Metal concentrations in seagrass (Halophila ovalis) tissue and ambient sediment in a highly modified estuarine environment (Sydney estuary, Australia)

Marine Pollution Bulletin 131 (2018) 130–141

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Metal concentrations in seagrass (Halophila ovalis) tissue and ambient sediment in a highly modified estuarine environment (Sydney estuary, Australia)

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G.F. Bircha, , B.M. Coxa, C.H. Besleyb a b

School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia Monitoring, Design and Reporting, Customer Delivery, Sydney Water, NSW, 2143, Australia

A R T I C LE I N FO

A B S T R A C T

Keywords: Accumulation factors Tissue enrichment Management implications Sediment-tissue relationships

Research into sediment-seagrass tissue metal relationships has been undertaken in Sydney estuary due to the recognized role contamination plays in threats to seagrass health. Seagrass (Halophila ovalis) leaf tissue concentrations are elevated in Cu, Pb and Zn and contain the highest reported root Cr concentrations. Seagrass metal concentrations were significantly different between species H. ovalis and Zostera capricorni; between root and leaf tissue; and between sampling locations. Greatest tissue enrichment was for Pb, however metals were not enriched in seagrass relative to surficial sediment. Fine and total sediment metal concentrations were temporally consistent between collection years 2013/15, whereas root tissue metals changed between years and sites and leaf metal contents were temporally inconsistent. Extractable metal concentrations in fine sediment (< 62.5 μm) showed moderate significant correlation with root tissue and a weak significant relationship with leaf tissue, whereas total sediment metal showed no such relationships. Management implications are provided.

1. Introduction Seagrass meadows form some of the most productive ecosystems in the world (McRoy and McMillan, 1977) and provide high-value ecological services (Watson et al., 1993; Costanza et al., 1997, 2014; Halpern, 2008; Valiela, 1997). Seagrass debris provides abundant food to epiphytes, which are fed upon by epifaunal organisms, which then provide food to fish foraging in seagrass beds. Seagrass thereby provides an important link between primary producers, e. g. microalgae and higher-level consumers (Ambo-Rappe et al., 2007) and are positioned in a crucial ecological niche between infauna and pelagic species. Seagrass also support important economic services, for example by providing a habitat for the echinoid Paracentrotus lividus, which in many parts of the Mediterranean Sea is commercially important for gonads considered a seafood delicacy in European countries (Halpern, 2008; Valiela, 1997; Warnau et al., 1995). Seagrass communities also supply significant biogeochemical functions, e. g. nutrient cycling (McGlathery et al., 2007) and carbon sequestration (Duarte et al., 2005). An important feature of seagrass is the formation of a dense composite of leaves, rhizomes and roots, which acts to significantly reduce ambient energy resulting in sediment stabilisation (Orth et al., 2006; Caraco et al., 2006) and an increase in the fine fraction in bottom

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sediment. Elevated fine material provides additional adsorption surfaces increasing the abundance of metals in seagrass substrate (Schlacher-Hoenlinger and Schlacher, 1998), making metals a significant environmental companion of seagrass systems (Pergent-Martini and Pergent, 2000). Some metals may be incorporated into seagrass tissue from sediments resulting in inhibited growth (Ward, 1987) and adverse effects to biochemical pathways, e. g. photosynthesis (Ralph and Burchett, 1998). Sedimentary metals thus constitute a significant threat to seagrass functioning in estuarine environments (Lafabrie et al., 2007). Given that roots are more closely aligned to bottom sediments, a closer relationship between root-sediment than between leaves-sediment may be expected, however the relationship between metals in ambient surficial sediment and seagrass tissue is inconsistent and not well understood (Warnau et al., 1995; Howley, 2001). Because seagrass often occupies intensely urbanized sheltered coastal areas, these epiflora are frequently exposed and vulnerable to human disturbance (Ambo-Rappe, 2010). Two major causes have been recognized for loss of seagrass coverage, namely direct and indirect impacts (Waycott et al., 2009). Direct influences include disease and over-exploitation, including fishing, boating, coastal engineering (Howarth et al., 2000; Orth et al., 2006) and natural causes, e. g. cyclones and tsunamis. Indirect impacts are considered more damaging

Corresponding author. E-mail address: [email protected] (G.F. Birch).

https://doi.org/10.1016/j.marpolbul.2018.04.010 Received 24 January 2018; Received in revised form 28 February 2018; Accepted 7 April 2018 0025-326X/ © 2018 Published by Elsevier Ltd.

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Fig. 1. Study sites and sample locations.

2018). Because the concentration and bioavailability of metals in sediment is confounded by variable grain size (Forstner, 1982; Forstner and Calmano, 1998; Birch and Taylor, 2000a, 2000b), tissue-sediment relationships were investigated for both fine (< 62.5 μm) and total sediment. Seagrass tissue metal characteristics influence patterns of growth and morphology (Lyngby and Brix, 1984; Balestri et al., 2004) and possible seagrass loss (Prange and Dennison, 2000; Waycott et al., 2009). Dissimilar life histories for different seagrass species may have ramifications for biomonitoring and formulation of preventative measures (Nienhuis, 1986; Lafabrie et al., 2009). The four objectives of the current study were: to test for a statistically significant relationship between tissue (leaves and roots) and ambient sediment (total and fine - < 62.5 μm); to establish significant temporal change in metal concentration in seagrass tissue (leaves and roots) between sampling years 2013 and 2015 and a corresponding consistency in sediment (total and fines) metals concentrations during this period; to assess bio-sediment accumulation factors (BSAFs) for this species; and to test for statistically significant differences in tissue metal concentration between two seagrass species (Z. capricorni and H. ovalis) for roots and leaves.

and include declining water quality resulting from increased nutrient and contaminant inputs and sediment run-off (Ruiz et al., 2001; Giensen et al., 1990). Other indirect effects are from aquaculture, invasive species, overfishing causing loss of predators (herbivores) and climate change (Brouns, 1994). Historic declines in seagrass distribution worldwide have been associated with increased industrial and urban development (Larkum and West, 1982; Fortes, 1988). Since the earliest records of seagrass meadows in 1879, in all areas of the world for which data are available, seagrass meadows have declined. Globally, seagrass areas have disappeared at a rate of 110 km2/yr since 1980 and that 29% of the known areal extent of these meadows have disappeared since records were kept (Waycott et al., 2009). Moreover, the rate of decline has increased from a median of 0.9%/yr before 1940 to 7%/yr since 1990. Like the rest of the world, declining seagrass stocks are evident in Australian waters. The coastal environments of Australia support the highest number of seagrass species and the largest seagrass beds in the world (Walker and McComb, 1992a, 1992b). In recent years concern has been raised over the extensive loss in seagrass communities in Australian coastal environments where a loss of 45,000 ha of seagrass has been recorded since the 1960s (Walker and McComb, 1992a, 1992b). In Sydney estuary, the current area of seagrass coverage is approximately 50 ha, representing only 15% of the estimated pre-European, pristine distribution (West and Williams, 2008), whereas mean sedimentary metal enrichment has increased to > 10 times pre-anthropogenic concentrations (maximum is > 100 times) and adverse effects on benthic populations is estimated to take place in between 2% and 36% of the waterway, dependent on the metal (McCready et al., 2004, 2006a, 2006b, 2006c; Birch, 2017). Despite many recent studies of seagrass, there has been little attention to the response of seagrass metal tissue content to high sedimentary metal mixtures in the estuarine environment (Howley, 2001; Dowsett and Rayburg, 2011). Research into the relationship between sediment and seagrass tissue metals has been undertaken in Sydney estuary in recognition of the role contamination plays in threats to seagrass health and functioning in estuarine ecosystems (Lafabrie et al., 2007). These studies are essential to understanding the potential for adaptability and tolerance of seagrasses in declining coastal environments with varying degrees of environmental stability and suitability. The present investigation was part of earlier research on seagrass-sediment relationships for another epifloral species (Zostera capricorni), which co-habitats with Halophila ovalis in Sydney estuaries (Birch et al.,

2. Methods 2.1. Seagrass distribution and study areas In Sydney estuary, low-density distributions of H. ovalis are found interspersed with Z. capricorni in embayments of the upper estuary, including Hen and Chicken Bay, Iron Cove, Five Dock and in bays of Lane Cove with restricted occurrences in the lower waterway, i. e. Double and Rose Bays, Manly, North Harbour, Clontarf and Chinamans Beach (West et al., 2004; West and Williams, 2008) (Fig. 1). Minor beds of Posidonia oceanica are located in the more marine areas of the estuary, i. e. Manly and adjacent to North and South Head. Large seagrass meadows (West et al., 2004) of H. ovalis were easily located in upper Sydney estuary in the current study, but despite careful examination of the less impaired areas of the lower estuary and the adjacent, near-pristine Port Hacking estuary, no meadows of this seagrass species could be located. In the absence of a reference site for the study, two regions with vastly different sedimentary metal characteristics were used to investigate the influence on sedimentary metals on seagrass tissue. The contaminant status of sediments in Sydney estuary has been well established (McCready et al., 2004, 2006a, 2006b, 2006c; Birch et al., 1996, 1999, 2008, 2013) and showed sediment in Hen and 131

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ultrapure water. All glass- and plastic-ware and laboratory equipment were washed in detergent and dilute (5%) HNO3 and rinsed with MilliQ water. Fine (< 62.5 μm) and total sediment were analysed for As, Co, Cr, Cu, Mn, Pb and Zn (Birch and Taylor, 2000a, 2000b) by digesting approximately 0.5 g of dry material in 3 mL HCl and 1 mL HNO3 and heating to 120 °C for 2 h. The digest was boiled down to 1 mL and ultrapure water added to make up the total volume to 30 mL. After cooling to room temperature, the clear solution from each test tube was decanted into vials (modified USEPA 200.8 Rev. 4.4 method; US EPA, 1994; Clark et al., 2000; Siaka et al., 1998) for analysis by inductively coupled plasma optical emission spectrometry (ICP-OES).

Chicken Bay to be dominated by high As, Co, Cr, Cu and Mn contents, while Iron Cove was characterized by sediments containing high Pb and Zn concentrations. After 25 years of research on the chemistry of the water column and bottom sediments, the focus has moved towards understanding the influence of these sediments on ambient flora and fauna in the harbour (Chaudhuri et al., 2014, Nath et al., 2013, 2014a, b; Birch and Apostolatos, 2013, Lewtas et al., 2013, Muralidharan et al., 2012). Sydney estuary is a 30-km long drowned river valley draining 500 km2 (Fig. 1) located within the heavily-urbanized catchment of the City of Sydney on the east coast of New South Wales (NSW), Australia. The three sampling sites (two in Hen and Chicken Bay and one in Iron Cove) in the estuary were selected based on seagrass (H. ovalis) distribution maps (West and Williams, 2008) and on sediment metal concentrations (Birch, 1996; Birch and Taylor, 1999, 2000a, 2000b).

2.4. Seagrass tissue metals analysis Seagrass samples were dissected into leaf and root tissue using nonmetallic equipment and dried at 60°C until reaching constant weight (Marin-Guirao et al., 2005). Each sample (0.25 g dry weight) was digested in 30 mL glass test tubes using 6 mL HNO3 for roots and 8 mL for leaf tissue to cover tissues completely in the test tubes. Digestion started at room temperature overnight, followed by heating at 80°C for 1 h, and 120°C for 2 h until the liquid had boiled down to approximately 1 mL. After cooling to room temperature, each tube was made up to 30 mL and filtered before analysis.

2.2. Sampling In August 2013 six cores were randomly taken from the upper 15 cm of sediment (approximate depth of seagrass roots) at each of the two sites in Hen and Chicken Bay and one site in Iron Cove (Fig. 1) using a 90 mm diameter PVC tube and placed into polythene bags using nonmetallic equipment. Sediment was kept on ice for transport back to the laboratory within two hours of sampling. Five plants were taken at each site and pooled to provide sufficient dried mass for analysis and this was repeated six times per site. Samples were washed clean of sediment with in situ water, placed in plastic sample bags, transported to the laboratory on ice and immediately frozen. Insufficient material could be collected for rhizome metal analyses at all sites. Repeated sediment and seagrass tissue sampling were undertaken at the above sites in February 2015 (Tables 1 and 2) to investigate temporal variance in tissue metal concentrations.

2.5. Data quality A method blank and a replicate sample were included in each batch of 20 samples. All blank values were below detection limits (Table 3). Precision, determined by multiple analyses of certified reference materials (CRMs) (AGAL-10 and AGAL-6 for sediments and seagrass tissues, respectively), expressed as Relative Standard Deviation (RSD) was < 5% for all analytes for sediment and < 15% for seagrass tissue, except for Cr (28%) and Pb (27%). RSD for replicate analyses was < 6% for all analytes of sediment. Accuracy, expressed as percentage recovery and determined using the same CRMs, was between 92% and 106% for sediment and between 95% and 113% for all elements for seagrass tissue, except Cr (54%).

2.3. Sediment metals analysis Sediment was wet sieved through a 62.5 μm nylon mesh using

Table 1 Mean total and fine (< 62.5 μm) sediment metal concentrations (μg/g, dw) and enrichments (times background) for August 2013 and February 2015 sampling. Fine sediment (< 62.5 μm)

Total sediment Site August 2013 Hen & Chicken Bay HC 1A Hen & Chicken Bay HC 2A Iron Cove IC1A February 2015 Hen & Chicken Bay HC 1B Hen & Chicken Bay HC 2B Iron Cove IC1B Iron Cove IC2A Background concentrationsa Sediment enrichment (times background) August 2013 Mean Hen & Chicken Bay HC 1A + HC 2A Mean Iron Cove IC 1A + IC 2A February 2015 Mean Hen & Chicken Bay HC 1B + HC 2B Mean Iron Cove IC 1B + IC 2B Sediment quality guidelines ERLb ERMb ISQG-Lc ISQG - Hc a b c

As

Co

Cr

Cu

Mn

Ni

Pb

Zn

As

Co

Cr

Cu

Mn

Ni

Pb

Zn

15 12 12

4.9 4.1 3.9

56 46 36

118 131 75

48 46 40

9.3 8.5 8.7

112 127 146

268 256 303

28 26 24

11 9.6 7.9

144 139 81

294 342 189

111 110 90

21 21 19

278 296 351

677 683 710

13 12 13 11

4.6 5.1 4.6 4.3

50 49 41 37

103 138 89 99

45 44 57 50

9 8 11 12

93 138 161 175

233 285 330 341

27 26 23 30 24

12.0 8.9 8.2 11.0 6.5

144 133 82 101 30

294 342 189 288 10

108 114 89 119 111

20 20 20 26 15

275 300 347 460 20

677 694 712 926 50

1.2 1

1.5 1

5 3

32 23

1 1

1 1

14.5 20

14 16

1 1

1.5 1.5

5 3

32 24

1 1

1 1

14.5 20

14 17

8.2 70 20 70

na na na na

81 370 80 370

34 270 50 270

na na na na

21 52 21 52

47 218 50 220

150 410 200 410

Background concentrations from Birch et al., 2013 for Co, Cr, Cu, Mn, Ni, Pb and Zn and Irvine, 1980 for As. Long et al., 1998, ERL = effects range low; ERM = effects range median. ANZECC, 2000, ISQG-L and -H = Interim Sediment Quality Guideline-Low and -High; values in bold are > ERL, but < ERM; na = not available. 132

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Table 2 Mean metal seagrass (H. ovalis) tissue concentrations (μg/g, dw), tissue enrichment and Bio-sediment Accumulation Factors (BSAF) for August 2013 and February 2105 sampling. Leaves

August 2013 Hen & Chicken Bay HC 1A Hen & Chicken Bay HC 2A Iron Cove IC1A February 2015 Hen & Chicken Bay HC 1A Hen & Chicken Bay HC 2A Iron Cove IC1A Iron Cove IC2A Tissue enrichmenta Backgroundb August 2013 Mean Hen & Chicken Bay Mean Iron Cove February 2015 Mean Hen & Chicken Bay Mean Iron Cove Bio-sediment Accumulation Factors (BSAF)c August 2013 Mean Hen & Chicken Bay Mean Iron Cove February 2015 Mean Hen & Chicken Bay Mean Iron Cove

Roots

As

Co

Cr

Cu

Mn

Ni

Pb

Zn

As

Co

Cr

Cu

Mn

Ni

Pb

Zn

6.8 7.5 13

3.3 3.2 2.9

3.7 2.5 4.2

39 39 49

492 470 103

1.7 1.6 1.5

58 67 74

260 237 161

59 52 47

2.0 1.5 2.6

4.7 3.8 3.6

33 25 40

282 182 41

2.5 3.2 2.4

65 64 70

194 140 138

34 30 18 16

3.0 2.7 2.4 3.0

2.6 3.1 1.7 2.0

27 35 32 22

292 154 475 458

3.6 4.3 1.5 3.1

30 32 45 45

130 287 165 136

33 63 25 17

0.8 1.7 0.8 1.0

3.1 4.6 1.0 0.9

12 21 8.3 5.8

91 77 38 27

1.6 3.1 1.8 2.6

22 38 12 8.2

55 94 30 24

1.5

0.4

0.2

5.1

30

0.6

1.1

92

5.0

0.2

0.5

9.5

3.0

0.5

1.3

47

4.8 8.8

8.2 7.3

15 21

7.6 9.7

16 3.4

2.8 2.6

57 67

2.7 1.7

11 9.4

8.8 13

8.5 7.3

3.1 4.2

77 14

5.7 4.8

50 54

3.6 2.9

21 11

7.0 6.7

14 9.3

6.1 5.3

7.4 16

6.6 3.8

28 41

2.3 1.6

10 4.2

6.3 4.4

7.7 1.9

1.7 0.7

28 11

4.7 4.4

23 7.6

1.6 0.6

0.5 1.1

0.7 0.8

0.1 0.1

0.3 0.6

10 2.3

0.2 0.2

0.5 0.5

0.9 0.5

4.1 3.8

0.4 0.7

0.1 0.1

0.2 0.5

4.9 0.9

0.3 0.2

1 0

0.6 0.4

2.5 1.4

0.6 0.6

0.1 0.0

0.3 0.3

5 8.7

0.5 0.2

0.3 0.3

0.8 0.4

3.9 1.7

0.3 0.2

0.1 0.02

0.1 0.1

1.9 0.6

0.3 0.2

0 0

0.3 0.1

a

Mean tissue concentration/tissue background concentration. From Birch et al., 2018. c Mean tissue metal concentration/Mean total sediment metal concentration; To convert dry mass to wet mass divide by: leaf 8.9 and root 5.5 (also see Campanella et al., 2001: leaf 3.6). b

To assess the relationship of metal concentrations in seagrass tissue to predictor variables represented in this case by the various metal concentrations in the sediment across the two bays (Hen and Chicken Bay and Iron Cove) and both years (2013 and 2015), the multivariate regression technique Distance-based Linear Models (DISTLM) (McArdle and Anderson, 2001) was employed. Before running the DISTLM routine each of the metal concentrations in the sediment (total and fine) and seagrass tissue (leaf and root) datasets were normalised (subtracting the mean and dividing by the standard deviation for each variable). A dissimilarity matrix based on Euclidean distance was raised for each of the seagrass tissue datasets. To increase the sensitivity of the DISTLM analysis, strongly correlated variables (r > 0.9) in the sediment (predictor variable) datasets were omitted to account for multicollinearity. Modelled output of DISTLM was displayed in a constrained dbRDA ordination plot. To assess the adequacy of the plot, both fitted variation and total variation were inspected. If fitted variation exceeds 70%, the plot is likely to capture most of the salient pattern in the fitted DISTLM model (Anderson et al., 2008).

Table 3 Accuracy, precision and detection limits for analytical procedures.

Sediment (using AGAL-10) Precision (% RSD)a Precision (% RSD)b Accuracy (recovery %)b Detection limit (mg/L) Tissue (using AGAL-6) Precision (% RSD) Accuracy (recovery %) Detection limit (mg/L) a b

As

Co

Cr

Cu

Mn

Pb

Zn

8 6 104 0.01

9.4 6.7 102 0.05

10 5.0 101 0.01

6 3.0 96 0.01

110 6.1 108 0.001

13 3.0 101 0.05

12 1.0 92 0.001

62 92 0.01

17 109 0.05

10 54 0.01

6.2 98 0.01

7.1 98 0.001

6.7 113 0.05

5.3 93 0.001

Using replicates. Using AGAL-10; RSD = relative standard deviation.

2.6. Statistical analysis of sediment-tissue metal relationships 2.6.1. Relationship between (H. ovalis) tissue (leaves and roots) and ambient sediment (total and fine 62.5 μm) Canonical Analysis of Principal coordinates (CAP) (Anderson and Willis, 2003) was used to model change in metal concentrations of seagrass (H. ovalis) tissue along a metal concentration gradient of either total, or fine sediment. Each of the metal concentrations in seagrass tissue (leaf and root) datasets was normalised (subtracting the mean and dividing by the standard deviation for each variable) before a dissimilarity matrix based on Euclidean distance was raised for each of the two seagrass tissues. The CAP analysis for each set of seagrass tissue data was analysed against the metal gradient based on PC1 from a PCA run on a subset of total, or fine sediment data points that matched the number of available data points in each seagrass tissue type. CAP is designed to find an axis through the multivariate data cloud, which has the strongest relationship with the environmental variable of interest (Anderson et al., 2008). In this case, the environmental variable of interest was the metal pollution gradient in total, or fine sediment.

2.6.2. To assess for consistency in sediment (total and fines) metals concentrations between 2013 and 2015 sampling occasions, and to assess for temporal change in metal concentrations in seagrass (H. ovalis) tissue (leaves and roots) and ambient sediment (total and fines) between sampling times in 2013 and 2015 To assess for consistency in sediment (total and fines) metals concentrations these fractions were initially tested under an ANOVA model with the fixed factors of ‘Year’ and ‘Bay’. ‘Year’ had two levels 2013 and 2015, while ‘Bay’ had two levels Hen and Chicken Bay and Iron Cove. Inclusion of these two factors in the analysis allowed the interaction term ‘Year × Bay’ to also be tested. Conservative Type III Sums of Squares were inspected to base hypothesis decisions. Where results for the above interaction term ‘Year × Bay’ and the factor ‘Year’ were nonsignificant a subsequent ANOVA model based on the single factor ‘Bay’ 133

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was run. Significant test results for the factor ‘Bay’ allowed test outcomes of a subsequent Student-Newman-Keuls multiple mean comparison test to be inspected for differences in metal concentrations between bays. The inclusion of the factor ‘Bay’ in this analysis, avoided problems associated with potential spatial autocorrelation between the Hen and Chicken Bay sites, as under the above ANOVA and multiple mean comparison testing of sedimentary metal concentrations, samples collected from Hen and Chicken Bay were tested against samples collected from Iron Cove. Another ANOVA model based on the single factor ‘Year’ was assessed if metal concentrations in seagrass tissue types changed between 2013 and 2015. This model was run for each bay for the two (leaf, root) seagrass tissue types. Significant ‘Year’ factor results allow StudentNewman-Keuls multiple mean comparison tests to inspected for significant differences in tissue metal concentrations between 2013 and 2015 years.

for Iron Cove, while this relationship was not evident for these tissue types in the February 2015 sampling (Table 2). In February 2015 Cu, Mn, Pb and Zn root tissue concentrations were substantially lower than in August 2013 in both bays, but Mn concentrations in leaf tissue in Iron Cove increased from August 2013 to February 2015. 3.3. Analyses of the sediment-tissue metal relationship 3.3.1. Relationship between (H. ovalis) tissue (leaves and roots) and ambient sediment (total and fine 62.5 μm) Two PCAs were raised based on a subset of fine sediment data points that matched the number of available data points in each seagrass tissue type and another two PCAs were raised based on a subset of total sediment data points that matched the number of available data points in each seagrass tissue type. PC1 on the subset of fine sediment data points that matched the root tissue data points explained a large percentage of the variance (79%). Lower percentages of variance were explained by PC1 for the other three PCAs, 47%, 59% and 47% respectively, for the total sediment data points that matched the root tissue data points, for the subset of fine sediment data points that matched the leaf tissue, and for the total sediment data points that matched the leaf tissue data points. The Canonical Analysis of Principal coordinates (CAP) of metal concentrations in root tissue to PC1 from a Principle Components Analysis (PCA) of fine sediment (< 62.5 μm) metal concentrations indicated a moderate significant correlation (as described by the squared canonical correlation δ) between the metal pollution gradient in fine sediments and metal concentrations in root tissue (δ = 0.59, p = 0.0004) (Fig. 2). Weak to negligible correlations were returned for the other three CAP analyses of the total sediment data points that matched the root tissue data points (δ = 0.37, p = 0.0971), for the subset of fine sediment data points that matched the leaf tissue (δ = 0.37, p = 0.0064), and for the total sediment data points that matched the leaf tissue data points (δ = 0.003, p = 0.9983). Out of the four DISTLM models run, the model with marginally better levels of total and fitted variation was of root tissue metal concentrations to predictor metal concentrations in fine sediment constructed with As, Co, Cr, Mn, Ni, Pb and Zn (Table S1). To account for multi-collinearity, Cr also represented the omitted variable of Cu. A method of visualising the relationships of predictor variables is to examine the default vector overlay, which is produced as part of the dbRDA plot (Fig. 3). The longer the vector, the bigger the effect it has had in the construction of first two dbRDA axes being viewed. The longest vectors in this plot were Cr, Co and Pb. Positioning of these vectors suggested Cr, Co and Pb were most influential in differentiating Iron Cove and Hen and Chicken Bay samples, while As, Mn and Zn also contributed to this separation (Fig. 3). Fitted variation (88%) of this ordination plot was returned at a level suggesting the two broad data patterns were adequately displayed. The level of total variation (31%) explained suggested other unaccounted-for variables contributed to shaping the data pattern and placement of individual sample points should not be over interpreted.

2.6.3. Comparison of 2013 tissue (leaf and root) metal concentrations in H. ovalis and Z. capricorni seagrass species An ANOVA model based on the single factor ‘Tissue’ was used to assess if metal concentrations were different in tissue of H. ovalis and Z. capricorni seagrass species. As Z. capricorni tissue samples were only collected in 2013, tissue samples of H. ovalis were compared with those collected in 2013. This model was run on leaf tissue samples collected from Iron Cove and also run on leaf tissue samples collected from Hen and Chicken Bay. This ANOVA model was also run on root tissue samples collected from Hen and Chicken Bay only, as insufficient root tissue samples of Z. capricorni were collected in Iron Cove. A metric MDS (mMDS) ordination plot of 2013 collected seagrass (H. ovalis and Z. capricorni) tissue (root and leaf) metal concentrations was constructed based on an Euclidean distance association matrix. This ordination was run with 1000 random starts. Based on these same 2013 data, a PERMANOVA model (Anderson, 2001) was run with two factors ‘Plant’ that had two levels (H. ovalis and Z. capricorni) and ‘Tissue’ that also had two levels (root and leaf). Inclusion of these two factors in the PERMANOVA model allowed a corresponding interaction term ‘Plant × Tissue’ to be run. Univariate statistical tests were conducted with SAS software version 9.4. Prior to hypothesis testing, normal probability plots and results of Brown and Forsythe's test for homogeneity of variance were inspected for each of the eight metals for both fine sediments and total sediment. After inspection, metal concentrations were left untransformed, as untransformed values best met the underlying assumptions of analysis of variance (ANOVA). Multivariate data analyses (mMDS, dbRDA, CAP, DISTLM, PERMANOVA) were performed using the PRIMER Version 7.0.13 software package (Clarke et al., 2014) and the PERMANOVA+ (Anderson et al., 2008) add on module. 3. Results 3.1. Sedimentary metal concentrations

3.3.2. To assess for consistency in sediment (total and fines) metals concentrations between 2013 and 2015 sampling occasions and to assess temporal change in metal concentrations in seagrass (H. ovalis) tissue (leaves and roots) and ambient sediment (total and fines) during this period Temporal variance in metal concentrations for fine and total sediment, as well as for leaves and roots are provided for sampling years 2013 and 2015 in Table S2. Under the initial ANOVA model outlined above, the interaction term ‘Year × Bay’ were non-significant for all eight metals measured in fine sediment and for seven of the eight metals for total sediment (Table S3) A single significantly differently ‘Year × Bay’ interaction result was for Mn in total sediment. All eight metal concentrations in both total sediment and fine sediment were non-significant for the factor ‘Year’. Metal concentrations for the factor

Chromium and Cu concentrations for total sediment in 2013 were considerably higher (46 μg/g–56 μg/g and 118 μg/g–131 μg/g, respectively) in Hen and Chicken Bay than Iron Cove (35 μg/g–36 μg/g, and 75 μg/g–90 μg/g, respectively), which was mantled in sediment containing high Pb and Zn concentrations 146 μg/g–156 μg/g and 303 μg/ g–312 μg/g, respectively) (Table 1). This difference in metal concentrations in the two embayments was more pronounced for fine sediments. 3.2. Seagrass tissue metal concentrations In August 2013, leaf and root seagrass tissue Mn and Zn concentrations from Hen and Chicken Bay were substantially higher than 134

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Fig. 2. Canonical Analysis of Principal coordinates (CAP) ordination plot of metal concentrations in H. ovalis root tissue to PC1 (79%) from a Principle Components Analysis (PCA) fine sediment (< 62.5 μm) (δ = 0.59; m = 4).

‘Bay’ were significantly different for five of eight metals measured in total sediment and were also significantly different for six of eight metals measured in fine sediments (Table S3). Results of the second ANOVA model outlined above with the single factor ‘Bay’ returned the same pattern of significant results (Table 4) as under the initial ANOVA model for total sediment and for five of the six significant metal concentrations for fine sediment (Table S3). Corresponding multiple mean comparison tests demonstrated that metal concentrations in fine sediment best separated the two bays with higher Co, Cr, Cu, and Mn concentrations in Hen and Chicken Bay, while the concentrations of Pb and Zn were higher in Iron Cove (Table S3). The ANOVA model based on the single factor ‘Year’ to assess if metal concentrations in seagrass tissue types changed between 2013 and 2015 was confirmed for five of the eight metal concentrations for root tissue at Hen and Chicken Bay and a statistically significant change in root tissue metal concentrations also occurred for six of eight metals for Iron Cove (Table S4). Results of the same ANOVA model conducted

on leaf tissue indicated concentrations for four of eight metals were significantly different for Hen and Chicken Bay, and one metal from Iron Cove (Table S4). Subsequent Student-Newman-Keuls multiple mean comparison tests indicated root tissue concentrations were higher in 2013 in Hen and Chicken Bay and Iron Cove (Table S4). The Student-Newman-Keuls multiple mean comparison test of leaf tissue concentrations for Iron Cove were higher in 2015 while for Hen and Chicken Bay out of the four Student-Newman Keuls multiple mean comparison tests, two were higher in 2015 and two were higher in 2013 (Table S4). 3.3.3. Comparison of 2013 tissue (leaf and root) metal concentrations in H. ovalis and Z. capricorni seagrass species Copper in leaves and Cr in roots of Z. capricorni were substantially higher than in H. ovalis, while Pb in leaves of H. ovalis was more enriched than in Z. capricorni (Table 5). The ANOVA model based on the single factor ‘Tissue’ used to assess differences in metal concentrations

Fig. 3. dbRDA ordination plot of DISTLM results of H. ovalis root tissue metal concentrations to fine sediment metal concentrations from three sites sampled in 2013 and 2015 with vector overlay of fine sediment metals (Cr represented Cu to allow for multi-collinearity). 135

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Table 4 Results from ANOVA comparing metal concentrations in total and fine sediment between bays (Hen and Chicken, and Iron Cove) for samples from both collection periods (2013 and 2015) and corresponding Student-Newman-Keuls multiple mean comparison tests. Metal variable SNK

As SNK Co SNK Cr SNK Cu SNK Mn SNK Ni SNK Pb SNK Zn SNK

Total sediment

Fine sediment

F

p-Value

F

p-Value

1.12

0.2960 – 0.0604 – < 0.0001a HC IC < 0.0001a HC IC 0.5213 – 0.0124a IC HC < 0.0001a IC HC 0.0003a IC HC

0.50

0.4847 – 0.0186a HC IC < 0.0001a HC IC < 0.0001a HC IC 0.0479a HC IC 0.0690 – < 0.0001a IC HC < 0.0001a IC HC

3.75 21.01 32.07 0.42 6.89 27.16 15.65

6.05 296.03 42.06 4.18 3.50 66.18 23.38

Table 6 Results from ANOVA of factor ‘Plant’ with two levels (H. ovalis and Z. capricorni) of metal concentrations in 2013 tissue samples.

Sydney estuary August 2013 Hen & Chicken Bay Iron Cove February 2015 Hen & Chicken Bay Iron Cove Hen & Chicken Bay Iron Cove

Species

Leaves Cu

Pb

Zn

Cr

Cu

Pb

Zn

HC Leaf tissue

IC Leaf Tissue

As

F P SNK F P SNK F P SNK F P SNK F P SNK F P SNK F P

0.00 0.9705 – 0.01 0.9224 – 2.34 0.1518 – 0.10 0.7519 – 14.82 0.0023a H. ovalis 3.54 0.0843 – 1.19 0.2969

10.02 0.0047a H. ovalis 0.16 0.6907 – 8.21 0.0093a Z. capricorni 13.49 0.0014a Z. capricorni 1.83 0.1903 – 16.19 0.0006a H. ovalis 0.56 0.4628

2.29 0.1810 – 10.47 0.0178a H. ovalis 0.02 0.8881 – 0.20 0.6698 – 0.52 0.4981 – 2.51 0.1641 – 0.40 0.8411

Cu

Mn

Pb

Zn

a Bold = significantly different. Brown and Forsythe's tests for homogeneity of variance were non-significant. SNK the seagrass species displayed indicates significantly higher mean concentration. Comparison of Ni not possible as Ni was not analysed for Z. capricorni.

statistically significant as a corresponding PERMANOVA test of ‘Plant’ (df = 1, MS = 25.575, Pseudo F = 6.2188, P(perm) = 0.0014) and ‘Tissue’ (df = 1, MS = 84.578, Pseudo F = 20.566, P(perm) = 0.0001) factors were significantly different. Inclusion of these two factors in the PERMANOVA model allowed a corresponding interaction term ‘Plant × Tissue’, which was non-significant (df = 1, MS = 2.895, Pseudo F = 0.70396, P(perm) = 0.5512), and this test outcome allowed noting the above ‘Plant’ and ‘Tissue’ test outcomes.

Roots

Cr

HC Root tissue

Cr

Table 5 Seagrass tissue metal concentrations (μg/g, dw) for Halophila ovali and Zostera capricorni species from Sydney estuary. Reference

Statistic

Co

a Bold = significantly different. SNK given in order of decreasing mean concentrations. Brown and Forsythe's tests for homogeneity of variance were non-significant for seven of the eight metals tested for total sediment and for half of the metals tested for fine sediment. Exceptions were for Cu for total sediment Cu, Mn, Ni, Pb and Zn for fine sediment. Transformation did not improve homogeneity of variance for these exceptions.

Sydney estuary locations

Metal variable

1

H

3.1

39

63

249

4.3

29

65

167

4. Discussion

1

H

4.2

49

74

161

3.6

40

70

138

4.1. Seagrass tissue metal concentrations in Australia and globally

1

H

2.9

31

31

209

3.9

16

30

75

1 2

H ZC

1.9 5.0

27 60

45 45

150 235

0.9 9.5

7.1 42

10 66

27 184

2

ZC

3.4

61

45

197

na

na

na

na

Seagrass (H. ovalis) leaf tissue concentrations in Sydney estuary were high in Cu, Pb and Zn compared to other global locations, however these levels were not the highest reported in the literature, except for Cr (4.3 μg/g) in root tissue (Table 7). Leaf (P. australis) tissue concentrations at the near-field sampling locations at the site of a large Pb and Zn smelter in the Spencer Gulf, South Australia were the highest recorded for Pb (167 μg/g). The highest Zn (397 μg/g) leaf concentrations for Z. capricorni was found in Cockle Bay, Lake Macquarie (NSW) and this site also supports this seagrass species with the highest recorded Cu (84 μg/g), Pb (212 μg/g) and Zn (592 μg/g) root tissue concentrations.

References: 1 Current study; 2 Birch et al., 2018. H = Halophila ovalis; ZC = Zostera capricorni; na = not available.

in tissue of H. ovalis and Z. capricorni seagrass species collected in 2013 identified one significant difference for Mn in root tissue metal concentrations in Hen and Chicken Bay and a single significant difference for Co in leaf tissue metal concentrations in Iron Cove. Corresponding Student-Newman-Keuls multiple mean comparison tests indicated mean concentrations were higher for H. ovalis (Table 6). The model run for leaf tissue metal concentrations for Hen and Chicken Bay samples indicated significant difference for As, Pb, Cr and Cu. Student-NewmanKeuls multiple mean comparison tests indicated mean concentrations of As and Pb were higher for H. ovalis and Cr and Cu were higher for Z. capricorni (Table 6). Fifteen of the 21 possible univariate comparisons of plant tissue between the two-plant species were non-significant. The mMDS of metal concentrations for 2013 samples of root and leaf tissue in both H. ovalis and Z. capricorni seagrass species for the two sites in Hen and Chicken Bay displayed differences for tissue types and seagrass species (Fig. 4). These differences were confirmed to be

4.2. Tissue-specific metal concentrations In Sydney estuary, leaves of the H. ovalis had higher Cu (49 μg/g), Pb (74 μg/g) and Zn (249 μg/g) concentrations than roots, while root Cr tissue concentrations (4.3 μg/g) were higher than leaves in Hen and Chicken Bay, but not in Iron Cove. At Cockle Bay the reverse trend was evident for Z. capricorni with Cu (84 μg/g), Pb (212 μg/g) and Zn (592 μg/g) being higher in root tissue than in leaves. Above-ground tissue (leaf) typically contains higher Cu and Zn concentrations than below-ground tissue (Brix and Lyngby, 1982: Lyngby and Brix, 1982, 1984). However, this trend is not consistent. A review of 13 global locations, mainly in the Mediterranean region and Europe, (Table 7), indicated leaf tissue contained higher Zn than roots, 136

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Fig. 4. Three dimensional mMDS ordination plot of metal concentrations in H. ovalis and Z. capricorni root and leaf tissue for 2013 samples from Hen and Chicken Bay: a) axis 1 versus 2; b) axis 1 versus 3; c) axis 2 versus 3. L = leaf; R = root.

137

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Table 7 Seagrass tissue metal concentrations (μg/g, dw) from Australian and global locations. Australian and global studies

Sydney estuary August 2013 Hen & Chicken Bay HC 1 + 2 Iron Cove IC 1 February 2015 Hen & Chicken Bay HC 1 + 2 Iron Cove IC 1 + 2 Pittwater, NSW Botany Bay, NSW Port Hacking, NSW Reference sites Lake Illawarra, NSW N Giffin Bay (highest) Entrance (lowest) Lake Macquarie, NSW Cockle Bay (highest) Wangi-Eraring Bay (lowest) Port Curtis, Queensland Spencer Gulf, S Australia Near smelter Far from smelter Global studies Italy, Sardinia Corsica Favignana Is., Sicily Canari, Sardinia Livorno, Sardinia Calvi, Corsica Inchia, Italy Marseille, France Alacant, Spain Corsica Corsica Cote d'Azur, France Thau Lagoon, France Limfjord, Denmark

Ref

Species

Leaf

Root

Cr

Cu

Pb

Zn

Cr

Cu

Pb

Zn

1 1

H H

3.1 4.2

39 49

63 74

249 161

4.3 3.6

29 40

65 70

167 138

1 1 2 2

H H ZC ZC

2.9 1.9

31 27 55 10

31 45

209 150 160 250

3.9 0.9

16 7.1 19 6

30 10

75 27 125 180

1

ZC

0.2

39

0.1

93

0.5

9.5

1.3

47

3 3

ZC ZC

15 7.0

< 2.0 < 2.0

133 44

4 4 5 6 6 6

ZC ZC ZC PA PA PA

52 15 11

148 3.4

397 115 45

84 15

212 4.1

592 66

1.6 1.2

167 3.7

379 118

7 8 9 9 10 10 10 11 11 11 11 12 13

PO PO PO PO PO PO PO PO PO PO PO ZM ZM

15 22 19

15 11 12

111 107 112

14

1.2 0.6 1.2 0.3 1 1.7 1.5

0.3

15

10 16 12 7.7 8.6 23 10 6.3

2.7 2.7 1.5 1.4 6 8.4 7.8 2 4.1 8.4 18 1 1.1

120

154 144 179 125 111 20 57 83 101

1.5 1.8 2

References: 1 Current study; 2 MacInnis-Ng and Ralph, 2004a, 2004b, 2004c; 3 Howley, 2001; 4 Ambo-Rappe et al., 2007; 5 Frange and Dennison, 2000; 6 Ward, 1987; 7 Lafabrie et al., 2009; 8 Campanella et al., 2001; 9 Lafabrie et al., 2007; 10 Warnau et al., 1995; 11 Schlacher-Hoenlinger and Schlacher, 1998; 12 Casabianca et al., 2004; 13 Brix and Lyngby, 1982. H = Halophila ovalis; ZC = Zostera capricorni; PO = Posidonia oceanica; ZM = Zostera marina; PA = Posidonia australis. To convert dry mass to wet mass divide by: leaf 8.9; and root 5.5 (also see Campanella et al., 2001: leaf 3.6).

off the Italian mainland (Lafabrie et al., 2007, 2009). Background seagrass tissue metal concentrations were compiled from these four European studies and local data from the near-pristine Port Hacking reference estuary (Birch et al., 2018) (Table 2). Greatest enrichment was recorded for Pb in H. ovalis leaf (28–67 times) and root tissue (8–54 times), followed closely by Mn in roots (11–77 times) (Table 3). Moderate enrichment was observed for As, Co, Cr and Cu (4.8 to 21 times) in H. ovalis leaves and roots, while Zn and Ni were only minimally enriched (< 6 times) for these tissue types. These enrichment levels cannot be compared to other locations as none have been published previously.

whereas Cr, Cu and Pb were slightly more enriched in root tissue than in leaves. The inconsistent preferred accumulation of metals in different types of seagrass tissue in the Sydney region and globally has been related to variance in environmental factors, e. g. salinity, water temperature and turbidity in different locations and to different mechanisms of uptake, growth rates and translocation (Phillips, 1990; Bond et al., 1988). 4.3. Background metal concentrations and enrichment in sediment and seagrass tissue The magnitude of human-induced change (enrichment) is estimated by dividing surficial sediment metal concentrations by background levels (Irvine and Birch, 1998; Birch et al., 2013) based on size-normalised data (Birch, 2017). Enrichment of sedimentary metals is highest for Cu (24 to 32 times), Pb (14.5 to 20 times) and Zn (14 to 17). Sedimentary Cr is moderately enriched (three to five times) and As, Co, Mn and Ni are not enriched over pre-anthropogenic concentrations (Table 1). Nienhuis (1986) published background metal tissue concentrations for nine seagrass species for temperate, sub-tropical and tropical regions and Campanella et al. (2001) provided background tissue metal concentrations for a variety of biota for the Mediterranean region based on data from an isolated Sicilian island (Favignana Island). Background seagrass tissue metal data were also obtained from remote locations on Sardinia and Corsica, which were used to assess the status of seagrass

4.4. Bio-sediment accumulation factors (BSAFs) Bio-sediment accumulation factors are the ratio of tissue metal concentrations to contemporary sediment metal levels, which indicate the ability of the plant to translocate metals from sediment to various parts of the plant, however BSAFs have been reported sparsely (Lafabrie et al., 2007; Casabianca et al., 2004). Generally, metals were not enriched in H. ovalis tissue relative to ambient surficial sediment, i.e. BSAFs were typically < 1.0. BSAFs were highest for Mn in leaves (2.3 to 10) and root tissue (0.9–4.9 times) and As in roots (1.7 to 4.1 times) (Table 3). A similar result was reported for Z. marina in a French lagoon (Casabianca et al., 2004) where all BSAFs were < 1.0, except for Zn (2.5), however BSAFs of up to 2.5 times (Ni) have been reported for the Tyrrhenian Sea (Lafabrie et al., 2007). In these areas sediment metal 138

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this embayment increased from an absence in 1982 to 38,170 m2 in 1998 before declining to 29,650 m2 in 2003. Although no causality could be demonstrated, a trend of increasing seagrass distribution and decreasing metal contamination was observed with fine sediment content remaining constant, i. e. the change was not related to textural variance. The recent decline in seagrass coverage may be due to an increase in boat moorings and boating activities over this period.

concentrations were considerably lower than for Sydney estuary, resulting in high BSAFs (except for Cd), rather than due to high tissue metal concentrations. 4.5. Sediment-tissue metal relationships ANOVA results indicated metal concentrations in fine and total sediment did not change between the two collections years, while differences in metal concentrations between bays were best characterized by fine sediment. Corresponding Student-Newman-Keuls tests of metal concentrations in fine sediment indicated Hen and Chicken Bay had higher mean levels for five (Co, Cr, Cu and Mn) of the seven significantly different metals than that of Iron Cove, while mean concentrations of Pb and Zn were higher in fine sediment of Iron Cove. The CAP analysis of metal concentrations in root tissue to PC1 from a PCA of fine sediment (< 62.5 μm) metal concentrations indicated a moderate significant correlation. The CAP ordination plot displayed a clear difference between root tissue samples from the Hen and Chicken Bay and Iron Cove locations. A weak significant relationship was indicated for the CAP comparison of metal concentrations in leaf tissue to fine sediment. Non-significant relationships were returned for CAP comparisons of metal content in root and leaf tissue to metal concentrations in total sediment. This suggests the response of seagrass H. ovalis metal tissue content is related to fine and not to total sediment metal concentrations. The DISTLM multivariate regression analysis of root tissue metal content to fine sediment metal concentrations displayed clear differences between the two locations and differences between the two collection years (2013 and 2015) were also apparent. The vector overlay of fine sediment metals reflected the above ANOVA pattern between sites. A trend of decreasing H. ovalis root tissue metal content was indicated by the Student-Newman-Keuls test results that displayed lower mean concentrations in 2015 than those of 2013 for the 11 significant comparisons across the eight metals for both Hen and Chicken Bay and Iron Cove. Evenly mixed increasing and decreasing trends in leaf tissue metal content was evident for Hen and Chicken Bay over the sampling period, while Iron Cove leaf tissue was statistically similar for seven of eight tested metals between 2013 and 2015. These mixed leaf tissue results probably influenced the lower percentage of fitted variation in the DISTLM model runs that assessed the relationship of metal concentrations in H. ovalis leaf tissue to sedimentary (fine and total) metal concentrations. Although the current study has demonstrated a significant relationship between metals in seagrass roots and leaves and ambient fine sediment, it is not possible to determine whether sedimentary metals affected seagrass coverage in Sydney estuary. A large apparent decline in seagrass in Sydney estuary between 1978 and 2000 from 128.6 ha to 51.7 ha, (60% loss) was reported with large losses at some locations (Clontarf) and small gains at others (Iron Cove) (West et al., 1985). This decline in seagrass distribution occurred during a general significant increase in sedimentary metal concentrations in the estuary (Birch et al., 2013). However, the estimate of seagrass coverage was later revised using improved GIS techniques (previous methodologies involved optical superimposition) to 59.2 ha in 1978 and 51.9 ha in 2000, i.e. a loss of only 12.3% over 22 years (West et al., 2004; West and Williams, 2008). Only approximately 25% of seagrass mapped over a 25-year period in Sydney estuary was permanent (West and Williams, 2008), suggesting that at least some of this spatial change is consistent with short-term temporal variance. A more specific spatio-temporal study of relationships between changes in seagrass distribution and metal concentrations was made in Hen and Chicken Bay (Butland, 2004) (Fig.1). Changes in seagrass distribution determined between 1982 and 2003 using kriging interpolation of historical aerial photography were compared to changes in fine (< 62.5 μm) surficial sediment metal (Cu, Pb and Zn) concentrations (Birch et al., 2013). The study showed the extent of seagrass in

4.6. Concentration of metals in tissue of Halophila ovalis and Zostera capricorni Significant differences in metal concentrations were identified between these seagrass species and also between root and leaf tissue under PERMANOVA multivariate testing for data collected in 2013 from Hen and Chicken Bay. These differences were also illustrated in the corresponding mMDS ordination plot. Companion ANOVA of root and leaf tissue for the two-plant species from Hen and Chicken Bay identified no consistent trend across tissue types where significant differences were identified with corresponding Student-Newman-Keuls test indicated Mn mean root tissue concentrations were higher in H. ovalis, while mean leaf tissue concentrations were higher in Cu and Cr for Z. capricorni and in As and Pb for H. ovalis (Table 6). These metal content differences probably shaped the above multivariate PERMANOVA (see Section 3.3.3) pattern of Hen and Chicken Bay samples of the two-plant species and two tissue types. Leaf metal content of the two-seagrass species in Iron Cove samples were statistically similar with only Co mean concentrations higher for H. ovalis. Insufficient root tissue samples for Z. capricorni prohibit a similar multivariate analysis of Iron Cove and possible confirmation of bay-specific patterns. Dissimilarities in the life histories of H. ovalis and Z. capricorni may result in some of the observed differences in tissue metal concentrations between these two seagrass species. Z. capricorni is larger and longerlived than H. ovalis and leaf and rhizome mass is also greater for Z. capricorni. H. ovalisis is annual or perennial, whereas Z. capricorni is perennial, which would affect metal accumulation loads and possibly resilience/sequestration, however it is not known whether Z. capricorni being monoecious and H. ovalis being dioecious, has any effect on metal uptake. 5. Conclusions Seagrass (H. ovalis) Cr root tissue concentrations in Sydney estuary are the highest reported and leaves had higher Cu, Pb and Zn concentrations than roots. Greatest leaf and root tissue enrichment was for Pb, however metals were not enriched in seagrass tissue relative to ambient surficial sediment, i. e. BSAFs were typically < 1.0. Fine and total sediment metal concentrations did not change in the study areas between collections years (2013 and 2015), however leaf tissue metal content was inconsistent for seagrass from one bay (Hen and Chicken Bay) and statistically similar for seven of eight tested metals in the other embayment investigated (Iron Cove) over the period. Metal concentrations in fine sediment (< 62.5 μm) showed a moderate significant correlation with root tissue and a weak significant relationship with leaf tissue. No significant relationships were displayed for metal content in root, or leaf tissue to total sediment metal concentrations, emphasising seagrass metal tissue content is related to fine and not to total sediment metals. Root tissue metal concentrations were statistically different in seagrass from the two bays studied, whereas significant differences in metal concentrations were identified between seagrass species (H. ovalis than Z. capricorni) and also between root and leaf tissue collected in 2013 from Hen and Chicken Bay. Mean root Mn tissue concentrations were higher in H. ovalis than Z. capricorni, while mean leaf tissue concentrations were higher in Cu and Cr for Z. capricorni and in As and Pb for H. ovalis. 139

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Although seagrass-based indicators have been widely used to assess coastal ecosystem status, there is little universality in the manner of application. Matching the many available indicators to specific management objectives requires a detailed knowledge of species-specific sensitivities and response to environmental stressors. Although tissue metal concentrations were enriched relative background values these levels were less than ambient total sediment and are only moderately related to the fine sediment fraction. Tissue metal content displayed temporal and spatial variance and considerable inter-species and intertissue differences. These characteristics continue to make biomonitoring using these media a challenge.

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