基于遥感数据的东海浮游植物生物量时空变化研究

基于地理位置、纬度和生态特征的不同在东海选取了9个面积相同的子区域,采用1997-2015年由SeaWiFS(Sea-Viewing Wide Field-of-View Sensor)和MODIS(Moderate-Resolution Imaging Spectroradiometer)传感器获得的叶绿素a浓度资料,对我国东海浮游植物生物量的时空变化和藻华现象进行了分析。通过高斯曲线模型拟合,得到了藻华爆发的起始时间、峰值时间、结束时间及持续时间。研究表明东海浮游植物生物量在空间上的分布规律为:外海浮游植物生物量小于近岸;长江口和台州列岛海域的浮游植物生物量较大,近黄海海域的两个区域次之,较小的位于南麂列岛海域和台湾海峡,越靠近南部海域浮游植物生物量越低。藻华发生的规律为:以南麂列岛为分界线,由高纬度到低纬度,浮游植物到达藻华发生峰值的时间持续推后,爆发持续时间增长。

Temporal and spatial variation in phytoplankton biomass based on remote sensing data in the East China Sea

The rich natural resources that occur in the East China Sea (ECS) provide great economic benefits to the associated coastal districts; therefore, research on the water quality in this region is of great significance. As biological indicators of water quality, information regarding temporal and spatial distributions of phytoplankton biomass and growth cycles, as well as modifications caused by climate change is important for understanding the ecology of the ECS. Many researchers have been concerned about the characteristics of phytoplankton blooms in the North Atlantic Ocean; however, there are few relevant studies in this region. The present study occurred during a period of phytoplankton bloom in the ECS and provides a significant reference value for an ecologically representative area. The present study selected nine regions with the same area at different geographical locations, latitudes, and ecological characteristics, and applied chlorophyll a (Chl-a) data from Sea-Viewing Wide Field-of-View Sensor and Moderate-Resolution Imaging Spectroradiometer to analyze the spatial-temporal variation of phytoplankton biomass and phytoplankton bloom phenomenon in the ECS during 1997-2015. The Gauss curve model was adopted by fitting the data collected to obtain the time of bloom initiation, bloom peak, bloom completion, and bloom duration in the ECS. The Gauss curve fitting model was applicable to conform to the Gaussian distribution of the data. To test whether the dataset accorded with a normal distribution (Gaussian distribution), the study applied the Kolmogorov-Smirnov test. The single-peak moving Gaussian model was applied to fit the spring and summer algal bloom outbreaks and define the phytoplankton blooms at the beginning and end of the marker for Chl-a concentration to reach a peak of 20%. The research demonstrated the distribution pattern at the spatial scale, with phytoplankton biomass in the open sea being lower than that in the offshore area. The areas with maximum biomass were the seas of the Yangtze River estuary, the Taizhou region, and the two areas closest to the Yellow Sea. The areas with minimum biomass were the seas of the Nanji Islands and Taiwan Strait. Therefore, the closer the phytoplankton was to the South China Sea, the lower was the biomass. Algal blooms occurred in the Yangtze River estuary from June to September and in the Yangtze River estuary in May and from July to August. Phytoplankton blooms at Taizhou Island occurred during May and July. The algae in the eastern part of the ECS occurred from November and December to January and February in the following year. Phytoplankton blooms at Nanji Islands concentrated during February and March, and the ECS algae in the northern areas between May and June. The biomass of phytoplankton in the northern outer seas was low and algae were mostly present in March and April. In general, the two sections of the research region, which were divided by the Nanji Islands, demonstrated the same regularity, the time taken for phytoplankton to reach peak biomass was prolonged, and the duration of the phytoplankton blooms increased from high latitudes to low latitudes.