Phytoplankton dynamics and their relationship with environmental variables of Lake Poyang

Field investigations were conducted to identify environmental variables in ﬂ uencing phytoplankton dynamics in Lake Poyang. The results showed that diatoms predominated in the phytoplankton community. Concentrations of nutrients were high, and levels of phytoplankton biomass and chlorophyll a were low. During the low water level period (WLP), from January to May 2013, phytoplankton biomass was low. It increased from July 2013 and peaked in September 2013 during the high WLP. From October 2013 to January 2014, phytoplankton biomass decreased again. Highest values were generally measured in the middle district and lowest in the northern district. It decreased from October 2013 to January 2014. Redundancy analysis showed that water temperature and suspended solids (SS) concentrations were the principal factors regulating the growth of phytoplankton. The variations in SS were contrary to the biomass variations at the spatial level. During the high WLP, the blocking effect of the Yangtze River led to decreased water velocity and prolonged water retention time in Lake Poyang. Due to both the SS sedimentation and increase in water temperature, phytoplankton grew rapidly. Based on these ﬁ ndings, the variety of phytoplankton dynamics was caused by the combined effects of the Yangtze River effect, water temperature, and SS.


INTRODUCTION
Phytoplankton is the main primary producer of water ecosystems and plays an important role in food chains (Reynolds ). Alterations in phytoplankton composition and distribution characteristics in water reflect a changing environment and indicate the trophic status have received particular attention in the world's northernmost temperate lakes. When compared to other macronutrients required by biota, phosphorus is the least abundant and commonly the first element to limit biological productivity (Wetzel ). However, the nutrient-chlorophyll a (Chl a) relationship is generally nonlinear, and suggests that other factors, e.g., physical (water level, water flow, light) and biotic (predation, competition) also limit algal growth (Millard et al. ; Schernewski et al. ).
With regard to lotic lakes, hydrological factors such as water level, water flow, and water retention time are thought to be of greater importance to phytoplankton development (Pace et  As one of the largest floodplains in the world, the Yangtze River floodplain is characterized by numerous shallow lakes which are freely connected to the Yangtze River (Pan et al. ). Lake Poyang, which is the largest freshwater lake in China and connected to the Yangtze River, is characterized by complex hydrographic conditions. Nitrogen and phosphorus concentrations of Lake Poyang have increased in the last 30 years (Zhen ). The concentrations of nitrogen and phosphorus were 0.684 mg/L and 0.076 mg/L in 1998, but were 2 times and 0.2 times higher, respectively, in 2013. However, the Chl a content of Lake Poyang increased slowly relative to other eutrophic lakes, such as Taihu and Chaohu in the mid-lower regions of the Yangtze River. Lake Poyang has five tributaries and connects to the Yangtze River (Pan et al. ). Water exchange between Lake Poyang and the five tributaries, the Yangtze River, or the upstream reservoirs is closely related and determines the unique seasonal fluctuation of inflow discharge, water level, and flow velocity of the lake ( Jiang & Huang ; Guo et al. ; Zhang et al. ). These characteristics have made phytoplankton dynamics and environmental factors very complicated. Wu et al. () found that the biomass of major algal groups (i.e., Bacillariophyta, Cryptophyta, and Chlorophyta) and the total biomass of Lake Poyang were significantly and positively correlated with the average transparency determined from seasonal data. The annual trends in phytoplankton Chl a were associated with nutrient concentrations and temperature, but few significant correlations between Chl a and the nutrient concentrations were observed in the dry and mid-dry seasons of Lake Poyang (Wu et al. ; Wang et al. ), and light (or turbidity) and water retention time is more important than nutrients for restricting phytoplankton biomass (Wu et al. a, b). Pan et al. () showed that phytoplankton Chl a was closely related to certain environmental factors, especially water velocity (U) at lotic sites. Regression analyses in lotic regions revealed that a higher amount of variance in log 10 Chl a was accounted for by U 0.5 (r 2 ¼ 0.34), and that U was the major factor influencing Chl a.
However, under the complicated variations in the riverlake relationship, especially the blocking effect of the Yangtze River to Lake Poyang during the high water level period

Study area
Lake Poyang ( spatial variations in phytoplankton, the study area was divided into three regions, the northern district (sites 1-5), the middle district (sites 6-11), and the southern district Selected environmental parameters, including water temperature (T), pH, and dissolved oxygen (DO), were obtained using a Hydrolab Data Sonde 5 sensor in situ.
Water samples were obtained and placed into acid-cleaned 1 L plastic containers and kept cool and shaded before being transported to the laboratory for analysis, which was conducted in 24 hours. TN was measured by the alkaline potassium persulfate digestion-UV spectrophotometric method, while ammonia nitrogen (NH 3 -N) was analyzed by Nessler's reagent spectrophotometry. TP was measured using the ammonium molybdate method, SS were analyzed using the weighing method (105 W C) and water transparency (Tran) was determined using a Secchi disk. All of the above

RESULTS
Phytoplankton community structure and dominant species Overall, 81 genera belonging to eight phyla were identified during 2013 (Appendix and Table 1; the Appendix is available with the online version of the paper). Chlorophyta (40 genera) were the largest group, representing 49.38% of the total number of genera, followed by Cyanophyta (17)  was much lower than that of the phyla listed above. The order of magnitude of cell density was not the same as that of the phytoplankton biomass. Cyanophyta, Bacillariophyta, and Chlorophyta accounted for most of the cells (78.37%).

Temporal-spatial distribution of phytoplankton
The biomass varied greatly in different WLPs. The average biomass was highest in the high WLP (0.562 mg/L), which was much higher than in the normal and low WLPs  Table 2). The distributions of Cyanophyta, Chlorophyta, Bacillariophyta, and Euglenophyta were mainly related to temperature, while Pyrrophyta and Chrysophyta were influenced by transparency ( Figure 5; Table 2).

DISCUSSION
Nutrients such as TN and TP were relatively high, while phytoplankton biomass and Chl a levels were relatively low and Bacillariophyta still dominated in Lake Poyang.
These findings suggest that phytoplankton dynamics in Lake Poyang were affected not only by the nutrients, but also by other factors.

Phytoplankton biomasses and environmental variables
Being connected to five tributaries and the Yangtze River, all of which had large water flow, Lake Poyang exhibits strong hydrodynamic conditions and high SS concentrations. Figure 5 shows that SS and velocity may be the important factors affecting phytoplankton biomass.    Table 3.

Dynamics of phytoplankton biomass
From January to May (the normal WLP), the phytoplankton biomass of Lake Poyang increased slowly. From July to August (the high WLP), the phytoplankton biomass increased rapidly in the static lake water. After October (the normal and low WLP), the biomass began to decline.
The water level and water volume of Lake Poyang increased gradually from January to May. During this time, phytoplankton biomass increased with an increase in the amount of light (Figure 6), which suggested that increases in radiant energy are conducive to the growth of phytoplankton. In July, water level and water volume increased to maximum values of 16.71 m and 13,000 m 3 /s, respectively. Phytoplankton biomass increased rapidly from July, and peaked in August. At this time, the water velocity of Lake Poyang decreased (Figure 7), the water retention time was prolonged (25.5 d) (Wu et al. a) and the SS sedimentation increased. The five tributaries carried high volumes of nutrients into the lake, which, when coupled with the higher water temperature, accelerated the growth of the phytoplankton. However, the amount of radiant energy cannot explain the increase in biomass ( Figure 6).   high. Furthermore, water temperature and the radiant energy ( Figure 6) were decreasing rapidly, which was not beneficial to phytoplankton growth (Wang et al. ). In addition, the opposite trend was observed on the spatial level for phytoplankton biomass with SS ( Figure 8). Specifically, the biomass decreased as the SS increased. The relationship between phytoplankton biomass and SS was more pronounced on the spatial level than on the temporal level.

Dominant phytoplankton of Lake Poyang
Although TN and TP of Lake Poyang were relatively high, Diatoms also have the highest algae density in

Cyanobacterial risk in local area
Despite diatoms being the dominant group in Lake Poyang,

CONCLUSION
The phytoplankton community of Lake Poyang was found to be composed of 8 phyla and 81 genera. The biomass was much higher in the high WLP than in the normal WLP and the low WLP. During the high WLP, phytoplankton biomass increased rapidly; however, after the high WLP it decreased greatly. Phytoplankton biomass was generally highest in the middle district and lowest in the northern district. Nutrients in Lake Poyang were high, while phytoplankton biomass and chlorophyll a contents were low and the phytoplankton community was still dominated by Bacillariophyta, which may be the reason for the strong hydrodynamic condition and high SS concentrations. The relationship between biomass and SS mainly reflected on the spatial distribution. Phytoplankton biomass was extremely high in the high WLP, which was caused by the combined effects of the blocking effect of the Yangtze River, water temperature, and SS.