Impacts of the Rising Opportunity Cost of Farm Labor on Agricultural Land Use Structure: Theory and Empirical Evidences

Abstract

Nowadays the rising of opportunity cost of farm labor comes to the forefront of attention in China. In order to understand its impact on agricultural land-use structure, a theoretical framework of household economics is formulated drawn on Low’s model. Under the theoretical framework, the impact of the rising opportunity cost of on-farm on cropping structure is deduced in theory. And then, using statistic and survey data, taking mountain area of southern Ningxia as an example, the theoretical assumes are verified. The results show that the rise of opportunity cost of farm labor leads to less diversified cropping structure.     

The spatial-temporal differentiation of green land use in Beijing–Tianjin–Hebei urban agglomeration

ABSTRACT

As the space carrier of the construction of ecological civilization, land’s green and efficient utilization is an important guarantee for realizing national sustainable development. Based on traditional land evaluation, this paper scientifically defines the green land use, puts land as one of the production factors, and brings energy consumption, environmental pollution, etc. into the input-output system to measure the green land utilization efficiency of the urban construction land of Beijing-Tianjin-Hebei Urban Agglomeration from 2006 to 2016. The study shows that the overall efficiency variation of the urban agglomeration is related with the land and environment policies. Efficiency of 2016 is higher than that of 2006, and energy and environment are the principal factors affecting the green land use. The efficiency of each city is positively correlated with its economic development, negatively correlated with the construction land expansion. Efficiency gaps in different cities are expanding. There is positive correlation with overall weak space between cities, and the partial spatial agglomeration phenomenon appears. Therefore, the green land use efficiency could be improved by improving land utilization efficiency, coordinating economic growth of construction land utilization with environmental protection and taking feasible ways to transregional renovation of the stock ecological land utilization, etc.     

南水北调丹江口库区土壤中微塑料分布特征及风险评估

为探究丹江口库区土壤中微塑料赋存特征及影响因素,通过对果园、旱地、水田和湿地进行土壤样品采集,利用密度分选、显微镜观察和拉曼光谱仪测定等方法对土壤中微塑料进行鉴定.结果表明,研究区采集的64个样本均有微塑料检出,丰度范围为645~15161 n·kg^-1.空间分布上,库尾高于库中和库首,且表层土壤（0~20 cm）中微塑料的丰度明显低于下层土壤（20~40 cm）.微塑料主要类型为聚丙烯（26.4%）和聚酰胺（20.2%）,粒径主要集中在50~500 μm之间（75%）,常见形状为碎片状（66.2%）.相关性分析显示,土壤微塑料丰度与土地利用、距水面和住宅的距离、人口密度和土壤性状密切相关.从微塑料污染风险来看,72.1%区域微塑料聚合物污染指数处于Ⅲ级和Ⅳ级,丹江口库区存在一定的微塑料污染风险.研究结果可为微塑料风险评估提供支撑.     

知识生产视角下应急管理学科建设的使命与路径

为厘清应急管理学科建设机制、推进应急管理学科良性发展,通过回顾学科建设历史,来分析应急管理学科建设面临的困境与肩负的使命,并提出相应的建设路径.研究表明:在知识生产模式转型视角下,应急管理学科建设面临知识生产者离散、知识创新度不足、知识转化率有限的三重困境,需要完成"朝向人才培养的应急管理知识直接再生产""朝向科学研究...     

土地利用方式对土壤团聚体稳定性和有机碳含量的影响

探究不同土地利用方式下土壤团聚体的粒径分布、稳定性及有机碳在各粒径团聚体中的分布规律,以期为重庆地区土壤结构的改善及土壤有机碳库的维持及提高提供依据.以重庆市北碚区6种土地利用方式(针阔叶混交林、竹林、果园、旱地、水田和荒草地)为研究对象,采用湿筛法对土壤进行粒径分组,对比分析了6种土地利用方式处理下土壤团聚体和团聚体有机碳在0～20、20～40、40～60和60～100 cm土壤剖面中的分布规律.结果表明,不同土地利用方式下,土壤的结构和肥力水平存在显著的差异.在0～100 cm土层土壤的各粒径团聚体中,6种土地利用方式的团聚体粒径均以 0. 25 mm为主;其中,竹林 0. 25 mm团聚体含量最高,其次是荒草地,旱地与果园含量最低.不同土地利用方式下0. 25～2 mm的粒径团聚体主要分布在0～20 cm土层(28. 78%～50. 08%),而0. 053～0. 25 mm和0. 053 mm的粒径团聚体主要集中在40～60cm土层.在整个土壤深度内,竹林和荒草地的土壤团聚体MWD和GMD均高于其他土地利用方式,即二者的土壤团聚体稳定性较强.土壤团聚体稳定性与土壤团聚体有机碳呈极显著正相关(r=0. 569,P 0. 01),在0～100 cm土层中,土壤0. 25～2 mm和0. 053 mm粒径的有机碳含量较高,其中0. 25～2 mm的最高,平均含量为56. 54 g·kg~(-1).除旱地土壤各粒径团聚体有机碳含量在20～40 cm土层内最高,其他土地利用方式下土壤各粒径团聚体内有机碳含量均随土壤深度的增加而降低,表现出显著的表层富集现象.总体上,6种土地利用方式下,竹林和荒草地在各土层中的土壤团聚体稳定性较好,且在各土层中,竹林土壤各粒径团聚体有机碳含量最高.     

公共部门危机学习动态过程及其知识管理研究

当前国内外对企业组织学习和危机管理的研究都已经较为成熟,在经历了几次大的危机之后,公共危机管理引起了我国许多学者的重视,但是关于高校危机学习的研究开展并不多,而国外的学者已经先一步提出了危机学习的概念并取得一些进展。随着危机种类越来越多,发生频率越来越高,高校必须要学习掌握应对危机的方法,并以此来教育学生。然而,无论是在危机管理中还是在组织学习中,知识管理都是不可或缺的一部分。因此本文以理论研究的方式,借鉴国内外学者对危机学习中知识管理的研究,希望能对高校危机学习的更深一步探索提供思路。     

Residential Demand for Water in the Chicago Metropolitan Area1

Mieno, Taro and John B. Braden, 2011. Residential Demand for Water in the Chicago Metropolitan Area. Journal of the American Water Resources Association (JAWRA) 47(4):713‐723. DOI: 10.1111/j.1752‐1688.2011.00536.x Abstract: This paper provides the first contemporary analysis of residential water demand in humid Northeastern Illinois, in the vicinity of Chicago, and explores seasonal and income‐based differentials in the responsiveness of water use to water prices. Using a panel of system‐level data for eight water systems and controlling for seasons, weather, incomes, and community characteristics, the analysis yields low estimates of price elasticity of demand for water in line with other studies. Furthermore, price response is greater in summer and less in higher income communities. We suggest that use of seasonal pricing can help mitigate equity issues arising from differential income elasticities while taking advantage of the greater price responsiveness of summertime water use.     

Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.     

Pressure cookers or pressure valves: Do roads lead to deforestation in China?

The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1 km² (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation.