洞庭湖区不同利用方式下农田土壤有机碳含量特征

土地利用方式是影响土壤有机碳含量和动态的重要因子之一。其利用方式的改变必将引起土壤有机碳含量发生相应的变化。在洞庭湖腹地选取典型样区，通过调查走访和密集取样，分析了不同土地利用方式（旱地、水旱轮作地、一季稻水田和双季稻水田）下623个农田耕层土样有机碳含量。结果表明，研究区内土壤有机碳含量高低顺序为双季稻水田（28.12 g/kg） > 一季稻水田（27.03 g/kg） > 水旱轮作地（24.79 g/kg） > 旱地（17.96 g/kg），其差异均达到极显著水平（P < 0.01）。土地生产力、秸秆还田量和土壤水文状态是导致不同利用方式下耕层土壤有机碳含量差异的主要原因。进一步分析表明：加强作物秸秆还田（土）、提高土地复种指数、增加地表覆盖是维持和提高洞庭湖区耕作土壤有机碳含量的可行措施，尤其是旱作土壤。     

岩溶槽谷区不同土地利用方式下土壤微生物特征研究

为探索岩溶山区农村不同用地类型土壤肥力及微生物活性状况,对青木关地区五种土地利用类型的土壤肥力、微生物数量及其相关性进行了分析.结果表明：（1）岩溶山区土壤微生物数量的变化受人为影响较大,在总体数量上均以细菌为主,且与一般土壤微生物数量分布情况相吻合;（2）不同用地类型土壤中微生物总量与土壤微生物多样性指数二者的变化趋势不一致,但玉米地例外;（3）通过Pearson相关性分析得出,土壤中有机质、全钾、有效钾和有效磷的含量与土壤微生物之间的相互关系显著。     

土地利用变化环境影响的可拓学评价

文章通过引入可拓学理论,对区域土地利用变化的环境影响进行评价。文章把物元模型、可拓集合和关联函数应用于武汉市黄陂区土地利用变化环境影响评价研究,建立黄陂区土地利用变化环境影响评价指标体系,并对土地利用变化的环境影响评价标准化和定级化。通过计算单指标关联度和综合关联度,确定评价体系各指标的影响程度以及综合影响程度,研究结果直观有效,能全面反应区域土地利用环境影响程度。     

基于Agent建模的农户土地利用行为模拟研究——以陕西省米脂县孟岔村为例

以Agent强化学习（Reinforcement Learning）模型框架为基础,选择政策、市场、Agent自身及与其它Agent相互作用、土壤肥沃程度等因素作为Agent对环境认识的基础,结合环境反馈值,初步构建了农户土地利用行为决策模型,这对于从微观主体层面揭示土地利用变化的内在机理具有重要意义。论文以陕西省米脂县孟岔村为例,采用农户Agent强化学习模型,模拟了农户土地利用行为,得出以下3个结论：①经过对Agent强化学习模型的检验和验证（按面积统计误差率为5.5%）,认为该模型较适合于微观层面农户土地利用行为的研究;②该模型可定量表达政策、市场、农户自身及与其他农户相互作用等因素对农户土地利用行为决策的影响;③与离散函数的土地利用决策相比,应用连续函数表达农户的土地利用决策比较符合实际农户决策状况（农户最终决策中玉米、蔬菜和其它作物的决策值分别为0.3233、0.4035和0.2732）。同时,在文章的最后还分析了需要进一步研究和探讨的问题：①模型在实现农户决策的空间位置方面取得一定进展,但还存在决策位置失误的问题,函待进一步的研究;②对于影响农户决策的自然因素,探讨定量化表达其对农户影响作用,是下一步研究的重点。     

基于多层次模型的农户土地利用决策影响因素分析——以陕西省米脂县高西沟村为例

土地利用变化驱动力研究一直是学者们关注的热点问题之一,土地利用驱动力在不同尺度的变化也越来越受学者们关注。论文以陕西省米脂县高西沟村为研究区域,在地形图、航片解译数据及2009年实际测量数据和农户调查数据的基础上,基于多层次模型的理论,借助HLM6.07(student)软件工具,构建从地块(微观尺度)到农户(中观尺度)的二层土地利用决策影响因素模型,试图揭示微观层面土地利用决策的影响因素在不同尺度上的变化机制。研究结果表明:①农户选择种植土豆、谷子作物的土地利用决策与地块的自然因素和农户的社会经济因素有关;②农户种植土豆、谷子行为决策的影响因素存在差异;③将多层次模型应用到从微观尺度到中观尺度分析农户土地利用决策影响因素是符合实际情况的,这为进一步构建影响农户土地利用决策的因素——微观尺度(地块)、中观尺度(农户)、宏观尺度(村庄)的三层模型奠定了基础,同时为研究土地利用决策机制提供了一种方法。     

上海市不同土地利用类型春季中小型土壤动物群落结构研究

城市不同土地利用方式对土壤动物具有一定影响,为了解城市不同土地利用方式中小型土壤动物群落结构,于2006年春季对包括学校、居住区、公园、工厂、垃圾填埋场和道路等绿地中的中小型土壤动物进行采样研究。研究表明,9种生境中小型土壤动物平均密度为62653只,分别隶属于3门16个类群,优势类群为线虫纲(Nematoda)、蜱螨目(Acarina),常见类群为弹尾目(Collembola)、近孔寡毛目(Oligochaeta plesiopora)、涡虫纲(Turbellaria)和轮虫纲(Rotatoria),它们共占了总捕获量的98.27%。不同城市绿地生境中的土壤动物的类群组成以及个体数不同,群落复杂性指数(Cj)比其它多样性指数更能体现群落的复杂性与多样性。群落聚类以及排序的结果显示,9种生境中的中小型土壤动物群落可以分为6大类:即浦东路旁绿化、工业区乔木及草地类型、植物园草地及废弃地乔木类型、校园乔木及居住区草地类型、校园草地类型、植物园乔木类型。     

Monitoring land use/land cover change impacts on soils in data scarce environments: a case of south-central Ethiopia

To monitor land-use/land-cover (LULC) change and assess its impact on the soil property, the availability of benchmark data is indispensable, which is hardly available in the intensively cultivated regions of developing countries. Our study attempts to solve this problem by generating a benchmark soil data through the development of modified spatial analogue (MSA) method in the context of the Upper Dijo River catchment, south-central Ethiopia. The magnitude and patterns of LULC changes were extracted from air photos and satellite imageries, along with the acquisition of soil samples from the reference and target sites through ground survey. Analysis of digital image processing shows significant LULC changes in a period that spanned three decades. The impact of LULC change on soil quality was assessed by comparing the soil physico-chemical properties sampled from the reference and target sites. The result shows a decline in total nitrogen, organic matter, available potassium and pH levels in soils collected from target sites, which conforms to results reported by studies conducted in data-rich environment. With careful validation, MSA could be useful for monitoring soil property changes in data-scarce environment and generate soil-related parameters for agro-ecological models.     

Land-use choices: the case of conservation reserve program (CRP) re-enrollment in Kansas,USA

Among the important alternatives for land conservation is the US Conservation Reserve Program (CRP) that celebrated its 30th anniversary in 2015. This paper explores how landowners decide on alternative land-use choices made available by the expiration of CRP contracts in Kansas. The study uses survey data and multinomial Logit models to predict land-use choices. Two models were tested. The first model does not incorporate variables concerning farmer perceptions and attitudes about land-use choices, while the second model does. The results show that CRP re-enrollment depends on factors, such as years of experience in cropping and percent of cropland irrigated. However, when perception variables are added, the models become more robust in explaining other land choice alternatives. The results suggest that as the perception of unfairness of more inflexible environmental policy rises, these farmers may be more likely to re-enroll their marginal land in the CRP program.     

Land-use planning via enhanced multi-objective evolutionary algorithms: optimizing the land value of major Greenfield initiatives

The successful implementation of major development initiatives relies on the sound allocation of land uses against critical design criteria and constraints. The discovery of optimum development plans introduces severe complexities in formulating and solving the underlying multi-objective optimization problem. Moreover, in the presence of conflicting planning criteria decision-makers should be provided with a set of alterative-yet-optimum solutions that uniformly cover the spectrum of feasible maps. The introduction of sophisticated optimization algorithms addresses this challenge by pursuing a complete approximation of the Pareto front containing all prominent spatial allocations. This study demonstrates the effectiveness of a new evolutionary algorithm (UDT-MOEA) against the results of an established multi-objective genetic algorithm (NSGA-II) when applied on a major greenfield initiative against the optimum location(s), size and shape of three new land uses. Each algorithm performs best in different areas of the feasible objective space, providing planning alternatives with distinct characteristics.     

The impacts of warfare and armed conflict on land systems

ABSTRACT

Land-use decisions can change abruptly in response to shocks, and warfare and armed conflicts are among the most drastic and globally frequent shocks. Yet, our understanding of where armed conflict affects land systems, how land-use patterns are impacted, and how far-reaching and persistent these changes are, is partial. We used a spatially detailed dataset on armed conflict and a literature review to explore these questions. A number of key insights emerged from our study: (1) warfare and armed conflict affect land systems mainly in more densely populated areas, regardless of the dominating land use; (2) warfare and armed conflict can impact land systems in major ways, but these effects are diverse and not unidirectional; (3) warfare and armed conflict primarily affects land systems locally, but can forge telecouplings; and (4) although the impact of warfare and armed conflict is often immediate, it can instigate long-lasting land-use legacies.