风险规避、非牧用途使用与牧户草原流转行为

基于新疆12个牧业县232户微观数据,运用风险收益理论、期望效应理论构建了草原流转风险规避理论模型与基于博弈论构建了草原流转非牧用途使用理论模型,分析了风险规避和非牧用途使用对牧户草原流转的内在机理。使用二元Logit模型、中介效应与调节效应分别探析风险规避和非牧用途使用对牧户流转行为的影响。研究表明：违约风险、生态风险、经营风险对牧户草原流转行为存在显著影响,草原流转存在的各类风险可能导致牧户的风险规避行为;非牧用途使用、转移就业能力担忧与家庭收入结构对于牧户草原流转行为存在显著影响;家庭收入结构在牧户面临非牧用途使用时存在调节效应,而其转移就业能力担忧在牧户面临非牧用途使用时存在遮蔽效应。同时,违约风险、生态风险在牧户面临非牧用途使用时存在中介效应。在此基础上,进一步讨论了造成流转风险、非牧用途使用问题的成因与对策。     

东北地区产业结构优化与城市土地集约利用协调性

精准识别产业结构优化与城市土地集约利用的协调状况,对于推动东北地区产业结构转型升级、协调国土空间规划及产业布局具有重要现实意义。运用耦合协调度模型及探索性空间数据分析法,深入探究了2009—2018年东北地区产业结构优化与城市土地集约利用的耦合协调水平及其空间相关性。结果表明：（1）东北地区城市产业结构合理化水平逐年降低,且区域差异程度较大;产业结构高级化水平小幅上升,但不存在明显的空间分异特征。（2）城市土地集约利用水平呈现出先上升后下降的倒“U”型演变特征,并沿着哈大交通经济带的中心城市向两侧梯度递减。（3）产业结构合理化、产业结构高级化与城市土地集约利用协调度分别呈现先上升后下降及稳步上升的演变态势。两协调度均以大连、哈尔滨等城市为中心向外辐射,呈现“多中心多圈层”的空间分布特征。（4）城市两系统协调度存在显著的空间正相关,但显著性逐年减弱,其中高—高聚集类型主要集中在辽中南城市群,低—低聚集类型集中在黑龙江东部城市群。     

不同尺度土地利用方式对地表水环境质量的影响及驱动机制

土地利用作为人类活动的重要载体对地表水环境状况有重要影响.以若尔盖湿地为例,基于面向对象的土地利用类型遥感解译,结合水质检测数据,从小流域和缓冲区尺度,分析不同尺度土地利用方式对地表水环境的影响及驱动机制.结果发现：（1）若尔盖湿地水质为Ⅴ类水,且整体呈现轻度富营养化,主要污染物为总氮（TN）和总磷（TP）,污染来自生活污水和放牧;（2）土地利用方式与地表水环境质量联系紧密,水体面积占比与化学需氧量（COD）呈现负相关关系、沼泽面积占比与TN呈现正相关关系和TP呈现负相关关系;（3）不同尺度土地利用方式与地表水环境存在显著关联性,1 000 m缓冲范围内的土地利用方式解释度最高,200 m的土地利用方式对COD的解释度最大,500 m的土地利用方式对TP和TN的解释度最大,800 m的土地利用方式对叶绿素（Chl-a）的解释度最大.本研究结果表明：若尔盖湿地对污染物和富营养化有一定的净化作用,但不同的土地利用方式对不同污染物作用存在差异,水体对Fe²⁺、 COD和Chl-a有净化作用,沼泽对TP有净化作用但对TN却呈现累积效应.应控制小尺度（≤1 000 m）的土...     

地块尺度重金属污染风险耕地安全利用区划方法

耕地安全利用是保证粮食安全,实现生态文明建设的重要举措之一.为解决污染风险耕地安全利用与修复治理过程中技术措施选择盲目的问题,在重庆市黔江区鹅池镇采集表层土壤样品244件和水稻-根系土样品100套,在分析土壤和水稻中Cd、Hg、Pb、As和Cr这5种重金属含量及土壤中氧化物、有机质和pH等指标的基础上,利用多元回归和地统计分析法建立预测模型,并为地块赋值,结合地块中土壤和水稻中重金属全量、土壤重金属有效态及土壤pH,给出相应的地块尺度耕地安全利用建议.结果表明,研究区土壤以酸性和强酸性为主,Cd超过土壤污染风险筛选值和管制值的比例分别为33.61%和2.05%,Cd有效态占比为60%,水稻Cd超标率为28%,研究区存在明显Cd的生态风险.土壤Cd有效态主要受到土壤Cd全量和pH的影响,水稻中Cd的富集主要受到土壤有机质、Mn和CaO含量的影响.区划结果显示,研究区土壤以优先保护类为主,占比为59.30%;安全利用类占比为40.44%,其中安全利用（IAa）、安全利用（IAb）、安全利用（IBa）、安全利用（IIAa）、安全利用（IIAb）、安全利用（IIBa）占比分别为19.49%、8.01%、1.43%、7.04%、1.41%和3.06%;严格管控类占比为0.26%.该方法将土壤及农产品的安全风险相结合,并针对性给出安全利用建议,为因地制宜地开展受污染耕地安全利用工作提供了方法参考.     

Reservoir Sedimentation Rates in the Little Washita River Experimental Watershed,Oklahoma: Measurement and Controlling Factors

Forty‐five flood control reservoirs, authorized in the Watershed Protection and Flood Prevention Act 1954, were installed by United States Department of Agriculture (USDA) between 1969 and 1982 in the Little Washita River Experimental Watershed (LWREW), located in central Oklahoma. Over time, these reservoirs have lost sediment and flood storage capacity due to sedimentation, with rates dependent on upstream land use and climate variability. In this study, sedimentation rates for 12 reservoirs representing three major land use categories within LWREW were measured based on bathymetric surveys that used acoustic profiling system. Physiographic and climate attributes of drainage area of surveyed reservoirs were extracted from publicly available data sources including topographic maps, digital elevation models, USDA Natural Resource Conservation Service soils, and weather station databases. Correlation, principal component analysis, and stepwise regression were utilized to analyze the relationship between normalized reservoir sedimentation rates (ReSRa) and the drainage area characteristics to determine the major variables controlling sedimentation within the LWREW. Percent of drainage area with extreme slopes, saturated hydraulic conductivity, and maximum daily rainfall event recorded in spring explained most of the variability in ReSRa. It was also found that percent reduction in reservoir surface area can be used as a surrogate for estimating ReSRa. The implications of the results are discussed.     

Calculating Field‐Scale Evapotranspiration with Closed‐Chamber and Remote Sensing Methods

Currently, there is no agreed upon method for estimating evapotranspiration (ET) across large regions such as the state of New Mexico. Remote sensing methods have potential for providing a solution, but require validation. A comparison between field‐scale ET measurements using a portable chamber ET measurement device and modeled ET using the remote sensing Regional Evapotranspiration Estimation Model (REEM) was performed where the model had not been previously evaluated. Data were collected during the growing season of 2015 in three irrigated agricultural valleys of northern New Mexico in agricultural and nonagricultural settings. No statistically significant difference was observed in agricultural datasets between means of measured (M = 3.7 mm/day, SE = 0.31 mm/day) and modeled (M = 4.0 mm/day, SE = 0.01 mm/day) daily ET; t(17) = ?1.50, p = 0.15, α = 0.05. As there was no statistical difference observed between agricultural datasets, results support the use of REEM in irrigated agricultural areas of northern New Mexico. A statistically significant difference was observed in nonagricultural datasets between means of measured (M = 1.7 mm/day, SE = 0.22 mm/day) and modeled (M = 0.0 mm/day, SE = 0.00 mm/day) daily ET; t(9) = 1.79, p = 5.7 × 10^?6, α = 0.05. With additional calibrations and air temperature sensors placed outside of agricultural areas, REEM may be suitable for use in nonagricultural areas of northern New Mexico.     

Harnessing place attachment for local climate mitigation? Hypothesising connections between broadening representations of place and readiness for change

Public engagement in local environmental planning and decision-making is often advocated on various grounds, both instrumental and normative. Yet in developed countries in the context of renewable energy infrastructure deployment, place attachment, place identity and place-protective action continue to be implicated in public objection. We set out an interdisciplinary change readiness hypothesis of specifically how local participatory scenario or visioning processes that include climate mitigation measures may support the mobilisation of place attachment for climate mitigation, including renewable energy deployment. We hypothesise that local visioning may support movement towards change readiness by helping to anchor unfamiliar social representations of low carbon energy infrastructure and new patterns of urban form in existing, more positive representations of localities and associated attachments. To this end, seeking ways to modify threat perceptions relating to climate change and renewable energy infrastructure is advocated as a key direction for study.     

Implementing service-based chemical procurement: lessons and results

Chemical use reduction is strongly desirable for environmental and public welfare reasons, and is a critical element of moving towards more sustainable consumption in the business-to-business economy. However, the fundamental economic relationship between chemical supplier and chemical customer creates supply side incentives for increased chemical use. Chemical management services (CMS) is a business model that aligns economic incentives in the chemical supplier–customer relationship towards reduced chemical use by making chemical services rather than chemical volume the basis of supplier compensation. CMS thus ‘servicizes’ the chemical supply chain and is a Product Service System with significant potential environmental benefits. CMS enjoys high penetration in the US auto and semiconductor sectors, and is emergent in other sectors. The paper synthesizes lessons learned from hands-on work with 15 chemical-using firms over 5 years in all aspects of CMS program implementation. Key points are that poor cost accounting and chemical information management form significant barriers to making, understanding and evaluating the CMS business case. The details of contractual compensation mechanisms are critical to achieving in practice the potential environmental benefits of the CMS model.     

遗传算法在多目标土地利用规划中的应用

在建立和求解多目标土地利用规划模型过程中，采用遗传算法并结合多目标模糊优选理论处理多目标土地利用结构优化问题。其详细步骤为：在分析区域特征基础上构建时间序列；通过现状分析设置土地利用类型决策变量、确定优化目标和约束条件。构建土地利用结构多目标优化模型；用灰色GM（1，1）预测模型对土地利用结构优化多目标模型参数进行预测；用遗传算法多目标优化方法对土地利用结构优化模型求解得pareto解集；最后运用多目标模糊动态优选方法对规划期内各时间段的pareto解集进行模糊动态优选，以最大优属度判定原则确定出最优决策序列。自贡实例表明，该方法有助于解决多目标协调问题，通过遗传算法避免了人为偏好权重的主观性，并通过提供多方案选择性，从而使规划更具灵活性，同时又便于充分吸纳公众参与，减少规划中的不确定性，增加规划的科学性、现实性和可操作性。     

基于多维特征优选支持向量机算法的城市土地利用变化遥感监测

随着遥感影像时、空、谱、辐分辨率和数据处理能力的提升,综合多维影像特征已成为提高土地利用分类精度的关键.目前并非所有特征均有助于分类,且传统分类仍拘泥于单一特征,因此,急需有效的特征优化选择方法.基于光谱指数、穗帽变换、最小噪声分离、高斯滤波、灰度共生矩阵等变换提取了Landsat TM/ETM+/OLI影像的31维特...