An Automated Technique for Delineating and Characterizing Valley-Bottom Settings

Accurate delineation and characterization of valley-bottom settings is crucial to the assessment of the biological and geomorphological components of riverine systems; yet, to date, most valley-bottom mapping endeavors have been done manually. To improve this situation, we developed automated techniques in a Geographic Information System (GIS) for delineating and characterizing valley-bottom settings in river basins ranging in size from approximately 1,000–10,000 km². All procedures were developed with ARC/INFO GIS software and fully automated in Arc Macro Language (AML). The GRID module is required for valley-bottom delineation and slope calculations; whereas characterization (i.e., measuring the width of the valley-bottom zone) requires Coordinate Geometry (COGO) in the ARCEDIT module. The process requires three inputs: a polygon coverage of the analysis area; an arc coverage of its hydrography, and a grid representing its digital elevation. The AML is designed to operate within a wide range of computer memory/disk space options, and it allows users to customize several procedures to match the scale and complexity of a given analysis area with available computer hardware.     

Classification and spatial mapping of riparian habitat with applications toward management of streams impacted by nonpoint source pollution

Management of riparian habitats has been recognized for its importance in reducing instream effects of agricultural nonpoint source pollution. By serving as a buffer, well structured riparian habitats can reduce nonpoint source impacts by filtering surface runoff from field to stream. A system has been developed where key characteristics of riparian habitat, vegetation type, height, width, riparian and shoreline bank slope, and land use are classified as discrete categorical units. This classification system recognizes seven riparian vegetation types, which are determined by dominant plant type. Riparian and shoreline bank slope, in addition to riparian width and height, each consist of five categories. Classification by discrete units allows for ready digitizing of information for production of spatial maps using a geographic information system (GIS). The classification system was tested for field efficiency on Tom Beall Creek watershed, an agriculturally impacted third-order stream in the Clearwater River drainage, Nez Perce County, Idaho, USA. The classification system was simple to use during field applications and provided a good inventory of riparian habitat. After successful field tests, spatial maps were produced for each component using the Professional Map Analysis Package (pMAP), a GIS program. With pMAP, a map describing general riparian habitat condition was produced by combining the maps of components of riparian habitat, and the condition map was integrated with a map of soil erosion potential in order to determine areas along the stream that are susceptible to nonpoint source pollution inputs. Integration of spatial maps of riparian classification and watershed characteristics has great potential as a tool for aiding in making management decisions for mitigating off-site impacts of agricultural nonpoint source pollution.     

济南泉域地下水补给区保护分级及核心保护区承载力分析

近年来由于地下水补给区的盲目开发和市区地下水超采，素以“泉城”闻名的济南市泉水持续断流，加强泉域地下水补给区的生态环境保护是解决这一问题的关键，在详细研究区域地质水文条件的基础上借助地理信息系统，将补给区划分为三级保护区，即核心保护区，直接补给区和间接补给区，并应用环境承载力分析的理论方法，确定出保护区23个汇水区的环境承载人口，本文对泉域地下水补给区总体发展战略和具体保护规划的制定具有重要的意义。     

基于神经网络的红树林景观特性遥感提取技术研究

利用神经网络法对广西山口红树林保护区2003年1月8日获取的Landsat TM 卫星图像进行分类.Landsat TM5卫星数据的3、4、5假彩色合成图像空间分辨率比较好,影像层次丰富,地物界限清晰.因此,采用3、4、5波段作为输入层.经过目视判读和现场调查,将输出层单元设置为5个,包括是红树林、陆地植被、裸地(其他建筑用地)、水体和虾池.经过流程实际运算和精度对比,设定训练阈值的贡献是0.9,训练率是0.2,训练次数是1000,最大个体允许误差为0.1.分类精度达到86.86%,高于最大似然分类(50.79%)和光谱角分类精度(75.39%),从而最终获取红树林生态系统的景观格局指标.结果显示研究区红树林均匀度(1.7789)和聚集度指数(0.6854)较高;红树林种类的优势度指数是-1.5850,为弱势群体;红树林的斑块破碎化指数是0.0325,破碎化程度较低.     

广东省耕地地力等级研究与评价

广东省耕地地力等级研究与评价工作根据《全国耕地类型区、耕地地力等级划分》标准为依据，以土种为评价单元，采用的方法有归纳法、限制因素法、专家经验法，建立了省级土种数据库、耕地地力评价指标体系，并对各等级耕地进行面积统计、科学评价。研究结果表明，广东省水稻田地力等级分为八个等级，以一至四等为主，占水稻田总面积的87．1％；一、二等的水稻田占水稻田总面积的32．3％，是高产稳产农田；三至八等水稻田占水稻田总面积的67．7％，是粮食生产的主要基地，也是主要的中低产水稻田。必须针对后者的障碍因素，因地制宜采取不同的改良措施，加强改造，提高地力。旱地地力分为九个等级，全省高产旱地比例较低，一至四等旱地只占旱地总面积的7．9％，五至八等旱地占旱地总面积的73．79％，是经济作物和水果的主要生产基地。低产的旱地在田间管理上必须重视施用有机肥，增加土壤粘粒，培肥地力，提高作物产量，促进农业生产的发展。     

不同甘蔗基因型光合特性的数值分类

对30个甘蔗基因型光合性状进行数值分类、主成分、聚类和判别分析研究认为，甘蔗基因型间光合性状存在较大差异；利用主成分分析选出3个主成分，方差累计贡献率达到98．5％，蒸腾速率、气孔导度为第一主成分的主导因子，而净光合速率和气孔导度分别为二、三主成分的主导因子；经系统聚类将30个基因型分为三大类，在聚类分析基础上用判别分析选出对甘蔗光合性状数值分类有显著影响的4个光合参数，建立3个判别能力较高的判别模型．表5图1参22     

中国海洋自然保护区功能分区模式及分类管理初探

我斟海洋自然保护区目前正处于高速发展过程中，保护区已有的功能分区模式已不能满足保护区建设和管理工作的需要。本文通过对海洋自然保护区的功能分区的分析探讨，提出不同类型的保护区应采用不同的功能分区模式进行管理。另外，以中华白海豚自然保护区为例，在分析其功能分区和种群分布特点的基础上，提出了不设核心区模式。最后，提出在保护区高速发展的同时，应加强海洋自然保护区本身的研究，应加强保护区的分类及功能分区的研究。     

Using multi-objective classification to model communities of soil microarthropods

In agricultural soil, a suite of anthropogenic events shape the ecosystem processes and populations. However, the impact from anthropogenic sources on the soil environment is almost exclusively assessed for chemicals, although other factors like crop and tillage practices have an important impact as well. Thus, the farming system as a whole should be evaluated and ranked according to its environmental benefits and impacts. Our starting point is a data set describing agricultural events and soil biological parameters. Using machine learning methods for inducing regression and model trees, we produce empirical models able to predict the soil quality from agricultural measures in terms of quantities describing the soil microarthropod community. We are also interested in discovering additional higher level knowledge. In particular, we have identified the most important factors influencing the population densities of springtails and mites and their biodiversity. We also identify to which agricultural actions different microarthropods react distinctly. To obtain this higher level knowledge, we employ multi-objective regression trees.     

我国东部七省生态系统对酸沉降的相对敏感性

讨论了影响亚热带生态系统对酸沉降敏感性的生态因子，提出了敏感性等级划分的指标体系，根据大量资料编制了我国东部７省１市生态系统对酸沉降相对敏感性分区图。结果表明，在研究区域内生态系统的敏感性有相当大的差别，极敏感区和敏感区面积占全区总面积的１／３以上，主要分布在福建、浙江、江西３省。