Microbial Observatory at North Temperate Lakes LTER Time series of bacterial community dynamics in Lake Mendota 2000 - 2009

With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.

依托来自温带富营养化湖泊（temperate eutrophic lake）的前所未有的十年时长时间序列数据集，我们针对细菌与环境共现网络（co-occurrence networks）展开分析，以揭示群落层面的季节动态规律。研究结果表明：其一，细菌共现网络并非随机形成；其二，季节变化可解释网络复杂度的差异；其三，不同季节下共现网络复杂度与对应群落多样性呈负相关关系。网络复杂度与关联环境因子的变异程度无显著关联。与调控不同纬度区域生物多样性的机制类似，温度与初级生产力或许是驱动温带水生系统中季节尺度群落多样性变化的核心因素。尽管浮游细菌（bacterioplankton）网络结构对生态系统功能的潜在影响目前仍未被充分阐明，但结合传统多变量统计技术开展的网络分析，仍在持续深化我们对浮游细菌时间动态特征的认知。