This page has only limited features, please log in for full access.

Unclaimed
Yinru Lei
Beijing Key Laboratory of Wetland Services and Restoration, Beijing 100091, China

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 21 September 2020 in Water
Reads 0
Downloads 0

Decomposition of emergent macrophytes is now recognized as an internal nutrient source for shallow lakes. Temperate lakes always experience seasonal ice cover in winter, but the influences of emergent macrophytes decomposition on water quality have rarely been examined under ice. Here, we conducted an incubation experiment to investigate winter decomposition of two common emergent macrophytes species (Typha orientalis and Phragmites australis) and its influences on water quality in the Hengshui Lake, North China. Mesocosms simulating a lake ice regime were incubated in the field for 120 days in winter and were treated with and without plant material addition. Water quality was monitored through dissolved oxygen (DO), dissolved organic carbon (DOC), total nitrogen (TN), total phosphorus (TP), ammonium nitrogen (NH4-N), and nitrate nitrogen (NO3-N). We found that both species were significantly decomposed in winter and that the majority of mass loss occurred in the first 10 days of decomposition when the water surface of mesocosms were already frozen. The concentrations of DO rapidly dropped to values close to zero after plant material submergence. At the end of incubation, the concentrations of DOC, TN, and NO3-N in the mesocosms with plant material addition were significantly higher than initial concentrations. In contrast, the concentrations of DOC, TN, TP, NO3-N, and NH4-N in the mesocosms without plant material addition were equal to or less than initial concentrations. Our research suggests that winter decomposition of emergent macrophytes produces negative influences on water quality under ice that lasts for the whole winter.

ACS Style

Yuanyun Wei; Manyin Zhang; Lijuan Cui; Xu Pan; Weiwei Liu; Wei Li; Yinru Lei. Winter Decomposition of Emergent Macrophytes Affects Water Quality under Ice in a Temperate Shallow Lake. Water 2020, 12, 2640 .

AMA Style

Yuanyun Wei, Manyin Zhang, Lijuan Cui, Xu Pan, Weiwei Liu, Wei Li, Yinru Lei. Winter Decomposition of Emergent Macrophytes Affects Water Quality under Ice in a Temperate Shallow Lake. Water. 2020; 12 (9):2640.

Chicago/Turabian Style

Yuanyun Wei; Manyin Zhang; Lijuan Cui; Xu Pan; Weiwei Liu; Wei Li; Yinru Lei. 2020. "Winter Decomposition of Emergent Macrophytes Affects Water Quality under Ice in a Temperate Shallow Lake." Water 12, no. 9: 2640.

Journal article
Published: 10 April 2018 in Sustainability
Reads 0
Downloads 0

Wetlands are one of the world’s most productive ecosystems, and therefore it is crucial that management decisions regarding wetlands incorporate awareness of accurate assessments of the value of their respective ecosystem services. In this paper, we seek to improve the modelling precision in the scale transform process of ecosystem service evaluation. Firstly, we selected eight services as the criteria to calculate wetland ecosystem values: substance production, flood control, carbon sequestration, gas regulation, climate regulation, wave reduction, adding new lands, recreation and education. Then, six coastal wetlands of Liaoning province were chosen as the case study areas, and their ecosystem values were calculated by empirical method. Next, we simulated ecosystem values of the six cases by two spatial-scales transform methods named meta-analysis and wavelet transform. Finally, we compared the two groups of simulated values with the empirical measured values to examine their evaluation precisions. The results indicated that the total precision of the wavelet transform model (0.968) was higher than that of meta-analysis (0.712). In addition, the simulated values of single services such as substance production, flood control, carbon sequestration, gas regulation, and climate regulation were closer to the measured values using wavelet transform model. This research contributes to identifying an evaluation model with higher precision for evaluating wetland ecosystem services in the process of scale transform.

ACS Style

Baodi Sun; Yinru Lei; Lijuan Cui; Wei Li; XiaoMing Kang; Manyin Zhang. Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands. Sustainability 2018, 10, 1136 .

AMA Style

Baodi Sun, Yinru Lei, Lijuan Cui, Wei Li, XiaoMing Kang, Manyin Zhang. Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands. Sustainability. 2018; 10 (4):1136.

Chicago/Turabian Style

Baodi Sun; Yinru Lei; Lijuan Cui; Wei Li; XiaoMing Kang; Manyin Zhang. 2018. "Addressing the Modelling Precision in Evaluating the Ecosystem Services of Coastal Wetlands." Sustainability 10, no. 4: 1136.

Journal article
Published: 09 April 2018 in Sustainability
Reads 0
Downloads 0

The chlorophyll content can indicate the general health of vegetation, and can be estimated from hyperspectral data. The aim of this study is to estimate the chlorophyll content of mangroves at different stages of restoration in a coastal wetland in Quanzhou, China, using proximal hyperspectral remote sensing techniques. We determine the hyperspectral reflectance of leaves from two mangrove species, Kandelia candel and Aegiceras corniculatum, from short-term and long-term restoration areas with a portable spectroradiometer. We also measure the leaf chlorophyll content (SPAD value). We use partial-least-squares stepwise regression to determine the relationships between the spectral reflectance and the chlorophyll content of the leaves, and establish two models, a full-wave-band spectrum model and a red-edge position regression model, to estimate the chlorophyll content of the mangroves. The coefficients of determination for the red-edge position model and the full-wave-band model exceed 0.72 and 0.82, respectively. The inverted chlorophyll contents are estimated more accurately for the long-term restoration mangroves than for the short-term restoration mangroves. Our results indicate that hyperspectral data can be used to estimate the chlorophyll content of mangroves at different stages of restoration, and could possibly be adapted to estimate biochemical constituents in leaves.

ACS Style

Zhiguo Dou; Lijuan Cui; Jing Li; Yinuo Zhu; Changjun Gao; Xu Pan; Yinru Lei; Manyin Zhang; Xinsheng Zhao; Wei Li. Hyperspectral Estimation of the Chlorophyll Content in Short-Term and Long-Term Restorations of Mangrove in Quanzhou Bay Estuary, China. Sustainability 2018, 10, 1127 .

AMA Style

Zhiguo Dou, Lijuan Cui, Jing Li, Yinuo Zhu, Changjun Gao, Xu Pan, Yinru Lei, Manyin Zhang, Xinsheng Zhao, Wei Li. Hyperspectral Estimation of the Chlorophyll Content in Short-Term and Long-Term Restorations of Mangrove in Quanzhou Bay Estuary, China. Sustainability. 2018; 10 (4):1127.

Chicago/Turabian Style

Zhiguo Dou; Lijuan Cui; Jing Li; Yinuo Zhu; Changjun Gao; Xu Pan; Yinru Lei; Manyin Zhang; Xinsheng Zhao; Wei Li. 2018. "Hyperspectral Estimation of the Chlorophyll Content in Short-Term and Long-Term Restorations of Mangrove in Quanzhou Bay Estuary, China." Sustainability 10, no. 4: 1127.

Journal article
Published: 18 January 2018 in Water
Reads 0
Downloads 0

Nutrient removal in tidal flow constructed wetlands (TF-CW) is a complex series of nonlinear multi-parameter interactions. We simulated three tidal flow systems and a continuous vertical flow system filled with synthetic wastewater and compared the influent and effluent concentrations to examine (1) nutrient removal in artificial TF-CWs, and (2) the ability of a backpropagation (BP) artificial neural network to predict nutrient removal. The nutrient removal rates were higher under tidal flow when the idle/reaction time was two, and reached 90 ± 3%, 99 ± 1%, and 58 ± 13% for total nitrogen (TN), ammonium nitrogen (NH4+-N), and total phosphorus (TP), respectively. The main influences on nutrient removal for each scenario were identified by redundancy analysis and were input into the model to train and verify the pollutant effluent concentrations. Comparison of the actual and model-predicted effluent concentrations showed that the model predictions were good. The predicted and actual values were correlated and the margin of error was small. The BP neural network fitted best to TP, with an R2 of 0.90. The R2 values of TN, NH4+-N, and nitrate nitrogen (NO3−-N) were 0.67, 0.73, and 0.69, respectively.

ACS Style

Wei Li; Lijuan Cui; YaQiong Zhang; Zhangjie Cai; Manyin Zhang; Weigang Xu; Xinsheng Zhao; Yinru Lei; Xu Pan; Jing Li; Zhiguo Dou. Using a Backpropagation Artificial Neural Network to Predict Nutrient Removal in Tidal Flow Constructed Wetlands. Water 2018, 10, 83 .

AMA Style

Wei Li, Lijuan Cui, YaQiong Zhang, Zhangjie Cai, Manyin Zhang, Weigang Xu, Xinsheng Zhao, Yinru Lei, Xu Pan, Jing Li, Zhiguo Dou. Using a Backpropagation Artificial Neural Network to Predict Nutrient Removal in Tidal Flow Constructed Wetlands. Water. 2018; 10 (1):83.

Chicago/Turabian Style

Wei Li; Lijuan Cui; YaQiong Zhang; Zhangjie Cai; Manyin Zhang; Weigang Xu; Xinsheng Zhao; Yinru Lei; Xu Pan; Jing Li; Zhiguo Dou. 2018. "Using a Backpropagation Artificial Neural Network to Predict Nutrient Removal in Tidal Flow Constructed Wetlands." Water 10, no. 1: 83.

Journal article
Published: 27 October 2017 in Water
Reads 0
Downloads 0

Wetland plants are important components in constructed wetlands (CWs), and one of their most important functions in CWs is to purify the water. However, wetland plant litter can also increase eutrophication of water via decomposition and nutrient release, and few studies have focused on the interspecific variation in the decomposition rate and nutrient release of multiple plant species in CWs. Here a greenhouse litter-bag experiment was conducted to quantify the decomposition rates and nutrient release of 7 dominant macrophytes (2 floating plants and 5 emergent plants) in three types of water substrate. The results showed that plant litter species and growth forms significantly affected the litter mass losses. The nutrient release was significantly different among plant litter species, but not between floating and emergent plants. Litter traits, such as litter lignin, total nitrogen (TN) and total phosphorus (TP) can well predict the decomposition rates of submerged litter. These results indicated that submerging litter in water did not change the relationships between litter traits and litter decomposition rates, and leaching might play a more important role in the decomposition of submerged litter in CWs than that in other terrestrial ecosystems. These findings can provide suggestions for managers about the maintenance of constructed wetlands.

ACS Style

Yunmei Ping; Xu Pan; Lijuan Cui; Wei Li; Yinru Lei; Jian Zhou; Jiaming Wei. Effects of Plant Growth Form and Water Substrates on the Decomposition of Submerged Litter: Evidence of Constructed Wetland Plants in a Greenhouse Experiment. Water 2017, 9, 827 .

AMA Style

Yunmei Ping, Xu Pan, Lijuan Cui, Wei Li, Yinru Lei, Jian Zhou, Jiaming Wei. Effects of Plant Growth Form and Water Substrates on the Decomposition of Submerged Litter: Evidence of Constructed Wetland Plants in a Greenhouse Experiment. Water. 2017; 9 (11):827.

Chicago/Turabian Style

Yunmei Ping; Xu Pan; Lijuan Cui; Wei Li; Yinru Lei; Jian Zhou; Jiaming Wei. 2017. "Effects of Plant Growth Form and Water Substrates on the Decomposition of Submerged Litter: Evidence of Constructed Wetland Plants in a Greenhouse Experiment." Water 9, no. 11: 827.

Journal article
Published: 04 August 2017 in Sustainability
Reads 0
Downloads 0

Given that increasing migration has been addressed as a major consequence of climate change, a growing number of scholars suggest that the planned relocation of people or Government Resettlement Projects (GRPs) should be included in climate change adaptation. This paper reviews the status of climate change and environmentally induced migration in China, and then presents an empirical case study in Shangnan County in northwest China, where a specific GRP called the ‘Massive Southern Shaanxi Migration Program’ (MSSMP) has been initiated in response to climate change-related impacts. The results showed that the MSSMP helped local residents to adapt better climate change by reducing exposures to risk, enabling mobility, providing financial incentives, raising living standards, and improving emotional status. Furthermore, the MSSMP added additional benefits for migrants compared with traditional GRPs by respecting voluntary participation, preparing for future risks, and reducing social isolation via a short relocation distance. However, GRPs could also be seen as a maladaptation to climate change because they disproportionately increase the burden on the most vulnerable community members, such as those who are financially disadvantaged, new migrants, and people who are left behind. The paper further suggests that the GRPs should be designed by involving multiple adaptation strategies as supplements for GRPs, and broadening the political schemes to consider the special needs of vulnerable groups. This study contributes to an understanding of the roles of GRPs in sustainable climate change adaptation, thereby facilitating the design, organization, and implication of future similar programs.

ACS Style

Yinru Lei; C. Max Finlayson; Rik Thwaites; Guoqing Shi; Lijuan Cui. Using Government Resettlement Projects as a Sustainable Adaptation Strategy for Climate Change. Sustainability 2017, 9, 1373 .

AMA Style

Yinru Lei, C. Max Finlayson, Rik Thwaites, Guoqing Shi, Lijuan Cui. Using Government Resettlement Projects as a Sustainable Adaptation Strategy for Climate Change. Sustainability. 2017; 9 (8):1373.

Chicago/Turabian Style

Yinru Lei; C. Max Finlayson; Rik Thwaites; Guoqing Shi; Lijuan Cui. 2017. "Using Government Resettlement Projects as a Sustainable Adaptation Strategy for Climate Change." Sustainability 9, no. 8: 1373.

Journal article
Published: 07 November 2016 in Water
Reads 0
Downloads 0

We monitored the water quality and hydrological conditions of a horizontal subsurface constructed wetland (HSSF-CW) in Beijing, China, for two years. We simulated the area-based constant and the temperature coefficient with the first-order kinetic model. We examined the relationships between the nitrogen (N) removal rate, N load, seasonal variations in the N removal rate, and environmental factors—such as the area-based constant, temperature, and dissolved oxygen (DO). The effluent ammonia (NH4+-N) and nitrate (NO3−-N) concentrations were significantly lower than the influent concentrations (p < 0.01, n = 38). The NO3−-N load was significantly correlated with the removal rate (R2 = 0.96, p < 0.01), but the NH4+-N load was not correlated with the removal rate (R2 = 0.02, p > 0.01). The area-based constants of NO3−-N and NH4+-N at 20 °C were 27 ± 26 (mean ± SD) and 14 ± 10 m∙year−1, respectively. The temperature coefficients for NO3−-N and NH4+-N were estimated at 1.004 and 0.960, respectively. The area-based constants for NO3−-N and NH4+-N were not correlated with temperature (p > 0.01). The NO3−-N area-based constant was correlated with the corresponding load (R2 = 0.96, p < 0.01). The NH4+-N area rate was correlated with DO (R2 = 0.69, p < 0.01), suggesting that the factors that influenced the N removal rate in this wetland met Liebig’s law of the minimum.

ACS Style

Lijuan Cui; Wei Li; YaQiong Zhang; Jiaming Wei; Yinru Lei; Manyin Zhang; Xu Pan; Xinsheng Zhao; Kai Li; Wu Ma. Nitrogen Removal in a Horizontal Subsurface Flow Constructed Wetland Estimated Using the First-Order Kinetic Model. Water 2016, 8, 514 .

AMA Style

Lijuan Cui, Wei Li, YaQiong Zhang, Jiaming Wei, Yinru Lei, Manyin Zhang, Xu Pan, Xinsheng Zhao, Kai Li, Wu Ma. Nitrogen Removal in a Horizontal Subsurface Flow Constructed Wetland Estimated Using the First-Order Kinetic Model. Water. 2016; 8 (11):514.

Chicago/Turabian Style

Lijuan Cui; Wei Li; YaQiong Zhang; Jiaming Wei; Yinru Lei; Manyin Zhang; Xu Pan; Xinsheng Zhao; Kai Li; Wu Ma. 2016. "Nitrogen Removal in a Horizontal Subsurface Flow Constructed Wetland Estimated Using the First-Order Kinetic Model." Water 8, no. 11: 514.