Critical environmental indicators: performance indices and assessment models for sustainable rural development planning

Sustainable development planning must be based on environmental and biophysical baseline indices that effectively define comparative development potential and environmental constraints. As such, indices must define the comparative advantage of the natural resource base and measure the fundamental capacity to sustain production rates of natural resource goods and services used to create societal well being. Complex biophysical and socioeconomic characteristics affect the identification and selection of sustainable development strategies. When derived from effective baseline indicators, indices may be used to define the spatial and temporal distribution of economically viable production opportunities and may be expressed in derived indices that realistically describe basic production opportunities and guide the selection of feasible, long-term development strategies. Specifically, representative indices are critical in the identification of development goals and realistic objectives and can be used to evaluate, select and implement sustainable development strategies and plans. It is stressed that the relevancy and effectiveness of public policies depend on the identification of representative evaluation models and baseline indices to define development strategies that are both environmentally sustainable and economically viable. In this context, the role of baseline indicators that define natural resource production capacities is discussed. This includes potential resource uses, derived benefits and their economic and environmental impacts. Key thematic indicators are suggested that may be especially useful in identifying development alternatives and impacts. This suggested that clearly defined environmental pollution limits or impact standards be used to define public risk tolerance limits and carrying capacity constraints. It is argued that these measures may be more effective in directing policy choices than economic valuation of non market goods and services that represent environmental externalities associated with resource exploitation options and economic development strategies. To this end, examples of thematic indicators and derived indices are introduced that may prove effective in resource assessment, economic evaluation and strategic development planning.     

The influence of potential reproductive rate and variation in mate quality on male and female choosiness in the sand goby, Pomatoschistus minutus

Recent models of choosiness in mate choice have identified two particularly important factors: the potential reproductive rate (PRR) of the choosing sex relative to that of the chosen sex, and the variation in quality of potential mates. This experimental study tested how these factors affected choosiness in male and female sand gobies, Pomatoschistus minutus. We manipulated relative PRR by means of water temperature, and mate quality by means of body length. The choosing male or female was offered a choice between two mates with either a small or a large difference in body length representing a small or a large variation in mate quality. Choosiness was measured as (1) preference for the larger mate, and (2) as whether or not spawning occurred with the smaller mate, while the larger mate was visible but screened off. We found that females preferred large males, and that their level of choosiness was affected by variation in male quality, but not by their own relative PRR. Males, on the other hand, seemed unselective in all treatments and were in general more likely than females to spawn with their provided partner. This suggests that in the sand goby, variation in male mate quality has a greater influence than relative PRR on facultative changes in female choosiness. However, a general difference in PRR between males and females may be one important factor explaining the observed sex difference in choosiness. Received: 17 April 2000 / Revised: 24 June 2000 / Accepted: 17 July 2000     

电磁环境对采后芒果的生理影响

系统研究了采后芒果在静电场,磁场,放电生成气环境下的生理变化。测试了呼吸速率,果体与果皮电解质渗出率,商品果率与病情指数等生理指标。研究结果表明,采后芒果在呼吸速率达到高峰之前电磁环境对其均有明显的作用,而在呼吸高峰之后,无明显影响。在我们设置的电磁环境参数中有几项显示保鲜作用。表１参６     

柚园间种作物及施用不同有机肥对土壤与柚果的影响

柚树间种短期经济作物在提高柚园经济效益的同时,还可提高土壤的有机质和N、P、K养分质量分数,改善柚园小区气候,增加有机肥来源。间种物残余体作为绿肥,可显著地提高柚果产量和质量。     

水质丁基黄原酸测定难点探讨

丁基黄原酸是水质监测的重要项目之一。水中丁基黄原酸的测定,在样品采集保存、前处理及仪器分析各阶段都存在一定的技术难点。实际分析时很容易出现测定结果不理想,甚至定性定量错误等问题。结合实验对丁基黄原酸测定中容易出现的问题及注意事项进行探讨,正确区分丁基黄原酸及其盐,有效保存样品,采用低损失的前处理方法以及选择性好的分析仪器,有利于提高丁基黄原酸测定的准确性。众多丁基黄原酸测定方法中,液相色谱质谱法、离子色谱法以及液相色谱法在选择性和灵敏度方面更具优势,也可用于其他方法检出丁基黄原酸时对测定进行确认。     

基于SHERPA的环境空气质量减排情景模拟评估

分析了SHERPA综合评价模型的基本原理和主要建模理念,重点介绍了其在环境空气质量减排情景模拟评估方面的作用,以及在排放源与受体关系(SRR)方面的处理方法,比较了其与欧盟常用的其他情景模拟模型的优缺点。SHERPA模型的特点是空间灵活性较好,对于任何给定地点,可以快速评估不同地区对该研究地点空气质量的影响。SHERPA模型的3个主要功能为污染物来源分析、决策支持和情景模拟。基于SHERPA模型对法国环境空气中PM_(2.5)、PM_(10)和NO_2年均浓度进行污染来源分析、决策支持分析和减排情景模拟评估,展示了模型在环境治理措施优先级筛选和政府间联合治理措施协调建议方面的功能和作用,以期为中国环境空气质量预测预报、环境质量管理措施的制定和成效评估等环境服务与管理工作提供借鉴。     

河流水质自动监测站选址适宜性评价

为建立和量化适于河流水质自动监测站选址的评价方法体系,提出了河流水质自动监测站选址一致性、可行性和适宜性评价问题,并建立了选址可行性和适宜性评价2套指标体系。以自动站选址与手工断面位置不一致为前提,利用累乘指数判断选址可行性,在可行的基础上利用模糊综合评价进一步分析选址的适宜性。应用案例显示,罗汉大桥断面水质自动站选址于手工断面下游150 m处是可行的,并且此选址高度适宜,在具有水质代表性的同时兼顾成本和运维管理需求。     

衡阳市区和衡山背景站臭氧浓度变化规律的对比分析

选取衡阳市区和衡山背景站臭氧自动监测数据,分析两地的臭氧污染特征。对空气质量的优良率情况、臭氧作为首要污染物的变化情况、臭氧浓度的日变化特征、典型时段的浓度变化特征、臭氧浓度的月际变化特征和臭氧与PM_(2.5)的关联情况等进行了分析。结果表明,多云及阴雨天气时,衡阳市区的臭氧浓度日变化幅度大于衡山背景站。夏季,衡阳市区和衡山背景站的臭氧浓度的日变化特征规律差异较大,臭氧浓度分布比较分散,前者为典型的单峰形,后者则波动平缓。冬季,日变化幅度不大,但衡阳市区的臭氧浓度明显低于衡山背景站。衡山背景站和衡阳市区的臭氧基本同步变化,但日均值高于衡阳市区。     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取;提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列;发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性;构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测;在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

气相色谱法测定水质中的内吸磷

优化了气相色谱法测定水质中的内吸磷,当取样量为100 m L时,内吸磷-O方法检出限为0. 30μg/L,测定下限为1. 20μg/L;内吸磷-S方法检出限为0. 80μg/L,测定下限为3. 20μg/L。内吸磷-O和内吸磷-S标准曲线线性良好,相关系数分别为0. 999 2和0. 999 8。不同水质中内吸磷-O的加标回收率为90. 3%～104%,相对标准偏差为3. 6%～9. 2%;内吸磷-S的加标回收率为92. 1%～94. 9%,相对标准偏差为4. 6%～8. 7%。该方法灵敏度高,能有效分离内吸磷-O和内吸磷-S,同时能将内吸磷-O、内吸磷-S与其他有机磷农药类干扰物分离。