Handbook of Meta-analysis in Ecology and Evolution

By J. Koricheva, J. Gurevitch, Kerrie L. Mengersen. 2013

1,026 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/7c8aa57099148823a39e034c7d49eed053e69b84

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In Ecological Modeling

In Ecology

In Nature and Landscape Conservation

Citations in the corpus

The role of human-related risk in breeding site selection by wolves (2016, methodology): “The number of studies (26) is within the mean range of sample sizes found in ecological meta-analyses (between 20 and 30; Koricheva et al., 2013).”
Shrub encroachment and vertebrate diversity: A global meta‐analysis (2018, methodology): “We assessed global effect sizes and confidence intervals without moderators or control variables to determine the overall effects of shrub encroachment on vertebrate community structure (Koricheva et al., 2013).”
The effect of experimental design on the measurement of mate choice: a meta-analysis (2015, background): “to r is simple (Koricheva et al. 2013), and it has the advantage of being an intuitive measure of the size of an effect.”
Using functional and phylogenetic diversity to infer avian community assembly along elevational gradients (2019, positive): “Then, we used these two new variables (slopes and their variances) to calculate weighted values of the slope and used these new values as response variables for a multivariate meta‐regression with absolute latitude as predictor and hemisphere as covariate (Koricheva, Gurevitch, & Mengersen, 2013).”
Meta-Analysis Reveals Artificial Reefs Can Be Effective Tools for Fish Community Enhancement but Are Not One-Size-Fits-All (2020, methodology): “We used the reported F value to calculate Hedges’ g as: ∣ ∣g ∣ ∣ = √ F (nAR + nNR) nARnNR (9) and ensured that g was positive if the metric was higher on artificial than natural reefs and negative if the opposite (Koricheva et al., 2013).”
Experimental studies of dead-wood biodiversity — A review identifying global gaps in knowledge (2015, neutral): “large effect (Koricheva et al., 2013).”
Doing Meta-Analysis with R - A Hands-On Guide (2022, background): “…published as papers (Impellizzeri and Bizzini 2012), reviews that describe when and why to apply (Crocetti 2015), extensive support for packages published on the CRAN task view “Meta-Analysis” (Dewey 2022), and texts that describe the process in depth (Koricheva, Gurevitch, and Mengersen 2013).”
Structuring evidence for invasional meltdown: broad support but with biases and gaps (2018, background): “Our approach is distinct from vote counting where empirical tests are classified based only on the statistical significance they report (Borenstein et al. 2009; Koricheva et al. 2013).”