Responses of soil moisture to vegetation restoration type and slope length on the loess hillslope

Soil moisture, a critical variable in the hydrologic cycle, is highly influenced by vegetation restoration type. However, the relationship between spatial variation of soil moisture, vegetation restoration type and slope length is controversial. Therefore, soil moisture across soil layers (0-400 cm depth) was measured before and after the rainy season in severe drought (2015) and normal hydrological year (2016) in three vegetation restoration areas (artificial forestland, natural forestland and grassland), on the hillslopes of the Caijiachuan Catchment in the Loess area, China. The results showed that artificial forestland had the lowest soil moisture and most severe water deficit in 100-200 cm soil layers. Water depletion was higher in artificial and natural forestlands than in natural grassland. Moreover, soil moisture in the shallow soil layers (0-100 cm) under the three vegetation restoration types did not significantly vary with slope length, but a significant increase with slope length was observed in deep soil layers (below 100 cm). In 2015, a severe drought hydrological year, higher water depletion was observed at lower slope positions under three vegetation restoration types due to higher transpiration and evapotranspiration and unlikely recharge from upslope runoff. However, in 2016, a normal hydrological year, there was lower water depletion, even infiltration recharge at lower slope positions, indicating receiving a large amount of water from upslope. Vegetation restoration type, precipitation, slope length and soil depth during a rainy season, in descending order of influence, had significant effects on soil moisture. Generally, natural grassland is more beneficial for vegetation restoration than natural and artificial forestlands, and the results can provide useful information for understanding hydrological processes and improving vegetation restoration practices on the Loess Plateau     

Optimum temperature for the growth performance of juvenile orange-spotted grouper （Epinephelus coioides H.）

Effects of water temperature （17, 21, 25, 30 and 35℃） and body size （14.75-281.41 g initial body weight） on food consumption, growth, feed conversion, and dry matter content in orange-spotted grouper fed to satiation were investigated. The combined effect of temperature （T, ℃） and body weight （W, g） on maximum food consumption （Cmax, g/day） was described as： InCmax=-7.411＋0.828 InW＋0.317T4）.004 7T2, and the optimum feeding temperature was 33.9℃. The combined effect of temperature and body weight on growth （G） was described as： lnG=-4.461-0.2081nW＋0.394T-0.006 3T^2. The optimum growth temperature was 31.4℃, whereas overall growth rates were high at 25, 30 and 35 ℃. Feed conversion efficiencies （FCE, %）, increasing first and then decreasing with increasing temperature, averaged from 1.8 to 2.1 in terms of dry weight of food fish. The optimum temperature for FCE tended to be lower than that for growth or feeding. Dry matter content increased with both increasing water temperature （17, 25, 30 and 35℃） and body weight, and the combined effect of temperature and body weight on dry matter content （DM, %） was described as： lnDM =3.232＋0.01 4 lnW-0.004 4T＋0.001 2TInW.     

Biodegradation of <Emphasis Type="Italic">Enteromorpha</Emphasis> polysaccharides by intestinal micro-community from <Emphasis Type="Italic">Siganus oramin</Emphasis>

Micro-communities are supposed to have more potential functions of biodegradation of polysaccharides than single strain; however, the intestinal micro-communities involved in the biodegradation of Enteromorpha polysaccharides (EP) were seldom reported. In order to obtain the EP-degrading micro-community, the intestines of Siganus oramin was obtained to isolate the micro-communities, which were enriched by 0.3% of EP as the sole carbon source. A stable micro-community with EP degradative capability was achieved after seven generations of subculture, named H1. Results showed that H1 was able to degrade 75% of EP within 24 hours, and the activity of EP lyases reached 500 U mL^?1 in 32 hours. With denaturing gradient gel electrophoresis (DGGE) and 16S rRNA gene clone library analysis, ten bacteria closely related to Marinomonas pontica, Microbacterium sp., Leucobacter chironomi, Cyclobacterium sp., Algoriphagus winogradskyi, Pseudoalteromonas sp. and Vibrio sp. were determined. Furthermore, compared with the DGGE bands sequence and the clone library analysis, the dominant bacteria of the EP-biodegrading micro- community were Pseudoalteromonas sp. and Vibrio sp., with the respective proportion of 38% and 46%, and they should play an important role in EP degradation together with other degrading bacteria in the micro-community H1.     

新疆和田河流域柽柳沙堆的生物地貌发育过程

Tamarix nabkha is one of the most widespread nabkhas,distributing in the arid region of China.Based on the observations outdoors and the simulation experiments in laboratories,analysis in this paper refers to the biological geomorphologic features and growth process of Tamarix nabkhas in the middle and lower reaches of the Hotan River,Xin- jiang.And the results indicate that the ecological type of Tamarix in the study area is a kind of Tugaic soil habitat based on the deep soil of the Populus Diversifolia f...     

Aluminum Consumption and Economic Growth: Evidence from Rich Countries

The article attempts to test the aluminum consumption–economic growth nexus for 20 rich economies for the period 1970–2009. Various panel data unit root and cointegration tests are applied. The series are found to be integrated of order one and cointegrated, especially after controlling for cross-sectional dependence. Moreover, the Blundell–Bond system generalized methods-of-moments is employed to conduct a panel causality test in a vector error-correction mechanism setting. Unidirectional causality running from aluminum consumption to real GDP is uncovered in the short-run, while real GDP is found to Granger-cause aluminum consumption in the long-run. Moreover, a 1% increase in real GDP generates an increase of 0.44% in aluminum consumption in the long-run for the whole panel.     

Automatic mapping of lunar landforms using DEM-derived geomorphometric parameters

Developing approaches to automate the analysis of the massive amounts of data sent back from the Moon will generate significant benefits for the field of lunar geomorphology. In this paper, we outline an automated method for mapping lunar landforms that is based on digital terrain analysis. An iterative self-organizing (ISO) cluster unsupervised classification enables the automatic mapping of landforms via a series of input raster bands that utilize six geomorphometric parameters. These parameters divide landforms into a number of spatially extended, topographically homogeneous segments that exhibit similar terrain attributes and neighborhood properties. To illustrate the applicability of our approach, we apply it to three representative test sites on the Moon, automatically presenting our results as a thematic landform map. We also quantitatively evaluated this approach using a series of confusion matrices, achieving overall accuracies as high as 83.34% and Kappa coefficients (K) as high as 0.77. An immediate version of our algorithm can also be applied for automatically mapping large-scale lunar landforms and for the quantitative comparison of lunar surface morphologies.     

Automated mapping of rock slope geometry,kinematics and stability with RSS-GIS

A GIS-implemented, deterministic approach for the automated spatial evaluation of geometrical and kinematical properties of rock slope terrains is presented. Based on spatially distributed directional information on planar geological fabrics and DEM-derived topographic attribute data, the internal geometry of rock slopes can be characterized on a grid cell basis. For such computations, different approaches for the analysis and regionalization of available structural directional information applicable in specific tectonic settings are demonstrated and implemented in a GIS environment. Simple kinematical testing procedures based on feasibility criteria can be conducted on a pixel basis to determine which failure mechanisms are likely to occur at particular terrain locations. In combination with hydraulic and strength data on geological discontinuities, scenario-based rock slope stability evaluations can be performed. For conceptual investigations on rock slope failure processes, a GIS-based specification tool for a 2-D distinct element code (UDEC) was designed to operate with the GIS-encoded spatially distributed rock slope data. The concepts of the proposed methodology for rock slope hazard assessments are demonstrated at three different test sites in Germany.     

GIS Course Planning: A Comparison of Syllabi at US College and Universities

Despite the enormous growth of college courses dealing with spatial information, curriculum planning involving geographic information science (GIS) courses and programs has received little attention within the GIS literature. As the number and variety of GIS courses expands, so too does the importance of both systematic and inclusive planning and campus‐wide coordination. In this article we explore course planning through an exploration of 312 GIS course syllabi used at US colleges and universities with the goal of characterizing the degree to which learning resources, student evaluation methods, and course topics have become standardized across institution types, academic levels, and disciplines. Our findings reveal a consensus in the use of GIS software across courses but no similar agreement in the use of textbooks. Hands‐on activities were used as evaluation methods in nearly every course in the sample regardless of institution type or academic level. However, quizzes, tests and final exams were used more often in community colleges while papers and projects were used more frequently in four‐year and comprehensive research universities. The frequency of topic categories listed on syllabi was relatively consistent across institutions, academic levels and disciplines with a few topics such as vector analytic operations, data models, and data creation/acquisition/editing included on more than 50% of syllabi.     

Singular value decomposition and cluster analysis as regression diagnostics tools for geodetic applications

It is well known that high-leverage observations significantly affect the estimation of parameters. In geodetic literature, mainly redundancy numbers are used for the detection of single high-leverage observations or of single redundant observations. In this paper a further objective method for the detection of groups of important and less important (and thus redundant) observations is developed. In addition, the parameters which are predominantly affected by these groups of observations are identified. This method thus complements other diagnostics tools, such as, e.g., multiple row diagnostics methods as described in statistical literature (see, e.g., Belsley et al. in Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New York, 1980). The method proposed in this paper is based on geometric aspects of adjustment theory and uses the singular value decomposition of the design matrix of an adjustment problem together with cluster analysis methods for regression diagnostics. It can be applied to any geodetic adjustment problem and can be used for the detection of (groups of) observations that significantly affect the estimated parameters or that are of negligible impact. One of the advantages of the proposed method is the improvement of the reliability of observation plans and thus the reduction of the impact of individual observations (and outliers) on the estimated parameters. This is of particular importance for the very long baseline interferometry technique which serves as an application example of the regression diagnostics tool.     

The determination of potential difference by the joint application of measured and synthetical gravity data: a case study in Hungary

In an elementary approach every geometrical height difference between the staff points of a levelling line should have a corresponding average g value for the determination of potential difference in the Earth’s gravity field. In practice this condition requires as many gravity data as the number of staff points if linear variation of g is assumed between them. Because of the expensive fieldwork, the necessary data should be supplied from different sources. This study proposes an alternative solution, which is proved at a test bed located in the Mecsek Mountains, Southwest Hungary, where a detailed gravity survey, as dense as the staff point density (~1 point/34 m), is available along a 4.3-km-long levelling line. In the first part of the paper the effect of point density of gravity data on the accuracy of potential difference is investigated. The average g value is simply derived from two neighbouring g measurements along the levelling line, which are incrementally decimated in the consecutive turns of processing. The results show that the error of the potential difference between the endpoints of the line exceeds 0.1 mm in terms of length unit if the sampling distance is greater than 2 km. Thereafter, a suitable method for the densification of the decimated g measurements is provided. It is based on forward gravity modelling utilising a high-resolution digital terrain model, the normal gravity and the complete Bouguer anomalies. The test shows that the error is only in the order of 10⁻³mm even if the sampling distance of g measurements is 4 km. As a component of the error sources of levelling, the ambiguity of the levelled height difference which is the Euclidean distance between the inclined equipotential surfaces is also investigated. Although its effect accumulated along the test line is almost zero, it reaches 0.15 mm in a 1-km-long intermediate section of the line.