searchRxiv: A Resource for Sharing Database Search Strategies.

Medical librarians can increase their work visibility and highlight their unique role on evidence synthesis teams with searchRxiv, an open access repository that makes librarian's efforts easily citable and resolves longstanding challenges pertaining to reproducing full search strategies within literature review articles. This column will discuss how to navigate searchRxiv to find, reuse, and cite published search strategies, as well as the process of depositing search strategies.

How to Interpret Effect Sizes for Biopsychosocial Outcomes and Implications for Current Research.

Biopsychosocial factors are associated with pain, but they can be difficult to compare. One way of comparing them is to use standardized mean differences. Previously, these effects sizes have been termed as small, medium, or large, if they are bigger than or equal to, respectively, .2, .5, or .8. These cut-offs are arbitrary and recent evidence showed that they need to be reconsidered. We argue it is necessary to determine cut-offs for each biopsychosocial factor. To achieve this, we propose 3 potential approaches: 1) examining, for each factor, how the effect size differs depending upon disease severity; 2) using an existing minimum clinically important difference to anchor the large effect size; and 3) define cut-offs by comparing data from people with and without pain. This is important for pain research, as exploring these methodologies has potential to improve comparability of biopsychosocial factors and lead to more directed treatments. We note assumptions and limitations of these methods that should also be considered. PERSPECTIVE: Standardized mean differences can estimate effect sizes between groups and could theoretically allow for comparison of biopsychosocial factors. However, common thresholds to define effect sizes are arbitrary and likely differ based on outcome. We propose methods that could overcome this and be used to derive biopsychosocial outcome-specific effect sizes.

Understanding 'it depends' in ecology: a guide to hypothesising, visualising and interpreting statistical interactions.

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale - whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry - whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.

A Shape Reconstruction and Measurement Method for Spherical Hedges Using Binocular Vision.

The center coordinate and radius of the spherical hedges are the basic phenotypic features for automatic pruning. A binocular vision-based shape reconstruction and measurement system for front-end vision information gaining are built in this paper. Parallel binocular cameras are used as the detectors. The 2D coordinate sequence of target spherical hedges is obtained by region segmentation and object extraction process. Then, a stereo correcting algorithm is conducted to keep two cameras to be parallel. Also, an improved semi-global block matching (SGBM) algorithm is studied to get a disparity map. According to the disparity map and parallel structure of the binocular vision system, the 3D point cloud of the target is obtained. Based on this, the center coordinate and radius of the spherical hedges can be measured. Laboratory and outdoor tests on shape reconstruction and measurement are conducted. In the detection range of 2,000-2,600 mm, laboratory test shows that the average error and average relative error of standard spherical hedges radius are 1.58 mm and 0.53%, respectively; the average location deviation of the center coordinate of spherical hedges is 15.92 mm. The outdoor test shows that the average error and average relative error of spherical hedges radius by the proposed system are 4.02 mm and 0.44%, respectively; the average location deviation of the center coordinate of spherical hedges is 18.29 mm. This study provides important technical support for phenotypic feature detection in the study of automatic trimming.

Dynamics of Pathogenic Fungi in Field Hedges: Vegetation Cover Is Differentially Impacted by Weather.

Landscape effects might impede or increase spore dispersal and disease risk for crops, as trees and hedges buffer winds and can behave as spore traps, therefore limiting diffusion of fungi, or, on the contrary, behave as disease relay once vegetation is infected and become inoculum sources. In this study, we investigated weekly prevalence of the pathogenic fungus Colletotrichum gloeosporioides on guava tree leaves, differentiating impacts of leaf height on tree, age, and location within leaf. We first estimated differences in prevalence for each covariate, and then related infection rates to weather effects during the year. Our results highlighted a great variance of prevalence among individual trees, and a lower contamination of tree tops, as well as a tendency for greater odds of infection in tips of young leaves compared to older ones. Last, we show evidence that individual tree contaminations are associated with different disease dynamics: early and dispersal-based, late and growth-based, as well as with intermediate dynamic ranges. Pathogen infection dynamics will thus be greatly impacted by cover characteristics at local scale, and tree cover should not be perceived as homogeneously driving disease levels.

Understanding the effects of roadside hedges on the horizontal and vertical distributions of air pollutants in street canyons.

Built-up environments limit air pollution dispersion in street canyons and lead to complex trade-offs between green infrastructure (GI) usage and its potential to reduce near-road exposure. This study evaluated the effects of an evergreen hedge on the distribution of particulate matter (PM1, PM2.5, PM10), black carbon (BC) and particle number concentrations (PNCs) in a street canyon in West London. Instrumentation was deployed around the hedge at 13 fixed locations to assess the impact of the hedge on vertical and horizontal concentration distributions. Changes in concentrations behind the hedge were measured with reference to the corresponding sampling point in front of the hedge for all sets of measurements. Results showed a significant reduction in vertical concentrations between 1 and 1.7 m height, with maximum reductions of -16% (PM1 and PM10) and -17% (PM2.5) at âˆ¼1 m height. Horizontal concentrations revealed two zones between the building façade and the hedge, with opposite trends: (i) close to hedge (within 0.2 m), where a reduction of PM1 and PM2.5 was observed, possibly due to dilution, deposition and the barrier effect; and (ii) 0.2-3 m from the hedge, showing an increase of 13-37% (PM1) and 7-21% (PM2.5), possibly due to the blockage effect of the building, restricting dispersion. BC showed a significant reduction at breathing height (1.5 m) of between -7 and -50%, followed by -15% for PNCs in the 0.02-1 µm size range. The ELPI + analyser showed a peak of âˆ¼30 nm. The presence of the hedge led to a âˆ¼39 ± 32% decrease in total PNCs (0.006-10 µm), suggesting a greater removal in different modes, such as a 83 ± 12% reduction in nucleation mode (0.006-0.030 µm), 74 ± 15% in ultrafine (≤0.1 µm), and 34 ± 30% in accumulation mode (0.03-0.3 µm). These findings indicate graded filtering of particles by GI in a near-road street canyon environment. This insight will guide the improved design of GI barriers and the validation of microscale dispersion models.

A case for associational resistance: Apparent support for the stress gradient hypothesis varies with study system.

According to the stress gradient hypothesis (SGH), ecological interactions between organisms shift positively as environmental stress increases. In the case of associational resistance, habitat is modified to ameliorate stress, benefitting other organisms. The SGH is contentious due to conflicting evidence and theoretical perspectives, so we adopted a meta-analytic approach to determine if it is widely supported across a variety of contexts, including different kingdoms, ecosystems, habitats, interactions, stressors, and life history stages. We developed an extensive list of Boolean search criteria to search the published ecological literature and successfully detect studies that both directly tested the hypothesis, and those that were relevant but never mentioned it. We found that the SGH is well supported by studies that feature bacteria, plants, terrestrial ecosystems, interspecific negative interactions, adults, survival instead of growth or reproduction, and drought, fire, and nutrient stress. We conclude that the SGH is indeed a broadly relevant ecological hypothesis that is currently held back by cross-disciplinary communication barriers. More SGH research is needed beyond the scope of interspecific plant competition, and more SGH research should feature multifactor stress. There remains a need to account for positive interactions in scientific pursuits, such as associational resistance in tests of the SGH.

Evaluation of various estimators for standardized mean difference in meta-analysis.

Meta-analyses of a treatment's effect compared with a control frequently calculate the meta-effect from standardized mean differences (SMDs). SMDs are usually estimated by Cohen's d or Hedges' g. Cohen's d divides the difference between sample means of a continuous response by the pooled standard deviation, but is subject to nonnegligible bias for small sample sizes. Hedges' g removes this bias with a correction factor. The current literature (including meta-analysis books and software packages) is confusingly inconsistent about methods for synthesizing SMDs, potentially making reproducibility a problem. Using conventional methods, the variance estimate of SMD is associated with the point estimate of SMD, so Hedges' g is not guaranteed to be unbiased in meta-analyses. This article comprehensively reviews and evaluates available methods for synthesizing SMDs. Their performance is compared using extensive simulation studies and analyses of actual datasets. We find that because of the intrinsic association between point estimates and standard errors, the usual version of Hedges' g can result in more biased meta-estimation than Cohen's d. We recommend using average-adjusted variance estimators to obtain an unbiased meta-estimate, and the Hartung-Knapp-Sidik-Jonkman method for accurate estimation of its confidence interval.

Effect sizes of the differences between means without assuming variance equality and between a mean and a constant.

Effect sizes of the difference, or standardized mean differences, are widely used for meta-analysis or power-analysis. However, common effect sizes of the difference such as Cohen's d or Hedges' d assume variance equality that is fragile and is often violated in practical applications. Based on Welch's t tests, we defined a new effect size of the difference between means, which did not assume variance equality, thereby providing a more accurate value for data with unequal variance. In addition, we presented the unbiased estimator of an effect size of the difference between a mean and a known constant. An R package is also provided to compute these effect sizes with their variance and confidence interval.

Enhanced activity of soil nutrient-releasing enzymes after plant invasion: a meta-analysis.

Plant invasion can significantly alter soil nutrient cycling of ecosystems. How these changes are linked to soil enzyme activities is still unknown, however, even though these are proximate agents of organic matter decomposition and nutrient release. We performed a meta-analysis of 60 case studies examining responses of 10 unique soil enzymes to plant invasion, and tested whether invaded soils differed in their enzyme activities from uninvaded soils. We also examined whether increases in soil nutrient-releasing enzyme activity were paralleled by enhanced soil nutrient availability after plant invasion. Overall, we found that plant invasion had significant impacts on the activities of seven types of soil enzymes. Plant invasion had inconsistent impacts on C-decomposing enzymes, but invaded sites had significantly higher activities of soil enzymes related to N- and P-release than noninvaded sites. Increases in nutrient-releasing enzyme activity after plant invasion ranged from +23% to +69%, which potentially results in a linear increase of soil nutrient availability in response to enhanced enzyme activities. Invaded soils also had higher nutrient stocks and soil microbial biomass than uninvaded soils. Our results suggest that enhanced activity of soil nutrient-releasing enzymes after plant invasion may accelerate nutrient cycling, potentially creating a nutrient-rich soil environment that benefits invaders and promotes their persistence, as invasive plants often appear to be more resource-demanding and competitive than native species.

Development and validation of a search filter to identify equity-focused studies: reducing the number needed to screen.

BACKGROUND: Health inequalities, worse health associated with social and economic disadvantage, are reported by a minority of research articles. Locating these studies when conducting an equity-focused systematic review is challenging due to a deficit in standardised terminology, indexing, and lack of validated search filters. Current reporting guidelines recommend not applying filters, meaning that increased resources are needed at the screening stage. METHODS: We aimed to design and test search filters to locate studies that reported outcomes by a social determinant of health. We developed and expanded a 'specific terms strategy' using keywords and subject headings compiled from recent systematic reviews that applied an equity filter. A 'non-specific strategy' was compiled from phrases used to describe equity analyses that were reported in titles and abstracts, and related subject headings. Gold standard evaluation and validation sets were compiled. The filters were developed in MEDLINE, adapted for Embase and tested in both. We set a target of 0.90 sensitivity (95% CI; 0.84, 0.94) in retrieving 150 gold standard validation papers. We noted the reduction in the number needed to screen in a proposed equity-focused systematic review and the proportion of equity-focused reviews we assessed in the project that applied an equity filter to their search strategy. RESULTS: The specific terms strategy filtered out 93-95% of all records, and retrieved a validation set of articles with a sensitivity of 0.84 in MEDLINE (0.77, 0.89), and 0.87 (0.81, 0.92) in Embase. When combined (Boolean 'OR') with the non-specific strategy sensitivity was 0.92 (0.86, 0.96) in MEDLINE (Embase 0.94; 0.89, 0.97). The number needed to screen was reduced by 77% by applying the specific terms strategy, and by 59.7% (MEDLINE) and 63.5% (Embase) by applying the combined strategy. Eighty-one per cent of systematic reviews filtered studies by equity. CONCLUSIONS: A combined approach of using specific and non-specific terms is recommended if systematic reviewers wish to filter studies for reporting outcomes by social determinants. Future research should concentrate on the indexing standardisation for equity studies and further development and testing of both specific and non-specific terms for accurate study retrieval.

Correction for bias in meta-analysis of little-replicated studies.

Meta-analyses conventionally weight study estimates on the inverse of their error variance, in order to maximize precision. Unbiased variability in the estimates of these study-level error variances increases with the inverse of study-level replication. Here, we demonstrate how this variability accumulates asymmetrically across studies in precision-weighted meta-analysis, to cause undervaluation of the meta-level effect size or its error variance (the meta-effect and meta-variance).Small samples, typical of the ecological literature, induce big sampling errors in variance estimation, which substantially bias precision-weighted meta-analysis. Simulations revealed that biases differed little between random- and fixed-effects tests. Meta-estimation of a one-sample mean from 20 studies, with sample sizes of 3-20 observations, undervalued the meta-variance by c. 20%. Meta-analysis of two-sample designs from 20 studies, with sample sizes of 3-10 observations, undervalued the meta-variance by 15%-20% for the log response ratio (lnR); it undervalued the meta-effect by c. 10% for the standardized mean difference (SMD).For all estimators, biases were eliminated or reduced by a simple adjustment to the weighting on study precision. The study-specific component of error variance prone to sampling error and not parametrically attributable to study-specific replication was replaced by its cross-study mean, on the assumptions of random sampling from the same population variance for all studies, and sufficient studies for averaging. Weighting each study by the inverse of this mean-adjusted error variance universally improved accuracy in estimation of both the meta-effect and its significance, regardless of number of studies. For comparison, weighting only on sample size gave the same improvement in accuracy, but could not sensibly estimate significance.For the one-sample mean and two-sample lnR, adjusted weighting also improved estimation of between-study variance by DerSimonian-Laird and REML methods. For random-effects meta-analysis of SMD from little-replicated studies, the most accurate meta-estimates obtained from adjusted weights following conventionally weighted estimation of between-study variance.We recommend adoption of weighting by inverse adjusted-variance for meta-analyses of well- and little-replicated studies, because it improves accuracy and significance of meta-estimates, and it can extend the scope of the meta-analysis to include some studies without variance estimates.

Utilização de diagramas causais e a comunicação de fontes de incerteza em estudos observacionais / Use of causal DAG and reporting of uncertainty in observational studies

Os diagramas causais (gráficos acíclicos direcionados ­ DAG) têm sido apontados como uma das principais ferramentas que podem contribuir para a qualidade metodológica e do relato de estudos observacionais. No entanto, pouco se sabe sobre como essas ferramentas têm sido utilizadas nas investigações empíricas. Neste trabalho, foi realizada uma revisão da literatura com o objetivo de descrever o quanto, como e onde os diagramas causais têm sido utilizados em estudos observacionais analíticos nos últimos 18 anos. Foram realizadas buscas por citações e pesquisas por palavras-chaves nas bases de dados do PubMed e Web of Science. Em uma amostra de 100 artigos que apresentaram a estrutura causal, foram avaliadas as características dos modelos gráficos e o relato de confundimento. Além disso, foi realizada uma análise comparativa do relato das limitações do estudo e da frequência de marcadores linguísticos de incerteza (hedges) nos artigos com e sem a utilização de DAG causais. Foram identificadas 1034 publicações, totalizando 5021 autores e 85 países de afiliação. Apenas 430 artigos (42%) forneceram a estrutura gráfica. A maioria das publicações contém apenas um DAG causal (87%) e poucos modelos gráficos contêm confundidores não observados (23%), ou a representação de erros de mensuração (6%) e mecanismos de seleção (3%). O relato de modificações no conjunto de ajuste foi observado em 19% das publicações. Além disso, 20% foram classificadas como possível ocorrência da falácia da tabela 2. O número de limitações do estudo reconhecidas pelos autores e a frequência de marcadores de incerteza foram semelhantes nas amostras de artigos com e sem diagramas causais. No entanto, o relato de avaliações quantitativas das limitações do estudo foi mais frequente entre os artigos com DAG (52% vs. 21%). Há necessidade de mais discussões e estudos sobre a construção e análise de modelos causais e o desenvolvimento de recomendações gerais para apresentação de DAG causais nos artigos científicos

Effects of livestock grazing on rangeland biodiversity: A meta-analysis of grouse populations.

Livestock grazing affects over 60% of the world's agricultural lands and can influence rangeland ecosystem services and the quantity and quality of wildlife habitat, resulting in changes in biodiversity. Concomitantly, livestock grazing has the potential to be detrimental to some wildlife species while benefiting other rangeland organisms. Many imperiled grouse species require rangeland landscapes that exhibit diverse vegetation structure and composition to complete their life cycle. However, because of declining populations and reduced distributions, grouse are increasingly becoming a worldwide conservation concern. Grouse, as a suite of upland gamebirds, are often considered an umbrella species for other wildlife and thus used as indicators of rangeland health. With a projected increase in demand for livestock products, better information will be required to mitigate the anthropogenic effects of livestock grazing on rangeland biodiversity. To address this need, we completed a data-driven and systematic review of the peer-reviewed literature to determine the current knowledge of the effects of livestock grazing on grouse populations (i.e., chick production and population indices) worldwide. Our meta-analysis revealed an overall negative effect of livestock grazing on grouse populations. Perhaps more importantly, we identified an information void regarding the effects of livestock grazing on the majority of grouse species. Additionally, the reported indirect effects of livestock grazing on grouse species were inconclusive and more reflective of differences in the experimental design of the available studies. Future studies designed to evaluate the direct and indirect effects of livestock grazing on wildlife should document (i) livestock type, (ii) timing and frequency of grazing, (iii) duration, and (iv) stocking rate. Much of this information was lacking in the available published studies we reviewed, but is essential when making comparisons between different livestock grazing management practices and their potential impacts on rangeland biodiversity.

Tree Wave Migration Across an Elevation Gradient in the Altai Mountains, Siberia.

The phenomenon of "tree waves" (hedges and ribbons) formation within the alpine ecotone in Altai Mountains and its response to observed air temperature increase was considered. At the upper limit of tree growth Siberian pine (Pinus sibirica) forms hedges on windward slopes and ribbons on the leeward ones. Hedges were formed by prevailing winds and oriented along winds direction. Ribbons were formed by snow blowing and accumulating on the leeward slope and perpendicular to the prevailing winds, as well as to the elevation gradient. Hedges were always linked with microtopography features, whereas ribbons were not. Trees are migrating upward by waves and new ribbons and hedges are forming at or near tree line, whereas at lower elevations ribbons and hedges are being transformed into closed forests. Time series of high-resolution satellite scenes (from 1968 to 2010) indicated an upslope shift in the position ribbons averaged 155±26 m (or 3.7 m yr-1) and crown closure increased (about 35-90%). The hedges advance was limited by poor regeneration establishment and was negligible. Regeneration within the "ribbon zone" was approximately 2.5 times (5060 vs 2120 ha-1) higher then within the "hedges zone". During the last four decades, Siberian pine in both hedges and ribbons strongly increased its growth increment and recent tree growth rate for 50 year old trees was about twice higher than recorded for similarly aged trees at the beginning of the 20th century. Hedges and ribbons are phenomena that are widespread within the southern and northern Siberian Mountains.

Differences between urban and rural hedges in England revealed by a citizen science project.

BACKGROUND: Hedges are both ecologically and culturally important and are a distinctive feature of the British landscape. However the overall length of hedges across Great Britain is decreasing. Current challenges in studying hedges relate to the dominance of research on rural, as opposed to urban, hedges, and their variability and geographical breadth. To help address these challenges and to educate the public on the importance of hedge habitats for wildlife, in 2010 the Open Air Laboratories (OPAL) programme coordinated a hedge-focused citizen science survey. RESULTS: Results from 2891 surveys were analysed. Woody plant species differed significantly between urban and rural areas. Beech, Holly, Ivy, Laurel, Privet and Yew were more commonly recorded in urban hedges whereas Blackthorn, Bramble, Dog Rose, Elder and Hawthorn were recorded more often in rural hedges. Urban and rural differences were shown for some groups of invertebrates. Ants, earwigs and shieldbugs were recorded more frequently in urban hedges whereas blowflies, caterpillars, harvestmen, other beetles, spiders and weevils were recorded more frequently in rural hedges. Spiders were the most frequently recorded invertebrate across all surveys. The presence of hard surfaces adjacent to the hedge was influential on hedge structure, number and diversity of plant species, amount of food available for wildlife and invertebrate number and diversity. In urban hedges with one adjacent hard surface, the food available for wildlife was significantly reduced and in rural hedges, one adjacent hard surface affected the diversity of invertebrates. CONCLUSIONS: This research highlights that urban hedges may be important habitats for wildlife and that hard surfaces may have an impact on both the number and diversity of plant species and the number and diversity of invertebrates. This study demonstrates that citizen science programmes that focus on hedge surveillance can work and have the added benefit of educating the public on the importance of hedgerow habitats.

Crop cover the principal influence on non-crop ground beetle (Coleoptera, Carabidae) activity and assemblages at the farm scale in a long-term assessment.

Ground beetle data were generated using pitfall traps in the 17-year period from 1993 to 2009 and used to investigate the effects of changes in surrounding crop cover on beetle activity and assemblages, together with the effects of weather variability. Beetles were recorded from non-crop field margins (overgrown hedges). Crop cover changes explained far more variation in the beetle assemblages recorded than did temperature and rainfall variation. A reduction in management intensity and disturbance in the crops surrounding the traps, especially the introduction and development of willow coppice, was concomitant with changes in individual species activity and assemblage composition of beetles trapped in non-crop habitat. There were no consistent patterns in either overall beetle activity or in the number of species recorded over the 17-year period, but there was a clear change from assemblages dominated by smaller species with higher dispersal capability to ones with larger beetles with less dispersal potential and a preference for less disturbed agroecosystems. The influence of surrounding crops on ground beetle activity in non-crop habitat has implications for ecosystem service provision by ground beetles as pest predators. These results are contrary to conventional assumptions and interpretations, which suggest activity of pest predators in crops is influenced primarily by adjacent non-crop habitat. The long-term nature of the assessment was important in elucidation of patterns and trends, and indicated that policies such as agri-environment schemes should take cropping patterns into account when promoting management options that are intended to enhance natural pest control.

Calculando o tamanho de efeito no SPSS / Calculating the Effect Size in SPSS

O tamanho de efeito é uma estatística descritiva que serve como complemento aoteste de significância estatística. Cada vez mais esse tipo de abordagem vem sendoestimulada, em alguns casos até exigida, pelas publicações da área científica.Foram escolhidas algumas medidas de tamanho de efeito para uma explicaçãomais detalhada: o tamanho de efeito de d de Cohen, g de Hedges, D de Glass paracomparação das médias de dois grupos e o f2 de Cohen utilizado na análise demedidas correlacionadas. Esses tamanhos de efeito foram calculados em exemplosobtidos a partir de simulação usando o SPSS v.18.0.0.

Effect size is a descriptive statistic that complements the statistical significancetest. The use of this type of approach has been increasingly stimulated, or evenrequired, in scientific publications. We selected some measures of effect size inorder to provide a more detailed explanation: the effect size of Cohen’s d, Hedges’g, Δ of Glass for comparison of the means of two groups, and Cohen’s f² was used inthe analysis of correlated measures. These effect sizes were calculated in samplesobtained from simulation using the SPSS v.18.