Strength of Belief Guides Information Foraging.

Theories of how people value and search for information share the assumption that beliefs give rise to the perceived value of information. However, few studies have directly addressed the pre-search processes that influence information-foraging behavior. This experiment examined the influence of pre-search belief updating on the perceived value of information sources. A sample of college students completed a hypothesis-testing, medical-diagnosis task. The experiment used medical tests with equal objective informative value before unveiling a presenting symptom intended to alter the strength of belief in different disease hypotheses. The observed patterns of test selection suggest that changes in beliefs about disease hypotheses result in systematic and predictable changes in test preference-a notion we refer to as the principle of hypothesis-guided search. We also present a simulation of how pre-search processes (e.g., hypothesis generation and working memory capacity) and task variables (e.g., time pressure) influence subsequent information search.

Characteristics of free air carbon dioxide enrichment of a northern temperate mature forest.

In 2017, the Birmingham Institute of Forest Research (BIFoR) began to conduct Free Air Carbon Dioxide Enrichment (FACE) within a mature broadleaf deciduous forest situated in the United Kingdom. BIFoR FACE employs large-scale infrastructure, in the form of lattice towers, forming 'arrays' which encircle a forest plot of ~30 m diameter. BIFoR FACE consists of three treatment arrays to elevate local CO2 concentrations (e[CO2 ]) by +150 µmol/mol. In practice, acceptable operational enrichment (ambient [CO2 ] + e[CO2 ]) is ±20% of the set point 1-min average target. There are a further three arrays that replicate the infrastructure and deliver ambient air as paired controls for the treatment arrays. For the first growing season with e[CO2 ] (April to November 2017), [CO2 ] measurements in treatment and control arrays show that the target concentration was successfully delivered, that is: +147 ± 21 µmol/mol (mean ± SD) or 98 ± 14% of set point enrichment target. e[CO2 ] treatment was accomplished for 97.7% of the scheduled operation time, with the remaining time lost due to engineering faults (0.6% of the time), CO2 supply issues (0.6%) or adverse weather conditions (1.1%). CO2 demand in the facility was driven predominantly by wind speed and the formation of the deciduous canopy. Deviations greater than 10% from the ambient baseline CO2 occurred <1% of the time in control arrays. Incidences of cross-contamination >80 µmol/mol (i.e. >53% of the treatment increment) into control arrays accounted for <0.1% of the enrichment period. The median [CO2 ] values in reconstructed three-dimensional [CO2 ] fields show enrichment somewhat lower than the target but still well above ambient. The data presented here provide confidence in the facility setup and can be used to guide future next-generation forest FACE facilities built into tall and complex forest stands.

Black carbon solar absorption suppresses turbulence in the atmospheric boundary layer.

The introduction of cloud condensation nuclei and radiative heating by sunlight-absorbing aerosols can modify the thickness and coverage of low clouds, yielding significant radiative forcing of climate. The magnitude and sign of changes in cloud coverage and depth in response to changing aerosols are impacted by turbulent dynamics of the cloudy atmosphere, but integrated measurements of aerosol solar absorption and turbulent fluxes have not been reported thus far. Here we report such integrated measurements made from unmanned aerial vehicles (UAVs) during the CARDEX (Cloud Aerosol Radiative Forcing and Dynamics Experiment) investigation conducted over the northern Indian Ocean. The UAV and surface data reveal a reduction in turbulent kinetic energy in the surface mixed layer at the base of the atmosphere concurrent with an increase in absorbing black carbon aerosols. Polluted conditions coincide with a warmer and shallower surface mixed layer because of aerosol radiative heating and reduced turbulence. The polluted surface mixed layer was also observed to be more humid with higher relative humidity. Greater humidity enhances cloud development, as evidenced by polluted clouds that penetrate higher above the top of the surface mixed layer. Reduced entrainment of dry air into the surface layer from above the inversion capping the surface mixed layer, due to weaker turbulence, may contribute to higher relative humidity in the surface layer during polluted conditions. Measurements of turbulence are important for studies of aerosol effects on clouds. Moreover, reduced turbulence can exacerbate both the human health impacts of high concentrations of fine particles and conditions favorable for low-visibility fog events.

Atmospheric Sampling on Ascension Island Using Multirotor UAVs.

As part of an NERC-funded project investigating the southern methane anomaly, a team drawn from the Universities of Bristol, Birmingham and Royal Holloway flew small unmanned multirotors from Ascension Island for the purposes of atmospheric sampling. The objective of these flights was to collect air samples from below, within and above a persistent atmospheric feature, the Trade Wind Inversion, in order to characterise methane concentrations and their isotopic composition. These parameters allow the methane in the different air masses to be tied to different source locations, which can be further analysed using back trajectory atmospheric computer modelling. This paper describes the campaigns as a whole including the design of the bespoke eight rotor aircraft and the operational requirements that were needed in order to collect targeted multiple air samples up to 2.5 km above the ground level in under 20 min of flight time. Key features of the system described include real-time feedback of temperature and humidity, as well as system health data. This enabled detailed targeting of the air sampling design to be realised and planned during the flight mission on the downward leg, a capability that is invaluable in the presence of uncertainty in the pre-flight meteorological data. Environmental considerations are also outlined together with the flight plans that were created in order to rapidly fly vertical transects of the atmosphere whilst encountering changing wind conditions. Two sampling campaigns were carried out in September 2014 and July 2015 with over one hundred high altitude sampling missions. Lessons learned are given throughout, including those associated with operating in the testing environment encountered on Ascension Island.

Model-data synthesis for the next generation of forest free-air CO2 enrichment (FACE) experiments.

The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.

Using a model of hypothesis generation to predict eye movements in a visual search task.

We used a model of hypothesis generation (called HyGene; Thomas, Dougherty, Sprenger, & Harbison, 2008) to make predictions regarding the deployment of attention (as assessed via eye movements) afforded by the cued recall of target characteristics before the onset of a search array. On each trial, while being eyetracked, participants were first presented with a memory prompt that was diagnostic regarding the target's color in a subsequently presented search array. We assume that the memory prompts led to the generation of hypotheses (i.e., potential target characteristics) from long-term memory into working memory to guide attentional processes and ocular-motor behavior. However, given that multiple hypotheses might be generated in response to a prompt, it has been unclear how the focal hypothesis (i.e., the hypothesis that exerts the most influence on search) affects search behavior. We tested two possibilities using first fixation data, with the assumption that the first item fixated within a search array was the focal hypothesis. We found that a model assuming that the first item generated into working memory guides overt attentional processes was most consistent with the data at both the aggregate and single-participant levels of analysis.

Using the memory activation capture (MAC) procedure to investigate the temporal dynamics of hypothesis generation.

Research investigating top-down capture has demonstrated a coupling of working memory content with attention and eye movements. By capitalizing on this relationship, we have developed a novel methodology, called the memory activation capture (MAC) procedure, for measuring the dynamics of working memory content supporting complex cognitive tasks (e.g., decision making, problem solving). The MAC procedure employs briefly presented visual arrays containing task-relevant information at critical points in a task. By observing which items are preferentially fixated, we gain a measure of working memory content as the task evolves through time. The efficacy of the MAC procedure was demonstrated in a dynamic hypothesis generation task in which some of its advantages over existing methods for measuring changes in the contents of working memory over time are highlighted. In two experiments, the MAC procedure was able to detect the hypothesis that was retrieved and placed into working memory. Moreover, the results from Experiment 2 suggest a two-stage process following hypothesis retrieval, whereby the hypothesis undergoes a brief period of heightened activation before entering a lower activation state in which it is maintained for output. The results of both experiments are of additional general interest, as they represent the first demonstrations of top-down capture driven by participant-established WM content retrieved from long-term memory.

Effects of delayed weather radar images on pilots' spatial awareness.

Data-linked Next Generation Weather Radar (NEXRAD) images can be delayed up to 20 min in the cockpit. Pilots' underappreciating or ignoring the time delay may be the major cause of two fatal accidents. No studies have connected spatial awareness with accidents. This study evaluated how delayed radar information affects the spatial awareness of pilots at three levels of analysis. Thirty-one student pilots and flight instructors completed three sequential estimation tasks (i.e., the current location of storms, the current relative distance to storms, and the future relative distance to storms). Fifty-four weather scenarios were developed for three factors (storm speeds, delays, displays) and presented to pilots. The results indicated that delays and the storm speed significantly affected the three levels of spatial awareness. Participants' estimation accuracy was the lowest under long delay and fast speed in the current location estimation, under medium delay and speed in the current distance estimation, and under short delay and slow speed in the future distance estimation. Spatial awareness could be high under the long delay and fast speed conditions if pilots had no time limits. Thus, pilots can process 20-min delayed radar information. However, there were no differences in estimation accuracy between the static and animation displays in any of the conditions. Well-designed features on displays, such as scale or distance measuring tools, can aid pilots' spatial estimation and support all levels of spatial awareness.

Contextual biases in the interpretation of auditory evidence.

Noisy recordings of dialogue often serve as evidence in criminal proceedings. The present article explores the ability of two types of contextual information, currently present in the legal system, to bias subjective interpretations of such evidence. The present experiments demonstrate that the general context of the legal system and the presence of transcripts of the recorded speech are both able to bias interpretations of degraded & benign recordings into interpretable & incriminating. Furthermore we demonstrate a curse of knowledge whereby people become miscalibrated to the true quality of degraded recordings when provided transcripts. Current methods of dealing with auditory evidence are insufficient to mollify the effects of biasing information within the criminal justice system.

Nature and Children's Health: A Systematic Review.

CONTEXT: Daily outdoor play is encouraged by the American Academy of Pediatrics. Existing evidence is unclear on the independent effect of nature exposures on child health. OBJECTIVE: We systematically evaluated evidence regarding the relationship between nature contact and children's health. DATA SOURCES: The database search was conducted by using PubMed, Cumulative Index to Nursing and Allied Health Literature, PsychInfo, ERIC, Scopus, and Web of Science in February 2021. STUDY SELECTION: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In all searches, the first element included nature terms; the second included child health outcome terms. DATA EXTRACTION: Of the 10 940 studies identified, 296 were included. Study quality and risk of bias were assessed. RESULTS: The strongest evidence for type of nature exposure was residential green space studies (n = 147, 50%). The strongest evidence for the beneficial health effects of nature was for physical activity (n = 108, 32%) and cognitive, behavioral, or mental health (n = 85, 25%). Physical activity was objectively measured in 55% of studies, and 41% of the cognitive, behavioral, or mental health studies were experimental in design. LIMITATIONS: Types of nature exposures and health outcomes and behaviors were heterogenous. Risk of selection bias was moderate to high for all studies. Most studies were cross-sectional (n = 204, 69%), limiting our ability to assess causality. CONCLUSIONS: Current literature supports a positive relationship between nature contact and children's health, especially for physical activity and mental health, both public health priorities. The evidence supports pediatricians in advocating for equitable nature contact for children in places where they live, play, and learn.

Psychological plausibility of the theory of probabilistic mental models and the fast and frugal heuristics.

The theory of probabilistic mental models (PMM; G. Gigerenzer, U. Hoffrage, & H. Kleinbölting, 1991) has had a major influence on the field of judgment and decision making, with the most recent important modifications to PMM theory being the identification of several fast and frugal heuristics (G. Gigerenzer & D. G. Goldstein, 1996). These heuristics were purported to provide psychologically plausible cognitive process models that describe a variety of judgment behavior. In this article, the authors evaluate the psychological plausibility of the assumptions upon which PMM were built and, consequently, the psychological plausibility of several of the fast and frugal heuristics. The authors argue that many of PMM theory's assumptions are questionable, given available data, and that fast and frugal heuristics are, in fact, psychologically implausible.

Diagnostic hypothesis generation and human judgment.

Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinicians generate disease hypotheses to explain symptoms and help guide treatment, auditors generate hypotheses for identifying sources of accounting errors, and laypeople generate hypotheses to explain patterns of information (i.e., data) in the environment. The authors introduce a general model of human judgment aimed at describing how people generate hypotheses from memory and how these hypotheses serve as the basis of probability judgment and hypothesis testing. In 3 simulation studies, the authors illustrate the properties of the model, as well as its applicability to explaining several common findings in judgment and decision making, including how errors and biases in hypothesis generation can cascade into errors and biases in judgment.

Long-term serial position effects in cue-based inference.

An important theoretical question in decision making concerns the nature of cue-generation: What mechanism drives the generation of cues used to make inferences? Most models of decision making assume that the properties of cues, often cue validity, initiate a set of dynamic pre-decision processes. In two studies, we test how memory accessibility affects cue use by manipulating both ecological cue validity and cue accessibility in a stock-forecasting task. Cue accessibility was manipulated by the pattern of accurate cue discriminations within experiment blocks of the learning phase of the experiments. Specifically, we manipulated the serial positions in which the cues accurately discriminated while holding overall cue validity constant. At test, participants preferred cues that discriminated early in the learning phase-a kind of primacy effect. The findings suggest that cue use is influenced by memory retrieval mechanisms and that cue use is not solely determined by cue validity. The results have implications for the development of computational models of heuristic decision-making.

Does constraining memory maintenance reduce visual search efficiency?

We examine whether constraining memory retrieval processes affects performance in a cued recall visual search task. In the visual search task, participants are first presented with a memory prompt followed by a search array. The memory prompt provides diagnostic information regarding a critical aspect of the target (its colour). We assume that upon the presentation of the memory prompt, participants retrieve and maintain hypotheses (i.e., potential target characteristics) in working memory in order to improve their search efficiency. By constraining retrieval through the manipulation of time pressure (Experiments 1A and 1B) or a concurrent working memory task (Experiments 2A, 2B, and 2C), we directly test the involvement of working memory in visual search. We find some evidence that visual search is less efficient under conditions in which participants were likely to be maintaining fewer hypotheses in working memory (Experiments 1A, 2A, and 2C), suggesting that the retrieval of representations from long-term memory into working memory can improve visual search. However, these results should be interpreted with caution, as the data from two experiments (Experiments 1B and 2B) did not lend support for this conclusion.

Determination of velocity correction factors for real-time air velocity monitoring in underground mines.

When there are installations of air velocity sensors in the mining industry for real-time airflow monitoring, a problem exists with how the monitored air velocity at a fixed location corresponds to the average air velocity, which is used to determine the volume flow rate of air in an entry with the cross-sectional area. Correction factors have been practically employed to convert a measured centerline air velocity to the average air velocity. However, studies on the recommended correction factors of the sensor-measured air velocity to the average air velocity at cross sections are still lacking. A comprehensive airflow measurement was made at the Safety Research Coal Mine, Bruceton, PA, using three measuring methods including single-point reading, moving traverse, and fixed-point traverse. The air velocity distribution at each measuring station was analyzed using an air velocity contour map generated with Surfer®. The correction factors at each measuring station for both the centerline and the sensor location were calculated and are discussed.

Order-constrained linear optimization.

Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data.

Explicit awareness supports conditional visual search in the retrieval guidance paradigm.

In four experiments we explored whether participants would be able to use probabilistic prompts to simplify perceptually demanding visual search in a task we call the retrieval guidance paradigm. On each trial a memory prompt appeared prior to (and during) the search task and the diagnosticity of the prompt(s) was manipulated to provide complete, partial, or non-diagnostic information regarding the target's color on each trial (Experiments 1-3). In Experiment 1 we found that the more diagnostic prompts was associated with faster visual search performance. However, similar visual search behavior was observed in Experiment 2 when the diagnosticity of the prompts was eliminated, suggesting that participants in Experiment 1 were merely relying on base rate information to guide search and were not utilizing the prompts. In Experiment 3 participants were informed of the relationship between the prompts and the color of the target and this was associated with faster search performance relative to Experiment 1, suggesting that the participants were using the prompts to guide search. Additionally, in Experiment 3 a knowledge test was implemented and performance in this task was associated with qualitative differences in search behavior such that participants that were able to name the color(s) most associated with the prompts were faster to find the target than participants who were unable to do so. However, in Experiments 1-3 diagnosticity of the memory prompt was manipulated via base rate information, making it possible that participants were merely relying on base rate information to inform search in Experiment 3. In Experiment 4 we manipulated diagnosticity of the prompts without manipulating base rate information and found a similar pattern of results as Experiment 3. Together, the results emphasize the importance of base rate and diagnosticity information in visual search behavior. In the General discussion section we explore how a recent computational model of hypothesis generation (HyGene; Thomas, Dougherty, Sprenger, & Harbison, 2008), linking attention with long-term and working memory, accounts for the present results and provides a useful framework of cued recall visual search.

When decision heuristics and science collide.

The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.

What counts as evidence for working memory training? Problems with correlated gains and dichotomization.

The question of whether computerized cognitive training leads to generalized improvements of intellectual abilities has been a popular, yet contentious, topic within both the psychological and neurocognitive literatures. Evidence for the effective transfer of cognitive training to nontrained measures of cognitive abilities is mixed, with some studies showing apparent successful transfer, while others have failed to obtain this effect. At the same time, several authors have made claims about both successful and unsuccessful transfer effects on the basis of a form of responder analysis, an analysis technique that shows that those who gain the most on training show the greatest gains on transfer tasks. Through a series of Monte Carlo experiments and mathematical analyses, we demonstrate that the apparent transfer effects observed through responder analysis are illusory and are independent of the effectiveness of cognitive training. We argue that responder analysis can be used neither to support nor to refute hypotheses related to whether cognitive training is a useful intervention to obtain generalized cognitive benefits. We end by discussing several proposed alternative analysis techniques that incorporate training gain scores and argue that none of these methods are appropriate for testing hypotheses regarding the effectiveness of cognitive training.

Reply to Rouder (2014): good frequentist properties raise confidence.

Established psychological results have been called into question by demonstrations that statistical significance is easy to achieve, even in the absence of an effect. One often-warned-against practice, choosing when to stop the experiment on the basis of the results, is guaranteed to produce significant results. In response to these demonstrations, Bayes factors have been proposed as an antidote to this practice, because they are invariant with respect to how an experiment was stopped. Should researchers only care about the resulting Bayes factor, without concern for how it was produced? Yu, Sprenger, Thomas, and Dougherty (2014) and Sanborn and Hills (2014) demonstrated that Bayes factors are sometimes strongly influenced by the stopping rules used. However, Rouder (2014) has provided a compelling demonstration that despite this influence, the evidence supplied by Bayes factors remains correct. Here we address why the ability to influence Bayes factors should still matter to researchers, despite the correctness of the evidence. We argue that good frequentist properties mean that results will more often agree with researchers' statistical intuitions, and good frequentist properties control the number of studies that will later be refuted. Both help raise confidence in psychological results.