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Ecological and paleontological implications of trematode-induced morphospace inflation and pallial sinus reduction in bivalve hosts

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DataONE2026-02-05 更新2026-02-14 收录
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Digenean trematodes are parasites with a complex life cycle that often infest shell-bearing mollusks and produce distinct traces on the host skeleton that are recognizable in the fossil record. Here, three bivalve species (Transennella conradina, Abra segmentum, and Chamelea gallina) from Pleistocene and Holocene deposits of Florida and Italy were used to evaluate the hypothesis that trematode infestation affects shell morphology. The morphological effects of infestation were evaluated using geometric morphometrics and the Pallial Sinus Index (PSI = Pallial Sinus Length / Shell Length). For all three host species: (1) large size classes possess higher trematode prevalence (i.e., proportion of specimens possessing trematode-induced pits within a population) and higher per-specimen frequency of trematode-induced scars when compared to smaller size classes, suggesting ontogenetic accumulation of parasites; (2) infested and non-infested specimens significantly differ in shell landmark-based..., , # Ecological and paleontological implications of trematode-induced morphospace inflation and pallial sinus reduction in bivalve hosts Dataset DOI: [10.5061/dryad.fqz612k61](https://doi.org/10.5061/dryad.fqz612k61) ## Description of the data and file structure All specimens were photographed individually using a HAYEAR microscope camera. A metric scale was included with each image for calibrated linear measurements for morphological analysis. Landmark data was digitized in TPSDig. ### Files and variables #### File: R_Script__Raw_Data_(Dryad).zip **Code, Landmark Data Folder:** * **Jang et al. 2025.R:** R script of all statistical analyses (e.g., Procrustes Analysis, Principal Component Analysis, bootstrap). * **Transennella conradina.tps, Abra segmentum.tps, Chamelea gallina.tps:** Raw digitized landmark data. This data is used for Procrustes analysis and subsequent Principal Component analysis. * **Jang et al. 2025. Spreadsheet.csv:** Spreadsheet including linear measurements, sp...,
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2026-02-06
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