Using unobtrusive sensors to measure and minimize Hawthorne effects: Evidence from cookstoves

People act differently when they know they are being observed. This phenomenon, the Hawthorne effect, can bias estimates of program impacts. Unobtrusive sensors substituting for human observation can alleviate this bias. To demonstrate this potential, we used temperature loggers to measure fuel-efficient cookstoves as a replacement for three-stone fires. We find a large Hawthorne effect: when in-person measurement begins, participants increase fuel-efficient stove use approximately three hours/day (53%) and reduce three-stone fire use by approximately two hours/day (29%). When in-person measurement ends, participants reverse those changes. We then examine how this Hawthorne effect biases estimates of fuel use and pollution concentrations. Our results reinforce concerns about Hawthorne effects, especially in policy-relevant impact evaluations. By measuring the Hawthorne effect we permit researchers to correct for the bias it introduces.     

Black swans,cognition, and the power of learning from failure

Failure carries undeniable stigma and is difficult to confront for individuals, teams, and organizations. Disciplines such as commercial and military aviation, medicine, and business have long histories of grappling with it, beginning with the recognition that failure is inevitable in every human endeavor. Although conservation may arguably be more complex, conservation professionals can draw on the research and experience of these other disciplines to institutionalize activities and attitudes that foster learning from failure, whether they are minor setbacks or major disasters. Understanding the role of individual cognitive biases, team psychological safety, and organizational willingness to support critical self‐examination all contribute to creating a cultural shift in conservation to one that is open to the learning opportunity that failure provides. This new approach to managing failure is a necessary next step in the evolution of conservation effectiveness.     

露天煤矿待复垦土地生产潜力评价方法研究

露天煤矿待复垦土地生产潜力评价是编制土地复垦规划的一个重要内容。本文从露天煤矿待复垦土地生产潜力评价的必要性和特殊性出发,分别对评价因子指标定量或定性易量化和定性不易量化等不同类问题进行了评价方法及评价过程的研究,并根据安太堡露天煤矿复垦10年的经验进行了验证。同时,验证的结果应用于生态条件相似的将要开采的安家岭露天煤矿。     

The impact of bias in MoM values on patient risk and screening performance for Down syndrome

First and second trimester screening protocols for Down syndrome rely on marker values being referred to smoothed median values to produce adjusted multiple of the median (MoM) values to standardise for factors such as assay, gestation, maternal weight, smoking status, and so on. Changes in assay components, such as reagent lot, and inappropriate use of published regression equations for smoothed medians have resulted in biases in reported MoM values that in many applications remain uncorrected. This paper investigates the impact of these biases on patient-specific risk estimates and screening performance, and concludes that a 10% bias for an individual marker can result in an increase of between 1 and 2% in the false positive rate of the programme. A simple formula is also derived that enables the impact of these biases to be determined without the need for simulation, thus making it easier to design effective statistical quality control procedures to monitor the output of screening software algorithms. Objective To determine the impact of bias in MoM values on detection rates, false positive rates and patient-specific risks for Down syndrome. Methods We show that bias in MoM values affects risk through a multiplicative factor, and present an approximation to estimate this factor. We then show how bias in MoM values changes the effective risk threshold in the screening test, and hence the test's performance characteristics are determined by reference to a different point on the ROC curve for that test. Our approximation is based on the assumption of equal variance covariance structure for the unaffected and T21 log MoM values. We demonstrate, using computer simulation and supportive theoretical results, that the approximation is reliable in situations encountered in practice. Applications of the approximation are also discussed in respect of establishing effective quality control rules for median MoMs. Results Substantial changes in patient risk estimates and overall screening performance can result from the sort of biases in marker MoM values encountered in routine practice. In particular, biases of 10% in individual median marker MoM values can produce a four-fold range of risks when using the triple test. A 10% bias in a single marker will change the false positive rates by up to 2%. The effects on the false positive rate are approximately additive and, in cases where all markers are biased towards Down syndrome, biases in all three markers for the triple test can more than double the false positive rate. Conclusions Biases in marker MoM values can occur in many ways, inappropriate median values, kit lot change, drift in assay performance and operator effects. We present methods which allow the impact of these changes to be assessed in relation to patient-specific risks and the overall screening performance. This, in turn, will enable appropriate quality control procedures to be established to control the magnitude of reported marker MoM biases, or equivalently, the magnitude of biases associated with the calculation of patient-specific risks. Copyright © 2007 John Wiley & Sons, Ltd.     

Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

The perils of flawed science in wildlife trade literature

Despite broad scientific consensus that sustainable use of wildlife can enhance conservation efforts, ethical concerns have led some community groups to oppose use of wild animals. Voicing those concerns is legitimate, but underlying philosophical bias should not influence science-based analysis and interpretation. We argue that philosophical biases are common in the scientific literature on trade in wildlife. The critically important case of bias surrounding the use of reptile leathers for luxury fashion illustrates the problem. Based on analysis of official seizures of fashion products made from wildlife, a recent study inferred that criminal activity (as inferred by noncompliance with regulations) was common and increasing and, hence, that authorities needed to adopt more stringent restrictions on the trade. In fact, the conclusions of that study are artifacts of pseudoreplication (e.g., multiple counts of single violations) and biased sampling (e.g., focus on companies with high rates of error) and run directly opposite to actual patterns in the data. As a proportion of overall trade, rates of noncompliance are exceptionally low (<0.4%), are declining, and result primarily from paper-work errors rather than criminal intent (e.g., such errors are more frequent for goods shipped by government authorities than by the commercial fashion industry). The recommendation by the study authors to prohibit the international trade in wildlife-based fashion products is imperiling a sustainable trade that can benefit biodiversity and people's livelihoods by providing financial incentives for conservation of species and habitats. This example offers a warning of the dangers of basing research on the wildlife trade on ethical or philosophical positions rather than objective evaluations of evidence.     

The challenge of biased evidence in conservation

Efforts to tackle the current biodiversity crisis need to be as efficient and effective as possible given chronic underfunding. To inform decision-makers of the most effective conservation actions, it is important to identify biases and gaps in the conservation literature to prioritize future evidence generation. We used the Conservation Evidence database to assess the state of the global literature that tests conservation actions for amphibians and birds. For the studies in the database, we investigated their spatial and taxonomic extent and distribution across biomes, effectiveness metrics, and study designs. Studies were heavily concentrated in Western Europe and North America for birds and particularly for amphibians, and temperate forest and grassland biomes were highly represented relative to their percentage of land coverage. Studies that used the most reliable study designs—before-after control-impact and randomized controlled trials—were the most geographically restricted and scarce in the evidence base. There were negative spatial relationships between the numbers of studies and the numbers of threatened and data-deficient species worldwide. Taxonomic biases and gaps were apparent for amphibians and birds—some entire orders were absent from the evidence base—whereas others were poorly represented relative to the proportion of threatened species they contained. Metrics used to evaluate effectiveness of conservation actions were often inconsistent between studies, potentially making them less directly comparable and evidence synthesis more difficult. Testing conservation actions on threatened species outside Western Europe, North America, and Australasia should be prioritized. Standardizing metrics and improving the rigor of study designs used to test conservation actions would also improve the quality of the evidence base for synthesis and decision-making.     

The International Environmental Expert Panel for Major Dam/Reservoir Projects: The Yellow River, China

The experience of the International Expert Panel on Environment for the Xiaolangdi dam/reservoir project in China (XEP) showed that the Panel meetings resulted in a marked improvement in project environmental performance by all parties participating in project implementation, with no parties exempt from the Panel's evaluations. Unfortunately the Loan Agreement authorizes use of the Panel only through the project stages of final design and construction, hence the 12th Panel meeting, which matched project construction completion, ended this series. The Panel has recommended that some meetings of the Panel be held during the project's operations stage in order to maintain continuing attention to environmental needs. The XEP experience showed that the XEP, in addition to monitoring project environmental performance, was very valuable for (i) training of Chinese staff involved in project implementation, and (ii) serving in the role as expert consultant for guiding the work of the Chinese participants. The XEP experience also showed the need for making a clear separation between evaluation, the overall resettlement program per se, and the environmental effects of the program. The Panel recommended that the Ministry of Water Resources and World Bank cooperate in sponsoring a book on The Environmental History of the Xiaolangdi Project, including both dam construction as well as resettlement problems, which would serve as a very valuable reference for guiding environmental planning for future dam projects in China (Ludwig, H.F. 1994–2000).     

Whom to Trust? Public Concerns, Late Modern Risks, and Expert Trustworthiness

This article discusses the conditions under which the use of expert knowledge may provide an adequate response to public concerns about high-tech, late modern risks. Scientific risk estimation has more than once led to expert controversies. When these controversies occur, the public at large – as a media audience – faces a paradoxical situation: on the one hand it must rely on the expertise of scientists as represented in the mass media, but on the other it is confused by competing expert claims in the absence of any clear-cut standard to judge these claims. The question then arises, what expertise can the public trust? I argue that expert controversies cannot be settled by appealing to neutral, impartial expertise, because each use of expert knowledge in applied contexts is inextricably bound up with normative and evaluative assumptions. This value-laden nature of expert contributions, however, does not necessarily force us to adopt a relativist conception of expert knowledge. Nor does it imply active involvement of ordinary citizens in scientific risk estimation – as some authors seem to suggest. The value-laden, or partisan, nature of expert statements rather requires an unbiased process of expert dispute in which experts and counter-experts can participate. Moreover, instead of being a reason for discrediting expert contributions, experts' commitment may enhance public trustworthiness because it enlarges the scope of perspectives taken into account, to include public concerns. Experts who share the same worries as (some of) the public could be expected to voice these worries at the level of expert dispute. Thus, a broadly shaped expert dispute, that is accessible to both proponents and opponents, is a prerequisite for public trust.     

EFFECT OF SERIAL CORRECTION ON GROUND WATER QUALITY SAMPLING FREQUENCY1

ABSTRACT: Methods of calculating uncertainty in estimates of serial correlation coefficients, and correcting for bias in short and medium length (less than 50 data point) records, are presented. Uncertainty and bias in the estimation of serial correlation coefficients for ground water quality data is shown to be considerable and to result in inaccurate calculation of the sampling frequencies for monitoring purposes. The methods are applied to a ground water data set consisting of 87 monthly measurements of nitrate concentrations. The variation in serial correlation coefficients with variation of record length is examined. The optimum sampling frequencies for detection of changes in ground water nitrate concentrations are estimated.