Coastal seagrass habitat suitability model (wet and dry season) in the Great Barrier Reef World Heritage Area (MTSRF, JCU)

Brief description

This dataset is consists of modelled habitat suitability of coastal seagrass distribution in the wet and dry seasons along the Great Barrier Reef World Heritage Area coastline. A Bayesian belief network was used to quantify the relationship (dependencies) between seagrass and eight environmental drivers: relative wave exposure, bathymetry, spatial extent of flood plumes, season, substrate, region, tidal range and sea surface temperature. We found that at the scale of the entire GBRWHA, the main drivers of inshore seagrass presence are tidal range and relative exposure. The outputs of our analysis included a probabilistic GIS-surface of inshore seagrass presence and distribution for both the wet and dry seasons, and across four regions at the scale of 2km*2km planning units. The model can be used by managers in the GBRWHA to delineate seagrass ecological units, and assist them in marine planning at broad spatial scales. For more information about methods see: Grech, A. and Coles, R.J. 2010, An ecosystem-scale predictive model of coastal seagrass distribution, Aquatic Conservation: Marine and Freshwater Ecosystems 20: 437-444 Data Location: This dataset is filed in the eAtlas enduring data repository at: data\MTSRF\QLD_MTSRF-1-1-3_JCU_Grech-A_Seagrass-coastal-model-2007

Lineage

Statement: This dataset was developed as part of a Alana Grech's PhD: "Spatial models and risk assessments to inform marine planning at ecosystem-scales: seagrasses and dugongs as a case study", James Cook University, 2009.

Notes

Purpose
Ecosystem-scale networks of marine protected areas (MPA) are an important planning tool, but the information used to delineate ecological units is difficult to quantify at broad spatial scales because of the cost associated with collecting information at that scale. The Great Barrier Reef World Heritage Area (GBRWHA) is the world’s largest World Heritage area (approximately 348,000 km2) and second largest MPA. To inform the management of inshore (<15 m) seagrass communities at the scale of the entire GBRWHA, we determined their presence and distribution at a regional and sub- regional scale by generating a GIS-based habitat model.