Program 1: Regioanl Environmental Status

(Program Leader: Dr T Done, AIMS)

Objective

To develop the understanding of regional environmental status, events and processes necessary to minimise and solve problems associated with increasing use and impacts on the Great Barrier Reef Marine Park. The six projects in this Program characterise the pattern, status and trends in the environment, and on the status and sustainability of key ecological systems - especially coral reefs, seagrass meadows and pelagic systems. Achievement of Program objectives is demonstrated through good rates of output in scientific journals, CRC Technical Reports, commissioned reports and contributions to books and special editions of journals targeted at resource managers and policy makers. Program members made major contributions to international, national and local conferences, and the Program's work was the focus of a well-received presentation to the 15th meeting of the Prime Minister's Science and Engineering Council. Task researchers continue to provide briefings and research input to Reef managers and industry.

The Program's strategy involves the following range of activities:

1. Survey and monitoring - to provide information about status and trends in natural systems (water quality, reefs, seagrass areas, sediments) at strategic locations.

2. Studies and modelling of pattern and process - from physiological to ecological, stratigraphic, sedimentological, oceanographic and climatological - as the basis for historical reconstruction of human impacts on the environment, and prediction of status and trends in organisms to ecosystems.

3. Management-oriented modelling to combine results of survey and monitoring with understanding of pattern and process, in order to:-

   • interpolate status and threats beyond monitored locations
   • forecast and hindcast over appropriate time scales
   • provide `best estimate' assessments of ecosystem status and threats based on data and models.

4. Sensitivity analyses - to quantify the limitations of the `best estimate' assessments in light of deficiencies in data, understanding and models.

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