Geographical Distribution and Multimethod Species Identification of Forensically Important Necrophagous Flies on Hainan Island

SIMPLE SUMMARY: Forensic entomology offers unique advantages for the minimum postmortem interval (PMImin) estimation of decomposed corpses in forensic investigations. Molecular identification has become a routine and accurate tool. In this study, the community structure of the necrophagous flies on Hainan Island was investigated in detail according to the geographical environment. A GenBank database was preliminarily constructed to provide reference data for species identification in this area. We found that a high-resolution melt (HRM) curve analysis was a fast, cost-effective method for the species identification of flies. This study enriches the database of forensically important flies in tropical rainforest regions. ABSTRACT: Forensic entomology offers unique advantages for the minimum postmortem interval (PMImin) estimation of decomposed corpses in forensic investigations. Accurate species identification and up-to-date locality information are essential. Hainan Island has a tropical rainforest climate and a vast territory. In this study, the community structure of necrophagous flies on Hainan Island was investigated in detail according to geographical environment. The results showed that the dominant species included C. megacephala, S. peregrina, C. rufifacies, S. misera, H. ligurriens, S. sericea, S. cinerea, S. dux, C. pinguis, and M. domestica. Furthermore, C. rufifacies and C. villeneuvi were found only in the high-altitude areas of Wuzhi Mountain, while S. cinerea was distributed only in coastal areas; the latter is a representative species of Hainan Island and has not been reported before. Furthermore, a GenBank database of forensically important flies was established, whilst a high-resolution melt (HRM) curve analysis was applied to identify the common species of Hainan Island for the first time. This study enriches the database of forensically important flies in tropical rainforest regions.