Sediment-bound heavy metals as indicators of human influence and biological risk in coastal water bodies

ICES Journal of Marine Science, Nov 2008

Birch, Gavin F., Olmos, Marco A.

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Sediment-bound heavy metals as indicators of human influence and biological risk in coastal water bodies

Sediment-bound heavy metals as indicators of human influence and biological risk in coastal water bodies. - ICES Journal of Marine Science Sediment-bound heavy metals as indicators of human influence and biological risk in coastal water bodies Gavin F. Birch Marco A. Olmos Currently, many institutions are conducting or planning large, regional-scale ecosystem assessments of estuarine health. A full, integrated assessment of these environments requires a large suite of biological, physical, and chemical indicators, including sedimentary chemistry, ecotoxicology, benthic community structure, and bioaccumulation. This commitment is beyond the capacity of most organizations, and a simpler approach is required to accommodate limited financial resources. A case is made for the use of sedimentary heavy metals as an easy and inexpensive indicator. The advantages are that sediments identify the “pristine” condition and give baseline information against which future management strategies may be benchmarked, and that they differentiate solely humaninduced change from natural variation. Sediment indicators in depositional environments are also less dynamic than those associated with water and biota. Our objective is to demonstrate that sediment-bound heavy metals data provide the spatial extent and magnitude of chemical change, as well as the risk of biological stress attributable to contamination in estuarine ecosystems. An assessment of this scheme involving seven New South Wales (Australia) estuaries suggests that sedimentary heavy-metal indicators used in a weightof-evidence approach, with data collected during the recent Australian National Land and Water Resources Audit, enhances estuarine condition assessment. estuarine health; heavy metals; indicators; sediment quality Introduction The increased effort of achieving sustainable use of the marine environment, in particular of coastal zones, has resulted in a search for reliable indicators of “healthy” ecosystems. Ecosystem health has been defined as the ability of an environment to maintain biodiversity and integrity (ANZECC/ARMCANZ, 2000) . For the system to be healthy, it should also be temporally stable, resilient to change, and lack distress signals (Rapport, 1995) . The Intergovernmental Oceanographic Commission (IOC) of the United Nations Conference on Environment and Development (UNCED) initiated several programmes to address the sustainable use of the marine environment (Magni, 2003; Magni et al., 2004) . The Health of the Ocean (HOTO) module of the Global Ocean Observation System (GOOS), formed under the auspices of the Global Investigation of Pollution in the Marine Environment (GIPME), is encouraging the adoption of a common, integrated strategy for assessing the effect of anthropogenic activities on the marine environment. The UNESCO-sponsored, ad hoc Benthic Indicator Group, formed in 1999 by the IOC, is assessing options for determining ecosystem health that are globally applicable, as well as being easy and inexpensive to measure (AHBIG, 2000) . This group recognizes that, for such a purpose, a wide range of tools, methods, and models would be preferable to a single indicator. A weight-of-evidence approach is being promoted, whereby information from multiple indicators (chemical, biogeochemical, toxicological, physical, and hydrologic) is assessed within a decision framework. A hierarchical approach is also being applied to the assessment of estuaries in Australia, so that limited resources can be distributed most effectively. An initial qualitative assessment of the condition of Australia’s 970 estuaries was completed recently by the National Land and Water Resources Audit (NLWRA, 2002) . Four conditions were distinguished: near-pristine, largely unmodified, modified, and extensively modified, using criteria including catchment or watershed land cover, land use, catchment hydrology, estuary use, and ecology. The second stage, assessing the extent of change for modified estuaries, proved difficult, mainly because of limited availability and inconsistency of data. A more detailed, second-generation assessment will require the use of a suite of environmental indicators. An additional motivation for establishing a scheme to assess estuarine condition has come from the development of Catchment Action Plans (CAPs), which have been mandated in Australia through a State/Federal Government Bilateral Agreement, under which targets are set for key natural resources, including estuarine/coastal/marine environments. Some indicators of ecosystem health are compromised by being spatially and temporally variable and by being influenced by natural stress (Birch et al., 2001) . Such confounding makes it difficult to identify and quantify the human-induced component of change (Hogg and Norris, 1991) . Natural stress during droughts, storms, and floods may expose or erode marine substratum or smother benthic floral and faunal communities. Although seagrass distribution is a common and valuable indicator of ecosystem health (Dennison, 1999; Dennison and Abal, 1999) , large (natural) run-off events may result in widespread decrease in seagrass distribution in some regions (Dennison and Abal, 1999) . Considerable increase in the area of mangrove stands in some east coast estuaries comes at the expense of saltmarsh coverage. Turbidity, another commonly used indicator, varies temporally by a factor of .100 in response to changes in rainfall, wind, tide, and temperature (Schoellhamer, 1996; Taylor, 2000) . Variation in turbidity affects other ecosystem indicators associated with suspended particulate matter in the water column, such as nutrients, contaminants, and dissolved oxygen. Thus, indicator variance may be the result of natural processes, making it difficult to determine the “non-disturbed” (pristine) state under variable ambient conditions. Assessment of estuarine condition requires baseline information from undisturbed areas or historical-trend data to detect anthropogenic influence and to determine the magnitude of change. However, on high-population seaboards, the entire environment being assessed is altered, and commonly pristine control sites are unavailable and historical contaminant information is limited (Birch et al., 1999; Maher et al., 1999) . For the second phase audit of Australian estuaries, a detailed scheme incorporating a full range of chemical, biological, and ecotoxicological analyses, as undertaken in the Environmental Monitoring and Assessment Programme (EMAP) and the National Status and Trends Programme (NS&T) in the USA (Hyland et al., 1999, 2000) , will not be financially feasible. Instead, a limited set of key indicators will have to be chosen. The list of potential indicators of benthic condition compiled by the Benthic Indicator Group discriminated non-disturbed from heavily disturbed environments (Magni, 2003; Magni et al., 2004) . The list included biological- (community composition, structure, biomass, and functional species) and sedimentassociated abiotic factors (salinity, pore-water chemistry, sediment organic matter, and contaminants). Sediment quality guidelines (SQGs) for assessing individual chemicals as well as mixtures of contaminants (Hyland et al., 2000) were also listed. Our objective is to demonstrate that heavy metals in sediments provide an inexpensive approach to measuring human-induced change and act as an indicator of contaminant-related biological stress. Use of the scheme is demonstrated using Brisbane Water, an estuary 30 km north of Sydney, as a case study, and the ability of the approach to differentiate estuaries at various stages of degradation is illustrated using seven estuaries on the Australian east coast (Figure 1). These assessments are compared against estuarine health as determined by the National Audit. The coastal monitoring and assessment programme General approach The objective of the coastal monitoring and assessment programme at Sydney University is to provide a cost-effective, integrated, and regionally consistent assessment of estuarine health. Further, the programme aims to provide baseline data, against which future temporal trends can be assessed and against which success of management strategies can be judged. Currently, 34 of the 130 estuaries in New South Wales (NSW) are being investigated as part of a coastal monitoring and assessment programme. Sediments are used as indicators of estuarine health to determine the magnitude and spatial extent of human-induced change and to assess sediment quality, i.e. the ability of sediment to sustain a healthy biological community. The seven estuaries used to demonstrate the approach are Durras Lake, Burril Lake, Myall Lake, Saint Georges Basin, Pittwater, Brisbane Water, and Port Jackson (Figure 1). The procedure for collection and analysis of surficial sediment samples has been described in detail by Birch and Taylor (1999, 2004). Preferably, unconsolidated sediment should be characterized chemically using a wide range of analytes, including heavy metals as well as the whole range of organic contaminants, as was carried out in the USA by EMAP and NS&T. A similar investigation was made in Port Jackson (Birch and Taylor, 1999, 2000; McCready et al., 2006a, b) . However, a lack of resources prohibited its incorporation in the current regional monitoring programme; it is expected that scarce resources will have the same effect on any future, large-scale national assessment programme. A less expensive approach is required to estimate the risk of adverse biological effects caused by sedimentary contaminants. A suite of nine elements that are ubiquitous in estuarine environments and are easily and inexpensively analysed (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) was selected to determine possible biological stress resulting from contamination. To investigate the extent to which heavy metals reflect the distribution of other priority contaminants of concern [organochloride pesticides (OCs), polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs)] in estuarine sediments, a regression analysis was made of multi-chemical data available from studies in Australia and the US (Long and Sloane, 2005; McCready et al., 2006b, c) . Because an initial investigation of the data for four estuaries revealed that three metals (Cu, Pb, and Zn) closely correlated with the full suite of nine metals (Port Jackson: r2 future ¼ 0.92; Hawkesbury River: r2 ¼ 0.87; New York: r2 ¼ 0.71; Tampa Bay: r2 ¼ 0.68), only these metals were used in the assessment, to simplify the process further. The correlation between the three (Cu, Pb, and Zn) metals and other analytes, including OCs, PCBs, and PAHs, from 103 sites in Port Jackson and nearby estuaries (McCready et al., 2006b, c) was significant (r2 ¼ 0.63, p , 0.05). The correlation between the same three metals and a suite of nine OCs and hexachlorobenzene was also significant (r2 ¼ 0.75, p , 0.05) in published data from the Hawkesbury River (Birch et al., 1999) . The same was true for the three metals and PCBs in data from New York (r2 ¼ 0.77, p , 0.05), but less so (r2 ¼ 0.43) in data from San Diego sediments (Long et al., 1995b; Wolfe et al., 1996) . Contaminants in estuarine sediments will not always co-vary spatially, but are more likely to do so in areas dominated by stormwater discharge, because the chemical mix of urban stormwater appears reasonably consistent in both US (NURP, 1983; US EPA, 1983) and Australian studies (Fletcher et al., 2004) . This welldocumented relationship is also the basis of urban stormwater run-off models (Fletcher et al., 2004) . However, in areas receiving elevated, chemical-specific industrial discharge, contaminants are less likely to co-vary spatially. Determining the extent of human-induced change We determined the impact of human influence on the estuarine environment using grain-size-normalized (,62.5 mm) sedimentary heavy-metal data obtained from piston and push cores taken in undisturbed areas of deposition (Forstner and Wittmann, 1979; Birch, 2003) . Cores were subsampled at 2-cm intervals to 10-cm depth, then over 2 cm every 10 cm to the bottom of the core. The magnitude and spatial extent of human-induced change was determined by expressing current metal concentrations as enrichment over pre-anthropogenic or background levels observed at greater depths in the sediment (Figure 2). Typically, the preanthropogenic, or pristine, condition for the environment being assessed is expressed as consistently low metal concentrations towards the bottom of the core (Carballeira et al., 2000) . This section of the metal profile has been demonstrated, using dated cores, to be pre-European in 12 cores from Sydney Harbour (Birch, 2007) , and historical trends of trace metal accumulation have demonstrated this section of the core to be pre-anthropogenic in other estuaries (Zwolsman et al., 1993; Deely and Fergusson, 1994) . A continuous historical record of humaninduced change, and therefore the date of onset of contamination, may be obtained from core material using 210Pb and 137Cs isotopic data (Taylor et al., 2004; Birch, 2007) . Core data should be interpreted with caution because subsurface sediments may be affected by bioturbation (Luoma and Phillips, 1988; Geyh and Schleicher, 1990) and post-depositional mobilization (Ridgway and Price, 1987; Benoit and Hemond, 1991) . The depth of bioturbation averages 20 cm in Port Jackson (Taylor et al., 2004) , and oxic/ sub-oxic chemical conditions, leading to mobilization in reducing organic-rich sediment and preferential sorption by particle-reactive chemical species (Koide et al., 1973; Mayer, 1994) , is restricted to the upper few centimetres in this area (Simpson et al., 2002). An enrichment factor (EF ¼ concentration in top layer/background concentration) of .1.5 was considered indicative of human influence and (arbitrarily) an EF of 1.5 – 3, 3 – 5, 5 – 10, and .10 was considered evidence of minor, moderate, severe, and very severe modification, respectively. A mean enrichment quotient (MEQ) for the three metals was used to estimate the magnitude of human-induced change in each estuary by summing EFs for Cu, Pb, and Zn and dividing by three. The spatial extent of heavy-metal distributions was determined by ordinary kriging interpolation, using the geostatistical analyst tool in ArcGIS. Assessing possible biological stress The activity, diversity, and functionality of a biological community may be determined by measuring its structure and abundance. However, these measurements are time-consuming and expensive, and the interpretation of the results can be problematic if a pristine control site is lacking. The relationship between the chemical composition of sediment and adverse biological effect is now well established in many parts of the world, including the US, Canada, Australia, the Netherlands, and Hong Kong (Long and MacDonald, 1998; Birch and Taylor, 2002a, b) . The SQGs adopted by Australia and New Zealand (ANZECC/ ARMCANZ, 2000) are based largely on a scheme developed in North America (Long and Morgan, 1990; Long et al., 1995a; Long and MacDonald, 1998) . The US scheme provides two values for each particular chemical: effects range low (ERL) and effects range median (ERM), which delineate three concentration ranges. Concentrations below ERL values (65, 50, and 200 mg g21 for Cu, Pb, and Zn, respectively) identify conditions where adverse biological effects would be observed rarely; concentrations equal to or greater than ERL but below ERM (270, 220, and 410 mg g21, respectively) represent a range within which biological effects occur occasionally; concentrations at or above ERM values represent a range above which adverse biological effects are frequent. The ANZECC scheme provides interim sediment quality guidelines-low (ISQG-L) and -high (ISQG-H) values, which are broadly equivalent to the ERL and ERM values, respectively, and are exactly the same for Cu, Pb, and Zn (ANZECC/ARMCANZ, 2000; Simpson et al., 2005) . Contaminants rarely occur in sediment as single chemicals. To assess the adverse effects of mixtures of chemicals, mean ERM quotients (MERMQs) have been developed by normalizing the concentration of each substance for its ERM value, summing the quotients for each substance, and dividing the sum by the number of chemicals used (Long et al., 2000, 2006; Ingersoll et al., 2005) . The MERMQ was derived from field-collected sediment data for mixtures of metallic and organic toxicants, which act together to cause adverse biological effects that were measured, either in the benthos or in laboratory animals. When potentially toxic chemicals are found in sediments alone, concentrations that induce toxicity may differ from those that are part of a increased to values .6 towards the source of contamination in contaminant mixture (Berry et al., 2004; Becker et al., 2006) . The the industrialized north of the estuary, and was intermediate use of MERMQs for only three metals, therefore, will not predict (3 , MEQ , 6) in the west, next to a sewage treatment plant adverse effect accurately. However, increasing MERMQs indicate (Figure 3a). Surficial sediment was unlikely to have had an increasing risk of detrimental biological effects posed by sediment. adverse effect on benthic animals over most of the waterway, Brisbane Water estuary: a case study Brisbane Water is a shallow (6 – 8 m), wave-dominated barrier 2 estuary (Figure 1). Catchment (168 km ) land use comprises because individual metal concentrations were ,ISQG-L, and MERMQ for combined metals was ,0.5 (Figure 3b). Comparison of seven NSW estuaries mainly residential (27%), agricultural (33%), and parkland The estuaries selected for the regional comparison covered the full (35%), with commercial and industrial centres in the northwest. range of four estuarine conditions established by NLWRA (2002) : Pre-anthropogenic or background metal (Cu, Pb, and Zn) connear-pristine (Durras Lake); largely unmodified (Burril Lake, centrations were established for estuarine sediments from five cores Myall Lake); modified (Saint Georges Basin, Pittwater); and extenthat penetrated the full post-glacial section (Table 1). The MEQ in sively modified (Brisbane Water and Port Jackson). Sediment surficial samples (n ¼ 83) over most of the estuary was ,3 but in Port Jackson contained the highest mean concentrations of Cu, Pb, and Zn in surficial sediment for seven selected New South Wales estuaries. Downloaded from https://academic.oup.com/icesjms/article-abstract/65/8/1407/714053 Estuary Durras Lake Burril Lake Myall Lakes St Georges Basin Pittwater Brisbane Water Port Jackson Normalized n Cu Total n Pb Zn Cu Pb Zn (total as well as normalized) for the three metals, whereas the mean concentrations were lowest in Myall Lake (Table 1). Background concentrations of heavy metals in sediments depend on the geology of the catchment area and the local physiochemical conditions, and may vary considerably (Olmos and Birch, 2008) . Therefore, the background Cu concentrations vary from 75 mg g21 in Burril Lake, attributable to Cu-rich porphyry rocks in the catchment (Gillis and Birch, 2006) , to 3 mg g21 in Myall Lake, which is mantled in organic-rich sediments. Port Jackson had the highest MEQ, followed by Pittwater, although the values for the other five estuaries were considerably lower (Table 2). Ranking based on MEQ was: Durras and Myall Lakes , Burril Lake , St Georges Basin , Brisbane Water , Pittwater , Port Jackson. The ISQG-L value for total sediment was exceeded for Cu in Burril Lake and Pittwater, for Pb in Brisbane Water and Pittwater, and for Zn in Brisbane Water. The only area to exceed ISQG-H values was in Port Jackson for all three metals (Table 1). The recently completed National Land and Water Resources Audit (NLWRA, 2002) of Australia’s 970 estuaries made extensive use of two important criteria, i.e. catchment land cover and catchment land use. Port Jackson has the largest proportion of residential, commercial, and industrial land use, followed by Pittwater, whereas Durras and Myall lakes have almost undeveloped catchments (Table 2). Land use was correlated with the magnitude of human-induced change and the risk of adverse biological effects attributable to chemical contamination to assess the extent to which these parameters are related, using Pearson correlation coefficient analysis. A strong positive correlation between the three factors was found, particularly between land use and MEQ (0.9), and also between MERMQ and MEQ (0.98). The impact of a highly urbanized catchment on the adjacent receiving basin was substantial. Sediment in estuaries with more than 85% of the land use dedicated to parkland, agriculture, and educational facilities (St Georges Basin, Myall, Burril, and Durras lakes) did not exceed sediment quality guidelines (Birch and Taylor, 1999, 2004) . Sediment in Pittwater and Brisbane Water estuaries, where 45 and 29%, respectively, of the land use is dedicated to residential, commercial, and industrial activities, exceeded ISQG-L for total sediment, whereas Port Jackson (74%) was the most affected of all estuaries explored, with heavymetal enrichment of .50 times background in some areas. The parameters considered, i.e. land use, MEQ, and MERMQs, for the seven estuaries related broadly to the NLWRA assessment of estuarine condition, except for Brisbane Water, which appears to be less affected than Pittwater estuary, based on heavy-metal concentrations, and Myall Lake, which appears to be near-pristine. NLWRA (2002) recognized that, owing to lack of data, the Audit was unable to define benchmarks to establish the extent of change for modified estuaries. Our results suggest that the use of sediment MERMQs and MEQs, based on three heavy-metal concentrations (Cu, Pb, and Zn) and catchment land use, would be valid indicators of ecosystem health and should be considered in future assessment of estuarine health. These indicators provide additional lines-of-evidence in assessments of estuary condition relative to pristine conditions and provide added value to allow a greater differentiation of estuarine ecosystem health (Birch and Davies, 2003; Davies and Birch, 2003) . Conclusions Sedimentary heavy metals provide an inexpensive approach to measuring human-induced change and act as an indicator of contaminant-related biological stress. The data required for this type of assessment is acquired relatively easily and inexpensively, and provides the contaminant framework on which more detailed and focused multidisciplinary investigations can be based for large regional or national estuarine monitoring and trend programmes. 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Birch, Gavin F., Olmos, Marco A.. Sediment-bound heavy metals as indicators of human influence and biological risk in coastal water bodies, ICES Journal of Marine Science, 2008, 1407-1413, DOI: 10.1093/icesjms/fsn139