. beccarii and E.

advenum var. 1 also regularly discoloured.

Wall structure analysis reveals the dominance of hyaline forms with

porcellaneous types sub-dominant throughout the bay (Fig. 4.10; Appendix 4.7). This is

expected due to the widespread abundance of the Elphidiidae, Rotaliidae, Cibicididae and

Glabratellidae families. Agglutinated structures only obtain >4% abundance in stations

from the entrance, Snug Cove and Cattle Bay (TFB11, TFB13, TFB26, TFB15, TFB16,

and TFB17), with maximum abundance is recorded at TFB16 (14%) (Fig. 4.11).

While all stations fall within normal marine Fisher Alpha diversity values, species

diversity is shown to vary around the bay (Table 4.2). Lowest diversity (α 8-9) is

recorded in the western bay (station TFB3) while highest diversities (>α 20) are found

independently at stations from the eastern and northern regions (TFB11, TFB26 and

TFB18). Most stations in the bay’s entrance (TFB1, TFB10, TFB11, TFB13 and TFB14)

record diversity scores of α 16 or above, indicating steadily high diversities.

Foraminiferal similarity matrices constructed using standard and squared

Euclidian distances resulted in slight variations between clustered associations (Fig.

4.12). Each analysis confirms the presence of three distinct foraminiferal provinces which

correspond with western shore, open water, and harbour settings. Using the standard

Euclidian distance Association A encompasses stations TFB12 and TFB18 (Fig. 4.12a),

whilst the squared Euclidian distance links these stations late to Association B (Fig.

4.12b). Association scores were calculated for all benthonic foraminifera in each

statistical association (Table 4.3, Table 4.4). Despite the variations in association

38

Table 4.2 – Graph of Fisher Alpha Diversity Indices for stations within Twofold Bay based on both total benthonic assemblage and stained benthonic assemblage.Note: Fisher Alpha Indices require a minimum of 100 individuals to estimatediversity. Asterisks denote stations where an informed estimate of diversity was made. Blanks indicate stations where 100 individuals were not recovered.

composition, the characteristic taxa of associations A-C remains altered. Due to this

feature combined with the late linkage under squared Euclidian distancing all discussions

of foraminiferal distributions will herein refer to Fig. 4.12a.

Figure 4.12 – Dendrographs for the distribution of total foraminiferal assemblages within Twofold Bay: (a) associations determined under standard Euclidian distancing, (b) associations determinedunder squared Euclidian distancing. Clusters deemed as significant are coloured and labelled withletters corresponding to foraminiferal associations described in the text.

a. b.

39

Tab

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4.4

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tati

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(Fig

. 4.1

2a).

40

Chapter 5: Discussion

Field observations are useful in exploring the spatial shift in a number of

individual parameters; however, the use of these trends in establishing a broader

environmental narrative is inherently subjective. Cluster analysis is able to characterise

statistically similar provinces which field observations alone cannot. By exploring the

totality of the physical and faunal data these analyses are able to recognise statistically

significant regions of physico-chemical and faunal similarly. When integrated and

assessed in unison, these analyses reveal significant ecological provinces with a

resolution unachievable through standard methods. It is therefore only through a

combination of field and statistical observations that an environment can be confidently

characterised in a holistic and objective manner.

5.1 Abiotic facies

Abiotic conditions appear relatively homogenous in Twofold Bay, with the

measured parameters showing little change between stations. Depth and DO are

exceptions and serve to separate the bay’s three abiotic associations (Fig. 4.2.)

Recorded bottom water salinities of Twofold Bay are notably lower than expected

(28-30 psu). In principle, bottom waters commonly have salinities of 34-37 psu, while

estuarine bottom waters experience strong fluctuations in salinity and oxygen (Potter et

al., 2005). Due to the fact only bottom water samples were collected results are

representative of this environment only, however two hypotheses are proposed. Reduced

salinities may potentially be affecting the entire water mass due to El Niña conditions

causing above average rainfall and riverine discharge into the bay prior to sampling. The

5-8 day flushing time estimated by Forteath (1996) could serve to temporarily dilute

Twofold Bay and extensively reduce salinities throughout the entire water column.

However, submarine groundwater discharge is a more plausible cause of decreased

bottom water salinities. Shifts in the freshwater-saltwater interface are controlled by

seasonal changes in water table elevation and lateral migration, with the interface

regularly moving landward in winter and seaward in summer (Michael et al., 2005). The

abnormally wet summer experienced in the Eden area would serve to recharge and lift the

41

water table, moving the freshwater-seawater interface into the coastal realm with the

submarine groundwater discharged into nearshore areas. This would serve to reduce

bottom water salinities, until the effect is minimised via dilution. A combination of the

two hypotheses is likely, but separation would be hard without isotopic work of the

groundwater reservoir. This is beyond the scope of this study.

DO levels are highest in the inner bay and decrease in Eden Harbour and the

entrance to Twofold Bay, with lowest levels of DO recorded at TFB9 (69.6%). This

Edrom Bay location coincides with dense Zosteraceae seagrass beds, including Zostera

muelleri and Heterozostera tasmanica species (Pollard and Rankin, 2003). These

seagrass beds, located inshore of the Multi-Purpose Naval Ammunitioning Wharf, could

result in localised depletion of oxygen due to decomposition of seagrass and subsequent

increase in particulate organic material (Eyre and Ferguson, 2002). However, similar

seagrass beds are also located in Quarantine Bay (station TFB1) and north East Boyd Bay

(station TFB10), and no related drop in DO is recorded (Pollard and Rankin, 2003). Lack

of circulation at TFB9 is potentially a factor due to its high degree of natural shelter,

however the breakwater at Quarantine Bay would also serve to reduce circulation yet no

trend is evident between the two locations. More information is required to explain the

cause of this discrepancy. Interestingly, DO levels recorded within Snug Cove (stations

TFB14, TFB26, TFB15 and TFB16) are comparative with levels recorded from the open

water stations despite recovered sediment being black (7.5YR 2/1) and pungent,

suggesting dysoxic conditions. This incongruity may be a result of inaccurate

measurements or the sediment reflecting seasonal patterns of dysoxia. Further study of

this location is needed to quantify potential stresses on benthonic foraminiferal

populations.

5.2 Sedimentary facies

Provinces of sediment with similar grain size as determined through cluster

analysis (Fig. 4.5) indicate a number of geographically restricted facies (Fig. 5.1). These

facies are likely the result of bottom currents and water circulation within Twofold Bay

and are named for the dominant substrate type.

42

5.2.1 Association A: Very Fine–Fine Sand

Stations TFB1, TFB2, TFB3, TFB4, TFB5, TFB9, TFB12 and TFB15.

This association is characterised predominantly by a very fine to fine sand

fraction, and a notable silty tail (Fig. 4.6a). The bulk of these stations are located in the

inner bay, where the fine, mica-rich tailings of Towamba River are distributed by

clockwise currents. Despite shallow depths, wave action is reduced due to diffraction

resulting in a low to medium energy environment.

TFB9 is included in this association due to its high proportion of very fine sands

and comparatively large fine silt content. While this may be at odds because it is

geographically removed, TFB9 is a logical inclusion as this station is relatively sheltered

due to the Harris-Daishowa Woodchip Wharf, the prominent adjacent headlands and its

Figure 5.1 – Geographical distribution of sedimentary associations derived from the clusteranalysis dendrogram in Fig. 4.5.

43

north-facing aspect. Local seagrass beds further act as a sediment trap, and are potentially

responsible for the increased silt component (Pollard and Rankin, 2003).

TFB15 records a finer sand component than its surrounding stations, and displays

an almost equal distribution of all size ranges spanning from very fine silts to fine sands.

This is likely due to natural sheltering within Snug Cove and reduced fluvial and oceanic

current penetration.

This study is largely in agreement with the Fine Sand (Quartz + Lithics + Mica)

province designated by Hudson (1991). Exceptions are TFB9, which falls within the Fine

Sand (Carbonates) province, and TFB12, which was characterised as Coarse Sand

(Quartz + Carbonate). This could be due to insufficient resolution of provincial

boundaries afforded by the small number of samples used in this study, or changes in

hydrological characteristics between the two studies.

5.2.2 Association B: Fine–Medium Sand

Stations TFB14, TFB26 and TFB18.

This association has a restricted geographical occurrence and is characterised by a

varied grain-size range (Fig. 4.6b). This association displays an increased bimodality of

grain size distribution, with the recurrence of very fine-medium silt components. A fine-

grained fraction is largely expected due to the sheltered nature of this setting. The

localised dominance of fine-medium sands could be attributed to the Eden Breakwater

serving to impede longshore transport of sands, effecting their precipitation. Distributions

of medium sand are less peaky than the Medium Sand association, and stations within

this grouping also display an increased fine sand fraction, further indicating calmer

conditions than experienced in Association D (as discussed below).

5.2.3 Association C: Medium–Very Coarse Sand

Stations TFB6 and TFB13.

This association is recorded from two stations and is treated as a separate

association due to its late linkage with Association D (Fig. 4.5) and its large distribution

of medium to very coarse sands (Fig. 4.6c). Both stations were difficult to sample with

44

very little sample retrieved via grab sampling, indicating submarine rock outcropping of

neighbouring material (Torarago Point and Lookout Point, respectively). The coarseness

of this sample is potentially due to shoaling which removes finer substrates, leaving

coarse sands atop bare outcrop. Interestingly, station TFB13 falls clearly within this

association, while its neighbouring station, TFB12, records no coarse sand. This indicates

a localised and restricted change in bottom-sediment environments and warrants further

investigation.

Again, this association is in agreement with conclusions drawn by Hudson (1991),

with TFB6 falling within the Coarse Sand (Quartz + Lithics + Mica) province and TFB13

within the Coarse Sand (Quartz + Carbonate) province.

5.2.4 Association D: Medium Sand

Stations TFB7, TFB8, TFB10, TFB11, TFB16 and TFB17.

This association is largely restricted to high energy sites in the deep entrance

where active fluvio-marine mixing occurs, and to a lesser extent in Cattle Bay where

energy levels are slightly higher than those encountered in Snug Cove.

A comparatively reduced percentage of medium sands and slight bimodality is

recorded from stations TFB16 and TFB17 (Fig. 4.6d), however the proportion of fine

particles is not nearly as dominant as Association B. This increase of silt is again

attributed to mixed energy conditions within Cattle Bay. The remainder of stations are

likely affected by marine currents, tidal forcings and fluvial outputs. The highest

abundance of medium sands as evidenced at TFB8 could be the effect of slightly stronger

bottom water currents related to the outlet of Towamba River, or a relict of dredging for

the Naval Ammunitioning Wharf. Station TFB7 has a reduced abundance of medium

sands and an increased grain size distribution, likely due to slightly increased distance

from the river mouth.

In this instance, this association does not appear to correspond with any single

province outlined by Hudson (1991). TFB7 and TFB8 fall within Hudson’s Coarse Sand

(Quartz + Lithics + Mica) province, TFB10 and TFB11 within the Coarse Sand (Quartz +

Carbonate) province, and TFB16 and TFB17 within the Fine Sand (Quartz + Lithics)

province. This is likely due to the restricted sampling undertaken in this study. Increased

45

sampling would refine the geographical extent of the facies as well as better define its

characteristics.

5.3 General distribution of total foraminiferal populations

The distribution of foraminifera is the result of two main environmental

conditions: the normal habitat to which a species has adapted, and the effects of post-

mortem transport. An analysis of the abundance of individuals (population) and the

variety of species (assemblages) makes it possible to recognize overall distribution trends

of total populations as well as any slight changes in population composition in an

environment. These variations suggest a persistent alteration in the environmental

conditions experienced between locations, and are important indicators of different

ecological regions. While analysis of total foraminiferal populations can often suggest

various boundaries to distribution, integrated statistical analysis is necessary to

effectively delineate ecological provinces (biotopes).

In Towamba River, Fisheries Creek, Nullica River and Curalo Lagoon

foraminiferal populations were found to be insufficient for this study. Assemblage studies

have therefore not been carried out on these locations due to inadequate counting

statistics. Two explanations are proposed: that (a) foraminiferal populations are naturally

Figure 5.2 – (a) Relative abundance of the three suborders of benthonic foraminifersin Twofold Bay as a percentage of total population; (b) Comparison of the three suborders as a number of species identified from the total benthonic population.

a. b.

46

limited in these areas; and (b) the flood events of summer 2010-2011 served to flush the

foraminiferal populations into Twofold Bay, with recruitment insufficient to be registered

in the February 2011 sampling. These hypotheses are supported by the predominance of

coarse sand in these samples, indicating regular high energy environments.

In conjunction, sites near the outlets of major estuaries may be altered by these

flood events. The sea floor may be covered with fluvial sediment which serves to bury

the natural biocenose and alter the recorded foraminiferal populations. It is important to

note that the following discussion represents a narrow window in time, and that the

application of trends to all temporal and seasonal scales would be imprudent. Such trends

can only be accurately determined through repeat studies.

The benthonic foraminiferal fauna of Twofold Bay is shown diagrammatically in

Fig. 5.2 where the number of individuals forming the three suborders are expressed both

as a percentage of the total recorded population (3542 individuals), and as the number of

species within this population. The species identified in this study are common along the

eastern coast of Australia. Most species are present in nearly all stations, suggesting

Figure 5.3 – A visual guide to the distribution of total benthonic foraminiferalpopulations, as a calculation of number per gram of sediment (from Fig. 4.7).Contouring is automatically generated and as a result, does not accurately representsome stations (e.g. TFB9). However, two regions of high population abundance (TFB2and TFB12) are easily recognisable, as are zones of reduced abundance (TFB6, TFB7,TFB8, TFB13, TFB16). Low population densities off Whale Beach (Towamba River)are the result of high energy experienced at these sites, while decreased abundances inEden Harbour are likely due to restricted circulation and periods of dysoxia.

47

marine conditions are widespread. All the sampling stations are interrelated and directly

dependent upon exchange with marine waters.

The distributional map of the total benthonic foraminifera, as a calculation of

number per gram of sediment, (Fig. 5.3) reveals very low population densities on the

southern side of Twofold Bay at stations TFB6, TFB7 and TFB8. This may be related to

the total instability of the bottom sediment, due to active tidal reworking and the effect of

shoaling on Torarago Point, or fluvial influences from Towamba River. The low

abundance value shown by station TFB13 near Lookout Point suggests relatively high

sediment mobility and active reworking. This is supported by coarse grain sediments, and

may be caused by ocean current diffraction against submarine rock outcrops creating

turbulent localised currents.

The relatively high abundance of populations at stations TFB2, TFB9, TFB12 and

TFB18 indicate a low sediment input with large collection of foraminiferal tests (Albani,

1993). By contrast, stations TFB4, TFB5, TFB11, and TFB17 reflect either a greater

sediment input or elevated erosion, although neither to the extent of stations of lowest

abundance. Interestingly, low abundance values at stations TFB1, TFB14, TFB26,

TFB15 and TFB16 correspond with areas of high marine traffic (Quarantine Bay and

Snug Cove). All stations are sheltered, with dominant fine grain sediment components,

suggesting possible nutrient deficit or partial pollution effects due to restricted

circulation.

Alternatively, the abnormally high population density at stations TFB2, TFB9 and

TFB12 could be the result of increased nutrient input. Studies indentify that increased

nutrient supply stimulates the growth of benthonic foraminiferal communities, with local

populations often several orders of magnitude greater than surrounding areas (Watkins,

1961; Bandy et al., 1965; Schafer and Cole, 1974; Mojtahid et al., 2008). However,

studies also indicate that increased nutrient input allows foraminifera to reach their full

growth potential and results in anomalously large test sizes and robust forms (Setty and

Nigam, 1984; Yanko et al., 1994). Only one station (TFB9) recorded notably robust

foraminifera, while TFB2 showed the inverse (small and delicate tests) and TFB12

displayed no apparent change in test size or thickness

These inconsistencies suggest variations in the stability of nutrient levels. The

reduced size of foraminifera and increased population density at TFB2 suggests an

increased abundance of juvenile forms. This mixed population might reflect episodic

nutrient pulses which promote foraminiferal reproduction (Loubere and Fariduddin,

48

1999). Conversely, the large and robust forms recorded from TFB9 indicate permanently

raised nutrient levels. This is likely attributed to the presence of dense seagrass beds at

this location which produce organic carbon, particulate organic matter and cause a

localised nutrient increase through seagrass frond decay (Zieman and Zieman, 1989; Eyre

and Ferguson, 2002). In addition to a large food supply, seagrass beds also provide

stability, shelter and anchor for a diverse biota (Posey, 1988; Sen Gupta, 1999). These

seagrass beds and the numerous roles they play may be another explanation for the

localised rise in population density and robustness of benthonic foraminifera in Edrom

Bay.

Stability of the benthonic environment can be assessed by comparing population

abundance and population variability, as indicated by the number of species which form

the population (Albani, 1993). Stable environments can support a diverse community

structure whereas unstable environments tend to have fewer, more highly adapted

species. The number of individuals expected in one gram of sediment has been replotted

and related to the number of species identified from each Twofold Bay station (Fig. 5.4).

As the amount of sediment analysed at each site was not constant, the number of species

is expected to be slightly higher than the numbers used here. However, this is sufficient

to give a graphic representation of stability.

Stations TFB6 and TFB13 appear to be the least stable, which is to be expected

from to their coarse sand fractions. Stations TFB7 and TFB8 reflect instabilities expected

in an environment subject to constant wave and tidal activity. Similar instabilities are

reflected in stations TFB1, TFB14, TFB26, TFB15 and TFB16 which appear to suggest a

local increase in sediment mobility. However this is unsupported by sedimentary

Figure 5.4 – Substrate stability shown by the relationship between number of species identified from a station and total number of individuals estimated per 1 gm of sediment.

49

analysis. Increased silt component suggests low energy environments with other

unknown factors likely responsible for population instabilities.

The distribution of planktonic foraminifera reflects the oceanic contribution and

depositional features of the open embayment, and transportation into the near-shore by

surface and tidal currents. Only adult planktonic individuals were found in this study,

which suggests an incomplete life assemblage and implies significant transportation

effects. Adult forms are significantly more robust than juveniles and are analogous to

sand grains in transportation, being buffered by bottom-water currents and deposited in

areas of varied energy flows (P. De Deckker, 2011, pers. comm.). Stations TFB10 and

TFB15 record the highest number of planktonic individuals, indicating that conditions at

these sites allow for the settling of their tests (Fig. 4.9). The predominance of planktonic

species in the entrance region is expected with precipitation of tests likely due to

increased ocean current diffraction around Jews Head. Increased abundance at station

TFB15 can also be attributed to ocean current transportation, with marine forms being

identified up to 80 km inland until a change in current energy initiates their precipitation

(Wang and Chappell, 2001). Conversely, low abundance values at TFB7 and TFB8

reflect high energy flows while the near absence of planktonic foraminifera at TFB16 and

TFB17 also suggest the existence of consistent stronger currents.

As a measure of extant species the number of stained (live) individuals is

compared with the number of unstained (dead) individuals (Fig. 4.8). Stations TFB1 and

TFB15 record the greatest proportion of unstained tests, with 85-92% of their respective

recorded assemblages nonreactive to staining. This is not surprising, as both stations are

sheltered harbours where dead tests are likely to have been transported and deposited.

This supports the low energy conditions identified for these sites through sedimentary

analysis.

Stations TFB6, TFB7 TFB8 and TFB9 record the greatest proportion of stained

foraminifera, suggesting an overall favourable environment. However, this is misleading

as low population densities and coarse grain sediments indicate high energy conditions. A

high energy environment would remove dead tests through tidal and current forcings,

leaving only those foraminifera who are alive and can sufficiently attach to the substrate.

This would account for the high proportion of living foraminifera recovered from this

site. As a result, information gathered from these live/dead techniques indicates the same

conditions determined through sedimentary analysis and signify a robust measure of

environmental characteristics.

50

Variety within the benthonic population is given through a comparison of the

number of individuals with the number of species (Fig. 5.2). Of the three foraminiferal

orders, the Rotaliina has the highest occurrence (71% of the total population; 24 common

species) with Miliolina the next dominant (27% of total population; 8 commonly

recurring species). However, the Textulariina behave atypically by first occurring in the

open marine setting and recording highest abundances in Cattle Bay and Snug Cove. This

is at odds with estuarine studies which show textularids to have higher abundance in

areas of freshwater influence, with higher salinities generally favouring calcareous tests

(Scott, 1974, 1976). Interestingly, a similar trend of higher abundance of agglutinated

forms with increased marine influence was noted from Broken Bay (Albani, 1978).

Further atypically, textularids in Twofold Bay first appear in areas of greatest

depth. Traditionally, the textularid to rotalid ratio is used as indicator of palaeodepth – the

former decreasing or increasing with falling or rising relative sea level, respectively, and

the latter increasing or decreasing, respectively (Mason and Laws, 2011). However, this

is unsupported in this study as textularids are completely absent from the western regions

despite relatively invariant salinities. The restricted distribution of textularids to the

entrance and Eden Harbour may therefore be related to other environmental factors such

as comparative oxygen depletion or organic matter ‘build-up’ (Albani, 1978; Mojtahid et

al., 2008). Further information is required to explain these distributions.

Foraminiferal diversity is high throughout the entire study site according to the

Fisher Alpha Diversity Index (Table 4.2). Fisher Alpha is used as an indication of

environmental stress, with marine associations having higher mean diversity values (α

6.5-21) than brackish associations (α 1-3.5; Hayward et al., 1999). Diversities within

Twofold Bay are lowest at station TFB3 (α 8-9) and TFB4 (α 10-11), with comparatively

low diversities also recorded around the Towamba River mouth (TFB6, TFB7 and TFB8:

each α 11-12). The low Alpha Index of TFB3 is a result of the restricted number of

species identified from this station, despite the overall high population density. On the

other hand, stations TFB6, TFB7 and TFB8 display a stable number of species, but with

vastly reduced total populations suggesting. This indicates an environment restricted to a

small number of species which have a higher tolerance of instable conditions. This

restricted niche is supported by low stability scores (Fig. 5.8) and coarse grained

sediment (Figs. 4.6c and 4.6d) which suggest high energy conditions.

As expected, diversities increase at the entrance with increase marine influence,

with the highest diversities recorded at stations TFB11, TFB26 and TFB18 (each >α 20).

51

While this is potentially influenced by post-mortem distribution and the increased

proportion of unstained tests in these sites, diversities remain comparable when Fisher

Alpha indexes are calculated using only the stained (live) benthonic population. This is

true of all stations that recorded >100 stained individuals, with TFB2 the only exception.

This indicates that the Fisher Alpha Index is an accurate indicator of species diversity,

regardless of whether total or live populations are used.

Despite Twofold Bay being subject to high amounts of marine traffic and several

shore-based industries, deformities were relatively infrequent and no gross abnormal

morphologies noted from any station (Table 4.1). Frequent small distortions of the test

(over inflation of the last chamber and abnormal test periphery) were restricted to Snug

Cove and Cattle Bay, and largely effected Elphidium advenum var. 1, Elphidium crispum

and Cribroelphidium poeyanum. The largest record of chamber distortion was from

station TFB17, however even this was restricted to less than 6% of the total population.

While aberrant morphologies are widely used as pollution indicators, percentages of

morphological abnormalities in areas of high contamination are vastly higher than

experienced in this study (30% of total populations in Yanko et al., 1998; 16% in

Romano et al., 2008).

The small and infrequent aberrations recorded from Snug Cove and Cattle Bay are

likely the result of natural stresses such as availability of food, natural fluxes in pH, or

possible periodic dysoxic conditions (Murray, 1963; Le Cadre et al., 2003).

Discolouration is frequent within stations TFB11, TFB13, TFB14, TFB26 and TFB15

and has the highest abundance at TFB16, suggesting organic build-up and eutrophication

of bottom sediment in Eden Harbour. Similarly, the fluctuation of oxygen within Eden

Harbour is suggested by the increased number of foraminifera displaying effects of pyrite

or iron oxide staining. While still restricted to less than 6% of the total population,

abundance of tests with pyrite infilling or pyretic grains on the external surface is highest

within Eden Harbour (stations TFB14, TFB26 and TFB15). This indicates dysoxic

bottom sediment, either as a constant condition or intermittently. Seasonality may be an

important factor, with increased dysoxia likely over the summer. Repeat studies and

down-core analysis would reveal the extent and frequency of such aberrations, and

determine their seasonal and annual extent.

52

5.4 Foraminiferal biotopes

The environmental trends interpreted through analysis of sedimentary and

foraminiferal data is strengthened through the production of biotopes and the

identification of their principle components. These biotopes not only delineate

statistically significant regions of similarity, but provide an overall view of dominant

environmental characteristics.

Three benthonic faunal associations were identified from a dendrogram produced

by cluster analysis (Fig. 4.12a). These clusters, linked on the basis of faunal

characteristics, are interpreted as a function of the physico-chemical parameters which

may be responsible for the variation in faunal composition (Fig. 5.5). The biotopes are

interpreted as reflecting more or less energetic environments, as indicated by average

grain size distributions (Fig. 5.6). Based on these correlations, these biotopes indicate a

mildly energetic nearshore environment, affected primarily by wave action, a highly

energetic, large fluviomarine mixing zone, and a more or less energetic harbour

environment affected primarily by tidal currents.

The various biotopes are named according to the most conspicuous geographical

unit that they occupy, with the terminology used being restricted to Twofold Bay.

Figure 5.5 – Foraminiferal biotopes of Twofold Bay and their relationship interpretedas a function of physico-chemical parameters.

53

Geographic distributions are shown in Fig. 5.7. Each biotope is identified both in terms of

its characteristic species (as determined by the highest association score: Table 4.3) and

its predominant assemblage (those species with the highest occurrence: Appendix 4.8). It

must be remembered that the characterising specie/species is defined by the degree of

variability associated with relative abundance and the degree to which that species is

Figure 5.6 – Average grain size distributions for the three Twofold Bay biotopes,recording the average percentage weighting of each grain size fraction.

Figure 5.7 – Geographical distribution of the three biotopes derived for Twofold Bay fromthe cluster analysis dendrogram in Fig. 4.12a.

54

restricted to one association. This accounts for why each association is defined by a

separate species, while the predominant assemblage remains similar across all stations.

5.4.1 Inner Bay Biotope – Elphidium advenum

Stations TFB1, TFB2, TFB3, TFB4, TFB5, TFB12, TFB18.

Depth: 7-11 m, pH: 8.49-8.67, EC: 54.6-54.9 mS/cm, DO: 74.1-80.6%,

salinity: 28-30 psu. Sediment: very fine sand. Diversity: α range: 8-20;

mean α: 13-14.

This biotope is dominant in Nullica Bay, and occupies the western landward part

of Twofold Bay and a single station in the bay’s entrance. Its boundary with the Outer

Bay Biotope on the southern shore corresponds with a distinct change in substrate. The

Inner Bay Biotope is characterised by fine sands associated with fluvial currents and

medium wave action with the exception of TFB12. This station forms its own subcluster

indicating that it is influenced by different factors than its surrounding stations. A coarse

silt-fine sand component would indicate reduced energy however this is at odds with its

surrounding stations. This abnormality is inexplicable as no geomorphological difference

between TFB12 and its surrounding sites is noted. This warrants further research.

This biotope is characterised by Elphidium advenum, with Glabratella

patelliformis and Rosalina bradyi also producing high association scores. The

predominant foraminiferal assemblage consists of nine species:

Rosalina bradyi Elphidium advenum

Ammonia beccarii Cribroelphidium poeyanum

Glabratella patelliformis Quinqueloculina incisa

Quinqueloculina seminula Glabratella australensis

Nonionella auris

The high number of individuals (1717) indicates minimal sediment input, with the

presence of seagrass beds in Quarantine Bay and a high individual to species ratio

indicative of its stability. The presence of C. poeyanum, a small form generally correlated

55

with low energy environments, also indicates minimum sediment input and movement

(Albani, 1993).

The absence of textularids indicates freshwater influence in this biotope is not

strong. When compared to the remaining biotopes reduced marine influence in the Inner

Bay is also suggested by the increased abundance of Rosalina bradyi and Ammonia

beccarii and the reduced record of Elphidium spp.. Previous studies have shown A.

beccarii to be characteristic of less marine conditions, i.e. low-nutrient fluvial areas, with

higher salinity (normal marine) assemblages generally dominated by Elphidium spp.

(Albani and Johnson, 1975; Haslett, 2007). It must be noted that while most Elphidium

species in this association have low abundances, E. advenum is the exception. The

association of A. beccarii and a single Elphidium species is also recorded elsewhere in

Australia, where an A. beccarii-E. advenum association is recorded from a muddy sand

facies in Gippsland Lakes (Apthorpe, 1980). The same association is widely reported

from sheltered sand flats and beaches in New Zealand, indicating certain Elphidium

species may be more euryhaline than first thought (Hayward and Hollis, 1994).

5.4.2 Outer Bay Biotope – Lamellodiscorbus sp. 1

Stations TFB6, TFB7, TFB8, TFB9, TFB10, TFB11, TFB13.

Depth: 18-23 m, pH: 8.57-8.67, EC: 54.6-54.9 mS/cm, DO: 76.5-79.5%,

salinity: 28.5-30 psu. Sediment: medium to coarse sand, in places very

coarse sand and slightly shelly. Diversity: α range: 11-20; mean α: 15-16.

This biotope dominates the eastern part of Twofold Bay, from Kiah Inlet to East

Boyd Bay and the deep open entrance. A distinct change in sediment type marks its

northern boundary with the Harbour Biotope. Characterised by medium to coarse sands,

the Outer Bay Biotope is associated with the high energy environments characteristic of

strong tidal and ocean currents.

This association is characterised by Lameollodiscorbus sp. 1, with E. crispum

sub-dominant. Textularids first appear in this biotope, with Textularia conica and T.

sagittula atrata the most abundant forms. The Outer Bay Biotope is characterised by the

following foraminiferal assemblage:

56

Lamellodiscorbus sp. 1 Quinqueloculina seminula

Elphidium crispum Triloculina trigonula

Quinqueloculina incisa Elphidium advenum var. 1

Rosalina bradyi Ammonia beccarii

Glabratella australensis Cibicides sp. 2

Energy flow is often demonstrated by increased abundances of foraminifera with

thicker, heavier tests (Albani, 1993). When compared to the Inner Bay Biotope, the

increased flow energy of this biotope is suggested by the reduced abundance of C.

poeyanum, the increased abundance of E. crispum, the presence of Q. seminula, T.

trigonula and Miliolinella circularis, and the increased abundance of the miliolid group

in general. Further indicative of an unstable environment with high levels of disturbance

are species such as Lamellodiscorbus sp. 1 which are represented by very large

individuals. Similar faunal associations were recorded in the Dropover and Channel

Biotopes of Port Hacking (Albani, 1993), and in the High-Nutrient Fluviomarine Biotope

of Broken Bay (Albani and Johnson, 1975). These regions were also associated with

mixing between fluvial and open marine waters and increasingly active environments.

5.4.3 Harbour Biotope – Elphidium advenum var. 1

Stations TFB14, TFB26, TFB15, TFB16, TFB17.

Depth: 6.9-10 m, pH: 8.49-8.6, EC: 54.7-54.9 mS/cm, DO: 85.2-87.2%,

salinity: 28-30 psu. Sediment: medium sand with fine silts, in places very

shelly and sometimes muddy. Diversity: α range: 14-20; mean α: 16-20.

This biotope is restricted to Snug Cove and Cattle Bay and is last recorded at

Cocora Point. Sediment is characterised by medium sands, with large populations of

disarticulated bivalves recovered from Snug Cove. The high distribution of silty sediment

types suggest reduced water circulation in this area, with sands likely a result of

infrequent storm events or longshore transport. This relative lack of throughflow is

suggested to cause the high level of test staining, increase in test deformities, and change

in wall structure composition.

57

The Harbour Biotope shows a reduction of the rotalids, with the textularids

recording their highest abundance (Fig. 5.8c). Trochammina inflata is the most dominant

textularid (4% mean abundance), while Haplophragmoides, Reophax, and Textularia are

also recorded.

This biotope is characterised by the widespread species E. advenum var. 1, which

records its greatest dominance in this biotope. The foraminiferal association is similar to

the Outer Bay Biotope, from which it differs by the reduced abundance of

Lamellodiscorbus sp. 1 and greater abundance of E. advenum var. 1. The dominant

foraminiferal assemblage is composed of:

Elphidium advenum var. 1 Elphidium advenum var. 3

Quinqueloculina incisa Rosalina bradyi

Elphidium advenum var. 2 Lamellodiscorbus sp. 1

Trochammina inflata Elphidium crispum

a. b.

c.

Figure 5.8 – Population abundance of the three foraminiferal types in each biotope as a percentage of total benthonic population. The Miliolina type corresponds with porcellaneous wall structures, Rotaliina with hyaline wall structure.

58

While substrate is deemed to define this biotope, an interesting incongruity

between increased Elphidiidae (6 of the biotope’s top 10 most abundant species) and

increased textularids (7% of the biotope’s total population) indicate that other factors are

also potentially important. Higher Elphidiidae diversities could be taken to denote areas

of increased salinity, possibly due to reduced fluvial mixing (Albani and Johnson, 1975).

However, T. inflata has been recorded from estuarine inlets and harbours in New Zealand

and suggests a slightly more brackish environment (Murray, 1991; Hayward and Hollis,

1994; Hayward et al., 1999).

An Elphidium sp. and Trochammina sp. association has been identified from

several athalassic (non-marine) saline lakes in Southern Australia which displayed

seasonal variations in environmental conditions and foraminiferal populations (Cann and

De Deckker, 1981). It was proposed that Elphidium sp. could survive the summer

evaporative episodes where salinities and eutrophication increased, by possibly entering a

dormant stage. This periodic dormancy when conditions become too harsh could account

for the presence of morphological irregularities in Eden Harbour’s Elphidiidae, but also

their restricted degree of deformity.

Cann and De Deckker (1981) also proposed that the euryhaline Trochammina sp.

dominated in organic rich sediments and could maintain continuing populations in the

ephemeral saline lake cycles. It is therefore suggested that the high T. inflata abundance

found in this study is representative of increased organic matter and low oxygen levels

linked to the summer season, and recorded due to timing of sampling.

The seemingly contradictory dominance of Elphidiidae and various textularids

found in this biotope is proposed to represent strong seasonal effects in Eden Harbour.

Repeat monitoring of the area, particularly concerning the presence of juvenile

specimens, would help resolve potential mixed conditions and determine whether

different groups reproduce and dominate under separate conditions.

In this study the overall examination of abiotic, sedimentary and foraminiferal

data produces comparable indications of environmental characteristics. Field

observations recognise the consistent spatial variability of a wide range of parameters

such as depth, available oxygen, nutrient supply, sediment type, and effects of waves,

tides and currents. While benthonic environments can be interpreted from these

parameters alone, this study shows that cluster analysis is a useful addition. Cluster

analysis is proven to be useful in determining the geographical extent of similar

59

parameters, and groups stations in a logical and meaningful manner. These statistical

clusters can then be used to knowledgeably characterise the ecologic limits of

foraminiferal distributions in a location-specific approach.

60

Chapter 6: Conclusions and Recommendations

6.1 Conclusions

In conclusion, this study demonstrates the effectiveness of CA in determining the

geographical distribution of similar characteristics. CA of abiotic, sedimentary and

foraminiferal data from Twofold Bay show consistent associations and indicate

significant relationships between sites. In this study the integration of field observations

and CA successfully characterises Twofold Bay in a holistic and objective manner,

revealing statistically significant environmental processes which are taken to influence

foraminiferal distributions.

Through statistical correlation this study recognises four sedimentary associations

in Twofold Bay:

1. Very Fine-Fine Sand Association – occupies the western part of the bay and

indicates medium energy environments largely linked to tidal and fluvial

action.

2. Medium Sand Association – predominantly occupies the open entrance to the

bay and indicates high energy environments linked to shoaling, tidal action

and intermittent oceanic currents.

3. Medium-Very Coarse Sand Association – geographically restricted to two

stations and potentially reflects submarine rock outcropping or strong

localised currents.

4. Fine-Medium Sand Association – restricted to the northern bay and reflects

mixed conditions. Bimodal substrates in Eden Harbour suggest mixed energy

environments, while high silt components from Snug Cove and Cattle Bay

indicate chiefly calm ports. The fine sand fraction found in this association is

likely the result of longshore transport or storm events.

This study also successfully serves as a baseline study into the composition and

distribution of modern foraminiferal populations. From the study of recent benthonic

foraminifera in Twofold Bay and its tributaries, a number of conclusions can be drawn:

61

1. Faunal densities in Curalo Lagoon, Nullica River, Towamba River and

Fisheries Creek are notably small. This is likely due to insufficient flushing

and high summer temperatures due its shallow nature in the case of Curalo

Lagoon, and high energy flows in the rivers.

2. The fauna of Twofold Bay is diverse and has a high degree of similarity,

indicating an even distribution of water qualities throughout the study area.

3. No substantial evidence of local pollution has been detected through faunal

depletion or morphological deformities.

4. The areas off Torarago Point (TFB6) and Lookout Point (TFB13) have poor

and quite unstable populations due to very high energy conditions.

5. Seagrass beds play a significant role in the composition and stability of

foraminiferal faunas in East Boyd Bay.

6. The fauna of the western landward extent of Twofold Bay generally display a

rich and diverse community of generally small forms. This is parallel with

relatively small sediment inputs and a relatively low energy environment,

despite being situated near the opening of the Nullica River.

7. The fauna of the eastern areas display higher diversity, reflecting an increased

marine influence. This area is also characterised by thicker, more robust

forms, reflective of a high energy environment, likely linked to the effects of

tidal action and open oceanic circulation.

8. The fauna of Eden Harbour display highest overall diversity and the highest

abundance of textularids. Staining of tests is common in this environment with

pyrite and iron oxide also identified, reflecting a low energy environment and

poor exchange.

This study successfully uses CA to determine three foraminiferal biotopes from

Twofold Bay. Through correlation of foraminiferal distributions and sedimentary

characteristics and associated environmental conditions, substrate type and energy

intensity are proposed as factors which limit foraminiferal geographical distribution and

composition in Twofold Bay. The biotopes indentified in this study are concluded as

such:

1. Inner Bay Biotope – occupies Nullica Bay and a single station in the entrance

to Twofold Bay. This rich biotope is characterised by Elphidium advenum,

with subdominant Glabratella patelliformis and Rosalina bradyi. Nine species

62

comprise the predominant foraminiferal assemblage and textularids are

notably absent. Substrate is predominantly very fine-fine sand (63-250 µm).

This biotope reflects a medium energy environment with minimum sediment

input and largely tidal forcings.

2. Outer Bay Biotope – dominates the eastern part of Twofold Bay, from Kiah

Inlet to East Boyd Bay and the deep open entrance. This biotope is

characterised by Lameollodiscorbus sp. 1, with E. crispum sub-dominant. The

fauna is dominated by forms with large and relatively thicker test and

Textularids first appear in this biotope. Substrate is medium-coarse sands

(250-1000 µm). This biotope reflects high energy environments characteristic

of strong tidal and ocean currents.

3. Harbour Biotope – geographically restricted to Snug Cove and Cattle Bay.

Sediment displays bimodality with very fine-coarse silts (2-63 µm) and

medium sands (250-500 µm). Characterised by the widespread species E.

advenum var. 1, this biotope records the reduced abundance of rotalids and

displays the highest abundance of textularids. Staining and test deformation is

most abundant in this association. This biotope reflects a low energy

environment of reduced water circulation and potentially significant seasonal

effects.

While field observations are useful in exploring a number of individual

parameters, this study demonstrates that integrated use of statistical treatments is

necessary to establish a broader environmental narrative. CA is effective in determining

environmental similarities across a broad scale, and can be used to postulate

environmental controls on benthonic foraminiferal associations. Localised ecologic

studies such as this are necessary to determine relationships between foraminiferal

composition and distribution and environmental parameters. Only through similar

baseline studies can the application of benthonic foraminifera as bioindicators be refined

for application in Australian coastal environments.

63

6.2 Recommendations for further research

This study was intended only as a preliminary investigation into the distribution

of Foraminifera within Twofold Bay, and the factors that limit their geographic trends.

The conclusions discussed above are inherently restricted to Twofold Bay, rather than

representing ubiquitous characteristics. In order to determine the degree to which trends

discovered here can be applied to other locations on the south-eastern coast of New South

Wales, further studies are recommended.

In order to refine which parameter is driving the correlations, it would be ideal to

carry out a comparable study in an area of similar size, shape and marine influence, but

one in which aquaculture and marine-based industry is limited and alterations to natural

harbours are few. Such studies would provide important baseline information regarding

pre-anthropogenic faunal composition and distribution.

While anthropogenic activities have not been isolated by this study as a direct

limiting factor, subsequent foraminiferal studies in Eden may help clarify the role that

human activities, such as shipping, cleaning of vessels, infrastructure construction and

dredging, have on benthonic populations. In order to assess anthropogenic stresses on

Twofold Bay, an ideal site would be Snug Cove, the main port of Eden. A down-core

study of Snug Cove would determine whether species distribution, densities and/or

composition have changed in Eden Harbour over time. Analysis of sediment cores would

help verify the possibility of mixed conditions within Eden Harbour and resolve the

extent to which seasonal effects impact foraminiferal composition. Ideally, these down-

core samples would pre-date anthropogenic use of the cove in order to explore the

temporal extent of test staining and deformations. This may serve to reveal how long

Eden Harbour has displayed dysoxic conditions, and whether conditions have been

exacerbated or reduced since intensive human use of the area.

While the estuarine data recovered in this study was not informative, the estuaries

must be revisited if down-core studies are to be performed. The foraminiferal fauna of the

main Twofold Bay tributaries (i.e. Nullica and Towamba Rivers) needs to be identified in

order to determine the degree of exchange between the estuarine and marine

environments. Such studies would be able to identify how much of the thanatocenose is

actually transported. This information would have secondary application with down-core

64

analyses of flood events or determining the historical freshwater extent into Twofold

Bay.

Further investigation is desired in order to determine the fidelity of the abiotic data

uncovered in this study. This study was conducted in an abnormal year and while there is

always variation in abiotic parameters the data recovered by this study may not be

reflective of average conditions. While possible explanations for the reduced salinity

trend have been discussed, future studies could address this issue by analysing a number

of CTD profiles of the water column. This would determine whether salinities are low

throughout the entire column or only from one layer. Seasonal profiles would also be

beneficial in order to determine whether the reduced salinity uncovered in this study is

the result of seasonal freshening, or a year-round occurrence. Ideally, this study should be

repeated in an average meteorological year, i.e. one that is under stable neutral conditions

and not subject to abnormal rainfall or flooding events. In doing so, true species densities

in Twofold Bay and its tributary estuaries may be revealed. Similarly, the ‘normal’ extent

of the fluvial influence of Towamba River may be determined.

Increased information regarding the bottom water currents of Twofold Bay would

help shed light on levels of energy experienced by the benthonic environment. This is

desirable in order to explore the extreme juxtaposition of neighbouring environments

suggested by stations TFB5, TFB6, TFB7 and TFB11, TFB12, TFB13, and determines

the regional extent of these high energy currents. The exploration of bottom-water

currents on both a seasonal and temporal scale would help to ascertain their importance

both in shaping live benthonic populations, and the distribution of dead tests.

Several trace element studies on the foraminifera of Twofold Bay are also

recommended. If significant salinity fluxes are found to be a common occurrence, their

temporal extent can be explored using trace elements or isotopic analyses of tests in a

down-core study. This would not only act as a potential proxy for groundwater discharge

events, but also continental rainfall. Trace elements can also be employed in order to

examine taphonomic processes, such as the degree to which the thanatocenose of

Twofold Bay is the result of transportation or reworking. Such studies would serve to

determine how accurately the foraminiferal fossil community reflects the living

ecosystem.

This study showed that aquatic vegetation is important in shaping foraminiferal

populations, however the distribution of seagrass beds are subject to change. Seagrass

meadows can change in response to light availability and changes in water movement due

65

to coastal developments or direct damage caused by fishing pressures, sand extraction

and dredging (Butler, 1999). The distribution and temporal extent of seagrass beds could

be explored through trace element or isotopic composition studies of foraminiferal tests

and current seagrass beds, such as has occurred using the otolith chemistry of juvenile

fish (Dorval, et al. 2005; Larkum et al., 2006). Such studies could isolate the occurrence

and potential causes of mass vegetative die-off events and, in conjunction with down-

core studies, could inform the role seagrasses play in the composition and health of

benthonic foraminiferal populations. Seagrass studies could also better refine the

relationship between vegetation and specific foraminiferal species.

Broadly speaking, there are inherent difficulties with any foraminiferal study such

as the one undertaken here. Scott et al. (2001) allude to the species identification problem

which describes the near impossibility of identifying a single species in isolation, and the

degree to which different micropalaeontologists either under or overestimate species

diversity by ‘lumping’ or ‘splitting.’ While this study aimed to identify foraminifera

accurately to species level across many samples, many encountered species could not be

satisfactorily found in compendia of identified and illustrated species. Additionally, these

compendia are based on Scanning Electron Microscope (SEM) micrographs which do not

adequately reflect what is seen when using a light microscope. As a result, slight

morphological differences noted between individuals were recorded in this study as

separate morphological variants. Ideally, identification books should present both light

and SEM micrographs of holotype forms and their accepted variants.

Random order of identification is also recommended for any similar foraminiferal

study in order to minimise problems of identification. While this method may make trend

spotting between samples difficult, it may also serve to limit the ‘splitting’ factor,

whereby slight differences in morphology are recorded as a separate species entirely.

On the same issue, future research into coiling directions of benthonic

foraminifera would resolve identification issues encountered by this study. Several

miliolids were found to have comparable sinistral and dextral forms, despite being

represented in the literature as being uniformly one or the other. As a result, such forms

were noted in this study as ‘var. dextral’ or the reverse. No literature was found regarding

changes in coiling direction of shallow, benthonic foraminifera. Future studies are

therefore needed in order to clarify whether a benthonic species can have mixed

directional coiling, or whether the variants uncovered in this study are truly separate

66

species. Genetic testing would easily resolve whether these forms represent different

genetic groups.

On a separate issue, this study originally intended to explore foraminiferal

distributions in conjunction with similar ostracoda studies. However, an inverse pattern

between these two groups was noted to occur in the study site as the sampled estuaries

were ostracod rich and foraminifera poor, while the main bay displayed the opposite

trend. This is of interest as normally these two microfaunal groups cohabitate and

therefore should reflect similar conditions. The incongruity between distribution patterns

and relative abundance of foraminifera and ostracods therefore warrants further research

regarding the Twofold Bay area.

These recommendations would greatly improve our ability to accurately identify

foraminiferal compositions and explore the complex relationships between environmental

conditions and foraminiferal distributions, not only Twofold Bay, but in a broader

Australian context.

67

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APPENDICES NOTE:

Appendix prefix refers to chapter number, with suffix relating to order within that chapter.

e.g. Appendix 3.1 = Chapter 3, first appendix

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Appendix 3.1 GPS co-ordinates of all sample locations referenced in this study. From top: T = Towamba River, C = Curalo Lagoon, N = Nullica River, F = Fisheries Creek, TFB = Twofold Bay.

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Appendix 4.1 Raw data of the abiotic parameters gathered for each Twofold Bay (TFB) station, as discussed in the text.

84

Appendix 4.2 Drivers of abiotic clusters were determined by plotting the mean and standard error at

95% confidence for each measured parameter and determining where the difference

between plotted values was greatest (depth [m], DO [mg/L], DO [%]).

85

86

Appendix 4.3 Raw data from the laser diffraction sedimentary analysis of all Twofold Bay (TFB) samples. Samples labelled ‘take 2’ indicate repeat analyses of their prefix station.

87

Appendix 4.4 Soil size fractions as referenced in the text, according to the standard British sieve size scale.

88

Appendix 4.5 Total foraminiferal species count data compiled from analysis of all Twofold Bay (TFB)

samples.

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90

91

92

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Appendix 4.6 Foraminiferal identification and deformity data sheets from each Twofold Bay (TFB)

station – see CD-ROM. Appendix 4.7 Data sheets detailing breakdown of benthonic foraminiferal wall structure from each

Twofold Bay (TFB) station – see CD-ROM.

Appendix 4.8 List of foraminiferal fauna from each biotope in order of highest abundance. Used to

determine predominant assemblages – see CD-ROM.