Availability and type of energy regulate the global distribution of neritic carbonates

Abstract

The study of carbonate rocks is primarily reliant on microfacies analysis, which is strongly based on the comparison with modern allochem assemblages. Despite the existence of several models aimed at comprehensively explaining, on the bases of abiotic factors, the distribution of carbonate-producing organisms, a global, quantitative and standardized overview of the composition of shallow-water carbonate sediments is still missing. Aiming to address this gap in knowledge, the current study provides a global database of the available quantitative data on neritic carbonate sediments. This is paired with satellite-based observations for the abiotic parameters. The results highlight a non-linear, multi-variable, dependence in the distribution of allochems and suggest that depth, temperature, and trophic state are, to a certain extent, interchangeable. The implication of which is a level of non-uniqueness for paleoenvironmental interpretation. The resulting distribution is rather continuous and stretches along an energy gradient. A gradient extending from solar energy, with autotrophs and symbiont-bearing organisms to chemical energy with heterotrophs. Further, quantitative data from modern oceans are still required to disentangle the remaining elements of uncertainty.

Figure 1

Location map of data points aggregated for this study and delineation of the climate belts discussed in the text. Green points are locations for which sufficient information was available; red points are locations for which some description exists, but no quantitative data. Abbreviation mbpsl stands for meters below present sea level. Map generated with QGIS 3.28.1.

Figure 2

Box and whiskers plot showing the range of all the variables discussed in this study. The center of the box represents the median with the boxes ranging from the 25th to the 75th percentiles. Abbreviation mbpsl stands for meters below present sea level. See text for other abbreviations.

Figure 3

Correlation matrix with Spearman’s ρ for all the variables analysed in this study. Note that SW is a function of WD while KD is a function of Chlα, and as such, their correlation is expected. Red indicates a positive correlation, and Blue negative. Cells with no statistical significance were left uncolored. See text for abbreviations.

Figure 4

Ordination analyses. (a) CCA analysis showing the data points with respect to environmental variables and climate belts grouping. (b) As in (a) but showing allochems vectors without data points. (c) DCA analysis with all variables and data points, specific allochems groups are noted; arrow and additional text are for visualization.