This dataset contains the sea surface temperature data derived from the MODIS Terra sensor, the chlorophyll data derived from the SeaWIFS satellite, and the K490 data derived from the SeaWIFS satellite. Ocean temperature is a useful indicator of the type of marine life that could be found at a particular location. Many marine plants and organisms have a relatively narrow range of tolerance for temperature, and will either perish or be out-competed where temperatures are outside their comfort zone. Chlorophyll a is a plant pigment which provides a measurement of the biomass (or quantity) of plants. In the water column, it is a measure of the suspended (or planktonic) biomass of single-celled microscopic plants. Chlorophyll is a commonly used measure of water quality. K490 indicates the turbidity of the water column; the depth to which the visible light in the blue-green region of the spectrum penetrates the water column. It is directly related to the presence of particles in the water column. Turbidity has consequences for benthic marine life, ranging from the availability of light to the quantity of nutrients in the water column. The datasets contain 6 grids. Two for each variable: mean and standard deviation. Please see the metadata for detailed information.

Monitoring changes in the spatial distribution and health of biotic habitats requires spatially extensive surveys repeated through time. Although a number of habitat distribution mapping methods have been successful in clear, shallow-water coastal environments (e.g. aerial photography and Landsat imagery) and deeper (e.g. multibeam and sidescan sonar) marine environments, these methods fail in highly turbid and shallow environments such as many estuarine ecosystems. To map, model and predict key biotic habitats (seagrasses, green and red macroalgae, polychaete mounds [Ficopamatus enigmaticus] and mussel clumps [Mytilus edulis]) across a range of open and closed estuarine systems on the south-west coast of Western Australia, we integrated post-processed underwater video data with interpolated physical and spatial variables using Random Forest models. Predictive models and associated standard deviation maps were developed from fine-scale habitat cover data. Models performed well for spatial predictions of benthic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality parameters. The results of this study refine existing baseline maps of estuarine habitats and highlight the importance of biophysical processes driving plant and invertebrate species distribution within estuarine ecosystems. This study also shows that machine-learning techniques, now commonly used in terrestrial systems, also have important applications in coastal marine ecosystems. When applied to video data, these techniques provide a valuable approach to mapping and managing ecosystems that are too turbid for optical methods or too shallow for acoustic methods.

The characterisation of benthic habitats based on their abiotic (physical and chemical) attributes remains poorly defined in the marine environment, but is becoming increasingly central in the development of marine management plans in Australia and elsewhere in the world. The current study tested this link between physical and biological datasets for the southern Gulf of Carpentaria, Australia. The results presented were based on a range of physical factors, including the sediment composition (grain size and carbonate content), sediment mobility, water depth and organic carbon flux, and their relationship to the distribution and diversity of benthic macrofauna was tested. The results reveal the importance of process-based indices, such as sediment mobility, in addition to other environmental factors in defining the distribution of the benthic macrofauna. The distribution of the benthic macrofauna changes gradationally across the south-eastern Gulf, associated with changes in the per cent mud and gravel, the seabed exposure and the water depth. Patterns of diversity also reveal the importance of physical processes such as sediment mobility in defining benthic habitats. The species' environment relationships observed at the small scale of the current study are consistent with broader associations observed for other organisms within the Gulf.

A number of terms used in this book are derived from the fields of biogeography and benthic ecology and these are defined in the glossary; the reader is also referred to the works cited at the end of this chapter for further information. Many of the case studies presented in this book refer to habitat classification schemes that have been developed based on principles of biogeography and ecology. For these reasons a brief overview is provided here to explain the concepts of biodiversity, biogeography and benthic ecology that are most relevant to habitat mapping and classification. Of particular relevance is that these concepts underpin classification schemes employed by GeoHab scientists in mapping habitats and other bioregions. A selection of published schemes, from both deep and shallow water environments, are reviewed and their similarities and differences are examined.

In ecology, a common form of statistical analysis relates a biological variable to variables that delineate the physical environment, typically by fitting a regression model or one of its extensions. Unfortunately, the biological data and the physical data are frequently obtained from eparate sources of data. In such cases there is no guarantee that the biological and physical data are co-located and the regression model cannot be used. A common and pragmatic solution is to predict the physical variables at the locations of the biological variables and then to use the predictions as if they were observations.We show that this procedure can cause potentially misleading inferences and we use generalized linear models as an example. We propose a Berkson error model which overcomes the limitations. The differences between using predicted covariates and the Berkson error model are illustrated by using data from the marine environment, and a simulation study based on these data.

The Carnarvon shelf at Point Cloates, Western Australia, is characterised by a series of prominent ridges and hundreds of mounds that provide hardground habitat for coral and sponge gardens. The largest ridge is 20 m high, extends 15 km alongshore in 60 m water depth and is interpreted as a drowned fringing reef. To landward, smaller ridges up to 1.5 km long and 16 m high are aligned to the north-northeast and are interpreted as relict aeolian dunes. Mounds are less than 5 m high and may also have a sub-aerial origin. In contrast, the surrounding seafloor is sandy with relatively low densities of epibenthic organisms. The dune ridges are estimated to be Late Pleistocene in age and their preservation is attributed to cementation of calcareous sands to form aeolianite, prior to the postglacial marine transgression. On the outer shelf, sponges grow on isolated low profile ridges at ~85 m and 105 m depth and are also interpreted as partially preserved relict shorelines.

The East Antarctic continental shelf has had very few studies examining the macrobenthos structure or relating biological communities to the abiotic environment. In this study, we apply a hierarchical method of benthic habitat mapping to Geomorphic Unit and Biotope levels at the local (10s of kilometers) scale across the George V Shelf between longitudes 1421E and 1461E. We conducted a multi-disciplinary analysis of seismic profiles, multibeam sonar, oceanographic data and the results of sediment sampling to define geomorphology, surficial sediment and near-seabed water mass boundaries.

The Oceanic Shoals Commonwealth Marine Reserve (CMR) (>71,000 km2) is located in the Timor Sea and is part of the National Representative System of Marine Protected Areas of Australia. The Reserve incorporates extensive areas of carbonate banks and terraces that are recognised in the North and North West Marine Region Management Plans as Key Ecological Features (KEFs). Although poorly studied, these features have been identified as potential biodiversity hotspots for the Australian tropical north. As part of the National Environment Research Program (NERP), Geoscience Australia (GA) in collaboration with the Australian Institute of Marine Sciences (AIMS) undertook a marine biodiversity survey in 2012 to improve the knowledge of this area and better understand the importance of these KEFs. Amongst the many activities undertaken, continuous high-resolution multibeam mapping, video and still camera observations, and physical seabed sampling of four areas covering 510 km2 within the western side of the CMR was completed. Multibeam imagery reveals a high geomorphic diversity in the Oceanic Shoals CMR, with numerous banks and terraces, elevated 30 to 65 m above the generally flat seabed (~105 m water depth), that provide hard substrate for benthic communities. The surrounding plains are characterised by fields of depressions (pockmarks) formed in soft silty sediments that are generally barren of any epibenthos. A distinctive feature of many pockmarks is a linear scour mark that extends several tens of metres (up to 150 m) from pockmark depressions. Previous numerical and flume tank simulations have shown that scouring of pockmarks occurs in the direction of the dominant near-seabed flow. These geomorphic features may therefore serve as a proxy for local-scale bottom currents, which may in turn inform on sediment processes operating in these areas and contribute to the understanding of the distribution of biodiversity. This study focused on characterising these seabed scoured depressions and investigating their potential as an environmental proxy for habitat studies. The study used ArcGIS spatial analyst tools to quantify the features and explored their potential relationships with other variables (e.g. multibeam backscatter, regional modelled bottom stress, biological abundance and presence/absence) to provide insight into their development, and contribute to a better understanding of the environment surrounding carbonate banks. Preliminary results show a relationship between pockmark types, i.e. with or without scour mark, and backscatter strength. This relationship suggests some additional shallow sub-surface control, mainly related to the presence of buried carbonate bank. In addition, the results suggest that tidal flows are redirected by the banks, leading to locally varied flow directions and 'shadowing' in the lee of the larger banks. This in turn is likely to have an influence on the observed density and abundance of benthic assemblages.

A range of physical descriptors of the seabed can potentially be used as surrogates for defining patterns of benthic marine biodiversity, including bathymetry, geomorphology and sediment type. These variables can be mapped, described and sampled across spatial scales that are of value to the management of the marine estate by providing a template for monitoring benthic ecosystems. As part of a four-year program (2007-2010) funded by the Australian Government, Geoscience Australia led marine surveys designed to collect robust datasets for the analysis of surrogacy relationships between a suite of physical variables and benthic biota in select areas of the Australian continental shelf. This paper focuses on results of the 2008 Carnarvon shelf survey, located within a Commonwealth Marine Park and adjacent to the World Heritage-listed Ningaloo Reef (Western Australia). High resolution multibeam sonar mapping, underwater video and benthic sampling revealed a complex geomorphology of ridges, mounds and sandy bedforms. The largest ridge extends 15 km alongshore is 20 m high and interpreted as a drowned forereef. Smaller ridges are ~1 km long, oriented northeast and preserve the form of aeolian dunes. Mounds are up to 5 m high and form extensive fields surrounded by flat sandy seabed. These ridges and mounds provide hardground habitat for diverse coral and sponge communities, whereas the surrounding sandy seafloor is characterised by few sessile benthic organisms. Multivariate analysis of these relationships is used to develop predictive models of benthic habitats, demonstrating the utility of high resolution physical data for informing management of these ecosystems.

Deep sea environments occupy much of the sea floor, yet little is known about diversity patterns of biological assemblages from these environments. Physical mapping technologies and their availability are increasing rapidly. Sampling deep-sea biota over vast areas of the deep sea, however, is time consuming, difficult, and costly. Consequently, the growing need to manage and conserve marine resources, particularly deep sea areas that are sensitive to anthropogenic disturbance and change, is leading the promotion of physical data as surrogates to predict biological assemblages. However, few studies have directly examined the predictive ability of these surrogates. The physical environment and biological assemblages were surveyed for two adjacent areas - the western flank of Lord Howe Rise (LHR) and the Gifford Guyot - spanning combined water depths of 250 to 2,200 m depth on the northern part of the LHR, in the southern Pacific Ocean. Multibeam acoustic surveys were used to generate large-scale geomorphic classification maps that were superimposed over the study area. Forty two towed-video stations were deployed across the area capturing 32 hours of seabed video, 6,229 still photographs, that generated 3,413 seabed characterisations of physical and biological variables. In addition, sediment and biological samples were collected from 36 stations across the area. The northern Lord Howe Rise was characterised by diverse but sparsely distributed faunas for both the vast soft-sediment environments as well as the discrete rock outcrops. Substratum type and depth were the main variables correlated with benthic assemblage composition. Soft-sediments were characterised by low to moderate levels of bioturbation, while rocky outcrops supported diverse but sparse assemblages of suspension feeding invertebrates, such as cold water corals and sponges which in turn supported epifauna, dominated by ophiuroids and crinoids. While deep environments of the LHR flank .