For continental shelf reef habitat the base-case parameters for the habitat equations were determined by least squares optimization. The Simplex method of minimising the sum of squares was used to fit the model to the benthos observations, with some parameters constrained to a biologically meaningful range. For the seagrass, macroalgae and mangrove habitats there was considerably less information available from which to estimate madel parameters. For these habitats the base-case parameters for the habitat equations were determined from expert information and heuristic fitting to available data on historical cover and distributions. The pessimistic and optimistic parameterisations were determined by considering the extremes of the relevant parameters in the literature and by exploring the dynamics of the system in the parameter space around the base case results. The pessimistic parameters were selected so that the impact of disturbances on the habitat groups was stronger than in the base case and the rate of recovery was slower. Conversely, in the optimistic specification, the parameters were selected so that impacts were smaller and the rate of recovery faster. However, the parameter selection was constrained such that the resulting habitat cover predictions were plausible given the available data sets and expert opinion on historical and present habitat cover. Where statistical methods could be applied the 80% confidence interval was used to identify the optimistic and pessimistic bounds. The optimistic and pessimistic bounds were much wider for the seagrass, macroaglae and mangrove habitats than for the continental shelf habitats, because of the different quantity and quality of the information available.

Distribution and size frequency patterns of sessile organisms such as sponges may vary among and within neighbouring reefs. In this study, we examine small scale variation of dictyoceratid sponges (class Demospongiae), commonly found on coral reefs, by surveying six neighbouring islands in central Torres Strait. Each island had four study sites, at least 1 km apart, with each site consisting of three shallow (4-6 m) and three deep (10-15 m) 20 m2 transects. For each transect, we recorded the number of each species and measured the size of the more common dictyoceratid sponges. Seven species of dictyoceratid were recorded in central Torres Strait, with only three species, Coscinoderma sp., Dysidea herbacea and Hyrtios erecta, common to all six islands. Abundance patterns generally varied greatly among islands or sites within islands, perhaps resulting from a combination of physical, biological and stochastic factors. More dictyoceratids were found in deeper water, although abundance across depth for some species varied among islands or sites. Size frequency distribution patterns also varied greatly among islands and between dictyoceratid species, indicating that factors that may promote growth for one species may not necessarily promote growth for a related species. This study shows that patterns of abundance and size of dictyoceratids can vary greatly over small spatial scales and that patterns are species specific.

Spatial variability in community structure of dictyoceratid sponges (Class Demospongiae; Order Dictyoceratida) was examined on coral reefs in Torres Strait, an archipelago of islands and reefs between northern Queensland, Australia, and Papua New Guinea. Dictyoceratid sponge abundances and environmental parameters were recorded at 4 locations, separated by 50-220 km. Each location was subdivided into 5-7 sites, each ≥2 km apart. At each site four 50x2 m belt transects were quantitatively surveyed, recording dictyoceratid numbers, substrate type (rock, rubble and sand), water clarity, degree of reef slope and depth. Dictyoceratid abundance was similar among locations, averaging 15.5 individuals per 100 m2, but varied significantly among sites. Twenty three dictyoceratid species were recorded in Torres Strait, with approximately half (12/23) found in only one location. Canonical Correspondence Analysis determined that the measured environmental factors explained only 26% of the spatial variation. Cluster analysis revealed a complex dictyoceratid community structure with consistent patterns among neighbouring sites and among sites separated by hundreds of kilometres. Conversely the dictyoceratid community could vary greatly between neighbouring sites 2 km apart and on the same reef complex. The results of this study suggest that spatial variability of dictyoceratid sponges in Torres Strait is influenced by a combination of environmental, biological and stochastic processes.

Human behaviour and the impact of human activities on the marine environment were represented in the MSE using a combination of analytical decision models, response functions, specified rules and scenarios, and input data. These are detailed in Fulton, et al.(2006)

This dataset contains information on closures collected from various NPF Management meetings, from the 1970's to 2004 (see below). Information was collected on why closures were proposed, evidence presented, and reasons why the proposals were accepted, rejected or modified. Emphasis is placed on obtaining information on why a closure was instigated, and the reasons why closures undergo subsequent modification. Scientific research carried out within or near each closures is also listed. Data were collected for closures that already existed at the time of database creation (2004), and it is planned that data collection will be ongoing, subject to funding and personnel availability. The data collected is linked to an existing GIS database containing spatial information on gazetted closures. Data sources for the historical review included: NORPAC/ NORMAC agendas and minutes, 1982 - 2004; Northern Fisheries Council documentation; Closures Task Force /Closure Committee minutes; Departmental Correspondence; Government Gazettes; AFMA NPF Directions; NPF publications (e.g. Pownall, 1994); Meeting notes kept by some research representatives on the above committees. The project objectives were: a. Identify the reasons for the designation of each closure and any information from research surveys that are available to evaluate the reasoning (including instances where no information exists). b. Develop agreed criteria to classify the different types of closures in the fishery. c. Develop and document protocols and criteria to be used to review (change or remove) an existing closure. d. Develop and document protocols and criteria to be used to establish new closures in the fishery. e. Provide Industry with succinct information that allows the consideration of the implementation, success and future advantage of the current closures.

Bathurst Harbour and Macquarie Harbour are estuarine systems on the west coast of Tasmania, Australia. While Macquarie Harbour is grossly polluted from mine operations via contamination of the King River, Bathurst Harbour is surrounded by World Heritage wilderness and is essentially free of anthropogenic influences. The vegetation of the catchments of both harbours is similar and the waters of both harbours are deep brown due to the presence of humic substances. A hydrographic survey of the pristine Bathurst Harbour estuarine system was carried out over 4 days in January/February of 1990 (Austral Summer). Sampling and laboratory analyses for a range of trace elements (Cd, Co, Cu, Fe, Mn, Ni, and Zn) were made using non-contaminating procedures.

Bathurst Harbour and Macquarie Harbour are estuarine systems on the west coast of Tasmania, Australia. While Macquarie Harbour is grossly polluted from mine operations via contamination of the King River, Bathurst Harbour is surrounded by World Heritage wilderness and is essentially free of anthropogenic influences. The vegetation of the catchments of both harbours is similar and the waters of both harbours are deep brown due to the presence of humic substances. A hydrographic survey of the pristine Bathurst Harbour estuarine system was carried out over 4 days in January/February of 1990 (Austral Summer). Sampling and laboratory analyses for a range of trace elements (Cd, Co, Cu, Fe, Mn, Ni, and Zn) were made using non-contaminating procedures. Comparison of results from this survey, with those from Macquarie Harbour in the summer of 1989, provided a clearer assessment of the effects of mining operations on trace metal concentrations in Macquarie Harbour.