5:15 PM - 7:15 PM
[MIS11-P06] DNA analysis of microbial communities in tsunami and storm surge deposits
Keywords:Tsunami deposit, Storm surge deposit, DNA analysis, Microbial communities
Since the distribution and age of tsunami deposits can be used to estimate inundation extent and the frequency of past tsunamis, establishing reliable methods for identifying tsunami deposits in geological strata is essential for assessing future tsunami risks. Identification has been conducted using a multi-proxy approach that combines geological techniques, paleontological analysis, and geochemical analysis. However, since these proxies may not always be preserved in geological strata, more advanced proxies for identifying tsunami deposits are necessary to improve identification accuracy. In recent years, DNA analysis of organisms contained within sediments has attracted attention as a new identification proxy. DNA analysis of microbial communities has been reported to successfully distinguish 2004 Indian Ocean tsunami deposits and storm surge deposits from soils unaffected by inundation (Yap et al., 2021). However, there are still few reports, and it remains unclear whether DNA analysis can be applied in various environmental settings. In this presentation, we report the results of evaluating whether modern and historical tsunami and storm surged deposits collected from four locations in Japan can be distinguished from soil and sediments unaffected by inundation using DNA analysis of microbial communities.
The analyzed samples included two tsunami deposit samples (one is the 2011 Tohoku tsunami deposit and another is from a tsunami deposit approximately 400 years ago) and two storm surge deposit samples (one deposited 3 months to several decades ago and another believed to have been formed by a storm surge thousands of years ago), all collected from different locations in Japan. As controls, we also collected soil samples from non-inundated areas, coastal sand, and samples from layers above and below event deposits at each site. DNA was extracted from each sample using the DNeasy PowerSoil Pro kit, and next-generation sequencing was performed targeting the 16S rRNA gene of microbial origin. Based on the obtained sequences, we inferred the closest related species, organized the types and relative abundance of microorganisms present in each sample, and statistically evaluated the similarity of microbial communities among the samples.
The results showed that the microbial communities of the 2011 Tohoku tsunami deposit differed from those of non-inundated soils and coastal sands. Similarly, the tsunami deposit approximately 400 years ago exhibited distinct microbial communities compared to surface soils and the layers above and below the tsunami deposit. For storm surge deposits, analysis of the deposit believed to have been formed thousands of years ago revealed that the microbial communities in the event layer and its immediately adjacent layers differed from those in other layers. Meanwhile, the microbial communities in the storm surge deposit three months after deposition differed from those in coastal sand and the underlying soil, but six months after deposition, the microbial communities became similar to those of the underlying soil. This result may be attributed to influences from nearby rivers or groundwater.
These findings suggest that DNA analysis of microbial communities could serve as an identification proxy not only for modern tsunami deposits but also for tsunami deposits approximately 400 years ago. Additionally, this method may be applicable for identifying storm surge deposits as well. However, changes in microbial communities over time after deposition have been observed in some cases. Thus, it is necessary to evaluate the environmental conditions and changes at sampling sites and increase the number of cases in the future to enhance the accuracy of identification.
The analyzed samples included two tsunami deposit samples (one is the 2011 Tohoku tsunami deposit and another is from a tsunami deposit approximately 400 years ago) and two storm surge deposit samples (one deposited 3 months to several decades ago and another believed to have been formed by a storm surge thousands of years ago), all collected from different locations in Japan. As controls, we also collected soil samples from non-inundated areas, coastal sand, and samples from layers above and below event deposits at each site. DNA was extracted from each sample using the DNeasy PowerSoil Pro kit, and next-generation sequencing was performed targeting the 16S rRNA gene of microbial origin. Based on the obtained sequences, we inferred the closest related species, organized the types and relative abundance of microorganisms present in each sample, and statistically evaluated the similarity of microbial communities among the samples.
The results showed that the microbial communities of the 2011 Tohoku tsunami deposit differed from those of non-inundated soils and coastal sands. Similarly, the tsunami deposit approximately 400 years ago exhibited distinct microbial communities compared to surface soils and the layers above and below the tsunami deposit. For storm surge deposits, analysis of the deposit believed to have been formed thousands of years ago revealed that the microbial communities in the event layer and its immediately adjacent layers differed from those in other layers. Meanwhile, the microbial communities in the storm surge deposit three months after deposition differed from those in coastal sand and the underlying soil, but six months after deposition, the microbial communities became similar to those of the underlying soil. This result may be attributed to influences from nearby rivers or groundwater.
These findings suggest that DNA analysis of microbial communities could serve as an identification proxy not only for modern tsunami deposits but also for tsunami deposits approximately 400 years ago. Additionally, this method may be applicable for identifying storm surge deposits as well. However, changes in microbial communities over time after deposition have been observed in some cases. Thus, it is necessary to evaluate the environmental conditions and changes at sampling sites and increase the number of cases in the future to enhance the accuracy of identification.