How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes? (original) (raw)
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Mapping seabed habitats over large areas: prospects and limits
2021
Since its inception, in 2009, EMODnet Seabed Habitats has brought together a European consortium of specialists in benthic ecology and seabed habitat mapping to develop a transnational broad-scale seabed habitat map, named EUSeaMap. EUSeaMap is the only pan-European cartographic product that provides a standardised trans-boundary overview of the spatial distribution of seabed habitats across Europe. As such, it has been extensively used in various applications such as Marine Protected Area evaluation or cumulative impact of stressors on habitats, and it is likely to be used again in the future in various marine ecosystem assessments. It is therefore important to continue to update it regularly when significant improvements to the data products that constitute its basis, i.e. the seabed substrate, bathymetry or environmental variables, are published. In addition to EUSeaMap, it would be desirable to provide stakeholders with products on the spatial distribution of targeted habitats/b...
Towards prediction of seabed habitats
… '06, University of …, 2006
Marine seabed habitats are highly influenced by the geophysical variables they feature. These are firstly seabed type, topography and exposure, but in the more inshore areas also include water transparency, salinity, temperature etc. Some relations have been established in a top-down approach between adequate combinations of these variables and the higher levels of the Eunis (European Nature Information System) habitat classification which is currently being used to harmonise seabed habitat mapping throughout Europe. These levels have been referred to as "Marine landscapes", as they are aggregations of a number of lower Eunis habitats from levels 4 to 6. More elaborate variables that are thought to have a bearing on habitat types can be computed from the initial basic ones through comprehensive use of GIS functions. The depth provides slope and orientation. An aggregation of currents and wave action on the seabed provides exposure. Sediment grain size along with currents and slopes allow bedforms on sedimentary bottoms to be predicted. Adequate binning of these quantities and their cross-tabulation leads to a number of landscape types which usually pertain to level 3, but also 4 at times. That raises the question: to which extent could assimilating of biological samples (by way of, e.g., a point-to-polygon method) allow a holistic habitat map at a lower typology level to be produced? The notion of marine landscape can be further exploited to describe any particular habitat, provided that the distribution laws of this habitat with respect to the geophysical parameters are established on the basis of adequate field data sets. This is a bottom-up approach of habitat modelling adapted to mapping individual priority habitats for which field samples are available.
Hydrographic surveys are carried out mainly to ensure safe navigation, but there are other reasons for mapping the seafloor. These include: (1) to support government spatial marine planning, management, and decision making; (2) to support and underpin the design of marine-protected areas (MPAs) and fishing reserves; (3) to conduct scientific research programs aimed at generating knowledge of benthic ecosystems and seafloor geology; (4) to conduct living and nonliving seabed resource assessments for economic and management purposes; and (5) to support the construction of ports and offshore structures (oil and gas production facilities, wind farms, etc.). The geomorphology of the seafloor, interpreted from bathymetric data combined with geological knowledge, can provide a basic level of information to support goals such as these. By combining multiple spatial biophysical data layers (eg. depth, slope, rugosity, water temperature, primary production, etc.) using multivariate statistical techniques, scientists have produced integrated "seascape" maps to further assist ocean managers. Adding direct observations of marine life to seascapes provides the basis for generating predictive habitat maps, derived using statistical methods (maximum entropy or decision-tree techniques), which depict the potential distribution of species and benthic communities and that are useful for decision-making regarding conservation and management. These three broad categories of spatial seafloor classification (geomorphology, seascapes, and predictive habitats) also represent a progression for the utilization of environmental information, from data-poor to data-rich situations. Here we review some examples of seabed maps derived from the three categories and their applications and uses in the management of Australia's marine jurisdiction. Introduction-information that marine managers need The governments of maritime nations commonly employ public servants (ocean managers) whose task it is to implement government polices that aim to limit the impact of human activities on the environment while simultaneously minimizing any added costs to maritime industries. The ocean manager's job is further complicated by the need to account for the cumulative impacts of industry activities (fishing, shipping, port construction, defense, laying of communication cables, oil and gas exploration and development, seabed mining, coastal development) intersecting with a range of legislation enacted to meet different conservation goals. The most common, overarching conservation goals covered by legislation relate to the preservation of biodiversity and the protection of ecosystems. Many books and articles have been published on this topic (for a recent review see Baker and Harris, 2012).
EUSeaMap. A European broad-scale seabed habitat map
2017
In order to most benefit from the potential offered by the European marine basins in terms of growth and employment (Blue Growth), and to protect the marine environment, we need to know more about the seafloor. European Directives, such as the MSFD, but also the Horizon 2020 roadmap explicitly called for a multi-resolution full coverage of all European seas including bathymetry, geology and habitats. The present work, following on a suite of past initiatives, has made a big step forward in this direction. It has first boosted the collation of existing maps from surveys by setting up a framework and a procedure to encourage people to submit their maps and data. This resulted in a more attractive EMODnet seabed habitat portal and a snowball effect with more and more people willing to join. However, collation will eventually come to an end and as new creations of seabed habitat maps are so complex and time-consuming, a cost-efficient way to meet the need for a full-coverage habitat map...
Marine Technology Society Journal, 2005
There is a great need for accurate, comprehensive maps of seafloor habitat for use in fish stock assessments, marine protected area design, and other resource management pursuits. Recent advances in acoustic remote sensing technology have made it possible to obtain high-resolution (meter to sub-meter) digital elevation models (DEMs) of seafloor bathymetry that can rival or surpass those available for the terrestrial environment. The acquisition and processing of these data are expensive, however, requiring specialized equipment, expertise, and large amounts of both field and laboratory effort per unit area mapped. Further, the interpretation and classification of these data into maps of habitat type is typically (and appropriately) performed only by trained experts that are familiar with both seafloor geomorphology and the nature and limitations of the data sources. Because it is done visually, this interpretation can be very time-consuming and may yield subjective results that are ...
Continental Shelf Research, 2012
The coastal waters of the Maltese Islands, central Mediterranean Sea, sustain a diversity of marine habitats and support a wide range of human activities. The islands' shallow waters are characterised by a paucity of hydrographic and marine geo-environmental data, which is problematic in view of the requirements of the Maltese Islands to assess the state of their coastal waters by 2012 as part of the EU Marine Strategy Directive. Multibeam echosounder (MBES) systems are today recognised as one of the most effective tools to map the seafloor, although the quantitative characterisation of MBES data for seafloor and habitat mapping is still an underdeveloped field. The purpose of this study is to outline a semi-automated, Geographic Information System-based methodology to map the distribution of habitats in shallow coastal waters using high-resolution MBES data. What distinguishes our methodology from those proposed in previous studies is the combination of a suite of geomorphometric and textural analytical techniques to map specific types of seafloor morphologies and compositions; the selection of the techniques is based on identifying which geophysical parameter would be influenced by the seabed type under consideration.
Remote Sensing, 2018
Recently, the rapid development of the seabed mapping industry has allowed researchers to collect hydroacoustic data in shallow, nearshore environments. Progress in marine habitat mapping has also helped to distinguish the seafloor areas of varied acoustic properties. As a result of these new developments, we have collected a multi-frequency, multibeam echosounder dataset from the valuable nearshore environment of the southern Baltic Sea using two frequencies: 150 kHz and 400 kHz. Despite its small size, the Rowy area is characterized by diverse habitat conditions and the presence of red algae, unique on the Polish coast of the Baltic Sea. This study focused on the utilization of multibeam bathymetry and multi-frequency backscatter data to create reliable maps of the seafloor. Our approach consisted of the extraction of 70 secondary features of bathymetric and backscatter data, including statistic and textural attributes of different scales. Based on ground-truth samples, we have identified six habitat classes and selected the most relevant features of the bathymetric and backscatter data. Additionally, five types of image processing pixel-based and object-based classifiers were tested. We also evaluated the performance of algorithms using an accuracy assessment based on the validation subset of the ground-truth samples. Our best results reached 93% overall accuracy and a kappa coefficient of 0.90, confirming that nearshore seabed habitats can be accurately distinguished based on multi-frequency, multibeam echosounder measurements. Our predictive habitat mapping of shallow euphotic zones creates a new scientific perspective and provides relevant data for the management of natural resources. Object-based approaches previously used in various environments and areas suggest that methodology presented in this study may be scalable.
ICES Journal of Marine Science, 2009
. Prediction of benthic biotopes on a Norwegian offshore bank using a combination of multivariate analysis and GIS classification. -ICES Journal of Marine Science, 66: 000-000. This study is part of the multidisciplinary seabed mapping programme MAREANO (Marine AREAdatabase for NOrwegian coast and sea areas). The mapping programme includes acquisition of multibeam bathymetry and acoustic backscatter data together with a comprehensive, integrated biological and geological sampling programme. The equipment used includes underwater video, boxcorer, grab, hyperbenthic sled, and beam trawl. The Tromsøflaket offshore bank was used as a case-study area to develop suitable methods for mapping habitats and biotopes. A procedure for producing maps of predicted biotopes is described that combined information on the distribution of biological communities with environmental factors and indicators. Detrended correspondence analysis (DCA) was used to relate bottom environment [including multiscale physical descriptors of the seabed derived from multibeam echosounder (MBES) data] and faunal distribution to find the best physical biotope descriptors. DCA of 252 video samples (sequences 200 m long) revealed six groups of locations representing different biotopes. These were characterized by different compositions of species, substrata, depths, and values for terrain parameters. Prediction of biotope distribution was performed using a supervised GIS classification with the MBES-derived physical seabed descriptors with the strongest explanatory ability (depth, backscatter, and broad-scale bathymetric position index) identified by the DCA. The species diversity of the identified biotopes was described from the content of the bottom samples. For future MAREANO cruises, an important task will be to ground-truth predictions of habitat and biotopes and to test the reliability of these predictions in the wider MAREANO area.
Process-driven characterization and mapping of seabed habitats
The creation of habitat maps commonly is based on defining regions having similar chemical, physical and biological characteristics. Traditionally, the boundaries between habitat types are established on arbitrarily-chosen levels of physical variables and on approximation of spatial location. Here, we demonstrate a practical method for creating seabed habitat maps using the habitat template approach to integrate multiple environmental fields into a single map. The resulting map shows the distribution of habitats where organisms with particular life history traits are likely to flourish, and provides a spatial framework for integrated management of ocean uses. A case study for the Scotian Shelf and Bay of Fundy in the northwest Atlantic Ocean illustrates that the parsimonious nature of the modelling approach allows prediction of spatial patterns in benthic habitat types based on readily available oceanographic data.
2011
The relationship between the distribution of benthic marine fauna and different aspects of the physical environment has been a key topic of research for many years. The nature of seabed sediments, in particular, their grain size composition, has been identified as one of the main drivers determining benthic community composition. Sediment maps are therefore a primary determinant in producing reliable predictive biotope maps of the marine environment. A number of classification schemes have been developed over the last decade as a means of standardising the way in which the marine environment is categorised. The most widely used scheme in Europe being the European Nature Information System, more commonly referred to as ‘EUNIS’. Recent attempts to apply this scheme to a series of regional level mapping projects have identified a number of issues and inconsistencies within the classification scheme, including, but not limited to, the way in which sediment deposits are categorised. Four...