土地·回归

当河边的芦苇丛。

Soil Wettability as Affected by Soil Characteristics and Land Use

Depth distribution of soil wettability and its correlations with vegetation type, soil texture, and pH were investigated under various land use (cropland, grassland, and forestland) and soil management systems. Wettability was evaluated by contact angle with the Wilhelmy plate method. Water repellency was likely to be present under permanently vegetated land, but less common on tilled agricultural land. It was mostly prevalent in the topsoil, especially in coarse-textured soils, and decreased in the subsoil. However, the depth dependency of wettability could not be derived from the investigated wide range of soils. The correlation and multiple regression analysis revealed that the wettability in repellent soils was affected more by soil organic carbon (SOC) than by soil texture and pH, whereas in wettable soils, soil texture and pH were more effective than SOC. Furthermore, the quality of SOC seemed to be more important in determining wettability than its quantity, as proofed by stronger hydrophobicity under coniferous than under deciduous forestland. Soil management had a minor effect on wettability if conventional and conservation tillage or different grazing intensities were considered.

The Impacts of Permafrost Change on NPP and Implications:A Case of the Source Regions of Yangtze and Yellow Rivers

This paper studies the relationship between net primary productivity (NPP) and annual average air temperature (GT) at 0cm above ground in permafrost regions by using revised Chikugo NPP model,cubic spline interpolating functions,and non-linear regression methods.The source regions of the Yangtze and Yellow Rivers were selected as the research areas.Results illustrate that:(1) There is significant non-linear relationship between NPP and GT in various typical years;(2) The maximum value of NPP is 6.17,5.87,7.73,and 5.41 DM·t·hm-2 ·a-1 respectively,and the corresponding GT is 7.1,10.0,21.2,and 8.9 o C respectively in 1980,1990,2000 and 2007;(3) In 1980,the sensitivity of NPP to GT is higher than in 1990,2000 and 2007.This tendency shows that the NPP presents change from fluctuation to an adaptation process over time;(4) During 1980～2007,the accumulated NPP was reduced to 8.05,and the corresponding carrying capacity of theoretical livestock reduced by 11%;(5) The shape of the demonstration region of ecological compensation system,livelihood support system,and science appraisal system in the source regions of Yangtze and Yellow Rivers are an important research for increasing the adaptation capacity and balancing protection and development.

Regression Equations for Predicting the Effect of Tine Width on Draught and Soil Translocation in Moderately Fine Textured Soil

Experiments were conducted in an indoor soil bin filled with sandy clay loam soil. Tests were carried out with tillage tines to study the effect tool width on soil disturbance and draught. Depth of operation was held constant at 35 mm and then at 70 mm while speed was varied at three levels of 1.0, 3.6 and 9.0 km/h. The widths of the tines tested were 10, 20, 31, 40, 51, 88, 126, 163 and 200 mm. The cone penetration resistance of the soil varied from 400 to 600 kPa. Draught was measured with a load cell while soil disturbance was measured with a profile meter and meter rule. Draught increased at a decreasing rate with tine width. Quadratic models best fitted the data points with high R2 values. The increase in draught was affected by the forward speed since higher draught values were obtained at higher speed. Results show that the parameters of soil disturbance increased with increase in tine width, except height of ridge （hr）, which did not show any specific trend. The specific draught was highest （10.63 N/cm） with tine T20 while Tine T1 had the least specific draught of 5.2 N/cm.

The Interaction of Population,Industry and Land in Process of Urbanization in China:A Case Study in Jilin Province

Urbanization is a complex process that covers a wide range of topics, of which population, industry and land urbanization are three important aspects. Jilin Province is an important agricultural province in China. The contradiction between population, industry and land urbanization is especially prominent here, and its coupling development is of great practical significance. In this paper, the coupling degree of population-industry-land urbanization in Jilin Province in 1990, 2000 and 2010 is measured by coupling mode. The spatial pattern of the coupling degree is analyzed by trend surface analysis and global and local spatial autocorrelation. The influence factors and their spatial differentiation are discussed using multiple linear regression(MLR) model and geographic weighted regression(GWR) model. The results show that: 1) the coupling degree of population-industry-land urbanization in Jilin Province is at a low level. Judging from the change of time scale, the urbanization of most research units is becoming more and more coordinated. From the comparison of spatial scales, there is significant spatial difference in the research units of different administrative levels. 2) Judging from the global change trend, the coupling degree of population-industry-land urbanization in the central region is higher than that in western and eastern regions. The coordination of urbanization in the central region is relatively good, and the distribution of the cold and hot spots is basically the same as that overall. 3) The spatial pattern of the coupling degree is related to the cold and hot spot distribution of the influence coefficient of urban population density and per capita urban construction land. The variation of the coupling degree spatial pattern is synchronous with the spatial change of the urban population density influence coefficient. 4) The degree of agglomeration of the urban population is the main factor promoting the coupling pattern of population-industry-land urbanization in Jilin Province, and the extent of its influence is gradually increasing. In addition, the level of city administrative, the efficiency of urban expansion and the capacity of market consumption also have an important influence on the coupling pattern.

Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna- woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species- specific regression models relating biomass with measured tree dimen- sions were highly significant （p 〈 0.001）. The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interac- tions. The best-fit equations for total above-ground biomass and stem biomass bad R2 〉 0.70, except for the Acacia species; for branches including twig biomass, R2-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.

Comparative Analysis of the Determinants of Residential Land Values

City development is a result of many factors, of which land value is one of the major determinants. The past urban economics studies have shown that land value is largely determined by location factors such as distance from Central Business District （CBD） ignoring the non-location factors like time of purchase and neighbourhood infrastructures. Therefore, this paper attempts to establish the relative importance of location and non-location factors in the determination of residential land value by positing Onitsha, Nigeria as a case study. Eight hundred and fifty residential housing units were selected and questionnaire administered to the landlords through multi-stage sampling technique. The stepwise regression analysis results showed that non-location factors, especially, time of land purchase, contribute more to the variation in residential land values. The paper suggests the revision of the classical economic theories to represent the conditions of urban areas in developing countries .

The Impact of Land Fragmentation in the Qualitative and Quantitative Aspect of Seeds and Their Production

Due to the pedo-climate conditions in the region of Korca, this area is considered to be one of the most favorable regions for cultivating various kinds of plants such as cereals, vegetables, wood-trees, vineyards, etc. All the factors such as rain, temperature, the impact of sunlight, and the pathological structure of the land, make this region one of the most productive and qualitative among the others. Changing the political systems in Albania during the last decades in Albania had its own impact even in the agricultural aspect. Shifting from communism into a modem, capitalist economy built a huge barrier for farmers in their way to intensifying the agricultural production. Dividing the land according to the law number 7,501, was accompanied by a severe fragmentation of the plot, reducing the degree of mechanization and chemical process. In this paper, the authors will try to analyze the effect of law fragmentation in the regional farmers working process in the region of Korea, and other municipalities such as Bilisht and Maliq, nearby Korea. There were randomly interviewed 150 farmers, from which 30 from the municipality of Bilisht, 22 from Korca municipality and 15 from Maliqi. From each farmer, these were the variables taken into consideration： Total land area, irrigated land, the number of plots, the area planted with wheat, corn, vegetables, fruit, vineyards, and forages. All the data that were gathered and translated into figures have indicated statistic elements such as the average value of each variable, deviation or standard deviation, coefficient of variation, correlation and regression. For instance in the municipality of Bilisht, it has been concluded that between the total variable area and number of plots, the related correlation value of the correlation coefficient is r = ＋ 0.73 and the value of regression coefficient is R = 2.71. In this municipality, correlative links between the variable and the total area planted with wheat area, are of medium category, with a value of the correlation coefficient of r = ＋ 0.52 and the regression coefficient is R = 0.89. Regarding the studies in the municipality of Maliq, it has been a correlation link between the weak variable category： in the surface of the irrigated area and the land planted with vegetables and corn, the value of the correlation coefficient is r = ＋ 0.24 and the regression coefficient R = 2.11. In the municipality of Korea, among the variable of irrigated area and the surface of the land planted with vegetables, there is a weak correlative link with a value of the correlation coefficient r = ＋ 0.17 and the regression coefficient R = 0.58.

A Community and Ecosystem-based Sustainable Forest Management Model for Small Islands in Maluku

The research objective was to investigate past and current forest management practices in the Maluku archipelago, then to create a better management model to improve prosperity for local communities and to guarantee sustainability of forest ecosystems for future generations. Forest land use, the deforestation process, the potential for maintaining natural production forests and the need to establish a management unit for sustainability of natural production forests （PFMU） were analysed. The analysis model used Geographic Information System （GIS） and satellite imaging. The deforestation process was analysed using the multiple regression model. The research determined the importance of two concepts i.e., （1） A macro concept involving the integration of forest development with regional development and （2） A micro concept which detailed the format of the PFMU as a sub-set of the macro concept. The macro concept involves a new Forest Land Use Plan （FLUP）, and the micro concept is a more detailed analysis of a sustainable PFMU, a Management Unit for Protection Forest （PrFMU） and a Management Unit for Conservation Forest （CFMU）. Results showed that the existing FLUCP （Forest Land Use Consensus Plan） policy rather than guaranteeing the sustainability of forests, contributed to their deforestation. The integration of forest management and regional development strategies required the establishment of a new FLUP.

Spatiotemporal Patterns and Drivers of Forest Change from 1985–2000 in the Beijing-Tianjin-Hebei Region of China

Forests are fundamental to maintaining ecological security and achieving regional sustainable development in China. Forest land change can result in many ecological problems including soil erosion, water shortages drought and biodiversity loss. Based on landscape ecology and logistic regression we explored the spatiotemporal patterns and factors affecting forest land changes from 1985 to 2000 in the Beijing-Tianjin-Hebei Region of China. The results show decreased local fragmentation of woodland landscapes and that the shapes of forest patches have become more regular. For forest land cover change, soil organic matter content, slope type I （〈5°）, distance to the nearest village and per capita GDP were the most important independent variables from 1985 to 2000. This study indicates that spatial heterogeneity can affect the predictability of logistic regression models for forest land change.

A method characterizing urban expansion based on land cover map at 30 m resolution

Based on the global land cover data at 30 m resolution(Globe Land30) in the year 2000 and 2010, the urban expansion process of 320 cities in China was analyzed using lognormal regression, and the expansion model were established. Three metrics were presented for the models, including the peak position, the full width at half maximum, and the skewness. It was found that the three metrics could reveal different patterns of the urban expansion process of cities with different sizes. Specifically, cities with larger size tend to expand outward strongly, and their expansion intensity and influence are likely to be higher. Moreover, most cities' expansion occurs around the urban core with spatially limited influence. In addition, it was also found that the city's expansion intensity is related to the city size. These results showed that the lognormal regression model could describe the distribution of urban expansion with effectiveness and robustness.

An improved Landsat Image Mosaic of Antarctica

A revised Landsat Image Mosaic of Antarctica （LIMA） is presented, using the 1073 multi-band scenes of the original Land- sat-7 ETM＋ LIMA image collection available at the United States Geological Survey （USGS： http：//lima.usgs.gov/）. Three improvements have been applied during the data processing： （1） DN saturation is adjusted by adopting a linear regression, which has a lower root mean square error than the ratio regression used by LIMA; （2） solar elevation angle is calculated using pixel-level latitude/longitude and the acquisition time and date of the central pixel of the scene, improving slightly upon the bi- linear interpolation of the solar elevation angles of scene comers applied in LIMA; and （3） two additional image bands, Band 5 and Band 7, are sharpened using the panchromatic band （Band 8） and a Gram-Schmidt Spectral Sharpening algorithm to more easily distinguish snow, cloud and exposed rocks. The final planetary reflectance product is stored in 16-bit bands to preserve the full radiometric content of the scenes. A comparative statistical analysis among 12 sample regions indicates that the new mosaic has enhanced visual qualities, information entropy, and information content for land cover classification relative to LIMA.

Modeling Runoff from Semi-Arid Agricultural Lands in Northwest Iran

Transformation of rainfall into runoff over an area is a very complex process which exhibits both temporal and spatial variability;runoff in a defined area can be affected by factors such as topography, vegetation, rainfall characteristics and soil properties. This study was conducted to develop an empirical model using the rainfall characteristics and soil properties for predicting runoff from dry-farming lands in a semi-arid agricultural area in Hashtroud, Northwest Iran. Runoff plots(1.83 m × 22.1 m) in triplicate were installed in thirty-six sloped dry-farming lands in the study area. Runoff under natural rainfalls was measured in each plot during a2-year period. The results showed that runoff for 41 runoff-producing rainstorm events with duration longer than 30 min was largely associated with a rainfall index obtained by multiplying the positive square root of rainfall depth(h0.5) by the logarithm of the maximum 30-minute intensity(LogI30)(R2= 0.81). Runoff significantly varied among the plots(P < 0.001), which was considerably related to the effective soil properties(R2= 0.74), i.e., soil permeability(Per) and aggregate stability(AS). A multiple linear regression model was developed between runoff and the rainfall index(h0.5logI30) and the effective soil properties(AS and Per). Evaluation of the model using 34 runoff-producing rainstorm events that occurred during the next two years resulted in high values of the efficiency coefficient and R2(0.88 and 0.91, respectively), which revealed that the model developed in this study could be used in predicting runoff from the dry-farming lands in the semi-arid regions.