The Effects of Water Level Fluctuation on Zooplankton Communities in Shahu Lake Based on DNA Metabarcoding and Morphological Methods

Abstract

Background: The water level of Poyang Lake (China) fluctuates seasonally. Shahu Lake, a smaller body of water connected to Poyang Lake during the wet season, is separated in the dry season. Due to a special fishing method termed ‘lake enclosed in autumn’, the water level is lowered and reaches its lowest point in January, which is <0.5 m deep in the middle of the lake. Our research investigated the effect of water level changes on the zooplankton community composition in Shahu Lake. Methods: We used both DNA metabarcoding method (MBC) (18S rRNA gene V4 region) and morphological method (MOI) to track the zooplankton community structure over four seasons in Shahu Lake (China). Results: Totals of 90 and 98 species of zooplankton were detected by MOI and MBC, respectively, with rotifers being the main zooplankton component. The α-diversity index of both methods increased from spring to summer and decreased from summer to autumn, reaching the lowest value in winter. NMDS and a cluster analysis showed that all zooplankton communities detected by MOI and MBC were significantly separated by season. The zooplankton community in winter was separated from that of the other three seasons, but the summer and autumn communities were more similar. Conclusions: Changes in the water level had significant effects on the zooplankton community composition. We found that MBC was more able to detect the differences in the zooplankton composition than MOI. MBC also had more advantages in copepod recognition. In our study, 37 species of copepods were detected by MBC, but only 11 species were detected by MOI. We concluded that MBC should be used to research the seasonal variations of zooplankton.

Developing an eDNA approach for wetland biomonitoring: Insights on technical and conventional approaches

“…Meanwhile, greater overlap was observed for bird and fish species, with 8/11 bird species and 10/15 fish species detected in the eDNA versus conventional methods used here (Reeves, 2011; https://nzffdms.niwa.co.nz/). These patterns are consistent with other research, where eDNA has detected more zooplankton species than morphological‐based methods in marine and lake environments (Qiu et al., 2022; Suter et al., 2021). Similarly, Mejia et al.…”

“…nz/ ). These patterns are consistent with other research, where eDNA has detected more zooplankton species than morphologicalbased methods in marine and lake environments (Qiu et al, 2022;Suter et al, 2021). Similarly, Mejia et al (2021) observed low concordance between a botanist survey and eDNA results at Mojave Desert Springs.…”

Current Utilization and Further Application of Zooplankton Indices for Ecosystem Health Assessment of Lake Ecosystems

“…Owing to these advantages, eDNA analyzers have been actively applied to abundance and species diversity monitoring based on zooplankton abundance. Recent studies have suggested that eDNA analysis methods can identify biodiversity with equal or better performance than morphological analysis methods [105,106]. For example, in the analysis of seasonal changes in zooplankton α-diversity, metabarcoding showed a consistent relationship with morphological methods in identifying changes in species composition of zooplankton and species diversity of Copepoda; 37 species were detected by metabarcoding analysis and 11 species by morphological analysis, demonstrating the applicability of eDNA analysis methods in monitoring species diversity [106].…”

The effects of water quality parameters, water level changes, and mixing on zooplankton community dynamics in a tropical high-mountain Lake Ardibo, Ethiopia

“…Climate change and rainfall variability will magnify the water level uctuations that (Heinsalu et al, 2008) affect the physicochemical variables and the functioning of an aquatic environment (Liu et al, 2019), potentially altering the biological communities of lake ecosystem (Kobayashi et al, 2020). The diversity and abundance of zooplankton community are largely in uenced by the amplitude of water-level regims (Chaparro et al, 2019;Hu et al, 2019;Wang et al, 2019;Tan et al, 2021;Qiu et al, 2022). How ever, little is known about the effect of water level uctuations in deep tropical lakes.…”