职业卫生信息化网络平台研究

当前我国职业卫生监管工作存在薄弱环节、监管手段相对落后,难以满足我国职业病防治工作形势的需求。将信息化技术应用于职业卫生监管,可有效提高职业卫生监管工作的科学性和有效性。阐述了职业卫生信息化网络平台建设的必要性,提出了职业卫生信息化建设的整体框架,分析并论述了具体建设内容以及建设过程中应注意的几点问题。     

工程项目现场安全标志有效性评价

为改善工程项目现场作业安全状况,需要对安全标志的有效性进行评价。通过划分施工人员的认知行为阶段,从人机工程学系统优化的角度构建安全标志有效性评价指标体系,确立指标打分规则,采用网络层次分析法(ANP),运用超级决策(SD)软件确定指标权重、综合评分,并加以示例说明。结果表明:安全标志的有效性受注意阶段的显著性、识别阶段的可理解性、判断阶段的安全倾向性和行为阶段的易遵守性交互影响,其中,安全倾向性权重值最高。     

人工神经网络用于铅的化学形态模拟计算

用前馈线性网络法求解水体系中Ｐｂ（２＋）与ＯＨ－之间的反应常数，不同训练算法对求解结果的精度、收敛速度及权值均有影响．结果表明，批处理算法的精度最好，权值不出现负值，但运算时间最长；在线算法的精度虽不如批处理算法，而比数据变换－在线算法好，权值有时会出现负值．运算时间较长；数据变换－在线算法的优点是运算时间短，但相对误差较大，权值出现负值的机会多。采用反馈网络模拟计算铅的各种化学形态的浓度．用物料核算的方法对反馈网络模型进行检验表明，此种模型用于平衡计算是可行的，详细分析了理论模拟和实验曲线的差异的原因，温度的影响最小，在４＜ｐＨ＜９时，ＣＯ有重要的影响．在国代检验时，ｎ值取整所引入的误差的影响亦不可忽视。从本文的结果可以看到，采用前馈网络和反馈网络相结合的方法考察水体中的化学形态是可行的．从而为解决这一类问题提供了一种可能的途径．     

人工神经网络在水环境质量评价中的应用

为了将人工神经网络应用于水环境质量评价,应用了人工神经网络Ｂ—Ｐ算法,构造了水环境质量评价模型,该模型应用于实例评价结果表明,人工神经网络用于环境质量评价具有客观性,通用性和实用性。     

Evaluation of ecological network analysis: Validation of output

Ecological network analysis (ENA) is a modeling approach increasingly being used to evaluate food webs and provide an ecosystem-based approach to resource management. Unfortunately, validation of ENA output is rarely performed. This study represents part of a larger effort to critically evaluate ENA. Here we validate ENA output using stable isotope analysis (SIA), and where validation is not met, determine the effects of modifying trophic networks to reflect validation.     

Key considerations and challenges in the application of social-network research for environmental decision making

Attempts to better understand the social context in which conservation and environmental decisions are made has led to increased interest in human social networks. To improve the use of social-network analysis in conservation, we reviewed recent studies in the literature in which such methods were applied. In our review, we looked for problems in research design and analysis that limit the utility of network analysis. Nineteen of 55 articles published from January 2016 to June 2019 exhibited at least 1 of the following problems: application of analytical methods inadequate or sensitive to incomplete network data; application of statistical approaches that ignore dependency in the network; or lack of connection between the theoretical base, research question, and choice of analytical techniques. By drawing attention to these specific areas of concern and highlighting research frontiers and challenges, including causality, network dynamics, and new approaches, we responded to calls for increasing the rigorous application of social science in conservation.     

基于BP神经网络算法的密云水库水质参数反演研究

密云水库是北京市重要的地表饮用水源地,在保障首都水源安全方面起着重要作用,而密云水库水质参数的区域监测已成为当前亟待解决的问题。为了实现密云水库水质参数大范围、实时获取,该文基于遥感和GIS技术,采用BP神经网络算法,结合地面监测数据和Landsat 8遥感影像,分别建立了反演总磷、总氮、氨氮和COD(化学需氧量)4个水质参数的BP神经网络模型,并反演了密云水库2013-2018年非结冰期主要水质参数,分析了密云水库主要水质参数的年际变化特征、季节变化特征和空间分异特征。结果表明,(1)水质参数的Landsat 8敏感波段分别为:总氮为1、4波段,氨氮为1-7波段,总磷为1、3-7波段,COD为2-5波段。(2)密云水库主要水质参数在2013-2018年总体呈下降趋势,氨氮和COD为Ⅰ类水质,总磷为Ⅱ类水质,总氮为Ⅲ类水质。(3)4个水质参数指标春季最高、秋季次之、夏季最低,总氮、总磷、氨氮和COD的春季值分别是夏季值的1.08、1.36、1.6、1.45倍。(4)密云水库不同水质参数的空间差异性较大,总体来看,水库北部和东部的4个水质参数含量相对较高,这种分布与北部和东部村庄密集以及密云水库两大入库河流有关。综上所述,基于BP神经网络算法的密云水库水质反演研究是可行的,且得到了较为可信的研究结果,该研究可为密云水库水质管理与政策制定提供重要的科学依据。     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

平原河网地区滨岸带外来植物入侵现状及影响研究——以上海青浦区为例

河流滨岸带作为一种典型的开放系统,在受到外界干扰的条件下极易被外来植物所入侵并受到严重影响。以上海青浦区为例,通过对河流滨岸带生态系统入侵植物分布及现状调查,以及对两种入侵植物：白花三叶草（Trifolium repens）和加拿大一枝黄花（Solidago canadensis）群落的物种多样性及其土壤特性的实证研究,探讨外来植物入侵对河流滨岸带生态系统造成的影响。结果表明：目前该地区河流滨岸带外来入侵植物共有14科24种,其科、种数分别占到该生态系统所有植物的48．3％与26．1％。入侵植物白花三叶草与加拿大一枝黄花在春、秋两季均显著降低了河流滨岸带植物群落的物种多样性。此外,两种人侵植物也对当地河流滨岸及土壤特性造成了不同程度的影响,其中对土壤含水量、pH值的影响最为显著。该研究填补了平原河网地区河流滨岸带生态系统外来植物入侵研究的空白,有助于今后开展对该生态系统的评价、恢复及管理工作。     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.