Effects of Aquatic Plant Coverage on Diversity and Resource Use Efficiency of Phytoplankton in Urban Wetlands: A Case Study in Jinan, China

Biology (Basel). 2024 Jan 14;13(1):44. doi: 10.3390/biology13010044.

Abstract

With the acceleration of urbanization, biodiversity and ecosystem functions of urban wetlands are facing serious challenges. The loss of aquatic plants in urban wetlands is becoming more frequent and intense due to human activities; nevertheless, the effects of aquatic plants on wetland ecosystems have received less attention. Therefore, we conducted field investigations across 10 urban wetlands in Jinan, Shandong Province, as a case in North China to examine the relationships between aquatic plant coverage and phytoplankton diversity, as well as resource use efficiency (RUE) in urban wetlands. Multivariate regression and partial least squares structural equation modeling (PLS-SEM) were used to analyze the water quality, phytoplankton diversity, and RUE. The results demonstrate that the increase in aquatic plant coverage significantly reduced the concentration of total nitrogen and suspended solids' concentrations and significantly increased the phytoplankton diversity (e.g., species richness and functional diversity). The aquatic plant coverage significantly affected the composition of phytoplankton functional groups; for example, functional groups that had adapted to still-water and low-light conditions became dominant. Furthermore, the increase in phytoplankton diversity improved phytoplankton RUE, highlighting the importance of aquatic plants in maintaining wetland ecosystem functions. This study may provide a scientific basis for the management strategy of aquatic plants in urban wetlands, emphasizing the key role of appropriate aquatic plant cover in maintaining the ecological stability and ecosystem service functions of wetlands.

Keywords: aquatic plants; ecosystem functions; phytoplankton diversity; resource use efficiency; wetland degradation.

Grants and funding

This research was funded by the National Natural Science Foundation of China (41977193), and the National Science and Technology Basic Resources Survey Program of China (2019FY101700).