Department of Ecology, College of Environment & Ecology, Hunan Provincial Key Laboratory of Rural Ecosystem Health in Dongting Lake Area, Hunan Agricultural University, Changsha 410128, PR China.
Department of Ecology, College of Environment & Ecology, Hunan Provincial Key Laboratory of Rural Ecosystem Health in Dongting Lake Area, Hunan Agricultural University, Changsha 410128, PR China.
Water Res. 2024 Apr 1;253:121325. doi: 10.1016/j.watres.2024.121325. Epub 2024 Feb 15.
Phytoplankton taxa are strongly interconnected as a network, which could show temporal dynamics and non-linear responses to changes in drivers at both seasonal and long-term scale. Using a high quality dataset of 20 Danish lakes (1989-2008), we applied extended Local Similarity Analysis to construct temporal network of phytoplankton communities for each lake, obtained sub-network for each sampling month, and then measured indices of network complexity and stability for each sub-network. We assessed how lake re-oligotrophication, climate warming and grazers influenced the temporal dynamics on network complexity and stability of phytoplankton community covering three aspects: seasonal trends, long-term trends and detrended variability. We found strong seasonality for the complexity and stability of phytoplankton network, an increasing trend for the average degree, modularity, nestedness, persistence and robustness, and a decreasing trend for connectance, negative:positive interactions and vulnerability. Our study revealed a cascading effect of lake re-oligotrophication, climate warming and zooplankton grazers on phytoplankton network stability through changes in network complexity characterizing diversity, interactions and topography. Network stability of phytoplankton increased with average degree, modularity, nestedness and decreased with connectance and negative:positive interactions. Oligotrophication and warming stabilized the phytoplankton network (enhanced robustness, persistence and decreased vulnerability) by enhancing its average degree, modularity, nestedness and by reducing its connectance, while zooplankton richness promoted stability of phytoplankton network through increases in average degree and decreases in negative interactions. Our results further indicate that the stabilization effects might lead to more closed, compartmentalized and nested interconnections especially in the deeper lakes, in the warmer seasons and during bloom periods. From a temporal dynamic network view, our findings highlight stabilization of the phytoplankton community as an adaptive response to lake re-oligotrophication, climate warming and grazers.
浮游植物类群作为一个网络紧密相连,这个网络可能会表现出季节性和长期尺度上对驱动因素变化的时间动态和非线性响应。利用丹麦 20 个湖泊(1989-2008 年)的高质量数据集,我们应用扩展的局部相似性分析来构建每个湖泊浮游植物群落的时间网络,获得每个采样月的子网,并测量每个子网的网络复杂性和稳定性指数。我们评估了湖泊复氧、气候变暖以及食草动物如何通过三个方面影响浮游植物群落的网络复杂性和稳定性的时间动态:季节性趋势、长期趋势和去趋势变异性。我们发现浮游植物网络的复杂性和稳定性具有很强的季节性,平均度、模块性、嵌套性、持久性和稳健性呈上升趋势,而连接度、正负相互作用和脆弱性呈下降趋势。我们的研究揭示了湖泊复氧、气候变暖以及食草动物通过改变网络复杂性来影响浮游植物网络稳定性的级联效应,这种网络复杂性可以描述多样性、相互作用和地形。浮游植物网络的稳定性随着平均度、模块性、嵌套性的增加而增加,随着连接度和正负相互作用的减少而减少。富营养化和变暖通过增加平均度、模块性、嵌套性以及减少连接度和负正相互作用,稳定了浮游植物网络(增强了稳健性、持久性,降低了脆弱性)。而浮游动物丰富度通过增加平均度和减少负相互作用,促进了浮游植物网络的稳定性。我们的研究结果进一步表明,这种稳定化效应可能导致浮游植物网络的连接更加封闭、分隔和嵌套,尤其是在较深的湖泊、较温暖的季节和浮游植物爆发期间。从时间动态网络的角度来看,我们的研究结果强调了浮游植物群落的稳定化是对湖泊复氧、气候变暖以及食草动物的适应性反应。