Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-109-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-109-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A synthetic map of the north-west European Shelf sedimentary environment for applications in marine science
Robert J. Wilson
CORRESPONDING AUTHOR
812 Livingstone Tower, Department of Mathematics and Statistics, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, UK
Douglas C. Speirs
812 Livingstone Tower, Department of Mathematics and Statistics, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, UK
Alessandro Sabatino
812 Livingstone Tower, Department of Mathematics and Statistics, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, UK
Michael R. Heath
812 Livingstone Tower, Department of Mathematics and Statistics, University of Strathclyde, 26 Richmond Street, Glasgow G1 1XH, UK
Related authors
Robert J. Wilson, Yuri Artioli, Giovanni Galli, James Harle, Jason Holt, Ana M. Queiros, and Sarah Wakelin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3810, https://doi.org/10.5194/egusphere-2024-3810, 2024
Short summary
Short summary
Marine heatwaves are of growing concern around the world. We use a state of the art ensemble of downscaled climate models to project how often heatwaves will occur in future across northwest Europe under a high-emissions scenario. The projections show that without emissions reductions, heatwaves will occur more than half of the time in future. We show that the seafloor is expected to experience much more frequent heatwaves than the sea surface in future.
Robert J. Wilson and Michael R. Heath
Ocean Sci., 15, 1615–1625, https://doi.org/10.5194/os-15-1615-2019, https://doi.org/10.5194/os-15-1615-2019, 2019
Short summary
Short summary
The North Sea became much less clear during the 20th century, with potential consequences for primary production. This study analyses the hypothesis that changes in wave regime were a key driver of this change. We hindcast bed shear stress over the 20th century using a long-term wave reanalysis. Shear stress increased by over 20 % in large parts of the southern and central North Sea during the 20th century. An increase of this magnitude would have caused a large decline in water clarity.
Robert J. Wilson, Yuri Artioli, Giovanni Galli, James Harle, Jason Holt, Ana M. Queiros, and Sarah Wakelin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3810, https://doi.org/10.5194/egusphere-2024-3810, 2024
Short summary
Short summary
Marine heatwaves are of growing concern around the world. We use a state of the art ensemble of downscaled climate models to project how often heatwaves will occur in future across northwest Europe under a high-emissions scenario. The projections show that without emissions reductions, heatwaves will occur more than half of the time in future. We show that the seafloor is expected to experience much more frequent heatwaves than the sea surface in future.
Ricardo González-Gil, Neil S. Banas, Eileen Bresnan, and Michael R. Heath
Biogeosciences, 19, 2417–2426, https://doi.org/10.5194/bg-19-2417-2022, https://doi.org/10.5194/bg-19-2417-2022, 2022
Short summary
Short summary
In oceanic waters, the accumulation of phytoplankton biomass in winter, when light still limits growth, is attributed to a decrease in grazing as the mixed layer deepens. However, in coastal areas, it is not clear whether winter biomass can accumulate without this deepening. Using 21 years of weekly data, we found that in the Scottish coastal North Sea, the seasonal increase in light availability triggers the accumulation of phytoplankton biomass in winter, when light limitation is strongest.
Matthew C. Pace, David M. Bailey, David W. Donnan, Bhavani E. Narayanaswamy, Hazel J. Smith, Douglas C. Speirs, William R. Turrell, and Michael R. Heath
Earth Syst. Sci. Data, 13, 5847–5866, https://doi.org/10.5194/essd-13-5847-2021, https://doi.org/10.5194/essd-13-5847-2021, 2021
Short summary
Short summary
We present synthetic maps of continuous properties of seabed sediments in the Firth of Clyde, SW Scotland. The data include proportions of mud, sand, and gravel fractions; whole-sediment median grain size; permeability; porosity; organic carbon and nitrogen content; and rates of natural disturbance by tidal currents. We show that the firth stores 3.42 and 0.33 million tonnes of organic carbon and nitrogen, respectively, in the upper 10 cm of sediment.
Robert J. Wilson and Michael R. Heath
Ocean Sci., 15, 1615–1625, https://doi.org/10.5194/os-15-1615-2019, https://doi.org/10.5194/os-15-1615-2019, 2019
Short summary
Short summary
The North Sea became much less clear during the 20th century, with potential consequences for primary production. This study analyses the hypothesis that changes in wave regime were a key driver of this change. We hindcast bed shear stress over the 20th century using a long-term wave reanalysis. Shear stress increased by over 20 % in large parts of the southern and central North Sea during the 20th century. An increase of this magnitude would have caused a large decline in water clarity.
Alessandro D. Sabatino, Chris McCaig, Rory B. O'Hara Murray, and Michael R. Heath
Ocean Sci., 12, 875–897, https://doi.org/10.5194/os-12-875-2016, https://doi.org/10.5194/os-12-875-2016, 2016
Short summary
Short summary
The present research describes the effect of wave–current interactions and wave–wave interactions during severe storms on the east coast of Scotland. In this area, results show that the currents contribute substantially to the modification of wave properties in the shallow coastal areas, while the wave–wave interactions are more important offshore.
Related subject area
Geosciences – Sedimentology
Modelling seabed sediment physical properties and organic matter content in the Firth of Clyde
A worldwide meta-analysis (1977–2020) of sediment core dating using fallout radionuclides including 137Cs and 210Pbxs
A database of marine and terrestrial radiogenic Nd and Sr isotopes for tracing earth-surface processes
Surficial sediment texture database for the south-western Iberian Atlantic margin
Matthew C. Pace, David M. Bailey, David W. Donnan, Bhavani E. Narayanaswamy, Hazel J. Smith, Douglas C. Speirs, William R. Turrell, and Michael R. Heath
Earth Syst. Sci. Data, 13, 5847–5866, https://doi.org/10.5194/essd-13-5847-2021, https://doi.org/10.5194/essd-13-5847-2021, 2021
Short summary
Short summary
We present synthetic maps of continuous properties of seabed sediments in the Firth of Clyde, SW Scotland. The data include proportions of mud, sand, and gravel fractions; whole-sediment median grain size; permeability; porosity; organic carbon and nitrogen content; and rates of natural disturbance by tidal currents. We show that the firth stores 3.42 and 0.33 million tonnes of organic carbon and nitrogen, respectively, in the upper 10 cm of sediment.
Anthony Foucher, Pierre-Alexis Chaboche, Pierre Sabatier, and Olivier Evrard
Earth Syst. Sci. Data, 13, 4951–4966, https://doi.org/10.5194/essd-13-4951-2021, https://doi.org/10.5194/essd-13-4951-2021, 2021
Short summary
Short summary
Sediment archives provide a powerful and unique tool for reconstructing the trajectory and the resilience of terrestrial and aquatic ecosystems facing major environmental changes. Establishing an age depth–model is the first prerequisite of any paleo-investigation. This study synthesizes the distribution of two radionuclides classically used to this aim, providing a worldwide reference to help the scientific community reach a consensus for dating recent sedimentary archives.
Cécile L. Blanchet
Earth Syst. Sci. Data, 11, 741–759, https://doi.org/10.5194/essd-11-741-2019, https://doi.org/10.5194/essd-11-741-2019, 2019
Short summary
Short summary
Processes occurring at the earth's surface (erosion, dust formation, weathering) determine the evolution of the landscape and play an important role in the global climate. The present database (compiled from a literature search) helps to determine the neodymium and strontium radioisotope signature of terrestrial and marine sediments to determine their provenance as well as present and past sediment transport pathways to oceanic basins.
Susana Costas, Margarida Ramires, Luisa B. de Sousa, Isabel Mendes, and Oscar Ferreira
Earth Syst. Sci. Data, 10, 1185–1195, https://doi.org/10.5194/essd-10-1185-2018, https://doi.org/10.5194/essd-10-1185-2018, 2018
Short summary
Short summary
This sample collection presents a database that integrates surficial sediment samples collected and analysed for textural characterization within the framework of a series of research projects. A total of 4727 samples within the framework of 24 projects developed between 1996 and 2015 along the southern Atlantic coast of the Iberian Peninsula, focusing along the Portuguese coast, including sediments from the continental shelf, beaches, estuaries, and coastal lagoons.
Cited articles
Akima, H. and Gebhardt, A.: akima: Interpolation of Irregularly and Regularly
Spaced Data, R package version 0.6-12, 2016. a
Aldridge, J. N., Parker, E. R., Bricheno, L. M., Green, S. L., and van der
Molen, J.: Assessment of the physical disturbance of the northern European
Continental shelf seabed by waves and currents, Cont. Shelf Res.,
108, 121–140, https://doi.org/10.1016/j.csr.2015.03.004, 2015. a, b, c, d, e, f, g, h, i
Avelar, S., van der Voort, T. S., and Eglinton, T. I.: Relevance of carbon
stocks of marine sediments for national greenhouse gas inventories of
maritime nations, Carbon Balance Manag., 12, 10,
https://doi.org/10.1186/s13021-017-0077-x, 2017. a
Bahn, V. and McGill, B. J.: Testing the predictive performance of distribution
models, Oikos, 122, 321–331, https://doi.org/10.1111/j.1600-0706.2012.00299.x, 2013. a
Baretta, J. W., Ebenhöh, W., and Ruardij, P.: The European regional seas
ecosystem model, a complex marine ecosystem model, Netherlands J.
Sea Res., 33, 233–246, https://doi.org/10.1016/0077-7579(95)90047-0, 1995. a
Basford, D. and Eleftheriou, A.: The benthic environment of the North Sea
(56∘ to 61∘ N), J. Mar. Biol. Assoc. UK, 68, 125–141,
https://doi.org/10.1017/S0025315400050141, 1988. a
BGS: BGS Legacy Particle Size Analysis uncontrolled data export, Tech. rep.,
British Geological Survey, 2013. a
Blackford, J. C.: An analysis of benthic biological dynamics in a North Sea
ecosystem model, J. Sea Res., 38, 213–230,
https://doi.org/10.1016/S1385-1101(97)00044-0, 1997. a
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001. a, b
Bricheno, L. M., Wolf, J., and Aldridge, J.: Distribution of natural
disturbance due to wave and tidal bed currents around the UK, Cont.
Shelf Res., 109, 67–77, https://doi.org/10.1016/j.csr.2015.09.013, 2015. a
Canty, A. J.: Resampling methods in R: the boot package, R News, 2, 2–7,
2002. a
Cavalli, M., Tarolli, P., Marchi, L., and Dalla Fontana, G.: The
effectiveness of airborne LiDAR data in the recognition of channel-bed
morphology, Catena, 73, 249–260, https://doi.org/10.1016/j.catena.2007.11.001, 2008. a
De Dominicis, M., O'Hara Murray, R., and Wolf, J.: Multi-scale ocean
response to a large tidal stream turbine array, Renewable Energ.,
114, 1160–1179,
https://doi.org/10.1016/j.renene.2017.07.058, 2017. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler,
M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J.,
Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N.,
and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of
the data assimilation system, Q. J. Roy. Meteor.
Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Diesing, M., Stephens, D., and Aldridge, J.: A proposed method for assessing
the extent of the seabed significantly affected by demersal fishing in the
Greater North Sea, ICES J. Mar. Sci., 70, 1085–1096,
https://doi.org/10.1093/icesjms/fst048, 2013. a, b
Diesing, M., Green, S. L., Stephens, D., Lark, R. M., Stewart, H. A., and Dove,
D.: Mapping seabed sediments: Comparison of manual, geostatistical,
object-based image analysis and machine learning approaches, Cont.
Shelf Res., 84, 107–119, https://doi.org/10.1016/j.csr.2014.05.004, 2014. a
Diesing, M., Kroger, S., Parker, R., Jenkins, C., Mason, C., and Weston, K.:
Predicting the standing stock of organic carbon in surface sediments of the
North-West European continental shelf, Biogeochemistry, 135, 183–200,
https://doi.org/10.1007/s10533-017-0310-4, 2017. a, b
Eddelbuettel, D., François, R., Allaire, J., Chambers, J., Bates, D., and
Ushey, K.: Rcpp: Seamless R and C++ integration, J. Stat.
Softw., 40, 1–18, 2011. a
Edmonds, D. and Slingerland, R.: Significant effect of sediment cohesion on
delta morphology, Nature Geosci., 3, 105–109, https://doi.org/10.1038/ngeo730,
2009. a
Egbert, G. D., Erofeeva, S. Y., and Ray, R. D.: Assimilation of altimetry data
for nonlinear shallow-water tides: Quarter-diurnal tides of the Northwest
European Shelf, Cont. Shelf Res., 30, 668–679,
https://doi.org/10.1016/j.csr.2009.10.011, 2010. a
Ellis, J. R., Milligan, S. P., Readdy, L., Taylor, N., and Brown, M. J.:
Spawning and nursery grounds of selected fish species in UK waters, Science
Series Technical Report, 147, 56, 2012. a
Falcini, F. and Jerolmack, D. J.: A potential vorticity theory for the
formation of elongate channels in river deltas and lakes, J.
Geophys. Res.-Earth Surface, 115, 1–18, https://doi.org/10.1029/2010JF001802,
2010. a
Falcini, F., Fagherazzi, S., and Jerolmack, D. J.: Wave-supported sediment
gravity flows currents: Effects of fluid-induced pressure gradients and flow
width spreading, Cont. Shelf Res., 33, 37–50,
https://doi.org/10.1016/j.csr.2011.11.004, 2012. a
Foden, J., Rogers, S. I., and Jones, A. P.: Human pressures on UK seabed
habitats: a cumulative impact assessment, Mar. Ecol. Prog. Ser.,
428, 33–47, 2011. a
Galparsoro, I., Connor, D. W., Borja, Á., Aish, A., Amorim, P., Bajjouk,
T., Chambers, C., Coggan, R., Dirberg, G., Ellwood, H., Evans, D., Goodin,
K. L., Grehan, A., Haldin, J., Howell, K., Jenkins, C., Michez, N., Mo, G.,
Buhl-Mortensen, P., Pearce, B., Populus, J., Salomidi, M., Sánchez, F.,
Serrano, A., Shumchenia, E., Tempera, F., and Vasquez, M.: Using EUNIS
habitat classification for benthic mapping in European seas: Present concerns
and future needs, Mar. Pollut. Bull., 64, 2630–2638,
https://doi.org/10.1016/j.marpolbul.2012.10.010, 2012. a
George, D. A. and Hill, P. S.: Wave climate, sediment supply and the depth of
the sand-mud transition: A global survey, Mar. Geol., 254, 121–128,
https://doi.org/10.1016/j.margeo.2008.05.005, 2008. a
Gray, J. S.: Species richness of marine soft sediments, Mar. Ecol.
Prog. Ser., 244, 285–297, https://doi.org/10.3354/meps244285, 2002. a
Halpern, B. S., Walbridge, S., Selkoe, K. A., Kappel, C. V., Micheli, F.,
D'Agrosa, C., Bruno, J. F., Casey, K. S., Ebert, C., Fox, H. E., Fukita, R.,
Heinemann, D., Lenihan, H. S., Madin, E. M. P., Perry, M. T., Selig, E. R.,
Spalding, M., Steneck, R., and Watson, R.: A Global Map of Human Impact on
Marine Ecosystems, Science, 319, 948–953, https://doi.org/10.1126/science.1149345,
2014. a
Hamilton, N.: ggtern: An Extension to `ggplot2', for the Creation of Ternary
Diagrams, R package version 2.2.1, 2017. a
Heath, M. R.: Ecosystem limits to food web fluxes and fisheries yields in the
North Sea simulated with an end-to-end food web model, Prog.
Oceanogr., 102, 42–66, https://doi.org/10.1016/j.pocean.2012.03.004, 2012. a
Heath, M., Sabatino, A., Serpetti, N., McCaig, C., and O'Hara Murray, R.:
Modelling the sensitivity of suspended sediment profiles to tidal current
and wave conditions, Ocean Coast. Manage., 147, 49–66,
https://doi.org/10.1016/j.ocecoaman.2016.10.018, 2016. a, b
Hijmans, R. J., Williams, E., and Vennes, C.: geosphere: Spherical
Trigonometry. R package version 1.2–28, CRAN, R-project, org/package=
geosphere, 2012. a
Huang, Z., Nichol, S. L., Siwabessy, J. P., Daniell, J., and Brooke, B. P.:
Predictive modelling of seabed sediment parameters using multibeam acoustic
data: a case study on the Carnarvon Shelf, Western Australia, International
J. Geogr. Information Sci., 26, 283–307,
https://doi.org/10.1080/13658816.2011.590139, 2012. a
James, G., Witten, D., Hastie, T., and Tibshirani, R.: An introduction to
Statistical Learning, Springer, New York, https://doi.org/10.1007/978-1-4614-7138-7, 2013. a
Li, J., Heap, A. D., Potter, A., Huang, Z., and Daniell, J. J.: Can we improve
the spatial predictions of seabed sediments? A case study of spatial
interpolation of mud content across the southwest Australian margin,
Cont. Shelf Res., 31, 1365–1376, https://doi.org/10.1016/j.csr.2011.05.015,
2011. a
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, R
news, 2, 18–22, https://doi.org/10.1177/154405910408300516, 2002. a, b
Loh, W.-Y.: Classification and regression trees, Wiley Interdisciplinary
Reviews: Data Mining and Knowledge Discovery, 1, 14–23,
https://doi.org/10.1002/widm.8, 2011. a
Lohse, L., Malschaert, J. F. P., Slomp, C. P., Helder, W., and Vanraaphorst,
W.: Nitrogen cycling in North Sea sediments: interaction of denitrification
and nitrification in offshore and coastal areas, Mar. Ecol. Prog.
Ser., 101, 283–296, https://doi.org/10.3354/meps101283, 1993. a, b
McLaren, P., Collins, M. B., Gao, S., and Powys, R. I. L.: Sediment dynamics
of the Severn Estuary and Inner Bristol Channel, J. Geol.
Soc., 150, 589–603, https://doi.org/10.1144/gsjgs.150.3.0589, 1993. a
Neill, S. P., Scourse, J. D., Bigg, G. R., and Uehara, K.: Changes in wave
climate over the northwest European shelf seas during the last 12,000 years,
J. Geophys. Res., 114, C06015, https://doi.org/10.1029/2009JC005288, 2009. a
Neill, S. P., Scourse, J. D., and Uehara, K.: Evolution of bed shear stress
distribution over the northwest European shelf seas during the last 12,000
years, Ocean Dynam., 60, 1139–1156, https://doi.org/10.1007/s10236-010-0313-3,
2010. a
Pateiro-López, B. and Rodríguez-Casal, A.: Generalizing the Convex Hull of a Sample: The R
Package Alphahull, J. Stat. Softw., 34, 1–28,
https://doi.org/10.18637/jss.v034.i05, 2010. a
Porter-Smith, R., Harris, P. T., Andersen, O. B., Coleman, R., Greenslade, D.,
and Jenkins, C. J.: Classification of the Australian continental shelf based
on predicted sediment threshold exceedance from tidal currents and swell
waves, Mar. Geol., 211, 1–20, https://doi.org/10.1016/j.margeo.2004.05.031, 2004. a
Roberts, D. R., Bahn, V., Ciuti, S., Boyce, M. S., Elith, J., Guillera-Arroita,
G., Hauenstein, S., Lahoz-Monfort, J. J., Schroder, B., Thuiller, W., Warton,
D. I., Wintle, B. A., Hartig, F., and Dormann, C. F.: Cross-validation
strategies for data with temporal, spatial, hierarchical, or phylogenetic
structure, Ecography, pp. 1–17, https://doi.org/10.1111/ecog.02881, 2017. a, b
Robinson, K. A., Ramsay, K., Lindenbaum, C., Frost, N., Moore, J., Wright,
A. P., and Petrey, D.: Predicting the distribution of seabed biotopes in the
southern Irish Sea, Cont. Shelf Res., 31, S120–S131,
https://doi.org/10.1016/j.csr.2010.01.010, 2011. a
Ruardij, P. and Van Raaphorst, W.: Benthic nutrient regeneration in the
ERSEM ecosystem model of the North Sea, Neth. J. Sea Res.,
33, 453–483, https://doi.org/10.1016/0077-7579(95)90057-8, 1995. a, b, c
Scourse, J., Uehara, K., and Wainwright, A.: Celtic Sea linear tidal sand
ridges, the Irish Sea Ice Stream and the Fleuve Manche: Palaeotidal modelling
of a transitional passive margin depositional system, Mar. Geol., 259,
102–111, https://doi.org/10.1016/j.margeo.2008.12.010, 2009. a
Serpetti, N., Heath, M., Rose, M., and Witte, U.: High resolution mapping of
sediment organic matter from acoustic reflectance data, Hydrobiologia, 680,
265–284, https://doi.org/10.1007/s10750-011-0937-4, 2012. a, b, c
Serpetti, N., Witte, U. F. M., and Heath, M. R.: Statistical modelling of
variability in sediment-water nutrient and oxygen fluxes, Front. Earth
Sci., 4, 1–17, https://doi.org/10.3389/feart.2016.00065, 2016. a, b
Soulsby, R. L. and Smallnan, J. V.: A direct method of calculating bottom
orbital velocity under waves, Tech. rep., Report SR76, Hydraulics Research
Wallingford, 1986. a
Stephens, D. and Diesing, M.: Towards quantitative spatial models of seabed
sediment composition, PLoS ONE, e0142502,
https://doi.org/10.1371/journal.pone.0142502, 2015. a, b, c, d
Thrush, S. F., Hewitt, J. E., Norkko, A., Nicholls, P. E., Funnell, G. A., and
Ellis, J. I.: Habitat change in estuaries: Predicting broad-scale responses
of intertidal macrofauna to sediment mud content, Mar. Ecol. Prog.
Ser., 263, 101–112, https://doi.org/10.3354/meps263101, 2003. a
Tiessen, M. C., Eleveld, M. A., Nauw, J. J., Nechad, B., and Gerkema, T.:
Depth dependence and intra-tidal variability of Suspended Particulate Matter
transport in the East Anglian plume, J. Sea Res., 127, 2–11,
https://doi.org/10.1016/j.seares.2017.03.008, 2017. a
Uehara, K., Scourse, J. D., Horsburgh, K. J., Lambeck, K., and Purcell, A. P.:
Tidal evolution of the northwest European shelf seas from the Last Glacial
Maximum to the present, J. Geophys. Res.-Oceans, 111, 1–15,
https://doi.org/10.1029/2006JC003531, 2006. a, b
Valerius, J., V., V. L., S., V. H., Let, J. O., and Zeiler, M.: Trans-national
database of North Sea sediment data. Data compilation by Federal Maritime and
Hydrographic Agency (Germany); Royal Belgian Institute of Natural Sciences
(Belgium); TNO (Netherlands) and Geological Survey of Denmark and Greenland
(Denmark)., Tech. rep., 2015. a, b
VanDerWal, J., Falconi, L., Januchowski, S., Shoo, L., and Storlie, C.:
SDMTools: Species Distribution Modelling Tools: Tools for processing data
associated with species distribution modelling exercises, R package version 1.1-221, 2014. a
Vasquez, M., Mata Chacón, D., Tempera, F., O'Keeffe, E., Galparsoro,
I., Sanz Alonso, J. L., Gonçalves, J. M. S., Bentes, L., Amorim, P.,
Henriques, V., McGrath, F., Monteiro, P., Mendes, B., Freitas, R., Martins,
R., and Populus, J.: Broad-scale mapping of seafloor habitats in the
north-east Atlantic using existing environmental data, J. Sea Res., 100, 120–132, https://doi.org/10.1016/j.seares.2014.09.011, 2015. a, b, c
Ward, S. L., Neill, S. P., Van Landeghem, K. J. J., and Scourse, J. D.:
Classifying seabed sediment type using simulated tidal-induced bed shear
stress, Mar. Geol., 367, 94–104, https://doi.org/10.1016/j.margeo.2015.05.010,
2015. a, b, c
Wessel, P. and Smith, W. H. F.: A global, self-consistent, hierarchical,
high-resolution shoreline, J. Geophys. Res., 101, 8741–8743,
1996. a
Wickham, H.: ggplot2: elegant graphics for data analysis, Springer, New York, 2016. a
Wickham, H., Francois, R., Henry, L., and Müller, K.: dplyr: A Grammar of Data Manipulation, R package version 0.7.0, 2017. a
Wiesner, M. G., Haake, B., and Wirth, H.: Organic facies of surface sediments
in the North Sea, Org. Geochem., 15, 419–432,
https://doi.org/10.1016/0146-6380(90)90169-Z, 1990. a, b
Wilson, M. F. J., O'Connell, B., Brown, C., Guinan, J. C., and Grehan, A. J.:
Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping
on the Continental Slope, Marine Geodysy., 30, 3–35, https://doi.org/10.1080/01490410701295962, 2007. a
Wilson, R., Heath, M., Speirs, D., and Sabatino, A.: Data for: “A synthetic map of the northwest European Shelf sedimentary environment for applications in marine
science”, available at:
https://doi.org/10.15129/1e27b806-1eae-494d-83b5-a5f4792c46fc, last access:
8 November 2017.
Wood, S. N.: mgcv: GAMs and generalized ridge regression for R, R News, 1,
20–25, https://doi.org/10.1159/000323281, 2001. a
Wood, S. N.: Generalized Additive Models: an introduction with R, Chapman and
Hall, London, https://doi.org/10.1111/j.1541-0420.2007.00905_3.x, 2006. a
Wright, L. D. and Friedrichs, C. T.: Gravity-driven sediment transport on
continental shelves: A status report, Cont. Shelf Res., 26,
2092–2107, https://doi.org/10.1016/j.csr.2006.07.008, 2006. a
Wright, M. N. and Ziegler, A.: ranger: A Fast Implementation of Random Forests
for High Dimensional Data in C++ and R, J. Stat. Softw., 77,
https://doi.org/10.18637/jss.v077.i01, 2017. a
Short summary
We provide new maps of the sedimentary environment in the north-west European Continental Shelf. Maps are blended products of interpolated field estimates and statistical predictions. Data products include mud, sand and gravel percentages, median grain sizes, rock cover, carbon and nitrogen content, porosity and permeability, wave and tidal velocities, and natural disturbance rates. These maps can be used in applications such as species distribution modelling and ecosystem modelling.
We provide new maps of the sedimentary environment in the north-west European Continental Shelf....
Altmetrics
Final-revised paper
Preprint