Spatio-Temporal Patterns of Water Table and Vegetation Status of a Deserted Area

Understanding groundwater-vegetation interactions is crucial for sustaining fragile environments of desert areas such as the Horqin Sandy Land (HSL) in northern China. This study examined spatio-temporal variations in the water table and the associated vegetation status of a 9.71 km2 area that contains meadowland, sandy dunes, and intermediate transitional zones. The depth of the water table and hydrometeorologic parameters were monitored and Landsat Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) data were utilized to assess the vegetation cover. Spatio-temporal variations over the six-year study period were examined and descriptive groundwater-vegetation associations developed by overlaying a water table depth map onto a vegetation index map derived from MODIS. The results indicate that the water table depends on the local topography, localized geological settings, and human activities such as reclamation, with fluctuations occurring at annual and monthly scales as a function of precipitation and potential evapotranspiration. Locations where the water table is closer to the surface tend to have more dense and productive vegetation. The water table depth is more closely associated with vegetative density in meadowlands than in transitional zones, and only poorly associated with vegetation in sandy dunes

Historical Trends in Air Temperature, Precipitation, and Runoff of a Plateau Inland River Watershed in North China

Understanding historical trends in temperature, precipitation, and runoff is important but incomplete for developing adaptive measures to climate change to sustain fragile ecosystems in cold and arid regions, including the Balagaer River watershed on the Mongolian Plateau of northeast China. The objective of this study was to detect such trends in this watershed from 1959 to 2017. The detection was accomplished using a Mann-Kendall sudden change approach at annual and seasonal time scales. The results indicated that the abrupt changes in temperature preceded that in either runoff or precipitation; these abrupt changes occurred between 1970 and 2004. Significant (α = 0.05) warming trends were found at the minimum temperatures in spring (0.041 °C a−1), summer (0.037 °C a−1), fall (0.027 °C a−1), and winter (0.031 °C a−1). In contrast, significant decreasing trends were found in the precipitation (−1.27 mm a−1) and runoff (−0.069 mm a−1) in the summer. Marginally increasing trends were found in the precipitation in spring (0.18 mm a−1) and fall (0.032 mm a−1), whereas an insignificant decreasing trend was found in the runoffs in these two seasons. Both precipitation and runoff in the wet season exhibited a significant decreasing trend, whereas in the dry season, they exhibited a marginally increasing trend. Sudden changes in spring runoff and sudden rises in temperature are the main causes of sudden changes in basin rainfall

Upscaling Stem to Community-Level Transpiration for Two Sand-Fixing Plants: Salix Gordejevii and Caragana Microphylla

The information on transpiration is vital for sustaining fragile ecosystem in arid/semiarid environment, including the Horqin Sandy Land (HSL) located in northeast China. However, such information is scarce in existing literature. The objectives of this study were to: (1) measure sap flow of selected individual stems of two sand-fixing plants, namely Salix gordejevii and Caragana microphylla, in HSL; and (2) upscale the measured stem-level sap flow for estimating the community-level transpiration. The measurements were done from 1 May to 30 September 2015 (i.e., during the growing season). The upscaling function was developed to have one dependent variable, namely sap flow rate, and two independent variables, namely stem cross-sectional area of Salix gordejevii and leaf area of Caragana microphylla. The results indicated that during the growing season, the total actual transpiration of the Salix gordejevii and Caragana microphylla communities was found to be 287 31 and 197 24 mm, respectively, implying that the Salix gordejevii community might consume 1.5 times more water than the Caragana microphylla community. For this same growing season, based on the Penman-Monteith equation, the total actual evapotranspiration for these two communities was estimated to be 323 and 229 mm, respectively. The daily transpiration from the upscaling function was well correlated with the daily evapotranspiration by the Penman-Monteith equation (coefficient of determination R2 0.67), indicating the applicability of this upscaling function, a useful tool for managing and restoring sand-fixing vegetations. 2017 by the authors

Water–Soil–Vegetation Dynamic Interactions in Changing Climate

Previous studies of land degradation, topsoil erosion, and hydrologic alteration typically focus on these subjects individually, missing important interrelationships among these important aspects of the Earth\u27s system. However, an understanding of water–soil–vegetation dynamic interactions is needed to develop practical and effective solutions to sustain the globe\u27s eco-environment and grassland agriculture, which depends on grasses, legumes, and other fodder or soil-building crops. This special issue is intended to be a platform for a discussion of the relevant scientific findings based on experimental and/or modeling studies. Its 12 peer-reviewed articles present data, novel analysis/modeling approaches, and convincing results of water–soil–vegetation interactions under historical and future climates. Two of the articles examine how lake/pond water quality is related to human activity and climate. Overall, these articles can serve as important references for future studies to further advance our understanding of how water, soil, and vegetation interactively affect the health and productivity of the Earth\u27s ecosystem. © 2017 by the authors

Estimated Grass Grazing Removal Rate in a Semiarid Eurasian Steppe Watershed as Influenced by Climate

Grazing removal rate of grasses needs to be determined for various climate conditions to address eco-environmental concerns (e.g., desertification) related to steppe grassland degradation. The conventional approach, which requires survey data on animal species and heads as well as grass consumption per individual animal, is too costly and time-consuming to be applied at a watershed scale. The objective of this study was to present a new approach that can be used to estimate grazing removal rate with no requirement of animal-related data. The application of this new approach was demonstrated in a Eurasian semiarid typical-steppe watershed for an analysis period of 2000 to 2010. The results indicate that the removal rate tended to become larger, but its temporal variation tended to become smaller, from the upstream to downstream. Averaged across the watershed, the removal rate ranged from 63.9 to 401.0 g DM m-2 (or 22.4 to 60.9%) during the analysis period. As expected, the removal rate in an atmospherically wetter year was higher than that in an atmospherically drier year. Nevertheless, none of the eleven analysis years had a removal rate higher than the threshold value of 65%, above which the risk of grassland degradation would become much greater

Characteristics and Pollution Contribution of the Internal Nitrogen Release From the Sediments in the Dahekou Reservoir in Inner Mongolia

To clarify the influence of the changes in the overlying water environment on the internal nitrogen release from reservoir sediments in different seasons, the quantitative linear relationship between the intensity of the nitrogen release from the sediment and the environmental factors of the overlying water was established, and their contribution rate to the nitrogen pollution of the reservoir during different storage periods was investigated. In this study, the sediment samples were collected from the Dahekou Reservoir in the Xilingol League, and the orthogonal simulation experiments were conducted in the laboratory. The mathematical model, which was established using multiple linear regression methods, revealed the following. The order of the significance of the influences of the environmental factors on the nitrogen release from the sediments in the Dahekou Reservoir is water temperature (T) > dissolved oxygen (DO) > pH value > hydrodynamic force (K). The total nitrogen release flux from the sediments in the Dahekou Reservoir was 14.278 t/a in 2018, accounting for 27.91% of the total nitrogen (TN) pollution load input during the same period. In particular, in winter, the contribution rate of the nitrogen released from the sediments reached the highest level (57.06–63.26%), which was significantly higher than the river’s contribution to the total nitrogen pollution load of the reservoir. The nitrogen released from the sediments became the main source of nitrogen nutrients in the reservoir in the ice-sealed period

Development of In Vitro Denture Biofilm Models for Halitosis Related Bacteria and Their Application in Testing the Efficacy of Antimicrobial Agents

Objective: Since dentures can serve as a reservoir for halitosis-causing oral bacteria, halitosis development is a concern for denture wearers. In this study, we surveyed the prevalence of four selected halitosis-related species (Fusobacterium nucleatum, Tannerella forsythia, Veillonella atypica and Klebsiella pneumoniae) in clinical denture plaque samples, and developed denture biofilm models for these species in vitro to facilitate assessment of antimicrobial treatment efficacy. Design: Denture plaque from ten healthy and ten denture stomatitis patients was screened for the presence of aforementioned four species by PCR. Biofilm formation by these halitosis-associated species on the surfaces of denture base resin (DBR) discs was evaluated by crystal violet staining and confocal laser scanning microscopy. The efficacy of denture cleanser treatment on these mono-species biofilms was evaluated by colony counting. Results: 80% of the subjects in the denture stomatitis group and 60% in the healthy group contained at least one of the targeted halitosis-related species in their denture plaque. All halitosis species tested were able to form biofilms on DBR disc surfaces to varying degrees. These in vitro mono-species resin biofilm models were used to evaluate the efficacy of denture cleansers, which exhibited differential efficacies. When forming biofilms on resin surfaces, the halitosis-related species displayed enhanced resistance to denture cleansers compared with their planktonic counterparts. Conclusion: The four selected halitosis-related bacterial species examined in this study are present on the majority of dentures. The mono-species biofilm models established on DBR discs for these species are an efficient screening tool for dental product evaluation

The Sent-down Movement: Navigating Collective Memories of Trauma in Contemporary China

The sent-down movement in the 1960s and 1970s China influences a generation of urban youths. Despite the lively discussion of the movement in the two decades since its end, the collective memory of the movement has almost disappeared from public view in contemporary China in the twenty-first century. Through interviews and digital ethnography, this paper explores what specific factors most interrupted the inheritance and spread of collective memory of the sent-down movement from a transgenerational perspective. From the sent-down youth to their children and grandchildren, collective memory does not simply develop undistorted. Instead, the personal experience of each generation, the relationships within and between their respective communities, and the bigger pictures painted of social change all play a crucial role. The complexity of the memory inheritance process calls into question our assumptions about memory, agency, and oblivion

Multi-Spectral Image Classification Based on an Object-Based Active Learning Approach

In remote sensing, active learning (AL) is considered to be an effective solution to the problem of producing sufficient classification accuracy with a limited number of training samples. Though this field has been extensively studied, most papers exist in the pixel-based paradigm. In object-based image analysis (OBIA), AL has been comparatively less studied. This paper aims to propose a new AL method for selecting object-based samples. The proposed AL method solves the problem of how to identify the most informative segment-samples so that classification performance can be optimized. The advantage of this algorithm is that informativeness can be estimated by using various object-based features. The new approach has three key steps. First, a series of one-against-one binary random forest (RF) classifiers are initialized by using a small initial training set. This strategy allows for the estimation of the classification uncertainty in great detail. Second, each tested sample is processed by using the binary RFs, and a classification uncertainty value that can reflect informativeness is derived. Third, the samples with high uncertainty values are selected and then labeled by a supervisor. They are subsequently added into the training set, based on which the binary RFs are re-trained for the next iteration. The whole procedure is iterated until a stopping criterion is met. To validate the proposed method, three pairs of multi-spectral remote sensing images with different landscape patterns were used in this experiment. The results indicate that the proposed method can outperform other state-of-the-art AL methods. To be more specific, the highest overall accuracies for the three datasets were all obtained by using the proposed AL method, and the values were 88.32%, 85.77%, and 93.12% for “T1,” “T2,” and “T3,” respectively. Furthermore, since object-based features have a serious impact on the performance of AL, eight combinations of four feature types are investigated. The results show that the best feature combination is different for the three datasets due to the variation of the feature separability

Ecological Impact Prediction of Groundwater Change in Phreatic Aquifer under Multi-Mining Conditions

In aeolian sandy grass shoal catchment areas that rely heavily on groundwater, mining-induced geological deformation and aquifer drainage are likely to cause irreversible damage to natural groundwater systems and affect the original circulation of groundwater, thus threatening the ecological environment. This study aimed to predict the impact of groundwater level decline on vegetation growth in the Hailiutu River Basin (HRB), which is a coal-field area. Based on remote-sensing data, the land use/cover change was interpreted and analyzed, and the central areas of greensward land in the basin were determined. Subsequently, the correlation between groundwater depth and grassland distribution was analyzed. Then, the groundwater system under natural conditions was modeled using MODFLOW, and the groundwater flow field in 2029 was predicted by loading the generalized treatment of coal mine drainage water to the model. The change in groundwater depth caused by coal mining and its influence on the grassland were obtained. The results show that coal mining will decrease the groundwater depth, which would induce degradation risks in 4 of the original 34 aggregation centers of greensward land that originally depended on groundwater for growth in HRB because they exceeded the groundwater threshold. The prediction results show that the maximum settlement of groundwater level can reach 5 m in the northern (Yinpanhao), 6 m in the eastern (Dahaize), and 10 m in the southern (Balasu) region of HRB. Attention should be paid to vegetation degradation in areas where groundwater depth exceeds the minimum threshold for plant growth