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.

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.

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.

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.

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.

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.