DOI: 10.5281/zenodo.17116216
title: Data and R codes from: Naturalized and invasive species integrate differently in the trait space of local plant communities

description: Data and R codes from the article:

Divíšek, J., Pyšek, P., Richardson, D.M., Gotelli, N.J., Beckage, B., Molofsky, J., Lososová, Z. & Chytrý, M. (2025): Naturalized and invasive species integrate differently in the trait space of local plant communities. Ecology Letters 28(11), e70235. https://doi.org/10.1111/ele.70235

Species data

The dataset “SpecData.txt” contains the list of 1,705 vascular plant taxa (species) occurring in the Czech Republic and their characteristics:



NATIVE.ALIEN = Native/alien status of the species (values: native, alien).

INVASION.STATUS = Invasion status for alien species (values: native, naturalized, invasive).

Life.form = Aggregated life forms (values: Macrophanerophyte, Nanophanerophyte, Epiphyte, Chamaephyte, Herb).

Herb.Tree = Vector distinguishing herbs & dwarf shrubs from trees & tall shrubs (values: Tree, Herb).

T = Species occurrence frequency (no. of vegetation plots) in grassland vegetation.

X = Species occurrence frequency (no. of vegetation plots) in ruderal and weed vegetation.

S = Species occurrence frequency (no. of vegetation plots) in rock and scree vegetation.

M = Species occurrence frequency (no. of vegetation plots) in wetland vegetation.

K = Species occurrence frequency (no. of vegetation plots) in scrub vegetation.

L = Species occurrence frequency (no. of vegetation plots) in forest vegetation.

HEIGHT = Maximum plant height (m).

SLA = Specific leaf area (mm2 mg−1).

Seed.mass = Seed mass (mg).

Leaf.area = Leaf area (mm2).

LDMC.mean = Leaf dry matter content (mg g−1).

FLOWERING.MEAN = Middle of the flowering period (month).

FLOWERING.LENGTH = Length of the flowering period (number of months).

Gen.size.2C = 2C genome size (Mbp).


Data on species’ functional traits come from the following sources: Chytrý et al. (2021), E-Vojtkó et al. (2020), Findurová (2018), Kleyer et al. (2008), Kubát et al. (2002), Šmarda et al. (2019) and Weigelt et al. (2020).

Since some of the functional traits in this dataset (SLA, Seed.mass, Leaf.area, LDMC.mean and Gen.size.2C) contain missing values (NA), three different methods were used for their imputation and the complete datasets are provided as follows:

“SpecData.missFor.txt” = NAs in species traits were imputed using the missForest method (Stekhoven & Bühlmann 2012).

“SpecData.MICE.txt” = NAs imputed using the MICE-PMM method (van Buuren & Groothuis-Oudshoorn 2011).

“SpecData.Rphylo.txt” = NAs imputed using the Phylopars method (Goolsby et al. 2024).

Community data

The dataset “CommData.txt” contains species recorded in 24,918 vegetation plots in the Czech Republic. These plots come from the Czech National Phytosociological Database (Chytrý & Rafajová 2003; GIVD code EU-CZ-001). Each plot was assigned to one of the six main terrestrial habitat types of Central Europe: (1) grassland and heathland vegetation below the timberline (T; 6,554 plots), (2) ruderal and weed vegetation (X; 6,265 plots), (3) rock and scree vegetation (S; 325 plots), (4) wetland vegetation (M; 6,371 plots), (5) scrub vegetation (K; 553 plots) and (6) forest vegetation (L; 4,850 plots). The dataset contains the following columns:



ID = ID of the vegetation plot.

Species = Taxon name.

cover = Taxon cover in the vegetation plot (%).

Habitat = Habitat type (values: T, X, S, M, K, L)

NATIVE.ALIEN = Native/alien status (values: native, alien).

INVASION.STATUS = Invasion status for alien species (values: native, naturalized, invasive).

Life.form = Aggregated life forms (values: Macrophanerophyte, Nanophanerophyte, Epiphyte, Chamaephyte, Herb).

Herb.Tree = Vector distinguishing herbs & dwarf shrubs from trees & tall shrubs (values: Tree, Herb).


R codes

The R codes used for the analyses are attached as a zip archive. They are also available at: https://github.com/jdivisek/IntegrationOfAlienSpecies.

The following scripts are included:

01_ReadData.R – Code for reading and preparing the data for analyses.

02_NullModel1.R – Simulates virtual communities by unweighted drawing of species from the native/naturalized species pool. Returns distance statistics, their deviations from the null expectation, and empirical p-values.

03_NullModel2.R – Simulates virtual communities by weighted drawing of species from the native/naturalized species pool. Species frequency in the habitat is used as a weight. The higher frequency, the higher the chance of being selected. Returns distance statistics, their deviations from the null expectation, and empirical p-values.

04_NullModel3.R – Simulates virtual communities by co-occurrence weighted drawing of species from the native/naturalized species pool. Beal's probability of species occurrence in the plot is used as a weight. The higher the probability, the higher the chance of being selected. Returns distance statistics, their deviations from the null expectation, and empirical p-values.

05_NullModel3-GowerPCoA.R – Simulates virtual communities by co-occurrence weighted drawing of species from the native/naturalized species pool. Beal's probability of species occurrence in the plot is used as a weight. The higher the probability, the higher the chance of being selected. This function uses Gower's (1971) distance with Podani's (1999) extension for ordinal variables. The Gower distance matrix is ordinated using principal coordinate analysis, and species scores on ordination axes are used instead of original trait values. Returns distance statistics, their deviations from the null expectation, and empirical p-values.

06_Figure2.R – Plots mean distances (ΔD) of native, naturalized, and invasive species from the native center of the trait space in each plot.

07_Figure3.R – Plots probability of overlap between native, naturalized, and invasive species.

08_CARTnatz.R – Regression tree for naturalized species.

09_CARTinv.R – Regression tree for invasive species.

Functions used in these scripts are included in the attached folder.

References



van Buuren, S. & Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. J Stat Softw, 45, 1–67.

Chytrý, M., Danihelka, J., Kaplan, Z., Wild, J., Holubová, D., Novotný, P., et al. (2021). Pladias Database of the Czech Flora and Vegetation. Preslia, 93, 1–87.

Chytrý, M. & Rafajová, M. (2003). Czech National Phytosociological Database: basic statistics of the available vegetation plot-data. Preslia, 75, 1–15.

E-Vojtkó, A., Balogh, N., Deák, B., Kelemen, A., Kis, S., Kiss, R., et al. (2020). Leaf trait records of vascular plant species in the Pannonian flora with special focus on endemics and rarities. Folia Geobot, 55, 73–79.

Findurová, A. (2018). Variabilita listových znaků SLA a LDMC vybraných druhů rostlin České republiky [Variability of leaf traits SLA and LDMC in selected species of the Czech flora]. Master thesis. Masaryk University, Brno.

Goolsby, E., Bruggeman, J. & Ane, C. (2024). _Rphylopars: Phylogenetic Comparative Tools for Missing Data and Within-Species Variation_. R package version 0.3.10. Available at: <https://CRAN.R-project.org/package=Rphylopars>

Gower, J.C. (1971). A general coefficient of similarity and some of its properties. Biometrics, 27, 857–871.

Kleyer, M., Bekker, R. m., Knevel, I. c., Bakker, J. p., Thompson, K., Sonnenschein, M., et al. (2008). The LEDA Traitbase: a database of life-history traits of the Northwest European flora. Journal of Ecology, 96, 1266–1274.

Kubát, K., Hrouda, L., Chrtek, J., Kaplan, Z., Kirschner, J. & Štěpánek, J. (2002). Klíč ke květeně České republiky [Key to the flora of the Czech Republic]. Academia, Praha.

Podani, J. (1999). Extending Gower’s general coefficient of similarity to ordinal characters. TAXON, 48, 331–340.

Šmarda, P., Knápek, O., Březinová, A., Horová, L., Grulich, V., Danihelka, J., et al. (2019). Genome sizes and genomic guanine+cytosine (GC) contents of the Czech vascular flora with new estimates for 1700 species. Presila, 91, 117–142.

Stekhoven, D.J. & Bühlmann, P. (2012). MissForest—non-parametric missing value imputation for mixed-type data. Bioinformatics, 28, 112–118.

Weigelt, P., König, C. & Kreft, H. (2020). GIFT – A Global Inventory of Floras and Traits for macroecology and biogeography. Journal of Biogeography, 47, 16–43.