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Aquatic vegetation of different heights is widely scattered in natural rivers and is conducive to their environmental function while affecting the flow hydrodynamic conditions. A semi-analytical velocity model is constructed and used to study the longitudinal velocity profile in open channel flow through double-layered rigid vegetation. The double-layered vegetation flow is separated into three zones according to the velocity profile: 1) nearly uniform distributed velocity zone 1A in the lower region of the short vegetation layer, 2) a mixing layer zone B, 3) uniform distributed velocity zone 2A in the upper region of the tall vegetation layer. Two force equilibrium equations about the gravity-driving and vegetation drag are solved to obtain the uniform velocity distribution equations in zone 1A and 2A. The velocity of zone 1A and B is further modeled as a linear superposition of two concepts: the uniform velocity distribution term of zone 1A and a hyperbolic tangent profile. Meanwhile, longitudinal velocity and the lateral vorticity profiles of open channel flow through double-layered rigid vegetation are studied by laboratory flume tests of different vegetation arrangements exposed to two water depths and three slopes. The experimental results show that the longitudinal velocity increases with the slope increase. The verification of the velocity model is based on the instantaneous velocity measured by Acoustic Doppler Velocimetry (ADV), which shows acceptable agreement, indicating that the model can give a reference to the longitudinal velocity of multi-layered vegetation flow in some cases. The effects of wake vortices and boundary friction on the model are further explored in the discussions. The results presented in this study could contribute to the management of aquatic vegetation configurations and the restoration of freshwater ecology.

The Qinghai-Tibet Plateau (QTP) encompasses areas with a remarkably high degree of biodiversity, harboring exceptional species-rich radiations. How these radiations formed by interacting with geology, climate and ecology remains seldom examined.We investigate the roles of abiotic (environmental) and biotic (species-intrinsic) factors in driving radiating diversification of Saussurea (Asteraceae) by deploying a number of time-dependent, paleoenvironment-dependent and trait-dependent models, as well as ecological distribution data.We show that three main clades of Saussurea begin to diversify in the Miocene almost simultaneously, with increasing diversification rates toward the present and negative dependence to paleotemperature. Acceleration in diversification rates are correlated with adaptive traits, as well climate lability, niche breadth and species range.We conclude that fluctuation of paleoclimate along with complex QTP environments provided opportunities for increased diversification rates of Saussurea with diverse adaptive traits, highlighting the importance of combinations of clade-specific traits and ecological niches in driving rapid radiation.

In semiarid terrestrial ecosystems, optimized eco-rehabilitation strategies, such as land preparations and planting vegetation, are keys to achieve a successful ecological restoration. Land preparations and vegetation are supposed to have the coupled and respective impacts on soil ecosystem services, which are still unclear now. In this study, eighteen experimental plots with six different combinations and repetitions of land preparations and vegetation were built in the Chinese Loess Plateau in 2014 and soil moisture storages (SMS), soil carbon stocks (SCS) and other soil nutrient stocks were calculated at 0–100 cm, also the effects of land preparations and planting vegetation on soil eco-hydrological services are analyzed by mathematical methods. The results show that leveled ditches-M. sativa had the highest SMS (125 mm) while zig terraces-P. tabulaeformis had the lowest values (88 mm). Fish-scale pits-P. tabulaeformis had the most SCS (9804 g/m2) and leveled ditches-M. sativa had the lowest values (8163 g/m2). For soil nutrient stocks, leveled benches-C. microphylla and fish-scale pits-P. tabulaeformis had the highest levels while leveled ditches-M. sativa had the lowest values. The partial redundancy analysis (pRDA) and variation partitioning (VP) analysis indicated that soil nutrient stocks were most affected by the coupling effects of land preparation and vegetation. SMS at surface (0–10 cm) were mainly affected by precipitation (58.8%). Furthermore, SMS at subsurface (10–60 cm) and deep soil layer (60–100 cm) were affected by the shared effects of vegetation and land preparation (61.3%), and vegetation (72.2%), respectively. The findings quantified the coupling and respective contributions of vegetation restoration and land preparation to soil eco-hydrological services and demonstrate that the optimal combination of eco-rehabilitation strategies can achieve a sustainable land restoration.

The combination of land preparation techniques and vegetation could be an effective way to combat soil degradation on vulnerable, steep slopes. Because of the scale of re-vegetation and man-made micro-topographies in regions of hillies and gullies, quantifying the effects of land preparation techniques, precipitation, and vegetation on runoff and soil erosion remains challenging, particularly in semi-arid areas. This study investigated the runoff and erosion characteristics associated with different land preparation techniques (level bench, level ditch, fish-scale pits and adverse-grade tableland) in combination with different tree species (i.e., Caragana microphylla, Pinus tabulaeformis, Armeniaca sibirica, Platycladus orientalis) using network and redundancy analyses (RDA). Network analysis was used to identify the factors (rainfall features, vegetation types, and land preparation techniques) influential in surface runoff and erosion, while RDA was used to focus on the relations between surface runoff, soil erosion, and all of the influencing factors. Our results suggested that land preparation technique could reduce runoff generation on steep slopes, a key process that affects soil loss, although the extent was affected largely by the influence of the combination of the design of the engineering structure and the shape of the vegetation canopy. Our study indicated that Network analysis and RDA are practical methods to quantify the interactions and co-dependencies between rainfall features and other critical factors (vegetation type and ecological engineering) on runoff and soil loss that were difficult to assess previously using classical regression.

In water-restricted erosive mountains environments, large-scale vegetation plantation and diverse terracing measures have been widely used as the most powerful ecological-restoration tools to control water erosion and improve local degraded ecosystems, further enhancing the complexity of terracing, vegetation, and soil water relationships. In this study, 70 sampling sites across different hillslopes were selected and used for biweekly soil water measurement in a typical loess hilly catchment of China. The most typical terracing measures (broad bench terraces-BBT, narrow bench terraces-NBT, level ditch terraces-LDT, counter-slope terraces-CST, and half-moon terraces-HMT) and introduced vegetation types (wild peach, apricot, arborvitae, poplar, and Chinese pine) were included in the study. Based on multi-site measurements, the effects of terracing and vegetation on the profile of soil moisture dynamics at a depth of 2 m were analyzed. Results show that terracing generally has a very positive role in soil water enhancement. Compared with slope risers, terracing can increase soil moisture by 0.87% (±0.82%) to 37.71% (±9.01%), which benefits ecological restoration. However, the effects of various terracing measures on soil water differed. BBT measures were the most powerful in soil water recharge, with an incremental ratio of 21.88%, which is 4.94, 5.95 and 4.21 times that of CST (5.19%), LDT (4.43%) and NBT (3.68%), respectively. The existence of different plant communities can increase the uncertainties and complexities of soil water status. Introduced trees and shrubs generally induce a greater reduction in soil water than do natural plants in similar environmental conditions. The few remaining original hillslopes covered by natural grasses can better preserve soil water, because of large differences in water use strategies between planted and natural species. Such findings are expected to provide important references for the proper selection of terracing and artificial vegetation toward enhancing the efficiency of water conservation and ecological restoration in dry and degraded regions.

Dew, as an important contribution of non-rainfall water (NRW), plays a vital role in ecosystem processes in arid and semi-arid regions and is expected to be affected by climate warming. Infrared heater warming systems have been widely used to simulate climate warming effects on ecosystems. However, how this warming system affects dew formation has been long ignored and rarely addressed. In a typical alpine grassland ecosystem on the northeast of the Tibetan Plateau, we measured dew amount and duration using three independent methods: artificial condensing surfaces, leaf wetness sensors and in situ dew formation on plants from 2012 to 2017. We also measured plant traits related to dew conditions. The results showed that (1) warming reduced the dew amount by 41.6%-91.1% depending on the measurement method, and reduced dew duration by 32.1 days compared to the ambient condition. (2) Different plant functional groups differed in dew formation. (3) Under the infrared warming treatment, the dew amount decreased with plant height, while under the ambient conditions, the dew amount showed the opposite trend. We concluded that warming with an infrared heater system greatly reduces dew formation, and if ignored, it may lead to overestimation of the effects of climate warming on ecosystem processes in climate change simulation studies.

For thousands of years, humans have created different types of terraces in different sloping conditions, meant to mitigate flood risks, reduce soil erosion and conserve water. These anthropogenic landscapes can be found in tropical and subtropical rainforests, deserts, and arid and semiarid mountains across the globe. Despite the long history, the roles of and the mechanisms by which terracing improves ecosystem services (ESs) remain poorly understood. Using literature synthesis and quantitative analysis, the worldwide types, distributions, major benefits and issues of terracing are presented in this review. A key terracing indicator, defined as the ratio of different ESs under terraced and non-terraced slopes (δ), was used to quantify the role of terracing in providing ESs. Our results indicated that ESs provided by terracing was generally positive because the mean values of δ were mostly greater than one. The most prominent role of terracing was found in erosion control (11.46 ± 2.34), followed by runoff reduction (2.60 ± 1.79), biomass accumulation (1.94 ± 0.59), soil water recharge (1.20 ± 0.23), and nutrient enhancement (1.20 ± 0.48). Terracing, to a lesser extent, could also enhance the survival rates of plant seedlings, promote ecosystem restoration, and increase crop yields. While slopes experiencing severe human disturbance (e.g., overgrazing and deforestation) can generally become more stable after terracing, negative effects of terracing may occur in poorly-designed or poorly-managed terraces. Among the reasons are the lack of environmental legislation, changes in traditional concepts and lifestyles of local people, as well as price decreases for agricultural products. All of these can accelerate terrace abandonment and degradation. In light of these findings, possible solutions regarding socio-economic changes and techniques to improve already degraded terraces are discussed.

Land preparation (e.g., leveled ditches, leveled benches, adversely graded tableland, and fish-scale pits) is one of the most effective ecological engineering practices to reduce water erosion in the Loess Plateau, China. Land preparation greatly affects soil physicochemical properties. This study investigated the influence of different land preparation techniques during vegetation restoration on soil conditions, which remained poorly understood to date. Soil samples were collected from depths of 0–10, 10–20, 20–40, 40–60, 60–80, and 80–100 cm, in the typical hilly watershed of Dingxi City, Loess Plateau. Soil bulk density (BD), soil organic matter (SOM), and total nitrogen (TN) were determined for different land preparations and vegetation type combinations. Fractal theory was used to analyze soil particle size distribution (PSD). (1) The effect of land preparation on soil properties and PSD varied with soil depth. For each land preparation category, SOM and TN values showed a significant difference between the top soil layer and the underlying soil depths. (2) The fractal dimension of PSD showed a significant positive correlation with clay and silt content, but a significant negative correlation with sand content. (3) The 20 cm soil layer was a boundary that distinguished the explanatory factors, with land preparation and vegetation type as the controlling factors in the 0–20- and 20–100-cm soil layers, respectively. Land preparation and vegetation type significantly influenced soil properties, with 20 cm soil depth being the boundary for these two factors. This study provided a foundation for developing techniques for vegetation restoration in water-limited ecosystems.

To start the tracking of targets in the environment with heavy clutters is always a problem in radar data procedure. In this paper, a Hough Transform method based on Morphology is proposed to solve the problem of starting track in radar system. This method first uses morphological method to reduce clutter and noise in imagery domain, then use the Hough transform to detect the starting tracks. Simulation results show that the method well detected the short straight lines of target starting track.

Soil moisture plays a key role in vegetation restoration and ecosystem stability in arid and semiarid regions. The response of soil moisture to rainfall pulses is an important hydrological process, which is strongly influenced by land use during the implementation of vegetation restoration. In this study, vertical soil moisture variations of woodland (Pinus tabulaeformis), native grassland (Stipa bungeana), shrubland (Hippophea rhamnoides), cropland (Triticum aestivum) and artificial grassland (Onobrychis viciaefolia) in five soil profiles were monitored in a typical loess hilly area during the 2010 growing season. The results demonstrated that rainfall pulses directly affected soil moisture variation. A multi-peak pattern of soil moisture appeared during the growing season, notably in the surface soil layer. Meanwhile, the response of each vegetation type to rainfall was inconsistent, and a time-lag effect before reaching the peak value was detected, following each heavy rainfall event. The response duration of soil moisture, however, varied markedly with the size of rainfall events. Furthermore, higher soil water content was detected in grassland and shrubland. Woodland was characterized by relatively lower soil moisture values throughout the investigation period. Our research suggests that vegetation restoration efforts should give priority to grassland and shrubland at the research site. We suggest that more studies should be focused on the characteristics of community structure and spatial vegetation distribution on soil moisture dynamics, particularly within the grass and shrub ecosystems.

A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are optimized with quantum simulated annealing algorithm (QSA). In order to verify the effectiveness of the proposed algorithm, the normal SVM method has been chosen as comparing algorithm. The experimental results show that the proposed method can effectively extract the eigenfeatures and improve the classification accuracy of pancreatic images.

A new method is proposed to establish the statistical fractal model for liver diseases classification. Firstly, the fractal theory is used to construct the high-order tensor, and then Generalized N-dimensional Principal Component Analysis (GND-PCA) is used to establish the statistical fractal model and select the feature from the region of liver; at the same time different features have different weights, and finally, Support Vector Machine Optimized Ant Colony (ACO-SVM) algorithm is used to establish the classifier for the recognition of liver disease. In order to verify the effectiveness of the proposed method, PCA eigenface method and normal SVM method are chosen as the contrast methods. The experimental results show that the proposed method can reconstruct liver volume better and improve the classification accuracy of liver diseases.

Mild cognitive impairment (MCI) is a transitional stage between normal aging and Alzheimer's disease (AD). Recent functional imaging studies have demonstrated regional deactivation magnitudes changes of default-mode network (DMN) in patients, accompanied by a defect of memory function. However, functional connectivity in the DMN during task performance was rarely investigated. METHODS : 26 amnestic MCI and 27 healthy controls underwent functional magnetic resonance imaging (fMRI) during an episodic memory task. Resting-state fMRI data were also collected. The changes in default-mode networks under both task-related and resting-state fMRI were obtained with a temporal correlation analysis. RESULTS: Significantly decreased functional connectivity was found mainly in anterior-posterior connectivity of DMN in aMCI groups. And a correlation existed between the anterior-posterior functional connectivity and MMSE scores. CONCLUSIONS: This study showed that disconnectivity of DMN could be used as an imaging biomarker for predicting the future cognitive decline of aMCI patients.

This article summarizes the progress of the application of functional magnetic resonance image (fMRI) on neuropharmacology. Cholinergic drugs are types of neurotransmitters which are usually used to treat neurological disorders. fMRI is widely used in the research of evaluation of cholinergic drugs. This article systematically summerizes the research of drug evaluation on memory, attention, emotion and vision by fMRI using the cholinergic drugs for example. Combined with the charactors and disciplines of traditional Chinese medicine (TCM), this article also makes a prospect of the application of fMRI on traditional Chinese medicine evaluation, especially the drugs on brain disease and emotional modulation.