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).     

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.      

尕海湿地植被退化过程中有机碳及相关土壤酶活性变化特征

以青藏高原东缘尕海湿地不同植被退化程度样地为研究对象,采用定位研究与室内试验相结合的方法,研究植被退化过程对土壤有机碳和土壤酶活性的影响。结果表明：植被退化显著影响土壤有机碳含量和土壤酶活性,降低了土壤有机碳的含量和酶促反应效率,且这种影响随土层深度变化有所不同。四种植被退化阶段有机碳含量和酶活性均值总体上（0~100 cm）表现为未退化>轻度退化>中度退化>重度退化。不同土层中,20~40 cm土层的有机碳含量中度退化>轻度退化;0~10 cm土层中淀粉酶和纤二糖酶中度退化阶段活性值较高;20~100 cm土层中蔗糖酶重度退化阶段活性值最高,纤二糖酶活性重度退化>中度退化。同一退化程度土壤有机碳含量、蔗糖酶和纤二糖酶活性随土层深度增加显著降低（P<0.05）;淀粉酶和纤维素酶活性在>40 cm土层中活性值有所上升,整体呈波动下降趋势。     

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.     

基于地形位置指数的赤水河流域植被时空变化研究

地形因子和植被覆盖是区域灾害评价的关键指标,也是山区型村镇建设生态安全评估的重要内容.为探析山区型村镇建设的生态约束条件,以赤水河流域为研究对象,基于1998—2018年SPOT_VGT NDVI数据,利用地形位置指数（Topographic Position Index,TPI）和坡度位置指数方法,研究了赤水河流域植被生长季NDVI时空变化及地形分异特征.结果表明:①赤水河流域内,1998—2018年植被生长季平均NDVI呈缓慢上升趋势,斜率为0.004 7;NDVI>0.60的集中连片区域主要分布在古蔺县北部、赤水市大部和习水县西北部,占赤水河流域总面积的8.42%;Sen's slope在0.009~0.015区间时,赤水河流域植被生长增强趋势最明显,主要集中分布在赤水河中上游、二道河以及下游的大同河干流地区.②TPI在-39.4~34.3区间的面积最多,为6 221.63 km2,占赤水河流域总面积的34.05%;将赤水河流域坡度类型划分为山脊、上坡、中坡、平坡、下坡、山谷6个坡度位置类型,其中,中坡面积（7 792.02 km2）最大,占流域总面积的42.64%,表明TPI数值较小且坡度大于5°的区域是赤水河流域地形主体.③赤水河流域植被在山脊的平均NDVI最高,为0.747,且山脊平均Sen's slope最高,为0.007 2;山谷平均NDVI最低,为0.709.研究显示,赤水河流域植被分布在118.5~486.9的TPI区间或分布在山脊处时整体生长较好,且生长增强趋势最明显.      

基于高分1号影像的森林植被信息提取

实时最新森林植被信息的提取是林业航空植保作业的必要前提。论文以安徽省蚌埠市为研究区域,探讨了基于高分1号卫星遥感数据在亚热带农林植被混合地区的森林植被信息提取。根据植被物候信息差异选择了提取森林植被信息的5个关键时期高分影像,采用分区决策树方法监测森林植被的空间分布和面积信息,并与未分区决策树法的提取结果进行比较。结果表明：采用分区决策树法和未分区决策树法对于大中尺度森林植被信息提取的总体精度均优于85%。但分区决策树森林植被提取总体精度达到90.72%,较未分区决策树法提高3.80%、4.65%,Kappa系数达到0.81,较未分区决策树法提高约0.07~0.10,结合植被物候信息的分区决策树森林植被提取法好于未分区决策树法,能够满足林业航空植保作业的精度需求。具有较高空间分辨率、宽覆盖、短重访周期的高分1号影像,对于大区域的林业航空植保当年最新森林植被信息的提取表现出较大的潜力。     

兰州市南山季节性土壤微生物特征及影响因素

为了探究不同季节和不同植被类型对土壤微生物分布的影响,以兰州市南山不同海拔的两种植被类型为研究对象,采用稀释涂布平板法测定了土壤微生物的季节动态变化特征.结果表明：研究区内细菌数量占微生物总数的96.22%~99.80%,远高于真菌和放线菌数量.土壤微生物类群随季节变化呈现明显差异,其总数整体表现为夏季最高,为89.22×10⁶cfu/g soil,分别是春、秋、冬季的12.02、3.28、2.74倍,其中夏季细菌数量最高,真菌与放线菌数量均在春季达到最大值.人工林样地土壤微生物数量略低于荒坡,环境因子中土壤含水量和有机碳含量高于荒坡.随着海拔的升高,pH值逐渐上升,土壤温度、有机碳与全氮含量逐渐下降,土壤微生物总数则呈现先减少后增加的趋势.相关分析表明,不同季节各微生物类群与环境因子的相关系数各有不同,春季放线菌与有机碳,秋季真菌与有机碳、全氮均呈极显著正相关（P<0.01）.冗余分析表明,环境因子中有机碳与第一物种轴的相关系数最高,为0.520,说明土壤有机碳含量是影响土壤微生物类群分布的主导因素.     

A Survey of Trace Metals in Vegetation, Soil and Lower Animal Along Some Selected Major Roads in Metropolitan City of Lagos

The concentration of trace metals (Cd, Cu, Pb and Zn) in a total of 144 samples of grass, soil and lower animal (earthworm, Lybrodrilus violaceous) were collected and analysed for their metallic content. Levels of cadmium ranged from 0.01–0.07 g g^–1; 0.01–0.12 g g^–1 and from trace–0.05 g g^–1 dry weight for plant, soil and animal samples respectively. Mean concentration of copper ranged 0.10–1.48 g g^–1; 0.10–2.90 g g^–1 and 0.01–0.08 g g^–1 for samples in similar order as above. The levels of Pb varied from 0.01–0.14 g g^–1; 0.02–0.23 g g^–1 and from trace–0.07 g g^–1 while that of Zn ranged from 0.19–1.80 g g^–1; 0.51–3.35 g g^–1and 0.01–0.08 g g^–1 also in the same order of samples as mentioned above. Levels of metals in soil samples were higher than the background levels with the exception of Zn but lower than European Union (EU) limits. The results generally revealed the presence of metals in plant and animal samples and metal dynamics up the food chain is highly possible. Acceptable recoveries of the spiking experiment validate the experimental protocol.     

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.