Abstract
Aquatic biodiversity is important in mediating ecosystem functioning, contributing to ecosystem sustainability and human wellbeing. However, how microbial network complexity affects the biodiversity-nutrient cycling relationship in saline freshwater ecosystems remains underexplored. Using high-resolution time-series data, we examined the relationships between microeukaryotic-bacterial community network complexity, biodiversity and multi-nutrient cycling in an urban reservoir undergoing a freshwater salinization-desalinization cycle. We found that low microbial diversity enhanced ecosystem multi-nutrient cycling under high salinity stress. In addition, multi-nutrient cycling declined with increased network complexity. Further, we found a non-linear relationship between salinity-induced shifts in the complexity of the microbial network and biodiversity-nutrient cycling (BNC) relationship of keystone taxa, i.e. the strength of the BNC relationship first became weak and then strong with increased network complexity. Together, these results highlighted the significant insight that there is not always positive relationship between biodiversity/network complexity and multi-nutrient cycling, even between network complexity and BNC relationship in real-world ecosystems, suggesting that preserving microbial association is important in aquatic health managing and evaluating the freshwater salinization problem.
A conceptual paradigm showing the biodiversity/network complexity affects ecosystem nutrient cycling, and network complexity affects biodiversity-nutrient cycling relationship in freshwater salinization urban reservoir. [Display omitted]
•Freshwater salinization decreased plankton biodiversity and community complexity.•Low plankton diversity enhanced ecosystem multi-nutrient cycling at high salinity.•Plankton network complexity decreased multi-nutrient cycling index at low salinity.•U-shaped biodiversity-nutrient cycling appeared as plankton complexity increased.•Keystone taxa as drivers of plankton community network structure and functioning.