Water depth affects submersed macrophyte more than herbivorous snail in mesotrophic lakes

Abstract

Introduction: Water depth (WD) and snail abundance (SA) are two key factors affecting the growth of submersed aquatic plants in freshwater lake ecosystems. Changes in WD and SA drive changes in nutrients and other primary producers that may have direct or indirect effects on submersed plant growth, but which factor dominates the impact of both on aquatic plants has not been fully studied.

Methods: To investigate the dominant factors that influence aquatic plant growth in plateau lakes, a one-year field study was conducted to study the growth of three dominant submersed macrophyte (i.e., Vallisneria natans, Potamogeton maackianus, and Potamogeton lucens) in Erhai Lake.

Results: The results show that, the biomass of the three dominant plants, P.maackianus, is the highest, followed by P.lucens, and V.natans is the lowest. Meanwhile, periphyton and snails attached to P.maackianus are also the highest. Furthermore, WD had a positive effect on the biomass of two submersed macrophyte species of canopy-type P.maackianus and P.lucens, while it had a negative effect on rosette-type V.natans. Snail directly inhibited periphyton attached on V.natans and thereby increasing the biomass of aquatic plants, but the effect of snails on the biomass of the other two aquatic plants is not through inhibition of periphyton attached to their plants.

Discussion: The dominant factors affecting the biomass of submersed macrophyte in Erhai Lake were determined, as well as the direct and indirect mechanisms of WD and snails on the biomass of dominant submersed macrophyte. Understanding the mechanisms that dominate aquatic plant change will have implications for lake management and restoration.

Keywords: herbivory; periphyton; snail abundance; submersed macrophytes; water depth.

Figure 1

The location of Erhai Lake and sampling bays.

Figure 2

Biomass of three dominant submersed macrophytes in Erhai Lake across four seasons. Mean and standard deviation are shown in each bar. The different letters on the bars indicate significant differences at p < 0.05.

Figure 3

Changes in SA and periphyton biomass attached to three submerged macrophytes. Mean and standard deviation are shown in each bar. The different letters on the bars indicate significant differences at p < 0.05.

Figure 4

Changes in total nitrogen (TN), total phosphorus (TP), phytoplankton chlorophyll- a (Chl a) and light extinction coefficient (K) in Erhai Lake across four seasons. Mean and standard deviation are shown in each bar. The different letters on the bars indicate significant differences at p < 0.05.

Figure 5

Inclusive R2 and 95% CI for each driver on (A) V.natans biomass and (B) P.maackianuss biomass and (C) P.lucens biomass.

Figure 6

Piecewise structural equation model (SEM) showing the effects of WD, SA and nutrients on macrophyte biomass directly and indirectly. Solid black line shows a significant positive correlation and the solid red line shows a significant negative correlation, with the dotted line indicates no significance. Standardized path coefficients (similar to relative regression weights) are shown as numbers next to the path lines. Next to each response variable in the model is the proportion of variance explained (R2). Model fit: V.natans: Fisher’s C = 2.139, P=0.508; P. maackianus: Fisher’s C = 0.469, P=0.791; P.lucens: Fisher’s C = 0.214, P=0.899. *p < 0.0 5, **p < 0.01, ***p < 0.001.