Ranhao Sun

Major Ecosystems in China: Dynamics and Challenges for Sustainable Management

Ecosystems, though impacted by global environmental change, can also contribute to the adaptation and mitigation of such large scale changes. Therefore, sustainable ecosystem management is crucial in reaching a sustainable future for the biosphere. Based on the published literature and publicly accessible data, this paper discussed the status and trends of forest, grassland, and wetland ecosystems in China that play important roles in the ecological integrity and human welfare of the nation. Ecological degradation has been observed in these ecosystems at various levels and geographic locations. Biophysical (e.g., climate change) and socioeconomic factors (e.g., intensive human use) are the main reasons for ecosystem degradation with the latter factors serving as the dominant driving forces. The three broad categories of ecosystems in China have partially recovered from degradation thanks to large scale ecological restoration projects implemented in the last few decades. China, as the largest and most populated developing nation, still faces huge challenges regarding ecosystem management in a changing and globalizing world. To further improve ecosystem management in China, four recommendations were proposed, including: (1) advance ecosystem management towards an application-oriented, multidisciplinary science; (2) establish a well-functioning national ecological monitoring and data sharing mechanism; (3) develop impact and effectiveness assessment approaches for policies, plans, and ecological restoration projects; and (4) promote legal and institutional innovations to balance the intrinsic needs of ecological and socioeconomic systems. Any change in China’s ecosystem management approach towards a more sustainable one will benefit the whole world. Therefore, international collaborations on ecological and environmental issues need to be expanded.

Effect of land-use patterns on total nitrogen concentration in the upstream regions of the Haihe River Basin, China.

Nutrient loading into rivers is generally increased by human-induced land-use changes and can lead to increased surface water pollution. Understanding the extent to which land-use patterns influence nutrient loading is critical to the development of best-management practices aimed at water-quality improvement. In this study, we investigated total nitrogen (total N) concentration as a function of land-use patterns and compared the relative significance of the identified land-use variables for 26 upstream watersheds of the Haihe River basin. Seven land-use intensity and nine landscape complexity variables were selected to form the land-use pattern metrics on the landscape scale. After analyzing the significance of the land-use pattern metrics, we obtained five dominant principal components: human-induced land-use intensity, landscape patch-area complexity, area-weighted landscape patch-shape complexity, forest and grassland area, and landscape patch-shape complexity. A linear regression model with a stepwise selection protocol was used to identify an optimal set of land-use pattern predictors. The resulting contributions to the total N concentration were 50% (human-induced land-use intensity), 23.13% (landscape patch-shape complexity), 14.38% (forest and grassland area), and 12.50% (landscape patch-area complexity), respectively. The regression model using land-use measurements can explain 87% of total N variability in the upstream regions of Haihe River. The results indicated that human-related land-use factors, such as residential areas, population, and road density, had the most significant effect on N concentration. The agricultural area (30.1% of the study region) was not found to be significantly correlated with total N concentration due to little irrigative farmland and rainfall. Results of the study could help us understand the implications of potential land-use changes that often occur as a result of the rapid development in China.

Spatial Scale Effects of Water Erosion Dynamics: Complexities, Variabilities, and Uncertainties

Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.

The Impact of Greenspace on Thermal Comfort in a Residential Quarter of Beijing, China

With the process of urbanization, a large number of residential quarters, which is the main dwelling form in the urban area of Beijing, have been developed in last three decades to accommodate the rising population. In the context of intensification of urban heat island (UHI), the potential degradation of the thermal environment of residential quarters can give rise to a variety of problems affecting inhabitants’ health. This paper reports the results of a numerical study of the thermal conditions of a residential quarter on a typical summertime day under four greening modification scenarios, characterized by different leaf area density (LAD) profiles. The modelling results demonstrated that vegetation could evidently reduce near-surface air temperature, with the combination of grass and mature trees achieving as much as 1.5 °C of air temperature decrease compared with the non-green scenario. Vegetation can also lead to smaller air temperature fluctuations, which contribute to a more stable microclimate. The Universal Thermal Climate Index (UTCI) was then calculated to represent the variation of thermal environment of the study area. While grass is helpful in improving outdoor thermal comfort, trees are more effective in reducing the duration and expansion of suffering from severe heat stress. The results of this study showed that proper maintenance of vegetation, especially trees, is significant to improving the outdoor thermal environment in the summer season. In consideration of the deficiency of the current code in the management of greenspace in residential areas, we hope the results reported here will help promote the improvement of the code and related regulations for greenspace management.

Multivariate Statistical Analysis and Risk Assessment of Heavy Metals Monitored in Surface Sediment of the Luan River and its Tributaries, China

ABSTRACT In this study, a total of 84 sites in the Luan River Basin of China and its tributaries were monitored in 2012 for seven heavy metals (Cu, Ni, Pb, Zn, Cd, Cr, Hg) in the surface sediments. Cluster analysis (CA), principal component analysis (PCA), correlation analysis, and pollution indices were applied to the interpretation of the monitoring results. The results show that: (1) sampling sites in the mainstream are classified into two groups, upstream and downstream, with downstream representing higher levels of heavy metals and degrees of pollution; (2) three clusters were identified for the 10 tributaries, the downstream having the highest levels of heavy metals’ pollution; (3) the PCA suggests there are significant correlations among Zn, Cu, and Pb between Cr in the basin. Sediment pollution assessment was carried out using Pollution Index (PI) and Geo-Accumulation Index (Igeo). Mercury was the metal with the highest contamination level, followed by Cd and Cr. The results provide an overview of the current status of sediment contamination with measured data and support future policy development for the protection of water quality in the Luan River Basin.

Assessment of Heavy Metal Pollution in Topsoil around Beijing Metropolis

The topsoil around Beijing metropolis, China, is experiencing impacts of rapid urbanization, intensive farming, and extensive industrial emissions. We analyzed the concentrations of Cu, Ni, Pb, Zn, Cd, and Cr from 87 topsoil samples in the pre-rainy season and 115 samples in the post-rainy season. These samples were attributed to nine land use types: forest, grass, shrub, orchard, wheat, cotton, spring maize, summer maize, and mixed farmland. The pollution index (PI) of heavy metals was calculated from the measured and background concentrations. The ecological risk index (RI) was assessed based on the PI values and toxic-response parameters. The results showed that the mean PI values of Pb, Cr, and Cd were > 1 while those of Cu, Ni, and Zn were < 1. All the samples had low ecological risk for Cu, Ni, Pb, Zn, and Cr while only 15.35% of samples had low ecological risk for Cd. Atmospheric transport rather than land use factors best explained the seasonal variations in heavy metal concentrations and the impact of atmospheric transport on heavy metal concentrations varied according to the heavy metal types. The concentrations of Cu, Cd, and Cr decreased from the pre- to post-rainy season, while those of Ni, Pb, and Zn increased during this period. Future research should be focused on the underlying atmospheric processes that lead to these spatial and seasonal variations in heavy metals. The policymaking on environmental management should pay close attention to potential ecological risks of Cd as well as identifying the transport pathways of different heavy metals.

Analysis and assessment of heavy metal contamination in surface water and sediments: a case study from Luan River, Northern China

Concentrations of the heavy metals Cu, Ni, Pb, Zn, Cd, and Cr were examined in surface water and sediment from the Luan River inChina,. With a decline in Cu and Ni concentration found in surface water at downstream stations. This finding suggests that water currents are a major explanatory factor in heavy metal contamination. The abundance of Cr, Pb, and Cd observed in the middle reaches of the river indicates heavy metal contamination in local areas, although there was an obvious decrease in concentrations in the water downstream of the Daheiting Reservoir. The significant rising trend in Cu, Pb, and Ni seen the sediment farther away from the river also suggests that anthropogenic activities contribute to heavy metal pollution Sediments were therefore used as environmental indicators, with sediment assessment was conducted using the geo-accumulation index (Igeo) and the potential ecological risk index (RI). The Igeo values revealed that Cd (3.13) and Cr (2.39) had accumulated significantly in the Luan River. The RI values for most (89%) of the sampling stations were higher than 300, suggesting that sediment from the Luan River poses a severe ecological risk, with the potential ecological risks downstream higher than that in the upper and middle streams. Good correlations among Pb/Ni, Pb/Cd, Cu/Pb, and Cu/Cd in the water and Cr/Ni in the sediment were observed. Cluster analysis suggested that Cd may have various origins, being derived from anthropogenic sources.

PREDICTING MONTHLY PRECIPITATION WITH MULTIVARIATE REGRESSION METHODS USING GEOGRAPHIC AND TOPOGRAPHIC INFORMATION

Multivariate regression models that integrate topographic and geographic information are developed to predict monthly precipitation in the Daqing Mountains of northern China. Five geographic and topographic factors, including longitude, latitude, elevation, slope, and aspect, are taken into account in the model development. The data are acquired from a 100 m resolution DEM of the national topographic databases. Measured precipitation data at 56 stations between 1955 and 1990 are used for model development, and a leave-one-out cross-validation method is used for model evaluation. The model explains most of the spatial variability in monthly precipitation, and can also quantify the relative importance of different geographic and topographic variables. The overall MAE and RMSE account for 10.42% and 13.64% of the measured precipitation for the entire year, respectively, and the relative errors of the monthly models are higher in the dry season (October to March) than in the wet season, because precipitation in the dry season is hard to model owing to little rainfall (11.77% of the annual total) and a different synoptic system. The results indicate that the models accuracy is influenced by the synoptic system and rainfall amount. The model provides a way to link the descriptive and explanatory functions of precipitation modeling, and could potentially be used in mountain climate and hydrology research.

Effects of soil conservation techniques on water erosion control: A global analysis

Water erosion control is one of the most important ecosystem services provided by soil conservation techniques (SCTs), which are being widely used to alter soil and water processes and improve ecosystem services. But few studies have focused on providing this service using various techniques across the world. Here, a comprehensive review was conducted to compare the effects of SCTs on water erosion control. We conducted a meta-analysis consisting of 1589 sample plots in 22 countries to identify SCTs, which we classified into three groups: biological techniques (BTs, such as afforestation and grain for green), soil management techniques (STs, such as no tillage and soil amendment), and engineering techniques (ETs, such as terraces and contour bunds). Our results were as follows: (1) The SCTs had significant positive effects on water erosion control, and they were generally more effective at reducing annual soil loss (84%) than at reducing annual runoff (53%). (2) The BTs (e.g., 88% for soil and 55% for runoff) were generally more effective at reducing soil and water loss than ETs (e.g., 86% for soil and 44% for runoff) and STs (e.g., 59% for soil and 48% for runoff). (3) On bare lands, the efficiency of water erosion control decreased as the terrain slope increased, but this value increased as the slope increased on croplands and orchards. Furthermore, the effects of SCTs on runoff and soil loss reduction were most efficient on 25°-40° slopes in croplands and on 20°-25° slopes in orchards. (4) The SCTs were more efficient on croplands and orchards in temperate climate zone (CZ), while those on bare lands were more effective in tropical CZ. (5) The SCTs in Brazil and Tanzania were more effective at reducing runoff and soil loss than those in the USA, China and Europe.

Effects of riparian vegetation patterns on the distribution and potential loss of soil nutrients: a case study of the Wenyu River in Beijing

A riparian ecosystem is an ecological transition zone between a river channel and terrestrial ecosystems. Riparian ecosystems play a vital role in maintaining stream health and bank stabilization. The types of riparian vegetation have changed greatly because of human activities along the Wenyu River. This study examines the impact of riparian vegetation patterns on water pollution due to soil nutrient loss. Four riparian vegetation patterns from the river channel to the upland were chosen as the focus of this study: grassland, cropland, grassland-cropland, and grassland-manmade lawn. The different distributions of soil nutrients along vegetation patterns and the potential risk of nutrient loss were observed and compared. The results showed that riparian cropland has the lowest value of total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), and organic matter (OM), but it has the highest soil bulk density (BD). The distributions of soil TN, TP, AN, AP, and OM exhibited a declining trend from the upland toward the river channel for riparian cropland, whereas a different trend was observed for the riparian grassland. The vegetation patterns of grassland-cropland and grassland-manmade lawn show that the grassland in the lower slope has more nutrients and OM but lower soil BD than the cropland or manmade lawn in the upper slope. So, the lower-slope grassland may intercept and infiltrate surface runoff from the upland. The lower-slope grassland has higher levels of soil TN, TP, AN, and AP, and thus it may become a new source of nutrient loss. Our results suggest that the management of the riparian vegetation should be improved, particularly in densely populated areas, to control soil erosion and river pollution.