abiotic surrogates
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Geoscience Australia carried out marine surveys in southeast Tasmania in 2008 and 2009 (GA0315) to map seabed bathymetry and characterise benthic environments through observation of habitats using underwater towed video. Data was acquired using the Tasmania Aquaculture and Fisheries Institute (TAFI) Research Vessel Challenger. Bathymetric mapping was undertaken in seven survey areas, including: Freycinet Pensinula (83 sq km, east coast and shelf); Tasman Peninsula (117 sq km, east coast and shelf); Port Arthur and adjacent open coast (17 sq km); The Friars (41 sq km, south of Bruny Island); lower Huon River estuary (39 sq km); D Entrecastreaux Channel (7 sq km, at Tinderbox north of Bruny Island), and; Maria Island (3 sq km, western side). Video characterisations of the seabed concentrated on areas of bedrock reef and adjacent seabed in all mapped areas, except for D Entrecastreaux Channel and Maria Island. The datasets contains 7 backscatter grids of the south east Tasmania Shelf produced from the processed EM3002 backscatter data of the survey area using the CMST-GA MB Process.
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This study investigated bio-environment relationships in Jervis Bay, a sandy partially enclosed embayment in NSW. Three decision tree models and a robust model selection process were applied to a wide-range of physical data (multibeam bathymetry and backscatter grids and derivatives, parameters that describe seabed sediment and water column physical/geochemical characteristics, seabed exposure) and co-located biological data. The models for selected infaunal species and three diversity indices explained 32-79% of data variance. Patterns of abundance and diversity were statistically related to a wide range of environmental variables, including sediment physical (e.g. mud, CaCO3, gravel) and geochemical properties (e.g. chlorophyll a, total sediment metabolism, total sulphur), seabed morphometric characteristics (e.g. local Moran's I of bathymetry, rugosity), seabed exposure regime and water column light attenuation. The modelled response curves together with results from an earlier habitat mapping study informed the development of a conceptual model that provides a process-based framework for the interpretation of biodiversity patterns in the southern part of the Bay. The conceptual model had three zones which were noted for: (i) fine-sediment resuspension and macroalgae accumulation (leading to anoxia; extreme); (ii) bioturbation (in-between); and (iii) exposure of the seabed to waves (extreme in places). Most bio-environment relationships pointed to complex relationships between multiple biological and physical factors occurring in the different process domains/zones. The combined use of co-located samples and bio-environment and conceptual models enabled a mechanistic understanding of benthic biodiversity patterns in Jervis Bay.
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A growing need to manage marine biodiversity sustainably at local, regional and global scales cannot be met by applying the limited existing biological data. Abiotic surrogates of biodiversity are thus increasingly valuable in filling the gaps in our knowledge of biodiversity patterns, especially identification of hotspots, habitats needed by endangered or commercially valuable species and systems or processes important to the sustained provision of ecosystem services. This review examines the use of abiotic variables as surrogates for patterns in benthic assemblages with particular regard to how variables are tied to processes affecting biodiversity and how easily those variables can be measured at scales relevant to resource management decisions.
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This chapter presents a broad synthesis and overview based on the 57 case studies included in Part 2 of this book, and on questionnaires completed by the authors. The case studies covered areas of seafloor ranging from 0.15 to over 1,000,000 km2 (average of 26,600 km2) and a broad range of geomorphic feature types. The mean depths of the study areas ranged from 8 to 2,375 m, with about half of the studies on the shelf (depth <120 m) and half on the slope and at greater depths. Mapping resolution ranged from 0.1 to 170 m (mean of 13 m). There is a relatively equal distribution of studies among the four naturalness categories: near-pristine (n=17), largely unmodified (n = 16), modified (n=13) and extensively modified (n=10). In terms of threats to habitats, most authors identified fishing (n=46) as the most significant threat, followed by pollution (n=12), oil and gas development (n=7) and aggregate mining (n=7). Anthropogenic climate change was viewed as an immediate threat to benthic habitats by only three authors (n=3). Water depth was found to be the most useful surrogate for benthic communities in the most studies (n=17), followed by substrate/sediment type (n=14), acoustic backscatter (n=12), wave-current exposure (n=10), grain size (n=10), seabed rugosity (n=9) and BPI/TPI (n=8). Water properties (temperature, salinity) and seabed slope are less useful surrogates. A range of analytical methods were used to identify surrogates, with ARC GIS being by far the most popular method (23 out of 44 studies that specified a methodology).
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Demands are being made of the marine environment that threaten to erode the natural, social and economic benefits that human society derives from the oceans. Expanding populations ensure a continuing increase in the variety and complexity of marine based activities - fishing, power generation, tourism, mineral extraction, shipping etc. The two most commonly acknowledged purposes for habitat mapping in the case studies contained in this book are to support government spatial marine planning, management and decision-making and to support and underpin the design of marine protected areas (MPAs; see Ch. 64).
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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.
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Physical and biological characteristics of benthic communities on the George V Shelf have been analysed from underwater camera footage collecting during Aurora Australis voyages in 2007/08 and 2010/11. The 2007/08 data revealed a high degree of variability in the benthic communities across the shelf, with the benthic habitats strongly structured by physical processes. Iceberg scouring recurs over timescales of years to centuries along shallower parts of this shelf, creating communities in various stages of maturity and recolonisation. Upwelling of modified circumpolar deep water (MCDW) onto the outer shelf and cross-shelf flow of high salinity shelf water (HSSW) create spatial contrasts in nutrient and sediment supply, which are largely reflected in the distribution of deposit and filter feeding communities. Long term cycles in the advance and retreat of icesheets (over millennial scales) and subsequent focussing of sediments in troughs such as the Mertz Drift create patches of consolidated and soft sediments, which also provide distinct habitats for colonisation by different biota. These interacting physical processes of iceberg scouring, current regimes and depositional environments, in addition to water depth, are important factors in the structure of benthic communities across the George V Shelf. In February 2010, iceberg B09B collided with the Mertz Glacier Tongue, removing about 80% or 78km from the protruding tongue. This event provided a rare opportunity to access a region previously covered by the glacier tongue, as well as regions to the east where dense fast ice has built up over decades, restricting access. The 2010/11 voyage imaged 3 stations which were previously beneath the floating tongue, as well as 9 stations covered by multi-year and annual fast ice since the mid 1970s.
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The overarching theme of this book (and for the GeoHab organisation in general) is that mapping seafloor geomorphic features is useful for understanding benthic habitats. Many of the case studies in this volume demonstrate that geomorphic feature type is a powerful surrogate for associated benthic communities. Here we provide a brief overview of the major geomorphic features that are described in the detailed case studies (which follow in Part II of this book). Starting from the coast we will consider sandy temperate coasts, rocky temperate coasts, estuaries and fjords, barrier islands and glaciated coasts. Moving offshore onto the continental shelf we will consider sandbanks, sandwaves, rocky ridges, shallow banks, coral reefs, shelf valleys and other shelf habitats. Finally, on the continental slope and deep ocean environments we will review the general geomorphology and associated habitats of escarpments, submarine canyons, seamounts, plateaus and deep sea vent communities.
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Cold seeps and hydrothermal vents can be detected by a number of oceanographic and geophysical techniques as well as the recovery of characteristic organisms. While the definitive identification of a seep or vent and its accompanying fauna is seldom unequivocal without significant effort. We suggest an approach to identifying associated VMEs in the CCAMLR region that uses the results of scientific surveys to identify confirmed features while documenting a series of criteria that can be used by fishing vessels to reduce the accidental disturbance of seep communities.
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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 .