社会发展的软件建设

本文认为社会发展的软件建设,首先要研究制定社会发展的战略与规划,并把握战略的全局谋划和規划的总体安排;其次是以人为主体,将提高人的素质作为社会发展的基础,来促进社会发展的良性循环;再者以深化改革促进社会发展过程中人与自然的协调共存,逐步形成社会发展的良性运行机制;最后是探索管理模式,保证社会持续发展。     

A MONTE CARLO TEST OF LOAD CALCULATION METHODS,LAKE TAHOE BASIN,CALIFORNIA‐NEVADA1

ABSTRACT: The sampling of streams and estimation of total loads of nitrogen, phosphorus, and suspended sediment play an important role in efforts to control the eutrophication of Lake Tahoe. We used a Monte Carlo procedure to test the precision and bias of four methods of calculating total constituent loads for nitrate‐nitrogen, soluble reactive phosphorus, particulate phosphorus, total phosphorus, and suspended sediment in one major tributary of the lake. The methods tested were two forms of the Beale's Ratio Estimator, the Period Weighted Sample, and the Rating Curve. Intensive sampling in 1985 (a dry year) and 1986 (a wet year) provided a basis for estimating loads by the “worked record” method for comparison with estimates based on resampling actual data at the lower intensity that characterizes the present monitoring program. The results show that: (1) the Period Weighted Sample method was superior to the other methods for all constituents for 1985; and (2) for total phosphorus, particulate phosphorus, and suspended sediment, the Rating Curve gave the best results in 1986. Modification of the present sampling program and load calculation methods may be necessary to improve the precision and reduce the bias of estimates of total phosphorus loads in basin streams.     

铁矿周边地下水金属元素分布及健康风险评价

以崇左市红阳村、两岸村、亭乐村和孔甲村所在地为研究区域,对该区域内某铁矿周边30个地下水样品中12种金属元素（Hg、Mn、Fe、Al、Zn、Ni、As、Pb、Cr、Cd、Co、Cu）进行测定和分析,运用多元统计的方法和健康风险评价模型研究了地下水金属元素的分布特征及其引起的健康风险.结果表明,地下水中Zn和Fe平均浓度（250.32,103.96μg/L）较高,Hg、Mn、Fe、Al和Zn超过了《地下水质量标准》（GB/T 14848-2017）规定的Ⅲ类标准限值.Fe、Mn、Al高浓度主要分布在红阳村和亭乐村,Zn、Hg高浓度主要分布在红阳村和两岸村.多元统计分析表明,Fe、Mn、Al、Pb、As、Co元素主要来源于铁矿开采,Cu、Zn、Cr、Ni元素主要与铅锌矿的开采与区域地质背景有关,Hg主要来源于本底值及糖厂和造纸厂等企业污染,Cd主要来源于自然源.健康风险评价表明,两岸村地下水金属元素引起的健康总风险（8.82×10^-5a^-1）最高,儿童健康总风险大于成人,经饮水途径引起的健康风险比皮肤接触途径高2~3个数量级,Cr的致癌风险接近或高于最大可接受风险水平5.0×10^-5a^-1,非致癌风险水平在10^-14~10^-9a^-1,低于最大可接受风险水平4~9个数量级.     

降雨型泥石流（水石流）预报模型研究

根据泥石流暴发具有某种周期性的特点，在获取了大量野外调查资料和历史资料的基础上，对降雨型泥石流进行了预报模型研究，并以北京市北部山区密云县为例作了泥石流预报尝试。以层次分析法和多元回归方法所得出的泥石流空间预报和时间预报模型对于泥石流的预报具有重要意义。     

复杂DNAPL污染源区溶解相污染通量的升尺度计算

重非水相液体(DNAPL)污染场地中NAPL相污染物会持续溶解于地下水中,释放出溶解相污染羽,对人体健康产生威胁.准确评估DNAPL污染场地源区下游的溶解相污染通量至关重要.由于介质的非均质性常形成复杂DNAPL污染源区,其溶解相污染通量往往呈现出阶段性变化.目前溶解相污染通量计算普遍采用Christ等提出的双域升尺度模型,但该模型仅适用于弱非均质性的污染源区.本文基于大量强非均质性条件下的污染源区数值算例,修正了Christ双域模型中污染源区衰减指数的经验公式,将该模型的适用范围推广至强非均质性的复杂污染源区.通过蒙特卡罗数值算例及两个二维砂箱试验数据验证了修正模型的适用性和精度.对比结果表明:修正模型可广泛适用于不同结构的复杂DNAPL污染源区,与以往的计算方法相比,修正模型计算的溶解相污染通量精度提高了约35%.     

Source apportionment of polycyclic aromatic hydrocarbons (PAHs) in a sediment core from Lake Dagze Co, Tibetan Plateau, China: Comparison of three receptor models

Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons (PAHs) in multiple environmental media. In this study, three different receptor models (including the principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and Unmix models) were used to apportion the sources of 16 priority PAHs in a sediment core of Lake Dagze Co. The ∑PAHs (sum of all 16 measured PAHs) concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g. The ∑PAHs were dominated by 2-3 ring PAHs, accounting for 80.12% on average, thereby indicating that they mainly originated from biomass and coal combustion and/or from long-range atmospheric transportation. The three models produced consistent source apportionment results. The greatest contributor to ∑PAHs was biomass combustion, followed by coal combustion, vehicle emissions, and petrogenic sources. Moreover, the temporal variation of the common sources was well-correlated among models. The multi-method comparison and evaluation results showed that all three models were useful tools for source apportionment of PAHs, with the PMF model providing better results than the PCA-MLR and Unmix models. The temporal trends of factor contributions were verified by PAHs with different ring numbers. Significant correlations were found between the simulated concentrations of each source factor and the PAHs with different ring numbers (P<0.01), except for the petrogenic source identified by the Unmix model (P>0.05). This study can provide useful information for further investigation of source apportionment of PAHs in the sediment cores.     

A guide to representing variability and uncertainty in biodiversity indicators

Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.     

Incorporating Climate Science in Applications of the U.S. Endangered Species Act for Aquatic Species

Aquatic species are threatened by climate change but have received comparatively less attention than terrestrial species. We gleaned key strategies for scientists and managers seeking to address climate change in aquatic conservation planning from the literature and existing knowledge. We address 3 categories of conservation effort that rely on scientific analysis and have particular application under the U.S. Endangered Species Act (ESA): assessment of overall risk to a species; long‐term recovery planning; and evaluation of effects of specific actions or perturbations. Fewer data are available for aquatic species to support these analyses, and climate effects on aquatic systems are poorly characterized. Thus, we recommend scientists conducting analyses supporting ESA decisions develop a conceptual model that links climate, habitat, ecosystem, and species response to changing conditions and use this model to organize analyses and future research. We recommend that current climate conditions are not appropriate for projections used in ESA analyses and that long‐term projections of climate‐change effects provide temporal context as a species‐wide assessment provides spatial context. In these projections, climate change should not be discounted solely because the magnitude of projected change at a particular time is uncertain when directionality of climate change is clear. Identifying likely future habitat at the species scale will indicate key refuges and potential range shifts. However, the risks and benefits associated with errors in modeling future habitat are not equivalent. The ESA offers mechanisms for increasing the overall resilience and resistance of species to climate changes, including establishing recovery goals requiring increased genetic and phenotypic diversity, specifying critical habitat in areas not currently occupied but likely to become important, and using adaptive management. Incorporación de las Ciencias Climáticas en las Aplicaciones del Acta Estadunidense de Especies en Peligro para Especies Acuáticas     

Estimation of spatiotemporal trends in bat abundance from mortality data collected at wind turbines

Renewable energy sources, such as wind energy, are essential tools for reducing the causes of climate change, but wind turbines can pose a collision risk for bats. To date, the population-level effects of wind-related mortality have been estimated for only 1 bat species. To estimate temporal trends in bat abundance, we considered wind turbines as opportunistic sampling tools for flying bats (analogous to fishing nets), where catch per unit effort (carcass abundance per monitored turbine) is a proxy for aerial abundance of bats, after accounting for seasonal variation in activity. We used a large, standardized data set of records of bat carcasses from 594 turbines in southern Ontario, Canada, and corrected these data to account for surveyor efficiency and scavenger removal. We used Bayesian hierarchical models to estimate temporal trends in aerial abundance of bats and to explore the effect of spatial factors, including landscape features associated with bat habitat (e.g., wetlands, croplands, and forested lands), on the number of mortalities for each species. The models showed a rapid decline in the abundance of 4 species in our study area; declines in capture of carcasses over 7 years ranged from 65% (big brown bat [Eptesicus fuscus]) to 91% (silver-haired bat [Lasionycteris noctivagans]). Estimated declines were independent of the effects of mitigation (increasing wind speed at which turbines begin to generate electricity from 3.5 to 5.5 m/s), which significantly reduced but did not eliminate bat mortality. Late-summer mortality of hoary (Lasiurus cinereus), eastern red (Lasiurus borealis), and silver-haired bats was predicted by woodlot cover, and mortality of big brown bats decreased with increasing elevation. These landscape predictors of bat mortality can inform the siting of future wind energy operations. Our most important result is the apparent decline in abundance of four common species of bat in the airspace, which requires further investigation.     

Analysis of herbicide residues by gas chromatography

The extraction and clean‐up, and gas Chromatographic conditions for the detection and determination of herbicides, their metabolites and related compounds are reviewed. The literature material is examined critically in the text and presented in tabular form for quick reference. The section dealing with extraction/clean‐up techniques is sub‐divided with respect to water, soil, plant material, animal, fish and micro‐organisms. Under eight herbicide group headings the important gas Chromatographic parameters such as stationary phase, support phase, column temperature and mode of detection are tabulated. Also tabulated are the application of various detectors to herbicide analyses and limits of detection where information was available. Most commonly used liquid and support phases are listed and their frequency of use given. Different aspects of derivative formation used for the positive identification and quantitation of herbicides are discussed with emphasis on esterification, alkylation and silylation. Other important conversion techniques are outlined, particularly those associated with enhancement of sensitivity e.g. bromination, iodination, dinitrophenylation etc. Efforts that have been made towards general and automated analytical methods are discussed.