journal article May 27, 2020

Cumulative meta‐analysis identifies declining but negative impacts of invasive species on richness after 20 yr

Ecology Vol. 101 No. 8 · Wiley
Abstract
AbstractA principal impact of invasive species is that they reduce local species richness. However, it is unknown whether the magnitude of the richness decrease has been consistent over the past two decades of published research. We used cumulative meta‐analysis to synthesize evidence from 240 articles evaluating whether this cumulative evidence base generally supports, or refutes, the association between invasive species presence and richness declines. First, we determined whether evidence accumulation lowered the mean effect size of invasive species on local native richness through time; termed the “decline effect.” Then, as mean effect sizes changed over time, we identified when accumulated evidence reached sufficiency, indicating that the mean effect direction (positive or negative) was unlikely to be reversed by unpublished research. We also assessed whether the mean effect size reached a threshold of stability over publication years. To date, no research has tested mechanisms of the decline effect, and here we determine whether publication bias, sample size, time since invasion, or invader trophic position are driving a decline effect in the published evidence base. We found a clear decline in the cumulative mean effect of invasive species on local native species richness as published evidence accumulated between 1999 and 2016. Despite this decline, an average negative association was stable and sufficiently robust to unpublished studies by 2007, showing a 21% mean richness decrease by 2016. Contrary to our expectation, the decline effect manifested consistently regardless of invasive species trophic position, time since invasion, or journal rank. Within taxonomic subgroups, trees, insects, and herbaceous plants exhibit a decline effect, yet still show sufficient and stable negative impacts on richness. However, many other taxonomic subgroups (e.g., crustaceans, fish, mammals) lack evidence for average negative impacts on richness, or have not met sufficiency or stability thresholds.
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References
66
[4]
Fitting Linear Mixed-Effects Models Using lme4

Douglas Bates, Martin Mächler, Ben Bolker et al.

Journal of Statistical Software 10.18637/jss.v067.i01
[9]
Invasive species are a leading cause of animal extinctions

M CLAVERO, E GARCIABERTHOU

Trends in Ecology & Evolution 10.1016/j.tree.2005.01.003
[11]
Don't judge species on their origins

Mark A. Davis, Matthew K. Chew, Richard J. Hobbs et al.

Nature 10.1038/474153a
[13]
WOLVES INFLUENCE ELK MOVEMENTS: BEHAVIOR SHAPES A TROPHIC CASCADE IN YELLOWSTONE NATIONAL PARK

Daniel Fortin, Hawthorne L. Beyer, Mark S. Boyce et al.

Ecology 10.1890/04-0953
[14]
THE INVASION PARADOX: RECONCILING PATTERN AND PROCESS IN SPECIES INVASIONS

J. D. Fridley, J. J. Stachowicz, S. NAEEM et al.

Ecology 10.1890/0012-9658(2007)88[3:tiprpa]2.0.co;2
[18]
Are invasive species a major cause of extinctions?

J GUREVITCH, D PADILLA

Trends in Ecology & Evolution 10.1016/j.tree.2004.07.005
[21]
Huang X. "Evaluation of PICO as a knowledge representation for clinical questions" AMIA Annual Symposium Proceedings (2006)
[30]
Kossmier M. U. S.Tran andM.Voracek.2018.metaviz: Forest plots funnel plots and visual funnel plot inference for meta‐analysis.https://cran.r‐project.org/web/packages/metaviz/vignettes/metaviz.html 10.32614/cran.package.metaviz
[43]
Empirical Evaluation of Very Large Treatment Effects of Medical Interventions

Tiago V. Pereira, Ralph I. Horwitz, John P. A. Ioannidis

JAMA 10.1001/jama.2012.13444
[47]
[49]
R Development Core Team (2019)

Showing 50 of 66 references

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