Tolerance and the Assessment of Heavy Metal Pollution in Sessile Invertebrates

Tolerance and the assessment of heavy metal pollution in sessile invertebrates

By Mailie L. Gall

Evolution and Ecology Research Centre School of Biological, Earth and Environmental Sciences University of New South Wales Sydney, NSW 2052 Australia

A thesis submitted in fulfillment of the requirements for the degree of a Masters of Philosophy

October 2010

PLEASE TYPE THE UI\IIVERSITY OF NEW SOUTH WALES 'Thesls/Olssertatlon Sheet

.Surname or fan1Vy nam\?: Gall

First name: Mailie Other nameis: Lee

Abbreviation for degree as given in the Umversity ca!endar: M Phil scnoci School of Science Faculty Biological, Earth and Environmental Sciences

Title; Tolerance and the assessment of heavy metal pollution in sessile invertebrates

Abstract 350 words maximum: (PLEASE TYPE}

Heavy metals are powertul agents of disturbance, and it is therefore important that stringent and effective monitoring practices be in place. This thesis examines the eco1ogical~relevance of metal accumulation in a biomonitor to sessile invertebrate fauna. However there is the potential tor effects of metals to be different depending on the level of tolerance of the population being sampled. Therefore, differential tolerance across four estuaries was examined ln a common sessile species.

The levels of metals were quantified around an industrialised harbour, Port Kembla, using the common native oyster, Saccostrea glomerata. Settlement plates were concurrently deployed at each site to capture the level of sessile invertebrate recruitment at each site. rncreaslng !eve!s of lead and copper were associated with severe decreases in the abundance of the native barnacle, Amphibalanus variegatus. !n striking comparison, positive correlations were found between the abundance of a cosmopolitan worm and lead and copper. The biomonltor was found to provide a sensitive measure of rnelais which were found to be of ecological~ relevance.

Organisms have been shown to develop tolerance to heavy metals, therefore, the effects measured may have been different depending on the level of tolerance in the community. Populations of the native barnacle, Amphibafanus variegatus, collected from within heav!ly~modified estuaries (including Port Kembla) were found to be more tolerant to a copper challenge than populations from within un-modified estuaries. High levels of copper were recorded within the heavily-modified estuaries compared to the un modified estuaries suggesting tolerance had developed in response to this contaminant.

In summary, metals were found to be correlated with severe effects ln the abundance of a native barnacle, however, populations of this species were found to be more tolerant to copper than populations from heavily-modified estuaries. This suggests that the same level of contaminants in pristine estuaries could potentiaHy have much greater impacts than measured in this study. It may also suggest that a greater tolerance may not equate to a greater ecological success.

Declaration

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iii

Abstract

Heavy metals are powerful agents of disturbance, and it is therefore important that stringent

and effective monitoring practices be in place. This thesis examines the ecological-relevance

of metal accumulation in a biomonitor to sessile invertebrate fauna. However there is the

potential for effects of metals to be different depending on the level of tolerance of the

population being sampled. Therefore, differential tolerance across four estuaries was

examined in a common sessile species.

The levels of metals were quantified around an industrialised harbour, Port Kembla, using the

common native oyster, Saccostrea glomerata. Settlement plates were concurrently deployed

at each site to capture the level of sessile invertebrate recruitment at each site. Increasing

levels of lead and copper were associated with severe decreases in the abundance of the native

barnacle, Amphibalanus variegatus. In striking comparison, positive correlations were found

between the abundance of a cosmopolitan worm and lead and copper. The biomonitor was

found to provide a sensitive measure of metals which were found to be of ecological-

relevance.

Organisms have been shown to develop tolerance to heavy metals, therefore, the effects

measured may have been different depending on the level of tolerance in the community.

Populations of the native barnacle, Amphibalanus variegatus, collected from within heavily- modified estuaries (including Port Kembla) were found to be more tolerant to a copper challenge than populations from within un-modified estuaries. High levels of copper were recorded within the heavily-modified estuaries compared to the un-modified estuaries suggesting tolerance had developed in response to this contaminant.

In summary, metals were found to be correlated with severe effects in the abundance of a

native barnacle, however, populations of this species were found to be more tolerant to copper than populations from heavily-modified estuaries. This suggests that the same level of contaminants in pristine estuaries could potentially have much greater impacts than measured in this study. It may also suggest that a greater tolerance may not equate to a greater ecological success.

Table of Contents

Abstract ...... iv

Acknowledgements...... viii

List of figures ...... ix

List of tables ...... x

General Introduction ...... 1 1.1 Overview ...... 1 1.2 Biomonitors...... 1 Interpretation of tissue concentrations in a biomonitor ...... 3 Biomonitors: an ecologically-relevant measure of metals contamination?...... 3 1.3 Tolerance and heavy metals ...... 4 The evidence for tolerance ...... 5 1.4 Sessile invertebrates and the assessment of marine pollution ...... 6 1.5 Research aims ...... 7 1.6 Thesis structure ...... 7 A biomonitor as a measure of an ecologically-significant fraction of metals in an industrialized harbour ...... 8 2.1 Abstract ...... 8 2.2 Introduction ...... 8 2.3 Materials and methods ...... 11 Site description ...... 11 Deployment of biomonitors and settlement plates ...... 12 Analysis of metal concentrations in oysters ...... 14 Data analyses ...... 14 2.4 Results ...... 16 Metal concentrations in oyster tissue ...... 16 Relationship between biological assemblages and environmental variables ...... 17 2.5 Discussion ...... 23 Implicating sediments as the source of metals ...... 23 Relationships between metal tissue concentrations in Saccostrea glomerata and associated fauna ...... 25 Implications for the use of biomonitors ...... 28

Differential tolerance to copper, but no evidence of population-level genetic differences in a widely-dispersing native barnacle ...... 30 3.1 Abstract ...... 30 3.2 Introduction ...... 31 3.3 Materials and Methods ...... 34 Study sites ...... 34 Larval collection ...... 36 24 h larval toxicity test ...... 36 Molecular methods ...... 37 Data analysis ...... 39 3.4 Results ...... 40

Variation in 24 h EC50 among estuaries ...... 40 Population genetics and evidence of selection ...... 42 3.5 Discussion ...... 43 Implications ...... 46 General Discussion ...... 48 4. 1 Accumulated metal concentrations in a biomonitor: broader ecological significance? ...... 48 4.2 A Biomonitor: a highly sensitive tool ...... 49 4.3 Generality of response across populations: the role of prior contaminant exposure...... 49 4.4 Implications...... 51 References ...... 53

References……………………………………………………………………..52

Appendix 1………………………………………………………………….…69

vii

Acknowledgements

Firstly, thank you to Emma and Alistair for providing ideas, support and motivation throughout this project. A very special thankyou to Emma for taking me on as a student, when you had so little to go on. I hope that the whole experience hasn’t been too regretful!

Thankyou Arron for being my rock over the last two years. Thankyou for the late nights, the cold, wet and miserable fieldwork days, the long weekends and putting up with me during all the stressful times.

I am grateful to everyone in the Johnston/Poore lab for their support and advice. The experience wouldn’t have been the same without you! I am especially grateful to Marty Hing for his guidance, expertise and help on all things marine and Port Kembla. Also to Ceiwen

Pease for being so-so-so handy and reliable in the field and in the laboratory. A huge thankyou to all the volunteers who have helped me carry out my research. Special thanks have to go to Halley Durrant and James Lavender for persisting with hours of barnacle plucking (trust me, it’ll look great on your resume)! And Katherine Dafforn, Graeme Clark,

Valeria and Mel Sun for collecting and looking after my barnacles.

viii

List of figures

2.1 Sampling sites within Port Kembla Harbour, Australia. Numbers refer to the site labels.

2.2. Distance-based redundancy analysis showing relationships between ordination of sites based on biological assemblages and the environmental factors. Environmental and biological variables overlayed vectors using multiple correlation type. - - - refers to biological variables and – refers to environmental variables. Species abbreviated as follows: AV, A. variegatus;

BL, B. leachii; HE, H. elegans; CN, C. nodulosa; AU, A. unicornis; BS, bare space; BM, B. magellanicus; SA, S. australis; ZV, Z. verticilliatum.

2.3. Scatterplots of the percentage cover of (a) bare space, (c) Amphibalanus variegatus, (e)

Celloporaria nodulosa (g) Arachnopusia unicornis and (i) Hydroides elegans against copper

concentrations. Scatterplots of the percentage cover of (b) bare space, (d) Amphibalanus

variegatus, (f) Celloporaria nodulosa (h) Arachnopusia unicornis and (j) Hydroides elegans

against copper concentrations. * denotes significant relationship (p < 0.01). † denotes log

transformation.

3.1. Map of study sites located along the NSW coastline, SE Australia. a) Botany Bay and b)

Port Kembla are industrialised estuaries; c) The Clyde and d) Wagonga Inlet are reference

estuaries. Circles represent the sites within each estuary at which A. variegatus were collected from. Levels of copper in the benthic sediments and tissue of oysters also measured at each of these sites (some exceptions, white and grey-filled circles represent sites where no copper measurement taken from the sediment and oyster tissue respectively, see Dafforn et al. 2012).

Stars represent the sites also used in the molecular study.

3.2. Copper content measured in the tissue of oysters and sediment (left axis, based on dry weight values) and mean EC50 24 h for Amphibalanus variegatus nauplii from each estuary

(right axis). Sediment and oyster tissue values from Dafforn et al. (2012). NB: mean copper

values presented are based on measurements taken from each of the sites at which A.

variegatus were collected from. Error bars represent standard error.

3.3. PCO plot of the AFLP fragments generated for the three Amphibalanus variegatus

populations and based on a Euclidean distance matrix.

List of tables

2.1. Mean metal concentrations (µg.g-1 wet weight) of each site measured in oyster tissues.

Bold denotes values above background concentrations.

2.2. A) DistlM tests for relationships between individual environmental variables and

composition of the sessile invertebrate fauna. B) Tests for relationships between

environmental variables and the composition of the sessile invertebrate fauna considering all

environmental variables the model. Bold denotes a significant relationship.

2.3. Correlation coefficients (Spearman rank, ρ) for the relationships between the percent

cover of dominant species, and of bare space vs. metals. Bold denotes significant relationship

(p < 0.01).

3.1. Primer sequences used in AFLP analyses and number of loci amplified for each primer

pair.

3.2. Pairwise PhiPT values among Amphibalanus variegatus samples from 3 sites in South-

Eastern Australia. PhiPT values are shown below the diagonal and probability values shown

above. Probability values based on 9999 permutations.

3.3. AFLP markers in genome scans detected under selection (outlier loci) with test between

industrialised versus reference estuaries, and pairwise estuarine comparisons.

CHAPTER 1: General Introduction

1.1 Overview

Heavy metal pollution is posited as one of the top threats to the biodiversity of marine systems. Metals are an essential and natural component in marine systems, however high levels of metals due to anthropogenic activities can act as powerful agents of disturbance

(Bryan 1971; White and Rainbow 1985). Since the 1970’s, pollution reduction schemes have significantly reduced the unsolicited ‘dumping’ of metals into coastal systems, however inputs from both new and historical sources continue to have an impact on marine fauna

(Fukunaga et al. 2010). While companies in most countries are subject to strict regulations and checks, metals continue to pollute coastal systems from sources such as run-off from urban and industrial centres, and anti-foulant paints (Valkirs et al. 2003; Matthai and Birch

2000). Further, due to the high persistence and strong affinity metals have for particulate matter, metals may be stored in the sediment (Ridgway and Shimmield 2002; Cundy et al.

2003) and continue to have effects long after first entering the system (Knott et al. 2009).

1.2 Biomonitors

A first step in a pollution monitoring study may be to establish the presence of a potential perturbation which would then be followed by an extensive assessment of biological or ecological response (Scanes and Roach 1999). For both financial and conservation reasons, it is important that this first step provide a reliable and sensitive measure of contaminants in the system to accurately assess contaminant risk (Sigg et al. 2006; Chapman 2008). Of greatest threat would be the under representation of a potential pollutant in a system which may halt further investigation and/or remediation. Metals are commonly quantified by measuring levels in the sediment or water but there are several limitations associated with this (Rainbow

2006). For example, water-column values, over short-time frames, may show high variability thus high numbers of samples may be required to account for this (Mastala et al. 1992).

Conversely, sediment may provide a more stable and long-term ‘mean’ of metal levels, however, such measurements may not provide an accurate picture of its significance to the current system (Rainbow 2006; Phillips 1977), and may only be relevant to fauna directly in contact (e.g. sediment dwellers). Furthemore, it cannot necessarily be interpreted what fraction of this is bioavailable (Luoma 1989) and level at which organisms are exposed.

Biomonitors are a commonly used approach to measure contamination in a system. Some advantages of using a biomonitor include: measurement of an available fraction of metal, provision of an integrated measure of contamination (e.g. measurement of water-column exposure via body surfaces and sediment through feeding), the simplicity of chemical analysis, and their cost effectiveness (Scanes 1998).

A biomonitor can be defined as an organism which accumulates a contaminant in its tissue and provides a time-integrated measure of contamination in a system (Rainbow 1995).

Biomonitors are used world-wide in large-scale monitoring programs to identify areas with elevations in contaminants from anthropogenic sources (Kim et al. 2001; Morgado and

Bebianno 2005; Presley et al. 2004). Numerous species have been shown to be useful in identifying elevations in various contaminants such as metals and hydrocarbons. When employed as component of long-term monitoring programs, the use of a biomonitor may enable the identification of new inputs of pollution and temporal changes in contaminant loads (e.g. mussel watch program). Phillips and Rainbow (1993) suggested that a good metal biomonitor should possess the following characteristics:

1) Be a poor regulator of metal

2) Sedentary thus providing a representation of the area being sampled

3) Easy to collect and handle

4) Highly tolerant to metals

5) Highly abundant organism (or easily transplanted) to enable comparisons between

locations and sufficient number for accurate analyses.

Interpretation of tissue concentrations in a biomonitor Accumulated values in a biomonitor are mostly interpreted in monitoring studies by comparing values to references locations or by verifying elevations with other forms of contaminant measure. For example if accumulated values are highly elevated in comparison to reference locations, it is likely that there is an anthropogenic input of a contaminant into the system and this suggests there is strong ‘potential for impact’. However, simple comparisons to background values come with several pitfalls. Firstly, elucidation of clear ‘background values’ may be difficult, especially if appropriate reference sites are already effected by human activities (O'Connor 2002). Secondly, since even closely-related organisms regulate and accumulate contaminants to different degrees, thus ‘background values’ for each species may need to be derived (Rainbow 1993). Thirdly, since we have a poor understanding of how these values relate to toxic thresholds in other organisms, if values are only slightly elevated relative to reference values, it may be very difficult to interpret the significance of these elevations. Fourthly, if sites have only slightly raised metal loadings, it may be difficult to detect this (Rainbow 1993). In conjunction with measurement of levels of contaminants in the sediment and/or water, a biomonitor can further strengthen assessments by providing an account of contaminant levels which may be of ecological concern. However if sediment, water and biomonitor contaminant values do not concur (for example increasing levels of contaminants are measured in the sediments however the biomonitor does not reflect this), it may be difficult to interpret the significance of these differences.

Biomonitors: an ecologically-relevant measure of metals contamination? Despite their widespread use, few studies have established the ecological-relevance of a biomonitor (but see some examples in Weis and Weis 1992; Luoma et al. 2010; Dafforn et al.

2009; Maret et al. 2003). While a biomonitor provides a measure of a bioavailable fraction of a contaminant in a system, strictly speaking, a single biomonitor only provides information on metals which are available to that organism (Rainbow et al. 2002). Organisms uptake metals

via different pathways (Rainbow and White 1989). For example, algae primarily take-up metals dissovled in the water column whereas bivalves take-up food-bound, sediment and dissolved fractions of metals. Organisms also utilise different strategies to process metals which have been taken up (Wang and Rainbow 2008). It therefore may not be relevant to generalise about the availability of metal to other fauna based on values from a single monitoring species. Since few studies have assessed whether accumulated values relate to toxic thresholds in other organisms, it is unclear what the ‘meaning’ of accumulated values are.

1.3 Tolerance and heavy metals

Populations of organisms have been shown to display wide variation in their response to toxic agents (Posthuma and Vanstraalen 1993). Populations may be tolerant to contaminants via two mechanisms: Exposure to contaminants can trigger a physiological response in individuals which infers a greater tolerance to contaminants with subsequent exposures

(acclimation). This form of tolerance may disappear quickly upon removal of the stressor

(Wirgin and Waldman 2004). Tolerance via aclimatory mechanisms may also be conferred to offspring via maternal provisioning of resources (Wu et al. 2008).

In contrast, if a directional, selective force is applied for long enough, this can lead to a change in the genetic structure of the population (van Straalen and Timmermans 2002).

Ongoing selection of individuals with advantageous traits can lead to these traits becoming genetically-fixed in the population. This form of tolerance is inherited by offspring, and upon removal of the stressor, tolerance will continue to persist for several generations unless the cost of tolerance is very high (Wirgin and Waldman 2004). Adapted populations will have a higher frequency of individuals which display a greater ability to acclimate to contaminants and/or greater permanent resistance (Johnston 2011). In the laboratory, within a few generations of selection, greater tolerance has been found to develop in laboratory populations

(e.g. Ward et. al 2005, Athrey et. al. 2007, Spurgeon et. al. 2000, Wallace et. al. 1982; Colin

et. al. 2005, Brausch, 2009). This effect can be sustained, even when populations have been reared in ‘clean’ conditions, for several years (Colpaert et al. 2000).

In order to distinguish between the two forms of tolerance, the offspring of populations need to be reared in a common garden environment. Subsequent generations must also be tested for tolerance in order to eliminate potential maternal effects (Johnston 2011). A finding that the mean fitness of the population returns to the same level as reference populations in the first generation, would confirm that tolerance is due to acclimation. A finding that tolerance disappears in the second generation would confirm that tolerance was inferred via maternal provisioning. Alternatively, in the presence of a strong selective force, there may be changes in the genetic structure of a population (e.g. Williams & Oleksiak 2008), through differential survival of individuals which may lead to a shift in genotypic frequencies or novel genotypes may arise (e.g. mutations).

The evidence for tolerance Numerous laboratory experiments have been able to create populations composed of individuals which display substantially higher tolerance compared to the original population.

These experiments are conducted by exposing populations usually to a predetermined LC50 of

a contaminant. Survivors are then reared and a similar selection process is performed on the

offspring of these individuals. Using this methodology, tolerance has been induced in a range

of taxa including of fish (Athrey et al. 2007; Xie and Klerks 2003), bacteria, terrestrial

invertebrates (Wallace 1982; Spurgeon and Hopkin 2000) and aquatic invertebrates (Reinecke

et al. 1999; Klerks and Levinton 1989).

Other evidence for tolerance comes from studies which have collected populations from

contaminated and clean, ‘reference’ locations. Populations have been collected from

‘contaminated’ locations, exposed to a contaminant challenge in the laboratory and have been

found to have a higher tolerance than populations from ‘clean’ locations. Populations

collected from the field have been found to display a greater tolerance to toxic substances in fish (Nacci et al. 2002; Meyer and Di Giulio 2003; Knapen et al. 2004), terrestrial invertebrates (Spurgeon and Hopkin 2000; Langdon et al. 2001; Lagisz and Laskowski 2008) and aquatic invertebrates (Lopes et al. 2006; Mouneyrac et al. 2003; Miliou et al. 2000). In some cases, differences in tolerance between field-collected populations have been found to be substantial, for example Gale et.al (2003) found an 8-fold increase in tolerance to copper in populations of the fish Melanotaenia nigrans collected from heavily-contaminated locations compared to reference populations. Notably in one instance, populations of the estuarine fish

Fundulus heteroclitus were found to be 347,000 times more tolerant to dioxin exposure than a reference population (Nacci et al. 2002).

1.4 Sessile invertebrates and the assessment of marine pollution

Sessile invertebrates are a highly diverse group and constitute a significant portion of the biodiversity in marine systems worldwide. They are found in abundance on numerous hard- substrates including rocky-reefs, artificial substrates such as hulls of ships, and biological substrates such as shells. Sessile invertebrates provide a habitat for other taxa (Stone 2006) and may be an important food source for higher trophic levels (Lidgard 2008). They also contribute to the health of the system by improving water quality by filtering particulates or pollutants from the water column (Gifford et al. 2007; Nelson et al. 2004).

Several characteristics of sessile invertebrates make them excellent model organisms for assessing contaminant effects. Since sessile invertebrates are sedentary, they cannot escape contaminant exposure and should provide highly sensitive assessments of the distribution of pollution since they should reflect contaminant exposure at a given location. Assemblages have a high /metre square diversity (Piola and Johnston 2008) potentially enabling a rapid assessment of impacts across a large number of species. The early life-stages have also been shown to be highly sensitive to the effects of contaminants and are therefore a useful endpoint in contaminant assessment (Connor 1972; Gopalakrishnan et al. 2008). Further, assessing

impacts on the early life-stages is potentially indicative of how the assemblage develops and the composition of the adult assemblage (Sutherland and Karlson 1977; Osman and Whitlatch

1995b; Bros 1984), so are both potentially an early indicator of effects and ecologically- relevant. For example Sutherland and Karlson, (1977) found that the first settlers were generally extremely competitive for space, and tended to dominate the assemblage. Other taxa are known to have a large effect on the settlement of other species. For example barnacles create a heterogenous surface which promotes the settlement of other species (Young and

Gotelli 1988), whereas ascidians tend to inhibit the recruitment of other species (Osman and

Whitlatch 1995a).

1.5 Research aims

The first aim of this thesis was to assess the ecological relevance of tissue metal loads measured in a biomonitor. The second aim was to assess whether different populations of a common sessile invertebrate differed in their ability to tolerate metals.

1.6 Thesis structure

In chapter 2, a survey of sessile invertebrate recruitment was carried out in an industrial harbour, alongside the deployment of a biomonitor, in order to test whether metal loads correspond with the ecological effects in sessile invertebrate assemblages. In chapter 3, a laboratory toxicity assay was performed on a native barnacle, originating from four estuaries with different contaminant loads to assess whether populations from polluted locations an increased ability to withstand a toxicant challenge. The population genetic structure was also examined to explore whether localised adaptation had occurred.

CHAPTER 2: A biomonitor as a measure of an ecologically-significant fraction of

metals in an industrialized harbour

2.1 Abstract

Biomonitors are commonly used to quantify levels of bioavailable contaminants in the

environment, however the relationships between biomonitor tissue concentrations and

ecological effects are rarely assessed. The present study investigated metal contamination

within a highly industrialised harbour and ecological effects on sessile invertebrates. The

native oyster Saccostrea glomerata was deployed as a biomonitor across twenty-six sites to

quantify metal levels, and test for correlations with the recruitment of hard-substrate

invertebrates. Concentrations of lead and copper in oyster tissues were negatively correlated

with densities of the dominant barnacle, Amphibalanus variegatus and positively correlated with densities of the dominant polychaete, Hydroides elegans, and the two native encrusting

bryozoans Celloporaria nodulosa and Arachnopusia unicornis. Results suggest that highly

localised events drive contaminant availability and that these events pose a significant risk to

fauna. Biomonitoring studies may be enhanced by running concurrent ecological surveys.

2.2 Introduction

Biomonitors have long been used as a means to measure environmental contamination of air

(Murphy et al. 1999; Thomas 1986), water (Leal et al. 1997; Rainbow and White 1989) and

soil (Madejón et al. 2004; Olowoyo et al. 2010). They tend to be highly resistant to toxic

effects and efficient accumulators of one or more toxic substances.(Rainbow 1995) Many

have argued that the use of biomonitors represents a more accurate assessment of biologically

available contamination when compared to direct analytical measurements of concentrations

within inanimate media such as soils or sediments.(Rainbow 2006) However, biomonitors

reflect only the proportion of the contaminant available to that particular organism, and it is

not necessarily the case that the “dose” will reflect the fraction of available contaminants which is toxic to other organisms.(Roberts et al. 2008) To enhance the utility of biomonitors, it is therefore necessary to identify clear relationships between contaminant loads in the tissues of a biomonitor and toxicological effects in an organism or ecological effects in a community.

Few studies have established whether the fraction of contaminants accumulated by a biomonitor has relevance to organisms other than the monitoring species (e.g. Dafforn et al.

2009; Luoma et al. 2010; Maret et al. 2003; Weis and Weis 1992). Studies commonly interpret the significance of accumulated concentrations by comparing to background concentrations (Scanes and Roach 1999) or verifying values with other contaminant measures

(e.g. Apeti et al. 2009; de Astudillo et al. 2002; Foster 1976; Hayes et al. 1998; Park and

Presley 1997). While both approaches show the potential for effects on associated organisms, they do not enable us to conclusively establish contaminant risk unless it has also been established how tissue concentrations relate to toxic thresholds in other organisms. While great advances have been made in our understanding of how contaminant loads in sediments relate to toxic thresholds in organisms (Long and MacDonald 1998), we are less certain of their relationships with accumulated loads in biomonitoring organisms.

Biomonitors are frequently used to assess levels of metal contamination in aquatic environments (Rainbow 1995). Metal accumulation is the sum of available metal balanced by the rate of uptake vs. the level of regulation by that particular organism (Rainbow 2007). For example, we know some organisms are strong net accumulators of some metals (e.g. barnacles are ‘hyperaccumulators’ of zinc (Luoma and Rainbow 2005) whereas others excrete metals readily (e.g. the clam Ruditapes philippinarum was found to accumulate 65 times less copper than the oyster Saccostrea cucullata, Pan and Wang 2009). Uptake may reflect the metabolic requirements of the element in question for that organism (Blackmore and Morton

2001) and organisms may also primarily uptake metals from different compartments of the

system. For example, macroalgae are believed to primarily take-up metals dissolved in the water column whereas barnacles take-up metals dissolved in the water column and those bound to sediments (Rainbow 2006). Organisms may also utilize very different strategies to prevent uptake, and to store or excrete metals (Luoma and Rainbow 2005). Variation in the ability of different biomonitoring organisms to regulate or process contaminants is a characteristic which may make a biomonitor an invaluable monitoring tool if there is a large discrepancy between contaminant uptake by the biomonitoring organism and contaminant exposure of the broader ecological community.

In this study, I investigated how levels of accumulated metals in a biomonitor related to ecological effects in a sessile invertebrate community. The study was performed over a large number of sites that varied in ambient metal concentrations in an industrial harbour which is heavily contaminated (He and Morrison 2001). Dominant members of the sessile invertebrate community show predictable dose-response relationships when exposed to increasing levels of metals in the laboratory, so I predicted increasing levels of metal (quantified by use of a biomonitor) would correlate with a decrease in the recruitment of some fauna, and thus changes to community structure.

The Sydney rock oyster, Saccostrea glomerata, was selected as a biomonitor because it is sedentary, known to be a poor regulator of metals and since tissue metal concentrations have been shown to clearly relate to gradients of pollution (Jordan et al. 2008; Lincoln-Smith and

Cooper 2004; Scanes 1998). Oysters are filter-feeders and may take-up metals both dissolved in the water-column and bound to particulate matter (Rainbow 2006). I therefore expect routes of exposure to be similar between the monitoring organism and members of the focal community. S. glomerata has previously been used as a biomonitor during dredging activities within the study location (Hedge et al. 2009) and is tolerant to the levels of metal contamination occurring within this harbour.

Sessile invertebrates were selected as the focal group to quantify biological and ecological effects since they are sedentary, highly diverse and an ecologically-important group of fauna found on hard-substrates worldwide. Sessile invertebrates may increase the overall health and diversity of the system by improving water quality (Gifford et al. 2007; Nelson et al. 2004), providing a habitat for numerous other taxa (Perrett et al. 2006) and acting as a food source for higher trophic levels (Lidgard 2008). The recruitment stage of this fauna was targeted since this stage is often highly susceptible to metal stress (Connor 1972; Gopalakrishnan et al.

2007), and the first settlers often affect the diversity and development of the later assemblage by creating a suitable surfaces or inhibiting the settlement of other species (Bros 1987; Osman and R.B. 1995). Therefore, measurement of how recruitment is affected by metal pollution is likely to be a strong predictor of the composition of the adult assemblage (Sutherland and

Karlson 1977).

The specific aims of this study were to: 1) quantify the variation in metal concentrations in

Saccostrea glomerata experimentally deployed across sites in an industrial harbour, and 2) test the hypothesis that increasing tissue concentrations in S. glomerata would be correlated with the recruitment of other sessile invertebrate species nearby.

2.3 Materials and methods

Site description

Port Kembla harbour (34°27’S, 150°54’E), Australia, is a small, heavily modified estuary which has a long history of industry and continues to be one of the major ports on the New

South Wales coast (ABS 2002). Industry along and adjacent to the harbour has previously included a copper smelter and fertilizer manufacturing plant. Current activity around the harbour includes steel manufacturing and the import and export of bulk products such as copper and grain. The pollution reduction schemes implemented since the 1970’s have significantly reduced the input of new sources of pollution, however high levels of metals are

still detected in the harbour sediments (reviewed in He and Morrison 2001) and recent works

suggests they may be toxic to fauna suspended in the water-column (Knott et al. 2009).

Figure 2.1: Sampling sites within Port Kembla Harbour, Australia. Numbers refer to the site labels.

Deployment of biomonitors and settlement plates

To quantify metal levels around Port Kembla Harbour, Saccostrea glomerata were deployed

at twenty-six sites (Fig. 2.1). Sites were chosen such that they provided a broad spatial

representation of the harbour. All sampling occurred from November 2008 to January 2009.

Saccostrea glomerata were sourced from a commercial seller (Holberts Oyster, Port Stephens

NSW, 32°43’S 152° 4’E) to minimise variation resulting from differences in exposure

history, genetics, size and age. The cohort was further standardised by size and weight to

further reduce any variance arising from these variables. S. glomerata were only deployed if they had a shell length between 7-9 cm and a weight between 35-45 g. Ten oysters were randomly allocated to oyster cages and deployed at each site. Oyster cages were made of black plastic with 15 mm aperture and approximately 30 x 30 x 15 cm.

To test the hypothesis that tissue concentrations in the biomonitor were related to the recruitment of sessile invertebrates, settlement plates were deployed at each site alongside the cage of oysters. Two black settlement plates (11 x 11 cm) were attached to a vertically orientated, PVC backing panel (30 x 30 cm). Settlement plates had one surface slightly roughened to encourage recruitment to the plates. This methodology is frequently used in studies examining sessile recruitment (e.g. Johnston and Keough 2005; Stachowicz et al.

2002). Plates were hung from a pre-existing artificial structure (platform, jetty or ladder) or attached to bottom-weighted subsurface float at c. 2 m depth (MSLW) below the surface. The cage of oysters was then secured to the top of the backing panel with cable ties. The cage was attached to ensure no interference with the settlement plates. All sampling devices were deployed at the same time for a duration of 12 weeks.

After 12 weeks, settlement plates and oysters were retrieved from each site. Plates were photographed and preserved in 7% formalin. The abundance of each species per 100 cm2 was quantified by counting the number of individuals which fell under 100 evenly space points using a dissecting microscope. Both primary and secondary cover were quantified, in order to estimate the abundance of all members of the community, not just those that dominate primary space. Primary and secondary space were combined for the analyses. Taxa were identified to the lowest possible taxonomic level (most taxa could be identified to species).

Two settlement plates were censused from each site and statistical analysis was performed on the average cover of the two plates for each site.

A significant correlation between metals and invertebrate density may be confounded by changes in other physicochemical variables that covary with metal concentrations. To check that our conclusions were not confounded by changes in physiochemical variables, water quality parameters (salinity, temperature, dissolved oxygen, turbidity, pH, total dissolved solids or TDS) were monitored monthly (3 measurements per site in total) throughout the

study at every site using a YEOKAL water quality probe (Yeo-kal Model 611, Yeo-Kal

Electronics, Sydney).

Analysis of metal concentrations in oysters

Oysters collected from each site were placed on ice in an insulated container before

transportation to the laboratory. Oysters from each site were placed separately in a container

of 10 L of seawater sourced from a well-flushed, coastal site (Malabar, New South Wales,

Australia, 33°57' S 151°15' E) for 72 h in order to depurate. All instrumentation and

containers used were acid washed (7% nitric acid for 24 h) then rinsed with Milli Q© water.

Oysters were shucked with a stainless steel knife and tissue was removed and rinsed in Milli

Q© water to remove seawater and any residual shell before weighing and storing in separate

70 ml sample vials at - 20°C. Tissue was then freeze-dried and the dry weight recorded for each individual. Each oyster was separately ground to a fine powder using a Retsch© mixer

mill.

For each site, three oysters were randomly selected and equal weights of the ground tissue

were homogenised. A 0.4 g subsample of the homogenised tissue was weighed into a Teflon

polytetrafluoroacetate (PFA) digestion vessel with 5 ml of Milli-Q© water, 3 ml of Nitric acid

(Aristar Grade) and 3 ml of hydrogen peroxide. Samples were microwave digested at 100°C

for 10 min and then 200°C for 10 min. After digestion, samples were diluted to 30 ml with

Milli Q© water and analysed by Inductively coupled plasma mass spectrometry (ICP-MS) for a suite of metals (As, Cd, Cu, Fe, Mn, Ni, Pb, Se, Zn). Analysis was performed by the

University of New South Wales Analytical Centre. Standard reference material NIST 1556b oyster tissue was routinely digested and reagent blanks analysed every 20 samples to check metal recovery and for contamination of samples. Recoveries for each metal were checked and any outside the expected 90-110% range were excluded from the analysis (Fe, Se, Zn).

Data analyses

A distance-based linear model routine (DistlM, Legendre and Anderson 1999) was applied in order to analyse and model the relationship between biological data and environmental factors. The selection criterion and procedure used were stepwise and AICc. The biological dataset was initially square-root transformed and a similarity matrix constructed using the

Bray-Curtis index for similarity among samples. For the environmental data-set, a draftsman plot was first constructed to detect possible violation of multivariate assumptions and/or strong correlations among pairs of variables. As a high correlation was found between temperature and TDS, TDS was removed and temperature left in as a proxy in the analyses.

Lead was square-root transformed to reduce its ‘skewed’ distribution. The environmental variables were normalised since the scale of differences will vary for each variable due to the different measures between variables. Fitted model was visualised on a distance-based redundancy analysis (dbRDA) plot.

To test the strength of the relationships between individual metals and species, correlation analyses were also performed (Spearman-rank coefficient). Only metals which were elevated by at least 1.5 times above background levels were analysed. To reduce the chance of inflated type 1 error due to a high number of tests, only a subset of species were tested (those which had a correlation coefficient of r > 0.3 with the multivariate patterns) and a more conservative p value taken (p < 0.01). Although, there may be significant relationships between species not tested and metals, the relationships will be weak and it is unlikely that any robust conclusions can be drawn from those analyses.

To check that differences in the growth rates of oysters following the 12 week deployment were not confounding our conclusions, a one factor analysis of variance was used to contrast the dry weights of oysters across sites. The assumptions of ANOVA were checked visually

(by frequency histograms of residuals and scatterplots of residuals against means) and no transformations of the data were necessary.

The spatial representation of the harbour is in some instances uneven (i.e. sites which are

close may essentially be replicates of that area). To check for autocorrelation, the distance

between each site and the difference in metal values was calculated and correlated against

each other.

2.4 Results

Metal concentrations in oyster tissue

The tissue concentrations of most metals tested were above concentrations expected in

Saccostrea glomerata collected from clean locations (referred to as ‘background

concentrations’ for the remainder of the paper) as reported by Scanes and Roach (1999)

(Table 2.1). Tissue concentrations were converted to µg of metal/g wet-weight to allow

comparisons with Scanes and Roach (1999) whose presented values based on µg metal/ g

wet-weight tissue. Levels of lead, copper and arsenic were moderately elevated above

background levels at all sites, whereas manganese was only slightly elevated at half of the

sites sampled. Cadmium and nickel were not elevated above background levels. Lead (0.9–

5.2 µg g-1) was on average 5 times greater than background concentrations, copper (194–325

µg g-1) on average times 2.5, arsenic (9–14.9 µg g-1) on average 1.3 times enriched above

levels expected in a clean estuary (Scanes and Roach 1999). Manganese (2.4–8.3 µg g-1)

levels were at background values at most sites (Table 2.1). ‘Spikes’ in lead and copper worth

noting are at sites 3, 4, 9 and 10 which correlate with previous and current copper-related

industry.

Minimal mortality was recorded in oysters (< 0.5% over all sites, with no more than one death

at any single site). No significant differences were found between sites in the size of oysters

(F25,76 = 1.36, P = 0.156). Comparisons of metal concentrations between sites were therefore unlikely to be confounded by growth or mortality of the deployed oysters.

There was no significant relationship between distance among sites and differences in metal values. Sites thus appear to be independent (i.e. distance between sites sufficient to be

capturing different environmental conditions). In fact, some of the greatest differences in values of lead and copper were between sites which were close together. For example, sites 4 and 6 were separated by approximately 200 m, however there was a 4.25 µg g-1 and 90 µg g-1 difference in lead and copper values respectively. In the case of lead, this is the greatest difference in values between any two sites.

Relationship between biological assemblages and environmental variables

Forty-seven taxa were identified in this study, however assemblages were primarily dominated by the barnacle Amphibalanus variegatus, the tube-worm Hydroides elegans, the colonial ascidian Diplosoma listerianum, and tubes of amphipods from the family

Corophiidae. Forty-four of the species identified, on average, only occupied < 5% of space on each settlement surface.

The physicochemical variables showed minimal variation across the harbour, with values ranging across all sites, for temperature (18.6 -2 0.9˚C), salinity (35.7 - 36.6 ppt), TDS (30.5 -

31.7 ppm), DO% (123.8 - 147.37 %), pH (13.03 - 11.99) and turbidity (3.6 - 11.2 ntu) (see appendix 1 for individual site values).

The DistlM analysis shows a significant relationship between biological and environmental data when predictor variables are considered individually. Temperature, lead and turbidity explain the highest percentage of variation (14, 13 and 10 % of variation respectively, p <

0.01, Table 2.2A). Copper was also significantly correlated with the assemblage patterns, however only explaining 0.09 % of the variation.

When considering the environmental factors together to predict the biological patterns, temperature and lead provide the best fit for the model (14 and 13% of variation explained respectively, Table 2B). The total variation explained by these two factors is 28.7%.

Examination of the dbRDA plot (Fig. 2.2) suggests the differences in assemblages associated

with temperature are due to changes in the percent cover of the tube worm Salmacina australis, the bryozoans Beania magellanica, Zoobotryon verticilliatum (all increase in cover) and the colonial ascidian Botrylloides leachii (decrease in cover). Changes in the percent cover of the tube worm Hydroides elegans, the bryozoans Celloporaria nodulosa,

Arachnopusia unicornis, bare space (all increase in cover) and the barnacle Amphibalanus variegatus (decrease in cover) are associated with changes in lead concentrations (Fig. 2.2).

The univariate correlations are mostly in agreement with the results from the distlM, although the concentration of copper was found to be significantly correlated with the cover of

Amphibalanus variegatus, Arachnopusia unicornis, Celloporaria nodulosa and Hydroides elegans (Figs. 3b, e, g, i) which was not clear in the Distlm analyses. Since copper and lead were strongly correlated it could be that the effects I have attributed to lead in the Distlm analyses are being simultaneously affected by both copper and lead concentrations.

Significant negative correlations were found between A. variegatus and lead concentrations

(Fig. 2.3d). H. elegans, A. unicornis and bare space were positively correlated with lead

concentrations (Figs. 3b, h, j). No significant relationships were found with the density of any

of the tested species and arsenic and manganese (see Table 2.3).

Site Arsenic Cadmiu Copper Mangane Nickel Lead m se 1 2.66 0.38 38.92 2.20 0.10 0.33 2 2.58 0.35 54.41 3.04 0.05 0.52 3 1.99 0.29 65.16 1.49 0.05 0.67 4 2.07 0.20 61.26 2.94 0.06 1.05 5 1.80 0.28 52.98 1.02 0.06 0.57 6 2.16 0.26 43.39 2.03 0.05 0.20 7 2.48 0.40 40.18 3.35 0.09 0.26 8 2.15 0.40 62.66 1.95 0.07 0.32 9 2.89 0.35 55.26 1.91 0.06 0.33 10 2.64 0.38 61.53 3.22 0.11 0.58 11 2.56 0.41 36.93 3.91 0.06 0.29 12 2.44 0.48 48.14 1.72 0.14 0.36 13 1.95 0.22 46.95 2.49 0.06 0.30 14 2.19 0.31 40.68 1.47 0.05 0.35 15 2.41 0.40 50.08 2.69 0.07 0.44 16 2.58 0.26 55.56 2.45 0.08 0.44 17 2.42 0.46 48.48 1.19 0.08 0.44 18 2.50 0.30 43.74 2.57 0.10 0.45 19 2.89 0.34 45.47 3.12 0.05 0.52 20 2.80 0.31 54.14 4.07 0.10 0.54 21 2.97 0.38 51.83 4.15 0.07 0.45 22 2.55 0.29 50.70 1.98 0.06 0.39 23 2.72 0.35 43.27 2.56 0.05 0.32 24 2.59 0.53 37.15 2.63 0.07 0.33 25 2.98 0.38 49.80 3.84 0.08 0.34 26 2.35 0.28 39.52 2.18 0.06 0.34

Background concentrations (Scanes & Roach, 1999)

Mean 1.88 0.54 21.6 2.53 0.13 0.085

Table 2.1: Mean metal concentrations (µg g-1 wet weight) of each site measured in oyster tissues. Bold denotes values above background concentrations

Variable Pseudo-F P % var. A) Marginal tests Temperature 4.15 0.001 14.75 Salinity 1.226 0.248 4.83 Dissolved oxygen (%) 1.15 0.328 4.56 pH 0.94 0.465 3.78 Turbidity 2.95 0.004 10.94 Arsenic 1.58 0.095 6.19 Copper 2.56 0.008 9.63 Manganese 1.31 0.212 5.17 Lead 3.69 0.001 13.32 B) Sequential tests Temperature 4.15 0.001 14.75 Lead 4.50 0.001 13.95

Table 2.2: A) DistlM tests for relationships between individual environmental variables and composition of the sessile invertebrate fauna. B) Tests for relationships between environmental variables and the composition of the sessile invertebrate fauna considering all environmental variables the model. Bold denotes a significant relationship.

Arsenic Copper Manganese Lead

Bare space -0.276 0.315 -0.021 0.591 Amphibalanus variegatus 0.178 -0.519 -0.092 -0.42 Celloporaria nodulosa -0.236 0.304 -0.162 0.285

Arachnopusia unicornis -0.414 0.682 -0.165 0.573 Hydroides elegans 0.121 0.436 0.22 0.495

Table 2.3: Correlation coefficients (Spearman rank, ρ) for the relationships between the percent cover of dominant species, and of bare space vs. metals. Bold denotes significant relationship (p < 0.01).

Figure 1.2: Distance-based redundancy analysis showing relationships between ordination of sites based on biological assemblages and the environmental factors. Environmental and biological variables overlayed vectors using multiple correlation type. - - - refers to biological variables and – refers to environmental variables. Species abbreviated as follows: AV, A. variegatus; BL, B. leachii; HE, H. elegans; CN, C. nodulosa; AU, A. unicornis; BS, bare space; BM, B. magellanicus; SA, S. australis; ZV, Z. verticilliatum.

Figure 2.3: Scatterplots of the percentage cover of (a) bare space, (c) Amphibalanus variegatus, (e) Celloporaria nodulosa (g)

Arachnopusia unicornis and (i) Hydroides elegans against copper concentrations. Scatterplots of the percentage cover of (b) bare space,

(d) Amphibalanus variegatus, (f) Celloporaria nodulosa (h) Arachnopusia unicornis and (j) Hydroides elegans against copper concentrations. * denotes significant relationship (p < 0.01). † denotes log transformation.

2.5 Discussion

Increasing metal concentrations measured in the tissues of the oyster Saccostrea glomerata were associated with a decline in recruitment of an abundant native barnacle, and associated with an increase in the recruitment of a cryptogenic tube-building polychaete and several native encrusting bryozoans. The Sydney Rock Oyster may therefore be a useful monitor of the fraction of available metals which alters the composition of the invertebrate community.

However, poor relationships were found for other species, possibly due to interspecific variation in the routes of exposure, metal-handling strategies or recruitment variability driven by other environmental variables. Importantly, by recording an ecological endpoint alongside the tissue concentrations in a biomonitor, I was able to get a strong indication of whether the metal levels recorded by the biomonitor were of ecological concern. Site by site correlations between tissue metal concentrations and community traits suggest that highly localised events predict contaminant availability and that these events pose a significant risk to fauna.

Implicating sediments as the source of metals

Lead, copper, arsenic and manganese, were found to be elevated above levels expected in a

‘clean’ estuary, suggesting that metal contamination from anthropogenic sources may pose a threat to organisms in this industrialised harbour. However, since the late 1970’s, increasingly stringent pollution control programs have been implemented in many countries which have lead to a significant reduction in new inputs of pollution into coastal waterways including

Port Kembla Harbour. Monitoring studies since the 1970’s in Port Kembla harbour have found levels of zinc, cadmium and iron in the sediments and in the water-column have undergone significant reductions whereas levels of lead, copper and arsenic continued to remain highly elevated (He and Morrison 2001; Moran 1984). In a recent study by Dafforn et al. (2012), levels of arsenic, lead, zinc and copper measured in the sediment were found to be highly elevated across the harbour. Therefore, despite a significant reduction in new inputs of pollution into the harbour, the results from this study suggest that metals continue to pose a

threat to the organisms in the system, the source of which is likely to be previous industrial activity.

Metals latent in the sediments may be the primary source of metals detected in oyster tissues in this study. A notable ‘hotspot’ of metals was detected at sites 3 and 4 which are located near a drain outlet in the outer harbour involved in waste disposal from a copper smelter that ceased operations in 2003 (Damris et al. 2005). Sediments are known to act as a sink for contaminants (Cundy et al. 2003; Ridgway and Shimmield 2002) and these may become available in the water-column through disturbance of the sediments by large-scale events such as dredging or storms or small-scale events such as shipping movement (Eggleton and

Thomas 2004). Large disturbances to bottom sediments during dredging operations have been shown to lead to severe decreases in the recruitment of sessile invertebrates in Port Kembla harbour (Knott et al. 2009) and release of metals or sediment-bound metals during these disturbances have been implicated as a causative agent of these effects (Hedge et al. 2009).

During our study, there were no large-scale sediment disturbances, however, localised sediment disturbances by shipping movements were regularly observed throughout the harbour (pers. obs). Therefore, it is likely that regular shipping movements are causing significant amounts of bedded sediments to become suspended thus exposing sediment- associated metals to fauna suspended in the water-column. The effects of metals appear to be highly localised in this study (large differences in metal values < 200 m), which further would support this hypothesis.

Sediment-associated metals can be toxic to water-column fauna via several pathways: upon disturbance, metals within the sediment compartment may be released which may then diffuse across membranes. Alternatively, sediment-bound metals may be ingested (reviewed in

Eggleton and Thomas 2004). In laboratory studies, metal-release and ingestion of sediment- bound metals have been associated with negative effects in invertebrates (Gillis et al. 2006;

Hill et al. 2009), including cellular damage, sublethal effects (Amiard et al. 1995) and the development of abnormal larvae (Fichet et al. 1998). Although high levels of sedimentation

can have serious consequences for fauna (Airoldi 2003), Hill et al. (2009) found that suspension of ‘clean’ sediment had no effect on the health of an encrusting polychaete.

Relationships between metal tissue concentrations in Saccostrea glomerata and associated fauna

Increasing lead concentrations measured in the tissues of Saccostrea glomerata were associated with a decline in the recruitment of an abundant, native barnacle, and associated with an increase in the recruitment of a cosmopolitan polychaete and two native encrusting bryozoans. Increasing copper concentrations were also associated with effects in several taxa, however relationships were not as strong as with lead. Thus, static tissue concentrations in S. glomerata appear to reflect a fraction of the metals in the system that is of relevance to taxa from several invertebrate groups.

Increasing tissue concentrations of lead and copper in our biomonitor were related to a decrease in the spatial dominance of the barnacle Amphibalanus variegatus. Both lead and copper can be highly toxic to aquatic organisms in high concentrations (Besser et al. 2005;

Hall et al. 1998; Sanchez-Marin et al. 2010). The addition of a ‘copper dose’ to settlement plates by application of a border of an anti-foulant paint has been shown to inhibit 100% of A. variegatus recruitment (Piola and Johnston 2008). Increasing levels of copper quantified using Saccostrea glomerata were also negatively correlated with the abundance of A. variegatus, over two recreational and two industrial harbours (Dafforn et al. 2009). The consistency between the patterns in this study and those in Dafforn’s study conducted at different spatial scales supports the hypothesis that copper affects the recruitment of A. variegatus both within and across harbours, and that metal tissue concentrations in S. glomerata are a reliable indicator of the fraction of the metals which is toxic to A. variegatus.

The dbRDA plot suggests the the levels of copper covaries with those of lead so it is possible that the effects in fauna are being driven by lead and/or copper. Both lead and copper are

highly toxic to marine invertebrates, however, only sediment-associated copper has been associated with effects. However, a conclusion that sediment-associated lead cannot produce effects in fauna is prevented by a paucity of studies which have specifically examined its toxicity via this pathway. Sediment-associated copper, both bound and fractions released during sediment disturbance, can be detrimental to invertebrate larvae and adults (e.g. Geffard et al. 2002; Kosalwat and Knight 1987; Gillis et al. 2006). Hill et al.1999 found that during the resuspension of copper-contaminated sediments, dissolved concentrations were found to be within the EC50 range of a hard-substrate, filter-feeding organism. Similarly Gillis et al.

(2006), found that the dissolved copper fraction was acutely toxic to juvenile Daphnia magna.

In contrast, Hill et al. (2009) found that only a small fraction of lead was released during resuspension of sediments ‘spiked’ with different concentrations of lead, with water-borne levels never reaching EC50 values of the test subjects. Lead is largely insoluble in seawater and tends to remain associated with particulate matter. Further, speciation to less toxic states rapidly occurs following the dissolution of lead into the water-column. However, although a large fraction of the dissolved lead released may bind to particulate matter, very low concentrations are required to induce toxic effects in marine organisms (Prosi 1989;

ANZECC 2001). Filter-feeding organisms may also be exposed to lead through ingestion of lead bound to particulate matter (Fichet et al. 1998). Experimental studies would need to be performed to allocate causality to either element.

In striking contrast to the relationship with Amphibalanus variegatus, increasing levels of lead and copper were associated with an increase in the spatial dominance of Hydroides elegans,

Celloporaria nodulosa and Arachnopusia unicornis. The increase in abundance of several taxa is likely mediated through competitive interactions with the barnacle A. variegatus which dominated space in the ‘cleaner’ sites. An increase in bare space was also correlated with a decrease in A. variegatus abundance which further supports this hypothesis. H. elegans is known to have a high tolerance to copper (Allen 1953; Dafforn et al. 2009), and can benefit indirectly from contamination via the reduction in densities of competitively superior species

(Johnston and Keough 2003; Johnston et al. 2002). If a few recruits are able to successfully settle and persist through the early metamorphosis’ processes, the adults may be able to increase in spatial dominance.

The cover of only four species from a total of forty-seven was found to correlate with increasing metal tissue concentrations in Saccostrea glomerata. This may relate to differences in metabolic requirements and metal-handling strategies between the biomonitor and fauna within the assemblage. Differences in routes of metal uptake among species may alter the toxicity of ambient metal levels to different groups of fauna. For example, no relationships were found between lead and copper concentrations and the density of amphipod tubes.

Amphipods have a chitinous exoskeleton which may reduce the uptake of metals dissolved in the water column (Marsden and Rainbow 2004) in contrast to S. glomerata which is known to uptake metals from this compartment of the system. Furthermore, metal handling strategies between even closely related biomonitors can be highly variable (Roberts et al. 2008) and a given biomonitor may reflect a fraction of the available metals which is of significance to only some subsets of the associated fauna.

Elevations in metals across Port Kembla harbour may not have reached lethal concentrations for some organisms due to their high tolerance for metal pollution. For example, the ascidian,

Diplosoma listerianum, dominated cover in assemblages across the harbour but showed no relationship with any metals, and was still present at sites with the highest recorded concentrations of copper and lead. Others such as Hydroides elegans, Arachnopusia unicornis and Celloporaria nodulosa increased in cover with increasing levels of metals. Interspecific variation in tolerance to metals is commonplace (Lehmann and Rebele 2004), and variation can also arise among populations within a species due to the evolution of tolerance to metal exposure (e.g. Gale et al. 2003; Lopes et al. 2006; Johnston 2011).The increase in dominance of several species in metal-contaminated sites would support the hypothesis that these species have evolved tolerance to metal pollution.

The ability of a biomonitor to predict associated sessile invertebrate assemblages is also

affected by the naturally high variation in recruitment of this fauna (Butler 1986; Glasby

1998; Gerrodette 1987). For example, Keough (1983) found recruitment of a sessile

invertebrate assemblage varied strongly between settlement panels deployed at scales of less

than 5 metres, with patterns of recruitment ranging from random to highly aggregated. The

results suggested that some species (e.g. Hydroides norvegica) recruited in ‘swarms’, that is,

some panels located close together had large patches of these species however this pattern

was not consistent across replicates.

Implications for the use of biomonitors

In this instance, a biomonitor appeared to be an effective measure of a fraction of available

metals which was of significance to several sessile invertebrate taxa. Consideration of these

results in conjunction with Dafforn’s study (Dafforn et al. 2009) suggests the results are

applicable across different temporal and spatial scales. Bivalves, including Saccostrea

glomerata, have frequently been used as a proxy for measurements of bioavailable metals in marine studies. The results from this study suggest such a use is justified, although the poor predictability for a large number of rare species brings into question the generality of the use as a single measure of risk. By using sessile invertebrate recruitment as a measure of impact however, I was able to validate the ecological-relevance of our static measure. Although our results suggest tissue concentrations in S. glomerata are ecologically-meaningful, parallel faunal-surveys should still be performed until the efficacy of such measures is tested across other environmental gradients, metal-concentrations and the relevance of tissue concentrations demonstrated across a wider number of taxa.

Across a small, but industrially-diverse harbour, large differences in copper and lead concentrations were seen and associated with large differences in the invertebrate assemblages, suggesting the metal effects can be highly localised and that this biomonitor

provides a spatially-sensitive measure. Possible small scale variation should be considered in biomonitoring studies, as most consider only distances between sites at the scale of kilometres

(e.g. mussel watch program). Our study suggests that metals can strongly correlate with important ecological changes at the scale of metres. If studies do not quantify variance in metal loads at small spatial scales, it is possible a conclusion of ‘no effect’ will be drawn or instead an effect may be detected that may not be a good representation of the greater area.

While in reality for a monitoring study, the scale at which impacts are assessed may have to be limited by either management, monetary or other arbitrary measures, the ecological importance of variance at smaller spatial scales should be quantified in order for results to be interpreted correctly to enable informed and justified decisions (Morrisey et al. 1994).

A potential application of the approach utilised in this study, recently suggested by Luoma et al. (2010), is the derivation of water quality guidelines using tissue concentrations in a biomonitor as a measure of contaminants. Unlike measurements of contaminants from other compartments of the system, a biomonitor potentially has the capacity to provide an integrated measure of contaminant exposure from multiple compartments as well as a fraction known to be of some direct biological significance. The concept holds great promise and the results from our study would suggest, more generally, that biomonitors may be an excellent method to measure the component of metal in the system which is of significance to fauna.

CHAPTER 3: Differential tolerance to copper, but no evidence of population-level genetic differences in a widely-dispersing native barnacle

3.1 Abstract

Despite many estuaries having high levels of metal pollution, species are found to persist in these stressful environments. Populations of estuarine invertebrates exposed to toxic concentrations of such metals may be under selection. However, in species with a wide- dispersal potential, any short-term results of localized selection may be counteracted by external recruitment from populations not under selection. The barnacle Amphibalanus variegatus is found in nearshore coastal environments as well as sheltered embayments and estuaries, including metal-impacted estuaries, from New South Wales, Australia to Western

Australia. The fertilised eggs of A. variegatus are brooded internally and released as larvae

(nauplii), which remain in the water-column for ~14 days before settling. Hence the species has a considerable dispersal capacity. The purpose of this study was to examine whether populations of A. variegatus from metal-impacted sites, displayed a greater tolerance to a toxicant (copper) than reference populations. Adult barnacles where collected from twenty sites within two metal-impacted and fourteen sites within two reference estuaries. Within 24 h, adults were induced to spawn and the offspring were exposed to copper in a laboratory assay. Larvae collected from the metal-impacted estuaries demonstrated a greater tolerance to copper compared to those from reference sites. To determine if selection/localised in the metal impacted sites was occurring, the genetic structure of populations at three sites was examined using an AFLP methodology. No evidence of unique population identity and or selection (outlier loci) was detected suggesting that: 1) the tolerance displayed in the assay was derived from acclimation during development; and/or 2) that the populations are open preventing the fixation of any unique alleles.

3.2 Introduction

Anthropogenic activities are changing the nature of estuarine and coastal environments with many organisms now being exposed to novel agents and/or unnaturally high levels of trace elements (Medina et al. 2007; Sarkar et al. 2006; Bryan and Langston 1992). Consequently, the phenotype and genetic identity of populations residing in these locations may undergo substantial changes (Klerks and Weis 1987; Posthuma and Van Straalen 1993; Meyer and

Giulio 2003). When a contaminant enters a system, an individual can respond in a number of ways: it may tolerate the stress, avoid it, or die (Lopes et al. 2004). The first response will have no effect on the genetic structure of the population, whereas the latter two may affect it by changing the frequency/identity of alleles within that population (Belfiore and Anderson

2001; Wirgin and Waldman 2004).

Exposure to contaminants can change the phenotype of an organism (Klerks and Weis 1987;

Wang and Rainbow 2005), with these changes reflecting both its exposure history and its genetic background (Morgan et al. 2007). Following exposure, individuals can respond by activation of physiological/biochemical pathways which can ameliorate detrimental effects in subsequent exposures (e.g. Fritsch et al. 2011; Klerks and Lentz 1998). Although tolerance acquired through acclimatory responses is based on traits which are genetically-determined, in contrast to resistance acquired through selection, the induced effect is not generally transmitted across multiple generations and should disappear in remediated environments

(Wirgin and Waldman 2004).

At a population level, genetically-determined resistance is acquired through the survival of tolerant genotypes and the demise of those that are sensitive (Klerks and Weis 1987). This can lead to a change in the distribution of a trait/s within an affected population (Belfiore and

Anderson 2001). Traits conferring resistance may not be limited to a single gene, and may involve a suite of genes (Van Straalen et al. 2011). In addition, in an affected population, there may be a diverse range of genotypes that confer tolerance (Depledge 1994), and

between populations the genes involved may not be conserved (Fisher and Oleksiak 2007), i.e. tolerance can evolve independently.

Although there are a number of studies that simultaneously examine both the phenotypic and genetic affects of contaminants in freshwater and terrestrial organisms (reviewed in Klerks and Weis 1987; Posthuma and Van Straalen 1993; Johnston 2011; Belfiore and Anderson

2001; Wirgin and Waldman 2004; Morgan et al. 2007; Grant 2002), there are few examples of this in marine organisms (examples see Klerks and Levinton 1989; Grant et al. 1989;

Miliou et al. 2000; Untersee and Pechenik 2007). One notable exception to this is the detailed research on the estuarine fish Fundulus heteroclitus (reviewed in Wirgin and Waldman 2004).

The extent to which resistance is maintained within a local population, is a balance between the selection pressures acting on an individual versus the level of gene flow into the affected population (García-Ramos and Kirkpatrick 1997; Slatkin 1987). While natural selection acts as a driving force for local adaptation, the introduction of new alleles (gene flow) can act as an opposing force by homogenizing genotypes (Clarke et al. 2010; Lenormand 2002; Barton and Partridge 2000; Kawecki and Ebert 2004) preventing resistant genotypes from becoming fixed within a population. In freshwater systems there can be strong barriers to gene flow

(e.g. ponds and lakes Coors et al. 2009) and flow is unidirectional (e.g. riverine systems,

Groenendijk et al. 2002), which ensures that populations are closed or of a metapopulation structure (i.e. there are restrictions to gene flow). This can promote the fixation of alleles in response to a localized impact. In contrast, in the marine environment there are few barriers to gene flow, and it is commonly considered that many populations are panmictic in structure i.e. they are large and genetically/demographically ‘open’ (Caley et al. 1996; Cowen and

Sponaugle 2009). Thus, in marine organisms, it is unclear what mechanisms drive local adaptation, and based on a paucity of studies, how commonly it occurs (see Sanford and Kelly

2011 and Sotka 2005 for review of local adaptation in marine invertebrates).

Marine species with a long larval duration have the potential to disperse across wide distances, thus demographic and genetic connectivity between widely separated populations is thought to be high (Sanford and Kelly 2011; Palumbi 1994). Untersee & Pechenik (2007) have suggested that larval duration may be an important determinant of the likelihood of localized adaptation, with adaptation less likely to occur in species with a long larval duration

(i.e. a widespread dispersal capacity). To test this hypothesis, they examined the copper tolerance of two gastropod species (Crepidula fornicata and C. convexa), collected from metal-polluted and reference sites, which produce offspring with different larval longevities.

For the species with the short-dispersing larvae, populations in polluted sites exhibited a heritable tolerance, whereas no evidence of this was exhibited by the species with the wide dispersing larvae. Rainbow et al. (1999) have posited a similar hypothesis, but in contrast to

Untersee & Pechenik (2007), they found no evidence of physiological differences between populations of species which brooded their young (amphipod crustaceans) and a species with produced long-lived larvae (crabs) between metal-contaminated and reference sites.

The barnacle Amphibalanus variegatus is native to Australia, and found in nearshore coastal environments as well as estuaries and sheltered embayments from Western Australia to

Northern NSW, including industrialized/metal-impacted estuaries along the NSW coast

(Dafforn et al. 2009; chapter 2). A. variegatus produce larvae which remain in the water- column for up to 14 days (Egan and Anderson 1986) before settlement and hence have a widespread dispersal capacity. The purpose of this study was therefore to determine whether populations of the widely-dispersing barnacle A. variegatus residing within metal-impacted estuaries have a greater tolerance to a toxicant (copper) compared to those from reference populations. Secondary to this, was to determine whether pollution is having an impact at the population genetic level, which would indicate localised selection and/or adaptation. The specific aims of this study were:

1) Examine whether populations from metal-impacted estuaries display a greater tolerance

to a toxicant compared to reference populations

2) Using an Amplified Fragment Length Polymorphism (AFLP) methodology, examine

whether there are differences in population structure which correspond with level of

estuarine pollution.

3.3 Materials and Methods

Study sites Populations of Amphibalanus variegatus were collected from four estuaries along the east coast of NSW, two metal-impacted (‘industrialised’, Port Kembla & Botany Bay), and two reference (The Clyde & Wagonga Inlet, see Fig. 3.1). In each estuary, adult barnacles were collected from 5 – 10 sites. The designated a priori estuarine categories (industrialised versus reference) were verified by the measurement of copper levels in the tissue of oysters and the benthic sediments, which were deployed/collected in a larger, parallel study, throughout the duration of this experiment (see Dafforn et al. 2012, also summarized in Fig. 3.2)

Port Kembla (‘industrialised’) is a small artificial-estuary which functions as a commercial

port. The shoreline and area adjacent to the port has supported heavy industry for over 80

years including the processing and production of steel, copper and zinc products (He and

Morrison 2001). During 1990, monitoring studies found substantial improvements in the

levels of metals and polycyclic hydrocarbons in fish, sediments and dissolved in the water

column, however in particular levels of lead, copper and arsenic were still found to be

severely elevated above the current high trigger sediment quality guideline values (reviewed

in He and Morrison, 2001). In chapter 2, it was determined that the levels of copper and lead

in the tissue of oysters are still elevated above ecologically-significant levels of contamination

(Scanes and Roach 1999) and a negative relationship was observed between the density

Amphibalanus variegatus and copper and lead concentrations (also in Dafforn et al. 2009).

Dafforn et al. (2012) in a parallel study, reported loadings of copper between 64 - 1737 mg/kg and 76 - 956 mg/kg in the benthic sediments and transplanted oyster tissue, respectively across the sites used in this study. Botany Bay (‘industrialised’) is a commercial port, with

Figure 3.1 Map of study sites located along the NSW coastline, SE Australia. a) Botany Bay and b)

Port Kembla are industrialised estuaries; c) The Clyde and d) Wagonga Inlet are reference estuaries.

Circles represent the sites within each estuary at which A. variegatus were collected from. Levels of

copper in the benthic sediments and tissue of oysters also measured at each of these sites (some

exceptions, white and grey-filled circles represent sites where no copper measurement taken from the

sediment and oyster tissue respectively, see Dafforn et al. 2012). Stars represent the sites also used in

the molecular study.

several sources of contaminants from both industrial and residential sources. The two main tributaries into Botany Bay, Georges and Cooks River, are documented to have elevated levels of copper and other metal contaminants in the sediments (Hayes et al. 1998; Spooner et al. 2003), particularly in upstream areas with pollutants radiating as far as the mouth of the estuary (see Birch 1996). Correspondingly, Dafforn et al. (2012) found that benthic sediments in the upper estuary had the highest copper loadings, but also found levels of copper measured in the tissue of oysters to be elevated at a number of sites in the outer harbour, with the highest copper reading recorded at a site near the mouth of the estuary. Loadings of copper across the sites used in this study, range from 18 - 66 mg/kg and 52 - 262 mg/kg in the

benthic sediments and oyster tissue respectively (Dafforn et al. 2012).

The Clyde and Wagonga Inlet (reference estuaries) contain no commercial ports or any

significant industrial presence, current or historical. Over 95% of the catchment running into

the Clyde is National Park and state forest (DLWC 2000) and both are part of the Batemans

Bay Marine Reserve, i.e. the level of commercial and urban development is restricted.

Larval collection Amphibalanus variegatus adults were collected from each site (Fig. 3.1) by deploying

settlement panels (60 x 60 cm grey PVC sheets) for 3 months between November 2009 and

March 2010 and allowing barnacles to recruit to the surface. Panels were deployed by

attaching them to a rope which was anchored to the seafloor at 5 m depth and held upright in

the water-column by a float. Individual panels were retrieved from ten sites in Botany Bay

(Fig. 3.1a), ten sites in Port Kembla (Fig. 3.1b), six sites in The Clyde (Fig. 3.1c), and from

eight sites in Wagonga Inlet (Fig. 3.1d). Panel retrieval was staggered across an 8 week

period, however, no evidence of differences in the quality or quantity of nauplii was observed,

and all populations were easily induced to spawn, indicating all tests were performed at the

peak of A. variegatus reproductive season.

Upon retrieval, the panels were ‘cleaned’ by gently scrubbing with a soft brush in FSW and

all other invertebrates removed. Panels were only used if Amphibalanus variegatus was found to be occupying > 15% cover of the panel (approximately 150 individuals). To induce spawning, the panels were left overnight in the dark maintained at 20°C and exposed to a bright light the following morning. This induced the release of nauplii, which were attracted to point sources of light enabling collection with a pipette.

24 h larval toxicity test All test solutions were derived from a stock solution of 1000 mg/l of copper which was

water and kept at 4°C to prevent reduction of copper ions in the solution. A 1000 µg/l Cu

solution was prepared each day from this stock solution and diluted with UV sterilized,

filtered seawater (0.2 micron) to obtain the treatment concentrations.

The tolerance sensitivity of Amphibalanus variegatus nauplii was investigated by measuring

the swimming activity of nauplii during a 24 h toxicity assay, which encompassed the moult

from Nauplii 1 to Nauplii 2. Within 2 h of spawning, nauplii from each site were exposed to

five nominal concentrations of copper (50, 100, 150, 200, 250 µg/l Cu) and a seawater

control. Containers were presoaked in appropriate solutions overnight to ensure the

concentrations of the test solutions were maintained. For each test concentration, twenty

nauplii were exposed to 10 ml of each test solution. Exposures were carried out in 6-well

Corning© polystyrene culture plates, with each plate containing a single replicate of each test solution. For each site, each treatment was replicated six times in order to obtain a more robust measure of within site variation (i.e. 120 larvae x 5 treatments and control, for each site). After 24 h, treatments were censused by counting the number of nauplii which had become immobilized under a light microscope. Nauplii were deemed ‘immobilized’ if they lay on the bottom surface of the well for 15 seconds without swimming (as in Qiu et al.

2005).

Molecular methods AFLP fingerprinting was performed on individuals collected from one site within Port

Kembla (15 individuals, 285 mg/kg and 330 mg/kg copper recorded in the benthic sediment

and oyster tissue respectively), Botany Bay (13 individuals, 63.5 mg/kg and 243 mg/kg

copper recorded in the benthic sediment and oyster tissue respectively) and Wagonga inlet (15

individuals, 28 mg/kg and 35 mg/kg copper recorded in the benthic sediment and oyster tissue

respectively). The choice of site tested within each estuary was random. Adults were

harvested from the panels following larval collection and stored in 95% ethanol. DNA was

extracted using a standard proteinase K digestion and phenol-chloroform extraction procedure

(Hillis et al. 1996). The Amplified Fragment Length Polymorphism (AFLP) protocol was

adapted from, and similar to, the original protocol of Vos et al. (1995) as follows: for each

digest reaction, 1 µl of DNA stock solution (50 - 200 ng) was mixed with 20 µl PCR H2O,

2.50 µl NEBbuffer 4 (New England BioLabs (NEB), Ipswich, USA), 1 µl MseI (10 U) and

0.50 µl EcoRI (10 U). Mixtures were incubated at 37 °C for 2 hr and then at 70 °C for 15 min

to denature the restriction enzymes. Five µl of digest products were combined with a ligation

reaction mixture (9.75 µl PCR H2O, 2.00 µl NEB T4 DNA Ligase reaction buffer (10x), 0.25

µl T4 DNA Ligase ((50 U–rxn)), 1 µl pre-prepared adapters Eco (5 pMol) and 2.00 µl pre-

prepared adapters Mse (5 pMol)) and incubated at 37 °C for 3 hr.

One µl of ligation product was then combined with a pre-selective PCR reaction mix

consisting of 12.25 µl PCR H2O, 2.50 µl dNTP mix (0.25mM), 0.25 µl NEB Taq (1.25 U), 2

µl Thermopol buffer (10x), 1 µl forward primer (0.5 µM) and 1 µl reverse primer (0.5µM)

(see Table 1 for primer sequences). PCR conditions were 20 cycles of 94˚C for 30 s, 56˚C for

60 s, and 72˚C for 60 s. For the selective amplification, a 1:10 dilution of the pre-selective

PCR products was made and 1 µl of each added to a selective amplification mix consisting of

12.25 µl PCR H2O, 2.50 µl dNTP mix (0.25 mM), 0.25 µl NEB Taq (1.25 U), 2 µl Thermopol buffer (10x), 1 µl selective fluorescent labelled (6-FAM, VIC, NED, PET) forward (E01) primer (0.5 µM) and 1 µl selective reverse (M02) primer (0.5 µM). PCR conditions in the first cycle was an initial denaturation at 94˚C for 2min, followed by 94˚C for 30 s, 65˚C for 30 s,

72˚C for 60s with the annealing temperature reduced by 0.7˚C for 13 cycles, then 18 cycles of

94˚C for 30 s, 56˚C for 30 s and 72˚C for 2 min, followed by a final extension step of 72˚C for 30 min.

Initially, 32 different primer pairs were tested, from which 8 primer pairs (see Table 1) were selected, based on their ability to discriminate between samples and their consistency.

Reactions using selective forward (E01) primers with different fluorescent labels were

subsequently pooled, 1:1:1:2 (6-FAM:VIC:NED:PET) and analysed using an Applied

Biosystems 3730 DNA Analyzer with GeneScan-500 (LIZ) (Applied Biosystems, Foster City,

USA) as the size standard. Fragment analysis was performed using SequentiX GelQuest software version 2.6.5 (SequentiX, Klein Raden, Germany) with bands being scored in a binary fashion as present (1) or absent (0). Bands were assigned to bins based upon three base pair (bp) size intervals. All fragments below 100 bp were excluded from the analysis. The quality and quantity of the digest, pre-amplified and amplified products was checked by running a diluted sample of each product on a 1.5% agarose gel.

Data analysis

The median effects concentration (EC50) for each site was calculated using the trimmed

Spearman-Karber method (US EPA Trimmed Spearman-Karber Analysis Program, Ver 1.5,

Environmental Monitoring Systems Laboratory, Cincinnati, OH, USA). A nested ANOVA was used to test for the effects of copper with category (industrialised vs reference) as a main factor, and estuary as a random, nested factor. Data was log-transformed to meet the assumptions of ANOVA.

For the population genetic analyses, total genetic diversity was partitioned between each estuarine category using an analysis of molecular variance (AMOVA) using GenAlEx version

6.41 (Peakall and Smouse 2006) with P-values generated based on 9999 permutations. A nested AMOVA was performed, with Port Kembla and Botany Bay nested within the

‘industrialised’ category, and Wagonga Inlet within the ‘reference’ category (termed as

‘regions’ in the AMOVA software package). Pairwise comparisons between all estuaries were also performed in order to elucidate individual variance components. The percentage of polymorphic loci was determined using AFLPsurv version 1.0. To visualize the data, a PCO plot was generated using the binary dataset and based on a Euclidean distance matrix.

To determine whether there was evidence of loci under directional selection within the

populations from the industrialized estuaries, the genetic data was analysed using Bayescan

version 2.1 (Foll and Gaggiotti 2008), which scans the data for marker loci which show

excess differentiation (outliers) from neutral evolution expectations. The software generates

E01 primer M02 primer No. loci

GAC TGC GTA CCA ATT CAAG GAT GAG TCC TGA GTA ACGG 29

GAC TGC GTA CCA ATT CAAG GAT GAG TCC TGA GTA ACTT 16

GAC TGC GTA CCA ATT CAGT GAT GAG TCC TGA GTA ACAG 72

GAC TGC GTA CCA ATT CAGT GAT GAG TCC TGA GTA ACGG 40

GAC TGC GTA CCA ATT CAGC GAT GAG TCC TGA GTA ACAG 66

GAC TGC GTA CCA ATT CAGC GAT GAG TCC TGA GTA ACGT 42

GAC TGC GTA CCA ATT CACT GAT GAG TCC TGA GTA ACGG 60

GAC TGC GTA CCA ATT CACT GAT GAG TCC TGA GTA ACAG 67

Table 3.2: Primer sequences used in AFLP analyses and number of loci amplified for each primer pair.

and compares two alternative models; one model includes the effects of selection, the other

excludes it. Default values as suggested by Foll and Gaggiotti (2008) were used,

monomorphic loci were removed and a low threshold of log(BF) > 0.5 was used in

accordance with Fischer et al. 2011 (i.e. a log(BF) > 0.5 would be considered as substantial

evidence for selection, log(BF) > 1, strong and log(BF) > 2, decisive). Analysis was made at

the global level (i.e. industrialised versus reference populations) and pairwise comparisons

also performed to check for population specific outliers.

3.4 Results

Variation in 24 h EC50 among estuaries

The 24 h EC50 for barnacle nauplii exposed to copper varied among industrialised and reference estuaries. Nauplii from the industrialised estuaries showed a significantly greater tolerance to copper than those from the reference estuaries (F1,2 = 194.62, p = 0.001). There

was no significant difference in the 24 h EC50 values between estuaries within each category

(F2,29 = 0.1474 p = 0.864).The average 24 h EC50 for nauplii from the industrialised and reference estuaries was 111.01 µg/l Cu (SE = 3.01) and 81.29 µg/l Cu (SE = 3.28) respectively (see Fig. 3.2 for mean estuary 24 h EC50 values).

Figure 3.2: Copper content measured in the tissue of oysters and sediment (left axis, based on dry weight values) and mean EC50 24 h for Amphibalanus variegatus nauplii from each estuary (right axis).

Sediment and oyster tissue values from Dafforn et al. (2012). NB: mean copper values presented are based on measurements taken from each of the sites at which A. variegatus were collected from. Error bars represent standard error.

Botany Port Wagonga

0.080 0.170 Botany Bay

0.011 0.450 Port Kembla

0.006 0.001 Wagonga Inlet

Table 2.3: Pairwise PhiPT values among Amphibalanus variegatus samples from 3 sites in southeastern

Australia. PhiPT values are shown below the diagonal and probability values shown above. Probability values based on 9999 permutations.

Figure 3.2: PCO plot of the AFLP fragments generated for the three Amphibalanus variegatus populations and based on a Euclidean distance matrix.

Population genetics and evidence of selection The eight primer combinations used produced 392 loci among the 43 samples, 78.83% of which were polymorphic. The percentage of loci which were polymorphic for Botany Bay,

Port Kembla and Wagonga inlet is 61.0, 58.7 and 54.8 % respectively. No differentiation was

found among estuarine categories (PhiPR = 0.008 p = 0.816) and/or among the 3 populations

(PhiPT = 0.003, p = 0.296, see Table 2). Examination of the data using a PCO plot revealed,

in line with the AMOVA, no evidence of any structure (Fig. 3.3). No evidence for the

selection of loci (outliers) was detected at the global level and/or between populations even at

the lowest threshold PO value (logPO > 0.5), thus all of the loci amplified can be considered

neutral (see Table 3.3).

Number of Number of Number

Analysis Populations polymorphic individuals in markers

markers analysis logPO > 0.5

Disturbance Indust vs ref 309 43 None

Estuaries Kem vs Bot 307 28 None

Kem vs Wag 293 30 None

Bot vs Wag 306 28 None

Table 3.3: AFLP markers in genome scans detected under selection (outlier loci) with test between industrialised versus reference estuaries, and pairwise estuarine comparisons.

3.5 Discussion

In-line with the general response of a range of aquatic organisms (reviewed in Johnston

2011), larvae of populations of Amphibalanus variegatus from the impacted estuaries

displayed a greater tolerance to copper than those from the reference estuaries. This response

was observed for populations collected from twenty sites within the two industrialised

estuaries and fourteen sites within the two reference estuaries. To our knowledge this

represents the largest assessment of metal-tolerance of wild-collected organisms ever

conducted in a marine system. However, A. variegatus brood their fertilised eggs for a period

and offspring may have acclimated to copper and/or other contaminants during development.

Based on results of the laboratory assay alone, it cannot be distinguished whether the bioassay

response is due to acclimation, or reflects a greater resistance. The lack of associated changes

in population genetic structure and absence of outlier loci within the industrialised

populations would indicate the former. There was, however, evidence of high gene flow

between the three estuaries, so it is possible that selection has occurred but is not fixed within

the population (i.e. local adaptation). With examination of the genome using a technique which provides greater resolution, the presence of loci under selection may have become evident.

Although the population genetic results indicate that no selection for resistant individuals has occurred, evidence from other work suggests that copper and/or other toxicants may be operating as selective agents within the impacted estuaries. Over the past 80 years, estuarine- wide levels of copper in Port Kembla and Botany Bay, based on water, biotic and sediment measures, have been shown to be high, or in the case of Port Kembla, grossly elevated and ecologically-detrimental (He and Morrison 2001; Birch et al. 1996; Birch 1996; Teutsch

1992; Evenden 1992; Hayes et al. 1998; Moran 1984). Over the past decade, conditions within Port Kembla have undergone significant improvement, but currently levels are still elevated above ANZECC guidelines and are predicted to be of ecological significance

(chapter 2; Dafforn et al. 2009; Dafforn et al. 2012). Thus the observed tolerance may reflect selective processes which have been operating within these estuaries for many generations.

Recently, in two independent studies, lower rates of recruitment were documented for

Amphibalanus variegatus in Port Kembla, although small numbers were still recorded suggesting tolerant individuals were being selected for and surviving (Dafforn et al. 2009; chapter 2). In another study, levels of copper found within recreational estuaries, were shown to be highly toxic to A. variegatus adults, although only a portion of individuals within the assemblage were affected (50% mortality recorded, Piola and Johnston 2008). In the barnacle

Amphibalanus amphitrite, differences in tolerance to the anti-fouling agent copper pyrithione, were found among families suggesting there may be substantial genetic variability in barnacle tolerance to a toxicant (Romano et al. 2010).

Although a greater tolerance to copper was seen in the bioassay, this effect may not be due to previous exposure to copper alone. In the real-world, polluted locations are rarely found to be composed of a single pollutant, but rather are characterised by a suite a pollutants (Klerks and

Moreau 2001). The impacted locations selected for this study conform to this pattern, and although copper was found to be elevated, high levels of other metals and contaminants have also been documented (see Dafforn et al. 2012). Exposure to other contaminants has been shown to increase tolerance to other metals, which is likely to due to similarities in the pathways involved in processing the contaminant (Wang and Rainbow 2005). For example

Münzinger and Monicelli (1992) found that Daphnia magna strains which had been acclimated to chromium over seven generations displayed a greater tolerance to copper and nickel compared to individuals with no previous chromium exposure (see also Wang and

Rainbow 2005; Klerks 1999).

No evidence of differences in population structure was seen and no outlier loci detected, indicating selection had not occurred. However, whilst the AFLP methodology provides a genome-wide census, which makes it a powerful tool in detecting differences in loci which might be implicated with selection (Wang et al. 2012), it is possible the loci/genes associated with tolerance were not amplified as the AFLP methodology only provides information on a limited portion of the genome. In a study by Williams and Oleksiak (2008), where breeding experiments have determined that there is considerable adaptation to a strong pollutant in the estuarine fish Fundulus heteroclitus, examination of the genome using the AFLP methodology, detected only a small number of loci (1-6%) under selection. In our study, by increasing the number of loci, using a methodology with greater genetic resolution (e.g. 454 sequencing, Stapley et al. 2010) and/or targeting specific regions of the genome, the effects of selection may have become evident. However, if a strong localised structuring force was in effect (i.e. selected loci fixed within the population/local adaptation), it would be expected the molecular approach used to have the power to detect this (Campbell and Bernatchez 2004).

The population genetic results indicate, in-line with predictions based on larval duration, that

Amphibalanus variegatus is a widely-dispersing species. Populations separated by as much as

300 km were found to show a high degree of genetic similarity (PhiPT = 0.003). Thus, as

postulated by Untersee and Pechenik (2007), it is possible that although selection may be operating at a local scale, for species whose populations experience high and frequent inputs of external recruitment, the effect may be quickly lost. For example Groenendijk et al. (2001) found that metal tolerance in the F1 generation of the midge Chironomus riparius was quickly lost when adapted and non-adapted individuals were crossbred.

Implications Risk assessments often rely heavily on results of tests performed on laboratory-reared animals, which have been acclimated to laboratory conditions, often for many generations. As already discussed by other authors, the development of tolerance by natural populations, has implications for how toxicity data should be extrapolated to actual risks faced by biota. Tests, which do not incorporate the influence of acclimation and/or genetic variability arising due to previous exposure, could lead to overestimations of long-term ecological risks. Furthermore, tests performed on field-collected populations whose exposure history has not been considered, could lead to the ecological assessments which underestimate potential impacts.

Although, in this instance, the differences seen between populations, were not extreme, in other studies, differences of up to 8-fold have been documented (Johnston 2011).

In this study, a greater tolerance to the toxicant copper was observed across a large number of sites spread across two impacted and two reference estuaries in one of the most spatially- extensive aquatic studies to date. In a recent review Johnston (2011) examined the literature on tolerance in aquatic organisms and found that most studies tested organisms from only 2 -

4 sites, thus limiting our ability to generalise with regards to how common or widespread toxicant tolerance is in aquatic systems. The spatially-extensive toxicant response observed would suggest that, for at least the studied species, tolerance may not be a rare phenomenon.

Thus, where induced tolerance may previously been considered a complicating, but uncommon ‘nuisance’ (Millward and Klerks 2002; Chapman 1985), perhaps it may be more extensive and prevalent than previously thought.

CHAPTER 4: General Discussion

The aims of this thesis were to evaluate the broader, ecological significance of levels of metals measured in the tissue of a biomonitor and to examine how exposure history effects the response of a common sessile invertebrate, to a contaminant challenge. Specifically in chapter 2, I investigated whether relationships could be found between tissue loadings of metals in the common native oyster Saccostrea glomerata and sessile invertebrate recruitment within an industrial harbour. I found relationships between copper/lead levels measured in S. glomerata and the density of the dominant barnacle Amphibalanus.variegatus and the dominant polychaete Hydroides elegans. Based on the observations seen in chapter 2, a second study was designed (chapter 3) which addressed whether this was a normal response or whether long-term exposure to contaminants had imbued this population with a greater capacity to tolerate metal stress. To test this, nauplii of the dominant species in the study,

Amphibalanus variegatus¸ collected from metal-exposed and pristine locations and challenged to copper in a laboratory assay.

4. 1 Accumulated metal concentrations in a biomonitor: broader ecological significance?

Traditionally, biomonitors have been used independently for the assessment of pollution

(Luoma et al., 2010), and interpretation is commonly limited to assessing temporal changes in loads (Rainbow, 1995), or if large differences between sites are obtained, predictions are made regarding the potential for contaminant effect. The value of using a biomonitor over measurements of metals in other matrices (e.g. sediment, water) lies in the assumption that it will capture levels of metals which are bioavailable. Thus, given the biomonitor is a living organism, this fraction is of biological importance. However, there are few studies which evaluate, or have examined the importance of tissue levels in a single biomonitoring species, to other species.

In chapter 2, I found that several metals were elevated above natural background levels across the entire harbour, but in particular, levels of copper/lead were correlated with the density of several species. This suggests the assumption that tissue loads, do in fact reflect levels which are biologically-relevant to a wider suite of species. Although, based on these results alone, I cannot generalise as to whether using a biomonitor is more effective than other approaches, these results indicate tissue levels relate to effects in other species, which few studies have ever tested, thus a biomonitor can be valuable. Further studies examining whether different biomonitoring species yield similar relationships would be valuable in determining the generality of this approach, both for evaluation of whether the patterns remain the same across different biomonitoring species, and also how these loadings correspond with effects across different communities.

4.2 A Biomonitor: a highly sensitive tool

Most studies when examining the impacts of metal pollution, derive results from stark comparisons between heavily-polluted vs pristine sites. Consequently, any subtle trends, within the data may be lost. In chapter 2, it was found that small differences in tissue levels across small spatial scales, was correlated with large effects in the sessile invertebrate communities. This indicates that disturbance events can remain highly localised, and that our biomonitor is sensitive enough to detect this. This has implications for how data should be interpreted, as community-level implications may be very difficult to predict if tissue values show high spatial variability, as this variability may correspond with significant effects in the community. The coupling of a biomonitor with an ecological measure, in this case, a survey of sessile invertebrate recruitment, proved to assist with the interpretation of the tissue values.

This methodology was found to be easily implemented, simple and highly effective, thus proved itself to be valuable tool in environmental monitoring studies.

4.3 Generality of response across populations: the role of prior contaminant exposure

Within Port Kembla, copper/lead tissue levels were correlated with the density of the

common native barnacle Amphibalanus variegatus, indicating metals were responsible for

mortailities across the harbour. However, Port Kembla has long been a highly disturbed

harbour, thus, the population of A. variegatus in this harbour may have evolved tolerance to metals, through long-term selection of tolerant individuals. If tolerance has been selected for, the effects seen in Port Kembla may be a gross under-estimation of how the same levels of metal would affect a population from a pristine location.

To explore whether the response of populations within Port Kembla is indicative of how other populations may response to disturbance, the tolerance of Amphibanus variegatus nauplii

across a range of populations was examined. In chapter 3, tolerance to copper was found to

differ between Amphibalanus variegatus nauplii collected from disturbed and relatively-

pristine estuaries, with individuals from Port Kembla displaying a greater tolerance to copper

in the bioassay, than those from pristine estuaries. Nauplii from another disturbed estuary

(Botany Bay), also displayed an increased tolerance to copper, at a level which was similar to

Port Kembla. This indicates it may be common for this species to develop tolerance to copper,

however, but effects within populations with no prior exposure may be at severe risk of

localised extinction.

Based on this finding alone, it cannot be interpreted whether the difference in response is due

to acclimation or adaptation. Barnacles brood their young for a period, thus during nauplii

development, mechanisms may have been activated which conferred tolerance in laboratory

assay (i.e. response due to acclimation). Alternatively, copper-tolerant individuals may have

been selected for and the population may have become locally-adapted to the high

contaminant levels. To elucidate whether tolerance was due to acclimation or selection for

tolerant individuals, the population genetic structure was also examined using an AFLP

methodology. No evidence of population structure was found across populations examined,

and there was no evidence of outlier loci, indicating local adaptation has not occurred.

However, it should also be considered that the genetic approach used was not sufficient to

detect loci which may be conferring tolerance. Use of a genetic approach which provides a more extensive genome-wide scan might have yielded different results.

There are very few studies in the literature which have tested tolerance across as many sites as in chapter 3. Consequently, it is difficult to conclude whether I should expect tolerance to arise across a number of populations, or whether the published work only reflects anomalous populations. The results from chapter 3 indicate that it might be common for populations to acquire tolerance. Also, despite spatial variability in background levels across each of the disturbed estuaries, the response was similar across a large number of sites. This indicates, atleast for the tested species, the mechanism imbuing individuals with tolerance, may be easily activated and conserved across a large number of individual within the population.

Although this might indicate that nauplii from the pristine estuaries should have demonstrated similar tolerance to those from the disturbed estuaries, it might be that the mechanism conferring tolerance may need to be activated at earlier stages of development (e.g. fertilisation), or may be maternally-derived (i.e. the parents need to be exposed to the stressor prior to fertilisation).

4.4 Implications

The greater tolerance of nauplii from Port Kembla and Botany Bay, in the assay, indicates that it may be common for individuals to acclimate to stressors during development, which confers tolerance in subsequent exposures. Based on this, it might be concluded that pollution-tolerant communities may be quite common. There have been a number of suggestions that based on the assumption that populations may frequently adapt to pollution, that water-quality guidelines should be relaxed (see Klerks & Weis, 1986). However, despite the capacity for individuals to acclimate, a decrease in Amphibalanus variegatus recruitment was seen across Port Kembla. Thus, irrespective of the mechanism conferring tolerance, there appear to be thresholds in the levels acclimated individuals can tolerate, thus the possibility that populations may develop tolerance is poor reasoning for why water quality guidelines

should be relaxed. Moreover, it is unclear what levels are required to trigger acclimation, thus in clean-harbours, depending on the pattern and levels of exposure, contaminants are still likely to cause significant mortality and pose a significant risk.

Klerks and Weis (1986) suggested, based on the evidence of the time, it seemed dangerous to relax water quality criteria based on the assumption that organisms may evolve tolerance.

Klerks and Weis based this assessment on the fact that laboratory selection experiments were not always able to successfully create tolerant populations and the observation that polluted locations were still frequently found to have a low diversity and abundance of species. In a recent review on differential tolerance between field-collected populations of aquatic organisms, Johnston (2011) concluded that there was not enough evidence to generalize about the occurrence of tolerance (Johnston, 2011). Johnston (2011) also highlighted that although a high incidence of tolerance was found in the studies, a bias in the publication of significant results might explain this result. The results of my thesis indicate that although it may be common for populations to develop tolerance, relaxing water quality criteria may be risky since the results of my thesis suggest that even if a species has developed tolerance, threshold levels which individuals can withstand, can still be much lower than the levels the population may be exposed to. Thus demonstrated tolerance in laboratory bioassays, does not necessarily infer greater success in the natural environment.

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Appendix 1

Mean site values (± SE) for all physicochemical variables measured 1 .- 79 75 51 .: , 4 1 9 1 . 08 75 252 971 821 639 996 161 1 1 1.89 1.08 16.3 v 3.09 3.45 545 3 3.17 599 07~ 0-416 0 0.985 0 0 0 0 ± ± ± ± :': 1 5± 5± 3± 5± 8± 5± 4± . . . . . 4.3± 47± 45± 05± 5 3.7 5 6 9.9± 9.7± 5.4± 4 4 233± 667 11.2 7.77! 10.6± 4 4_83:!: g 5.57± 6 8 10.57 3 5033:': 8 Turbidity(ntu) 1 2 16 25 31 03 5 108 136 274 258 2\l!l 345 508 0 0 0 0 0 0606 0974 0 0 0 0 0 04.3.8 0 0 0452 0.492 0.437 0.544 0254 0.397 0.423 0.414 0.442 0.572 0 0 ±: ± 7 23:!:: 24:!: 03:!:: 38+: 99±: 55± 267+: 567:1: 577+: 507:!: 725:!:: 533± 557±: 5 723+: 713±: 12 11 12 12 12 12 2 1303:!:: 12 12 12 12.743:!:: 12.427:!:: 12.233± 12.513.!: 1 '12457:1: '12533:!:: ' ' ' , 2 , ·12 12 12 12 12 12.373:!: 12.437 pH 1 4 5 5 18 15 28 2 71 97 84 .. 1 6 1 4 1 93 8 127 10 145 2_S5 6.17 6.29 3 625 7.09 5.12 585 3 5 346 5 8.44 7 4 4.79 4.72 0 ± ± ± ± ± ± ± ± :': I 1 6± 7 5± 9 7± 8± 4:': 13 63± 95 37 97± 73 75 73:': 139± 1.23± ' 137 127 132 140.2! 131 136 14.3.8± 130 126 123 137.5± 1.35 12'6 137 129.93± 143.97± 14 147.37± 123 129 128 132 142 130 DO(%) 1 3 0 0 0 0 0 0 ; 05 05 667 333 333 333 333 333 333 577 .3.3 . 0 0 0 0 0 0 0 0.577 0.333 0.333 0.333 0.333 0.882 0.577 0.577 0 0 ± ± ± ± ± ± :': 5± 5± JH JH 31 31± 31± 31± 31± .31 .31:': .31:': 667 667 667± 667 667 667± 667 30 30 (ppm) 30 30 31 30.61)7± 30 30 30.6t.J7± 30.667± 31.333! 30 30 M667± 30.61)7± 1 :ros 24 01 02 07 36 186 159 235 0:35 547 0 0 0 0 0 002 0348 0384 0874 0285 0353 0769 1)6(:;6 1)176 o.-128 0 0 0 0 0 0.195 0.118 O.Ov-44 0 0 0 0 0 0.0058 0 0.0713 0 0 ± ± :': 1 · 17± 11± 09± 07 05± 36± 61 9 235± 185± 127:': 073± 983± 023± 943± 987:': 907:': 683± 31) 36 36 36 36 36.22± 36 .35 36 36 35 35 36 35 35 36.007± 36.093± 3EL067± 36 35 35.927± 35.903± 35777± 36 nity(ppt) Sali 1 ,, 13 52 62 '109 275 615 376 564 318 5;3;3 947 745 476 423 424 427 1.05 1.06 0 0 0 0.11 0 024 0 0 0 0.708 0 0 0 0 0 0.391 0 0.641 0 0 0 0.598 0 ("C) ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± :': :': :': 65 61 92 32 64 67 ·17.3 117 067 843 823 987 995 823 997 743 19.7 18 19 19.35! '18.89 '18.86 18 18 18 18 19.71 1~ 19.067 18.573 18 18 19 18 13815± 20 18 1S.607 18 18 19 Temper.ature 1 2 9 3 7 6 5 8 4 17 14 18 2'1 22 23 25 26 11 15 10 12 13 16 19 20 Site