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Data from: Latitudinal patterns of alien plant invasions

Citation

Guo, Qinfeng et al. (2021), Data from: Latitudinal patterns of alien plant invasions, Dryad, Dataset, https://doi.org/10.5061/dryad.qnk98sfd8

Abstract

Latitudinal patterns of biodiversity have long been a central topic in ecology and evolutionary biology. However, while most previous studies have focused on native species, little effort has been devoted to latitudinal patterns of plant invasions (with a few exceptions based on data from sparse locations). Using the most up-to-date worldwide native and alien plant distribution data from 801 regions (including islands), we compared invasion levels (i.e. alien richness/total richness) in the Northern and Southern Hemispheres and across continental regions and islands around the globe. Results from quantile regressions using B-splines to model nonlinearity showed (1) declining richness with increasing latitude, although the highest alien richness occurs at around 40 degrees in both hemispheres, (2) decreasing invasion levels towards higher latitudes on islands but a unimodal pattern in invasion level in continental regions in each hemisphere, (3) significantly higher invasion levels on islands than in continental regions, and (4) a greater variability in invasThrough field observations and published records (e.g., literature search).ion levels on islands at low latitudes than on high-latitude islands. In continental regions, only the mid-latitudes had high variability with both low and high invasion levels. Our findings identified latitudes with invasion hotspots where management is urgently needed, and latitudes with many areas of low invasions but high conservation potential where prevention of future invasions should be the priority.

Methods

Through field observations and published records (e.g., literature search).

Usage Notes

The dataset excludes the regions/islands for which the native species richness is not certain.

Invasion level was calculated as "aliens/(aliens + natives)".

We included 4 files:

1) A file with the complete dataset ("Appendix I_801 sites.csv"), 

2) A file with R code ("Guo.etal2020.R.scripts"),

3) A file for running R ("Essl.SppRichness.csv") for richness data, and

4) A file for running R ("Essl.2019.csv") for invasion level data.

Funding

Austrian Science Foundation FWF, Award: I 3757-B29

German Research Foundation DFG, Award: 264740629

Czech Academy of Sciences, Award: EXPRO19-28807X, RVO67985939

National Science Foundation, Award: DEB- 1241932, DEB-1638702

Austrian Science Foundation FWF, Award: I 3757-B29

German Research Foundation DFG, Award: 264740629