Temporal And Spatial Variation Of Phytoplankton Community In Jiulong River Estuary And Xiamen Bay

The intensification of human activities is spurring changes in the ecological environment of the estuary,which increases the frequency of hazardous ecological events such as harmful algal blooms in these years.However,it is difficult to reflect the actual dynamics of the phytoplankton community comprehensively when using one single method to observe the phytoplankton community.In this study,we chose a typical estuary-Jiulong River estuary and Xiamen Bay as the study area.From the perspective of methodology,the applicability of three different observation methodschemical classification method based on photosynthetic pigments,image recognition method based on microscopic imaging,and navigation observation method based on bio-optics technology were discussed in complex estuaries.Simultaneously,using these observation methods,combined with environmental factors and alkaline phosphatase activity,the dominant factors affecting the temporal and spatial changes of phytoplankton groups in the Jiulong River Estuary and Xiamen Bay were explored from both spatial and seasonal scales.The main results were as follows:1.Image recognition method based on microscopic imagingThrough the deep learning technology based on convolutional neural network,the classification and recognition of the plankton images were completed and the database was constructed in the Jiulong River Estuary and Xiamen Bay.The cross-validation results indicated that the accuracy of image recognition was ideal,and the accuracy of 9 categories was more than 90%among all the 34 categories.However,several plankton groups were misjudged because of the similar morphology among these groups,such as Navicula,Nitzschia and so on.The cross-validation results indicated the recognition accuracy of our model was close to manual recognition.Therefore,it could be applied to the automated analysis of samples in the Jiulong River Estuary and Xiamen Bay.2.Comparison of the results of different phytoplankton community observation methodsIn general,different observation methods could be applied to most different water environments,and had good consistency in characterization for most taxa.Among the methods,the image recognition method had the widest applicability and good accuracy of the characterization of phytoplankton in different water environments and different groups.Therefore,when there was a certain deviation between the different methods,it was recommended to use the results of this method as a standard to correct other results.The characterization effect of bio-optical method in oligohaline area was better than that of polyhaline area,and the observation results of dominant groups with higher biomass were more accurate.For example,the correlation coefficient between the concentration of chlorophytes and chlorophyll b in oligohaline area reached 0.70(p<0.001).The results of polyhaline area and non-dominant taxa such as blue algae should be further corrected.Compared with the results obtained by the bbe algae analyzer,the results of the phytoplankton group inversion model established by the partial least square regression(PLSR)in Jiulong River Estuary and Xiamen Bay were closer to the results of the chemical taxonomy method.The separation of diatoms and dinoflagellates and the observation of haptophytes were achieved.Therefore,it could better reflect the actual biomass and community composition of phytoplankton.The image recognition method and the chemical classification method matched well in the overall trend.Chlorophytes had the highest matching degree,followed by cryptophytes and diatoms.However,there was a difference between dinoflagellates biomass measured by these two methods,and the chemical taxonomy method may cause a underestimation of dinoflagellates.3.Temporal and spatial distribution of phytoplankton community in Jiulong River Estuary and Xiamen BayThe concentration of chlorophyll a in the whole study area was highest in spring(3.54±2.61μg/L),and lowest in autumn(1.07±0.37μg/L),the concentration in winter(2.89±1.24 μg/L)was slightly higher than in summer(2.21 ±1.12 μg/L).On the spatial scale,the concentration of chlorophyll a performed a high value in the upstream area of the Jiulong River Estuary.In the midstream of Jiulong River Estuary,a maximum concentration of chlorophyll a could be observed in freshwater-seawater mixing zone,and then the concentration of chlorophyll a decreased rapidly.The downstream area maintained a relatively stable concentration and was close to Xiamen Bay,showing a good spatial continuity.Jiulong River Estuary and Xiamen Bay showed a strong spatial heterogeneity in terms of the composition of the phytoplankton community.In the upstream area of Jiulong River Estuary,phytoplankton was dominated by cryptophytes and prasinophytes.In the midstream area,the proportion of prasinophytes and green algae dropped rapidly,while the proportion of diatoms rose rapidly and became the dominant phytoplankton in this area.Diatoms were also the dominant phytoplankton in the downstream area of Jiulong River Estuary and Xiamen Bay.The dominant groups were usually diatoms and cryptophytes in different seasons except for summer.In summer,the dominant groups in the upstream area were green algae and cryptophytes or blue algae and cryptophytes.The main factors affecting the phytoplankton biomass and the spatial distribution pattern of phytoplankton were salinity and nutrients.The results of bulk APA indicated that the upstream area of the Jiulong River Estuary may suffer from strong phosphorus stress,while chlorophytes had the lowest degree of phosphorus stress,and therefore had a competition advantage in the upstream area.The main factors that caused seasonal changes in phytoplankton biomass were nutrients and river discharge.Nutrients was the dominant factor in spring and autumn.The richer the nutrient,the higher the biomass;discharge was the dominant factor in winter and summer.The main factor affecting the seasonal changes of community structure was temperature.