Shuangyu Liu

Ms. Shuangyu Liu

Ningxia University, Yinchuan, Ningxia, China
orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 March 2023 in Water
Verified
Journal Article
Open access
PDF file
LLLee Lin
Lee Lin
SLShuangyu Liu
Shuangyu Liu
XQXiaocong Qiu
Xiaocong Qiu
RZRui-Zhi Zhao
Rui-Zhi Zhao
ZZZengfeng Zhao
Zengfeng Zhao
ZCZhanqi Cao
Zhanqi Cao
To investigate the health of the Diannong River water ecosystem, we collected and analyzed phytoplankton, zooplankton, and microorganisms from the Diannong River in April, July, and October 2021. We also analyzed the physical and chemical factors of the water environment and analyzed the habitat quality. The reference points were determined by the habitat composite index and water quality score. Phytoplankton index of biotic integrity (P-IBI), Zooplankton index of biotic integrity (Z-IBI), and microbial index of biotic integrity (M-IBI) which evaluated the health status of Diannong River were constructed by distribution range analysis, discriminatory ability analysis and correlation analysis of candidate biological indicators. Stepwise regression analysis and path coefficient analysis were conducted to determine the environmental factors driving the changes in aquatic IBI. The results showed that the indicators of P-IBI were the number of Cyanobacteria taxonomic units %, the number of Green Algae taxonomic units%, the relative abundance of Euglena, the relative abundance of Green Algae, and the relative abundance of toxic-producing algae. The indicators of Z-IBI were the total number of zooplankton taxonomic units, the relative abundance of Copepods, the relative abundance of the top 3 dominant species, and the Simpson index; the indicators of M-IBI were the Observed species, the relative abundance of Chloroflexi, the relative abundance of Proteobacteria, the relative abundance of the highest dominant taxonomic unit, the relative abundance of the top 5 dominant taxonomic units, the relative abundance of pollution intermediate genus, and the Ace index. The results of the IBI evaluation for three aquatic organisms showed that most of the sites in the upper reaches of the Diannnong River were at healthy or healthier levels; most of the sites in the middle reaches of the Diannnong River and the Yuehai Lake area were at mediocre or poor levels; and most of the sites in the downstream reaches of the Diannong River were average or mediocre levels. the main water environment factors driving the changes in P-IBI were water temperature (WT) and pH. The main water environment factors driving the changes in Z-IBI were total dissolved solids (TDS), WT and total nitrogen (TN); the main water environment factors driving the changes of M-IBI were fluoride ion (F−) and electrical conductivity (EC). This study provides the scientific reference for the application of the index of biotic integrity (IBI) for a variety of aquatic organisms in the river and lake waters and a basis for the management and optimization of the Diannong River aquatic ecosystem.

16 March 2022 in Water
Verified
Journal Article
Open access
PDF file
SLShuangyu Liu
Shuangyu Liu
RZRui-Zhi Zhao
Rui-Zhi Zhao
XQXiaocong Qiu
Xiaocong Qiu
GQGUO Qi
GUO Qi
The purpose of this study was to evaluate the optimum environmental condition required for reaching the maximum growth rate of P. parvum. Eight ions (Na+, K+, CO32−, HCO3−, Ca2+, Mg2+, Cl−, and SO42−) were divided into two groups with a uniform design of 4 factors and 10 levels. The results showed a rising trend in growth rate with increasing ion concentrations. However, concentrations that exceeded the threshold led to a slowdown in the growth rate. Therefore, adequate supply of ion concentrations promoted growth of P. parvum, whereas excessively abundant or deficient ion concentrations inhibited its growth rate. Specifically, the order of impact of the first four ion factors on the growth rate was Na+ > HCO3− > K+ > CO32−. The growth rate of P. parvum reached the maximum theoretical 0.999 when the concentrations of Na+, K+, CO32−, and HCO3− ions were 397.98, 11.60, 3.37, and 33.31 mg/L, respectively. This theoretical growth maximum was inferred from the experimental results obtained in this study. For other ion factors, SO42− had the most influence on the growth rate of P. parvum, followed by Mg2+, Ca2+, and Cl− ions. The growth rate of P. parvum reached the maximum theoretical value of 0.945 when the concentrations of Ca2+, Mg2+, Cl−, and SO42− ions were 11.52, 32.95, 326.29, and 377.31 mg/L, respectively. The findings presented in this study add to our understanding of the growth conditions of P. parvum and provide a theoretical basis for dealing with the water bloom it produces in order to control and utilize it.

13 December 2023 in Water
Verified
Journal Article
Open access
PDF file
JMJunjie Meng
Junjie Meng
RZRui-Zhi Zhao
Rui-Zhi Zhao
XQXiaocong Qiu
Xiaocong Qiu
SLShuangyu Liu
Shuangyu Liu
The Diannong River, a valuable river and lake resource of the northern Ningxia Yellow River Irrigation Area, plays an instrumental role in regional flood control, drought resistance, climate regulation, and biodiversity conservation. Phytoplankton and zooplankton, as crucial elements of the aquatic ecosystem, have their distribution patterns evaluated and potential influencing factors identified, thereby enhancing the understanding of community distribution patterns. Nested structures and interspecies interaction relationships bear significant implications for community distribution patterns, functions, and stability. The upstream section of the Diannong River in Yinchuan City was chosen as the study object. Water samples were collected in January, April, July, and October 2021, and the community composition of phytoplankton and zooplankton was analyzed using relative abundance, density, and biomass. The distribution matrix temperature and bipartite network methodologies were deployed to investigate their nested pattern and interaction network seasonal characteristics. The findings indicate that the water environment of the Diannong River’s upstream section displays pronounced spatiotemporal heterogeneity, characterized by weak alkalinity and high fluoride content. The plankton community composition and relative abundance showed marked differences among the distinct sampling periods. The temperature of the random distribution matrix shows a significant difference compared to the zero-sum model, revealing a notable nested pattern in plankton in the Diannong River’s upstream section. The bipartite network suggests that the plankton composition was the simplest in January and the most complex in July, with the fiercest species competition observed in January and the lowest levels of species specificity, vulnerability, and generality. Water temperature (WT), dissolved oxygen (DO), total phosphorus (TP), available phosphorus (AP), CODCr, F−, and Cl− constitute the environmental parameters influencing the overall structure of the phytoplankton community in the Diannong River’s upstream section, whereas zooplankton did not present a significant correlation with water environmental factors.