Bathymetric trend of Late Cretaceous southern Tethys upwelling regime based on benthic foraminifera |
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| Institution: | 1. Dead Sea and Arava Science Center, Tamar Regional Council, Dead Sea Mobile Post, 86910, Israel;2. Department of Geological and Environmental Sciences, Ben-Gurion University of the Negev, P.O.B 653, Beer Sheva, 84105, Israel;3. Geological Survey of Israel, Jerusalem, 95501, Israel;1. CEREGE UM34, CNRS (UMR 7330), IRD (UMR 161), Collège de France, USC INRA, OSU-Institut PYTHEAS, Aix-Marseille Université, Centre Saint-Charles, Case 67, Place Victor Hugo 3, F-13331 Marseille cedex 03, France;2. NARG, School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Williamson Building, Oxford Road, Manchester M13 9PL, United Kingdom;3. Groupement d''Intérêt Paléontologique, Science et Exposition, 60 bd Georges Richard, 83000 Toulon, France;4. University of Geneva, Department of Earth Sciences, 13 Rue des Maraîchers, 1205 Geneva, Switzerland;1. Exploration Department, Egyptian Petroleum Research Institute, Nasr City, 11727, Egypt;2. Earth and Environmental Sciences Department, Hashemite University, PO Box 150459, 13115, Jordan;3. Halliburton, 97 Jubilee Avenue, Milton Park, Oxford, OX14 4RW, UK;1. Institut für Geologie, Mineralogie und Geophysik, Ruhr-Universität Bochum, Universitätsstraße 150, 44801 Bochum, Germany;2. Senckenberg Naturhistorische Sammlungen Dresden, Museum für Mineralogie und Geologie, Sektion Paläozoologie, Königsbrücker Landstraße 159, 01109 Dresden, Germany;1. Instituto de Estudios Andinos Don Pablo Groeber (UBA-CONICET), Departamento de Ciencias Geológicas, Universidad de Buenos Aires, Pabellón II, Ciudad Universitaria, 1428, Buenos Aires, Argentina;2. School of Environmental Sciences, University of Hull, Cottingham Road, Hull, HU6 7RX, UK;3. Department of Earth Sciences, University College London, Gower Street, London, WC1E 6BT, UK |
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| Abstract: | Benthic foraminifera are one of the most commonly used indicators to infer paleodepth. The information on depth distribution of fossil benthic foraminifera is generally obtained from normal marine environments. However, a significant gap exists with respect to implications of benthic foraminiferal distributions in unique sedimentary successions, such as those deposited under upwelling regimes. In such settings, the paleobathymetric signal is somewhat obscured by the extreme food fluxes and oxygen depletion at the seafloor that cause changes in benthic foraminiferal assemblage composition. Nevertheless, the dynamics of upwelling systems, and as a result the sediment and organic matter accumulation, are known to be directly influenced by eustatic changes, making paleobathymetric reconstruction highly valuable for understanding these systems.The Upper Cretaceous high productivity marine succession of southern Israel, with its variable lithologies, provides a unique opportunity for addressing this issue. Through this succession, a significant turnover in the benthic foraminiferal assemblages is observed associated with a sharp change in lithology from phosphate (Phosphate Member) to organic rich carbonates (Oil Shale Member; OSM). Statistical nMDS analysis distinguished four groups of species indicative of distinct depth habitats: <200 m, 100–300 m, 300–500 m, and >500 m. Each one of these groups corresponds to different parts of the sequence. According to our analysis, the shift in the benthic foraminiferal assemblages is attributed to a distinct regional deepening from shelf environment (<200 m) in the Phosphate Member (upper Campanian) to upper bathyal (200–500 m) at the base of OSM (base Maastrichtian), and deeper to middle bathyal (>500 m) during the Maastrichtian. While taking into account other factors affecting benthic foraminiferal distribution, this study demonstrates that depth distribution models based on normal marine settings might also be applicable as proxies for paleobathymetry in high productivity environments. |
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| Keywords: | High productivity Israel Campanian-Maastrichtian interval Depth distribution model Statistical nMDS analysis |
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