Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

Stability of a Coal Waste Artificial Reef

The feasibility of using U.K. coal-fired power station waste materials for artificial reef production is being examined. in June, 1989, an experimental artificial reef was constructed in Poole Bay, off the central south coast of the U.K., using three different mixtures of pulverised fuel ash (PFA), flue gas desulphurisation (FGD) gypsum and slurry, stabilized with cement and formed into blocks. Fifty tonnes of 40 × 20 × 20 cm blocks were formed into eight conical reef units replicating three different PFA/gypsum mixtures and one concrete control. the reef structure is 10m below chart datum on a flat sandy sea-bed.

Combustion of coal concentrates the heavy metal content in the resultant ash. the purpose of stabilization of the ash as blocks is twofold: to immobilize heavy metals (or other components) and to provide hard substratum for the attachment of organisms. to examine the effectiveness of this stabilization and hence the environmental compatibility of the block materials, heavy metal (Cd, Cr, Cu, Pb, Mn, Ni, Zn) content of the blocks has been monitored routinely over two years, to determine leaching rates. Sectional profiles indicate partial replacement of calcium content by magnesium. Associated with this there has also been some redistribution of heavy metals. Only in the case of cadmium has there been a detectable loss from the surface of blocks. Chromium and manganese concentrations appear to have increased. the metal content of the reef epibiota (including ascidians, Ascidia mentula; hydroids, Halecium spp.; bryozoans, Bugula spp. and red algae) growing on the ash blocks has been compared to that of epibiota attached to the concrete controls and surrounding sea-bed. to date no evidence of excess bioaccumulation of metals has been detected.

The physical integrity of the ash reef blocks has been maintained. There is evidence that the blocks are increasing in compressive strength.

An indication of the fishery enhancement potential of the experimental structure is given by the presence of eight commercially fished species (crustaceans and molluscs) including lobsters (Homarus gammarus).     

湖泊水质模型研究进展

湖泊是最重要的淡水资源之一，对社会和经济的发展起着不可估量的作用。保护和改善湖泊水环境问题已成为当前世界关注的一个焦点。湖泊水质模型是一种利用数学语言来描述湖泊污染过程中的物理、化学、生物化学及生物生态各方面之内在规律和相互联系的手段。作为湖泊水环境污染治理、规划决策分析中的一个重要工具，它可以为湖泊的综合整治和科学管理提供科学的依据，在环境保护领域中发挥着举足轻重的作用。分别介绍了湖泊水质模型国内外研究动态、类型、常用软件（WASP、EFDC、CE QUAL W2、CE QUAL R1、CE QUAL ICM、MIKE、SMS等）和应用实例，并综观湖泊水质模型的研究历史和应用前景，系统分析了湖泊水质模型研究的发展趋势。     

北方湖库沉积物重金属区域特征及生态风险评价

以白洋淀、衡水湖、于桥水库、松花湖、大伙房水库和小兴凯湖沉积作为研究对象,通过对北方六湖库沉积物中Cu、Zn、Pb、Cr、Ni等重金属元素进行分析,并与国内外其他水域重金属污染情况进行多因素比较,探讨了六湖库主要重金属污染源的差异性,区域分布特征以及与国内外其他水域污染的相似性和区别.结果表明,六湖库沉积物重金属污染处于中等偏下水平.六湖库之间主要重金属污染源存在差别.沉积物重金属含量未出现明显上升的趋势.其中Zn、Pb存在富集现象,但Pb含量与历史数据相比出现下降,Zn的含量与其他地区相比整体偏高.大伙房水库沉积物重金属污染较重,Cu、Zn、Pb、Cr、Ni含量平均值分别为56.28,142.3,17.44,97.9,44.44mg/kg.小兴凯湖沉积物重金属含量最低,Cu、Zn、Pb、Cr、Ni含量平均值分别为2.41,63.90,13.37,56.36,26.09mg/kg.六湖库综合风险评价结果为大伙房水库>于桥水库>白洋淀>衡水湖>松花湖>小兴凯湖,重金属整体潜在生态风险指数为低.     

人工智能技术对长江流域水污染治理的思考

随着经济的快速发展和城市化进程的不断加速,促使水污染严重的长江流域需从污染物去除过程的建模与优化、污水处理过程的优化控制、水污染监测系统的构建开展水污染治理研究.传统的水污染处理技术存在污染物去除效率预测精度较低、污水优化控制成本较高、水污染监测滞后效应严重的问题.人工智能技术能够有效克服上述问题,因此通过梳理国内外学者利用人工智能技术在污水污染物去除过程的建模与优化、污水处理过程的优化控制及水污染监测系统的构建等方面的研究成果,为全面加强长江流域水污染治理能力提供科学可靠的技术指导.结果表明:①利用人工神经网络技术（径向基神经网络、多层前馈网络-人工神经网络、多层感知器神经网络）对污水污染物去除过程进行建模与优化,为精确预测长江流域重金属（Cr、Cu）、营养盐（TN、TP）、持久性有机污染物〔PBDEs（多溴二苯醚）、HCH（六氯环己烷）〕的去除率提供重要参考价值.②采用污水处理的自动控制技术与人工智能技术（递归神经网络、支持向量机、模糊神经网络等）构建污水智能控制系统,为长江流域实现高效节能的污水优化控制提供重要的技术指导.③利用在线监测仪器和人工智能技术（小波神经网络、多元线性回归-人工神经网络、叠层去噪自动编码器等）建立水污染智能监测系统,为解决长江流域水污染监测响应滞后问题提供有力的技术支持.因此,人工智能技术对长江流域提高污水污染物去除率,降低污水优化控制成本,提升水污染监测时效性具有重要的推广价值.      

中国淡水生态系统甲烷排放基本特征及研究进展

本文基于中国境内的湖泊、水库、河流等淡水系统CH₄排放研究的相关成果,对203个湖泊（595个样点）、46个水库（221个样点）、112条河流（441个样点）,总计1257个样点的CH₄通量数据进行统计分析,探讨了中国淡水系统（湖泊、水库、河流）CH₄排放的一般特征,总结了当前研究进展,并进一步估算和评估了中国淡水系统CH₄排放总量水平.结果表明：1）中国湖泊CH₄排放通量平均为（1.17±1.87） mg/（m²·h）,蒙新湖区（（3.84±0.57） mg/（m²·h））和东北湖区（（2.62±3.54） mg/（m²·h））较高,青藏湖区（（1.94±4.13） mg/（m²·h））次之,东部湖区（（0.81±0.90） mg/（m²·h））较低,云贵湖区（（0.19±0.26） mg/（m²·h））最低;湖泊CH₄排放通量呈显著的纬度模式,高纬度地区湖泊CH₄排放高于低纬度地区;2）水库CH₄排放通量（（1.25±1.78） mg/（m²·h））与湖泊相似,水库消落带较高的排放通量（（4.34±4.45）mg/（m²·h））对水库CH₄排放具有重要贡献;3）河流CH₄排放（（0.82±1.14） mg/（m²·h））略低于湖库,长江水系CH₄排放通量（（0.98±2.38） mg/（m²·h））和黄河水系（（0.85±0.75） mg/（m²·h））相近,高于海河水系（（0.54±0.93） mg/（m²·h））,辽河、珠江水系研究较少,数据变异性极大;4）受降水、温度、径流稀释等影响,淡水系统CH₄排放呈显著的季节变化,其中湖库排放夏季高于秋季,冬春季较低,而河流则春秋季高于夏冬季;5）基于外推法估算全国湖泊、水库、河流CH₄排放总量分别约为0.96,0.29,0.76Tg/a,相当于全国湿地系统排放的75%.由于较大的时空变异性以及监测数据分布的不均匀性,目前估算存在较大的不确定性,但淡水系统CH₄排放在全球气候变化中的贡献仍不容小觑.     

基于神经网络的东北地区秸秆焚烧预测

选取农作物秸秆露天燃烧严重的东北地区,采用人工神经网络的方法,结合卫星火点和气象数据,开展秸秆露天燃烧预测研究.结果表明：人工神经网络预测模型成功验证了松嫩平原地区2015年10月25日~11月15日的秸秆露天燃烧情况,其准确度为67.1%,经过多次试验,在神经网络建模与验证数据配比为80：20时,预测准确度最高,可达69.7%,同时该模型的稳定性较好.而对不同区域,不同时间段的预测研究表明,人工神经网络较适用于长时间序列的预测.就影响因素而言,相对湿度是影响秸秆露天燃烧的最重要因素.本研究结果可为空气质量模式提供火点预测数据,提高其预报预警能力,为区域联防联控政策的制定提供科技支持.     

博斯腾湖富营养化状态水平调查

通过水质特征和生物学特征的一个水文年规范化实地调查,采用Scirgesew参数分类标准和相关加权综合营养状态指数,对博斯腾湖水体富营养化状态水平进行了调查和评价。     

乌伦古湖水质现状及污染防治对策

着重对乌伦古湖所监测的项目作了全面系统的分析，评价了该湖的水环境质量，指出乌伦古湖水质的主要问题是严重咸化，这是该湖可持续发展的最大障碍。并指出做好湖区规划，增加水源供给，加强污水处理和湿地建设，是乌伦古湖未来发展的有利措施。     

Land User Participation in Developing a Computerised Decision Support System for Combating Desertification

Combating desertification in natural rangelands has recently become a priority in large parts of southern Africa. Rangeland managers, farmers, scientists, conservationists and land users have been applying a variety of restoration technologies to address this problem. Bush encroachment, as part of the desertification process, involves the natural replacement of the herbaceous plant cover by undesirable problem woody species. The active and passive restoration technologies that are applied, are mainly based on indigenous knowledge and include the chemical, mechanical or manual reclamation of unproductive rangelands, as well as the combating of woody and alien species encroachment. Indigenous practices and knowledge play a major role in the effectiveness and success rate of these technologies. This project faces the challenge of bringing together both local and scientific knowledge in a single user-friendly, computerised Decision Support System (DSS) which is directly accessible by land users to support them in the process of decision making, concerning the combating of desertification. Case studies from central and northern Namibia were used to combine qualitative and quantitative data to develop this Decision Support System. The DSS currently consists of two databases and an expert system, which evaluates the results of land users’ management practices, and provides easily accessible information and advice for participants in the system, based on the incorporated data. The DSS is also linked to national and international web sites and databases to offer a wider range of information on technologies concerning agricultural and conservation practices.