Biodiversity Of Zooplankton And Community Effects Of Environmental Pollution In Tai Lake Basin

Environmental pollution and global climate change can lead to the decline of aquatic biodiversity,loss of biological integrity and extinction of particular species,which eventually result in the damage of aquatic ecosystem function.Freshwater ecosystem is an important resource for human and social development.It is also the most disturbed ecosystem by human activities.Biodiversity is the key factor of ecosystem to maintain a stable and healthy environment.However,the traditional biological monitoring is time-consuming,inefficiency and prone to misidentification,can not meet the growing demand for environmental monitoring.Zooplankton communities are the one of the most important ecological groups for the aquatic ecosystem,plays an important role in the energy transferation and material recycling.Zooplankton have a short life cycle and quickly response to the environmental pressures,is an important bioindicator for ecological health.Therefore,the present study developed a DNA metabarcoding monitoring technique based on environmental DNA(eDNA)for rapid monitoring of zooplankton communities.Reference barcode database of native species is the foundation of DNA metabarcoding.This study first used high-throughput sequencing constructed a local zooplankton barcode database of Taihu basin.PCR primer sets and sampling methods of DNA metabarcoding were optimized to provide a standardized biomonitoring pipline.The traditional morphological monitoring results were also compared with DNA metabarcoding monitoring.Through the study on the ecological response of zooplankton communities on the pressure of human activities,identify the key stressor of zooplankton in Taihu basin.We also developed a new method based on the DNA metabarcoding to derive the environmental criteria of key pollutant of Taihu basin.The main contents and conclusions of this thesis are as follows:High throughput sequencing(HTS)significantly improved the construction of zooplankton barcoding databases.HTS provides multiple sequences for each specimen,avoiding the failure of species barcoding because of DNA contamination.In this study,a total of 1034 native zooplankton specimens were sequenced,including 87 morphological species,covering 91%of the common zooplankton species in the Taihu basin.Although COI barcoding has been growing rapidly in NCBI Genbank in recent years,most of the COI sequences are belong to insects,and zooplankton sequences are still very scarce.Moreover,the high evolution of zooplankton resulting in a large difference of barcode sequences of the same species at different regions,and limited the annotation of Taihu metabarcoding sequencing data by public databases.About 90%of the common species and 50%of the rare species in the Taihu basin can be annotated by the local database,which greatly improves the monitoring efficiency of DNA metabarcoding.Mitochondrial cytochrome C oxidase subunit I(COI)is the most suitable primer of zooplankton diversity by DNA metabarcoding.The COI primer can cover most of the zooplankton species and have no obvious preference of the three major zooplanktnic groups(rotifers,cladocerans and copepods).The mitochondrial 16S gene is suitable for the study diversity of rotifer,which has a good specificity for rotifer community,but has poor amplification ability for copepods and cladocera.Although the V9 region of 18S gene can cover a wider range of species(including algae,protozoa and fungi),the species specificity is poor and it is difficult to evaluate biodiversity at the species level.The "direct water sampling method" is more suitable for the study of rotifer and protozoan diversity,and the sampling volume of 1L is enough to detecte most rotifer species."Net sampling method" is more suitable for monitoring the diversity of meso-zooplankton(cladocera and copepod),and the filtration volume of 10-20L can monitor most of the Cladocera and copepods.DNA metabarcoding monitoring results were consisting with morphological monitoring of zooplankton.More than 80%of morphological species can be detected by DNA metabacoding technology.High morphological frequency species also were found have high frequency by metabarcoding.The number of species detected by metabarcoding was positively correlated with traditional morphological methods(R2 =0.41,P = 0.0004).The frequency of common species was also significantly positively correlated(R2=0.43,P,<0.0001)with the two methods.Besides the frequency of species,the Mantel test(R2 = 0.52,P = 0.0001,mantel test,with,nPERM = 9999)showed a strong consistency in the distribution of the common species.Metabarcoding monitoring can significantly improve the number of zooplankton species found,and can effectively monitor the differences in zooplankton composition between different water types,and achieve a semi-quantitative monitoring of zooplankton communities.Nutrients and eutrophication is the main stressors of zooplankton communities in the Taihu Basin.Total ammonia nitrogen(TAN)have the largest effects on zooplankton communities than other environmental factors.The diversity and abundance of meso-zooplankton(cladocerans and copepods)were decreased with the increase of TAN concentration.The diversity of dominant cladoceran Bosmina sp.and dominant copepods Sinocalanus dorrii also decreased.However,the diversity rotifer increased with the increase of TAN.Metbarcoding monitoring found that 13.4%of total zooplankton OTUs sensitive to TAN which the abundance of OTUs negatively correlated with TAN,represented 32.1%of total sequences.Most of the sensitive OTUs were Cladocera and Copepods.According to the sensitive OTUs and SSD models,the HC5 and HC10 of TAN in Taihu basin are 1.4 and 2.9 mg/L,respectively.Based on the DNA metabarcoding monitoring,the deduced TAN criteria is close to the criteria derived from the morphological monitoring data and is more sensitive than that derived from laboratory toxicity data.The metabarcoding OTUs based approach(f-OSDs)for development of ecologically relevant,site-specific,water quality criteria(WQI)to protect aquatic organisms from effects of TAN based on the quantifiable changes of biodiversity of zooplankton populations was presented.The f-OSDs approach incorporates advantages of environmental relevance from field-based SSD and the advantages of comprehensive,high throughput,high sensitivity and low cost in species identification from metabarcoding.This method also allowed for rapid assessment of which species/OTUs were more sensitive to a particular contaminant.Once calibrated to a local environment,f-OTUs can be used for rapid screening to understand the status and trend in structures of aquatic ecosystem.There were significant differences in zooplankton community composition between different sampling seasons(April,August and November).Copepod have the largest proportion in November(dry season)and have the smallest proportion in August(wet season).Cladocera have the largest proportion in August and have the smallest proportion in April(dry season).Rotifer have the largest proportion in August and have the smallest proportion in November(mormal season).The structure and community networks of zooplankton have significant differences between different seasons.The correlations between zooplankton in august are most densed.The negative correlations of zooplankton were also strongest in august.The sampling season can be predicted according to zooplankton communities by supervised machine learning.Total 60 biological indexes were calculated to generate an integrity index of zooplankton community(IZI).The IZI has significant correlation(P<0.0001)with water quality index(WQI),indicated that IZI is a good indication of water quality.Supervised machine learning of metabarcoding data can be a good evaluation of the water quality,the neural network model is the most suitable for eutrophication assessment(R2 = 0.44),random forest model is the most suitable for the water quality assessment(R2=0.59).according to the different seasons of the decision tree can quickly evaluate aquatic health.The decision trees that construted by zooplankton DNA metabarcoding can quickly evaluate the health of aquatic ecosystem.