The bean method as a tool to measure sensitive behavior

Conservationists need to measure human behavior to guide decisions and evaluate their impact. However, activities can be misreported and reporting accuracy may change following conservation interventions, making it hard to verify any apparent changes. Techniques for asking sensitive questions are increasingly integrated into survey designs to improve data quality, but some can be costly or hard for nonexperts to implement. We demonstrate a straightforward, low-cost approach, the bean method in which respondents give anonymous answers by adding a colored bean to a jar to denote a yes or no response. We applied the bean method to measure wild-meat hunting and trading over 2 years at a conservation-project (hunting reduction) site in Gola Forest, Liberia. We extended the technique to accommodate questions about hunting and meat-selling frequency. We compared responses given using the bean method and direct questioning for groups that did and did not participate in conservation interventions. Results from the bean method corresponded to those from direct questioning, and there was no indication of change in question sensitivity following conservation interventions. Estimates from both methods indicated that wild-meat trading decreased in project and nonproject households (from 36% to 20%) and that hunting decreased in 1 project group (38–28%). Where inconsistent answers were given (2–6% of respondents), differences were in both directions and were most likely attributable to measurement error. The bean method was quick and straightforward to administer in a low-literacy setting. We showed how it can be modified for answers of more than 2 categories and consider it a valuable tool that could be adapted for a wide range of conservation settings.     

Same stimuli,different responses: a pilot study assessing air pollution visibility impacts on emotional well-being in a controlled environment

● Emotional responses to visibility-reducing haze was assessed in a controlled lab. ● Valence and arousal have non-linear responses to pollution-caused low visibility. ● Repetitive exposure aggravates negative emotions in severely polluted conditions. ● Emotional bias to pollution relates with gender, decisiveness, attitude to clean air. A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing. However, evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment. Herein, we designed a lab-based experiment (41 subjects, 6 blocks) where participants were presented with real-scene images of 12 different PM_2.5 concentrations in each block. Emotional valence (negative to positive) and arousal (calm to excited) were self-rated by participants per image, and the response time for each rating was recorded. We find that as pollution level increases from 10 to 260 µg/m³, valence scores decrease, whereas arousal scores decline first and then bounce back, following a U-shaped trend. When air quality deteriorates, individual variability decreases in hedonic valence but increases in arousal. Over blocks, repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions (> 150 µg/m³). Finally, we find females, people who are slow in making responses, and those who are highly aroused by clean air tend to express more negative responses (so-called negativity bias) to ambient pollution than their respective counterparts. These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment. Although the findings in our pilot study should only be directly applied to the conditions assessed herein, we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.     

Overcoming Endpoint Bias in Climate Change Communication: The Case of Arctic Sea Ice Trends

Unusually cold winters, a slowing in upward global temperatures, or an increase in Arctic sea ice extent are often falsely cast as here-and-now disconfirmation of the scientific consensus on climate change. Such conclusions are examples of “end point bias,” the well documented psychological tendency to interpret a recent short-term fluctuation as a reversal of a long-term trend. End point bias poses a challenge to those trying to communicate cross-decade climate warming trends. In this study, we demonstrate that exposure to misleading scientific information on FoxNews.com that evokes end point bias can affect the beliefs of liberals and moderates as well as conservatives. We also show that the leveraging-involving-visualizing-analogizing communication model can reduce the effects of endpoint bias among moderates and liberals at the same time as it dampens both the ideological and endpoint biasing of conservatives.     

小净距偏压隧道在特殊素填土施工顺序研究

在较特殊素填土中,为能更好地确定在相同的施工方法下,不同的施工顺序对改善隧道围岩变形和衬砌内力的影响,文章重点以重庆曾家岩浅埋暗挖隧道为依托,运用二维数值模拟分析,研究在特殊回填土下,隧道不同施工顺序引起的围岩变形、衬砌内力变化、塑性区分布规律.从数值模拟结果可以看出,不同施工顺序下,围岩变形、衬砌内力、塑性区分布存在...     

环境温度下SBR实现稳定部分亚硝化研究

采用SBR反应器建立了一套通过特定pH终值调控曝气停止点,以实现稳定部分亚硝化的策略,整个运行过程分为3个阶段,阶段Ⅰ启动亚硝化,阶段Ⅱ在稳定亚硝化的同时探索pH终值的设定规律,阶段Ⅲ采用pH终值设定规律实现稳定部分亚硝化,通过跨越夏、冬季（7~35℃）共148d的运行,考察SBR系统内有机物、氮素的转化规律,并分析不同温度（23、18、13℃）对部分亚硝化反应过程的影响.结果表明,在低DO（0.2~0.4mg/L）和MLSS为4000mg/L的条件下,控制pH终值为（7.73±0.02）,使出水FA在0.5~1.2mg/L,可稳定部分亚硝化期间的出水NO₂^--N/NH₄⁺-N值在1~1.4之间,出水亚硝积累率（NAR）维持在85%以上,有机物去除率在60%以上.比氨氧化速率、比亚硝态氮氧化速率、比COD去除速率均随温度下降而降低,但降低趋势较缓,且反应均能稳定完成.     

Orientation behavior of homing pigeons at the Gernsheim anomaly

Pigeons were released at four release sites within the Gernsheim anomaly, a magnetic 'hill' with a peak 199 nT above the regional reference field and gentle 'slopes' to all sides, situated 44 km south of the Frankfurt loft. Local magnetic conditions at the sites differed in total intensity and in direction and steepness of the intensity gradient. At all sites, the pigeons were well oriented, showing counterclockwise deviations from the home directions that were most pronounced in the western part of the anomaly. There was no systematic difference in orientation behavior or homing performance between the sites within the anomaly and a control site outside. No effect of the local gradient direction was found, nor did the difference in intensity between home loft and the release site affect behavior. This argues against the use of magnetic navigational factors. However, pigeons released for the first time within the anomaly tended to have longer mean vectors with increasingly steeper gradients, which could mean that the birds might somehow have realized the anomalous nature of the local magnetic conditions and ignored them, relying on non-magnetic cues instead.Communicated by R. Gibson     

Hedonic analysis of hazardous waste sites in the presence of other urban disamenities

Hedonic research indicates that residential property values are reduced by increased proximity to hazardous waste sites, a measure of diminished environmental quality. Standard hedonic procedures measure proximity by the linear distance between a property and a waste site of interest. A sample of properties is then used to estimate a distance-to-site coefficient that measures the effect of the hazardous waste site on surrounding property values. These estimates can help policy makers assess the external effects of hazardous waste sites and may also be useful in both prioritizing and assessing the benefits of cleanup. In an urban situation, hazardous waste sites are often located near other industrial disamenities such as railroads, storage tanks, industrial noises, and air pollution. This spatial grouping of hazards may be due to economic forces or due to policy instruments such as zoning. As a result, distance to hazardous waste site may be correlated with distances to other industrial disamenities. Standard hedonic procedures that use a distance-to-site variable may suffer from omitted variable bias when the bundled industrial disamenities are present but ignored. Our empirical analysis examines this bias by assessing hedonic regressions with and without a measure that accounts for industrial activity.     

Joint versus separate estimation of state and change in category frequencies from repeat stratified two-phase sampling with a fallible classifier

Joint maximum likelihood estimates (JML) of category frequencies and change from repeat stratified two-phase samplingsurveys with a fallible classifier are often seriously biased andhave large root mean square errors when they are obtained for small populations (<5000) with three or more categories and amoderate to small phase II sample size (<1000). JML estimates of state also depend on antecedent or posterior data, a recipe for inconsistency. In these situations, a separate maximum likelihood estimation (SML) of category frequenciesat each survey date appears preferable. SML estimates of net change are obtained as the difference in states. SML standard errors of change are obtained via an estimate of the temporal correlation and variances of state. A bivariate binarylogistic model of change provided the estimate of temporal correlation. SML generally outperformed JMLsignificantly in terms of bias and root mean square errors in eight case studies.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

管制员认知偏差测评量表的编制与应用

利用信息加工模型,结合管制工作的特殊性,编制出管制员认知偏差测评量表。利用该量表对管制员认知偏差进行测量,结果表明管制员管制过程中存在较大的认知偏差;不同性别及年龄的管制员在认知偏差方面存在显著差异。