Horizontal distribution of pelagic crustacean zooplankton biomass and body size in contrasting habitat types in Lake Poyang, China

Seasonal and spatial variability of zooplankton diversity in the Poyang Lake Basin using DNA metabarcoding

Freshwater ecosystems face multiple threats to their stability globally. Poyang Lake is the largest lake in China, but its habitat has been seriously degraded because of human activities and natural factors (e.g. climate change), resulting in a decline in freshwater biodiversity. Zooplankton are useful indicators of environmental stressors because they are sensitive to external perturbations. DNA metabarcoding is an approach that has gained significant traction by aiding ecosystem conservation and management. Here, the seasonal and spatial variability in the zooplankton diversity were analyzed in the Poyang Lake Basin using DNA metabarcoding. The results showed that the community structure of zooplankton exhibited significant seasonal and spatial variability using DNA metabarcoding, where the community structure was correlated with turbidity, water temperature, pH, total phosphorus, and chlorophyll‐a. These results indicated habitat variations affected by human activities and seasonal change could be the main driving factors for the variations of zooplankton community. This study also provides an important reference for the management of aquatic ecosystem health and conservation of aquatic biodiversity.

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

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.

Seven Years Study of the Seasonal Dynamics of Zooplankton Communities in a Large Subtropical Floodplain Ecosystem: A Test of the PEG Model

Irregular hydrological events, according to a classic plankton ecology group (PEG) study, can generate major deviations from the standard PEG model. However, little is known about the function of hydrological factors in influencing the seasonal dynamics of plankton. We used multivariate and Partial Least Squares Path Modeling to analyze the seasonal variation in crustacean zooplankton and related environmental factors from winter 2009 to winter 2016 in Lake Poyang, the largest freshwater lake in China. We found a distinct seasonal pattern in zooplankton development, which deviated, in part, from the PEG model, as we found indications of (1) a weaker degree of food limitation in winter and spring, likely due to high concentrations of allochthonous sources caused by decomposition of seasonally flooded hygrophytes, also affecting sediment dynamics; (2) a peak in crustacean zooplankton biomass in summer when the water level was high (and predation was lower), and where horizontal transport of zooplankton from the littoral zone to the pelagic was possibleand (3) a higher predation pressure in autumn, likely due to a shrinking water volume that left the fish concentrated in less water. The majority of these differences can be attributed to the direct or indirect impacts of physical factor variation.

Metacommunity Concepts Provide New Insights in Explaining Zooplankton Spatial Patterns within Large Floodplain Systems

Flood pulse related physical variables (FLOOD) can affect zooplankton community structure through local factors directly and can also influence through regional dispersal factors of metacommunity concepts indirectly. Therefore, we infer that spatial patterns of zooplankton communities could be related to metacommunity concepts and their importance may depend on the size of the aquatic/terrestrial transition zone (ATTZ). Herein, we explored the relative importance of limnological (LIMNO) and FLOOD variables in zooplankton community by analyzing data from 272 sites across three floodplain lakes in the middle reaches of the Yangtze River. Our results showed that the variation in the zooplankton community can be well explained by the LIMNO and FLOOD variables in all of the lakes under the low water level season. However, during the high water level season, neither LIMNO nor FLOOD can explain the spatial variances of zooplankton. Therefore, our results indicated that testing biogeographical theories and macroecological laws using zooplankton should consider temporal aspects of flood pulse. Furthermore, we noted that the number of explained variance by local variables is negatively correlated with the size of the ATTZ. Metacommunity concepts provide complementary insights in explaining zooplankton spatial patterns within large floodplain systems, which also provide a theoretical basis for ATTZ protection in floodplain management.

Linking human activities and global climatic oscillation to phytoplankton dynamics in a subtropical lake

Human activities and climate change are two major stressors affecting lake ecosystems as well as phytoplankton communities worldwide. However, how the temporal dynamics of phytoplankton are directly or indirectly linked to anthropogenic activities and climatic oscillation remains unclear. We assessed the annual trends (1988-2018) in phytoplankton abundance (PA) in Lake Dongting, China and related it to five groups of variables characterizing human activities, global climate oscillation, water nutrients, hydrology, and meteorology. We found a significant increase in PA, urbanization (Upop), total nitrogen (TN), fertilizer application (FA), number of summer days (SU), and the warm speed duration index (WSDI) and a significant decrease in the water discharge of three inlets (TIWD) and the sediment discharge of three inlets (TISD) and four tributaries (FTSD) and the net sediment deposition (NSD). However, no significant annual trends were observed for the number of rainstorm days (R50mm), the simple precipitation intensity index (SDII) and yearly anomalies of El Niño-Southern oscillation events (ENSOi). Cross-correlation Function analyses demonstrated that the operation of the Three George Dam (TGD) strengthened the effects of hydrology, rainfall patterns and ENSOi on phytoplankton, but strongly weakened the association between water nutrients, human activities and phytoplankton abundance. Path analysis revealed that TP, TN, FA, R50 mm as well as WSDI had a direct positive effect on PA, while a direct negative effect was found for ENSO_i, NSD and TISD. Human activities (Upop and FA), warming (WSDI and SU), and rainfall patterns (SDII and R50 mm) exerted indirect controls on phytoplankton through changes in water nutrients and hydrology. Climate change (ENSOi) had a direct effect on PA, but also showed twelve indirect pathways via changes in hydrology and meteorology (both positive and negative effects were found). Overall, meteorology contributed most markedly to the variations of PA (29.3%), followed by hydrology (25.3%), human activities (24%), water nutrients (10.5%), and ENSOi (1.9%). Our results highlight a strongly causal connection between human activities as well as global climate change and phytoplankton and the benefits of considering multiple environmental drivers in determining the temporal dynamics of lake biotic communities.