Wei Wang

and 10 more

To investigate the intricate relationship between phytoplankton taxonomy composition and functional group structure, and identifying the key environmental drivers of phytoplankton community dynamics, we conducted a comprehensive study encompassing 11 lakes and reservoirs located in North China. Environmental parameters, spanning climato-geographic factors and hydrochemical variables, were comprehensively assessed. Phytoplankton were categorized utilizing both traditional taxonomic criteria and functional group classifications. Our investigation unveiled rich phytoplankton diversity across these 11 water bodies, comprising 81 genera spanning 7 phyla. This taxonomic diversity was further organized into 30 distinct functional groups (FG). Remarkably, when comparing community structures, we observed a high degree of similarity between taxonomic and functional group-based classifications in lakes. Redundancy analysis (RDA) results underscored the pivotal role of climato-geographic factors as dominant drivers influencing both taxonomic composition and functional group distribution. Intriguingly, variance partitioning analysis (VPA) revealed that while climato-geographic factors exerted substantial influence, their impact was eclipsed by hydrochemical factors. The intricate interplay of six environmental parameters emerged as influential through stepwise regression analysis. These included chlorophyll-a (chl-a), Chemical Oxygen Demand (CODMn), Total Phosphorus (TP), Total Nitrogen (TN), Secchi Depth (SD), and Longitudinal Position (LON).

Jing Yang

and 7 more

Microorganisms play a key role in aquatic ecosystems. Recent studies have showed that some keystone taxa in microbial communities can drive the changes in community composition and function. However, most studies have focused on abundant taxa, whereas rare taxa are neglected because of their low abundance. Therefore, it is important to clarify the seasonal variation of bacterial and microalgal communities and understand the synergistic adaptation of these organisms to different environmental factors. We investigated the bacterial and eukaryotic phytoplankton communities and their seasonal co-occurrence patterns using16S and 18S rDNA sequencing approach. Our results indicated that in eukaryotic phytoplankton networks, spring and autumn networks had higher connectivity and complexity, forming the highly stable community structure. The positive interactions of bacterial network were significantly higher than the negative interactions, indicating that more mutual cooperation can make the microbial communities better resist changes in the external environment, thereby maintaining the stability of microbial network. The main genera identified as keystone taxa in bacterial networks were Pseudomonas, Stenotrophobacter, Bosea, and Hyphomicrobium, which were significantly related to many predicted functions. The main genera identified as keystone taxa in eukaryotic phytoplankton networks were Monodus, Tetradesmus, Scenedesmus, Monoraphidium, and Amphora, which were affected by dissolved organic carbon, nitrate, nitrite, and phosphate, changes in these environmental factors can affect the stability of network. Through the co-occurrence patterns, we analyzed the internal mechanism of interaction between bacteria and eukaryotic phytoplankton and understood the potential importance of keystone taxa in ecological processes such as carbon, nitrogen, and phosphorus dynamics.