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1,200 results for “Meta analysis”
The Interaction between Competition and Predation: A Meta-analysis of Field Experiments
Ecologists working with a range of organisms and environments have carried out manipulative field experiments that enable us to ask questions about the interaction between competition and predation (including herbivory) and about the relative strength of competition and predation in the field. Evaluated together, such a collection of studies can offer insight into the importance and function of these factors in nature. Therefore, this dataset was created by combining the results of 20 articles reporting on 39 published field experiments on the interaction between competition and predation. These experiments tested whether the presence of predators affects the intensity of competitive effects. The combined data was then analyzed using a factorial meta-analysis technique, the results of which were published in the study titled The Interaction between Competition and Predation: A Meta‐analysis of Field Experiments (Gurevitch et al., 2000).
Data from Comparative effectiveness of common therapies for Wilson disease: A systematic review and meta‐analysis of controlled studies
<p>This dataset contains three text files in RIS format. They represent the screening process during study selection for "Comparative effectiveness of common therapies for Wilson disease: A systematic review and meta‐analysis of controlled studies" (<a href="https://doi.org/10.1111/liv.14179">https://doi.org/10.1111/liv.14179</a>). The file DOKU_All TiAb-Screening_20200116_cap contains all 3453 records (merged from original and update search) that were subjected to title-abstract screening. The file DOKU_All FT-Screening_20200116_cap contains all 174 records that were subjected to full-text screening. The file DOKU_All Included_20200116_cap contains all 26 records that were included into the final review.</p> <p>In addition, a PRISMA flow diagram (Fig. 1 in the paper) is available in TIF format.</p>
Remaining useful life estimation of bearings: Meta-analysis of Experimental Procedure
<p>The file <strong>analysis.xlsx</strong> contains the data and statistics obtained from a survey that analyzed the machine learning procedures used for estimating the remaining useful life (RUL) of bearings. The goal is to evaluate the extent to which proper protocol is adhered to for RUL estimation in the domain of predictive maintenance. We surveyed 3 knowledge bases with keywords targeting this specific field, sampled the research and recorded the current practices. Below we present the details of the various spreadsheets where the collected data is registered and analyzed.</p>
Results for eQTL and sQTL meta-analysis and colocalization
<p>This dataset is part of the manuscript: "<em>Atlas of genetic effects in human microglia transcriptome across brain regions, aging and disease pathologies</em>", by Lopes KP, Snijders GJL, Humphrey J, et al.</p> <p> </p> <p>Description of files:</p> <p><em>COLOC_supp_table_all_results.tsv.gz - </em>Table with results from <strong>COLOC</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>disease - disease name (Alzheimer’s disease - AD, Bipolar Disorder - BPD, Multiple sclerosis - MS, Parkinson’s disease - PD, Schizohphrenia - SCZ)</li> <li>GWAS - GWAS study (IMSGC_2019, Jansen_2018, Kunkle_2019, Lambert_2013, Marioni_2018, Nalls23andMe_2019, Ripke_2014, Stahl_2019)</li> <li>locus - locus id according to each GWAS study</li> <li>GWAS_SNP - SNP reported in the GWAS study</li> <li>GWAS_P - <em>P</em>-value of the GWAS_SNP reported in the GWAS study</li> <li>GWAS_chr - chromosome of the GWAS_SNP (hg38)</li> <li>GWAS_pos - genomic position in the chromosome of the GWAS_SNP (hg38)</li> <li>QTL - id for the QTL study</li> <li>type - the type of QTL (eQTL or sQTL)</li> <li>QTL_SNP - SNP id from the QTL association</li> <li>QTL_P - <em>P</em>-value for the QTL association </li> <li>QTL_Beta - Slope (beta) for the QTL association</li> <li>QTL_MAF - minor allele frequency for the QTL_SNP in each QTL study. If not available, values were obtained from the European superpopulation of 1000 Genomes phase 3</li> <li>QTL_chr - chromosome for the QTL_SNP (hg38)</li> <li>QTL_pos - genomic position in the chromosome of the QTL_SNP (hg38)</li> <li>QTL_junction - splicing junction tested in the association (for sQTLs only)</li> <li>QTL_Gene - gene name for the QTL association</li> <li>QTL_Ensembl - Ensembl gene id for the QTL_gene (GENCODE v30)</li> <li>nsnps - number of SNPs tested </li> <li>PP.H0.abf - posterior probability for H0 (no causal variant)</li> <li>PP.H1.abf - posterior probability for H1 (causal variant for trait 1 only)</li> <li>PP.H2.abf - posterior probability for H2 (causal variant for trait 2 only)</li> <li>PP.H3.abf - posterior probability for H3 (two distinct causal variants)</li> <li>PP.H4.abf - posterior probability for H4 (one common causal variant)</li> <li>cell_type - cell type of the QTL study</li> <li>SNP_distance - the absolute distance between GWAS_SNP and QTL_SNP</li> <li>LD - linkage disequilibrium between the GWAS_SNP and the QTL_SNP according to 1000 genomes phase 3 European reference panel 3 (only for PP4>0.5, -Inf otherwise)</li> </ol> <p><em>mashR_lfsr_eQTL.txt.gz - </em><strong>mashR </strong>results for <strong>eQTL</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>ensembl_snp - Ensembl ID and the SNP prioritized by mashR (best SNP per gene)</li> <li>MFG_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the MFG region</li> <li>STG_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the STG region</li> <li>SVZ_eur_expression_peer5.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the SVZ region</li> <li>THA_eur_expression_peer10.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the THA region</li> </ol> <p><em>mashR_lfsr_eQTL.txt.gz - </em><strong>mashR </strong>results for <strong>sQTL</strong><em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>pos_ensembl_rsnp - splicing junction coordinates, Ensembl ID, and SNP ID prioritized by mashR (best SNP per junction)</li> <li>MFG_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the MFG region</li> <li>STG_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the STG region</li> <li>SVZ_eur_rsplicing_peer0_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the SVZ region</li> <li>THA_eur_rsplicing_peer5_gene.cis_qtl_nominal - local false sign rate (lfsr) of the gene-SNP pair for the THA region</li> </ol> <p><em>out_mfg_stg_svz_tha.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>eQTLs</strong> meta-analysis from MiGA four brain regions<em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by gene Ensembl and SNP ID separated by an underscore for each gene-SNP pair tested in the eQTL study</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> </ol> <p><em>out_miga_young_mynd_fairfax.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>eQTL</strong> meta-analysis from MiGA four brain regions plus microglia eQTL from Young et al. (2019), and monocytes eQTL from Navarro et al. (2020) and Fairfax et al. (2014)<em> </em>(gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by gene Ensembl and SNP ID separated by an underscore for each gene-SNP pair tested in the eQTL study</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA, 5-Young et al., 6-Navarro et al., 7-Fairfax et al.</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA, 5-Young et al., 6-Navarro et al., 7-Fairfax et al.</li> </ol> <p><em>out_mfg_stg_svz_tha_sClusters.metasoft.gz - </em><strong>METASOFT</strong> results<strong> </strong>for <strong>sQTLs</strong> meta-analysis from MiGA four brain regions (gzip-compressed). Table columns are formatted as follows:</p> <ol> <li>RSID - Id composed by splicing junction coordinates, gene Ensembl ID, and SNP ID separated by underscores for each junction-SNP pair tested in the sQTL study (e.g. chr1_962047_962355_ENSG00000187961.14_1:11008:C:G)</li> <li>#STUDY - number of studies included in the meta-analysis</li> <li>PVALUE_FE - <em>P</em>-value of the fixed-effects model (FE) according to METASOFT</li> <li>BETA_FE - Estimated Beta under the fixed-effects model according to METASOFT</li> <li>STD_FE - Standard error of BETA_FE</li> <li>PVALUE_RE - <em>P</em>-value of the random effects model (RE) according to METASOFT</li> <li>BETA_RE - Estimated Beta under the random-effects model (RE) according to METASOFT</li> <li>STD_RE - Standard error of BETA_RE</li> <li>PVALUE_RE2 - <em>P</em>-value of the Han and Eskin's Random Effects model (RE2) according to METASOFT</li> <li>STAT1_RE2 - RE2 statistic mean effect part</li> <li>STAT2_RE2 - RE2 statistic heterogeneity part</li> <li>PVALUE_BE - BE P-value (“NA” in all row, -binary_effects option is not used)</li> <li>I_SQUARE - I-square heterogeneity statistic</li> <li>Q - Cochran's Q statistic</li> <li>PVALUE_Q - Cochran's Q statistic's <em>P</em>-value</li> <li>TAU_SQUARE - Tau-square heterogeneity estimator of DerSimonian-Laird</li> <li>PVALUES_OF_STUDIES(Tab_delimitered) - <em>P</em>-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> <li>MVALUES_OF_STUDIES(Tab_delimitered) - M-values of each study in the respective order 1-MFG, 2-STG, 3-SVZ, 4-THA</li> </ol> <p><strong>NOTE:</strong> The effect sizes of eQTLs and sQTL are defined as the effect of the alternative allele (ALT) relative to the reference (REF) allele in the human genome reference (GRCh38). A file containing that information for all alleles tested is available at 10.5281/zenodo.4301005</p>
Supplementary material: Prophylactic antibiotics for adults with chronic obstructive pulmonary disease: a network meta-analysis
<p>Supplementary material for Cochrane review: Janjua S , Mathioudakis AG , Fortescue R , Walker RAE , Sharif S , Threapleton CJD , Dias S . Prophylactic antibiotics for adults with chronic obstructive pulmonary disease: a network meta-analysis. Cochrane Database of Systematic Reviews 2021, Issue 1. Art. No.: <a href="https://archie.cochrane.org/sections/documents/CD013198">CD013198</a>. DOI: <a href="https://archie.cochrane.org/sections/documents/10.1002/14651858.CD013198.pub2">10.1002/14651858.CD013198.pub2</a>.</p>
Trophic-meta-analysis: Second release of tritrophic meta-analysis data, code and appendices
<p>Data, R script and appendices for "Interaction strength and the impact of introduced omnivores: A meta-analysis of introduced aquatic invasive species" submitted to Oikos</p>
PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) of the research entitled "Development of Competences for the Fashion Designer: a Scope Review
<p>PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 checklist: recommended items to address in a systematic review protocol and Check list CAPSI - Critical analysis of the articles related to the specific objective: map the current themes that permeate the competencies of fashion design professionals through a scoping review.</p>
A meta-analysis on global change drivers and the risk of infectious disease database and code
<p>Data and code associated with the manuscript "A Meta-analysis on Global change drivers and the risk of infectious disease".</p>
Effects of nutrient enrichment on freshwater macrophyte and invertebrate abundance: A meta-analysis
<p>The zip-file contains the data and code accompanying the paper 'Effects of nutrient enrichment on freshwater macrophyte and invertebrate abundance: A meta-analysis'. Together, these files should allow for the replication of the results.</p> <p>The 'raw_data' folder contains the 'MA_database.csv' file, which contains the extracted data from all primary studies that are used in the analysis. Furthermore, this folder contains the file 'MA_database_description.txt', which gives a description of each data column in the database.</p> <p>The 'derived_data' folder contains the files that are produced by the R-scripts in this study and used for data analysis. The 'MA_database_processed.csv' and 'MA_database_processed.RData' files contain the converted raw database that is suitable for analysis. The 'DB_IA_subsets.RData' file contains the 'Individual Abundance' (IA) data subsets based on taxonomic group (invertebrates/macrophytes) and inclusion criteria. The 'DB_IA_VCV_matrices.RData' contains for all IA data subsets the variance-covariance (VCV) matrices. The 'DB_AM_subsets.RData' file contains the 'Total Abundance' (TA) and 'Mean Abundance' (MA) data subsets based on taxonomic group (invertebrates/macrophytes) and inclusion criteria.</p> <p>The 'output_data' folder contains maps with the output data for each data subset (i.e. for each metric, taxonomic group and set of inclusion criteria). For each data subset, the map contains random effects selection results ('Results1_REsel_<subset>.csv'), the fixed effects selection results ('Results2_FEsel_<subset>.csv'), the random variance components and R^2 values for the best models subset ('Results3_BestModels_<subset>.csv'), the parameter value estimations for the fixed effects ('Results4_Parameters_<subset>.csv'), the standard errors for the estimated parameter values ('Results5_SE_<subset>.csv'), and the consensus model parameter values ('Results6_ConsensusModel_<subset>.csv'). Furthermore, each map contains a file with the best-selected random effects model structure ('BestRanEf_<subset>.RData'), the model with the best-selected random effects structure without moderators (only for IA) ('BestRanEfModel_<subset>.RData'), and a file with the consensus model ('ConsensusModel_<subset>.RData').</p> <p>The 'scripts' folder contains all R-scripts that we used for this study. The 'PrepareData.R' script takes the database as input and adjusts the file so that it can be used for data analysis. The 'PrepareDataIA.R' and 'PrepareDataAM.R' scripts make subsets of the data and prepare the data for the meta-regression analysis and mixed-effects regression analysis, respectively. The regression analyses are performed in the 'SelectModelsIA.R' and 'SelectModelsAM.R' scripts to calculate the regression model results for the IA metric and MA/TA metrics, respectively. These scripts require the 'RandomAndFixedEffects.R' script, containing the random and fixed effects parameter combinations, as well as the 'Functions.R' script. The 'CreateMap.R' script creates a global map with the location of all studies included in the analysis (figure 1 in the paper). The 'CreateForestPlots.R' script creates plots showing the IA data distribution for both taxonomic groups (figure 2 in the paper). The 'CreateHeatMaps.R' script creates heat maps for all metrics and taxonomic groups (figure 3 in the paper, figures S11.1 and S11.2 in the appendix). The 'CalculateStatistics.R' script calculates the descriptive statistics that are reported throughout the paper, and creates the figures that describe the dataset characteristics (figures S3.1 to S3.5 in the appendix). The 'CreateFunnelPlots.R' script creates the funnel plots for both taxonomic groups (figures S6.1 and S6.2 in the appendix) and performs Egger's tests. The 'CreateControlGraphs.R' script creates graphs showing the dependency of the nutrient response to control concentrations for all metrics and taxonomic groups (figures S10.1 and S10.2 in the appendix).</p> <p>The 'figures' folder contains all figures that are included in this study.</p>
Database for: Meta-analysis of the impact of land use intensification on earthworms in global agroecosystems
<p>The dataset comprises a compilation of studies investigating the impact of land use intensification on earthworms across global agroecosystems. Extracted from peer-reviewed publications, the dataset includes various fields such as climate characteristics are described using the Köppen-Geiger climate classification system. Soil properties such as type, texture, pH, and organic content are documented. Additionally, details regarding experimental parameters like replicates, sampling depth, and extraction methods are provided. Furthermore, the dataset encompasses information on agricultural practices including herbicide, insecticide, pesticide usage, fertilizer type and rate, grazing, tillage methods, and days after tillage for earthworm collection. Abundance, diversity, and their associated metrics are recorded for both control and treatment sites.</p>
A systematic review and meta-analysis of eyespot anti-predator mechanisms
<p>This is the raw data, analysis script, and supplementary materials for "<em>A systematic review and meta-analysis of eyespot anti-predator mechanisms</em>." (<a href="https://doi.org/10.7554/eLife.96338.2">https://doi.org/10.7554/eLife.96338</a>)</p>
Dataset underpinning "Understanding health behaviours in context: A systematic review and meta-analysis of Ecological Momentary Assessment studies of five key health behaviours"
<p>This is the dataset underpinning the article "Understanding health behaviours in context: A systematic review and meta-analysis of Ecological Momentary Assessment studies of five key health behaviours": https://pubmed.ncbi.nlm.nih.gov/35975950/</p>
Outdoor air pollution impacts chronic obstructive pulmonary disease deaths in South Asia and China: a systematic review and meta-analysis
<p><strong>Background: </strong>Chronic obstructive pulmonary disease (COPD) is among leading causes of death globally. Exposure to outdoor pollution is an important cause for increased mortality and morbidity. This study presents a systemic review regarding the impact of outdoor pollution on COPD mortality in South Asia and China.</p> <p><strong>Methods: </strong>A systematic search was conducted from 1990 to June 30<sup>th</sup> 2020 in English electronic databases: PubMed, Google Scholar and CDSR (Cochrane Database of Systematic Reviews) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following terms were used: Chronic Obstructive Pulmonary disease OR COPD OR Chronic Bronchitis OR Emphysema OR COPD Deaths OR Chronic Obstructive Lung Disease OR Airflow Obstruction OR Chronic Airflow Obstruction OR Airflow Obstruction, Chronic OR Bronchitis, Chronic AND Mortality OR Death OR Deceased AND Outdoor pollution, ambient pollution was conducted.</p> <p><strong>Results:</strong> Out of 1899 papers screened only 17 were found eligible to be included. Subjects with COPD exposed to higher levels of outdoor air pollution had a 49% higher risk of death as compared to COPD subjects exposed to lower levels of outdoor air pollution. When taking common air pollutants individually into consideration, PM10 had an odds ratio (OR) of 1.99 respectively at CI 95%, whereas SO2 had OR of 1.8 at 95% CI, and NO2 had an OR of 1.23 OR at 95% CI. These values suggest that there is an effect of outdoor pollution on COPD but not to a significant level.</p> <p><strong>Conclusion: </strong>Despite heterogeneity across selected studies, individuals exposed to outdoor pollutants were found to be at risk of COPD mortality. Though it appears to have risk, COPD mortality was not significantly associated with outdoor pollutants. Controlling air pollution can substantially decrease the risk of COPD in South Asia and China. Further researches including more prospective and longitudinal studies are urgently needed in COPD sub-groups.</p>
Impact of heat stress on the fitness outcomes of symbiotic infection in aphids: a meta-analysis
<p>This is the dataset for the article "<em><strong>Impact of heat stress on the fitness outcomes of symbiotic infection in aphids: a meta-analysis</strong></em>". </p> <p>Beneficial symbiosis shape their host eco-evolutionary responses. Here we show how the responses of insect-microbe associations may be modulated by rising temperatures. The outcome of the symbiotic association is therefore temperature-dependent, but also trait-dependent. We show the importance of better understanding the cost-benefits balance of insect-microbe associations faced with climate change.</p>
Comparative host transcriptomics as a tool to identify candidate biomarkers for immune reactions in leprosy: A meta-analysis study
<p>The dataset consists of R source code for the individual dataset analysis of the studies and their meta-analysis. It also contains supplementary tables and figure.</p>
Individual repeatability of avian migration phenology: a systematic review and meta-analysis
<p>Changes in phenology and distribution are being widely reported for many migratory species in response to shifting environmental conditions. Understanding these changes and the situations in which they occur can be aided by understanding consistent individual differences in phenology and distribution and the situations in which consistency varies in strength or detectability.</p> <p>Studies tracking the same individuals over consecutive years are increasingly reporting migratory timings to be a repeatable trait, suggesting that flexible individual responses to environmental conditions may contribute little to population-level changes in phenology and distribution. However, how this varies across species and sexes, across the annual cycle and in relation to study (tracking method, study design) and/or ecosystem characteristics is not yet clear.</p> <p>Here, we take advantage of the growing number of publications in movement ecology to perform a phylogenetic multilevel meta-analysis of repeatability estimates for avian migratory timings to investigate these questions. Of 2,433 reviewed studies, 54 contained suitable information for meta-analysis, resulting in 177 effect sizes from 47 species.</p> <p>Individual repeatability of avian migratory timings averaged 0.414 (95% confidence interval: 0.3–0.5) across landbirds, waterbirds and seabirds, suggesting consistent individual differences in migratory timings is a common feature of migratory systems. Timing of departure from the non-breeding grounds was more repeatable than timings of arrival at or departure from breeding grounds, suggesting that conditions encountered on migratory journeys and outcome of breeding attempts can influence individual variation.</p> <p>Population-level shifts in phenology could arise through individual timings changing with environmental conditions and/or through shifts in the numbers of individuals with different timings. Our findings suggest that, in addition to identifying the conditions associated with individual variation in phenology, exploring the causes of between-individual variation will be key in predicting future rates and directions of changes in migratory timings. We, therefore, encourage researchers to report the within- and between- individual variance components underpinning the reported repeatability estimates to aid interpretation of migration behaviour. In addition, the lack of studies in the tropics means that levels of repeatability in less strongly seasonal environments are not yet clear.</p>
Eco-evolutionary causes and consequences of rarity in plants: a meta-analysis
<p>Species differ dramatically in their prevalence in the natural world, with many species characterized as rare due to restricted geographic distribution, low local abundance, and/or habitat specialization.</p> <p>We investigated eco-evolutionary causes and consequences of rarity with phylogenetically-controlled meta-analyses of population genetic diversity, fitness, and functional traits in rare and common congeneric plant species. Our syntheses included 252 rare species and 267 common congeners reported in 153 peer-reviewed articles published from 1978-2020 and one manuscript in press.</p> <p>Rare species have reduced population genetic diversity<span>, depressed fitness, and smaller reproductive structures </span>than common congeners. <span>Rare species also could suffer from inbreeding depression and reduced fertilization efficiency.</span></p> <p><span>By limiting their capacity to adapt and migrate, these characteristics could influence contemporary patterns of rarity and increase the susceptibility of rare species to rapid environmental change. We recommend that </span>future studies present more nuanced data on the extent of rarity in focal species, expose rare and common species to ecologically-relevant treatments, including reciprocal transplants, and conduct quantitative genetic and population genomic analyses across a greater array of systems. This research could elucidate the processes that contribute to rarity and generate robust predictions of extinction risks under global change.</p>
Supporting dataset for: "Plasma essential amino acid concentration and profile are associated with performance of lactating dairy cows as revealed through meta-analysis and hierarchical clustering"
<p>This dataset was used in the meta-analysis and hierarchical clustering published in "Plasma essential amino acid concentration and profile are associated with performance of lactating dairy cows as revealed through meta-analysis and hierarchical clustering" in the Journal of Dairy Science. We searched Web of Science and Google Scholar databases through March 2020 with the terms “plasma EAA,” “milk urea” or “blood urea,” and “dairy” or lactating dairy”. To be included in our study, the papers must have met the following selection criteria: (1) been published in English in a peer-reviewed journal; (2) reported dietary ingredients on a DM basis and at minimum dietary CP concentration; (3) used treatments based on diet changes (e.g., no infusion trials were included); (4) reported DMI, lactation performance, and milk components yield; (5) reported all individual [EAA]p (excluding Trp); and (6) reported blood urea-N or plasma urea-N. Infusion studies were excluded to avoid possible effects of method of EAA supply (e.g., infusion vs. feeding) and to narrow the scope of application. The final dataset included 22 studies and 96 dietary treatments. For a more complete description of the methods, please refer to the published paper. </p>
Meta-analysis suggests variable, but pCO2-specific, effects of ocean acidification on crustacean biomaterials
Crustaceans comprise an ecologically and morphologically diverse taxonomic group. They are typically considered resilient to many environmental perturbations found in marine and coastal environments, due to effective physiological regulation of ions and hemolymph pH, and a robust exoskeleton. Ocean acidification can affect the ability of marine calcifying organisms to build and maintain mineralized tissue and poses a threat for all marine calcifying taxa. Currently, there is no consensus on how ocean acidification will alter the ecologically-relevant exoskeletal properties of crustaceans. Here, we present a systematic review and meta-analysis on the effects of ocean acidification on the crustacean exoskeleton, assessing both exoskeletal ion content (calcium and magnesium) and functional properties (biomechanical resistance and cuticle thickness). Our results suggest that the effect of ocean acidification on crustacean exoskeletal properties varies based upon seawater <i>p</i>CO<sub>2</sub> and species identity, with significant levels of heterogeneity for all analyses. Calcium and magnesium content were significantly lower in animals held at <i>p</i>CO<sub>2</sub> levels of 1500-1999 μatm as compared to those under ambient <i>p</i>CO<sub>2</sub>. At lower <i>p</i>CO<sub>2</sub> levels, however, statistically significant relationships between changes in calcium and magnesium content within the same experiment were observed: a negative relationship between calcium and magnesium content at <i>p</i>CO<sub>2</sub> of 500-999 μatm and a positive relationship at 1000-1499 μatm. Exoskeleton biomechanics, such as resistance to deformation (microhardness) and shell strength, also significantly decreased under <i>p</i>CO<sub>2</sub> regimes of 500-999 μatm and 1500-1999 μatm, indicating functional exoskeletal change coincident with decreases in calcification. Overall, these results suggest that the crustacean exoskeleton can be susceptible to ocean acidification at the biomechanical level, potentially predicated on changes in ion content, when exposed to high influxes of CO<sub>2</sub>. Future studies will need to accommodate the high variability of crustacean responses to ocean acidification, as well as ecologically-relevant ranges of <i>p</i>CO<sub>2</sub> conditions, when designing experiments with conservation-level endpoints. --
Data from: Controlled drainage and subirrigation suitability in the United States: A meta-analysis of crop yield and soil moisture effects
<p>Controlled drainage and subirrigation (CDSI) is an important water management strategy in many regions, but the conditions under which CDSI is most likely to increase crop yield and soil moisture are not fully understood. A meta-analysis, consisting of 154 pairwise observations from replicated and randomized trials in 30 peer-reviewed primary research articles on CDSI (6 controlled drainage, 24 CDSI, analyzed together due to data scarcity), was conducted to study the responses of yield and soil moisture to CDSI, and investigate how crop type, soil texture, and cumulative growing season precipitation (PGS) influence these responses. Based on the yield response to these moderating factors, we used a fuzzy-logic approach to map potentially suitable locations for CDSI in the conterminous United States. On average, CDSI increased yield by 8.0% (95% CI = 1.8–14.7%) compared with conventional free drainage. The yield response to CDSI did not differ among crops. However, a greater yield response to CDSI was observed in medium-textured soils (19.4% increase; 95% CI = 12.4–27.0%) than in coarse- or fine-textured soils. The positive effect of CDSI on yield increased with decreasing PGS in coarse- and medium-textured soils. There was no clear effect of CDSI on soil moisture, nor did any moderators influence this relationship, though this may be attributed to the scarcity of studies on CDSI reporting soil moisture. The fuzzy-logic-based approach revealed that while potentially suitable areas are mostly concentrated in the well studied U. S. Midwest, these areas also exist in other regions where CDSI may warrant further study.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.