Research on the carbon isotopic composition of organic matter from Lake Chenghai and Caohai Lake sediments

The carbon isotopic composition of organic matter from lake sediments has been extensively used to infer variations in productivity. In this paper, based on the study of the contents and δ13C values of organic matter in different types of lakes, it has been found that δ13C values of organic matter have different responses to lake productivity in different lakes. As to the lakes dominated by aqutic macrophytes such as Lake Caohai, organic matter becomes enriched in 13C with increasing productivity. As to the lakes dominated by aquatic algae such as Lake Chenghai, δ13C values of organic matter decrease with increasing productivity, and the degradation of aquatic algae is the main factor leading to the decrease of δ13C values of organic matter with increasing productivity. Therefore, we should be cautious to use the carbon isotopic composition of organic matter to deduce lake productivity.

Temporal and spatial distribution of phytoplankton functional groups and role of environment factors in a deep subtropical reservoir

Phytoplankton and environment factors were investigated in 2015 and phytoplankton functional groups were used to understand their temporal and spatial distribution and their driving factors in Wanfeng Reservoir. Seventeen functional groups(B, D, E, F, G, J, Lo, MP, P, S1, T, W1, W2, X1, X2, Xph, Y) were identified based on 34 species. The dominant groups were: J/B/P/D in dry season, X1/J/Xph/G/T in normal season and J in flood season. Phytoplankton abundance ranged from 5.33×10~4 cells/L to 3.65×10~7 cells/L, with the highest value occurring in flood season and lowest in dry season. The vertical profi le of dominant groups showed little differentiation except for P, which dominated surface layers over 20 m as a result of mixing water masses and higher transparency during dry season. However, the surface waters presented higher values of phytoplankton abundance than other layers, possibly because of greater irradiance. The significant explaining variables and their ability to describe the spatial distribution of the phytoplankton community in RDA diff ered seasonally as follows: dry season, NH4-N, NO_3-N, NO_2-N, TN:TP ratio and transparency(SD); normal season, temperature(WT), water depth, TN, NH4-N and NO_3-N; flood season, WT, water depth, NO_3-N and NO_2-N. Furthermore, nitrogen, water temperature, SD and water depth were significant variables explaining the variance of phytoplankton communities when datasets included all samples. The results indicated that water physical conditions and hydrology were important in phytoplankton community dynamics, and nitrogen was more important than phosphorus in modifying phytoplankton communities. Seasonal differences in the relationship between the environment and phytoplankton community should be considered in water quality management.

δ13C-δ18O Covariance:An Effective Indicator of Hydrological Closure for Lakes?

The correlation between the δ^13C and δ^13C-δ^18O in primary carbonates is affected by several factors such as hydrological balance, total CO2 concentrations, climatic condition and lake productivity. The influence of these factors on the δ^13C-δ^18O correlation may be different on different time scales. In this paper, two different-type lakes in southwestern China, Lake Erhai and Lake Chenghai, are selected to investigate the influence of climatic pattern on the δ^13C-δ^18O correlation and to evaluate the reliability of the δ^13C-δ^18O covariance as an indicator of hydrological closure. The results show that there exists good correlation between the δ^13C and δ^18O in Lake Erhai （overflowing open lake） and in Lake Chenghai （closed lake）. This suggests that the δ^13C-δ^18O covariance may be not an effective indicator of hydrological closure for lakes, especially on short time scales. On the one hand, a hydrologically open lake may display covariant δ^13C and δ^18O as a result of climatic influence. The particular alternate warm-dry and cold-wet climatic pattern in southwestern China may be the principal cause of the δ^13C-δ^18O covariance in Lake Erhai and Lake Chenghai. On the other hand, a hydrologically closed lake unnecessarily displays covariant trends between δ^13C and δ^18O because of the buffering effect of high CO2 concentration on the δ^13C shift in hyper-alkaline lakes. We should be prudent when we use the covariance between δ^13C and δ^18O to judge the hydrological closure of lake.