Although recent studies explored using microbial succession during decomposition to estimate the postmortem interval (PMI) and postmortem submersion interval (PMSI), there is currently no published research using aquatic eukaryotic community succession to estimate the minimum postmortem submersion interval (PMSI). The goals of this study were to determine whether eukaryotic community succession occurs on porcine skeletal remains in a lentic environment, and, if so, to develop a statistical model for PMSI prediction. Fresh porcine bones (rib N = 100, scapula N = 100) were placed in cages (10” x 10”) attached to floatation devices and submerged in a fresh water lake (Crozet, VA), using waterproof loggers and a YSI Sonde to record temperature and water quality variables, respectively. In addition to baseline samples, one cage, containing five ribs and five scapulae, and water samples (500 mL) were collected approximately every 250 accumulated degree days (ADD). Nineteen sample cohorts were collected over a period of 5200 ADD (579 Days). Variable region nine (V9) of the 18S ribosomal DNA (rDNA) was amplified and sequenced using a dual-index strategy on the MiSeq FGx sequencing platform. Resulting sequences underwent quality control parameters and analysis in mothur v 1.42.3, R v 3.5.3, and R v 3.6.0. Permutational multivariate analysis of variance (PERMANOVA) revealed a significant difference in phylogenetic β-diversity among ribs, scapulae and water (p = 0.001) and among ADD (p ≤ 0.011), which was supported by distinct clustering of samples associated with each ADD in UniFrac distance based non-metric multidimensional scaling (NMDS) ordinations. Using similarity percentage (SIMPER) analysis of class and family level taxa, differences observed between bone types were attributed to Peronosporomycetes_cl, Eukaryota_unclassified, and Intramacronucleata (e.g., Armophorida), however these differences were not statistically significant. Alpha diversity revealed a non-linear increase in phylogenetic diversity with an increase in ADD. Random forest models for ribs and scapulae predicted PMSI with an error rate within±104 days (937 ADD) and±63 days (564 ADD), respectively. In conclusion, this study suggests that eukaryotic succession is capable of predicting long term PMSI in lentic systems.
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