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1 Title: Author(s): Document owner: Worked example - Marine-Landscape Map of the Dutch Continental Shelf Pieter Doornenbal, Jeroen Schokker, Denise Maljers, Jan Tjalling van der Wal & Sytze van Heteren TNO Built Environment and Geosciences Sytze van Heteren (sytze.vanheteren@tno.nl) File name: Language: GMHM4_WE_TNO_Marine_Landscape_map_DCS.pdf English Number of pages: 16 Summary: Reference/citation: Keywords: A summary of a landscape modelling study to use physical data layers to create a map of marine landscapes for the Dutch Continental Shelf.

2 Worked example Marine-Landscape Map of the Dutch Continental Shelf Pieter Doornenbal¹, Jeroen Schokker¹, Denise Maljers¹, Jan Tjalling van der Wal¹ Sytze van Heteren¹ ¹ TNO Built Environment and Geosciences, Utrecht Introduction The seabed is influenced by human-induced changes and natural processes. Examples of human activities impacting the seabed are: commercial fishing, sand extraction, the exploration and exploitation of oil and gas, and shipping-lane maintenance. Natural processes impacting the seabed include physical and biological elements. Jointly, organisms living and foraging on and in their physical seabed environment form marine habitats and ecosystems. Owing to increasing human activities, there is an increasing pressure on marine ecosystems. To gain insight in the changing state of the seabed and its biological communities, and in the impact of human actions on marine habitats, information on the present state of the seabed and its biological communities is needed. Marine ecosystems and benthic community distributions commonly mirror the physical characterization of the seabed. To get a general view of the state of the seabed, the marine-landscape approach can be used. The approach is based on a broad-scale classification of the marine environment by combining abiotic datasets, such as bathymetry, slope, bedforms, median grain size, mud content, gravel content, and bed stress (Golding et al, 2004; Schelfaut, 2004). By combining these parameters, it is possible to define and delineate marine landscapes, which can be seen as proxies for discrete ecological units. The term marine landscape is used, whereas terms as habitat and marine ecosystem are already used in other contexts, where they usually imply the inclusion of biological data. The marine-landscape approach is well suited for areas where biological data are scarce or absent and where human activities need to be monitored. The study area is the Dutch Continental Shelf (NCP) (see Figure 1), excluding the estuarine areas of the Wadden Sea and the Delta region in the south-west: smaller-scale coastal waters that need to be classified at a more detailed level, using additional parameters. An example is the exposure duration of the intertidal flats, which is a much more significant factor in these shallow coastal waters than on the NCP. An annual biological monitoring program provides the benthos data necessary to calibrate the marine-landscape map.

3 Figure 1 Study area the Dutch Continental Shelf with frequently used names in the text plotted on the bathymetry.

4 A marine-landscape map of the NCP has not been made thus far. Bouma et al. (2005) created an ecotope map, but they used only bathymetry and sediment type. Van Alphen and Demoiseaux (1987) made a series of morphologic maps of the Dutch shoreface and the adjacent part of the continental shelf, on the basis of water depth and morphology, but they cover only part of the NCP and do not consider sediment and bed stress. The new map presented here covers the entire NCP and reflects the influence of a range of physical parameters. Datasets and methodology For this study, we used four distinct unclassified datasets (see table 1): bathymetry, two sediment characteristics and bottom shear stress. Six abiotic parameters were extracted from these datasets. These were subsequently merged into three classified maps, and these three classified maps were combined to make the marine landscape map. The six parameters that were extracted from the four datasets are: bathymetry, bathymetric position index, median grain size of the sand fraction ( µm), mud content, gravel content, and bottom shear stress. Because the NCP is relatively flat and bottom variation is also reflected in the bathymetric position index, slope was not taken into account. The UKSeaMap (Conner et al., 2006), one of the first marine-landscape maps, includes additional abiotic parameters such as salinity, water temperature and wave-base depth. These parameters were not considered in the present study of the NCP, but will be included in follow-up work. The datasets used to extract the parameters cover the entire NCP. In order to combine the datasets the data were extrapolated to raster grids with a cell size of 200 x 200 m. The bathymetric map results from the interpolation of many datasets, soundings from the Directorate-General of Public Works and Water Management and from the Hydrographic Service of the Royal Netherlands Navy. For each area, the most recent sounding available is used. The datum used for the soundings is the average Low Low Water Springtide level in 5 years (LLWS). A derivative of the bathymetric map is the bathymetric position index and is an index that characterizes bathymetric features in their local/regional context. A positive value represents a cell that is higher than its neighboring cells (ridge). A negative value represents a cell that is lower than its neighboring cells (valley). Flat areas or areas with a constant slope produce near-zero values (Rinehart et al., 2004). Within ArcGis 9.1, the following configuration is used: for the Finescale BPI, the inner radius is set at 1 cell and the outer radius is set at 2 cells. For the Broadscale BPI the inner radius is set at 1 cell and the outer radius at 6 cells.

5 Data sets Data structure Data source Bathymetry Merger of several datasets, extrapolated to a 200 m raster. Granulometry database Gravel content Bottom shear stress 6038 point measurements interpolated and extrapolated to a 200m raster Digitized sea bed sediment and Holocene geology maps projected on a 200m raster. Zuno-coarse model projected on a 200m raster. Table 1 Data sets, data structure and data source. Directorate-General of Public Works and Water Management, and Hydrographic Service of the Royal Netherlands Navy TNO Built environment and Geosciences TNO Built environment and Geosciences WL Delft Hydraulics, The map showing the median grain size of the sand fraction ( µm) (ds50) gives values where 50% (by weight) of the grains is coarser and 50% is finer. The values are extracted from a granulometry database with uniform size-class intervals. The database is the result of interpolating 6038 fully measured grainsize distributions. By using this method, it is possible to interpolate varying grainsize indicators, for example ds10 and ds90 (Maljers and Gunnink, 2006). The mud-content map presents the mud percentage of seabed sediment on the NCP. Mud is defined as particles smaller than 63 µm. For each sample (6038 in total) the mud percentage was determined. Subsequently, the point measurements were interpolated to create a full-coverage map (Maljers and Gunnink, 2006). The gravel-content map presents the gravel percentahe of seabed sediment on the NCP. The map is the result of digitizing the maps Sea Bed Sediments and Holocene Geology of the NCP (Jeffrey et al., 1988). The bottom shear stress was estimated using the ZUNO-coarse (southern North Sea) model created by WL Delft Hydraulics. The model calculates water-depth fluctuations, current velocities and salinity variations on a varying grid resolution. In areas where a large variability is expected (coastal zone) the cell size decreases, whereas in areas where no variation is expected the model uses larger grid cells. Comparisons between the model outcomes and in-situ measurements showed a good correlation (van Ledden et al., 2005). The modeled bottom shear stress is the result of a uniform bottom roughness and the velocity of the lowest water layer, whereby the orbital velocity governed by waves is also taken into account. Differences in grain size and in bedforms are not taken into account by this model. A disadvantage of this exclusion is that in areas with similar hydrodynamic conditions, values for the bottom shear stress are

6 identical, even though the bottom shear stress is not only the result of the velocity in the lowest water layer but is influenced by bottom roughness as well (van Rijn, 1993). Classification The method behind the marine-landscape approach is combining maps on a cell by cell basis (see figure 2). The result of this coupling is a new map, where each cell represents the underlying cells. To limit the number of classes in the final map, a broad but relevant classification is needed of the underlying maps. Classification needs to be done in a biological meaningful context. Sediment type and bedform morphology show various relationships with benthic communities (Baptist et al. 2006), but only the most relevant ones can be used to determine class intervals and boundaries. We extracted 6 parameters from the 4 unclassified datasets. These were subsequently combined into 3 classified maps. The rationale behind combining layers into fewer new layers is the great reduction in final classes thus achieved. The Figure 2 The marine-landscape approach couples the layers on a cell by cell basis first version of the marine-landscape map combined 6 layers, each with three classes. This gives a possible outcome of = 729 classes. The final marine-landscape map is the result of combining three layers. The first layer is a combination of the classified bathymetry and BPI, and contains 9 classes. The second layer is a combination of median grain size, mud content and gravel content, and contains 5 classes. The third layer is the classified bed shear stress, and contains 3 classes. By following this method, the maximum number of final classes is reduced to: = 135 classes. The first classified map (see Figure 3) consists of a combination of bathymetry and bedforms. Areas with elevations higher than 0.0 m are neglected from the dataset; these areas occur mainly in the Wadden Sea and in the southwestern estuaries. From the bathymetric map, it is clear that the transition between the sloping shoreface and the deeper shelf can be found around the -15 m depthcontour line. Hence the first class boundary is set at -15 m. From a physical point of view, the other class boundary is set at -35 m, because with this value, the basin (Oyster Grounds) and the Dogger Bank (two areas that have been distinguished on traditional NCP habitat maps) becomes visible in the northern half of the NCP. In figure 3c, bedforms are classified as small-scale features

7 (sand waves) and large-scale features (tidal ridges and shoreface-connected ridges). The second classified map (Figure 4) is a sediment-distribution map. The bottom of the North Sea consists mainly of sand, mud, gravel, and shells. In this layer, the mud content (Figure 3c,d) and gravel content (Figure 3e,f) are coupled with the grain-size distribution (Figure 3a,b). The grain-size values (ds50) are classified as fine sand (<150 µm), medium sand ( µm) and coarse sand (>300 µm). We assume that in areas with a mud percentage greater than 15, this factor is more important than the median grain size of the sand fraction. Likewise, we assume that in areas with a gravel percentage greater than 30, the median grain size of the sand fraction is neglected. The third classified map is a map showing the bottom shear stress. The bottom shear stress is classified into low (<0.5 N/m²), medium ( N/m²) and medium-high ( N/m²) (see Figure 5a,b). The result of the combination of the three classified maps (the marine-landscape map) is presented in Figure 6 (see results). Datasets Range original data Classified data bathymetry (m) BPI (bed forms) flats 1 flats, slope, valley slope 2 large scale ridge Coupling valley 3 small scale ridge large scale ridge small scale ridge Classified median sand grain size (µm) < > mud content (%) > gravel content (%) > bottom shear stress (N/m²) Table 2 Classification of the data sets

8 Figure 3 a) unclassified bathymetric map b) classified bathymetric map c) classified map of bathymetric position index d) classified map of bathymetry and bathymetric position index

9 Figure 4 a) unclassified ds50 map b) classified Ds50 map c) mud-content (%) map d) classified mud-content map e) unclassified gravel-content (%) map f) classified gravelcontent map f) final sediment characteristics by coupling b, d and f

10 Figure 5 a) unclassified map of bed shear stress (N/m²) b) classified map of bed shear stress

11 Results Marine landscape map of the Dutch Continental Shelf The final marine-landscape map of the NCP is shown in Figure 5. Combining the three classified maps gave 97 unique classes. The largest 3 classes make up 51 % of the total area, and 12 classes make up 90% the total area. In adopting an appropriate color scheme for the legend, sediment characteristics were determined to be the most important. Green colors indicate mud-rich environments, light yellow indicates areas with fine sand (<150 µm), yellow indicates areas with medium sand ( µm), orange indicates areas with coarse sand (>300 µm), and pink indicates gravel-rich areas. Water depth is shown as darker hues for deeper areas and lighter hues for shallower areas. The sand-wave fields and tidal ridges are highlighted in black, forming separate legend units. The bottom shear stress is indicated as zones on the map, where each zone is fringed by a dashed line. Low bed shear stress can be found in the northern part of the NCP (blue line), medium shear stress (green line) in the area between the coastal zone and the northern zone, and high bed shear stress in the coastal zone (red line). The marine-landscape map shows several units that correspond to known and named areas on the NCP. In the north, the deep (<-35 m) low energetic Oyster Grounds (see also Figure 1 for commonly used names) stands out. This basin is rich in mud and fine sand. The relatively shallow Dogger Bank borders the Oyster Grounds in the northernmost part of the NCP. The bank is 300 km long and extends into English, German, and Danish waters. Its shallowest point is 18 m deep (English part), and it slopes towards a depth of 35 m at its edges. Medium sand ( µm) is found on a great part of the bank, but coarse sand is present in the south. South of the Dogger Bank and west of the Oyster Grounds, a deeper (< -35 m) area with coarse sand and gravel fields is found. This area is known as the Cleaver Bank. finally, the coastal zone (-15-0 m) is a medium- to high-energy zone ( N/m²) with mainly medium sand. On the marine-landscape map, some distinct morphological features are shown, such as sand-wave fields, tidal ridges and shoreface-connected ridges. North of the barrier island Texel and in the southern part of the NCP, large sand-wave fields occupy areas of medium to coarse sand. Tidal ridges are located in the central part of the NCP and shoreface-connected ridges occur north of the barrier islands and west of the province Zeeland.

12 Figure 6 Marine-landscape map of the NCP, created by coupling data shown in figures 3d, 4g and 5b.

13

14 A first validation of the marine-landscape map by plotting the distribution of Caleanassa subterranea on the NCP. Callianassa subterranea is a decapod shrimp (see figure 7) with a right pincher that is significant larger than the left one. The shrimp does not grow larger than 4.5 cm. It digs complex burrow systems in muddy (sandy) sediments that can be up to 80 cm deep. The highest densities (individuals/m²) of Callianassa subterranea in the years are plotted as an overlay on the marine-landscape map (see figure 8). The map does not show densities of less than 10 Figure 7 Callianassa subterranea digs burrow systems in muddy sediments individuals per m². We conclude that there is a high correlation between the distribution of the densities and the area occupied by the deep (< -35 m) muddy basin in the north. In the northern areas with fine sand rather than mud, there are Callianassa subterranean present, but in lower densities.

15 Figure 8 Maximum density (individuals/m²) of Calianassa subterranea, plotted on the marine-landscape map. Dot sizes in legend are smaller than those on map.

16 Discussion The marine-landscape map as created using the class intervals selected in this study is one way to show the distribution of habitats on the NCP. By using BPI and bed shear stress as input parameters, one can identify areas with distinct bedforms and bed shear stresses, both of which are known to affect benthos. To limit the number of landscapes shown on the map, it is necessary to classify the underlying data layers. Such classification brings two main disadvantages. First, the resulting resolution in relatively uniform areas is low. Secondly, any classification, whether based on expert judgement or on calculated optimal class boundaries, will show some relevant units while leaving out others..it is important to realize that the resulting pattern and associated habitat distribution is only one possible reflection of the actual situation. For example: classifying the bathymetry at a boundary of -50 m would result in a disappearance of the Dogger Bank on your final map. Different questions may require different maps to provide answers. When improving the marine-landscape map presented here, focus must be on the collection of more grain-size data from the northern part of the NCP. Presently, data density is low, particularly in areas with a significant grain-size variability. In its present form, the marine-landscape map of the NCP cannot easily be connected to marine landscape maps of the Wadden Sea, the Zeeland estuaries and the Belgian Continental Shelf. For easy merger, the same physical parameters and in the same parameter classes must be used. Conclusions The marine-landscape approach was used to create a marine-landscape map of the NCP. The approach relies on combining geophysical datasets. We used bathymetry, bathymetric position index, median grain size, mud content, gravel content and bed shear stress. The datasets were classified, which limits the number of landscapes mapped, but also results in a loss of resolution. The marine-landscape map shows distinct marine landscapes, with a muddy basin in the north, several sand-wave fields, tidal ridges, and a more energetic shoreface. Comparison of the density distribution of Calianassa subterranea and the marinelandscape map shows a high correlation between the occurrence of the shrimp and the confines of the muddy basin in the north. We conclude that the initial validation of the marine-landscape map is promising, but further validation is needed.

17 References Aller, J. Y., Stupakoff, I., The distribution and seasonal characteristics of benthic communities on the Amazon shelf as indicators of physical processes. Continental Shelf Research, Vol. 16. No. 516, pp Alphen, van J.S.L.J., Damoiseaux, M.A., A morphological map of the Dutch shore face and adjacent part of the continental shelf (1: ). Nota directie Noordzee, pp Bouma, H. et al., A Dutch ecotope system for coastal waters. Report RIKZ, pp Connor, D.W., Gilliland, P.M., Golding, N, Robinson, P., Todd, D., & Verling, E UKSeaMap: the mapping of seabed and water column features of UK seas. Joint Nature Conservation Committee, Peterborough. Degraer, S., Wittoeck, J., Appeltans, W., Cooreman, K., Deprez, T., Hillewaert, H., Hostens, K., Mees, J., VanDen Berghe, W., Vincx, M., De macrobenthosatlas van het Belgisch deel van de Noordzee. Federaal Wetenschapsbeleid D/2005/1191/5. p Jeffrey, D. Laban, C., Niessen, A.H.C.M., Shuttenhelm, R.T.E Seabed sediments and Holocene geology. Ordance Survey. Golding, N., Vincent, M. A., and Connor, D. W., Irish Sea Pilot - Report on the development of a Marine Landscape classification for the Irish Sea. JNCC, pp Ledden, M. van, et al Effecten van Maasvlakte 2 op de Waddenzee en Noordzee kustzone Spoor 1 Gedetailleerd Modellenonderzoek. Havenbedrijf Rotterdam N.V. & Rijksinstituut voor Kust en Zee Maljers, D., J. Gunnink., Interpolation of measured grain-size fractions. In this issue. Schelfaut, K., Defining marine landscapes on the Belgian continental shelf as an approach to holistic habitat mapping. Master thesis, University Ghent, pp Rijn, L.C., Principles of sediment in transport in rivers, estuaries and coastal seas. Aqua publications, p Rinehart, R.W., et al., ArcGIS 8.x Benthic Terrain Modeler: Analysis in American Samoa. Proceedings of the 24th Annual ESRI User Conference, San Diego, CA, Paper 1433.

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