Domenico Chiarella , Sergio G. Longhitano, Marcello Tropeano

Traditional sequence stratigraphic models provide limited understanding of internal complexity and variability when applied to mixed siliciclastic-carbonate strata accumulated in tectonically active settings. Coeval Lower Pleistocene (Gelasian) shallow-marine, mixed siliciclastic-carbonate depositional wedges accumulated within an active piggy-back basin along the southern Italy fold-and thrust-belt are characterized by similar internal architecture of sequences but different stacking patterns. In particular, four coastal wedges (up to 30 m thick each), just a few kilometers (~2 km) apart from each other, show aggradational versus progradational stacking patterns related to their location within a deforming piggy-back basin. In all the studied sections, mixed siliciclastic-carbonate strata form isolated sedimentary wedges organized into three vertically stacked transgressive–regressive sequences bounded by sharp flooding surfaces. Aggradational versus progradational internal architecture results from (1) local syndepositional compressive and/or extensional tectonics controlling differential uplift and subsidence, and (2) sediment supply characterized by a combination of intrabasinal and extrabasinal siliclicastics and carbonates. Aggradation occurs in areas showing a balance between both accommodation and sediment supply, and siliciclastic and carbonate fractions. Progradation is typical of supply-dominated areas located close to the active anticline, and dominated by the carbonate fraction. The present work documents the local variability of stratal stacking patterns and sediment supply (siliciclatic-carbonate ratio). We highlight the limitations of using sequence architectures and systems tracts for base-level changes and basin reconstructions in tectonically active settings. It is of great importance not only to correctly interpret the stacking pattern, but also to increase our understanding of the type of sediment (siliciclastic versus carbonate) and sedimentation rate, sedimentation loci, and subsurface prediction.