Spatial vulnerability assessment of anchor damage within the Great Barrier Reef World Heritage Area, Australia

The coral reefs and seagrass habitats in the Great Barrier Reef World Heritage Area (GBRWHA) are vulnerable to physical disturbances, including the anchoring of vessels. Both the anchor being deployed and retrieved, as well as the movement of the attaching rode, can cause damage to corals and seagrasses. Understanding the contributing processes that influence the deployment of anchors can assist with managing anchor damage in the GBRWHA, particularly in the context of climate change. Providing a spatial description of the vulnerability, rather than just a list of factors, requires the incorporation of social, geophysical and ecological factors. An integrated GIS-Bayesian Belief Network was utilised to combine 19 spatial datasets, 6 spatial models and expert opinion. The base scale was set to match the 250 m lattice interval of the Great Barrier Reef digital elevation model. With approximately 5 million data points the model was able to spatially describe the likelihood of damage from anchor deployment across the GBRWHA. While only 19% of the GBRWHA is considered susceptible to anchor damage, the assessment indicates that coral reefs and seagrass meadows adjacent to population centres and in particular close to islands are highly vulnerable. Comparisons with coral reef health surveys (Eye on the Reef Program) and detailed anchorage records from a scientific research vessel indicate the model is robust despite extensive use of disparate spatial data and expert opinion. The effect of each node in the Bayesian Belief Network on the anchor vulnerability beliefs was measured by standard variance reduction and this found that anchor site familiarity and accessibility were the dominant influences aside from the presence of sensitive habitat. Visualisation of the model outputs, including the intermediate stages, provided additional qualitative evaluation. Enhancing the vulnerability assessment to describe every location in the GBRWHA will contribute to the development of policy and governance mechanisms whilst supporting focused monitoring of sites vulnerable to anchor damage.

[1]  Peter T. Harris,et al.  Submerged banks in the Great Barrier Reef, Australia, greatly increase available coral reef habitat , 2013 .

[2]  S. Banks,et al.  Latitudinal variation in coral communities in eastern Australia: a qualitative biophysical model of factors regulating coral reefs , 2002, Coral Reefs.

[3]  M. Rasheed,et al.  Evaluating risk to seagrasses in the Tropical Indo-Pacific Region , 2012 .

[4]  M. Milazzo,et al.  Short-term response of the slow growing seagrass Posidonia oceanica to simulated anchor impact. , 2007, Marine environmental research.

[5]  Núria Marbà,et al.  Boat anchoring impacts coastal populations of the pen shell, the largest bivalve in the Mediterranean , 2013 .

[6]  R. Cole,et al.  Biological impacts of boating at Kawau Island, north-eastern New Zealand , 2000 .

[7]  Giulia Ceccherelli,et al.  Boat anchoring on Posidonia oceanica beds in a marine protected area (Italy, western Mediterranean): effect of anchor types in different anchoring stages , 2004 .

[8]  P. Marshall,et al.  Building resilience into practical conservation: identifying local management responses to global climate change in the southern Great Barrier Reef , 2010, Coral Reefs.

[9]  B. Willis,et al.  Developments in understanding relationships between environmental conditions and coral disease , 2012 .

[10]  Mark E. Borsuk,et al.  A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis , 2004 .

[11]  R. Grosberg,et al.  Climate Change, Human Impacts, and the Resilience of Coral Reefs , 2003, Science.

[12]  Robert A. Johnson,et al.  Development of a collaborative science plan to evaluate the conservation efficacy of a no-fishing, no-anchor marine reserve in Dry Tortugas National Park, Florida, USA , 2013 .

[13]  Jon Brodie,et al.  A critical review of environmental management of the 'not so Great' Barrier Reef , 2012 .

[14]  C. S. Holling,et al.  Resilience, Adaptability and Transformability in Social–ecological Systems , 2004 .

[15]  K. R. Hayes,et al.  How believable is your BBN , 2009 .

[16]  T. Done,et al.  Decadal trends in a coral community and evidence of changed disturbance regime , 2008, Coral Reefs.

[17]  Olli Varis,et al.  A Belief Network Approach to Optimization and Parameter Estimation: Application to Resource and Environmental Management , 1998, Artif. Intell..

[18]  J. Terrados,et al.  Modeling the influence of attitudes and beliefs on recreational boaters' use of buoys in the Balearic Islands , 2013 .

[19]  Päivi Elisabet Haapasaari,et al.  Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon , 2011 .

[20]  J. Creed,et al.  Disturbance and recovery of the macroflora of a seagrass (Halodule wrightii Ascherson) meadow in the Abrolhos Marine National Park, Brazil: an experimental evaluation of anchor damage , 1999 .

[21]  B. Willis,et al.  Epidemiology of skeletal eroding band on the Great Barrier Reef and the role of injury in the initiation of this widespread coral disease , 2008, Coral Reefs.

[22]  M. Stachowitsch.  Coral Reef Restoration Handbook , 2008 .

[23]  J. Kool,et al.  Coral reef recovery dynamics in a changing world , 2011, Coral Reefs.

[24]  J. Veron.  Mass extinctions and ocean acidification: biological constraints on geological dilemmas , 2008, Coral Reefs.

[25]  G. Schmahl,et al.  Science-based design of coral protected areas in the Gulf of Mexico , 2012 .

[26]  Glenn De'ath,et al.  Declining Coral Calcification on the Great Barrier Reef , 2009, Science.

[27]  P. Mumby,et al.  Global disparity in the resilience of coral reefs. , 2012, Trends in ecology & evolution.

[28]  T. Bridge,et al.  Mesophotic coral reef ecosystems in the Great Barrier Reef World Heritage Area , 2012 .

[29]  A. GRECHa,et al.  An ecosystem-scale predictive model of coastal seagrass distribution , 2010 .

[30]  G. De’ath,et al.  Water quality of the Great Barrier Reef: distributions, effects on reef biota and trigger values for the protection of ecosystem health , 2008 .

[31]  V Stelzenmüller,et al.  Assessment of a Bayesian Belief Network-GIS framework as a practical tool to support marine planning. , 2010, Marine pollution bulletin.

[32]  G. E. Davis.  Anchor damage to a coral reef on the coast of Florida , 1977 .

[33]  W. Jaap.  Coral reef restoration , 2000 .

[34]  C. Rogers,et al.  Ten years after the crime: Lasting effects of damage from a cruise ship anchor on a coral reef in St. John, U.S. Virgin Islands , 2001 .

[35]  P. Marshall,et al.  No-anchoring areas reduce coral damage in an effort to build resilience in Keppel Bay, southern Great Barrier Reef , 2014 .

[36]  B. Marcot,et al.  Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement , 2001 .

[37]  S. Jameson,et al.  A coral damage index and its application to diving sites in the Egyptian Red Sea , 1999, Coral Reefs.

[38]  P. Bongaerts,et al.  The role of deep reefs in shallow reef recovery: an assessment of vertical connectivity in a brooding coral from west and east Australia , 2011, Molecular ecology.

[39]  D. Dupont.  Not so great , 2009 .

[40]  Elizabeth A Dinsdale,et al.  Assessing Anchor Damage on Coral Reefs: A Case Study in Selection of Environmental Indicators , 2004, Environmental management.

[41]  Janice M. Lough,et al.  Climate change and the Great Barrier Reef: A vulnerability assessment , 2007 .

[42]  J. Mcmanus,et al.  Effects of Some Destructive Fishing Methods on Coral Cover and Potential Rates of Recovery , 1997, Environmental management.

[43]  G. De’ath,et al.  The 27–year decline of coral cover on the Great Barrier Reef and its causes , 2012, Proceedings of the National Academy of Sciences.

[44]  B. Marcot,et al.  Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation , 2006 .

[45]  R. Mitchell.  Great Barrier Reef Marine Park Authority—Annual report 1980/81 , 1982 .

[46]  D. Gilliam,et al.  Dredging and Shipping Impacts on Southeast Florida Coral Reefs , 2012 .

[47]  M. Gooch,et al.  Assessing community resilience to climate change , 2012 .

[48]  Wisdom M. Dlamini,et al.  A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland , 2010, Environ. Model. Softw..

[49]  J. Choat,et al.  Abundance patterns of reef sharks and predatory fishes on differently zoned reefs in the offshore Townsville region final report to the Great Barrier Reef Marine Park Authority , 2008 .

[50]  J. Day,et al.  Effective governance of a large and complex cross-jurisdictional marine protected area: Australia's Great Barrier Reef , 2013 .

[51]  Dsewpc.  Great Barrier Reef Marine Park Zoning Plan 2003 , 2005 .

[52]  C. D. Kemp,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[53]  Christina C. Hicks,et al.  A social–ecological approach to conservation planning: embedding social considerations , 2013 .

[54]  Helene Marsh,et al.  A broad-scale assessment of the risk to coastal seagrasses from cumulative threats , 2011 .