我国东北黑土丘陵区小流域土壤有机质空间分布模拟

为探索小流域w(SOM)(SOM为土壤有机质)空间分布模拟的最佳方法,以我国东北黑土丘陵区海沟河小流域为例,借助地统计学和3S技术提取与w(SOM)显著相关的地形及环境因子,对海沟河小流域表层(0~20 cm)w(SOM)分别进行协同克里格插值、回归克里格插值和地理加权回归克里格空间插值模拟,并进行精度验证. 结果表明:我国东北黑土丘陵区海沟河小流域表层w(SOM)平均值为12.96 g/kg,空间变异程度为中等. 海拔、距水系距离均与w(SOM)显著相关,能够用来辅助w(SOM)的空间分布插值;与协同克里格插值结果相比,回归克里格对w(SOM)的插值精度提高了56.09%;地理加权回归克里格插值精度提高了90.87%;对地理加权回归克里格插值所产生的残差进行二次统计分析及合理插值,能够进一步提高插值模拟精度;将人类干扰因素纳入插值模型,是未来提高w(SOM)空间分布模拟精度的关键. 研究显示,地理加权回归克里格插值有效提高了w(SOM)空间插值模拟的精度,并且存在改进和提高的空间.      

基于DEA-Tobit的城市生态效率评价及影响因素研究——以江苏省为例

基于DEA-Tobit两阶段分析框架,利用超效率DEA模型评价了江苏省13个地级市及苏南、苏中、苏北3个区域2009~2013年的工业生态效率,并采用Tobit模型测量了城镇化率、产业结构、环境规制对该效率值的影响。研究表明:江苏省城市工业生态效率整体处于中上水平,但地区间差异较大:苏中优于苏南,苏南优于苏北;工业用水、工业用地消耗过多,工业废气排放过量是目前影响江苏省城市工业生态效率提升的主要原因;提高城镇化率对江苏省城市工业生态效率有积极的影响,产业结构调整对城市工业生态效率有微弱的抑制作用,环境规制对城市工业生态效率影响并不显著。     

Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis

Introduction: Although stop signs are popular in North America, they have become controversial in cities like Montreal, Canada where they are often installed to reduce vehicular speeds and improve pedestrian safety despite limited evidence demonstrating their effectiveness. The purpose of this study is to evaluate the impact of stop-control configuration (and other features) on safety using statistical models and surrogate measures of safety (SMoS), namely vehicle speed, time-to-collision (TTC), and post-encroachment time (PET), while controlling for features of traffic, geometry, and built environment. Methods: This project leverages high-resolution user trajectories extracted from video data collected for 100 intersections, 336 approaches, and 130,000 road users in Montreal to develop linear mixed-effects regression models to account for within-site and within-approach correlations. This research proposes the Intersection Exposure Group (IEG) indicator, an original method for classifying microscopic exposure of pedestrians and vehicles. Results: Stop signs were associated with an average decrease in approach speed of 17.2 km/h and 20.1 km/h, at partially and fully stop-controlled respectively. Cyclist or pedestrian presence also significantly lower vehicle speeds. The proposed IEG measure was shown to successfully distinguish various types of pedestrian-vehicle interactions, allowing for the effect of each interaction type to vary in the model. Conclusions: The presence of stop signs significantly reduced approach speeds compared to uncontrolled approaches. Though several covariates were significantly related to TTC and PET for vehicle pairs, the models were unable to demonstrate a significant relationship between stop signs and vehicle–pedestrian interactions. Therefore, drawing conclusions regarding pedestrian safety is difficult. Practical Applications: As pedestrian safety is frequently used to justify new stop sign installations, this result has important policy implications. Policies implementing stop signs to reduce pedestrian crashes may be less effective than other interventions. Enforcement and education efforts, along with geometric design considerations, should accompany any changes in traffic control.     

How to evaluate models: Observed vs. predicted or predicted vs. observed?

A common and simple approach to evaluate models is to regress predicted vs. observed values (or vice versa) and compare slope and intercept parameters against the 1:1 line. However, based on a review of the literature it seems to be no consensus on which variable (predicted or observed) should be placed in each axis. Although some researchers think that it is identical, probably because r² is the same for both regressions, the intercept and the slope of each regression differ and, in turn, may change the result of the model evaluation. We present mathematical evidence showing that the regression of predicted (in the y-axis) vs. observed data (in the x-axis) (PO) to evaluate models is incorrect and should lead to an erroneous estimate of the slope and intercept. In other words, a spurious effect is added to the regression parameters when regressing PO values and comparing them against the 1:1 line. Observed (in the y-axis) vs. predicted (in the x-axis) (OP) regressions should be used instead. We also show in an example from the literature that both approaches produce significantly different results that may change the conclusions of the model evaluation.     

Identifying Biotic Integrity and Water Chemistry Relations in Nonwadeable Rivers of Wisconsin: Toward the Development of Nutrient Criteria

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII—Mostly Glaciated Dairy Region, and VIII—Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R ² = 60.6%) and fish (R ² = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses.     

基于梯度提升回归树算法的地面臭氧浓度估算

将机器学习中的梯度提升回归树（GBRT）算法应用到中国地区地面O₃浓度制图中,利用地面O₃浓度观测数据,结合WRF气象数据、MODIS植被归一化指数以及高程人口数据建立训练预测数据集.通过反向变量选择法选取模型最佳特征变量对其进行训练,十折交叉验证结果：决定系数R²=0.89、均方根误差RMSE=4.75μg/m³.同时对全国O₃人口暴露水平进行评估.结果表明：在暴露强度上,我国人口加权O₃浓度值排在前5的省依次是山东、河南、江苏、河北、上海,均值浓度为94.48μg/m³.在暴露持续时间上,非达标天数最多的5个省依次是河南、山东、河北、宁夏、北京,一年内有42%的天数处于非达标的状态.     

分光光度法测定余氯的线性范围探讨

用分光光度法测定水样中的余氯，按照国际GB11898－89中的要求，整个浓度范围内（余氯0－5.00mg/L)所制得的标准曲线的相关系数在0.99-0.999之间。经对其标准曲线的线性范围进行探讨发现，当余氯的浓度范围为0－1.00mg/L时，标准曲线的线性较好，相关系数＞0．999；当余氯的浓度＞1.00mg/L，所绘制的标准曲线呈负偏离现象，相关系数＜0．999。     

支持向量回归方法在震级预测中的应用

本文阐述了支持向量回归(SVR)理论及其特性,提出了基于SVR的次年最大震级的预测方法,并对所选样本进行训练和预测,结果与实际值符合较好,理论分析和实例结果验证了基于SVR的震级预测方法比BP神经网络具有更高的预测精度和可靠性.     

Sequential extraction of copper from soils and relationships with copper in maize

We studied copper uptake by maize grown on soils that have been contaminated with CuSO₄. In soil the total copper level ranged from 24 to 135 mg kg^–1. The copper distribution in soil fractions was assessed by sequential extraction, showing that anthropogenic copper is mainly concentrated in oxides fractions. The copper concentration of maize at the maturity stage reached values from 36.3 to 65.9 mg kg^–1 compared to copper levels usually found in non-contaminated crops (5–30 mg kg^–1). Here we demonstrate that copper can be accumulated by maize and that copper concentration in maize can be predicted by equations including copper concentration of soil fractions.     

Convexity in projection matrices: Projection to a calibration problem

Convexity, as a fundamental property of sets and functions defined on convex sets, plays an important role in many mathematical and applied disciplines, including extremal and optimal-control problems. We prove the set of all feasible projection matrices in a general class of matrix models for stage-structured population dynamics to be convex and the dominant eigenvalue (λ₁) of any projection 2 × 2 matrix to be either a convex, or a concave function on a simplex of the matrix first-row entries (i.e., stage-specific reproduction rates). The latter is also conjectured for the general n × n case. Though looking far from practical needs of matrix population models, this mathematical result has appeared to be quite useful in solving a practical problem to calibrate the projection matrix, i.e., to estimate all the stage-specific vital rates, from empirical data. The data from monitoring of individual life histories of marked plants on permanent sample plots during successive years enable direct calculation of the stage-specific survival and ontogenetic transition rates, but the rates of reproduction do remain uncertain as far as the parent plants can hardly be determined for the (not yet marked!) recruitment.