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Taphonomic and supplement data for: Quantification and mitigation of taphonomic biases in multi-taxon marine fossil assemblages using a mass-based, fragment-inclusive sampling approach

Torres, Luis12; Kowalewski, Michał12

Published Sep 24, 2026 on Dryad. https://doi.org/10.5061/dryad.g4f4qrg4f

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Abstract

Here we propose a fragment-inclusive mass-based (FIMB) approach to mitigate taphonomic biases and improve quantitative estimates of faunal composition in paleoecological studies. Using sympatric assemblages of irregular echinoids and shell-bearing mollusks collected from contemporary, shallow-water seafloors across four regions ([1] Carrabelle, Florida; [2] Cedar Key, Florida; [3] Curaçao, Netherlands Antilles; [4] Florida Keys, Florida), we tested the hypothesis that FIMB produces less biased estimates of faunal composition than traditional fragment-exclusionary (complete specimens only) mass or count-based approaches. We also tested two auxiliary taphonomic hypotheses, implied by the expected lower preservational potential of irregular echinoids compared to sympatric mollusks: (1) Irregular echinoid tests fragment more frequently than mollusk shells; (2) Whole specimen live-dead proportions are higher for irregular echinoids than for mollusks. Results support both taphonomic hypotheses, with irregular echinoids exhibiting higher fragmentation estimates and live-dead proportions than sympatric mollusks. However, both taxa are well represented by fragments. Consequently, the FIMB approach provides estimates of relative abundance of echinoids that better approximate their relative abundance in live assemblages. In contrast, traditional fragment-exclusionary approaches indicated that irregular echinoids were either absent or at most extremely rare in death assemblages. Our results demonstrate that although the FIMB approach offers lower taxonomic resolution than the methods based entirely on whole specimens, the fragment-inclusive method improves estimates of faunal composition by mitigating pronounced taphonomic biases that can affect multi-taxic assemblages.