Revisiting Sustainable Development of Dry Valleys in Hengduan Mountains Region

Dry valleys are a striking geographic landscape in Hengduan Mountains Region and are characterized by low rainfall, desert type of vegetation and fragile environment. Past efforts and resources have been concentrated mainly on rehabilitation of degraded ecosystem and fragile environment, particularly reforestation, while socio-economic development has been largely overlooked. Despite successes in pocket areas, the overall trend of unsustainability and environmental deterioration are continuing. It is important to understand that uplift of the Tibetan Plateau is the root cause of development of dry valleys, and development and formation of dry valleys is a natural process. Human intervention has played a secondary role in development of dry valleys and degradation of dry valleys though human intervention in many cases has speeded up environmental degradation of the dry valleys. It is important to understand that dry valleys are climatic enclaves and an integrated approach that combines rehabilitation of degraded ecosystems and socio-economic development should be adopted if the overall goal of sustainable development of dry valleys is to be achieved. Promotion of niche-based cash crops, rural energy including hydropower, solar energy, biogas and fuelwood plantation is recommended as the priority activities.     

GMOs and their contexts: A comparison of potential and actual performance of GM crops in a local agricultural setting

In this paper, I argue that genetically modified organisms (GMOs) have inherent potential to contribute to socially and environmentally sustainable agriculture by virtue of their ‘biological embeddedness’. Their actual ‘performance’ and how this contributes to sustainability depends on the ‘mutual shaping’ of technology and context. While much attention has been given to the design context of GMOs, this paper considers the influence of the application context and of users. A case study investigating the use of insect-resistant and herbicide-tolerant GM cotton in the cotton-growing region of New South Wales in Australia is presented. The study was based on focus groups with farmers and other stakeholders in a cotton-growing community. It demonstrated a range of direct and indirect effects of GM cotton use, both positive and negative for sustainability, and the ways in which these effects were influenced by the local social context. The influences of the biotechnology industry context, in limiting the contributions that gene technologies can make to sustainability, were also considered, and remedies suggested. I argue that the polarity of the GM debate is hindering progress on these issues, and that a more balanced approach to our analysis of GMOs is necessary in order to fully understand, and to influence, their role in the future of rural spaces.     

GM（1，1）动态模型在吴江市地下水水位预测中的应用

以吴江市地下水水位预测为例,详细阐述了地下水水位时间序列的GM（1,1）动态模型的原理和建立过程,并根据模型的预测值和实测值,对模型的精度进行了检验,结果表明,模型的预测精度达到了99．27％,等级属于Ⅰ级,具有实际的应用价值,为地下水资源的科学管理提供了依据。     

19802000北京市农业土地生产性的变动分析

根据1980、1990、2000年的统计资料和实地走访观察,本文分析了北京市乡镇一级的粮食作物、蔬菜作物和果品作物的分布格局及农业土地生产性近20年的变化。研究认为:1980年北京农业生产分布格局与土地生产性为比较典型的杜能模式;随着农业经营的多样化,1990年和2000年北京农业土地生产性呈现出多样的分布格局;北京粮食作物、蔬菜作物、果品作物的分布格局及农业土地生产性近20年的变化与此阶段的农业生产政策、农业以外的社会经济活动变化有较强的关联性;对北京以上问题的研究为验证杜能、辛克利亚、布莱昂特城市周边农业地域研究经典理论的演变提供了实证案例。     

预测陕西关中地区需水量的改进GM(1,1)模型

需水量评价与预测是水资源规划与管理一项重要的研究内容。本文采用定额法计算需水量。通过对陕西关中地区需水量要素组成的分析,认为需水量要素属平稳时间序列,且一阶累加生成数据系列满足指数规律,符合灰色预测条件。为了提高GM(1,1)模型的精度,采用一种改变背景值的新方法,即:中心逼近方法。通过精度检验,中心逼近式GM(1,1)模型平均误差百分比、误差平方和分别比传统的GM(1,1)模型提高了0.147和1.579。用中心逼近式GM(1,1)模型预测需水量各要素近期和中长期值,经检验,其中非农业人口、农业人口、耕地面积、工业总产值预测模型满足一级模型,等级为良好。牲畜头数预测模型为不合格模型,分析其原因,主要是因为时间序列数据不完全符合指数规律。通过定额法计算,预计75%保证率时2005年和2010年关中地区工农业需水量分别占总需水量的92.21%和89.75%,生活需水量分别占7%和9.04%。     

广东省特色农作物标准波谱数据库框架设计与示范应用

本研究着眼于广东省典型特色农作物的波谱，建立了波谱数据库，该库分为知识库、遥感实测波谱库、模型库、波谱分析和 荔枝园示范5大部分。 在波谱分析模块设计上提供了波谱数据查询、分析等功能，通过对荔枝园种植面积应用示范，给用户提供了极 大方便。     

基于GM(1,1)优化模型的岩石边坡变形预报

岩石边坡系统是一典型灰色系统，其变形发展过程可以用灰色预测模型完成。尽管传统GM（1，1）模型预测有很多成功的实例，但是也存在一些预测偏差过大的情况，必须对其进行优化。逐步迭代法GM（1，1）模型不仅收敛速度快，而且与原始数据库序列的凹凸性保护一致。利用自编的计算程序对马步坎边坡预测测点G1沉降和开裂进行预测分析，结果表明逐步迭代法GM（1，1）优化模型计算精度较传统GM（1，1）模型和背景构造法GM（1，1）优化模型高，较好地反映了岩石边坡的变形趋势。     

灰色系统理论预测大气氮氧化物污染的应用

根据中国南方某省所辖城市近年来N0x污染指数的测量数据的统计资料，建立了GM(1，1）灰色预测模型，通过预测探讨了大气中氮氧化物指数的变化趋势。所建模型残差仅1．17％，关联系数为0．9067，精度较高，具有较好的可行性和适应性，可以为管理规则提供决策依据。     

灰色系统在地面沉降分析中的应用

该文将灰色系统理论引入地面沉降的研究之中。根据上海地面沉降的历史数据建立了上海地面沉降发展的GM(1,1)模型以及地面沉降与地下水位变化的映射GM(1,2)模型,最后运用所建立的模型对地面沉降的发展态势进行了预测。     

灰色GM(1,1)模型最优维数的研究

灰色GM(1,1)模型的维数对模型的预测精度有很大的影响,本文通过自编的FORTRAN程序,在合适的范围内对GM(1,1)模型的维数进行自动优化,通过对宁波市地面沉降数据的计算分析,得到了C和P的定性关系,确定了优化的评价标准,维数最优化后的模型能反映预测数列变化幅度的大小。