江苏省农村土地征用与收益分配研究

本文立足江苏省的土地征用和土地收益分配现实，指出目前存在“圈地”现象严重、征地补偿过低、失地农民未来生活无保障等问题。从政府、制度、城市建设三个层面探讨了问题产生的根源，并提出了提高土地补偿标准、建立失地农民保障体系、广开就业门路、健全法律体系等改革措施。     

CONJUNCTIVE SURFACE AND GROUND WATER MANAGEMENT IN THE JAKARTA REGION,INDONESIA1

ABSTRACT: This study investigates the degree of economic inefficiency of the current institutional arrangements for surface and ground water management in meeting urban water demand in the Jakarta region. A numerical model of integrated surface and ground water management is developed using GAMS (General Algebraic Modelling System) software. The model maximizes the net present value of social benefits from piped water and ground water consumption across all users over time from 1999 to 2025. Four policy scenarios are examined: the status quo, the social planner's solution, and two ground water pumping quota scenarios: an aggregate ground water pumping quota and a partial quota applied to commercial and industrial users. Three variations in each policy scenario are considered: investment in water infrastructure of the Jakarta water enterprise (PAM Jaya), water demand growth, and discount rates. The status quo, depending on the investment option, the growth of water demand, and the discount rate, results in a 7.4 to 47.8 percent loss in economic efficiency relative to the social planner's solution. The partial quota is the most feasible, applicable, and manageable scenario. The optimal investment option could increase the volume of piped water supply and reduce the cost of water production. The volume of water delivery could increase by up to 156 percent, but it implies only a 35 percent increase in the surface raw water demands above the current level. However, it does not significantly reduce cumulative ground water extraction over the time period considered.     

科技资源开发与区域经济增长研究--以河南为例

本文以河南为例，对科技资源的存量动态变化、配置效率及其对区域经济增长的推动作用进行了定量分析。结果表明。1991．2002年。河南科技资源存在总体上呈持续上升趋势。但是。科技资源的配置效率却呈现出下降趋势。在这个期间。科技资源开发对河南区域经济增长的贡献率为42．1％，达到了全国的平均水平。为了进一步发挥科技资源开发对河南经济增长的推动作用，建议河南继续加快科技资源的积累；重点提高科技资源配置的效率；特别重视大幅度提高对R＆D的投入。     

Evidence for sexy sons in European starlings (Sturnus vulgaris)

The sexy son hypothesis suggests that females obtain future fitness benefits from mating with polygynous males through the inheritance by their sons of traits contributing to mating success. We tested this hypothesis in the facultatively polygynous European starling (Sturnus vulgaris) in two ways. We first compared sons of monogynous and polygynous free-living males for their abilities in nest site acquisition and female-directed behaviors in controlled aviary tests. We then investigated eggs laid in monogynous and polygynous matings for concentrations of maternal steroid hormones that could affect behavioral differentiation of sons. Sons of polygynous fathers defended more nest boxes and produced more courtship song than sons of monogynous fathers. Mean concentrations of maternal androstenedione (A4), 5-dihydrotestosterone (DHT), testosterone (T), and 17-estradiol (E) in yolks were not affected by mating status. However, the within-clutch pattern of A₄ depended on mating status, with higher concentrations in last than in first eggs of clutches of monogynous but not polygynous matings. These results suggest that (1) sons may inherit from their fathers behavioral qualities for the successful acquisition of nest sites and attraction of mates; (2) differential exposure to maternal steroid hormones during development in the egg is unlikely the cause of the behavioral differences between adult sons of monogynous and polygynous fathers; and (3) females adjust the within-clutch pattern of androgen to mating status, possibly in response to the expected contribution of their mate to nestling care.     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

HUD状态下飞行员视觉注意资源分配机制研究

为了解决平视显示器（Head Up Display,HUD）飞行中的注意资源分配问题，基于飞行模拟器，设计双作业飞行任务开展相关研究。基于事件相关电位（Event Related Potential，ERP）技术，选取行为绩效和P300成分为评价指标，采用oddball模式，在双作业飞行任务条件下开展实验研究。结果表明:随主任务难度的增加，主、辅任务的作业绩效均显著下降，被试者对HUD上异常信息的正确操作率降低，且反应时间延长；随主任务难度的增加，由辅任务所诱发的P300的波幅显著降低。在实验结果的基础上，最终提出了HUD状态下飞行员视觉注意资源分配机制。     

湖库型水体总氮总量控制目标的区域分配研究

基于层次分析法原理,以资源禀赋、社会经济、农业生产生活、污染治理水平为主要考虑因素设计指标体系和层次结构,建立了湖库型水体总氮总量控制目标分配方法,并在石头口门水库流域进行了应用,为湖库型水体总氮总量控制目标分配及石头口门水库流域总氮总量控制提供借鉴。