Effects of arsenic on seed germination and physiological activities in wheat seedlings

The effects of arsenic(As)were investigated on seed germination,root and shoot length and their biomass and some other factors to elucidate the toxicity of As.The results showed low concentrations of As(O-1 mg/kg)stimulated seed germination and the growth of root and shoot,however,these factors all decreased gradually at high concentrations of As(5-20 mg/kg).The contents Of O2-,MDA,soluble protein and peroxidase(POD)activity all increased with increasing As concentrations.Soluble sugar content,ascorbate peroxidase(APX),and superoxide dismutase(SOD)activities decreased at low concentrations of As,and increased at high concentrations of As.While acetylsalicylic acid(ASA)and chlorophyll contents,catalase(CAT)activity displayed increasing trend when the concentrations of As was lower than 1 mg/kg,and then decreasing trend.By polyacrylamide gel electrophoresis(PAGE).As induced the expression of POD isozymes of wheat seedlings.As induced the expression of CAT isozymes but inhibited the expression of SOD isozymes of wheat seedlings at concentrations lower than 1 mg/kg.However,As inhibited the expression of CAT isozymes but induced the expression of SOD isozymes at concentrations higher than 5 mg/kg.The results indicated As could exert harmfulness in the early development stage of wheat at inappropriate concentrations.     

移动脚手架升降作业的FMECA分析

利用FMECA(故障模式,影响及危险度分析)方法回顾了升降作业的典型事故,阐述了架体结构和升降作业流程,对移动脚手架升降作业进行了故障类型、影响及危险度分析,认为保障移动脚手架升降施工作业安全的重点是:保证防坠装置的有效可靠性、维护防护装置的功能完整性、确保提升机构和架体结构的整体稳定性。     

Uncertainty Reduction of the Flood Stage Forecasting Using Neural Networks Model1

Abstract: The Elman Discrete Recurrent Neural Networks Model (EDRNNM), which is one of the special types of neural networks model, is developed and applied for the flood stage forecasting at the Musung station (No. 1) of the Wi‐stream catchment, which is one of the International Hydrological Program representative basins, Korea. A total of 135 different training patterns, which involve hidden nodes, standardization process, data length, and lead‐time, are selected for the minimization of the architectural uncertainty. The model parameters, such as optimal connection weights and biases, are estimated during the training performance of the EDRNNM, and we apply them to evaluate the validation performance of the EDRNNM. Sensitivity analysis is used to reduce the uncertainty of input data information of the EDRNNM. As the results of sensitivity analysis, the Improved EDRNNM consists of four input nodes resulting from the exclusion of Dongkok station (No.5) in initial five input nodes group of the EDRNNM. The accuracy of flood stage forecasting during the training and validation performances of the Improved EDRNNM remains the same as that of the EDRNNM. The Improved EDRNNM, therefore, gives highly reliable flood stage forecasting. The best optimal EDRNNM, so called the Improved EDRNNM, is determined by elimination of the uncertainties of architectural and input data information in this study. Consequently, we can avoid unnecessary data collection and operate the flood stage forecasting system economically.     

全球系统科学若干问题

全球系统科学是一门关于人类圈同地球圈层关系的学问。本文主要讨论(1)全球系统科学的研究对象;(2)全球系统的进化规律;(3)地球的最新圈层,(4)地球演化的新突变期;(5)全球问题的实质和前景等问题。     

MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.     

云南稻核心种质苗期与孕穗期耐冷性特点及关系分析

以544份云南地方稻核心种质为材料,在昆明自然低温(苗期平均5.5～12.3℃,孕穗期平均17.8℃)冷害下,按籼粳、稻作区进行云南稻核心种质苗期耐冷性与孕穗期耐冷性的特点及关系研究.结果表明:(1)苗期耐冷性与孕穗期耐冷性密切相关,苗期耐冷性强的材料表现为孕穗期株高、剑叶长和宽、穗颈长、穗下节长、1～2节长、穗长较长、穗粒数较多,耐冷性较强.通过对苗期耐冷性的严格选择,可以间接获得孕穗期耐冷性较强的材料.(2)苗期和孕穗期耐冷性在籼粳间、稻作区间差异明显.籼粳间均表现为粳稻强于籼稻;稻作区间苗期耐冷性为滇中一季籼粳稻区和滇南单双季籼稻区最强,滇中一季籼粳稻区和滇西北高寒粳稻区孕穗期耐冷性较强,揭示了水稻苗期与穗期耐冷性的形成演化机制存在一致性和差异性.     

Case studies of conservation plans that incorporate geodiversity

Geodiversity has been used as a surrogate for biodiversity when species locations are unknown, and this utility can be extended to situations where species locations are in flux. Recently, scientists have designed conservation networks that aim to explicitly represent the range of geophysical environments, identifying a network of physical stages that could sustain biodiversity while allowing for change in species composition in response to climate change. Because there is no standard approach to designing such networks, we compiled 8 case studies illustrating a variety of ways scientists have approached the challenge. These studies show how geodiversity has been partitioned and used to develop site portfolios and connectivity designs; how geodiversity‐based portfolios compare with those derived from species and communities; and how the selection and combination of variables influences the results. Collectively, they suggest 4 key steps when using geodiversity to augment traditional biodiversity‐based conservation planning: create land units from species‐relevant variables combined in an ecologically meaningful way; represent land units in a logical spatial configuration and integrate with species locations when possible; apply selection criteria to individual sites to ensure they are appropriate for conservation; and develop connectivity among sites to maintain movements and processes. With these considerations, conservationists can design more effective site portfolios to ensure the lasting conservation of biodiversity under a changing climate.     

开花后小麦地上部镉、砷分布及其转运特征

为了探明小麦开花后叶片和茎节对籽粒中镉(Cd)和砷(As)累积的影响效应,采用田间小区试验,研究了山农28(SN28)和济麦22(JM22)两个小麦品种地上部各器官Cd和As的分布规律和迁移特征.结果表明,在灌浆期,小麦地上部的Cd主要分布在节中,Cd由节间3到节2、节间2到节1和叶鞘1到节1的转运能力显著强于其他部位.在成熟期,Cd主要分布于叶片中,Cd由叶鞘到叶片和由节1到穗轴的转运能力显著增强.此外,JM22中颖壳到穗轴和穗轴到籽粒的Cd转运能力显著低于SN28,使JM22的穗轴、颖壳和籽粒中Cd含量与SN28相比分别显著降低了22.3%、 40.8%和44.4%.同时,从灌浆期到成熟期小麦地上部的As主要分布于叶片中,且JM22颖壳和籽粒中As含量显著低于SN28,降幅分别为25.8%和33.3%.在灌浆期和成熟期,小麦中As转运系数由叶鞘到节显著高于叶到叶鞘和节到节间,平均增幅为438%和190%.此外,JM22中As由颖壳到籽粒和穗轴到籽粒的转运系数分别比SN28显著降低40.6%和44.4%.总之,开花后小麦旗叶、节1和穗轴调控了Cd转运及其在籽粒的累积,而小麦的叶3、旗...     

通过多阶段暴露试验评价嘧菌酯对斑马鱼的急性毒性与发育毒性

嘧菌酯作为最畅销的甲氧丙烯酸酯类杀菌剂,是防治水稻病害的常用农药,其对水生生态环境的负面效应值得重视.为研究嘧菌酯对水生生物的危害,进行多阶段(成鱼、仔鱼、胚胎)斑马鱼毒性试验,分析了嘧菌酯对鱼类的急性毒性,同时,通过6 d胚胎发育试验,研究了嘧菌酯对鱼类早期发育阶段的影响.结果表明,斑马鱼3个生命阶段对嘧菌酯的敏感性(以96 h-LC50(致死中浓度)表示)顺序为:仔鱼(0.39 mg·L~(-1))胚胎(0.61 mg·L~(-1))成鱼(1.37 mg·L~(-1)).6 d胚胎发育试验结果发现,嘧菌酯可诱导斑马鱼胚胎出现一系列不良症状,包括孵化率下降、心率异常、生长抑制和心包水肿等.0.25 mg·L~(-1)的嘧菌酯可显著促进斑马鱼胚胎自主运动和心率,并能明显抑制孵化仔鱼的体长.0.6 mg·L~(-1)及更高浓度的嘧菌酯可明显抑制斑马鱼胚胎眼睛、体节、尾部和心脏的发育.研究显示,嘧菌酯对斑马鱼多个生命阶段均具有一定毒性,但对早期生命阶段毒性更强,因此,其对鱼类早期生命阶段的影响值得重视.     

Understanding the Factors That Influence Headwater Stream Flows in Response to Storm Events1

Stanfield, Les W. and Don A. Jackson, 2011. Understanding the Factors That Influence Headwater Stream Flows in Response to Storm Events. Journal of the American Water Resources Association (JAWRA) 1‐22. DOI: 10.1111/j.1752‐1688.2010.00518.x Abstract: Headwater drainage features (first‐ to second‐order streams) are the capillaries of the landscape that, among other things, moderate the timing and volumes of water available to the riparian and aquatic ecosystems. How these features respond to summer rainfall is poorly understood. We studied how geology and an index of land use/land cover influenced peak flows following rainfall events in 110 headwater stream sites that were studied over a four‐month period during a drought year. Highest peak flows were observed in the most urbanized catchments and in poorly drained soils, but specific responses were variable depending on both geology and land disturbance. Redundancy analysis indicated that both surficial geology and land disturbance were important factors influencing peak flows under drought conditions. We conclude that responses of these headwater streams to individual storms during drought conditions are unpredictable from data collected using our methods, but increased peak flows were associated with increased urban and agricultural development, but mitigated by surficial geology. These findings demonstrate the challenges to accurately predict flow conditions in headwater streams during periods of extreme weather that concurrently have the greatest potential effect on biota. The combination of these challenges and importance of such events indicates the need to develop new approaches to study and manage these resources.