基于LUCC的艾比湖区域生态风险评价及预测研究

以新疆内陆艾比湖流域典型区域为研究区,基于RS和GIS技术分析1998、2013年土地利用变化,尝试用CA-Markov模型预测2028年土地利用/覆盖变化.借助Fragstats3.4软件,基于土地利用/覆盖变化构建景观生态风险评价模型,分析1998~2028年景观生态风险的时空分异特征.结果表明：（1）1998~2013年,研究区土地类型面积变化明显.耕地面积增加量最大,增加的面积为152139hm²,而未利用地面积减少量最大,减少的面积为67605hm².2013~2028年,耕地和裸露的河床及盐渍地的面积增加明显,增加的面积分别为30730hm²,12427hm²,而未利用地和水体的面积分别从954376hm²和44889hm²,减至921079hm²和37157hm².（2）1998~2028年,研究区生态风险等级空间分布差异明显.高生态风险区面积变化较为显著,其面积分别约占总面积的36.6%,7.3%,23.7%.1998~2028年,全局Moran's Ⅰ值分别为0.436962,0.442202,0.506622,表现为一定程度的正相关.（3）1998~2028年,耕地分布在低,较低生态风险的比重上升,所占百分比分别为58.46%,78.58%,79.9%.林、草地类型的各生态风险等级的所占的比重的波动较大.     

基于过程的农户土地利用行为模型的设计与模拟研究

通过基于过程的方式来研究农户决策行为已经成为学者们关注的焦点问题之一。论文依据Belief、Desire、Intention（BDI）决策框架,设计基于过程的农户土地利用行为决策模型。模型以农户实际决策而非效益最大化作为行为模拟的假设,对陕西省米脂县高渠乡的典型村落马蹄洼和姜兴庄土地利用变化进行模拟。模拟可以再现农户决策的动态性和反馈性,展示农户学习行为的过程及其影响,揭示农户决策变化的内在机理。利用该模型,对3 种情景下农户土地利用行为进行模拟,对比分析3 种情景的优劣,指出政府未来应当在降低市场风险、规范合作社经营、提高市场预测方面多做工作。文章最后对该种方法的优点和不足进行总结,并指出今后需要加强的方向。     

基于面向对象的海岸带土地利用信息提取研究

针对海岸带复杂多样的土地利用信息,选取山东省乳山市海岸带为研究区域,运用 Landsat TM遥感影像数据,基于面向对象分类方法,利用不同地物的光谱、形状、纹理和空间关系等特征,通过多尺度分割、隶属度函数法和标准最邻近分类法提取研究区土地利用信息,并对分类结果进行精度评估。结果表明：①隶属度函数法和标准最邻近分类法结合,提取出乳山市海岸带12 种土地利用类型信息,很好地区分了盐田和养殖水面、林地和园地,可提取出主要的道路和河流等细长线状地物;②将提取结果与最大似然法对比,面向对象分类方法提取精度达到82.50%,Kappa系数为0.809 1,分别比最大似然法提高了11.44%和0.105 5,很好地避免“同物异谱”和“异物同谱”对分类精度造成的影响,有效地避免了“椒盐”现象。面向对象分类方法提取中分辨率遥感影像精度较高,为海岸带土地利用信息的快速、准确提取提供了有效的技术手段。     

快速城市化地区的土地利用时空动态变化研究 --以南京市为例

20年来,在中国城市化快速发展的过程中,一系列与城市化相关的环境问题随之产生。六朝古都——南京,作为我国经济最发达的长江流域四大中心城市之一,其快速的城市化过程也不可避免地带来了同样的环境问题。为了研究南京市的城市化和土地利用变化规律及其对水文过程的影响,利用1987、1998、2000年的三期遥感数据,通过分层分类的方法对各土地利用类型进行专题信息提取,结合GIS技术,获得研究区1987~1998,1998~2000年两个时段的土地利用变化转移矩阵。据此全面分析了南京市的土地利用时空变化特征。结果表明：南京市13年来,城乡居民及建设用地以大量蚕食耕地而显著增加,年均增幅达到1.92％;耕地和未利用地则明显减少,年均减幅分别为0.62％ 和1.21％;林地和水域有所增加,主要来自未利用地的转变,剩余12.35％的未利用地则转化为城乡居民及建设用地。引起这一土地利用变化的主要驱动力是人口的增长和经济的发展以及政策制度的激励和导向作用。     

环鄱阳湖浅层地下水水化学特征的时空变化

系统采集了鄱阳湖周边地下水,分析测定各单元的水化学参数.结果表明,环鄱阳湖浅层地下水整体偏酸性,呈低矿化度,局部地区出现微咸水.环鄱阳湖浅层地下水丰、枯水期的优势阴离子为HCO3-,阳离子为Ca2+和Mg2+.运用SPSS软件做离子相关性分析,各离子间均呈正相关性,说明可能有相同的来源.地下水的水化学类型整体表现为HCO3-Ca-Mg型,丰水期相对于枯水期出现较多的NO3-型和SO24-型水体,局部区域优势阴离子改变,出现了NO3-型、Cl-型地下水,可能受到农业化肥和工业废水排放的影响.整体上地下水的水化学类型受当地岩石类型的影响比较大,个别地区受人为的活动干扰较为强烈.     

Extreme events and environmental changes: Tracing sedimentary processes in Central Vietnam coastal lagoons

Sediment cores, obtained in 2004–2005 and in 2008 from seven coastal lagoons of Central Vietnam (Lang Co, Nuoc Man, Nuoc Ngot, Thi Nai, O Loan, Thuy Trieu and Dam Nai), were analysed to assess changes in ²¹⁰Pb, porosity, grain size, and depth distributions of selected major and trace elements (Al, As, Ni, and Zn). The aim was to trace sedimentary processes in areas periodically subject to extreme events. The occurrence of lateral sedimentary inhomogeneities has been hypothesised to explain the differences observed at depth for some tracer profiles, whereas topmost levels present evidence that accounts for the loss of a sediment layer (from 2.0 to 7.5 cm thick) between the two samplings. These losses might be attributed to major typhoons that impacted the coasts of Central Vietnam during the study period.     

Historical evidence of climatic variability and changes,and its effect on high-altitude regions: insights from Rara and Langtang,Nepal

ABSTRACT

Climatic variability and its effects have been experienced in the high-altitude regions of Nepal for some considerable time. Most of the studies on local people’s perception available so far in Nepal on climate include with respect to weather changes, and almost none have been verified with satellite imagery. This study thus attempts to combine meteorological and satellite imagery for comparing local people’s perception so that a more robust validation can be established. Both qualitative (transect walk, key informant interview, focus group discussion and institutional visit) and quantitative (meteorological and satellite image) data and techniques were employed. Local people from Rara and Langtang in Nepal shared their observations and perceptions on the changing climate for the last three decades and the effects on them and their local microclimate. Apart from temperature, rainfall and snowfall anomalies, locals observed changes in the water sources and increasing drought along with alteration in the phenology of tree and agricultural crops as well as vegetation range migration. Satellite image analysis also confirms a change in snow cover as notified by the local people. This study shows that local people’s knowledge could be considered as a complement to the observed scientific evidences of climate change science and their perceptions can be used reliably where scientific data are lacking. Finally, perceived climatic risks, current gaps and future opportunities are discussed and some recommendations are suggested.     

The temporal changes of the concentration level of typical toxic organics in the river sediments around Beijing

In this study, the current situation of five types of toxic organics and endocrine disrupters in the sediments of rivers around Beijing, i.e., polycyclic aromatic hydrocarbons (PAHs), phthalic acid esters (PAEs), organic chlorinated pesticides (OCPs), estrogens (Es), and bisphenol A (BPA), which included 56 contaminants, was analyzed and compared with that registered by the historical literatures. The ecological risks were also assessed. The total concentration of PAHs, PAEs, OCPs, Es, and BPA ranged from 232.5 ng·g^–1 to 5429.7 ng·g^–1, 2047.2 ng·g^–1 to 18051.5 ng·g^–1, 4.5 ng·g^–1 to 11.7 ng·g^–1, 18.1 ng·g^–1 to 105.2 ng·g^–1, and 36.3 ng·g^–1 to 69.6 ng·g^–1, respectively. Among these five types of organic compounds, the concentration levels of PAHs and OCPs have decreased significantly in the last ten years, while those of PAEs and Es had an upward trend compared with the previous studies. BPA still remained at a moderately high level, as it was ten years ago. The risks of the PAEs in all of the sample sites, and fluoranthene, benzo[a]anthrene, and benzo[a]pyrene in the Wenyu River sediment, were relatively high. These results supplemented the database of toxic organics’ concentration levels in the sediments of Beijing rivers.

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Estimating the influence of overhead transmission power lines and landscape context on the density of little bustard Tetrax tetrax breeding populations

Collision with conductors and earth cables is a known impact generated by transmission power lines, however there is virtually no information on how these infrastructures might affect bird distribution in a landscape context. With this work we specifically hypothesise that transmission power lines may affect the occurrence of a threatened bird, the little bustard (Tetrax tetrax). To test this hypothesis we used a Stochastic Dynamic Methodology (StDM), analysing the effects of power lines in a landscape perspective and simulating population trends as a response to power line installation and habitat changes induced by agricultural shifts in southern Portugal. The data used in the dynamic model construction included relevant gradients of environmental conditions and was sampled during the breeding seasons of 2003-2006. Transmission power lines were significantly avoided by the little bustard and the developed StDM model showed that the distance to these utility structures is the most important factor determining breeding densities in sites with suitable habitat for the species, which possibly leads to displacement of populations and habitat fragmentation. The model simulations also provided the base to analyse the cumulative effects caused by the habitat degradation that can ultimately lead to the extinction of local populations. Within priority conservation sites, the dismantling of existing transmission lines should be considered whenever possible, in order to ensure adequate breeding habitat. The model is considered useful as an auxiliary tool to be used in environmental impact assessments, management and conservation studies.     

Analysis of the global warming dynamics from temperature time series

Global warming is the observed increase of the average temperature of the Earth. The primary cause of this phenomenon is the release of the greenhouse gases by burning of fossil fuels, land cleaning, agriculture, among others, leading to the increase of the so-called greenhouse effect. An approach to deal with this important problem is the time series analysis. In this regard, different techniques can be applied to evaluate the global warming dynamics. This kind of analysis allows one to make better predictions increasing our comprehension of the phenomenon. This article applies nonlinear tools to analyze temperature time series establishing state space reconstruction and prediction. Since noise contamination is unavoidable in data acquisition, it is important to employ robust techniques. The method of delay coordinates is employed for state space reconstruction and delay parameters are evaluated using the method of average mutual information and the method of false nearest neighbors. Afterwards, the simple nonlinear prediction method is employed to estimate temperatures of the future. Temperature time series from different places of the planet are used. Initially, the approach is verified considering known parts of the time series and afterwards, results are extrapolated for future values estimating temperature until 2028. Results show that these techniques are interesting to estimate temperature time history, presenting coherent estimations.