New insights into geochemical behaviour in ancient marine carbonates (Upper Jurassic Ammonitico Rosso): Novel proxies for interpreting sea‐level dynamics and palaeoceanography

Abstract

Elemental concentrations in Phanerozoic sea water are known to fluctuate both in time and space. With regard to carbonates precipitated from marine fluids, elemental concentrations in the carbonate crystal lattice are affected by a complex array of equilibrium and non-equilibrium as well as postdepositional alteration processes. To assess the potential of carbonate elemental chemostratigraphy, seven Upper Jurassic sections were investigated along a proximal to distal transect across the south-east Iberian palaeomargin. The aim was to explore stratigraphic and spatial variations in calcium, strontium, magnesium, iron and manganese elemental abundances. The epicontinental geochemical record is influenced by the combination of continental runoff and a significant diagenetic overprint. In contrast, the epioceanic geochemical record agrees with reconstructed open marine sea water values, reflecting a moderate degree of syn-depositional to early marine pore water diagenesis. Establishing a fair degree of preservation of matrix micrite, a thorough statistical approach was applied and elemental associations tested for their environmental significance. Principal component and hierarchical cluster analyses revealed a persistent relation between carbonate magnesium, iron and strontium abundances. Processes related to early diagenetic nodulation in Ammonitico Rosso facies most probably account for the incorporation of these elements in the calcium carbonate lattice. The clear decoupling of carbonate manganese abundance with respect to the remaining elements is documented and related to high sea floor spreading rates and hydrothermal activity during the Late Jurassic. The investigation of potential time-fluctuation of geochemical patterns was approached through variogram computation. The observed temporal behaviour is most likely to be forced by relative sea-level dynamics, reflecting Late Jurassic palaeoceanographic conditions and potential planetary interactions. The data obtained in this study highlight the utility of elemental data from carbonate matrix micrites as geochemical proxies for studying the influence of remote trigger factors.

Regression trees for modeling geochemical data—An application to Late Jurassic carbonates (Ammonitico Rosso)

“…The averaged estimated skeletal abundance for the entire stratigraphic interval under scope is used to allow a comparison with the applied model. This approach clearly masks fluctuations of this parameter during the studied time frame, addressed elsewhere (Coimbra and Olóriz, 2012a;Coimbra et al, 2014;and work in progress).…”

“…Changes in the selected variables will be interpreted as reflecting paleoenvironmental information. This interpretation is valid for all the samples under consideration since a thorough diagenetic screening was performed (not shown here, see Coimbra et al, 2009Coimbra et al, , 2014Coimbra and Olóriz, 2012b).…”

“…Isotopic values are reported in the standard δ-notation in per mil (‰) relative to Vienna-Pee Dee Belemnite (V-PDB) and elemental abundance in absolute values (ppm). All geochemical measurements were performed at the facilities of the Institute for Geology, Mineralogy and Geophysics, Ruhr University Bochum (Germany), for details on used equipments and analytical precision see Coimbra et al (2009Coimbra et al ( , 2014 and Coimbra and Olóriz (2012b). Photomicrographs of thin sections produced from each hand specimen provided a quantitative estimate of skeletal abundance by means of pixel counting (Coimbra and Olóriz, 2012a and examples shown in Fig.…”

“…This contribution reports the application of regression trees to a previously explored ancient carbonate record (Coimbra et al, 2009(Coimbra et al, , 2014Coimbra and Olóriz, 2012b). This approach is, to the knowledge of the authors, attempted here for the first time.…”

“…This is the case of the present research, related to a considerably large geochemical dataset retrieved from ancient carbonates. This dataset was previously and successfully interpreted with standard statistic tools (Coimbra et al, 2014). It is now used to apply more advanced tools in order to extract information that was otherwise masked.…”