<i>Open<scp>MEE</scp></i>: Intuitive, open‐source software for meta‐analysis in ecology and evolutionary biology

Wallace, Byron C.; Lajeunesse, Marc J.; Dietz, George; Dahabreh, Issa J; Trikalinos, Thomas A; Schmid, Christopher H.; Gurevitch, Jessica

doi:10.1111/2041-210x.12708

Cited by 292 publications

(149 citation statements)

References 53 publications

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“…Initial data exploration was conducted by using OpenMEE software (Wallace et al. ; software available online ) . Full analyses were conducted in R version 3.3.3 using the metafor package (Viechtbauer , R Core Team ).…”

Section: Methodsmentioning

confidence: 99%

“…The Pearson's product-moment correlation coefficient (r) from each case was normalized using Fisher's z Study area within country Geographic coordinates midpoint of study area (latitude, longitude) Spatial extent (0, 10), [10, 100), [10 2 , 10 3 ), [10 3 , 10 4 ), [10 4 , 10 5 ), [10 5 , 10 6 ) and [10 6 ) km 2 Research type observational or experimental Habitat type forest, grassland, shrubland, wetland, riparian, savanna, agricultural habitat (refers to the non-crop semi-natural areas in an agricultural landscape), urban, many habitat types included in study, and miscellaneous other habitats (e.g., freshwater, old fields) Climatic zone tropical, temperate, or polar transformation as an effect size, where the sample size was the number of plots for which of exotic and native species numbers were calculated (see Appendix S2 for details). Initial data exploration was conducted by using OpenMEE software (Wallace et al 2017; software available online). 6 Full analyses were conducted in R version 3.3.3 using the metafor package (Viechtbauer 2010, R Core Team 2017.…”

Section: Statistical Analysesmentioning

confidence: 99%

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Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales

Peng

Kinlock

Gurevitch

et al. 2019

Ecology

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Support for the “biotic resistance hypothesis,” that species‐rich communities are more successful at resisting invasion by exotic species than are species‐poor communities, has long been debated. It has been argued that native–exotic richness relationships (NERR) are negative at small spatial scales and positive at large scales, but evidence for the role of spatial scale on NERR has been contradictory. However, no formal quantitative synthesis has previously examined whether NERR is scale‐dependent across multiple studies, and previous studies on NERR have not distinguished spatial grain and extent, which may drive very different ecological processes. We used a global systematic review and hierarchical mixed‐effects meta‐analysis to provide a comprehensive quantitative assessment of the patterns of NERR over a range of spatial grain sizes and spatial extents, based on 204 individual cases of observational (non‐experimental) NERRs from 101 publications. We show that NERR was indeed highly scale dependent across studies and increased with the log of grain size. However, mean NERR was not negative at any grain size, although there was high heterogeneity at small grain sizes. We found no clear patterns of NERR across different spatial extents, suggesting that extent plays a less important role in determining NERR than does grain, although there was a complex interaction between extent and grain size. Almost all studies on NERR were conducted in North America, western Europe, and a few other regions, with little information on tropical or Arctic regions. We did find that NERR increased northward in temperate regions and also varied with longitude. We discuss possible explanations for the patterns we found, and caution that our results do not show that invasive species are benign or have no negative consequences for biodiversity preservation. This study represents the first global quantitative analysis of scale‐based NERR, and casts doubt on the existence of an “invasion paradox” of negative NERR at small scales and positive correlations at large scales in non‐experimental studies.

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Section: Methodsmentioning

confidence: 99%

Section: Statistical Analysesmentioning

confidence: 99%

Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales

Peng

Kinlock

Gurevitch

et al. 2019

Ecology

Self Cite

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“…The I 2 index is easily interpreted as a percentage of the total variability in effect sizes due to true heterogeneity or between‐studies variability compared to sampling error within studies (e.g., I 2 = 0; Wallace et al. ).…”

Section: Methodsmentioning

confidence: 99%

“…Random-effects models not only account for variation among studies (i.e., sampling error, s 2 ; Viechtbauer 2010), but are also considered more appropriate for the synthesis of ecological data ( Using the I 2 index, we evaluated whether effect sizes across studies were truly heterogeneous (i.e., variance among effect sizes were greater than sampling error alone). The I 2 index is easily interpreted as a percentage of the total variability in effect sizes due to true heterogeneity or between-studies variability compared to sampling error within studies (e.g., I 2 = 0; Wallace et al 2017).…”

Section: Effect Size Calculationmentioning

confidence: 99%

Neonicotinoid insecticides negatively affect performance measures of non‐target terrestrial arthropods: a meta‐analysis

Main

Webb

Goyne

et al. 2018

Ecological Applications

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Neonicotinoid insecticides are currently the fastest-growing and most widely used insecticide class worldwide. Valued for their versatility in application, these insecticides may cause deleterious effects in a range of non-target (beneficial) arthropods. However, it remains unclear whether strong patterns exist in terms of their major effects, if broad measures of arthropod performance are negatively affected, or whether different functional groups are equally vulnerable. Here, we present a meta-analysis of 372 observations from 44 field and laboratory studies that describe neonicotinoid effects on 14 arthropod orders across five broad performance measures: abundance, behavior, condition, reproductive success, and survival. Across studies, neonicotinoids negatively affected all performance metrics evaluated; however, magnitude of the effects varied. Arthropod behavior and survival were the most negatively affected and abundance was the least negatively affected. Effects on arthropod functional groups were inconsistent. Pollinator condition, reproductive success, and survival were significantly lower in neonicotinoid treatments compared to untreated controls; whereas, neonicotinoid effects on detritivores were not significant. Although magnitude of arthropod response to neonicotinoids varied among performance measures and functional groups, we documented a consistent negative relationship between exposure to neonicotinoid insecticides in published studies and beneficial arthropod performance.

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“…Many of these models can be run in widely available software packages including metafor (Viechtbauer ), mcmcglmm (Hadfield ) and openmee (Wallace et al . ). Given we are only interested in the overall pooled effect size estimate (i.e.…”

Section: Nonindependence and The Role Of Sensitivity Analysesmentioning

confidence: 97%

Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses

et al. 2017

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Meta-analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta-analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta-analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta-analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta-analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta-analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta-analyses, leading to greater transparency and more robust conclusions.

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OpenMEE: Intuitive, open‐source software for meta‐analysis in ecology and evolutionary biology

Cited by 292 publications

References 53 publications

Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales

Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales

Neonicotinoid insecticides negatively affect performance measures of non‐target terrestrial arthropods: a meta‐analysis

Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses

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