The DNA Barcoding Technology Applied To Macroinvertebrate Biodiversity Assessment And Biomonitoring For Stream Ecosystem

Stream ecosystems not only provide the most important ecological fuctions for human, but also maintain a highly concentrated biodiversity. However, human activities have seriously affected the stream ecosystem, in which aquatic biodiversity decline was severe. Since the levels of biodiversity in the ecosystem, it will reflect the ecological health of a stream ecosystem, and determine the extent of the ecological functions of stream ecosystem degradation. Therefore, the study on the assessment of biological diversity in the ecosystem of the community is based analysis for river ecosystems of many problems. Given the traditional taxa identification methods had many disadvantages for study of bio-diversity, we used DNA metabarcoding technology on river ecosystem biodiversity assessment and monitoring in this study, such as community structure analysis of the region, the impact of environmental conditions on biological community structure biodiversity and ecosystems biological indicators monitored. The main findings are as follows:(1) Molecular operational taxonomic units (MOTUs) compared with GenBank, BOLD database found that more than 84.7% of the sequence (> 97% similarity) can be identified, while higher levels (family, genus level) does not exceed the rate of recognition 50%; According to the composition of benthic community structure based on the similarity of the animal, we found that Reads abundance data and the presence/absence data of MOTUs can be accurately reflect the situation of the community in different habitats, and based on principal coordinate analysis (PCoA) analysis showed that group 1, group 2 and group 3 are also distributed in different 2-D spaces. Axis 1 can explain the community structure variation about 21.1% in Reads abundance and 18.2% of the presence/absence data of MOTUs. Axis 2 can explain Reads and the presence/absence data of MOTUs deletion mutation rate were 13.5%, 14.3% in community structure. The number of MOTUs of Diptera was highest in Group 1, following Ephemeroptera and Hemiptera, etc; The highest number MOTUs was Ephemeroptera, following with Diptera; the MOTUs of Ephemeroptera was also highest in Group 3, followed with Hemiptera. The results of one-way AN OVA showed that, the number of MOTUs of Ephemeroptera was significant differences among the groups, particularly the number of Ephemeroptera in groups 2 and 3 were significantly higher than group 1; For environmental factors, the vegetation land use in groups 2 and 3 were significantly higher than group 1, yet the farmland coverage was contrary. BODs, conductivity and ammonia concentration of group 1 was significantly higher than Groups 2 and 3, the total phosphorus concentration in group 1 was significantly higher than group 2. In addition, based on linear regression model (dbRDA) analysis showed that ammonia nitrogen and BOD5 is the most significant environmental impact factors on macrobenthic community distribution. And after Threshold Indicator Taxa Analysis (TITAN) suggested that concentrations of ammonia and BOD5 exceed 0.20 mg/L and 3.50 mg/L respectively, it will cause a lot of loss of sensitive species within a biome.(2) Compared to the environmental condition and heterogeneity of natural environment in this region, the environmental conditions and heterogeneous of anthropogenic environmental stress were significant differences among the groups. For the further analysis indicated that anthropogenic disturbance could effect significantly differences of community structure among different groups. The correlation analysis concluded that with the increase of water nutrient concentrations, a biodiversity significant recession. In addition, based on distance matrix of the multiple regression model (MRM) analysis results showed that nutrients and pollutants have a significant effect on βtotal and βsim, in which the concentration of nutrients was significantly positive correlation with βtotal and βsim, and could interpreted 22% and 14% of the variance respectively. With the in nutrient concentrations in water increased, the variance rate of βtotal and βsim will increases significantly, which also increase significantly for the turnover of the species. Conversely, increased the concentration of organic pollutants would decrease βtotal and βsim significantly, explaining 32% and 14% of the variation respectively.(3) eDNA technology-based approach was an effective method for monitoring specific species, and although eDNA technology exhibit a great advantage, combined the traditional species monitoring means with eDNA technology methods would be well complement for ecosystem monitoring biodiversity each other.