Drivers to spatial and temporal dynamics of column integrated phytoplankton biomass in the shallow lake of Chaohu, China
Drivers to spatial and temporal dynamics of column integrated phytoplankton biomass in the shallow lake of Chaohu, China
复制标题
巢湖浅湖柱状综合浮游植物生物量时空动态驱动因素
DOI：
10.1016/j.ecolind.2019.105812
复制
发表时间：
2020-02-01
影响因子：
6.9
通讯作者：
Loiselle, Steven
中科院分区：
文献类型：
--
作者：
Li, Jing;Ma, Ronghua;Loiselle, Steven
内陆淡水体富营养化是生态系统服务的主要威胁。许多研究集中于利用表面或近表面浮游植物生物量来确定营养状态或水华条件。然而，由于浮游植物的垂直迁移，表层浮游植物生物量可能会迅速变化。更合适的指标是柱综合生物量，它考虑了浮游植物的垂直分布。在这项研究中，我们利用生物量估算算法和十四年的卫星数据估算了中国巢湖浅层富营养化湖泊的柱综合生物量的时空动态。所建立的算法通过原位数据集进行了验证，其相关性显着，确定系数（R-2）为0.89，平均绝对相对差，MARD = 25.97%，均方根误差，RMSE = 20.17 mg.m(-2)。我们将卫星时间序列的时间动态分解为不同湖段生物量的年际趋势、季节和不规则行为。我们将这些个体动态与养分、气象和气候变量进行了比较，特别是在管理这个复杂湖泊和流域的养分的持续努力方面。养分浓度被证明是年际趋势的决定因素。人们发现生物量的不规则变化对影响区域降水和温度条件的全球气候变化事件（ENSO）很敏感。通过考虑浮游植物的垂直剖面，得出的浮游植物生物量（而不是地表生物量）的时间和空间分布为湖泊状况提供了新的视角，并被视为对湖泊管理工作的良好支持。
Eutrophication of inland freshwater bodies is a major threat to the ecosystem services. Many studies have focused on using surface or near surface phytoplankton biomass to determine trophic status or bloom conditions. However, surface phytoplankton biomass can change quickly due to the vertical migration of phytoplankton. A more appropriate indicator is column integrated biomass which considers the vertical distribution of the phytoplankton. In this study, we estimated the spatial and temporal dynamics of column integrated biomass in a shallow eutrophic lake, Lake Chaohu in China, using a biomass estimation algorithm and fourteen years of satellite data. The built algorithm was validated by in situ datasets with a significant correlation with the coefficient of determination (R-2) of 0.89, mean absolute relative difference, MARD = 25.97%, the root-mean-square error, RMSE = 20.17 mg.m(-2).We decomposed the temporal dynamics of the satellite-based time series into inter-annual trends, seasonal and irregular behaviors of biomass in different lake sections. We compared these individual dynamics to nutrients, meteorological and climate variables, in particular with respect to ongoing effort to manage nutrients in this complex lake and catchment. Nutrient concentrations were shown to be determinant in the inter-annual trends. Irregular variation of biomass was found to be sensitive to global climate change events (ENSO) which influence regional conditions of precipitation and temperature. By taking the vertical profile of phytoplankton into consideration, the derived temporal and spatial distribution of phytoplankton biomass, rather than surface biomass, provided new sights into lake conditions and were seen to be a good support for lake management efforts.