我国农业主产区粮食补贴政策的分析评价

粮食补贴是许多国家采取的旨在保护和发展农业的政策。对我国农业主产区粮食直接补贴政策的实施现状和存在问题进行了具体评价和分析,并在研究国外发达国家实行的相关农业补贴政策的基础上提出了我国农业主产区粮食补贴政策的发展对策,如国家应建立符合世界贸易组织农业协议的补贴方式,构建农业收入支持体系,提高政策的执行效率等。为今后我国粮食补贴政策的科学实施和进一步完善提供了研究资料和理论思路。     

Soil erosion assessment tools from point to regional scales—the role of geomorphologists in land management research and implementation

Geomorphological research has played an important role in the development and implementation of soil erosion assessment tools. Because policy and management approaches include the use of soil erosion assessment tools, soil erosion research directly affects the public in terms of providing information on natural hazards and human impacts, and also as the basis for regulatory policy on land management. For example, soil loss calculations and geomorphological expertise are used to support soil conservation planning, both through agricultural legislation that defines maximum tolerable soil loss rates, and through federal and local legislation that requires soil erosion controls on many construction sites.To be useful for decision makers, soil erosion models must have simple data requirements, must consider spatial and temporal variability in hydrological and soil erosion processes, and must be applicable to a variety of regions with minimum calibration. The growing use of erosion models and Geographic Information Systems (GIS) in local to regional scale soil and water conservation raises concerns about how models are used. This has prompted interest in methods to assess how models function at management scales and with the types of data that are commonly available to users. A case study of a GIS-based soil erosion assessment tool using the process-based Water Erosion Prediction Project (WEPP) shows that using commonly available data rather than research grade data can have (predictably) a significant impact on model results. If model results are then used in management decisions, it is critical to assess whether the scale and direction of variation in results will affect management and policy decisions. Geomorphologists provide unique perspectives on soil erosion and can continue to affect policy through soil erosion research. This research should focus on fundamental processes, but equally important is continued development and evaluation of models that are matched to real world data availability, geomorphic settings, and information needs.     

Geographically weighted regression with parameter-specific distance metrics

Geographically weighted regression (GWR) is an important local technique to model spatially varying relationships. A single distance metric (Euclidean or non-Euclidean) is generally used to calibrate a standard GWR model. However, variations in spatial relationships within a GWR model might also vary in intensity with respect to location and direction. This assertion has led to extensions of the standard GWR model to mixed (or semiparametric) GWR and to flexible bandwidth GWR models. In this article, we present a strongly related extension in fitting a GWR model with parameter-specific distance metrics (PSDM GWR). As with mixed and flexible bandwidth GWR models, a back-fitting algorithm is used for the calibration of the PSDM GWR model. The value of this new GWR model is demonstrated using a London house price data set as a case study. The results indicate that the PSDM GWR model can clearly improve the model calibration in terms of both goodness of fit and prediction accuracy, in contrast to the model fits when only one metric is singly used. Moreover, the PSDM GWR model provides added value in understanding how a regression model’s relationships may vary at different spatial scales, according to the bandwidths and distance metrics selected. PSDM GWR deals with spatial heterogeneities in data relationships in a general way, although questions remain on its model diagnostics, distance metric specification, and computational efficiency, providing options for further research.     

美国俄亥俄州土壤有机碳密度空间分布(英文)

Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon(SOC) for the soils of Ohio,USA.Specific objective of the study was to estimate the spatial distribution of SOC density(C stock per unit area) to 1.0-m depth for soils of Ohio using geographically weighted regression(GWR),and compare the results with that obtained from multiple linear regression(MLR).About 80% of the analytical data were used for calibration and 20% for validation.A total of 20 variables including terrain attributes,climate data,bedrock geology,and land use data were used for mapping the SOC density.Results showed that the GWR provided better estimations with the lowest(3.81 kg m 2) root mean square error(RMSE) than MLR approach.Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg.This study demonstrates that,the local spatial statistical technique,the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR.Thus,GWR enhances the accuracy for mapping SOC density.     

中国水资源平行定价系统和统一定价系统的比较评估:基于取消灌溉补贴的模拟研究（英文）

中国水资源定价改革对农业生产有重要影响,而中国农业生产具有很大的节水潜力。本研究将取消灌溉补贴作为模拟背景,将中国水资源平行定价系统和统一定价系统分别引入可计算一般均衡(CGE)模型进行模拟实验及比较评估。结果显示,与平行定价系统相比,统一定价系统将促进农业进口增加,减少农业产出损失,且更有利于促进水资源节约利用,同时城乡居民也可以实现收入增长和食物消费需求增加,而增加的食物消费主要来源于进口。然而,取消灌溉补贴作为一项政策建议需考虑如何降低乃至抵消其对农业产出的负面影响。此外,为进一步改善节水政策实施效果,特别是在统一定价系统下,提高农业劳动力流动性和水资源需求弹性需要得到更多关注。     

A comment on geographically weighted regression with parameter-specific distance metrics

A recent paper in this journal proposed a form of geographically weighted regression (GWR) that is termed parameter-specific distance metric geographically weighted regression (PSDM GWR). The central focus of the PSDM generalization of the GWR framework is that it allows the kernel function that weights nearby data to be specified with a distinct distance metric. As with the recent paper on Multiscale GWR (MGWR), the PSDM framework presents a form of GWR that also allows for parameter-specific bandwidths to be computed. As a result, a secondary focus of the PSDM GWR framework is to reduce the computational overhead associated with searching a massive parameter space to find a set of optimal parameter-specific bandwidths and parameter-specific distance metrics. In this comment, we discuss several concerns with the PSDM GWR framework in terms of model interpretability, complexity, and computational efficiency. We also recommend some best practices when using these models, suggest how to more holistically assess model variations, and set out an agenda to constructively focus future research endeavors.     

基于演化博弈的中国橡胶主产区目标价格补贴政策及其敏感性研究——以西双版纳为例

当前,橡胶收入不足于吸引农户继续种植橡胶,为保障国家橡胶战略安全,利用演化博弈模型分析了目标价格补贴政策的有效性边界,并对影响目标价格补贴政策的因素进行了敏感性分析。结果发现,依据2019年西双版纳18个样本村的947个截面数据及地区统计公报等测算得出,在橡胶价格为8元/kg时,应将目标补贴价格定位为12.8元/kg;橡胶树单产为影响目标价格补贴额度变量中敏感系数最大的因素;在当前其他因素不变的情况下,橡胶树单产提升10%可使目标补贴价格额度下降25%。建议采取积极稳健的财政补贴政策,利用浮动的目标价格补贴稳定橡胶产区的农户预期,同时辅以橡胶价格保险等配套政策激励农户提高橡胶树单产,在达到政策目标的同时降低财政成本。     

Continuity and change: Spatiotemporal land use dynamics on Bellona Island, Solomon Islands

Traditional agricultural land use systems in the humid tropics of the Southwest Pacific are, as elsewhere, affected by globalization processes. This paper analyzes the directions of change in the land use system of Bellona, a small outer island in the Solomon Islands. We focus on the human–environmental interaction that shapes land use patterns and practices in the context of theoretical lines of thought concerning intensification of agricultural systems in the tropics. Aerial photography from 1966 and satellite imagery from 2006 in conjunction with studies from the 1960s and a contemporary household survey reveal only minor changes in the agricultural system. Land use and land cover dynamics are related to agricultural strategies, demographic factors, institutional actors as well as biophysical drivers or constraints. Local agricultural production still contributes significantly to local subsistence but imported food has also become a major food source. Hence, land use has become partially disconnected from the local population pressure and therefore remains relatively stable while the larger livelihood portfolio has undergone significant diversification. At present, the agricultural system is a supplement to a range of strategies supporting the increasing number of people on the island. This explains why land use patterns continue relatively unchanged while livelihood and food supply strategies have changed.     

Unexpected Results from China's Agricultural Subsidies Policy

Given the huge demand for food created by China's large population and the high cost of transporting food across such a large nation, a food security strategy based on local self-sufficiency seems vital. To encourage agricultural production, agricultural subsidies have therefore been implemented since 1997. Although subsidies to support food production in China arose from the desire to combat poverty and hunger, they may have instead led to adverse health impacts, food insecurity, and environmental degradation because the complexity of socioeconomic systems prevented governments from fully understanding the relationships among the many factors in such systems. China therefore faces enormous challenges before it can attain sustainable food production at levels high enough to end hunger, without undesirable consequences.     

SOUTH AFRICA'S NATIONAL HOUSING SUBSIDY PROGRAM AND APARTHEID'S URBAN LEGACY

This study examines the ability of the South African housing subsidy program to hasten desegregation and integration of South Africa's cities. It reviews the basic elements of recent local government reform and housing subsidy legislation. Highlighting the experiences of the city of George, it notes that in order to achieve a rapid provision of housing, the racial division of urban areas has initially been perpetuated. [Key words: Housing, post-apartheid, public policy, South Africa, subsidies, urban.]     

土地系统多主体模型的理论与应用

土地变化科学是理解人类—自然耦合系统的交叉学科研究方向。多主体模型（ABM）作为过程导向模型,对揭示土地变化驱动力,理解土地变化过程有重要作用。本文从理论、应用与建模框架三方面出发,总结了ABM理论基础和相关概念;阐述了ABM在城市和农业土地系统两方面的应用与发展,进一步介绍了横断山区退耕还林ABM研究案例;在梳理ABM建模协议的基础上,提出了主体视角的土地系统ABM建模框架和实施流程。在城市土地利用方面,ABM研究从最初基于景观研究城市扩张,到研究城市内部居住分隔,规划分区,生态功能等多方面;在农业土地利用方面,ABM应用则呈现出更加多样化和个性化的特征,包括农民行为、农户决策、种植系统、农业政策等。相比于传统模型,ABM因其依靠本地知识与数据而使得其构建更为复杂,且不易推广;但因其独特的自下而上模型构架,在探究土地变化驱动力、刻画人类行为对自然环境影响等方面具有不可或缺的作用。     

Agent-based model of land system: Theory,application and modelling framework

Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems. As a process-oriented modelling approach, agent based model(ABM) plays an important role in revealing the driving forces of land change and understanding the process of land change. This paper starts from three aspects: The theory, application and modeling framework of ABM. First, we summarize the theoretical basis of ABM and introduce some related concepts. Then we expound the application and development of ABM in both urban land systems and agricultural land systems, and further introduce the case study of a model on Grain for Green Program in Hengduan Mountainous region, China. On the basis of combing the ABM modeling protocol, we propose the land system ABM modeling framework and process from the perspective of agents. In terms of urban land use, ABM research initially focused on the study of urban expansion based on landscape, then expanded to issues like urban residential separation, planning and zoning, ecological functions, etc. In terms of agricultural land use, ABM application presents more diverse and individualized features. Research topics include farmers' behavior, farmers' decision-making, planting systems, agricultural policy, etc. Compared to traditional models, ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data. However, due to its unique bottom-up model structure, ABM has an indispensable role in exploring the driving forces of land change and also the impact of human behavior on the environment.     

中国居民耕地资源保护偏好研究：选择实验法的应用

耕地资源保护有效方案与政策一直是国内外政府决策者和学术界关注的热点。本文利用武汉市农民和市民实地调查数据,基于选择模型法构建假设的政策与交易市场,模拟在此假设市场下主要相关利益群体耕地资源保护偏好意愿。依据选择实验法的基本原理选取耕地面积、耕地质量、耕地周边景观与生态环境、支付耕地保护费用作为环境商品的属性。首先考查了主要相关利益群体的偏好,并获得了对于保护属性主要相关利益群体农民和市民不同偏好的实验证据;然后分析不同环境商品属性组合方案所可能引起的福利变化水平。本文研究所得出的结论,为中国的农地保护制度和目前实施的耕地保护基金、农业补贴制度提供理论上的支持和决策参考。     

Concrete evidence & geographically weighted regression: A regional analysis of wealth and the land cover in Massachusetts

Several studies indicate that there is a positive relationship between green vegetation land cover and wealthy socio-economic conditions in urban areas. The purpose of this research is to test for and explore spatial variation in the relationship between socio-economic and green vegetation land cover across urban, suburban, and rural areas, using geographically weighted regression (GWR). The analysis was conducted at the census block group level for Massachusetts, using Census 2000 data and impervious surface data at 1-m resolution. To explore regional variations in the relationship, four scenarios were generated by regressing each of the following socio-economic variables – median household income, percentage of poverty, percentage of minority population, and median home value – against two environmental variables – percent of impervious surface and population density. GWR results show that there is a considerable spatial variation in the character and the strength of the relationship for each model. There are two main conclusions in this study. First, the impervious surface is generally a strong predictor of the level of wealth as measured by four variables included in the analysis, at the scale of census block group; however, the strength of the relationship varies geographically. Second, GWR, not ordinary least squares technique, should be used for regional scale spatial analysis because it is able to account for local effects and shows geographical variation in the strength of the relationship.     

多元统计回归及地理加权回归方法在多尺度人口空间化研究中的应用

对统计型人口数据进行格网形式的空间化可更直观地展示人口的空间分布,但不同的人口空间化建模方法和不同的格网尺度在表达人口空间化结果方面存在差异。本文在人口特征分区的基础上,引入DMSP/OLS夜间灯光对城镇用地进行再分类,采用多元统计回归和地理加权回归方法(GWR),开展人口统计数据空间化多尺度模型研究,生成1 km、5 km和10 km等3个尺度的2010年安徽省人口空间数据,并对3个尺度下2个模型结果进行精度评价与比较。结果表明：人口空间数据精度不仅与建模所用方法关系密切,还受到建模格网尺度大小的影响。基于多元统计回归方法的模型估计人口数与实际人口的平均相对误差值随着尺度的增加而降低,而基于GWR方法获得的人口空间数据误差值随着尺度的增加而升高。整体来看,基于GWR方法的1 km研究尺度的人口空间数据平均相对误差最低(22.31%)。区域地形地貌条件与人口空间数据误差有较强的关联,地貌类型复杂的山区人口空间数据误差较大。     

Women Agricultural Landowners—Past Time to Put Them “On the Radar”

While women own 25% of the acres rented out for farming, little has been done in terms of federal policy that focuses on these women. In this policy analysis, we detail how (1) lack of data on these women landowners and (2) the invisibility of these women to federal natural resource and agricultural agency staff contribute to women nonoperating landowners (WNOLs) not being on the federal policy radar. We discuss how the persistence of these factors continues to marginalize WNOLs in federal agricultural policy, despite the mandate of U.S. Department of Agriculture (USDA) agencies to be serving underserved populations such as WNOLs. Our study findings clearly illustrate a critical point: federal agricultural/conservation agencies are not fulfilling their mandate to reach WNOLs. Using data from USDA Production Regions in the United States, we detail how WNOLs are marginalized and provide specific policy recommendations to allow for intentional inclusion of these women.     

基于3种地理加权回归方法的安徽省土壤pH空间预测制图对比研究

基于安徽省140个采样点的土壤pH数据,综合考虑土壤、地形、气候、生物等因子对土壤pH的影响,采用地理加权回归(Geographically Weighted Regression, GWR)、主成分地理加权回归(Principal Component Geographically Weighted Regression, PCA-GWR)和混合地理加权回归(Mixed Geographically Weighted Regression, M-GWR)3种模型对安徽省土壤pH空间分布进行建模预测,揭示环境因子对土壤pH的影响在空间上的差异,最后以多元线性回归模型(Multiple Linear Regression, MLR)为基准比较3种GWR模型的精度。研究表明：(1)安徽省土壤pH具有空间异质性,且集聚特征明显。(2) 3种GWR模型中M-GWR模型略优,GWR、PCA-GWR和M-GWR的建模集调整后决定系数(R_adj²)分别为0.59、0.62和0.63;对比MLR模型,3种GWR模型的R_adj^2<...     

Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations

Geographically Weighted Regression (GWR) is a widely used tool for exploring spatial heterogeneity of processes over geographic space. GWR computes location-specific parameter estimates, which makes its calibration process computationally intensive. The maximum number of data points that can be handled by current open-source GWR software is approximately 15,000 observations on a standard desktop. In the era of big data, this places a severe limitation on the use of GWR. To overcome this limitation, we propose a highly scalable, open-source FastGWR implementation based on Python and the Message Passing Interface (MPI) that scales to the order of millions of observations. FastGWR optimizes memory usage along with parallelization to boost performance significantly. To illustrate the performance of FastGWR, a hedonic house price model is calibrated on approximately 1.3 million single-family residential properties from a Zillow dataset for the city of Los Angeles, which is the first effort to apply GWR to a dataset of this size. The results show that FastGWR scales linearly as the number of cores within the High-Performance Computing (HPC) environment increases. It also outperforms currently available open-sourced GWR software packages with drastic speed reductions – up to thousands of times faster – on a standard desktop.     

Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression

Scientific interpretation of the relationships between agricultural landscape patterns and urbanization is important for ecological planning and management. Ordinary least squares (OLS) regression is the primary statistical method in previous studies. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between several urbanization indicators (urbanization intensity index, distance to urban centers and distance to road) and changes in metrics describing agricultural landscape patterns (total area, patch density, perimeter area ratio distribution and aggregation index) at two block scales (5 km and 10 km). Results denoted that GWR was more powerful than OLS in interpreting relationships between agricultural landscape patterns and urbanization, since GWR was characterized by higher adjust R², lower Akaike Information Criterion values and reduced spatial autocorrelations in model residuals. Character and strength of the relationships identified by GWR varied spatially. In addition, GWR results were scale-dependent and scale effects were particularly significant in three aspects: kernel bandwidth of weight determination, block scale of pattern analysis, and window size of local variance analysis. Homogeneity and heterogeneity in the relationships between agricultural landscape patterns and urbanization were subject to the coupled influences of the three scale effects. We argue that the spatially varying relationships between agricultural landscape patterns and urbanization are not accidental but nearly universal. This study demonstrated that GWR has the potential to provide references for ecological planners and managers to address agricultural landscapes issues at all scales.     

Impact of Agricultural Labor Transfer on Agricultural Nonpoint Source Pollution: A Case Study of Jiangxi,China

A large proportion of the rural labor force in China will continue to transfer to non-agricultural sectors in the near future, which will inevitably lead to the transformation of the agricultural production mode and the structure of the farmers’ livelihood. The Chinese government is making great efforts to govern agricultural nonpoint source pollution (ANSP), and farmers' environmental behavior is a key factor that must be considered in the formulation of agricultural environmental policies. Based on a set of micro survey data on farmers in the study area and econometric methods, this study investigates the impact of agricultural labor transfer on ANSP by considering the substitution effect of agricultural factors and the effect of agricultural economies of scale. The results show that the increase of the agricultural labor force will not be conducive to reducing ANSP, while the income increase brought by agricultural labor transfer will improve the input structure of agricultural factors and have a positive impact on ANSP reduction. Government departments should provide subsidies or incentive measures to help agricultural social service organizations to expand their coverage and increase the frequency of socialized agricultural services, in order to guide farmers in the use of environment-friendly agricultural technology to reduce the ANSP caused by agricultural factors at the source. Furthermore, it is necessary to facilitate the development of small-sized agricultural machinery suitable for small-area land cultivation.