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opencc-zeroMar 2022View details →

Cheirogaleus population density meta-analysis data

Aim: Global animal populations are in decline due to destruction and degradation of their natural habitat. Understanding the factors that determine the distribution and density of threatened animal populations is therefore now a crucial component of their study and conservation. The Cheirogaleidae are a diverse family of small-bodied, nocturnal lemurs that are widespread throughout the forests of Madagascar. However, many cheirogaleid lemurs are now highly threatened with extinction and the environmental factors that determine their distribution and population density are still little known. Here, I investigated the environmental drivers of Cheirogaleidae population density at genus level. Location: Various forest sites across Madagascar. Methods: I investigated how six environmental variables affect Cheirogaleidae population density at the genus level via random effect meta-analyses. I then used a Generalized Linear Mixed-effects Model to identify the primary predictors of Cheirogaleidae population density. Finally, I investigated how the population density of this family of lemurs varies between protected and unprotected areas of Madagascar via a GLM analysis. Results: My results indicate that the relationships between the tested environmental factors and population density are genus-specific among the Cheirogaleidae. Rather remarkably, the density of Microcebus appears to have a profoundly positive relationship with anthropogenic disturbance and a negative relationship with forest cover, a finding that is also reflected by larger population densities within unprotected areas in comparison to localities within Madagascar's protected area network. Main Conclusions: The results of this study are highly encouraging for the conservation of the Cheirogaleidae and highlight the remarkable resilience of these lemurs to habitat degradation and anthropogenic activity. However, this study also outlines the dearth of knowledge that we have for many species, and why these data are urgently needed to understand the biogeography and ecology of threatened animal populations and implement successful conservation.

opencc-zeroDec 2014View details →

Data from: A systematic review and meta-analysis of gene therapy in animal models of cerebral glioma: why did promise not translate to human therapy?

Background: The development of therapeutics is often characterized by promising animal research that fails to translate into clinical efficacy; this holds for the development of gene therapy in glioma. We tested the hypothesis that this is because of limitations in the internal and external validity of studies reporting the use of gene therapy in experimental glioma. Method: We systematically identified studies testing gene therapy in rodent glioma models by searching three online databases. The number of animals treated and median survival were extracted and studies graded using a quality checklist. We calculated median survival ratios and used random effects meta-analysis to estimate efficacy. We explored effects of study design and quality and searched for evidence of publication bias. Results: We identified 193 publications using gene therapy in experimental glioma, including 6,366 animals. Overall, gene therapy improved median survival by a factor of 1.60 (95% CI 1.53–1.67). Study quality was low and the type of gene therapy did not account for differences in outcome. Study design characteristics accounted for a significant proportion of between-study heterogeneity. We observed similar findings in a data subset limited to the most common gene therapy. Conclusion: As the dysregulation of key molecular pathways is characteristic of gliomas, gene therapy remains a promising treatment for glioma. Nevertheless, we have identified areas for improvement in conduct and reporting of studies, and we provide a basis for sample size calculations. Further work should focus on genes of interest in paradigms recapitulating human disease. This might improve the translation of such therapies into the clinic.

opencc-zeroDec 2010View details →

Data from: A meta-analysis of factors affecting local adaptation between interacting species

Adaptive divergence among populations can result in local adaptation, whereby genotypes in native environments exhibit greater fitness than genotypes in novel environments. A body of theory has developed that predicts how different species traits, such as rates of gene flow and generation times, influence local adaptation in coevolutionary species interactions. We used a meta‐analysis of local‐adaptation studies across a broad range of host‐parasite interactions to evaluate predictions about the effect of species traits on local adaptation. We also evaluated how experimental design influences the outcome of local adaptation experiments. In reciprocally designed experiments, the relative gene flow rate of hosts versus parasites was the strongest predictor of local adaptation, with significant parasite local adaptation only in the studies in which parasites had greater gene flow rates than their hosts. When nonreciprocal studies were included in analyses, species traits did not explain significant variation in local adaptation, although the overall level of local adaptation observed was lower in the nonreciprocal than in the reciprocal studies. This formal meta‐analysis across a diversity of host‐parasite systems lends insight into the role of both biology (species traits) and biologists (experimental design) in detecting local adaptation in coevolving species interactions.

opencc-zeroFeb 2020View details →

Biological subtypes of Alzheimer's disease: a systematic review and meta-analysis

Objective: We conducted a systematic review and meta-analysis on subtype studies of Alzheimer's disease (AD) based on postmortem and neuroimaging data, with the ultimate goal of advancing our understanding of mechanisms driving heterogeneity in AD. Methods: EMBASE, PubMed and Web of Science databases were consulted until July 2019. Results: Neuropathology and neuroimaging studies have consistently identified three subtypes of AD based on the distribution of tau-related pathology and regional brain atrophy: typical, limbic-predominant, and hippocampal-sparing AD. A fourth subtype, minimal atrophy AD, has been identified in several neuroimaging studies. Typical AD displays tau-related pathology and atrophy both in hippocampus and association cortex, and has a pooled frequency of 55%. Limbic-predominant, hippocampal-sparing, and minimal atrophy AD had a pooled frequency of 21%, 17%, and 15%, respectively. Between-subtype differences were found in age at onset, age at assessment, sex distribution, years of education, global cognitive status, disease duration, APOE e4 genotype, and CSF biomarker levels. Conclusion: We identified two core dimensions of heterogeneity: "typicality" and "severity". We propose that these two dimensions determine individuals' belonging to one of the AD subtypes based on the combination of protective factors, risk factors, and concomitant non-AD brain pathologies. This model is envisioned to aid with framing hypotheses, study design, results interpretation, and understanding mechanisms in future subtype studies. Unraveling the heterogeneity within AD is critical for implementing precision medicine approaches and for ultimately developing successful disease-modifying drugs for AD.

Data from: Meta‐analysis of chromosome‐scale crossover rate variation in eukaryotes and its significance to evolutionary genomics

Understanding the distribution of crossovers along chromosomes is crucial to evolutionary genomics because the crossover rate determines how strongly a genome region is influenced by natural selection. Nevertheless, generalities in the chromosome-scale distribution of crossovers have not been investigated formally. We fill this gap by synthesizing joint information on genetic and physical maps across 62 animal, plant, and fungal species. Our quantitative analysis reveals a strong and taxonomically wide-spread reduction of the crossover rate in the center of chromosomes relative to their peripheries. We demonstrate that this pattern is poorly explained by the position of the centromere, but find that the magnitude of the relative reduction in the crossover rate in chromosome centers increases with chromosome length. That is, long chromosomes often display a dramatically low crossover rate in their center whereas short chromosomes exhibit a relatively homogeneous crossover rate. This observation is compatible with a model in which crossovers are initiated from the chromosome tips, an idea with preliminary support from mechanistic investigations of meiotic recombination. Consequently, we show that organisms achieve a higher genome-wide crossover rate by evolving smaller chromosomes. Summarizing theory and providing empirical examples, we finally highlight that taxonomically wide-spread and systematic heterogeneity in crossover rate along chromosomes generates predictable broad-scale trends in genetic diversity and population differentiation by modifying the impact of natural selection among regions within a genome. We conclude by emphasizing that chromosome-scale heterogeneity in crossover rate should urgently be incorporated into analytical tools in evolutionary genomics, and in the interpretation of emerging patterns.

opencc-zeroDec 2016View details →

Data from: Environmental stress correlates with increases in both genetic and residual variances: a meta-analysis of animal studies

Adaptive evolutionary responses are determined by the strength of selection and the amount of genetic variation within traits, however, both are known to vary across environmental conditions. As selection is generally expected to be strongest under stressful conditions, understanding how the expression of genetic variation changes across stressful and benign environmental conditions is crucial for predicting the rate of adaptive change. While theory generally predicts increased genetic variation under stress, previous syntheses of the field has found limited support for this notion. These studies have focused on heritability, which is dependent on other environmentally sensitive, but non-genetic, sources of variation. Here, we aim to complement these studies with a meta-analysis where we examine changes in coefficient of variation (CV) in maternal, genetic, and residual variances across stressful and benign conditions. Confirming previous analyses, we did not find any clear direction in how heritability changes across stressful and benign conditions. However, when analyzing CV, we found higher genetic and residual variance under highly stressful conditions in life-history traits but not in morphological traits. Our findings are of broad significance to contemporary evolution suggesting that rapid evolutionary adaptive response may be mediated by increased evolutionary potential in stressed populations.

Data from: NMDA receptor antagonists and pain relief: a meta-analysis of experimental trials

OBJECTIVES: We conducted a meta-analysis of controlled trials that used experimental models of acute pain and hyperalgesia to examine the analgesic effects of N-methyl-D-aspartate receptor (NMDAR) antagonists. METHODS: Six major databases were systematically searched (to 03/2018) for studies using human evoked pain models to compare NMDAR antagonists with no-intervention controls. Pain outcome data were analyzed with random-effects meta-analysis. RESULTS: Searches identified 70 eligible trials (N=1069). Meta-analysis found that low-dose ketamine (<1 mg/kg) produced a decrease in the size of hyperalgesic area (Standardized Mean Difference=0.54, CI95[0.34, 0.74], p<.001), and a 1.2-point decrease (CI95[0.88, 1.44], p<.001) in pain ratings from 4.6 to 3.4 on a 0-10 scale (a 26% reduction). Similar analgesia was observed for acute and hyperalgesic models and was constant across the dosing range (0.03-1.00 mg/kg). Moderate-high variability in effect size was observed and mild side effects (e.g. sedation, sensory disturbance) were common. No effects of dextromethorphan were found. CONCLUSIONS: Findings provide robust evidence for analgesic and anti-hyperalgesic effects of ketamine, supporting its utility for acute and chronic pain management. However, pain relief was modest, suggesting ketamine may potentially be most useful when opioids are contraindicated, rapid analgesia is required or for pain resistant to conventional medication.

Data from: A meta-analysis of the agents of selection on floral traits

Floral traits are hypothesized to evolve primarily in response to selection by pollinators. However, selection can also be mediated by other environmental factors. To understand the relative importance of pollinator-mediated selection and its variation among trait and pollinator types, we analyzed directional selection gradients on floral traits from experiments that manipulated the environment to identify agents of selection. Pollinator-mediated selection was stronger than selection by other biotic factors (e.g. herbivores), but similar in strength to selection by abiotic factors (e.g. soil water), providing partial support for the hypothesis that floral traits evolve primarily in response to pollinators. Pollinator-mediated selection was stronger on pollination efficiency traits than on other trait types, as expected if efficiency traits affect fitness via interactions with pollinators, but other trait types also affect fitness via other environmental factors. In addition to varying among trait types, pollinator-mediated selection varied among pollinator taxa: selection was stronger when bees, long-tongued flies, or birds were the primary visitors than when the primary visitors were Lepidoptera or multiple animal taxa. Finally, reducing pollinator access to flowers had a relatively small effect on selection on floral traits, suggesting that anthropogenic declines in pollinator populations would initially have modest effects on floral evolution.

opencc-zeroDec 2014View details →

Data from: The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta-analysis

Introduction: There is little evidence regarding the influence of conflicts of interest on preclinical research. This study examines whether industry sponsorship is associated with increased risks of bias and/or effect sizes of outcomes in published preclinical thiazolidinedione (TZD) studies. Methods: We identified preclinical TZD studies published between January 1, 1965, and November 14, 2012. Coders independently extracted information on study design criteria aimed at reducing bias, results for all relevant outcomes, sponsorship source and investigator financial ties from the 112 studies meeting the inclusion criteria. The average standardized mean difference (SMD) across studies was calculated for plasma glucose (efficacy outcome) and weight gain (harm outcome). In subgroup analyses, TZD outcomes were assessed by sponsorship source and risk of bias criteria. Results: Seven studies were funded by industry alone, 17 studies funded by both industry and non-industry, 49 studies funded by non-industry alone and 39 studies had no disclosures. None of the studies used sample size calculations, intention-to-treat analyses, blinding of investigators or concealment of allocation. Most studies reported favourable results (88 of 112) and conclusions (95 of 112) supporting TZD use. Efficacy estimates were significantly larger in six studies sponsored by industry alone (−3.41; 95% CI −5.21, −1.53; I2 = 93%) versus 42 studies sponsored by non-industry sources (−0.97; 95% CI −1.37, −0.56; I2 = 81%; p-value = 0.01). Harms estimates were significantly larger in four studies sponsored by industry alone (5.00; 95% CI 1.22, 8.77; I2 = 93%) versus 38 studies sponsored by non-industry sources (0.30; 95% CI −0.08, 0.68; I2 = 79%; p-value = 0.02). TZD efficacy and harms did not differ by disclosure of financial COIs or risks of bias. Conclusions: Industry-sponsored TZD animal studies have exaggerated efficacy and harms outcomes compared with studies funded by non-industry sources. There was poor reporting of COIs.

opencc-zeroOct 2019View details →

Data from: Epidemiology of placenta previa accreta: a systematic review and meta-analysis

Objective To estimate the prevalence and incidence of placenta previa complicated by placenta accreta spectrum (PAS) and to examine the different criteria being used for the diagnosis. Design Systematic review and meta-analysis. Methods PubMed, Google Scholar, clinicalTrials.gov and MEDLINE were searched between August 1982 and September 2018 for studies reporting on placenta previa and placenta previa with PAS diagnosed in a defined obstetric population. Two independent reviewers performed the data extraction using a predefined protocol and assessed the risk of bias using the Newcastle-Ottawa scale for observational studies, with difference agreed by consensus. The primary outcomes were overall prevalence of placenta previa, incidence of PAS according to the type of placenta previa and the reported clinical outcomes including number of peri-partum hysterectomies and direct maternal mortality. The secondary outcomes included the criteria used for the prenatal ultrasound diagnosis of placenta previa and the criteria used to diagnose and grade PAS at birth. Results A total of 258 articles were reviewed and 13 retrospective and 7 prospective studies were included in the analysis which reported on 587 women with placenta previa and PAS. The median prevalence of placenta previa was 0.56% (IQR 0.39;1.24) whereas the median prevalence of placenta previa with PAS was 0.07% (IQR 0.05;0.16). The incidence of PAS in women with a placenta previa was 11.10% (IQR 7.65;17.35). The meta-analysis indicated a significant level of overall heterogeneity between study estimates for the prevalence of placenta previa (P<.001), the prevalence of placenta previa with PAS and the incidence of PAS in the placenta previa cohort. The high heterogeneity between studies emphasizing the need to implement standardized protocols for the diagnoses of both placenta previa and PAS, including the type of placenta previa on ultrasound imaging and grading of villous invasiveness at delivery.

Data from: What is behind the variation in mate quality dependent sex ratio adjustment? – A meta-analysis

Theory predicts that parents adjust the sex ratio of their brood to the sexually selected traits of their mate because the reproductive success of sons may be more dependent on inherited paternal attractiveness than that of daughters. Empirical studies vary in terms of whether they support the theory, and this variation has often been regarded as evidence against sex ratio adjustment or has been ascribed to methodological differences. Applying phylogenetic meta-analyses, we aimed to find biological explanations for the variation observed in songbirds. In particular, we tested the role extra-pair paternity, because infidelity occurs in the majority of these species and may reduce the adaptive value of adjusting brood sex ratio to the phenotype of the social mate. However, we found that the variation in effect sizes was unrelated to the proportion of extra-pair paternity. Thus future studies should consider that mate quality dependent sex ratio adjustment may be driven by direct (material) rather than indirect (genetic) benefits. We also tested if the effect sizes are influenced by whether the focal male trait is indeed under sexual selection as it is assumed by the sex allocation theory. We found that for male traits with proven role in sexual selection, effect sizes significantly differed from the null expectation of random production of sons and daughters. For male traits with only presumed sexual role in sexual selection, the deviation from the null expectation was less convincing, and the effect sizes were significantly smaller. This result indicates that studies that neglect the assumptions of the hypotheses concerned, may lead to the underestimation of the mean effect size and, eventually, false conclusions.

opencc-zeroDec 2016View details →

Data from: Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis

Objective: The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using in-built smartphone-sensors. Methods: Systematic Review - Medline, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until December 15th, 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used in-built sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the QUADAS-2 tool and the reporting quality with the STARD statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarized. Results We screened 3'296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1'048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % confidence interval (CI); 0.56 to 0.94) and 0.89 (95 %CI; 0.70 to 0.97) for specificity. Conclusions The diagnostic evidence of available health apps on Apple's and Google's app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.

Data from: Meta-analysis reveals enhanced growth of marine harmful algae from temperate regions with warming and elevated CO2 levels

Elevated pCO2 and warming may promote algal growth and toxin production, and thereby possibly support the proliferation and toxicity of HABs. Here, we tested whether empirical data supports this hypothesis using a meta-analytic approach and investigated the responses of growth rate and toxin content or toxicity of numerous marine and estuarine HAB species to elevated pCO2 and warming. Most of the available data on HAB responses towards the two tested climate change variables concerns dinoflagellates, as many members of this phytoplankton group are known to cause HAB outbreaks. Toxin content and toxicity did not reveal a consistent response towards both tested climate change variables, while growth rate increased consistently with elevated pCO2 . Warming also led to higher growth rates, but only for species isolated at higher latitudes. The observed gradient in temperature growth responses shows the potential for enhanced development of HABs at higher latitudes. Increases in growth rates with more CO2 may present an additional competitive advantage for HAB species, particularly as CO2 was not shown to enhance growth rate of other non-HAB phytoplankton species. However, this may also be related to the difference in representation of dinoflagellate and diatom species in the respective HAB and non-HAB phytoplankton groups. Since the proliferation of HAB species may strongly depend on their growth rates, our results warn for a greater potential of dinoflagellate HAB development in future coastal waters, particularly in temperate regions.

opencc-zeroDec 2015View details →

Data from: Efficacy and safety of bevacizumab plus erlotinib versus bevacizumab or erlotinib alone in the treatment of non-small-cell lung cancer: a systematic review and meta-analysis

Objectives: Bevacizumab and erlotinib inhibit different tumour growth pathways, and both exhibit beneficial effects in the treatment of non-small-cell lung cancer (NSCLC). However, the efficacy of bevacizumab in combination with erlotinib remains controversial. Therefore, we conducted a meta-analysis to compare combination treatment with bevacizumab and erlotinib to bevacizumab or erlotinib monotherapy in the treatment of NSCLC. Methods: Randomised controlled trials (RCTs) published in PubMed, Web of Science and EMBASE were systematically reviewed. The main outcome measures included overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and adverse events. Results were expressed as HRs or risk ratios (RRs) with 95% CIs. Results: 5 RCTs involving a total of 1736 patients were included in this meta-analysis. The combination of bevacizumab and erlotinib significantly improved PFS (HR=0.63, 95% CI 0.53 to 0.75; p=0.000) and the ORR (RR=1.91, 95% CI 1.19 to 3.06; p=0.007) in the second-line treatment of NSCLC compared with bevacizumab or erlotinib alone. However, no significant difference in OS was observed between the combination and monotherapy groups (HR=0.96, 95% CI 0.83 to 1.11; p=0.573). A subgroup analysis has shown that the greatest PFS benefit was associated with an age of <65 years(HR=0.74, 95% CI 0.57 to 0.96; p=0.026), Asian/Pacific Islander ethnicity (HR=0.23, 95% CI 0.10 to 0.54; p=0.001), Eastern Cooperative Oncology Group performance status (ECOG PS) 1 (HR=0.82, 95% CI 0.68 to 0.98; p=0.033), stage IIIB or IV disease (HR=0.68, 95% CI 0.57 to 0.82; p=0.000) and no history of smoking (HR=0.48, 95% CI 0.32 to 0.71; p=0.000). The incidence of grade 3/4 adverse events such as rash and diarrhoea was higher in the combination group than in the monotherapy group. Conclusions: The addition of bevacizumab to erlotinib can significantly improve PFS and the ORR in the second-line treatment of NSCLC with an acceptable and manageable risk of rash and diarrhoea. Further well-conducted, large-scale trials are needed to validate these findings.

Data from: Copepod respiration increases by 7% per degree °C increase in temperature: a meta-analysis

Exponential increase in respiration rate with increasing temperature in poikilotherms is well documented, however, the overall rate of change varies greatly across copepod taxa. Studies often report magnitude of change, but the rate of change in respiration across multiple temperatures is equivocal. We used 32 studies spanning 78 years of research and 50 copepod species (three orders) to quantify percent increase in respiration rates per one-unit increase in temperature. We found that copepod respiration rates increased with temperature by 7% across three well-studied orders, Calanoida, Cyclopoida, and Harpacticoida. Neither food availability nor scaling respiration to copepod dry weight affected the rate of change of respiration rates. Studies using Winkler titration to measure oxygen consumption produced significantly larger percent changes in respiration, whereas newer methods such as fiber optics produced smaller effects. These results have far reaching implications, suggesting that copepods can adapt to increasing temperatures brought forth by climate change.

Data from: On the relationship between body condition and parasite infection in wildlife: a review and meta‐analysis

Body condition metrics are widely used to infer animal health and to assess costs of parasite infection. Since parasites harm their hosts, ecologists might expect negative relationships between infection and condition in wildlife, but this assumption is challenged by studies showing positive or null condition–infection relationships. Here, we outline common condition metrics used by ecologists in studies of parasitism, and consider mechanisms that cause negative, positive, and null condition–infection relationships in wildlife systems. We then perform a meta‐analysis of 553 condition–infection relationships from 187 peer‐reviewed studies of animal hosts, analysing observational and experimental records separately, and noting whether authors measured binary infection status or intensity. Our analysis finds substantial heterogeneity in the strength and direction of condition–infection relationships, a small, negative average effect size that is stronger in experimental studies, and evidence for publication bias towards negative relationships. The strongest predictors of variation in study outcomes are host thermoregulation and the methods used to evaluate body condition. We recommend that studies aiming to assess parasite impacts on body condition should consider host–parasite biology, choose condition measures that can change during the course of infection, and employ longitudinal surveys or manipulate infection status when feasible.

Data from: Virulence-driven trade-offs in disease transmission: a meta-analysis

The virulence--transmission trade-off hypothesis proposed more than 30 years ago is the cornerstone in the study of host-parasite co-evolution. This hypothesis rests on the premise that virulence is an unavoidable and increasing cost because the parasite uses host resources to replicate. This cost associated with replication ultimately results in a deceleration in transmission rate because increasing within-host replication increases host mortality. Empirical tests of predictions of the hypothesis have found mixed support, which cast doubt about its overall generalizability. To quantitatively address this issue, we conducted a meta-analysis of 30 empirical studies, after reviewing over 4000 published papers, focusing on the four core relationships between (1) virulence and recovery rate, (2) within-host replication rate and virulence, (3) within-host replication and transmission rate, and (4) virulence and transmission rate. We found strong support for an increasing relationship between replication and virulence, and replication and transmission. While the overall mean effect suggests that these relationships decelerate with increasing parasite replication, which theoretically arises from limited host resources to exploit, the effect was uncertain due to high within-study variability. There was insufficient data to quantitatively test the other two core relationships predicted by the theory. Overall, the results suggest that the current empirical evidence provides partial support for the trade-off hypothesis, but more work remains to be done.

opencc-zeroDec 2016View details →

Data from: Correction for bias in meta-analysis of little-replicated studies

1. 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). 2. 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 to 20 observations, undervalued the meta-variance by ~20%. Meta-analysis of two-sample designs from 20 studies, with sample sizes of 3 to 10 observations, undervalued the meta-variance by 15-20% for the log response ratio (lnR); it undervalued the meta-effect by ~10% for the standardised mean difference (SMD). 3. 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 assumption 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. 4. 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. 5. 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.

opencc-zeroDec 2015View details →

Data from: Species diversity can be overestimated by a fixed empirical threshold: insights from DNA barcoding of the genus Cletus (Hemiptera: Coreidae) and the meta-analysis of COI data from previous phylogeographical studies

The use of genetic distances to identify species within the framework of DNA barcoding has to some extent improved the development of biodiversity studies. However, using a fixed empirical threshold to delimit species may lead to overestimating species diversity. In this study, we use a new data set of COI sequences for 366 specimens within the genus of Cletus as well as conduct an analysis on the same genetic data for collected morphologically defined species from previous phylogeographical studies, to test whether high intraspecific genetic divergences are common with the premises of comprehensive sampling. The results indicate C. graminis Hsiao & Cheng 1964, is the same species with C. punctiger (Dallas, 1852) and should be synonymized and that the distributional record of C. pugnator (Fabricius, 1787) in China is correct. High intraspecific genetic differentiations (0%–4.35%) were found in C. punctiger. Furthermore, as to the mined data, the maximum intraspecific K2P distances of 186 species (48.44% of 384) exceed 3%, and 101 species (26.30%) can be divided into two or more clusters with a threshold of 3% in cluster analysis. If genetic distance is used to delimit species boundaries, the minimum interspecific K2P distance of the congeneric species should be considered rather than only using the fixed empirical value; otherwise, the species richness may be overestimated in some cases.

Data from: Impacts of honeybee density on crop yield: a meta-analysis

1. There is increasing recognition that pollination deficits are limiting crop yields worldwide. However, management strategies for optimal insect pollination are still unclear for most crops. Current management focuses on providing high densities of honeybees, but recommended densities are highly variable, even within single crops and cultivars. 2. We performed an extensive literature search to record honeybee densities (colony density and/or flower visitation rates) and crop productivity (fruit set, seed set, fruit weight, and/or yield). Effect sizes were represented as the difference in crop productivity between the two most extreme levels of honeybee densities. 3. Out of 795 reviewed studies, only 22 analysed the effect of at least two levels of honeybee densities on crop productivity (reporting 60 resulting effect sizes in total). Moreover, few recommendations for crop pollination management are based on results from controlled experimental designs, and with comparable methodology. 4. We found that both colony density and visitation rates increased all the productivity variables. However, effects were non-linear for visitation rates, suggesting that there is an optimum (mean of 8-10 visits per flower) beyond which more honeybees are not beneficial (or even detrimental) for crop productivity. 5. Effect sizes for visitation rates were greater than that for colony densities, suggesting that visitation rates are a more direct measure of the pollination process. Data on the relation between colony density and visitation rates are lacking. Interestingly, effect sizes for visitation rates were greater for crops with separate sexes than those with hermaphroditic flowers; therefore, the benefits of honeybee pollination vary according to the crop biology. 6. Synthesis and applications. Current practices for crop pollination assume that more honeybees are always better for crop yield, even if the effect of this management on crop production still unclear. In contrast, our analyses suggest that there is an optimum for honeybee densities. Despite the importance of honeybees and pollinator-dependent crops worldwide, there is a lack of studies designed for finding such an optimal level of crop pollination. Our analyses further suggest that visitation rates could be used as a proxy to guide management recommendations such as colony density and spatial arrangement.