Submarine canyons have been recognised as areas of significant ecological and conservation value for their enhanced primary productivity, benthic biomass and biodiversity. In Australia, 753 submarine canyons were mapped on all margins of the continent by the Marine Biodiversity Hub through the Australian Government's National Environmental Research Program. An analysis of canyon geomorphic metrics provided the basis to objectively classify these canyons across a hierarchy of physical characteristics (e.g. volume, depth range, rugosity) separately for shelf-incising and slope-confined canyons (Huang et al., 2014). Here we extend this analysis to include oceanographic variables in presenting a first pass assessment of habitat quality for all canyons on the Australian margin, with a focus on their upper reaches. This study is based on the premise that habitat heterogeneity, productivity and disturbance are the three factors that potentially determine the quality of a canyon habitat. For each factor we derived a range of variables to inform the assessment of habitat quality (see Table). Habitat heterogeneity was measured using a selection of eight geomorphic metrics including canyon volume and rugosity that are considered likely to have a positive relationship with habitat heterogeneity. Canyon productivity was assessed from five variables including: distance to the shelf break as a proxy of nutrient inputs from land and the continental shelf; bottom current speed as an indicator of nutrient supply to benthic epifauna (derived from time-series re-analysis of the BLUElink oceanographic model and in-situ data), and; measures of the probability, frequency and intensity of upwelling (also from BLUElink data). The BLUElink variables have positive relationships with productivity whereas the relationship between distance to shelf and productivity is negative. Benthic disturbance was assessed from the maximum and range of bottom current speeds, and the frequency and intensity of tropical cyclones. According to these relationships, individual canyons were assigned habitat quality scores, first separately for each variable and then aggregated for the three habitat factors. The final scores were obtained by averaging the scores of the three habitat factors. The results show that many submarine canyons on the eastern Australian margin have high habitat quality scores (see Figure). This is interpreted to be mainly due to the influence of the upwelling-favourable East Australian Current which generates high productivity throughout the year. The Albany canyons on the south-western margin also offer high habitat quality for marine species due to complex geometrical and geophysical structures. They also benefit from the upwelling-favourable Flinders Current. In contrast, canyons on the northern and western margins have lower habitat quality. Many of these canyons receive little input from land and continental shelf. In addition, the downwelling- favourable Leeuwin Current, which flows along the western margin of the continent, hampers the supply of deep water nutrients from reaching the upper reaches of canyons, particularly canyon heads that intersect the euphotic zone. Overall, these results provide a framework for targeted studies of canyons aimed at testing and verifying the habitat potential identified here and for establishing monitoring priorities for the ongoing management of canyon ecosystems.

Marine organisms are exposed not only to natural environmental stressors, but also the additional effects of anthropogenic stressors, notably increasing temperatures and reduced pH. Early life stages of marine organisms have been recognised as potentially vulnerable to the stressors associated with climate change and ocean acidification, but identifying patterns across studies, species and a range of response variables is challenging. This study is supported by the Marine Biodiversity Hub through the National Environmental Research Program and identifies knowledge gaps in research on multiple abiotic stressors and early life stage (embryo to larvae), while quantifying interactions based on life history. Temperature was the most common stressor (91% of studies), while the most common combination of stressors was temperature and salinity (66%), followed by temperature and pH (17.5%). All studies were conducted in the laboratory although four studies also undertook field experiments. Synergistic interactions (68% of individual tests) were more common than additive (16%) or antagonistic (16%) interactions. The meta-analysis yielded several key results: 1) Embryos are not more vulnerable to stress than larvae in combined stressor treatments. 2) Sub-lethal responses are not more likely to be affected by stress than lethal responses. 3) Interaction types vary among stressors, phyla, ontogenetic stages, and biological responses. 4) Elevated temperature is generally a greater stressor than ocean acidification, but this depends on ontogenetic stage and phylum. 5) Ocean acidification is a greater stressor for calcifying than non-calcifying larvae. Our findings will assist in monitoring and predicting the health of marine populations and communities by identifying sensitive and robust taxa.

A fully four-dimensional (3D x time) object-oriented biophysical dispersal model was developed to simulate the movement of marine larvae over semi-continuous surfaces. The model is capable of handling massive numbers of simulated larvae, can accommodate diverse life history patterns and distributions of characteristics, and saves point-level information to a relational database management system.

Promotional magnetic panel produced for the conference booth to be used at seabed mapping conferences. The panel highlights research conducted by Geoscience Australia in mapping and modelling processes that occur in Australian submarine canyons under the National Enrvironmental Research Program.

Population connectivity science involves investigating how populations are related to one another through biological dispersal. Here, we review tools, techniques and analyses used by connectivity researchers, and place them in the context of how they can be used by marine managers and policy-makers to enhance their decision-making capabilities. Specific examples of developing technologies include: advances in mark and recapture techniques, underwater imaging systems, population genetic analyses, as well as four-dimensional dispersal simulations (3D space x time). These data can then be analysed using a wide array of analyses, including matrix analysis, graph theory, and various GIS-based routines. The results can be used to identify key source and sink areas, critical linkages (keystones), natural clusters and groups, levels of accuracy, precision and variability, as well as areas of asymmetric exchange. In turn, this information can be used to help identify natural management units, to target critical conservation areas, to develop efficient sampling strategies through power analysis, and to negotiate equitable allocation of resources to upstream management in cases where downstream benefits are significant. Through a better understanding of how connectivity science can assist decision-making, we hope to encourage increased uptake of these kinds of information into institutional planning processes.

This report provides details of activities undertaken by the Australian Institute of Marine Science (AIMS), Geoscience Australia, the University of Western Australia and the Museum and Art Gallery of the Northern Territory during a marine biodiversity survey to the Oceanic Shoals Commonwealth Marine Reserve (Timor Sea) in 2012. The survey was an activity within the Australian Government's National Environmental Research Program Marine Biodiversity Hub and is a key component of Theme 4 - Regional Biodiversity Discovery to Support Marine Bioregional Plans. Data collected during the survey will be used to support research being undertaken in other Themes of the Marine Biodiversity Hub, including the modelling of ecosystem processes for the northern region, and to support the work programs of the Department of Environment.

The datasets measure the K490 parameter (Downwelling diffuse attenuation coefficient at 490 nm, a turbidity parameter) of Australian oceans. They are derived products from MODIS (aqua) images using NASA's SeaDAS image processing software. The extent of the datasets covers the entire Australian EEZ and surrounding waters (including the southern ocean). The spatial resolution of the datasets is 0.01 dd. The datasets contain 36 monthly k490 layers between 2009 and 2011. The unit of the datasets is 1/m.

The datasets measure the Sea Surface Temperature (SST) of Australian oceans. They are derived products from MODIS (aqua) images using NASA's SeaDAS image processing software. The extent of the datasets covers the entire Australian EEZ and surrounding waters (including the southern ocean). The spatial resolution of the datasets is 0.01 dd. The datasets contain 126 monthly SST layers between 2002 and 2012.

Seafloor bathymetric data and its derivatives fulfil a range of applications that are relevant to supporting the management of marine ecosystems and can provide a potentially powerful physical surrogate for benthic biodiversity. Similarly, morphological and seafloor terrain variables such as slope, curvature and rugosity derived from bathymetry data through GIS analysis not only describe seabed morphology but can also act as proxies for oceanographic processes The distributions of benthic marine fauna and flora most commonly respond to local changes in the topography of the seafloor. When seafloor topography is coupled with biological surveys it can help managers understand which environments contribute most to the growth, reproduction and survival of marine species. These models of habitat suitability provide natural resource managers with a tool with which to visualise the potential habitats of particular species. The accuracy of the habitat suitability models however, is critically reliant on the accuracy of underlying bathymetric data. The uncertainty in the bathymetric data is often ignored and often there is little recognition that the input bathymetric data and the derived spatial data products of the bathymetric data are merely modelled representations of one reality. These models can contain significant levels of uncertainty that are dependent upon the original depth measurements. This research paper explores a method to represent the uncertainty in bathymetric data. We discover that multibeam bathymetry data uncertainties are stochastic at individual soundings but exhibit a distinct spatial distribution with increasing magnitude from nadir to outer beams. We find that the restricted spatial randomness method is able to realistically simulate both the stochastic and spatial characteristics of the data uncertainty. This research concludes that the Monte Carlo method is appropriate for the uncertainty analysis of GIS operations and although the multibeam bathymetry data have notable overall uncertainty level, its impact on subsequent derivative analysis is likely to be minor in this dataset at the 2 m scale. Monitoring and change detection of the seafloor requires detailed baseline data with uncertainty estimates to ensure that features that display change are reliably detected. The accuracy of marine habitat maps and their associated levels of uncertainty are extremely hard to convey visually or to quantify with existing methodologies. The new techniques developed in this research integrate existing statistical techniques in a novel way to improve insights into classification and related uncertainty for seabed habitat maps which will progress and improve resource management for regional and national ocean policy.

As the oceans simultaneously warm and acidify, prospects for marine biota are of growing concern. In addition to these global change stressors, marine organisms are also exposed to many other anthropogenic stressors with likely interactive effects, including synergisms in which the combined effects of multiple stressors are greater than the sum of individual effects. Early life stages of marine organisms have been recognised as potentially vulnerable to the stressors associated with global change, but identifying patterns across studies, species and a range of response variables is challenging. In this study, we identify knowledge gaps in research on multiple abiotic stressors and early life stages (embryo to larvae), and we perform a meta-analysis to quantify stressor interactions on early life history stages of marine invertebrates, specifically between temperature, salinity and pH as these are the best studied. Temperature was the most common stressor (91% of studies), while the most common combination of stressors was temperature and salinity (66%), followed by temperature and pH (17.5%). All studies were conducted in the laboratory although four studies also undertook field experiments. Synergistic interactions (68% of individual tests) were more common than additive (16%) or antagonistic (16%) interactions. The meta-analysis yielded several key results: 1) Temperature and salinity synergistically interacted to negatively affect marine embryos and larvae, while temperature and pH antagonistically interact. 2) Embryos are more vulnerable than larvae to thermal and salinity stress but not to pH stress. 3) Survival is less likely to be affected than sub-lethal responses in stress treatments incorporating pH, but there is no discernible pattern in temperature, salinity, and temperature/salinity treatments. 4) Interaction types vary among stressors, phyla, ontogenetic stages, and biological responses. 5) Elevated temperature is generally not a greater stressor than ocean acidification and salinity, but this depends on ontogenetic stage and phylum 6) Ocean acidification is a greater stressor for calcifying than non-calcifying embryos and larvae. We use these results to identify organisms that may be particularly vulnerable or robust to stress associated with temperature, pH, and salinity. Although several clear patterns have emerged from this review and meta-analysis, the challenge now is to develop recommendations for stress ecology experiments in order to facilitate inter-study comparisons, as well as to translate these results to the field.