Balancing the Tradeoffs between Ecological and ...

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Balancing the Tradeoffs between Ecological and Economic Risks for the Great Barrier Reef: A Pragmatic Conceptual Framework a

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C. R. Thomas , I. J. Gordon , S. Wooldridge & P. Marshall

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CSIRO Sustainable Ecosystems, Davies Laboratory, Townsville, QLD, Australia b

Australian Institute for Marine Science, Townsville, QLD, Australia

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Great Barrier Reef Marine Park Authority, Townsville, QLD, Australia Available online: 13 Jan 2012

To cite this article: C. R. Thomas, I. J. Gordon, S. Wooldridge & P. Marshall (2012): Balancing the Tradeoffs between Ecological and Economic Risks for the Great Barrier Reef: A Pragmatic Conceptual Framework, Human and Ecological Risk Assessment: An International Journal, 18:1, 69-91 To link to this article: http://dx.doi.org/10.1080/10807039.2012.631470

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Human and Ecological Risk Assessment, 18: 69–91, 2012 Copyright C Taylor & Francis Group, LLC ISSN: 1080-7039 print / 1549-7860 online DOI: 10.1080/10807039.2012.631470

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Balancing the Tradeoffs between Ecological and Economic Risks for the Great Barrier Reef: A Pragmatic Conceptual Framework C. R. Thomas,1 I. J. Gordon,1 S. Wooldridge,2 and P. Marshall3 CSIRO Sustainable Ecosystems, Davies Laboratory, Townsville, QLD, Australia; 2 Australian Institute for Marine Science, Townsville, QLD, Australia; 3Great Barrier Reef Marine Park Authority, Townsville, QLD, Australia

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ABSTRACT Coral reefs are threatened globally by the climatic consequences of rising atmospheric CO2 levels; in many regions they are also threatened locally, for example, by reductions in the water quality of runoff from adjacent catchments. Interaction between global and local pressures makes it possible to use local actions to mitigate the impacts of climate change. To this end, managers and policy-makers are seeking to implement agricultural land management regimes that improve runoff water quality and thereby reduce risks to the Great Barrier Reef. Although components of the Great Barrier Reef Region have been researched for some time, a systemic approach capable of representing the Region’s key functional relationships as a social–ecological system is lacking. Here we provide a conceptual framework of the Great Barrier Reef social–ecological system that identifies a range of complex socioeconomic tradeoffs that may be required to maintain resilient reefs under climate change. The conceptual framework is the first step toward development of a functional analytical tool that is capable of helping policy-makers choose between alternative management actions. Key Words:

decision support, water quality, ecosystem services, contested landscapes.

INTRODUCTION The Great Barrier Reef region is a complex social–ecological system. A social–ecological system is a system of people and nature (Carpenter 2008). In social–ecological systems, resource-use activities that benefit stakeholders in one location can have flow-on effects that penalize stakeholders in “downstream” locations. Interventions are often required to manage the system in an equitable and sustainable way. Interventions can also have lasting repercussions for human and Address correspondence to C. R. Thomas, CSIRO Sustainable Ecosystems, CSIRO Private Mail Bag, Aitkenvale, QLD, Australia, 4814. E-mail: [email protected] 69


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ecological communities, and the risk of inadvertently creating negative outcomes needs to be assessed before management actions are implemented, and tradeoffs between ecological protection and human livelihoods manifest. The social, economic, or ecological risks and benefits of resource-use activities have typically been investigated and managed as separate sectors operating at separate locations (van Kerkhoff 2005; Tress et al. 2007; Macleod et al. 2008). Scientific and/or managerial approaches have been developed with relatively ad hoc consideration of other sectors, resulting in a fragmented knowledge base that maps poorly to larger scales most relevant to policy-makers (Stevens et al. 2007). Decisions and policies can be difficult to formulate and implement for problems that arise externally to a sector (i.e., “upstream”), affect external sectors (i.e., “downstream”), or are resolved externally. A systems approach is required to clarify and quantify important interdependencies that affect inter-sectoral functionality, and that underpin effective policy formulation. This is the case with the Great Barrier Reef social–ecological system, which has until recently been characterized by reductionist and fragmentary research activity (Gordon 2007; Thomas 2008). The research base for agriculture and tourism acknowledges their roles as major sectors of the Great Barrier Reef Region. For example, research and monitoring conducted for 20 years in various catchments has vastly improved our understanding of how agricultural productivity interacts with river flows and water quality (e.g., Belperio 1979; Brodie et al. 1984; McKergow et al. 2005). Thirty years of marine research and monitoring have clarified the roles that biophysical factors such as water quality, predation, and climate play in determining reef condition and how these stressors might be managed (Connell 1978; Hoegh-Guldberg et al. 2007). Similarly, tourism research has revealed much about who visits the Great Barrier Reef, what they do when they get there, and why they came (Kenchington 1991; Shafer and Inglis 2000; Coghlan and Prideaux 2009a). Despite this strong research foundation, the understanding of functional linkages between these elements has remained relatively elusive and no single framework exists to represent the key functional relationships of the system as a whole. Under a future dominated by climate change, managers and policy-makers must understand how components function as a single system. For example, they must know: (1) how the biophysical and economic components of agricultural, tourism, and ecological sectors are structured and function under different climate and human-use regimes; (2) how these sectors interact; (3) the range of alternatives available to manage them; (4) the risks and benefits of each alternative; and (5) how risks and benefits of alternative interventions are distributed across sectors. By clarifying the climatic and land management conditions under which desirable/undesirable consequences of policy tradeoffs might best be enabled/disabled, risk models can be created that support development of informed policy interventions. Given this complex and multidimensional problem (Carolan 2008), a framework must first be developed to identify which sectoral interactions will produce the most fruitful analysis. The purpose of the framework presented here is to build on existing knowledge and thereby distill and illuminate the connections within and between key elements of the Great Barrier Reef social–ecological system that are likely targets for intervention. This framework is conceptual in that no new data or system understanding 70

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Balancing Risks and Benefits for the Great Barrier Reef

is introduced. However, the framework is pragmatic also in that it demonstrates the capacity to functionally link system sectors so that quantitative ecological–economic risk–benefit tradeoffs can be made at subsequent stages of research. Functional linkages are evidence-based mechanisms explaining relationships of quantitative change. Although all conceptual frameworks are derived a priori from data at some level, our requirement to operationalize our conceptual model necessitated that key linkages be underpinned by data as much as possible. The framework structure thus strongly reflects data availability and presents the best structure for operationalization and risk assessment. Alternative structures could be developed that better reflect other aspects of the system and its management. Our contribution provides a conceptual framework that pulls together diverse strands of scientific research to facilitate the assessment of cross-sectoral ecological and economic change. This is a first step toward developing a functional analytical framework for the complex social–ecological system that is the Great Barrier Reef Region. The Great Barrier Reef Region, or “the Region,” is comprised of the Great Barrier Reef (i.e. “the Reef”), and the catchments that drain to it (i.e., “the Catchments”). To make the problem tractable and relevant, assessment of the Great Barrier Reef is first undertaken within a single catchment, by way of a case study. The case study provides a mechanism for developing a framework for clarifying key social–ecological risk–benefit tradeoffs in the Great Barrier Reef, and that can be expanded and operationalized at the regional level.

THE GREAT BARRIER REEF SOCIAL–ECOLOGICAL SYSTEM Many issues faced by science are characterized by complexity and uncertainty (Funtowicz and Ravetz 1993). Such issues cannot be addressed by research undertaken within individual disciplines, but must rely on approaches that broadly span the social, economic, and ecological disciplinary domains. The most challenging aspect of developing this framework was identifying quantifiable cross-sectoral linkages to represent functional relationships between these domains (Figure 1). Identifying these relationships may help improve the understanding of how the Great Barrier Reef Region might be managed under a range of plausible global climate change scenarios. Reef Ecology and Climate Change Several processes threaten the ongoing health and resilience of the Reef, including predation by crown-of-thorns starfish (Kenchington 1978; Moran et al. 1992), ocean acidification (Hoegh-Guldberg et al. 2007; De’ath et al. 2009), and cyclones (Massel and Done 1993), although there are many others (Wilkinson 1999). These are potentially devastating processes, which may intensify in a warmer climate (Hoegh-Guldberg 1999). In particular, the synergistic interaction between rising sea surface temperatures (SSTs) and elevated nutrient loads represents a potentially quantifiable threat to the future persistence of coral reef ecosystems (Wooldridge and Done 2009). Increased SSTs are predicted to exacerbate the incidence of coral bleaching, coral mortality, and biodiversity depletion beyond rates previously experienced in recent history (Hoegh-Guldberg 1999). This emerging disturbance Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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Ecological Processes

Industry Income

Agriculture Land use type

Terrestrial Sugar cane

Management pracce


Grazing

Climate change

Water Quality

Forestry

Suspended sediment Dissolved inorganic N

Coral Bleaching

Cross-sectoral income

Annual return interval

Reef Condion

Marine

Biodiversity

Fishing

Visual amenity

Tourism

Relaonships not explored in detail

Figure 1.

Mud map of the key elements of the Great Barrier Reef social–ecological system within the context of climate-driven coral bleaching. System components and inter-relationships relevant to the case study are indicated with a solid line (adapted from Thomas et al. 2009).

regime will have serious consequences for the Reef’s biodiversity, ecology, amenity, and dependent recreational use and economic activity (Done et al. 2003). While little can be done at the local level to mitigate rising SSTs, there is emerging evidence to suggest that the thermal tolerance of coral reefs is synergistically linked to local water quality (Wooldridge 2009b; Carilli et al. 2009a,b). Corals that are regularly exposed to poor water quality are thus predicted to be less resistant to thermal stress such that, upon exposure to sub-optimal temperatures, they may display higher rates of bleaching and mortality (Wooldridge and Done 2009). A relationship between climate change, water quality and coral bleaching indicates a strong interdependence between the marine and terrestrial sectors of the Great Barrier Reef region, and thus it is one of the key linkages developed in the framework. 72




The Economic Loop Identifying how to maintain high water quality is a key research problem for the Region. The Wet Tropics rainforest and the Great Barrier Reef World Heritage Area are both adjacent to substantial agricultural areas. Although agriculture is economically important to the Region (Productivity Commission 2003), it also has potential for negative ecological effects for the Reef (Brodie et al. 2001). High levels of nutrients in runoff, such as dissolved inorganic nitrogen (DIN), are predicted to exacerbate climate-driven thermal bleaching damage (Wooldridge 2009b). DIN concentrations are managed by implementing land management practices that reduce loss of nitrogen in runoff by, among other things, controlling nitrogen fertilizer application rates to sugar cane (Roebeling et al. 2007a). However, land management practices that reduce nitrogen loss can in some cases reduce farm productivity and income (Roebeling et al. 2007a). Thus, the degree of DIN reduction required to achieve meaningful protection of coral reefs may come at significant cost to the agricultural sector being managed. This represents a tradeoff decision for policymakers and the interdependence between agricultural livelihoods and water quality is, therefore, another key linkage developed in the framework. Much reef-related research examines how reef health depends on the regulation of economically driven human influences, such as fishing and pollution. We diverge from this tradition to consider an inverse relationship between reef health and human activities; that is, we examine how economic health as indexed by income also depends on reef ecology. This “economic loop” exists because the ecological attributes that make the Great Barrier Reef a global icon also provide a critical resource for commercial enterprises, most notably fishing and tourism. For example, recent studies show that commercial activities undertaken on the Great Barrier Reef generate an estimated AU$6.9 billion/yr of which tourism accounts for approximately 84% or AU$5.8 billion (Fenton et al. 2007). Reef trips (e.g., scuba diving, snorkelling, visiting pontoons) are an important component of this income; between 1994 and 2008 an annual average of 2.1 ± 0.2 million visitor days were spent on the Reef (GBRMPA 2009 unpubl. data). Although the primary drawcard for reef tourists is the beauty and diversity of the Reef, its visual amenity can be devalued in many ways, including cyclone damage, oil spills, and bleaching. Reef-based tourism thus depends on high quality ecological conditions in order to contribute to the regional economy. The interdependence between reef condition and the tourism economy is therefore another key linkage developed in the framework, and “closes” the regional economic loop. Reef Social Policy Although we do not explicitly investigate the impacts of economic and ecological degradation of the Reef system to the social well-being of its communities, any decline in aesthetic, functional or financial value of the system will have implicit social consequences. To use an example from the sugar cane industry, reduced sugar cane productivity (e.g., via reductions in yield and/or area harvested) directly impacts the viability of sugar processing mills. The commercial value of sugar cane is realized entirely by the mills, which must process the cane within 16 hours of cutting (Productivity Commission 2003). Consequently, sugar cane is processed Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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in the same locality where it is grown. Hence, regional towns can rely heavily on the sugar industry because centrally located mills (Productivity Commission 2003; Garner 2008) employ a substantial subset of the local community (CSIRO 2002). Increased requirements to improve water quality clearly have the potential to lower the socioeconomic conditions of a community or region (van Grieken et al. 2011). Although the framework does not yet quantify potential social losses that may result from well-intentioned system interventions, it does clarify some pathways by which these losses may occur. This allows social consequences to be more coherently articulated and considered during policy formulation.

CASE STUDY Stretching 2000 km along Queensland’s eastern coastline, and covering roughly 348,000 km2, the Great Barrier Reef is among the richest and most complex marine systems on Earth (Figure 2). In 1982 the unique biological diversity, size, and significant role in the cultural history of traditional peoples led to the listing of the Great Barrier Reef as a World Heritage Area (UNESCO 2007). The Great Barrier Reef Marine Park and adjacent coastal catchments jointly comprise the Great Barrier Reef Region. Despite their moderate populations (in modern global terms), the Great Barrier Reef catchment is a highly productive economy. The key industries of the

Figure 2.

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Location of the study area within the Great Barrier Reef Region (adapted from Kroon 2009). Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012



Great Barrier Reef catchment are agriculture, mining, and tourism, which collectively contribute approximately AU$21.5 billion annually to the Australian economy and are the largest employers in the Region (Productivity Commission 2003). The Catchment covers an area of 278,700 km2 (Armour et al. 2009) and has a mean annual rainfall of 2500 mm (Faithful and Finlayson 2004). The Great Barrier Reef is a complex network of approximately 2900 coral reefs that cover about 6% of the total 350,000 km2 area (Wachenfeld et al. 2007). Most reefs are situated on the outer shelf at depths of 1–150 m (Wachenfeld et al. 2007). As a case study application, we chose the Tully-Murray catchment (“Tully”), which lies on the north-eastern seaboard of Queensland between the major regional centers of Townsville and Cairns (Figure 2). Characteristic of its location with the Wet Tropics region, Tully receives extensive summer rainfall with an annual average rainfall just greater than 4.2 m over 2,780 km2, of which approximately 68% leaves the catchment as runoff (Furnas 2003). Land cover in Tully is dominated by tropical rainforest (71%) and on the floodplains, sugarcane is the main agricultural land use (367 km2; 13%), followed by beef production from permanent pasture (5%), bananas and other horticulture (3%), and forestry (1%) (Armour et al. 2009). In years 2005–06 the catchment sustained a population of about 2600 people (OESR 2005). Most people living in these far north Queensland catchments are employed in the tourism, sugar cane, and horticulture industries (Productivity Commission 2003). Tully’s reliance on the sugar industry is second only to that of the Herbert River district (CSIRO 2002). Despite being relatively resource-rich, Tully ranks well above the Australian average of socioeconomic disadvantage, but is close to average for the Region (Hug and Larson 2006).

CONCEPTUAL FRAMEWORK Scientific understanding of the mechanisms linking the various elements of the Great Barrier Reef system is at different stages of scientific maturity. Some sectors have been researched for many years, and mature models are available. For sectors such as agriculture a relatively deep understanding exists about the nature of the domain and its relationship to other mature domains (Roebeling et al. 2007a). However, in contrast, the interactions of sectors such as marine ecology and tourism with other systems are less understood. Reef ecology (Johnson and Marshall 2007; Hoegh-Guldberg et al. 2007) and the economics of reef-based tourism (Hoegh-Guldberg and Hoegh-Guldberg 2004; Access Economics 2007; Driml 1999) are well studied, but the ecological–economic linkages between these sectors have not been developed to the level achieved in agriculture. To produce an operationalizable framework, functional relationships within and between the reef ecology and tourism sectors first need to be conceptualized. Shown in Figure 3 is that one existing process model and two purpose-built models form the backbone of the pragmatic conceptual framework. The agricultural ecological–economic model “EESIP” (Environmental and Economic Spatial Investment Prioritisation) estimates the changes in agricultural income and water quality at the river mouth under a range of hypothetical management practice regimes. EESIP is a spatially explicit model that evaluates a suite (range) of optimal mixes Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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Figure 3.

Schematic overview of how the framework will be operationalized for the case study system (adapted from Thomas et al. 2009). The framework requires integration of existing (i.e., global climate models, MECCA, EESIP) and two purpose-built (i.e., Coral Bleaching and ReefDIVE) models. EESIP draws on two additional models, “APSIM” and “SedNet/ANNEX.” Temporary links between models are indicated with a dashed line, the darker solid lines and shaded boxes highlight economic components and relationships. Existing models that produce outputs as scenarios are indicated.

of land management practices required to achieve a given level of DIN at the river mouth, and returns also estimates the financial economic return (profits or losses) associated with each mix (Roebeling et al. 2007a). EESIP integrates an agricultural production simulation model (APSIM; Keating et al. 2003), a catchment water quality model (SedNet/ANNEX; Prosser et al. 2001) and a spatial land use model with a GIS database. Water quality outputs from this model, in conjunction with SST projections based on global climate models (GCMs) and a hydrodynamic model (i.e., MECCA), are used in the coral bleaching model (see below) to estimate future bleaching risk. Projected changes in coral condition are integrated with social factors in the reef tourism model in order to estimate future risks and benefits to reef tourism. The following sections describe each sector in detail. 76




Sugarcane Cropping Areas of the Reef within the runoff–seawater mixing zone are currently enriched by nutrients (measured as chlorophyll-a) by up to 10-fold compared to areas outside this zone (Wooldridge et al. 2006). This enrichment of reef waters has been attributed to an approximate 4–10-fold (average) increase in DIN loads entering the Reef lagoon since European arrival (Furnas 2003). The majority of DIN entering the Reef is generated as runoff from intensely fertilized agricultural lands (viz. sugarcane and banana plantations) that tend to be located in close proximity to the coast (Furnas 2003). Fertilizer application rates and associated land-use practices dominate the DIN signal, and landscape nutrient budget models indicate significant capacity for management initiatives to reduce nitrogen loads in receiving waters. However, such management initiatives come at the risk of considerable social and economic costs to local farming communities (Roebeling et al. 2007a). EESIP estimates the contribution of a range of land management practices to DIN concentrations at the Tully River mouth (Roebeling et al. 2007a). To simplify the framework we focused only on sugar cane. Sugar cane is the most intensively fertilized land use in the Tully and the Region (Pulsford 1996); from 1994–2000 total nitrogen fertilizer use on Queensland cane increased by ∼35% (Productivity Commission 2003). Sugar cane management practices that can improve water quality outcomes include various improvements to tillage practices, fallow management, trash management, and nitrogen application rates and methods (Roebeling et al. 2007b). In reality management practices are more akin to a management regime. Different management regimes affect cost and productivity differently depending on characteristics such as rainfall, soil type, slope, distance to the river and distance to the mill. EESIP can determine and map, for a given land use such as sugar cane, the contribution of each land management practice, soil type, and fertilizer use rate to catchment nutrient generation, transport, and delivery. Additionally, EESIP calculates production costs, productivity and profits generated under each land practice and location. The integrated structure of EESIP allows it to estimate, for a given management regime, the optimal reduction in river DIN and associated change in farm productivity and financial profit/loss incurred to the sugar industry (Figure 4). Estimates of DIN reduction are used to drive the water quality component of the Coral Bleaching model. Estimates of financial performance are used in conjunction with the economic elements of the tourism model to determine the degree of change in income that would result from implementing a given management regime. Coral Bleaching The Coral Bleaching model estimates the future frequency and extent of severe coral bleaching for the Reef. Bleaching occurs when the symbiotic relationship between corals and dinoflagellate algae (“zooxanthellae”) breaks down, leading to the mass expulsion of zooxanthellae from the coral host (Glynn 1996; Brown 1997). For coral colonies, varying the symbiont population influences the amount of carbon (energy) that is photosynthetically fixed by the symbionts and translocated to the coral host (e.g., Hoegh-Guldberg and Smith 1989). Of primary concern is the Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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Figure 4.

Pragmatic conceptual framework for the ecological–economics of sugar cane in the Great Barrier Reef Region, with the ecological–economic model (below) showing a hypothetical example of the relationship between costs (e.g., increases in on-farm costs, decreases in productivity) and water quality improvement (% DIN reduction at the river mouth).

potential for the breakdown of the coral-zooxanthellae symbiosis to cause colony mortality (Marshall and Baird 2000; Loya et al. 2001), heighten the susceptibility of corals to disease (e.g., Muller et al. 2008) and reduce the future reproductive output of colonies (Baird and Marshall 2002). At a reef level, large scale coral bleaching can alter coral and fish species composition (Bellwood et al. 2006; Graham 2007), and encourage macro-algal dominance of coral reefs (Done 1992; McCook 1999; Ostrander et al. 2000). Colony mortality and subsequent changes to biological complexity substantially alter the visual reefscape. The primary triggering condition for large-scale bleaching events is the combination of high solar irradiance and anomalously warm sea surface temperatures (SSTs) (reviewed by Hoegh-Guldberg 1999). Indeed, only relatively short exposures (∼1 week) to small increases (1–2◦ C) in SSTs beyond normal summer maxima can trigger the deleterious bleaching response (Berkelmans 2008). Such thermal sensitivity makes coral reefs vulnerable to global climate change, with some scientists predicting that current warming trends could see the majority of the world’s coral reefs severely degraded or transformed to non-coral-dominated states by as early as 2030 (for example see Hoegh-Guldberg 1999; Sheppard 2003; Donner 2009). While it was originally conceived that upper thermal bleaching limits were relatively stable and the result of long-term adaptation of the coral symbiosis to its 78




local thermal regime (Fitt et al. 2001; Coles and Brown 2003), recent research suggests that the ability of corals to resist thermal stress may be more dynamic, and includes the possibility that local stressors (e.g., poor water quality) can lower thermal bleaching thresholds (Brown 2000; Wooldridge and Done 2009; Wooldridge 2009a; Carilli et al. 2009a,b). Beyond simple additive (cumulative) stress models, mechanistic explanation for the negative impact of poor water quality on bleaching susceptibility has centered on the potential for elevated levels of dissolved DIN to synergistically enhance the damaging cellular processes that underpin the thermal bleaching process (Wooldridge 2009a; Wooldridge and Done 2009). Agricultural runoff containing sediments, nutrients, and pesticides are transported to reefs by river flood plumes (Devlin and Brodie 2005). Flood plumes are natural events, but there is concern that the supply of land-derived materials has now increased beyond the capacity of the reef to absorb them without deleterious change (Brodie et al. 2008). Relationships between agricultural land use practices and end-of-river water quality have been investigated in the Great Barrier Reef for many years, and reasonably robust models quantifying key land management processes have been developed (Roebeling et al. 2007a). Sixty-five percent of Tully’s rainfall drains into the Reef as runoff (Pulsford 1996). In a typical year the Tully experiences at least two major river discharge events, and coral reefs within reach of the flood plume (e.g ., some reefs are only 10 kms from the coast) are at high risk from elevated levels of nutrients and sediments it transports (Brodie et al. 1997; Devlin et al. 2001). Links between coral survival and water quality have also been investigated for many years (Brodie 1992; Brodie et al. 2001; Fabricius 2005). However, direct relationships between bleaching risk and specific water quality components have only recently been proposed (Wooldridge et al. 2006; Anthony et al. 2007). Here, we developed a purpose-built Coral Bleaching model to forecast the effect of changes in flood plume DIN-enrichment and SST on bleaching risk (Figure 5).

Figure 5.

Pragmatic conceptual framework for coral health in the Great Barrier Reef Region, including a hypothetical example of the relationship between climate-driven changes in sea surface temperatures (SSTs) and bleaching risk for different nutrient regimes (graph adapted from Wooldridge 2009b) (color figure available online).


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Hydrodynamic processes combine with runoff nutrient concentrations to create a DIN exposure profile that is unique to each receiving reef. For example, reefs that are located closer to the river mouth (e.g., inshore reefs) will be exposed to plumes that have had less time to become diluted with seawater as they expand and are carried across and along the reef shelf. The capacity of a plume to reach a given reef will likewise vary depending on the volume of water it carries, the speed that it pushes out from the river mouth, and the hydrodynamic environment it enters. The hydrodynamic environment is itself a complex system subject to geomorphologic characteristics of the local coastline, wind patterns and seasonal currents. All of these factors combine to determine the degree to which the plume dilutes before it reaches a reef. Beyond the dynamic flood plume characteristics, the specific DIN exposure profile for each reef will vary depending on how upstream land is managed, information that is incorporated into an operational Coral Bleaching model using EESIP. The SST exposure profile at a given reef is likewise dependent on the global management imperative to mitigate future CO2 emissions. Similarly, output summaries from global climate models will also be incorporated into the Coral Bleaching model. For both DIN and SST, projections of future management scenarios can provide plausible glimpses of future conditions. The exposure profile of each reef is therefore unique in time and space, changing dynamically to reflect changes in land management, climate management, natural stochasticity and decadal trends in system variables. These variables all conspire to influence the frequency of future severe coral bleaching, which provides a key linkage to, and input for, the ReefDIVE (Reef Degradation’s Influence on Visitation Economics) model.

Reef-Based Tourism Reef degradation represents a direct loss of reef amenity and, therefore, a significant risk to the economic viability of the tourism industry. The ReefDIVE model allows assessments to be made about whether declines in reef quality present substantial risks to tourism demand for the Reef (Figure 6). This model is driven in part by outcomes generated by the Coral Bleaching model, and produces estimates of economic change that feed into the Region’s economic loop. Coral reefs provide key ecosystem services to tourism (Moberg and Folke 1999), and coral bleaching can have substantial socioeconomic impacts to associated industries, especially reef tour operators. Disturbances capable of inducing massive coral mortality (e.g., ocean acidification, predation, cyclones, disease, bleaching) can substantially degrade coral reefs (Marshall and Schuttenberg 2006). Mass coral mortality reduces reef connectivity, slows coral recovery, and depresses coral diversity (Bellwood et al. 2004). These processes facilitate algal invasion, promote species with bioerosive grazing behaviors, and so prevent active reef growth (Done 1992; Hoegh-Guldberg et al. 2007). Mass coral mortality has also been observed to create long-term changes in reef fish assemblages (Booth and Beretta 2002; Bellwood et al. 2006). Increases in the frequency and scale of reef disturbances (e.g., as a result of climate change) reduce reef resilience, impeding the capacity of algal-dominated reefs to return to a hard-coral-dominated reefscape (but see Adjeroud et al. 2009; 80




Figure 6.

Pragmatic conceptual framework for the ecological–economics of reef tourism in the Great Barrier Reef, including a hypothetical example of the relationship between changes in reef condition (e.g., % coral cover) and visitation (color figure available online).

Diaz-Pulido et al. 2009). This has been recognized by the Region’s tourism industry as a major challenge for their future sustainability (GBR Tourism and Climate Change Action Group 2009). A handful of studies on the Great Barrier Reef have quantified relationships between disturbance frequency (or inter-disturbance interval) and ecological parameters such as coral cover and diversity. Inter-disturbance intervals of up to 16 years resulted in monopolization of the reefscape by a single fast-growing coral species, and intervals shorter than 8 years increased the dominance of the more resilient soft corals relative to hard corals (Wakeford et al. 2008). A similar assessment showed that bleaching disturbances at 10–20 year frequencies (which is comparable to the frequency of disturbances observed in the last two decades) result in a rapid decline in cover of branching corals (Thompson and Dolman 2010). These and similar studies (Connell et al. 1997; Done et al. 2007; Madin et al. 2008; Adjeroud et al. 2009; Riegl and Purkis 2009) suggest that for disturbance frequencies shorter than 8–20 years, hard coral dominated reefscapes will be replaced by those dominated by soft corals, fleshy macroalgae, or coral rubble. These changes represent a significant loss of ecological function, and also a loss of reef amenity. Relationships between ecological function and amenity can be used to link forecasts of severe bleaching from the Coral Bleaching model and the Reef’s condition and visual amenity in the ReefDIVE model, the conceptual framework for the ReefDIVE model is shown in Figure 6. Tourists, especially divers, are attracted to spend their money in areas with intact and rich marine environments (Pendleton 1994; Arin and Kramer 2002; Park et al. 2002; Rudd and Tupper 2002). When reefs become dominated by large areas of dead coral or macroalgae (Wilkinson 1996; van Beukering and Cesar 2004), amenity is Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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reduced (Done et al. 2003; Hoegh-Guldberg et al. 2007). If the damage is on a large scale, it is reasonable to expect that future tourism demand may also decrease. The current inability of operators to anticipate such shocks reduces their capacity to prepare for or recover from decreases in demand. Several studies have used recreational welfare metrics to broadly estimate how tourism income changes with reef damage (Wilkinson et al. 1999; Westmacott et al. 2000; Wielgus et al. 2002; Williams and Polunin 2002; Kragt et al. 2009). Relationships between reef condition and tourism are complicated by an array of social factors including: tourists’ awareness that reefs can suffer disturbances (Westmacott et al. 2000); the different motivations and expectations that tourists have about their reef trip (Dearden et al. 2006; Meisel-Lusby and Cottrell 2008); their capacity to detect declines in reef quality; and the influence of externalities such as weather conditions and service quality (Shafer and Inglis 2000). Therefore, tourist perceptions and expectations about the quality of their reef experience (visitor characteristics) interact with the actual condition of the visited site (reef condition) to influence their intention to return or recommend the trip to others (trip satisfaction), and the price they are willing to pay. These are considered the key determinants of reef tourism viability in the ReefDIVE model. When operationalized, the model will integrate estimates of reef condition and visual amenity derived from the Coral Bleaching model and reef monitoring data (AIMS and GBRPMA, unpubl. data) with information on visitor characteristics and satisfaction from tourist surveys (Shafer et al. 1998; Moscardo et al. 2003; Coghlan and Prideaux 2009b; Kragt et al. 2009) and reef visitation data (GBRMPA unpubl. data) to forecast the effects of changes in reef condition on the economic viability of reef-based tourism. Effects of Climate Change on the Regional Economy We have attempted to demonstrate how a clear understanding of key economic and ecological interrelationships within the Great Barrier Reef system is pivotal to effective management. For example, agricultural management regimes affect the quality of marine ecological health, which in turn affects the tourism economy. This is a purely “downstream” or unidirectional flow of influence. However, we have also introduced the concept of an ‘economic loop’ to show that tourism and agriculture are also linked via the co-location of their communities within the region (Figure 7). Local communities provide much of the workforce supporting agriculture and tourism in the Region (Productivity Commission 2003). Income generated through these activities, whether personal income or corporate profit, sustains and enlivens regional communities. The tourism industry is the largest source of employment in the Region, slightly higher than agriculture, and is the predominant industry in the far north. However, sugar cane is an extremely important industry to local towns on the coastal plain such as Tully (Productivity Commission 2003). Economic flows from both tourism and sugar cane (and other agriculture, subject to similar requirements to maintain high water quality) therefore contribute strongly to the economic health, wealth, and well-being of the local community. A substantial decline in one or both sources of income can be expected to affect local communities, especially those with high employment in tourism and sugar cane. 82




Figure 7.

Integrated pragmatic conceptual framework for the Great Barrier Reef social–ecological system (color figure available online).

By considering the economic impacts of climate and land management scenarios across both sectors, the framework can provide a mechanism for considering how a large component of the regional income stream will fare under a range of policies. This gives policy-makers a powerful insight into the net socioeconomic effects of alternative intervention options. Operationalization of the Conceptual Framework as a Decision Support Tool The above review of the existing knowledge base identified critical interdependencies between system components. Linkages between and within the tourism sector and risks of coral bleaching had not been previously developed to an extent that would allow a framework to be rapidly operationalized in subsequent research phases. To support the subsequent development of a functional analytical tool, the conceptual framework was developed in a way that allowed easy conversion from a conceptual to an operational format capable of incorporating extant models with new, purpose-built models. Bayesian network (BN) technology was selected as the modeling platform for the analytical tool (not described here), and for the purpose-built models that would partly comprise it (i.e., the Coral Bleaching model and ReefDIVE model). BNs are tools for representing and reasoning about uncertainty in dependence relationships (Cain 2001; Jensen 2001). BNs provide a suitable platform for integrating data from diverse extant models and, being probabilistic, also support the quantitative risk-based analysis. BNs are also capable of integrating a range of data types (e.g., tourist surveys, ecological metrics), and dealing with data gaps. BNs are not the only choice for this type of modeling, but provide the best means of assembling the available knowledge. This approach also provides a flexible platform for updating Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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and extending sectoral models as the field matures, to include for example effects of climate change on the agriculture and tourism sectors.


DISCUSSION AND CONCLUSION We have outlined the development of a conceptual framework that forms the basis for an ecological–economic risk analysis tool for the Great Barrier Reef. The framework builds on previous research on the key relationships governing the Reef system, namely: (1) land use effects on water quality; (2) water quality effects on coral reef health; (3) reef health effects on visual amenity; and (4) visual amenity effects on tourism economies. These relationships influence the Region’s socioeconomic well-being. The conceptual framework (Figure 7) formalizes the ecological–economic system within a risk framework. This aids the difficult task of prioritizing alternative management actions. The complexity of the problem represents a challenging future modeling task, with a large envelope of solutions needing to be represented, each with its own scale and configuration of “wins” and “losses” across diverse system sectors. To simplify the framework, we specifically targeted key elements of the reef, agriculture and tourism sectors, and then focused on developing the most parsimonious set of cross-sector linkages to generate an integrated systems model. The diverse nature of the individual sectors presented a major challenge for model construction, not least because the causal (i.e., dependence) relationships within individual sectors exist at different levels of understanding and scientific development, as do the relationships between the separate sectors. Furthermore, the data that captures the functional behavior of each sector (as well as crosssector interactions) exists as an eclectic mix of simulated, empirical and subjectively derived information. By making these tradeoff uncertainties explicit, the framework supports development of catchment level questions in future risk analysis phases, such as: • Which reef protection target provides the lowest risk and maximum benefit for the local community? • How soon must reef protection targets be realized in order to maximize crosssector benefits? • Can win/win strategies be pursued with acceptable levels of certainty? • For a given reef protection target, what are the costs to industry and how are they distributed across sectors? • What are the risks and benefits of maximum and “do nothing” reef protection targets, and those in between, and how are these risks and benefits distributed? • Are the economic benefits to tourism likely to be large enough to balance economic losses to agriculture? • Are economic losses in any sector likely to exist at levels that substantially reduce community well-being? • What are the most influential system components, and are they amenable to policy development? 84




• How do different climate change scenarios interact with and compound all of the above? The framework uses water quality outcomes to link reef condition with socioeconomic attributes of both river and reef. Impacts of climate change such as elevated sea surface temperatures can not be managed at the level of individual catchments, but synergizing processes such as elevated levels of coastal DIN can be managed by improving agricultural land management practices, thus reducing the risk of severe bleaching and reef degradation. If DIN from farm runoff can be minimized, reefs will have a higher chance of remaining healthy. Implementation of environmentally protective land management regimes can benefit some growers through decreased costs and higher productivity, but there is a risk that some land practice mixes that improve water quality will also lower community incomes. This raises the question of how costs and benefits of reef protection activities will be distributed through the agricultural industry. For example, it may be useful to know whether changes in land management regimes can reduce sugar cane productivity below the minimum throughput volume for the local sugar processing mill (at which point the local industry could be at risk) (van Grieken et al. 2011). Reductions in local income may be socially acceptable at the national level but not at the regional or community level. Effective policy instruments will anticipate the social consequences of economic change, for example by identifying effective approaches for buffering affected communities against government-induced economic shocks, for example via applying economic incentives for growers that actively manage river water quality (e.g., tax breaks, compensation, financially supported stewardship programs) or by developing programs to help landholders transition away from unsustainable livelihoods to new livelihoods that are more in concert with environmental requirements (e.g., changing from sugar cropping to tourism). This work makes it clear that the social implications of environmental management strategies need to be well understood if landholder transitions are to be adequately supported in water quality policy frameworks. If the costs to a region of water quality improvement strategies are not well understood, negative consequences could arise for both communities and governments. The costs of protecting the reef through the use of improved land management regimes will be identified through the integration of the EESIP and Coral Bleaching models. The costs or benefits of changes in land management regimes to the local tourism community via enhanced ecological protection will be identified in the ReefDIVE model. Collectively these models have the capacity to identify net costs to the Region (sugar and tourism) of reef protection actions. Cross-sectoral resource issues create a complex policy environment wherein multiple resource values must be managed to achieve maximum benefit for current and prospective generations. Current and future social, environmental, and economic needs and desires are continually traded against each other. These tradeoffs are problematic, because they require benefits and costs to be weighed across diverse and frequently incommensurable values, often under considerable uncertainty. We have developed a conceptual framework that identifies critical information requirements for weighing ecological and economic risks and benefits against each other. Hum. Ecol. Risk Assess. Vol. 18, No. 1, 2012

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The framework is also developed to be functionally pragmatic, that is, capable of being readily operationalized for quantitative risk analysis. However, this holistic view of the system raises additional questions, such as whether or not the risk–benefit tradeoffs for any specific reef condition target are equally distributed across industries, or if these tradeoffs produce a net benefit to the catchment community as a whole. By addressing economic tradeoffs for ecological outcomes for whole catchments/regions rather than on an industry-by-industry basis, the chances of developing effective and socially acceptable policies will improve.

ACKNOWLEDGMENTS This research was funded by the Marine and Tropical Science Research Facility and the CSIRO Water for a Healthy Country National Research Flagship. For their valuable experience, insights, and observations, we thank Daniel Gschwind, Gianna Moscardo, Ali Coghlan, Terry Done, Peter Roebeling, Julian Caley, David Souter, Col McKenzie, Lisha Mulqueeny, Alistair Birtles, Ingrid van Putten, Martijn van Grieken, and Bruce Prideaux. Sincere thanks also go to Nick Webb, Lynise Wearne, and Peter Bayliss for helpful comments on an earlier draft and to Brett Abbot and Caroline Bruce for amending the map.

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