Quantifying the sources of pollutants in the Great Barrier Reef catchments and the relative risk to reef ecosystems

Marine Pollution Bulletin 65 (2012) 394–406

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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Quantifying the sources of pollutants in the Great Barrier Reef catchments and the relative risk to reef ecosystems J. Waterhouse ⇑, J. Brodie, S. Lewis, A. Mitchell Catchment to Reef Research Group, Australian Centre for Tropical Freshwater Research, ATSIP (Building 145), James Cook University, Townsville, Queensland 4811, Australia

a r t i c l e Keywords: Great Barrier Reef Pollutant sources Sediments Nutrients Pesticides Risk assessment

i n f o

a b s t r a c t Development of the Great Barrier Reef (GBR) catchments in the last 150 years has increased the loads of suspended sediment, nutrients and pesticides (‘pollutants’) delivered to the GBR. The scale and type of development, the pollutants generated and the ecosystems offshore vary regionally. We analysed the relative risk of pollutants from agricultural land uses and identified the sources of these pollutants from different land uses for each region to develop priorities for management. The assessment showed the Wet Tropics and Mackay Whitsunday regions to be of relatively high risk dominated by sugarcane cultivation, contributing pesticide and dissolved inorganic nitrogen (DIN). The Burdekin and Fitzroy ranked medium–high risk dominated by grazing suspended sediment inputs for both, and additionally sugarcane DIN and pesticide inputs for the Burdekin. The Burnett Mary ranked medium risk, dominated by grazing and sugarcane. Cape York was not formally ranked but is considered to be low risk. Ó 2011 Elsevier Ltd. All rights reserved.

1. Introduction Many tropical marine ecosystems around the world are exposed to increasing pressures from land runoff, fishing pressure, resource extraction, increasing temperatures and ocean acidification (Burke et al., 2011) and many show signs of degradation (Halpern et al., 2008; Lotze et al., 2006). Managers of coastal marine ecosystems are faced with the challenge of balancing environmental outcomes with social and economic needs of local and regional communities. These challenges are being addressed in many countries through planning exercises which adopt a system wide approach, incorporating best available knowledge and stakeholder engagement to define suitable targets and objectives for management and attempt to integrate catchment land use planning with coastal planning (e.g. Pressey and Bottrill, 2009). Global examples of frameworks to address land-sea analysis and management include the Land Ocean Interactions in the Coastal Zone (LOICZ) program (LOICZ, 2011) and the EU Water Framework Directive (EU, 2011) while specific examples of direct action management which has slowly restored coastal ecosystems includes Chesapeake Bay in the USA (e.g. Dauer et al., 2000). Internationally there is a clear consensus that land sourced pollution, primarily from agricultural, urban and industrial sources, is ⇑ Corresponding author. Address: P.O. Box 290, Belgian Gardens, Queensland 4810, Australia. Tel.: +61 409053367. E-mail addresses: [email protected] (J. Waterhouse), jon.brodie@jcu. edu.au (J. Brodie), [email protected] (S. Lewis), [email protected] (A. Mitchell). 0025-326X/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.marpolbul.2011.09.031

having a profound effect in coastal and marine ecosystems (Doney, 2010; Lotze et al., 2006). Similarly in coral reef ecosystems, landsourced pollution especially from agriculture, is seen as one of the major stressors degrading ecosystems along with fishing and climate change stressors (Hughes et al., 2010; Pandolfi et al., 2003). The iconic Great Barrier Reef (GBR) in Australia also faces increasing pressure from human activities and has considerable ecological (70 bioregions), cultural, social and economic values. It was declared a Marine Park in 1975 and is managed as a zoned, multi-use area with over 30% protected in high conservation, no take zones incorporated into a park-wide zoning plan (Day et al., 2004). The catchment area adjacent to the GBR also has considerable values but has received much less protection. Coral cover on the GBR has declined markedly from estimates of near 50% GBR wide in the 1960s to near 20% currently (Hughes et al., 2011; Sweatman et al., 2011; Sweatman and Syms, 2011) although the rate of decline appears to have decreased in recent years (Osborne et al., 2011). The decline is generally agreed to be attributable to three main stressors – water quality impacts including outbreaks of the coral-eating crown of thorns starfish (Fabricius et al., 2010), fishing and climate change impacts (Hughes et al., 2011). Declining water quality is recognized as one of the greatest threats to the long term health of the GBR, and it is now agreed that management of this issue can aid in building ecosystem resilience to other pressures such as those associated with a changing climate (McCook et al., 2007; Wooldridge and Done, 2009; Hughes et al., 2010). The GBR receives fresh water inputs from the diverse river catchments along the adjacent Queensland coast that vary in size, land use, biophysical and socio-economic characteristics

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(Fig. 1). There is well-documented evidence of the adverse impacts of anthropogenic pollutants on the health of aquatic ecosystems

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both within the catchment and in the GBR (for example, see Brodie et al., 2008) and the relationship between land use, catchment

Fig. 1. The Great Barrier Reef catchments, primary land use and Regional Natural Resource Management regions.

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management, declining water quality and GBR ecosystem health (Brodie et al., 2007, 2010, 2012; De’ath and Fabricius, 2010; Fabricius, 2005, 2011a,b; Lewis et al., 2009). The primary pollutants of concern to the GBR are suspended sediments (with more concern on the finer, mud-sized fraction (<63 lm) which may potentially be influencing the long-term turbidity of coastal and inshore areas), nutrients (particularly dissolved inorganic nitrogen and phosphorus and particulate nitrogen and phosphorus) and pesticides (particularly the Photosystem II Inhibiting herbicides (PS-II herbicides) diuron, hexazinone, atrazine, ametryn and tebuthiuron). A pollutant is defined here as a concentration/load of material that is elevated above natural levels that are known to cause environmental harm. Each of the pollutants has different sources, pathways and impacts on GBR ecosystems. The results of regional water quality monitoring programs established to measure pollutant concentrations from different land uses have been used to identify the sources and pathways of priority pollutants in each Region, and in some cases, each catchment (e.g. Bainbridge et al., 2006a,b, 2007a, 2008, 2009a,b; Mitchell et al., 2005, 2009; Packett et al., 2009; Rohde et al., 2008). A variety of evidence clearly indicates that export of these pollutants has increased substantially with catchment development, although the magnitude of the increases compared with natural conditions is not precisely known (Brodie et al., 2008). Most recent estimates indicate that sediment loads have increased approximately five times, total nitrogen loads increased approximately 6 times and total phosphorus loads increased approximately 9 times (Kroon et al., 2012). Cattle grazing, sugarcane production and horticulture are the predominant land uses in the GBR catchments. Each of these primary industries adopts management practices that vary within and between different regions, depending on many factors. Export of pollutants in each catchment consequently occurs to varying extents, predominantly during the wet season, depending on the management practices adopted. Management of these water quality issues in the GBR has posed many challenges to managers and the issues are similar to those experienced in other coral reef systems, for example, in the USA (Florida) (Pandolfi et al., 2005) and in many small island states (Wilkinson and Brodie, 2011). To date, management approaches in the GBR have focused on geographic locations, system components (i.e. catchments, coastal ecosystems and reefs), particular species management or particular users (e.g. tourism, fishing). This is partly due to the institutional complexities of the jurisdiction of the landscape, although limitations of knowledge of the cause and effect relationship between catchment management and GBR ecosystem health has made a system-wide approach difficult to implement. However, considerable progress has been made in the last 10–15 years to address the issue of declining water quality in the GBR. The first actions in early 2000’s were related to definition and agreement of the issues through collation of existing scientific evidence. This lead to agreement between the Australian and Queensland Governments that action was required to address water quality issues in the GBR and its catchments, and the preparation of the Reef Water Quality Protection Plan (Reef Plan) in 2003 (Queensland Department of the Premier and Cabinet, 2003). The goal of the Reef Plan is to halt and reverse the decline of water quality entering the Reef within 10 years (i.e. 2013). While the actions in the Plan were progressed to some extent in the first 5 years, it was not until 2008 when the Australian Government announced a major incentives program – Reef Rescue – to improve agricultural management practices, that large scale changes in catchment management were implemented. Reef Plan was also updated in 2009 (Queensland Department of the Premier and Cabinet, 2009) to include more specific targets and an additional overarching goal related to the long term health of the GBR (until

this point ecological outcomes for the GBR had not been defined). The Queensland Government also introduced regulations to target sugarcane and grazing activities in priority areas to reduce the amount of sediment, nutrients and pesticides discharged to the GBR (Great Barrier Reef Protection Amendment Act, 2009). Implementation of these policy frameworks has been supported by the definition of water quality targets and guidelines at regional and GBR wide scales (Brodie et al., 2011, 2012). These targets are related to uptake of agricultural management practices, catchment condition, and end of catchment pollutant loads. Marine ecosystem targets have not been defined specifically but Water Quality Guidelines for the GBR have been developed (GBRMPA, 2009). The capacity to relate compliance with these Guidelines to specific end of catchment pollutant loads and in turn, quantified improvement in management practices in terms in water quality outcomes, is yet to be achieved although several ‘exploratory’ studies have been carried out (Brodie et al., 2009c; Wooldridge et al., 2006). However, monitoring and evaluation activities have been established through the Reef Plan Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (see Carroll et al., 2012) to assess the outcomes of improvements in management practice and ultimately, GBR ecosystem health. In the context of achievement of these targets, and given the large geographic scale of the GBR catchments (total area 424,000 km2), managers need to prioritise catchment management actions to maximise the return on their investment. They need to identify which pollutants are of greatest concern, understand the sources of different pollutants in the catchments and define the areas of high pollutant generation. Previously the prioritisation of management response between different pollutants, different land uses/industries and different regions has used methods such as Multiple Criteria Analyses but with limited input data (Cotsell et al., 2009; Greiner et al., 2005). While these have proved useful for the initial prioritisation under Reef Rescue and selection of priority catchments under the Reef Plan, more sophisticated analyses with better input data are needed to confidently prioritise between pollutants. The current study aimed to address this deficiency by using more and better input data and assessing the reliability of these data. This paper presents an analysis of the relative risk of pollutants generated from agricultural land uses in the catchment to the GBR and identifies the sources of these pollutants from different land uses for each region to develop priorities for management. This research was carried out to inform investment and management response in the GBR catchment. The outcomes of our research informed the selection of priority areas and priority land uses for the Great Barrier Reef Protection Amendment Act, 2009.

2. Relative risk assessment of the impacts of pollutants on the GBR 2.1. Study area The GBR extends over 2000 km along the coast of Queensland, Australia (Fig. 1). The adjacent catchment, herein referred to as the GBR catchment, consists of 35 main river catchments that discharge into the GBR, largely in the wet summer months (December to March). These catchments are also grouped by six Natural Resource Management (NRM) regions: Cape York, Wet Tropics, Burdekin, Mackay Whitsunday, Fitzroy and the Burnett Mary (Fig. 1). The Cape York region remains mostly undeveloped and is considered to have the least impact on GBR ecosystems from existing land based activities. In contrast, the Wet Tropics, Burdekin, Mackay Whitsunday, Fitzroy and the Burnett Mary regions are characterised by agricultural land uses including sugarcane,

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grazing, bananas and other horticulture, other cropping such as grains and cotton, mining and urban development. The patterns of land use in the GBR catchment result in large differences in the pollutants of concern between the wet and dry catchments. Due to the wetter climates and prevalence of intensive agricultural cropping land uses (sugarcane and horticulture) and their associated fertiliser and pesticide usage, the Wet Tropics and Mackay Whitsunday areas have been identified as regions of high dissolved nutrient and pesticide runoff (Devantier et al., 2006; Fabricius et al., 2005; Furnas, 2003). The significantly larger Fitzroy and Burdekin River catchments (each 135,000 km2) on the other hand, dominated by unimproved savannah/woodland rangeland grazing, are identified as considerable contributors of particulate nutrients and suspended sediment to the GBR lagoon (Bainbridge et al., 2006a,b, 2007a,b; Furnas, 2003; Mitchell and Furnas, 2001; O’Reagain et al., 2005; Packett, 2007; Packett et al., 2009; Waters and Packett, 2007). The Burnett Mary region supports a mix of cropping and grazing land uses and therefore has issues associated with nutrients, sediments and pesticides (Brodie et al., 2003; Fentie et al., 2006). 2.2. Methods This part of the study was undertaken to assist the Queensland Government in identification of the relative risk of pollutant loadings from broad-scale agriculture in the GBR catchments to GBR health. It was based on a desk top assessment of a range of information sources related to pollutant loads, the current condition of the GBR and the estimated delivery of pollutants within the GBR. A detailed technical report is available for the assessment (Brodie and Waterhouse, 2009). To identify the relative risk of pollutant loadings from broadscale agriculture in the GBR catchments to GBR health, we calculated a relative risk score for each NRM region based on 3 primary factors: Anthropogenic load, reef condition and reef exposure. These factors were combined and are explained below.

(affecting the energy and nutrient transfer between zooxanthellae and host; Marubini and Davies, 1996), and potentially higher rates of coral diseases (Bruno et al., 2003). More frequent outbreaks of crown-of-thorns starfish (COTS) are also linked to high nutrient levels which sustain higher levels of large phytoplankton and allow increased survival of COTS larvae (Brodie et al., 2005; Fabricius et al., 2010). COTS larval development increases by 8-fold with every doubling of chlorophyll a concentrations (Fabricius et al., 2010). The load of terrestrially-sourced DIN has also been quantitatively linked to the upper thermal bleaching thresholds of symbiotic reef corals on inshore reefs on the GBR (Wooldridge, 2009). PS-II herbicides are a priority contaminant because they are residual herbicides, relatively soluble and mobile and hence have a higher propensity to reach the marine environment at detectable concentrations. They have relatively long half lives (>30 days) and are widely used in agricultural practices throughout the GBR catchment. Concentrations in waterways are highest in areas of intensive agricultural activity including sugarcane and grains but also from grazing lands (tebuthiuron) (Bainbridge et al., 2009a; Davis et al., 2008; Lewis et al., 2009; Packett et al., 2009). Low-level, chronic exposure to herbicides may exert subtle selective pressure on lower trophic levels due to their mode of action and speciesspecific differences in sensitivity, with potentially negative consequences for the resilience of the reef ecosystem (Negri et al., 2005). While the PS-II herbicides are capable of affecting marine plants directly, they may also impact upon animals such as corals by inhibiting photosynthesis in symbiotic microalgae (Jones and Kerswell, 2003; Jones, 2005). Laboratory work has also shown impacts of pesticides on reef ecosystems from a cellular to system change within coral (e.g. Jones, 2005), seagrass (e.g. Haynes et al., 2000) and algal communities (e.g. Magnusson, 2009), and increased impacts associated with rising sea surface temperature (Negri et al., 2011). Other parameters were not included in the assessment for the following reasons: d

Relative Risk = Anthropogenic Load Score (sum of scores for suspended sediments, DIN, PS-II herbicide Anthropogenic Loads) (Source: Brodie et al., 2009a) + Reef Condition Score (sum of scores for Coastal and Inner Shelf Macroalgal cover, Coastal and Inner Shelf Hard Coral Richness, Coastal and Inner Shelf Secchi Depth, Coastal and Inner Shelf Chlorophyll) (Source: De’ath and Fabricius, 2008) + Reef Exposure Score (sum of scores for suspended sediments exposure, DIN exposure, PS-II herbicide exposure) (Source: Maughan et al., 2008)

d

d

d

2.2.1. Priority pollutants The pollutants considered in the assessment were suspended sediment, dissolved inorganic nitrogen and PS-II herbicides. Suspended sediment is sourced from erosion, particularly in grazing lands and increased loads can have detrimental impacts on marine ecosystems, primarily through reduced light availability (e.g. Anthony and Hoegh-Guldberg, 2003; Fabricius, 2011b; Schaffelke et al., 2005). Dissolved inorganic nitrogen (DIN) is largely sourced from fertiliser products and is readily bioavailable in the marine environment. The main way in which dissolved inorganic nutrients affect corals appears to be by enriching organic matter in the plankton and in sediments (Fabricius, 2011b) which can lead to declining calcification, higher concentrations of photo-pigments

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Particulate phosphorus and particulate nitrogen are associated with suspended sediment and therefore was not considered individually in this assessment largely because the management options are the same. Primary production in the GBR system is generally considered to be nitrogen limited (Furnas et al., 2005) and hence phosphorus is often regarded as a lower priority pollutant. However, our understanding of the relative importance of nitrogen and phosphorus in the GBR is highly uncertain and further studies on this issue are needed (Brodie et al., 2012). Dissolved inorganic phosphorus (DIP) may be significant in some regions, however in our study it was not considered high priority to include in the analysis. Current nutrient management options will address phosphorus runoff/losses in combination with nitrogen. Dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP) are not particularly relevant given the management options that are currently available and are currently considered to have limited but variable bioavailability in marine ecosystems (e.g. Seitzinger et al., 2002).

2.2.2. Method for estimating Anthropogenic Load Many studies have attempted to determine pollutant load estimates for all of the GBR catchments (e.g. Belperio, 1983; Cogle et al., 2006; Furnas, 2003; Moss et al., 1992; Neil and Yu, 1996; Neil et al., 2002; NLWRA, 2001). Techniques for estimating pollutant loads are continually improving for the GBR catchments, with the most recent estimates presented in Kroon et al. (2012). Attempts to quantify uncertainty in the load estimates are also being progressed (e.g. Herr and Kuhnert, 2007; Kuhnert et al., 2010).

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The pollutant loads used in this study were based on a compilation of previous data and selection of the ‘best estimates’. To do this, we collated load data derived from various modeling activities and/or monitoring data for the 35 major river basins discharging to the GBR for the following parameters: suspended sediment, DIN, DON, particulate nitrogen, DIP (filterable reactive phosphorus), DOP and PS-II herbicides. Pre-European estimates for sediment and nutrient loads were also collated as a basis for comparison and were based on those presented in Brodie et al. (2003) and Furnas (2003). A set of criteria based on the availability of monitoring data and currency of modeling efforts were then applied to define the ‘best estimate’ of pollutant loads for each catchment. Justification for each estimate was documented, and our confidence in the estimates was represented by a qualitative rating between 1 (low confidence) and 5 (high confidence). Land use contributions of sediment and nutrient loads for each catchment were determined by applying the proportional allocations presented in Brodie et al. (2003) to the ‘best estimates’. Further detail of the method and the results is described in Brodie et al. (2009a). The earliest study to model herbicide loads to the GBR used limited monitoring data to develop a single PS-II herbicide pollutant export rate coefficient for all agricultural lands within the GBR catchment area (Maughan et al., 2008). Since this preliminary study, additional monitoring data became available (e.g. Lewis et al., 2009; Packett et al., 2009) to develop pollutant export rate coefficients for key individual land uses such as sugarcane, grazing and dryland cereal crops. This study established pollutant export rate coefficients for key land uses (kg of herbicide runoff per hectare of land use) for the six key herbicides designed to inhibit photosystem II in plants which are commonly detected in the GBR lagoon – diuron, atrazine, hexazinone, ametryn, simazine and tebuthiuron. These coefficients were developed based on the loads calculated for the Haughton River, Barratta Creek, Pioneer River, Sandy Creek, O’Connell River and Fitzroy River and published in Lewis et al. (2009) and Packett et al. (2009). The event mean concentrations (EMC) were calculated (Eq. (1)) from these loads and an average EMC for each stream was calculated where multiple years were monitored.

EMCðmg L1 Þ ¼

LðgÞ QðMLÞ

ð2Þ

where  xAL is mean annual load in grams, the xQ represents the mean annual flow for the Basin as specified in Brodie et al. (2003). The upstream land use (in Ha using QLUMP, 1999) for the sampled point of each stream was then established and major land uses included forest, grazing, sugarcane, other crops (horticulture, cereals, etc.) as well as land uses including urban and mining. The average herbicide pollutant export rate in kg per hectare was calculated for sugarcane lands (Eq. (3)) assuming that all loads of diuron, atrazine, hexazinone and ametryn from the Haughton River, Barratta Creek, Pioneer River, Sandy Creek and O’Connell River are sourced to the sugarcane industry.

PCxs ¼

xALðkgÞ As ðHaÞ

xALPS-IIs ¼ PCxs  As

ð4Þ

where the mean annual load of PS-II herbicides from sugarcane (xALPS-IIs) is equal to the pollutant export rate coefficient for sugar multiplied by the total area of sugar in the basin (As). Similarly, pollutant export rate coefficients for atrazine, diuron and simazine in crop lands were generated using the load data from the Fitzroy River and assuming that these herbicides in this river are only sourced to crop lands. This coefficient was then applied to the ‘other crops’ land use to estimate atrazine, diuron and simazine loads. Since tebuthiuron is only sourced to the grazing industry, a pollutant export rate coefficient for tebuthiuron in grazing lands was also developed using the mean kg per ha load data from the Fitzroy River, Haughton River and O’Connell River (as for Eq. (3)). As there were considerable differences in the individual kg per ha calculations between the Fitzroy River and the Haughton and O’Connell Rivers, the kg per ha calculation for the Fitzroy River was used exclusively for dryland grazing lands (including the Burdekin River and Fitzroy River). The tebuthiuron grazing coefficient was only applied for the catchments where it had been detected in either grab or passive samples. A flaw in this model is that several land uses which are now known to leak PS-II herbicides, particularly forestry for simazine, crops other than sugarcane (e.g. bananas) and urban centres, are not included in the analysis. A more robust model that incorporates additional monitoring data, develops regional pollutant export rate coefficients for individual land uses and calculates uncertainties in loads is being developed by Lewis and others to overcome some of these deficiencies (Lewis et al., in review).

ð1Þ

where EMC is the event mean concentration, L is the total load in grams and Q is the discharge in ML. The ‘mean annual load’ was then calculated (Eq. (2)) using the ‘average discharge’ from each of the monitored streams determined by a SedNet model run (Brodie et al., 2003).

xAL ¼ EMCðmg L1 Þ  xQ ðMLÞ

This assumption is reasonable given that sugarcane is the predominant industry within these regions and these herbicides are widely used in sugarcane, and studies have shown a direct relationship between sugarcane area and the concentration of these herbicides in streams (e.g. Bainbridge et al., 2009a; Lewis et al., 2009). The mean of the pollutant export rate coefficients for each stream was then taken to produce an average coefficient for sugarcane lands for the GBR catchment area. This coefficient was then used to estimate the loads of these herbicides from all sugarcane lands within the GBR catchment area (Eq. (4)).

ð3Þ

where PCxs is the pollutant export rate coefficient for herbicide x in sugar (s) and As represents the total area of sugar in the upstream catchment area.

2.2.3. Pollutant sources The primary sources of each pollutant (proportional land use contributions) were drawn from our estimates presented in Brodie et al. (2009a), where we calculated the land use pollutant load contributions using the Brodie et al. (2003) study to calculate proportional contributions for each parameter (using land use data from 1999 to QLUMP, 1999) and then applied that to the current ‘best estimates’. This is at best a crude estimate of the contribution of different land uses to the overall load. We also undertook a review of new information for each NRM region collated for recent regional planning processes (e.g. Dight, 2009; Drewry et al., 2008; Johnston et al., 2008; Kroon, 2008) and incorporated updated figures of land use contributions where possible. For example, in the Wet Tropics region, estimates for the proportion of DIN delivered by sugar land uses were modified to take into account more recent studies for the region undertaken by Armour et al. (2007) and Hunter and Walton (2008). Land-use groupings are an amalgam of common land use categories that follow the ALUM (1999) classification and were derived from the latest QLUMP data (2005; latest available). We used Sugarcane (dryland and irrigated), Grazing (natural vegetation grazing), Other crops (cropping except sugarcane and horticulture), Forest (natural environment) and Other (forestry plantation, animal production, urban, industrial and water areas). It is currently difficult to differentiate sources of pollutants from specific horticultural activities in each region due to limited data availability,

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however, where this information was available (e.g. bananas in Wet Tropics catchments), it was included. Therefore in most cases, the figures for horticulture represent the collection of intensive fruit and vegetable cropping activities. Urban activities were incorporated into the land use type defined as ‘Other’, but were not explicitly addressed in the study in accordance with the scope. 2.2.4. Method for estimating Reef Condition The Reef Condition data used in the analysis was derived from the report prepared by De’ath and Fabricius (2008) to support the development of the Great Barrier Reef Marine Park Authority Water Quality Guidelines (GBRMPA, 2009). Current reef condition coupled with water quality data provides an indication of the previous exposure of an ecosystem to declining water quality. It could also be considered to be a useful indicator of the resilience of a reef to future pollutant exposure. However, it is difficult to make assumptions about the likelihood of the impact of ongoing or increased pollutant exposure without considering more detailed data on a baseline or reference condition (generalised on a regional basis). While this would produce a more robust assessment of the risk of pollutant exposure to particular reef assemblages, the effort involved was considered to be beyond the scope of this study. Therefore, we used the current condition of coastal and inshore reefs and water quality reported in De’ath and Fabricius (2008), and acknowledge the limitations. It should also be noted that the Burnett Mary region (refer Fig. 1) does not include any data for Inner Shelf Macroalgal Cover or Hard Coral Richness. This is true for the marine areas within the GBR Marine Park boundary which is the scope of the assessment completed by De’ath and Fabricius (2008), but datasets for reefs south of the GBR Marine Park boundary and still relevant to the Burnett Mary catchments are available (Maria Zann, personal communication). Sourcing these datasets was not within the scope of our assessment at the time but is recommended for any future work. For the incorporation of the Reef Condition data in our assessment, the following aspects are important: 1. The method applied in Death and Fabricius (2008) was used to define the cross shelf boundaries. This approach uses relative distance across the shelf to define offshore structure to define three regions: coastal, inner shelf and offshore. The coastal zone boundary is located 5–7 km off the shore in the Cape York, Wet Tropics and Burnett Mary Regions where the shelf width is 50– 70 km, 10–15 km off the shore in the Burdekin and Mackay Whitsunday Regions (shelf width 120–150 km) and 20 km off the shore in the Fitzroy Region (shelf width 200 km). 2. The ‘Inner Shelf’ data (24–80 km off the shore) is reported for each of the parameters (in addition to ‘Coastal’ data), as the extent of influence of land runoff extends to the areas defined as ‘Inner Shelf’ in most locations. Recent access to satellite imagery indicates that the influence of river plumes also extends to offshore locations, but those ecosystems likely to be exposed to pollutants most frequently and most severely are those in the coastal and inner shelf assemblages. 3. The GBR mean is reported for each value to provide reference for categorising the Reef Condition values as low, medium or high. Further explanation of the parameters used to describe Reef Condition is provided in Supplementary information. 2.2.4.1. Macroalgal cover. Macroalgal cover, reported as % cover, can be used as an indicator of exposure of reefs to poor water quality and reduced grazing (particularly fish) pressure. Research has shown that high levels of nutrients and sediments lead to high

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macroalgal cover, low coral biodiversity and low rates of coral recruitment on inshore reefs, slowing rates of coral recovery after disturbances, and increasing frequency of outbreaks of crown-ofthorns starfish. 2.2.4.2. Hard coral richness. Coral richness is the number of coral species present in a survey area. While hard coral cover is predominantly determined by disturbance history, the species richness of hard corals appears to be a sensitive indicator of the physicochemical environmental conditions of a site. Data are based on surveys conducted on 110 reefs (599 transects) of the GBR between 1994 and 2001 (Devantier et al. 2006). The analyses presented here are based on reef averaged data. 2.2.4.3. Secchi depth. Reported as metres (m), secchi depth provides a useful indicator of suspended sediment and particulate matter in the water column which is enhanced from land based runoff. High secchi depth generally reflects a light climate suitable for benthic coral growth, whilst low secchi depth reflects turbid water and a poorer light climate. The GBRMPA Water Quality Guideline for secchi depth is defined as >10 m (GBRMPA, 2009). 2.2.4.4. Chlorophyll. Reported as micrograms per litre (lg/L), concentrations of the plant pigment ‘‘chlorophyll a’’ (which occurs in all marine phytoplankton) provide a useful proxy indicator of the amount of nutrients incorporated into phytoplankton biomass, because phytoplankton have predictable nutrient-to-chlorophyll ratios. Chlorophyll a is the most commonly used parameter for monitoring phytoplankton biomass and nutrient status, as an index of water quality (Brodie et al., 2007). The GBRMPA Water Quality Guideline for chlorophyll is defined as <0.45 lg/L (GBRMPA, 2009). 2.2.5. Method for estimating Reef Exposure An estimate of the exposure of individual reefs to various pollutants provides the basis of a vulnerability assessment of GBR condition from water quality influences. Ideally, an exposure criterion would factor parameters such as the proximity of the reef to the source of the pollutant, the likelihood and frequency of exposure of the reef to river plumes, and the amount of a pollutant within the plumes at a range of distances. The best attempt of this kind of assessment for the GBR at the time of our study was the Reef Exposure model developed by Maughan et al. (2008), which has since been improved by Devlin et al. (2012). The model provided a relatively simple way of combining pollutant load estimates, river flow and variability characteristics with plume and pollutant behaviour, and the distance of every reef to each river mouth to give an estimated reef exposure class. The classes ranged from Low to Very High for each pollutant, and the classes were defined arbitrarily. There are limitations with the model that are important for the incorporation of the results in our assessment. In particular, the River Variability Index was given a higher weighting in the model that what is now considered to be appropriate. Essentially the low variable rivers like the Wet Tropics are given a high weighting which substantially over emphasizes this index against other more variable rivers such as the Mackay Whitsunday catchments. A revised version of the model that addresses this limitation has been undertaken for the Tully region (Maughan and Brodie, 2009). However, this same adjustment needs to be made to the model for the rest of the GBR. The Reef Exposure score was based on calculation of the number of reefs in the exposure categories ‘Medium’, ‘High’ or ‘Very High’ from Maughan et al. (2008) for suspended sediments, DIN and PS-II herbicides. These values were then classified (arbitrarily, 1–5) and added to give a ‘Reef Exposure Score’.

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2.2.6. The relative risk assessment To provide an estimate of risk of pollutants from each NRM region to the GBR using the parameters described above, we completed a simple exercise to combine the parameters using an additive scoring technique. Each parameter was given a score between 1 and 5 based on data ranges and assumed relationships between the value and the degree of impact or risk (for example, high load = high risk and high macroalgal cover = high impact). The upper and lower boundaries of the classes were defined by the range of the parameter values and were then (arbitrarily) equally divided into 5 classes depending on the relationship between the parameter, and impact or risk. The range and classes for each parameter are in Table 1. The scores for the parameters in each of the three primary factors were summed, and the sum of the scores for the three factors was used to calculate the Overall Score. We categorized the scores into 5 classes of Relative Risk where 1 = Low, 2 = Medium–Low, 3 = Medium, 4 = Medium–High and 5 = High. The boundaries for the classes of the Overall Score were (arbitrarily) equally divided within the range from the minimum Overall Score to the top of the range of the Overall Score. To test the importance of each factor, we completed a simple sensitivity analysis of three factors and the parameters within them to define the overall score. A series of alternative combinations of factors, and ways of defining the factors in terms of parameters (for Reef Condition and Reef Exposure), were tested. We found that the pattern of the regional priorities is evident with many combinations of the factors, providing confidence to the final outcome. The following specific conclusions were drawn:

d

d

Exclusion of water quality parameters in the Reef Condition factor: The assessment was not particularly sensitive to changing the Reef Condition criteria to exclude the chlorophyll and secchi depth parameters. This is likely due to an internal correlation between chlorophyll and secchi depth, and Hard Coral Richness and Macroalgal Cover, i.e. Research shows that elevated chlorophyll concentrations and reduced secchi depth can lead to high macroalgal cover, low coral biodiversity and low rates of coral recruitment on inshore reefs, slowing rates of coral recovery after disturbances, and increasing frequency of outbreaks of crown-of-thorns starfish. Adjustment of the Reef Exposure factor: An internal correlation exists between Anthropogenic loads and the Reef Exposure criteria derived from Maughan et al. (2008). The Reef Exposure model incorporates current pollutant loads as a factor, thereby essentially double counting the influence of pollutant load in the assessment. However, it is not considered to be a major concern because loads are considered to be a critical factor in our assessment. This was tested by using an alternative measure of Reef Exposure – the number of reefs within 50 km of the coast. The results of the assessment using the two approaches were not substantially different, however, the Maughan et al. (2008) Reef Exposure model provides a more considered assessment as it factors in other aspects that influence exposure including river variability and plume direction which would help to differentiate the varying behaviour of the rivers in the wet and dry tropics.

2.3. Results of the risk assessment d

Exclusion of the Reef Condition factor: Consideration of only Anthropogenic Load and Reef Exposure resulted in a greater spread of the final scores, and a shift in the highest priority regions, i.e. The Wet Tropics become more prominent than Mackay Whitsunday because the Reef Condition scores for the Wet Tropics are lower. It was concluded that Reef Condition should not be excluded because it can be an indicator of previous exposure and reduced resilience to further impacts.

The overall relative risk of the GBR regions considered for priority contaminants is summarised in Table 2 and presented in Fig. 2. Further detail including the scores for each parameter is provided in the Supplementary information (Table S1). From these results we were able to develop a risk ranking between the NRM regions. This was coupled with the information on pollutant sources by land use for each NRM region to identify

Table 1 Parameter ranges, assumed relationships and defined categories for determining the Relative Risk of parameters by NRM region in the GBR catchment. Parameter

Data range

Relationship

Category 1

2

3

4

5

Anthropogenic load TSS DIN PSII Herb

Range: 292,000–5164,000t Range: 840–3244t Range: 0.51–3.55t

High load = High risk High load = High risk High load = High risk

0–1 M 0–700 0–0.7

1–2 M 701–1400 0.7–1.4

2–3 M 1401–2100 1.4–2.1

3–4 M 2101–2800 2.1–2.8

4–5 M 2801–3500 2.8–3.6

Reef condition Macroalgal cover Hard coral richness Secchi depth Chlorophyll

Range: Range: Range: Range:

High cover = High impact Low richness = High impact Low depth = High impact High Chl = High impact

0–8 125–100 15–12.5 0–0.25

8–17 100–75 12.5–10 0.25–0.5

17–26 75–50 10–7.5 0.5–0.75

26–35 50–25 7.5–5 0.75–1.0

35–41 25–0 5–2.5 1.0–1.25

0–2 0–13 0–8 14–19

3–5 14–27 9–17 20–25

6–8 28–41 18–26 26–30

9–11 42–55 26–34 31–36

12–14 56–69 34–42 37–42

Reef exposure TSS exposure DIN exposure PSII Herb exposure Risk rating

7–41% 121–7.3 15–4.3 m 0.45–1.2 lg/L

High% exposure = High impact Range: 1–10% Range: 0–65% Range: 0–40% Min score = 14 Max score = 70

Table 2 Results of the relative risk assessment of priority contaminants in the GBR catchments. Region

Relative risk

Dominant agricultural land use

Priority contaminants

Wet Tropics Burdekin Mackay Whitsunday Fitzroy Burnett Mary

High Medium–high High Medium–high Medium

Sugarcane Grazing with sugarcane in the lower Burdekin Sugarcane Grazing Grazing with sugarcane in the coastal areas

DIN, PS-II herbicides TSS, DIN, PS-II herbicides DIN, PS-II herbicides TSS, PS-II herbicides DIN, PS-II herbicides

J. Waterhouse et al. / Marine Pollution Bulletin 65 (2012) 394–406

401

Fig. 2. Comparison of the relative risk scores for the GBR catchments.

priority regions and land uses for management. Note that it is the order of the scores across the regions that is of most interest in the context of undertaking a relative risk assessment between the regions, and that the final classes may be useful for communicating the results. However, a more sophisticated assessment should incorporate further investigation of regional differences and the relative importance of different pollutants to better inform future management priorities. The assessment showed that the Wet Tropics and Mackay Whitsunday regions rank the highest priority (ranked high), with Burdekin and Fitzroy catchments relatively high priority (medium– high) and the Burnett Mary catchments of moderate priority in terms of the contribution and influence of land based pollutants. This concurs with several principles of the current understanding of priority pollutants and land uses in the GBR, namely: 1. Sugarcane and horticultural land uses that generate large quantities of DIN and PS-II herbicides runoff per unit area are dominant in the coastal areas of the Wet Tropics, Burdekin, Mackay Whitsunday and Burnett Mary catchments. 2. The predominantly coastal location of intensive agricultural land uses in the GBR catchment results in efficient delivery of contaminants to the GBR. 3. A high number of reefs are located close to the coast in the northern area of the GBR, particularly in the Wet Tropics, whereas reefs in the southern area tend to be located further offshore. 4. The assessment reflects the importance of dry tropics grazing activities and the contribution of sediment by erosion to receiving waters. A large proportion of the reefs in the waters influenced by runoff from grazing areas of the Fitzroy and Burdekin regions are located further offshore and this runoff thus may present a lower risk to reef habitats. However, suspended sediment risk to other important GBR ecosystems such as seagrass beds has not been included in this assessment and if this was done the importance of the Burdekin and Fitzroy regions could be enhanced. The following priorities were developed: Priority 1: Sugarcane (DIN) in the Wet Tropics, Burdekin and Mackay Whitsunday regions.

Priority 2: Grazing (TSS) in the Burdekin and Fitzroy regions. Priority 3: Sugarcane (PS-II herbicides) in the Wet Tropics, Burdekin and Mackay Whitsunday regions and grazing (PS-II herbicides – tebuthiuron) in the Fitzroy region. Priority 4: Sugarcane (DIN and PS-II herbicides) and grazing (TSS) in the Burnett Mary region, and cotton (DIN) and grains (DIN and PS-II herbicides) in the Fitzroy region. Priority 5: Bananas (DIN) in the Wet Tropics region. Priority 6: Horticulture (except Wet Tropics bananas) and other cropping across all of the regions (DIN).

3. Identification of regional priorities for management 3.1. Study area This assessment was undertaken in the Wet Tropics, Burdekin, Mackay Whitsunday and Fitzroy Regions of the GBR catchment (see Fig. 1). It did not include the rivers in the Cape York and Burnett Mary NRM regions. 3.2. Methods Following the completion of the relative risk of pollutant loadings from broad-scale agriculture in the GBR catchments to GBR health, we undertook an assessment of management priorities or ‘hot spots’ within the basins of the priority regions in terms of water quality outcomes. We analysed the three priority pollutants included in the relative risk assessment: suspended sediments, DIN and PS-II herbicides. We also used the same categories of major land uses which potentially contribute to GBR water quality issues i.e. Sugarcane, Grazing, Other Crops, Forest and Other. The fact that specific land uses such as urban, dairy or grains (incorporated into categories such as Other or Other crops) were not specifically assessed does not mean that these land uses do not have a contributory effect, but does mean that the contribution is known to be small at a GBR scale as is the case for dairy, or only important in one region such as grains in the Fitzroy. We used a series of questions included below to develop information within the priority regions – the Wet Tropics, Burdekin, Mackay Whitsunday and Fitzroy – for each of the priority pollutants.

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3.2.1. Suspended sediment d

d

d

d

Which basin of the region delivers the most suspended sediment (current) on an annual basis to the GBR? Which basin of the region delivers the most anthropogenic suspended sediment on an annual basis to the GBR? Within the basins, which land use contributes the majority of the suspended sediment? Within all of the basins what is the erosion type that generates the most suspended sediment?

GBR catchments. The results of regional pollutant load assessments indicate that: d

d

3.2.2. Dissolved inorganic nitrogen d

d

d

Which basin of the region delivers the most DIN on an annual basis to the GBR? Within the basins, which land use contributes the majority of the DIN? Within the primary source land use, which basins deliver the most DIN per hectare?

3.2.3. PS-II herbicides d

d

Which basins of the region deliver the most herbicides on an annual basis to the GBR? What kind of herbicide is delivered from which basins?

The data used to answer these questions were largely derived from the risk assessment described above (Section 2), our current load estimations for each catchment (presented in Brodie et al., 2009a) and regionally specific information generated to support the development of regional water quality plans. However, for DIN, we used a different approach to estimate the natural load to address uncertainties related to modeling undertaken in the preEuropean estimates presented in Brodie et al. (2003). The natural load was calculated using a ‘natural’ generation rate using the following steps: (1) Calculate the natural DIN load for the forest area as kg/ha to determine a ‘natural DIN generation rate’. (2) Assume that the total current area of sugarcane was forest prior to anthropogenic influence. (3) Calculate the ‘natural’ DIN load by multiplying the area of sugarcane by the ‘natural DIN generation rate’. (4) Calculate the anthropogenic load as the difference between the new calculation of the natural DIN load and Current DIN load. This method is believed to be robust in Wet Tropics catchments where variability in rainfall across the catchment is low but may not work (and has not been used) in large catchments such as the Fitzroy and Burdekin where there are large variations in the spatial distribution of rainfall. In addition, revised estimates of current loads were included for other parameters where new information was available. For example, in several coastal areas, the gauging station for the river flow data is located several kilometers upstream of the coast and above large areas of agriculture. This is the case in the lower Burdekin catchments and the coastal areas of the Burnett River and local studies were used to improve the end of catchment load estimates at these locations. Within each region, the measures and major contributing factors estimated for each basin are shown in Table 3. We also reported a qualitative statement of data confidence for each result, explaining for example low confidence due to reliance on modeled data and limited availability of monitoring data.

d

d

d

The areas of the highest generation of pollutant loads are: DIN – sugarcane in the Burdekin and Wet Tropics regions; suspended sediments – grazing lands in the Burdekin and Fitzroy regions; and PS-II herbicides – sugarcane in the Wet Tropics and Mackay Whitsunday regions. A large proportion of the anthropogenic load of DIN (approximately 80%) is derived from sugarcane fertiliser losses (Wet Tropics 84%, lower Burdekin 80%, Mackay Whitsunday 88%), except in the Fitzroy region where almost all of the DIN load is from cereal grains and cotton. Hillslope erosion contributes the most suspended sediment to the overall load across the GBR catchments in comparison to bank and gully erosion (but this is highly uncertain, see for example Wilkinson et al., in press). Diuron is the dominant herbicide found in the Wet Tropics, lower Burdekin and Mackay Whitsunday regions. It is generally associated with areas of sugarcane but is also found in other cropping areas. Tebuthiuron is the dominant herbicide in the Burdekin and Fitzroy regions associated with beef grazing lands. Atrazine is associated with other crops in the Fitzroy region.

To illustrate the type of information generated for each region included in our analysis, a case study example of the Wet Tropics Region is provided below. Further detail is provided in Brodie et al. (2009b). 3.3.1. Case study example – Wet Tropics Region The basins for the Wet Tropics Region in the study are shown in Fig. 3 with the basin boundaries for the Wet Tropics as defined in Brodie et al. (2003). A summary table of results is also presented in Supplementary information (Table S2). 3.3.2. Dissolved inorganic nitrogen d

d

d

The Russell Mulgrave basin generates the highest total DIN load on an annual basis, followed by the Johnstone, Herbert and Tully basins. The key contributing land use to DIN loads is sugarcane and associated fertiliser application. The largest proportion of total anthropogenic DIN load from sugarcane is from the Johnstone basin, with high contributions also from the Russell Mulgrave, Herbert, Tully and Murray basins.

Table 3 Measures and major contributing factors for the risk assessment. Pollutant

Measure

Most relevant land use

Dominant erosion

TSS

Current load Anthropogenic load Current load per area Anthropogenic load per area Current load Anthropogenic load Current load per area Anthropogenic load per area Current load Current load per area

Grazing

Hillslope Gully Bank

DIN

3.3. Results of the regional prioritization PS-II herbicides

The results of the regional prioritizations are relevant to each region but can be used to draw a set of conclusions about the

Sugarcane

Sugarcane and/ or grazing and Other crops

J. Waterhouse et al. / Marine Pollution Bulletin 65 (2012) 394–406

d

d

In terms of DIN load from sugarcane per unit area of sugarcane cultivation, the highest loads per unit area are from the Russell Mulgrave, Tully, Murray and Johnstone basins. In the Wet Tropics Region, it is estimated that the source of DIN loads is approximately 75% sugarcane and 5% bananas, 12% grazing and forest, and 8% other crops/dairy and urban.

Data confidence: The DIN load data are mostly derived from ANNEX modeling in the Daintree, Russell Mulgrave and Mossman catchments, so the results may be highly uncertain in these catchments due to insufficient monitoring data being available to validate the models. Greater confidence in the Tully, Johnstone, Barron and Herbert results is provided through the monitoring data used to support the models and the ranked order between these catchments is probably acceptable. However, there are limitations in the load estimations at the end of catchments across the GBR catchments. The gauging stations and monitoring sites are in most cases located upstream of the coastal strip, and often exclude a large drainage area, often characterized by sugar cane. Furthermore, a proportion of the drainage in each basin discharges via small waterways that discharge directly in the coastal waters and not via the main river system. Accordingly, the load is not accurately reflected by unit area of sugarcane land use, and in most cases is most likely to be under estimated. This partly explains differences between the DIN load per area of land use

403

in the Wet Tropics basins, which otherwise may be expected to be relatively similar. 3.3.3. PS-II herbicides d

d

d

d

The Herbert basin delivers the greatest load of PS-II herbicide followed by the Johnstone, Russell Mulgrave and Tully basins. The loads from remaining basins are comparatively lower. The greatest proportion of PS-II herbicides is generated from sugarcane areas in all Wet Tropics basins. Diuron is the PS-II herbicide discharged in the highest amounts from the region, followed by atrazine and hexazinone. The Herbert, Russell Mulgrave, Johnstone and Tully basins deliver substantial exports of diuron. It is believed that tebuthiuron is derived from grazing but there are little monitoring data for tebuthiuron in the Wet Tropics and all tebuthiuron conclusions need to be treated with caution. The other PS-II herbicides are known to be derived from sugarcane with high certainty (with the exception of simazine). The sources of simazine are not widely known but it is known to be used in plantation forestry.

Data confidence: High confidence in the data given that for comparison purposes the relationship between land use area and PS-II herbicide delivery is robust.

Fig. 3. Basins in the Wet Tropics Region.

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3.3.4. Suspended sediment d

d

d

Generally suspended sediment loading from Wet Tropics catchments is believed to have stabilized or declined over the last 10 years, although river monitoring data to support this is problematic as yet due to natural variability in flow and time lags (Bainbridge et al., 2009b). This is the expected trend associated with improved management practices in sugarcane (e.g. minimum tillage and green cane harvesting) and, to some extent, grazing in the region over the last 20 years (Rayment, 2003). The Herbert basin generates the most current total and anthropogenic suspended sediment load on an annual basis, followed by the Johnstone, Daintree and Russell Mulgrave basins. However, the Mossman basin generates the most suspended sediment per basin area on an annual basis, followed by the Russell Mulgrave, Daintree and Johnstone basins. The greatest anthropogenic load of suspended sediment to the GBR per unit area of land use is from sugarcane in most Wet Tropics basins (except Murray where ‘Other crops’ are higher). Grazing is also an important bulk source in the Herbert, Daintree and Mossman basins.

Data confidence: Modeled data results are uncertain for suspended sediment generation by land use, particularly in forest areas, and there is limited supporting monitoring data in some catchments. Therefore, it is concluded that there is insufficient data to make any further assessment of the sources of suspended sediment in the Wet Tropics Region, other than to identify areas known to generate higher rates of suspended sediment including grazing areas, and areas of high slope and sugarcane cropping lands during plant crop stage (Rayment, 2003).

evidence from monitoring and modeling data clearly identify that the principle sources of suspended sediments in the GBR catchments are grazing. One of the most challenging aspects of this and other risk assessments is the incorporation of social and economic factors which can have a significant influence over land management in the GBR catchment. These were not specifically incorporated in our assessment. Important factors include the capacity of landholders to change management practices, the economic climate and presence or absence of incentive programs, the existence of a coordinating body such as an industry association (e.g. Canegrowers) or a regional natural resource management group to manage and deliver policy or incentive programs and current institutional arrangements. Future risk assessments should address these factors to provide a more holistic assessment of factors that influence risk from pollutants in the GBR. The outcomes of this research have many direct management applications. For example, the development of the best estimate of pollutants loads for all of the GBR catchments (Brodie et al. 2009a) informed the prioritisation of Reef Rescue expenditure across Regions and within Regions (across land uses and industries) of the GBR. The load estimations were incorporated into the Multi Criteria Analysis undertaken by the Department of the Environment, Water, Heritage and the Arts (now the Department of Sustainability, Environment, Water, Population and Communities) in the selection of investment areas for the Reef Rescue. The data used in this assessment were also used as the basis for the improvement of baseline pollutant loads for the Reef Plan Paddock to Reef Program (in Kroon et al., 2012). Importantly, these studies were used to identify priority areas and land uses for application of the Great Barrier Reef Protection Amendment Act 2009 introduced by the Queensland Government in 2009.

4. Discussion and conclusions

Acknowledgements

Research programs in the last 5 years have generated significant outcomes in identifying the priority pollutants in the GBR and its catchments, estimating pollutant loads and determining the priority areas for management. Our analyses supports the understanding that the priority pollutants derived from anthropogenic land uses considered most likely to pose a threat to the quality of runoff water entering the GBR ecosystem are suspended sediment, dissolved inorganic nitrogen and PS-II herbicides. However, particulate nitrogen (PN) and particulate phosphorus (PP) are also high risk pollutants to the GBR but can be considered as co-pollutants with suspended sediments as can be seen from the results of pollutant load estimates (Kroon et al., 2012). Loads of these pollutants have increased by large factors over natural, 16 times for PP and 70 times for PN (Kroon et al., 2012). The main source of PN and PP is as for suspended sediments, i.e. Erosion in grazing lands in the Burdekin, Fitzroy and Burnett. A considerable portion of PP and PN delivered from soil erosion to the GBR is known to be bioavailable after mineralization processes (Furnas et al., 2005) and hence in the longer term presents a similar risk to GBR ecosystems as does dissolved inorganic nutrients. Our analysis also demonstrates that our current knowledge of pollutant sources and pollutant load estimations do enable ‘hotspots’ of pollutant delivery to the GBR to be identified with a reasonable degree of certainty. Most uncertainty associated with the assessment is related to the absolute values of pollutant loads in some locations, and hence land use contributions, and are well documented in other studies (e.g. Kroon et al., 2012; Lewis et al., 2007). The important outcome of our analysis is the source of pollutants relative to each other and to different land uses, and this is considered to be strong. For example, uncertainties exist in the estimates of suspended sediment loads in some places, but

Funding for this research came from the Queensland Department of Environment and Resource Management and the Department of the Environment, Water, Heritage and the Arts (now the Department of Sustainability, Environment, Water, Population and Communities). This research was carried out in conjunction with parallel projects funded by the CSIRO Great Barrier Reef Water Quality Options project under the Water for a Healthy Country Flagship, and the Marine and Tropical Sciences Research Facility administered through the Reef and Rainforest Research Centre. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.marpolbul.2011.09.031. References Anthony, K.R.N., Hoegh-Guldberg, O., 2003. Variation in coral photosynthesis, respiration and growth characteristics in contrasting light microhabitats: an analogue to plants in forest gaps and understoreys? Functional Ecology 17, 246–259. Armour, J.D., Hateley, L.R., Pitt, G.L. 2007. Improved SedNet and Annex modelling of the Tully-Murray catchment. A report prepared for the Tully Water Quality Improvement Plan. Department of Natural Resources and Water, Mareeba. 27 pp. Bainbridge, Z., Brodie, J., Lewis, S., Faithful, J., Duncan, I., Furnas, M., Post, D. (2006a). Event-based Water Quality Monitoring in the Burdekin Dry Tropics Region: 2004–2005 Wet Season. ACTFR Report No. 06/01 for BDTNRM. ACTFR, JCU, Townsville, 83 pp. Bainbridge, Z.T., Brodie, J.E., Faithful, J.W., Sydes, D.A., Lewis, S.E., 2009a. Identifying the land-based sources of suspended sediments, nutrients and pesticides discharged to the Great Barrier Reef from the Tully-Murray Basin, Queensland, Australia. Marine and Freshwater Research 60 (11), 1081–1090, doi:10.1071/ MF08333.

J. Waterhouse et al. / Marine Pollution Bulletin 65 (2012) 394–406 Bainbridge, Z.T., Brodie, J.E., Lewis, S.E., Waterhouse, J., Wilkinson, S.N., 2009b. Utilising catchment modelling as a tool for monitoring Reef Rescue outcomes in the Great Barrier Reef catchment area. Proceedings of 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation In: 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, 13–17 July 2009, Cairns, QLD, Australia. ISBN 978-09758400-7-8. . Bainbridge, Z., Lewis, S., Brodie, J., 2007b. Sediment and nutrient exports for the Burdekin River catchment, NQ: A comparison of monitoring and modelling data. MODSIM 2007. International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 10–13th December 2007, pp. 874–880. Bainbridge, Z.T., Lewis, S., Davis, A., Brodie, J., 2008. Event-based community water quality monitoring in the Burdekin Dry Tropics region: 2007–2008 wet season update. Australian Centre for Tropical Freshwater Research Report 08/19. Bainbridge, Z., Lewis, S., Brodie, J., Faithful, J., Maughan, M., Post, D., O’Reagain, P., Bartley, R., Ross, S., Schaffelke, B., McShane, T., Baynes, L., 2006b. Monitoring of sediments and nutrients in the Burdekin Dry Tropics region: 2005–2006 wet season. ACTFR Report No. 06/13 for BDTNRM. ACTFR, JCU, Townsville, 97 pp. Bainbridge, Z.T., Lewis, S.E., Brodie, J.E., Liessmann, L., Davis, A.M., Maughan, M., Lymburner, L., Bartley, R., Hawdon, A., Keen, R., Verwey, P., 2007a. Event-based community water quality monitoring in the Burdekin Dry Tropics Region: 2006–2007, Volume 1 (2006/07 Wet Season Report) and 2002–2007 Volume 2 (Integrated 2002–2007 Wet Season Report). ACTFR Technical Report 07/22, Australian Centre for Tropical Freshwater Research, Townsville. Belperio, A.P., 1983. Late Quaternary terrigenous sedimentation in the Great Barrier Reef lagoon. In: Baker, J.T., Carter, R.M., Sammarco, P.W., Stark, K.P. (Eds.), Proceedings of the Great Barrier Reef Conference, Townsville, pp. 71–76. Brodie, J., Binney, J., Fabricius, K., Gordon, I., Hoegh-Guldberg, O., Hunter, H., O’Reagain, P., Pearson, R., Quirk, M., Thorburn, P., Waterhouse, J., Webster, I., Wilkinson, S., 2008. Synthesis of evidence to support the Scientific Consensus Statement on Water Quality in the Great Barrier Reef. The State of Queensland (Department of Premier and Cabinet) Brisbane. . Brodie, J., De’ath, G., Devlin, M., Furnas, M., Wright, M., 2007. Spatial and temporal pattern of near-surface chlorophyll a in the Great Barrier Reef lagoon. Marine and Freshwater Research 58, 342–353. Brodie, J.E., Devlin, M.J., Haynes, D., Waterhouse, J., 2010. Nutrients, eutrophication and the Great Barrier Reef (Australia). Biogeochemistry, doi: 10.1007/s10533010-9542-2. Brodie, J., Fabricius, K., De’ath, G., Okaji, K., 2005. Are increased nutrient inputs responsible for more outbreaks of crown-of-thorns starfish? An appraisal of the evidence. Marine Pollution Bulletin 51, 266–278. Brodie, J., Kroon, F., Schaffelke, B., Wolanski, E., Lewis, S., Devlin, M., Bainbridge, Z., Waterhouse, J., Davis, A., 2012. Terrestrial pollutant runoff to the Great Barrier Reef: current issues, priorities and management responses. Marine Pollution Bulletin 65, 81–100. Brodie, J., Lewis, S., Bainbridge, Z., Mitchell, A., Waterhouse, J., Kroon, F., 2009c. Target setting for pollutant discharge management of rivers in the Great Barrier Reef catchment area. Marine and Freshwater Research 60 (11), 1141–1149. Brodie, J., McKergow, L.A., Prosser, I.P., Furnas, M., Hughes, A.O., Hunter, H., 2003. Sources of Sediment and Nutrient Exports to the Great Barrier Reef World Heritage Area. ACTFR Report No. 03/11. Australian Centre for Tropical Freshwater Research, James Cook University, Townsville. Brodie, J., Mitchell, A., Waterhouse, J., 2009b. Regional assessment of the relative risk of the impacts of broad-scale agriculture on the Great Barrier Reef and priorities for investment under the Reef Protection Package, Stage 2 Report, July 2009. ACTFR Report 09/30. Brodie, J., Waterhouse, J., 2009. Assessment of relative risk of the impacts of broadscale agriculture on the Great Barrier Reef and priorities for investment under the Reef Protection Package, Stage 1 Report April 2009. ACTFR Report 09/17. Brodie, J., Waterhouse, J., Lewis, S., Bainbridge, Z., Johnson, J., 2009a. Current loads of priority pollutants discharged from Great Barrier Reef Catchments to the Great Barrier Reef. ACTFR Report Number 09/02. Bruno, J., Petes, L.E., Harvell, D., Hettinger, A., 2003. Nutrient enrichment can increase the severity of coral diseases. Ecology Letters 6, 1056–1061. Burke, L., Reytar, K., Spalding, M., Perry, A., 2011. Reefs at risk revisited. World Resources Institute, Washington, DC, p. 114. Available from: . Carroll, C., Waters, D., Vardy, S., Silburn, D.M., Attard, S., Thorburn, P.J., Davis, A.M., Halpin, N., Schmidt, M., Wilson, B., Clark, A., 2012. A Paddock to Reef Monitoring and Modelling framework for the Great Barrier Reef: Paddock and Catchment component. Marine Pollution Bulletin 65, 136–149. Cogle, A.L., Carroll, C., Sherman, B.S., 2006. The use of SedNet and ANNEX to guide GBR catchment sediment and nutrient target setting. QNRM06138. Department of Natural Resources Mines and Water, Brisbane. Cotsell, P., Gale, K., Hajkowicz, S., Lesslie, R., Marshall, N., Randall, L., 2009. Use of a multiple criteria analysis (MCA) process to inform Reef Rescue regional allocations. In: Proceedings of the 2009 Marine and Tropical Sciences Research Facility Annual Conference 28–30 April 2009 Rydges Southbank Hotel, Townsville. Compiled by Shannon Hogan and Suzanne Long Reef and Rainforest Research Centre Limited. . Dauer, D.M., Ranasinghe, J.A., Weisberg, S.B., 2000. Relationships between benthic community condition, water quality, sediment quality, nutrient loads, and land use patterns in Chesapeake Bay. Estuaries 23, 80–96.

405

Davis, A.M., Lewis, S.E., Bainbridge, Z.T., Brodie, J.E., Shannon, E., 2008. Pesticide residues in waterways of the lower Burdekin region: challenges in ecotoxicological interpretation of monitoring data. Australasian Journal of Ecotoxicology 14, 89–108. Day, J., Fernandes, L., Lewis, A., Innes, J., 2004. RAP – an ecosystem level approach to biodiversity protection planning. In: Proceedings of the second International Tropical Ecosystem Management Symposium (ITMEMS), Manila 24–27 March 2003. Department of Environment and Natural Resources, pp. 251–265. De’ath, G., Fabricius, K.E., 2008. Water Quality of the Great Barrier Reef: Distributions, Effects on Reef Biota and Trigger Values for the Protection of Ecosystem Health. Research Publication No. 89. Great Barrier Marine Park Authority, Townsville, 104 pp. De’ath, G., Fabricius, K.E., 2010. Water quality as a regional driver of coral biodiversity and macroalgal cover on the Great Barrier Reef. Ecological Applications 20, 840–850. Devantier, L., De’ath, G., Turak, E., Done, T., Fabricius, K., 2006. Species richness and community structure of reef-building corals on the nearshore Great Barrier Reef. Coral Reefs 25, 329–340. Devlin, M.J., Harkness, P., McKinna, L.W., Abbott, B., Romero, J.A., Brodie, J.E., 2012. Mapping the extent of the surface exposure of river plume waters in the Great Barrier Reef. Marine Pollution Bulletin 65, 224–235. Dight, I., 2009. Burdekin Water Quality Improvement Plan, NQ Dry Tropics, Townsville. . Doney, S.C., 2010. The growing human footprint on coastal and open-ocean biogeochemistry. Science 328, 1512–1516. Drewry, J., Higham, W., Mitchell, C., 2008. Water Quality Improvement Plan. Final report for Mackay Whitsunday Region. Mackay Whitsunday Natural Resource Management Group. . EU, 2011. Available from: . Fabricius, K.E., 2005. Effects of terrestrial runoff on the ecology of corals and coral reefs: review and synthesis. Marine Pollution Bulletin 50, 125–146. Fabricius, K.E., 2011a. Factors determining the resilience of coral reefs to eutrophication: a review and conceptual model. In: Dubinski, Z., Stambler, N. (Eds.), Coral Reefs: An Ecosystem in Transition, Part 5. Springer, pp. 493–505, doi:10.1007/978-94-007-0114-4_28. Fabricius, K.E., 2011b. Nutrient pollution. In: Hopley, D. (Ed.), Encyclopedia of Modern Coral Reefs. Springer, pp. 722–731. Fabricius, K., De’ath, G., McCook, L., Turak, E., Williams, D., 2005. Changes in algal, coral and fish assemblages along water quality gradients on the inshore Great Barrier Reef. Marine Pollution Bulletin 51, 384–398. Fabricius, K., Okaji, K., De’ath, G., 2010. Three lines of evidence to link outbreaks of the crown-of-thorns seastar Acanthaster planci to the release of larval food limitation. Coral Reefs 29, 593–605. Fentie, B., Duncan, I., Sherman, B.S., Read, A., Chen, Y., Brodie, J., Cogle, A.L., 2006. Sediment and nutrient modelling in the Burdekin NRM region. Volume 3. In: Cogle, A.L., Carroll, C., Sherman, B.S. (Eds.), The use of SedNet and ANNEX models to guide GBR catchment sediment and nutrient target setting. Department of Natural Resources Mines and Water, Brisbane. QNRM06138. Furnas, M.J., 2003. Catchments and Corals: Terrestrial Runoff to the Great Barrier Reef. Australian Institute of Marine Science and Reef CRC, Townsville. Furnas, M.J., Mitchell, A., Skuza, M., Brodie, J., 2005. In the other 90%: phytoplankton responses to enhanced nutrient availability in the Great Barrier Reef Lagoon. Marine Pollution Bulletin 51, 253–265. Great Barrier Reef Marine Park Authority, 2009. Water Quality Guidelines for the Great Barrier Reef Marine Park. Great Barrier Reef Marine Park Authority, Townsville. Greiner, R., Herr, A., Brodie, J., Haynes, D., 2005. A multi-criteria approach to Great Barrier Reef catchment (Queensland, Australia) diffuse-source pollution problem. Marine Pollution Bulletin 51, 128–137. Halpern, B.S., Walbridge, S., Selkoe, K.A., Kappel, C.V., Micheli, F., D’Agrosa, C., Bruno, J.F., Casey, K.S., Ebert, C., Fox, H.E., Fujita, R., Heinemann, D., Lenihan, H.S., Madin, E.M.P., Perry, M.T., Selig, E.R., Spalding, M., Steneck, R., Watson, R., 2008. A global map of human impact on marine ecosystems. Science 319, 948–952. Haynes, D., Ralph, P., Prange, J., Dennison, W., 2000. The impact of the herbicide diuron on photosynthesis in three species of tropical seagrass. Marine Pollution Bulletin 41, 288–293. Herr, A., Kuhnert, P., 2007. Assessment of uncertainty in Great Barrier Reef catchment models. Water Science and Technology 56, 181–186. Hughes, T.P., Bellwood, D.R., Baird, A.H., Brodie, J., Bruno, J.F., Pandolfi, J.M., 2011. Shifting base-lines, declining coral cover, and the erosion of reef resilience. Comment on Sweatman et al. (2011) Coral Reefs: online. Hughes, T.P., Graham, N.A.J., Jackson, J.B.C., Mumby, P.J., Steneck, R.S., 2010. Rising to the challenge of sustaining coral reef resilience. Trends in Ecology and Evolution 25, 633–642. Hunter, H.M., Walton, R.S., 2008. Land-use effects on fluxes of suspended sediment, nitrogen and phosphorus from a river catchment of the Great Barrier Reef, Australia. Journal of Hydrology 356, 131–146. Johnston, N., Peck, G., Ford, P., Dougall, C., Carroll, C., 2008. Fitzroy Basin Water Quality Improvement Report, December 2008. Fitzroy Basin Association Inc, Queensland, Australia. ISBN: 978-0-9758172-2-3. .

406

J. Waterhouse et al. / Marine Pollution Bulletin 65 (2012) 394–406

Jones, R., 2005. The ecotoxicological effects of Photosystem II herbicides on corals. Marine Pollution Bulletin 51, 495–506. Jones, R.J., Kerswell, A.P., 2003. Phytotoxicity of photosystem II (PSII) herbicides to coral. Marine Ecology Progress Series 261, 149–159. Kroon, F.J., 2008. Draft Tully Water Quality Improvement Plan. CSIRO: Water for a Healthy Country National Research Flagship. http://www.csiro.au/files/files/ pm8v.pdf. Kroon, F.J., Kuhnert, P.M., Henderson, B.L., Wilkinson, S.N., Kinsey-Henderson, A., Abbott, B.N., Brodie, J.E., Turner, R., 2012. River loads of suspended solids, nitrogen, phosphorus and herbicides delivered to the Great Barrier Reef lagoon. Marine Pollution Bulletin 65, 167–181. Kuhnert, P.M., Henderson, A.-K., Bartley, R., Herr, A., 2010. Incorporating uncertainty in gully erosion calculations using the Random Forests modelling approach. Environmetrics 21, 493–509, doi: 10.1002/env.999. Lewis, S.E., Bainbridge, Z.T., Brodie, J.E., 2007. A review of load tools available for calculating pollutant exports to the Great Barrier Reef lagoon: a case study of varying catchment areas. In: Oxley, L., Kulasiri, D. (Eds.), MODSIM 2007 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2007, pp. 2396–2402. ISBN: 978-0-9758400-4-7. . Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: a new threat to the Great Barrier Reef. Environmental Pollution 157, 2470–2484. Lewis, S.E., Smith, R., Brodie, J.E., Bainbridge, Z.T., Davis, A.M., Turner, R., in review. Using monitoring data to model herbicides exported to the Great Barrier Reef, Australia. MODSIM 2011 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2011. LOICZ, 2011. Available from: . Lotze, H.K., Lenihan, H.S., Bourque, B.J., Bradbury, R.H., Cooke, R.G., Kay, M.C., Kidwell, S.M., Kirby, M.X., Peterson, C.H., Jackson, J.B.C., 2006. Depletion, degradation, and recovery potential of estuaries and coastal seas. Science 312, 1806–1809. Marubini, F., Davies, P.S., 1996. Nitrate increases zooxanthellae population density and reduces skeletogenesis in corals. Marine Biology 127, 319–328. Maughan, M., Brodie, J.E., 2009. Reef exposure to river-borne contaminants: a spatial model. Marine and Freshwater Research 60, 1132–1140. Maughan, M., Brodie, J., Waterhouse, J., 2008. What river impacts this reef? A simple reef exposure model. In: Lambert, M., Daniell, T., Leonard, M. (Eds.), Proceedings of Water Down Under 2008, incorporating 31st Hydrology and Water Resources Symposium and 4th International Conference on Water Resources and Environment Research, Adelaide 14–17 April 2008, Adelaide, 1912–1923. McCook, L.J., Folke, C., Hughes, T.P., Nystrom, M., Obura, D., Salm, R., 2007. Ecological resilience, climate change and the Great Barrier Reef. In: Johnson, J.E., Marshall, P.A. (Eds.), Climate Change and the Great Barrier Reef: A Vulnerability Assessment. Great Barrier Reef Marine Park Authority, Townsville, Australia, pp. 75–96. Mitchell, C., Brodie, J., White, I., 2005. Sediments, nutrients and pesticide residues in event flow conditions in streams of the Mackay Whitsunday Region, Australia. Marine Pollution Bulletin 51, 23–36. Mitchell, A., Furnas, M., 2001. River loggers – a new tool to monitor riverine suspended particle fluxes. Water Science and Technology 43, 115–120. Mitchell, A., Reghenzani, J., Faithful, J., Furnas, M., Brodie, J., 2009. Relationships between land use and nutrient concentrations in streams draining a ‘wettropics’ catchment in northern Australia. Marine and Freshwater Research 60, 1097–1108. Moss, A.J., Rayment, G.E., Reilly, N., Best, E.K., 1992. A preliminary assessment of sediment and nutrient exports from Queensland coastal catchments. Queensland Department of Environment and Heritage, and Queensland Department of Primary Industries, Queensland Government. National Land and Water Resources Audit, 2001. Volume 1 Australian Agriculture Assessment 2001. Natural Heritage Trust, Australian Government. Negri, A.P., Flores, F., Rothig, T., Uthicke, S., 2011. Herbicides increase the vulnerability of corals to rising sea surface temperature. Limnology Oceanography 56, 471–485. Negri, A., Vollhardt, C., Humphrey, C., Heyward, A., Jones, R., Eaglesham, G., Fabricius, K., 2005. Effects of the herbicide diuron on the early life history stages of coral. Marine Pollution Bulletin 51, 370–383. Neil, D.T., Orpin, A.R., Ridd, P.V., Yu, B., 2002. Sediment yield and impacts from river catchments to the Great Barrier Reef lagoon. Marine and Freshwater Research 53, 733–752. Neil, D.T., Yu, B., 1996. Simple climate-driven models for estimating sediment input to the Great Barrier Reef Lagoon. Department of Earth Sciences, JCU, pp. 122– 127. Osborne, K., Dolman, A.M., Burgess, S.C., Kerryn, J.A., 2011. Disturbance and dynamics of coral cover on the Great Barrier Reef (1995–2009). PLoS One 6, e17516.

O’Reagain, P.J., Brodie, J., Fraser, G., Bushell, J.J., Holloway, C.H., Faithful, J.W., Haynes, D., 2005. Nutrient loss and water quality under extensive grazing in the upper Burdekin river catchment, North Queensland. Marine Pollution Bulletin 51, 37–50. Packett, R., 2007. A mouthful of mud: the fate of contaminants from the Fitzroy River, Queensland, Australia and implications for reef water policy. In: Wilson, A.L., Dehaan, R.L., Watts, R.J., Page, K.J., Bowmer, K.H., Curtis, A. (Eds.), Proceedings of the 5th Australian Stream Management Conference. Australian rivers: making a difference. Charles Sturt University, Thurgoona, New South Wales. Packett, R., Dougall, C., Rohde, K., Noble, R., 2009. Agricultural lands are hot-spots for annual runoff polluting the southern Great Barrier Reef lagoon. Marine Pollution Bulletin 58, 976–986. Pandolfi, J.M., Bradbury, R.H., Sala, E., Hughes, T.P., Bjorndal, K.A., Cooke, R.G., McArdle, D., McClenachan, L., Newman, M.J.H., Paredes, G., Warner, R.R., Jackson, J.B.C., 2003. Global trajectories of the long-term decline of coral reef ecosystems. Science 301, 955–958. Pandolfi, J.M., Jackson, K.B.C., Baron, N., Bradbury, R.H., Guzman, H.M., Hughes, T.P., Kappel, C.V., Micheli, F., Ogden, J.C., Possingham, H.P., Sala, E., 2005. Are U.S. coral reefs on the slippery slope to slime? Science 307, 1725–1726. Pressey, R.L., Bottrill, M., 2009. Approaches to landscape- and seascape-scale conservation planning: convergence, contrasts and challenges. Fauna and Flora International. Oryx 43 (4), 464–475. QLUMP, 1999. Queensland Land Use Mapping Program. Queensland Government. . Queensland Department of the Premier and Cabinet, 2003. Reef Water Quality Protection Plan: for catchments adjacent to the Great Barrier Reef World Heritage Area. Queensland Department of Premier and Cabinet. Brisbane. The State of Queensland and Commonwealth of Australia. Available from: . Queensland Department of the Premier and Cabinet, 2009. Reef Water Quality Protection Plan 2009. For the Great Barrier Reef World Heritage Area and adjacent catchments. Queensland Department of Premier and Cabinet, Brisbane. . Rayment, G.E., 2003. Water quality in sugar catchments in Queensland. Water Science and Technology 48 (7), 35–47. Rohde, K., Masters, B., Fries, N., Noble, R., Carroll, C., 2008. Fresh and Marine Water Quality in the Mackay Whitsunday region 2004–05 to 2006–07. Queensland Department of Natural Resources and Water for the Mackay Whitsunday Natural Resource Management Group, Australia. Schaffelke, B., Mellors, J., Duke, N.C., 2005. Water Quality in the Great Barrier Reef Region: Responses of mangrove, seagrass and macroalgal communities. Marine Pollution Bulletin 51, 279–296. Seitzinger, S.P., Sanders, R.W., Styles, R., 2002. Bioavailability of DON from natural and anthropogenic sources to estuarine plankton. Limnology and Oceanography 47 (2), 353–366. Sweatman, H., Delean, S., Syms, C., 2011. Assessing loss of coral cover on Australia’s Great Barrier Reef over two decades, with implications for longer term-trends. Coral Reefs 30, 521–531. Sweatman, H., Syms, C., 2011. Assessing loss of coral cover on the Great Barrier Reef: A response to Hughes et al. (2011). Coral Reefs. doi: 10.1007/s00338-011-07947. Waters, D., Packett, R., 2007. Sediment and nutrient generation rates for Queensland rural catchments-an event monitoring program to improve water quality modelling. In: Wilson, A.L., Dehaan, R.L., Watts, R.J., Page, K.J., Bowmer, K.H., Curtis, A. (Eds.), Proceedings of the 5th Australian Stream Management Conference. Australian rivers: making a difference. Charles Sturt University, Thurgoona, New South Wales. Wilkinson, C., Brodie, J., 2011. Catchment Management and Coral Reef Conservation: a practical guide for coastal resource managers to reduce damage from catchment areas based on best practice case studies. Global Coral Reef Monitoring Network and Reef and Rainforest Research Centre Townsville, Australia, 120 p. Wilkinson, S.N., Hancock, G.J., Bartley, B., Hawdon, A.A., Keen, R.J., in press. Using sediment tracing to assess processes and spatial patterns of erosion in grazed rangelands, Burdekin River basin, Australia. Agriculture Ecosystems & Environment. doi:10.1016/j.agee.2012.02.002. Wooldridge, S.A., 2009. Water quality and coral bleaching thresholds: formalising the linkage for the inshore reefs of the Great Barrier Reef (Australia). Marine Pollution Bulletin 58, 745–751. Wooldridge, S., Brodie, J., Furnas, M., 2006. Exposure of inner-shelf reefs to nutrient enriched runoff entering the Great Barrier Reef Lagoon: post-European changes and the design of water quality targets. Marine Pollution Bulletin 52, 1467– 1479. Wooldridge, S.A., Done, T.J., 2009. Improved water quality can ameliorate effects of climate change on corals. Ecological Applications 19, 1492–1499.