Yifei Wang

Effect of mangrove restoration on crab burrow density in Luoyangjiang Estuary, China

BackgroundMangrove restoration seeks to restore or rebuild degraded mangrove systems. The methods of mangrove restoration include ecological projects and restoration-oriented technologies, the latter of which are designed to restore the structure, processes as well as related physical, chemical and biological characteristics of wetlands and to ensure the provision of ecosystem services. As important components of mangrove ecosystem, benthic organisms and crabs play a key role in nutrient cycling. In addition, mangrove restoration, such as vegetation restoration measures, can lead to changes in the benthic faunal communities. This study investigates whether the presence of different mangrove species, age and canopy cover of mangrove communities affect the density of crab burrows.MethodsThe Luoyangjiang Estuary, in the southeast of Fujian Province, was selected as our research area. A survey, covering 14 sites, was conducted to investigate the impacts of mangrove restoration on the density of crab burrows in four rehabilitated forests with different stand ages and canopy.ResultsIt was found that differences in vegetation types had a large impact on crab density and that the density of crab burrows was lower on exposed beaches (non-mangrove) than under mature Kandelia candel, Aegiceras corniculatum and Avicennia marina communities. In general, the amount of leaf litter and debris on mangrove mudflats was greater than on the beaches as food sources for crabs. Two-factor analysis of variance (ANOVA) shows that changes in mangrove species and age since restoration had different effects on crab burrow density. The effect of canopy cover was highly significant on crab burrow density.ConclusionsThe results suggest that in the process of mangrove restoration the combined effects of mangrove stand age, canopy cover and other factors should be taken into account. This study further supports the findings of the future scientific research and practice on mangrove restoration and management measures.

Modeling total phosphorus removal in an aquatic environment restoring horizontal subsurface flow constructed wetland based on artificial neural networks

A horizontal subsurface flow constructed wetland (HSSF-CW) was designed to improve the water quality of an artificial lake in Beijing Wildlife Rescue and Rehabilitation Center, Beijing, China. Artificial neural networks (ANNs), including multilayer perceptron (MLP) and radial basis function (RBF), were used to model the removal of total phosphorus (TP). Four variables were selected as the input parameters based on the principal component analysis: the influent TP concentration, water temperature, flow rate, and porosity. In order to improve model accuracy, alternative ANNs were developed by incorporating meteorological variables, including precipitation, air humidity, evapotranspiration, solar heat flux, and barometric pressure. A genetic algorithm and cross-validation were used to find the optimal network architectures for the ANNs. Comparison of the observed data and the model predictions indicated that, with careful variable selection, ANNs appeared to be an efficient and robust tool for predicting TP removal in the HSSF-CW. Comparison of the accuracy and efficiency of MLP and RBF for predicting TP removal showed that the RBF with additional meteorological variables produced the most accurate results, indicating a high potentiality for modeling TP removal in the HSSF-CW.

Identification and modelling the HRT distribution in subsurface constructed wetland

This study focused on the identification of the hydrodynamics of a horizontal subsurface constructed wetland (HSSF-CW) located in Beijing wildlife rescue and rehabilitation center, Beijing. The effects of plant growth of iris tectorum on the hydrodynamic behaviours were studied and the distribution of the hydraulic residence time was simulated by several mathematical models in order to understand the fluctuations and mixing processes of pollutants in the HSSF-CW. Treatment performance of the HSSF-CW was evaluated by comparing the area-based removal rates of different pollutants. According to the results, water depth has a negative effect on the plant growth and a larger hydraulic loading rate is not conducive to the growth of wetland plants. Modelling the probability density of the residence time distribution indicated that the shorter hydraulic residence time of 10.16 hours compared with a theoretical hydraulic residence time of 12.81 hours was responsible for the lower removal efficiency of pollutants (T-P: 0.17 ± 0.04 g m(-2) day(-1), T-N: 1.10 ± 0.05 g m(-2) day(-1), PO(4)-P: 0.08 ± 0.04 g m(-2) day(-1), NH(4)-N: 0.19 ± 0.02 g m(-2) day(-1), NO(3)-N: 0.52 ± 0.03 g m(-2) day(-1), Chl_a: 18.26 ± 0.09 g m(-2) day(-1)). The results of a superposition simulation of residence time distribution indicated that the asymmetric double sigmoidal (asym2sig) model is competent at providing a reasonable match between the measured and the predicted values to some extent. Based on the good fit of the experimental datasets by the asym2sig probability density function, the mathematical expectation approximated to the actual hydraulic residence time (10.16 hours) of the HSSF-CW.