Lichens as indicators of a perturbation/stability gradient in the Asperillo dunes, SW spain

In the asperillo dune system, Southwest Spain, lichen vegetation covering the dune sand, has a low species diversity but is an important component of the perennial vegetation, providing stability, nutrients, and moisture to the soil layer. The Asperillo dunes harbour (1) natural ecosystems, (2) disturbed systems affected by forestry activities where the natural vegetation is eliminated, and (3) pine forest resulting from afforestation withPinus pinea since the end of the 1940s where the composition and abundance of the lichen flora has been drastically changed. Our hypothesis was that the lichen species composition and distribution are influenced by the type and period of human intervention. To test this hypothesis a 1.2 km × 1.1 km area, which includes zones with different degrees of conservation and perturbation, consisting of five different habitats, was selected: well preservedJuniperus woodland,Pinus pinea plantations with dense scrub, dense scrub,P. pinea plantations cleared from scrub, and pioneer scrub in recent pine afforestation. In each area, randomly located 5m × 5 m homogeneous plots were sampled. In each plot the cover of shrub and lichen species was recorded. The first results show that lichen cover is higher in the most preserved areas,Cladonia mediterranea being the dominant species under theJuniperus phoenicea canopy. The lichen community changes in composition and abundance depending on the time elapsed since the last perturbation.     

Seasonal food use by white-tailed deer at Valley Forge National Historical Park,Pennsylvania, USA

Food habits of white-tailed deer (Odocoileus virginianus) were examined from January to November 1984 via fecal-pellet analysis at Valley Forge National Historical Park (VFNHP), which represents an island habitat for deer surrounded by extensive urbanization, in southeastern Pennsylvania. In addition, use of fields by deer was compared to food habits. Herbaceous vegetation (forbs, leaves of woody plants, and conifer needles) was the predominant food type in all seasons except fall. Acorns and graminoids (grasses and sedges) were important food resources in fall and spring, respectively. Use of woody browse (twigs) was similar among seasons. Field use was relatively high during fall, winter without snow cover (<20 cm), and spring when food resources in fields were readily available. In contrast, use of fields was lowest in summer when preferred woodland foods were available and in winter with snow cover when food in fields was not readily accessible. Patterns of food-type use by deer at VFNHP indicate the year-round importance of nonwoody foods and field habitats to deer populations on public lands such as national parks in the northeastern United States.     

The Water Table: The Shifting Foundation of Life on Land

Hyperarid, arid, and semi-arid lands represent over a third of the Earth’s land surface, and are home to over 38 % of the increasing world population. Freshwater is a limiting resource on these lands, and withdrawal of groundwater substantially exceeds recharge. Withdrawals of groundwater for expanding agricultural and domestic use severely limit water availability for groundwater dependent ecosystems. We examine here, with emphasis on quantitative data, case histories of groundwater withdrawals at widely differing scales, on three continents, that range from the impact of a few wells, to the outcomes of total appropriation of flow in a major river system. The case histories provide a glimpse of the immense challenge of replacing groundwater resources once they are severely depleted, and put into sharp focus the question whether the magnitude of the current and future human, economic, and environmental consequences and costs of present practices of groundwater exploitation are adequately recognized.     

Using digital image projections to visualize forest landscape changes due to management activities and forest growth

A pedagogic problem in forestry and landscape management is to visualize future landscape effects of forest growth and current management activities in the forest. This paper presents a method for forecasting digital image projections of forest landscape dynamics. Static nonlinear regression functions estimate the digital numbers in a Landsat Thematic Mapper image. Regressors used are forest stand variables. By estimating the future forest stand data, based on intermediate treatment and growth, future satellite digital images are created. In a case study example, the future landscape of a forest block in the province of Västernorrland, Sweden, is projected to demonstrate the application of this visualization technique.     

燃烧风洞的研制及其燃烧特性研究

本文介绍了为可燃物燃烧特性研究而建立起来的模拟自然环境条件的燃烧风洞设备以及在燃烧设备中进行的模拟火场的火蔓延特性研究。在燃烧风洞中进行的可燃物燃烧实验为林火机理的研究、火蔓延模型的建立提供了实验依据．     

北京松山国家级自然保护区典型植被类型表层土壤碳密度及周转速率特征

为阐明不同植被类型下表层土壤有机碳的分布特征,本文选取北京松山国家级自然保护区内胡桃楸阔叶林、蒙古栎阔叶林、油松针叶林、针阔叶混交林、灌丛和草甸6种典型植物群落作为研究对象,基于野外调查、采样与实验室分析对不同植被类型下表层土壤有机碳含量、密度及周转速率进行了研究。结果表明：草甸表层土壤有机碳含量和密度最高,分别为188.5 g/kg和10.9 kg/m²,周转速率最低,为0.019 6/a;针阔叶混交林表层土壤有机碳含量和密度最低,分别为68.6 g/kg和5.7 kg/m²,周转速率为0.074 9/a;灌丛表层土壤有机碳周转速率为0.077 4/a。土壤有机碳含量整体上随土壤深度增加而逐渐减少。土壤水分的增加和土壤温度的下降使表层土壤有机碳含量及密度呈上升趋势,而使有机碳周转速率呈下降趋势。土壤有机碳密度随海拔升高呈逐渐上升趋势。海拔通过影响不同植被群落土壤水热条件来影响微生物活动及凋落物的分解,进而影响表层土壤有机碳含量、密度和周转速率。本文为松山国家级自然保护区典型植被类型土壤碳储量和周转研究提供了有效参考。     

燃煤锅炉烟气脱硫技术选择探讨

简要介绍了国内外锅炉烟气脱硫技术的发展状况、目前国内外典型的烟气脱硫技术、所建装置运转状况，引进技术在国内建设的装置应用情况等，对不同工艺之间的技术优劣及工业应用条件等进行了对比分析，并提出了一些个人观点，以期为国内的用户和科研单位决策提供参考。     

基于第二次全国土地调查的云南省坝区县、半山半坝县和山区县的划分

云南是我国西部的典型山区省份,地形坡度<8°的坝区面积仅占土地总面积的6%左右。应用云南省第二次全国土地调查中对各县（市、区）≥1 km²坝子的调查和核定成果,选取坝区耕地面积比例、坝区土地面积比例、≥100 km²坝子数等3 个单项指标,并构建了综合指标--坝区土地综合指数,采用主导指标与综合分析相结合的方法,对全省129 个县（市、区） 进行坝区县、半山半坝县和山区县的划分。结果表明,全省有21 个县属于坝区县,37 个县属于半山半坝县,71 个县属于山区县。这一研究修订了以往云南省仅以坝区耕地面积比例为指标而划分出的坝区县、半山半坝县和山区县方案,为云南省及各地合理地进行产业布局（尤其是农业生产布局）、保护坝区优质耕地资源提供科学依据和基础支撑。     

基于机器学习分类算法解析EIS数据的有机涂层性能评价方法

目的 基于机器学习分类算法快速评估有机涂层的防腐性能。方法 通过实验室加速试验模拟涂层真实的退化过程,并根据测得的电化学数据,分析不同退化阶段的等效电路元件参数。随后,采用随机抽样方法获取大量数据,用于机器学习模型训练。通过对比支持向量机(SVM)、k最近邻(k-NN)和随机森林(RF)3种不同的机器学习算法,以及多种输入特征集训练的涂层性能分类器模型的准确率,分析最适合用于涂层性能快速评估的机器学习算法和电化学特征。结果 根据不同输入特征训练的k-NN和RF模型均表现出良好的预测效果,而SVM模型的预测效果相对较差。根据不同频率范围训练的分类器模型中,在低频区表现最佳,而在高频区表现较差。结论 基于阻抗虚部、虚部+实部和阻抗模值3种输入特征训练的RF分类器模型的预测效果最准确。不同频率区间内,低频区的阻抗特征更能准确表征涂层性能。