TAPHONOMIC PUZZLE: DECODING SHELL FRAGMENTATION AS A WINDOW INTO FRESHWATER BIVALVE PRESERVATION

Shell fragmentation is a key taphonomic process shaping the fidelity of molluscan death and fossil assemblages. Fragmentation and breakage reflect complex interactions between physical, chemical, and biological factors. In freshwater bivalves, recognizing fragmentation patterns helps uncover preservation and conservation biases, offering insights into the environmental conditions influencing shell accumulations. Decoding these signatures is essential for reconstructing accurate paleoenvironmental and paleoecological scenarios. The study was carried out in the Santa Maria watershed in southwestern Rio Grande do Sul, near the Uruguay border. Sampling occurred on point bars along the Santa Maria River, within the municipalities of Rosário do Sul and Cacequi. Manual collection was performed by two researchers over two-hour sessions at each of the 10 sampling sites during the dry season. The analysis focused on shells from two native bivalve genera, Anodontites and Diplodon, selecting only specimens showing structural damage. A total of 410 fragmented shells were examined. Each shell was divided into a 3×3 grid to identify damage across nine defined regions, with damage codes from 1 to 12—codes 1 to 9 for specific areas and 10 to 12 for broader, multi-region damage. The data were then tabulated and subjected to statistical analysis to assess patterns of selective shell loss. The analysis of fragmentation patterns revealed that the umbonal region (code 2) is the most frequently affected area in D. martensi, D. delodontus, and D. hildae showed predominant fragmentation at the posterior-bottom-margin (code 7), while A. trapezialis exhibited fragmentation across multiple non-adjacent regions (code 12). These results indicate preferential breakage-dissolution zones in the umbonal area, posterior-bottom margin, and randomly scattered regions. A geographic Principal Component Analysis (gPCA) was applied to investigate the spatial variation of fragmentation patterns across sampling sites. The first principal component (PC1) separated sites with negative scores (SMa-3A, SMa-3B, SMa-4, SMa-17) from those with positive scores (SMa-5, SMa-7, SMa-10, SMa-14, SMa-15A, SMa-15B), suggesting a geographic or environmental gradient. PC2 highlighted additional variation, distinguishing sites like SMa-10 and SMa-17 (high positive scores) from SMa-15B (negative score). These spatial patterns likely reflect local environmental factors such as topography, hydrology, or land use and geomorphological alterations.