Highlighting broad-scale morphometric diversity of the seabed using geomorphons

Authors

DOI:

https://doi.org/10.34194/geusb.v52.8337

Keywords:

morphometric features, geodiversity, geomorphons, seabed mapping, marine geology

Abstract

Morphometric diversity is an important component of overall seabed geodiversity. Automated methods for classification of morphometric features (ridges, peaks, valleys etc.) provide a convenient way of classifying large volumes of data in a consistent and repeatable way and a basis for assessing morphometric diversity. Here, we apply ‘geomorphons’, a pattern recognition approach to morphometric feature classification, to 100 m resolution multibeam bathymetry data in the Barents and Norwegian Seas, Norway. The study area spans depths from a few metres to nearly 6000 m across several geological settings. Ten unique morphometric features are delineated by the geomorphon analysis. From these results, we compute the variety of features per 10 km2. This simple ‘geomorphon richness’ measure highlights broad-scale morphometric diversity across the study area. We compare the richness results with terrain attributes and across physiographic regions. Our results provide new regional insights, which together with more detailed information will help guide follow-up surveys as well as identifying diversity hotspots, which may require special management.

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References

Bailey, J.J., Boyd, D.S., Hjort, J., Lavers, C.P. & Field, R. 2017: Modelling native and alien vascular plant species richness: At which scales is geodiversity most relevant? Global Ecology and Biogeography 26(7), 763–776. https://doi.org/10.1111/geb.12574

Bøe, R., Bjarnadóttir, L.R., Elvenes, S., Dolan, M., Bellec, V., Thorsnes, T., Lepland, A. & Longva, O. 2020: Revealing the secrets of Norway’s seafloor – geological mapping within the MAREANO programme and in coastal areas. Geological Society, London, Special Publications 505, 57–59. https://doi.org/10.1144/sp505-2019-82

Dekavalla, M. & Argialas, D. 2017: Object-based classification of global undersea topography and geomorphological features from the SRTM30_PLUS data. Geomorphology 288, 66–82. https://doi.org/10.1016/j.geomorph.2017.03.026

Di Stefano, M. & Mayer, L.A. 2018: An automatic procedure for the quantitative characterization of submarine bedforms. Geosciences 8(1), 28. https://doi.org/10.3390/geosciences8010028

Dikau, R. 1989: The application of a digital relief model to landform analysis. In: Raper, J.F. (ed.): Three dimensional applications in Geographical Information Systems. 51–77. Taylor and Francis.

Dolan, M.F.J., Bøe, R. & Bjarnadóttir, L.R. 2022: Delivering seabed geodiversity information through multidisciplinary mapping initiatives: experiences from Norway. GEUS Bulletin 52, 8325. https://doi.org/10.34194/geusb.v52.8325

Dove, D. et al. 2016: Seabed geomorphology: a two-part classification system. OR/16/001. Unpublished report, British Geological Survey, UK. http://nora.nerc.ac.uk/id/eprint/514946 (accessed November 2022).

Dove, D. et al. 2020: A two-part seabed geomorphology classification scheme (v.2); part 1: morphology features glossary. https://doi.org/10.5281/zenodo.4075248

Elvenes, I.S. 2014: Landscape Mapping in MAREANO. NGU Report 2013.035. 40 pp. Institutional report, Geological Survey of Norway, Trondheim. https://www.ngu.no/upload/Publikasjoner/Rapporter/2013/2013_035.pdf

Evans, I.S. 2012: Geomorphometry and landform mapping: What is a landform? Geomorphology 137(1), 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029

Evans, J.S. 2020: _spatialEco_. R package version 1.34. https://github.com/jeffreyevans/spatialEco

Federal Geographic Data Committee. 2012: Coastal and marine ecological classification standard version 4.0. 339 pp. https://www.fgdc.gov/standards/projects/cmecs-folder/CMECS_Version-_4_Final_for_FGDC-20120111.pdf (accessed Novemer 2022).

Fisher, P., Wood, J. & Cheng, T. 2004: Where is Helvellyn? Fuzziness of multi-scale landscape morphometry. Transactions of the Institute of British Geographers 29(1), 106–128.

Gray, M. 2004: Geodiversity: valuing and conserving abiotic nature. 512 pp. Chichester, UK: John Wiley & Sons.

GEBCO Bathymetric Compilation Group: 2019. The GEBCO_2019 Grid – a continuous terrain model of the global oceans and land. British Oceanographic Data Centre, National Oceanography Centre, NERC, UK. https://doi.org/10.5285/836f016a-33be-6ddc-e053-6c86abc0788e

Jasiewicz, J. & Stepinski, T.F. 2013: Geomorphons – a pattern recognition approach to classification and mapping of landforms. Geomorphology 182, 147–156. https://doi.org/10.1016/j.geomorph.2012.11.005

Lecours, V., Dolan, M.F.J., Micallef, A. & Lucieer, V.L. 2016: A review of marine geomorphometry, the quantitative study of the seafloor. Hydrology and Earth System Sciences 20(8), 3207–3244. https://doi.org/10.5194/hess-20-3207-2016

MacMillan, R.A. & Shary, P.A. 2009: Chapter 9 landforms and landform elements in geomorphometry. In: Hengl, T. & Reuter, H.I. (eds): Developments in soil science 33, 227–254. Elsevier. https://doi.org/10.1016/S0166-2481(08)00009-3

Masetti, G. 2022: BRESS v.2.3. https://www.hydroffice.org/bress/main

Masetti, G., Mayer, L.A. & Ward, L.G. 2018: A bathymetry- and reflectivity-based approach for seafloor segmentation. Geosciences 8(1), 14. https://doi.org/10.3390/geosciences8010014

Nanson, R.A., Borissova, I., Huang, Z., Post, A., Nichol, S.L., Spinoccia, M., Siwabessy, J.W., Sikes, E.L. & Picard, K. 2022: Cretaceous to Cenozoic controls on the genesis of the shelf-incising Perth Canyon; insights from a two-part geomorphology mapping approach. Marine Geology 445, 106731. https://doi.org/10.1016/j.margeo.2022.106731

Nanson, R. et al. 2023: A two-part seabed geomorphology classification scheme; Part 2: Geomorphology classification framework and glossary (Version 1.0). Zenodo. https://doi.org/10.5281/zenodo.7804019

Novaczek, E., Devillers, R. & Edinger, E. 2019: Generating higher resolution regional seafloor maps from crowd-sourced bathymetry. PLoS One 14(6), e0216792. https://doi.org/10.1371/journal.pone.0216792

Pál, M. & Albert, G. 2021: The use of geomorphons in geodiversity assessment. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1363. https://doi.org/10.5194/egusphere-egu21-1363

Sappington, J.M., Longshore, K.M. & Thompson, D.B. 2007: Quantifying landscape ruggedness for animal habitat analysis: A case study using bighorn sheep in the Mojave Desert. Journal of Wildlife Management 71(5), 1419–1426. https://doi.org/10.2193/2005-723

Schmidt, J. & Andrew, R. 2005: Multi-scale landform characterization. Area 37(3), 341–350. https://doi.org/10.1111/j.1475-4762.2005.00638.x

Schrodt, F. et al. 2019: To advance sustainable stewardship, we must document not only biodiversity but geodiversity. Proceedings of the National Academy of Sciences 116(33), 16155–16158. https://doi.org/10.1073/pnas.1911799116

Sowers, D.C., Masetti, G., Mayer, L.A., Johnson, P., Gardner, J.V. & Armstrong, A.A. 2020: Standardized geomorphic classification of seafloor within the United States Atlantic canyons and continental margin. Frontiers in Marine Science 7, 9. https://doi.org/10.3389/fmars.2020.00009

Tukiainen, H. & Bailey, J.J. 2022: Enhancing global nature conservation by integrating geodiversity in policy and practice. Conservation Biology 37, e14024. https://doi.org/10.1111/cobi.14024

Vörös, F., Pál, M., van Wyk de Vries, B. & Székely, B. 2021: Development of a new type of geodiversity system for the scoria cones of the Chaîne des Puys based on geomorphometric studies. Geosciences 11(2), 58. https://doi.org/10.3390/geosciences11020058

Wood, J. 1996: The geomorphological characterisation of digital elevation models. University of Leicester. Thesis. https://hdl.handle.net/2381/34503 (accessed November 2022)

Maps of Norway sea

Published

06-09-2023

How to Cite

Dolan, M. F. J., & Bjarnadóttir, L. R. (2023). Highlighting broad-scale morphometric diversity of the seabed using geomorphons. GEUS Bulletin, 52. https://doi.org/10.34194/geusb.v52.8337