%0 Report %D 2021 %T Beagle Marine Park Post Survey Report: South-east Marine Parks Network %A Neville Barrett %A Jacquomo Monk %A Scott L Nichol %A Falster, G %A Andrew Carroll %A Justy P W Siwabessy %A Deane, A %A Nanson, R %A K Picard %A Dando, N %A Hulls, J %A Evans, H %K Australian Marine Park %K bathymetry %K benthic %K Biodiversity %K demersal fish %K epifauna %K seabed %K temperate reef %X
This report presents preliminary results from a seabed mapping and biodiversity survey of Beagle Marine Park, undertaken in 2018 by the University of Tasmania, Geoscience Australia and University of Sydney Centre for Field Robotics. The primary audience includes researchers and marine park managers. Bathymetry mapping and seabed imagery reveals the area is dominated by soft sediments, with localised areas of low-profile reef, including rare examples of relict terrestrial dunes that formed when Bass Strait was a land bridge. The reefs provide important habitat for sessile invertebrates, while adjacent soft sediment areas include scallop beds interspersed among coarse sand, with shell fragments and extensive fields of sediment bedforms. Demersal fish were abundant and diverse, but with few commercial or recreational target species. These new data provide insights into the distribution of seabed habitats and biota within Beagle Marine Park, and provides a baseline on its natural values.
%8 6 May 2021 %G eng %0 Report %D 2018 %T Field manuals for marine sampling to monitor Australian waters %A Rachel Przeslawski %A Scott D Foster %A Vanessa L Lucieer %A Jacquomo Monk %A Phil J. Bouchet %A Tim J. Langlois %A Andrew Carroll %A Joel Williams %A Neville Barrett %A Althaus, Franziska %A Beaman, Robin J. %A Berents, Penny %A Tom Bridge %A Malcolm R Clark %A Jamie Colquhoun %A Leanne M. Currey Randall %A Graham J. Edgar %A Fellows, Melissa %A Frid, Chris %A Friedman, Ariell %A Daniel C Gledhill %A Jordan S. Goetze %A David Harasti %A K.R. Hayes %A Nicole A. Hill %A G.R. Hosack %A Charlie Huveneers %A Ierodiaconou, Daniel %A T Ingleton %A Alan Jordan %A Gary A. Kendrick %A Kennedy, David M. %A E Lawrence %A Tom B. Letessier %A Linklater, Michelle %A Lowry, Michael %A Hamish A. Malcolm %A Jessica J. Meeuwig %A Scott L Nichol %A Tim O'Hara %A K Picard %A Alix Post %A Matthew J Rees %A Santana-Garcon, Julia %A Scott, Molly %A Justy P W Siwabessy %A Smith, Jodie %A Marcus Stowar %A Taylor, Matt %A Thompson, Christopher %A Maggie Tran %A Tyndall, Aaron %A Laurent, Vigliola %A Sasha Whitmarsh %K monitoring %K standard operating procedures %K survey methods %XAustralia has one of the world’s largest marine estates that includes many vulnerable habitats and a high biodiversity, with many endemic species crossing a wide latitudinal range. The marine estate is used by a variety of industries including fishing, oil & gas, and shipping, in addition to traditional, cultural, scientific and recreational uses. The Commonwealth government has recently established the Australian Marine Parks (AMPs), the largest network of marine protected areas in the world, complementing existing networks in State and Territory waters.
Monitoring the impacts of these uses on the marine environment is a massive shared responsibility that can only be achieved by making the best use of all the information that is collected. Australia now has a number of significant long-term marine monitoring and observing programs, as well as a national ocean data network. Without some common and agreed standards, much of the information collected will not be comparable with other areas or sectors. This may reduce its value to regional and national management, while the individual project or survey may lose the opportunity to interpret results in a regional or national context.
We have therefore developed a suite of field manuals for the acquisition of marine benthic (i.e. seafloor) data from a variety of frequently-used sampling platforms so that data can become directly comparable in time and through space, thus supporting nationally relevant monitoring in Australian waters and the development of a monitoring program for the AMP network. This objective integrates with one of the eight high-level priorities identified by the National Marine Science Plan (2015-25): the establishment of national baselines and long-term monitoring.
Related information
Spatial distribution of sponge species richness (SSR) and its relationship with environment are important for marine ecosystem management, but they are either unavailable or unknown. Hence we applied random forest (RF), generalised linear model (GLM) and their hybrid methods with geostatistical techniques to SSR data by addressing relevant issues with variable selection and model selection. It was found that: 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model selection methods are unsuitable for identifying GLM predictive models and joint application of RF and AIC can select accuracy-improved models; 3) highly correlated predictors may improve RF predictive accuracy; 4) hybrid methods for RF can accurately predict count data; and 5) effects of model averaging are method-dependent. This study depicted the non-linear relationships of SSR and predictors, generated spatial distribution of SSR with high accuracy and revealed the association of high SSR with hard seabed features.
%B Environmental Modelling & Software %V 97 %P 112 - 129 %8 01 Nov 2017 %G eng %U http://linkinghub.elsevier.com/retrieve/pii/S1364815217301615 %! Environmental Modelling & Software %R 10.1016/j.envsoft.2017.07.016 %0 Journal Article %J Marine Geodesy %D 2016 %T Analysing uncertainty in multibeam bathymetry data and the impact on derived seafloor attributes %A Vanessa L Lucieer %A Z Huang %A Justy P W Siwabessy %XMultibeam bathymetric data provides critical information for the modelling of seabed geology and benthic biodiversity. The accuracy of these models is dependent on the accuracy of the bathymetric data which contains uncertainties that are stochastic at individual soundings but exhibit a distinct spatial distribution with increasing magnitude from nadir to the outer beams. A restricted spatial randomness method which simulates both the stochastic and spatial characteristics of the data uncertainty performed better than a complete spatial randomness method in analysing the impact of bathymetric data uncertainty on derived seafloor attributes.
%B Marine Geodesy %8 01 Mar 2016 %G eng %U http://dx.doi.org/10.1080/01490419.2015.1121173 %! Marine Geodesy %R 10.1080/01490419.2015.1121173 %0 Report %D 2016 %T Analysis of Approaches for Monitoring Biodiversity in Commonwealth Waters - Field work report %A Althaus, Franziska %A Neville Barrett %A Jeffrey M Dambacher %A P Davies %A Renata Ferrari %A Jessica H. Ford %A Keith R Hayes %A Nicole A. Hill %A G.R. Hosack %A Renae Hovey %A Z Huang %A J Hulls %A T Ingleton %A Alan Jordan %A Gary A. Kendrick %A Johnathan T. Kool %A E Lawrence %A Leeming, Rhys %A Vanessa L Lucieer %A Hamish A. Malcolm %A Meyer, L %A Jacquomo Monk %A Scott L Nichol %A David Peel %A Nicholas R. Perkins %A Justy P W Siwabessy %A Sherlock, M %A Martin, Tara %A Maggie Tran %A Walsh, A %A Williams, Alan %XThe overall objective of this project was to contribute to a blue-print for a sustained national environmental monitoring strategy for monitoring biodiversity in the Commonwealth Marine Areas. The approach would apply to Key Ecological Features (KEFs) and the Commonwealth Marine Reserve (CMR) Network, focusing initially on the Southeast Marine Region. CMRs and KEFs are large, remote and poorly known, so this project focussed on identifying flexible, statistically robust approaches to survey design and data collection that could result in comprehensive descriptions of the surveyed area and at the same time provide a statistical baseline for future repeat surveys in the same area. Given the conservation status and values of these areas, non-destructive sampling tools were prioritized, including remote sensing using acoustics (e.g. multibeam) that provide information on seafloor characteristics (bathymetry, hardness and texture), and direct observation using video and camera stills, taken by towed units, autonomous units or baited units. The final report is of necessity highly technical, reporting on the design and analytical issues addressed by this project. This executive summary is designed to provide an overview of the project and highlight the key findings relevant to policy makers and managers, omitting most of the technical detail. Readers interested in technical detail are referred to the main body of this report or the many research papers resulting from this work that are listed at the end of this summary.
Three field programs were undertaken. The largest survey was for the Flinders Commonwealth Marine Reserve (CMR) located offshore, northeast of Tasmania. This provided a baseline of the continental shelf, in the multiple use zone of this reserve, on which future monitoring can be built, and provides an initial characterization of the upper slope areas in the same zone of this CMR. A smaller survey targeted at known shelf reefs features in the Solitary Islands Marine Park (SIMP) and Solitary Islands Marine Reserve (SIMR) was designed to address specific sampling issues including: extending State-based research to this Commonwealth KEF, comparing autonomous and towed platforms for capturing video imagery, and examining statistical issues associated with the use of baited underwater remote videos (BRUVs). The third survey in the KEF east of the Houtman-Abrolhos islands was an exploratory survey designed to identify whether coral-kelp and other shelf reef communities in the State MPA extended into this KEF, and explore whether seabird diet could be used as a reliable indicator of pelagic ecosystem health.
Seafloor habitats on continental shelf margins are increasingly being the subject of worldwide conservation efforts to protect them from human activities due to their biological and economic value. Quantitative data on the epibenthic taxa which contributes to the biodiversity value of these continental shelf margins is vital for the effectiveness of these efforts, especially at the spatial resolution required to effectively manage these ecosystems. We quantified the diversity of morphotype classes on an outcropping reef system characteristic of the continental shelf margin in the Flinders Commonwealth Marine Reserve, southeastern Australia. The system is uniquely characterized by long linear outcropping ledge features in sedimentary bedrock that differ markedly from the surrounding low-profile, sand-inundated reefs. We characterize a reef system harboring rich morphotype classes, with a total of 55 morphotype classes identified from the still images captured by an autonomous underwater vehicle. The morphotype class Cnidaria/Bryzoa/Hydroid matrix dominated the assemblages recorded. Both α and β diversity declined sharply with distance from nearest outcropping reef ledge feature. Patterns of the morphotype classes were characterized by (1) morphotype turnover at scales of 5 to 10s m from nearest outcropping reef ledge feature, (2) 30 % of morphotype classes were recorded only once (i.e. singletons), and (3) generally low levels of abundance (proportion cover) of the component morphotype class. This suggests that the assemblages in this region contain a considerable number of locally rare morphotype classes. This study highlights the particular importance of outcropping reef ledge features in this region, as they provide a refuge against sediment scouring and inundation common on the low profile reef that characterizes this region. As outcropping reef features, they represent a small fraction of overall reef habitat yet contain much of the epibenthic faunal diversity. This study has relevance to conservation planning for continental shelf habitats, as protecting a single, or few, areas of reef is unlikely to accurately represent the geomorphic diversity of cross-shelf habitats and the morphotype diversity that is associated with these features. Equally, when designing monitoring programs these spatially-discrete, but biologically rich outcropping reef ledge features should be considered as distinct components in stratified sampling designs.
%B Biodiversity and Conservation %8 01 Mar 2016 %G eng %U http://link.springer.com/10.1007/s10531-016-1058-1 %! Biodivers Conserv %R 10.1007/s10531-016-1058-1 %0 Journal Article %J Environmental Chemistry %D 2015 %T Characterising sediments of a tropical sediment-starved shelf using cluster analysis of physical and geochemical variables %A Lynda Radke %A Jin Li %A Douglas, Grant %A Rachel Przeslawski %A Scott L Nichol %A Justy P W Siwabessy %A Z Huang %A Trafford, Janice %A Watson, Tony %A Whiteway, Tanya %K ANOSIM %K Backscatter %K carbonate banks %K Commonwealth Marine Reserve %K conceptual model %K epifauna %K Marine %K rare earth elements %K subsurface seepage %XBaseline information on habitats is required to manage Australia's northern tropical marine estate. This study aims to develop an improved understanding of seafloor environments of the Timor Sea. Clustering methods were applied to a large data set comprising physical and geochemical variables that describe organic matter (OM) reactivity, quantity and source, and geochemical processes. Arthropoda (infauna) were used to assess different groupings. Clusters based on physical and geochemical data discriminated arthropods better than geomorphic features. Major variations among clusters included grain size and a cross-shelf transition from authigenic-Mn–As enrichments (inner shelf) to authigenic-P enrichment (outer shelf). Groups comprising raised features had the highest reactive OM concentrations (e.g. low chlorin indices and C : N ratios, and high reaction rate coefficients) and benthic algal δ13C signatures. Surface area-normalised OM concentrations higher than continental shelf norms were observed in association with: (i) low δ15N, inferring Trichodesmium input; and (ii) pockmarks, which impart bottom–up controls on seabed chemistry and cause inconsistencies between bulk and pigment OM pools. Low Shannon–Wiener diversity occurred in association with low redox and porewater pH and published evidence for high energy. Highest β-diversity was observed at euphotic depths. Geochemical data and clustering methods used here provide insight into ecosystem processes that likely influence biodiversity patterns in the region.
he recently declared Australian Commonwealth Marine Reserve (CMR) Network covers a total of 3.1 million km2 of continental shelf, slope, and abyssal habitat. Managing and conserving the biodiversity values within this network requires knowledge of the physical and biological assets that lie within its boundaries. Unfortunately very little is known about the habitats and biological assemblages of the continental shelf within the network, where diversity is richest and anthropogenic pressures are greatest. Effective management of the CMR estate into the future requires this knowledge gap to be filled efficiently and quantitatively. The challenge is particularly great for the shelf as multibeam echosounder (MBES) mapping, a key tool for identifying and quantifying habitat distribution, is time consuming in shallow depths, so full coverage mapping of the CMR shelf assets is unrealistic in the medium-term. Here we report on the results of a study undertaken in the Flinders Commonwealth Marine Reserve (southeast Australia) designed to test the benefits of two approaches to characterising shelf habitats: (i) MBES mapping of a continuous (~30 km2) area selected on the basis of its potential to include a range of seabed habitats that are potentially representative of the wider area, versus; (ii) a novel approach that uses targeted mapping of a greater number of smaller, but spatially balanced, locations using a Generalized Random Tessellation Stratified sample design. We present the first quantitative estimates of habitat type and sessile biological communities on the shelf of the Flinders reserve, the former based on three MBES analysis techniques. We contrast the quality of information that both survey approaches offer in combination with the three MBES analysis methods. The GRTS approach enables design based estimates of habitat types and sessile communities and also identifies potential biodiversity hotspots in the northwest corner of the reserve’s IUCN zone IV, and in locations close to shelf incising canyon heads. Design based estimates of habitats, however, vary substantially depending on the MBES analysis technique, highlighting the challenging nature of the reserve’s low profile reefs, and improvements that are needed when acquiring MBES data for small GRTS locations. We conclude that the two survey approaches are complementary and both have their place in a successful and flexible monitoring strategy; the emphasis on one method over the other should be considered on a case by case basis, taking into account the survey objectives and limitations imposed by the type of vessel, time available, size and location of the region where knowledge is required.
%B PLOS ONE %V 10 %P e0141051 %8 23 Oct 2015 %G eng %U http://dx.plos.org/10.1371/journal.pone.0141051 %N 10 %! PLoS ONE %R http://dx.plos.org/10.1371/journal.pone.0141051 %0 Journal Article %J Marine Geology %D 2014 %T Predictive Mapping of Seabed Substrata Using High-Resolution Multibeam Data %A Z Huang %A Justy P W Siwabessy %A Scott L Nichol %A Brendan P Brooke %K Angular response curves %K Backscatter %K bathymetry %K Feature extraction %K multibeam %K Prediction %K Seabed mapping %XThis study explores the full potential of high-resolution multibeam data for the automated and accurate mapping of complex seabed features under a predictive modelling framework. For an area of seabed on the Carnarvon shelf in Western Australia, morphometric variables and textural measures were derived from multibeam bathymetry and backscatter data. Several feature extraction approaches were applied to backscatter angular response curves to obtain new features. These derivatives and new features were used separately and in combination in the predictions. Despite the complex distribution of various hard substrata within the study area, we achieved a nearly perfect prediction of “hard vs soft” seabed types with an AUC (Area Under Curve) close to 1.0. The predictions were also satisfactory for gravel, sand and mud content, with R2 values that range from 0.55 to 0.73. This study demonstrates that using a full range of derivatives and new features from both multibeam bathymetry and backscatter data optimises the accuracy of seabed mapping. From the modelled relationships between sediment properties and multibeam data, we confirmed that coarser sediment generally generates stronger backscatter return. Importantly, the results again highlight the advantages of applying proper feature extraction approaches over using original backscatter angular response curves.
A key requirement for informed marine-zone management is an understanding of the spatial patterns of marine biodiversity, often measured as species richness, total abundance or presence of key taxa. In the present study, we focussed on the diversity of benthic infauna and applied a predictive modelling approach to map biodiversity patterns for three study sites on the tropical Carnarvon shelf of Western Australia. A random forest decision tree model was used to generate spatial predictions of two measures of infaunal diversity, namely, species richness and total abundance. Results explained between 20% and 37% of the variance of each measure. The modelling process also identified potential physical surrogates for species richness and abundance, with sediment physical properties ranked as most important across the study region. Specifically, coarse-grained heterogeneous sediments were associated with higher infaunal species richness and total abundance. Seabed topographic properties were also important at the local scale. The study demonstrated the value of a surrogacy approach to the prediction of biodiversity patterns, particularly when the number of biological samples was limited. Such an approach may facilitate an understanding of ecosystem processes in the region and contribute to integrated marine management.
The Oceanic Shoals Commonwealth Marine Reserve (CMR), situated in tropical northern Australia, incorporates extensive areas of carbonate banks and terraces. These are recognised by the Australian Government as potential biodiversity hotspots.
In September 2012, Geoscience Australia collected shallow seabed information to characterise the CMR and to better understand the carbonates banks and their role in supporting biodiversity.
The survey area is located on the widest part of the Continental Shelf (250 km) which is subject to a storm-influenced micro tidal energy regime (mean range: <2 m). However, the coast immediately to the south is macro-tidal (~7 m). The net tidal direction is westerly and the sediment transport regime is flood-dominated (Porter-Smith et al., 2004).
High-resolution mapping has revealed that the seafloor is characterised by multiple carbonate banks that rise tens of metres above otherwise vast soft-sediment plains.
%B GEOHAB (Marine Geological and Biological Habitat Mapping) 2014 Conference %8 09 May 2014 %G eng %U http://www.geohab2014.org/ %0 Conference Paper %B GEOHAB (Marine Geological and Biological Habitat Mapping) %D 2013 %T How robust are your prediction derivatives? Error propagation modelling for seafloor terrain analysis of multibeam bathymetric data using dynamic simulation tools %A Vanessa L Lucieer %A Z Huang %A Justy P W Siwabessy %A K Hayes %X
There are many potential applications of seabed habitat mapping for which estimates of uncertainty in
seafloor terrain derivatives will provide additional crucial information. This information is useful to
assess the robustness of multibeam bathymetric data for seabed monitoring, change detection and
habitat prediction analysis.
As multibeam data collections build up over time a method to assess the compatibility to spatially
merge these data are essential. These datasets then become the input data for spatial analysis
procedures to characterise the seabed. The accuracy of seabed terrain first and second order
derivatives and their associated levels of uncertainty are extremely hard to convey visually or to
quantify with existing methodologies.
In this study Monte-Carlo simulation techniques were used to represent DEM (digital elevation model)
uncertainty and its effect on three topographic parameters (slope, curvature and aspect). Different
methods for representing error and quantifying uncertainty are investigated. In these results the
analysis the multibeam bathymetric error are assumed to be spatially auto correlated across a
neighbourhood zone, methods for the assessment of autocorrelation will be discussed. Each terrain
derivative layer was perturbed using its error model with increasing levels of error, and the effect on
the seabed map was assessed.
Quantifying uncertainty in the input data for habitat suitability modelling is imperative to establishing
methods for prediction, and monitoring, as we need to be able to separate potential mapping error
from change and variation in the system that we are monitoring. By combining bathymetric processing
and uncertainty modelling techniques we can make an important step towards identifying tools for
seabed monitoring and risk assessment for policy-making. These tools will improve our ability to
assess and communicate the accuracy of the seabed maps through spatially mapping the degrees of
uncertainty in our predictions and therefore make more informed choices of the data we use to inform
ocean management policies and subsequent seafloor analysis.
This report provides details of activities undertaken by the Australian Institute of Marine Science (AIMS), Geoscience Australia (GA), 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 the 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 the Environment (previously Department of Sustainability, Environment, Water, Population and Communities). These data will be made publicly available, via the Marine Biodiversity Hub website and the Australian Ocean Data Network Portal, adding to the knowledge base of Australian tropical shelf habitats and contributing to the long term management of these poorly understood areas.
Angular response curves of multibeam backscatter data are used to predict the distributions of seven seabed cover types in an acoustically-complex area of the continental shelf of Western Australia. Several feature analysis approaches on the angular response curves are examined. A Probability Neural Network model was chosen for the predictive mapping, which accuracy measurement is given by a statistical coefficient Kappa. The prediction results have demonstrated the value of angular response curves for seabed mapping with Kappa=0.59 and a reasonable spatial prediction based on a visual assessment. This study also demonstrates the potential of various feature analysis approaches to improve seabed mapping. The approach to derive statistical parameters from the curves achieved significant feature reduction and some gain in statistical performance (e.g., Kappa=0.62). Its prediction map also represents a notable improvement. The first derivative analysis approach achieved the best overall statistical performance (e.g., Kappa=0.84); while the approach to remove the global slope produced the best overall prediction map as well as a significant gain in statistical performance (e.g., Kappa=0.74). We therefore recommend these three feature analysis approaches, along with the original angular response curves, for future seabed classification studies.
%B Continental Shelf Research %V 61-62 %P 12 - 22 %8 01 Jul 2013 %G eng %U http://www.sciencedirect.com/science/article/pii/S0278434313001246 %! Continental Shelf Research %R 10.1016/j.csr.2013.04.024 %0 Journal Article %J International Journal of Geographical Information Science %D 2012 %T Developing physical surrogates for benthic biodiversity using co-located samples and regression tree models: a conceptual synthesis for a sandy temperate embayment %A Z Huang %A Matthew McArthur %A Lynda Radke %A Tara J Anderson %A Scott L Nichol %A Justy P W Siwabessy %A Brendan P Brooke %K benthic biodiversity %K conceptual model %K Jervis Bay %K surrogates %XMarine physical and geochemical data can be valuable surrogates for predicting
the distributions and assemblages of marine species. This study investigated the
bio-environment (surrogacy) relationships in Jervis Bay, a sandy marine embayment
in south-eastern Australia. A wide range of co-located physical data were analysed
together with biological data, including multibeam bathymetry and backscatter surfaces
and derivatives, parameters that describe seabed sediment and water column
physical/geochemical characteristics and seabed exposure. Three decision tree models
and a robust model selection process were applied. The models for three diversity
indices and seven out of eight infaunal species explained 32–79% of the variance.
A diverse range of physical surrogates for biodiversity were identified. The surrogates
are presented in a conceptual model that identifies the mechanisms that potentially
link to biodiversity patterns. While some surrogates may exert direct influence over
organisms to exposure and chlorophyll-a, for example, most pointed to complex
relationships between multiple biological and physical factors occurring in different
process domains/zones. The reliable bio-environment relationships identified from
co-located samples and conceptual models enabled a mechanistic understanding of benthic
biodiversity patterns in a sandy coastal embayment that may have implications for
marine environmental management.